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Note: This page contains sample records for the topic "household members number" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


1

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 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 Use an Oven...................................... 1.5 0.6 0.4 Q Q Q Most-Used Oven Fuel Electric....................................................... 67.9 18.2 22.5 11.2 9.5 6.5 Natural Gas................................................ 36.4 9.9 10.0 6.1 5.6 4.7 Propane/LPG.............................................

2

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 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 Equipment Natural Gas....................................................... 58.2 15.6 18.0 9.5 8.4 6.7 Central Warm-Air Furnace............................. 44.7 10.7 14.3 7.6 6.9 5.2 For One Housing Unit................................ 42.9 10.1 13.8 7.3 6.5 5.2 For Two Housing Units...............................

3

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 7 Air-Conditioning Usage Indicators by Number of Household Members, 2005 Total........................................................................ 111.1 30.0 34.8 18.4 15.9 12.0 Do Not Have Cooling Equipment.......................... 17.8 5.4 5.3 2.7 2.5 2.0 Have Cooling Equipment...................................... 93.3 24.6 29.6 15.7 13.4 10.0 Use Cooling Equipment....................................... 91.4 24.0 29.1 15.5 13.2 9.7 Have Equipment But Do Not Use it...................... 1.9 0.6 0.5 Q 0.2 0.4 Type of Air-Conditioning Equipment 1, 2 Central System................................................... 65.9 15.3 22.6 10.7 9.9 7.3 Without a Heat Pump....................................... 53.5 12.5 17.9 8.7 8.2 6.3 With a Heat Pump............................................ 12.3

4

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 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 Heated Floorspace (Square Feet) None............................................................ 3.6 1.0 0.8 0.5 0.5 0.7 1 to 499........................................................ 6.1 3.0 1.6 0.6 0.6 0.3 500 to 999.................................................... 27.7 11.6 8.3 3.6 2.7 1.6 1,000 to 1,499..............................................

5

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

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

2 Home Electronics Usage Indicators by Number of Household Members, 2005 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..................................................... 58.6 10.0 20.0 11.2 10.1 7.3 Laptop Model........................................................ 16.9 3.7 5.4 3.2 3.1 1.5 Hours Turned on Per Week Less than 2 Hours................................................. 13.6 4.0 4.7 1.7 1.8 1.4 2 to 15 Hours........................................................

6

Table HC6.7 Air-Conditioning Usage Indicators by Number of Household...  

Gasoline and Diesel Fuel Update (EIA)

7 Air-Conditioning Usage Indicators by Number of Household Members, 2005 Total... 111.1 30.0 34.8 18.4 15.9...

7

Table HC6.11 Home Electronics Characteristics by Number of Household...  

Gasoline and Diesel Fuel Update (EIA)

1 Home Electronics Characteristics by Number of Household Members, 2005 Total... 111.1 30.0 34.8 18.4 15.9 12.0...

8

Characteristics, Welfare Use and Material Hardship Among California AFDC Households with Disabled and Chronically Ill Family Members  

E-Print Network (OSTI)

completed telephone survey o f AFDC-recipient households tocare for disabled members. When AFDC and SSI are consideredfamilies in this sample of AFDC recipient families were very

Meyers, Marcia k.

1996-01-01T23:59:59.000Z

9

Vehicle Technologies Office: Fact #301: January 5, 2004 Number of Household  

NLE Websites -- All DOE Office Websites (Extended Search)

1: January 5, 1: January 5, 2004 Number of Household Vehicles has Grown Significantly to someone by E-mail Share Vehicle Technologies Office: Fact #301: January 5, 2004 Number of Household Vehicles has Grown Significantly on Facebook Tweet about Vehicle Technologies Office: Fact #301: January 5, 2004 Number of Household Vehicles has Grown Significantly on Twitter Bookmark Vehicle Technologies Office: Fact #301: January 5, 2004 Number of Household Vehicles has Grown Significantly on Google Bookmark Vehicle Technologies Office: Fact #301: January 5, 2004 Number of Household Vehicles has Grown Significantly on Delicious Rank Vehicle Technologies Office: Fact #301: January 5, 2004 Number of Household Vehicles has Grown Significantly on Digg Find More places to share Vehicle Technologies Office: Fact #301:

10

Characteristics, Welfare Use and Material Hardship Among California AFDC Households with Disabled and Chronically Ill Family Members  

E-Print Network (OSTI)

Families with Severely Disabled Members, 262 cases weightedA F D C Households with Disabled and Chronically 111 Familylevels. 1'he treatment o f disabled individuals in these

Meyers, Marcia k.

1996-01-01T23:59:59.000Z

11

PRELIMINARY DATA Housing Unit and Household Characteristics  

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

PRELIMINARY DATA Housing Unit and Household Characteristics RSE Column Factor: Total Households (million) Households With Fans (million) Percent of Households With Fans Number of...

12

,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member"  

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

1 Average Square Footage of Midwest Homes, by Housing Characteristics, 2009" 1 Average Square Footage of Midwest Homes, by Housing Characteristics, 2009" " Final" ,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member" "Housing Characteristics","Millions","Total2","Heated","Cooled","Total2","Heated","Cooled" "Total Midwest",25.9,2272,1898,1372,912,762,551 "Midwest Divisions and States" "East North Central",17.9,2251,1869,1281,892,741,508 "Illinois",4.8,2186,1911,1451,860,752,571 "Michigan",3.8,1954,1559,962,729,582,359 "Wisconsin",2.3,2605,2091,1258,1105,887,534

13

,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member"  

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

3 Average Square Footage of West Homes, by Housing Characteristics, 2009" 3 Average Square Footage of West Homes, by Housing Characteristics, 2009" " Final" ,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member" "Housing Characteristics","Millions","Total2","Heated","Cooled","Total2","Heated","Cooled" "Total West",24.8,1708,1374,800,628,506,294 "West Divisions and States" "Mountain",7.9,1928,1695,1105,723,635,415 "Mountain North",3.9,2107,1858,912,776,684,336 "Colorado",1.9,2082,1832,722,896,788,311 "Idaho, Montana, Utah, Wyoming",2,2130,1883,1093,691,610,354

14

Household vehicles energy consumption 1994  

SciTech Connect

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.

NONE

1997-08-01T23:59:59.000Z

15

,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member"  

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

2 Average Square Footage of South Homes, by Housing Characteristics, 2009" 2 Average Square Footage of South Homes, by Housing Characteristics, 2009" " Final" ,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member" "Housing Characteristics","Millions","Total2","Heated","Cooled","Total2","Heated","Cooled" "Total South",42.1,1867,1637,1549,732,642,607 "South Divisions and States" "South Atlantic",22.2,1944,1687,1596,771,668,633 "Virginia",3,2227,1977,1802,855,759,692 "Georgia",3.5,2304,1983,1906,855,736,707 "Florida",7,1668,1432,1509,690,593,625 "DC, DE, MD, WV",3.4,2218,1831,1440,864,713,561

16

,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member"  

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

4 Average Square Footage of Single-Family Homes, by Housing Characteristics, 2009" 4 Average Square Footage of Single-Family Homes, by Housing Characteristics, 2009" " Final" ,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member" "Housing Characteristics","Millions","Total2","Heated","Cooled","Total2","Heated","Cooled" "Total Single-Family",78.6,2422,2002,1522,880,727,553 "Census Region" "Northeast",12.7,2843,2150,1237,1009,763,439 "Midwest",19.2,2721,2249,1664,1019,842,624 "South",29.7,2232,1945,1843,828,722,684 "West",16.9,2100,1712,1009,725,591,348 "Urban and Rural3"

17

,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member"  

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

0 Average Square Footage of Northeast Homes, by Housing Characteristics, 2009" 0 Average Square Footage of Northeast Homes, by Housing Characteristics, 2009" " Final" ,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member" "Housing Characteristics","Millions","Total2","Heated","Cooled","Total2","Heated","Cooled" "Total Northeast",20.8,2121,1663,921,836,656,363 "Northeast Divisions and States" "New England",5.5,2232,1680,625,903,680,253 "Massachusetts",2.5,2076,1556,676,850,637,277 "CT, ME, NH, RI, VT",3,2360,1781,583,946,714,234 "Mid-Atlantic",15.3,2080,1657,1028,813,647,402

18

,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member"  

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

6 Average Square Footage of Mobile Homes, by Housing Characteristics, 2009" 6 Average Square Footage of Mobile Homes, by Housing Characteristics, 2009" " Final" ,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member" "Housing Characteristics","Millions","Total2","Heated","Cooled","Total2","Heated","Cooled" "Total Mobile Homes",6.9,1087,985,746,413,375,283 "Census Region" "Northeast",0.5,1030,968,711,524,492,362 "Midwest",1.1,1090,1069,595,400,392,218 "South",3.9,1128,1008,894,423,378,335 "West",1.4,995,867,466,369,322,173 "Urban and Rural3" "Urban",3.5,1002,919,684,396,364,271

19

,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member"  

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

9 Average Square Footage of U.S. Homes, by Housing Characteristics, 2009" 9 Average Square Footage of U.S. Homes, by Housing Characteristics, 2009" " Final" ,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member" "Housing Characteristics","Millions","Total2","Heated","Cooled","Total2","Heated","Cooled" "Total",113.6,1971,1644,1230,766,639,478 "Census Region" "Northeast",20.8,2121,1663,921,836,656,363 "Midwest",25.9,2272,1898,1372,912,762,551 "South",42.1,1867,1637,1549,732,642,607 "West",24.8,1708,1374,800,628,506,294 "Urban and Rural3" "Urban",88.1,1857,1546,1148,728,607,450

20

,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member"  

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

5 Average Square Footage of Multi-Family Homes, by Housing Characteristics, 2009" 5 Average Square Footage of Multi-Family Homes, by Housing Characteristics, 2009" " Final" ,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member" "Housing Characteristics","Millions","Total2","Heated","Cooled","Total2","Heated","Cooled" "Total Multi-Family",28.1,930,807,535,453,393,261 "Census Region" "Northeast",7.6,991,897,408,471,426,194 "Midwest",5.6,957,857,518,521,466,282 "South",8.4,924,846,819,462,423,410 "West",6.5,843,606,329,374,269,146 "Urban and Rural3" "Urban",26.9,927,803,531,450,390,258

Note: This page contains sample records for the topic "household members number" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


21

Table HC6.12 Home Electronics Usage Indicators by Number of...  

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...

22

Crime and the Nation’s Households, 2000 By  

E-Print Network (OSTI)

experienced 1 or more violent or property crimes in 2000, according to data from the National Crime Victimization Survey (NCVS). About 4.3 million households had members who experienced 1 or more nonfatal violent crimes, including rape, sexual assault, robbery, and aggravated or simple assault. About 14.8 million households experienced 1 or more property crimes — household burglary, motor vehicle theft, or theft. Vandalism, presented for the first time in a Bureau of Justice Statistics (BJS) report, victimized about 6.1 million households. The households that sustained vandalism were counted separately from those experiencing other crimes. Because vandalism is included for the first time, findings are presented in a box on page 4. Beginning in 2001, NCVS victimizations will be measured both with and without vandalism. Measuring the extent to which households are victimized by crime One measure of the impact of crime throughout the Nation is gained through estimating the number and percentage of households victimized Highlights During 2000, 16 % of U.S. households had a member who experienced a crime, with 4 % having a member victimized by violent crime. During 1994, 25 % of households experienced at least one crime; 7 % a violent crime.

Patsy A. Klaus

2002-01-01T23:59:59.000Z

23

Table WH1. Total Households Using Water Heating Equipment, 2005 ...  

U.S. Energy Information Administration (EIA)

Table WH1. Total Households Using Water Heating Equipment, 2005 Million U.S. Households Fuels Used (million U.S. households) Number of Water Heaters Used

24

Household Vehicles Energy Consumption 1991  

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

Aggregate Aggregate Ratio: See Mean and Ratio Estimate. AMPD: Average miles driven per day. See Appendix B, "Estimation Methodologies." Annual Vehicle Miles Traveled: See Vehicle Miles Traveled. Automobile: Includes standard passenger car, 2-seater car and station wagons; excludes passenger vans, cargo vans, motor homes, pickup trucks, and jeeps or similar vehicles. See Vehicle. Average Household Energy Expenditures: A ratio estimate defined as the total household energy expenditures for all RTECS households divided by the total number of households. See Ratio Estimate, and Combined Household Energy Expenditures. Average Number of Vehicles per Household: The average number of vehicles used by a household for personal transportation during 1991. For this report, the average number of vehicles per household is computed as the ratio of the total number of vehicles to the

25

Household Vehicles Energy Consumption 1991  

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

. . Trends in Household Vehicle Stock The 1991 RTECS counted more than 150 million vehicles in use by U.S. households. This chapter examines recent trends in the vehicle stock, as measured by the RTECS and other reputable vehicle surveys. It also provides some details on the type and model year of the household vehicle stock, and identifies regional differences in vehicle stock. Because vehicles are continuously being bought and sold, this chapter also reports findings relating to turnover of the vehicle stock in 1991. Finally, it examines the average vehicle stock in 1991 (which takes into account the acquisition and disposal of household vehicles over the course of the year) and identifies variations in the average number of household vehicles based on differences in household characteristics. Number of Household Vehicles Over the past 8 years, the stock of household vehicles has

26

Household Vehicles Energy Consumption 1991  

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

3. 3. Vehicle Miles Traveled This chapter presents information on household vehicle usage, as measured by the number of vehicle miles traveled (VMT). VMT is one of the two most important components used in estimating household vehicle fuel consumption. (The other, fuel efficiency, is discussed in Chapter 4). In addition, this chapter examines differences in driving behavior based on the characteristics of the household and the type of vehicle driven. Trends in household driving patterns are also examined using additional information from the Department of Transportation's Nationwide Personal Transportation Survey (NPTS). Household VMT is a measure of the demand for personal transportation. Demand for transportation may be viewed from either an economic or a social perspective. From the economic point-of-view, the use of a household vehicle represents the consumption of one

27

Energy Information Administration/Household Vehicles Energy Consumption 1994  

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

, , Energy Information Administration/Household Vehicles Energy Consumption 1994 ix Household Vehicles Energy Consumption 1994 presents statistics about energy-related characteristics of highway vehicles available for personal use by members of U.S. households. The data were collected in the 1994 Residential Transportation Energy Consumption Survey, the final cycle in a series of nationwide energy consumption surveys conducted during the 1980's and 1990's by the Energy Information Administrations. Engines Became More Powerful . . . Percent Distribution of Total Residential Vehicle Fleet by Number of Cylinders, 1988 and 1994 Percent Distribution of Vehicle Fleet by Engine Size, 1988 and 1994 Percent Percent 4 cyl Less than 2.50 liters 6 cyl 2.50- 4.49 liters 8 cyl 4.50 liters or greater 20 20 40 40 Vehicle

28

EIA - Household Transportation report: Household Vehicles ...  

U.S. Energy Information Administration (EIA)

This report, Household Vehicles Energy Use: Latest Data & Trends, provides details on the nation's energy use for household passenger travel. A primary purpose of ...

29

1997 Residential Energy Consumption and Expenditures per Household ...  

U.S. Energy Information Administration (EIA)

Return to: Residential Home Page . Changes in the 1997 RECS: Housing Unit Type Per Household Member Per Building Increase. Residential Energy Consumption ...

30

Household Vehicles Energy Consumption 1994 - PDF Tables  

U.S. Energy Information Administration (EIA)

Table 1 U.S. Number of Vehicles, Vehicle Miles, Motor Fuel Consumption and Expenditures, 1994 Table 2 U.S. per Household Vehicle Miles Traveled, Vehicle Fuel ...

31

Number  

Office of Legacy Management (LM)

' ' , /v-i 2 -i 3 -A, This dow'at consists ~f--~-_,_~~~p.~,::, Number -------of.-&--copies, 1 Series.,-a-,-. ! 1 THE UNIVERSITY OF ROCHESTER 1; r-.' L INTRAMURALCORRESPONDENCE i"ks' 3 2.. September 25, 1947 Memo.tor Dr. A. H, Dovdy . From: Dr. H. E, Stokinger Be: Trip Report - Mayvood Chemical Works A trip vas made Nednesday, August 24th vith Messrs. Robert W ilson and George Sprague to the Mayvood Chemical F!orks, Mayvood, New Jersey one of 2 plants in the U.S.A. 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. Survey conditions of eeosure of personnel associated vith these chemical processes. 3. Obtain samples of atmospheric contaminants in the plant, as

32

Member Get a Member Program  

Science Conference Proceedings (OSTI)

AOCS Member Recruitment Program. Member Get a Member Program Membership Information achievement application award Awards distinguished division Divisions fats job Join lipid lipids Member member get a member Membership memorial nomination oils pos

33

Section J: HOUSEHOLD CHARACTERISTICS  

U.S. Energy Information Administration (EIA)

2001 Residential Energy Consumption Survey Form EIA-457A (2001)--Household Questionnaire OMB No.: 1905-0092, Expiring February 29, 2004 42 Section J: HOUSEHOLD ...

34

Household vehicles energy consumption 1991  

Science Conference Proceedings (OSTI)

The purpose of this report is to provide information on the use of energy in residential vehicles in the 50 States and the District of Columbia. Included are data about: the number and type of vehicles in the residential sector, the characteristics of those vehicles, the total annual Vehicle Miles Traveled (VMT), the per household and per vehicle VMT, the vehicle fuel consumption and expenditures, and vehicle fuel efficiencies. The data for this report are based on the household telephone interviews from the 1991 RTECS, conducted during 1991 and early 1992. The 1991 RTECS represents 94.6 million households, of which 84.6 million own or have access to 151.2 million household motor vehicles in the 50 States and the District of Columbia.

Not Available

1993-12-09T23:59:59.000Z

35

homeoffice_household2001.pdf  

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

3a. Home Office Equipment by Household Income, 3a. Home Office Equipment by Household Income, Million U.S. Households, 2001 Home Office Equipment RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral Assist- ance 1 RSE Row Factors Less than $14,999 $15,000 to $29,999 $30,000 to $49,999 $50,000 or More 0.4 1.9 1.2 1.0 0.6 1.9 0.9 Total ............................................... 107.0 18.7 22.9 27.1 38.3 15.0 47.6 3.0 Households Using Office Equipment .......................... 96.2 13.2 19.8 25.5 37.7 10.7 38.8 3.2 Personal Computers 2 ................... 60.0 3.7 8.7 16.0 31.6 3.7 17.4 4.6 Number of Desktop PCs 1 .................................................. 45.1 2.8 7.1 12.8 22.4 2.8 13.6 5.1 2 or more .................................... 9.1 0.6 0.7 1.7 6.2 0.6 2.2 13.0 Number of Laptop PCs

36

char_household2001.pdf  

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

Household Tables Household Tables (Million U.S. Households; 24 pages, 122 kb) Contents Pages HC2-1a. Household Characteristics by Climate Zone, Million U.S. Households, 2001 2 HC2-2a. Household Characteristics by Year of Construction, Million U.S. Households, 2001 2 HC2-3a. Household Characteristics by Household Income, Million U.S. Households, 2001 2 HC2-4a. Household Characteristics by Type of Housing Unit, Million U.S. Households, 2001 2 HC2-5a. Household Characteristics by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 2 HC2-6a. Household Characteristics by Type of Rented Housing Unit, Million U.S. Households, 2001 2 HC2-7a. Household Characteristics by Four Most Populated States, Million U.S. Households, 2001 2

37

char_household2001.pdf  

Annual Energy Outlook 2012 (EIA)

9a. Household Characteristics by Northeast Census Region, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total U.S. Northeast Census Region RSE Row...

38

SAC Members  

NLE Websites -- All DOE Office Websites (Extended Search)

Former members Scientific Advisory Committee (SAC) Members Name and Address Contact Information Current Position Research Interests Term Kirz, Janos Lawrence Berkeley National...

39

Table 1. Household Characteristics by Ceiling Fans, 2001  

U.S. Energy Information Administration (EIA)

A reporting of the number of housing units using ceiling fans in U.S. households as reported in the 2001 Residential Energy Consumption Survey

40

homeoffice_household2001.pdf  

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

0a. Home Office Equipment by Midwest Census Region, 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 14.1 9.9 4.2 3.7 Number of Desktop PCs 1 ................................................................ 45.1 10.4 7.2 3.2 3.7 2 or more ................................................... 9.1 2.3 1.6 0.7 10.1 Number of Laptop PCs 1 ................................................................

Note: This page contains sample records for the topic "household members number" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


41

homeoffice_household2001.pdf  

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

9a. Home Office Equipment by Northeast Census Region, 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 7.7 3.3 3.1 Number of Desktop PCs 1 ................................................................ 45.1 8.7 6.2 2.5 3.7 2 or more ................................................... 9.1 1.4 0.9 0.5 12.9 Number of Laptop PCs 1 ................................................................

42

EIA - Household Transportation report: Household Vehicles Energy  

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

4 4 Transportation 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. Based on the 1994 Residential Transportation Energy Consumption Survey conducted by the Energy Information Administration (EIA) - survey series has been discontinued Only light-duty vehicles and recreational vehicles are included in this report. EIA has excluded motorcycles, mopeds, large trucks, and buses. 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

43

Patterns of rural household energy use: a study in the White Nile province - the Sudan  

Science Conference Proceedings (OSTI)

The study investigates rural household domestic energy consumption patterns in a semiarid area of the Sudan. It describes the socioeconomic and evironmental context of energy use, provides an estimation of local woody biomass production and evaluates ecological impacts of increased energy demand on the local resource base. It is based on findings derived from field surveys, a systematic questionnaire and participant observations. Findings indicate that households procure traditional fuels by self-collection and purchases. Household members spent on average 20% of their working time gathering fuels. Generally per caput and total annual expenditure and consumption of domestic fuels are determined by household size, physical availability, storage, prices, income, conservation, substitution and competition among fuel resource uses. Households spend on average 16% of their annual income on traditional fuels. Aggregation of fuels on heat equivalent basis and calculation of their contribution shows that on average firewood provides 63%, charcoal 20.7%, dung 10.4%, crop residues 3.4% and kerosene/diesel 2.5% of the total demand for domestic purposes. Estimated total household woodfuel demand exceeds woody biomass available from the local forests. This demand is presently satisfied by a net depletion of the local forests and purchases from other areas. Degradation of the resource base is further exacerbated by development of irrigation along the White Nile River, increasing livestock numbers (overgrazing) and forest clearance for rainfed cultivation. The most promising relevant and appropriate strategies to alleviate rural household domestic energy problems include: conservation of the existing forest, augmentation through village woodlots and community forestry programmes and improvements in end-use (stoves) and conversion (wood to charcoal) technologies.

Abdu, A.S.E.

1985-01-01T23:59:59.000Z

44

Car Sharing within Households  

E-Print Network (OSTI)

The objective of this paper was to analyse two activities: who rents a car and why? Which households share the driving of their cars? In order to do that, the Parc-Auto (Car-Fleet) database, built from annual postal surveys conducted with a panel of 10,000 French households, has been processed. Among approximately one hundred questions in the survey, two key questions have been crossed against many social, economic, demographic, geographic or time variables. KQ1: “During the last 12 months, did you — or another person from your home — rent a car in France for personal purposes? ” KQ2: “Is this car occasionally used by other persons?” Here are the main findings. Renting households are mainly working, high income households, living in the core of big cities, and in particular in Paris. Most of them have two wage-sheets and two cars, one of which is generally a recent, high power, high quality car. Car rental is mainly an occasional practice. Yet for a minority of renters, it is a sustained habit. Households with more licence holders than cars share the most: about three quarters of them share their cars. On the contrary, single driver-single car households have less opportunity to share: only 15 % share. Household car sharing shed light on the gender role within households: while 58 % of the main users of the shared cars are male, 55 % of secondary users are female. Household car sharing is mainly a regular practice. Finally, without diminishing the merits of innovative transport solutions proposed here and there, it is not a waste of time to give some insight on self established behaviour within households. This reveals that complex patterns have been built over time by the people themselves, to cope with diverse situations that cannot be easily handled by straightforward classifications. The car cannot be reduced to a personal object. Household car sharing also carries strong links with the issue of car dependency. Sifting car availability and choice

Francis Papon; Laurent Hivert

2008-01-01T23:59:59.000Z

45

Household Vehicles Energy Consumption 1991  

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

1. 1. Introduction The purpose of this report is to provide information on the use of energy in residential vehicles in the 50 States and the District of Columbia. Included are data about: the number and type of vehicles in the residential sector, the characteristics of those vehicles, the total annual Vehicle Miles Traveled (VMT), the per household and per vehicle VMT, the vehicle fuel consumption and expenditures, and vehicle fuel efficiencies. The Energy Information Administration (EIA) is mandated by Congress to collect, analyze, and disseminate impartial, comprehensive data about energy--how much is produced, who uses it, and the purposes for which it is used. To comply with this mandate, EIA collects energy data from a variety of sources covering a range of topics 1 . Background The data for this report are based on the household telephone interviews from the 1991 RTECS, conducted

46

Household Vehicles Energy Consumption 1991  

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

Detailed Detailed Tables The following tables present detailed characteristics of vehicles in the residential sector. Data are from the 1991 Residential Transportation Energy Consumption Survey. The "Glossary" contains the definitions of terms used in the tables. Table Organization The "Detailed Tables" section consists of three types of tables: (1) Tables of totals such as number of vehicle miles traveled (VMT) or gallons consumed; (2) Tables of per household statistics such as VMT per household; and (3) Tables of per vehicle statistics such as vehicle fuel consumption per vehicle. The tables have been grouped together by specific topics such as model year data, or family income data to facilitate finding related information. The Quick-Reference Guide to the detailed tables indicates major topics of each table. Row and Column Factors These tables present estimates

47

A Framework for Corporate Householding  

E-Print Network (OSTI)

Previous research on corporate household and corporate householding has presented examples, literature review, and working definitions. In this paper, we first improve our ...

Madnick, Stuart

2003-03-21T23:59:59.000Z

48

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

Science Conference Proceedings (OSTI)

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 = household, cooling degree days, heating degree days, year the housing unit was built, and number of stories in the housing unit.

Guerin, D.A.

1988-01-01T23:59:59.000Z

49

Household carbon dioxide production in relation to the greenhouse effect  

SciTech Connect

A survey of 655 households from eastern suburbs of Melbourne was undertaken to determine householders[prime] attitudes to, and understanding of, the greenhouse effect. Carbon dioxide emissions resulting from car, electricity and gas use were computed and household actions which could reduce CO[sub 2] emissions were addressed. Preliminary analysis of the results indicates that householders in this area are aware of, and concerned about, the greenhouse effect, although their understanding of its causes is often poor. Many appreciate the contribution of cars, but are unclear about the relative importance of other household activities. Carbon dioxide emissions from the three sources examined averaged 21[center dot]2 tonnes/year per household and 7[center dot]4 tonnes/year per person. Electricity was the largest contributor (8[center dot]6 tonnes/year), cars the next largest (7[center dot]7 tonnes/year) and gas third (5[center dot] tonnes/year) per household. Emissions varied considerably from household to household. There was a strong positive correlation between availability of economic resources and household CO[sub 2] output from all sources. Carbon dioxide production, particularly from car use, was greater from households which were most distant from a railway station, and from larger households, and numbers of children in the household had little effect on emissions. There were also some economics of scale for households containing more adults. Understanding the causes of the greenhouse bore little relation to change in CO[sub 2] emissions; being concerned about it was associated with a small reduction; but actual actions to reduce car use and household heating, however motivated, produced significant reductions. 12 refs., 9 figs., 6 tabs.

Stokes, D.; Lindsay, A.; Marinopoulos, J.; Treloar, A.; Wescott, G. (Deakin Univ., Clayton (Australia))

1994-03-01T23:59:59.000Z

50

AP Members  

NLE Websites -- All DOE Office Websites (Extended Search)

Group Members Group Members Principal Investigators Etsuko Fujita (Lead PI) Photochemical carbon dioxide reduction using transition-metal complexes; electrocatalysis of hydrogen and carbon dioxide reduction with non-noble metal based catalysts; water oxidation catalysis; kinetics and mechanism of photochemical and redox reactions Javier Concepcion (PI) David Grills (PI) Application of transient infrared spectroscopy to kinetics and catalysis; characterization of reaction intermediates, CO2 reduction in supercritical CO2 Jim Muckerman (PI) Application of theory and computation to photocatalysis and electrocatalysis; mechanistic studies of hydrogen production, carbon dioxide reduction and water oxidation in both homogeneous and heterogeneous systems Dmitry Polyansky (PI)

51

usage_household2001.pdf  

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

Usage Indicators Tables Usage Indicators Tables (Million U.S. Households; 60 pages, 247 kb) Contents Pages HC6-1a. Usage Indicators by Climate Zone, Million U.S. Households, 2001 5 HC6-2a. Usage Indicators by Year of Construction, Million U.S. Households, 2001 5 HC6-3a. Usage Indicators by Household Income, Million U.S. Households, 2001 5 HC6-4a. Usage Indicators by Type of Housing Unit, Million U.S. Households, 2001 5 HC6-5a. Usage Indicators by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 5 HC6-6a. Usage Indicators by Type of Rented Housing Unit, Million U.S. Households, 2001 5 HC6-7a. Usage Indicators by Four Most Populated States, Million U.S. Households, 2001 5

52

housingunit_household2001.pdf  

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

Housing Unit Tables Housing Unit Tables (Million U.S. Households; 49 pages, 210 kb) Contents Pages HC1-1a. Housing Unit Characteristics by Climate Zone, Million U.S. Households, 2001 5 HC1-2a. Housing Unit Characteristics by Year of Construction, Million U.S. Households, 2001 4 HC1-3a. Housing Unit Characteristics by Household Income, Million U.S. Households, 2001 4 HC1-4a. Housing Unit Characteristics by Type of Housing Unit, Million U.S. Households, 2001 4 HC1-5a. Housing Unit Characteristics by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 4 HC1-6a. Housing Unit Characteristics by Type of Rented Housing Unit, Million U.S. Households, 2001 4 HC1-7a. Housing Unit Characteristics by Four Most Populated States, Million U.S. Households, 2001 4

53

homeoffice_household2001.pdf  

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

Home Office Equipment Tables Home Office Equipment Tables (Million U.S. Households; 12 pages, 123 kb) Contents Pages HC7-1a. Home Office Equipment by Climate Zone, Million U.S. Households, 2001 1 HC7-2a. Home Office Equipment by Year of Construction, Million U.S. Households, 2001 1 HC7-3a. Home Office Equipment by Household Income, Million U.S. Households, 2001 1 HC7-4a. Home Office Equipment by Type of Housing Unit, Million U.S. Households, 2001 1 HC7-5a. Home Office Equipment by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 1 HC7-6a. Home Office Equipment by Type of Rented Housing Unit, Million U.S. Households, 2001 1 HC7-7a. Home Office Equipment by Four Most Populated States, Million U.S. Households, 2001 1

54

Elastomeric member  

DOE Patents (OSTI)

An energy storage device (10) is disclosed consisting of a stretched elongated elastomeric member (16) disposed within a tubular housing (14), which elastomeric member (16) is adapted to be torsionally stressed to store energy. The elastomeric member (16) is configured in the relaxed state with a uniform diameter body section (74), and transition end sections (76, 78), attached to rigid end piece assemblies (22, 24) of a lesser diameter. The profile and deflection characteristic of the transition sections (76, 78) are such that upon stretching of the elastomeric member (16), a substantially uniform diameter assembly results, to minimize the required volume of the surrounding housing (14). Each of the transition sections (76, 78) are received within and bonded to a woven wire mesh sleeve (26, 28) having helical windings at a particular helix angle to control the deflection of the transition section. Each sleeve (26, 28) also contracts with the contraction of the associated transition section to maintain the bond therebetween. During manufacture, the sleeves (26, 28) are forced against a forming surface and bonded to the associated transition section (76, 78) to provide the correct profile and helix angle.

Hoppie, Lyle O. (Birmingham, MI)

1985-01-01T23:59:59.000Z

55

homeoffice_household2001.pdf  

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

2a. Home Office Equipment by Year of Construction, 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 ................... 60.0 11.0 11.6 10.3 7.2 7.8 12.0 5.3 Number of Desktop PCs 1 .................................................. 45.1 8.0 9.0 7.7 5.3 6.1 9.1 5.8 2 or more .................................... 9.1 1.8 1.6 2.0 1.1 1.0 1.6 11.8 Number of Laptop PCs 1 ..................................................

56

homeoffice_household2001.pdf  

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

1a. Home Office Equipment by South Census Region, 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 ................................. 60.0 20.7 11.7 3.2 5.8 4.0 Number of Desktop PCs 1 ................................................................ 45.1 15.5 8.6 2.6 4.3 4.9 2 or more ................................................... 9.1 3.1 2.0 0.4 0.7 9.6 Number of Laptop PCs

57

homeoffice_household2001.pdf  

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

a. Home Office Equipment by Climate Zone, a. Home Office Equipment by Climate Zone, Million U.S. Households, 2001 Home Office Equipment RSE Column Factor: Total Climate Zone 1 RSE Row Factors Fewer than 2,000 CDD and -- 2,000 CDD or More and Fewer than 4,000 HDD More than 7,000 HDD 5,500 to 7,000 HDD 4,000 to 5,499 HDD Fewer than 4,000 HDD 0.4 1.9 1.1 1.2 1.1 1.0 Total ............................................... 107.0 9.2 28.6 24.0 21.0 24.1 7.9 Households Using Office Equipment .......................... 96.2 8.4 26.2 21.1 19.0 21.5 7.8 Personal Computers 2 ................... 60.0 5.7 16.7 13.1 12.1 12.6 7.4 Number of Desktop PCs 1 .................................................. 45.1 4.2 12.8 9.6 8.8 9.6 7.8 2 or more .................................... 9.1 0.8 2.4 2.3 2.0 1.7 12.1 Number of Laptop PCs 1 ..................................................

58

Household Vehicles Energy Use Cover Page  

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

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

59

Household Hazardous Waste Household hazardous waste is the discarded, unused, or leftover portion of household products  

E-Print Network (OSTI)

Household Hazardous Waste Household hazardous waste is the discarded, unused, or leftover portion of household products containing toxic chemicals. These wastes CANNOT be disposed of in regular garbage. Any should be considered hazardous. You cannot treat hazardous wastes like other kinds of garbage

de Lijser, Peter

60

Projecting household energy consumption within a conditional demand framework  

SciTech Connect

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).

Teotia, A.; Poyer, D.

1991-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "household members number" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


61

Projecting household energy consumption within a conditional demand framework  

Science Conference Proceedings (OSTI)

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).

Teotia, A.; Poyer, D.

1991-12-31T23:59:59.000Z

62

Model documentation: household model of energy  

Science Conference Proceedings (OSTI)

The Household Model of Energy is an econometric model, meaning that energy use is determined quantitatively with the use of economic variables such as fuel prices and income. HOME is also primarily a structural model, meaning that energy use is determined as the result of interactions of intermediate components such as the number of households, the end use fuel shares and the energy use per household. HOME forecasts energy consumption in all occupied residential structures (households) in the United States on an annual basis through 1990. The forecasts are made based upon a number of initial conditions in 1980, various estimated elasticities, various parameters and assumptions, and a set of forecasted fuel prices and income. In addition to the structural detail, HOME operates on a more disaggregated level. This includes four end-use services (space heating, water heating, air conditioning, and others), up to seven fuel/technology types (dependent upon the end use service), two housing types, four structure vintages, and four Census regions. When the model is run as a module in IFFS, a sharing scheme further disaggregates the model to 10 Federal regions.

Holte, J.A.

1984-02-01T23:59:59.000Z

63

An examination of how households share and coordinate the completion of errands  

Science Conference Proceedings (OSTI)

People often complete tasks and to-dos not only for themselves but also for others in their household. In this work, we examine how household members share and accomplish errands both individually and together. We conducted a three-week diary study with ... Keywords: cooperative errands, coordination, families, roommates

Timothy Sohn; Lorikeet Lee; Stephanie Zhang; David Dearman; Khai Truong

2012-02-01T23:59:59.000Z

64

ac_household2001.pdf  

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

Air Conditioning Tables Air Conditioning Tables (Million U.S. Households; 24 pages, 138 kb) Contents Pages HC4-1a. Air Conditioning by Climate Zone, Million U.S. Households, 2001 2 HC4-2a. Air Conditioning by Year of Construction, Million U.S. Households, 2001 2 HC4-3a. Air Conditioning by Household Income, Million U.S. Households, 2001 2 HC4-4a. Air Conditioning by Type of Housing Unit, Million U.S. Households, 2001 2 HC4-5a. Air Conditioning by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 2 HC4-6a. Air Conditioning by Type of Rented Housing Unit, Million U.S. Households, 2001 2 HC4-7a. Air Conditioning by Four Most Populated States, Million U.S. Households, 2001 2 HC4-8a. Air Conditioning by Urban/Rural Location, Million U.S. Households, 2001 2

65

Table CE1-7c. Total Energy Consumption in U.S. Households by Four ...  

U.S. Energy Information Administration (EIA)

Other Appliances and Lighting ... It does include the small number of households where the fuel for central air-conditioning equipment was something other than ...

66

Household Vehicles Energy Use: Latest Data and Trends - Table A01  

U.S. Energy Information Administration (EIA)

Table A1. U.S. Number of Vehicles, Vehicles-Miles, Motor Fuel Consumption and Expenditures, 2001: 2001 Household and Vehicle Characteristics

67

Energy Spending and Vulnerable Households  

E-Print Network (OSTI)

 off than before. In particular large households with low  incomes seem to have been adversely affected by the new tariff structures since  they have comparably large energy expenditure (Bennet et al., 2002).    5. Vulnerable Households and Energy Spending  The...  tariffs can play an important part in the public debate  on  eradicating  fuel  poverty  and  helping  the  vulnerable  households.  Smart  metering  can  provide  consumers  with  information  on  the  actual  energy  consumption and might  lead  to...

Jamasb, Tooraj; Meier, Helena

2011-01-26T23:59:59.000Z

68

Household Vehicles Energy Consumption 1991  

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

DOEEIA-0464(91) Distribution Category UC-950 Household Vehicles Energy Consumption 1991 December 1993 Energy Information Administration Office of Energy Markets and End Use U.S....

69

Household Vehicles Energy Consumption 1991  

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

a regular basis at the time of the 1990 RECS personal interviews. Electricity: See Main Heating Fuel. Energy Information AdministrationHousehold Vehicles Energy Consumption 1991...

70

Household Vehicles Energy Consumption 1994  

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

AdministrationHousehold Vehicles Energy Consumption 1994 110 Electricity: See Main Heating Fuel. Energy Used in the Home: For electricity or natural gas, the quantity is the...

71

Household Energy Consumption and Expenditures  

Reports and Publications (EIA)

Presents information about household end use consumption of energy and expenditures for that energy. These data were collected in the 2005 Residential Energy Consumption Survey (RECS)

Information Center

2008-09-01T23:59:59.000Z

72

char_household2001.pdf  

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

3a. Household Characteristics by Household Income, 3a. Household Characteristics by Household Income, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral Assist- ance 1 RSE Row Factors Less than $14,999 $15,000 to $29,999 $30,000 to $49,999 $50,000 or More 0.6 1.3 1.1 1.0 0.9 1.4 1.0 Total ............................................... 107.0 18.7 22.9 27.1 38.3 15.0 33.8 3.3 Household Size 1 Person ....................................... 28.2 9.7 -- -- -- 6.5 11.3 5.7 2 Persons ...................................... 35.1 4.3 -- -- -- 2.0 7.8 5.8 3 Persons ...................................... 17.0 -- 3.3 -- -- 2.2 5.2 7.3 4 Persons ...................................... 15.6 -- 2.2 -- -- -- 4.3 8.1 5 Persons ...................................... 7.1

73

char_household2001.pdf  

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

2a. Household Characteristics by West Census Region, 2a. Household Characteristics by West Census Region, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total U.S. West Census Region RSE Row Factors Total Census Division Mountain Pacific 0.5 1.0 1.8 1.1 Total .............................................................. 107.0 23.3 6.7 16.6 NE Household Size 1 Person ...................................................... 28.2 5.6 1.8 3.8 5.4 2 Persons .................................................... 35.1 7.3 1.9 5.5 4.9 3 Persons .................................................... 17.0 3.5 0.9 2.6 7.6 4 Persons .................................................... 15.6 3.5 1.1 2.4 6.4 5 Persons .................................................... 7.1 2.0 0.6 1.4 9.7 6 or More Persons

74

Household Vehicles Energy Consumption 1991  

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

. . Vehicle Fuel Efficiency and Consumption Fuel consumption is estimated from RTECS data on the vehicle stock (Chapter 2) and miles traveled (Chapter 3), in combination with vehicle fuel efficiency ratings, adjusted to account for individual driving circumstances. The first two sections of this chapter present estimates of household vehicle fuel efficiency and household fuel consumption calculated from these fuel efficiency estimates. These sections also discuss variations in fuel efficiency and consumption based on differences in household and vehicle characteristics. The third section presents EIA estimates of the potential savings from replacing the oldest (and least fuel-efficient) household vehicles with new (and more fuel-efficient) vehicles. The final section of this chapter focuses on households receiving (or eligible to receive) supplemental income under

75

char_household2001.pdf  

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

0a. Household Characteristics by Midwest Census Region, 0a. Household Characteristics by Midwest Census Region, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total U.S. Midwest Census Region RSE Row Factors Total Census Division East North Central West North Central 0.5 1.0 1.2 1.7 Total .............................................................. 107.0 24.5 17.1 7.4 NE Household Size 1 Person ...................................................... 28.2 6.7 4.7 2.0 6.2 2 Persons .................................................... 35.1 8.0 5.4 2.6 5.0 3 Persons .................................................... 17.0 3.8 2.7 1.1 7.9 4 Persons .................................................... 15.6 3.5 2.5 1.0 8.1 5 Persons .................................................... 7.1 1.7

76

Extending Efficiency Services to Underserved Households: NYSERDA...  

NLE Websites -- All DOE Office Websites (Extended Search)

Extending Efficiency Services to Underserved Households: NYSERDA's Assisted Home Performance with ENERGY STAR Program Title Extending Efficiency Services to Underserved Households:...

77

www.eia.gov  

U.S. Energy Information Administration (EIA)

ESTIMATE Consumption Expenditures Residential Buildings per Total per Total Total Floorspace Building Foot Household Member Household Households Number

78

EIA - Household Transportation report: Household Vehicles Energy Use:  

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

Transportation logo printer-friendly version logo for Portable Document Format file Household Vehicles Energy Use: Latest Data & Trends November 2005 Release (Next Update: Discontinued) Based on the 2001 National Household Travel Survey conducted by the U.S. Department of Transportation and augmented by EIA Only light-duty vehicles and recreational vehicles are included in this report. EIA has excluded motorcycles, mopeds, large trucks, and buses in an effort to maintain consistency with its past residential transportation series, which was discontinued after 1994. This report, Household Vehicles Energy Use: Latest Data & Trends, provides details on the nation's energy use for household passenger travel. A primary purpose of this report is to release the latest consumer-based data

79

Household Vehicles Energy Consumption 1994  

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

W as hi ng to n, DC DOEEIA-0464(94) Distribution Category UC-950 Household Vehicles Energy Consumption 1994 August 1997 Energy Information Administration Office of Energy Markets...

80

ac_household2001.pdf  

Annual Energy Outlook 2012 (EIA)

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

Note: This page contains sample records for the topic "household members number" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


81

Household savings and portfolio choice  

E-Print Network (OSTI)

This thesis consists of three essays that examine household savings and portfolio choice behavior. Chapter One analyses the effects of employer matching contributions and tax incentives on participation and contribution ...

Klein, Sean Patrick

2010-01-01T23:59:59.000Z

82

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

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

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

83

Modelling household electricity consumption.  

E-Print Network (OSTI)

??A number of conclusions are drawn, however given the limited and non-representative na- ture of the data on which the model is calibrated, these can… (more)

de la Rue, Philip Martin

2010-01-01T23:59:59.000Z

84

ac_household2001.pdf  

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

3a. Air Conditioning by Household Income, 3a. Air Conditioning by Household Income, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral Assist- ance 1 RSE Row Factors Less than $14,999 $15,000 to $29,999 $30,000 to $49,999 $50,000 or More 0.5 1.4 1.1 1.0 0.9 1.5 0.9 Households With Electric Air-Conditioning Equipment ........ 82.9 12.3 17.4 21.5 31.7 9.6 23.4 3.9 Air Conditioners Not Used ............ 2.1 0.4 0.7 0.5 0.5 0.4 0.9 20.8 Households Using Electric Air-Conditioning 2 .......................... 80.8 11.9 16.7 21.0 31.2 9.1 22.6 3.9 Type of Electric Air-Conditioning Used Central Air-Conditioning 3 .............. 57.5 6.2 10.7 15.2 25.3 4.5 12.4 5.3 Without a Heat Pump .................. 46.2 4.9 9.1 12.1 20.1 3.6 10.4 6.1 With a Heat Pump

85

char_household2001.pdf  

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

5a. Household Characteristics by Type of Owner-Occupied Housing Unit, 5a. Household Characteristics by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total Owner- Occupied Units Type of Owner-Occupied Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Homes Two to Four Units Five or More Units 0.3 0.4 2.0 2.9 1.3 Total Owner-Occupied Units ....... 72.7 63.2 2.1 1.8 5.7 6.7 Household Size 1 Person ....................................... 15.8 12.5 0.8 0.9 1.6 10.3 2 Persons ...................................... 25.9 23.4 0.5 0.5 1.5 10.1 3 Persons ...................................... 11.6 9.6 0.5 Q 1.3 12.1 4 Persons ...................................... 11.8 10.9 Q Q 0.7 15.7 5 Persons ...................................... 5.1 4.5 Q Q 0.4 24.2 6 or More Persons

86

char_household2001.pdf  

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

1a. Household Characteristics by South Census Region, 1a. Household Characteristics by South Census Region, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total U.S. South Census Region RSE Row Factors Total Census Division South Atlantic East South Central West South Central 0.5 0.8 1.1 1.5 1.6 Total .............................................................. 107.0 38.9 20.3 6.8 11.8 NE Household Size 1 Person ...................................................... 28.2 9.9 5.0 1.8 3.1 6.3 2 Persons .................................................... 35.1 13.0 6.7 2.5 3.8 4.2 3 Persons .................................................... 17.0 6.6 3.7 1.2 1.7 8.8 4 Persons .................................................... 15.6 6.0 3.3 0.8 1.9 10.7 5 Persons ....................................................

87

char_household2001.pdf  

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

8a. Household Characteristics by Urban/Rural Location, 8a. Household Characteristics by Urban/Rural Location, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total Urban/Rural Location 1 RSE Row Factors City Town Suburbs Rural 0.5 0.8 1.4 1.3 1.4 Total .............................................................. 107.0 49.9 18.0 21.2 17.9 4.1 Household Size 1 Person ...................................................... 28.2 14.6 5.3 4.8 3.6 6.4 2 Persons .................................................... 35.1 15.7 5.7 6.9 6.8 5.4 3 Persons .................................................... 17.0 7.6 2.8 3.5 3.1 7.2 4 Persons .................................................... 15.6 6.8 2.3 4.1 2.4 8.1 5 Persons .................................................... 7.1 3.1 1.3 1.3 1.4 12.3 6 or More Persons

88

char_household2001.pdf  

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

a. Household Characteristics by Climate Zone, a. Household Characteristics by Climate Zone, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total Climate Zone 1 RSE Row Factors Fewer than 2,000 CDD and -- 2,000 CDD or More and Fewer than 4,000 HDD More than 7,000 HDD 5,500 to 7,000 HDD 4,000 to 5,499 HDD Fewer than 4,000 HDD 0.4 1.9 1.1 1.1 1.2 1.0 Total ............................................... 107.0 9.2 28.6 24.0 21.0 24.1 7.8 Household Size 1 Person ....................................... 28.2 2.5 8.1 6.5 4.8 6.2 9.9 2 Persons ...................................... 35.1 3.1 9.4 8.2 6.5 7.9 8.7 3 Persons ...................................... 17.0 1.3 4.3 4.0 3.3 4.1 10.7 4 Persons ...................................... 15.6 1.4 3.9 3.4 3.4 3.5 10.5 5 Persons ......................................

89

char_household2001.pdf  

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

6a. Household Characteristics by Type of Rented Housing Unit, 6a. Household Characteristics by Type of Rented Housing Unit, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total Rented Units Type of Rented Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.5 0.8 1.1 0.9 2.5 Total Rented Units ........................ 34.3 10.5 7.4 15.2 1.1 6.9 Household Size 1 Person ....................................... 12.3 2.5 2.6 7.0 0.3 10.0 2 Persons ...................................... 9.2 2.5 2.5 4.1 Q 11.8 3 Persons ...................................... 5.4 2.0 1.1 2.0 0.4 13.9 4 Persons ...................................... 3.8 1.6 0.7 1.4 Q 17.7 5 Persons ...................................... 2.0 0.9 0.4 0.6 Q 24.1 6 or More Persons ........................

90

char_household2001.pdf  

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

2a. Household Characteristics by Year of Construction, 2a. Household Characteristics by Year of Construction, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total Year of Construction RSE Row Factors 1990 to 2001 1 1980 to 1989 1970 to 1979 1960 to 1969 1950 to 1959 1949 or Before 0.4 1.6 1.2 1.0 1.2 1.2 0.9 Total ............................................... 107.0 15.5 18.2 18.8 13.8 14.2 26.6 4.2 Household Size 1 Person ....................................... 28.2 2.5 4.5 5.1 4.0 3.7 8.3 7.5 2 Persons ...................................... 35.1 4.8 6.2 6.6 4.5 5.3 7.8 5.8 3 Persons ...................................... 17.0 2.5 3.3 2.9 2.3 1.9 4.1 8.4 4 Persons ...................................... 15.6 3.4 2.8 2.3 1.9 1.8 3.4 9.6 5 Persons ...................................... 7.1 1.6 1.2 1.3 0.6 0.7 1.6 14.3 6 or More Persons

91

Table 2. Number of U.S. Housing Units by Census Region and ...  

U.S. Energy Information Administration (EIA)

Home > Households, Buildings & Industry > Energy Efficiency > Residential Buildings Energy Intensities > Table 2. Number of U.S. ...

92

The Household Market for Electric Vehicles: Testing the Hybrid Household Hypothesis--A Reflively Designed Survey of New-car-buying, Multi-vehicle California Households  

E-Print Network (OSTI)

HOW MANY HYBRID HOUSEHOLDS IN THE CALIFORNIA NEW CAR MARKET?average 2.43 cars per household, then the hybrid householdnumber of multi-car households that fit our hybrid household

Turrentine, Thomas; Kurani, Kenneth

1995-01-01T23:59:59.000Z

93

Postdoctoral Society of Argonne - Members  

NLE Websites -- All DOE Office Websites (Extended Search)

The PSA is composed of a board of approximately 12 postdocs that organize activities and coordinate functions derived from our mission. Andrew Skipor and Kristene (Tina) Henne oversee the operations of the PSA board. The number of members varies as postdocs enter and exit the program, and we are always looking for new members. Meetings are open to all interested postdocs and are held the third Friday of the month in Building 223, Room L119. Send mail to Kristene (Tina) Henne to inquire. The PSA is composed of a board of approximately 12 postdocs that organize activities and coordinate functions derived from our mission. Andrew Skipor and Kristene (Tina) Henne oversee the operations of the PSA board. The number of members varies as postdocs enter and exit the program, and we are always looking for new members. Meetings are open to all interested postdocs and are held the third Friday of the month in Building 223, Room L119. Send mail to Kristene (Tina) Henne to inquire. PSA Officers: Martin Bettge, CSE (President) Prasanna Balaprakash, MCS (Vice President) Milind Malshe, CSE (Liaison Officer) Board Members: Chithra Kumaran Nair, NE Deepkishore Mukhopadhyay, CNM Kuldeep Mistry, ES Maxim Nikiforov, CNM Shaolin Liao, NE Si Chen, MSD General Members:

94

Household energy in South Asia  

Science Conference Proceedings (OSTI)

This research study on the use of energy in South Asis (India, Pakistan, Sri Lanka and Bangladesh) was sponsored by the Food and Agriculture Organization of the UN, the International Bank for Reconstruction and Development (the World Bank), and the Directorate-General for Development of the Commission of the European Communities. The aim of this book is to improve the understanding of household energy and its linkages, by reviewing the data resources on household energy use, supply, prices and other relevant factors that exist in South Asia.

Leach, G.

1987-01-01T23:59:59.000Z

95

A spotlight on security and privacy risks with future household robots: attacks and lessons  

Science Conference Proceedings (OSTI)

Future homes will be populated with large numbers of robots with diverse functionalities, ranging from chore robots to elder care robots to entertainment robots. While household robots will offer numerous benefits, they also have the potential to introduce ... Keywords: cyber-physical systems, domestic robots, household robots, multi-robot attack, privacy, robots, security, single-robot attack, ubiquitous robots

Tamara Denning; Cynthia Matuszek; Karl Koscher; Joshua R. Smith; Tadayoshi Kohno

2009-09-01T23:59:59.000Z

96

Assumptions to the Annual Energy Outlook 2002 - Household Expenditures...  

Annual Energy Outlook 2012 (EIA)

Expenditures Module The Household Expenditures Module (HEM) constructs household energy expenditure profiles using historical survey data on household income, population and...

97

spaceheat_household2001.pdf  

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

3a. Space Heating by Household Income, 3a. Space Heating by Household Income, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral Assist- ance 1 RSE Row Factors Less than $14,999 $15,000 to $29,999 $30,000 to $49,999 $50,000 or More 0.6 1.3 1.1 1.0 0.9 1.4 1.0 Total ............................................... 107.0 18.7 22.9 27.1 38.3 15.0 33.8 3.3 Heat Home ..................................... 106.0 18.4 22.7 26.8 38.1 14.6 33.4 3.3 Do Not Heat Home ........................ 1.0 0.3 Q 0.3 0.3 0.3 0.4 23.4 No Heating Equipment .................. 0.5 Q Q Q 0.2 Q Q 35.0 Have Equipment But Do Not Use It ................................ 0.4 Q Q Q Q 0.2 0.3 22.8 Main Heating Fuel and Equipment (Have and Use Equipment) ............ 106.0 18.4 22.7

98

appl_household2001.pdf  

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

3a. Appliances by Household Income, 3a. Appliances by Household Income, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral Assist- ance 1 RSE Row Factors Less than $14,999 $15,000 to $29,999 $30,000 to $49,999 $50,000 or More 0.5 1.4 1.1 1.0 0.8 1.6 1.0 Total ............................................... 107.0 18.7 22.9 27.1 38.3 15.0 33.8 3.2 Kitchen Appliances Cooking Appliances Oven ........................................... 101.7 18.0 22.0 26.1 35.6 14.4 32.6 3.2 1 ................................................ 95.2 17.3 21.1 24.8 32.0 13.8 31.1 3.4 2 or More .................................. 6.5 0.8 0.9 1.3 3.6 0.6 1.5 13.1 Most Used Oven ........................ 101.7 18.0 22.0 26.1 35.6 14.4 32.6 3.2

99

nSoft Member Agreements  

Science Conference Proceedings (OSTI)

Member Agreement. Members of the consortium will be required to sign a member cooperative research and development agreement (CRADA). ...

2013-02-20T23:59:59.000Z

100

Number, Energy Consumption, and Energy-Related Carbon ...  

U.S. Energy Information Administration (EIA)

Tabulation of changes in the number, energy consumption, and energy-related carbon emissions of U.S. households, 1980-1997.

Note: This page contains sample records for the topic "household members number" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


101

Household Energy Consumption and Expenditures 1993 -- Executive ...  

U.S. Energy Information Administration (EIA)

national level data on energy-related issues on households and energy expenditures in the residential sector.

102

Administrative Committee Members  

Science Conference Proceedings (OSTI)

Volunteer Training Module. March 2013. 1. Your Professional Partner for Career Advancement. Administrative Committee. Members. Online Training Module.

103

Technical Committee Member - TMS  

Science Conference Proceedings (OSTI)

Volunteer Training Module. March 2013. 1. Your Professional Partner for Career Advancement. Technical Committee Member. Online Training Module.

104

Award Committee Member  

Science Conference Proceedings (OSTI)

Volunteer Training Module. March 2013. 1. Your Professional Partner for Career Advancement. Award Committee Member. Online Training Module. March 2013 ...

105

Energy and household expenditure patterns  

Science Conference Proceedings (OSTI)

Since households account, either directly or indirectly, for two-thirds of the energy consumed in the US, changes in household activities will affect energy use. Expected changes in prices, personal income, and family spending over the next 20 years are looked at as well as the implications for energy consumption. The analysis shows that direct energy purchases will break with past trends, dropping from 2.6% to 0.2% annual growth for the rest of the century. Growth in spending on energy-using goods is also likely to slow down. The year 2000 will see a marked decrease in the growth of national energy consumption. 58 references, 3 figures, 35 tables.

Lareau, T.J.; Darmstadter, J.

1983-01-01T23:59:59.000Z

106

ac_household2001.pdf  

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

0a. Air Conditioning by Midwest Census Region, 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 ........................................ 80.8 20.2 13.4 6.7 2.3 Type of Electric Air-Conditioning Used Central Air-Conditioning 2 ............................ 57.5 14.3 9.5 4.8 3.8 Without a Heat Pump ................................ 46.2 13.6 9.0 4.6 3.9 With a Heat Pump .....................................

107

ac_household2001.pdf  

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

8a. Air Conditioning by Urban/Rural Location, 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 18.6 13.3 4.3 Type of Electric Air-Conditioning Used Central Air-Conditioning 3 ............................ 57.5 23.6 8.6 15.8 9.4 5.1 Without a Heat Pump ................................ 46.2 19.3 7.4 13.1 6.4 6.3 With a Heat Pump ..................................... 11.3 4.4

108

ac_household2001.pdf  

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

5a. Air Conditioning by Type of Owner-Occupied Housing Unit, 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 Electric Air-Conditioning 1 .......................... 58.2 57.6 6.3 11.8 5.1 5.3 Type of Electric Air-Conditioning Used Central Air-Conditioning 2 .............. 44.7 43.6 3.2 7.1 3.5 7.0 Without a Heat Pump .................. 35.6 35.0 2.4 6.1 2.7 7.7 With a Heat Pump .......................

109

ac_household2001.pdf  

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

6a. Air Conditioning by Type of Rented Housing Unit, 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 1 .......................... 22.5 57.6 6.3 11.8 5.1 6.2 Type of Electric Air-Conditioning Used Central Air-Conditioning 2 .............. 12.7 43.6 3.2 7.1 3.5 8.5 Without a Heat Pump .................. 10.6 35.0 2.4 6.1 2.7 9.3 With a Heat Pump ....................... 2.2 8.6 0.8 1.0

110

char_household2001.pdf  

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

2001 2001 Household Characteristics RSE Column Factor: Total U.S. Four Most Populated States RSE Row Factors New York California Texas Florida 0.4 1.1 1.0 1.5 1.5 Total .............................................................. 107.0 7.1 12.3 7.7 6.3 NE Household Size 1 Person ...................................................... 28.2 2.2 2.4 1.8 1.7 7.3 2 Persons .................................................... 35.1 2.2 4.0 2.4 2.0 6.9 3 Persons .................................................... 17.0 1.1 2.0 1.2 1.2 9.5 4 Persons .................................................... 15.6 0.8 1.9 1.3 0.9 11.2 5 Persons .................................................... 7.1 0.4 1.1 0.4 0.5 19.8 6 or More Persons ....................................... 4.0 0.4 0.9 0.4 0.1 16.4 2001 Household Income Category

111

ac_household2001.pdf  

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

1a. Air Conditioning by South Census Region, 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 ........................................ 80.8 36.9 19.0 6.4 11.5 1.6 Type of Electric Air-Conditioning Used Central Air-Conditioning 2 ............................ 57.5 30.4 16.1 5.0 9.2 2.8 Without a Heat Pump ................................ 46.2 22.1 10.4 3.4 8.3 5.6 With a Heat Pump

112

ac_household2001.pdf  

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

9a. Air Conditioning by Northeast Census Region, 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 ........................................ 80.8 14.2 11.1 3.2 3.4 Type of Electric Air-Conditioning Used Central Air-Conditioning 2 ............................ 57.5 5.7 4.9 0.8 8.9 Without a Heat Pump ................................ 46.2 5.2 4.5 0.7 9.2 With a Heat Pump .....................................

113

ac_household2001.pdf  

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

2a. Air Conditioning by Year of Construction, 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 .......................... 80.8 13.4 15.8 14.2 10.1 10.2 17.1 4.7 Type of Electric Air-Conditioning Used Central Air-Conditioning 3 .............. 57.5 12.6 13.7 11.0 7.1 6.6 6.4 5.9 Without a Heat Pump .................. 46.2 10.1 10.4 8.0 6.1 5.9 5.7 7.0 With a Heat Pump ....................... 11.3 2.5 3.3

114

Inconsistent pathways of household waste  

Science Conference Proceedings (OSTI)

The aim of this study was to provide policy-makers and waste management planners with information about how recycling programs affect the quantities of specific materials recycled and disposed of. Two questions were addressed: which factors influence household waste generation and pathways? and how reliable are official waste data? Household waste flows were studied in 35 Swedish municipalities, and a wide variation in the amount of waste per capita was observed. When evaluating the effect of different waste collection policies, it was found to be important to identify site-specific factors influencing waste generation. Eleven municipal variables were investigated in an attempt to explain the variation. The amount of household waste per resident was higher in populous municipalities and when net commuting was positive. Property-close collection of dry recyclables led to increased delivery of sorted metal, plastic and paper packaging. No difference was seen in the amount of separated recyclables per capita when weight-based billing for the collection of residual waste was applied, but the amount of residual waste was lower. Sixteen sources of error in official waste statistics were identified and the results of the study emphasize the importance of reliable waste generation and composition data to underpin waste management policies.

Dahlen, Lisa [Division of Waste Science and Technology, Lulea University of Technology, SE, 971 87 Lulea (Sweden)], E-mail: lisa.dahlen@ltu.se; Aberg, Helena [Department of Food, Health and Environment, University of Gothenburg, P.O. Box 12204, SE, 402 42 Gothenburg (Sweden); Lagerkvist, Anders [Division of Waste Science and Technology, Lulea University of Technology, SE, 971 87 Lulea (Sweden); Berg, Per E.O. [HB Anttilator, Stagnellsgatan 3, SE, 652 23, Karlstad (Sweden)

2009-06-15T23:59:59.000Z

115

ac_household2001.pdf  

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

4a. Air Conditioning by Type of Housing Unit, 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 .......................... 80.8 57.6 6.3 11.8 5.1 4.9 Type of Electric Air-Conditioning Used Central Air-Conditioning 2 .............. 57.5 43.6 3.2 7.1 3.5 6.7 Without a Heat Pump .................. 46.2 35.0 2.4 6.1 2.7 7.7 With a Heat Pump ....................... 11.3 8.6 0.8 1.0 0.8 19.7 Room Air-Conditioning

116

YOUR MEMBER CONNECTION  

Science Conference Proceedings (OSTI)

Korea Institute of Geoscience and Mineral. Resources in Daejeon, Republic of Korea. Dr. Lee has been a TMS member since. 1993. Page 29. Marks, Jerry Y. is  ...

117

YOUR MEMBER CONNECTION - TMS  

Science Conference Proceedings (OSTI)

the University of Kentucky. Mr. Abu-. Farha is an eight year member of TMS. Page 72. Apelian, Diran is Howmet Professor of Engineering at. Worcester Poly-.

118

New York Household Travel Patterns: A Comparison Analysis  

SciTech Connect

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

Hu, Patricia S [ORNL; Reuscher, Tim [ORNL

2007-05-01T23:59:59.000Z

119

Measurement of nicotine in household dust  

Science Conference Proceedings (OSTI)

An analytical method of measuring nicotine in house dust was optimized and associations among three secondhand smoking exposure markers were evaluated, i.e., nicotine concentrations of both house dust and indoor air, and the self-reported number of cigarettes smoked daily in a household. We obtained seven house dust samples from self-reported nonsmoking homes and 30 samples from smoking homes along with the information on indoor air nicotine concentrations and the number of cigarettes smoked daily from an asthma cohort study conducted by the Johns Hopkins Center for Childhood Asthma in the Urban Environment. House dust nicotine was analyzed by isotope dilution gas chromatography-mass spectrometry (GC/MS). Using our optimized method, the median concentration of nicotine in the dust of self-reported nonsmoking homes was 11.7 ng/mg while that of smoking homes was 43.4 ng/mg. We found a substantially positive association (r=0.67, P<0.0001) between house dust nicotine concentrations and the numbers of cigarettes smoked daily. Optimized analytical methods showed a feasibility to detect nicotine in house dust. Our results indicated that the measurement of nicotine in house dust can be used potentially as a marker of longer term SHS exposure.

Kim, Sungroul [Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Institute for Global Tobacco Control, 627 N. Washington Street, 2nd Floor Baltimore, MD 21205 (United States); Department of Environmental Health Sciences, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205 (United States)], E-mail: srkim@jhsph.edu; Aung, Ther; Berkeley, Emily [Department of Environmental Health Sciences, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205 (United States); Diette, Gregory B. [Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205 (United States); Department of Medicine, Johns Hopkins University School of Medicine (United States); Breysse, Patrick N. [Department of Environmental Health Sciences, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205 (United States)

2008-11-15T23:59:59.000Z

120

Collapsable seal member  

DOE Patents (OSTI)

A hollow, collapsable seal member normally disposed in a natural expanded state offering fail-safe pressure sealing against a seating surface and adapted to be evacuated by a vacuum force for collapsing the seal member to disengage the same from said seating surface.

Sherrell, Dennis L. (Kennewick, WA)

1990-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "household members number" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


121

RECS data show decreased energy consumption per household  

Reports and Publications (EIA)

Total United States energy consumption in homes has remained relatively stable for many years as increased energy efficiency has offset the increase in the number and average size of housing units, according to the newly released data from the Residential Energy Consumption Survey (RECS). The average household consumed 90 million British thermal units (Btu) in 2009 based on RECS. This continues the downward trend in average residential energy consumption of the last 30 years. Despite increases in the number and the average size of homes plus increased use of electronics, improvements in efficiency for space heating, air conditioning, and major appliances have all led to decreased consumption per household. Newer homes also tend to feature better insulation and other characteristics, such as double-pane windows, that improve the building envelope.

2012-06-06T23:59:59.000Z

122

Home > Households, Buildings & Industry > Energy Efficiency Page ...  

U.S. Energy Information Administration (EIA)

Home > Households, Buildings & Industry > Energy Efficiency Page > Energy Intensities >Table 7a Glossary U.S. Residential Housing Primary Page Last Revised: July 2009

123

Home > Households, Buildings & Industry > Energy Efficiency ...  

U.S. Energy Information Administration (EIA)

Glossary Home > Households, Buildings & Industry > Energy Efficiency > Residential Buildings Energy Intensities > Table 4 Total Square Feet of U.S. Housing Units

124

Home > Households, Buildings & Industry > Energy Efficiency Page ...  

U.S. Energy Information Administration (EIA)

Home > Households, Buildings & Industry > Energy Efficiency Page > Energy Intensities > Table 5c Glossary U.S. Residential Housing Site Page Last Revised: July 2009

125

Residential Energy Usage by Origin of Householder  

U.S. Energy Information Administration (EIA)

Home > Energy Users > Residential Home Page > Energy Usage by Origin of Householder. Consumption and Expenditures. NOTE: To View and/or Print PDF's ...

126

Home > Households, Buildings & Industry > Energy Efficiency Page ...  

U.S. Energy Information Administration (EIA)

Home > Households, Buildings & Industry > Energy Efficiency Page > Energy Intensities >Table 7b Glossary U.S. Residential Housing Primary Energy Intensity

127

Home > Households, Buildings & Industry > Energy Efficiency Page ...  

U.S. Energy Information Administration (EIA)

Home > Households, Buildings & Industry > Energy Efficiency Page > Energy Intensities > Table 8b Glossary U.S. Residential Buildings Primary Energy Intensity

128

Nationwide Survey on Household Energy Use  

U.S. Energy Information Administration (EIA)

4 ~ Apartment in house or building divided into 2, 3, or 4 apartments ... of your family (living in your household). Include income from all sources--before taxes

129

Alston S. Householder Fellowship | Careers | ORNL  

NLE Websites -- All DOE Office Websites (Extended Search)

in Scientific Computing honors Dr. Alston S. Householder, founding Director of the Mathematics Division (now Computer Science and Mathematics Division) at the Oak Ridge National...

130

ac_household2001.pdf  

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

2001 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 Air-Conditioning 2 ............................ 57.5 1.3 3.9 6.2 5.7 6.7 Without a Heat Pump ................................ 46.2 1.2 3.2 5.5 3.8 8.1 With a Heat Pump ..................................... 11.3 Q 0.8 0.6 1.9 14.7 Room Air-Conditioning ................................ 23.3 3.4 1.2 1.2 0.3 13.6 1 Unit

131

Electricity Prices for Households - EIA  

Gasoline and Diesel Fuel Update (EIA)

Households for Selected Countries1 Households for Selected Countries1 (U.S. Dollars per Kilowatthour) Country 2001 2002 2003 2004 2005 2006 2007 2008 2009 Argentina NA NA NA NA NA NA 0.023 NA NA Australia 0.091 0.092 0.094 0.098 NA NA NA NA NA Austria 0.144 0.154 0.152 0.163 0.158 0.158 0.178 0.201 NA Barbados NA NA NA NA NA NA NA NA NA Belgium NA NA NA NA NA NA NA NA NA Bolivia NA NA NA NA NA NA NA NA NA Brazil NA NA NA NA NA NA 0.145 0.171 NA Canada 0.067 0.069 0.070 0.071 0.076 0.078 NA NA NA Chile NA NA NA NA NA NA 0.140 0.195 NA China NA NA NA NA NA NA NA NA NA Chinese Taipei (Taiwan) 0.075 0.071 0.074 0.076 0.079 0.079 0.080 0.086 NA Colombia NA NA NA NA NA NA 0.111 0.135 NA

132

Assumptions to the Annual Energy Outlook - Household Expenditures Module  

Gasoline and Diesel Fuel Update (EIA)

Household Expenditures Module Household Expenditures Module Assumption to the Annual Energy Outlook Household Expenditures Module Figure 5. United States Census Divisions. Having problems, call our National Energy Information Center at 202-586-8800 for help. The Household Expenditures Module (HEM) constructs household energy expenditure profiles using historical survey data on household income, population and demographic characteristics, and consumption and expenditures for fuels for various end-uses. These data are combined with NEMS forecasts of household disposable income, fuel consumption, and fuel expenditures by end-use and household type. The HEM disaggregation algorithm uses these combined results to forecast household fuel consumption and expenditures by income quintile and Census Division (see

133

YOUR MEMBER CONNECTION  

Science Conference Proceedings (OSTI)

www.tms.org/jom.html. OTHER MEMBERS FEATURED IN THIS ISSUE. Allison, John, p. 5. Alvear, Gerardo R.F., p. 3. Apelian, Diran, p. 10. Bakker, Martin L., p. 3.

134

YOUR MEMBER CONNECTION  

Science Conference Proceedings (OSTI)

Zhang, Fan is President of CompuTherm,. LLC, Madison, Wisconsin. She became a. TMS member in 1994 when she was a Ph.D. student at the University of ...

135

Hydraulic Institute Member Benefits  

Energy.gov (U.S. Department of Energy (DOE))

As the developer of the universally acclaimed ANSI/HI Pump Standards, a key reference for pump knowledge and end-user specifications, the Hydraulic  nstitute (HI) provides its members with timely...

136

Fuelwood Use by Rural Households in the Brazilian Atlantic Forest  

E-Print Network (OSTI)

Fuelwood is an important source of domestic energy in rural regions of Brazil. In the Zona da Mata of Minas Gerais, native species from the Atlantic Forest are an important source of fuelwood, supplemented by wood from eucalyptus and coffee plantations. The use of native species is complicated by their increasing scarcity and the recent enforcement of forest policies that prohibit the felling of even dead natives trees without a permit. In this study, the factors contributing to the use of fuelwood in this region, despite the simultaneous use of liquid petroleum gas in most households, are explored by examining fuelwood use patterns in four small rural communities in the Zona da Mata Mineira using household surveys and semi-structured interviews. Two hypotheses were tested using a Jacknife regression. The first hypothesis, based on the energy ladder model, tested the predictive power of socioeconomic status in relation to fuelwood use. Two dependent variables were used to represent the importance of fuelwood to a household: the amount of time a household spent collecting fuelwood (Effort) and the number of purposes a household used fuelwood for (Class of Fuelwood Use). Socioeconomic status did explain a statistically significant percentage of the variance in Effort, but not in Class of Fuelwood Use. The second hypothesis tested for a moderating effect of the availability of fuelwood on the relationship between the socioeconomic status of a household and the dependent variables. The interaction between access to fuelwood and socioeconomic status was shown to explain a significant percentage of the variance in Effort, thereby indicating that the effect of socioeconomic status on time spent collecting fuelwood depends on access to fuelwood. However, there was no statistically significant interaction found between Class of Fuelwood Use and fuelwood availability. The Atlantic Forest Policy was found to have little influence on domestic energy decisions made by surveyed households. Few research subjects had a good understanding of the basic tenets of this policy and the Forest Police do not have adequate resources to enforce the policy at this level.

Wilcox-Moore, Kellie J.

2010-05-01T23:59:59.000Z

137

A Mixed Nordic Experience: Implementing Competitive Retail Electricity Markets for Household Customers  

Science Conference Proceedings (OSTI)

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)

Olsen, Ole Jess; Johnsen, Tor Arnt; Lewis, Philip

2006-11-15T23:59:59.000Z

138

appl_household2001.pdf  

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

9a. Appliances by Northeast Census Region, 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 .............................................................. 95.2 18.2 13.3 4.9 1.1 2 or More ................................................. 6.5 1.4 1.1 0.3 11.7 Most Used Oven ...................................... 101.7 19.6 14.5 5.2 1.1 Electric .....................................................

139

spaceheat_household2001.pdf  

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

1a. Space Heating by South Census Region, 1a. Space Heating by South Census Region, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total U.S. South Census Region RSE Row Factors Total Census Division South Atlantic East South Central West South Central 0.5 0.9 1.2 1.4 1.3 Total .............................................................. 107.0 38.9 20.3 6.8 11.8 NE Heat Home .................................................... 106.0 38.8 20.2 6.8 11.8 NE Do Not Heat Home ....................................... 1.0 Q Q Q Q 20.1 No Heating Equipment ................................ 0.5 Q Q Q Q 39.8 Have Equipment But Do Not Use It ............................................... 0.4 Q Q Q Q 39.0 Main Heating Fuel and Equipment (Have and Use Equipment) ........................... 106.0

140

spaceheat_household2001.pdf  

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

9a. Space Heating by Northeast Census Region, 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 Heating Equipment ................................ 0.5 Q Q Q 39.5 Have Equipment But Do Not Use It ............................................... 0.4 Q Q Q 38.7 Main Heating Fuel and Equipment (Have and Use Equipment) ........................... 106.0 20.1 14.7 5.4 NE Natural Gas .................................................

Note: This page contains sample records for the topic "household members number" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


141

spaceheat_household2001.pdf  

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

0a. Space Heating by Midwest Census Region, 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 Heating Equipment ................................ 0.5 Q Q Q 39.2 Have Equipment But Do Not Use It ............................................... 0.4 Q Q Q 38.4 Main Heating Fuel and Equipment (Have and Use Equipment) ........................... 106.0 24.5 17.1 7.4 NE Natural Gas

142

spaceheat_household2001.pdf  

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

2a. Space Heating by West Census Region, 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 ................................ 0.5 0.4 Q 0.4 18.1 Have Equipment But Do Not Use It ............................................... 0.4 0.2 Q 0.2 27.5 Main Heating Fuel and Equipment (Have and Use Equipment) ........................... 106.0 22.6 6.7 15.9 NE Natural Gas .................................................

143

appl_household2001.pdf  

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

2a. Appliances by West Census Region, 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 .............................................................. 95.2 20.9 6.4 14.5 1.1 2 or More ................................................. 6.5 1.2 0.2 1.0 14.6 Most Used Oven ...................................... 101.7 22.1 6.6 15.5 1.1 Electric .....................................................

144

Factors influencing county level household fuelwood use  

Science Conference Proceedings (OSTI)

This study explains household fuelwood consumption behavior at the county level by linking it to economic and demographic conditions in counties. Using this link, counties are identified where potential fuelwood use problems and benefits are greatest. A probit equation estimates household probability of wood use (percent woodburners in a county heating degree days, household income, nonwood fuel price, fuelwood price, percent forest land, population density, and fraction of households using various types of heating equipment. A linear-in-parameters equation estimates average wood consumed by a woodburner based on county heating degree days, household income, percent forest land, and price of nonwood fuel divided by fuelwood price. Parameters are estimated using fuelwood use data for individual households from a 1908-81 nationwide survey. The probit equation predicts percentage of wood burns well over a wide range of county conditions. The wood consumption equation overpredicts for counties with high income and high population density (over 6000 persons per square mile). The model shows average woodburning per household over all households decreases with increasing population density, and the influence of county economic characteristics varies with density.

Skog, K.E.

1986-01-01T23:59:59.000Z

145

Characterization of household waste in Greenland  

Science Conference Proceedings (OSTI)

The composition of household waste in Greenland was investigated for the first time. About 2 tonnes of household waste was sampled as every 7th bag collected during 1 week along the scheduled collection routes in Sisimiut, the second largest town in Greenland with about 5400 inhabitants. The collection bags were sorted manually into 10 material fractions. The household waste composition consisted primarily of biowaste (43%) and the combustible fraction (30%), including anything combustible that did not belong to other clean fractions as paper, cardboard and plastic. Paper (8%) (dominated by magazine type paper) and glass (7%) were other important material fractions of the household waste. The remaining approximately 10% constituted of steel (1.5%), aluminum (0.5%), plastic (2.4%), wood (1.0%), non-combustible waste (1.8%) and household hazardous waste (1.2%). The high content of biowaste and the low content of paper make Greenlandic waste much different from Danish household waste. The moisture content, calorific value and chemical composition (55 elements, of which 22 were below detection limits) were determined for each material fraction. These characteristics were similar to what has been found for material fractions in Danish household waste. The chemical composition and the calorific value of the plastic fraction revealed that this fraction was not clean but contained a lot of biowaste. The established waste composition is useful in assessing alternative waste management schemes for household waste in Greenland.

Eisted, Rasmus, E-mail: raei@env.dtu.dk [Department of Environmental Engineering, Technical University of Denmark, Kongens Lyngby (Denmark); Christensen, Thomas H. [Department of Environmental Engineering, Technical University of Denmark, Kongens Lyngby (Denmark)

2011-07-15T23:59:59.000Z

146

Modeling patterns of hot water use in households  

E-Print Network (OSTI)

7 No Dishwashers . . . . . . . .to households without dishwashers. no_cw is only applied towasher; the absence of a dishwasher; a household consisting

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

1996-01-01T23:59:59.000Z

147

Probit Model Estimation Revisited: Trinomial Models of Household Car Ownership  

E-Print Network (OSTI)

Household Ownership of Car Davidon, W. C. (1959) VariableStudy Report 9: Models of Car Ownership and License Holding.Trinomial Models of Household Car Ownership. Transportation

Bunch, David S.; Kitamura, Ryuichi

1991-01-01T23:59:59.000Z

148

ASSESSMENT OF HOUSEHOLD CARBON FOOTPRINT REDUCTION POTENTIALS  

SciTech Connect

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.

Kramer, Klaas Jan; Homan, Greg; Brown, Rich; Worrell, Ernst; Masanet, Eric

2009-04-15T23:59:59.000Z

149

Urban household energy use in Thailand  

SciTech Connect

Changes in household fuel and electricity use that accompany urbanization in Third World countries bear large economic and environmental costs. The processes driving the fuel transition, and the policy mechanisms by which it can be influenced, need to be better understood for the sake of forecasting and planning, especially in the case of electricity demand. This study examines patterns of household fuel use and electrical appliance utilization in Bangkok, Chieng Mai and Ayutthaya, Thailand, based on the results of a household energy survey. Survey data are statistically analyzed using a variety of multiple regression techniques to evaluate the relative influence of various household and fuel characteristics on fuel and appliance choice. Results suggest that changes to the value of women's time in urban households, as women become increasingly active in the labor force, have a major influence on patterns of household energy use. The use of the home for small-scale commercial activities, particularly food preparation, also has a significant influence on fuel choice. In general, household income does not prove to be an important factor in fuel and appliance selection in these cities, although income is closely related to total electricity use. The electricity use of individual household appliances is also analyzed using statistical techniques as well as limited direct metering. The technology of appliance production in Thailand is evaluated through interviews with manufacturers and comparisons of product performance. These data are used to develop policy recommendations for improving the efficiency of electrical appliances in Thailand by relying principally on the dynamism of the consumer goods market, rather than direct regulation. The annual electricity savings from the recommended program for fostering rapid adoption of efficient technologies are estimated to reach 1800 GWh by the year 2005 for urban households alone.

Tyler, S.R.

1992-01-01T23:59:59.000Z

150

Did Household Consumption Become More Volatile?  

E-Print Network (OSTI)

I show that after accounting for predictable variation arising from movements in real interest rates, preferences, income shocks, liquidity constraints and measurement errors, volatility of household consumption in the US increased between 1970 and 2004. For households headed by nonwhite and/or poorly educated individuals, this rise was significantly larger. This stands in sharp contrast with the dramatic fall in instability of the aggregate U.S. economy over the same period. Thus, while aggregate shocks affecting households fell over time, idiosyncratic shocks increased. This finding may lead to significant welfare implications.

Olga Gorbachev

2009-01-01T23:59:59.000Z

151

appl_household2001.pdf  

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

a. Appliances by Climate Zone, 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 .............................................. 101.7 9.1 27.9 23.1 19.4 22.2 7.8 1 ................................................... 95.2 8.7 26.0 21.6 17.7 21.2 7.9 2 or More ..................................... 6.5 0.4 1.9 1.5 1.7 1.0 14.7 Most Used Oven ........................... 101.7 9.1 27.9 23.1 19.4 22.2

152

appl_household2001.pdf  

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

4a. Appliances by Type of Housing Unit, 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 ................................................ 95.2 63.7 8.9 16.2 6.3 4.3 2 or More .................................. 6.5 5.4 0.4 0.4 0.2 15.9 Most Used Oven ........................ 101.7 69.1 9.4 16.7 6.6 4.3 Electric ...................................... 63.0 43.3 5.2 10.9 3.6

153

spaceheat_household2001.pdf  

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

8a. Space Heating by Urban/Rural Location, 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 Equipment ................................ 0.5 0.4 0.1 Q 0.1 33.2 Have Equipment But Do Not Use It ............................................... 0.4 0.3 Q Q Q 30.2 Main Heating Fuel and Equipment (Have and Use Equipment) ........................... 106.0 49.1 18.0 21.2 17.8 4.3 Natural Gas

154

spaceheat_household2001.pdf  

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

2a. Space Heating by Year of Construction, 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 ........................ 1.0 Q Q Q 0.2 0.3 Q 23.2 No Heating Equipment .................. 0.5 Q Q Q 0.2 Q Q 30.3 Have Equipment But Do Not Use It ................................ 0.4 Q Q Q Q Q Q 37.8 Main Heating Fuel and Equipment (Have and Use Equipment) ............ 106.0 15.4 18.2 18.6 13.6 13.9 26.4 4.3 Natural Gas ...................................

155

appl_household2001.pdf  

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

5a. Appliances by Type of Owner-Occupied Housing Unit, 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 ........................................... 68.3 59.1 2.0 1.7 5.4 7.0 1 ................................................ 62.9 54.1 2.0 1.6 5.2 7.1 2 or More .................................. 5.4 5.0 Q Q 0.2 22.1 Most Used Oven ........................ 68.3 59.1 2.0 1.7 5.4 7.0 Electric ......................................

156

spaceheat_household2001.pdf  

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

4a. Space Heating by Type of Housing Unit, 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 Heating Equipment .................. 0.5 0.2 Q 0.3 Q 24.2 Have Equipment But Do Not Use It ................................ 0.4 Q Q 0.3 Q 28.1 Main Heating Fuel and Equipment (Have and Use Equipment) ............ 106.0 73.4 9.4 16.4 6.8 4.5 Natural Gas ...................................

157

spaceheat_household2001.pdf  

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

5a. Space Heating by Type of Owner-Occupied Housing Unit, 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 ........................ 0.4 0.2 Q Q Q 46.2 No Heating Equipment .................. 0.3 0.2 Q Q Q 39.0 Have Equipment But Do Not Use It ................................ Q Q Q Q Q NF Main Heating Fuel and Equipment (Have and Use Equipment) ............ 72.4 63.0 2.0 1.7 5.7 6.7 Natural Gas

158

appl_household2001.pdf  

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

2a. Appliances by Year of Construction, 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 ................................................ 95.2 13.1 16.3 16.6 12.1 12.7 24.3 4.4 2 or More .................................. 6.5 1.2 0.9 1.1 0.7 1.0 1.6 14.8 Most Used Oven ........................ 101.7 14.3 17.2 17.8 12.9 13.7 25.9 4.2 Electric ......................................

159

spaceheat_household2001.pdf  

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

6a. Space Heating by Type of Rented Housing Unit, 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 ........................ 0.6 Q Q 0.5 Q 21.4 No Heating Equipment .................. 0.2 Q Q Q Q 84.5 Have Equipment But Do Not Use It ................................ 0.4 Q Q 0.3 Q 36.4 Main Heating Fuel and Equipment (Have and Use Equipment) ............ 33.7 10.4 7.4 14.8 1.1 6.9 Natural Gas ...................................

160

AOCS Member Lapel Pin  

Science Conference Proceedings (OSTI)

AOCS logo pin. AOCS Member Lapel Pin Membership Merchandise Membership Merchandise Wear this logo and proudly proclaim your association with the AOCS. Fashioned from brass and enamel. F81E3365C84403AD09C61361EDCFB7EF M-PIN 2015

Note: This page contains sample records for the topic "household members number" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


161

Development of the Household Sample for Furnace and Boiler Life-Cycle Cost  

NLE Websites -- All DOE Office Websites (Extended Search)

Development of the Household Sample for Furnace and Boiler Life-Cycle Cost Development of the Household Sample for Furnace and Boiler Life-Cycle Cost Analysis Title Development of the Household Sample for Furnace and Boiler Life-Cycle Cost Analysis Publication Type Report LBNL Report Number LBNL-55088 Year of Publication 2005 Authors Whitehead, Camilla Dunham, Victor H. Franco, Alexander B. Lekov, and James D. Lutz Document Number LBNL-55088 Pagination 22 Date Published May 31 Publisher Lawrence Berkeley National Laboratory City Berkeley Abstract 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.

162

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 ï‚· California households use 62 million Btu of energy per home, 31% less than the U.S. average. The lower than average site consumption results in households spending 30% less for energy than the U.S. average. ï‚· Average site electricity consumption in California homes is among the lowest in the nation, as the mild climate in much of the state leads to less reliance on

163

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 ï‚· California households use 62 million Btu of energy per home, 31% less than the U.S. average. The lower than average site consumption results in households spending 30% less for energy than the U.S. average. ï‚· Average site electricity consumption in California homes is among the lowest in the nation, as the mild climate in much of the state leads to less reliance on

164

U.S. Household Electricity Report  

Reports and Publications (EIA)

Brief analysis reports on the amount of electricity consumed annually by U.S. households for each of several end uses, including space heating and cooling, water heating, lighting, and the operation of more than two dozen appliances.

Barbara Fichman

2005-07-14T23:59:59.000Z

165

Household gasoline demand in the United States  

E-Print Network (OSTI)

Continuing rapid growth in U.S. gasoline consumption threatens to exacerbate environmental and congestion problems. We use flexible semiparametric and nonparametric methods to guide analysis of household gasoline consumption, ...

Schmalensee, Richard

1995-01-01T23:59:59.000Z

166

Household energy consumption and expenditures 1993  

Science Conference Proceedings (OSTI)

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.

NONE

1995-10-05T23:59:59.000Z

167

Do Disaster Expectations Explain Household Portfolios?  

E-Print Network (OSTI)

use the American Consumer Expenditure Survey (CEX) for consumption ex- penditure information. The data covers the period between 1983 and 2004. The expenditure information is recorded quarterly with approximately 5000 households in each wave. Every...

Alan, Sule

168

The Determinants of Homeonwership in Presence of Shocks Experienced by Mexican Households  

E-Print Network (OSTI)

Homeownership is both an individual and society objective, because of the positive neighborhood effects associated with areas of higher homeownership. To help realize these positive effects, the Mexican government has several programs directed to increasing homeownership. Many factors, however, may influence homeownership including shocks experienced by households. Shocks such as death in family, illness or accidents, unemployment, and business, crop, or livestock loss affect homeownership if households are unable to cushion the impact of the shock. Government income support programs, however, may help cushion the effect of a shock. The main objective is to determine how shocks that households’ experience and government income support programs influence homeownership in Mexico. A secondary objective is to determine how socio-demographic variables influence homeownership in Mexico. Based on the Random Utility Model, logit models of homeownership are estimated using data are from the 2002 Mexican National Survey on Living Levels of Households. Two models are estimated; with and without income. Income is excluded because of a large number of households that did not report income. Generally, inferences from the two models are similar. Homeownership appears to not be affected by shocks experienced by households. It appears households are able to cushion the impact of shocks. The two income support programs, the Program of Direct Rural Support of Mexico (PROGRESA) and the Program of Direct Rural Support of Mexico (PROCAMPO), appear to be increasing homeownership. These social welfare programs provide cash transfers to households. For whatever reason, PROGRESA has a larger effect on homeownership than PROCAMPO. Households with older heads have a larger probability of being a homeowner than households with younger heads. No statistically significance relationship exists between education and homeownership. Regional differences are seen in homeownership, with households located in the northwest region having a higher probability of homeownership than other regions. Differences in the significance of variable representing the household head’s gender, marital status, and occupation on homeownership exist between logit models that include and do not include current income. The most likely reason for these differences is interactions between the variables and a wealth effect.

Lopez Cabrera, Jesus 1977-

2012-12-01T23:59:59.000Z

169

Table A1. U.S. Number of Vehicles, Vehicle-Miles, Motor Fuel ...  

U.S. Energy Information Administration (EIA)

Number of Vehicles Vehicle-Miles Traveled Motor Fuel Consumption Motor Fuel 2001 Household and Vehicle Expenditures ... Age of Primary Driver 16 to 17 Years ...

170

" Million U.S. Housing Units"  

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

3 Lighting Usage Indicators by Number of Household Members, 2005" " Million U.S. Housing Units" ,,"Number of Households With --" ,"Housing Units (millions)" ,,"1 Member","2...

171

" Million U.S. Housing Units"  

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

7 Air-Conditioning Usage Indicators by Number of Household Members, 2005" " Million U.S. Housing Units" ,,"Number of Households With --" ,"Housing Units (millions)" ,,"1 Member","2...

172

Cryogenic support member  

DOE Patents (OSTI)

A cryogenic support member is comprised of a nonmetallic rod having a depression in at least one end and a metallic end connection assembled to the rod. The metallic end connection comprises a metallic plug which conforms to the shape and is disposed in the depression and a metallic sleeve is disposed over the rod and plug. The plug and the sleeve are shrink-fitted to the depression in the rod to form a connection good in compression, tension and bending.

Niemann, R.C.; Gonczy, J.D.; Nicol, T.H.

1986-05-15T23:59:59.000Z

173

The federal energy policy: An example of its potential impact on energy consumption and expenditures in minority and poor households  

SciTech Connect

This report presents an analysis of the relative impacts of the National Energy Strategy on majority and minority households and on nonpoor and poor households. (Minority households are defined as those headed by black or Hispanic persons; poor households are defined as those having combined household income less than or equal to 125% of the Office of Management and Budget`s poverty-income threshold.) Energy consumption and expenditures, and projected energy expenditures as a share of income, for the period 1987 to 2009 are reported. Projected consumptions of electricity and nonelectric energy over this period are also reported for each group. An analysis of how these projected values are affected under different housing growth scenarios is performed. The analysis in this report presents a preliminary set of projections generated under a set of simplifying assumptions. Future analysis will rigorously assess the sensitivity of the projected values to various changes in a number of these assumptions.

Poyer, D.A.

1991-09-01T23:59:59.000Z

174

Rediness Review Team Member Training  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

MEMBER MEMBER TRAINING Idaho National Engineering Laboratory Michael Hillman DOE HQ - HSS Idaho National Engineering Laboratory Dan M. Stover, PE Technical And Professional Services, Inc. 47 James Habersham Blvd Beaufort, SC 29906 Official DOE Team Member Readiness Review Training November 8-9, 2010 Module 1 Module 1 READINESS REVIEW TEAM MEMBER TRAINING Introduction & Course Conduct Readiness Review Readiness Review Official DOE Team Member Readiness Review Training November 2010 TRAINING READINESS REVIEW TEAM MEMBER TRAINING Purpose of this Course Provide Prospective Readiness Review Team members h with: * An understanding of the background behind the Readiness Review Process; e e ocess; * Training in the mechanics of performance and reporting of

175

Effects on minority and low-income households of the EPA proposal to reduce leaded gasoline use  

DOE Green Energy (OSTI)

To reduce the potentially harmful environmental effects of lead in the environment, the US Environmental Protection Agency (EPA) has proposed a reduction in the amount of lead used in leaded gasoline. This report examines the potential impacts of such action on minority and low-income households in the US. The benefits of the EPA's proposal would presumably accrue primarily to households that contain small children and that are located in the central cities of metropolitan areas. This is because small children (under age seven) are particularly susceptible to the effects of lead and also because the automobile traffic density in central cities is higher than in any other area. Potential costs are examined in terms of households that own vehicles requiring leaded gasoline. Costs could accrue either because of higher gasoline prices due to reduced lead content or because of higher vehicle repair costs for engines that must use leaded gasoline to prevent excessive wear. Because of their location and number, minority and low-income households with small children would benefit more than the average US household. No costs would be incurred by the relatively large segment of minority and low-income households that own no vehicles. However, the Hispanic and other minority (except black) and low-income households that do own vehicles have a greater than average share of vehicles that require leaded gasoline; costs to these households because of the EPA's proposed action would be comparatively high.

Rose, K.; LaBelle, S.; Winter, R.; Klein, Y.

1985-04-01T23:59:59.000Z

176

Vehicle Technologies Office: Fact #451: January 8, 2007 Household Vehicle  

NLE Websites -- All DOE Office Websites (Extended Search)

1: January 8, 1: January 8, 2007 Household Vehicle Trips to someone by E-mail Share Vehicle Technologies Office: Fact #451: January 8, 2007 Household Vehicle Trips on Facebook Tweet about Vehicle Technologies Office: Fact #451: January 8, 2007 Household Vehicle Trips on Twitter Bookmark Vehicle Technologies Office: Fact #451: January 8, 2007 Household Vehicle Trips on Google Bookmark Vehicle Technologies Office: Fact #451: January 8, 2007 Household Vehicle Trips on Delicious Rank Vehicle Technologies Office: Fact #451: January 8, 2007 Household Vehicle Trips on Digg Find More places to share Vehicle Technologies Office: Fact #451: January 8, 2007 Household Vehicle Trips on AddThis.com... Fact #451: January 8, 2007 Household Vehicle Trips In a day, the average household traveled 32.7 miles in 2001 (the latest

177

Vehicle Technologies Office: Fact #392: October 3, 2005 Household Vehicle  

NLE Websites -- All DOE Office Websites (Extended Search)

2: October 3, 2: October 3, 2005 Household Vehicle Ownership to someone by E-mail Share Vehicle Technologies Office: Fact #392: October 3, 2005 Household Vehicle Ownership on Facebook Tweet about Vehicle Technologies Office: Fact #392: October 3, 2005 Household Vehicle Ownership on Twitter Bookmark Vehicle Technologies Office: Fact #392: October 3, 2005 Household Vehicle Ownership on Google Bookmark Vehicle Technologies Office: Fact #392: October 3, 2005 Household Vehicle Ownership on Delicious Rank Vehicle Technologies Office: Fact #392: October 3, 2005 Household Vehicle Ownership on Digg Find More places to share Vehicle Technologies Office: Fact #392: October 3, 2005 Household Vehicle Ownership on AddThis.com... Fact #392: October 3, 2005 Household Vehicle Ownership Household vehicle ownership has changed significantly over the last 40

178

A Multi Agent-Based Framework for Simulating Household PHEV Distribution and Electric Distribution Network Impact  

DOE Green Energy (OSTI)

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.

Cui, Xiaohui [ORNL; Liu, Cheng [ORNL; Kim, Hoe Kyoung [ORNL; Kao, Shih-Chieh [ORNL; Tuttle, Mark A [ORNL; Bhaduri, Budhendra L [ORNL

2011-01-01T23:59:59.000Z

179

Vehicle Technologies Office: Fact #453: January 22, 2007 Household Vehicle  

NLE Websites -- All DOE Office Websites (Extended Search)

3: January 22, 3: January 22, 2007 Household Vehicle Ownership to someone by E-mail Share Vehicle Technologies Office: Fact #453: January 22, 2007 Household Vehicle Ownership on Facebook Tweet about Vehicle Technologies Office: Fact #453: January 22, 2007 Household Vehicle Ownership on Twitter Bookmark Vehicle Technologies Office: Fact #453: January 22, 2007 Household Vehicle Ownership on Google Bookmark Vehicle Technologies Office: Fact #453: January 22, 2007 Household Vehicle Ownership on Delicious Rank Vehicle Technologies Office: Fact #453: January 22, 2007 Household Vehicle Ownership on Digg Find More places to share Vehicle Technologies Office: Fact #453: January 22, 2007 Household Vehicle Ownership on AddThis.com... Fact #453: January 22, 2007 Household Vehicle Ownership

180

Vehicle Technologies Office: Fact #455: February 5, 2007 Household Vehicle  

NLE Websites -- All DOE Office Websites (Extended Search)

5: February 5, 5: February 5, 2007 Household Vehicle Miles to someone by E-mail Share Vehicle Technologies Office: Fact #455: February 5, 2007 Household Vehicle Miles on Facebook Tweet about Vehicle Technologies Office: Fact #455: February 5, 2007 Household Vehicle Miles on Twitter Bookmark Vehicle Technologies Office: Fact #455: February 5, 2007 Household Vehicle Miles on Google Bookmark Vehicle Technologies Office: Fact #455: February 5, 2007 Household Vehicle Miles on Delicious Rank Vehicle Technologies Office: Fact #455: February 5, 2007 Household Vehicle Miles on Digg Find More places to share Vehicle Technologies Office: Fact #455: February 5, 2007 Household Vehicle Miles on AddThis.com... Fact #455: February 5, 2007 Household Vehicle Miles The graphs below show the average vehicle miles of travel (VMT) - daily

Note: This page contains sample records for the topic "household members number" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


181

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

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

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...

182

Vehicle Technologies Office: Fact #259: March 17, 2003 Household...  

NLE Websites -- All DOE Office Websites (Extended Search)

9: March 17, 2003 Household Travel by Gender to someone by E-mail Share Vehicle Technologies Office: Fact 259: March 17, 2003 Household Travel by Gender on Facebook Tweet about...

183

Essays on household decision making in developing countries  

E-Print Network (OSTI)

This dissertation contains three essays on household decision making in the areas of education and health in developing countries. The first chapter explores intra-household decision making in the context of conditional ...

Berry, James W. (James Wesley)

2009-01-01T23:59:59.000Z

184

Development of the Household Sample for Furnace and Boiler Life...  

NLE Websites -- All DOE Office Websites (Extended Search)

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...

185

ANALYSIS OF CEE HOUSEHOLD SURVEY NATIONAL AWARENESS OF ENERGY STAR  

NLE Websites -- All DOE Office Websites (Extended Search)

ANALYSIS OF CEE HOUSEHOLD SURVEY ANALYSIS OF CEE HOUSEHOLD SURVEY NATIONAL AWARENESS OF ENERGY STAR ® FOR 2012 TABLE OF CONTENTS Acknowledgements .................................................................................. ii Executive Summary ............................................................................ ES-1 Introduction ............................................................................................... 1 Methodology Overview ............................................................................. 2 Key Findings ............................................................................................. 5 Recognition .................................................................................................................. 5 Understanding ........................................................................................................... 12

186

Household Vehicles Energy Consumption 1991  

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

C C Quality of the Data Appendix C Quality of the Data Introduction This appendix discusses several issues relating to the quality of the Residential Transportation Energy Consumption Survey (RTECS) data and to the interpretation of conclusions based on these data. The first section discusses under- coverage of the vehicle stock in the residential sector. The second section discusses the effects of using July 1991 as a time reference for the survey. The remainder of this appendix discusses the treatment of sampling and nonsampling errors in the RTECS, the quality of specific data items such as the Vehicle Identification Number (VIN) and fuel prices, and poststratification procedures used in the 1991 RTECS. The quality of the data collection and the processing of the data affects the accuracy of estimates based on survey data. All the statistics published in this report such as total

187

Household energy and consumption and expenditures, 1990. Supplement, Regional  

Science Conference Proceedings (OSTI)

The purpose of this supplement to the Household Energy Consumption and Expenditures 1990 report is to provide information on the use of energy in residential housing units, specifically at the four Census regions and nine Census division levels. This report includes household energy consumption, expenditures, and prices for natural gas, electricity, fuel oil, liquefied petroleum gas (LPG), and kerosene as well as household wood consumption. For national-level data, see the main report, Household Energy Consumption and Expenditures 1990.

Not Available

1993-03-02T23:59:59.000Z

188

Residential energy consumption and expenditure patterns of low-income households in the United States  

SciTech Connect

The principal objective of this study is to compare poor and non-poor households with respect to energy consumption and expenditures, housing characteristics, and energy-related behavior. We based our study on an analysis of a national data base created by the US Department of Energy, the 1982-1983 Residential Energy Consumption Survey (RECS). RECS includes detailed information on individual households: demographic characteristics, energy-related features of the structure, heating equipment and appliances, recent conservation actions taken by the household, and fuel consumption and costs for April 1982-March 1983. We found a number of statistically significant (at the 0.05 level) differences between the two income groups in terms of demographics, heating/cooling/water heating systems, appliance saturation, the thermal integrity of their home, energy conservation behavior, energy consumption, energy expenditures, and the percentage of income spent on energy costs. For example, the non-poor used 22% more energy and paid 25% more money on utilities than the poor; however, the poor spent 20% more energy per square foot than the non-poor and spent about 25% of their income on energy expenditures, compared to 7% for the non-poor. These differences suggest different approaches that might be taken for targeting energy conservation programs to low-income households. Since the poor's ''energy burden'' is large, informational, technical, and financial assistance to low-income households remains an urgent, national priority. 13 refs., 26 tabs.

Vine, E.L.; Reyes, I.

1987-09-01T23:59:59.000Z

189

Indoor Secondary Pollutants from Household Product Emissions in the  

NLE Websites -- All DOE Office Websites (Extended Search)

Indoor Secondary Pollutants from Household Product Emissions in the Indoor Secondary Pollutants from Household Product Emissions in the Presence of Ozone: A Bench-Scale Chamber Study Title Indoor Secondary Pollutants from Household Product Emissions in the Presence of Ozone: A Bench-Scale Chamber Study Publication Type Journal Article LBNL Report Number LBNL-58785 Year of Publication 2006 Authors Destaillats, Hugo, Melissa M. Lunden, Brett C. Singer, Beverly K. Coleman, Alfred T. Hodgson, Charles J. Weschler, and William W. Nazaroff Journal Environmental Science and Technology Volume 40 Start Page Chapter Pagination 4421-4428 Abstract Ozone-driven chemistry is a major source of indoor secondary pollutants of health concern. This study investigates secondary air pollutants formed from reactions between constituents of household products and ozone. Gas-phase product emissions were introduced along with ozone at constant rates into a 198-L Teflon-lined reaction chamber. Gas-phase concentrations of reactive terpenoids and oxidation products were measured. Formaldehyde was a predominant oxidation byproduct for the three studied products, with yields under most conditions of 20-30% with respect to ozone consumed. Acetaldehyde, acetone, glycolaldehyde, formic acid and acetic acid were each also detected for two or three of the products. Immediately upon mixing of reactants, a scanning mobility particle sizer detected particle nucleation events that were followed by a significant degree of ultrafine particle growth. The production of secondary gaseous pollutants and particles depended primarily on the ozone level and was influenced by other parameters such as the air-exchange rate. Hydroxyl radical concentrations in the range 0.04-200 × 105 molecules cm-3 were measured. OH concentrations were observed to vary strongly with residual ozone level in the chamber, which was in the range 1 - 25 ppb, as is consistent with expectations from a simplified kinetic model. In a separate test, we exposed the dry residue of two products to ozone in the chamber and observed the formation of gas-phase and particle-phase secondary oxidation products

190

Number Description Administrative  

E-Print Network (OSTI)

Public Warehousing --Including Farm ProductsSUITE HOTELS), Refrigerated Goods, Household Goods Exclude 4900 Utilities --Electric, Gas, Water, Sanitary Wholesale Trade - Durable Goods Exclude Exclude

191

Mitigating Carbon Emissions: the Potential of Improving Efficiency of Household Appliances in China  

E-Print Network (OSTI)

Efficiency of Household Appliances in China Jiang Lin8 Appliance Market inEfficiency of Household Appliances in China Executive

Lin, Jiang

2006-01-01T23:59:59.000Z

192

APS Diversity Issues Committee Members  

NLE Websites -- All DOE Office Websites (Extended Search)

SUF Diversity Issues Committee Members 2006 - 2008 Daniela Capatina (AES) Frederick Carter (AES) Diego Casa (XSD) Kathy Harkay, Chair (ASD) Quentin Hasse (IPNS) Jyotsana Lal (IPNS)...

193

The Household Market for Electric Vehicles: Testing the Hybrid Household Hypothesis--A Reflively Designed Survey of New-car-buying, Multi-vehicle California Households  

E-Print Network (OSTI)

by electric and hybrid vehicles", SAE Technical Papers No.household response to hybrid vehicles. Finally, we suggestas electric or hybrid vehicles. Transitions in choices of

Turrentine, Thomas; Kurani, Kenneth

1995-01-01T23:59:59.000Z

194

Householder’s Perceptions of Insulation Adequacy and Drafts in the Home in 2001  

E-Print Network (OSTI)

In order to improve the estimation of end-use heating consumption, the Energy Information Administration's (EIA), 2001 Residential Energy Consumption Survey (RECS), for the first time, asked respondents to judge how drafty they perceived their homes to be as a measure of insulation quality. The analysis of the 2001 RECS data shows that householders in newlyconstructed homes perceived their homes to be better insulated and less drafty than do householders in older homes. Single-family homes are perceived to be better insulated and less drafty than are apartments in buildings with two to four units. Cross-variable comparisons also provide the associations between the level of insulation and winter drafts in the homes with household characteristics and location of the home.

Behjat Hojjati

2004-01-01T23:59:59.000Z

195

Special Topics on Energy Use in Household Transportation  

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

Home Page Welcome to the Energy Information Administration's Residential Transportation Energy Consumption Home Page. If you need assistance in viewing this page, please call (202) 586-8800 Home Page Welcome to the Energy Information Administration's Residential Transportation Energy Consumption Home Page. If you need assistance in viewing this page, please call (202) 586-8800 Home > Transportation Home Page > Special Topics Special Topics Change in Method for Estimating Fuel Economy for the 1988 and subsequent RTECS (Released 09/12/2000) Can Household Members Accurately Report How Many Miles Their Vehicles Are Driven? (Released 08/03/2000) Calculate your Regional Gasoline Costs of Driving using the “Transportation Calculator” updated for new model years! Choose your car or SUV and see the gasoline part of the cost of driving in various parts of the country using EIA's current weekly prices. This application uses DOE/EPA's Fuel Economy Guide to set the MPG, but you can change it to compare your estimate of your car's mpg to the average of everyone else who takes the test. (Released 04/11/2000; Updated Yearly for Fuel Economies and Weekly for Fuel Prices)

196

Household appliance choice: revision of REEPS behavioral models. Final report  

Science Conference Proceedings (OSTI)

This report describes the analysis of household decisions to install space heating, central cooling, and water heating in new housing as well as decisions to own freezers and second refrigerators. This analysis was conducted as part of the enhancements to the Residential End-Use Energy Planning System (REEPS) under EPRI project RP1918-1. The empirical models used in this analysis were the multinomial logit and its generalization the nested logit. The choice model parameters were estimated statistically on national and regional survey data. The results show that capital and operating costs are significant determinants of appliance market penetrations, and the relative magnitudes of the cost coefficients imply discount rates ranging from 3.4 to twenty-one percent. Several tests were conducted to examine the temporal and geographical stability of the key parameters. The estimated parameters have been incorporated into the REEPS computer code. The revised version of REEPS is now available on a limited release basis to EPRI member utilities for testing on their system.

Goett, A.A.

1984-02-01T23:59:59.000Z

197

JOM: The Member Journal of TMS  

Science Conference Proceedings (OSTI)

New Study Examines Gender Barriers in STEM... UPCOMING TMS MEETINGS. Member News Archive. Member News is TMS's monthly membership newsletter,

198

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

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

F (2001) -- Household Natural Gas Usage Form F (2001) -- Household Natural Gas Usage Form OMB No. 1905-0092, Expiring February 29, 2004 2001 Residential Energy Consumption Survey Answers to Frequently Asked Questions About the Household Natural Gas Usage Form What is the purpose of the Residential Energy Consumption Survey? The Residential Energy Consumption Survey (RECS) collects data on energy consumption and expenditures in U.S. housing units. Over 5,000 statistically selected households across the U.S. have already provided information about their household, the physical characteristics of their housing unit, their energy-using equipment, and their energy suppliers. Now we are requesting the energy billing records for these households from each of their energy suppliers. After all this information has been collected, the information will be used to

199

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

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

E (2001) - Household Electricity Usage Form E (2001) - Household Electricity Usage Form OMB No. 1905-0092, Expiring February 29, 2004 2001 Residential Energy Consumption Survey Answers to Frequently Asked Questions About the Household Electricity Usage Form What is the purpose of the Residential Energy Consumption Survey? The Residential Energy Consumption Survey (RECS) collects data on energy consumption and expenditures in U.S. housing units. Over 5,000 statistically selected households across the U.S. have already provided information about their household, the physical characteristics of their housing unit, their energy-using equipment, and their energy suppliers. Now we are requesting the energy billing records for these households from each of their energy suppliers. After all this information has been collected, the information will be used to

200

Towards sustainable household energy use in the Netherlands, Int  

E-Print Network (OSTI)

Abstract: Households consume direct energy, using natural gas, heating oil, gasoline and electricity, and consume indirect energy, the energy related to the production of goods and the delivery of services for the households. Past trends and present-day household energy use (direct and indirect) are analysed and described. A comparison of these findings with objectives concerning ecological sustainability demonstrates that present-day household energy use is not sustainable. A scenario towards sustainable household energy use is designed containing far-reaching measures with regard to direct energy use. Scenario evaluation shows a substantial reduction of direct energy use; however, this is not enough to meet the sustainability objectiv es. Based on these results, the possibilities and the limitations are discussed to enable households to make their direct and indirect energy use sustainable on the long run.

Jack Van Der Wal; Henri C. Moll

2001-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "household members number" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


201

Essays on the effects of demographics on household consumption.  

E-Print Network (OSTI)

??My dissertation analyses the relationship between households' consumption behavior and changes in family demographic characteristics. The first paper studies consumption over the period of the… (more)

Stepanova, Ekaterina, 1977-

2006-01-01T23:59:59.000Z

202

A Model of Household Demand for Activity Participation and Mobility  

E-Print Network (OSTI)

household car ownership, car usage, and travel by differentownership demand, and car usage demand. Modal travel demand,mode), car ownership, and car usage for spatial aggregations

Golob, Thomas F.

1996-01-01T23:59:59.000Z

203

Analysis of the energy requirement for household consumption.  

E-Print Network (OSTI)

??Humans in households use energy for their activities. This use is both direct, for example electricity and natural gas, but also indirect, for the production,… (more)

Vringer, Kees

2005-01-01T23:59:59.000Z

204

U.S. households are incorporating energy–efficient features ...  

U.S. Energy Information Administration (EIA)

... area of increased efficiency: about 60% of households use at least some energy-efficient compact fluorescent (CFL) or light-emitting diode (LED) ...

205

Householder's Perceptions of Insulation Adequacy and Drafts in the ...  

U.S. Energy Information Administration (EIA)

The 2001 RECS was the first RECS to request household perceptions regarding the presence of winter drafts in the home. The data presented in this report ...

206

Answers to Frequently Asked Questions About the Household ...  

U.S. Energy Information Administration (EIA)

Form EIA-457E (2001) – Household Electricity Usage Form OMB No. 1905-0092, Expiring February 29, 2004 2001 Residential Energy Consumption Survey

207

Barriers to household investment in residential energy conservation: preliminary assessment  

Science Conference Proceedings (OSTI)

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)

Hoffman, W.L.

1982-12-01T23:59:59.000Z

208

Household Responses to the Financial Crisis in Indonesia  

E-Print Network (OSTI)

on farm households in Indonesia and Thailand,” World Bank20. Cameron, Lisa. (1999). “Indonesia: a quarterly review,”The Real Costs of Indonesia's Economic Crisis: Preliminary

Thomas, Duncan; Frankenberg, Elizabeth

2005-01-01T23:59:59.000Z

209

Answers to Frequently Asked Questions About the Household Bottled ...  

U.S. Energy Information Administration (EIA)

Form EIA-457D (2001) -- Household Bottled Gas (LPG or Propane) Usage Form OMB No. 1905-0092, Expiring February 29, 2004 2001 Residential Energy Consumption Survey

210

SUPPLEMENTAL ENERGY-RELATED DATA FOR THE 2001 NATIONAL HOUSEHOLD ...  

U.S. Energy Information Administration (EIA)

... vehicle manufacturer, vehicle model, vehicle model year, and vehicle type – several ENERGY INFORMATION ADMINISTRATION/2001 NATIONAL HOUSEHOLD TRAVEL SURVEY K-23 ...

211

Appliance Commitment for Household Load Scheduling  

Science Conference Proceedings (OSTI)

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.

Du, Pengwei; Lu, Ning

2011-06-30T23:59:59.000Z

212

In-vessel composting of household wastes  

Science Conference Proceedings (OSTI)

The process of composting has been studied using five different types of reactors, each simulating a different condition for the formation of compost; one of which was designed as a dynamic complete-mix type household compost reactor. A lab-scale study was conducted first using the compost accelerators culture (Trichoderma viridae, Trichoderma harzianum, Trichorus spirallis, Aspergillus sp., Paecilomyces fusisporus, Chaetomium globosum) grown on jowar (Sorghum vulgare) grains as the inoculum mixed with cow-dung slurry, and then by using the mulch/compost formed in the respective reactors as the inoculum. The reactors were loaded with raw as well as cooked vegetable waste for a period of 4 weeks and then the mulch formed was allowed to maturate. The mulch was analysed at various stages for the compost and other environmental parameters. The compost from the designed aerobic reactor provides good humus to build up a poor physical soil and some basic plant nutrients. This proves to be an efficient, eco-friendly, cost-effective, and nuisance-free solution for the management of household solid wastes.

Iyengar, Srinath R. [Civil and Environmental Engineering Department, V.J. Technological Institute, H.R. Mahajani Road, Matunga, Mumbai 400 019 (India)]. E-mail: srinathrangamani@yahoo.com; Bhave, Prashant P. [Civil and Environmental Engineering Department, V.J. Technological Institute, H.R. Mahajani Road, Matunga, Mumbai 400 019 (India)]. E-mail: drppbhave@vsnl.net

2006-07-01T23:59:59.000Z

213

Household energy consumption and expenditures 1987  

SciTech Connect

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.

Not Available

1990-01-22T23:59:59.000Z

214

Members  

NLE Websites -- All DOE Office Websites (Extended Search)

engineer with SLR International Corporation and works on projects unrelated to EM or DOE. He holds a Bachelor of Science in Civil and Environmental Engineering from the...

215

Case Number:  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Name of Petitioner: Name of Petitioner: Date of Filing: Case Number: Department of Energy Washington, DC 20585 JUL 2 2 2009 DEPARTMENT OF ENERGY OFFICE OF HEARINGS AND APPEALS Appeal Dean P. Dennis March 2, 2009 TBA-0072 Dean D. Dennis filed a complaint of retaliation under the Department of Energy (DOE) Contractor Employee Protection Program, 10 C.F.R. Part 708. Mr. Dennis alleged that he engaged in protected activity and that his employer, National Security Technologies, LLC (NSTec ), subsequently terminated him. An Office of Hearings and Appeals (OHA) Hearing Officer denied relief in Dean P. Dennis, Case No. TBH-0072, 1 and Mr. Dennis filed the instant appeal. As discussed below, the appeal is denied. I. Background The DOE established its Contractor Employee Protection Program to "safeguard public

216

JOB NUMBER  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

. . . . . . . . . .: LEAVE BLANK (NARA use only) JOB NUMBER N/-&*W- 9d - 3 DATE RECEIVED " -1s - 9 J - NOTIFICATION TOAGENCY , In accordance with the provisions of 44 U.S.C. 3303a the disposition request. including amendments, is ap roved except , . l for items that may be marke,, ,"dis osition not approved" or "withdrawn in c o i m n 10. 4. NAME OF PERSON WITH WHOM TO CONFER 5 TELEPHONE Jannie Kindred (202) 5&-333 5 - 2 -96 6 AGENCYCERTIFICATION -. ~ - I hereby certify that I am authorized to act for this agency in matters pertaining to the disposition of its records and that the records roposed for disposal are not now needed for the business of this agency or wiRnot be needed after t G t r & s s d ; and that written concurrence from

217

KPA Number  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Supports CMM-SW Level 3 Supports CMM-SW Level 3 Mapping of the DOE Information Systems Engineering Methodology to the Software Engineering Institute (SEI) Software Capability Maturity Model (CMM-SW) level 3. Date: September 2002 Page 1 KPA Number KPA Activity SEM Section SEM Work Product SQSE Web site http://cio.doe.gov/sqse ORGANIZATION PROCESS FOCUS OPF-1 The software process is assessed periodically, and action plans are developed to address the assessment findings. Chapter 1 * Organizational Process Management * Process Improvement Action Plan * Methodologies ! DOE Methodologies ! SEM OPF-2 The organization develops and maintains a plan for its software process development and improvement activities. Chapter 1 * Organizational Process Management * Process Improvement

218

US CMS Members Picture Gallery  

NLE Websites -- All DOE Office Websites (Extended Search)

Members Picture Gallery Members Picture Gallery Developed by Ben Sadler, FSU Updated July 29, 2008. Please send comments and corrections to Sharon Hagopian. INSTITUTIONS: Boston University Brown University University of California, Davis University of California, Los Angeles University of California, Riverside University of California, San Diego University of California, Santa Barbara California Institute of Technology Carnegie Mellon University University of Colorado Cornell University Fairfield University Fermi National Accelerator Laboratory University of Florida Florida International University Florida State University Florida Institute of Technology University of Illinois, Chicago University of Iowa Johns Hopkins University University of Kansas Kansas State University Lawrence Livermore National Laboratory

219

Simulating household activities to lower consumption peaks: demonstration  

Science Conference Proceedings (OSTI)

Energy experts need fine-grained dynamics oriented tools to investigate household activities in order to improve power management in the residential sector. This paper presents the SMACH framework for modelling, simulating and analy- sis of household ... Keywords: agent-based modelling, energy, social simulation

Edouard Amouroux, Francois Sempé, Thomas Huraux, Nicolas Sabouret, Yvon Haradji

2013-05-01T23:59:59.000Z

220

Elements of consumption: an abstract visualization of household consumption  

Science Conference Proceedings (OSTI)

To promote sustainability consumers must be informed about their consumption behaviours. Ambient displays can be used as an eco-feedback technology to convey household consumption information. Elements of Consumption (EoC) demonstrates this by visualizing ... Keywords: a-life, eco-feedback, household consumption, sustainability

Stephen Makonin; Philippe Pasquier; Lyn Bartram

2011-07-01T23:59:59.000Z

Note: This page contains sample records for the topic "household members number" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


221

A REVIEW OF ASSUMPTIONS AND ANALYSIS IN EPRI EA-3409, "HOUSEHOLD APPLIANCE CHOICE: REVISION OF REEPS BEHAVIORAL MODELS"  

E-Print Network (OSTI)

EPRI EA-3409, "Household Appliance Choice: Revision of REEPSEA",3409: "HOUSEHOLD APPLIANCE CHOICE: REVISION OF REEPSreport EA-3409, "Household Appliance Choice: Revi- sion of

Wood, D.J.

2010-01-01T23:59:59.000Z

222

Empowering Advisory Board Members: Building Partnerships AAAbbbssstttrrraaacccttt  

E-Print Network (OSTI)

Empowering Advisory Board Members: Building Partnerships AAAbbbssstttrrraaacccttt BBuuiillddiinngg council members are often asked to assist in building partnerships and communicating with policymakers for communication at each political level. #12;Empowering Advisory Board Members: Building Partnerships 1

Hayes, Jane E.

223

Table CE2-3e. Space-Heating Energy Expenditures in U.S. Households ...  

U.S. Energy Information Administration (EIA)

Table CE2-3e. Space-Heating Energy Expenditures in U.S. Households by Household Income, 2001 RSE Column Factor: Total 2001 Household Income Below Poverty

224

An Analysis of the Price Elasticity of Demand for Household Appliances  

NLE Websites -- All DOE Office Websites (Extended Search)

the Price Elasticity of Demand for Household Appliances the Price Elasticity of Demand for Household Appliances Title An Analysis of the Price Elasticity of Demand for Household Appliances Publication Type Report LBNL Report Number LBNL-326E Year of Publication 2008 Authors Dale, Larry L., and Sydny K. Fujita Document Number LBNL-326E Pagination 19 Date Published 02/2008 Publisher Lawrence Berkeley National Laboratory City Berkeley Abstract This article summarizes our study of the price elasticity of demand1 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 chose to study this particular set of appliances because data for the elasticity calculation was more readily available for refrigerators, clothes washers, and dishwashers than for other appliances. We begin with a review of the 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 it over the past 20 years. We conclude with summary and interpretation of the results of our regression analysis and present estimates of the price elasticity of demand for the three appliances.

225

Family Member Definitions | Department of Energy  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Memorandum 21 clarifies the definition and application of family member in our directives and services Family Members Responsible Contacts Bruce Murray HR Policy Advisor...

226

Table AC1. Total Households Using Air-Conditioning Equipment, 2005 ...  

U.S. Energy Information Administration (EIA)

Table AC1. Total Households Using Air-Conditioning Equipment, 2005 Million U.S. Households Type of Air-Conditioning Equipment (millions) Central System

227

Table CE2-3c. Space-Heating Energy Consumption in U.S. Households ...  

U.S. Energy Information Administration (EIA)

Physical Units (PU) per Household4,a Physical Units of Space-Heating Consumption per Household,3 Where the Main Space-Heating Fuel Is:

228

Table CE2-7c. Space-Heating Energy Consumption in U.S. Households ...  

U.S. Energy Information Administration (EIA)

Physical Units (PU) per Household3,a Physical Units of Space-Heating Consumption per Household,2 Where the Main Space-Heating Fuel Is:

229

Table CE2-12c. Space-Heating Energy Consumption in U.S. Households ...  

U.S. Energy Information Administration (EIA)

Physical Units (PU) per Household3,a Physical Units of Space-Heating Consumption per Household,2 Where the Main Space-Heating Fuel Is:

230

Table CE2-4c. Space-Heating Energy Consumption in U.S. Households ...  

U.S. Energy Information Administration (EIA)

Physical Units (PU) per Household3,a Physical Units of Space-Heating Consumption per Household,2 Where the Main Space-Heating Fuel Is:

231

Table CE2-7c. Space-Heating Energy Consumption in U.S. Households ...  

U.S. Energy Information Administration (EIA)

Physical Units (PU) per Household3 Physical Units of Space-Heating Consumption per Household,2 Where the Main Space-Heating Fuel Is:

232

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

E-Print Network (OSTI)

of Household Income and Appliance Ownership. ECEEE Summerof decreasing prices of appliances, if price data becomesForecasting Household Appliance Ownership in a Growing

Letschert, Virginie

2010-01-01T23:59:59.000Z

233

Table SH1. Total Households Using a Space Heating Fuel, 2005 ...  

U.S. Energy Information Administration (EIA)

Total Households Using a Space Heating Fuel, 2005 Million U.S. Households Using a Non-Major Fuel 5 ... Space Heating (millions) Energy Information Administration

234

Testing Electric Vehicle Demand in `Hybrid Households' Using a Reflexive Survey  

E-Print Network (OSTI)

1994) Demand for Electric Vehicles in Hybrid Households: A nand the Household Electric Vehicle Market: A Constraintsthe mar- ket for electric vehicles in California. Presented

Kurani, Kenneth; Turrentine, Thomas; Sperling, Daniel

1996-01-01T23:59:59.000Z

235

" Million U.S. Housing Units"  

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

3 Household Characteristics by Number of Household Members, 2005" 3 Household Characteristics by Number of Household Members, 2005" " Million U.S. Housing Units" ,,"Number of Households With --" ,"Housing Units (millions)" ,,"1 Member","2 Members","3 Members","4 Members","5 or More Members" "Household Characteristics" "Total",111.1,30,34.8,18.4,15.9,12 "Household Size" "1 Person",30,30,"N","N","N","N" "2 Persons",34.8,"N",34.8,"N","N","N" "3 Persons",18.4,"N","N",18.4,"N","N" "4 Persons",15.9,"N","N","N",15.9,"N"

236

Department Members | Environmental Sciences | BNL  

NLE Websites -- All DOE Office Websites (Extended Search)

Department Members Department Members Administration and Support Staff Scientific and Technical Staff Mary Jane Bartholomew William J. Behrens Alexei Belochitski Alice T. Cialella Peter H. Daum Satoshi Endo Arokiasamy J. (AJ) Francis Michele Galletti Scott Giangrande Laurie Gregory John H. Heiser Dong Huang Michael P. Jensen Karen Lee Johnson Paul D. Kalb Lawrence I. Kleinman Chongai Kuang Stefanie Lasota Kathy Lazar Yin-Nan Lee Keith Lewin Ernie R. Lewis Min Liang Wuyin Lin Yangang Liu Edward Luke L. Lynn Ma Robert L. McGraw Andrew McMahon Laurence W. Milian Alistair Rogers Martin Schoonen - Chair Stephen E. Schwartz Arthur J. Sedlacek Gunnar I. Senum Scott Smith Hua Song Stephen R. Springston Terrence Sullivan Ryan Thalman Alison Tilp Tami Toto David Troyan Gabriel J. Vignato Andrew M. Vogelmann Richard Wagener

237

Table HC6.10 Home Appliances Usage Indicators by Number of Household...  

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

... 25.8 4.1 9.3 4.7 4.5 3.2 Use of Most-Used Ceiling Fan Used All Summer... 18.7 4.7 6.0 2.9 2.9...

238

Readiness Review Training - Member | Department of Energy  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Member Member Readiness Review Training - Member November 10, 2010 Readiness Review Member Training at the Idaho National Laboratory Course provides tools and tips to be an effective readiness review team member. Topics include: An understanding of the background behind the Readiness Review Process; Training in the mechanics of performance and reporting of a Readiness Review; Knowledge of current DOE Orders, Directives, and References for the Readiness Review process; Training in Performance-Based Assessment Processes and Official DOE Team Member Readiness Review Training Methods Readiness Review Training - Member More Documents & Publications Readiness Review Training - Team Leader Readiness Review Training - Development of Criteria And Review Approach Documents

239

Assumptions to the Annual Energy Outlook 2000 - Household Expenditures  

Gasoline and Diesel Fuel Update (EIA)

Key Assumptions Key Assumptions The historical input data used to develop the HEM version for the AEO2000 consists of recent household survey responses, aggregated to the desired level of detail. Two surveys performed by the Energy Information Administration are included in the AEO2000 HEM database, and together these input data are used to develop a set of baseline household consumption profiles for the direct fuel expenditure analysis. These surveys are the 1997 Residential Energy Consumption Survey (RECS) and the 1991 Residential Transportation Energy Consumption Survey (RTECS). HEM uses the consumption forecast by NEMS for the residential and transportation sectors as inputs to the disaggregation algorithm that results in the direct fuel expenditure analysis. Household end-use and personal transportation service consumption are obtained by HEM from the NEMS Residential and Transportation Demand Modules. Household disposable income is adjusted with forecasts of total disposable income from the NEMS Macroeconomic Activity Module.

240

Appliance Standby Power and Energy Consumption in South African Households  

Open Energy Info (EERE)

Appliance Standby Power and Energy Consumption in South African Households Appliance Standby Power and Energy Consumption in South African Households Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Appliance Standby Power and Energy Consumption in South African Households Focus Area: Appliances & Equipment Topics: Policy Impacts Website: active.cput.ac.za/energy/web/DUE/DOCS/422/Paper%20-%20Shuma-Iwisi%20M. Equivalent URI: cleanenergysolutions.org/content/appliance-standby-power-and-energy-co Language: English Policies: Deployment Programs DeploymentPrograms: Technical Assistance A modified engineering model is proposed to estimate standby power and energy losses in households. The modified model accounts for the randomness of standby power and energy losses due to unpredicted user appliance operational behavior.

Note: This page contains sample records for the topic "household members number" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


241

A Theoretical Basis for Household Energy Conservation UsingProduct...  

NLE Websites -- All DOE Office Websites (Extended Search)

A Theoretical Basis for Household Energy Conservation Using Product-Integrated Feedback Speaker(s): Teddy McCalley Date: October 11, 2002 - 12:00pm Location: Bldg. 90 Seminar Host...

242

Household Preferences for Supporting Renewable Energy, and Barriers...  

NLE Websites -- All DOE Office Websites (Extended Search)

Household Preferences for Supporting Renewable Energy, and Barriers to Green Power Demand Speaker(s): Ryan Wiser Date: May 9, 2002 - 12:00pm Location: Bldg. 90 Nearly 40% of the...

243

Energy Consumption of Refrigerators in Ghana - Outcomes of Household...  

NLE Websites -- All DOE Office Websites (Extended Search)

Energy Consumption of Refrigerators in Ghana - Outcomes of Household Surveys Speaker(s): Essel Ben Hagan Date: July 12, 2007 - 12:00pm Location: 90-3122 Seminar HostPoint of...

244

Profiling energy use in households and office spaces  

Science Conference Proceedings (OSTI)

Energy consumption is largely studied in the context of different environments, such as domestic, corporate, industrial, and public sectors. In this paper, we discuss two environments, households and office spaces, where people have an especially ...

Salman Taherian; Marcelo Pias; George Coulouris; Jon Crowcroft

2010-04-01T23:59:59.000Z

245

Smoothing consumption across households and time : essays in development economics  

E-Print Network (OSTI)

This thesis studies two strategies that households may use to keep their consumption smooth in the face of fluctuations in income and expenses: credit (borrowing and savings) and insurance (state contingent transfers between ...

Kinnan, Cynthia Georgia

2010-01-01T23:59:59.000Z

246

Characterizing Household Plug Loads through Self-Administered Load Research  

Science Conference Proceedings (OSTI)

Household miscellaneous loads, which include consumer electronics, are the fastest growing segment of household energy use in the United States. Although the relative energy intensity of applications such as heating and cooling is declining, the DOEAnnual Energy Outlook forecasts that the intensity of residential miscellaneous end uses will increase substantially by 2030. Studies by TIAX and Ecos Consulting reveal that miscellaneous devices8212smaller devices in terms of energy draw but growing in usage8...

2009-12-09T23:59:59.000Z

247

Household Vehicles Energy Use: Latest Data & Trends  

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

These mpg values are associated with various combinations of engine and drive-train technologies (e.g., number of cylinders, engine size, gasoline or diesel fuel, and...

248

Transferring 2001 National Household Travel Survey  

Science Conference Proceedings (OSTI)

Policy makers rely on transportation statistics, including data on personal travel behavior, to formulate strategic transportation policies, and to improve the safety and efficiency of the U.S. transportation system. Data on personal travel trends are needed to examine the reliability, efficiency, capacity, and flexibility of the Nation's transportation system to meet current demands and to accommodate future demand. These data are also needed to assess the feasibility and efficiency of alternative congestion-mitigating technologies (e.g., high-speed rail, magnetically levitated trains, and intelligent vehicle and highway systems); to evaluate the merits of alternative transportation investment programs; and to assess the energy-use and air-quality impacts of various policies. To address these data needs, the U.S. Department of Transportation (USDOT) initiated an effort in 1969 to collect detailed data on personal travel. The 1969 survey was the first Nationwide Personal Transportation Survey (NPTS). The survey was conducted again in 1977, 1983, 1990, 1995, and 2001. Data on daily travel were collected in 1969, 1977, 1983, 1990 and 1995. In 2001, the survey was renamed the National Household Travel Survey (NHTS) and it collected both daily and long-distance trips. The 2001 survey was sponsored by three USDOT agencies: Federal Highway Administration (FHWA), Bureau of Transportation Statistics (BTS), and National Highway Traffic Safety Administration (NHTSA). The primary objective of the survey was to collect trip-based data on the nature and characteristics of personal travel so that the relationships between the characteristics of personal travel and the demographics of the traveler can be established. Commercial and institutional travel were not part of the survey. Due to the survey's design, data in the NHTS survey series were not recommended for estimating travel statistics for categories smaller than the combination of Census division (e.g., New England, Middle Atlantic, and Pacific), MSA size, and the availability of rail. Extrapolating NHTS data within small geographic areas could risk developing and subsequently using unreliable estimates. For example, if a planning agency in City X of State Y estimates travel rates and other travel characteristics based on survey data collected from NHTS sample households that were located in City X of State Y, then the agency could risk developing and using unreliable estimates for their planning process. Typically, this limitation significantly increases as the size of an area decreases. That said, the NHTS contains a wealth of information that could allow statistical inferences about small geographic areas, with a pre-determined level of statistical certainty. The question then becomes whether a method can be developed that integrates the NHTS data and other data to estimate key travel characteristics for small geographic areas such as Census tract and transportation analysis zone, and whether this method can outperform other, competing methods.

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

2007-05-01T23:59:59.000Z

249

Source separation of household waste: A case study in China  

SciTech Connect

A pilot program concerning source separation of household waste was launched in Hangzhou, capital city of Zhejiang province, China. Detailed investigations on the composition and properties of household waste in the experimental communities revealed that high water content and high percentage of food waste are the main limiting factors in the recovery of recyclables, especially paper from household waste, and the main contributors to the high cost and low efficiency of waste disposal. On the basis of the investigation, a novel source separation method, according to which household waste was classified as food waste, dry waste and harmful waste, was proposed and performed in four selected communities. In addition, a corresponding household waste management system that involves all stakeholders, a recovery system and a mechanical dehydration system for food waste were constituted to promote source separation activity. Performances and the questionnaire survey results showed that the active support and investment of a real estate company and a community residential committee play important roles in enhancing public participation and awareness of the importance of waste source separation. In comparison with the conventional mixed collection and transportation system of household waste, the established source separation and management system is cost-effective. It could be extended to the entire city and used by other cities in China as a source of reference.

Zhuang Ying; Wu Songwei; Wang Yunlong [Department of Environmental Engineering, Zhejiang University, Hangzhou 310029 (China); Wu Weixiang [Department of Environmental Engineering, Zhejiang University, Hangzhou 310029 (China)], E-mail: weixiang@zju.edu.cn; Chen Yingxu [Department of Environmental Engineering, Zhejiang University, Hangzhou 310029 (China)

2008-07-01T23:59:59.000Z

250

Household waste disposal in Mekelle city, Northern Ethiopia  

SciTech Connect

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

Tadesse, Tewodros [Agricultural Economics and Rural Policy Group, Wageningen University, Hollandseweg 1 6706 KN Wageningen (Netherlands)], E-mail: tewodroslog@yahoo.com; Ruijs, Arjan [Environmental Economics and Natural Resources Group, Wageningen University, P.O. Box 8130, 6700 EW Wageningen (Netherlands); Hagos, Fitsum [International Water Management Institute (IWMI), Subregional Office for the Nile Basin and East Africa, P.O. Box 5689, Addis Ababa (Ethiopia)

2008-07-01T23:59:59.000Z

251

Ventilation Behavior and Household Characteristics in NewCalifornia Houses  

SciTech Connect

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.

Price, Phillip N.; Sherman, Max H.

2006-02-01T23:59:59.000Z

252

Glossary Term - Atomic Number  

NLE Websites -- All DOE Office Websites (Extended Search)

Particle Previous Term (Alpha Particle) Glossary Main Index Next Term (Avogadro's Number) Avogadro's Number Atomic Number Silver's atomic number is 47 The atomic number is equal to...

253

Number of U.S. Commercial Buildings  

U.S. Energy Information Administration (EIA)

Glossary Home > Households, Buildings & Industry > Energy Efficiency > Commercial Buildings Energy Intensities > Table 2

254

Delivering Energy Efficiency to Middle Income Single Family Households  

NLE Websites -- All DOE Office Websites (Extended Search)

Delivering Energy Efficiency to Middle Income Single Family Households Delivering Energy Efficiency to Middle Income Single Family Households Title Delivering Energy Efficiency to Middle Income Single Family Households Publication Type Report Year of Publication 2011 Authors Zimring, Mark, Merrian Borgeson, Ian M. Hoffman, Charles A. Goldman, Elizabeth Stuart, Annika Todd, and Megan A. Billingsley Pagination 102 Date Published 12/2011 Publisher LBNL City Berkeley Keywords electricity markets and policy group, energy analysis and environmental impacts department Abstract The question posed in this report is: How can programs motivate these middle income single family households to seek out more comprehensive energy upgrades, and empower them to do so? Research methods included interviews with more than 35 program administrators, policy makers, researchers, and other experts; case studies of programs, based on interviews with staff and a review of program materials and data; and analysis of relevant data sources and existing research on demographics, the financial status of Americans, and the characteristics of middle income American households. While there is no 'silver bullet' to help these households overcome the range of barriers they face, this report describes outreach strategies, innovative program designs, and financing tools that show promise in increasing the attractiveness and accessibility of energy efficiency for this group. These strategies and tools should be seen as models that are currently being honed to build our knowledge and capacity to deliver energy improvements to middle income households. However, the strategies described in this report are probably not sufficient, in the absence of robust policy frameworks, to deliver these improvements at scale. Instead, these strategies must be paired with enabling and complementary policies to reach their full potential.

255

Household solid waste characteristics and management in Chittagong, Bangladesh  

Science Conference Proceedings (OSTI)

Solid waste management (SWM) is a multidimensional challenge faced by urban authorities, especially in developing countries like Bangladesh. We investigated per capita waste generation by residents, its composition, and the households' attitudes towards waste management at Rahman Nagar Residential Area, Chittagong, Bangladesh. The study involved a structured questionnaire and encompassed 75 households from five different socioeconomic groups (SEGs): low (LSEG), lower middle (LMSEG), middle (MSEG), upper middle (UMSEG) and high (HSEG). Wastes, collected from all of the groups of households, were segregated and weighed. Waste generation was 1.3 kg/household/day and 0.25 kg/person/day. Household solid waste (HSW) was comprised of nine categories of wastes with vegetable/food waste being the largest component (62%). Vegetable/food waste generation increased from the HSEG (47%) to the LSEG (88%). By weight, 66% of the waste was compostable in nature. The generation of HSW was positively correlated with family size (r{sub xy} = 0.236, p management initiative. Of the respondents, an impressive 44% were willing to pay US$0.3 to US$0.4 per month to waste collectors and it is recommended that service charge be based on the volume of waste generated by households. Almost a quarter (22.7%) of the respondents preferred 12-1 pm as the time period for their waste to be collected. This study adequately shows that household solid waste can be converted from burden to resource through segregation at the source, since people are aware of their role in this direction provided a mechanism to assist them in this pursuit exists and the burden is distributed according to the amount of waste generated.

Sujauddin, Mohammad [Institute of Forestry and Environmental Sciences, Chittagong University, Chittagong-4331 (Bangladesh)], E-mail: mohammad.sujauddin@gmail.com; Huda, S.M.S. [Institute of Forestry and Environmental Sciences, Chittagong University, Chittagong-4331 (Bangladesh); Hoque, A.T.M. Rafiqul [Institute of Forestry and Environmental Sciences, Chittagong University, Chittagong-4331 (Bangladesh); Laboratory of Ecology and Systematics (Plant Ecophysiology Section), Faculty of Science, Biology Division, University of the Ryukyus, Okinawa 903-0213 (Japan)

2008-07-01T23:59:59.000Z

256

2012 JSD Subscription for AOCS Members  

Science Conference Proceedings (OSTI)

A monthly peer-reviewed journal for surfactants and detergents professionals. Subscription rates are for AOCS Members only. 2012 JSD Subscription for AOCS Members Surfactants and Detergents Subscriptions Journals Journals Forms Springer J

257

2012 JAOCS Subscription for AOCS Members  

Science Conference Proceedings (OSTI)

A monthly peer-reviewed journal. Subscription rates are for AOCS Members only. 2012 JAOCS Subscription for AOCS Members Subscriptions Journals Journals Forms Journal of the American Oil Chemists' Society, (JAOCS).JAOCS debuted in 1924 as

258

2012 Lipids Subscription for AOCS Members  

Science Conference Proceedings (OSTI)

One of the premier journals published in the lipid field today. Subscription rates are for AOCS Members only. 2012 Lipids Subscription for AOCS Members Subscriptions Journals Journals Forms Food Science Edible Applications Food Structure and Functio

259

ITL Staff Members Receive Tech Transfer Award  

Science Conference Proceedings (OSTI)

ITL Staff Members Receive Tech Transfer Award. ... Regional "Excellence in Technology Transfer" Award for ... the process of transferring a technology ...

2010-10-05T23:59:59.000Z

260

Household disposables as breeding habitats of dengue vectors: Linking wastes and public health  

SciTech Connect

Highlights: Black-Right-Pointing-Pointer An assessment of different household wastes as larval habitats of dengue vectors Aedes aegypti and Aedes albopictus was made using Kolkata, India as a model geographical area. Black-Right-Pointing-Pointer Household wastes of four major categories namely earthen, porcelain, plastic and coconut shells varied significantly for Aedes immature depending on species, month and location. Black-Right-Pointing-Pointer Based on the relative density of Aedes immature, cluster analyses allowed segregation and classification of the waste containers and relative importance as mosquito larval habitats. Black-Right-Pointing-Pointer Conversion of disposed wastes into larval habitats cautions for continuance of Aedes population in Kolkata and similar cities of tropics lacking suitable waste management practices. - Abstract: An assessment of the household wastes as larval habitats of the dengue vectors was made considering Kolkata, India, as geographical area. Wastes of four major categories, namely, earthen, porcelain, plastic and coconut shells were monitored for positive with immature of either Aedes aegypti or Aedes albopictus. Twenty six types of wastes with varying size and shape, resembling containers, were identified that hosted mosquito immature. The number of waste containers positive for Aedes immature varied significantly (P < 0.05) with respect to location, type and month. The relative density of Aedes immature in the waste containers varied significantly (P < 0.05) with the types and months. The significant interaction between the month, waste container types and density of Aedes immature suggest that the household wastes are important contributors to the maintenance of the population of Aedes mosquito in the city. Based on the relative density of mosquito immature in the wastes, cluster analysis allowed segregation and classification of the wastes and their importance as mosquito larval habitats. Apparently, the containers that are most frequently disposed off contributed largely to the sustenance of Aedes mosquito population in the city. This calls for a strict legislation towards disposal as well as enhanced management of the household wastes. A link between the wastes disposed and subsequent conversion to the mosquito larval habitats cautions for continuance of Aedes population and possibility of dengue epidemics if the existing management practices are not improved.

Banerjee, Soumyajit, E-mail: soumyajitb@gmail.com [Department of Zoology, University of Calcutta, 35 Ballygunge Circular Road, Kolkata 700 019 (India); Aditya, Gautam, E-mail: gautamaditya2001@gmail.com [Department of Zoology, University of Calcutta, 35 Ballygunge Circular Road, Kolkata 700 019 (India); Department of Zoology, The University of Burdwan, Golapbag, Burdwan 713 104 (India); Saha, Goutam K, E-mail: gkszoo@rediffmail.com [Department of Zoology, University of Calcutta, 35 Ballygunge Circular Road, Kolkata 700 019 (India)

2013-01-15T23:59:59.000Z

Note: This page contains sample records for the topic "household members number" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


261

TEC Working Group Members | Department of Energy  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Members Members TEC Working Group Members TEC members represent many different national, regional, tribal, state and local governmental, labor, industry and professional groups. To maximize the opportunity for broad-based input and information exchange, no single state, local or tribal governmental, or other entity is itself a member. Instead, membership is composed of organizations representing those perspectives. DOE programs participate in TEC by providing regular updates on key activities and provide resources and work on issues brought to the TEC by members or DOE. Members serve the group in three broad capacities: * Represent their constituent organizations; * Participate actively and consistently in TEC activities; and * Communicate the findings and recommendations of the group back to their

262

Energy Consumption of Refrigerators in Ghana - Outcomes of Household  

NLE Websites -- All DOE Office Websites (Extended Search)

Energy Consumption of Refrigerators in Ghana - Outcomes of Household Energy Consumption of Refrigerators in Ghana - Outcomes of Household Surveys Speaker(s): Essel Ben Hagan Date: July 12, 2007 - 12:00pm Location: 90-3122 Seminar Host/Point of Contact: Robert Van Buskirk Galen Barbose As part of activities to develop refrigerator efficiency standards regulations in Ghana, a national survey on the energy consumption of refrigerators and refrigerator-freezers has been conducted. The survey covered 1000 households in urban, peri-urban and rural communities in various parts of the country. The survey found that, on average, refrigerators and refrigerator-freezers in Ghana use almost three times what is allowed by minimum efficiency standards in the U.S., and a few refrigerators had energy use at levels almost ten times the U.S.

263

Assumptions to the Annual Energy Outlook 2001 - Household Expenditures  

Gasoline and Diesel Fuel Update (EIA)

Completed Copy in PDF Format Completed Copy in PDF Format Related Links Annual Energy Outlook2001 Supplemental Data to the AEO2001 NEMS Conference To Forecasting Home Page EIA Homepage Household Expenditures Module Key Assumptions The historical input data used to develop the HEM version for the AEO2001 consists of recent household survey responses, aggregated to the desired level of detail. Two surveys performed by the Energy Information Administration are included in the AEO2001 HEM database, and together these input data are used to develop a set of baseline household consumption profiles for the direct fuel expenditure analysis. These surveys are the 1997 Residential Energy Consumption Survey (RECS) and the 1991 Residential Transportation Energy Consumption Survey (RTECS). HEM uses the consumption forecast by NEMS for the residential and

264

Water Related Energy Use in Households and Cities - an Australian  

NLE Websites -- All DOE Office Websites (Extended Search)

Water Related Energy Use in Households and Cities - an Australian Water Related Energy Use in Households and Cities - an Australian Perspective Speaker(s): Steven Kenway Date: May 12, 2011 - 12:00pm Location: 90-3122 Seminar Host/Point of Contact: Anita Estner James McMahon This presentation covers the content of recent journal papers and reports focused on the water-energy nexus and the related theory of urban metabolism. This includes (i) a review of the water-energy nexus focused on cities (ii) quantifying water-related energy in cities (iii) modeling household water-related energy use including key factors, sensitivity and uncertainty analysis, and (iv) relevance and implications of the urban metabolism theoretical framework. Steven's work focuses on understanding the indirect connections between urban water management, energy use and

265

EIA - Gasoline and Diesel Fuel report: Household Vehicles Energy  

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

1 1 Transportation 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 Residential Transportation Energy Consumption Survey conducted by the Energy Information Administration (EIA) - survey series has been discontinued after EIA's 1994 survey. Only light-duty vehicles and recreational vehicles are included in this report. EIA has excluded motorcycles, mopeds, large trucks, and buses. This report, Household Vehicles Energy Consumption 1991, is based on data from the 1991 Residential Transportation Energy Consumption Survey (RTECS). Focusing on vehicle miles traveled (VMT) and energy enduse consumption and expenditures by households for personal transportation, the 1991 RTECS is

266

Table 2. Percent of Households with Vehicles, Selected Survey Years  

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

Percent of Households with Vehicles, Selected Survey Years " Percent of Households with Vehicles, Selected Survey Years " ,"Survey Years" ,1983,1985,1988,1991,1994,2001 "Total",85.5450237,89.00343643,88.75545852,89.42917548,87.25590956,92.08566108 "Household Characteristics" "Census Region and Division" " Northeast",77.22222222,"NA",79.16666667,82.9015544,75.38461538,85.09615385 " New England",88.37209302,"NA",81.81818182,82.9787234,82,88.52459016 " Middle Atlantic ",73.72262774,"NA",78.37837838,82.31292517,74.30555556,83.67346939 " Midwest ",85.51401869,"NA",90.66666667,90.17094017,92.30769231,91.47286822 " East North Central",82,"NA",88.81987578,89.88095238,91.51515152,90.55555556

267

The welfare effects of raising household energy prices in Poland  

Science Conference Proceedings (OSTI)

We examine the welfare effects from increasing household energy prices in Poland. Subsidizing household energy prices, common in the transition economies, is shown to be highly regressive. The wealthy spend a larger portion of their income on energy and consume more energy in absolute terms. We therefore rule out the oft-used social welfare argument for delaying household energy price increases. Raising prices, while targeting relief to the poor through a social assistance program is the first-best response. However, if governments want to ease the adjustment, several options are open, including: in-kind transfers to the poor, vouchers, in-cash transfers, and lifeline pricing for electricity. Our simulations show that if raising prices to efficient levels is not politically feasible at present and social assistance targeting is sufficiently weak, it may be socially better to use lifeline pricing and a large price increase than an overall, but smaller, price increase.

Freund, C.L. [Columbia Univ., New York, NY (United States); Wallich, C.I. [World Bank, Washington, DC (United States)

1996-06-01T23:59:59.000Z

268

Modeling patterns of hot water use in households  

Science Conference Proceedings (OSTI)

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.

Lutz, J.D.; Liu, Xiaomin; McMahon, J.E. [and others

1996-11-01T23:59:59.000Z

269

Modeling patterns of hot water use in households  

SciTech Connect

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.

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

1996-01-01T23:59:59.000Z

270

Econometric analysis of energy use in urban households  

SciTech Connect

This article analyzes the pattern of energy carrier consumption in the residential sector of Bangalore, a major city in south India. A 1,000-household survey was used to study the type of energy carrier used by households in different income groups for different end-uses, such as cooking, water heating, and lighting. The dependence of income on the carrier utilized is established using a carrier dependence index. Using regression analysis, the index analyses the impact of different explanatory variables such as family income, family size, and price of energy carrier on consumption. The results show that income plays an important role not only in the selection of an energy carrier but also on the quantity of consumption per household. Also, a source-service matrix is prepared for Bangalore`s residential sector, which shows the disaggregation of energy consumption by the type of energy carrier and end-use.

Reddy, B.S. [Indira Gandhi Inst. of Development Research, Bombay (India)

1995-05-01T23:59:59.000Z

271

Notices OMB Control Number: 1850-0803.  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

870 Federal Register 870 Federal Register / Vol. 78, No. 140 / Monday, July 22, 2013 / Notices OMB Control Number: 1850-0803. Type of Review: Extension without change of an existing collection of information. Respondents/Affected Public: Individuals or households. Total Estimated Number of Annual Responses: 135,000. Total Estimated Number of Annual Burden Hours: 27,000. Abstract: This is a request for a 3-year renewal of the generic clearance to allow the National Center for Education Statistics (NCES) to continue to develop, test, and improve its survey and assessment instruments and methodologies. The procedures utilized to this effect include but are not limited to experiments with levels of incentives for various types of survey operations, focus groups, cognitive laboratory

272

Household Energy Expenditure and Income Groups: Evidence from Great Britain  

E-Print Network (OSTI)

  and  0.024  for  district heating However, as income is not observed its effect cannot be analysed.  Wu et al. (2004) examine the demand for space heating in Armenia, Moldova, and  Kyrgyz  Republic  using  household  survey  data.  In  these  countries...  and in some regions incomes are not sufficient to  afford space heating from district heating systems making these systems unviable.  We  analyse  electricity,  gas  and  overall  energy  spending  for  a  large  sample  of  households  in  Great  Britain.  We  discern  inflection  points  and  discuss...

Jamasb, Tooraj; Meier, H

273

A Glance at China’s Household Consumption  

SciTech Connect

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.

Shui, Bin

2009-10-22T23:59:59.000Z

274

Glossary Term - Avogadro's Number  

NLE Websites -- All DOE Office Websites (Extended Search)

Atomic Number Previous Term (Atomic Number) Glossary Main Index Next Term (Beta Decay) Beta Decay Avogadro's Number Avogadro's number is the number of particles in one mole of a...

275

Racial and demographic differences in household travel and fuel purchase behavior  

Science Conference Proceedings (OSTI)

Monthly fuel purchase logs from the Residential Energy Consumption Survey's Household Transportation Panel (TP) were analyzed to determine the relationship between various household characteristics and purchase frequency, tank inventories, vehicle-miles traveled, and fuel expenditures. Multiple classification analysis (MCA) was used to relate observed differences in dependent variables to such index-type household characteristics as income and residence location, and sex, race and age of household head. Because it isolates the net effect of each parameter, after accounting for the effects of all other parameters, MCA is particularly appropriate for this type of analysis. Results reveal clear differences in travel and fuel purchase behavior for four distinct groups of vehicle-owning households. Black households tend to own far fewer vehicles with lower fuel economy, to use them more intensively, to purchase fuel more frequently, and to maintain lower fuel inventories than white households. Similarly, poor households own fewer vehicles with lower fuel economy, but they drive them less intensively, purchase fuel more frequently, and maintain lower fuel inventories than nonpoor households. Elderly households also own fewer vehicles with lower fuel economy. But since they drive them much less intensively, their fuel purchases are much less frequent and their fuel inventories are higher than nonelderly households. Female-headed households also own fewer vehicles but with somewhat higher fuel economy. They drive them less intensively, maintain higher fuel inventories, and purchase fuel less frequently than male-headed households. 13 refs., 8 tabs.

Gur, Y.; Millar, M.

1987-01-01T23:59:59.000Z

276

EvoNILM: evolutionary appliance detection for miscellaneous household appliances  

Science Conference Proceedings (OSTI)

To improve the energy awareness of consumers, it is necessary to provide them with information about their energy demand, not just on the household level. Non-intrusive load monitoring (NILM) gives the consumer the opportunity to disaggregate their consumed ... Keywords: evolutionary algorithm, load disaggregation, non-intrusive load monitoring

Dominik Egarter; Wilfried Elmenreich

2013-07-01T23:59:59.000Z

277

Modelling the Energy Demand of Households in a Combined  

E-Print Network (OSTI)

. Emissions from passenger transport, households'electricity and heat consumption are growing rapidly despite demand analysis for electricity (e.g. Larsen and Nesbakken, 2004; Holtedahl and Joutz, 2004; Hondroyiannis, 2004) and passenger cars (Meyer et al., 2007). Some recent studies cover the whole residential

Steininger, Karl W.

278

URTAC Committee Members | Department of Energy  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

URTAC Committee Members URTAC Committee Members URTAC Committee Members 2012-2014 Unconventional Resources Technology Advisory Committee Members Dr. Nancy J. Brown* Senior Scientist and Department Head Lawrence Berkeley National Laboratory Mr. Wayne K. Camp Senior Geological Advisor Anadarko Petroleum Corporation Ms. Jessica J. Cavens Geologist EnCana Oil & Gas (USA) Mr. William S. Daugherty Managing Partner Blackridge Resources Mr. James P. Dwyer VP Region Engineering Baker Hughes Mr. J. Chris Hall President Drilling & Production Co. Dr. Bob A. Hardage* Senior Research Scientist Univ. of Texas at Austin Mr. John A. Harju* Associate Director for Research Energy & Environmental Research Center University of North Dakota Dr. Robert L. Kleinberg Technical Lead, Unconventional Resources

279

February 2011 Member News 6.indd  

Science Conference Proceedings (OSTI)

Member. News. Updates on friends and colleagues in the materials community. Robert Shull Appointed NIST Fellow. The National Institute of Standards.

280

Deliver training to members | ENERGY STAR  

NLE Websites -- All DOE Office Websites (Extended Search)

Deliver training to members Secondary menu About us Press room Contact Us Portfolio Manager Login Facility owners and managers Existing buildings Commercial new construction...

Note: This page contains sample records for the topic "household members number" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


281

Evaluation program effectiveness of household hazardous waste collection: The Seattle-King County experience  

SciTech Connect

The Seattle-King County Hazardous Waste Management Plan provides the framework for an intensive effort to keep Household Hazardous and Small Quantity Generator (SQG) wastes from entering the normal'' municipal waste streams. The Plan sets ambitious goals for diverting thousands of tons of hazardous wastes from being thrown, poured or dumped in the municipal waste stream. During the first five years, over $30 millon will be spent for a variety of HHW and SQG programs. The Plan incorporates a wide range of elements, including education, collection, and compliance components. Many of the hazardous waste education and collection programs have been developed in response to the Plan, so their effectiveness is still undetermined. A key component of the Plan is program evaluation. This report provides descriptions of two evaluation methods used to establish baselines for assessing the effectiveness of the Hazardous Waste Management Plan's programs. Focusing on the Plan's household hazardous waste programs, the findings of the baseline evaluations are discussed and conclusions are made. A general population survey, conducted through telephone interviews, was designed to assess changes in knowledge, attitudes, and behaviors of area residents. Characterization of the solid waste stream was used to identify the hazardous constituents contributed to municipal solid waste by households. Monitoring changes in the amount of hazardous materials present in the waste stream was used to indicate whether or not Program strategies are influencing disposal behaviors. Comparing the data gathered by these two evaluation methods provided a unique opportunity to cross-check the findings and validate that change, if any, has occurred. From the comparisons, the report draws a number of conclusions.

1991-10-01T23:59:59.000Z

282

Using unlabeled Wi-Fi scan data to discover occupancy patterns of private households  

Science Conference Proceedings (OSTI)

This poster presents the homeset algorithm, a lightweight approach to estimate occupancy schedules of private households. The algorithm relies on the mobile phones of households' occupants to collect Wi-Fi scans. The scans are then used to determine ...

Wilhelm Kleiminger, Christian Beckel, Anind Dey, Silvia Santini

2013-11-01T23:59:59.000Z

283

California’s Immigrant Households and Public-Assistance Participation in the 1990s - Policy Brief  

E-Print Network (OSTI)

with Dependent Children (AFDC)/California Work Opportunitystate households participating in AFDC/ CalWORKs pro- grams.of noncitizen households received AFDC, compared to 4.5% of

2002-01-01T23:59:59.000Z

284

Table 1. Total Energy Consumption in U.S. Households by Origin ...  

U.S. Energy Information Administration (EIA)

Wood (million cords) ..... 21.4 19.8 0.8 0.6 0.3 19.3 Million Btu per Household3 Total Btu Consumption per Household, Fuels Used: Electricity Primary ...

285

An Analysis of the Price Elasticity of Demand for Household Appliances  

E-Print Network (OSTI)

Customers’ Choice of Appliance Efficiency Level: CombiningThe Effect of Income on Appliances in U.S. Households. U.S.Household’s Choice of Appliance Efficiency Level. Review of

Dale, Larry

2008-01-01T23:59:59.000Z

286

Household Vehicles Energy Consumption 1994 - Appendix C  

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

Introduction This appendix discusses several issues relating to the quality of the Residential Transportation Energy Consumption Survey (RTECS) data and to the interpretation of conclusions based on these data. The first section discusses undercoverage of the vehicle stock in the residential sector. The second section discusses the effects of using July 1994 as a time reference for the survey. The remainder of this appendix discusses the treatment of sampling and nonsampling errors in the RTECS, the quality of specific data items such as the Vehicle Identification Number (VIN) and fuel prices, and poststratification procedures used in the 1994 RTECS. The quality of the data collection and the processing of the data affects the accuracy of estimates based on survey data. All the statistics

287

Household energy and consumption and expenditures, 1990. [Contains Division, Census Region, and Climate Zone maps  

Science Conference Proceedings (OSTI)

The purpose of this supplement to the Household Energy Consumption and Expenditures 1990 report is to provide information on the use of energy in residential housing units, specifically at the four Census regions and nine Census division levels. This report includes household energy consumption, expenditures, and prices for natural gas, electricity, fuel oil, liquefied petroleum gas (LPG), and kerosene as well as household wood consumption. For national-level data, see the main report, Household Energy Consumption and Expenditures 1990.

Not Available

1993-03-02T23:59:59.000Z

288

Household Vehicles Energy Use: Latest Data and Trends - Table A04  

U.S. Energy Information Administration (EIA)

... Buildings & Industry > Transportation Surveys > Household Vehicles Energy ... U.S. Vehicles by Model ... Office of Coal, Nuclear, Electric, and Alternate ...

289

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

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

8 Water Heating Characteristics by Household Income, 2005" 8 Water Heating Characteristics by Household Income, 2005" " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ,"Housing Units (millions)" ,,"Less than $20,000","$20,000 to $39,999","$40,000 to $59,999","$60,000 to $79,999","$80,000 or More" "Water Heating Characteristics" "Total",111.1,26.7,28.8,20.6,13.1,22,16.6,38.6 "Number of Water Heaters" "1.",106.3,25.8,28,19.6,12.7,20.2,16,37.3 "2 or More",3.7,0.3,0.5,0.9,0.4,1.7,"Q",0.5 "Do Not Use Hot Water",1.1,0.6,0.3,"Q","N","Q",0.5,0.8

290

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

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

1 Home Electronics Characteristics by Household Income, 2005" 1 Home Electronics Characteristics by Household Income, 2005" " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ,"Housing Units (millions)" ,,"Less than $20,000","$20,000 to $39,999","$40,000 to $59,999","$60,000 to $79,999","$80,000 or More" "Home Electronics Characteristics" "Total",111.1,26.7,28.8,20.6,13.1,22,16.6,38.6 "Personal Computers" "Do Not Use a Personal Computer ",35.5,17.1,10.8,4.2,1.8,1.6,10.3,20.6 "Use a Personal Computer",75.6,9.6,18,16.4,11.3,20.3,6.4,17.9 "Number of Desktop PCs" "1.",50.3,8.3,14.2,11.4,7.2,9.2,5.3,14.2

291

" 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" 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 Units",111.1,26.7,28.8,20.6,13.1,22,16.6,38.6 "Indoor Lights Turned On During Summer" "Number of Lights Turned On" "Between 1 and 4 Hours per Day",91.8,20.8,23.6,17,11.3,19.1,13,30.7 "1.",28.6,9.4,9.1,4.5,2.4,3.2,5.7,12.6 "2.",29.5,6.8,8,5.8,3.7,5.2,4.2,10.2

292

Members | U.S. DOE Office of Science (SC)  

Office of Science (SC) Website

Members Fusion Energy Sciences Advisory Committee (FESAC) FESAC Home Meetings Members ChargesReports Charter .pdf file (140KB) FES Committees of Visitors FES Home Members Print...

293

2013 Secretary of Energy Advisory Board Members | Department...  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

3 Secretary of Energy Advisory Board Members 2013 Secretary of Energy Advisory Board Members 2013 Advisory Board Members John Deutch MIT Chemist, Former Under Secretary of Energy...

294

Established Materials Technologies - JOM: The Member Journal of ...  

Science Conference Proceedings (OSTI)

Dec 8, 2009 ... High power microwave equipment will be more common and cost much less, following the same trend as the household microwave, which cost ...

295

Pittsburgh, PA 15217 Members, County Council  

E-Print Network (OSTI)

Members, My name is Roger Dannenberg. I've lived in Pittsburgh since 1979, and I have been a member never be detected by testing. It might be detected by a complete inspection of the software programs, has recommended that electronic voting systems enable voters to inspect a paper record to verify

Eckhardt, Dave

296

Household Vehicles Energy Use: Latest Data & Trends  

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

B B : E S T I M AT I O N M E T H O D O L O G I E S APPENDIX B A P P E N D I X B ESTIMATION METHODOLOGIES INTRODUCTION The National Household Travel Survey (NHTS) is the nation's inventory of local and long distance travel, according to the U.S. Department of Transportation. Between April 2001 and May 2002, roughly 26 thousand households 41 were interviewed about their travel, based on the use of over 53 thousand vehicles. Using confidential data collected during those interviews, coupled with EIA's retail fuel prices, external data sources of test 42 fuel economy, and internal procedures for modifying test fuel economy to on-road, in-use fuel economy, EIA has extended this inventory to include the energy used for travel, thereby continuing a data series that was discontinued by EIA in 1994. This appendix presents the methods used for each eligible sampled

297

Household Vehicles Energy Use: Latest Data & Trends  

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

This page left blank. This page left blank. E N E R G Y O V E RV I E W ENERGY INFORMATION ADMINISTRATION/HOUSEHOLD VEHICLES ENERGY USE: LATEST DATA & TRENDS ENERGY OVERVIEW E N E R G Y O V E RV I E W INTRODUCTION Author's Note Estimates of gallons of fuel consumed, type of fuel used, price paid for fuel, and fuel economy are based on data imputed by EIA, using vehicle characteristics and vehicle-miles traveled data collected during the interview process for the 2001 National Household Travel Survey (NHTS). Rather than obtaining that information directly from fuel purchase diaries, EIA exploited its experience and expertise with modeling techniques for transportation studies, filling missing and uncollected data with information reported to other federal agencies, as described in Appendices

298

Household Vehicles Energy Use: Latest Data & Trends  

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

E E N E R G Y O V E RV I E W ENERGY INFORMATION ADMINISTRATION/HOUSEHOLD VEHICLES ENERGY USE: LATEST DATA & TRENDS ENERGY OVERVIEW E N E R G Y O V E RV I E W INTRODUCTION Author's Note Estimates of gallons of fuel consumed, type of fuel used, price paid for fuel, and fuel economy are based on data imputed by EIA, using vehicle characteristics and vehicle-miles traveled data collected during the interview process for the 2001 National Household Travel Survey (NHTS). Rather than obtaining that information directly from fuel purchase diaries, EIA exploited its experience and expertise with modeling techniques for transportation studies, filling missing and uncollected data with information reported to other federal agencies, as described in Appendices B and C of this report.

299

DEMEC Member Utilities - Green Energy Program Incentives (8 utilities...  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Member Utilities - Green Energy Program Incentives (8 utilities) DEMEC Member Utilities - Green Energy Program Incentives (8 utilities) Eligibility Agricultural Commercial...

300

Elasticities of Electricity Demand in Urban Indian Households  

E-Print Network (OSTI)

Energy demand, and in particular electricity demand in India has been growing at a very rapid rate over the last decade. Given, current trends in population growth, industrialisation, urbanisation, modernisation and income growth, electricity consumption is expected to increase substantially in the coming decades as well. Tariff reforms could play a potentially important role as a demand side management tool in India. However, the effects of any price revisions on consumption will depend on the price elasticity of demand for electricity. In the past, electricity demand studies for India published in international journals have been based on aggregate macro data at the country or sub-national / state level. In this paper, price and income elasticities of electricity demand in the residential sector of all urban areas of India are estimated for the first time using disaggregate level survey data for over thirty thousand households. Three electricity demand functions have been estimated using monthly data for the following seasons: winter, monsoon and summer. The results show electricity demand is income and price inelastic in all three seasons, and that household, demographic and geographical variables are important in determining electricity demand, something that is not possible to determine using aggregate macro models alone. Key Words Residential electricity demand, price elasticity, income elasticity Short Title Electricity demand in Indian households Acknowledgements: The authors would like to gratefully acknowledge the National Sample Survey Organisation, Department of Statistics of the Government of India, for making available to us the unit level, household survey data. We would also like to thank Prof. Daniel Spreng for his support of our research. 2 1.

Shonali Pachauri

2002-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "household members number" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


301

Energy conservation for household refrigerators and water heaters  

Science Conference Proceedings (OSTI)

An energy conservation arrangement for household refrigerators and water heaters, in which the source of cold water to the hot water heater is divided and part is caused to flow through and be warmed in the condenser of the refrigerator. The warmed water is then further heated in the oil cooling loop of the refrigerator compressor, and proceeds then to the top of the hot water tank.

Speicher, T. L.

1984-12-11T23:59:59.000Z

302

Sizing Wind/Photovoltaic Hybrids for Households in Inner Mongolia  

DOE Green Energy (OSTI)

Approximately 140,000 wind turbines currently provide electricity to about one-third of the non-grid-connected households in Inner Mongolia. However, these households often suffer from a lack of power during the low-wind summer months. This report describes an analysis of hybrid wind/photovoltaic (PV) systems for such households. The sizing of the major components is based on a subjective trade-off between the cost of the system and the percent unmet load, as determined by the Hybrid 2 software in conjunction with a simplified time-series model. Actual resource data (wind speed and solar radiation) from the region are processed so as to best represent the scenarios of interest. Small wind turbines of both Chinese and U.S. manufacture are considered in the designs. The results indicate that combinations of wind and PV are more cost-effective than either one alone, and that the relative amount of PV in the design increases as the acceptable unmet load decreases and as the average wind sp eed decreases.

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

1997-06-01T23:59:59.000Z

303

Elastomeric member for energy storage device  

DOE Patents (OSTI)

An energy storage device (10) is disclosed consisting of a stretched elongated elastomeric member (16), disposed within a tubular housing (14), which elastomeric member (16) is adapted to be torsionally stressed to store energy. The elastomeric member (16) is configured in the relaxed state with a uniform diameter body section, transition end sections, and is attached to rigid end piece assemblies (22, 24) of a lesser diameter. The profile and deflection characteristic of the transition sections (76, 78) are such that upon stretching of the member, a substantially uniform diameter assembly results to minimize the required volume of the surrounding housing (14). During manufacture, woven wire mesh sleeves (26, 28) are forced against a forming surface and bonded to the associated transition section (76, 78) to provide the correct profile and helix angle. Each sleeve (26, 28) contracts with the contraction of the associated transition section to maintain the bond therebetween.

Hoppie, Lyle O. (Birmingham, MI); Chute, Richard (Birmingham, MI)

1985-01-01T23:59:59.000Z

304

STRUCTURAL PERFORMANCE OF DEGRADED REINFORCED CONCRETE MEMBERS.  

Science Conference Proceedings (OSTI)

This paper describes the results of a study to evaluate, in probabilistic terms, the effects of age-related degradation on the structural performance of reinforced concrete members at nuclear power plants. The paper focuses on degradation of reinforced concrete flexural members and shear walls due to the loss of steel reinforcing area and loss of concrete area (cracking/spalling). Loss of steel area is typically caused by corrosion while cracking and spalling can be caused by corrosion of reinforcing steel, freeze-thaw, or aggressive chemical attack. Structural performance in the presence of uncertainties is depicted by a fragility (or conditional probability of failure). The effects of degradation on the fragility of reinforced concrete members are calculated to assess the potential significance of various levels of degradation. The fragility modeling procedures applied to degraded concrete members can be used to assess the effects of degradation on plant risk and can lead to the development of probability-based degradation acceptance limits.

Braverman, J.I.; Miller, C.A.; Ellingwood, B.R.; Naus, D.J.; Hofmayer, C.H.; Bezler, P.; Chang, T.Y.

2001-03-22T23:59:59.000Z

305

Environmental Management Advisory Board Members | Department...  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

comprise the current Board: Current Members James A. Ajello EMAB Board Chair Read Bio Dennis P. Ferrigno EMAB Board Vice-Chair Read Bio Franklin E. Coffman EMAB Board...

306

Jurisdiction Members Contact Info Key Staffers  

E-Print Network (OSTI)

Relevant Jurisdiction Members Contact Info Key Staffers House Science, Space, and Technology, aeronautics, civil aviation, environment, and marine science · America COMPETES · Energy labs · National Science Foundation, including NCAR · National Aeronautics and Space Administration · National Weather

307

Tell members how to save | ENERGY STAR  

NLE Websites -- All DOE Office Websites (Extended Search)

and Honest Buildings if you do. AH&LA educates its members about efficiency The American Hotel & Lodging Association (AH&LA) developed a robust educational campaign to bring...

308

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

SciTech Connect

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.

Jacobsen, R., E-mail: ray.jacobsen@ugent.be [Department of Agricultural Economics, Ghent University, Coupure Links 653, B-9000 Ghent (Belgium); Buysse, J., E-mail: j.buysse@ugent.be [Department of Agricultural Economics, Ghent University, Coupure Links 653, B-9000 Ghent (Belgium); Gellynck, X., E-mail: xavier.gellynck@ugent.be [Department of Agricultural Economics, Ghent University, Coupure Links 653, B-9000 Ghent (Belgium)

2013-01-15T23:59:59.000Z

309

Gaussian random number generators  

Science Conference Proceedings (OSTI)

Rapid generation of high quality Gaussian random numbers is a key capability for simulations across a wide range of disciplines. Advances in computing have brought the power to conduct simulations with very large numbers of random numbers and with it, ... Keywords: Gaussian, Random numbers, normal, simulation

David B. Thomas; Wayne Luk; Philip H.W. Leong; John D. Villasenor

2007-11-01T23:59:59.000Z

310

Amicalola Electric Member Corp | Open Energy Information  

Open Energy Info (EERE)

Amicalola Electric Member Corp Amicalola Electric Member Corp Jump to: navigation, search Name Amicalola Electric Member Corp Place Georgia Utility Id 562 Utility Location Yes Ownership C NERC Location SERC NERC SERC Yes Activity Distribution Yes References EIA Form EIA-861 Final Data File for 2010 - File1_a[1] LinkedIn Connections CrunchBase Profile No CrunchBase profile. Create one now! This article is a stub. You can help OpenEI by expanding it. Utility Rate Schedules Grid-background.png Security Lights Acorn 100 W Lighting Security Lights Acorn 150 W Lighting Security Lights Cobra 100 W Lighting Security Lights Cobra 150 W Lighting Security Lights Cobra 250 W Lighting Security Lights Cobra 400 W Lighting Security Lights Cobra MH 250 W Lighting Security Lights Cobra MH 400 W Lighting Security Lights Flood 250 W Lighting

311

Roanoke Electric Member Corp | Open Energy Information  

Open Energy Info (EERE)

Roanoke Electric Member Corp Roanoke Electric Member Corp Jump to: navigation, search Name Roanoke Electric Member Corp Place North Carolina Utility Id 16101 Utility Location Yes Ownership C NERC Location SERC NERC SERC Yes RTO PJM Yes Activity Distribution Yes References EIA Form EIA-861 Final Data File for 2010 - File1_a[1] LinkedIn Connections CrunchBase Profile No CrunchBase profile. Create one now! This article is a stub. You can help OpenEI by expanding it. Utility Rate Schedules Grid-background.png Commercial Service Single Phase (energy charge only) Commercial Commercial Service Single-Phase > 100 kW Commercial Commercial Service Single-Phase < 100 kW Commercial Commercial Service Three Phase (energy charge only) Commercial Commercial Service Three Phase Demand/Energy equal too or >100 kW

312

Brunswick Electric Member Corp | Open Energy Information  

Open Energy Info (EERE)

Brunswick Electric Member Corp Brunswick Electric Member Corp Jump to: navigation, search Name Brunswick Electric Member Corp Place North Carolina Utility Id 24889 Utility Location Yes Ownership C NERC Location SERC NERC SERC Yes Activity Distribution Yes References EIA Form EIA-861 Final Data File for 2010 - File1_a[1] Energy Information Administration Form 826[2] LinkedIn Connections CrunchBase Profile No CrunchBase profile. Create one now! This article is a stub. You can help OpenEI by expanding it. Utility Rate Schedules Grid-background.png Basic Sodium Vapor Light Lighting General Service - Single Phase Commercial General Service - Single Phase Curtailable Service Commercial General Service - Three Phase Commercial General Service - Three Phase Curtailable Service Commercial Net Metering Rider Commercial

313

Carroll Electric Member Corp | Open Energy Information  

Open Energy Info (EERE)

Member Corp Member Corp Jump to: navigation, search Name Carroll Electric Member Corp Place Georgia Utility Id 3081 Utility Location Yes Ownership C NERC Location SERC NERC SERC Yes Activity Distribution Yes References EIA Form EIA-861 Final Data File for 2010 - File1_a[1] LinkedIn Connections CrunchBase Profile No CrunchBase profile. Create one now! This article is a stub. You can help OpenEI by expanding it. Utility Rate Schedules Grid-background.png General Service Rate Industrial General Service Rate* Industrial Irrigation Off-Peak Seasonal Service Commercial Large Power Service Industrial Large Power Service* Load Management Service- Coincident W/ Multi-hr Peak Load Management Service- Coincident w/ ITS Peak Demand Load Management Service- Non Coincident Peak Demand

314

Oconee Electric Member Corp | Open Energy Information  

Open Energy Info (EERE)

Oconee Electric Member Corp Oconee Electric Member Corp Jump to: navigation, search Name Oconee Electric Member Corp Place Georgia Utility Id 13962 Utility Location Yes Ownership C NERC Location SERC NERC SERC Yes Activity Distribution Yes References EIA Form EIA-861 Final Data File for 2010 - File1_a[1] LinkedIn Connections CrunchBase Profile No CrunchBase profile. Create one now! This article is a stub. You can help OpenEI by expanding it. Utility Rate Schedules Grid-background.png General Service Commercial Large Power Service Commercial Large Power Service* Industrial Outdoor Lighting MV 175 W Overhead Lighting Outdoor Lighting MV 175 W Underground Lighting Outdoor Lighting S 100 W Overhead Lighting Outdoor Lighting S 100 W Underground Lighting Residential and Farm Service Residential

315

Upson Elec Member Corp | Open Energy Information  

Open Energy Info (EERE)

Elec Member Corp Elec Member Corp Place Georgia Utility Id 19581 Utility Location Yes Ownership C NERC Location SERC NERC SERC Yes Activity Distribution Yes References EIA Form EIA-861 Final Data File for 2010 - File1_a[1] LinkedIn Connections CrunchBase Profile No CrunchBase profile. Create one now! This article is a stub. You can help OpenEI by expanding it. Utility Rate Schedules Grid-background.png Rate 1,6 - Residental Service Residential Rate 3,7 - General Service Commercial Rate 8,10 - General Service Commercial Average Rates Residential: $0.1020/kWh Commercial: $0.1150/kWh Industrial: $0.0834/kWh References ↑ "EIA Form EIA-861 Final Data File for 2010 - File1_a" Retrieved from "http://en.openei.org/w/index.php?title=Upson_Elec_Member_Corp&oldid=411917

316

Tideland Electric Member Corp | Open Energy Information  

Open Energy Info (EERE)

Tideland Electric Member Corp Tideland Electric Member Corp Jump to: navigation, search Name Tideland Electric Member Corp Place North Carolina Utility Id 19108 Utility Location Yes Ownership C NERC SERC Yes RTO PJM Yes Activity Distribution Yes References EIA Form EIA-861 Final Data File for 2010 - File1_a[1] LinkedIn Connections CrunchBase Profile No CrunchBase profile. Create one now! This article is a stub. You can help OpenEI by expanding it. Utility Rate Schedules Grid-background.png Cotton Gin - On season Commercial Large Power (Time-of-use Service) Commercial Large Power Service Commercial NC GreenPower NC GreenPower Generator- Small Solar PV Systems - 5 to 10 kW NC GreenPower Generator- Small Solar PV Systems - Less than 5 kW NC GreenPower Generator-Small Wind Systems - 10 kW and under

317

Canoochee Electric Member Corp | Open Energy Information  

Open Energy Info (EERE)

Canoochee Electric Member Corp Canoochee Electric Member Corp Jump to: navigation, search Name Canoochee Electric Member Corp Place Georgia Utility Id 2903 Utility Location Yes Ownership C NERC Location SERC NERC SERC Yes Activity Distribution Yes References EIA Form EIA-861 Final Data File for 2010 - File1_a[1] LinkedIn Connections CrunchBase Profile No CrunchBase profile. Create one now! This article is a stub. You can help OpenEI by expanding it. Utility Rate Schedules Grid-background.png Demand Service- DM-1 Commercial GS-1 Commercial GS-3 Commercial IR-1 Commercial IR-3 Large Power Service- LP-1 Industrial Load Management Service- LM-2 Commercial Load Mangament Service- LM-3 Commercial Power and Light Industrial Residential Service- RS-1 Residential Security Lighting Service- SL (1000W HPS Flood) Lighting

318

LEDSGP/about/members | Open Energy Information  

Open Energy Info (EERE)

Page Page Edit History Facebook icon Twitter icon » LEDSGP/about/members < LEDSGP‎ | about Jump to: navigation, search LEDSGP Logo.png Advancing climate-resilient low emission development around the world Home About Tools Expert Assistance Events Publications Join Us About How We Work > Regional Platforms > Working Groups LEDS GP Members Steering Committee Guiding Structure Contacts Members of the LEDS Global Partnership More than 110 countries and international institutions have joined the partnership to support collaboration and peer learning on climate-resilient low emission development. AUSAidLogo.png AG-DOCC.JPG Sustentar.jpg Logotipo minambientevertical escala grises1.jpg Minaetlogo.png European Flag(1).gif GIZlogo.JPG Sponsor.jpg JICA-Logo.jpg Ine320.gif Logotipo minambientevertical escala grises1.jpg

319

Planters Electric Member Corp | Open Energy Information  

Open Energy Info (EERE)

Planters Electric Member Corp Planters Electric Member Corp Jump to: navigation, search Name Planters Electric Member Corp Place Georgia Utility Id 14649 Utility Location Yes Ownership C NERC Location SERC NERC SERC Yes Activity Distribution Yes References EIA Form EIA-861 Final Data File for 2010 - File1_a[1] LinkedIn Connections CrunchBase Profile No CrunchBase profile. Create one now! This article is a stub. You can help OpenEI by expanding it. Utility Rate Schedules Grid-background.png Schedule 1 - Home Energy Partner Service Residential Schedule 2 - Energy Partner Service Non Demand Option Schedule 20 - Large Commercial Partner Service Commercial Schedule 21 - Athletic or Recreational Complex Partner Service Commercial Schedule 3 - Energy Partner Service Demand Option Schedule 4 - Irrigation Service, Interruptible Commercial

320

Pataula Electric Member Corp | Open Energy Information  

Open Energy Info (EERE)

Pataula Electric Member Corp Pataula Electric Member Corp Jump to: navigation, search Name Pataula Electric Member Corp Place Georgia Utility Id 14588 Utility Location Yes Ownership C NERC Location SERC NERC SERC Yes Activity Distribution Yes References EIA Form EIA-861 Final Data File for 2010 - File1_a[1] LinkedIn Connections CrunchBase Profile No CrunchBase profile. Create one now! This article is a stub. You can help OpenEI by expanding it. Utility Rate Schedules Grid-background.png Schedule DGS - Distribution Generation Service, Multi Phase Commercial Schedule DGS - Distribution Generation Service, Single Phase Commercial Schedule FM - Farm and Home Service Residential Schedule GS - General Service, Multi Phase Commercial Schedule GS - Single Phase (First 200 kWh per kW of Billing Demand)

Note: This page contains sample records for the topic "household members number" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


321

Randolph Electric Member Corp | Open Energy Information  

Open Energy Info (EERE)

Electric Member Corp Electric Member Corp Jump to: navigation, search Name Randolph Electric Member Corp Place North Carolina Utility Id 15671 Utility Location Yes Ownership C NERC Location SERC NERC SERC Yes Activity Buying Transmission Yes Activity Distribution Yes Activity Retail Marketing Yes References EIA Form EIA-861 Final Data File for 2010 - File1_a[1] LinkedIn Connections CrunchBase Profile No CrunchBase profile. Create one now! This article is a stub. You can help OpenEI by expanding it. Utility Rate Schedules Grid-background.png A23 - SINGLE-PHASE SERVICE Residential A23EE - SINGLE-PHASE ENERGY EFFICIENT HOME SERVICE Residential A23TOU - SINGLE-PHASE TIME-OF-USE SERVICE Residential GS23 - SINGLE PHASE COMMERCIAL Commercial GS23 - SINGLE-PHASE COMMERCIAL - Two Part Tariff Commercial

322

Gibson Electric Members Corp | Open Energy Information  

Open Energy Info (EERE)

Gibson Electric Members Corp Gibson Electric Members Corp Jump to: navigation, search Name Gibson Electric Members Corp Place Tennessee Utility Id 7174 Utility Location Yes Ownership C NERC Location SERC NERC SERC Yes Activity Distribution Yes References EIA Form EIA-861 Final Data File for 2010 - File1_a[1] Energy Information Administration Form 826[2] LinkedIn Connections CrunchBase Profile No CrunchBase profile. Create one now! This article is a stub. You can help OpenEI by expanding it. Utility Rate Schedules Grid-background.png Commercial Rate-Poly Phase Commercial Commercial Rate-Single Phase Commercial Green Power Switch Industrial Rate-Poly Phase Industrial Industrial Rate-Single Phase Industrial Residential rates Residential Average Rates Residential: $0.0960/kWh Commercial: $0.1130/kWh

323

Altamaha Electric Member Corp | Open Energy Information  

Open Energy Info (EERE)

Altamaha Electric Member Corp Altamaha Electric Member Corp Jump to: navigation, search Name Altamaha Electric Member Corp Place Georgia Utility Id 407 Utility Location Yes Ownership C NERC Location SERC NERC SERC Yes Activity Distribution Yes References EIA Form EIA-861 Final Data File for 2010 - File1_a[1] LinkedIn Connections CrunchBase Profile No CrunchBase profile. Create one now! This article is a stub. You can help OpenEI by expanding it. Utility Rate Schedules Grid-background.png Industrial Service Industrial Irrigation Service- IRGS-8 Commercial Large Power Service- LPS Commercial Net Metering Service- NMS-8 Commercial Outdoor Security Lighting Service- SL-9 (1000W HPS-Flood) Lighting Outdoor Security Lighting Service- SL-9 (1000W MH-Flood) Lighting Outdoor Security Lighting Service- SL-9 (1000W MH-Flood) Lighting

324

Walton Electric Member Corp | Open Energy Information  

Open Energy Info (EERE)

Walton Electric Member Corp Walton Electric Member Corp (Redirected from Walton EMC) Jump to: navigation, search Name Walton Electric Member Corp Place Georgia Utility Id 20065 Utility Location Yes Ownership C NERC Location SERC NERC SERC Yes Activity Distribution Yes References EIA Form EIA-861 Final Data File for 2010 - File1_a[1] LinkedIn Connections CrunchBase Profile No CrunchBase profile. Create one now! This article is a stub. You can help OpenEI by expanding it. Utility Rate Schedules Grid-background.png 14' Aluminum Lighting 20' F/G Lighting 30' F/G Lighting 30-6 Wood Lighting Cobrahead- HPS 100 Watt Bronze (UG) Lighting Cobrahead- HPS 100 Watt Gray Lighting Cobrahead- HPS 100 Watt Gray (UG) Lighting Cobrahead- HPS 150 Bronze Watt (UG) Lighting Cobrahead- HPS 150 Watt Gray Lighting

325

Cumberland Elec Member Corp | Open Energy Information  

Open Energy Info (EERE)

Elec Member Corp Elec Member Corp Jump to: navigation, search Name Cumberland Elec Member Corp Place Tennessee Utility Id 4624 Utility Location Yes Ownership C NERC Location SERC NERC SERC Yes Activity Distribution Yes References EIA Form EIA-861 Final Data File for 2010 - File1_a[1] Energy Information Administration Form 826[2] LinkedIn Connections CrunchBase Profile No CrunchBase profile. Create one now! This article is a stub. You can help OpenEI by expanding it. Utility Rate Schedules Grid-background.png Commercial GSA 3 Commercial Commercial GSA 1 Commercial Commercial GSA 2 Commercial Facilities Rental (46-161 kV) Commercial Facilities Rental (less than 46 kV) Commercial Generation Partner 1 - Energy Credit Commercial Generation Partner 1 - Other Renewable Premium Commercial

326

Hart Electric Member Corp | Open Energy Information  

Open Energy Info (EERE)

Hart Electric Member Corp Hart Electric Member Corp Jump to: navigation, search Name Hart Electric Member Corp Place Georgia Utility Id 8210 Utility Location Yes Ownership C NERC Location SERC NERC SERC Yes Activity Distribution Yes References EIA Form EIA-861 Final Data File for 2010 - File1_a[1] LinkedIn Connections CrunchBase Profile No CrunchBase profile. Create one now! This article is a stub. You can help OpenEI by expanding it. Utility Rate Schedules Grid-background.png Schedule A-10 Farm and Home Service Residential Schedule A-EM-10 Residential Energy Management Residential Schedule B-10 Small Commercial Service Commercial Schedule B-10 Small Commercial Service Multi-Phase Commercial Schedule C-10 Large Commercial and Industrial Service Schedule CS-1,2,3 Contract School Service

327

Excelsior Electric Member Corp | Open Energy Information  

Open Energy Info (EERE)

Excelsior Electric Member Corp Excelsior Electric Member Corp Jump to: navigation, search Name Excelsior Electric Member Corp Place Georgia Utility Id 5905 Utility Location Yes Ownership C NERC Location SERC NERC SERC Yes Activity Distribution Yes References EIA Form EIA-861 Final Data File for 2010 - File1_a[1] LinkedIn Connections CrunchBase Profile No CrunchBase profile. Create one now! This article is a stub. You can help OpenEI by expanding it. Utility Rate Schedules Grid-background.png Athletic Field Lighting Service Lighting General Service- Single Phase Commercial General Service- Three Phase Commercial Irrigation Service- Controlled Commercial Irrigation Service- Non-Controlled Commercial Large Industrial Service Industrial Large Power Service Commercial Large School Service Commercial

328

Haywood Electric Member Corp | Open Energy Information  

Open Energy Info (EERE)

Electric Member Corp Electric Member Corp Jump to: navigation, search Name Haywood Electric Member Corp Place North Carolina Utility Id 8333 Utility Location Yes Ownership C NERC Location SERC NERC SERC Yes Activity Distribution Yes References EIA Form EIA-861 Final Data File for 2010 - File1_a[1] LinkedIn Connections CrunchBase Profile No CrunchBase profile. Create one now! This article is a stub. You can help OpenEI by expanding it. Utility Rate Schedules Grid-background.png 10 Small General Service Single Phase 11 Small General Service Three Phase 12 Small General Time of Day Service Single Phase Commercial 13 Small General Time of Day Service Three Phase 14 Small General Demand Service Single Phase Commercial 17 Small General $mart Rate Service Single Phase- Controlled Kwh Commercial

329

Coastal Electric Member Corp | Open Energy Information  

Open Energy Info (EERE)

Member Corp Member Corp Place Georgia Utility Id 3843 Utility Location Yes Ownership C NERC Location SERC NERC SERC Yes Activity Distribution Yes References EIA Form EIA-861 Final Data File for 2010 - File1_a[1] LinkedIn Connections CrunchBase Profile No CrunchBase profile. Create one now! This article is a stub. You can help OpenEI by expanding it. Utility Rate Schedules Grid-background.png General Demand Multi Phase Industrial General Demand Single Phase Industrial General Non Demand Multi Phase Commercial General Non Demand Single Phase Commercial Residential Residential Average Rates Residential: $0.1110/kWh Commercial: $0.1010/kWh Industrial: $0.0606/kWh References ↑ "EIA Form EIA-861 Final Data File for 2010 - File1_a" Retrieved from "http://en.openei.org/w/index.php?title=Coastal_Electric_Member_Corp&oldid=410484"

330

Mitchell Electric Member Corp | Open Energy Information  

Open Energy Info (EERE)

Mitchell Electric Member Corp Mitchell Electric Member Corp Jump to: navigation, search Name Mitchell Electric Member Corp Place Georgia Utility Id 12706 Utility Location Yes Ownership C NERC Location SERC NERC SERC Yes Activity Distribution Yes References EIA Form EIA-861 Final Data File for 2010 - File1_a[1] LinkedIn Connections CrunchBase Profile No CrunchBase profile. Create one now! This article is a stub. You can help OpenEI by expanding it. Utility Rate Schedules Grid-background.png SCHEDULE A-14 RESIDENTIAL SERVICE Residential SCHEDULE A-14 RESIDENTIAL SERVICE Multi-Phase Residential SCHEDULE AG-14 AGRICULTURAL SERVICE Commercial SCHEDULE AG-14 AGRICULTURAL SERVICE MULTI-PHASE SCHEDULE C-14 SINGLE-PHASE COMMERCIAL SERVICE Commercial SCHEDULE GS-14 GENERAL SERVICE Commercial SCHEDULE HLF-14 HIGH LOAD FACTOR LARGE POWER SERVICE Commercial

331

Facility Representative Program: Field Office Steering Committee Members  

NLE Websites -- All DOE Office Websites (Extended Search)

HQ Program Office Steering Committee Members HQ Program Office Steering Committee Members Field Office Steering Committee Members There are 43 records Click E-Mail to contact the person Office Location Last Name First Name Phone Number E-Mail NPO (Y-12_ Dep AM Ops Afong Scotty 865-574-0827 Scotty.Afong@npo.doe.gov NPO (PX) Am Ops Alvarado Carlos R. 806-477-4919 carlos.alvarado@npo.doe.gov ORO (EM) EM Fac Ops Dir Armstrong Jason 865-576-0654 armstrongja@emor.doe.gov FSO Fermilab Arnold Sally 630-840-2239 sally.arnold@ch.doe.gov SR NA26 MOX/WSB Caudle Keith 803-646-3339 keith.caudle@nnsa.srs.gov LAFO FR Team Lead Christie Ed 505-665-2821 edwin.christie@nnsa.doe.gov OSO (SC) HFIR Clifton Gary 865-576-6810 g7y@ornl.gov EMCBC SPRU Cochran Thomas 518-395-7201 Thomas.Cochran@emcbc.doe.gov

332

Quantum Random Number Generator  

Science Conference Proceedings (OSTI)

... trusted beacon of random numbers. You could conduct secure auctions, or certify randomized audits of data. One of the most ...

2013-08-30T23:59:59.000Z

333

Exemplifying Business Opportunities for Improving Data Quality From Corporate Household Research  

E-Print Network (OSTI)

Corporate household (CHH) refers to the organizational information about the structure within the corporation and a variety of inter-organizational relationships. Knowledge derived from this data is ...

Madnick, Stuart

2004-12-10T23:59:59.000Z

334

U.S. households forecast to use more heating fuels this ...  

U.S. Energy Information Administration (EIA)

What is the role of coal in the United States? ... 2012 U.S. households ... many located in rural areas. Propane inventories totaled almost 76 million ...

335

Methodology and Estimation of the Welfare Impact of Energy Reforms on Households in Azerbaijan.  

E-Print Network (OSTI)

??ABSTRACT Title of Dissertation: METHODOLOGY AND ESTIMATION OF THE WELFARE IMPACT OF ENERGY REFORMS ON HOUSEHOLDS IN AZERBAIJAN Irina Klytchnikova, Doctor of Philosophy, 2006 Dissertation… (more)

Klytchnikova, Irina

2006-01-01T23:59:59.000Z

336

Testing Electric Vehicle Demand in "Hybrid Households" Using a Reflexive Survey  

E-Print Network (OSTI)

In contrast to a hybrid vehicle whichcombines multiple1994) "Demand Electric Vehicles in Hybrid for Households:or 180 mile hybrid electric vehicle. Natural gas vehicles (

Kurani, Kenneth S.; Turrentine, Thomas; Sperling, Daniel

2001-01-01T23:59:59.000Z

337

The impact of physical planning policy on household energy use and greenhouse emissions .  

E-Print Network (OSTI)

??This thesis investigates the impact of physical planning policy on combined transport and dwelling-related energy use by households. Separate analyses and reviews are conducted into… (more)

Rickwood, Peter

338

Table AP1. Total Households Using Home Appliances and Lighting by ...  

U.S. Energy Information Administration (EIA)

Total Consumption for Home Appliances and Lighting by Fuels Used, 2005 Quadrillion British Thermal Units (Btu) U.S. Households (millions) Electricity

339

Table CE1-4c. Total Energy Consumption in U.S. Households by Type ...  

U.S. Energy Information Administration (EIA)

Total Energy Consumption in U.S. Households by Type of Housing Unit, 2001 RSE Column Factor: Total ... where the end use is electric air-conditioning, ...

340

The Other Energy Crisis: Managing Urban Household Energy Use in Senegal  

E-Print Network (OSTI)

for 62 percent of national energy consumption, or over 1 .1energy consumption, and (2) residential, because of the dominant role that households play in national

Leitmann, Josef

1989-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "household members number" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


341

Table 1. Consumption and Expenditures in U.S. Households, 1997  

U.S. Energy Information Administration (EIA)

A household is assigned to a climate zone according to the 30-year average annual degree-days for an appropriate nearby weather station. (5) ...

342

U.S. household expenditures for gasoline account for nearly 4% of ...  

U.S. Energy Information Administration (EIA)

Electricity. Sales, revenue and prices, power plants, fuel use, ... a rise in average gasoline prices has led to higher overall household gasoline expenditures.

343

Assessing the Environmental Costs and Benefits of Households Electricity Consumption Management.  

E-Print Network (OSTI)

?? In this study the environmental costs and benefits of smart metering technology systems installed in households in Norway have been assessed. Smart metering technology… (more)

Segtnan, Ida Lund

2011-01-01T23:59:59.000Z

344

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

E-Print Network (OSTI)

and V. Letschert (2005). Forecasting Electricity Demand in8364 Material World: Forecasting Household ApplianceMcNeil, 2008). Forecasting Diffusion Forecasting Variables

Letschert, Virginie

2010-01-01T23:59:59.000Z

345

An Analysis of the Price Elasticity of Demand for Household Appliances  

E-Print Network (OSTI)

Refrigerators Clothes Washers Dishwashers Economic VariablesWASHERS, AND DISHWASHERS……………………………3 Physical Household andclothes washers and dishwashers. In the context of

Dale, Larry

2008-01-01T23:59:59.000Z

346

In the UNITED STATES there are 96.6 million households  

U.S. Energy Information Administration (EIA)

In the UNITED STATES there are 96.6 million households 69% are single-family homes; 25% are apartments; and 6% are mobile homes. Housing stock is ...

347

Table 1. Total Energy Consumption in U.S. Households by ...  

U.S. Energy Information Administration (EIA)

This write-up presents 1997 Residential Energy Consumption and Expenditures by Origin of Householder. In 1997, there were 101.5 million residential ho ...

348

Table SH2. Total Households by Space Heating Fuels Used, 2005 ...  

U.S. Energy Information Administration (EIA)

Total Households by Space Heating Fuels Used, 2005 ... 2005 Residential Energy Consumption Survey: ... Electricity Natural Gas Fuel Oil Kerosene LPG Other

349

Table 2. Fuel Oil Consumption and Expeditures in U.S. Households ...  

U.S. Energy Information Administration (EIA)

Fuel Oil Consumption and Expeditures in U.S. Households ... Space Heating - Main or Secondary ... Forms EIA-457 A-G of the 2001 Residential Energy Consumption

350

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

Reports and Publications (EIA)

This web page page entails how people live, the factors that cause the most differences in home lifestyle, including energy use in Geographic Location, Socioeconomics and Household Income.

Michael Laurence

2004-01-01T23:59:59.000Z

351

Table 3. Total Energy Consumption in U.S. Households by ...  

U.S. Energy Information Administration (EIA)

This write-up presents 1997 Residential Energy Consumption and Expenditures by Origin of Householder. In 1997, there were 101.5 million residential ...

352

U.S. household expenditures for gasoline account for nearly 4% ...  

U.S. Energy Information Administration (EIA)

Gasoline expenditures in 2012 for the average U.S. household reached $2,912, or just under 4% of income before taxes, according to EIA estimates.

353

Table WH2. Total Households by Water Heating Fuels Used, 2005 ...  

U.S. Energy Information Administration (EIA)

Total Households by Water Heating Fuels Used, 2005 ... 2005 Residential Energy Consumption Survey: Energy Consumption and Expenditures Tables. Table WH2.

354

Residential energy consumption and expenditure patterns of black and nonblack households in the United States  

Science Conference Proceedings (OSTI)

Residential energy consumption and expenditures by black and nonblack households are presented by Census region and for the nation based on the Energy Information Administration's 1982-83 Residential Energy Consumption Survey (RECS). Black households were found to have significantly lower levels of electricity consumption at both the national and regional level. Natural gas is the dominant space heating fuel used by black households. Natural gas consumption was typically higher for black households. However, when considering natural gas consumption conditional on natural gas space heating no significant differences were found. 10 refs., 1 fig., 8 tabs.

Vyas, A.D.; Poyer, D.A.

1987-01-01T23:59:59.000Z

355

Household Vehicles Energy Use: Latest Data and Trends - Table A01  

U.S. Energy Information Administration (EIA)

U.S. Per Household Vehicle-Miles Traveled ... and Alternate Fuels, Form EIA-826, "Monthly Electric Utility Sales and Revenue Report with State Distributions."

356

Elastomeric member and method of manufacture therefor  

DOE Patents (OSTI)

An energy storage device (10) is disclosed consisting of a stretched elongated elastomeric member (16) disposed within a tubular housing (14), which elastomeric member (16) is adapted to be torsionally stressed to store energy. The elastomeric member (16) is configured in the relaxed state with a uniform diameter body section (74), and transition end sections (76, 78), attached to rigid end piece assemblies (22, 24) of a lesser diameter. The profile and deflection characteristic of the transition sections (76, 78) are such that upon stretching of the elastomeric member (16), a substantially uniform diameter assembly results, to minimize the required volume of the surrounding housing (14). Each of the transition sections (76, 78) are received within and bonded to a woven wire mesh sleeve (26, 28) having helical windings at a particular helix angle to control the deflection of the transition section. Each sleeve (26, 28) also contracts with the contraction of the associated transition section to maintain the bond therebetween. During manufacture, the sleeves (26, 28) are forced against a forming surface and bonded to the associated transition section (76, 78) to provide the correct profile and helix angle.

Hoppie, Lyle O. (Birmingham, MI)

1985-01-01T23:59:59.000Z

357

Successful Strategies for Teams Team Member Handbook  

E-Print Network (OSTI)

Successful Strategies for Teams Team Member Handbook by Frances A. Kennedy, Ph.D. Associate. Kennedy, 2008 Teaming Handbook Page 2 #12;Table of Contents PART 1: Introduction..................................................................... 88 Teaming Handbook Page 3 Whenever you see this box, you can find a template to help you

Stuart, Steven J.

358

Vacant, * Deputy Chief Administrative Judge (Technical) Members  

E-Print Network (OSTI)

*Permanent panel members iii PREFACE This is the fifty-third volume of issuances (1 – 572) of the Nuclear Regulatory Commission and its Atomic Safety and Licensing Boards, Administrative Law Judges, and Office Directors. It covers the period from January 1, 2001, to

Richard A. Meserve; Greta J. Dicus; Nils J. Diaz; Edward Mcgaffigan; Jeffrey S. Merrifield; William D. Travers; Executive Director For Operations; Karen D. Cyr; General Counsel; Dr. George; C. Anderson; Dr. Frank; F. Hooper; Thomas D. Murphy; Charles Bechhoefer; Dr. Charles; N. Kelber; Dr. Harry Rein; Dr. Richard; F. Cole; Dr. Peter; S. Lam; Lester S. Rubenstein; Dr. Harry; Foreman Dr; Linda W. Little; Ivan W. Smith; Dr. David; L. Hetrick; Thomas S. Moore; Ann M. Young

2001-01-01T23:59:59.000Z

359

APPOINTMENT OF A JOINT MEMBER New Appointment  

E-Print Network (OSTI)

APPOINTMENT OF A JOINT MEMBER Renewal: New Appointment: "A joint appointment reflects the active with an academic appointment in one academic unit may be given a joint appointment in another academic unit. ..." [Article 13.10.1] In the case of a new hire, where the intention is a Joint Appointment, there needs

Saskatchewan, University of

360

Member News Nano News Press Releases  

E-Print Network (OSTI)

NanoNEWS Member News Nano News Press Releases Nano Global News Nano Reports Nano Conferences", Exploring Matter with Synchrotron Light" and "Exploring Matter with Neutrons" by ordering from here. Nano. Send your Press R Judith.LightFeather@TNTG.org 14 Oct 2006 Researchers develop bistable nano switch

Espinosa, Horacio D.

Note: This page contains sample records for the topic "household members number" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


361

Environmental Management Advisory Board Members | Department of Energy  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Communication & Engagement » EMAB » Environmental Communication & Engagement » EMAB » Environmental Management Advisory Board Members Environmental Management Advisory Board Members EMAB membership reflects a diversity of views, demographics, expertise, and professional and academic experience. The following members comprise the current Board: Current Members James A. Ajello EMAB Board Chair Read Bio ‣ Dennis P. Ferrigno EMAB Board Vice-Chair Read Bio ‣ Franklin E. Coffman EMAB Board Member Read Bio ‣ Paul M. Dabbar EMAB Board Member Read Bio ‣ G. Brian Estes EMAB Board Member Read Bio ‣ Jane A. Hedges EMAB Board Member Read Bio ‣ Carolyn L. Huntoon EMAB Board Member Read Bio ‣ Kimberlee Kearfott EMAB Board Member Read Bio ‣ John A. Owsley EMAB Board Member Read Bio ‣ Willie Preacher EMAB Board Member

362

An analysis of residential energy consumption and expenditures by minority households by home type and housing vintage  

SciTech Connect

In this paper a descriptive analysis of the relationship between energy consumption, patterns of energy use, and housing stock variables is presented. The purpose of the analysis is to uncover evidence of variations in energy consumption and expenditures, and patterns of energy use between majority households (defines as households with neither a black nor Hispanic head of household), black households (defined as households with a black head of household), and Hispanic households (defined as households with a Hispanic head of household) between 1980 (time of the first DOE/EIA Residential Energy Consumption Survey, 1982a) and 1987 (time of the last DOE/EIA Residential Energy Consumption Survey, 1989a). The analysis is three-dimensional: energy consumption and expenditures are presented by time (1980 to 1987), housing vintage, and housing type. A comparative analysis of changes in energy variables for the three population groups -- majority, black, and Hispanic -- within and between specific housing stock categories is presented.

Poyer, D.A.

1992-01-01T23:59:59.000Z

363

An analysis of residential energy consumption and expenditures by minority households by home type and housing vintage  

SciTech Connect

In this paper a descriptive analysis of the relationship between energy consumption, patterns of energy use, and housing stock variables is presented. The purpose of the analysis is to uncover evidence of variations in energy consumption and expenditures, and patterns of energy use between majority households (defines as households with neither a black nor Hispanic head of household), black households (defined as households with a black head of household), and Hispanic households (defined as households with a Hispanic head of household) between 1980 (time of the first DOE/EIA Residential Energy Consumption Survey, 1982a) and 1987 (time of the last DOE/EIA Residential Energy Consumption Survey, 1989a). The analysis is three-dimensional: energy consumption and expenditures are presented by time (1980 to 1987), housing vintage, and housing type. A comparative analysis of changes in energy variables for the three population groups -- majority, black, and Hispanic -- within and between specific housing stock categories is presented.

Poyer, D.A.

1992-06-01T23:59:59.000Z

364

Ultra-Deepwater Advisory Committee Members | Department of Energy  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Advisory Committee Members Petroleum Reserves International Cooperation Natural Gas Regulation Advisory Committees 2011-2013 Ultra-Deepwater Advisory Committee Members Dr....

365

Albemarle Electric Member Corp | Open Energy Information  

Open Energy Info (EERE)

Albemarle Electric Member Corp Albemarle Electric Member Corp Place North Carolina Utility Id 240 Utility Location Yes Ownership C NERC Location SERC NERC SERC Yes Activity Distribution Yes References EIA Form EIA-861 Final Data File for 2010 - File1_a[1] LinkedIn Connections CrunchBase Profile No CrunchBase profile. Create one now! This article is a stub. You can help OpenEI by expanding it. Utility Rate Schedules Grid-background.png Athletic Field Lighting Lighting Irrigation TOD Industrial Large General Service Industrial Large General TOD Industrial Medium General Service Industrial Medium General Service - kWhs charge only Industrial Medium General TOD Industrial Outdoor Security Lighting - 100 watt HPS - Pendant Lighting Outdoor Security Lighting - 1000 watt MH - Flood Lighting Outdoor Security Lighting - 150 watt HPS - Ornamental Cobra Lighting

366

Washington Elec Member Corp | Open Energy Information  

Open Energy Info (EERE)

Washington Elec Member Corp Washington Elec Member Corp Place Georgia Utility Id 20146 Utility Location Yes Ownership C NERC Location SERC NERC SERC Yes ISO Other Yes Activity Distribution Yes References EIA Form EIA-861 Final Data File for 2010 - File1_a[1] LinkedIn Connections CrunchBase Profile No CrunchBase profile. Create one now! This article is a stub. You can help OpenEI by expanding it. Utility Rate Schedules Grid-background.png 1,000 Watt HPS Cobra Lighting 1,000 Watt HPS Flood Lighting 1,000 Watt MH Flood Lighting 100 Watt HPS Lighting 175 Watt MV 250 Watt HPS Lighting 250 Watt HPS Cobra Head Lighting 250 Watt HPS Flood Lighting 400 Watt HPS Cobra Head Lighting 400 Watt HPS Flood Lighting Rate-01 (RS) Residential Rate-02 (GSND) Commercial Rate-07 (GSD) Commercial Rate-08 (GS) Primary

367

Jackson Electric Member Corp | Open Energy Information  

Open Energy Info (EERE)

Member Corp Member Corp Place Georgia Utility Id 9601 Utility Location Yes Ownership C NERC Location SERC NERC SERC Yes ISO Other Yes Activity Distribution Yes References EIA Form EIA-861 Final Data File for 2010 - File1_a[1] Energy Information Administration Form 826[2] LinkedIn Connections CrunchBase Profile No CrunchBase profile. Create one now! This article is a stub. You can help OpenEI by expanding it. Utility Rate Schedules Grid-background.png AEA-06 Residential Energy Advantage Service Residential Commercial General Service All Electric Three Phase Commercial Commercial General Service Three Phase Commercial Commercial General Service Time-of-Use* Commercial Commercial Green Power Rider Fixed Size Blocks Commercial Commercial Green Power Rider Percentage Use Commercial Green Power Rider-Percentage Use* Commercial

368

Piedmont Electric Member Corp | Open Energy Information  

Open Energy Info (EERE)

Piedmont Electric Member Corp Piedmont Electric Member Corp Place North Carolina Utility Id 15023 Utility Location Yes Ownership C NERC Location SERC NERC SERC Yes Activity Distribution Yes References EIA Form EIA-861 Final Data File for 2010 - File1_a[1] LinkedIn Connections CrunchBase Profile No CrunchBase profile. Create one now! This article is a stub. You can help OpenEI by expanding it. Utility Rate Schedules Grid-background.png COOPERATIVE-OWNED AND MAINTAINED METERED OUTDOOR LIGHTING SERVICE Lighting GENERAL SERVICE Commercial GENERAL SERVICE-TIME-OF-DAY Commercial LARGE POWER SERVICE-LP Industrial LARGE POWER TIME OF DAY- PLANTATION PIPE LINE-LP-PPL-TOD. Industrial LARGE POWER-TIME-OF-DAY(LP-TOD) Industrial MEDIUM RENEWABLE GENERATION NET METERING RIDER(MRG-NM) NC GREENPOWER PROGRAM -1 Commercial

369

Sumter Electric Member Corp | Open Energy Information  

Open Energy Info (EERE)

Sumter Electric Member Corp Sumter Electric Member Corp Place Georgia Utility Id 18305 Utility Location Yes Ownership C NERC Location SERC NERC SERC Yes Activity Distribution Yes References EIA Form EIA-861 Final Data File for 2010 - File1_a[1] LinkedIn Connections CrunchBase Profile No CrunchBase profile. Create one now! This article is a stub. You can help OpenEI by expanding it. Utility Rate Schedules Grid-background.png Athletic Field Lighting Service Lighting Athletic Field Lighting Service* Commercial Cotton Gin Time-of-Use Service Commercial Cotton Gin Time-of-Use Service* Commercial General Service Commercial Irrigation Time-of-Use Service Commercial Irrigation Time-of-Use Service* Commercial Large Power Service Industrial Large Power Time-of-Use Service Industrial Large Power Time-of-Use Service* Industrial

370

Halifax Electric Member Corp | Open Energy Information  

Open Energy Info (EERE)

Halifax Electric Member Corp Halifax Electric Member Corp Place North Carolina Utility Id 7978 Utility Location Yes Ownership C NERC SERC Yes Activity Distribution Yes References EIA Form EIA-861 Final Data File for 2010 - File1_a[1] LinkedIn Connections CrunchBase Profile No CrunchBase profile. Create one now! This article is a stub. You can help OpenEI by expanding it. Utility Rate Schedules Grid-background.png MEDIUM GENERAL SERVICE Commercial NC GREENPOWER PROGRAM voluntary RENEWABLE ENERGY GENERATION-Solar RENEWABLE ENERGY GENERATION-Wind RESIDENTIAL SERVICE Residential SECURITY LIGHTING 100-watt high-pressure sodium Lighting SECURITY LIGHTING 140-watt LED Light Commercial SECURITY LIGHTING 175-watt mercury vapor Lighting SECURITY LIGHTING 175-watt metal halide Lighting SECURITY LIGHTING 250-watt high-pressure sodium Lighting

371

Midwest Electric Member Corp | Open Energy Information  

Open Energy Info (EERE)

Midwest Electric Member Corp Midwest Electric Member Corp Place Nebraska Utility Id 12539 Utility Location Yes Ownership C NERC Location MRO NERC MRO Yes Activity Distribution Yes References EIA Form EIA-861 Final Data File for 2010 - File1_a[1] Energy Information Administration Form 826[2] LinkedIn Connections CrunchBase Profile No CrunchBase profile. Create one now! This article is a stub. You can help OpenEI by expanding it. Utility Rate Schedules Grid-background.png Irrigation(All-Energy and Demand Charges) Commercial Large Power Industrial Rural Residential Residential School & Churches - Single Phase School & Churches - Three Phase Security Lights Metered Lighting Security Lights Unmetered Lighting Single-Phase Commercial - Monthly Commercial Single-Phase Dryer Service Commercial

372

Jefferson Electric Member Corp | Open Energy Information  

Open Energy Info (EERE)

Electric Member Corp Electric Member Corp Place Georgia Utility Id 9689 Utility Location Yes Ownership C NERC Location SERC NERC SERC Yes Activity Distribution Yes References EIA Form EIA-861 Final Data File for 2010 - File1_a[1] LinkedIn Connections CrunchBase Profile No CrunchBase profile. Create one now! This article is a stub. You can help OpenEI by expanding it. Utility Rate Schedules Grid-background.png GENERAL SERVICE SCHEDULE B Commercial HIGH LOAD FACTOR SERVICE SCHEDULE HLF-13-R Commercial PREPAID RESIDENTIAL SERVICE SCHEDULE APP Residential RESIDENTIAL SERVICE SCHEDULE A Residential SCHEDULE ARP-1 ALLOCATED RESOURCE PRICING Commercial SCHEDULE ARP-2 McE ALLOCATED RESOURCE PRICING Commercial SCHEDULE C TOU TIME-OF-USE SERVICE Commercial SCHEDULE I-8 - greater than 30 kVA (Single Phase - Time-of-Use Energy

373

Rutherford Elec Member Corp | Open Energy Information  

Open Energy Info (EERE)

Elec Member Corp Elec Member Corp Place North Carolina Utility Id 16496 Utility Location Yes Ownership C NERC Location SERC NERC SERC Yes Activity Transmission Yes Activity Distribution Yes References EIA Form EIA-861 Final Data File for 2010 - File1_a[1] Energy Information Administration Form 826[2] LinkedIn Connections CrunchBase Profile No CrunchBase profile. Create one now! This article is a stub. You can help OpenEI by expanding it. Utility Rate Schedules Grid-background.png Residential Service Average Rates Residential: $0.0984/kWh Commercial: $0.0988/kWh Industrial: $0.0667/kWh The following table contains monthly sales and revenue data for Rutherford Elec Member Corp (North Carolina). Month RES REV (THOUSAND $) RES SALES (MWH) RES CONS COM REV (THOUSAND $) COM SALES (MWH) COM CONS IND_REV (THOUSAND $) IND SALES (MWH) IND CONS OTH REV (THOUSAND $) OTH SALES (MWH) OTH CONS TOT REV (THOUSAND $) TOT SALES (MWH) TOT CONS

374

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

Annual Energy Outlook 2012 (EIA)

View History: Annual Download Data (XLS File) Texas Natural Gas Number of Industrial Consumers (Number of Elements) Texas Natural Gas Number of Industrial Consumers (Number of...

375

Household Vehicles Energy Use: Latest Data & Trends  

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

C C : Q U A L I T Y O F T H E D ATA APPENDIX C A P P E N D I X C QUALITY OF THE DATA INTRODUCTION This section discusses several issues relating to the quality of the National Household Travel Survey (NHTS) data and to the interpretation of conclusions based on these data. In particular, the focus of our discussion is on the quality of specific data items, such as the fuel economy and fuel type, that were imputed to the NHTS via a cold-decking imputation procedure. This imputation procedure used vehicle-level information from the NHTSA Corporate Average Fuel Economy files for model year's 1978 through 2001. It is nearly impossible to quantify directly the quality of this imputation procedure because NHTS does not collect the necessary fuel economy information for comparison. At best, we have indirect evidence on the quality of our

376

Load Component Database of Household Appliances and Small Office Equipment  

Science Conference Proceedings (OSTI)

This paper discusses the development of a load component database for household appliances and office equipment. To develop more accurate load models at both transmission and distribution level, a better understanding on the individual behaviors of home appliances and office equipment under power system voltage and frequency variations becomes more and more critical. Bonneville Power Administration (BPA) has begun a series of voltage and frequency tests against home appliances and office equipments since 2005. Since 2006, Researchers at Pacific Northwest National Laboratory has collaborated with BPA personnel and developed a load component database based on these appliance testing results to facilitate the load model validation work for the Western Electricity Coordinating Council (WECC). In this paper, the testing procedure and testing results are first presented. The load model parameters are then derived and grouped. Recommendations are given for aggregating the individual appliance models to feeder level, the models of which are used for distribution and transmission level studies.

Lu, Ning; Xie, YuLong; Huang, Zhenyu; Puyleart, Francis; Yang, Steve

2008-07-24T23:59:59.000Z

377

A Comprehensive Model for Evaluation of Carbon Footprint and Greenhouse Gages Emission in Household Biogas Plants  

Science Conference Proceedings (OSTI)

Based on Life Cycle Assessment and other related methods, this paper introduced a comprehensive model for the evaluation of the carbon footprint and greenhouse gases emission in household biogas plants including nearly all the processes of the household ... Keywords: Biogas Plant, Carbon Footprint, Life Cycle, Greenhouse Gas

Jie Zhou; Shubiao Wu; Wanqin Zhang; Changle Pang; Baozhi Wang; Renjie Dong; Li Chen

2012-07-01T23:59:59.000Z

378

Users and households appliances: design suggestions for a better, sustainable interaction  

Science Conference Proceedings (OSTI)

The Human Machine Interaction has a big role in the user approach with households appliances. During the main phase (the use one), users are called to manage energy choices, often without available efficient information regarding the best behavior they ... Keywords: energy saving, households appliances, interaction design, interfaces, sustainability

Anna Zandanel

2011-09-01T23:59:59.000Z

379

Residential energy use and conservation actions: analysis of disaggregate household data  

Science Conference Proceedings (OSTI)

The Energy Information Administration recently published data they collected from the National Interim Energy Consumption Survey (NIECS). NIECS includes detailed information on 4081 individual households: demographic characteristics, energy-related features of the structure, heating equipment and appliances therein, recent conservation actions taken by the household, and fuel consumption and cost for the April 1978 to March 1979 one-year period. This data set provides a new and valuable resource for analysis. The NIECS data on household energy consumption - total energy use, electricity use, and use of the primary space heating fuel, are summarized and analyzed. The regression equations constructed explain roughly half the variation in energy use among households. These equations contain ten or fewer independent variables, the most important of which are fuel price, year house was built, floor area, and heating degree days. Regression equations were developed that estimate the energy saving achieved by each household based on their recent retrofit actions. These equations predict 20 to 40% of the variation among households. Total annual energy use is the most important determinant of retrofit energy saving; other significant variables include age of household head, household income, year house was built, housing tenure, and proxies for the cost of heating and air conditioning the house.

Hirst, E.; Goeltz, R.; Carney, J.

1981-03-01T23:59:59.000Z

380

Export support of renewable energy industries. Task number 1, deliverable number 3. Final report  

DOE Green Energy (OSTI)

The United States Export Council for Renewable Energy (US/ECRE), a consortium of six industry associations, promotes the interests of the renewable energy and energy efficiency member companies which provide goods and services in biomass, geothermal, hydropower, passive solar, photovoltaics, solar thermal, wind, wood energy, and energy efficiency technologies. US/ECRE`s mission is to catalyze export markets for renewable energy and energy efficiency technologies worldwide. Under this grant, US/ECRE has conducted a number of in-house activities, as well as to manage activities by member trade associations, affiliate organizations and non-member contractors and consultants. The purpose of this document is to report on task coordination and effectiveness.

NONE

1998-01-14T23:59:59.000Z

Note: This page contains sample records for the topic "household members number" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


381

Export support of renewable energy industries, grant number 1, deliverable number 3. Final report  

DOE Green Energy (OSTI)

The United States Export Council for Renewable Energy (US/ECRE), a consortium of six industry associations, promotes the interests of the renewable energy and energy efficiency member companies which provide goods and services in biomass, geothermal, hydropower, passive solar, photovoltaics, solar thermal, wind, wood energy, and energy efficiency technologies. US/ECRE`s mission is to catalyze export markets for renewable energy and energy efficiency technologies worldwide. Under this grant, US/ECRE has conducted a number of in-house activities, as well as to manage activities by member trade associations, affiliate organizations and non-member contractors and consultants. The purpose of this document is to report on grant coordination and effectiveness.

NONE

1998-01-14T23:59:59.000Z

382

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

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Everyone in Your Household to Save Energy? Everyone in Your Household to Save Energy? How Do You Encourage Everyone in Your Household to Save Energy? June 18, 2009 - 5:25pm Addthis 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 yourself-just seem to need some extra reminders to take simple energy-saving steps. How do you encourage everyone in your household to save energy? Each Thursday, you have the chance to share your thoughts on a topic related to energy efficiency or renewable energy for consumers. Please comment with your answers, and also feel free to respond to other comments. Addthis Related Articles How Have You Helped Someone Else Save Energy?

383

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

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Do You Encourage Everyone in Your Household to Save Energy? Do You Encourage Everyone in Your Household to Save Energy? How Do You Encourage Everyone in Your Household to Save Energy? June 18, 2009 - 5:25pm Addthis 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 yourself-just seem to need some extra reminders to take simple energy-saving steps. How do you encourage everyone in your household to save energy? Each Thursday, you have the chance to share your thoughts on a topic related to energy efficiency or renewable energy for consumers. Please comment with your answers, and also feel free to respond to other comments. Addthis Related Articles How Have You Helped Someone Else Save Energy?

384

Household energy handbook: an interim guide and reference manual. World Bank technical paper  

SciTech Connect

A standard framework for measuring and assessing technical information on the household energy sector in developing countries is needed. The handbook is intended as a first step toward creating such a framework. Chapter I discusses energy terms and principles underlying the energy units, definitions, and calculations presented in the following chapters. Chapter II describes household consumption patterns and their relationship to income, location, and household-size variables. Chapter III evaluates energy end uses and the technologies that provide cooking, lighting, refrigeration, and space-heating services. Chapter IV examines household energy resources and supplies, focusing on traditional biomass fuels. Finally, Chapter V demonstrates simple assessment methods and presents case studies to illustrate how household energy data can be used in different types of assessments.

Leach, G.; Gowen, M.

1987-01-01T23:59:59.000Z

385

Vehicle Technologies Office: Information for Members of Media  

NLE Websites -- All DOE Office Websites (Extended Search)

Information for Members Information for Members of Media to someone by E-mail Share Vehicle Technologies Office: Information for Members of Media on Facebook Tweet about Vehicle Technologies Office: Information for Members of Media on Twitter Bookmark Vehicle Technologies Office: Information for Members of Media on Google Bookmark Vehicle Technologies Office: Information for Members of Media on Delicious Rank Vehicle Technologies Office: Information for Members of Media on Digg Find More places to share Vehicle Technologies Office: Information for Members of Media on AddThis.com... Vehicle Technologies News Blog Newsletters Information for Media Subscribe to News Updates Information for Members of Media The Vehicle Technologies Office provides press releases, photos, videos, and contact information for members of the media to cover Vehicle

386

Number | Department of Energy  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Number More Documents & Publications Analysis of Open Office of Inspector General Recommendations, OAS-L-08-07 Policy and International Affairs (WFP) Open Government Plan 2.0...

387

Expected Frobenius numbers  

E-Print Network (OSTI)

We show that for large instances the order of magnitude of the expected Frobenius number is (up to a constant depending only on the dimension) given by its lower bound.

Aliev, Iskander; Hinrichs, Aicke

2009-01-01T23:59:59.000Z

388

DOE/ID-Number  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

2/308 2/308 FCRD-FCT-2012-000232 Categorization of Used Nuclear Fuel Inventory in Support of a Comprehensive National Nuclear Fuel Cycle Strategy December 2012 Prepared by John C. Wagner, ORNL Joshua L. Peterson, ORNL Don E. Mueller, ORNL Jess C. Gehin, ORNL Andrew Worrall, ORNL Temitope Taiwo, ANL Mark Nutt, ANL Mark A. Williamson, ANL Mike Todosow, BNL Roald Wigeland, INL William G. Halsey, LLNL Ronald P. Omberg, PNNL Peter N. Swift, SNL Joe T. Carter, SRNL DOCUMENT AVAILABILITY Reports produced after January 1, 1996, are generally available free via the U.S. Department of Energy (DOE) Information Bridge. Web site http://www.osti.gov/bridge Reports produced before January 1, 1996, may be purchased by members of the public from the

389

Report number codes  

SciTech Connect

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.

Nelson, R.N. (ed.)

1985-05-01T23:59:59.000Z

390

Household Projection and Its Application to Health/Long-Term Care Expenditures in Japan Using INAHSIM-II  

Science Conference Proceedings (OSTI)

Using a microsimulation model named Integrated Analytical Model for Household Simulation (INAHSIM), the author conducted a household projection in Japan for the period of 2010â??2050. INAHSIM-II specifically means that the initial population is ... Keywords: dynamic micro simulation, health expenditure, household projection, initial population, long-term care expenditure, transition probabilities

Tetsuo Fukawa

2011-02-01T23:59:59.000Z

391

Number | Open Energy Information  

Open Energy Info (EERE)

Number Number Jump to: navigation, search Properties of type "Number" Showing 200 properties using this type. (previous 200) (next 200) A Property:AvgAnnlGrossOpCpcty Property:AvgTempGeoFluidIntoPlant Property:AvgWellDepth B Property:Building/FloorAreaChurchesChapels Property:Building/FloorAreaGroceryShops Property:Building/FloorAreaHealthServices24hr Property:Building/FloorAreaHealthServicesDaytime Property:Building/FloorAreaHeatedGarages Property:Building/FloorAreaHotels Property:Building/FloorAreaMiscellaneous Property:Building/FloorAreaOffices Property:Building/FloorAreaOtherRetail Property:Building/FloorAreaResidential Property:Building/FloorAreaRestaurants Property:Building/FloorAreaSchoolsChildDayCare Property:Building/FloorAreaShops Property:Building/FloorAreaSportCenters

392

Ocmulgee Electric Member Corp | Open Energy Information  

Open Energy Info (EERE)

Ocmulgee Electric Member Corp Ocmulgee Electric Member Corp Place Georgia Utility Id 13934 Utility Location Yes Ownership C NERC Location SERC NERC SERC Yes Activity Distribution Yes References EIA Form EIA-861 Final Data File for 2010 - File1_a[1] LinkedIn Connections CrunchBase Profile No CrunchBase profile. Create one now! This article is a stub. You can help OpenEI by expanding it. Utility Rate Schedules Grid-background.png 1000W Type -'MH-Flood', kWh-500 Lighting 100W Type -'Decorative HPS', kWh-40 Lighting 100W Type -'HPS-Open', kWh-40 Lighting 100W Type -'HPS-Open', kWh-Metered Lighting 150W Type -'HPS-Sidelite', kWh-60 Lighting 175W Type -'MV-Open', kWh-70 Lighting 250W Type -'HPS-Flood', kWh-100 Lighting 250W Type -'HPS-Flood', kWh-Metered Lighting 250W Type -'HPS-Open/Cobra', kWh-100 Lighting

393

Multiple capillary biochemical analyzer with barrier member  

DOE Patents (OSTI)

A multiple capillary biochemical analyzer for sequencing DNA and performing other analyses, in which a set of capillaries extends from wells in a microtiter plate into a cuvette. In the cuvette the capillaries are held on fixed closely spaced centers by passing through a sandwich construction having a pair of metal shims which squeeze between them a rubber gasket, forming a leak proof seal for an interior chamber in which the capillary ends are positioned. Sheath fluid enters the chamber and entrains filament sample streams from the capillaries. The filament sample streams, and sheath fluid, flow through aligned holes in a barrier member spaced close to the capillary ends, into a collection chamber having a lower glass window. The filament streams are illuminated above the barrier member by a laser, causing them to fluoresce. The fluorescence is viewed end-on by a CCD camera chip located below the glass window. The arrangement ensures an equal optical path length from all fluorescing spots to the CCD chip and also blocks scattered fluorescence illumination, providing more uniform results and an improved signal to noise ratio.

Dovichi, Norman J. (Edmonton, CA); Zhang, Jian Z. (Edmonton, CA)

1996-01-01T23:59:59.000Z

394

Multiple capillary biochemical analyzer with barrier member  

DOE Patents (OSTI)

A multiple capillary biochemical analyzer is disclosed for sequencing DNA and performing other analyses, in which a set of capillaries extends from wells in a microtiter plate into a cuvette. In the cuvette the capillaries are held on fixed closely spaced centers by passing through a sandwich construction having a pair of metal shims which squeeze between them a rubber gasket, forming a leak proof seal for an interior chamber in which the capillary ends are positioned. Sheath fluid enters the chamber and entrains filament sample streams from the capillaries. The filament sample streams, and sheath fluid, flow through aligned holes in a barrier member spaced close to the capillary ends, into a collection chamber having a lower glass window. The filament streams are illuminated above the barrier member by a laser, causing them to fluoresce. The fluorescence is viewed end-on by a CCD camera chip located below the glass window. The arrangement ensures an equal optical path length from all fluorescing spots to the CCD chip and also blocks scattered fluorescence illumination, providing more uniform results and an improved signal-to-noise ratio. 12 figs.

Dovichi, N.J.; Zhang, J.Z.

1996-10-22T23:59:59.000Z

395

Using Fractional Numbers of . . .  

E-Print Network (OSTI)

One of the design parameters in closed queueing networks is Np, the number of customers of class p. It has been assumed that Np must be an integer. However, integer choices will usually not achieve the target throughput for each class simultaneously. We use Mean Value Analysis with the Schweitzer-Bard approximation and nonlinear programming to determine the value of Np needed to achieve the production targets exactly, although the values of Np may be fractional. We interpret these values to represent the average number of customers of each class in the network. We implement a control rule to achieve these averages and verify our approach through simulation.

Rajan Suri; Rahul Shinde; Mary Vernon

2005-01-01T23:59:59.000Z

396

CHEMICAL SAFETY Emergency Numbers  

E-Print Network (OSTI)

- 1 - CHEMICAL SAFETY MANUAL 2010 #12;- 2 - Emergency Numbers UNBC Prince George Campus Security Prince George Campus Chemstores 6472 Chemical Safety 6472 Radiation Safety 5530 Biological Safety 5530 use, storage, handling, waste and emergency management of chemicals on the University of Northern

Bolch, Tobias

397

Disjunctive Rado numbers  

Science Conference Proceedings (OSTI)

If L1 and L2 are linear equations, then the disjunctive Rado number of the set {L1, L2} is the least integer n, provided that it exists, such that for every 2-coloring of ... Keywords: Rado, Ramsey, Schur, disjunctive

Brenda Johnson; Daniel Schaal

2005-11-01T23:59:59.000Z

398

A number of organizations,  

E-Print Network (OSTI)

buying power to purchase green power. The city of Chicago has formed an alliance with 47 other local installed solar electric systems on a number of the city's buildings, including the Chicago Center for Green to competition, the city of Chicago and 47 other local government agencies formed the Local Government Power

399

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

Gasoline and Diesel Fuel Update (EIA)

View History: Annual Download Data (XLS File) South Dakota Natural Gas Number of Commercial Consumers (Number of Elements) South Dakota Natural Gas Number of Commercial Consumers...

400

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

Annual Energy Outlook 2012 (EIA)

View History: Annual Download Data (XLS File) South Dakota Natural Gas Number of Residential Consumers (Number of Elements) South Dakota Natural Gas Number of Residential...

Note: This page contains sample records for the topic "household members number" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


401

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

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

View History: Annual Download Data (XLS File) South Dakota Natural Gas Number of Industrial Consumers (Number of Elements) South Dakota Natural Gas Number of Industrial Consumers...

402

Estimating household fuel oil/kerosine, natural gas, and LPG prices by census region  

SciTech Connect

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.

Poyer, D.A.; Teotia, A.P.S.

1994-08-01T23:59:59.000Z

403

A Reliable Natural Language Interface to Household Appliances  

E-Print Network (OSTI)

“I have always wished that my computer would be as easy to use as my telephone. My wish has come true. I no longer know how to use my telephone.” – Bjarne Stroustrop (originator of C++) As household appliances grow in complexity and sophistication, they become harder and harder to use, particularly because of their tiny display screens and limited keyboards. This paper describes a strategy for building natural language interfaces to appliances that circumvents these problems. Our approach leverages decades of research on planning and natural language interfaces to databases by reducing the appliance problem to the database problem; the reduction provably maintains desirable properties of the database interface. The paper goes on to describe the implementation and evaluation of the EXACT interface to appliances, which is based on this reduction. EXACT maps each English user request to an SQL query, which is transformed to create a PDDL goal, and uses the Blackbox planner [13] to map the planning problem to a sequence of appliance commands that satisfy the original request. Both theoretical arguments and experimental evaluation show that EXACT is highly reliable.

Alexander Yates

2003-01-01T23:59:59.000Z

404

Laboratory Testing of Demand-Response Enabled Household Appliances  

SciTech Connect

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.

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

2013-10-01T23:59:59.000Z

405

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

DOE Green Energy (OSTI)

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

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

1999-07-16T23:59:59.000Z

406

The New Element Berkelium (Atomic Number 97)  

DOE R&D Accomplishments (OSTI)

An isotope of the element with atomic number 97 has been discovered as a product of the helium-ion bombardment of americium. The name berkelium, symbol Bk, is proposed for element 97. The chemical separation of element 97 from the target material and other reaction products was made by combinations of precipitation and ion exchange adsorption methods making use of its anticipated (III) and (IV) oxidation states and its position as a member of the actinide transition series. The distinctive chemical properties made use of in its separation and the equally distinctive decay properties of the particular isotope constitute the principal evidence for the new element.

Seaborg, G. T.; Thompson, S. G.; Ghiorso, A.

1950-04-26T23:59:59.000Z

407

Walton Electric Member Corp | Open Energy Information  

Open Energy Info (EERE)

Jump to: navigation, search Jump to: navigation, search Name Walton Electric Member Corp Place Georgia Utility Id 20065 Utility Location Yes Ownership C NERC Location SERC NERC SERC Yes Activity Distribution Yes References EIA Form EIA-861 Final Data File for 2010 - File1_a[1] LinkedIn Connections CrunchBase Profile No CrunchBase profile. Create one now! This article is a stub. You can help OpenEI by expanding it. Utility Rate Schedules Grid-background.png 14' Aluminum Lighting 20' F/G Lighting 30' F/G Lighting 30-6 Wood Lighting Cobrahead- HPS 100 Watt Bronze (UG) Lighting Cobrahead- HPS 100 Watt Gray Lighting Cobrahead- HPS 100 Watt Gray (UG) Lighting Cobrahead- HPS 150 Bronze Watt (UG) Lighting Cobrahead- HPS 150 Watt Gray Lighting Cobrahead- HPS 150 Watt Gray (UG) Lighting Cobrahead- HPS 250 Watt Bronze (UG) Lighting

408

Cumberland Elec Member Corp | Open Energy Information  

Open Energy Info (EERE)

(Redirected from CEMC) (Redirected from CEMC) Jump to: navigation, search Name Cumberland Elec Member Corp Place Tennessee Utility Id 4624 Utility Location Yes Ownership C NERC Location SERC NERC SERC Yes Activity Distribution Yes References EIA Form EIA-861 Final Data File for 2010 - File1_a[1] Energy Information Administration Form 826[2] LinkedIn Connections CrunchBase Profile No CrunchBase profile. Create one now! This article is a stub. You can help OpenEI by expanding it. Utility Rate Schedules Grid-background.png Commercial GSA 3 Commercial Commercial GSA 1 Commercial Commercial GSA 2 Commercial Facilities Rental (46-161 kV) Commercial Facilities Rental (less than 46 kV) Commercial Generation Partner 1 - Energy Credit Commercial Generation Partner 1 - Other Renewable Premium Commercial

409

ELECTRICAL DISTRICT NUMBER EIGHT  

NLE Websites -- All DOE Office Websites (Extended Search)

ELECTRICAL DISTRICT NUMBER EIGHT ELECTRICAL DISTRICT NUMBER EIGHT Board of Directors Reply to: Ronald Rayner C. W. Adams James D. Downing, P.E. Chairman Billy Hickman 66768 Hwy 60 Brian Turner Marvin John P.O. Box 99 Vice-Chairman Jason Pierce Salome, AZ 85348 Denton Ross Jerry Rovey Secretary James N. Warkomski ED8@HARCUVARCO.COM John Utz Gary Wood PHONE:(928) 859-3647 Treasurer FAX: (928) 859-3145 Sent via e-mail Mr. Darrick Moe, Regional Manager Western Area Power Administration Desert Southwest Region P. O. Box 6457 Phoenix, AZ 85005-6457 moe@wapa.gov; dswpwrmrk@wapa.gov Re: ED5-Palo Verde Hub Project Dear Mr. Moe, In response to the request for comments issued at the October 6 Parker-Davis Project customer th meeting, and in conjunction with comments previously submitted by the Southwest Public Power

410

Preventive Action Number:  

NLE Websites -- All DOE Office Websites (Extended Search)

8 Preventive Action Report Planning Worksheet 11_0414 1 of 3 8 Preventive Action Report Planning Worksheet 11_0414 1 of 3 EOTA - Business Form Document Title: Preventive Action Report Planning Worksheet Document Number: F-018 Rev 11_0414 Document Owner: Elizabeth Sousa Backup Owner: Melissa Otero Approver(s): Melissa Otero Parent Document: P-008, Corrective/Preventive Action Notify of Changes: EOTA Employees Referenced Document(s): N/A F-018 Preventive Action Report Planning Worksheet 11_0414 2 of 3 Revision History: Rev. Description of Change 08_0613 Initial Release 09_0924 Worksheet modified to reflect External Audit recommendation for identification of "Cause for Potential Nonconformance". Minor editing changes. 11_0414 Added Preventive Action Number block to match Q-Pulse

411

Preventive Action Number:  

NLE Websites -- All DOE Office Websites (Extended Search)

7 Corrective Action Report Planning Worksheet 11_0414 1 of 3 7 Corrective Action Report Planning Worksheet 11_0414 1 of 3 EOTA - Business Form Document Title: Corrective Action Report Planning Worksheet Document Number: F-017 Rev 11_0414 Document Owner: Elizabeth Sousa Backup Owner: Melissa Otero Approver(s): Melissa Otero Parent Document: P-008, Corrective/Preventive Action Notify of Changes: EOTA Employees Referenced Document(s): N/A F-017 Corrective Action Report Planning Worksheet 11_0414 2 of 3 Revision History: Rev. Description of Change 08_0613 Initial Release 11_0414 Added problem statement to first block. F-017 Corrective Action Report Planning Worksheet 11_0414 3 of 3 Corrective Action Report Planning Worksheet Corrective Action Number: Source: Details/Problem Statement: Raised By: Raised Date: Target Date:

412

BERA Board Members, Brookhaven Employees Recreation Association (BERA)  

NLE Websites -- All DOE Office Websites (Extended Search)

Board Members Board Members as of May 2012 BERA Administrative Manual - May 2012 (pdf) Name Term Phone Bldg. E-Mail Fax Susan Wells - President 2014 7427 1005S swells@bnl.gov 2151 Terry Maugeri - Vice President 2016 5980 400B maugeri@bnl.gov - John Addessi - Executive Board Member 2016 7268 911A addessi@bnl.gov 5954 Cris Caccavale - Executive Board Member 2016 5341 400A caccavale@bnl.gov 2940 Christine Herbst - Executive Board Member 2016 7101 902 herbst@bnl.gov 3395 Ruth Comas - Executive Board Member 2014 3545 488 comas@bnl.gov 2069 Augie Hoffmann - Executive Board Member 2014 3884 510A ahoff@bnl.gov 5078 Linda Barrett - Executive Board Member 2014 5165 400D lbarrett@bnl.gov 6243 Affiliates Jeffrey Swenson - Staff Services Manager 2525 179B swenson@bnl.gov 2940

413

Global Nuclear Energy Partnership Members Convene in Jordan For...  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Members Convene in Jordan For Second Steering Group Meeting Global Nuclear Energy Partnership Members Convene in Jordan For Second Steering Group Meeting May 15, 2008 - 12:00pm...

414

Seasonality, precautionary savings and health uncertainty: Evidence from farm households in Central Kenya  

E-Print Network (OSTI)

on rural households in Kenya." World Development 32(1):91-Second report on poverty in Kenya. Incidence and depth ofPlanning. Government of Kenya. —. 2004. "Kenya Demographic

Ndirangu, Lydia; Burger, Kees; Moll, Hank A.J.; Kuyvenhoven, Arie

2009-01-01T23:59:59.000Z

415

Trends in the Use of Natural Gas in U.S. Households, 1987 to 2001  

U.S. Energy Information Administration (EIA)

used, the RECS is ideal as a data source so as to reveal the underlying factors behind the trends in energy demand--and in this paper, household natural gas demand.

416

The Design and Implementation of a Corporate Householding Knowledge Processor to Improve Data Quality  

E-Print Network (OSTI)

Advances in Corporate Householding are needed to address certain categories of data quality problems caused by data misinterpretation. In this paper, we first summarize some of these data quality problems and our more ...

Madnick, Stuart

2004-02-06T23:59:59.000Z

417

Household water treatment and safe storage options for Northern Region Ghana : consumer preference and relative cost  

E-Print Network (OSTI)

A range of household water treatment and safe storage (HWTS) products are available in Northern Region Ghana which have the potential to significantly improve local drinking water quality. However, to date, the region has ...

Green, Vanessa (Vanessa Layton)

2008-01-01T23:59:59.000Z

418

Facts about FEMA Household Disaster Aid: Examining the 2008 Floods and Tornadoes in Missouri  

Science Conference Proceedings (OSTI)

Very little empirical work has been done on disaster aid in the United States. This paper examines postdisaster grants to households from the Federal Emergency Management Agency in the state of Missouri in 2008, when the state experienced flooding,...

Carolyn Kousky

2013-10-01T23:59:59.000Z

419

Table CE1-10c. Total Energy Consumption in U.S. Households by ...  

U.S. Energy Information Administration (EIA)

Table CE1-10c. Total Energy Consumption in U.S. Households by Midwest Census Region, 2001 RSE Column Factor: Total U.S. Midwest Census Region RSE Row

420

10Tips to Spend Less on Household Goods Spend about $20 on a battery  

E-Print Network (OSTI)

10Tips to Spend Less on Household Goods Spend about $20 on a battery recharger. Over time, replace your used batteries with the kind you can use over and over again. 6 You can reuse plastic bags you get

Tullos, Desiree

Note: This page contains sample records for the topic "household members number" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


421

Table CE4-7c. Water-Heating Energy Consumption in U.S. Households ...  

U.S. Energy Information Administration (EIA)

Table CE4-7c. Water-Heating Energy Consumption in U.S. Households by Four Most Populated States, 1997 RSE Column Factor: Total U.S. Four Most Populated States

422

Residential energy consumption survey. Consumption patterns of household vehicles, supplement: January 1981-September 1981  

Science Conference Proceedings (OSTI)

Information on the fuel consumption characteristics on household vehicles in the 48 contiguous States and the District of Columbia is presented by monthly statistics of fuel consumption, expenditures, miles per gallon, and miles driven.

Not Available

1983-02-01T23:59:59.000Z

423

Table CE1-4c. Total Energy Consumption in U.S. Households by Type ...  

U.S. Energy Information Administration (EIA)

Table CE1-4c. Total Energy Consumption in U.S. Households by Type of Housing Unit, 1997 ... where the end use is electric air-conditioning, ...

424

Table CE1-1c. Total Energy Consumption in U.S. Households by ...  

U.S. Energy Information Administration (EIA)

Table CE1-1c. Total Energy Consumption in U.S. Households by Climate Zone, 2001 RSE Column Factor: Total Climate Zone1 RSE Row Factors Fewer than 2,000 CDD and --

425

Calculating economic indexes per household and censal section from official Spanish databases  

Science Conference Proceedings (OSTI)

In the competitive environments, in which all sorts of organisations move it is of utmost importance to have information about clients. Public databases offer information about households and families. However, the non-crossed and non-georeferenced format ...

Sonia Frutos; Ernestina Menasalvas; Cesar Montes; Javier Segovia

2003-12-01T23:59:59.000Z

426

California Immigrant Households and Public Assistance Participation in the 1990s - Detailed Research Findings  

E-Print Network (OSTI)

Seon Lee. 1999. “Transitions from AFDC to Child Welfare inHouseholds Receiving AFDC/TANF by Recency of Entry, 1993?Earnings for Those Receiving AFDC/TANF, Table 7. Proportion

2002-01-01T23:59:59.000Z

427

Table CE2-7e. Space-Heating Energy Expenditures in U.S. Households ...  

U.S. Energy Information Administration (EIA)

Table CE2-7e. Space-Heating Energy Expenditures in U.S. Households by Four Most Populated States, 2001 RSE Column Factor: Total U.S. Four Most Populated States

428

Households to pay more than expected to stay warm this winter  

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

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...

429

Monitoring effective use of household water treatment and safe storage technologies in Ethiopia and Ghana  

E-Print Network (OSTI)

Household water treatment and storage (HWTS) technologies dissemination is beginning to scale-up to reach the almost 900 million people without access to an improved water supply (WHO/UNICEF/JMP, 2008). Without well-informed ...

Stevenson, Matthew M

2009-01-01T23:59:59.000Z

430

Testing Electric Vehicle Demand in `Hybrid Households' Using a Reflexive Survey  

E-Print Network (OSTI)

or 180 mile hybrid electric vehicle. Natural gas vehicles (1994) Demand for Electric Vehicles in Hybrid Households: A nof Electric, Hybrid and Other Alternative Vehicles. A r t h

Kurani, Kenneth; Turrentine, Thomas; Sperling, Daniel

1996-01-01T23:59:59.000Z

431

Table CE5-2c. Appliances Energy Consumption in U.S. Households by ...  

U.S. Energy Information Administration (EIA)

Table CE5-2c. Appliances1 Energy Consumption in U.S. Households by Year of Construction, 2001 RSE Column Factor: Total Year of Construction RSE Row

432

Monetary Policy and Household Mobility: The Effects of Mortgage Interest Rats.  

E-Print Network (OSTI)

Homeowner Mobility and Mortgage Interest Rates: New Evidencenew mortgages. Table 2 Basic Hazard Models of Household Mobility (mobility decisions are related to increases in family size, the existence of a new

Quigley, John M.

2005-01-01T23:59:59.000Z

433

Distributional Impacts of Carbon Pricing: A General Equilibrium Approach with Micro-Data for Households  

E-Print Network (OSTI)

Many policies to limit greenhouse gas emissions have at their core efforts to put a price on carbon emissions. Carbon pricing impacts households both by raising the cost of carbon intensive products and by changing factor ...

Rausch, Sebastian

434

Table 4. LPG Consumption and Expeditures in U.S. Households by End ...  

U.S. Energy Information Administration (EIA)

Table 4. LPG Consumption and Expeditures in U.S. Households by End Uses and Census Region, 2001 RSE Column Factor: Total U.S. Census Region RSE Row

435

Two perspectives on household electricity use - Today in Energy ...  

U.S. Energy Information Administration (EIA)

... power plants, fuel use, stocks ... Unlike natural gas consumption in the ... and an ever-growing number of home entertainment and rechargeable devices.

436

Finite Neutrosophic Complex Numbers  

E-Print Network (OSTI)

In this book for the first time the authors introduce the notion of real neutrosophic complex numbers. Further the new notion of finite complex modulo integers is defined. For every $C(Z_n)$ the complex modulo integer $i_F$ is such that $2F_i = n - 1$. Several algebraic structures on $C(Z_n)$ are introduced and studied. Further the notion of complex neutrosophic modulo integers is introduced. Vector spaces and linear algebras are constructed using these neutrosophic complex modulo integers.

W. B. Vasantha Kandasamy; Florentin Smarandache

2011-11-01T23:59:59.000Z

437

Overview of CFC replacement issues for household refrigeration  

Science Conference Proceedings (OSTI)

In 1974, the famous ozone depletion theory of Rowland and Molina claimed that chlorofluorocarbons (CFCs) diffuse into the stratosphere where they are broken down by photolysis to release chlorine atoms that catalytically destroy ozone. Although the understanding of the science is still imperfect, there is little doubt that CFCs play a major role in the Antarctic ozone hole phenomenon and the decline in ozone observed in the rest of the world. Another issue that has become increasingly important is the potential of CFCs to change the earth's temperature and to modify the climate. While the main impact in global warming is made by increased concentrations of carbon dioxide, CFCs and other trace gases also contribute to this effect. In an effort to respond to the global environmental threat, a CFC protocol was adopted during a diplomatic conference in Montreal. This document, known as the Montreal Protocol, was ratified in 1988 and put into effect on January 1, 1989. In accordance with Article 6 of the Montreal Protocol, the countries that signed the agreement shall periodically assess the control measures provided for in the Protocol. As part of that assessment process, household refrigeration was investigated to determine the status of CFC-12 replacements. The conclusion was that much progress has been made towards finding a suitable replacement. Compressors designed for HFC-134a have efficiencies comparable to those for CFC-12 and acceptable reliability tests have been obtained with ester lubricants. In addition, other replacements such as R-152a and refrigerant mixtures exist, but will require more study. Cycle options, such as the Stirling cycle, may be viable, but are further out in the future. The impact of new refrigerants is expected to result in elimination of CFC-12 consumption in developed countries by 1997 and in developing countries by 2005.

Vineyard, E.A. (Oak Ridge National Lab., TN (United States)); Roke, L. (Fisher and Paykel, Auckland (New Zealand)); Hallett, F. (Frigidaire, Washington, DC (United States))

1991-01-01T23:59:59.000Z

438

Overview of CFC replacement issues for household refrigeration  

Science Conference Proceedings (OSTI)

In 1974, the famous ozone depletion theory of Rowland and Molina claimed that chlorofluorocarbons (CFCs) diffuse into the stratosphere where they are broken down by photolysis to release chlorine atoms that catalytically destroy ozone. Although the understanding of the science is still imperfect, there is little doubt that CFCs play a major role in the Antarctic ozone hole phenomenon and the decline in ozone observed in the rest of the world. Another issue that has become increasingly important is the potential of CFCs to change the earth`s temperature and to modify the climate. While the main impact in global warming is made by increased concentrations of carbon dioxide, CFCs and other trace gases also contribute to this effect. In an effort to respond to the global environmental threat, a CFC protocol was adopted during a diplomatic conference in Montreal. This document, known as the Montreal Protocol, was ratified in 1988 and put into effect on January 1, 1989. In accordance with Article 6 of the Montreal Protocol, the countries that signed the agreement shall periodically assess the control measures provided for in the Protocol. As part of that assessment process, household refrigeration was investigated to determine the status of CFC-12 replacements. The conclusion was that much progress has been made towards finding a suitable replacement. Compressors designed for HFC-134a have efficiencies comparable to those for CFC-12 and acceptable reliability tests have been obtained with ester lubricants. In addition, other replacements such as R-152a and refrigerant mixtures exist, but will require more study. Cycle options, such as the Stirling cycle, may be viable, but are further out in the future. The impact of new refrigerants is expected to result in elimination of CFC-12 consumption in developed countries by 1997 and in developing countries by 2005.

Vineyard, E.A. [Oak Ridge National Lab., TN (United States); Roke, L. [Fisher and Paykel, Auckland (New Zealand); Hallett, F. [Frigidaire, Washington, DC (United States)

1991-12-31T23:59:59.000Z

439

Construction Project Number  

NLE Websites -- All DOE Office Websites (Extended Search)

North Execution - (2009 - 2011) North Execution - (2009 - 2011) Construction Project Number 2009 2010 2011 Project Description ANMLPL 0001C 76,675.32 - - Animas-Laplata circuit breaker and power rights CRGRFL 0001C - - 7,177.09 Craig Rifle Bay and transfer bay upgrade to 2000 amps; / Convert CRG RFL to 345 kV out of Bears Ear Sub FGE 0019C - - 39,207.86 Replace 69/25kV transformer KX2A at Flaming Gorge FGE 0020C - - 52,097.12 Flaming Gorge: Replace failed KW2A transformer HDN 0069C 16,638.52 208,893.46 3,704,578.33 Replace failed transformer with KZ1A 250 MVA 230/138kv

440

KPA Activity Number  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

supports CMM-SW Level 2 supports CMM-SW Level 2 Mapping of the DOE Systems Engineering Methodology to the Software Engineering Institute (SEI) Software Capability Maturity Model (CMM- SW) level 2. Date: September 2002 Page 1 KPA Activity Number KPA Activity SEM Section SME Work Product SQSE Web Site http://cio.doe.gov/sqse REQUIREMENTS MANAGEMENT RM-1 The software engineering group reviews the allocated requirements before they are incorporated in the software project. Chapter 3.0 * Develop High-Level Project Requirements Chapter 4.0 * Establish Functional Baseline * Project Plan * Requirements Specification Document * Requirements Management awareness * Defining Project Requirements RM-2 The software engineering group uses the allocated requirements as the basis for

Note: This page contains sample records for the topic "household members number" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


441

Previous Members | U.S. DOE Office of Science (SC)  

Office of Science (SC) Website

Previous ASCAC Members Previous ASCAC Members Advanced Scientific Computing Advisory Committee (ASCAC) ASCAC Home Meetings Members ASCAC Members Bio Previous ASCAC Members Charges/Reports Charter .pdf file (38KB) ASCR Committees of Visitors ASCR Home Members Previous ASCAC Members Print Text Size: A A A RSS Feeds FeedbackShare Page Dr. F. Ronald Bailey Computer Sciences Corp. 591 Branciforte Ridge Santa Cruz, CA 95065 Dr. Horst D. Simon Director, Computational Research Division Lawrence Berkeley Laboratory 1 Cyclotron Road, MS 50B-4230 Berkeley, CA 94720 Mr. Gordon Bell Microsoft Research 835 Market St. Suite 700 San Francisco, CA 94103 Dr. Larry L. Smarr Calit2/UCSD 9500 Gilman Drive, MC 0436 La Jolla, CA 92093-0436 Marjory S. Blumenthal Office of the Provost Georgetown University 3700 O Street, NW, ICC 650

442

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

Gasoline and Diesel Fuel Update (EIA)

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...

443

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...

444

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

Annual Energy Outlook 2012 (EIA)

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...

445

Illinois Natural Gas Number of Industrial Consumers (Number of...  

Annual Energy Outlook 2012 (EIA)

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...

446

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...

447

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...

448

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

Annual Energy Outlook 2012 (EIA)

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...

449

California Natural Gas Number of Industrial Consumers (Number...  

Gasoline and Diesel Fuel Update (EIA)

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...

450

California Natural Gas Number of Commercial Consumers (Number...  

Gasoline and Diesel Fuel Update (EIA)

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...

451

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

Gasoline and Diesel Fuel Update (EIA)

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...

452

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...

453

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...

454

Colorado Natural Gas Number of Industrial Consumers (Number of...  

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...

455

Colorado Natural Gas Number of Residential Consumers (Number...  

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...

456

Colorado Natural Gas Number of Commercial Consumers (Number of...  

Gasoline and Diesel Fuel Update (EIA)

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...

457

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

Gasoline and Diesel Fuel Update (EIA)

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...

458

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

Annual Energy Outlook 2012 (EIA)

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...

459

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

Annual Energy Outlook 2012 (EIA)

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...

460

Michigan Natural Gas Number of Residential Consumers (Number...  

Gasoline and Diesel Fuel Update (EIA)

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...

Note: This page contains sample records for the topic "household members number" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


461

Michigan Natural Gas Number of Industrial Consumers (Number of...  

Annual Energy Outlook 2012 (EIA)

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...

462

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

Annual Energy Outlook 2012 (EIA)

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...

463

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

Annual Energy Outlook 2012 (EIA)

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...

464

Idaho Natural Gas Number of Residential Consumers (Number of...  

Annual Energy Outlook 2012 (EIA)

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...

465

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

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

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...

466

Hawaii Natural Gas Number of Residential Consumers (Number of...  

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...

467

Kentucky Natural Gas Number of Residential Consumers (Number...  

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...

468

Tennessee Natural Gas Number of Residential Consumers (Number...  

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...

469

Maryland Natural Gas Number of Residential Consumers (Number...  

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...

470

Louisiana Natural Gas Number of Residential Consumers (Number...  

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...

471

Alabama Natural Gas Number of Residential Consumers (Number of...  

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...

472

Oklahoma Natural Gas Number of Residential Consumers (Number...  

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...

473

Alaska Natural Gas Number of Residential Consumers (Number of...  

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...

474

Kansas Natural Gas Number of Residential Consumers (Number of...  

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...

475

Illinois Natural Gas Number of Residential Consumers (Number...  

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...

476

Maine Natural Gas Number of Residential Consumers (Number of...  

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...

477

Florida Natural Gas Number of Residential Consumers (Number of...  

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...

478

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...

479

Georgia Natural Gas Number of Residential Consumers (Number of...  

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...

480

Arkansas Natural Gas Number of Residential Consumers (Number...  

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...

Note: This page contains sample records for the topic "household members number" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


481

Missouri Natural Gas Number of Residential Consumers (Number...  

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...

482

Montana Natural Gas Number of Residential Consumers (Number of...  

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...

483

Nevada Natural Gas Number of Residential Consumers (Number of...  

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...

484

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

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

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...

485

Arizona Natural Gas Number of Residential Consumers (Number of...  

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...

486

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

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

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...

487

Nebraska Natural Gas Number of Residential Consumers (Number...  

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...

488

Minnesota Natural Gas Number of Residential Consumers (Number...  

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...

489

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

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

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...

490

Delaware Natural Gas Number of Residential Consumers (Number...  

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...

491

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

Annual Energy Outlook 2012 (EIA)

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...

492

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

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

(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 Year-7 Year-8 Year-9...

493

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

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

(Number of Elements) New Mexico 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...

494

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

Gasoline and Diesel Fuel Update (EIA)

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...

495

Texas Natural Gas Number of Residential Consumers (Number of...  

Annual Energy Outlook 2012 (EIA)

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...

496

Greenhouse gas emissions from home composting of organic household waste  

Science Conference Proceedings (OSTI)

The emission of greenhouse gases (GHGs) is a potential environmental disadvantage of home composting. Because of a lack of reliable GHG emission data, a comprehensive experimental home composting system was set up. The system consisted of six composting units, and a static flux chamber method was used to measure and quantify the GHG emissions for one year composting of organic household waste (OHW). The average OHW input in the six composting units was 2.6-3.5 kg week{sup -1} and the temperature inside the composting units was in all cases only a few degrees (2-10 {sup o}C) higher than the ambient temperature. The emissions of methane (CH{sub 4}) and nitrous oxide (N{sub 2}O) were quantified as 0.4-4.2 kg CH{sub 4} Mg{sup -1} input wet waste (ww) and 0.30-0.55 kg N{sub 2}O Mg{sup -1} ww, depending on the mixing frequency. This corresponds to emission factors (EFs) (including only CH{sub 4} and N{sub 2}O emissions) of 100-239 kg CO{sub 2}-eq. Mg{sup -1} ww. Composting units exposed to weekly mixing had the highest EFs, whereas the units with no mixing during the entire year had the lowest emissions. In addition to the higher emission from the frequently mixed units, there was also an instant release of CH{sub 4} during mixing which was estimated to 8-12% of the total CH{sub 4} emissions. Experiments with higher loads of OHW (up to 20 kg every fortnight) entailed a higher emission and significantly increased overall EFs (in kg substance per Mg{sup -1} ww). However, the temperature development did not change significantly. The GHG emissions (in kg CO{sub 2}-eq. Mg{sup -1} ww) from home composting of OHW were found to be in the same order of magnitude as for centralised composting plants.

Andersen, J.K., E-mail: jka@env.dtu.d [Department of Environmental Engineering, Technical University of Denmark, DK-2800, Kongens Lyngby (Denmark); Boldrin, A.; Christensen, T.H.; Scheutz, C. [Department of Environmental Engineering, Technical University of Denmark, DK-2800, Kongens Lyngby (Denmark)

2010-12-15T23:59:59.000Z

497

The impact of the Persian Gulf crisis on household energy consumption and expenditure patterns  

Science Conference Proceedings (OSTI)

The Iraqi invasion of the Kingdom of Kuwait on August 2, 1990, and the subsequent war between Iraq and an international alliance led by the United States triggered first immediate and then fluctuating world petroleum prices. Increases in petroleum prices and in U.S. petroleum imports resulted in increases in the petroleum prices paid by U.S. residential, commercial, and industrial consumers. The result was an immediate price shock that reverberated throughout the U.S. economy. The differential impact of these price increases and fluctuations on poor and minority households raised immediate, significant, and potentially long-term research, policy, and management issues for a variety of federal, state, and local government agencies, including the U.S. Department of Energy (DOE). Among these issues are (1) the measurement of variations in the impact of petroleum price changes on poor, nonpoor, minority, and majority households; (2) how to use the existing policy resources and policy innovation to mitigate regressive impacts of petroleum price increases on lower-income households; and (3) how to pursue such policy mitigation through government agencies severely circumscribed by tax and expenditure limitations. Few models attempt to assess household energy consumption and energy expenditure under various alternative price scenarios and with respect to the inclusion of differential household choices correlated with such variables as race, ethnicity, income, and geographic location. This paper provides a preliminary analysis of the nature and extent of potential impacts of petroleum price changes attributable to the Persian Gulf War and its aftermath on majority, black, and Hispanic households and on overlapping poor and nonpoor households. At the time this was written, the Persian Gulf War had concluded with Iraq`s total surrender to all of the resolutions and demands of the United Nations and United States.

Henderson, L. [Univ. of Baltimore, MD (United States); Poyer, D.; Teotia, A. [Argonne National Lab., IL (United States)

1994-09-01T23:59:59.000Z

499

Improving Demographic Components of Integrated Assessment Models: The Effect of Changes in Population Composition by Household Characteristics  

SciTech Connect

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.

Brian C. O'Neill

2006-08-09T23:59:59.000Z

500

"Table HC15.3 Household Characteristics by Four Most Populated States, 2005"  

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

3 Household Characteristics by Four Most Populated States, 2005" 3 Household Characteristics by Four Most Populated States, 2005" " Million U.S. Housing Units" ,"Housing Units (millions)","Four Most Populated States" "Household Characteristics",,"New York","Florida","Texas","California" "Total",111.1,7.1,7,8,12.1 "Household Size" "1 Person",30,1.8,1.9,2,3.2 "2 Persons",34.8,2.2,2.3,2.4,3.2 "3 Persons",18.4,1.1,1.3,1.2,1.8 "4 Persons",15.9,1,0.9,1,2.3 "5 Persons",7.9,0.6,0.6,0.9,0.9 "6 or More Persons",4.1,0.4,"Q",0.5,0.7 "2005 Annual Household Income Category" "Less than $9,999",9.9,0.8,0.7,0.9,1 "$10,000 to $14,999",8.5,0.8,0.4,0.6,0.7