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1

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

2

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

3

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 ...

4

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

5

,"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

6

,"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

7

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

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

2 Average Square Footage of South Homes, by Housing Characteristics, 2009" 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

8

,"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"

9

,"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

10

,"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

11

,"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

12

,"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

13

,"Selected National Average Natural Gas Prices"  

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

Selected National Average Natural Gas Prices" Selected National Average Natural Gas Prices" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Average Natural Gas Prices",11,"Monthly","11/2013","1/15/1973" ,"Data 2","Annual Average Natural Gas Prices",11,"Annual",2012,"6/30/1922" ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","ngm03vmall.xls" ,"Available from Web Page:","http://www.eia.gov/oil_gas/natural_gas/data_publications/natural_gas_monthly/ngm.html"

14

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

15

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

U.S. Energy Information Administration (EIA)

1 Test data was received from the U.S. Department of Transportation, National Highway and Traffic Safety Administration for model year’s 1978 through 2001.

16

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 ...

17

Average utilization of the nation's natural gas combined-cycle ...  

U.S. Energy Information Administration (EIA)

... (purple line) and 2010 (red line) average capacity factors for natural gas plant operations between 10 p.m. and 6 a.m. rose from 26% to 32%.

18

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 ď‚· 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. ď‚· 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

19

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 ď‚· 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. ď‚· 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

20

EIA Average Energy Consumption 2005  

U.S. Energy Information Administration (EIA)

Table US8. Average Consumption by Fuels Used, 2005 Physical Units per Household Fuels Used (physical units of consumption per household using the fuel)

Note: This page contains sample records for the topic "national average household" 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

The National Ignition Facility National Ignition Campaign Short Pulse Lasers High-Average-Power Laser  

E-Print Network (OSTI)

-Average-Power Laser NIF-1005-11471 07BEW/dj P9765 Agenda #12;P9516NIF-0805-11197 01EIM/dj Stockpile Stewardship #12;P9504NIF-0404-08345r2 27EIM/ld Basic Science and Cosmology #12;NIF-0702-05346rIFSA Fusion Energy Campaign and point design NIF-0305-10564 23MLS/cld P8719 The NIF Laser User Optics Physics Operations

22

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

23

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

24

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

25

National Household Travel Survey (NHTS): Travel Trends, Analysis and Data Tools  

E-Print Network (OSTI)

of the nation's transportation system to meet current demands and accommodate future demands; to assess of alternative transportation investment programs; and to assess the energy-use and air-quality impacts Analysis Data, Statistical Analysis Geo-Spatial Information Tools Defense Transportation Energy Policy

26

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.

27

Characterizing Walk Trips in communities by Using Data from 2009 National Household Travel Survey, American Community Survey, and Other Sources  

SciTech Connect

Non-motorized travel (i.e. walking and bicycling) are of increasing interest to the transportation profession, especially in context with energy consumption, reducing vehicular congestion, urban development patterns, and promotion of healthier life styles. This research project aimed to identify factors impacting the amount of travel for both walk and bike trips at the Census block group or tract level, using several public and private data sources. The key survey of travel behavior is the 2009 National Household Travel Survey (NHTS) which had over 87,000 walk trips for persons 16 and over, and over 6000 bike trips for persons 16 and over. The NHTS, in conjunction with the Census Bureau s American Community Survey, street density measures using Census Bureau TIGER, WalkScore , Nielsen Claritas employment estimates, and several other sources were used for this study. Stepwise Logistic Regression modeling techniques as well as Discriminant Analysis were applied using the integrated data set. While the models performed reasonably well for walk trips, travel by bike was abandoned due to sparseness of data. This paper discusses data sources utilized and modeling processes conducted under this study. It also presents a summary of findings and addresses data challenges and lesson-learned from this research effort.

Hwang, Ho-Ling [ORNL; Reuscher, Tim [Macrosys; Wilson, Daniel W [ORNL; Murakami, Elaine [FHWA USDOT

2013-01-01T23:59:59.000Z

28

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

29

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.

30

2 The Financial and Economic Crises: Implications for Consumer Finance and for Households in Michigan  

E-Print Network (OSTI)

IPPSR and MSUE at Michigan State University for financial support. This paper was partially written while a Visiting Scholar at the National Poverty Center at the University of Michigan, and its Michigan is an epicenter of the recent economic and financial crises. Median personal income was 8 percent above the national average at the beginning of the decade and was 8 percent below the national average by the end of it. Between 2008 and 2009, personal income fell for the first time since 1958. Rates of unemployment and foreclosure activity remain high and above the national average. Indeed, the Michigan economy is changing in dramatic and important ways, but there is little information on household responses to this changing environment. How are Michigan households responding to economic and financial shocks? Are they smoothing income, consumption, or both? What mechanisms are they using to achieve these outcomes? On which factors does the degree of adjustment depend? Using data collected from recent household surveys,

Lisa D. Cook; Lisa D. Cook; Ann Marie Schneider; Lauren Meunier; Lisa D. Cook

2010-01-01T23:59:59.000Z

31

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

Science Conference Proceedings (OSTI)

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.

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

2005-05-31T23:59:59.000Z

32

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

33

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...

34

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

35

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.

36

Table AP5. Average Consumption for Home Appliances and Lighting by ...  

U.S. Energy Information Administration (EIA)

Table AP5. Average Consumption for Home Appliances and Lighting by Fuels Used, 2005 Physical Units per Household U.S. Households (millions) Fuels Used

37

The household energy transition in India and China Shonali Pachauri a,, Leiwen Jiang b  

E-Print Network (OSTI)

household surveys. The two countries differ sharply in several respects. Residential energy consumption of national primary energy consumption statistics shows clearly that both India and China are countries energy consumption remains low in both countries, particularly in India. Average energy use is low

38

Insolation data manual: long-term monthly averages of solar radiation, temperature, degree-days and global anti K/sub T/ for 248 national weather service stations  

DOE Green Energy (OSTI)

Monthly averaged data is presented which describes the availability of solar radiation at 248 National Weather Service stations. Monthly and annual average daily insolation and temperature values have been computed from a base of 24 to 25 years of data. Average daily maximum, minimum, and monthly temperatures are provided for most locations in both Celsius and Fahrenheit. Heating and cooling degree-days were computed relative to a base of 18.3/sup 0/C (65/sup 0/F). For each station, global anti K/sub T/ (cloudiness index) were calculated on a monthly and annual basis. (MHR)

Knapp, C L; Stoffel, T L; Whitaker, S D

1980-10-01T23:59:59.000Z

39

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

40

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 ...

Note: This page contains sample records for the topic "national average household" 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

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

42

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

43

Table AP7. Average Expenditures for Home Appliances and Lighting ...  

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.

44

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

45

Vehicle Technologies Office: Fact #615: March 22, 2010 Average Vehicle Trip  

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

5: March 22, 5: March 22, 2010 Average Vehicle Trip Length to someone by E-mail Share Vehicle Technologies Office: Fact #615: March 22, 2010 Average Vehicle Trip Length on Facebook Tweet about Vehicle Technologies Office: Fact #615: March 22, 2010 Average Vehicle Trip Length on Twitter Bookmark Vehicle Technologies Office: Fact #615: March 22, 2010 Average Vehicle Trip Length on Google Bookmark Vehicle Technologies Office: Fact #615: March 22, 2010 Average Vehicle Trip Length on Delicious Rank Vehicle Technologies Office: Fact #615: March 22, 2010 Average Vehicle Trip Length on Digg Find More places to share Vehicle Technologies Office: Fact #615: March 22, 2010 Average Vehicle Trip Length on AddThis.com... Fact #615: March 22, 2010 Average Vehicle Trip Length According to the latest National Household Travel Survey, the average trip

46

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...

47

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

48

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

49

national average for heating oil  

U.S. Energy Information Administration (EIA)

Propane Missouri North Dakota X South Dakota TOTAL List of States included on Winter Heating Fuels Survey (SHOPP) Release date: January 2012 22.00 24.00. Author: MRO

50

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

51

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

52

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

53

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

54

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

55

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...

56

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

57

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

58

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

59

average | OpenEI  

Open Energy Info (EERE)

average average Dataset Summary Description This dataset is part of a larger internal dataset at the National Renewable Energy Laboratory (NREL) that explores various characteristics of large solar electric (both PV and CSP) facilities around the United States. This dataset focuses on the land use characteristics for solar facilities that are either under construction or currently in operation. Source Land-Use Requirements for Solar Power Plants in the United States Date Released June 25th, 2013 (7 months ago) Date Updated Unknown Keywords acres area average concentrating solar power csp Density electric hectares km2 land land requirements land use land-use mean photovoltaic photovoltaics PV solar statistics Data application/vnd.openxmlformats-officedocument.spreadsheetml.sheet icon Master Solar Land Use Spreadsheet (xlsx, 1.5 MiB)

60

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) ...

Note: This page contains sample records for the topic "national average household" 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

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.

62

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.

63

Table AC6. Average Consumption for Air-Conditioning by Equipment ...  

U.S. Energy Information Administration (EIA)

Central System 5 Table AC6. Average Consumption for Air-Conditioning by Equipment Type, 2005 Million British Thermal Units (Btu) per Household

64

Table AC7. Average Expenditures for Air-Conditioning by Equipment ...  

U.S. Energy Information Administration (EIA)

Central System 5 Table AC7. Average Expenditures for Air-Conditioning by Equipment Type, 2005 Dollars per Household Type of Air-Conditioning Equipment

65

Table SH9. Average Expenditures for Space Heating by Main Space ...  

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.

66

Table AC9. Average Cooled Floorspace by Equipment Type, 2005 Air ...  

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.

67

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

68

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

69

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

70

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

71

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 *...

72

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

73

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

74

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

75

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

76

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

77

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....

78

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...

79

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...

80

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

Note: This page contains sample records for the topic "national average household" 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 Vehicles Energy Consumption  

Reports and Publications (EIA)

This report provides newly available national and regional data and analyzes the nation's energy use by light-duty vehicles. This release represents the analytical component of the report, with a data component having been released in early 2005.

Mark Schipper

2005-11-30T23:59:59.000Z

82

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

83

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

84

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

85

AVERAGE SHIFTED HISTOGRAM  

Science Conference Proceedings (OSTI)

... LET YPPF = XCDF LET XPPF = YCDF. Default: None Synonyms: ASH is a synonym for the AVERAGE SHIFTED HISTOGRAM command. ...

2010-12-06T23:59:59.000Z

86

Average Commercial Price  

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

Residential Price Average Commercial Price Period: Monthly Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes...

87

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

88

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

89

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

90

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

91

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:...

92

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

93

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...

94

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...

95

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

96

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

97

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...

98

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

99

Average U.S. residential summer 2013 electric bill expected to be ...  

U.S. Energy Information Administration (EIA)

The average U.S. household electric bill for June through August is expected to total $395, down 2.5% from last summer and the cheapest in four years.

100

Table WH6. Average Consumption for Water Heating by Major Fuels ...  

U.S. Energy Information Administration (EIA)

Major Fuels Used 5 (physical units of consumption per household using the fuel as a water heating source) Electricity (kWh) Table WH6. Average Consumption for Water ...

Note: This page contains sample records for the topic "national average household" 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

"Table HC1.1.3 Housing Unit Characteristics by Average Floorspace...  

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

areas, determined according to the 30-year average (1971-2000) of the annual heating and cooling degree-days. A household is assigned to a climate zone according to the 30-year...

102

Table HC1.1.2 Housing Unit Characteristics by Average Floorspace...  

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

areas, determined according to the 30-year average (1971-2000) of the annual heating and cooling degree-days. A household is assigned to a climate zone according to the 30-year...

103

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

104

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 ....................................................

105

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

106

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 ......................................

107

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 ........................

108

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

109

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

110

National Household Travel Survey (2009)

The 2009 National...  

Open Energy Info (EERE)

level, etc.); and

  • vehicle attributes (make, model, model year, amount of miles driven in a year).
      • These data are collected for:

        ...

  • 111

    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

    112

    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

    113

    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...

    114

    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

    115

    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

    116

    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

    117

    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

    118

    DOE Average Results  

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

    DOE DOE Average Results FY 12 DOE Target FY 12 Customer Perspective: Customer Satisfaction: -Timeliness 92 88 -Quality 94 92 Effective Service Partnership: -Extent of Customer Satisfaction with the responsiveness, etc. 90 92 Internal Business Perspective: Acquisition Excellence: -Extent to which internal quality control systems are effective 90 88 Most Effective Use of Contracting Approaches to Maximize Efficiency and Cost Effectiveness: Use of Competition: -% of total $'s obligated on competitive acquisitions >$3000 (Agency Level Only) 94 85 -% of acquisition actions competed for actions > $3000 (Agency Level Only) 65 68 Performance Based Acquisition: - % PBA actions relative to total eligible new acquisition actions (applicable to new actions > $25K) 82

    119

    Census Division Number of Average Monthly Average Retail Price...  

    Gasoline and Diesel Fuel Update (EIA)

    Average Monthly Average Retail Price Average Monthly Bill State Consumers Consumption (kWh) (Cents per Kilowatthour) (Dollar and cents) New England 34,271 67,907 12.55 8,520.25...

    120

    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

    Note: This page contains sample records for the topic "national average household" 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

    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

    122

    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 ................................................................

    123

    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 ................................................................

    124

    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

    125

    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 .....................................

    126

    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

    127

    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 .......................

    128

    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

    129

    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

    130

    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

    131

    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 .....................................

    132

    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

    133

    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

    134

    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

    135

    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

    136

    Average wholesale electric power prices rose in 2010 - Today in ...  

    U.S. Energy Information Administration (EIA)

    Average wholesale electric power prices rose in 2010, due to higher national natural gas prices and increased demand for electricity, particularly in the Eastern ...

    137

    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

    138

    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

    139

    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

    140

    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 ...

    Note: This page contains sample records for the topic "national average household" 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

    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

    142

    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

    143

    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

    144

    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 ...

    145

    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 ..................................................

    146

    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

    147

    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

    148

    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

    149

    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 ..................................................

    150

    average air temperature | OpenEI  

    Open Energy Info (EERE)

    average air temperature average air temperature Dataset Summary Description (Abstract): Air Temperature at 10 m Above The Surface Of The Earth (deg C)NASA Surface meteorology and Solar Energy (SSE) Release 6.0 Data Set (Nov 2007)22-year Monthly & Annual Average (July 1983 - June 2005)Parameter: Air Temperature at 10 m Above The Surface Of The Earth (deg C)Internet: http://eosweb.larc.nasa.gov/sse/Note 1: SSE Methodology & Accuracy sections onlineNote 2: Lat/Lon values indicate the lower left corner of a 1x1 degree region. Negative values are south and west; Source U.S. National Aeronautics and Space Administration (NASA), Surface meteorology and Solar Energy (SSE) Date Released March 31st, 2009 (5 years ago) Date Updated April 01st, 2009 (5 years ago) Keywords average air temperature

    151

    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

    152

    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

    153

    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.

    154

    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

    155

    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 .....................................................

    156

    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

    157

    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 .................................................

    158

    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

    159

    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 .................................................

    160

    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 .....................................................

    Note: This page contains sample records for the topic "national average household" 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

    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

    162

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

    Science Conference Proceedings (OSTI)

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

    Figueroa, M.J.; Sathaye, J.

    1993-08-01T23:59:59.000Z

    163

    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

    164

    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

    165

    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

    166

    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

    167

    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

    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

    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

    170

    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

    171

    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

    172

    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

    173

    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

    174

    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 ...................................

    175

    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 ......................................

    176

    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 ...................................

    177

    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

    178

    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 ......................................

    179

    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 ...................................

    180

    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

    Note: This page contains sample records for the topic "national average household" 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

    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

    182

    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

    183

    Grid-Averaged Surface Fluxes  

    Science Conference Proceedings (OSTI)

    This study examines the inadequacies of formulations for surface fluxes for use in numerical models of atmospheric flow. The difficulty is that numerical models imply spatial averaging over each grid area. Existing formulations am based on the ...

    L. Mahrt

    1987-08-01T23:59:59.000Z

    184

    High average power pockels cell  

    DOE Patents (OSTI)

    A high average power pockels cell is disclosed which reduces the effect of thermally induced strains in high average power laser technology. The pockels cell includes an elongated, substantially rectangular crystalline structure formed from a KDP-type material to eliminate shear strains. The X- and Y-axes are oriented substantially perpendicular to the edges of the crystal cross-section and to the C-axis direction of propagation to eliminate shear strains.

    Daly, Thomas P. (Pleasanton, CA)

    1991-01-01T23:59:59.000Z

    185

    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

    186

    Food practices as situated action: exploring and designing for everyday food practices with households  

    Science Conference Proceedings (OSTI)

    Household food practices are complex. Many people are unable to effectively respond to challenges in their food environment to maintain diets considered to be in line with national and international standards for healthy eating. We argue that recognizing ... Keywords: everyday practice, food, health, situated action

    Rob Comber; Jettie Hoonhout; Aart van Halteren; Paula Moynihan; Patrick Olivier

    2013-04-01T23:59:59.000Z

    187

    Core Measure Average KTR Results  

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

    Measure Measure Average KTR Results FY 12 Target FY 12 DOE M&O CONTRACTOR (KTR) BSC RESULTS FY 2012 Customer Perspective and level of communication provided by the procurement office 95 92 Internal Business Perspective: Assessment (%) of the degree to which the purchasing system is in compliance with stakeholder requirements 97 Local Goals % Delivery on-time (includes JIT, excludes Purchase Cards) 88 84 % of total dollars obligated, on actions > $150K , that were awarded using effective competition 73 Local Goals Rapid Purchasing Techniques: -% of transactions placed by users 77 Local Goals -% of transactions placed through electronic commerce 62 Local Goals Average Cycle Time: -Average cycle time for <= $150K 8 6 to 9 days

    188

    West Texas Intermediate Spot Average ............................  

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

    Crude Oil (dollars per barrel) Crude Oil (dollars per barrel) West Texas Intermediate Spot Average ............................ 102.88 93.42 92.24 87.96 94.34 94.10 105.84 96.30 95.67 95.33 95.67 93.33 94.12 97.64 95.00 Brent Spot Average ........................................................... 118.49 108.42 109.61 110.09 112.49 102.58 110.27 108.29 106.33 105.00 103.00 102.00 111.65 108.41 104.08 Imported Average .............................................................. 108.14 101.18 97.18 97.64 98.71 97.39 103.07 100.03 99.64 99.33 99.69 97.35 101.09 99.85 99.04 Refiner Average Acquisition Cost ...................................... 107.61 101.44 97.38 97.27 101.14 99.45 105.24 100.44 100.15 99.82 100.18 97.83 100.83 101.61 99.50 Liquid Fuels (cents per gallon) Refiner Prices for Resale Gasoline .........................................................................

    189

    ANALYSIS OF CEE HOUSEHOLD SURVEY NATIONAL AWARENESS OF ENERGY...  

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

    2011 to four percent in 2012 and the proportion informed by their lender increased from zero percent in 2011 to one percent in 2012. All other responses were statistically...

    190

    National Household Travel Survey (2009) | OpenEI  

    Open Energy Info (EERE)

    education level, etc.); and vehicle attributes (make, model, model year, amount of miles driven in a year). These data are collected for: all trips, all modes, all purposes,...

    191

    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

    192

    Table HC1.2.2 Living Space Characteristics by Average Floorspace  

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

    2 Living Space Characteristics by Average Floorspace, " 2 Living Space Characteristics by Average Floorspace, " " Per Housing Unit and Per Household Member, 2005" ,,"Average Square Feet" ," Housing Units (millions)" ,,"Per Housing Unit",,,"Per Household Member" "Living Space Characteristics",,"Total1","Heated","Cooled","Total1","Heated","Cooled" "Total",111.1,2033,1618,1031,791,630,401 "Total Floorspace (Square Feet)" "Fewer than 500",3.2,357,336,113,188,177,59 "500 to 999",23.8,733,667,308,343,312,144 "1,000 to 1,499",20.8,1157,1086,625,435,409,235 "1,500 to 1,999",15.4,1592,1441,906,595,539,339 "2,000 to 2,499",12.2,2052,1733,1072,765,646,400

    193

    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

    194

    Could a Common Household Fungus Reduce Oil Imports? | Department of Energy  

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

    Could a Common Household Fungus Reduce Oil Imports? Could a Common Household Fungus Reduce Oil Imports? Could a Common Household Fungus Reduce Oil Imports? June 21, 2011 - 11:37am Addthis A view of Aspergillus niger with the fungus’ DNA highlighted in green | Photo Courtesy of: PNNL. A view of Aspergillus niger with the fungus' DNA highlighted in green | Photo Courtesy of: PNNL. Ben Squires Analyst, Office of Energy Efficiency & Renewable Energy What does this mean for me? The Department's Pacific Northwest National Laboratory (PNNL) are working to harness the natural process that spoils fruits and vegetables as a way to make fuel and other petroleum substitutes from the parts of plants that we can't eat. The genetic bases of the behaviors and abilities of these two industrially relevant fungal strains will allow researchers to exploit

    195

    Could a Common Household Fungus Reduce Oil Imports? | Department of Energy  

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

    a Common Household Fungus Reduce Oil Imports? a Common Household Fungus Reduce Oil Imports? Could a Common Household Fungus Reduce Oil Imports? June 21, 2011 - 11:37am Addthis A view of Aspergillus niger with the fungus’ DNA highlighted in green | Photo Courtesy of: PNNL. A view of Aspergillus niger with the fungus' DNA highlighted in green | Photo Courtesy of: PNNL. Ben Squires Analyst, Office of Energy Efficiency & Renewable Energy What does this mean for me? The Department's Pacific Northwest National Laboratory (PNNL) are working to harness the natural process that spoils fruits and vegetables as a way to make fuel and other petroleum substitutes from the parts of plants that we can't eat. The genetic bases of the behaviors and abilities of these two industrially relevant fungal strains will allow researchers to exploit

    196

    Feed the Future Bangladesh: Baseline Integrated Household Survey | Data.gov  

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

    Feed the Future Bangladesh: Baseline Integrated Household Survey Feed the Future Bangladesh: Baseline Integrated Household Survey Agriculture Community Menu DATA APPS EVENTS DEVELOPER STATISTICS COLLABORATE ABOUT Agriculture You are here Data.gov » Communities » Agriculture » Data Feed the Future Bangladesh: Baseline Integrated Household Survey Dataset Summary Description The Bangladesh Integrated Household Survey dataset is a thorough assessment of current standard of food security in Bangladesh taken from 2011-2012. The dataset includes all baseline household surveys made under the USAID-led Feed the Future initiative, a collaborative effort that supports country-owned processes and plans for improving food security and promoting transparency, and within the Zones of Influence as outlined by the Feed the Future Bangladesh plan .The BIHS sample is statistically representative at the following levels: (a) nationally representative of rural Bangladesh; (b) representative of rural areas of each of the seven administrative divisions of the country; and, (c) representative of the Feed the Future (FTF) zone of influence.

    197

    HIGH AVERAGE POWER OPTICAL FEL AMPLIFIERS.  

    SciTech Connect

    Historically, the first demonstration of the optical FEL was in an amplifier configuration at Stanford University [l]. There were other notable instances of amplifying a seed laser, such as the LLNL PALADIN amplifier [2] and the BNL ATF High-Gain Harmonic Generation FEL [3]. However, for the most part FELs are operated as oscillators or self amplified spontaneous emission devices. Yet, in wavelength regimes where a conventional laser seed can be used, the FEL can be used as an amplifier. One promising application is for very high average power generation, for instance FEL's with average power of 100 kW or more. The high electron beam power, high brightness and high efficiency that can be achieved with photoinjectors and superconducting Energy Recovery Linacs (ERL) combine well with the high-gain FEL amplifier to produce unprecedented average power FELs. This combination has a number of advantages. In particular, we show that for a given FEL power, an FEL amplifier can introduce lower energy spread in the beam as compared to a traditional oscillator. This properly gives the ERL based FEL amplifier a great wall-plug to optical power efficiency advantage. The optics for an amplifier is simple and compact. In addition to the general features of the high average power FEL amplifier, we will look at a 100 kW class FEL amplifier is being designed to operate on the 0.5 ampere Energy Recovery Linac which is under construction at Brookhaven National Laboratory's Collider-Accelerator Department.

    BEN-ZVI, ILAN, DAYRAN, D.; LITVINENKO, V.

    2005-08-21T23:59:59.000Z

    198

    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

    199

    Variable Average Absolute Percent Differences  

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

    Variable Variable Average Absolute Percent Differences Percent of Projections Over- Estimated Gross Domestic Product Real Gross Domestic Product (Average Cumulative Growth)* (Table 2) 1.0 42.6 Petroleum Imported Refiner Acquisition Cost of Crude Oil (Constant $) (Table 3a) 35.2 18.6 Imported Refiner Acquisition Cost of Crude Oil (Nominal $) (Table 3b) 34.7 19.7 Total Petroleum Consumption (Table 4) 6.2 66.5 Crude Oil Production (Table 5) 6.0 59.6 Petroleum Net Imports (Table 6) 13.3 67.0 Natural Gas Natural Gas Wellhead Prices (Constant $) (Table 7a) 30.7 26.1 Natural Gas Wellhead Prices (Nominal $) (Table 7b) 30.0 27.1 Total Natural Gas Consumption (Table 8) 7.8 70.2 Natural Gas Production (Table 9) 7.1 66.0 Natural Gas Net Imports (Table 10) 29.3 69.7 Coal Coal Prices to Electric Generating Plants (Constant $)** (Table 11a)

    200

    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

    Note: This page contains sample records for the topic "national average household" 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

    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...

    202

    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...

    203

    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

    204

    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...

    205

    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

    206

    Achronal averaged null energy condition  

    Science Conference Proceedings (OSTI)

    The averaged null energy condition (ANEC) requires that the integral over a complete null geodesic of the stress-energy tensor projected onto the geodesic tangent vector is never negative. This condition is sufficient to prove many important theorems in general relativity, but it is violated by quantum fields in curved spacetime. However there is a weaker condition, which is free of known violations, requiring only that there is no self-consistent spacetime in semiclassical gravity in which ANEC is violated on a complete, achronal null geodesic. We indicate why such a condition might be expected to hold and show that it is sufficient to rule out closed timelike curves and wormholes connecting different asymptotically flat regions.

    Graham, Noah; Olum, Ken D. [Department of Physics, Middlebury College, Middlebury, Vermont 05753 (United States) and Center for Theoretical Physics, Laboratory for Nuclear Science, and Department of Physics, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139 (United States); Institute of Cosmology, Department of Physics and Astronomy, Tufts University, Medford, Massachusetts 02155 (United States)

    2007-09-15T23:59:59.000Z

    207

    Achronal averaged null energy condition  

    E-Print Network (OSTI)

    The averaged null energy condition (ANEC) requires that the integral over a complete null geodesic of the stress-energy tensor projected onto the geodesic tangent vector is never negative. This condition is sufficient to prove many important theorems in general relativity, but it is violated by quantum fields in curved spacetime. However there is a weaker condition, which is free of known violations, requiring only that there is no self-consistent space-time in semiclassical gravity in which ANEC is violated on a complete, {\\em achronal} null geodesic. We indicate why such a condition might be expected to hold and show that it is sufficient to rule out wormholes and closed timelike curves.

    Noah Graham; Ken D. Olum

    2007-05-22T23:59:59.000Z

    208

    Techno-economics analysis of a wind/PV hybrid system to provide electricity for a household in Malaysia  

    Science Conference Proceedings (OSTI)

    This paper is study on techno-economics analysis of a wind/PV hybrid system for a household in Malaysia. One year recorded wind speed and solar radiation are used for the design of a hybrid energy system. In 2004 average annual wind speed in Kuala Terengganu ... Keywords: electrical load, techno-economics analysis, wind/PV hybrid system

    Ahmad Fudholi; Mohd Zamri Ibrahim; Mohd Hafidz Ruslan; Lim Chin Haw; Sohif Mat; Mohd Yusof Othman; Azami Zaharim; Kamaruzzaman Sopian

    2012-01-01T23:59:59.000Z

    209

    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

    210

    Electricity displacement by wood used for space heating in PNWRES (Pacific Northwest Residential Energy Survey) (1983) households  

    DOE Green Energy (OSTI)

    This report evaluates the amount of electricity for residential space heating displaced by the use of wood in a sample of single-family households that completed the 1983 Pacific Northwest Residential Energy Survey. Using electricity bills and daily weather data from the period of July 1981 to July 1982, it was determined that the average household used 21,800 kWh per year, normalized with respect to weather. If no households had used any wood, electricity use would have increased 9%, to 23,700 kWh; space heating electricity use would also have increased, by 21%, to 47% of total electricity use. In the unlikely event that all households had used a great deal of wood for space heating, electricity use could have dropped by 23.5% from the average use, to 16,700 kWh; space heating electricity use would have dropped by 56%, to 24% of total electricity use. Indications concerning future trends regarding the displacement of electricity by wood use are mixed. On one hand, continuing to weatherize homes in the Pacific Northwest may result in less wood use as households find using electricity more economical. On the other hand, historical trends in replacement decisions regarding old space heating systems show a decided preference for wood. 11 refs., 6 figs., 8 tabs.

    White, D.L.; Tonn, B.E.

    1988-12-01T23:59:59.000Z

    211

    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

    212

    Spectral and Parametric Averaging for Integrable Systems  

    E-Print Network (OSTI)

    We analyze two theoretical approaches to ensemble averaging for integrable systems in quantum chaos - spectral averaging and parametric averaging. For spectral averaging, we introduce a new procedure - rescaled spectral averaging. Unlike traditional spectral averaging, it can describe the correlation function of spectral staircase and produce persistent oscillations of the interval level number variance. Parametric averaging, while not as accurate as rescaled spectral averaging for the correlation function of spectral staircase and interval level number variance, can also produce persistent oscillations of the global level number variance and better describes saturation level rigidity as a function of the running energy. Overall, it is the most reliable method for a wide range of statistics.

    Tao Ma; R. A. Serota

    2013-06-03T23:59:59.000Z

    213

    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

    214

    The comparative impact of the market penetration of energy-efficient measures: A sensitivity analysis of its impact on minority households  

    SciTech Connect

    A sensitivity study was made of the potential market penetration of residential energy efficiency as energy service ratio (ESR) improvements occurred in minority households, by age of house. The study followed a Minority Energy Assessment Model analysis of the National Energy Strategy projections of household energy consumption and prices, with majority, black, and Hispanic subgroup divisions. Electricity and total energy consumption and expenditure patterns were evaluated when the households` ESR improvement followed a logistic negative growth (i.e., market penetration) path. Earlier occurrence of ESR improvements meant greater discounted savings over the 22-year period.

    Bozinovich, L.V.; Poyer, D.A.; Anderson, J.L.

    1993-12-01T23:59:59.000Z

    215

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

    SciTech Connect

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

    Letschert, Virginie; McNeil, Michael A.

    2009-03-23T23:59:59.000Z

    216

    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

    217

    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

    218

    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

    219

    annual average heating degree days | OpenEI  

    Open Energy Info (EERE)

    average heating degree days average heating degree days Dataset Summary Description (Abstract): Heating Degree Days below 18° C (degree days)The monthly accumulation of degrees when the daily mean temperature is below 18° C.NASA Surface meteorology and Solar Energy (SSE) Release 6.0 Data Set (Nov 2007)22-year Monthly Average & Annual Sum (July 1983 - June 2005)Parameter: Heating Degree Days Below 18 degrees C (degree days)Internet: http://eosweb.larc.nasa.gov/sse/ Source U.S. National Aeronautics and Space Administration (NASA), Surface meteorology and Solar Energy (SSE) Date Released March 31st, 2009 (5 years ago) Date Updated April 01st, 2009 (5 years ago) Keywords annual average heating degree days climate GIS NASA SWERA UNEP Data application/zip icon Download Shapefile (zip, 2.7 MiB)

    220

    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

    Note: This page contains sample records for the topic "national average household" 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 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

    222

    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

    223

    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

    224

    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) ...

    225

    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 ...

    226

    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 ...

    227

    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

    228

    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

    229

    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

    230

    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

    231

    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

    232

    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

    233

    Space-Heating energy used by households in the residential sector.  

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

    Detailed Tables Detailed Tables Energy End Uses Ranked by Energy Consumption, 1989 The following 28 tables present detailed data describing the consumption of and expenditures for energy used by households in the residential sector. The data are presented at the national level, Census region and division levels, for climate zones and for the most populous States, as well as for other selected characteristics of households. This section provides assistance in reading the tables by explaining some of the headings for the categories of data. It also explains the use of the row and column factors to compute the relative standard error of the estimates given in the tables. Organization of the Tables The tables cover consumption and expenditures for six topical areas: Major Energy Source

    234

    Average summer electric power bills expected to be lowest in four years  

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

    summer electric power bills expected to be lowest in summer electric power bills expected to be lowest in four years The average U.S. household is expected to pay $395 for electricity this summer. That's down 2.5% from last year and the lowest residential summer power bill in four years, according to the new forecast from the U.S. Energy Information Administration. Lower electricity use to meet cooling demand this summer because of forecasted milder temperatures compared with last summer is expected to more than offset higher electricity prices. The result is lower power bills for most U.S. households during the June, July, and August period. However electricity use and prices vary by region. EIA expects residential power bills will be lower in all areas of the country... except for the West South Central region, which includes

    235

    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)

    236

    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

    237

    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

    238

    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

    239

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

    SciTech Connect

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

    Eisenberg, Joel Fred [ORNL

    2008-06-01T23:59:59.000Z

    240

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

    SciTech Connect

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

    Eisenberg, Joel Fred [ORNL

    2008-06-01T23:59:59.000Z

    Note: This page contains sample records for the topic "national average household" 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

    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

    242

    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

    243

    Average Stock Levels: Crude Market & Propane  

    U.S. Energy Information Administration (EIA)

    This graph shows that propane was not alone in experiencing excess supply in 1998 and extraordinary stock builds. Note that the graph shows average stock levels ...

    244

    Optimization Online - String-Averaging Projected Subgradient ...  

    E-Print Network (OSTI)

    Aug 29, 2013 ... Optimization Online. String-Averaging Projected Subgradient Methods for Constrained Minimization. Yair Censor(yair ***at*** math.haifa.ac.il)

    245

    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

    246

    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:

    247

    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:

    248

    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:

    249

    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:

    250

    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:

    251

    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

    252

    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

    253

    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

    254

    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.

    255

    An economic assessment of the impact of two crude oil price scenarios on households  

    SciTech Connect

    The impact of two possible future crude oil price scenarios -- high and low price cases -- is assessed for three population groups: majority (non-Hispanic and nonblack), black, and Hispanic. The two price scenarios were taken from the energy security'' report published by the US Department of Energy in 1987. Effects of the two crude oil price scenarios for the 1986--95 period are measured for energy demand and composition and for share of income spent on energy by the three population groups at both the national and census-region levels. The effects on blacks are marginally more adverse than on majority householders, while effects on Hispanics are about the same as those on the majority. Little change is seen in percentage of income spent on energy over the forecast period. Both Hispanic and black households would spend a larger share of their incomes on energy than would majority households. The relatively adverse effects in the higher price scenario shift from the South and West Census regions to the Northeast and Midwest. 24 refs., 7 figs., 22 tabs.

    Poyer, D.A.; Teotia, A.P.S.; Hemphill, R.C.; Hill, L.G.; Marinelli, J.L.; Rose, K.J.; Santini, D.J.

    1990-02-01T23:59:59.000Z

    256

    Dynamic Multiscale Averaging (DMA) of Turbulent Flow  

    SciTech Connect

    A new approach called dynamic multiscale averaging (DMA) for computing the effects of turbulent flow is described. The new method encompasses multiple applications of temporal and spatial averaging, that is, multiscale operations. Initially, a direct numerical simulation (DNS) is performed for a relatively short time; it is envisioned that this short time should be long enough to capture several fluctuating time periods of the smallest scales. The flow field variables are subject to running time averaging during the DNS. After the relatively short time, the time-averaged variables are volume averaged onto a coarser grid. Both time and volume averaging of the describing equations generate correlations in the averaged equations. These correlations are computed from the flow field and added as source terms to the computation on the next coarser mesh. They represent coupling between the two adjacent scales. Since they are computed directly from first principles, there is no modeling involved. However, there is approximation involved in the coupling correlations as the flow field has been computed for only a relatively short time. After the time and spatial averaging operations are applied at a given stage, new computations are performed on the next coarser mesh using a larger time step. The process continues until the coarsest scale needed is reached. New correlations are created for each averaging procedure. The number of averaging operations needed is expected to be problem dependent. The new DMA approach is applied to a relatively low Reynolds number flow in a square duct segment. Time-averaged stream-wise velocity and vorticity contours from the DMA approach appear to be very similar to a full DNS for a similar flow reported in the literature. Expected symmetry for the final results is produced for the DMA method. The results obtained indicate that DMA holds significant potential in being able to accurately compute turbulent flow without modeling for practical engineering applications.

    Richard W. Johnson

    2012-09-01T23:59:59.000Z

    257

    Bayesian curve estimation by model averaging  

    Science Conference Proceedings (OSTI)

    A Bayesian approach is used to estimate a nonparametric regression model. The main features of the procedure are, first, the functional form of the curve is approximated by a mixture of local polynomials by Bayesian model averaging (BMA), second, the ... Keywords: BIC criterion, Bayesian model averaging, Local polynomial regression, Nonparametric curve fitting, Robustness

    Daniel Peńa; Dolores Redondas

    2006-02-01T23:59:59.000Z

    258

    Property:SalinityAverage | Open Energy Information  

    Open Energy Info (EERE)

    SalinityAverage SalinityAverage Jump to: navigation, search Property Name SalinityAverage Property Type Number Description Mean average of the low and high end measurements of the salinity [ppm] of the fluid. This is a property of type Page. Subproperties This property has the following 1 subproperty: C Coso Geothermal Area Pages using the property "SalinityAverage" Showing 19 pages using this property. A Amedee Geothermal Area + 975 + B Beowawe Hot Springs Geothermal Area + 700 + Blue Mountain Geothermal Area + 4300 + Brady Hot Springs Geothermal Area + 3500 + C Chena Geothermal Area + 325 + D Desert Peak Geothermal Area + 6700 + Dixie Valley Geothermal Area + 2295 + E East Mesa Geothermal Area + 3750 + G Geysers Geothermal Area + 217 + K Kilauea East Rift Geothermal Area + 18750 +

    259

    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

    260

    Table US14. Average Consumption by Energy End Uses, 2005 Million ...  

    U.S. Energy Information Administration (EIA)

    Million British Thermal Units (Btu) per Household U.S. Households (millions) Other Appliances and Lighting Space Heating 4 Air-Conditioning 5 Water Heating 6 ...

    Note: This page contains sample records for the topic "national average household" 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

    Residential energy consumption across different population groups: Comparative analysis for Latino and non-Latino households in U.S.A.  

    SciTech Connect

    Residential energy cost, an important part of the household budget, varies significantly across different population groups. In the United States, researchers have conducted many studies of household fuel consumption by fuel type -- electricity, natural gas, fuel oil, and liquefied petroleum gas (LPG) -- and by geographic areas. The results of past research have also demonstrated significant variation in residential energy use across various population groups, including white, black, and Latino. However, research shows that residential energy demand by fuel type for Latinos, the fastest-growing population group in the United States, has not been explained by economic and noneconomic factors in any available statistical model. This paper presents a discussion of energy demand and expenditure patterns for Latino and non-Latino households in the United States. The statistical model developed to explain fuel consumption and expenditures for Latino households is based on Stone and Geary`s linear expenditure system model. For comparison, the authors also developed models for energy consumption in non-Latino, black, and nonblack households. These models estimate consumption of and expenditures for electricity, natural gas, fuel oil, and LPG by various households at the national level. The study revealed significant variations in the patterns of fuel consumption for Latinos and non-Latinos. The model methodology and results of this research should be useful to energy policymakers in government and industry, researchers, and academicians who are concerned with economic and energy issues related to various population groups.

    Poyer, D.A.; Teotia, A.P.S. [Argonne National Lab., IL (United States); Henderson, L. [Univ. of Baltimore, MD (United States)

    1998-05-01T23:59:59.000Z

    262

    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.

    263

    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.

    264

    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...

    265

    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...

    266

    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...

    267

    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

    268

    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

    269

    The Shape of Averaged Drop Size Distributions  

    Science Conference Proceedings (OSTI)

    The shape of averaged drop size distributions (DSD) is studied from a large sample of data (892 h) collected at several sites of various latitudes. The results show that neither the hypothesis of an exponential distribution to represent rainfall ...

    Henri Sauvageot; Jean-Pierre Lacaux

    1995-04-01T23:59:59.000Z

    270

    Lagged Average Predictions in a Predictability Experiment  

    Science Conference Proceedings (OSTI)

    Lagged average predictions are examined here within the context of an idealized predictability experiment. Lagged predictions contribute to making better forecasts than the forecasts obtained from using only the latest initial state. Analytic ...

    John O. Roads

    1988-01-01T23:59:59.000Z

    271

    Probabilistic Visibility Forecasting Using Bayesian Model Averaging  

    Science Conference Proceedings (OSTI)

    Bayesian model averaging (BMA) is a statistical postprocessing technique that has been used in probabilistic weather forecasting to calibrate forecast ensembles and generate predictive probability density functions (PDFs) for weather quantities. ...

    Richard M. Chmielecki; Adrian E. Raftery

    2011-05-01T23:59:59.000Z

    272

    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

    273

    Average Data for Each Choke Setting (before 24-May 2010 06:00), 6-hour average (  

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

    Average Data for Each Choke Setting (before 24-May 2010 06:00), 6-hour average (after 24-May 2010 06:00):" Average Data for Each Choke Setting (before 24-May 2010 06:00), 6-hour average (after 24-May 2010 06:00):" ,,"Choke","Average","Average","Fluid","Methanol","Water","Oil","Gas","Hyd. Eq.","Gas" ,"Choke","Setting","Upstream","Upstream","Recovery","Recovery","Recovery","Recovery","Recovery","Recovery","Recovery" "Date and Time","Setting","Duration","Pressure","Temp.","Rate","Rate","Rate","Rate","Rate","Rate","Portion" "dd-mmm-yy","(64ths)","(hours)","(psia)","(degF)","(bfpd)","(bfpd)","(bwpd)","(bopd)","(mmcfpd)","(boepd)","(%)"

    274

    Average transmission probability of a random stack  

    E-Print Network (OSTI)

    The transmission through a stack of identical slabs that are separated by gaps with random widths is usually treated by calculating the average of the logarithm of the transmission probability. We show how to calculate the average of the transmission probability itself with the aid of a recurrence relation and derive analytical upper and lower bounds. The upper bound, when used as an approximation for the transmission probability, is unreasonably good and we conjecture that it is asymptotically exact.

    Yin Lu; Christian Miniatura; Berthold-Georg Englert

    2009-07-31T23:59:59.000Z

    275

    A high average power pockels cell  

    DOE Patents (OSTI)

    A high average power pockels cell is disclosed which reduced the effect of thermally induced strains in high average power laser technology. The pockels cell includes an elongated, substantially rectangular crystalline structure formed from a KDP-type material to eliminate shear strains. The X- and Y-axes are oriented substantially perpendicular to the edges of the crystal cross-section and to the C-axis direction of propagation to eliminate shear strains.

    Daly, T.P.

    1986-02-10T23:59:59.000Z

    276

    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

    277

    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

    278

    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

    279

    2011 Brief: U.S. average gasoline and diesel prices over $3 ...  

    U.S. Energy Information Administration (EIA)

    The average price U.S. drivers paid for gasoline and diesel during 2011 never fell below $3 per gallon, marking the first time the national pump price for both ...

    280

    Estimating Averaging Times for Point and Path-Averaged Measurements of Turbulence Spectra  

    Science Conference Proceedings (OSTI)

    Uncertainty over how long to average turbulence variables to achieve some desired level of statistical stability is a common concern in boundary-layer meteorology. Several models exist that predict averaging times for measurements of variances ...

    Edgar L. Andreas

    1988-03-01T23:59:59.000Z

    Note: This page contains sample records for the topic "national average household" 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

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

    DOE Green Energy (OSTI)

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

    Karvelas, D.E.; Jody, B.J.; Poykala, J.A. Jr.; Daniels, E.J. [Argonne National Lab., IL (United States). Energy Systems Div.; Arman, B. [Argonne National Lab., IL (United States). Energy Systems Div.]|[Praxair, Inc., Tarrytown, NY (United States)

    1996-03-01T23:59:59.000Z

    282

    ,"Housing Units1","Average Square Footage Per Housing Unit",...  

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

    the U.S. Department of Energy's Office of Energy and Efficiency and Renewable Energy (EERE). 5Rented includes households that occupy their primary housing unit without payment of...

    283

    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.

    284

    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

    285

    EREV and BEV Economic Viability vs. Household Retail Electric Pricing Strategies: Two Charges a Day?  

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

    EREV and BEV Economic Viability vs. EREV and BEV Economic Viability vs. Household Retail Electric Pricing Strategies: Two Charges a Day? By Dan Santini Argonne National Laboratory dsantini@anl.gov Remarks are attributable only to the author; not to Argonne or U.S. Department of Energy NAATBatt Conference: The Impact of PEVs on T&D Systems: Challenges and Solutions Dec. 7, 2010 The submitted manuscript has been created by Argonne National Laboratory, a U.S. Department of Energy laboratory managed by UChicago Argonne, LLC, under Contract No. DE-AC02-06CH11357. The U.S. Government retains for itself, and others acting on its behalf, a paid-up, nonexclusive, irrevocable worldwide license in said article to reproduce, prepare derivative works, distribute copies to the public, and perform publicly and display publicly,

    286

    Diesel prices increase nationally  

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

    Diesel prices increase nationally The U.S. average retail price for on-highway diesel fuel rose to 3.91 a gallon on Monday. That's up 1.3 cents from a week ago, based on the...

    287

    Diesel prices flat nationally  

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

    Diesel prices flat nationally The U.S. average retail price for on-highway diesel fuel remained the same from a week ago at 3.98 a gallon on Monday, based on the weekly price...

    288

    World average top-quark mass  

    SciTech Connect

    This paper summarizes a talk given at the Top2008 Workshop at La Biodola, Isola d Elba, Italy. The status of the world average top-quark mass is discussed. Some comments about the challanges facing the experiments in order to further improve the precision are offered.

    Glenzinski, D.; /Fermilab

    2008-01-01T23:59:59.000Z

    289

    STAFF FORECAST: AVERAGE RETAIL ELECTRICITY PRICES  

    E-Print Network (OSTI)

    CALIFORNIA ENERGY COMMISSION STAFF FORECAST: AVERAGE RETAIL ELECTRICITY PRICES 2005 TO 2018 report, Staff Forecast: Retail Electricity Prices, 2005 to 2018, was prepared with contributions from the technical assistance provided by Greg Broeking of R.W. Beck, Inc. in preparing retail price forecasts

    290

    Exact bounds for average pairwise network reliability  

    Science Conference Proceedings (OSTI)

    Several methods for finding exact bounds of average pairwise network connectivity (APNC) are proposed. These methods allows faster decision making about if a network is reliable for its purpose. Previous results on cumulitive updating of all-terminal ... Keywords: algorithm, network reliability, pairwise connectivity

    Alexey Rodionov; Olga Rodionova

    2013-01-01T23:59:59.000Z

    291

    High average power diode pumped solid state lasers for CALIOPE  

    Science Conference Proceedings (OSTI)

    Diode pumping of solid state media offers the opportunity for very low maintenance, high efficiency, and compact laser systems. For remote sensing, such lasers may be used to pump tunable non-linear sources, or if tunable themselves, act directly or through harmonic crystals as the probe. The needs of long range remote sensing missions require laser performance in the several watts to kilowatts range. At these power performance levels, more advanced thermal management technologies are required for the diode pumps. The solid state laser design must now address a variety of issues arising from the thermal loads, including fracture limits, induced lensing and aberrations, induced birefringence, and laser cavity optical component performance degradation with average power loading. In order to highlight the design trade-offs involved in addressing the above issues, a variety of existing average power laser systems are briefly described. Included are two systems based on Spectra Diode Laboratory`s water impingement cooled diode packages: a two times diffraction limited, 200 watt average power, 200 Hz multi-rod laser/amplifier by Fibertek, and TRW`s 100 watt, 100 Hz, phase conjugated amplifier. The authors also present two laser systems built at Lawrence Livermore National Laboratory (LLNL) based on their more aggressive diode bar cooling package, which uses microchannel cooler technology capable of 100% duty factor operation. They then present the design of LLNL`s first generation OPO pump laser for remote sensing. This system is specified to run at 100 Hz, 20 nsec pulses each with 300 mJ, less than two times diffraction limited, and with a stable single longitudinal mode. The performance of the first testbed version will be presented. The authors conclude with directions their group is pursuing to advance average power lasers. This includes average power electro-optics, low heat load lasing media, and heat capacity lasers.

    Comaskey, B.; Halpin, J.; Moran, B.

    1994-07-01T23:59:59.000Z

    292

    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

    293

    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

    294

    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

    295

    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

    296

    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

    297

    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

    298

    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

    299

    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

    300

    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

    Note: This page contains sample records for the topic "national average household" 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

    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

    302

    Sources Of Average Individual Radiation Exposure  

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

    Of Average Individual Radiation Exposure Of Average Individual Radiation Exposure Natural background Medical Consumer products Industrial, security, educational and research Occupational 0.311 rem 0.300 rem 0.013 rem 0.0003 rem 0.0005 rem Savannah River Nuclear Solutions, LLC, provides radiological protection services and oversight at the Savannah River Site (SRS). These services include radiation dose measurements for persons who enter areas where they may be exposed to radiation or radioactive material. The results are periodically reported to monitored individuals. The results listed are based on a radiation dose system developed by the International Commission on Radiation Protection. The system uses the terms "effective dose," "equivalent dose" and units of rem. You may be more familiar with the term "millirem" (mrem), which is 1/1000 of a rem.

    303

    Fat turnover in obese slower than average  

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

    9-04 9-04 For immediate release: 09/23/2011 | NR-11-09-04 Fat turnover in obese slower than average Anne M Stark, LLNL, (925) 422-9799, stark8@llnl.gov Printer-friendly This scanning electron micrograph image shows part of a lobule of adipose tissue (body fat). Adipose tissue is specialized connective tissue that functions as the major storage site for fat. Photo courtesy of David Gregory & Debbie Marshall/Wellcome Images LIVERMORE, Calif. -- It may be more difficult for obese people to lose fat because the "turnover" rate is much slower for those overweight than average weight individuals. New research in the Sept. 25 online edition of the journal Nature shows that the turnover (storage and loss rate) of fat in the human body is about 1 1/2 years compared to fat cells, which turnover about every 10 years,

    304

    Natural Gas Prices: Well Above Recent Averages  

    Gasoline and Diesel Fuel Update (EIA)

    5 5 Notes: The recent surge in spot prices at the Henry Hub are well above a typical range for 1998-1999 (in this context, defined as the average, +/- 2 standard deviations). Past price surges have been of short duration. The possibility of a downward price adjustment before the end of next winter is a source of considerable risk for storage operators who acquire gas at recent elevated prices. Storage levels in the Lower 48 States were 7.5 percent below the 5-year average (1995-1999) by mid-August (August 11), although the differential is only 6.4 percent in the East, which depends most heavily on storage to meet peak demand. Low storage levels are attributable, at least in part, to poor price incentives: high current prices combined with only small price

    305

    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

    306

    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

    307

    Impact Ionization Model Using Average Energy and Average Square Energy of Distribution Function  

    E-Print Network (OSTI)

    Impact Ionization Model Using Average Energy and Average Square Energy of Distribution Function Ken relaxation length, v sat ø h''i (¸ 0:05¯m), the energy distribution function is not well described calculation of impact ionization coefficient requires the use of a high energy distribution function because

    Dunham, Scott

    308

    Impacts of different data averaging times on statistical analysis of distributed domestic photovoltaic systems  

    Science Conference Proceedings (OSTI)

    The trend of increasing application of distributed generation with solar photovoltaics (PV-DG) suggests that a widespread integration in existing low-voltage (LV) grids is possible in the future. With massive integration in LV grids, a major concern is the possible negative impacts of excess power injection from on-site generation. For power-flow simulations of such grid impacts, an important consideration is the time resolution of demand and generation data. This paper investigates the impact of time averaging on high-resolution data series of domestic electricity demand and PV-DG output and on voltages in a simulated LV grid. Effects of 10-minutely and hourly averaging on descriptive statistics and duration curves were determined. Although time averaging has a considerable impact on statistical properties of the demand in individual households, the impact is smaller on aggregate demand, already smoothed from random coincidence, and on PV-DG output. Consequently, the statistical distribution of simulated grid voltages was also robust against time averaging. The overall judgement is that statistical investigation of voltage variations in the presence of PV-DG does not require higher resolution than hourly. (author)

    Widen, Joakim; Waeckelgaard, Ewa [Department of Engineering Sciences, The Aangstroem Laboratory, Uppsala University, P.O. Box 534, SE-751 21 Uppsala (Sweden); Paatero, Jukka; Lund, Peter [Advanced Energy Systems, Helsinki University of Technology, P.O. Box 2200, FI-02015 HUT (Finland)

    2010-03-15T23:59:59.000Z

    309

    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

    310

    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

    311

    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.

    312

    Average Price of Natural Gas Production  

    Gasoline and Diesel Fuel Update (EIA)

    . . Quantity and Average Price of Natural Gas Production in the United States, 1930-1996 (Volumes in Million Cubic Feet, Prices in Dollars per Thousand Cubic Feet) Table Year Gross Withdrawals Used for Repressuring Nonhydro- carbon Gases Removed Vented and Flared Marketed Production Extraction Loss Dry Production Average Wellhead Price of Marketed Production 1930 ....................... NA NA NA NA 1,978,911 75,140 1,903,771 0.08 1931 ....................... NA NA NA NA 1,721,902 62,288 1,659,614 0.07 1932 ....................... NA NA NA NA 1,593,798 51,816 1,541,982 0.06 1933 ....................... NA NA NA NA 1,596,673 48,280 1,548,393 0.06 1934 ....................... NA NA NA NA 1,815,796 52,190 1,763,606 0.06 1935 ....................... NA NA NA NA 1,968,963 55,488 1,913,475 0.06 1936 ....................... 2,691,512 73,507 NA 392,528 2,225,477

    313

    Average values and dispersion (in parentheses)  

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

    Average values and dispersion (in parentheses) Average values and dispersion (in parentheses) Base-pair Parameters --------------------------------------------------------------------------------------- Shear Stretch Stagger Buckle Propeller Opening 3DNA A 0.01(0.23) -0.18(0.10) 0.02(0.25) -0.13(7.77) -11.79(4.14) 0.57(2.80) B 0.00(0.21) -0.15(0.12) 0.09(0.19) 0.53(6.74) -11.35(5.26) 0.63(3.05) CEHS A 0.01(0.23) -0.18(0.10) 0.02(0.25) -0.13(7.75) -11.82(4.14) 0.56(2.78) B 0.00(0.21) -0.14(0.12) 0.09(0.19) 0.53(6.73) -11.37(5.27) 0.62(3.03) CompDNA A 0.01(0.23) -0.18(0.10) 0.02(0.25) -0.12(7.70) -11.81(4.14) 0.56(2.79) B 0.00(0.21) -0.15(0.12) 0.09(0.19) 0.53(6.70) -11.37(5.26) 0.62(3.03) Curves A 0.01(0.23) -0.18(0.10) 0.02(0.25) -0.13(7.85) -11.76(4.12) 0.57(2.80)

    314

    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

    315

    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

    316

    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

    317

    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 ...

    318

    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

    319

    Locally Calibrated Probabilistic Temperature Forecasting Using Geostatistical Model Averaging and Local Bayesian Model Averaging  

    Science Conference Proceedings (OSTI)

    The authors introduce two ways to produce locally calibrated grid-based probabilistic forecasts of temperature. Both start from the Global Bayesian model averaging (Global BMA) statistical postprocessing method, which has constant predictive bias ...

    William Kleiber; Adrian E. Raftery; Jeffrey Baars; Tilmann Gneiting; Clifford F. Mass; Eric Grimit

    2011-08-01T23:59:59.000Z

    320

    Geographic Gossip: Efficient Averaging for Sensor Networks  

    E-Print Network (OSTI)

    Gossip algorithms for distributed computation are attractive due to their simplicity, distributed nature, and robustness in noisy and uncertain environments. However, using standard gossip algorithms can lead to a significant waste in energy by repeatedly recirculating redundant information. For realistic sensor network model topologies like grids and random geometric graphs, the inefficiency of gossip schemes is related to the slow mixing times of random walks on the communication graph. We propose and analyze an alternative gossiping scheme that exploits geographic information. By utilizing geographic routing combined with a simple resampling method, we demonstrate substantial gains over previously proposed gossip protocols. For regular graphs such as the ring or grid, our algorithm improves standard gossip by factors of $n$ and $\\sqrt{n}$ respectively. For the more challenging case of random geometric graphs, our algorithm computes the true average to accuracy $\\epsilon$ using $O(\\frac{n^{1.5}}{\\sqrt{\\log ...

    Dimakis, Alexandros G; Wainwright, Martin J

    2007-01-01T23:59:59.000Z

    Note: This page contains sample records for the topic "national average household" 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

    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 ...

    322

    An Analysis of the Price Elasticity of Demand for Household Appliances  

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

    Analysis of the Price Elasticity of Demand for Analysis of the Price Elasticity of Demand for Household Appliances Larry Dale and K. Sydny Fujita February 2008 Energy Analysis Department Environmental Energy Technologies Division Lawrence Berkeley National Laboratory University of California Berkeley, CA 94720 DISCLAIMER This document was prepared as an account of work sponsored by the United States Government. While this document is believed to contain correct information, neither the United States Government nor any agency thereof, nor The Regents of the University of California, nor any of their employees, makes any warranty, express or implied, or assumes any legal responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not

    323

    Table 7.5 Average Prices of Selected Purchased Energy Sources, 2002  

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

    5 Average Prices of Selected Purchased Energy Sources, 2002;" 5 Average Prices of Selected Purchased Energy Sources, 2002;" " Level: National and Regional Data; " " Row: Values of Shipments and Employment Sizes;" " Column: Energy Sources;" " Unit: U.S. Dollars per Million Btu." " ",," "," ",," "," ","RSE" "Economic",,"Residual","Distillate","Natural ","LPG and",,"Row" "Characteristic(a)","Electricity","Fuel Oil","Fuel Oil(b)","Gas(c)","NGL(d)","Coal","Factors" ,"Total United States"

    324

    Table N8.2. Average Prices of Purchased Energy Sources, 1998  

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

    2. Average Prices of Purchased Energy Sources, 1998;" 2. Average Prices of Purchased Energy Sources, 1998;" " Level: National and Regional Data; " " Row: NAICS Codes; Column: All Energy Sources Collected;" " Unit: U.S. Dollars per Million Btu." ,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,"Selected","Wood and Other","Biomass","Components" ,,,,,,,"Coal Components",,,"Coke",,"Electricity","Components",,,,,,,,,,,,,"Natural Gas","Components",,"Steam","Components" ,,,,,,,,,,,,,,"Total",,,,,,,,,,,,,,,,,,,,,,,"Wood Residues" " "," "," ",,,,,"Bituminous",,,,,,"Electricity","Diesel Fuel",,,,,,"Motor",,,,,,,"Natural Gas",,,"Steam",,,," ",,,"and","Wood-Related",," ",," "

    325

    Table 7.1 Average Prices of Purchased Energy Sources, 2002  

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

    Average Prices of Purchased Energy Sources, 2002;" Average Prices of Purchased Energy Sources, 2002;" " Level: National and Regional Data; " " Row: NAICS Codes;" " Column: All Energy Sources Collected;" " Unit: U.S. Dollars per Physical Units." ,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,"Selected Wood and Other Biomass Components" ,,,,,,"Coal Components",,,"Coke",,,"Electricity Components",,,,,,,,,,,,,,"Natural Gas Components",,,"Steam Components" ,,,,,,,,,,,,,,"Total",,,,,,,,,,,,,,,,,,,,,,,"Wood Residues" " "," "," ",,,,,"Bituminous",,,,,,"Electricity","Diesel Fuel",,,,,,"Motor",,,,,,,"Natural Gas",,,"Steam",,,," ",,,"and","Wood-Related",," ",," "

    326

    Table 7.2 Average Prices of Purchased Energy Sources, 2002  

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

    2 Average Prices of Purchased Energy Sources, 2002;" 2 Average Prices of Purchased Energy Sources, 2002;" " Level: National and Regional Data; " " Row: NAICS Codes; " " Column: All Energy Sources Collected;" " Unit: U.S. Dollars per Million Btu." ,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,"Selected Wood and Other Biomass Components" ,,,,,,"Coal Components",,,"Coke",,,"Electricity Components",,,,,,,,,,,,,,"Natural Gas Components",,,"Steam Components" ,,,,,,,,,,,,,,"Total",,,,,,,,,,,,,,,,,,,,,,,"Wood Residues" " "," "," ",,,,,"Bituminous",,,,,,"Electricity","Diesel Fuel",,,,,,"Motor",,,,,,,"Natural Gas",,,"Steam",,,," ",,,"and","Wood-Related",," ",," "

    327

    Table 7.4 Average Prices of Selected Purchased Energy Sources, 2002  

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

    4 Average Prices of Selected Purchased Energy Sources, 2002;" 4 Average Prices of Selected Purchased Energy Sources, 2002;" " Level: National and Regional Data; " " Row: Values of Shipments and Employment Sizes;" " Column: Energy Sources;" " Unit: U.S. Dollars per Physical Units." " ",," "," ",," "," " ,,"Residual","Distillate","Natural ","LPG and",,"RSE" "Economic","Electricity","Fuel Oil","Fuel Oil(b)","Gas(c)","NGL(d)","Coal","Row" "Characteristic(a)","(kWh)","(gallons)","(gallons)","(1000 cu ft)","(gallons)","(short tons)","Factors"

    328

    Table 7.3 Average Prices of Purchased Electricity, Natural Gas, and Steam, 20  

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

    3 Average Prices of Purchased Electricity, Natural Gas, and Steam, 2002;" 3 Average Prices of Purchased Electricity, Natural Gas, and Steam, 2002;" " Level: National and Regional Data; " " Row: NAICS Codes;" " Column: Supplier Sources of Purchased Electricity, Natural Gas, and Steam;" " Unit: U.S. Dollars per Physical Units." ,,,"Electricity","Components",,"Natural Gas","Components",,"Steam","Components" " "," ",,,"Electricity",,,"Natural Gas",,,"Steam"," ",," " " "," ",,"Electricity","from Sources",,"Natural Gas","from Sources",,"Steam","from Sources"

    329

    "Table E8.1. Average Prices of Selected Purchased Energy Sources, 1998;"  

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

    1. Average Prices of Selected Purchased Energy Sources, 1998;" 1. Average Prices of Selected Purchased Energy Sources, 1998;" " Level: National and Regional Data; " " Row: Values of Shipments and Employment Sizes;" " Column: Energy Sources;" " Unit: U.S. Dollars per Physical Units." " ",," "," ",," "," " ,,"Residual","Distillate",,"LPG and",,"RSE" "Economic","Electricity","Fuel Oil","Fuel Oil(b)","Natural Gas(c)","NGL(d)","Coal","Row" "Characteristic(a)","(kWh)","(gallons)","(gallons)","(1000 cu ft)","(gallons)","(short tons)","Factors"

    330

    "Table E8.2. Average Prices of Selected Purchased Energy Sources, 1998;"  

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

    2. Average Prices of Selected Purchased Energy Sources, 1998;" 2. Average Prices of Selected Purchased Energy Sources, 1998;" " Level: National and Regional Data; " " Row: Values of Shipments and Employment Sizes;" " Column: Energy Sources;" " Unit: U.S. Dollars per Million Btu." " ",," "," ",," "," ","RSE" "Economic",,"Residual","Distillate",,"LPG and",,"Row" "Characteristic(a)","Electricity","Fuel Oil","Fuel Oil(b)","Natural Gas(c)","NGL(d)","Coal","Factors" ,"Total United States"

    331

    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

    332

    Table 5B. Commercial Average Monthly Bill by Census Division ...  

    U.S. Energy Information Administration (EIA)

    Home > Electricity > Electric Sales, Revenue, and Price > Commercial Average Monthly Bill by Census Division, and State: Table 5B. Commercial Average Monthly Bill by ...

    333

    Average summer gasoline prices expected to be slightly lower ...  

    U.S. Energy Information Administration (EIA)

    The retail price for regular gasoline is expected to average $3.63 per gallon during this summer driving season, slightly below average prices over ...

    334

    Table 5B. Commercial average monthly bill by census division...  

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

    " Census Division " " State ","Number of Consumers "," Average Monthly Consumption (kWh)","Price (Cents per Kilowatthour)","Average Monthly Bill (Dollar and cents)" "New...

    335

    On the String Averaging Method for Sparse Common Fixed Points ...  

    E-Print Network (OSTI)

    Jul 10, 2008 ... gate a string-averaging algorithmic scheme that favorably handles the ... are special cases of the string-averaging and of the BIP algorithmic ...

    336

    Table 5A. Residential Average Monthly Bill by Census Division ...  

    U.S. Energy Information Administration (EIA)

    Table 5A. Residential Average Monthly Bill by Census Division, and State, 2009: Census Division State Number of Consumers Average Monthly Consumption ...

    337

    Residential energy use and conservation in Venezuela: Results and implications of a household survey in Caracas  

    SciTech Connect

    This document presents the final report of a study of residential energy use in Caracas, the capital of Venezuela. It contains the findings of a household energy-use survey held in Caracas in 1988 and examines options for introducing energy conservation measures in the Venezuelan residential sector. Oil exports form the backbone of the Venezuelan economy. Improving energy efficiency in Venezuela will help free domestic oil resources that can be sold to the rest of the world. Energy conservation will also contribute to a faster recovery of the economy by reducing the need for major investments in new energy facilities, allowing the Venezuelan government to direct its financial investments towards other areas of development. Local environmental benefits will constitute an important additional by-product of implementing energy-efficiency policies in Venezuela. Caracas`s residential sector shows great potential for energy conservation. The sector is characterized by high saturation levels of major appliances, inefficiency of appliances available in the market, and by careless patterns of energy use. Household energy use per capita average 6.5 GJ/per year which is higher than most cities in developing countries; most of this energy is used for cooking. Electricity accounts for 41% of all energy use, while LPG and natural gas constitute the remainder. Specific options for inducing energy conservation and energy efficiency in Caracas`s residential sector include energy-pricing policies, fuel switching, particularly from electricity to gas, improving the energy performance of new appliances and customer information. To ensure the accomplishment of an energy-efficiency strategy, a concerted effort by energy users, manufacturers, utility companies, government agencies, and research institutions will be needed.

    Figueroa, M.J.; Ketoff, A.; Masera, O.

    1992-10-01T23:59:59.000Z

    338

    Time Series of Daily Averaged Cloud Fractions over Landfast First-Year Sea Ice from Multiple Data Sources  

    Science Conference Proceedings (OSTI)

    The time series of daily averaged cloud fractions (CFs) collected from different platforms—two Moderate Resolution Imaging Spectroradiometer (MODIS) instruments on Terra and Aqua satellites, the National Centers for Environmental Prediction (NCEP)...

    Xin Jin; John M. Hanesiak; David G. Barber

    2007-11-01T23:59:59.000Z

    339

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

    SciTech Connect

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

    Henderson, L.J. (Baltimore Univ., MD (United States)); Poyer, D.A.; Teotia, A.P.S. (Argonne National Lab., IL (United States). Energy Systems Div.)

    1992-09-01T23:59:59.000Z

    340

    Texas Gulf Coast Refinery District API Gravity (Weighted Average ...  

    U.S. Energy Information Administration (EIA)

    Texas Gulf Coast Refinery District API Gravity (Weighted Average) of Crude Oil Input to Refineries (Degree)

    Note: This page contains sample records for the topic "national average household" 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

    Diesel prices slightly decrease nationally  

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

    Diesel prices slightly decrease nationally The U.S. average retail price for on-highway diesel fuel fell to 3.97 a gallon on Monday. That's down 7-tenths of a penny from a week...

    342

    Diesel prices slightly increase nationally  

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

    Diesel prices slightly increase nationally The U.S. average retail price for on-highway diesel fuel rose slightly to 3.90 a gallon on Monday. That's up 4-tenths of a penny from a...

    343

    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 Ă— 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

    344

    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:

    345

    Patterns of residential energy demand by type of household: white, black, Hispanic, and low- and nonlow-income  

    SciTech Connect

    This report compares patterns of residential energy use by white, black, Hispanic, low-income, and nonlow-income households. The observed downward trend in residential energy demand over the period of this study can be attributed primarily to changes in space-heating energy demand. Demand for space-heating energy has experienced a greater decline than energy demand for other end uses for two reasons: (1) it is the largest end use of residential energy, causing public attention to focus on it and on strategies for conserving it; and (2) space-heating expenditures are large relative to other residential energy expenditures. The price elasticity of demand is thus greater, due to the income effect. The relative demand for space-heating energy, when controlled for the effect of climate, declined significantly over the 1978-1982 period for all fuels studied. Income classes do not differ significantly. In contrast, black households were found to use more energy for space heating than white households were found to use, although those observed differences are statistically significant only for houses heated with natural gas. As expected, the average expenditure for space-heating energy increased significantly for dwellings heated by natural gas and fuel oil. No statistically significant increases were found in electricity expenditures for space heating. Electric space heat is, in general, confined to milder regions of the country, where space heating is relatively less essential. As a consequence, we would expect the electricity demand for space heating to be more price-elastic than the demand for other fuels.

    Klein, Y.; Anderson, J.; Kaganove, J.; Throgmorton, J.

    1984-10-01T23:59:59.000Z

    346

    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

    347

    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 ...

    348

    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

    349

    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

    350

    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

    351

    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

    352

    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, ...

    353

    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...

    354

    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

    355

    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

    356

    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

    357

    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 ...

    358

    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 ...

    359

    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

    360

    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

    Note: This page contains sample records for the topic "national average household" 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

    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

    362

    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 ...

    363

    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.

    364

    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 ...

    365

    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."

    366

    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

    367

    Vehicle Technologies Office: Fact #328: July 12, 2004 Expected Average  

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

    8: July 12, 2004 8: July 12, 2004 Expected Average Annual Miles to someone by E-mail Share Vehicle Technologies Office: Fact #328: July 12, 2004 Expected Average Annual Miles on Facebook Tweet about Vehicle Technologies Office: Fact #328: July 12, 2004 Expected Average Annual Miles on Twitter Bookmark Vehicle Technologies Office: Fact #328: July 12, 2004 Expected Average Annual Miles on Google Bookmark Vehicle Technologies Office: Fact #328: July 12, 2004 Expected Average Annual Miles on Delicious Rank Vehicle Technologies Office: Fact #328: July 12, 2004 Expected Average Annual Miles on Digg Find More places to share Vehicle Technologies Office: Fact #328: July 12, 2004 Expected Average Annual Miles on AddThis.com... Fact #328: July 12, 2004 Expected Average Annual Miles Twenty-five percent of the respondents to a nationwide survey said that

    368

    Vehicle Technologies Office: Fact #87: May 4, 1999 Average Annual...  

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

    7: May 4, 1999 Average Annual Miles per Vehicle by Vehicle Type and Age to someone by E-mail Share Vehicle Technologies Office: Fact 87: May 4, 1999 Average Annual Miles per...

    369

    Vehicle Technologies Office: Fact #536: September 15, 2008 Average...  

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

    6: September 15, 2008 Average Used Car Prices Up and Used Light Truck Prices Down to someone by E-mail Share Vehicle Technologies Office: Fact 536: September 15, 2008 Average Used...

    370

    Vehicle Technologies Office: Fact #517: May 5, 2008 State Average...  

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

    7: May 5, 2008 State Average Gasoline Prices, April 18, 2008 to someone by E-mail Share Vehicle Technologies Office: Fact 517: May 5, 2008 State Average Gasoline Prices, April 18,...

    371

    Vehicle Technologies Office: Fact #744: September 10, 2012 Average...  

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

    4: September 10, 2012 Average New Light Vehicle Price Grows Faster than Average Used Light Vehicle Price to someone by E-mail Share Vehicle Technologies Office: Fact 744:...

    372

    Improving Wind Profiler–Measured Winds Using Coplanar Spectral Averaging  

    Science Conference Proceedings (OSTI)

    A method is presented that increases the detectability of weak clear-air signals by averaging Doppler spectra from coplanar wind profiler beams. The method, called coplanar spectral averaging (CSA), is applied to both simulated wind profiler ...

    Robert Schafer; Susan K. Avery; Kenneth S. Gage; Paul E. Johnston; D. A. Carter

    2004-11-01T23:59:59.000Z

    373

    On Lateral Dispersion Coefficients as Functions of Averaging Time  

    Science Conference Proceedings (OSTI)

    Plume dispersion coefficients are discussed in terms of single-particle and relative diffusion, and are investigated as functions of averaging time. To demonstrate the effects of averaging time on the relative importance of various dispersion ...

    C. M. Sheih

    1980-05-01T23:59:59.000Z

    374

    Vorticity Dynamics and Zonally Averaged Ocean Circulation Models  

    Science Conference Proceedings (OSTI)

    Diagnostic equations relating the zonally averaged overturning circulation to north–south density variations are derived and used to determine a new closure scheme for use in zonally averaged ocean models. The presentation clarifies the dynamical ...

    Daniel G. Wright; Cornelis B. Vreugdenhil; Tertia M. C. Hughes

    1995-09-01T23:59:59.000Z

    375

    Probabilistic Quantitative Precipitation Forecasting Using Bayesian Model Averaging  

    Science Conference Proceedings (OSTI)

    Bayesian model averaging (BMA) is a statistical way of postprocessing forecast ensembles to create predictive probability density functions (PDFs) for weather quantities. It represents the predictive PDF as a weighted average of PDFs centered on ...

    J. Mc Lean Sloughter; Adrian E. Raftery; Tilmann Gneiting; Chris Fraley

    2007-09-01T23:59:59.000Z

    376

    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

    377

    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

    378

    Table 5C. Industrial Average Monthly Bill by Census Division ...  

    U.S. Energy Information Administration (EIA)

    Home > Electricity > Electric Sales, Revenue, and Price > Industrial Average Monthly Bill by Census Division, and State: Table 5C. Industrial ...

    379

    Table 4. Average retail price for bundled and unbundled consumers ...  

    U.S. Energy Information Administration (EIA)

    Table 4. Average retail price for bundled and unbundled consumers by sector, Census Division, and State 2011

    380

    Maryland Average Price of Natural Gas Delivered to Residential and ...  

    U.S. Energy Information Administration (EIA)

    Average Price of Natural Gas Delivered to Residential and Commercial Consumers by Local Distribution and Marketers in Selected States

    Note: This page contains sample records for the topic "national average household" 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

    Optimization Online - "Block-Iterative and String-Averaging ...  

    E-Print Network (OSTI)

    Jul 19, 2009 ... Optimization Online. "Block-Iterative and String-Averaging Projection Algorithms in Proton Computed Tomography Image Reconstruction".

    382

    DOE/EIA-0193/P PRELIMINARY CONSERVATION TABLES FROM THE NATIONAL INTERIM ENERGY CONSUMPTION SURVEY  

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

    193/P 193/P PRELIMINARY CONSERVATION TABLES FROM THE NATIONAL INTERIM ENERGY CONSUMPTION SURVEY OFFICE OF THE CONSUMPTION DATA SYSTEM OFFICE OF PROGRAM DEVELOPMENT ENERGY INFORMATION ADMINISTRATION AUGUST 1, 1979 PRELIMINARY CONSERVATION TABLES FROM THE NATIONAL INTERIM ENERGY CONSUMPTION SURVEY Attached is the first report of the Office of the Consumption Data System, Office of Program Development, Energy Information Administration, presenting preliminary data from the National Interim Energy Consumption Survey (NIECS). The focus of this report is the conservation activities performed by households since January 1977, and the status of households with respect to insulation, storm windows, and other energy conserving characteristics. These tables are from preliminary data files.

    383

    202-328-5000 www.rff.orgA New Look at Residential Electricity Demand Using Household Expenditure Data  

    E-Print Network (OSTI)

    We estimate residential electricity demand for different regions of the country, assuming that consumers respond to average electricity prices. We circumvent the need for individual billing information by developing a novel generalized method of moments approach that allows us to estimate demand based on household electricity expenditure data from the Consumer Expenditure Survey, which does not have quantity and price information. We find that price elasticity estimates vary across the four census regions—the South at –1.02 is the most price-elastic region and the Northeast at –0.82 is the least—and are essentially equivalent across income quartiles. In general, these price elasticity estimates are considerably larger in magnitude than those found in other studies using household-level data that assume that consumers respond to marginal prices. We also apply our elasticity estimates in a U.S. climate policy simulation to determine how these elasticity estimates alter consumption and price outcomes compared to the more conservative elasticity estimates commonly used in policy analysis.

    Harrison Fell; Shanjun Li; Anthony Paul; Harrison Fell; Shanjun Li; Anthony Paul; Monte Carlo Analysis

    2010-01-01T23:59:59.000Z

    384

    Historical GIS as a Platform for Public Memory at Mammoth Cave National Park  

    Science Conference Proceedings (OSTI)

    The Mammoth Cave Historical GIS (MCHGIS) fosters new understandings of a national park landscape as a historic farming community and offers a web-based platform for public memory of pre-park inhabitants. It maps the 1920 manuscript census at the household ... Keywords: Historical GIS, Kentucky, Mammoth Cave, National Parks, Public Memory, Public Participation GIS, Virtual Community Building

    Katie Algeo; Ann Epperson; Matthew Brunt

    2011-10-01T23:59:59.000Z

    385

    National Woodfuels and Wood Energy Information Analysis Prepared by: Sok Bun Heng  

    E-Print Network (OSTI)

    supplies. - 90 % of wood energy is consumed by households. - Industry is only a very small consumer of wood % Charcoal 1.2 %, other biomass 1.7 % and imported petroleum product. The most recent national energy supply balance indicates traditional fuels contribute 85 % of the national energy supply, of which 80

    386

    Table SH7. Average Consumption for Space Heating by Main Space ...  

    U.S. Energy Information Administration (EIA)

    Fuel Oil (gallons) Main Space Heating Fuel Used (physical units of consumption per household using the fuel as a main heating source) Table SH7.

    387

    Table SH8. Average Consumption for Space Heating by Main Space ...  

    U.S. Energy Information Administration (EIA)

    Fuel Oil Main Space Heating Fuel Used (million Btu of consumption per household using the fuel as a main heating source) Any Major Fuel 4 Table SH8.

    388

    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

    389

    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

    390

    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

    391

    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

    392

    Personal vehicles preferred by urban Americans: household automobile holdings and new car purchases projected to the year 2000  

    DOE Green Energy (OSTI)

    A procedure is described for modeling the choices made in urban American households among personal vehicles on the bases of cost, passenger capacity, and engine technology, and it projects those preferences to the year 1990 and 2000. The results of this disaggregate technique are used by the other predictive research tasks undertaken by Argonne National Laboratory in a project entitled Technology Assessment of Productive Conservation in Urban Transportation (TAPCUT). The vehicle preferences reported here furnish data for the overall TAPCUT objective of forecasting the probable effects of energy conservation policies in transportation. In our projections, vehicles with standard spark-ignition (Otto-cycle) engines continue to dominate automobile holdings and new car purchases in either of two socioeconomic scenarios under any of three settings (an existing policy set and two alternative conservation strategies). From 1990, small cars (seating four or fewer passengers) dominate urban holdings and sales in two of the three TAPCUT energy strategies - the exception being the strategy that emphasizes individual travel - and this holds true with only a minor variation for both socioeconomic scenarios (an optimistic one and a slightly pessimistic one). Advanced-technology vehicles are most successful under the Individual Travel Strategy. It appears that vehicle charateristics are far more significant than demographic descriptors in estimating household vehicle choice using this modeling approach.

    Saricks, C.L.; Vyas, A.D.; Bunch, J.A.

    1982-01-01T23:59:59.000Z

    393

    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?

    394

    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?

    395

    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

    396

    Vehicle Technologies Office: Fact #310: March 8, 2004 Average Material  

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

    0: March 8, 2004 0: March 8, 2004 Average Material Consumption for a Domestic Automobile to someone by E-mail Share Vehicle Technologies Office: Fact #310: March 8, 2004 Average Material Consumption for a Domestic Automobile on Facebook Tweet about Vehicle Technologies Office: Fact #310: March 8, 2004 Average Material Consumption for a Domestic Automobile on Twitter Bookmark Vehicle Technologies Office: Fact #310: March 8, 2004 Average Material Consumption for a Domestic Automobile on Google Bookmark Vehicle Technologies Office: Fact #310: March 8, 2004 Average Material Consumption for a Domestic Automobile on Delicious Rank Vehicle Technologies Office: Fact #310: March 8, 2004 Average Material Consumption for a Domestic Automobile on Digg Find More places to share Vehicle Technologies Office: Fact #310:

    397

    Average Interest Rate for Treasury Securities | Data.gov  

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

    Average Interest Rate for Treasury Securities Average Interest Rate for Treasury Securities Consumer Data Apps Challenges Resources About Blogs Let's Talk Feedback Consumer You are here Data.gov » Communities » Consumer » Data Average Interest Rate for Treasury Securities Dataset Summary Description This dataset shows the average interest rates for U.S Treasury securities for the most recent month compared with the same month of the previous year. The data is broken down by the various marketable and non-marketable securities. The summary page for the data provides links for monthly reports from 2001 through the current year. Average Interest Rates are calculated on the total unmatured interest-bearing debt. The average interest rates for total marketable, total non-marketable and total interest-bearing debt do not include the U.S. Treasury Inflation-Protected Securities.

    398

    Orbit-averaged guiding-center Fokker-Planck operator  

    Science Conference Proceedings (OSTI)

    A general orbit-averaged guiding-center Fokker-Planck operator suitable for the numerical analysis of transport processes in axisymmetric magnetized plasmas is presented. The orbit-averaged guiding-center operator describes transport processes in a three-dimensional guiding-center invariant space: the orbit-averaged magnetic-flux invariant {psi}, the minimum-B pitch-angle coordinate {xi}{sub 0}, and the momentum magnitude p.

    Brizard, A. J. [Department of Chemistry and Physics, Saint Michael's College, Colchester, Vermont 05439 (United States); Decker, J.; Peysson, Y.; Duthoit, F.-X. [CEA, IRFM, Saint-Paul-lez-Durance F-13108 (France)

    2009-10-15T23:59:59.000Z

    399

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

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

    Skip to main content Energy.gov Search form Search Energy.gov Public Services Tax Credits, Rebates & Savings Homes Vehicles Building Design Manufacturing National Security & Safety...

    400

    Heating costs for most households are forecast to rise ...  

    U.S. Energy Information Administration (EIA)

    Solar › Energy in Brief ... Although winter temperatures are expected to be similar to last winter nationally, weather in the Northeast is expected to ...

    Note: This page contains sample records for the topic "national average household" 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

    Average Depth of Crude Oil and Natural Gas Wells  

    U.S. Energy Information Administration (EIA)

    -No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Average depth may ...

    402

    New York Average Price of Natural Gas Delivered to Residential ...  

    U.S. Energy Information Administration (EIA)

    Average Price of Natural Gas Delivered to Residential and Commercial Consumers by Local Distribution and Marketers in Selected States (Dollars per ...

    403

    Ohio Average Price of Natural Gas Delivered to Residential and ...  

    U.S. Energy Information Administration (EIA)

    Average Price of Natural Gas Delivered to Residential and Commercial Consumers by Local Distribution and Marketers in Selected States (Dollars per Thousand Cubic Feet ...

    404

    Average prices for spot sulfur dioxide emissions allowances at ...  

    U.S. Energy Information Administration (EIA)

    The weighted average spot price for sulfur dioxide (SO 2) emissions allowances awarded to winning bidders at Environmental Protection Agency's (EPA) annual auction on ...

    405

    Electric Sales, Revenue, and Average Price 2011 - Energy Information...  

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

    All Electricity Reports Electric Sales, Revenue, and Average Price With Data for 2011 | Release Date: September 27, 2012 | Next Release Date: September, 2013 Previous editions...

    406

    Chapter 5. Retail Sales, Revenue, and Average Retail Price of ...  

    U.S. Energy Information Administration (EIA)

    106 U.S. Energy Information Administration/Electric Power Monthly June 2012 Chapter 5. Retail Sales, Revenue, and Average Retail Price of Electricity

    407

    Table 14a. Average Electricity Prices, Projected vs. Actual  

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

    a. Average Electricity Prices, Projected vs. Actual" "Projected Price in Constant Dollars" " (constant dollars, cents per kilowatt-hour in ""dollar year"" specific to each AEO)"...

    408

    Electric Sales, Revenue, and Average Price 2011 - Energy ...  

    U.S. Energy Information Administration (EIA)

    Class of Ownership, Number of Consumers, Sales, Revenue, and Average Retail Price for Power Marketers and Energy Service Providers by State: T12:

    409

    Today in Energy - Average wholesale natural gas prices mostly ...  

    U.S. Energy Information Administration (EIA)

    Average spot natural gas prices, which reflect the wholesale price of natural gas at major trading points, generally declined in most U.S. regional markets about 7% ...

    410

    ,"U.S. Natural Gas Average Annual Consumption per Commercial...  

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

    ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","U.S. Natural Gas Average Annual Consumption per Commercial Consumer (Mcf)",1,"Annual",2011...

    411

    ,"U.S. Natural Gas Average Annual Consumption per Industrial...  

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

    ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","U.S. Natural Gas Average Annual Consumption per Industrial Consumer (Mcf)",1,"Annual",2011...

    412

    2012 Brief: Average wholesale electricity prices down compared ...  

    U.S. Energy Information Administration (EIA)

    2012 Brief: Average wholesale electricity prices down compared to last year. ... wholesale electric power prices often trend together with natural gas prices.

    413

    Figure 34. Ratio of average per megawatthour fuel costs ...  

    U.S. Energy Information Administration (EIA)

    Title: Figure 34. Ratio of average per megawatthour fuel costs for natural gas combined-cycle plants to coal-fired steam turbines in the RFC west ...

    414

    Average wholesale spot natural gas prices rose across the country ...  

    U.S. Energy Information Administration (EIA)

    Wholesale spot natural gas prices rose across the country in 2010. Average spot natural gas prices at the Henry Hub—a key benchmark location for pricing throughout ...

    415

    EIA Renewable Energy- Average Energy Conversion Efficiency of ...  

    U.S. Energy Information Administration (EIA)

    Renewables and Alternate Fuels > Solar Photovoltaic Cell/Module Annual Report > Annual Shipments of Photovoltaic Cells and Modules by Source: Average Energy ...

    416

    Solar: monthly and annual average global horizontal (GHI) GIS...  

    Open Energy Info (EERE)

    on cloud cover, atmospheric water vapor and trace gases, and the amount of aerosols in the atmosphere to calculate the monthly average daily total insolation (sun and...

    417

    Solar: monthly and annual average direct normal (DNI), global...  

    Open Energy Info (EERE)

    on cloud cover, atmospheric water vapor and trace gases, and the amount of aerosols in the atmosphere to calculate the monthly average daily total insolation (sun and...

    418

    Solar: monthly and annual average direct normal (DNI) GIS data...  

    Open Energy Info (EERE)

    on cloud cover, atmospheric water vapor and trace gases, and the amount of aerosols in the atmosphere to calculate the monthly average daily total insolation (sun and...

    419

    Climate: monthly and annual average relative humidity GIS data...  

    Open Energy Info (EERE)

    Climate: monthly and annual average relative humidity GIS data at one-degree resolution of the World from NASASSE

    (Abstract):  
    Relative Humidity at 10 m...

    420

    Pennsylvania Average Price of Natural Gas Delivered to Residential ...  

    U.S. Energy Information Administration (EIA)

    Average Price of Natural Gas Delivered to Residential and Commercial Consumers by Local Distribution and Marketers in Selected States (Dollars per Thousand Cubic Feet ...

    Note: This page contains sample records for the topic "national average household" 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

    District of Columbia Average Price of Natural Gas Delivered to ...  

    U.S. Energy Information Administration (EIA)

    Average Price of Natural Gas Delivered to Residential and Commercial Consumers by Local Distribution and Marketers in Selected States (Dollars per Thousand Cubic Feet ...

    422

    Michigan Average Price of Natural Gas Delivered to Residential and ...  

    U.S. Energy Information Administration (EIA)

    Average Price of Natural Gas Delivered to Residential and Commercial Consumers by Local Distribution and Marketers in Selected States (Dollars per Thousand Cubic Feet ...

    423

    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

    424

    Variation in Nimbus-7 Cloud Estimates. Part I: Zonal Averages  

    Science Conference Proceedings (OSTI)

    Zonal averages of low, middle and total cloud amount estimates derived from measurements from Nimbus-7 have been analyzed for the six-year period April 1979 through March 1985. The globally and zonally averaged values of six-year annual means and ...

    Bryan C. Weare

    1992-12-01T23:59:59.000Z

    425

    Solar: monthly and annual average direct normal (DNI), global horizontal  

    Open Energy Info (EERE)

    East Asia from NREL East Asia from NREL Dataset Summary Description (Abstract): Monthly Average Solar Resource for horizontal and tilted flat-plates, and 2-axis tracking concentrating collectors. (Purpose): Provide information on the solar resource potential for the data domain. The insolation values represent the average solar energy available to solar collectors. (Supplemental Information): These data provide monthly average and annual average daily total solar resource averaged over surface cells of approximately 40 km by 40 km in size. The solar resource value is represented as watt-hours per square meter per day for each month. The data were developed from NREL's Climatological Solar Radiation (CSR) Model. This model uses information on cloud cover, atmospheric water

    426

    Solar: monthly and annual average direct normal (DNI), global horizontal  

    Open Energy Info (EERE)

    Africa from NREL Africa from NREL Dataset Summary Description (Abstract): Monthly Average Solar Resource for horizontal and tilted flat-plates, and 2-axis tracking concentrating collectors. (Purpose): Provide information on the solar resource potential for the data domain. The insolation values represent the average solar energy available to solar collectors. (Supplemental Information): These data provide monthly average and annual average daily total solar resource averaged over surface cells of approximately 40 km by 40 km in size. The solar resource value is represented as watt-hours per square meter per day for each month. The data were developed from NREL's Climatological Solar Radiation (CSR) Model. This model uses information on cloud cover, atmospheric water

    427

    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

    428

    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

    429

    Long-run marginal costs lower than average costs  

    SciTech Connect

    The thesis of this article is that the long-run marginal costs of electricity are not always greater than the present average costs, as is often assumed. As long as short-run costs decrease with new plant additions, the long-run marginal cost is less than long-run average cost. When average costs increase with new additions, long-run marginal costs are greater than long-run average costs. The long-run marginal costs of a particular utility may be less than, equal to, or greater than its long-run average costs - even with inflation present. The way to determine which condition holds for a given utility is to estimate costs under various combinations of assumptions: probable load growth, zero load growth, and load growth greater than expected; and changes in load factor with attendant costs. Utilities that can demonstrate long-run marginal costs lower than long-run average costs should be encouraged to build plant and increase load, for the resulting productivity gains and slowing of inflation. Utilities that face long-run marginal costs greater than long-run average costs should discourage growth in sales through any available means.

    Hunter, S.R.

    1980-01-03T23:59:59.000Z

    430

    NREL GIS Data: Alaska Low Resolution Wind Resource Annual average...  

    Open Energy Info (EERE)

    and data instances (values) within the dataset do not contradict each other.

      National Renewable Energy Lab (NREL) 4 DISCLAIMER NOTICE This GIS data was developed by...

    431

    Estimated 2000 Interregional Pipeline Capacity and 1999 Average Flows  

    U.S. Energy Information Administration (EIA)

    ... the nation's natural gas interstate pipeline infrastructure appears more than adequate to meet the differing regional market demand requirements that are likely ...

    432

    National Laboratories  

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

    Laboratories Los Alamos National Laboratory (the Laboratory) is one of 17 National Laboratories in the United States and is one of the two located in New Mexico. The Laboratory has...

    433

    NATIONAL CONFERENCE  

    Science Conference Proceedings (OSTI)

    ... Oak Room ... of the Secretariats, the US National Work Groups ... the continued cooperation with the International Laboratory Accreditation Cooperation ...

    2010-12-17T23:59:59.000Z

    434

    Figure 33. Ratio of average per megawatthour fuel costs for ...  

    U.S. Energy Information Administration (EIA)

    Sheet3 Sheet2 Sheet1 Figure 33. Ratio of average per megawatthour fuel costs for natural gas combined-cycle plants to coal-fired steam turbines in the SERC southeast ...

    435

    Figure 27. Ratio of average per megawatthour fuel costs for ...  

    U.S. Energy Information Administration (EIA)

    Sheet3 Sheet2 Sheet1 Figure 27. Ratio of average per megawatthour fuel costs for natural gas combined-cycle plants to coal-fired steam turbines in five cases, 2008-2040

    436

    ARM - Evaluation Product - Average of Cloud Condensation Nuclei...  

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

    are averaged together. The %ss in the CCN data stream is calculated using a heat transfer and fluid dynamics model flow model (Lance et al., 2006). The model uses the...

    437

    Virginia Average Price of Natural Gas Delivered to Residential...  

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

    10.34 9.79 11.62 14.97 NA 20.70 1989-2013 Commercial Average Price 8.35 8.21 9.11 9.52 9.96 10.36...

    438

    New York Average Price of Natural Gas Delivered to Residential...  

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

    94 11.57 12.82 15.94 18.40 18.73 1989-2013 Commercial Average Price 8.38 8.32 8.27 8.38 7.91 6.66...

    439

    Maryland Average Price of Natural Gas Delivered to Residential...  

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

    0.35 10.04 12.02 15.43 17.45 16.48 1989-2013 Commercial Average Price 9.03 9.30 10.67 11.84 12.79 NA...

    440

    Figure 88. Annual average Henry Hub spot prices for natural ...  

    U.S. Energy Information Administration (EIA)

    Sheet3 Sheet2 Sheet1 Figure 88. Annual average Henry Hub spot prices for natural gas in five cases, 1990-2040 (2011 dollars per million Btu) Reference

    Note: This page contains sample records for the topic "national average household" 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

    Figure 86. Annual average Henry Hub spot natural gas prices ...  

    U.S. Energy Information Administration (EIA)

    Sheet3 Sheet2 Sheet1 Figure 86. Annual average Henry Hub spot natural gas prices, 1990-2040 (2011 dollars per million Btu) Henry Hub Spot Price 1990.00

    442

    Table 14b. Average Electricity Prices, Projected vs. Actual  

    Gasoline and Diesel Fuel Update (EIA)

    b. Average Electricity Prices, Projected vs. Actual Projected Price in Nominal Dollars (nominal dollars, cents per kilowatt-hour) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002...

    443

    2012 Brief: Average wholesale electricity prices down compared to ...  

    U.S. Energy Information Administration (EIA)

    Average, on-peak (weekdays from 7:00 a.m. to 11:00 p.m.) day-ahead electricity prices were lower across the entire United States in 2012 compared to 2011.

    444

    Table 14b. Average Electricity Prices, Projected vs. Actual  

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

    b. Average Electricity Prices, Projected vs. Actual" "Projected Price in Nominal Dollars" " (nominal dollars, cents per kilowatt-hour)" ,1993,1994,1995,1996,1997,1998,1999,2000,200...

    445

    Does anyone have access to 2012 average residential rates by...  

    Open Energy Info (EERE)

    Does anyone have access to 2012 average residential rates by utility company? I'm seeing an inconsistency between the OpenEI website and EIA 861 data set. Home > Groups > Utility...

    446

    Exact Averaging of Atmospheric State and Flow Variables  

    Science Conference Proceedings (OSTI)

    A new set of averaging rules is put forward that exactly determines the means of air temperature, mixing ratio, and velocity by incorporating weighting factors in accordance with physical conservation laws. For the temperature and velocity, ...

    Andrew S. Kowalski

    2012-05-01T23:59:59.000Z

    447

    Electric Sales, Revenue, and Average Price 2011 - Energy ...  

    U.S. Energy Information Administration (EIA)

    2001-2010 are Excel zipped files & 1994-2000 are PDF files ... and Average Retail Price for Power Marketers and ... U.S. Department of Energy USA.gov FedStats.

    448

    U.S. Natural Gas Average Consumption per Commercial Consumer...  

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

    Commercial Consumer (Thousand Cubic Feet) U.S. Natural Gas Average Consumption per Commercial Consumer (Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6...

    449

    Average Diurnal Variation of Summer Lightning over the Floirida Peninsula  

    Science Conference Proceedings (OSTI)

    Data derived from a large network of electric field mills have been used to determine the average diurnal variation of lightning in a Florida seacoast environment. These data were obtained at the NASA Kennedy Space Center (KSC) and the Cape ...

    Launa M. Maier; E. Philip Krider; Michael W. Maier

    1984-06-01T23:59:59.000Z

    450

    Benthic Boundary-Layer Velocity Profiles: Dependence on Averaging Period  

    Science Conference Proceedings (OSTI)

    The relationship between benthic boundary-layer velocity profiles and current meter averaging time is investigated using detailed (0.61 Hz) current measurements recorded within 1 m of the bottom on the inner continental shelf. The percentage of ...

    Barry M. Lesht

    1980-06-01T23:59:59.000Z

    451

    Solar: monthly and annual average global horizontal irradiance...  

    Open Energy Info (EERE)

    b>  
    Global Horizontal Irradiance
    NASA Surface meteorology and Solar Energy (SSE) Release 6.0 Data Set (Jan 2008)
    22-year Monthly & Annual Average...

    452

    Solar: monthly and annual average direct normal irradiance GIS...  

    Open Energy Info (EERE)

    >  
    Direct Normal Irradiance (kWhm2day)
    NASA Surface meteorology and Solar Energy (SSE) Release 6.0 Data Set (Jan 2008)
    22-year Monthly & Annual Average...

    453

    STATE OF CALIFORNIA AREA WEIGHTED AVERAGE CALCULATION WORKSHEET: RESIDENTIAL  

    E-Print Network (OSTI)

    there is more than one level of floor, wall, or ceiling insulation in a building, or more than one type of a building feature, material, or construction assembly occur in a building, a weighted average

    454

    Solar: monthly and annual average latitude tilt irradiance GIS...  

    Open Energy Info (EERE)

    & Annual Average (July 1983 - June 2005)
    Parameter: Latitude Tilt Radiation (kWhm2day)
    Internet: http:eosweb.larc.nasa.govsse
    Note 1:...

    455

    Using Bayesian Model Averaging to Calibrate Forecast Ensembles  

    Science Conference Proceedings (OSTI)

    Ensembles used for probabilistic weather forecasting often exhibit a spread-error correlation, but they tend to be underdispersive. This paper proposes a statistical method for postprocessing ensembles based on Bayesian model averaging (BMA), ...

    Adrian E. Raftery; Tilmann Gneiting; Fadoua Balabdaoui; Michael Polakowski

    2005-05-01T23:59:59.000Z

    456

    Pennsylvania Average Price of Natural Gas Delivered to Residential...  

    Gasoline and Diesel Fuel Update (EIA)

    7 10.55 11.24 13.80 16.87 19.85 1989-2013 Commercial Average Price 9.51 9.87 10.27 11.46 12.38 12.89...

    457

    Semi-supervised training for the averaged perceptron POS tagger  

    Science Conference Proceedings (OSTI)

    This paper describes POS tagging experiments with semi-supervised training as an extension to the (supervised) averaged perceptron algorithm, first introduced for this task by (Collins, 2002). Experiments with an iterative training on standard-sized ...

    Drahomíra "johanka" Spoustová; Jan Haji?; Jan Raab; Miroslav Spousta

    2009-03-01T23:59:59.000Z

    458

    A Statistical Averaging Method for Wind Profiler Doppler Spectra  

    Science Conference Proceedings (OSTI)

    A new method is presented for Doppler spectral averaging that more reliably identifies the profiler radar return from clear air in the presence of contamination—for example, from migrating bird echoes. These very sensitive radars profile the wind ...

    David A. Merritt

    1995-10-01T23:59:59.000Z

    459

    The averaged control system of fast oscillating control systems  

    E-Print Network (OSTI)

    For control systems that either have an explicit periodic dependence on time or have periodic solutions and small controls, we define an average control system that takes into account all possible variations of the control, and prove that its solutions approximate all solutions of the oscillating systems as oscillations go faster. The dimension of its velocity set is characterised geomtrically. When it is maximum the average system defines a Finsler metric, unfortunately not twice differntiable in general. Under particular assumptions, valid for the control two body system, this Finsler metric generates a Hamiltonian flow on the cotangent bundle. For minimum time control, this average system proves that averaging the Hamiltonian given by the maximum principle is a valid approximation.

    Bombrun, Alex

    2011-01-01T23:59:59.000Z

    460

    Implication of Spatial Averaging in Complex-Terrain Wind Studies  

    Science Conference Proceedings (OSTI)

    Studies of wind over complex terrain have been conducted at three times and two locations in Northern California. Instrumentation included conventional cup-vane anemometers and optical anemometers with spatial averaging over path lengths of 0.6-1 ...

    W. M. Porch

    1982-09-01T23:59:59.000Z

    Note: This page contains sample records for the topic "national average household" 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

    Vehicle Technologies Office: Fact #638: August 30, 2010 Average...  

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

    8: August 30, 2010 Average Expenditure for a New Car Declines in Relation to Family Earnings to someone by E-mail Share Vehicle Technologies Office: Fact 638: August 30, 2010...

    462

    Some Considerations Relevant to Computing Average Hemispheric Temperature Anomalies  

    Science Conference Proceedings (OSTI)

    Three data bases of gridded surface temperature anomalies were used to assess the sensitivity of the average estimated Northern Hemisphere (NH) temperature anomaly to: 1) extreme gridpoint values and 2) zonal band contributions. Over the last 100 ...

    S. L. Grotch

    1987-07-01T23:59:59.000Z

    463

    New Mexico Natural Gas Average Consumption per Industrial Consumer...  

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

    Industrial Consumer (Thousand Cubic Feet) New Mexico Natural Gas Average Consumption per Industrial Consumer (Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5...

    464

    New Mexico Natural Gas Average Consumption per Commercial Consumer...  

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

    Commercial Consumer (Thousand Cubic Feet) New Mexico Natural Gas Average Consumption per Commercial Consumer (Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5...

    465

    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

    466

    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.

    467

    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

    468

    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

    469

    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

    470

    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

    471

    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

    472

    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

    473

    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

    474

    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, ...

    475

    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 --

    476

    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

    477

    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

    478

    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

    479

    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...

    480

    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

    Note: This page contains sample records for the topic "national average household" 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

    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

    482

    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...

    483

    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

    484

    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

    485

    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

    486

    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

    487

    Table A44. Average Prices of Purchased Electricity and Steam  

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

    4. Average Prices of Purchased Electricity and Steam" 4. Average Prices of Purchased Electricity and Steam" " by Type of Supplier, Census Region, Census Division, and" " Economic Characteristics of the Establishment, 1994" " (Estimates in Dollars per Physical Units)" ," Electricity",," Steam" ," (kWh)",," (million Btu)" ,,,,,"RSE" ,"Utility","Nonutility","Utility","Nonutility","Row" "Economic Characteristics(a)","Supplier(b)","Supplier(c)","Supplier(b)","Supplier(c)","Factors"

    488

    Solar: monthly and annual average direct normal (DNI), global horizontal  

    Open Energy Info (EERE)

    South America from NREL South America from NREL Dataset Summary Description (Abstract): Monthly Average Solar Resource for horizontal and tilted flat-plates, and 2-axis tracking concentrating collectors. (Purpose): Provide information on the solar resource potential for the data domain. The insolation values represent the average solar energy available to solar collectors. (Supplemental Information): These data provide monthly average and annual average daily total solar resource averaged over surface cells of approximately 40 km by 40 km in size. The solar resource value is represented as watt-hours per square meter per day for each month. The data were developed from NREL's Climatological Solar Radiation (CSR) Model. This model uses information on cloud cover, atmospheric water vapor and trace gases, and the amount of aerosols in the atmosphere to calculate the monthly average daily total insolation (sun and sky) falling on a horizontal surface. Existing ground measurement stations are used to validate the data where possible. The modeled values are accurate to approximately 10% of a true measured value within the grid cell due to the uncertainties associated with meteorological input to the model. The local cloud cover can vary significantly even within a single grid cell as a result of terrain effects and other microclimate influences. Furthermore, the uncertainty of the modeled estimates increase with distance from reliable measurement sources and with the complexity of the terrain.

    489

    Solar: monthly and annual average direct normal (DNI), global horizontal  

    Open Energy Info (EERE)

    Central America and the Carribean from NREL Central America and the Carribean from NREL Dataset Summary Description (Abstract): Monthly Average Solar Resource for horizontal and tilted flat-plates, and 2-axis tracking concentrating collectors. (Purpose): Provide information on the solar resource potential for the data domain. The insolation values represent the average solar energy available to solar collectors. (Supplemental Information): These data provide monthly average and annual average daily total solar resource averaged over surface cells of approximately 40 km by 40 km in size. The solar resource value is represented as watt-hours per square meter per day for each month. The data were developed from NREL's Climatological Solar Radiation (CSR) Model. This model uses information on cloud cover, atmospheric water vapor and trace gases, and the amount of aerosols in the atmosphere to calculate the monthly average daily total insolation (sun and sky) falling on a horizontal surface. Existing ground measurement stations are used to validate the data where possible. The modeled values are accurate to approximately 10% of a true measured value within the grid cell due to the uncertainties associated with meteorological input to the model. The local cloud cover can vary significantly even within a single grid cell as a result of terrain effects and other microclimate influences. Furthermore, the uncertainty of the modeled estimates increase with distance from reliable measurement sources and with the complexity of the terrain.

    490

    U.S. Refiner Sales to End Users (Average) Prices  

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

    Sales Type: Sales to End Users, Average Through Retail Outlets Sales for Resale, Average DTW Rack Bulk Sales Type: Sales to End Users, Average Through Retail Outlets Sales for Resale, Average DTW Rack Bulk Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: Formulation/ Grade Sales Type Apr-13 May-13 Jun-13 Jul-13 Aug-13 Sep-13 View History Conventional, Average 3.030 3.137 3.122 3.063 3.042 2.972 1994-2013 Conventional Regular 3.005 3.116 3.102 3.040 3.017 2.948 1994-2013 Conventional Midgrade 3.167 3.256 3.239 3.200 3.193 3.121 1994-2013 Conventional Premium 3.269 3.354 3.327 3.291 3.274 3.203 1994-2013 Oxygenated, Average - - - - - - 1994-2013 Oxygenated Regular - - - - - - 1994-2013 Oxygenated Midgrade - - - - - - 1994-2013

    491

    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

    492

    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

    493

    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

    494

    Bayesian Model Averaging’s Problematic Treatment of Extreme Weather and a Paradigm Shift That Fixes It  

    Science Conference Proceedings (OSTI)

    Methods of ensemble postprocessing in which continuous probability density functions are constructed from ensemble forecasts by centering functions around each of the ensemble members have come to be called Bayesian model averaging (BMA) or “...

    Craig H. Bishop; Kevin T. Shanley

    2008-12-01T23:59:59.000Z

    495

    Average Soil Water Retention Curves Measured by Neutron Radiography  

    SciTech Connect

    Water retention curves are essential for understanding the hydrologic behavior of partially-saturated porous media and modeling flow transport processes within the vadose zone. In this paper we report direct measurements of the main drying and wetting branches of the average water retention function obtained using 2-dimensional neutron radiography. Flint sand columns were saturated with water and then drained under quasi-equilibrium conditions using a hanging water column setup. Digital images (2048 x 2048 pixels) of the transmitted flux of neutrons were acquired at each imposed matric potential (~10-15 matric potential values per experiment) at the NCNR BT-2 neutron imaging beam line. Volumetric water contents were calculated on a pixel by pixel basis using Beer-Lambert s law after taking into account beam hardening and geometric corrections. To remove scattering effects at high water contents the volumetric water contents were normalized (to give relative saturations) by dividing the drying and wetting sequences of images by the images obtained at saturation and satiation, respectively. The resulting pixel values were then averaged and combined with information on the imposed basal matric potentials to give average water retention curves. The average relative saturations obtained by neutron radiography showed an approximate one-to-one relationship with the average values measured volumetrically using the hanging water column setup. There were no significant differences (at p < 0.05) between the parameters of the van Genuchten equation fitted to the average neutron radiography data and those estimated from replicated hanging water column data. Our results indicate that neutron imaging is a very effective tool for quantifying the average water retention curve.

    Cheng, Chu-Lin [ORNL; Perfect, Edmund [University of Tennessee, Knoxville (UTK); Kang, Misun [ORNL; Voisin, Sophie [ORNL; Bilheux, Hassina Z [ORNL; Horita, Juske [Texas Tech University (TTU); Hussey, Dan [NIST Center for Neutron Research (NCRN), Gaithersburg, MD

    2011-01-01T23:59:59.000Z

    496

    Sandia National Laboratories X-ray Tube with Magnetic Electron ...  

    ... for the U.S. Department of Energy’s National ... high average power large area X-ray tube provides increased X-ray generation efficiency through ...

    497

    National Fuel Cell Electric Vehicle Learning Demonstration Final...  

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

    national daily average miles traveled. An effective 40-mile electric range would allow electrification of more than two-thirds of the Learning Demonstration vehicle miles and...

    498

    Development of a high average current polarized electron source with long cathode operational lifetime  

    SciTech Connect

    Substantially more than half of the electromagnetic nuclear physics experiments conducted at the Continuous Electron Beam Accelerator Facility of the Thomas Jefferson National Accelerator Facility (Jefferson Laboratory) require highly polarized electron beams, often at high average current. Spin-polarized electrons are produced by photoemission from various GaAs-based semiconductor photocathodes, using circularly polarized laser light with photon energy slightly larger than the semiconductor band gap. The photocathodes are prepared by activation of the clean semiconductor surface to negative electron affinity using cesium and oxidation. Historically, in many laboratories worldwide, these photocathodes have had short operational lifetimes at high average current, and have often deteriorated fairly quickly in ultrahigh vacuum even without electron beam delivery. At Jefferson Lab, we have developed a polarized electron source in which the photocathodes degrade exceptionally slowly without electron emission, and in which ion back bombardment is the predominant mechanism limiting the operational lifetime of the cathodes during electron emission. We have reproducibly obtained cathode 1/e dark lifetimes over two years, and 1/e charge density and charge lifetimes during electron beam delivery of over 2?105???C/cm2 and 200 C, respectively. This source is able to support uninterrupted high average current polarized beam delivery to three experimental halls simultaneously for many months at a time. Many of the techniques we report here are directly applicable to the development of GaAs photoemission electron guns to deliver high average current, high brightness unpolarized beams.

    C. K. Sinclair; P. A. Adderley; B. M. Dunham; J. C. Hansknecht; P. Hartmann; M. Poelker; J. S. Price; P. M. Rutt; W. J. Schneider; M. Steigerwald

    2007-02-01T23:59:59.000Z

    499

    Table 7.3 Average Prices of Purchased Electricity, Natural Gas, and Steam, 2010;  

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

    3 Average Prices of Purchased Electricity, Natural Gas, and Steam, 2010; 3 Average Prices of Purchased Electricity, Natural Gas, and Steam, 2010; Level: National and Regional Data; Row: NAICS Codes; Column: Supplier Sources of Purchased Electricity, Natural Gas, and Steam; Unit: U.S. Dollars per Physical Units. Electricity Components Natural Gas Components Steam Components Electricity Natural Gas Steam Electricity from Sources Natural Gas from Sources Steam from Sources Electricity from Local Other than Natural Gas from Local Other than Steam from Local Other than NAICS Total Utility(b) Local Utility(c) Total Utility(b) Local Utility(c) Total Utility(b) Local Utility(c) Code(a) Subsector and Industry (kWh) (kWh) (kWh) (1000 cu ft) (1000 cu ft) (1000 cu ft) (million Btu)

    500

    "2012 Average Monthly Bill- Residential"  

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

    Residential" Residential" "(Data from forms EIA-861- schedules 4A-D, EIA-861S and EIA-861U)" "State","Number of Customers","Average Monthly Consumption (kWh)","Average Price (cents/kWh)","Average Monthly Bill (Dollar and cents)" "New England",6203726,634.13095,15.713593,99.644755 "Connecticut",1454651,730.85302,17.343298,126.75402 "Maine",703770,530.56349,14.658797,77.774225 "Massachusetts",2699141,627.15845,14.912724,93.52641 "New Hampshire",601697,614.81776,16.070168,98.802249 "Rhode Island",435448,597.34783,14.404061,86.042344 "Vermont",309019,565.03618,17.006075,96.090478 "Middle Atlantic",15727423,700.63673,15.272654,107.00582