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Note: This page contains sample records for the topic "average household expenditures" from the National Library of EnergyBeta (NLEBeta).
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1

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

2

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...

3

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.

4

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

5

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

6

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.

7

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.

8

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

9

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

10

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

11

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

12

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.

13

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.

14

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

15

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

16

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

17

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

18

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

19

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 ...

20

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

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

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

22

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.

23

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) ...

24

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

25

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

26

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

27

Table WF01. Average Consumer Prices and Expenditures for ...  

U.S. Energy Information Administration (EIA)

Heating Oil U.S. Average Consumption (gallons) 522.7 531.7 572.5 538.2 574.1 465.3 539.9 546.9 1.3 ... Wood 2,094 2,179 2,353 2,424 2,454 2,520 2,582 ...

28

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

29

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

30

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

31

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

32

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

33

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

34

Buildings Energy Data Book: 2.3 Residential Sector Expenditures  

Buildings Energy Data Book (EERE)

4 4 2005 Average Household Expenditures as Percent of Annual Income, by Census Region ($2010) Item Energy (1) Shelter (2) Food Telephone, water and other public services Household supplies, furnishings and equipment (3) Transportation (4) Healthcare Education Personal taxes (5) Average Annual Expenditures Average Annual Income Note(s): Source(s): 1) Average household energy expenditures are calculated from the Residential Energy Consumption Survey (RECS), while average expenditures for other categories are calculated from the Consumer Expenditure Survey (CE). RECS assumed total US households to be 111,090,617 in 2005, while the CE data is based on 117,356,000 "consumer units," which the Bureau of Labor Statistics defines to be financially independent persons or groups of people that use their incomes to make joint expenditure decisions, including all members of a

35

Buildings Energy Data Book: 2.3 Residential Sector Expenditures  

Buildings Energy Data Book (EERE)

3 3 2005 Average Household Expenditures, by Census Region ($2010) Item Energy (1) Shelter (2) Food Telephone, water and other public services Household supplies, furnishings and equipment (3) Transportation (4) Healthcare Education Personal taxes (5) Other expenditures Average Annual Income Note(s): Source(s): 1) Average household energy expenditures are calculated from the Residential Energy Consumption Survey (RECS), while average expenditures for other categories are calculated from the Consumer Expenditure Survey (CE). RECS assumed total US households to be 111,090,617 in 2005, while the CE data is based on 117,356,000 "consumer units," which the Bureau of Labor Statistics defines to be financially independent persons or groups of people that use their incomes to make joint expenditure decisions, including all members of a

36

WF01.Selected U.S. Average Consumer Prices* and Expenditures for ...  

U.S. Energy Information Administration (EIA)

Households 4,837 4,917 4,982 4,939 4,972 4,929 5,006 5,039 5,039 5,039 0.7 0.7 0.7 Electricity Northeast Consumption (kwh***) ...

37

,"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

38

,"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

39

Table CE3-1e. Electric Air-Conditioning Energy Expenditures in U.S ...  

U.S. Energy Information Administration (EIA)

Dollars per Household4,a Electric Air-Conditioning Expenditures per Household ... per Household4 2001 Cooling Degree-Days per Household Total U.S. Households ...

40

,"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

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

,"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

42

,"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

43

,"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"

44

,"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

45

,"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

46

Microsoft Word - Household Energy Use CA  

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

0 20 40 60 80 100 US PAC CA Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US PAC CA Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 2,000 4,000 6,000 8,000 10,000 12,000 US PAC CA Site Consumption kilowatthours $0 $250 $500 $750 $1,000 $1,250 $1,500 US PAC CA Expenditures dollars ELECTRICITY ONLY average per household ï‚· California households use 62 million Btu of energy per home, 31% less than the U.S. average. The lower than average site consumption results in households spending 30% less for energy than the U.S. average. ï‚· Average site electricity consumption in California homes is among the lowest in the nation, as the mild climate in much of the state leads to less reliance on

47

Microsoft Word - Household Energy Use CA  

Gasoline and Diesel Fuel Update (EIA)

0 20 40 60 80 100 US PAC CA Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US PAC CA Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 2,000 4,000 6,000 8,000 10,000 12,000 US PAC CA Site Consumption kilowatthours $0 $250 $500 $750 $1,000 $1,250 $1,500 US PAC CA Expenditures dollars ELECTRICITY ONLY average per household ï‚· California households use 62 million Btu of energy per home, 31% less than the U.S. average. The lower than average site consumption results in households spending 30% less for energy than the U.S. average. ï‚· Average site electricity consumption in California homes is among the lowest in the nation, as the mild climate in much of the state leads to less reliance on

48

A comparative analysis of energy demand and expenditures by minority and majority households within the context of a conditional demand system  

SciTech Connect

Analysis and evaluation of the impact that programs and policies have on energy consumption and expenditures are confounded by many intervening variables. A clear understanding of how these variables influence energy consumption patterns should be grounded in a rigorously developed framework. In this regard much is documented in the literature. However, an analysis of the comparative relationship between energy demand and variables which influence it among different socioeconomic groups has not been thoroughly explored with any theoretical rigor. It is proposed that differences in patterns of energy use between black, Hispanic, and majority households (where the household head is neither black nor Hispanic) are due to both structural and distribution differences. It is felt that the structural dissimilarities are primarily due to the dynamic nature in which energy consumption patterns evolve, with differences in changing housing patterns playing a significant role. For minorities, this implies a potential difference in the effect of policy and programs on economic welfare when compared to majority households.To test this hypothesis, separate conditional demand systems are estimated for majority, black, and Hispanic households. With the use of separate variance/covariance matrices, various parameter groups are tested for statistically significant differences.

Poyer, D.A.

1992-08-01T23:59:59.000Z

49

A comparative analysis of energy demand and expenditures by minority and majority households within the context of a conditional demand system  

SciTech Connect

Analysis and evaluation of the impact that programs and policies have on energy consumption and expenditures are confounded by many intervening variables. A clear understanding of how these variables influence energy consumption patterns should be grounded in a rigorously developed framework. In this regard much is documented in the literature. However, an analysis of the comparative relationship between energy demand and variables which influence it among different socioeconomic groups has not been thoroughly explored with any theoretical rigor. It is proposed that differences in patterns of energy use between black, Hispanic, and majority households (where the household head is neither black nor Hispanic) are due to both structural and distribution differences. It is felt that the structural dissimilarities are primarily due to the dynamic nature in which energy consumption patterns evolve, with differences in changing housing patterns playing a significant role. For minorities, this implies a potential difference in the effect of policy and programs on economic welfare when compared to majority households.To test this hypothesis, separate conditional demand systems are estimated for majority, black, and Hispanic households. With the use of separate variance/covariance matrices, various parameter groups are tested for statistically significant differences.

Poyer, D.A.

1992-01-01T23:59:59.000Z

50

Buildings Energy Data Book: 2.3 Residential Sector Expenditures  

Buildings Energy Data Book (EERE)

2 2 2005 Household Energy Expenditures, by Vintage ($2010) | Year | Prior to 1950 887 | 22% 1950 to 1969 771 | 22% 1970 to 1979 736 | 16% 1980 to 1989 741 | 16% 1990 to 1999 752 | 16% 2000 to 2005 777 | 9% | Average 780 | Total 100% Note(s): Source(s): 1.24 2,003 1) Energy expenditures per square foot were calculated using estimates of average heated floor space per household. According to the 2005 Residential Energy Consumption Survey (RECS), the average heated floor space per household in the U.S. was 1,618 square feet. Average total floor space, which includes garages, attics and unfinished basements, equaled 2,309 square feet. EIA, 2005 Residential Energy Consumption Survey, Oct. 2008 for 2005 expenditures; and EIA, Annual Energy Review 2010, Oct. 2011, Appendix D, p. 353 for price inflators.

51

Residential Energy Expenditures for Water Heating (2005) | OpenEI  

Open Energy Info (EERE)

Expenditures for Water Heating (2005) Expenditures for Water Heating (2005) Dataset Summary Description Provides total and average household expenditures on energy for water heating in the United States in 2005. The data was collected as part of the Residential Energy Consumption Survey (RECS). RECS is a national survey that collects residential energy-related data. The survey collected data from 4,381 households in housing units statistically selected to represent the 111.1 million housing units in the United States. Data were obtained from residential energy suppliers for each unit in the sample to produce the data. Source EIA Date Released September 01st, 2008 (6 years ago) Date Updated January 01st, 2009 (6 years ago) Keywords Energy Expenditures Residential Water Heating Data application/vnd.ms-excel icon 2005_Total.Expenditures.for_.Water_.Heating_EIA.Sep_.2008.xls (xls, 70.1 KiB)

52

Buildings Energy Data Book: 2.3 Residential Sector Expenditures  

Buildings Energy Data Book (EERE)

1 1 2005 Energy Expenditures per Household, by Housing Type and Square Footage ($2010) Per Household Single-Family 1.16 Detached 1.16 Attached 1.20 Multi-Family 1.66 2 to 4 units 1.90 5 or more units 1.53 Mobile Home 1.76 All Homes 1.12 Note(s): Source(s): 1) Energy expenditures per square foot were calculated using estimates of average heated floor space per household. According to the 2005 Residential Energy Consumption Survey (RECS), the average heated floor space per household in the U.S. was 1,618 square feet. Average total floor space, which includes garages, attics and unfinished basements, equaled 2,309 square feet. EIA, 2005 Residential Energy Consumption Survey, Oct. 2008, Table US-1 part1; and EIA, Annual Energy Review 2010, Oct. 2011, Appendix D, p. 353 for

53

Table CE3-3e. Electric Air-Conditioning Energy Expenditures in U.S ...  

U.S. Energy Information Administration (EIA)

Electric Air-Conditioning Energy Expenditures in U.S. Households by Household Income, 2001 RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli-

54

Table CE2-5.1u. Space-Heating Energy Consumption and Expenditures ...  

U.S. Energy Information Administration (EIA)

Space-Heating Energy Consumption and Expenditures by Household Member and Demographics, 2001 Household ... Total Households Using a Major Space-Heating

55

Lower residential energy use reduces home energy expenditures as ...  

U.S. Energy Information Administration (EIA)

Aggregate home energy expenditures by U.S. households fell $12 billion in 2012 ... households spent $1,945 on heating, cooling, appliances, electronics, and lighting ...

56

1997 Consumption and Expenditures Tables  

U.S. Energy Information Administration (EIA)

Table CE5-1e. Appliances1 Energy Expenditures in U.S. Households by Climate Zone, 1997 RSE Column Factor: Total Climate Zone2 RSE Row Factors Fewer than 2,000 CDD and --

57

1997 Consumption and Expenditures Tables  

U.S. Energy Information Administration (EIA)

Table CE4-1e. Water-Heating Energy Expenditures in U.S. Households by Climate Zone, 1997 RSE Column Factor: Total Climate Zone1 RSE Row Factors Fewer than 2,000 CDD ...

58

Residential energy-consumption survey: consumption and expenditures, April 1978-March 1979  

SciTech Connect

Tables present data on energy consumption and expenditures for US households during a 12-month period. The total amount of energy consumed by the residential sector from April 1978 through March 1979 is estimated to have been 10,563 trillion Btu with an average household consumption of 138 million Btu. Table 1 summarizes residential energy consumption for all fuels (totals and averages) as wells as total amounts consumed and expenditures for each of the major fuel types (natural gas, electricity, fuel oil, and liquid petroleum gas). Tables 2 and 3 give the number of households and the average energy prices, respectively, for each of the major fuel types. In Tables 4 to 9, totals and averages for both consumption and expenditures are given for each of the major fuels. The consumption of each fuel is given first for all households using the fuel. Then, households are divided into those that use the fuel as their main source of heat and those using the fuel for other purposes. Electricity data (Tables 5 to 7) are further broken down into households that use electricity for air conditioning and those not using it for this purpose. Limited data are also presented on households that use each of the major fuels for heating water. Each of the consumption tables is given for a variety of general household features, including: geographical, structural and physical, and demographic characteristics. Tables 10 to 18 present the same information for the subgroup of households living in single-family owner-occupied detached houses. The third set of tables (19 to 27) is limited to households that paid directly for all of the energy they used. Tables 28 to 36 provide variance estimates for the data.

Not Available

1980-07-01T23:59:59.000Z

59

Table CE5-5.1u. Appliances Energy Consumption and Expenditures by ...  

U.S. Energy Information Administration (EIA)

Table CE5-5.1u. Appliances1 Energy Consumption and Expenditures by Household Member and Demographics, 2001 Household Demographics RSE Column Factor:

60

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

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

Residential energy consumption and expenditures by end use for 1978, 1980, and 1981  

Science Conference Proceedings (OSTI)

The end-use estimates of the average household consumption and expenditures are statistical estimates based on the 1978, 1980, and 1981 Residential Enery Consumption Surveys (RECS) conducted by the Energy Information Administration (EIA) rather than on metered observations. The end-use estimates were obtained by developing a set of equations that predict the percentage of energy used for each broad end-use category. The equations were applied separately to each household and to each fuel. The resulting household end-use estimates were averaged to produce estimates of the average end-use consumption and expenditures on a national and regional basis. The accuracy and potential biases of these end-use estimates vary depending on the fuel type, on the year of the survey, and on the type of end use. The figures and tables presented show the amount and the type of energy cosumed, plus the cost of this energy. National averages are given as well as averages for various categories including region, size and age of dwelling, number of heating degree-days, and income. Some of the significant findings; energy trends by end use for all fuels used in the home for 1978, 1980, and 1981; and electricity consumption and expenditures and natural gas consumption and expenditures are discussed.

Johnson, M.

1984-12-01T23:59:59.000Z

62

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 ...

63

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 ...

64

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

65

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)

66

Table US1. Total Energy Consumption, Expenditures, and Intensities ...  

U.S. Energy Information Administration (EIA)

Part 1: Housing Unit Characteristics and Energy Usage Indicators Energy Consumption 2 Energy Expenditures 2 Total U.S. (quadrillion Btu) Per Household (Dollars) Per

67

Energy Spending and Vulnerable Households  

E-Print Network (OSTI)

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

Jamasb, Tooraj; Meier, Helena

2011-01-26T23:59:59.000Z

68

Residential Energy Consumption Survey: Consumption and expenditures, April 1984 through March 1985: Part 2, Regional data. [Contains glossary  

SciTech Connect

Included here are data at the Census region and division level on consumption of and expenditures for the major fuels used in residential households - electricity, natural gas, fuel oil/kerosene, and liquefied petroleum gas (LPG). Data are also presented on wood consumption. Section 1 of this report contains data on the average amount of energy consumed per household for space heating in 1984 and the corresponding expenditures. Sections 2 through 7 summarize the energy consumption and expenditure patterns. Appendices A through D contain information on how the survey was conducted, estimates of the size of the housing unit in square feet and the quality of the data. Procedures for calculating relative standard errors (RSE) are located in Appendix C, Quality of the Data. Procedures for estimating the end-use statistics are located in Appendix D. Census and weather maps, and related publications are located in Appendices E through G.

Not Available

1987-05-13T23:59:59.000Z

69

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

70

Table AP4. Total Expenditures for Home Appliances and Lighting by ...  

U.S. Energy Information Administration (EIA)

and Lighting Table AP4. Total Expenditures for Home Appliances and Lighting by Fuels Used, 2005 Billion Dollars U.S. Households (millions) Electricity

71

Table CE4-6.1u. Water-Heating Energy Consumption and Expenditures ...  

U.S. Energy Information Administration (EIA)

Table CE4-6.1u. Water-Heating Energy Consumption and Expenditures by Household Member and Usage Indicators, 2001 Usage Indicators RSE Column Factor:

72

Table WH5. Total Expenditures for Water Heating by Major Fuels ...  

U.S. Energy Information Administration (EIA)

Total Table WH5. Total Expenditures for Water Heating by Major Fuels Used, 2005 Billion Dollars Electricity Natural Gas Fuel Oil LPG U.S. Households

73

Table WH11. Expenditures Intensity by Main Water Heating Fuel Used ...  

U.S. Energy Information Administration (EIA)

Main Water Heating Fuel Used (Dollars/number of household members) Electricity Table WH11. Expenditures Intensity by Main Water Heating Fuel Used, 2005

74

Table SH5. Total Expenditures for Space Heating by Major Fuels ...  

U.S. Energy Information Administration (EIA)

Space Heating Fuel 4 (millions) Fuel Oil U.S. Households ... 2005 Residential Energy Consumption Survey: Energy Consumption and Expenditures Tables. Natural Gas

75

Table CE5-6.1u. Appliances Energy Consumption and Expenditures by ...  

U.S. Energy Information Administration (EIA)

Table CE5-6.1u. Appliances1 Energy Consumption and Expenditures by Household Member and Usage Indicators, 2001 Usage Indicators RSE Column Factor:

76

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

77

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 ...

78

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.

79

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

80

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 ...

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

82

Buildings Energy Data Book: 2.3 Residential Sector Expenditures  

Buildings Energy Data Book (EERE)

9 9 Average Annual Energy Expenditures per Household, by Year ($2010) Year 1980 1,991 1981 1,981 1982 2,058 1983 2,082 1984 2,067 1985 2,012 1986 1,898 1987 1,846 1988 1,849 1989 1,848 1990 1,785 1991 1,784 1992 1,729 1993 1,797 1994 1,772 1995 1,727 1996 1,800 1997 1,761 1998 1,676 1999 1,659 2000 1,824 2001 1,900 2002 1,830 2003 1,978 2004 2,018 2005 2,175 2006 2,184 2007 2,230 2008 2,347 2009 2,173 2010 2,201 2011 2,185 2012 2,123 2013 2,056 2014 2,032 2015 2,030 2016 2,007 2017 1,992 2018 1,982 2019 1,973 2020 1,963 2021 1,961 2022 1,964 2023 1,962 2024 1,959 2025 1,957 2026 1,959 2027 1,960 2028 1,953 2029 1,938 2030 1,932 2031 1,937 2032 1,946 2033 1,956 2034 1,967 2035 1,978 Source(s): Average Expenditure EIA, State Energy Data 2009: Prices and Expenditures, Jun. 2011 for 1980-2009; EIA, Annual Energy Outlook 2012 Early Release, Jan. 2012, Table A2, p. 3-

83

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

84

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

85

Expenditures on Children by Families | Data.gov  

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

Expenditures on Children by Families Expenditures on Children by Families Agriculture Community Menu DATA APPS EVENTS DEVELOPER STATISTICS COLLABORATE ABOUT Agriculture You are here Data.gov » Communities » Agriculture » Data Expenditures on Children by Families Dataset Summary Description This dataset provides expenditures on Children by Families provides estimates of the cost of raising children from birth through age 17 for major budgetary components. Tags {children,families,expenditures,cost,budget,household,income,single-parent,husband-wife} Dataset Ratings Overall 0 No votes yet Data Utility 0 No votes yet Usefulness 0 No votes yet Ease of Access 0 No votes yet Dataset Additional Information Last Updated 2012 Publisher Food and Nutrition Service, Department of Agriculture Contact Name Contact Email Mark.Lino@cnpp.usda.gov

86

Table CE3-10e. Electric Air-Conditioning Energy Expenditures in U ...  

U.S. Energy Information Administration (EIA)

Table CE3-10e. Electric Air-Conditioning Energy Expenditures in U.S. Households by Midwest Census Region, 2001 RSE Column Factor: Total U.S. Midwest Census Region

87

Chapter 4. Fuel Economy, Consumption and Expenditures  

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

4. Fuel Economy, Consumption, and Expenditures 4. Fuel Economy, Consumption, and Expenditures Chapter 4. Fuel Economy, Consumption, and Expenditures This chapter analyzes trends in fuel economy, fuel consumption, and fuel expenditures, using data unique to the Residential Transportation Energy Consumption Survey, as well as selected data from other sources. Analysis topics include the following: Following the oil supply and price disruptions caused by the Arab oil embargo of 1973-1974, motor gasoline price increases, the introduction of corporate average fuel economy standards, and environmental quality initiatives helped to spur major changes in vehicle technology. But have the many advances in vehicle technology resulted in measurable gains in the fuel economy of the residential vehicle fleet?

88

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 ...

89

State energy price and expenditure report 1984  

Science Conference Proceedings (OSTI)

The average price paid by US consumers for energy in 1984 was $8.43 per million Btu, down 0.5% from the 1983 average price of $8.47 per million Btu. While the average price changed very little, total expenditures rose 5% from $418 billion in 1983 to $438 billion in 1984 due to increased energy consumption. By energy source, prices showed the most change in petroleum and electricity: the average price paid for petroleum products fell from $7.79 per million Btu in 1983 to $7.62 per million Btu in 1984, and the average price paid for electricity increased from $18.62 per million Btu in 1983 to $19.29 per million Btu in 1984. Expenditures in 1984 hit record high levels for coal, natural gas, nuclear fuel, and electricity, but were 16% below the 1981 peak for petroleum.

Not Available

1986-12-04T23:59:59.000Z

90

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

91

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

92

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

93

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

94

State Energy Price and Expenditure Estimates  

U.S. Energy Information Administration (EIA)

2010 Price and Expenditure Summary Tables. Table E1. Primary Energy, Electricity, ... Ranked by State, 2010 Rank Prices Expenditures Expenditures per Person State

95

1997 Consumption and Expenditures Tables  

U.S. Energy Information Administration (EIA)

... per Household3 1997 Cooling Degree-Days per Household Total U.S. Households ..... 1,274 1,166 1,562 1,010 6.6 No/Don’t Use Air-Conditioning ...

96

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

97

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

98

Assumptions to the Annual Energy Outlook 2000 - Household Expenditures  

Gasoline and Diesel Fuel Update (EIA)

Commercial Sector Demand Module generates forecasts of commercial sector energy demand through 2020. The definition of the commercial sector is consistent with EIAÂ’s State Energy Data System (SEDS). That is, the commercial sector includes business establishments that are not engaged in transportation or in manufacturing or other types of industrial activity (e.g., agriculture, mining or construction). The bulk of commercial sector energy is consumed within buildings; however, street lights, pumps, bridges, and public services are also included if the establishment operating them is considered commercial. Since most of commercial energy consumption occurs in buildings, the commercial module relies on the data from the EIA Commercial Buildings Energy Consumption Survey (CBECS) for characterizing the commercial sector activity mix as well as the equipment stock and fuels consumed to provide end use services.12

99

U.S. household winter natural gas heating expenditures ...  

U.S. Energy Information Administration (EIA)

Comprehensive data summaries, comparisons, analysis, ... and 5% lower for electric ... variety of services—depending on factors such as their load pro ...

100

Household Energy Consumption and Expenditures 1993 -- Index Page  

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

Fax: (202) 586-0018 URL: http:www.eia.govemeurecs1d.html If you are having any technical problems with this site, please contact the EIA Webmaster at wmaster@eia.doe.gov...

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

Buildings Energy Data Book: 2.3 Residential Sector Expenditures  

Buildings Energy Data Book (EERE)

5 5 2005 Households and Energy Expenditures, by Income Level ($2010) Energy Expenditures by Household Income Households (millions) Household Less than $10,000 9.9 9% $10,000 to $14,999 8.5 8% $15,000 to $19,999 8.4 8% $20,000 to $29,999 15.1 14% $30,000 to $39,999 13.6 12% $40,000 to $49,999 11.0 10% $50,000 to $74,999 19.8 18% $75,000 to $99,999 10.6 10% $100,000 or more 14.2 13% Total 111.1 100% Note(s): Source(s): 7% 1) See Table 2.3.15 for more on energy burdens. 2) A household is defined as a family, an individual, or a group of up to nine unrelated individuals occupying the same housing unit. EIA, 2005 Residential Energy Consumption Survey, Oct. 2008, Table US-1 part 2; and EIA, Annual Energy Review 2010, Oct. 2011, Appendix D, p. 353 for price inflators. 2,431 847 3% 2,774 909 3% 1,995

102

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 ...

103

Energy consumption and expenditure projections by population group on the basis on the annual energy outlook 2000 forecast.  

SciTech Connect

The changes in the patterns of energy use and expenditures by population group are analyzed by using the 1993 and 1997 Residential Energy Consumption Surveys. Historically, these patterns have differed among non-Hispanic White households, non-Hispanic Black households, and Hispanic households. Patterns of energy use and expenditures are influenced by geographic and metropolitan location, the composition of housing stock, economic and demographic status, and the composition of energy use by end-use category. As a consequence, as energy-related factors change across groups, patterns of energy use and expenditures also change. Over time, with changes in the composition of these factors by population group and their variable influences on energy use, the impact on energy use and expenditures has varied across these population groups.

Poyer, D. A.; Decision and Information Sciences

2001-05-31T23:59:59.000Z

104

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

105

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

106

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

107

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

108

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

109

State energy price and expenditure report, 1986  

SciTech Connect

The average price paid for energy in the United States in 1986 was $7.19 per million Btu, down significantly from the 1985 average of $8.42 per million Btu. While total energy consumption increased slightly to 74.3 quadrillion Btu from 1985 to 1986, expenditures fell from $445 billion to $381 billion. Energy expenditures per capita in 1986 were $1578, down significantly from the 1985 rate. In 1986, consumers used only 94 percent as much energy per person as they had in 1970, but they spent 3.9 times as much money per person on energy as they had in 1970. By state, energy expenditures per capita in 1986 ranged from the lowest rate of $1277 in New York to the highest of $3108 in Alaska. Of the major energy sources, electricity registered the highest price per million Btu ($19.00), followed by petroleum ($5.63), natural gas ($3.97), coal ($1.62), and nuclear fuel ($0.70). The price of electricity is relatively high because of significant costs for converting energy from various forms (e.g., fossil fuels, nuclear fuel, hydroelectric energy, and geothermal energy) into electricity, and additional, somewhat smaller costs for transmitting and distributing electricity to end users. In addition, electricity is a premium form of energy because of its flexibility and clean nature at energy consumers' sites.

Not Available

1988-10-28T23:59:59.000Z

110

1997 Consumption and Expenditures Tables  

U.S. Energy Information Administration (EIA)

5HVLGHQWLDO (QHUJ\\ &RQVXPSWLRQ 6XUYH\\V 1997 Consumption and Expenditures Tables Appliances Consumption Tables (17 pages, 60 kb) Contents Pages CE5-1c.

111

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...

112

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...

113

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

114

Energy Expenditures | OpenEI  

Open Energy Info (EERE)

Expenditures Expenditures Dataset Summary Description The State Energy Data System (SEDS) is compiled by the U.S. Energy Information Administration's (EIA); it is a comprehensive database of energy statistics by state (and includes totals for the entire US). SEDS includes estimates of energy production, consumption, prices, and expenditures broken down by energy source and sector. Annual estimates are available from 1960 - 2009 for production and consumption estimates and from 1970 - 2009 for price and expenditure estimates. Source EIA Date Released June 30th, 2011 (3 years ago) Date Updated Unknown Keywords EIA Energy Consumption Energy Expenditures energy prices energy production SEDS State energy data States US Data text/csv icon Complete SEDS dataset as csv (may be too big for Excel) (csv, 40.6 MiB)

115

Commercial Buildings Energy Consumption and Expenditures 1992...  

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

1992 Consumption and Expenditures 1992 Consumption & Expenditures Overview Full Report Tables National estimates of electricity, natural gas, fuel oil, and district heat...

116

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

117

1997 Consumption and Expenditures Tables  

U.S. Energy Information Administration (EIA)

Appliances ... include the small number of households where the fuel for central air-conditioning equipment was something other than electricity; ...

118

Buildings Energy Data Book: 1.2 Building Sector Expenditures  

Buildings Energy Data Book (EERE)

4 4 FY 2007 Federal Buildings Energy Prices and Expenditures, by Fuel Type ($2010) Fuel Type Electricity (1) Natural Gas Fuel Oil Coal Purchased Steam LPG/Propane Other Average Total Note(s): Source(s): 17.05 6028.63 Prices and expenditures are for Goal-Subject buildings. 1) $0.0776/kWh. 2) Energy used in Goal-Subject buildings in FY 2007 accounted for 33.8% of the total Federal energy bill. DOE/FEMP, Annual Report to Congress on FEMP FY 2007, Jan. 2010, Table A-4, p. 93 for prices and expenditures, and Table A-9, p. 97 for total energy expenditures; EIA, Annual Energy Review 2010, Oct. 2011, Appendix D, p. 353 for price deflators. 24.30 318.35 17.06 43.87 16.19 36.64 9.37 1138.21 15.25 419.30 3.62 62.87 Average Fuel Prices Total Expenditures ($/million BTU) ($ million) (2) 23.68

119

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

120

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

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

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...

122

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

123

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

124

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

125

Residential Buildings Historical Publications reports, data and...  

Gasoline and Diesel Fuel Update (EIA)

3 Average LPG Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per Household Households...

126

Residential Buildings Historical Publications reports, data and...  

Annual Energy Outlook 2012 (EIA)

7 Average LPG Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per Household Households...

127

Residential Buildings Historical Publications reports, data and...  

Annual Energy Outlook 2012 (EIA)

0 Average LPG Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per Household Households...

128

Residential Buildings Historical Publications reports, data and...  

Gasoline and Diesel Fuel Update (EIA)

2 Average LPG Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per Household Households...

129

Residential Energy Consumption Survey: Consumption and expenditures, April 1984 through March 1985: Part 1, National data  

Science Conference Proceedings (OSTI)

This report presents data collected in the 1984 Residential Energy Consumption Survey (RECS) conducted by the Energy Information Administration (EIA). The 1984 RECS was the sixth national survey of US households and their energy suppliers. The purpose of these surveys is to provide baseline information on how households use energy. Households in all types of housing units - single family homes (including townhouses), apartments, and mobile homes - were chosen to participate. Data from the surveys are available to the public in published reports such as this one and on public-use data tapes. The report presents data on the US consumption and expenditures for residential use of these ''major fuels'' - natural gas, electricity, fuel oil, kerosene, and liquefied petroleum gas (LPG) - from April 1984 through March 1985. These data are presented in tables in the Detailed Statistics section of this report. Except for kerosene and wood fuel, the consumption and expenditures data are based on actual household bills obtained, with the permission of the household, from the companies supplying energy to the household. Purchases of kerosene are based on respondent reports because records of ''cash and carry'' purchases of kerosene for individual households are usually unavailable. Data on the consumption of wood fuel (Table 27) covers the 12-month period ending November 1984 and are based on respondent recall of the amount of wood burned during the 12-month period. Both the kerosene and wood consumption data are subject to memory errors and other reporting errors. This report does not cover household use of motor fuel, which is reported separately.

Not Available

1987-03-04T23:59:59.000Z

130

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

131

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.

132

SEDS CSV File Documentation: Price and Expenditure  

Gasoline and Diesel Fuel Update (EIA)

Prices and Expenditures Prices and Expenditures The State Energy Data System (SEDS) comma-separated value (CSV) files contain the price and expenditure estimates shown in the tables located on the SEDS website. There are three files that contain estimates for all states and years. Prices contains the price estimates for all states and Expenditures contains the expenditure estimates for all states. The third file, Adjusted Consumption for Expenditure Calculations contains adjusted consumption estimates used in calculating expenditures (see Appendix E below). Zip files are also available for the large data files. In addition, there is a CSV file for each state, named with the two-letter U.S. Postal Code listed in Appendix A, as well as a file for the United States.

133

OpenEI - Energy Expenditures  

Open Energy Info (EERE)

State Energy Data State Energy Data System (SEDS) Complete Dataset through 2009 http://en.openei.org/datasets/node/883 The State Energy Data System (SEDS) is compiled by the U.S. Energy Information Administration's (EIA); it is a comprehensive database of energy statistics by state (and includes totals for the entire US). SEDS includes estimates of energy production, consumption, prices, and expenditures broken down by energy source and sector. Annual estimates are available from 1960 - 2009 for production and consumption estimates and from 1970 - 2009 for price and expenditure estimates.

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Type of

134

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

135

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

136

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

137

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 *...

138

State energy price and expenditure report 1994  

SciTech Connect

The State Energy Price and Expenditure Report (SEPER) presents energy price and expenditure estimates individually for the 50 States and the District of Columbia and in aggregate for the United States. The price and expenditure estimates developed in the State Energy Price and Expenditure Data System (SEPEDS) are provided by energy source and economic sector and are published for the years 1970 through 1994. Consumption estimates used to calculate expenditures and the documentation for those estimates are taken from the State Energy Data Report 1994, Consumption Estimates (SEDR), published in October 1996. Expenditures are calculated by multiplying the price estimates by the consumption estimates, which are adjusted to remove process fuel; intermediate petroleum products; and other consumption that has no direct fuel costs, i.e., hydroelectric, geothermal, wind, solar, and photovoltaic energy sources. Documentation is included describing the development of price estimates, data sources, and calculation methods. 316 tabs.

NONE

1997-06-01T23:59:59.000Z

139

State energy price and expenditure report 1992  

SciTech Connect

The State Energy Price and Expenditure Report (SEPER) presents energy price and expenditure estimates individually for the 50 States and the District of Columbia and in aggregate for the United States. The price and expenditure estimates are provided by energy source and economic sector and are published for the years 1970, 1980, and 1985 through 1992. Data for all years, 1970 through 1992, are available on personal computer diskettes.

1994-12-01T23:59:59.000Z

140

State energy price and expenditure report 1991  

SciTech Connect

The State Energy Price and Expenditure Report (SEPER) presents energy price and expenditure estimates individually for the 50 States and the District of Columbia and in aggregate for the United States. The price and expenditure estimates are provided by energy source and economic sector and are published for the years 1970, 1975, 1980, and 1985 through 1991. Data for all years, 1970 through 1991, are available on personal computer diskettes. Documentation in Appendix A describes how the price estimates are developed, including sources of data, methods of estimation, and conversion factors applied. This report is an update of the State Energy Price and Expenditure Report 1990, published in September 1992.

1993-09-01T23:59:59.000Z

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

2005 RECS Consumption and Expenditures Detailed Tables  

U.S. Energy Information Administration (EIA)

Detailed Consumption and Expenditures (C&E) tables containing Space Heating, Air-Conditioning, Water Heating, and Appliance residential energy data are now available.

142

Commercial Buildings Energy Consumption and Expenditures 1992  

Annual Energy Outlook 2012 (EIA)

(92) Distribution Category UC-950 Commercial Buildings Energy Consumption and Expenditures 1992 April 1995 Contacts The Energy Information Administration (EIA) prepared this...

143

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

144

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

145

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...

146

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

147

State energy price and expenditure report, 1995  

SciTech Connect

The State Energy Price and Expenditure Report (SEPER) presents energy price and expenditure estimates individually for the 50 States and the District of Columbia and in aggregate for the US. The estimates developed in the State Energy Price and Expenditure Data System (SEPEDS) are provided by energy source and economic sector and are published for the years 1970 through 1995. Data for all years are available on a CD-ROM and via Internet. Consumption estimates used to calculate expenditures and the documentation for those estimates are taken from the State Energy Data Report 1995, Consumption Estimates (SEDR), published in December 1997. Expenditures are calculated by multiplying the price estimates by the consumption estimates, which are adjusted to remove process fuel; intermediate petroleum products; and other consumption that has no direct fuel costs, i.e., hydroelectric, geothermal, wind, solar, and photovoltaic energy sources.

1998-08-01T23:59:59.000Z

148

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

149

Buildings Energy Data Book: 3.3 Commercial Sector Expenditures  

Buildings Energy Data Book (EERE)

Buildings Energy Consumption and Expenditures: Consumption and Expenditures Tables, Table C4; and EIA, Annual Energy Review 2010, Aug. 2011, Appendix D, p. 353 for price deflators...

150

Table F18: Coal Price and Expenditure Estimates and Imports ...  

U.S. Energy Information Administration (EIA)

Table F18: Coal Price and Expenditure Estimates and Imports and Exports of Coal Coke, 2011 State Coal Coal Coke Prices Expenditures Prices ...

151

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

152

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

153

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....

154

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...

155

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...

156

Residential Energy Consumption and Expenditures -- Detailed Tables ...  

U.S. Energy Information Administration (EIA)

Categories of Data in the Table Rows. The row categories classify data by specific features of the households. The following, listed in alphabetical order, are ...

157

Short-Term Energy Outlook - U.S. Energy Information Administration ...  

U.S. Energy Information Administration (EIA)

Although EIA expects average expenditures for households that heat with natural gas will be significantly higher than last winter, ...

158

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

159

State energy price and expenditure report 1993  

SciTech Connect

The State Energy Price and Expenditure Report (SEPER) presents energy price and expenditure estimates individually for the 50 states and the District of Columbia and in aggregate for the US. The five economic sectors used in SEPER correspond to those used in SEDR and are residential, commercial, industrial, transportation, and electric utility. Documentation in appendices describe how the price estimates are developed, provide conversion factors for measures used in the energy analysis, and include a glossary. 65 tabs.

1995-12-01T23:59:59.000Z

160

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

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

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

162

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

163

Residential Buildings Historical Publications reports, data and...  

Gasoline and Diesel Fuel Update (EIA)

0 Average Electricity Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per Household...

164

Residential Buildings Historical Publications reports, data and...  

Gasoline and Diesel Fuel Update (EIA)

1 Average Natural Gas Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per Household...

165

Residential Buildings Historical Publications reports, data and...  

Gasoline and Diesel Fuel Update (EIA)

2 Average Electricity Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per Household...

166

Residential Buildings Historical Publications reports, data and...  

Gasoline and Diesel Fuel Update (EIA)

4 Average Electricity Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per Household...

167

Residential Buildings Historical Publications reports, data and...  

Annual Energy Outlook 2012 (EIA)

1 Average Electricity Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per Household...

168

Residential Buildings Historical Publications reports, data and...  

Annual Energy Outlook 2012 (EIA)

3 Average Electricity Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per Household...

169

Residential Buildings Historical Publications reports, data and...  

Gasoline and Diesel Fuel Update (EIA)

7 Average Electricity Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per Household...

170

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:...

171

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)

172

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

173

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

174

Table US15. Average Expenditures by Energy End Uses, 2005 Dollars ...  

U.S. Energy Information Administration (EIA)

Climate Zone 1 Less than 2,000 CDD and--Greater than 7,000 HDD..... 10.9 1,982 839 90 300 145 671 5,500 to 7,000 HDD ...

175

"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...

176

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...

177

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.

178

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 ...

179

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

U.S. Energy Information Administration (EIA)

Rural or Open Country ..... 16.5 16.0 30.0 105 56 102 38 1,554 0.83 1,513 564 3.2 Climate Zone(4) Under 2,000 CDD and Over 7,000 HDD ..... 9.3 8.4 17 .9 136 64 123 47 ...

180

The Dynamics of Household Travel Time Expenditures and Car Ownership Decisions  

E-Print Network (OSTI)

or more of the others (say, car usage as a function of carnumberof workers, explains car usage, but not car ownership;locations imply higher car usage in terms of travel times

Golob, Thomas F.

1990-01-01T23:59:59.000Z

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

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

U.S. Energy Information Administration (EIA)

Appliances, 2 Electronics, and Lighting : Natural Gas: Elec-tricity 3: Fuel Oil 4: LPG 5: Total: Electricity 3: Natural Gas: Elec-tricity 3: Fuel Oil ...

182

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

U.S. Energy Information Administration (EIA)

Air Conditioning: Water Heating: Appliances, 2 Electronics, and Lighting : Natural Gas: Elec-tricity 3: Fuel Oil 4: LPG 5: Total: Electricity 3: Natural Gas: Elec ...

183

Table 4. LPG Consumption and Expenditures in U.S. Households by ...  

U.S. Energy Information Administration (EIA)

Notes: • To obtain the RSE percentage for any table cell, multiply the corresponding column and row factors. • Because of rounding, data may not sum to totals.

184

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

U.S. Energy Information Administration (EIA)

Notes: • To obtain the RSE percentage for any table cell, multiply the corresponding column and row factors. • Because of rounding, data may ...

185

Table 5. Kerosene Consumption and Expenditures in U.S. Households ...  

U.S. Energy Information Administration (EIA)

Notes: • To obtain the RSE percentage for any table cell, multiply the corresponding column and row factors. • Because of rounding, data may not sum to totals.

186

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

U.S. Energy Information Administration (EIA)

1 A small amount of fuel oil used for appliances is included in "Fuel Oil" under "All Uses." NF = No applicable RSE row factor.

187

Table 5. Kerosene Consumption and Expenditures in U.S. Households ...  

U.S. Energy Information Administration (EIA)

1 A small amount of kerosene used for water heating and appliances is included in "Kerosene" under "All Uses." (*) ...

188

U.S. household winter natural gas heating expenditures expected to ...  

U.S. Energy Information Administration (EIA)

LDCs typically buy the natural gas commodity using a variety of services—depending on factors such as their load profile/customer mix, geographic location, ...

189

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

U.S. Energy Information Administration (EIA)

Short-Term Energy Outlook › Annual Energy Outlook ... 1984: 20.66: 4.62: 8.51: 2.00: 35.79: 7.06: 6.63: 6.44: 1.09.58: 14.74: 2.31: 36.36.54: 39.21: 1987: 18.05: 5 ...

190

Annual Capital Expenditures Survey | Data.gov  

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

Annual Capital Expenditures Survey Annual Capital Expenditures Survey BusinessUSA Data/Tools Apps Challenges Let's Talk BusinessUSA You are here Data.gov » Communities » BusinessUSA » Data Annual Capital Expenditures Survey Dataset Summary Description Provides national estimates of investment in new and used buildings and other structures, machinery, and equipment by U.S. nonfarm businesses with and without employees. Data are published by industry for companies with employees for NAICS 3-digit and selected 4-digit industries. Data on the amount of business expenditures for new plant and equipment and measures of the stock of existing facilities are critical to evaluate productivity growth, the ability of U.S. business to compete with foreign business, changes in industrial capacity, and measures of overall economic performance. In addition, ACES data provide industry analysts with capital expenditure data for market analysis, economic forecasting, identifying business opportunities and developing new and strategic plans. The ACES is an integral part of the Federal Government's effort to improve and supplement ongoing statistical programs. Private companies and organizations,, educators and students, and economic researchers use the survey results for analyzing and conducting impact evaluations on past and current economic performance, short-term economic forecasts, productivity, long-term economic growth, tax policy, capacity utilization, business fixed capital stocks and capital formation, domestic and international competitiveness trade policy, market research, and financial analysis.

191

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...

192

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...

193

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...

194

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

195

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

196

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

197

A Review and Discussion of the Literature on Travel Time and Money Expenditures  

E-Print Network (OSTI)

Expenditure of Time and Money on Travel. Transport RoadExpenditure of Time and Money on Travel. Transp. Research6 I.2.4.2. Travel Money Expenditure …………………………………………………………..

Chen, Cynthia; Mokhtarian, Patricia

2008-01-01T23:59:59.000Z

198

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

199

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.

200

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

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

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

202

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

203

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

204

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

205

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

206

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

207

1997 Consumption and Expenditures-Detailed Data Tables  

U.S. Energy Information Administration (EIA)

1997 Resdiential Energy Consumption Survey(RECS)-1997 Consumption and Expenditures-1997 Detailed Tables, Energy Information Administration

208

U.S. Uranium Expenditures, 2003-2010  

U.S. Energy Information Administration (EIA)

Domestic Uranium Production Report presents information Operating Status of U.S. Uranium Expenditures, 2003-2005

209

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...

210

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

211

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

212

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

213

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

214

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.

215

wf01 - Energy_Expenditures.xlsx  

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

6-07 6-07 07-08 08-09 09-10 10-11 11-12 12-13 13-14 % Change Natural Gas Northeast Consumption (mcf**) 73.6 74.2 79.6 74.7 79.7 65.6 75.2 77.5 3.1 Price ($/mcf) 14.74 15.18 15.83 13.31 12.66 12.23 11.75 13.38 13.8 Expenditures ($) 1,085 1,127 1,260 994 1,010 802 883 1,036 17.3 Midwest Consumption (mcf) 74.5 78.2 80.8 78.6 80.1 65.4 77.5 77.9 0.5 Price ($/mcf) 11.06 11.40 11.47 9.44 9.23 8.96 8.23 9.15 11.2 Expenditures ($) 824 892 927 742 740 586 638 713 11.8 South Consumption (mcf) 45.3 44.8 47.0 53.4 49.5 41.1 46.6 47.5 1.9 Price ($/mcf) 13.57 14.19 14.08 11.52 11.03 11.47 10.69 11.78 10.3 Expenditures ($) 615 635 661 615 546 472 498 560 12.4 West Consumption (mcf) 46.4 48.1 46.2 47.7 47.2 47.6 46.9 46.5 -0.8 Price ($/mcf) 11.20 11.31 10.86 9.91 9.67 9.38 9.15 9.90 8.1 Expenditures ($) 520 544 502 473 457 447 429

216

Buildings Energy Data Book: 3.3 Commercial Sector Expenditures  

Buildings Energy Data Book (EERE)

5 5 2015 Commercial Energy End-Use Expenditure Splits, by Fuel Type ($2010 Billion) (1) Natural Petroleum Gas Distil. Resid. LPG Oth(2) Total Coal (3) Electricity Total Percent Lighting 28.4 28.4 16.3% Space Heating 14.6 2.9 1.3 0.1 4.3 0.1 4.7 23.7 13.6% Ventilation 15.1 15.1 8.6% Space Cooling 0.3 14.2 14.5 8.3% Refrigeration 9.9 9.9 5.7% Electronics 8.8 8.8 5.1% Water Heating 4.1 0.7 0.7 2.5 7.3 4.2% Computers 5.3 5.3 3.0% Cooking 1.7 0.6 2.3 1.3% Other (4) 2.9 0.3 3.7 1.4 5.4 22.8 31.1 17.8% Adjust to SEDS (5) 5.8 4.5 4.5 17.7 28.1 16.1% Total 29.3 8.4 1.3 3.7 1.5 14.9 0.1 130.0 174.5 100% Note(s): Source(s): 1) Expenditures include coal and exclude wood. 2) Includes kerosene space heating ($0.1 billion) and motor gasoline other uses ($1.4 billion). 3) Coal average price is from AEO 2012 Early Release, all users price. 4) Includes service station equipment, ATMs, medical equipment,

217

Buildings Energy Data Book: 3.3 Commercial Sector Expenditures  

Buildings Energy Data Book (EERE)

8 8 Average Annual Energy Expenditures per Square Foot of Commercial Floorspace, by Year ($2010) Year $/SF 1980 (1) 2.12 1981 2.22 (2) 1982 2.24 1983 2.21 1984 2.25 1985 2.20 1986 2.06 1987 2.00 1988 1.99 1989 2.01 1990 1.98 1991 1.92 1992 1.86 1993 1.96 1994 2.05 1995 2.12 1996 2.10 1997 2.08 1998 1.97 1999 1.88 2000 2.06 2001 2.20 2002 2.04 2003 2.13 2004 2.16 2005 2.30 2006 2.36 2007 2.35 2008 1.71 2009 2.43 2010 2.44 2011 2.44 2012 2.35 2013 2.28 2014 2.27 2015 2.29 2016 2.29 2017 2.28 2018 2.29 2019 2.29 2020 2.29 2021 2.31 2022 2.32 2023 2.32 2024 2.32 2025 2.32 2026 2.32 2027 2.33 2028 2.32 2029 2.31 2030 2.31 2031 2.32 2032 2.35 2033 2.37 2034 2.39 2035 2.42 Note(s): Source(s): EIA, State Energy Data Prices and Expenditures Database, June 2011 for 1980-2009; EIA, Annual Energy Outlook 2012 Early Release, Jan. 2012, Summary Reference Case Tables, Table A2, p. 3-5 and Table A5, p. 11-12 for consumption, Table A3, p. 6-8 for prices for 2008-2035; EIA, Annual Energy Review

218

Buildings Energy Data Book: 3.3 Commercial Sector Expenditures  

Buildings Energy Data Book (EERE)

4 4 2010 Commercial Energy End-Use Expenditure Splits, by Fuel Type ($2010 Billion) (1) Natural Petroleum Gas Distil. Resid. LPG Oth(2) Total Coal (3) Electricity Total Percent Lighting 35.4 35.4 19.7% Space Heating 15.0 2.9 0.9 0.1 3.9 0.1 8.5 27.5 15.3% Space Cooling 0.4 25.0 25.3 14.1% Ventilation 15.9 15.9 8.9% Refrigeration 11.6 11.6 6.5% Water Heating 4.0 0.6 0.6 2.7 7.3 4.1% Electronics 7.8 7.8 4.3% Computers 6.3 6.3 3.5% Cooking 1.6 0.7 2.3 1.3% Other (4) 2.7 0.3 3.3 1.2 4.8 20.4 28.0 15.6% Adjust to SEDS (5) 6.2 5.2 5.2 0.6 12.0 6.7% Total 29.9 9.0 0.9 3.3 1.3 14.5 0.1 134.8 179.4 100% Note(s): Source(s): 1) Expenditures include coal and exclude wood. 2) Includes kerosene space heating ($0.1 billion) and motor gasoline other uses ($1.2 billion). 3) Coal average price is from AEO 2012 Early Release, all users price. 4) Includes service station equipment, ATMs, medical equipment,

219

Buildings Energy Data Book: 3.3 Commercial Sector Expenditures  

Buildings Energy Data Book (EERE)

6 6 2025 Commercial Energy End-Use Expenditure Splits, by Fuel Type ($2010 Billion) (1) Natural Petroleum Gas Distil. Resid. LPG Oth(2) Total Coal (3) Electricity Total Percent Lighting 30.1 30.1 15.2% Space Heating 17.1 2.8 1.5 0.1 4.4 0.2 4.5 26.1 13.3% Electronics 11.2 11.2 5.7% Space Cooling 0.3 14.3 14.6 7.4% Water Heating 5.2 0.8 0.8 2.5 8.5 4.3% Computers 5.5 5.5 2.8% Refrigeration 9.4 9.4 4.8% Ventilation 16.6 16.6 8.4% Cooking 2.1 0.6 2.7 1.4% Other (4) 4.8 0.3 4.3 1.7 6.3 31.2 42.3 21.5% Adjust to SEDS (5) 5.9 4.9 4.9 19.2 30.0 15.2% Total 35.5 8.9 1.5 4.3 1.9 16.5 0.2 145.0 197.1 100% Note(s): Source(s): 1) Expenditures include coal and exclude wood. 2) Includes kerosene space heating ($0.1 billion) and motor gasoline other uses ($1.7 billion). 3) Coal average price is from AEO 2011 Early Release, all users price. 4) Includes service station equipment, ATMs, medical equipment,

220

Buildings Energy Data Book: 3.3 Commercial Sector Expenditures  

Buildings Energy Data Book (EERE)

7 7 2035 Commercial Energy End-Use Expenditure Splits, by Fuel Type ($2010 Billion) (1) Natural Petroleum Gas Distil. Resid. LPG Oth(2) Total Coal (3) Electricity Total Percent Lighting 32.3 32.3 14.4% Space Heating 19.0 2.7 1.6 0.2 4.5 0.2 4.6 28.2 12.5% Water Heating 6.3 1.0 1.0 18.1 25.4 11.3% Space Cooling 0.4 15.1 15.5 6.9% Electronics 13.0 13.0 5.8% Refrigeration 10.0 10.0 4.4% Computers 6.0 6.0 2.7% Cooking 2.6 0.6 3.2 1.4% Ventilation 2.4 2.4 1.1% Other (4) 9.3 0.4 4.9 2.0 7.2 40.9 57.5 25.5% Adjust to SEDS (5) 4.6 5.3 5.3 21.7 31.6 14.0% Total 42.2 9.4 1.6 4.9 2.2 18.0 0.2 164.8 225.1 100% Note(s): Source(s): 1) Expenditures include coal and exclude wood. 2) Includes kerosene space heating ($0.2 billion) and motor gasoline other uses ($2.0 billion). 3) Coal average price is from AEO 2012 Early Release, all users price. 4) Includes service station equipment, ATMs, medical equipment,

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

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

222

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

223

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

224

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

225

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

226

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

227

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

228

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

229

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

230

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

231

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

232

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

233

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

234

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

235

Comparative analysis of energy data bases for household residential and transportation energy use  

SciTech Connect

Survey data bases covering household residential and transportation energy use were reviewed from the perspective of energy policy analysts and data base users. Twenty-three surveys, taken from 1972 to 1985, collected information on household energy consumption and expenditures, energy-using capital stock, and conservation activities. Ten of the surveys covered residential energy use only, including that for space heating and cooling, cooking, water heating, and appliances. Six surveys covered energy use only for household travel in personal vehicles. Seven surveys included data on both of these household energy sectors. Complete energy use data for a household in one year can be estimated only for 1983, using two surveys (one residential and one transportation) taken in the same households. The last nine surveys of the 23 were recent (1983--1985). Review of those nine was based on published materials only. The large-scale surveys generally had less-comprehensive data, while the comprehensive surveys were based on small samples. The surveys were timely and useful for analyzing four types of energy policies: economic regulation, environmental regulation, federal energy production, and direct regulation of energy consumption or production. Future surveys of energy use, such as those of residential energy consumption, should try to link their energy-use questions to large surveys, such as the American Housing Survey, to allow more accurate analysis of comparative impacts of energy policies among population categories of interest (e.g., minority/majority, metropolitan/nonmetropolitan area, census regions, and income class). 78 refs., 9 figs., 29 tabs.

Teotia, A.; Klein, Y.; LaBelle, S.

1988-11-01T23:59:59.000Z

236

Table 1.5 Energy Consumption, Expenditures, and Emissions ...  

U.S. Energy Information Administration (EIA)

1 Expenditures include taxes where data are available. 5 In chained (2005) dollars. See "Chained Dollars" in Glossary. 2 Carbon dioxide emissions from energy consumption.

237

Table 2.10 Commercial Buildings Energy Consumption and Expenditure ...  

U.S. Energy Information Administration (EIA)

Table 2.10 Commercial Buildings Energy Consumption and Expenditure Indicators, Selected Years, 1979-2003: Energy Source and Year: Building Characteristics

238

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

239

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

240

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

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

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...

242

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

243

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

244

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

245

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

246

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

247

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

248

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

249

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

250

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

251

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

252

U.S. Department of Energy, Energy Information Administration (EIA  

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

A2 - Average per Households","Table A2. U.S. Per Household Vehicle-Miles Traveled, Vehicle Fuel Consumption and Expenditures, 2001" A2 - Average per Households","Table A2. U.S. Per Household Vehicle-Miles Traveled, Vehicle Fuel Consumption and Expenditures, 2001" "Std Errors for A2","Relative Standard Errors for Table A2. U.S. Per Household Vehicle-Miles Traveled, Vehicle Fuel Consumption and Expenditures, 2001 (Percent)" "N Cells for A2","Number of Sample Cases Contributing to Estimates in Table A2. U.S. Per Household Vehicle-Miles Traveled, Vehicle Fuel Consumption and Expenditures, 2001" " Page A-1 of A-N" "Table A2. U.S. Per Household Vehicle-Miles Traveled, Vehicle Fuel Consumption and Expenditures, 2001" "2001 Household Characteristics","Number of Households with Vehicles (million)","Average per Household with Vehicles"

253

EXPENDITURES General Fund Expenditures-2.0 % Page 12 NON-GENERAL FUND REVENUES  

E-Print Network (OSTI)

Key to revenue trend indicators: ?NEUTRAL ? = Variance of-1 % to +2 % compared to projections. ?POSITIVE ? = Positive variance of>+2 % compared to projections. ?WARNING ? = Negative variance of-1 % to-4 % compared to projections. ?NEGATIVE ? = Negative variance of>-4 % compared to projections. 1 First Quarter 2013- May 2013CITY FINANCIAL OVERVIEW EXECUTIVE SUMMARY Total General Fund revenue receipts for the first quarter of 2013, in the amount of $4,175,309, are above the projection by $172,955, or 4.3%. Total General Fund expenditures, in the amount of $4,508,707, are below the projection by $92,764, or 2.0%. Street Fund revenue receipts for the first quarter of 2013, including transfers in, total $511,302 and are $3,654, or 0.7%, above the projection. Street Fund expenditures, including transfers out, total $460,168 and are $19,734, or 4.1%, below the projection. Surface Water Utility Fund (SWM) revenue receipts for the first quarter of 2013 totaling $114,495 are $42,761, or 59.6%, above the projection. SWM expenditures total $691,401 and are $90,757, or 15.1%, above the projection. Real Estate Excise Tax (REET) revenue receipts for the first quarter of 2013 totaling $231,011 are $7,274, or 3.3%, ahead of the projection and

unknown authors

2013-01-01T23:59:59.000Z

254

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

255

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

256

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

257

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

258

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

259

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

260

spaceheat_household2001.pdf  

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

9a. Space Heating by Northeast Census Region, 9a. Space Heating by Northeast Census Region, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total U.S. Northeast Census Region RSE Row Factors Total Census Division Middle Atlantic New England 0.5 1.0 1.2 1.7 Total .............................................................. 107.0 20.3 14.8 5.4 NE Heat Home .................................................... 106.0 20.1 14.7 5.4 NE Do Not Heat Home ....................................... 1.0 Q Q Q 19.9 No Heating Equipment ................................ 0.5 Q Q Q 39.5 Have Equipment But Do Not Use It ............................................... 0.4 Q Q Q 38.7 Main Heating Fuel and Equipment (Have and Use Equipment) ........................... 106.0 20.1 14.7 5.4 NE Natural Gas .................................................

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

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

262

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

263

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

264

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

265

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

266

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

267

Vehicle Technologies Office: Fact #463: April 2, 2007 Transportation is a  

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

3: April 2, 2007 3: April 2, 2007 Transportation is a Large Share of Average Household Expenditures to someone by E-mail Share Vehicle Technologies Office: Fact #463: April 2, 2007 Transportation is a Large Share of Average Household Expenditures on Facebook Tweet about Vehicle Technologies Office: Fact #463: April 2, 2007 Transportation is a Large Share of Average Household Expenditures on Twitter Bookmark Vehicle Technologies Office: Fact #463: April 2, 2007 Transportation is a Large Share of Average Household Expenditures on Google Bookmark Vehicle Technologies Office: Fact #463: April 2, 2007 Transportation is a Large Share of Average Household Expenditures on Delicious Rank Vehicle Technologies Office: Fact #463: April 2, 2007 Transportation is a Large Share of Average Household Expenditures on Digg

268

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

269

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

270

Table US8. Average Consumption by Fuels Used, 2005 Physical ...  

U.S. Energy Information Administration (EIA)

Wood (cords) Energy Information Administration 2005 Residential Energy Consumption Survey: Energy Consumption and Expenditures Tables. Table US8.

271

Lower residential energy use reduces home energy expenditures as ...  

U.S. Energy Information Administration (EIA)

This Week in Petroleum › Weekly Petroleum Status Report › Weekly Natural Gas Storage ... households spent $1,945 on heating, cooling, appliances, electronics, and ...

272

2001 Consumption and Expenditures -- Electric Air-Conditioning ...  

U.S. Energy Information Administration (EIA)

CE3-1c. Electric Air-Conditioning Energy Consumption in U.S. Households by Climate Zone, 2001 : 2: CE3-2c. ...

273

Table US1. Total Energy Consumption, Expenditures, and Intensities ...  

U.S. Energy Information Administration (EIA)

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

274

CBECS 1992 - Consumption & Expenditures, Detailed Tables  

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

Detailed Tables Detailed Tables Detailed Tables Figure on Energy Consumption in Commercial Buildings by Energy Source, 1992 Divider Line The 49 tables present detailed energy consumption and expenditure data for buildings in the commercial sector. This section provides assistance in reading the tables by explaining some of the headings for the data categories. It will also explain the use of row and column factors to compute both the confidence levels of the estimates given in the tables and the statistical significance of differences between the data in two or more categories. The section concludes with a "Quick-Reference Guide" to the statistics in the different tables. Categories of Data in the Tables After Table 3.1, which is a summary table, the tables are grouped into the major fuel tables (Tables 3.2 through 3.13) and the specific fuel tables (Tables 3.14 through 3.29 for electricity, Tables 3.30 through 3.40 for natural gas, Tables 3.41 through 3.45 for fuel oil, and Tables 3.46 through 3.47 for district heat). Table 3.48 presents energy management and DSM data as reported by the building respondent. Table 3.49 presents data on participation in electric utility-sponsored DSM programs as reported by both the building respondent and the electricity supplier.

275

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

276

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

277

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

278

Commercial Buildings Energy Consumption and Expenditures 1992 - Publication  

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

and Expenditures > Publication and Tables and Expenditures > Publication and Tables 1992 Consumption & Expenditures Publication and Tables Figure ES1. Energy Consumption in Commercial Buildings by Energy Sources, 1992 Separater Bar To View and/or Print Reports (requires Adobe Acrobat Reader) - Download Adobe Acrobat Reader . If you experience any difficulties, visit our Technical Frequently Asked Questions. You have the option of downloading the entire report or selected sections of the report. Separater Bar Full Report - Commercial Buildings Energy Consumption and Expenditures, 1992 (file size 1.07 MB) pages: 214 Selected Sections Main Text - requires Adobe Acrobat Reader (file size 193,634 bytes) pages: 28, includes the following: Contacts Contents Executive Summary Introduction Background

279

Table 1.5 Energy Consumption, Expenditures, and Emissions ...  

U.S. Energy Information Administration (EIA)

Consumption per Capita: Energy Expenditures 1: Energy ... 2009. 94,559,407 [R] 308 : 1,061,220 [R] ... 2 Carbon dioxide emissions from energy consumption. See Table 11.1.

280

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

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

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

282

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

283

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

284

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

285

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

286

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

287

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

288

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

289

Table A39. Total Expenditures for Purchased Electricity and Steam  

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

9. Total Expenditures for Purchased Electricity and Steam" 9. Total Expenditures for Purchased Electricity and Steam" " by Type of Supplier, Census Region, Census Division, and" " Economic Characteristics of the Establishment, 1994" " (Estimates in Million Dollars)" ," Electricity",," Steam" ,,,,,"RSE" ,"Utility","Nonutility","Utility","Nonutility","Row" "Economic Characteristics(a)","Supplier(b)","Supplier(c)","Supplier(b)","Supplier(c)","Factors" ,"Total United States" "RSE Column Factors:",0.3,2,1.6,1.2

290

Table 7.9 Expenditures for Purchased Energy Sources, 2002  

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

9 Expenditures for Purchased Energy Sources, 2002;" 9 Expenditures for Purchased Energy Sources, 2002;" " Level: National and Regional Data;" " Row: NAICS Codes; Column: Energy Sources;" " Unit: Million U.S. Dollars." " "," "," ",," "," "," "," "," "," "," "," ",," " " "," ",,,,,,,,,,"RSE" "NAICS"," "," ",,"Residual","Distillate","Natural ","LPG and",,"Coke"," ","Row" "Code(a)","Subsector and Industry","Total","Electricity","Fuel Oil","Fuel Oil(b)","Gas(c)","NGL(d)","Coal","and Breeze","Other(e)","Factors"

291

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

292

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

293

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

294

U.S. Department of Energy, Energy Information Administration (EIA  

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

A2 - Average per Households","Table A2. U.S. Per Household Vehicle-Miles Traveled, Vehicle Fuel Consumption and Expenditures, 2001" A2 - Average per Households","Table A2. U.S. Per Household Vehicle-Miles Traveled, Vehicle Fuel Consumption and Expenditures, 2001" "Std Errors for A2","Relative Standard Errors for Table A2. U.S. Per Household Vehicle-Miles Traveled, Vehicle Fuel Consumption and Expenditures, 2001 (Percent)" "N Cells for A2","Number of Sample Cases Contributing to Estimates in Table A2. U.S. Per Household Vehicle-Miles Traveled, Vehicle Fuel Consumption and Expenditures, 2001" "A3 - Average per Vehicles","Table A3. U.S. Per Vehicle Average Miles Traveled, Vehicle Fuel Consumption and Expenditures, 2001" "Std Errors for A3","Relative Standard Errors for Table A3. U.S. Per Vehicle Average Miles Traveled, Vehicle Fuel Consumption and Expenditures, 2001

295

A model to assess the relative impact of policy in transportation energy expenditures  

Science Conference Proceedings (OSTI)

The research reported in this paper uses the 1977 and 1983 Nationwide Personal Transportation Study surveys (NPTS's) to estimate the cross-section and time responses of minority and majority households in terms of variations in vehicles held by the household, VMT per household vehicle, 1983 dollar income of the household, education and age of the household head, transit availability to the household, workers and nonworkers per household, and urban vs rural location.

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

1987-01-01T23:59:59.000Z

296

Residential Energy Consumption Survey (RECS) - Analysis ...  

U.S. Energy Information Administration (EIA)

Includes hydropower, solar, wind, geothermal, biomass and ethanol. ... For example, the average energy expenditure for a New Jersey household was $3,065, ...

297

Microsoft Word - Highlights.docx  

Annual Energy Outlook 2012 (EIA)

and Winter Fuels Outlook EIA projects average household expenditures for heating oil and natural gas will increase by 19 percent and 15 percent, respectively, this winter...

298

Residential Buildings Historical Publications reports, data and...  

Gasoline and Diesel Fuel Update (EIA)

1 Average Fuel OilKerosene Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per...

299

Residential Buildings Historical Publications reports, data and...  

Annual Energy Outlook 2012 (EIA)

3 Average Fuel OilKerosene Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per...

300

Residential Buildings Historical Publications reports, data and...  

Annual Energy Outlook 2012 (EIA)

90 Average Fuel OilKerosene Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per...

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

Residential Buildings Historical Publications reports, data and...  

Annual Energy Outlook 2012 (EIA)

7 Average Fuel OilKerosene Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per...

302

Residential Buildings Historical Publications reports, data and...  

Gasoline and Diesel Fuel Update (EIA)

4 Average Fuel OilKerosene Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per...

303

Residential Buildings Historical Publications reports, data and...  

Annual Energy Outlook 2012 (EIA)

0 Average Fuel OilKerosene Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per...

304

Residential Buildings Historical Publications reports, data and...  

Annual Energy Outlook 2012 (EIA)

2 Average Fuel OilKerosene Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per...

305

Natural Gas Weekly Update  

Annual Energy Outlook 2012 (EIA)

or 48 percent, more this winter in fuel expenditures. Households heating primarily with heating oil can expect to pay, on average, 378, or 32 percent, more this winter....

306

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

307

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)

308

Commercial Buildings Energy Consumption and Expenditures 1992 - Executive  

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

& Expenditures > Executive Summary & Expenditures > Executive Summary 1992 Consumption & Expenditures Executive Summary Commercial Buildings Energy Consumption and Expenditures 1992 presents statistics about the amount of energy consumed in commercial buildings and the corresponding expenditures for that energy. These data are based on the 1992 Commercial Buildings Energy Consumption Survey (CBECS), a national energy survey of buildings in the commercial sector, conducted by the Energy Information Administration (EIA) of the U.S. Department of Energy. Figure ES1. Energy Consumption is Commercial Buidings by Energy Source, 1992 Energy Consumption: In 1992, the 4.8 million commercial buildings in the United States consumed 5.5 quadrillion Btu of electricity, natural gas, fuel oil, and district heat. Of those 5.5 quadrillion Btu, consumption of site electricity accounted for 2.6 quadrillion Btu, or 48.0 percent, and consumption of natural gas accounted for 2.2 quadrillion Btu, or 39.6 percent. Fuel oil consumption made up 0.3 quadrillion Btu, or 4.0 percent of the total, while consumption of district heat made up 0.4 quadrillion Btu, or 7.9 percent of energy consumption in that sector. When the energy losses that occur at the electricity generating plants are included, the overall energy consumed by commercial buildings increases to about 10.8 quadrillion Btu (Figure ES1).

309

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

310

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

311

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

312

Capital expenditures of leading petroleum companies 1968-1982  

Science Conference Proceedings (OSTI)

A review of aggregate capital expenditures by 37 leading US petroleum companies from 1968 through 1982 examines data from several vantages, including capital expenditures by geographical and functional segment and in relation to sources of funds. The paper responds to a number of issues raised during and after the Arab oil embargo, when widespread public concern developed over the economic and security implications of US dependence on foreign energy supplies and over whether US petroelum companies were adequately using their profits to assure sufficient supplies. Contrary to the allegations made, this study finds that capital expenditures increased and were largely directed toward exploration and production in the US, with only a small proportion going to non-petroleum, non-energy purposes. 2 figures, 17 tables.

Gal, N.P.

1984-01-01T23:59:59.000Z

313

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

314

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

315

Buildings Energy Data Book: 2.9 Low-Income Housing  

Buildings Energy Data Book (EERE)

0 2005 Average Energy Expenditures per Household Member and per Square Foot, by Weatherization Eligibility (2010) Members Hhold Hhold Total U.S. Households 780 2.6 0.86 Federally...

316

Note on R&D expenditures and fixed capital formation  

Science Conference Proceedings (OSTI)

In this paper we deal with the fixed capital nature of the means of production and labour employed in research and development which generate scientific and technological knowledge. We argue that these R&D current expenditures typically have the ... Keywords: Capital, Innovation, Research

Mario Marchi; Maurizio Rocchi

2010-11-01T23:59:59.000Z

317

ORIGINAL PAPER Differential sperm expenditure by male sailfin mollies,  

E-Print Network (OSTI)

Introduction It is increasingly evident that sperm production is costly to males (Dewsbury 1982; Nakatsuru expected outcome of costly sperm production is differential control of sperm production and expenditure strategies that reduce costs associated with spermatogenesis. This is especially true when males

Gabor, Caitlin - Department of Biology, Texas State University

318

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

319

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...

320

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

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

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

322

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...

323

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

324

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...

325

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

326

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

327

Microsoft Word - Highlights Bullets.doc  

Gasoline and Diesel Fuel Update (EIA)

December 2004 December 2004 1 Short-Term Energy Outlook December 2004 Winter Fuels Update (Figure 1) Lower petroleum and natural gas prices in this Outlook marginally reduced our projections of winter heating fuel prices and winter household heating fuel expenditures. Heating oil expenditures by typical Northeastern households are now expected to average 34 percent above last winter's levels, with residential fuel prices averaging $1.85 per gallon for the October-to-March period. Expenditures for propane-heated households are expected to increase about 22 percent this winter. Expected increases in expenditures for natural gas-heated households have also been lowered in this Outlook to 9 percent. The reduction

328

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

329

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

330

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

331

Green Pricing Program Marketing Expenditures: Finding the Right Balance  

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

449 449 September 2009 Green Pricing Program Marketing Expenditures: Finding the Right Balance Barry Friedman and Mackay Miller National Renewable Energy Laboratory 1617 Cole Boulevard, Golden, Colorado 80401-3393 303-275-3000 * www.nrel.gov NREL is a national laboratory of the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy Operated by the Alliance for Sustainable Energy, LLC Contract No. DE-AC36-08-GO28308 Technical Report NREL/TP-6A2-46449 September 2009 Green Pricing Program Marketing Expenditures: Finding the Right Balance Barry Friedman and Mackay Miller Prepared under Task No. SAO9.3003 NOTICE This report was prepared as an account of work sponsored by an agency of the United States government. Neither the United States government nor any agency thereof, nor any of their employees, makes any

332

Buildings Energy Data Book: 3.3 Commercial Sector Expenditures  

Buildings Energy Data Book (EERE)

9 9 2003 Energy Expenditures per Square Foot of Commercial Floorspace and per Building, by Building Type ($2010) ($2010) Food Service 4.88 27.2 Mercantile 2.23 38.1 Food Sales 4.68 26.0 Education 1.43 36.6 Health Care 2.76 68.0 Service 1.39 9.1 Public Order and Safety 2.07 32.0 Warehouse and Storage 0.80 13.5 Office 2.01 29.8 Religious Worship 0.76 7.8 Public Assembly 1.73 24.6 Vacant 0.34 4.8 Lodging 1.72 61.5 Other 2.99 65.5 Note(s): Source(s): Mall buildings are no longer included in most CBECs tables; therefore, some data is not directly comparable to past CBECs. EIA, 2003 Commercial Buildings Energy Consumption and Expenditures: Consumption and Expenditures Tables, Oct. 2006, Table 4; and EIA, Annual Energy Review 2010, Oct. 2011, Appendix D, p. 353 for price deflators. Per Square Foot Per Building

333

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

334

Assumptions to the Annual Energy Outlook 1999 - Commercial Demand...  

Annual Energy Outlook 2012 (EIA)

household.gif (5637 bytes) The Household Expenditures Module (HEM) constructs household energy expenditure profiles using historical survey data on household income, population and...

335

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

336

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

337

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

338

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

339

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

340

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

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

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

342

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 ...

343

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

344

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

345

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) ...

346

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

347

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 ...

348

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

349

Buildings Energy Data Book: 3.3 Commercial Sector Expenditures  

Buildings Energy Data Book (EERE)

3.3 Commercial Sector Expenditures 3.3 Commercial Sector Expenditures March 2012 3.3.3 Commercial Buildings Aggregate Energy Expenditures, by Year and Major Fuel Type ($2010 Billion) (1) Electricity Natural Gas Petroleum (2) Total 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 148.6 37.0 17.0 202.6 148.9 37.2 17.1 203.2 145.9 36.2 16.7 198.9 147.5 36.8 16.9 201.2 143.8 35.1 16.4 195.2 145.0 35.5 16.6 197.0 141.1 34.0 16.0 191.1 142.5 34.6 16.2 193.3 136.9 32.1 15.7 184.8 139.1 33.0 15.9 188.0 133.5 31.0 15.4 179.9 135.0 31.6 15.6 182.2 131.0 29.7 15.1 175.8 131.9 30.3 15.3 177.5 128.1 28.7 14.5 171.3 130.0 29.3 15.0 174.4 129.4 29.7 15.4 174.5 127.7 29.2 13.8 170.7 134.8 29.9 14.5 179.2 134.5 28.5 16.9 180.0 141.1

350

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

351

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

352

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)

353

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 ...

354

Relationships between U.S. Consumer Expenditures on Communications and Travel: 1984-2002  

E-Print Network (OSTI)

and new and old communications technologies). The first fourchanges in new communications technology on personal vehiclePV items on old communications technology expenditures. The

Choo, Sangho; Lee, Taihyeong; Mokhtarian, Patricia L

2006-01-01T23:59:59.000Z

355

Table 3.6 Consumer Expenditure Estimates for Energy by End ...  

U.S. Energy Information Administration (EIA)

1999. 31,577 : 11,397 : 93,482: ... · Expenditures include taxes where data are ... includes fuel ethanol blended into motor gasoline that is not ...

356

Caloric expenditure and substrate utilization in underwater treadmill running versus land-based treadmill running.  

E-Print Network (OSTI)

??The objective of this study is to compare the caloric expenditure and oxidative sources of underwater treadmill running and land-based treadmill running at maximal and… (more)

Schaal, Courtney

2009-01-01T23:59:59.000Z

357

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

358

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 Peña; Dolores Redondas

2006-02-01T23:59:59.000Z

359

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)

360

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 +

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

Table 7.9 Expenditures for Purchased Energy Sources, 2010;  

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

9 Expenditures for Purchased Energy Sources, 2010; 9 Expenditures for Purchased Energy Sources, 2010; Level: National and Regional Data; Row: NAICS Codes; Column: Energy Sources; Unit: Million U.S. Dollars. NAICS Residual Distillate LPG and Coke Code(a) Subsector and Industry Total Electricity Fuel Oil Fuel Oil(b) Natural Gas(c) NGL(d) Coal and Breeze Other(e) Total United States 311 Food 10,111 5,328 130 431 3,391 150 442 29 210 3112 Grain and Oilseed Milling 2,130 932 2 12 673 Q 294 0 158 311221 Wet Corn Milling 1,002 352 1 5 296 1 239 0 107 31131 Sugar Manufacturing 367 105 7 18 87 1 118 29 2 3114 Fruit and Vegetable Preserving and Specialty Foods 1,408 698 17 Q 579 18 7 0 18 3115 Dairy Products 1,186 695 20 40 412 8 1 0 10 3116 Animal Slaughtering and Processing

362

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

363

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

364

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

365

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

366

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

367

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

368

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

369

"Table A28. Total Expenditures for Purchased Energy Sources by Census Region"  

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

Total Expenditures for Purchased Energy Sources by Census Region" Total Expenditures for Purchased Energy Sources by Census Region" " and Economic Characteristics of the Establishment, 1991" " (Estimates in Million Dollars)" " "," "," "," ",," "," "," "," "," ","RSE" " "," "," ","Residual","Distillate","Natural"," "," ","Coke"," ","Row" "Economic Characteristics(a)","Total","Electricity","Fuel Oil","Fuel Oil(b)","Gas(c)","LPG","Coal","and Breeze","Other(d)","Factors"

370

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

371

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

372

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)","(%)"

373

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 ...

374

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

375

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

376

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

377

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:

378

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:

379

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:

380

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:

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

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:

382

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

383

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

384

Buildings Energy Data Book: 1.2 Building Sector Expenditures  

Buildings Energy Data Book (EERE)

8 8 2035 Buildings Energy End-Use Expenditure Splits, by Fuel Type ($2010 Billion) (1) Natural Petroleum Gas Distil. Resid. LPG Oth(2) Total Coal Electricity Total Percent Space Heating (3) 63.4 13.0 1.6 7.7 0.8 23.1 0.2 20.6 107.2 20.9% Water Heating 23.8 2.2 1.2 3.4 35.8 63.0 12.3% Space Cooling 0.4 55.7 56.1 10.9% Lighting 47.8 47.8 9.3% Electronics (4) 27.2 27.2 5.3% Refrigeration (5) 27.0 27.0 5.3% Computers 14.8 14.8 2.9% Cooking 5.8 0.8 0.8 5.4 12.1 2.3% Wet Clean (6) 0.9 10.4 11.3 2.2% Ventilation (7) 2.4 2.4 0.5% Other (8) 9.3 0.4 12.6 2.0 15.0 88.8 113.2 22.0% Adjust to SEDS (9) 4.6 5.3 5.3 21.7 31.6 6.2% Total 108.2 21.0 1.6 22.3 2.8 47.6 0.2 357.8 513.8 100% Note(s): Source(s): 1) Expenditures include coal and exclude wood. 2) Includes kerosene space heating ($0.8 billion) and motor gasoline other uses ($2.0 billion). 3) Includes furnace fans ($4.8 billion). 4) Includes color televisions ($14.2 billion). 5) Includes refrigerators ($24.1 billion) and freezers ($3.0

385

Buildings Energy Data Book: 2.3 Residential Sector Expenditures  

Buildings Energy Data Book (EERE)

8 8 2035 Residential Energy End-Use Expenditure Splits, by Fuel Type ($2010 Billion) (1) Natural Petroleum Gas Distil. LPG Kerosene Total Coal Electricity Total Percent Space Heating (2) 44.3 10.3 7.7 18.6 0.0 16.0 79.0 27.4% Space Cooling (3) 0.0 40.6 40.6 14.1% Water Heating 17.6 1.2 1.2 2.3 17.7 37.6 13.0% Lighting 15.5 15.5 5.4% Refrigeration (4) 17.0 17.0 5.9% Electronics (5) 14.2 14.2 4.9% Wet Cleaning (6) 0.9 10.4 11.3 3.9% Cooking 3.2 0.8 0.8 4.8 8.9 3.1% Computers 8.7 8.7 3.0% Other (7) 0.0 7.7 7.7 47.9 55.7 19.3% Total 66.0 11.5 17.5 29.6 0.0 193.0 288.6 100% Note(s): Source(s): 0.6 0.6 1) Expenditures include coal and exclude wood. 2) Includes furnace fans ($4.8 billion). 3) Fan energy use included. 4) Includes refrigerators ($14.1 billion) and freezers ($2.9 billion). 5) Includes color televisions ($14.2 billion). 6) Includes clothes washers ($0.8 billion), natural gas

386

Buildings Energy Data Book: 2.3 Residential Sector Expenditures  

Buildings Energy Data Book (EERE)

5 5 2010 Residential Energy End-Use Expenditure Splits, by Fuel Type ($2010 Billion) (1) Natural Petroleum Gas Distil. LPG Kerosene Total Coal Electricity Total Percent Space Heating (2) 38.7 11.2 8.0 19.8 0.0 14.3 72.9 28.9% Space Cooling (3) 0.0 35.4 35.4 14.0% Water Heating (4) 14.3 2.1 2.0 4.0 14.2 32.6 12.9% Lighting 22.6 22.6 9.0% Refrigeration (5) 14.9 14.9 5.9% Electronics (6) 17.8 17.8 7.1% Cooking 2.4 0.8 0.8 6.0 9.2 3.7% Wet Cleaning (7) 0.6 10.7 11.3 4.5% Computers 5.6 5.6 2.2% Other (8) 0.0 4.4 4.4 6.7 11.1 4.4% Adjust to SEDS (9) 13.6 13.6 5.4% Total 56.1 13.3 15.2 29.0 0.0 166.8 251.8 100% Note(s): Source(s): 0.5 0.5 1) Expenditures include coal and exclude wood. 2) Includes furnace fans ($4.5 billion). 3) Fan energy use included. 4) Includes residential recreational water heating ($1.4 billion). 5) Includes refrigerators ($15.3 billion) and freezers ($4.4 billion). 6) Includes color televisions ($11.0

387

Buildings Energy Data Book: 1.2 Building Sector Expenditures  

Buildings Energy Data Book (EERE)

5 5 2010 Buildings Energy End-Use Expenditure Splits, by Fuel Type ($2010 Billion) (1) Natural Petroleum Gas Distil. Resid. LPG Oth(2) Total Coal Electricity Total Percent Space Heating (3) 53.7 14.2 0.9 8.0 0.6 23.7 0.1 23.2 100.8 23.4% Space Cooling 0.4 61.3 61.7 14.3% Lighting 59.3 59.3 13.8% Water Heating 18.3 2.6 2.0 4.6 17.8 40.7 9.4% Refrigeration (4) 26.9 26.9 6.2% Electronics (5) 26.1 26.1 6.1% Ventilation (6) 15.9 15.9 3.7% Cooking 4.0 0.8 0.8 8.8 13.6 3.2% Computers 12.1 12.1 2.8% Wet Cleaning (7) 0.6 11.0 11.6 2.7% Other (8) 2.7 0.3 7.7 1.2 9.2 27.3 39.2 9.1% Adjust to SEDS (9) 6.2 5.2 5.2 11.9 23.4 5.4% Total 86.0 22.3 0.9 18.5 1.8 43.5 0.1 301.6 431.2 100% Note(s): Source(s): 1) Expenditures include coal and exclude wood. 2) Includes kerosene space heating ($0.6 billion) and motor gasoline other uses ($1.2 billion). 3) Includes furnace fans ($4.5 billion). 4) Includes refrigerators ($24.1 billion) and freezers ($2.8 billion). 5) Includes color televisions ($11.0

388

Buildings Energy Data Book: 1.2 Building Sector Expenditures  

Buildings Energy Data Book (EERE)

6 6 2015 Buildings Energy End-Use Expenditure Splits, by Fuel Type ($2010 Billion) (1) Natural Gas Distil. Resid. LPG Oth(2) Total Coal Total Percent Space Heating (3) 49.5 15.9 1.3 8.1 0.7 25.9 0.2 18.7 94.3 22.7% Space Cooling 0.3 48.0 48.3 11.6% Lighting 45.9 45.9 11.0% Water Heating 17.6 2.6 1.5 4.1 18.3 40.0 9.6% Refrigeration (4) 24.9 24.9 6.0% Electronics (5) 19.8 19.8 4.7% Ventilation (6) 15.1 15.1 3.6% Computers 11.6 11.6 2.8% Wet Cleaning (7) 0.6 10.8 11.4 2.7% Cooking 3.9 0.9 0.9 4.4 9.1 2.2% Other (8) 2.9 0.3 8.9 1.4 10.6 54.1 67.6 16.3% Adjust to SEDS (9) 5.8 4.5 4.5 17.7 28.1 6.7% Total 80.6 23.3 1.3 19.4 2.1 46.1 0.2 289.3 416.2 100% Note(s): Source(s): Petroleum Electricity 1) Expenditures include coal and exclude wood. 2) Includes kerosene space heating ($0.7 billion) and motor gasoline other uses ($1.4 billion). 3) Includes furnace fans ($4.6 billion). 4) Includes refrigerators ($22.6 billion) and freezers ($2.8 billion). 5) Includes color televisions ($10.9

389

Buildings Energy Data Book: 2.3 Residential Sector Expenditures  

Buildings Energy Data Book (EERE)

7 7 2025 Residential Energy End-Use Expenditure Splits, by Fuel Type ($2010 Billion) (1) Natural Petroleum Gas Distil. LPG Kerosene Total Coal Electricity Total Percent Space Heating (2) 39.7 11.5 7.8 19.9 0.0 15.0 74.5 28.6% Space Cooling (3) 0.0 36.2 36.2 13.9% Water Heating 16.0 1.4 1.3 2.7 17.1 35.9 13.8% Lighting 15.2 15.2 5.8% Refrigeration (4) 15.5 15.5 6.0% Electronics (5) 12.0 12.0 4.6% Wet Cleaning (6) 0.8 9.8 10.5 4.1% Cooking 2.7 0.8 0.8 4.3 7.8 3.0% Computers 7.7 7.7 2.9% Other (7) 0.0 6.4 6.4 38.7 45.0 17.3% Total 59.1 12.9 16.3 29.8 0.0 171.3 260.3 100% Note(s): Source(s): 0.6 0.6 1) Expenditures include coal and exclude wood. 2) Includes furnace fans ($4.7 billion). 3) Fan energy use included. 4) Includes refrigerators ($12.7 billion) and freezers ($2.8 billion). 5) Includes color televisions ($12 billion). 6) Includes clothes washers ($0.8 billion), natural gas

390

Buildings Energy Data Book: 1.2 Building Sector Expenditures  

Buildings Energy Data Book (EERE)

7 7 2025 Buildings Energy End-Use Expenditure Splits, by Fuel Type ($2010 Billion) (1) Natural Petroleum Gas Distil. Resid. LPG Oth(2) Total Coal Electricity Total Percent Space Heating (3) 56.7 14.3 1.5 7.8 0.7 24.3 0.2 19.5 100.7 22.0% Space Cooling 0.3 50.5 50.9 11.1% Lighting 45.2 45.2 9.9% Water Heating 21.3 2.3 1.3 3.6 19.6 44.4 9.7% Refrigeration (4) 24.9 24.9 5.4% Electronics (5) 23.2 23.2 5.1% Computers 13.2 13.2 2.9% Wet Clean (6) 0.8 9.8 10.5 2.3% Cooking 4.8 0.8 0.8 4.9 10.5 2.3% Ventilation (7) 16.6 16.6 3.6% Other (8) 4.8 0.4 10.6 1.7 12.7 69.8 87.4 19.1% Adjust to SEDS (9) 5.9 4.9 4.9 19.2 30.0 6.6% Total 94.6 21.9 1.5 20.6 2.5 46.4 0.2 316.3 457.4 100% Note(s): Source(s): 1) Expenditures include coal and exclude wood. 2) Includes kerosene space heating ($0.7 billion) and motor gasoline other uses ($1.7 billion). 3) Includes furnace fans ($4.7 billion). 4) Includes refrigerators ($22.3 billion) and freezers ($2.6 billion). 5) Includes color televisions ($12.0

391

Buildings Energy Data Book: 2.3 Residential Sector Expenditures  

Buildings Energy Data Book (EERE)

6 6 2015 Residential Energy End-Use Expenditure Splits, by Fuel Type ($2010 Billion) (1) Natural Petroleum Gas Distil. LPG Kerosene Total Coal Electricity Total Percent Space Heating (2) 35.0 13.0 8.1 21.6 0.0 14.0 70.6 29.2% Space Cooling (3) 0.0 33.8 33.8 14.0% Water Heating 13.5 1.9 1.5 3.4 15.8 32.7 13.5% Lighting 17.6 17.6 7.3% Refrigeration (4) 15.0 15.0 6.2% Electronics (5) 10.9 10.9 4.5% Wet Cleaning (6) 0.6 10.8 11.4 4.7% Cooking 2.2 0.9 0.9 3.8 6.8 2.8% Computers 6.3 6.3 2.6% Other (7) 0.0 5.2 5.2 31.3 36.5 15.1% Total 51.3 14.9 15.7 31.1 0.0 159.3 241.7 100% Note(s): Source(s): 0.6 0.6 1) Expenditures include coal and exclude wood. 2) Includes furnace fans ($4.6 billion). 3) Fan energy use included. 4) Includes refrigerators ($12.3 billion) and freezers ($2.8 billion). 5) Includes color televisions ($10.9 billion). 6) Includes clothes washers ($1.1 billion), natural gas

392

Buildings Energy Data Book: 2.3 Residential Sector Expenditures  

Buildings Energy Data Book (EERE)

3 3 Residential Aggregate Energy Expenditures, by Year and Major Fuel Type ($2010 Billion) (1) Electricity Total 1980 158.5 1981 164.0 1982 172.3 1983 176.1 1984 178.5 1985 176.8 1986 169.2 1987 167.1 1988 170.1 1989 172.8 1990 168.2 1991 169.9 1992 166.7 1993 175.6 1994 174.9 1995 172.7 1996 181.8 1997 180.0 1998 173.5 1999 174.0 2000 192.8 2001 203.3 2002 192.1 2003 208.8 2004 215.1 2005 236.7 2006 240.0 2007 246.1 2008 259.6 2009 241.6 2010 251.8 2011 251.3 2012 247.1 2013 240.3 2014 239.4 2015 241.7 2016 241.8 2017 243.0 2018 244.7 2019 246.4 2020 247.9 2021 250.4 2022 253.3 2023 255.6 2024 257.8 2025 260.3 2026 263.2 2027 266.0 2028 267.6 2029 268.1 2030 269.7 2031 272.9 2032 276.6 2033 280.4 2034 284.6 2035 288.6 Note(s): Source(s): 1) Residential petroleum products include distillate fuel oil, LPG, and kerosene. EIA, State Energy Data 2009: Prices and Expenditures, Jun. 2011, Table 2 for 1980-2009; EIA, Annual Energy Outlook 2012 Early Release, Jan. 2012, Table

393

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

394

,"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...

395

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

396

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

397

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

398

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.

399

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

400

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...

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

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...

402

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

403

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...

404

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

405

Buildings Energy Data Book: 1.2 Building Sector Expenditures  

Buildings Energy Data Book (EERE)

3 3 Buildings Aggregate Energy Expenditures, by Year and Major Fuel Type ($2010 Billion) (1) Residential Buildings Commercial Buildings Total Building Electricity Natural Gas Petroleum (2) Total Electricity Natural Gas Petroleum (3) Total Expenditures 1980 89.1 40.5 28.9 158.5 70.9 20.5 17.2 108.6 267.2 1981 94.9 41.3 27.8 164.0 79.4 21.4 16.5 117.3 281.3 1982 99.9 47.9 24.5 172.3 83.4 25.1 13.7 122.2 294.5 1983 103.6 51.0 21.4 176.1 83.6 26.1 14.6 124.3 300.4 1984 103.3 51.6 23.6 178.5 87.6 25.9 14.7 128.2 306.7 1985 105.4 48.8 22.6 176.8 90.0 24.0 12.6 126.6 303.4 1986 106.9 44.2 18.1 169.2 90.5 20.7 9.1 120.2 289.4 1987 108.2 40.9 18.0 167.1 88.7 19.8 9.2 117.7 284.7 1988 110.3 41.8 18.0 170.1 89.9 20.4 8.2 118.5 288.7 1989 110.2 42.9 19.7 172.8 91.5 20.5 8.4 120.4 293.2 1990 110.9 39.0 18.2 168.2 92.9 19.4 9.2 121.5 289.7 1991 113.7 39.2 17.0 169.9 93.9 19.5 7.7 121.1 291.0

406

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

407

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

408

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

409

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

410

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.

411

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,

412

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

413

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

414

Energy Information Administration/Short-Term Energy Outlook - February 2005  

Gasoline and Diesel Fuel Update (EIA)

February 2005 February 2005 1 Short-Term Energy Outlook February 2005 Winter Fuels Update (Figure 1) Despite some cold weather during the second half of January, expected average consumer prices for heating fuels this heating season are little changed since the January Outlook, leaving projections for household heating fuel expenditures about the same as previously reported. Heating oil expenditures by typical Northeastern households are expected to average 32 percent above last winter's levels, with residential fuel oil prices averaging $1.82 per gallon for the October-to-March period. Expenditures for propane-heated households are expected to increase about

415

Table 1. Natural Gas Consumption and Expenditures in U.S ...  

U.S. Energy Information Administration (EIA)

Appliances Households Using Natural Gas (million) ... 1 A small amount of natural gas used for air conditioning is included in "Natural Gas" under "All Uses".

416

www.eia.gov  

U.S. Energy Information Administration (EIA)

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

417

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

418

Relationships between U.S. Consumer Expenditures on Communications and Travel: 1984-2002  

E-Print Network (OSTI)

is, an increase in the price of non-PV goods/services leadsimpact of a change in PV capital prices on expenditures forof Alt. 1, Table 5.4. PV own-price elasticities have also

Choo, Sangho; Lee, Taihyeong; Mokhtarian, Patricia L

2006-01-01T23:59:59.000Z

419

Table CE1-6.2u. Total Energy Consumption and Expenditures by ...  

U.S. Energy Information Administration (EIA)

Table CE1-6.2u. Total Energy Consumption and Expenditures by Square Feet and Usage Indicators, 2001 Usage Indicators RSE Column Factor: Total End-Use Energy

420

Table 3.5 Consumer Expenditure Estimates for Energy by Source ...  

U.S. Energy Information Administration (EIA)

1972. 5,415 -26: 13,198 : 7,552: 1,682: 2,834 : 35,346 : ... 8 Asphalt and road oil, aviation gasoline, kerosene, ... "State Energy Data 2010: Prices and Expenditures"

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

Social and cultural factors as a determinate of ICT expenditures: an empirical study  

Science Conference Proceedings (OSTI)

Information and communication technologies (ICT) have come to hold an important place in strategies for promoting economic growth and development in developing countries. It is known that ICT expenditures as a percent of GDP vary between countries. An ...

Larry Allen; Vivek Natarajan; Donald Price

2012-12-01T23:59:59.000Z

422

"Table A38. Total Expenditures for Purchased Electricity, Steam, and Natural Gas"  

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

8. Total Expenditures for Purchased Electricity, Steam, and Natural Gas" 8. Total Expenditures for Purchased Electricity, Steam, and Natural Gas" " by Type of Supplier, Census Region, Census Division, Industry Group," " and Selected Industries, 1994" " (Estimates in Million Dollars)" ,," Electricity",," Steam" ,,,,,,"RSE" "SIC",,"Utility","Nonutility","Utility","Nonutility","Row" "Code(a)","Industry Group and Industry","Supplier(b)","Supplier(c)","Supplier(b)","Supplier(c)","Factors" ,,"Total United States"

423

Table 7.10 Expenditures for Purchased Electricity, Natural Gas, and Steam, 2002  

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

0 Expenditures for Purchased Electricity, Natural Gas, and Steam, 2002;" 0 Expenditures for 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: Million U.S. Dollars." ,,,"Electricity","Components",,"Natural Gas","Components",,"Steam","Components" " "," ",,,"Electricity",,,"Natural Gas",,,"Steam"," ",," " " "," ",,"Electricity","from Sources",,"Natural Gas","from Sources",,"Steam","from Sources","RSE"

424

"Table A46. Total Expenditures for Purchased Electricity, Steam, and Natural"  

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

6. Total Expenditures for Purchased Electricity, Steam, and Natural" 6. Total Expenditures for Purchased Electricity, Steam, and Natural" " Gas by Type of Supplier, Census Region, Industry Group, and Selected Industries," 1991 " (Estimates in Million Dollars)" ,," Electricity",," Steam",," Natural Gas" ,,"-","-----------","-","-----------","-","------------","-","RSE" "SIC",,"Utility","Nonutility","Utility","Nonutility","Utility","Transmission","Other","Row" "Code(a)","Industry Groups and Industry","Supplier(b)","Supplier(c)","Supplier(b)","Supplier(c)","Supplier(b)","Pipelines","Supplier(d)","Factors"

425

"Table A36. Total Expenditures for Purchased Energy Sources by Census Region,"  

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

6. Total Expenditures for Purchased Energy Sources by Census Region," 6. Total Expenditures for Purchased Energy Sources by Census Region," " Census Division, Industry Group, and Selected Industries, 1994" " (Estimates in Million Dollars)" ,,,,,,,,,,,"RSE" "SIC"," "," "," ","Residual","Distillate ","Natural"," "," ","Coke"," ","Row" "Code(a)","Industry Group and Industry","Total","Electricity","Fuel Oil","Fuel Oil(b)","Gas(c)","LPG","Coal","and Breeze","Other(d)","Factors" ,,"Total United States"

426

"Table A48. Total Expenditures for Purchased Electricity, Steam, and Natural"  

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

8. Total Expenditures for Purchased Electricity, Steam, and Natural" 8. Total Expenditures for Purchased Electricity, Steam, and Natural" " Gas by Type of Supplier, Census Region, and Economic Characteristics of the" " Establishment, 1991" " (Estimates in Million Dollars)" ," Electricity",," Steam",," Natural Gas" ,"-","-----------","-","-----------","-","------------","-----------","RSE" " ","Utility","Nonutility","Utility","Nonutility","Utility","Transmission","Other","Row" "Economic Characteristics(a)","Supplier(b)","Supplier(c)","Supplier(b)","Supplier(c)","Supplier(b)","Pipelines","Supplier(d)","Factors"," "

427

Table N11.4. Expenditures for Purchased Electricity, Natural Gas, and Steam, 19  

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

4. Expenditures for Purchased Electricity, Natural Gas, and Steam, 1998;" 4. Expenditures for Purchased Electricity, Natural Gas, and Steam, 1998;" " Level: National Data and Regional Totals; " " Row: NAICS Codes;" " Column: Supplier Sources of Purchased Electricity, Natural Gas, and Steam;" " Unit: Million U.S. Dollars." ,,,"Electricity","Components",,"Natural Gas","Components",,"Steam","Components" " "," ",,,"Electricity",,,"Natural Gas",,,"Steam"," ",," " " "," ",,"Electricity","from Sources",,"Natural Gas","from Sources",,"Steam","from Sources","RSE"

428

"Table A37. Total Expenditures for Purchased Energy Sources by Census Region,"  

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

7. Total Expenditures for Purchased Energy Sources by Census Region," 7. Total Expenditures for Purchased Energy Sources by Census Region," " Census Division, and Economic Characteristics of the Establishment, 1994" " (Estimates in Million Dollars)" " "," "," "," ",," "," "," "," "," ","RSE" " "," "," ","Residual","Distillate","Natural"," "," ","Coke"," ","Row" "Economic Characteristics(a)","Total","Electricity","Fuel Oil","Fuel Oil(b)","Gas(c)","LPG","Coal","and Breeze","Other(d)","Factors"

429

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.

430

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

431

Table AC11. Expenditures Intensity by Equipment Type, 2005 Air ...  

U.S. Energy Information Administration (EIA)

climate zone according to the 30-year average annual degree-days for an appropriate nearby weather station. 2 Below 150 percent of poverty line or 60 percent of ...

432

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

433

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)

434

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

435

Buildings Energy Data Book: 2.3 Residential Sector Expenditures  

Buildings Energy Data Book (EERE)

2 2 Residential Energy Prices, by Year and Fuel Type ($2010) LPG ($/gal) 1980 2.24 1981 2.51 1982 2.30 1983 2.14 1984 2.10 1985 1.96 1986 1.54 1987 1.42 1988 1.39 1989 1.48 1990 1.69 1991 1.56 1992 1.40 1993 1.33 1994 1.27 1995 1.22 1996 1.37 1997 1.34 1998 1.15 1999 1.16 2000 1.70 2001 1.59 2002 1.42 2003 1.67 2004 1.84 2005 2.36 2006 2.64 2007 2.81 2008 3.41 2009 2.52 2010 2.92 2011 3.62 2012 3.65 2013 3.43 2014 3.60 2015 3.74 2016 3.79 2017 3.86 2018 3.89 2019 3.92 2020 3.96 2021 3.99 2022 4.02 2023 4.07 2024 4.10 2025 4.15 2026 4.19 2027 4.23 2028 4.26 2029 4.30 2030 4.34 2031 4.35 2032 4.38 2033 4.43 2034 4.50 2035 4.55 Source(s): EIA, State Energy Data 2009: Prices and Expenditures, Jun. 2011, Table 2, p. 24-25 for 1980-2009; EIA, Annual Energy Outlook 2012 Early Release, Jan. 2012, Table A3, p. 6-8 for 2010-2035 and Table G1, p. 215 for fuels' heat content; and EIA, Annual Energy Review 2010, Oct. 2011, Appendix D, p. 353 for

436

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

437

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

438

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

439

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

440

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

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

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

442

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

443

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

444

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

445

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

446

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

447

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

448

Energy Information Administration/Short-Term Energy Outlook - January 2005  

Gasoline and Diesel Fuel Update (EIA)

January 2005 January 2005 1 Short-Term Energy Outlook January 2005 Winter Fuels Update (Figure 1) Consumer prices for heating fuels are relatively unchanged since the December Outlook, leaving projections for household heating fuel expenditures about the same as previously projected, despite continued warm weather in the middle of the heating season. Heating oil expenditures by typical Northeastern households are expected to average 30 percent above last winter's levels, with residential fuel oil prices averaging $1.82 per gallon for the October-to-March period. Expenditures for propane-heated households are expected to increase about 20 percent this winter.

449

US SoAtl GA Site Consumption  

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

GA GA Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US SoAtl GA Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 4,000 8,000 12,000 16,000 US SoAtl GA Site Consumption kilowatthours $0 $300 $600 $900 $1,200 $1,500 $1,800 US SoAtl GA Expenditures dollars ELECTRICITY ONLY average per household * Site energy consumption (89.5 million Btu) and energy expenditures per household ($2,067) in Georgia are similar to the U.S. household averages. * Per household electricity consumption in Georgia is among the highest in the country, but similar to other states in the South. * Forty-five percent of homes in Georgia were built since 1990, a characteristic typically associated with lower per household consumption. Georgia homes,

450

US SoAtl GA Site Consumption  

Gasoline and Diesel Fuel Update (EIA)

GA GA Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US SoAtl GA Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 4,000 8,000 12,000 16,000 US SoAtl GA Site Consumption kilowatthours $0 $300 $600 $900 $1,200 $1,500 $1,800 US SoAtl GA Expenditures dollars ELECTRICITY ONLY average per household * Site energy consumption (89.5 million Btu) and energy expenditures per household ($2,067) in Georgia are similar to the U.S. household averages. * Per household electricity consumption in Georgia is among the highest in the country, but similar to other states in the South. * Forty-five percent of homes in Georgia were built since 1990, a characteristic typically associated with lower per household consumption. Georgia homes,

451

The cost of dying on Medicare: an analysis of expenditure data  

E-Print Network (OSTI)

Roughly one third of Medicare expenditures are made on behalf of beneficiaries in their terminal year, though only five percent of the Medicare-covered population dies annually. Per-capita spending on decedents is as much as six times the level of spending on survivors. The demographic, technological and political trends that will determine the future path of spending on terminal-year beneficiaries have important implications for the fiscal well-being of the Medicare program, and by extension, the American taxpayer. Coming to an understanding of the moving parts that will control the path of the cost of dying on Medicare is vital for careful consideration of Medicare??s future, and for any discussions about further reform of the program. Analysis of expenditures in the terminal year must be made while keeping in mind the fact that major expenditures are often made in surviving years. The spike in spending in the terminal period rightly focuses attention to expenditures near death, but also we should proceed in its analysis keeping in mind that it is not the only spell of elevated medical spending for a typical individual. Given those cautions, however, the cost of dying on Medicare stands as an important area of economic inquiry and policy consideration. As total Medicare expenditures top a quarter trillion dollars, the third of that spending which covers treatments in beneficiaries?? terminal years ought to be understood more fully than it is currently.

House, Donald Reed

2005-08-01T23:59:59.000Z

452

Short-Term Energy and Winter Fuels Outlook October 2013  

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

and Winter Fuels Outlook October 2013 1 October 2013 Short-Term Energy and Winter Fuels Outlook (STEO) Highlights EIA projects average U.S. household expenditures for natural...

453

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

454

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.

455

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

456

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

457

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

458

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 ...

459

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

460

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 ...

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

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 ...

462

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 ...

463

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 ...

464

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...

465

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 ...

466

"Table A24. Total Expenditures for Purchased Energy Sources by Census Region,"  

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

4. Total Expenditures for Purchased Energy Sources by Census Region," 4. Total Expenditures for Purchased Energy Sources by Census Region," " Industry Group, and Selected Industries, 1991" " (Estimates in Million Dollars)" ,,,,,,,,,,,"RSE" "SIC"," "," "," ","Residual","Distillate ","Natural"," "," ","Coke"," ","Row" "Code(a)","Industry Groupsc and Industry","Total","Electricity","Fuel Oil","Fuel Oil(b)","Gas(c)","LPG","Coal","and Breeze","Other(d)","Factors" ,,"Total United States" ,"RSE Column Factors:","0.6 ",0.6,1.3,1.3,0.7,1.2,1.2,1.5,1.1

467

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)

468

Microsoft Word - Highlights Bullets.doc  

Gasoline and Diesel Fuel Update (EIA)

November 2004 November 2004 1 Short-Term Energy Outlook November 2004 Winter Fuels Update (Figure 1) Higher oil prices in this Outlook raised our projections for heating oil and propane prices and household heating fuel expenditures this winter. Heating oil expenditures by typical Northeastern households are now expected to average about 37 percent above last winter's levels (compared to our previous projection of a 28-percent increase), with average residential prices averaging $1.88 per gallon for the October-to-March period. Propane-heated households can expect to see increased expenditures of about 26 percent this winter (compared with a 22-percent increase projected last month). Expected increases in expenditures for natural gas-heated households remain the same as last month at about 15

469

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

470

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.

471

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

472

US military expenditures to protect the use of Persian Gulf oil for motor vehicles  

E-Print Network (OSTI)

US military expenditures to protect the use of Persian Gulf oil for motor vehicles Mark A. Delucchi 2008 Keywords: Oil importing cost Motor fuel social cost Energy security cost a b s t r a c t Analyses of the full social cost of motor vehicle use in the US often estimate an ``oil import premium'' that includes

Murphy, James J.

473

TAX EXPENDITURES RELATED TO THE PRODUCTION AND CONSUMPTION OF MOTOR FUELS AND MOTOR VEHICLES  

E-Print Network (OSTI)

-miles of travel RECS = Residential Energy Consumption Survey SIC = standard industrial classification SOx = sulfur industries, or oil over other energy industries: virtually all major energy sources require large investments.......................24 18.5.1 Corporate income-tax expenditures for the oil industry

Delucchi, Mark

474

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

475

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

476

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

477

US Mnt(N) CO Site Consumption  

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

Mnt(N) CO Mnt(N) CO Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US Mnt(N) CO Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 2,000 4,000 6,000 8,000 10,000 12,000 US Mnt(N) CO Site Consumption kilowatthours $0 $250 $500 $750 $1,000 $1,250 $1,500 US Mnt(N) CO Expenditures dollars ELECTRICITY ONLY average per household * Colorado households consume an average of 103 million Btu per year, 15% more than the U.S. average. * Average household energy costs in Colorado are 23% less than the national average, primarily due to historically lower natural gas prices in the state. * Average electricity consumption per household is lower than most other states, as Colorado residents do not commonly use electricity for main space heating, air

478

US Mnt(N) CO Site Consumption  

Gasoline and Diesel Fuel Update (EIA)

Mnt(N) CO Mnt(N) CO Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US Mnt(N) CO Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 2,000 4,000 6,000 8,000 10,000 12,000 US Mnt(N) CO Site Consumption kilowatthours $0 $250 $500 $750 $1,000 $1,250 $1,500 US Mnt(N) CO Expenditures dollars ELECTRICITY ONLY average per household * Colorado households consume an average of 103 million Btu per year, 15% more than the U.S. average. * Average household energy costs in Colorado are 23% less than the national average, primarily due to historically lower natural gas prices in the state. * Average electricity consumption per household is lower than most other states, as Colorado residents do not commonly use electricity for main space heating, air

479

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

480

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

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

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...

482

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,...

483

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...

484

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

485

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:...

486

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

487

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

488

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

489

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 ...

490

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

491

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".

492

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

493

Buildings Energy Data Book: 2.3 Residential Sector Expenditures  

Buildings Energy Data Book (EERE)

4 4 Cost of a Generic Quad Used in the Residential Sector ($2010 Billion) (1) Residential 1980 10.45 1981 11.20 1982 11.58 1983 11.85 1984 11.65 1985 11.43 1986 10.90 1987 10.55 1988 10.18 1989 9.98 1990 10.12 1991 9.94 1992 9.78 1993 9.77 1994 9.78 1995 9.44 1996 9.44 1997 9.59 1998 9.23 1999 8.97 2000 9.57 2001 10.24 2002 9.33 2003 10.00 2004 10.32 2005 11.10 2006 11.60 2007 11.61 2008 12.29 2009 11.65 2010 9.98 2011 9.99 2012 9.87 2013 9.77 2014 9.76 2015 9.88 2016 9.85 2017 9.83 2018 9.86 2019 9.88 2020 9.91 2021 10.00 2022 10.09 2023 10.11 2024 10.12 2025 10.09 2026 10.10 2027 10.13 2028 10.11 2029 10.06 2030 10.06 2031 10.13 2032 10.23 2033 10.34 2034 10.45 2035 10.57 Note(s): 1) See Table 1.5.1 for generic quad definition. This table provides the consumer cost of a generic quad in the buildings sector. Use this table to estimate the average consumer cost savings resulting from the savings of a generic (primary) quad in the buildings sector. 2) Price of

494

Buildings Energy Data Book: 3.3 Commercial Sector Expenditures  

Buildings Energy Data Book (EERE)

Commercial Energy Prices, by Year and Major Fuel Type ($2010 per Million Btu) Electricity Natural Gas Petroleum (1) Average 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 (2) 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 27.39 10.47 27.48 21.15 27.10 10.45 27.73 21.01 27.56 10.32 27.04 21.10 27.52 10.45 27.28 21.18 27.86 10.05 26.41 21.06 27.74 10.12 26.73 21.07 28.00 9.75 25.85 20.90 27.96 9.93 26.16 21.01 27.78 9.21 25.46 20.46 27.90 9.45 25.69 20.67 27.76 8.95 24.95 20.23 27.72 9.09 25.24 20.32 27.96 8.64 24.34 20.11 27.81 8.77 24.80 20.14 27.91 8.46 23.15 19.90 28.07 8.59 24.07 20.11 28.61 8.72 23.94 20.36 28.05 8.70 22.00 19.99 29.73 9.10 20.28 20.99 29.57 8.61 24.24 21.03 30.95 12.12 23.75 23.21 30.09 9.79 15.83 21.13 29.70

495

Short-Term Energy Outlook - U.S. Energy Information Administration (EIA)  

Gasoline and Diesel Fuel Update (EIA)

Projected Winter Fuel Expenditures by Fuel and Region Projected Winter Fuel Expenditures by Fuel and Region The average household winter heating fuel expenditures discussed in this STEO provide a broad guide to changes compared with last winter. However, fuel expenditures for individual households are highly dependent on local weather conditions, market size, the size and energy efficiency of individual homes and their heating equipment, and thermostat settings (see Winter Fuels Outlook table). Forecast temperatures are close to last winter nationally, with the Northeast about 3% colder and the West 3% warmer. Natural Gas About one-half of U.S. households use natural gas as their primary heating fuel. EIA expects households heating with natural gas to spend an average of $80 (13%) more this winter than last winter. The increase in natural gas

496

Indoor Secondary Pollutants from Household Product Emissions in the  

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

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

497

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:

498

Table 7.10 Expenditures for Purchased Electricity, Natural Gas, and Steam, 2010;  

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

0 Expenditures for Purchased Electricity, Natural Gas, and Steam, 2010; 0 Expenditures for 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: Million U.S. Dollars. Electricity Components Natural Gas Electricity Electricity from Sources Natural Gas NAICS Electricity from Local Other than Natural Gas from Local Code(a) Subsector and Industry Total Utility(b) Local Utility(c) Total Utility(b) Total United States 311 Food 5,328 4,635 692 3,391 1,675 3112 Grain and Oilseed Milling 932 850 82 673 261 311221 Wet Corn Milling 352 331 21 296 103 31131 Sugar Manufacturing 105 87 18 87 39 3114 Fruit and Vegetable Preserving and Specialty Foods 698

499

EIA - Appendix B: Estimation Methodologies of Household Vehicles Energy  

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

If you have trouble viewing this page, contact the National Energy Informaiton Center at (202) 586-8800. Return to Energy Information Administration Home Page If you have trouble viewing this page, contact the National Energy Informaiton Center at (202) 586-8800. Return to Energy Information Administration Home Page EIA Home > Transportation Home Page > Appendix B Estimation MethodologiesIntroduction Appendix B Estimation Methodologies Introduction Statistics concerning vehicle miles traveled (VMT), vehicle fuel efficiency (given in terms of miles per gallon (MPG)), vehicle fuel consumption, and vehicle fuel expenditures are presented in this report. The methodology used to estimate these statistics relied on data from the 1993 Residential Energy Consumption Survey (RECS), the 1994 Residential Transportation Energy Consumption Survey (RTECS), the U.S. Environmental Protection Agency (EPA) fuel efficiency test results, the U.S. Bureau of Labor Statistics (BLS) retail pump price series, and the Lundberg Survey, Inc., price series for 1994.

500

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.