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Note: This page contains sample records for the topic "household expenditures module" from the National Library of EnergyBeta (NLEBeta).
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We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


1

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

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  

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

4

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.

5

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

6

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.

7

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

8

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

9

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

10

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

11

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

12

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

13

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.

14

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.

15

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

16

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

17

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 ...

18

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

19

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

20

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

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

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

22

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

23

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

24

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

25

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

26

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

27

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

28

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) ...

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

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 ...

31

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

32

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

33

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-

34

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

35

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 ...

36

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 --

37

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 ...

38

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

39

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:

40

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 "household expenditures module" 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

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 ...

42

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 ...

43

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

44

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

45

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

46

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

47

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

48

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

49

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

50

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:

51

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

52

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

53

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

54

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:

55

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 ...

56

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.

57

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

58

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 ...

59

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)

60

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

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

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...

62

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.

63

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

64

Microsoft Word - Household Energy Use CA  

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

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

65

Microsoft Word - Household Energy Use CA  

Gasoline and Diesel Fuel Update (EIA)

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

66

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

67

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

68

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

69

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 ...

70

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

71

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

72

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

73

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 ...

74

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

75

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 ...

76

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...

77

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

78

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

79

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 ...

80

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

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

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

82

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

83

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

84

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.

85

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

86

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...

87

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)

88

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...

89

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

90

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; ...

91

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

92

Assumptions to the Annual Energy Outlook  

Gasoline and Diesel Fuel Update (EIA)

Energy Module Oil and Gas Supply Module Household Expenditures Module Natural Gas Transmission and Distribution Module Residential Demand Module Petroleum Market Module...

93

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

94

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

95

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...

96

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

97

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

98

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

99

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

100

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.

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

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.

License
Type of

102

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

103

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

104

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

105

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

106

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

107

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 *...

108

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

109

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.

110

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...

111

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-

112

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

113

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

114

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

115

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

116

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

117

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...

118

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 ...

119

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

120

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

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


121

Household Vehicles Energy Consumption 1991  

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

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

122

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 ...

123

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?

124

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....

125

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...

126

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...

127

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

128

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

129

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

130

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

131

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

132

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.

133

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:...

134

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 ...

135

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

136

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 ...

137

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 ...

138

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.

139

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 ...

140

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.

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

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.

142

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." (*) ...

143

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, ...

144

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 ...

145

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

146

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

147

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

148

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...

149

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...

150

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...

151

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

152

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

153

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

154

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

155

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

156

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

157

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

158

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

159

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

160

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

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

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

162

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

163

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

164

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

165

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

166

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

167

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

168

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

169

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

170

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

171

Residential Demand Module  

Gasoline and Diesel Fuel Update (EIA)

2 2 Residential Demand Module The NEMS Residential Demand Module projects future residential sector energy requirements based on projections of the number of households and the stock, efficiency, and intensity of energy-consuming equipment. The Residential Demand Module projections begin with a base year estimate of the housing stock, the types and numbers of energy-consuming appliances servicing the stock, and the "unit energy consumption" (UEC) by appliance (in million Btu per household per year). The projection process adds new housing units to the stock, determines the equipment installed in new units, retires existing housing units, and retires and replaces appliances. The primary exogenous drivers for the module are housing starts by type

172

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.

173

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

174

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

175

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

176

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

177

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

178

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

179

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

180

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

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

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

182

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

183

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

184

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

185

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

186

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

187

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

188

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

189

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

190

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

191

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

192

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...

193

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

194

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

195

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

196

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

197

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

198

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

199

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

200

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

Note: This page contains sample records for the topic "household expenditures module" from the National Library of EnergyBeta (NLEBeta).
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201

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

202

A functional analysis of electrical load curve modelling for some households specific electricity end-uses  

E-Print Network (OSTI)

A functional analysis of electrical load curve modelling for some households specific electricity and the way electrical devices are used will evolve significantly. The energy consumption is likely of electrical devices; · integration of decentralized energy production and stocking (PV modules with battery

Paris-Sud XI, Université de

203

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

204

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

205

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

206

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

207

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

208

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

209

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

210

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

211

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.

212

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 ...

213

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.

214

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. ...

215

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 ...

216

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.

217

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

218

Assumptions to the Annual Energy Outlook  

Gasoline and Diesel Fuel Update (EIA)

Macroeconomic Macroeconomic Activity Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 International Energy Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 Household Expenditures Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 Residential Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 Commercial Demand Module. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 Industrial Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 Transportation Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 Electricity Market Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69 Oil and Gas Supply Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87 Natural Gas Transmission and Distribution Module . . . . . . . . . . . . . . . . . . . . . . 99 Petroleum Market Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105 Coal Market Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117 Renewable Fuels Module . . . . . . . . . . .

219

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

220

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"

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

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

222

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

223

:CorelVentura 7.0  

Gasoline and Diesel Fuel Update (EIA)

1999 1999 (AEO99) Assumptions to the December 1998 With Projections to 2020 Energy Information Administration Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Macroeconomic Activity Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 International Energy Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 Household Expenditures Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 Residential Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

224

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

225

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

226

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

227

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

228

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

229

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

230

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

231

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

232

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

233

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

234

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

235

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

236

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

237

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

238

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

239

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

240

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).

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

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

242

Assumptions  

Gasoline and Diesel Fuel Update (EIA)

1 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Macroeconomic Activity Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 International Energy Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 Household Expenditures Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 Residential Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 Commercial Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 Industrial Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 Transportation Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 Electricity Market Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 Oil and Gas Supply Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82 Natural Gas Transmission and Distribution Module . . . . . . . . . . . . . . . . . . . . . . . . . . . 92 Petroleum Market Module. . . . . . . . . . . . .

243

D:\assumptions_2001\assumptions2002\currentassump\demand.vp  

Gasoline and Diesel Fuel Update (EIA)

2 2 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Macroeconomic Activity Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 International Energy Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 Household Expenditures Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 Residential Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 Commercial Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 Industrial Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 Transportation Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49 Electricity Market Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66 Oil and Gas Supply Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 Natural Gas Transmission and Distribution Module . . . . . . . . . . . . . . . . . . . . . . . . . . . 89 Petroleum Market Module. . . . . . . . . . . . .

244

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

245

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

246

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

247

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

248

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

249

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

250

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...

251

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

252

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...

253

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

254

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...

255

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

256

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

257

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

258

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

259

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

260

Q:\asufinal_0107_demand.vp  

Gasoline and Diesel Fuel Update (EIA)

00 00 (AEO2000) Assumptions to the January 2000 With Projections to 2020 DOE/EIA-0554(2000) Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Macroeconomic Activity Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 International Energy Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 Household Expenditures Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 Residential Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 Commercial Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 Industrial Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 Transportation Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 Electricity Market Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66 Oil and Gas Supply Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 Natural Gas Transmission and Distribution

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

Assumptions to the Annual Energy Outlook  

Gasoline and Diesel Fuel Update (EIA)

Household Expenditures Module Household Expenditures Module 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. Key Assumptions The historical input data used to develop the HEM version for the AEO2003 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 AEO2003 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).

262

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

263

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

264

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

265

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

266

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 ...

267

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

268

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

269

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

270

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

271

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

272

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

273

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

274

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

275

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 ...

276

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

277

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

278

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) ...

279

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

280

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 ...

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

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

282

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

283

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

284

"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"

285

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

286

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

287

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

288

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

289

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,

290

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

291

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

292

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

293

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,

294

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

295

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

296

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

297

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

298

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,

299

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,

300

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

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

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

302

Assumptions to the Annual Energy Outlook 2002 - Residential Demand Module  

Gasoline and Diesel Fuel Update (EIA)

Residential Demand Module Residential Demand Module The NEMS Residential Demand Module forecasts future residential sector energy requirements based on projections of the number of households and the stock, efficiency, and intensity of use of energy-consuming equipment. The Residential Demand Module projections begin with a base year estimates of the housing stock, the types and numbers of energy-consuming appliances servicing the stock, and the “unit energy consumption” by appliance (or UEC—in million Btu per household per year). The projection process adds new housing units to the stock, determines the equipment installed in new units, retires existing housing units, and retires and replaces appliances. The primary exogenous drivers for the module are housing starts by type (single-family, multifamily and mobile homes) and

303

Assumptions to the Annual Energy Outlook 2001 - Residential Demand Module  

Gasoline and Diesel Fuel Update (EIA)

Residential Demand Module Residential Demand Module The NEMS Residential Demand Module forecasts future residential sector energy requirements based on projections of the number of households and the stock, efficiency, and intensity of use of energy-consuming equipment. The Residential Demand Module projections begin with a base year estimates of the housing stock, the types and numbers of energy-consuming appliances servicing the stock, and the “unit energy consumption” by appliance (or UEC—in million Btu per household per year). The projection process adds new housing units to the stock, determines the equipment installed in new units, retires existing housing units, and retires and replaces appliances. The primary exogenous drivers for the module are housing starts by type (single-family, multifamily and mobile homes) and

304

PDSF Modules  

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

Modules Modules Modules Modules Approach to Managing The Environment Modules is a system which you can use to specify what software you want to use. If you want to use a particular software package loading its module will take care of the details of modifying your environment as necessary. The advantage of the modules approach is that the you are not required to explicitly specify paths for different executable versions and try to keep their related man paths and environment variables coordinated. Instead you simply "load" and "unload" specific modules to control your environment. Getting Started with Modules If you're using the standard startup files on PDSF then you're already setup for using modules. If the "module" command is not available, please

305

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

306

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

307

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

308

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:

309

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:

310

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:

311

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:

312

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:

313

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

314

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

315

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

316

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.

317

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

318

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...

319

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...

320

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

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

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...

322

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.

323

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".

324

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

325

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

326

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"

327

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

328

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

329

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"

330

"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"

331

"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"

332

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"

333

"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"

334

"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"

335

"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"," "

336

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

337

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

338

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

339

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

340

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

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

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

342

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.

343

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

344

Module Configuration  

SciTech Connect

A stand alone battery module including: (a) a mechanical configuration; (b) a thermal management configuration; (c) an electrical connection configuration; and (d) an electronics configuration. Such a module is fully interchangeable in a battery pack assembly, mechanically, from the thermal management point of view, and electrically. With the same hardware, the module can accommodate different cell sizes and, therefore, can easily have different capacities. The module structure is designed to accommodate the electronics monitoring, protection, and printed wiring assembly boards (PWAs), as well as to allow airflow through the module. A plurality of modules may easily be connected together to form a battery pack. The parts of the module are designed to facilitate their manufacture and assembly.

Oweis, Salah (Ellicott City, MD); D' Ussel, Louis (Bordeaux, FR); Chagnon, Guy (Cockeysville, MD); Zuhowski, Michael (Annapolis, MD); Sack, Tim (Cockeysville, MD); Laucournet, Gaullume (Paris, FR); Jackson, Edward J. (Taneytown, MD)

2002-06-04T23:59:59.000Z

345

AEO Assumptions  

Gasoline and Diesel Fuel Update (EIA)

for the for the Annual Energy Outlook 1997 December 1996 Energy Information Administration Office of Integrated Analysis and Forecasting U.S. Department of Energy Washington, DC 20585 Energy Information Administration/Assumptions for the Annual Energy Outlook 1997 Contents Page Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Macroeconomic Activity Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 International Energy Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 Household Expenditures Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 Residential Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 Commercial Demand Module . . . . . . . . . . . . . . . . . .

346

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

347

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.

348

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

349

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

350

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

351

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

352

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

353

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

354

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

355

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

356

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

357

Assumptions to the Annual Energy Outlook - Residential Demand Module  

Gasoline and Diesel Fuel Update (EIA)

Residential Demand Module Residential Demand Module Assumption to the Annual Energy Outlook Residential Demand Module The NEMS Residential Demand Module forecasts future residential sector energy requirements based on projections of the number of households and the stock, efficiency, and intensity of use of energy-consuming equipment. The Residential Demand Module projections begin with a base year estimates of the housing stock, the types and numbers of energy-consuming appliances servicing the stock, and the “unit energy consumption” by appliance (or UEC—in million Btu per household per year). The projection process adds new housing units to the stock, determines the equipment installed in new units, retires existing housing units, and retires and replaces appliances. The primary exogenous drivers for the module are housing starts by type (single-family, multifamily and mobile homes) and Census Division and prices for each energy source for each of the nine Census Divisions (see Figure 5). The Residential Demand Module also requires projections of available equipment and their installed costs over the forecast horizon. Over time, equipment efficiency tends to increase because of general technological advances and also because of Federal and/or state efficiency standards. As energy prices and available equipment changes over the forecast horizon, the module includes projected changes to the type and efficiency of equipment purchased as well as projected changes in the usage intensity of the equipment stock.

358

Module Handbook Specialisation Photovoltaics  

E-Print Network (OSTI)

#12;Specialisation Photovoltaics, University of Northumbria Module 1/Photovoltaics: PHOTOVOLTAIC CELL AND MODULE TECHNOLOGY Module name: PHOTOVOLTAIC CELL AND MODULE TECHNOLOGY Section EUREC · Chemistry · Physics Target learning outcomes The module Photovoltaic Cell and Module Technology teaches

Habel, Annegret

359

"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

360

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

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

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.

362

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

363

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

364

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

365

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 ...

366

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

367

Assumptions  

Gasoline and Diesel Fuel Update (EIA)

to the to the Annual Energy Outlook 1998 December 1997 Energy Information Administration Office of Integrated Analysis and Forecasting U.S. Department of Energy Washington, DC 20585 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Macroeconomic Activity Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 International Energy Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 Household Expenditures Module. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 Residential Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 Commercial Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 Industrial Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 Transportation Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 Electricity Market Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 Oil and Gas Supply Module

368

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 ...

369

EIA-Assumptions to the Annual Energy Outlook - Residential Demand Module  

Gasoline and Diesel Fuel Update (EIA)

Residential Demand Module Residential Demand Module Assumptions to the Annual Energy Outlook 2007 Residential Demand Module Figure 5. United States Census Divisions. Need help, contact the National Energy Information Center at 202-586-8800. The NEMS Residential Demand Module forecasts future residential sector energy requirements based on projections of the number of households and the stock, efficiency, and intensity of use of energy-consuming equipment. The Residential Demand Module projections begin with a base year estimate of the housing stock, the types and numbers of energy-consuming appliances servicing the stock, and the "unit energy consumption" by appliance (or UEC-in million Btu per household per year). The projection process adds new housing units to the stock, determines the equipment installed in new

370

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.

371

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

372

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

373

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

374

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

375

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.

376

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

377

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

378

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

379

Thermionic modules  

DOE Patents (OSTI)

Modules of assembled microminiature thermionic converters (MTCs) having high energy-conversion efficiencies and variable operating temperatures manufactured using MEMS manufacturing techniques including chemical vapor deposition. The MTCs incorporate cathode to anode spacing of about 1 micron or less and use cathode and anode materials having work functions ranging from about 1 eV to about 3 eV. The MTCs also exhibit maximum efficiencies of just under 30%, and thousands of the devices and modules can be fabricated at modest costs.

King, Donald B. (Albuquerque, NM); Sadwick, Laurence P. (Salt Lake City, UT); Wernsman, Bernard R. (Clairton, PA)

2002-06-18T23:59:59.000Z

380

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

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

Relationships between US consumer expenditures on communications and transportation using almost ideal demand system modeling: 1984-2002  

E-Print Network (OSTI)

diture elasticity Price elasticity Non-PV Marshallian (impact of a change in PV capital prices on expenditures forin the non-PV category are own-price elastic, consistent

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

2007-01-01T23:59:59.000Z

382

Diacylglycerol Oil, 2nd Edition Chapter 5 The Effect of Diacylglycerols on Energy Expenditure and Substrate Utilization in Humans  

Science Conference Proceedings (OSTI)

Diacylglycerol Oil, 2nd Edition Chapter 5 The Effect of Diacylglycerols on Energy Expenditure and Substrate Utilization in Humans Food Science Health Nutrition Biochemistry eChapters Food Science & Technology Health - Nutrition - Bioc

383

Diacylglycerol Oil, 2nd EditionChapter 4 Activation of Lipid Metabolism and Energy Expenditure by Dietary Diacylglycerol  

Science Conference Proceedings (OSTI)

Diacylglycerol Oil, 2nd Edition Chapter 4 Activation of Lipid Metabolism and Energy Expenditure by Dietary Diacylglycerol Food Science Health Nutrition Biochemistry eChapters Food Science & Technology Health - Nutrition - Biochemistry

384

Nonresidential buildings energy consumption survey: 1979 consumption and expenditures. Part 2. Steam, fuel oil, LPG, and all fuels  

Science Conference Proceedings (OSTI)

This report presents data on square footage and on total energy consumption and expenditures for commercial buildings in the contiguous United States. Also included are detailed consumption and expenditures tables for fuel oil or kerosene, liquid petroleum gas (LPG), and purchased steam. Commercial buildings include all nonresidential buildings with the exception of those where industrial activities occupy more of the total square footage than any other type of activity. 7 figures, 23 tables.

Patinkin, L.

1983-12-01T23:59:59.000Z

385

New America Foundation Working Paper The Price-Induced Energy Trap Exploring the Impacts of Transportation Expenditures on the American Economy  

E-Print Network (OSTI)

Even though the U.S. economy grows at an anemic rate of perhaps 1.5 percent and 1.9 percent (or less) in this year and next, the world economy is likely to expand by well over 3 percent in that same two-year period. The world demand for oil is expected to increase, concurrently, by about 1.5 percent annually. The most recent projections by the U.S. Energy Information Administration (EIA 2011a) suggest that – absent major disruptions – the growing demand for energy worldwide will continue to push oil prices up in a slow but steady movement. Absent dramatic changes in U.S. energy policy, consumers are likely to continue to pay high and volatile prices. Despite an anticipated 1.8 percent decline this year in gasoline consumption, for example, the overall expenditures for gasoline will increase 25 percent, rising from $391 billion dollars in 2010 to $489 billion dollars in 2011. Both the size of the U.S. gasoline bill, and its dependence on global events, impact the lives and well-being of individuals, families, and households – especially those from the middle and lower income levels. And as consumers ’ incomes, already shrinking in the after-effects of the recession, continue to be absorbed by high fuel costs, gasoline is becoming a drag on the economy. How will U.S. policy makers navigate the future? For decades price has been the focus of policy-maker’s attention. Policy-byprice has taken three approaches. First, policymakers have tried to keep prices low through subsidies for ethanol and biofuels, increased domestic oil production and an active foreign policy toward oil suppliers, while letting “the market ” (i.e., rising prices),

John A. “skip Laitner; For The Energy Policy Initiative

2011-01-01T23:59:59.000Z

386

Summary of expenditures of rebates from the low-level radioactive waste surcharge escrow account for calendar year 1991  

SciTech Connect

This is the sixth report submitted to Congress under section 5(d)(2)(E)(ii)(II) of the Low-Level Radioactive Waste Policy Act of 1985 (the Act). This section of the Act directs the Department of Energy (DOE) to summarize the annual expenditures of funds disbursed from the DOE surcharge escrow account and to assess compliance of these expenditures with the limitations specified in the Act. In addition to placing limitations on the use of these funds, the Act also requires the nonsited compact regions and nonmember States to provide DOE with an itemized report of their expenditures on December 31 of each year in which funds are expended. Within 6 months after receiving the individual reports, the Act requires the Secretary to furnish Congress with a summary of the reported expenditures and an assessment of compliance with the specified usage limitations. This report fulfills that requirement. DOE disbursed funds totaling $15,037,778.91 to the States and compact regions following the July 1, 1986, January 1, 1988, and January 1, 1990, milestones specified in the Act. Of this amount, $3,517,020.56 was expended during calendar year 1991 and $6,602,546.24 was expended during the prior 5 years. At the end of December 1991, $4,918,212.11 was unexpended. DOE has reviewed each of the reported expenditures and concluded that all reported expenditures comply with the spending limitations stated in section 5(d)(2)(E)(i) of the Act.

Not Available

1992-06-01T23:59:59.000Z

387

Indoor Secondary Pollutants from Household Product Emissions in the  

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

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

388

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:

389

Assumptions to the Annual Energy Outlook 2000 - Residential Demand Module  

Gasoline and Diesel Fuel Update (EIA)

Residential Demand Module forecasts future residential sector energy requirements based on projections of the number of households and the stock, efficiency, and intensity of use of energy-consuming equipment. The Residential Demand Module projections begin with a base year estimates of the housing stock, the types and numbers of energy-consuming appliances servicing the stock, and the “unit energy consumption” by appliance (or UEC—in million Btu per household per year). The projection process adds new housing units to the stock, determines the equipment installed in new units, retires existing housing units, and retires and replaces appliances. The primary exogenous drivers for the module are housing starts by type (single-family, multifamily and mobile homes) and Census Division and prices for each energy source for each of the nine Census Divisions. The Residential Demand Module also requires projections of available equipment over the forecast horizon. Over time, equipment efficiency tends to increase because of general technological advances and also because of Federal and/or state efficiency standards. As energy prices and available equipment changes over the forecast horizon, the module includes projected changes to the type and efficiency of equipment purchased as well as projected changes in the usage intensity of the equipment stock.

390

Assumptions to the Annual Energy Outlook 1999 - Residential Demand Module  

Gasoline and Diesel Fuel Update (EIA)

residential.gif (5487 bytes) residential.gif (5487 bytes) The NEMS Residential Demand Module forecasts future residential sector energy requirements based on projections of the number of households and the stock, efficiency, and intensity of use of energy-consuming equipment. The Residential Demand Module projections begin with a base year estimates of the housing stock, the types and numbers of energy-consuming appliances servicing the stock, and the “unit energy consumption” by appliance (or UEC—in million Btu per household per year). The projection process adds new housing units to the stock, determines the equipment installed in new units, retires existing housing units, and retires and replaces appliances. The primary exogenous drivers for the module are housing starts by type (single-family, multifamily and mobile homes) and Census Division and prices for each energy source for each of the nine Census Divisions. The Residential Demand Module also requires projections of available equipment over the forecast horizon. Over time, equipment efficiency tends to increase because of general technological advances and also because of Federal and/or state efficiency standards. As energy prices and available equipment changes over the forecast horizon, the module includes projected changes to the type and efficiency of equipment purchased as well as projected changes in the usage intensity of the equipment stock.

391

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.

392

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***) ...

393

Exemplifying Business Opportunities for Improving Data Quality From Corporate Household Research  

E-Print Network (OSTI)

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

Madnick, Stuart

2004-12-10T23:59:59.000Z

394

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

U.S. Energy Information Administration (EIA)

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

395

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

E-Print Network (OSTI)

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

Klytchnikova, Irina

2006-01-01T23:59:59.000Z

396

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

U.S. Energy Information Administration (EIA)

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

397

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

E-Print Network (OSTI)

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

Leitmann, Josef

1989-01-01T23:59:59.000Z

398

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

Gasoline and Diesel Fuel Update (EIA)

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

399

In the UNITED STATES there are 96.6 million households  

U.S. Energy Information Administration (EIA)

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

400

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

U.S. Energy Information Administration (EIA)

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

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

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

U.S. Energy Information Administration (EIA)

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

402

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

E-Print Network (OSTI)

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

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

2001-01-01T23:59:59.000Z

403

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

E-Print Network (OSTI)

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

Rickwood, Peter

404

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

U.S. Energy Information Administration (EIA)

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

405

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

U.S. Energy Information Administration (EIA)

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

406

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

U.S. Energy Information Administration (EIA)

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

407

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

Reports and Publications (EIA)

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

Michael Laurence

2004-01-01T23:59:59.000Z

408

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

E-Print Network (OSTI)

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

Segtnan, Ida Lund

2011-01-01T23:59:59.000Z

409

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

E-Print Network (OSTI)

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

Letschert, Virginie

2010-01-01T23:59:59.000Z

410

An Analysis of the Price Elasticity of Demand for Household Appliances  

E-Print Network (OSTI)

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

Dale, Larry

2008-01-01T23:59:59.000Z

411

Do Households Smooth Small Consumption Shocks? Evidence from Anticipated and Unanticipated Variation in Home Energy Costs  

E-Print Network (OSTI)

Erik Hurst. 2004. “Consumption vs. Expenditure. ” National14: Attanasio, Orazio. 1999. “Consumption. ” In J.Taylor andThe Life-Cycle Model of Consumption and Saving. ” Journal of

Cullen, Julie Berry; Friedberg, Leora; Wolfram, Catherine

2005-01-01T23:59:59.000Z

412

Photovoltaic module and module arrays  

DOE Patents (OSTI)

A photovoltaic (PV) module including a PV device and a frame. The PV device has a PV laminate defining a perimeter and a major plane. The frame is assembled to and encases the laminate perimeter, and includes leading, trailing, and side frame members, and an arm that forms a support face opposite the laminate. The support face is adapted for placement against a horizontal installation surface, to support and orient the laminate in a non-parallel or tilted arrangement. Upon final assembly, the laminate and the frame combine to define a unitary structure. The frame can orient the laminate at an angle in the range of 3.degree.-7.degree. from horizontal, and can be entirely formed of a polymeric material. Optionally, the arm incorporates integral feature(s) that facilitate interconnection with corresponding features of a second, identically formed PV module.

Botkin, Jonathan (El Cerrito, CA); Graves, Simon (Berkeley, CA); Lenox, Carl J. S. (Oakland, CA); Culligan, Matthew (Berkeley, CA); Danning, Matt (Oakland, CA)

2012-07-17T23:59:59.000Z

413

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

Science Conference Proceedings (OSTI)

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

Anna Zandanel

2011-09-01T23:59:59.000Z

414

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

Science Conference Proceedings (OSTI)

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

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

2012-07-01T23:59:59.000Z

415

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

Science Conference Proceedings (OSTI)

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

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

1981-03-01T23:59:59.000Z

416

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

Science Conference Proceedings (OSTI)

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

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

2012-02-01T23:59:59.000Z

417

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

Science Conference Proceedings (OSTI)

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

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

2009-09-01T23:59:59.000Z

418

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

419

Load Component Database of Household Appliances and Small Office Equipment  

Science Conference Proceedings (OSTI)

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

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

2008-07-24T23:59:59.000Z

420

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

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

Do You Encourage Everyone in Your Household to Save Energy? Do You Encourage Everyone in Your Household to Save Energy? How Do You Encourage Everyone in Your Household to Save Energy? June 18, 2009 - 5:25pm Addthis Anyone who has decided to save energy at home knows that the entire household needs to be involved if you really want to see savings. Some people-be they roommates, spouses, children, or maybe even yourself-just seem to need some extra reminders to take simple energy-saving steps. How do you encourage everyone in your household to save energy? Each Thursday, you have the chance to share your thoughts on a topic related to energy efficiency or renewable energy for consumers. Please comment with your answers, and also feel free to respond to other comments. Addthis Related Articles How Have You Helped Someone Else Save Energy?

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

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

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

Everyone in Your Household to Save Energy? Everyone in Your Household to Save Energy? How Do You Encourage Everyone in Your Household to Save Energy? June 18, 2009 - 5:25pm Addthis Anyone who has decided to save energy at home knows that the entire household needs to be involved if you really want to see savings. Some people-be they roommates, spouses, children, or maybe even yourself-just seem to need some extra reminders to take simple energy-saving steps. How do you encourage everyone in your household to save energy? Each Thursday, you have the chance to share your thoughts on a topic related to energy efficiency or renewable energy for consumers. Please comment with your answers, and also feel free to respond to other comments. Addthis Related Articles How Have You Helped Someone Else Save Energy?

422

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

SciTech Connect

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

Leach, G.; Gowen, M.

1987-01-01T23:59:59.000Z

423

TOB Module Assembly  

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

SiTracker Home Page Participating Institutions and Principal Contacts Useful Links Notes Images TOB Module Assembly and Testing Project TOB Integration Data Tracker Offline DQM LHC Fluence Calculator Total US Modules Tested Graph Total US Modules Tested Graph Total US Modules Tested Total US Modules Tested US Modules Tested Graph US Modules Tested Graph US Modules Tested US Modules Tested Rod Assembly TOB Modules on a Rod TOB Rod Insertion Installation of a TOB Rod Completed TOB Completed Tracker Outer Barrel TOB Module Assembly and Testing Project All 5208 modules of the CMS Tracker Outer Barrel were assembled and tested at two production sites in the US: the Fermi National Accelerator Laboratory and the University of California at Santa Barbara. The modules were delivered to CERN in the form of rods, with the last shipment taking

424

Buildings Energy Data Book: 4.3 Federal Buildings and Facilities Expenditures  

Buildings Energy Data Book (EERE)

2 2 Annual Energy Expenditures per Gross Square Foot of Federal Floorspace Stock, by Year ($2010) FY 1985 2.13 FY 2000 1.36 FY 2001 1.58 FY 2002 1.49 FY 2003 1.45 FY 2004 1.54 FY 2005 1.59 FY 2006 2.01 (1) FY 2007 2.01 Note(s): Source(s): Total Federal buildings and facilities energy expenditures in FY 2006 were $5.79 billion (in $2010). 1) Increase due to change in FEMP categorization of Federal buildings. DOE/FEMP, Annual Report to Congress on FEMP FY 2007, Jan. 2010, Table A-9, p. 97 and Table 1, p. 13; DOE/FEMP, Annual Report to Congress on FEMP, Nov. 2008, Table A-9, p. 78 for energy costs, and Table 1, p. 12 for floorspace for 2006; DOE/FEMP, Annual Report to Congress on FEMP, Sep. 2006, Table A-12, p. 158 for energy costs for 1985-2005; DOE/FEMP, Annual Report on FEMP, Dec. 2002, Table 8-A, p. 61 for 2000; DOE/FEMP, Annual

425

Summary of expenditures of rebates from the low-level radioactive waste surcharge escrow account for calendar year 1992  

SciTech Connect

This is the seventh report submitted to Congress in accordance with section 5(d)(2)(E)(ii)(II) of Title I--Low-Level Radioactive Waste Policy Amendments Act of 1985 (the Act). This section of the Act directs the Department of Energy (DOE) to summarize the annual expenditures of funds disbursed from the DOE surcharge escrow account and to assess compliance of these expenditures with the limitations specified in the Act. In addition to placing limitations on the use of these funds, the Act also requires the nonsited compact regions and nonmember States to provide DOE with an itemized report of their expenditures on December 31 of each year in which funds are expended. Within 6 months after receiving the individual reports, the Act requires the Secretary to furnish Congress with a summary of the reported expenditures and an assessment of compliance with the specified usage limitations. This report fulfills that requirement. DOE disbursed funds totaling $15,037,778.91 to the States and compact regions following the July 1, 1986, January 1, 1988, and January 1, 1990, milestones specified in the Act. Of this amount, $1,445,701.61 was expended during calendar year 1992 and $10,026,763.87 was expended during the prior 6 years. At the end of December 1992, $3,565,313.43 was unexpended. DOE has reviewed each of the reported expenditures and concluded that all reported expenditures comply with the spending limitations stated in section 5(d)(2)(E)(i) of the Act.

Not Available

1993-06-01T23:59:59.000Z

426

Energy consumption and expenditure projections by income quintile on the basis of the Annual Energy Outlook 1997 forecast  

SciTech Connect

This report presents an analysis of the relative impacts of the base-case scenario used in the Annual Energy Outlook 1997, published by the US Department of Energy, Energy Information Administration, on income quintile groups. Projected energy consumption and expenditures, and projected energy expenditures as a share of income, for the period 1993 to 2015 are reported. Projected consumption of electricity, natural gas, distillate fuel, and liquefied petroleum gas over this period is also reported for each income group. 33 figs., 11 tabs.

Poyer, D.A.; Allison, T.

1998-03-01T23:59:59.000Z

427

Development of the TRANSIMS environmental module  

DOE Green Energy (OSTI)

The TRansportation ANalysis and SIMulation System (TRANSIMS) is one part of the multi-track Travel Model Improvement Program sponsored by the US Department of Transportation, the Environmental Protection Agency, and Department of Energy. Los Alamos National Laboratory is leading this major effort to develop a new, integrated transportation and air quality forecasting procedures necessary to satisfy the Intermodal Surface Transportation Efficiency Act and the Clean Air Act and its amendments. TRANSIMS is a set of integrated analytical and simulation models and supporting data bases. The TRANSIMS methods deal with individual behavioral units and proceed through several steps to estimate travel. TRANSIMS predicts trips for individual households, residents and vehicles rather than for zonal aggregations of households. TRANSIMS also predicts the movement of individual freight loads. A regional microsimulation executes the generated trips on the transportation network, modeling the individual vehicle interactions and predicting the transportation system performance. The purpose of the environmental module is to translate traveler behavior into consequent air quality, energy consumption, and carbon dioxide emissions. Transportation systems play a significant role in urban air quality, energy consumption, and carbon-dioxide emissions.

Williams, M.D.; Thayer, G.; Smith, L.R. [Los Alamos National Lab., NM (United States). Technology and Safety Assessment Div.

1997-05-01T23:59:59.000Z

428

The more you spend, the more you get? The effects of R&D and capital expenditures on the patenting activities of biotechnology firms  

Science Conference Proceedings (OSTI)

This paper provides evidence on the mechanisms influencing the patent output of a sample of small and large, entrepreneurial and established biotechnology firms from the input of indirect knowledge acquired from capital expenditures and direct ... Keywords: Biotechnology, Capital expenditure, L25, L65, O34, Patents, Poisson models, R&D

Roberta Piergiovanni; Enrico Santarelli

2013-02-01T23:59:59.000Z

429

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

E-Print Network (OSTI)

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

Lopez Cabrera, Jesus 1977-

2012-12-01T23:59:59.000Z

430

Ballasted photovoltaic module and module arrays  

DOE Patents (OSTI)

A photovoltaic (PV) module assembly including a PV module and a ballast tray. The PV module includes a PV device and a frame. A PV laminate is assembled to the frame, and the frame includes an arm. The ballast tray is adapted for containing ballast and is removably associated with the PV module in a ballasting state where the tray is vertically under the PV laminate and vertically over the arm to impede overt displacement of the PV module. The PV module assembly can be installed to a flat commercial rooftop, with the PV module and the ballast tray both resting upon the rooftop. In some embodiments, the ballasting state includes corresponding surfaces of the arm and the tray being spaced from one another under normal (low or no wind) conditions, such that the frame is not continuously subjected to a weight of the tray.

Botkin, Jonathan (El Cerrito, CA); Graves, Simon (Berkeley, CA); Danning, Matt (Oakland, CA)

2011-11-29T23:59:59.000Z

431

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)

432

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

Science Conference Proceedings (OSTI)

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

Goett, A.A.

1984-02-01T23:59:59.000Z

433

A Reliable Natural Language Interface to Household Appliances  

E-Print Network (OSTI)

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

Alexander Yates

2003-01-01T23:59:59.000Z

434

Laboratory Testing of Demand-Response Enabled Household Appliances  

SciTech Connect

With the advent of the Advanced Metering Infrastructure (AMI) systems capable of two-way communications between the utility's grid and the building, there has been significant effort in the Automated Home Energy Management (AHEM) industry to develop capabilities that allow residential building systems to respond to utility demand events by temporarily reducing their electricity usage. Major appliance manufacturers are following suit by developing Home Area Network (HAN)-tied appliance suites that can take signals from the home's 'smart meter,' a.k.a. AMI meter, and adjust their run cycles accordingly. There are numerous strategies that can be employed by household appliances to respond to demand-side management opportunities, and they could result in substantial reductions in electricity bills for the residents depending on the pricing structures used by the utilities to incent these types of responses.The first step to quantifying these end effects is to test these systems and their responses in simulated demand-response (DR) conditions while monitoring energy use and overall system performance.

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

2013-10-01T23:59:59.000Z

435

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...

436

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...

437

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...

438

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...

439

Summary of expenditures of rebates from the low-level radioactive waste surcharge escrow account for calendar year 1990  

SciTech Connect

This is the fifth report submitted to Congress under Title 1, section 5(d)(2)(E) of Public Law 99--240, The Low-Level Radioactive Waste Policy Amendments Act of 1985'' (the Act). This section of the Act requests the Department of Energy (DOE) to summarize the annual expenditures of funds disbursed from the DOE surcharge escrow account and to assess compliance of these expenditures with the specified limitations. The Act places limitations on the use of these funds and requires the nonsited compact regions and nonmember States to provide DOE with an itemized report of their expenditures on December 31 of each year in which funds are expended. Within 6 months after receiving the individual reports, DOE is to furnish Congress a summary of the reported expenditures and an assessment of compliance with the limitations on the use of these funds specified in the Act. This report fulfills that requirements. DOE disbursed funds totaling $15,006,587.76 to the States and compact regions following the July 1, 1986, January 1, 1988, and January 1, 1990, milestones. Of this amount, $4,328,340.44 was expended during calendar year 1990 and $2,239,205.80 was expended during the prior 4 years. At the end of December 1990, $8,439,041.52 was unexpended. 5 tabs.

Not Available

1991-06-01T23:59:59.000Z

440

Nonlinear Dynamics in an OLG Growth Model with Young and Old Age Labour Supply: The Role of Public Health Expenditure  

Science Conference Proceedings (OSTI)

This study analyses the dynamics of a two-dimensional overlapping generations economy with young and old age labour supply. We show that the public provision of investments in health, which, in turn, affects the demand for material consumption of the ... Keywords: C62, C68, Chaos, I18, J22, Labour supply, O41, OLG model, Public health expenditure

Luca Gori; Mauro Sodini

2011-10-01T23:59:59.000Z

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

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

E-Print Network (OSTI)

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

Quigley, John M.

2005-01-01T23:59:59.000Z

442

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

E-Print Network (OSTI)

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

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

2009-01-01T23:59:59.000Z

443

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

U.S. Energy Information Administration (EIA)

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

444

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

E-Print Network (OSTI)

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

Madnick, Stuart

2004-02-06T23:59:59.000Z

445

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

U.S. Energy Information Administration (EIA)

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

446

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

U.S. Energy Information Administration (EIA)

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

447

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

U.S. Energy Information Administration (EIA)

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

448

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

E-Print Network (OSTI)

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

Tullos, Desiree

449

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

E-Print Network (OSTI)

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

Green, Vanessa (Vanessa Layton)

2008-01-01T23:59:59.000Z

450

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

Science Conference Proceedings (OSTI)

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

Carolyn Kousky

2013-10-01T23:59:59.000Z

451

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

E-Print Network (OSTI)

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

Rausch, Sebastian

452

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

U.S. Energy Information Administration (EIA)

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

453

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

U.S. Energy Information Administration (EIA)

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

454

Households to pay more than expected to stay warm this winter  

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

stay warm this winter Following a colder-than-expected November, U.S. households are forecast to consume more heating fuels than previously expected....resulting in higher heating...

455

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

E-Print Network (OSTI)

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

Stevenson, Matthew M

2009-01-01T23:59:59.000Z

456

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

Science Conference Proceedings (OSTI)

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

Sonia Frutos; Ernestina Menasalvas; Cesar Montes; Javier Segovia

2003-12-01T23:59:59.000Z

457

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

E-Print Network (OSTI)

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

2002-01-01T23:59:59.000Z

458

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

E-Print Network (OSTI)

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

Kurani, Kenneth; Turrentine, Thomas; Sperling, Daniel

1996-01-01T23:59:59.000Z

459

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

Gasoline and Diesel Fuel Update (EIA)

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

460

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

U.S. Energy Information Administration (EIA)

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

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

NERSC Modules Software Environment  

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

Environment » Modules Environment Environment » Modules Environment Modules Software Environment NERSC uses the module utility to manage nearly all software. There are two huge advantages of the module approach: NERSC can provide many different versions and/or installations of a single software package on a given machine, including a default version as well as several older and newer versions; and Users can easily switch to different versions or installations without having to explicitly specify different paths. With modules, the MANPATH and related environment variables are automatically managed. Users simply ``load'' and ``unload'' modules to control their environment. The module utility consists of two parts: the module command itself and the modulefiles on which it operates. Module Command

462

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.

463

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

Science Conference Proceedings (OSTI)

Although the Nordic countries were among the first to develop competition in the electricity industry, it took a long time to make retail competition work. In Norway and Sweden a considerable number of households are actively using the market but very few households are active in Finland and Denmark. One problem has been institutional barriers involving metering, limited unbundling of distribution and supply, and limited access to reliable information on contracts and prices. (author)

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

2006-11-15T23:59:59.000Z

464

Overview of CFC replacement issues for household refrigeration  

Science Conference Proceedings (OSTI)

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

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

1991-01-01T23:59:59.000Z

465

Overview of CFC replacement issues for household refrigeration  

Science Conference Proceedings (OSTI)

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

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

1991-12-31T23:59:59.000Z

466

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

467

Improving Demographic Components of Integrated Assessment Models: The Effect of Changes in Population Composition by Household Characteristics  

SciTech Connect

This report describes results of the research project on "Improving Demographic Components of Integrated Assessment Models: The Effect of Changes in Population Composition by Household Characteristics". The overall objective of this project was to improve projections of energy demand and associated greenhouse gas emissions by taking into account demographic factors currently not incorporated in Integrated Assessment Models (IAMs) of global climate change. We proposed to examine the potential magnitude of effects on energy demand of changes in the composition of populations by household characteristics for three countries: the U.S., China, and Indonesia. For each country, we planned to analyze household energy use survey data to estimate relationships between household characteristics and energy use; develop a new set of detailed household projections for each country; and combine these analyses to produce new projections of energy demand illustrating the potential importance of consideration of households.

Brian C. O'Neill

2006-08-09T23:59:59.000Z

468

Advanced silicon photonic modulators  

E-Print Network (OSTI)

Various electrical and optical schemes used in Mach-Zehnder (MZ) silicon plasma dispersion effect modulators are explored. A rib waveguide reverse biased silicon diode modulator is designed, tested and found to operate at ...

Sorace, Cheryl M

2010-01-01T23:59:59.000Z

469

Special Inquiry on the Office of the Chief Financial Officer's Information Technology Expenditures, OAS-RA-L-12-01  

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

Special Inquiry on the Office of the Special Inquiry on the Office of the Chief Financial Officer's Information Technology Expenditures OAS-RA-L-12-01 November 2011 Department of Energy Washington, DC 20585 November 28, 2011 MEMORANDUM FOR THE DEPUTY SECRETARY FROM: Gregory H. Friedman Inspector General SUBJECT: INFORMATION: Special Report on "Inquiry on the Office of the Chief Financial Officer's Information Technology Expenditures" INTRODUCTION The Office of the Chief Financial Officer (OCFO) is responsible for ensuring the effective management and financial integrity of Department of Energy programs, projects, and resources. To achieve its mission, the OCFO develops, implements, and monitors policies and systems related to areas such as budget administration, program analysis, and strategic planning. The

470

A Look at Commercial Buldings in 1995: Characteristics, Energy Consumption, and Energy Expenditures  

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

DOE/EIA-0625(95) DOE/EIA-0625(95) Distribution Category UC-950 A Look at Commercial Buildings in 1995: Characteristics, Energy Consumption, and Energy Expenditures October 1998 En ergy In for ma tion Ad min istra tion Of fice of En ergy Mar kets and End Use U.S. De part ment of En ergy Wash ing ton, DC 20585 This re port was pre pared by the En ergy In for ma tion Ad min istra tion, the in de pend ent sta tis ti cal and ana lytic agency within the U.S. De part ment of En ergy. The in for ma tion con tained herein should be at trib uted to the En ergy In for ma tion Ad min istra tion and should not be con strued as ad vo cat ing or re flect ing any pol icy po si tion of the De part ment of En ergy or any other or gani za tion. Contacts The En ergy In for ma tion Ad min istra tion (EIA) pre pared this pub li ca tion un der the gen eral di rec tion of W. Cal vin

471

Modulating lignin in plants  

DOE Patents (OSTI)

Materials and methods for modulating (e.g., increasing or decreasing) lignin content in plants are disclosed. For example, nucleic acids encoding lignin-modulating polypeptides are disclosed as well as methods for using such nucleic acids to generate transgenic plants having a modulated lignin content.

Apuya, Nestor; Bobzin, Steven Craig; Okamuro, Jack; Zhang, Ke

2013-01-29T23:59:59.000Z

472

"Table HC15.3 Household Characteristics by Four Most Populated States, 2005"  

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

3 Household Characteristics by Four Most Populated States, 2005" 3 Household Characteristics by Four Most Populated States, 2005" " Million U.S. Housing Units" ,"Housing Units (millions)","Four Most Populated States" "Household Characteristics",,"New York","Florida","Texas","California" "Total",111.1,7.1,7,8,12.1 "Household Size" "1 Person",30,1.8,1.9,2,3.2 "2 Persons",34.8,2.2,2.3,2.4,3.2 "3 Persons",18.4,1.1,1.3,1.2,1.8 "4 Persons",15.9,1,0.9,1,2.3 "5 Persons",7.9,0.6,0.6,0.9,0.9 "6 or More Persons",4.1,0.4,"Q",0.5,0.7 "2005 Annual Household Income Category" "Less than $9,999",9.9,0.8,0.7,0.9,1 "$10,000 to $14,999",8.5,0.8,0.4,0.6,0.7

473

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

474

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

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

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

475

A dynamic model system of household car ownership, trip generation, and modal split: model development and simulation experiment  

E-Print Network (OSTI)

household car ownership, mode usage, and sociodemographictrip making and mode usage upon car ownership appears to beto predict car ownership and mode usage by the panel

Kitamura, Ryuichi

2009-01-01T23:59:59.000Z

476

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

Science Conference Proceedings (OSTI)

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

Figueroa, M.J.; Sathaye, J.

1993-08-01T23:59:59.000Z

477

Essays on the Consumption and Investment Decisions of Households in the Presence of Housing and Human Capital  

E-Print Network (OSTI)

2 Housing and the Consumption Allocation of Households:of Indivisibility on Housing Consumption Volatility . 2.5and consumption allocation . . . . . . . . . . . . . . .

Betermier, Sebastien

2010-01-01T23:59:59.000Z

478

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

E-Print Network (OSTI)

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

Meyers, Marcia k.

1996-01-01T23:59:59.000Z

479

Load-shifting in a new perspective: Smart scheduling of smart household appliances using an Agent-Bsaed Modelling Approach.  

E-Print Network (OSTI)

??The electricity demand of households in the Netherlands has been growing rapidly for the last decades and will continue to grow in the near future.… (more)

De Blécourt, M.J.

2012-01-01T23:59:59.000Z

480

Summary of expenditures of rebates from the low-level radioactive waste surcharge escrow account for calendar year 1988  

SciTech Connect

This is the third report submitted to Congress under Public Law 99-240, The Low-Level Radioactive Waste Policy Amendments Act of 1985'' (the Act). This section of the Act requires the Department of Energy to summarize the annual expenditures made by states and compacts of funds disbursed from the Department's Surcharge Escrow Account, and to assess the compliance of these expenditures with the specified limitations. This report covers expenditures made during calendar year 1988 from funds disbursed to states and compacts following the July 1, 1986, and January 1, 1988, milestones. The next milestone in the Act is January 1, 1990, following which the accumulated surcharge deposits in the Department's Surcharge Escrow Account will again be disbursed. The Act authorizes states with operating low-level radioactive waste disposal sites (sited states) to collect surcharges on disposal of waste from generators located in compact regions currently without disposal sites (non-sited compacts) and in states that do not have sites and that are not members of compacts (nonmember states). The Act requires the sited states to make a monthly deposit to the Department of Energy's Surcharge Escrow Account of 25 percent of the surcharges they collect. Following each milestone date, the Department is required to disburse these funds, with accrued interest, back to those non-sited compacts and nonmember states found in compliance with the milestone requirements for new disposal site development. 4 tabs.

Not Available

1989-06-01T23:59:59.000Z

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

Competition Helps Kids Learn About Energy and Save Their Households Some  

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

Competition Helps Kids Learn About Energy and Save Their Households Competition Helps Kids Learn About Energy and Save Their Households Some Money Competition Helps Kids Learn About Energy and Save Their Households Some Money May 21, 2013 - 2:40pm Addthis Students can register now to save energy and win prizes with the Home Energy Challenge. Students can register now to save energy and win prizes with the Home Energy Challenge. Eric Barendsen Energy Technology Program Specialist, Office of Energy Efficiency and Renewable Energy How can I participate? Visit HomeEnergyChallenge.org to register for the competition. Third through eighth grade students and teachers will be excited to hear about a competition starting up for next school year that challenges students to learn about energy, develop techniques for saving energy, and

482

"Table HC7.10 Home Appliances Usage Indicators by Household Income, 2005"  

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

0 Home Appliances Usage Indicators by Household Income, 2005" 0 Home Appliances Usage Indicators by Household Income, 2005" " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ,"Housing Units (millions)" ,,"Less than $20,000","$20,000 to $39,999","$40,000 to $59,999","$60,000 to $79,999","$80,000 or More" "Home Appliances Usage Indicators" "Total",111.1,26.7,28.8,20.6,13.1,22,16.6,38.6 "Cooking Appliances" "Frequency of Hot Meals Cooked" "3 or More Times A Day",8.2,2.9,2.5,1.3,0.5,1,2.4,4.6 "2 Times A Day",24.6,6.5,7,4.3,3.2,3.6,4.8,10.3 "Once a Day",42.3,8.8,9.8,8.7,5.1,10,5,12.9

483

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

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

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

484

"Table HC7.5 Space Heating Usage Indicators by Household Income, 2005"  

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

5 Space Heating Usage Indicators by Household Income, 2005" 5 Space Heating Usage Indicators by Household Income, 2005" " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ,"Housing Units (millions)" ,,"Less than $20,000","$20,000 to $39,999","$40,000 to $59,999","$60,000 to $79,999","$80,000 or More" "Space Heating Usage Indicators" "Total U.S. Housing Units",111.1,26.7,28.8,20.6,13.1,22,16.6,38.6 "Do Not Have Heating Equipment",1.2,0.5,0.3,0.2,"Q",0.2,0.3,0.6 "Have Space Heating Equipment",109.8,26.2,28.5,20.4,13,21.8,16.3,37.9 "Use Space Heating Equipment",109.1,25.9,28.1,20.3,12.9,21.8,16,37.3

485

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

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

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

486

NYSERDA's Green Jobs-Green New York Program: Extending Energy Efficiency Financing To Underserved Households  

Science Conference Proceedings (OSTI)

The New York legislature passed the Green Jobs-Green New York (GJGNY) Act in 2009. Administered by the New York State Energy Research and Development Authority (NYSERDA), GJGNY programs provide New Yorkers with access to free or low-cost energy assessments,1 energy upgrade services,2 low-cost financing, and training for various 'green-collar' careers. Launched in November 2010, GJGNY's residential initiative is notable for its use of novel underwriting criteria to expand access to energy efficiency financing for households seeking to participate in New York's Home Performance with Energy Star (HPwES) program.3 The GJGNY financing program is a valuable test of whether alternatives to credit scores can be used to responsibly expand credit opportunities for households that do not qualify for traditional lending products and, in doing so, enable more households to make energy efficiency upgrades.

Zimring, Mark; Fuller, Merrian

2011-01-24T23:59:59.000Z

487

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

488

Use of electricity billing data to determine household energy use fingerprints  

Science Conference Proceedings (OSTI)

Ways to analyze billing data are discussed. The starting point for these analyses is a method developed at Princeton University. Their Scorekeeping model permits decomposition of total household energy use into its weather- and nonweather-sensitive elements; the weather-sensitive portion is assumed proportional to heating degree days. The Scorekeeping model also allows one to compute weather-adjusted energy consumption for each household based on its billing data and model parameters; this is the model's estimate of annual consumption under long-run weather conditions. The methods discussed here extend the Scorekeeping results to identify additional characteristics of household energy use. In particular, the methods classify households in terms of the intensity with which the particular fuel is used for space heating (primary heating fuel vs supplemental heating fuel vs no heating at all with the fuel). In addition, households that use the particular fuel for air conditioning are identified. In essence, the billing data and model results are used to determine household energy use fingerprints. The billing data and model results can also be used to identify and correct anomalous bills. The automated method discussed here identifies anomalously high or low utility bills, which are then dropped before re-estimation of the Scorekeeping model parameters. Alternatively, a pair of bills may be combined if one is very high and a temporally adjacent bill is very low. The Scorekeeping model is then re-estimated after the two bills are combined into one. The methods permit careful examination and analysis of changes in energy use from one year to another.

Hirst, E.; Goeltz, R.; White, D.

1984-08-01T23:59:59.000Z

489

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

490

Form 1: Basic Household Information A B C D E F G H I J K L  

E-Print Network (OSTI)

household? (year) 44 Do your household have a micro-hydro generator? (1 yes; 2 no >>next form) 45 When microhydro; 3 powergrid; 4 other Code 35 1 too expensive; 2 not available; 3 other (specify) #12;ain water; 5 water; 5 river Code 33 1 generator; 2 microhydro; 3 powergrid; 4 other Code 35 1 too expensive; 2

Tullos, Desiree

491

Electricity Market Module  

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

Market Module Market Module This page inTenTionally lefT blank 101 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 Electricity Market Module The NEMS Electricity Market Module (EMM) represents the capacity planning, dispatching, and pricing of electricity. It is composed of four submodules-electricity capacity planning, electricity fuel dispatching, electricity load and demand, and electricity finance and pricing. It includes nonutility capacity and generation, and electricity transmission and trade. A detailed description of the EMM is provided in the EIA publication, Electricity Market Module of the National Energy Modeling System 2013, DOE/EIA-M068(2013). Based on fuel prices and electricity demands provided by the other modules of the NEMS, the EMM determines the most

492

Cyber Security Module  

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

Cyber Security Module Cyber security training is required for all facility users and must be submitted before or upon arrival at the GUV Center. System Requirements and Information...

493

Detailed Course Module Description  

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

Course Module Description Course Module Description Module/Learning Objectives Level of Detail in Module by Audience Consumers Gen Ed/ Community College Trades 1. Energy Issues and Building Solutions High High High Learning Objectives: * Define terms of building science, ecological systems, economics of consumption * Relate building science perspective, ecology, social science * Explain historical energy and environmental issues related to buildings * Compare Site and source energy * Examine the health, safety and comfort issues in buildings * Examine the general context for building solutions (zero energy green home with durability as the goal) * Explain a basic overview of alternative energy (total solar flux) - do we have enough energy * Examine cash flow to homeowners

494

Macroeconomic Activity Module  

Annual Energy Outlook 2012 (EIA)

d022412A. U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2012 18 Macroeconomic Activity Module To reflect uncertainty in the projection of...

495

International Energy Module  

Reports and Publications (EIA)

Summarizes the overall structure of the International Energy Model and its interface with other NEMS modules, mathematical specifications of behavioral relationships, and data sources and estimation methods.

Adrian Geagla

2012-11-05T23:59:59.000Z

496

International Energy Module  

Reports and Publications (EIA)

Summarizes the overall structure of the International Energy Model and its interface with other NEMS modules, mathematical specifications of behavioral relationships, and data sources and estimation methods.

Adrian Geagla

2013-10-22T23:59:59.000Z

497

Household Response To Dynamic Pricing Of Electricity: A Survey Of The  

Open Energy Info (EERE)

Household Response To Dynamic Pricing Of Electricity: A Survey Of The Household Response To Dynamic Pricing Of Electricity: A Survey Of The Experimental Evidence Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Household Response To Dynamic Pricing Of Electricity: A Survey Of The Experimental Evidence Focus Area: Crosscutting Topics: Market Analysis Website: www.hks.harvard.edu/hepg/Papers/2009/The%20Power%20of%20Experimentatio Equivalent URI: cleanenergysolutions.org/content/household-response-dynamic-pricing-el Language: English Policies: "Deployment Programs,Regulations,Financial Incentives" is not in the list of possible values (Deployment Programs, Financial Incentives, Regulations) for this property. DeploymentPrograms: Demonstration & Implementation Regulations: "Mandates/Targets,Cost Recovery/Allocation,Enabling Legislation" is not in the list of possible values (Agriculture Efficiency Requirements, Appliance & Equipment Standards and Required Labeling, Audit Requirements, Building Certification, Building Codes, Cost Recovery/Allocation, Emissions Mitigation Scheme, Emissions Standards, Enabling Legislation, Energy Standards, Feebates, Feed-in Tariffs, Fuel Efficiency Standards, Incandescent Phase-Out, Mandates/Targets, Net Metering & Interconnection, Resource Integration Planning, Safety Standards, Upgrade Requirements, Utility/Electricity Service Costs) for this property.

498

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

499

Recommending energy tariffs and load shifting based on smart household usage profiling  

Science Conference Proceedings (OSTI)

We present a system and study of personalized energy-related recommendation. AgentSwitch utilizes electricity usage data collected from users' households over a period of time to realize a range of smart energy-related recommendations on energy tariffs, ... Keywords: demand response, energy tariffs, load shifting, personalization, recommender systems, smart grid

Joel E. Fischer; Sarvapali D. Ramchurn; Michael Osborne; Oliver Parson; Trung Dong Huynh; Muddasser Alam; Nadia Pantidi; Stuart Moran; Khaled Bachour; Steve Reece; Enrico Costanza; Tom Rodden; Nicholas R. Jennings

2013-03-01T23:59:59.000Z

500