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


1

Household Vehicles Energy Consumption 1991  

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

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...

2

Abstract--Numerous studies have shown that households' consumption is an important part of the total energy consumed  

E-Print Network [OSTI]

appropriate strategies of giving households' effective feedback on their energy consumption. This study, Energy efficiency. I. INTRODUCTION HE energy consumption of households in buildings attracts a lot in the housing sector. Energy consumption in buildings accounts for 39% of Sweden's total final energy

Beigl, Michael

3

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

4

Household vehicles energy consumption 1991  

SciTech Connect (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

5

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

6

Household Vehicles Energy Use Cover Page  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

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

7

Communications on energy Household energy conservation  

Science Journals Connector (OSTI)

This study assesses the influence of attitudinal and socio-economic factors on household energy conservation actions. A household interview survey in Regina, Saskatchewan found that respondents perceive an energy problem, although no association with energy conservation actions was determined. Two attitudinal and five socio-economic variables influence household energy conservation. Energy and monetary savings are available to households through energy conservation. Public awareness of household energy conservation through the media can reinforce existing energy conservation actions and encourage new actions.

Fred A. Curtis; P. Simpson-Housley; S. Drever

1984-01-01T23:59:59.000Z

8

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

9

Household Vehicles Energy Consumption 1991  

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

vehicle aging have an additional but unknown effect on the MPG of individual vehicles. Energy Information AdministrationHousehold Vehicles Energy Consumption 1991 27 Of the...

10

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

11

Household vehicles energy consumption 1994  

SciTech Connect (OSTI)

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

12

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

Gasoline and Diesel Fuel Update (EIA)

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

13

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

14

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

15

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

16

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

17

Household energy consumption and expenditures 1993  

SciTech Connect (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

18

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

19

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.

20

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

Note: This page contains sample records for the topic "household total energy" 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

Microsoft Word - Household Energy Use CA  

Gasoline and Diesel Fuel Update (EIA)

0 20 40 60 80 100 US PAC CA Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US PAC CA Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 2,000 4,000 6,000 8,000 10,000 12,000 US PAC CA Site Consumption kilowatthours $0 $250 $500 $750 $1,000 $1,250 $1,500 US PAC CA Expenditures dollars ELECTRICITY ONLY average per household  California households use 62 million Btu of energy per home, 31% less than the U.S. average. The lower than average site consumption results in households spending 30% less for energy than the U.S. average.  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

22

Microsoft Word - Household Energy Use CA  

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

0 20 40 60 80 100 US PAC CA Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US PAC CA Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 2,000 4,000 6,000 8,000 10,000 12,000 US PAC CA Site Consumption kilowatthours $0 $250 $500 $750 $1,000 $1,250 $1,500 US PAC CA Expenditures dollars ELECTRICITY ONLY average per household  California households use 62 million Btu of energy per home, 31% less than the U.S. average. The lower than average site consumption results in households spending 30% less for energy than the U.S. average.  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

23

Household Vehicles Energy Consumption 1991  

Gasoline and Diesel Fuel Update (EIA)

or More...... 23.1 15.2 197 12.3 10.7 13.0 1.3 12.8 13.0| 6.7 | Race of Householder | White... 135.3 89.5 1,429 89.2 73.9 89.2 9.1 87.5 89.1| 2.0...

24

Survey of Household Energy Use (SHEU)  

E-Print Network [OSTI]

Survey of Household Energy Use (SHEU) 2003 Detailed Statistical Report #12;To obtain additional copies of this or other free publications on energy efficiency, please contact: Energy Publications Office of Energy Efficiency Natural Resources Canada c/o St. Joseph Communications Order Processing Unit

25

Household Vehicles Energy Consumption 1991  

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

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

26

Household Vehicles Energy Consumption 1991  

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

methodology used to estimate these statistics relied on data from the 1990 Residential Energy Consumption Survey (RECS), the 1991 Residential Transportation Energy Consumption...

27

Household transitions to energy efficient lighting  

Science Journals Connector (OSTI)

Abstract New energy efficient lighting technologies can significantly reduce household electricity consumption, but adoption has been slow. A unique dataset of German households is used in this paper to examine the factors associated with the replacement of old incandescent lamps (ILs) with new energy efficient compact fluorescent lamps (CFLs) and light emitting diodes (LEDs). The rebound effect of increased lamp luminosity in the transition to energy efficient bulbs is analyzed jointly with the replacement decision to account for household self-selection in bulb-type choice. Results indicate that the EU ban on \\{ILs\\} accelerated the pace of transition to \\{CFLs\\} and LEDs, while storage of bulbs significantly dampened the speed of the transition. Higher lighting needs and bulb attributes like energy efficiency, environmental friendliness, and durability spur IL replacement with \\{CFLs\\} or LEDs. Electricity gains from new energy efficient lighting are mitigated by 23% and 47% increases in luminosity for CFL and LED replacements, respectively. Model results suggest that taking the replacement bulb from storage and higher levels of education dampen the magnitude of these luminosity rebounds in IL to CFL transitions.

Bradford Mills; Joachim Schleich

2014-01-01T23:59:59.000Z

28

Delivering Energy Efficiency to Middle Income Single Family Households  

E-Print Network [OSTI]

Neighborhood Program GETS Green Energy Training ServicesGJGEI Green Jobs, Green Energy Initiative CEWO Cleanincome households. The Green Energy Training Services (GETS)

Zimring, Mark

2012-01-01T23:59:59.000Z

29

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.

2012-01-01T23:59:59.000Z

30

ANALYSIS OF CEE HOUSEHOLD SURVEY NATIONAL AWARENESS OF ENERGY STAR  

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

31

Barriers to household investment in residential energy conservation: preliminary assessment  

SciTech Connect (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

32

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.

33

Projecting household energy consumption within a conditional demand framework  

SciTech Connect (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

34

Projecting household energy consumption within a conditional demand framework  

SciTech Connect (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.

1991-01-01T23:59:59.000Z

35

Environmental and Resource Economics Household Energy Demand in Urban China: Accounting for regional prices and rapid  

E-Print Network [OSTI]

growth, China's energy consumption is rising at one of the fastest rates in the world, almost 8% per year over the period 2000-2010. Residential energy consumption has grown even faster than the national total . Although household energy consumption per capita is still low compared to the developed countries

36

Household energy consumption and its demand elasticity in Thailand  

Science Journals Connector (OSTI)

This study concentrates on the analysis of energy consumption, expenditure on oil and LPG use in cars and aims to examine the elasticity effect of various types of oil consumption. By using the Deaton's analysis framework, the cross-sectional data of Thai households economic survey 2009 were used. By defining energy goods in the scope of automobile fuel, the results reflect the low importance of high-quality automobile fuel on all income level households. Thai households tend to vary the quality rather than the quantity of thermal energy. All income groups have a tendency to switch to lower quality fuel. Middle and high-middle households (Q3 and Q4) are the income groups with the greatest tendency to switch to lower-quality fuel when a surge in the price of oil price occurs. The poorest households (Q1) are normally insensitive to a change of energy expenditure in terms of quality and quantity. This finding illustrates the LPG price subsidy policy favours middle and high-middle income households. The price elasticity of energy quantity demand is negative in all income levels. High to middle income families are the most sensitive to changes in the price of energy.

Montchai Pinitjitsamut

2012-01-01T23:59:59.000Z

37

Water Related Energy Use in Households and Cities - an Australian  

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

38

Residential Energy Consumption Survey Results: Total Energy Consumption,  

Open Energy Info (EERE)

Survey Results: Total Energy Consumption, Survey Results: Total Energy Consumption, Expenditures, and Intensities (2005) Dataset Summary Description The Residential Energy Consumption Survey (RECS) is a national survey that collects residential energy-related data. The 2005 survey collected data from 4,381 households in housing units statistically selected to represent the 111.1 million housing units in the U.S. Data were obtained from residential energy suppliers for each unit in the sample to produce the Consumption & Expenditures data. The Consumption & Expenditures and Intensities data is divided into two parts: Part 1 provides energy consumption and expenditures by census region, population density, climate zone, type of housing unit, year of construction and ownership status; Part 2 provides the same data according to household size, income category, race and age. The next update to the RECS survey (2009 data) will be available in 2011.

39

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

40

Delivering Energy Efficiency to Middle Income Single Family Households  

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

Note: This page contains sample records for the topic "household total energy" 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

Energy Consumption of Refrigerators in Ghana - Outcomes of Household  

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

42

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

43

Household Vehicles Energy Use: Latest Data & Trends  

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

E N E R G Y O V E RV I E W ENERGY INFORMATION ADMINISTRATIONHOUSEHOLD VEHICLES ENERGY USE: LATEST DATA & TRENDS ENERGY OVERVIEW E N E R G Y O V E RV I E W INTRODUCTION Author's...

44

Energy demand of German households and saving potential  

Science Journals Connector (OSTI)

The implementation of the principles of sustainable development requires both using potentialities in saving resources and cutting down emissions (efficiency strategies) as well as more conscious patterns of behaviour of the actors involved (sufficiency strategies). Starting from the current situation of annual CO2 emissions of about 10 t and a sustainability goal of 1??2 t CO2 emissions per inhabitant and year, the question arises in how far households can contribute to achieve this goal. Therefore, in this paper, the environmental impacts of the energy demand of German households will be evaluated by means of describing its status quo and there from deriving saving potentials.

Anke Eber; Dominik Most; Otto Rentz; Thomas Lutzkendorf

2008-01-01T23:59:59.000Z

45

The impact of the Persian Gulf crisis on household energy consumption and expenditure patterns  

SciTech Connect (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

46

Energy Perspectives, Total Energy - Energy Information Administration  

Gasoline and Diesel Fuel Update (EIA)

Total Energy Total Energy Glossary › FAQS › Overview Data Monthly Annual Analysis & Projections this will be filled with a highchart PREVIOUSNEXT Energy Perspectives 1949-2011 September 2012 PDF | previous editions Release Date: September 27, 2012 Introduction Energy Perspectives is a graphical overview of energy history in the United States. The 42 graphs shown here reveal sweeping trends related to the Nation's production, consumption, and trade of energy from 1949 through 2011. Energy Flow, 2011 (Quadrillion Btu) Total Energy Flow diagram image For footnotes see here. Energy can be grouped into three broad categories. First, and by far the largest, is the fossil fuels-coal, petroleum, and natural gas. Fossil fuels have stored the sun's energy over millennia past, and it is primarily

47

Household Vehicles Energy Use: Latest Data & Trends  

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

This page left blank. E N E R G Y O V E RV I E W ENERGY INFORMATION ADMINISTRATIONHOUSEHOLD VEHICLES ENERGY USE: LATEST DATA & TRENDS ENERGY OVERVIEW E N E R G Y O V E RV I E W...

48

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

49

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.

50

Household Vehicles Energy Use: Latest Data & Trends  

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

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...

51

Lifestyle change and energy use in Japan: Household equipment and energy consumption  

Science Journals Connector (OSTI)

Energy use in the Japanese residential sector has more than doubled (on a per-household basis) during the post-war period. Important factors contributing to the increase include changes in the types of housing built, heating, cooling, water-heating equipment, and other appliances. In this paper, the developments of household equipment and living conditions in Japan are described, from their 1950s state to the present. Trends in energy consumption by fuel types and end uses are reviewed over the same period. The past trends are combined with expectations for future developments in household equipment and quality, as well as with international comparisons of household-energy use, to predict further increases in household-energy consumption. The results indicate the importance of a renewed emphasis on energy efficiency in the residential sector.

Hidetoshi Nakagami

1996-01-01T23:59:59.000Z

52

Household Vehicles Energy Consumption 1994 - Appendix C  

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

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

53

total energy | OpenEI  

Open Energy Info (EERE)

total energy total energy Dataset Summary Description This dataset comes from the Energy Information Administration (EIA), and is part of the 2011 Annual Energy Outlook Report (AEO2011). This dataset is table 1, and contains only the reference case. The dataset uses quadrillion BTUs, and quantifies the energy prices using U.S. dollars. The data is broken down into total production, imports, exports, consumption, and prices for energy types. Source EIA Date Released April 26th, 2011 (3 years ago) Date Updated Unknown Keywords 2011 AEO consumption EIA export import production reference case total energy Data application/vnd.ms-excel icon AEO2011: Total Energy Supply, Disposition, and Price Summary - Reference Case (xls, 112.8 KiB) Quality Metrics Level of Review Peer Reviewed

54

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

55

Greenhouse Gas Implications of Household Energy Technology in Kenya  

Science Journals Connector (OSTI)

Energy and Resources Group, University of California, Berkeley, California 94720-3050, Risk, Resource, and Environmental Management Division, Resources for the Future, 1616 P Street NW, Washington, D.C. 20036, and Goldman School of Public Policy, University of California, Berkeley, California 94720-7320 ... Household energy policy is further complicated because charcoal markets in many sub-Saharan African countries operate within a complex political economy that can be hard to characterize and still more difficult to regulate. ... While charcoal consumption carries a larger burden of GHG emissions than firewood use, it also has more potential to attract investment in GHG mitigation activities. ...

Rob Bailis; Majid Ezzati; Daniel M. Kammen

2003-04-01T23:59:59.000Z

56

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

SciTech Connect (OSTI)

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

57

Rural household energy consumption and its implications for eco-environments in NW China: A case study  

Science Journals Connector (OSTI)

Abstract Rural household energy consumption plays an essential role in the daily life of farmers, especially in developing regions. In this paper, we present a study of household energy consumption in terms of energy sources and energy end uses, and analysis of technical and economic issues associated with the use of biomass and renewable energy and the replacement of fossil fuels. Results show that energy from biomass represents the largest share of total energy supply, and that 41.15% of total energy is consumed for home heating and cooking. The average cost of household energy is 1259 RMB ($US193.6) and this expense is no longer subsidized by the government. It takes less than one year to make a solar stove profitable and less than two years to pay back the household cost of biogas digesters. An 8m3 digester can produce as much energy as 500550kg of standard coal or 940kg of firewood, while a solar stove can generate 1.76נ103MJ heat each year. Moreover, it is estimated that in rural China the annual reduction of CO2 and SO2 emissions in 2020, due to the replacement of fossil fuel by biomass, will be 68.86נ106 and 54.37נ104 tons, respectively. Overall, the investigations and analyses have revealed that the structure of rural household energy consumption is undergoing a transformation from traditional low-efficiency biomass domination to integrated consumption of traditional and renewable energies. Renewable energy will significantly contribute to the sustainable development of rural households.

Hewen Niu; Yuanqing He; Umberto Desideri; Peidong Zhang; Hongyi Qin; Shijin Wang

2014-01-01T23:59:59.000Z

58

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

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

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?

59

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

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

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?

60

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

SciTech Connect (OSTI)

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

Note: This page contains sample records for the topic "household total energy" 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

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

SciTech Connect (OSTI)

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

62

National Fuel Cell and Hydrogen Energy Overview: Total Energy...  

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

and Hydrogen Energy Overview: Total Energy USA 2012 National Fuel Cell and Hydrogen Energy Overview: Total Energy USA 2012 Presentation by Sunita Satyapal at the Total Energy USA...

63

Energy Policy 30 (2002) 815826 Evaluating the health benefits of transitions in household energy  

E-Print Network [OSTI]

as the primary source of domestic energy, has put preventive measures to reduce exposure to indoor air pollutionEnergy Policy 30 (2002) 815­826 Evaluating the health benefits of transitions in household energy for the Future, 1616 P Street NW, Washington, DC 20036, USA b Epidemiology and Burden of Disease Unit, Global

Kammen, Daniel M.

64

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

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

Drivers of U.S. Household Energy Consumption, 1980-2009 February 2015 Independent Statistics & Analysis www.eia.gov U.S. Department of Energy Washington, DC 20585 U.S. Energy...

65

Modelling useful energy demand system as derived from basic needs in the household sector  

Science Journals Connector (OSTI)

Inter-fuel substitution in the household sector depends on whether their target energy use is similar or not. To account ... for the effect of end-use application on energy demand, the concept of useful energy is...

Zahra A. Barkhordar; Yadollah Saboohi

2014-10-01T23:59:59.000Z

66

Relation between total quanta and total energy for aquatic ...  

Science Journals Connector (OSTI)

Jan 22, 1974 ... ment of the total energy and vice versa. From a measurement of spectral irradi- ance ... unit energy (for the wavelength region specified).

2000-01-02T23:59:59.000Z

67

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)

68

Relation between total quanta and total energy for aquatic ...  

Science Journals Connector (OSTI)

Jan 22, 1974 ... havior of the ratio of total quanta to total energy (Q : W) within the spectral region of photosynthetic ..... For blue-green waters, where hRmax lies.

2000-01-02T23:59:59.000Z

69

Competition Helps Kids Learn About Energy and Save Their Households Some  

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

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

70

Solar total energy project Shenandoah  

SciTech Connect (OSTI)

This document presents the description of the final design for the Solar Total Energy System (STES) to be installed at the Shenandoah, Georgia, site for utilization by the Bleyle knitwear plant. The system is a fully cascaded total energy system design featuring high temperature paraboloidal dish solar collectors with a 235 concentration ratio, a steam Rankine cycle power conversion system capable of supplying 100 to 400 kW(e) output with an intermediate process steam take-off point, and a back pressure condenser for heating and cooling. The design also includes an integrated control system employing the supervisory control concept to allow maximum experimental flexibility. The system design criteria and requirements are presented including the performance criteria and operating requirements, environmental conditions of operation; interface requirements with the Bleyle plant and the Georgia Power Company lines; maintenance, reliability, and testing requirements; health and safety requirements; and other applicable ordinances and codes. The major subsystems of the STES are described including the Solar Collection Subysystem (SCS), the Power Conversion Subsystem (PCS), the Thermal Utilization Subsystem (TUS), the Control and Instrumentation Subsystem (CAIS), and the Electrical Subsystem (ES). Each of these sections include design criteria and operational requirements specific to the subsystem, including interface requirements with the other subsystems, maintenance and reliability requirements, and testing and acceptance criteria. (WHK)

None

1980-01-10T23:59:59.000Z

71

National Fuel Cell and Hydrogen Energy Overview: Total Energy...  

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

National Fuel Cell and Hydrogen Energy Overview: Total Energy USA 2012 National Fuel Cell and Hydrogen Energy Overview: Total Energy USA 2012 Presentation by Sunita Satyapal at the...

72

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

SciTech Connect (OSTI)

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

73

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

Gasoline and Diesel Fuel Update (EIA)

... 32.8 17.2 307 13.4 16.1 14.2 2.0 21.3 14.1 Race of Householder White... 149.5 78.3 1,774 77.6...

74

Reforming Household Energy Markets: Some Welfare Effects in the United Catherine Waddams Price  

E-Print Network [OSTI]

Reforming Household Energy Markets: Some Welfare Effects in the United Kingdom by Catherine Waddams remain vulnerable. The implications of these findings for the future of energy markets both in the UK This paper summarises some early effects of deregulating the UK energy sector, focusing on the effects

Feigon, Brooke

75

Using Circuit-Level Power Measurements in Household Energy Management Systems  

E-Print Network [OSTI]

Using Circuit-Level Power Measurements in Household Energy Management Systems Alan Marchiori and Qi to accurately measure en- ergy usage in the home. Measuring energy usage is not dif- ficult, however we must decide what to measure. Whole- home energy measurement is cheap and easy to setup be- cause only one

Han, Qi "Chee"

76

Compare All CBECS Activities: Total Energy Use  

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

Total Energy Use Total Energy Use Compare Activities by ... Total Energy Use Total Major Fuel Consumption by Building Type Commercial buildings in the U.S. used a total of approximately 5.7 quadrillion Btu of all major fuels (electricity, natural gas, fuel oil, and district steam or hot water) in 1999. Office buildings used the most total energy of all the building types, which was not a surprise since they were the most common commercial building type and had an above average energy intensity. Figure showing total major fuel consumption by building type. If you need assistance viewing this page, please call 202-586-8800. Major Fuel Consumption per Building by Building Type Because there were relatively few inpatient health care buildings and they tend to be large, energy intensive buildings, their energy consumption per building was far above that of any other building type.

77

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

78

Delivering Energy Efficiency to Middle Income Single Family Households  

E-Print Network [OSTI]

the residential energy efficiency market is a potentialinstitutions (CDFIs) to market energy improvements. Solve aapproach to energy efficiency market development is

Zimring, Mark

2012-01-01T23:59:59.000Z

79

Delivering Energy Efficiency to Middle Income Single Family Households  

E-Print Network [OSTI]

the residential energy efficiency market is a potentialinstitutions (CDFIs) to market energy improvements. Solve acan open significant markets for energy improvements among

Zimring, Mark

2014-01-01T23:59:59.000Z

80

Delivering Energy Efficiency to Middle Income Single Family Households  

E-Print Network [OSTI]

rentalhousing/Energy_Efficiency_Project/COB_rebates_8.2.11.PDS/rentalhousing/Energy_Efficiency_Project/SmartRegs_Final_s residential energy efficiency loan program November 2010-

Zimring, Mark

2012-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "household total energy" 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

Delivering Energy Efficiency to Middle Income Single Family Households  

E-Print Network [OSTI]

Clean Energy Works Oregon Bill Payment History as a ProxyEnergy and Clean Energy Works Oregon (CEWO), also use utility bill repayment history

Zimring, Mark

2012-01-01T23:59:59.000Z

82

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

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

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

83

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

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

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

84

Delivering Energy Efficiency to Middle Income Single Family Households  

E-Print Network [OSTI]

NASCSP). 2009. Weatherization Assistance Program Fundingof Energys Weatherization Assistance Program with State-2009. National Weatherization Assistance Program Training

Zimring, Mark

2012-01-01T23:59:59.000Z

85

Delivering Energy Efficiency to Middle Income Single Family Households  

E-Print Network [OSTI]

Vermont Energy Investment Corporation NYSERDA New Yorkfor a case study on New Yorks energy efficiency programNew York, the New York State Energy Research and Development

Zimring, Mark

2012-01-01T23:59:59.000Z

86

Delivering Energy Efficiency to Middle Income Single Family Households  

E-Print Network [OSTI]

and Renewable Energy (DOE EERE), Weatherization andand Roya Stanley (DOE EERE) for their support of thisfor Humanity International DOE EERE Department of Energy

Zimring, Mark

2012-01-01T23:59:59.000Z

87

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

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

N April 4, 2012 Extending Efficiency Services to Underserved Households: NYSERDA's Assisted Home Performance with ENERGY STAR Program Since 2001, New York residents have completed over 39,000 energy upgrades through NYSERDA's Home Performance with ENERGY STAR (HPwES) initiative. Approximately one third of these projects have been completed through the Assisted HPwES track, which offers large incentives to middle income

88

Delivering Energy Efficiency to Middle Income Single Family Households  

E-Print Network [OSTI]

energy assessments, title searches, and lien recordings. Theassessments, title searches, and lien recordings. Once INHP

Zimring, Mark

2012-01-01T23:59:59.000Z

89

Delivering Energy Efficiency to Middle Income Single Family Households  

E-Print Network [OSTI]

Energy Efficiency Programs. March 17, 2011. Available here:Efficiency Programs. March 17, 2011. Available here:

Zimring, Mark

2012-01-01T23:59:59.000Z

90

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

91

The influence of energy audits on the energy efficiency investments of private owner-occupied households in the Netherlands  

Science Journals Connector (OSTI)

Abstract Energy audits are promoted as an effective tool to drive investment in energy efficiency measures in the residential sector. Despite operating in many countries for several decades details of the impact of audits are mixed. The aim of research presented here is to explore the role of audits on investment in energy efficiency measures by private owner-occupied householders in the Netherlands. Results showed that the main influence of the energy audit was to confirm information held by householders. A significant portion of audit recommendations was ignored, the main reason being that householders considered their dwellings to be adequately energy efficient. A comparison of audit recipients to non-recipients showed that audit recipients did not adopt, plan to adopt or invest in more energy efficiency measures than non-recipients. In fact non-recipients adopted more and invested more in measures. It is concluded that energy based renovation is driven by householder perception of comfort and acceptable outlay on energy bills and not necessarily to expert technical tailored information on the potential to reduce CO2 emissions and environmental impact. Results support arguments for minimum energy efficiency standards and performance based incentives.

Lorraine Murphy

2014-01-01T23:59:59.000Z

92

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.

93

Household energy use: Applying behavioural economics to understand consumer decision-making and behaviour  

Science Journals Connector (OSTI)

Abstract Household energy conservation has emerged as a major challenge and opportunity for researchers, practitioners and policymakers. Consumers also seem to be gaining greater awareness of the value and need for sustainable energy practices, particularly amid growing public concerns over greenhouse gas emissions and climate change. Yet even with adequate knowledge of how to save energy and a professed desire to do so, many consumers still fail to take noticeable steps towards energy efficiency and conservation. There is often a sizeable discrepancy between peoples self-reported knowledge, values, attitudes and intentions, and their observable behaviourexamples include the well-known knowledge-action gap and value-action gap. But neither is household energy consumption driven primarily by financial incentives and the rational pursuit of material interests. In fact, people sometimes respond in unexpected and undesirable ways to rewards and sanctions intended to shift consumers costbenefit calculus in favour of sustainable behaviours. Why is this so? Why is household energy consumption and conservation difficult to predict from either core values or material interests? By drawing on critical insights from behavioural economics and psychology, we illuminate the key cognitive biases and motivational factors that may explain why energy-related behaviour so often fails to align with either the personal values or material interests of consumers. Understanding these psychological phenomena can make household and community responses to public policy interventions less surprising, and in parallel, can help us design more cost-effective and mass-scalable behavioural solutions to encourage renewable and sustainable energy use among consumers.

Elisha R. Frederiks; Karen Stenner; Elizabeth V. Hobman

2015-01-01T23:59:59.000Z

94

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 EIA’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

95

A comparative multivariate analysis of household energy requirements in Australia, Brazil, Denmark, India and Japan  

Science Journals Connector (OSTI)

In this paper, we appraise sustainable household consumption from a global perspective. Using per capita energy requirements as an indicator of environmental pressure, we focus on the importance of income growth in a cross-country analysis. Our analysis is supported by a detailed within-country analysis encompassing five countries, in which we assess the importance of various socioeconomic-demographic characteristics of household energy requirements. We bring together family expenditure survey data, inputoutput tables, and energy statistics in a multivariate analysis. Instead of a uniform Kuznet's curve, we find that the effect of increasing income varies considerably across countries, even when controlling for socioeconomic and demographic variations. The latter variables show similar influences, but differing importance across countries.

Manfred Lenzen; Mette Wier; Claude Cohen; Hitoshi Hayami; Shonali Pachauri; Roberto Schaeffer

2006-01-01T23:59:59.000Z

96

Household Vehicles Energy Use: Latest Data and Trends  

Reports and Publications (EIA)

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

2005-01-01T23:59:59.000Z

97

TENESOL formerly known as TOTAL ENERGIE | Open Energy Information  

Open Energy Info (EERE)

TENESOL formerly known as TOTAL ENERGIE TENESOL formerly known as TOTAL ENERGIE Jump to: navigation, search Name TENESOL (formerly known as TOTAL ENERGIE) Place la Tour de Salvagny, France Zip 69890 Sector Solar Product Makes polycrystalline silicon modules, and PV-based products such as solar powered pumps. References TENESOL (formerly known as TOTAL ENERGIE)[1] LinkedIn Connections CrunchBase Profile No CrunchBase profile. Create one now! This article is a stub. You can help OpenEI by expanding it. TENESOL (formerly known as TOTAL ENERGIE) is a company located in la Tour de Salvagny, France . References ↑ "TENESOL (formerly known as TOTAL ENERGIE)" Retrieved from "http://en.openei.org/w/index.php?title=TENESOL_formerly_known_as_TOTAL_ENERGIE&oldid=352112" Categories:

98

Hybrid application of biogas and solar resources to fulfill household energy needs: A potentially viable option in rural areas of developing countries  

Science Journals Connector (OSTI)

Abstract The absence of clean cooking facilities and electricity means billions of rural people are deprived of much needed socioeconomic development. Livestock residues (dung) and solar radiation are two renewable energy resources that are abundantly available in rural areas of developing countries. Although it is not feasible for these two resources separately to meet both thermal (cooking) and electricity demands, hybrid applications have not been given due attention. To facilitate integrating these two resources in rural energy planning, and to promote their dissemination through hybrid applications, it is necessary to evaluate their economic merits, and assess their ability to deal with the demands. In this paper, we examine the techno-economic performance of hybrid applications of these two resources by applying a simulation technique using the HOMER tool, and by giving derived cost-saving equations. We also quantify the monetary savings from replacing traditional fuels, and perform a sensitivity analysis on a number of variables (e.g. dung cost, fuelwood cost) to see how they affect the performance of different energy supply alternatives. Furthermore, we examine the practical applicability of the biogas system in the households through a structured survey of 72 ongoing household biogas plants. This study finds that households that have between three and six cattle can potentially meet their cooking and electricity loads through a hybrid implementation of biogas and solar PV (Photovoltaic) system. By replacing conventional fuels households can achieve savings that are more than the total annualized costs incurred for installing new services.

Md. Mizanur Rahman; Mohammad Mahmodul Hasan; Jukka V. Paatero; Risto Lahdelma

2014-01-01T23:59:59.000Z

99

HOUSEHOLD SOLAR POWER SYSTEM.  

E-Print Network [OSTI]

?? Photovoltaic power has become one of the most popular research area in new energy field. In this report, the case of household solar power (more)

Jiang, He

2014-01-01T23:59:59.000Z

100

Total Energy - Data - U.S. Energy Information Administration (EIA)  

Gasoline and Diesel Fuel Update (EIA)

Total Energy Flow, (Quadrillion Btu) Total Energy Flow, (Quadrillion Btu) Total Energy Flow diagram image Footnotes: 1 Includes lease condensate. 2 Natural gas plant liquids. 3 Conventional hydroelectric power, biomass, geothermal, solar/photovoltaic, and wind. 4 Crude oil and petroleum products. Includes imports into the Strategic Petroleum Reserve. 5 Natural gas, coal, coal coke, biofuels, and electricity. 6 Adjustments, losses, and unaccounted for. 7 Natural gas only; excludes supplemental gaseous fuels. 8 Petroleum products, including natural gas plant liquids, and crude oil burned as fuel. 9 Includes 0.01 quadrillion Btu of coal coke net exports. 10 Includes 0.13 quadrillion Btu of electricity net imports. 11 Total energy consumption, which is the sum of primary energy consumption, electricity retail sales, and electrical system energy losses.

Note: This page contains sample records for the topic "household total energy" 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

Energy efficiency in Norwegian households - identifying motivators and barriers with a focus group approach  

Science Journals Connector (OSTI)

This paper describes the theoretical background and results of a focus group study on determinants of energy related behaviour in Norwegian households. 70 Norwegians between 18 and 79 years of age participated in eight focus-groups in four Norwegian cities. The aim of the study was to identify behaviours that Norwegians consider relevant with respect to energy use, the main determinants of those behaviours, as well as barriers against and facilitators of energy efficiency. The most important behaviours from the participants' perspectives were heating, water heating, use of white ware and mobility. The main motivators named were minimising behavioural costs, value orientations, perceived consumer efficacy and social norms. The most important barriers were structural misfits, economic, effort, time consumption, low consumer efficacy and lack of relevant and trustworthy information. The most potent facilitators were economic incentives, gains in comfort, reduced effort, tailored practical information, individual feedback and legislative actions.

Christian A. Klöckner; Bertha M. Sopha; Ellen Matthies; Even Bjørnstad

2013-01-01T23:59:59.000Z

102

Understanding household energy consumption patterns: When West Is Best in Metro Manila  

Science Journals Connector (OSTI)

This paper addresses the topic of energy and development through a multi-disciplinary and systemic approach that combines environmental considerations with a social understanding of consumption. The focus is on electricity usage in the home and specifically lighting and cooling. Set in the urban mega-polis of Metro Manila, the Philippines, energy consumption is first placed in its biophysical perspective: the energy sources and electricity grid are presented, in relation to the Philippines as well as the region. The research findings then explore the social and cultural drivers behind household electricity consumption, revealing in several examples the strong influence of globalizationunderstood here as the flow of people, remittances, images and ideas. Policy recommendations are provided, based on the research results, with concluding remarks relevant to other similar contexts.

Marlyne D. Sahakian

2011-01-01T23:59:59.000Z

103

Residential energy consumption across different population groups : comparative analysis for latino and non-latino households in USA.  

SciTech Connect (OSTI)

Residential energy cost is an important part of the household budget and could vary significantly across different population groups in many countries. In the United States, many studies have analyzed household fuel consumption by fuel type, including electricity, natural gas, fuel oil, and liquefied petroleum gas (LPG), and by geographic areas. Past research has also demonstrated significant variation in residential energy use across various population groups, including white, black, and Latino. However, our research shows that residential energy demand by fuel type for Latinos, the fastest growing population group, has not been explained by economic and non-economic factors in any statistical model in public domain. The purpose of this paper was to discuss energy demand and expenditure patterns for Latino and non-Latino households in the United States as a case example of analyzing residential energy consumption across different population groups in a country. The linear expenditure system model developed by Stone and Geary is the basis of the statistical model developed to explain fuel consumption and expenditures for Latino households. For comparison, the models are also developed for non-Latino, black, and non-black households. These models estimate energy consumption of and expenditures for electricity, natural gas, fuel oil, and LPG by various households at the national level. Significant variations in the patterns of these fuels consumption for Latinos and non-Latinos are highlighted. The model methodology and results of this research should be useful to energy policymakers in government and industry, researches, and academicians who are concerned with economic and energy issues related to various population groups in their country.

Poyer, D. A.; Henderson, L.; Teotia, A. P. S.; Energy Systems; Univ. of Baltimore

1997-01-01T23:59:59.000Z

104

Total Energy Facilities Biomass Facility | Open Energy Information  

Open Energy Info (EERE)

Total Energy Facilities Biomass Facility Total Energy Facilities Biomass Facility Jump to: navigation, search Name Total Energy Facilities Biomass Facility Facility Total Energy Facilities Sector Biomass Facility Type Non-Fossil Waste Location Los Angeles County, California Coordinates 34.3871821°, -118.1122679° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":34.3871821,"lon":-118.1122679,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

105

Changing Trends: A Brief History of the US Household Consumption of Energy, Water, Food, Beverages and Tobacco  

E-Print Network [OSTI]

at 215 million Btu. The rate of consumption generally increased until the oil price shocks of the midChanging Trends: A Brief History of the US Household Consumption of Energy, Water, Food, Beverages understand energy conservation policies, we take a brief look at the history in the US of consumption

106

Simulation of household in-home and transportation energy use : an integrated behavioral model for estimating energy consumption at the neighborhood scale  

E-Print Network [OSTI]

Household in-home activities and out-of-home transportation are two major sources of urban energy consumption. In light of China's rapid urbanization and income growth, changing lifestyles and consumer patterns - evident ...

Yu, Feifei, S.M. Massachusetts Institute of Technology

2013-01-01T23:59:59.000Z

107

Total Energy - Data - U.S. Energy Information Administration (EIA)  

Gasoline and Diesel Fuel Update (EIA)

September 2012 PDF | previous editions September 2012 PDF | previous editions Release Date: September 27, 2012 A report of historical annual energy statistics. For many series, data begin with the year 1949. Included are data on total energy production, consumption, and trade; overviews of petroleum, natural gas, coal, electricity, nuclear energy, renewable energy, as well as financial and environmental indicators; and data unit conversion tables. About the data Previous Editions + EXPAND ALL Annual Energy Review 2011 Edition PDF (Full issue) Annual Energy Review 2011 - Released on September 27, 2012 PDF Annual Energy Review 2010 Edition PDF (Full issue) Annual Energy Review 2010 - Released on October 19, 2011 PDF Annual Energy Review 2009 Edition PDF (Full issue) Annual Energy Review 2009 - Released on August 19, 2010 PDF

108

The Household Pie  

Science Journals Connector (OSTI)

The discussion of theoretical, conceptual, and methodological concerns in the last three chapters has set the stage for an examination of the total effort that households devote to domestic and market activiti...

Sarah Fenstermaker Berk

1985-01-01T23:59:59.000Z

109

Serck standard packages for total energy  

Science Journals Connector (OSTI)

Although the principle of combined heat and power generation is attractive, practical problems have hindered its application. In the U.K. the scope for small scale combined heat and power (total energy) systems has been improved markedly by the introduction of new Electricity Board regulations which allow the operation of small a.c. generators in parallel with the mains low voltage supply. Following this change, Serck have developed a standard total energy unit, the CG100, based on the 2.25 1 Land Rover gas engine with full engine (coolant and exhaust gas) heat recovery. The unit incorporates an asynchronous generator, which utilising mains power for its magnetising current and speed control, offers a very simple means of generating electricity in parallel with the mains supply, without the need for expensive synchronising controls. Nominal output is 15 kW 47 kW heat; heat is available as hot water at temperatures up to 85C, allowing the heat output to be utilised directly in low pressure hot water systems. The CG100 unit can be used in any application where an appropriate demand exists for heat and electricity, and the annual utilisation will give an acceptable return on capital cost; it produces base load heat and electricity, with LPHW boilers and the mains supply providing top-up/stand-by requirements. Applications include residential use (hospitals, hotels, boarding schools, etc.), swimming pools and industrial process systems. The unit also operates on digester gas produced by anaerobic digestion of organic waste. A larger unit based on a six cylinder Ford engine (45 kWe output) is now available.

R. Kelcher

1984-01-01T23:59:59.000Z

110

Total Energy - Data - U.S. Energy Information Administration (EIA)  

Gasoline and Diesel Fuel Update (EIA)

Total Energy Total Energy Glossary › FAQS › Overview Data Monthly Annual Analysis & Projections All Reports Most Requested Annual Monthly Projections U.S. States Annual Energy Review September 2012 PDF | previous editions Release Date: September 27, 2012 Important notes about the data Note: The emphasis of the Annual Energy Review (AER) is on long-term trends. Analysts may wish to use the data in this report in conjunction with EIA's monthly releases that offer updates to the most recent years' data. In particular, see the Monthly Energy Review for statistics that include updates to many of the annual series in this report. Data Years Displayed: For tables beginning in 1949, some early years (usually 1951-1954, 1956-1959, 1961-1964, 1966-1969, and 1971-1974) are not

111

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

Reports and Publications (EIA)

In 2012, the residential sector accounted for 21% of total primary energy consumption and about 20% of carbon dioxide emissions in the United States (computed from EIA 2013). Because of the impacts of residential sector energy use on the environment and the economy, this study was undertaken to help provide a better understanding of the factors affecting energy consumption in this sector. The analysis is based on the U.S. Energy Information Administration's (EIA) residential energy consumption surveys (RECS) 1980-2009.

2015-01-01T23:59:59.000Z

112

Can ambient persuasive technology persuade unconsciously?: using subliminal feedback to influence energy consumption ratings of household appliances  

Science Journals Connector (OSTI)

In this paper we explore a fundamental characteristic of Ambient Persuasive Technology: Can it persuade the user without receiving the user's conscious attention? In a task consisting of 90 trials, participants had to indicate which of three household ... Keywords: ambient persuasive technology, energy conservation behavior, human-technology interaction, persuasion, social feedback, subliminal feedback

Jaap Ham; Cees Midden; Femke Beute

2009-04-01T23:59:59.000Z

113

Total..........................................................  

Gasoline and Diesel Fuel Update (EIA)

... 13.2 2.7 3.5 2.2 1.3 3.5 1.3 3.8 Table HC7.10 Home Appliances Usage Indicators by Household Income, 2005 Below Poverty Line Eligible for Federal...

114

Achieving Total Employee Engagement in Energy Efficiency  

Broader source: Energy.gov [DOE]

Ratheon and GM share their experiences with employee engagement to achieve energy efficiency and sustainability goals in this presentation.

115

Achieving Total Employee Engagement in Energy Efficiency  

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

Raytheon Employee Engagement Raytheon Employee Engagement in Energy Conservation Department of Energy August 5, 2010 Steve Fugarazzo Raytheon Company Enterprise Energy Team Copyright © 2007 Raytheon Company. All rights reserved. Customer Success Is Our Mission is a trademark of Raytheon Company. Page 2 8/9/2010 Presentation Overview  Company Background  Communication & Outreach Initiatives - Internal Partnerships - Energy Champions - Energy Citizens - Energy Awareness Events & Contests Page 3 8/9/2010 Raytheon ... What We Do Raytheon is a global technology company that provides innovative solutions to customers in 80 nations. Through strategic vision, disciplined management and world-class talent, Raytheon is delivering operational advantages for customers every day while helping them prepare for the

116

Property:TotalValue | Open Energy Information  

Open Energy Info (EERE)

TotalValue TotalValue Jump to: navigation, search This is a property of type Number. Pages using the property "TotalValue" Showing 25 pages using this property. (previous 25) (next 25) 4 44 Tech Inc. Smart Grid Demonstration Project + 10,000,000 + A ALLETE Inc., d/b/a Minnesota Power Smart Grid Project + 3,088,007 + Amber Kinetics, Inc. Smart Grid Demonstration Project + 10,000,000 + American Transmission Company LLC II Smart Grid Project + 22,888,360 + American Transmission Company LLC Smart Grid Project + 2,661,650 + Atlantic City Electric Company Smart Grid Project + 37,400,000 + Avista Utilities Smart Grid Project + 40,000,000 + B Baltimore Gas and Electric Company Smart Grid Project + 451,814,234 + Battelle Memorial Institute, Pacific Northwest Division Smart Grid Demonstration Project + 177,642,503 +

117

SolarTotal | Open Energy Information  

Open Energy Info (EERE)

SolarTotal SolarTotal Jump to: navigation, search Name SolarTotal Place Bemmel, Netherlands Zip 6681 LN Sector Solar Product The company sells and installs PV solar instalations Coordinates 51.894112°, 5.89881° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":51.894112,"lon":5.89881,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

118

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

SciTech Connect (OSTI)

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

119

EQUUS Total Return Inc | Open Energy Information  

Open Energy Info (EERE)

EQUUS Total Return Inc EQUUS Total Return Inc Jump to: navigation, search Name EQUUS Total Return Inc Place Houston, Texas Product A business development company and VC investor that trades as a closed-end fund. EQUUS is managed by MCC Global NV, a Frankfurt stock exchange listed management and merchant banking group. Coordinates 29.76045°, -95.369784° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":29.76045,"lon":-95.369784,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

120

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

SciTech Connect (OSTI)

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

Note: This page contains sample records for the topic "household total energy" 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

Correlation Of Surface Heat Loss And Total Energy Production...  

Open Energy Info (EERE)

Correlation Of Surface Heat Loss And Total Energy Production For Geothermal Systems Jump to: navigation, search OpenEI Reference LibraryAdd to library Conference Paper: Correlation...

122

Total Pollution Effect and Total Energy Cost per Output of Different Products for Polish Industrial System  

Science Journals Connector (OSTI)

For many years a broad use has been made of the indices of total energy requirements in the whole large production system corresponding to unit output of particular goods (Boustead I., Hancock G.F., 1979). The...

Henryk W. Balandynowicz

1988-01-01T23:59:59.000Z

123

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

124

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

125

Total....................................................................  

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

14.7 14.7 7.4 12.5 12.5 18.9 18.6 17.3 9.2 Household Size 1 Person.......................................................... 30.0 4.6 2.5 3.7 3.2 5.4 5.5 3.7 1.6 2 Persons......................................................... 34.8 4.3 1.9 4.4 4.1 5.9 5.3 5.5 3.4 3 Persons......................................................... 18.4 2.5 1.3 1.7 1.9 2.9 3.5 2.8 1.6 4 Persons......................................................... 15.9 1.9 0.8 1.5 1.6 3.0 2.5 3.1 1.4 5 Persons......................................................... 7.9 0.8 0.4 1.0 1.1 1.2 1.1 1.5 0.9 6 or More Persons........................................... 4.1 0.5 0.3 0.3 0.6 0.5 0.7 0.8 0.4 2005 Annual Household Income Category Less than $9,999............................................. 9.9 1.9 1.1 1.3 0.9 1.7 1.3 1.1 0.5 $10,000 to $14,999..........................................

126

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

SciTech Connect (OSTI)

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

127

Interaction between building design, management, household and individual factors in relation to energy use for space heating in apartment buildings  

Science Journals Connector (OSTI)

Abstract In Stockholm, 472 multi-family buildings with 7554 dwellings has been selected by stratified random sampling. Information about building characteristics and property management was gathered from each property owners. Energy use for space heating was collected from the utility company. Perceived thermal comfort, household and personal factors were assessed by a standardized self-administered questionnaire, answered by one adult person in each dwelling, and a proportion of each factor was calculated for each building. Statistical analysis was performed by multiple linear regression models with control for relevant factors all at the same time in the model. Energy use for heating was significantly related to the building age, type of building and ventilation, length of time since the last heating adjustment, ownership form, proportion of females, and proportion of occupants expressing thermal discomfort. How beneficial energy efficiency measures will be may depend on the relationship between energy use and factors related to the building and the property maintenance together with household and personal factors, as all these factors interact with each other. The results show that greater focus should be on real estate management and maintenance and also a need for research with a gender perspective on energy use for space heating.

Karin Engvall; Erik Lampa; Per Levin; Per Wickman; Egil fverholm

2014-01-01T23:59:59.000Z

128

UNCOVERING BASIC WANTS USING THE ROTTERDAM AND AIDS MODELS: THE US HOUSEHOLD ENERGY CONSUMPTION CASE  

E-Print Network [OSTI]

refers to these latent goods as transformed goods or T-goods. Leading researchers have explored this technique of incorporating characteristics. In this study, we revisit this technique by trying to uncover the basic wants behind the demand for gas..., distillate fuel oil, and the liquefied petroleum gases (LPG) by US households. To give some examples, electricity may be used for many basic wants such as lighting, cooking, and cooling. Similarly, without being exhaustive, gas may be used for heating...

Diallo, Ibrahima

2013-05-31T23:59:59.000Z

129

Estimating Total Energy Consumption and Emissions of China's Commercial and Office Buildings  

E-Print Network [OSTI]

Estimating Total Energy Consumption and Emissions of Chinasof Chinas total energy consumption mix. However, accuratelyof Chinas total energy consumption, while others estimate

Fridley, David G.

2008-01-01T23:59:59.000Z

130

Estimating Total Energy Consumption and Emissions of China's Commercial and Office Buildings  

E-Print Network [OSTI]

ABORATORY Estimating Total Energy Consumption and Emissionscomponent of Chinas total energy consumption mix. However,about 19% of Chinas total energy consumption, while others

Fridley, David G.

2008-01-01T23:59:59.000Z

131

Total and Peak Energy Consumption Minimization of Building HVAC Systems Using Model Predictive Control  

E-Print Network [OSTI]

combination of the total energy consumption and the peakalso reduces the total energy consumption of the occupancyTotal and Peak Energy Consumption Minimization of Building

Maasoumy, Mehdi; Sangiovanni-Vincentelli, Alberto

2012-01-01T23:59:59.000Z

132

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

133

Japan's Residential Energy Demand Outlook to 2030 Considering Energy Efficiency Standards "Top-Runner Approach"  

E-Print Network [OSTI]

Energy Source Demand per Household Coal, Oil, Gas, Heat, Electricity Total Energy Source Demand Coal, Oil, Gas, Heat, Electricity Demography Japan

Komiyama, Ryoichi

2008-01-01T23:59:59.000Z

134

Energy and Greenhouse Gas Emissions in China: Growth, Transition, and Institutional Change  

E-Print Network [OSTI]

was for 15% of total primary energy consumption to come fromis on domestic primary energy consumption, for most of thisdoes not include primary energy consumption by households

Kahrl, Fredrich James

2011-01-01T23:59:59.000Z

135

Total  

Gasoline and Diesel Fuel Update (EIA)

Total Total .............. 16,164,874 5,967,376 22,132,249 2,972,552 280,370 167,519 18,711,808 1993 Total .............. 16,691,139 6,034,504 22,725,642 3,103,014 413,971 226,743 18,981,915 1994 Total .............. 17,351,060 6,229,645 23,580,706 3,230,667 412,178 228,336 19,709,525 1995 Total .............. 17,282,032 6,461,596 23,743,628 3,565,023 388,392 283,739 19,506,474 1996 Total .............. 17,680,777 6,370,888 24,051,665 3,510,330 518,425 272,117 19,750,793 Alabama Total......... 570,907 11,394 582,301 22,601 27,006 1,853 530,841 Onshore ................ 209,839 11,394 221,233 22,601 16,762 1,593 180,277 State Offshore....... 209,013 0 209,013 0 10,244 260 198,509 Federal Offshore... 152,055 0 152,055 0 0 0 152,055 Alaska Total ............ 183,747 3,189,837 3,373,584 2,885,686 0 7,070 480,828 Onshore ................ 64,751 3,182,782

136

Property:Geothermal/TotalProjectCost | Open Energy Information  

Open Energy Info (EERE)

TotalProjectCost TotalProjectCost Jump to: navigation, search Property Name Geothermal/TotalProjectCost Property Type Number Description Total Project Cost Pages using the property "Geothermal/TotalProjectCost" Showing 25 pages using this property. (previous 25) (next 25) A A 3D-3C Reflection Seismic Survey and Data Integration to Identify the Seismic Response of Fractures and Permeable Zones Over a Known Geothermal Resource at Soda Lake, Churchill Co., NV Geothermal Project + 14,571,873 + A Demonstration System for Capturing Geothermal Energy from Mine Waters beneath Butte, MT Geothermal Project + 2,155,497 + A Geothermal District-Heating System and Alternative Energy Research Park on the NM Tech Campus Geothermal Project + 6,135,381 + A new analytic-adaptive model for EGS assessment, development and management support Geothermal Project + 1,629,670 +

137

An input-output approach to analyze the ways to increase total output of energy sectors: The case of Japan  

Science Journals Connector (OSTI)

The purpose of this study is to analyze the ways to increase total output of Japanese energy sectors in future time. In this study, Input-Output (IO) analysis is employed as a tool of analysis. This study focuses on petroleum refinery products and non-ferrous metals as analyzed sectors. The results show that positive impact observed in export and outside households consumption modifications while opposite impact is given by modification of import. The recommendations suggested based on these results are Japanese government should make breakthroughs so analyzed sector's export activities can increase and they have to careful in conducting import activities related to these sectors.

Ubaidillah Zuhdi

2014-01-01T23:59:59.000Z

138

Total Energy - Data - U.S. Energy Information Administration (EIA)  

Gasoline and Diesel Fuel Update (EIA)

What's New in Monthly Energy Review What's New in Monthly Energy Review December 2013 PDF | previous editions Release Date: December 24, 2013 Next Update: January 28, 2014 Listed below are changes in Monthly Energy Review content. Only months with changes beyond the standard updates are shown. CONTENT CHANGES + EXPAND ALL Changes in 2013 December 2013 Release Electricity statistics have been revised in coordination with EIA's Electric Power Annual 2012. Revisions affect data series in Energy Overview, Energy Consumption, Petroleum, Natural Gas, Coal, Electricity, Nuclear Energy, Energy Prices, Renewable Energy, and Environment. Final 2012 heat content values for electricity (Table A6) have also been incorporated. October 2013 Release Excel and CSV files now include pre-1973 data for all series except for Section 12. The Excel files now have two worksheets, one for monthly data and one for annual data.

139

Total............................................................  

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

Total................................................................... Total................................................................... 111.1 2,033 1,618 1,031 791 630 401 Total Floorspace (Square Feet) Fewer than 500............................................... 3.2 357 336 113 188 177 59 500 to 999....................................................... 23.8 733 667 308 343 312 144 1,000 to 1,499................................................. 20.8 1,157 1,086 625 435 409 235 1,500 to 1,999................................................. 15.4 1,592 1,441 906 595 539 339 2,000 to 2,499................................................. 12.2 2,052 1,733 1,072 765 646 400 2,500 to 2,999................................................. 10.3 2,523 2,010 1,346 939 748 501 3,000 to 3,499................................................. 6.7 3,020 2,185 1,401 1,177 851 546

140

Total...................  

Gasoline and Diesel Fuel Update (EIA)

4,690,065 52,331,397 2,802,751 4,409,699 7,526,898 209,616 1993 Total................... 4,956,445 52,535,411 2,861,569 4,464,906 7,981,433 209,666 1994 Total................... 4,847,702 53,392,557 2,895,013 4,533,905 8,167,033 202,940 1995 Total................... 4,850,318 54,322,179 3,031,077 4,636,500 8,579,585 209,398 1996 Total................... 5,241,414 55,263,673 3,158,244 4,720,227 8,870,422 206,049 Alabama ...................... 56,522 766,322 29,000 62,064 201,414 2,512 Alaska.......................... 16,179 81,348 27,315 12,732 75,616 202 Arizona ........................ 27,709 689,597 28,987 49,693 26,979 534 Arkansas ..................... 46,289 539,952 31,006 67,293 141,300 1,488 California ..................... 473,310 8,969,308 235,068 408,294 693,539 36,613 Colorado...................... 110,924 1,147,743

Note: This page contains sample records for the topic "household total energy" 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

National Fuel Cell and Hydrogen Energy Overview: Total Energy USA 2012  

Broader source: Energy.gov [DOE]

Presentation by Sunita Satyapal at the Total Energy USA 2012 meeting in Houston, Texas, on November 27, 2012.

142

Total Energy - Data - U.S. Energy Information Administration (EIA)  

Gasoline and Diesel Fuel Update (EIA)

Superseded -- see MER for key annual tables Superseded -- see MER for key annual tables Annual Energy Review archives for data year: 2011 2010 2009 2008 all archives Go CONTENT CHANGES + EXPAND ALL Changes in Annual Energy Review 2011 Annual Energy Review 2011 Release: September 27, 2012 1. Energy Consumption, Expenditures, and Emissions Indicators Estimates (Table 1.5) has been modified to include columns for Gross Output and Energy Expenditures as Share of Gross Output and remove Greenhouse Gas Emissions per Real Dollar of Gross Domestic Product. 2. Sales of Fossil Fuels Produced on Federal and American Indian Lands (Table 1.14) was previously titled "Fossil Fuel Production on Federally Administered Lands." It has been redesigned and now provides data on sales of fossil fuels from Federal and American Indian lands for fiscal years 2003 through 2011.

143

Total Energy - Data - U.S. Energy Information Administration (EIA)  

Gasoline and Diesel Fuel Update (EIA)

Primary Energy Consumption by Source and Sector, 2011 (Quadrillion Btu) Primary Energy Consumption by Source and Sector, 2011 (Quadrillion Btu) Primary Energy Consumption by Source and Sector diagram image Footnotes: 1 Does not include biofuels that have been blended with petroleum-biofuels are included in "Renewable Energy." 2 Excludes supplemental gaseous fuels. 3 Includes less than 0.1 quadrillion Btu of coal coke net exports. 4 Conventional hydroelectric power, geothermal, solar/PV, wind, and biomass. 5 Includes industrial combined-heat-and-power (CHP) and industrial electricity-only plants. 6 Includes commercial combined-heat-and-power (CHP) and commercial electricity-only plants. 7 Electricity-only and combined-heat-and-power (CHP) plants whose primary business is to sell electricity, or electricity and heat, to the public.

144

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

SciTech Connect (OSTI)

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

145

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

SciTech Connect (OSTI)

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

146

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

E-Print Network [OSTI]

Financing Home Energy Upgrades in New York Since 2001, New2009. Administered by the New York State Energy Research andA Diverse Energy Upgrade Platform in New York The new GJGNY

Zimring, Mark

2011-01-01T23:59:59.000Z

147

Energy use of US residential refrigerators and freezers: function derivation based on household and climate characteristics  

E-Print Network [OSTI]

Residential Energy Consumption Survey (RECS), U.S. Energyod for estimating field energy consumption of US residentialconsumption surveydetailed tables. Residential Energy Con- sumption Survey (RECS), U.S.

Greenblatt, Jeffery

2013-01-01T23:59:59.000Z

148

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

E-Print Network [OSTI]

of Cold Weather and High Energy Costs on the Health of Low-and NBER April 2005 Home energy costs comprise a significant1. Introduction Home energy costs comprise a significant

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

2005-01-01T23:59:59.000Z

149

Potential Energy Total electric potential energy, U, of a system of  

E-Print Network [OSTI]

Potential Energy Total electric potential energy, U, of a system of charges is obtained from of work done by the field, W*= -W. Bring q1 from , W *= 0 since no electric F yet #12;Potential Energy Total electric potential energy, U, of a system of charges is obtained from the work done by an external

Bertulani, Carlos A. - Department of Physics and Astronomy, Texas A&M University

150

Total...........................................................  

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

Q Q Million U.S. Housing Units Renter- Occupied Housing Units (millions) Type of Renter-Occupied Housing Unit U.S. Housing Units (millions Single-Family Units Apartments in Buildings With-- Living Space Characteristics Detached Attached Table HC4.2 Living Space Characteristics by Renter-Occupied Housing Units, 2005 2 to 4 Units 5 or More Units Mobile Homes Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Million U.S. Housing Units Renter- Occupied Housing Units (millions) Type of Renter-Occupied Housing Unit U.S. Housing Units (millions Single-Family Units Apartments in Buildings With-- Living Space Characteristics Detached Attached Table HC4.2 Living Space Characteristics by Renter-Occupied Housing Units, 2005

151

Total...................................................................  

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

Single-Family Units Single-Family Units Detached Type of Housing Unit Table HC2.7 Air Conditioning Usage Indicators by Type of Housing Unit, 2005 Million U.S. Housing Units Air Conditioning Usage Indicators Attached 2 to 4 Units 5 or More Units Mobile Homes Apartments in Buildings With-- Housing Units (millions) Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Single-Family Units Detached Type of Housing Unit Table HC2.7 Air Conditioning Usage Indicators by Type of Housing Unit, 2005 Million U.S. Housing Units Air Conditioning Usage Indicators Attached 2 to 4 Units 5 or More Units Mobile Homes Apartments in Buildings With-- Housing Units (millions) At Home Behavior Home Used for Business

152

Total...........................................................  

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

Q Q Table HC3.2 Living Space Characteristics by Owner-Occupied Housing Units, 2005 2 to 4 Units 5 or More Units Mobile Homes Million U.S. Housing Units Owner- Occupied Housing Units (millions) Type of Owner-Occupied Housing Unit Housing Units (millions) Single-Family Units Apartments in Buildings With-- Living Space Characteristics Detached Attached Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Table HC3.2 Living Space Characteristics by Owner-Occupied Housing Units, 2005 2 to 4 Units 5 or More Units Mobile Homes Million U.S. Housing Units Owner- Occupied Housing Units (millions) Type of Owner-Occupied Housing Unit Housing Units (millions)

153

Total..........................................................................  

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

7.1 7.1 19.0 22.7 22.3 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 2.1 0.6 Q 0.4 500 to 999........................................................... 23.8 13.6 3.7 3.2 3.2 1,000 to 1,499..................................................... 20.8 9.5 3.7 3.4 4.2 1,500 to 1,999..................................................... 15.4 6.6 2.7 2.5 3.6 2,000 to 2,499..................................................... 12.2 5.0 2.1 2.8 2.4 2,500 to 2,999..................................................... 10.3 3.7 1.8 2.8 2.1 3,000 to 3,499..................................................... 6.7 2.0 1.4 1.7 1.6 3,500 to 3,999..................................................... 5.2 1.6 0.8 1.5 1.4 4,000 or More.....................................................

154

Total..........................................................................  

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

0.7 0.7 21.7 6.9 12.1 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 0.9 0.6 Q Q 500 to 999........................................................... 23.8 9.0 4.2 1.5 3.2 1,000 to 1,499..................................................... 20.8 8.6 4.7 1.5 2.5 1,500 to 1,999..................................................... 15.4 6.0 2.9 1.2 1.9 2,000 to 2,499..................................................... 12.2 4.1 2.1 0.7 1.3 2,500 to 2,999..................................................... 10.3 3.0 1.8 0.5 0.7 3,000 to 3,499..................................................... 6.7 2.1 1.2 0.5 0.4 3,500 to 3,999..................................................... 5.2 1.5 0.8 0.3 0.4 4,000 or More.....................................................

155

Total..........................................................................  

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

25.6 25.6 40.7 24.2 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 0.9 0.5 0.9 1.0 500 to 999........................................................... 23.8 4.6 3.9 9.0 6.3 1,000 to 1,499..................................................... 20.8 2.8 4.4 8.6 5.0 1,500 to 1,999..................................................... 15.4 1.9 3.5 6.0 4.0 2,000 to 2,499..................................................... 12.2 2.3 3.2 4.1 2.6 2,500 to 2,999..................................................... 10.3 2.2 2.7 3.0 2.4 3,000 to 3,499..................................................... 6.7 1.6 2.1 2.1 0.9 3,500 to 3,999..................................................... 5.2 1.1 1.7 1.5 0.9 4,000 or More.....................................................

156

Total..........................................................................  

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

4.2 4.2 7.6 16.6 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 1.0 0.2 0.8 500 to 999........................................................... 23.8 6.3 1.4 4.9 1,000 to 1,499..................................................... 20.8 5.0 1.6 3.4 1,500 to 1,999..................................................... 15.4 4.0 1.4 2.6 2,000 to 2,499..................................................... 12.2 2.6 0.9 1.7 2,500 to 2,999..................................................... 10.3 2.4 0.9 1.4 3,000 to 3,499..................................................... 6.7 0.9 0.3 0.6 3,500 to 3,999..................................................... 5.2 0.9 0.4 0.5 4,000 or More.....................................................

157

Total.........................................................................  

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

Floorspace (Square Feet) Floorspace (Square Feet) Total Floorspace 2 Fewer than 500.................................................. 3.2 Q 0.8 0.9 0.8 0.5 500 to 999.......................................................... 23.8 1.5 5.4 5.5 6.1 5.3 1,000 to 1,499.................................................... 20.8 1.4 4.0 5.2 5.0 5.2 1,500 to 1,999.................................................... 15.4 1.4 3.1 3.5 3.6 3.8 2,000 to 2,499.................................................... 12.2 1.4 3.2 3.0 2.3 2.3 2,500 to 2,999.................................................... 10.3 1.5 2.3 2.7 2.1 1.7 3,000 to 3,499.................................................... 6.7 1.0 2.0 1.7 1.0 1.0 3,500 to 3,999.................................................... 5.2 0.8 1.5 1.5 0.7 0.7 4,000 or More.....................................................

158

Total..........................................................................  

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

. . 111.1 20.6 15.1 5.5 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 0.9 0.5 0.4 500 to 999........................................................... 23.8 4.6 3.6 1.1 1,000 to 1,499..................................................... 20.8 2.8 2.2 0.6 1,500 to 1,999..................................................... 15.4 1.9 1.4 0.5 2,000 to 2,499..................................................... 12.2 2.3 1.7 0.5 2,500 to 2,999..................................................... 10.3 2.2 1.7 0.6 3,000 to 3,499..................................................... 6.7 1.6 1.0 0.6 3,500 to 3,999..................................................... 5.2 1.1 0.9 0.3 4,000 or More.....................................................

159

Total..........................................................................  

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

7.1 7.1 7.0 8.0 12.1 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 0.4 Q Q 0.5 500 to 999........................................................... 23.8 2.5 1.5 2.1 3.7 1,000 to 1,499..................................................... 20.8 1.1 2.0 1.5 2.5 1,500 to 1,999..................................................... 15.4 0.5 1.2 1.2 1.9 2,000 to 2,499..................................................... 12.2 0.7 0.5 0.8 1.4 2,500 to 2,999..................................................... 10.3 0.5 0.5 0.4 1.1 3,000 to 3,499..................................................... 6.7 0.3 Q 0.4 0.3 3,500 to 3,999..................................................... 5.2 Q Q Q Q 4,000 or More.....................................................

160

Total..........................................................  

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

.. .. 111.1 24.5 1,090 902 341 872 780 441 Total Floorspace (Square Feet) Fewer than 500...................................... 3.1 2.3 403 360 165 366 348 93 500 to 999.............................................. 22.2 14.4 763 660 277 730 646 303 1,000 to 1,499........................................ 19.1 5.8 1,223 1,130 496 1,187 1,086 696 1,500 to 1,999........................................ 14.4 1.0 1,700 1,422 412 1,698 1,544 1,348 2,000 to 2,499........................................ 12.7 0.4 2,139 1,598 Q Q Q Q 2,500 to 2,999........................................ 10.1 Q Q Q Q Q Q Q 3,000 or More......................................... 29.6 0.3 Q Q Q Q Q Q Heated Floorspace (Square Feet) None...................................................... 3.6 1.8 1,048 0 Q 827 0 407 Fewer than 500......................................

Note: This page contains sample records for the topic "household total energy" 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

Total...................................................................  

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

2,033 2,033 1,618 1,031 791 630 401 Total Floorspace (Square Feet) Fewer than 500............................................... 3.2 357 336 113 188 177 59 500 to 999....................................................... 23.8 733 667 308 343 312 144 1,000 to 1,499................................................. 20.8 1,157 1,086 625 435 409 235 1,500 to 1,999................................................. 15.4 1,592 1,441 906 595 539 339 2,000 to 2,499................................................. 12.2 2,052 1,733 1,072 765 646 400 2,500 to 2,999................................................. 10.3 2,523 2,010 1,346 939 748 501 3,000 to 3,499................................................. 6.7 3,020 2,185 1,401 1,177 851 546 3,500 to 3,999................................................. 5.2 3,549 2,509 1,508

162

Total...........................................................  

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

26.7 26.7 28.8 20.6 13.1 22.0 16.6 38.6 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................... 3.2 1.9 0.9 Q Q Q 1.3 2.3 500 to 999........................................... 23.8 10.5 7.3 3.3 1.4 1.2 6.6 12.9 1,000 to 1,499..................................... 20.8 5.8 7.0 3.8 2.2 2.0 3.9 8.9 1,500 to 1,999..................................... 15.4 3.1 4.2 3.4 2.0 2.7 1.9 5.0 2,000 to 2,499..................................... 12.2 1.7 2.7 2.9 1.8 3.2 1.1 2.8 2,500 to 2,999..................................... 10.3 1.2 2.2 2.3 1.7 2.9 0.6 2.0 3,000 to 3,499..................................... 6.7 0.9 1.4 1.5 1.0 1.9 0.4 1.4 3,500 to 3,999..................................... 5.2 0.8 1.2 1.0 0.8 1.5 0.4 1.3 4,000 or More...................................... 13.3 0.9 1.9 2.2 2.0 6.4 0.6 1.9 Heated Floorspace

163

Total...........................................................  

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

14.7 14.7 7.4 12.5 12.5 18.9 18.6 17.3 9.2 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500.................................... 3.2 0.7 Q 0.3 0.3 0.7 0.6 0.3 Q 500 to 999........................................... 23.8 2.7 1.4 2.2 2.8 5.5 5.1 3.0 1.1 1,000 to 1,499..................................... 20.8 2.3 1.4 2.4 2.5 3.5 3.5 3.6 1.6 1,500 to 1,999..................................... 15.4 1.8 1.4 2.2 2.0 2.4 2.4 2.1 1.2 2,000 to 2,499..................................... 12.2 1.4 0.9 1.8 1.4 2.2 2.1 1.6 0.8 2,500 to 2,999..................................... 10.3 1.6 0.9 1.1 1.1 1.5 1.5 1.7 0.8 3,000 to 3,499..................................... 6.7 1.0 0.5 0.8 0.8 1.2 0.8 0.9 0.8 3,500 to 3,999..................................... 5.2 1.1 0.3 0.7 0.7 0.4 0.5 1.0 0.5 4,000 or More...................................... 13.3

164

Total................................................  

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

.. .. 111.1 86.6 2,522 1,970 1,310 1,812 1,475 821 1,055 944 554 Total Floorspace (Square Feet) Fewer than 500............................. 3.2 0.9 261 336 162 Q Q Q 334 260 Q 500 to 999.................................... 23.8 9.4 670 683 320 705 666 274 811 721 363 1,000 to 1,499.............................. 20.8 15.0 1,121 1,083 622 1,129 1,052 535 1,228 1,090 676 1,500 to 1,999.............................. 15.4 14.4 1,574 1,450 945 1,628 1,327 629 1,712 1,489 808 2,000 to 2,499.............................. 12.2 11.9 2,039 1,731 1,055 2,143 1,813 1,152 Q Q Q 2,500 to 2,999.............................. 10.3 10.1 2,519 2,004 1,357 2,492 2,103 1,096 Q Q Q 3,000 or 3,499.............................. 6.7 6.6 3,014 2,175 1,438 3,047 2,079 1,108 N N N 3,500 to 3,999.............................. 5.2 5.1 3,549 2,505 1,518 Q Q Q N N N 4,000 or More...............................

165

Household operational energy consumption in urban China : a multilevel analysis on Jinan  

E-Print Network [OSTI]

With decades of economic growth and socio-economic transformation, China's residential sector has seen rapid expansion in energy consumption, and is now the second largest energy consuming sector in the country. Faced with ...

Wang, Dong, M.C.P. Massachusetts Institute of Technology

2012-01-01T23:59:59.000Z

166

Retrofitting the domestic built environment: investigating household perspectives towards energy efficiency technologies and behaviour  

E-Print Network [OSTI]

Company Obligation EEPfH Energy Efficiency Partnership for Homes EPC Energy Performance Certificate EPSRC Engineering & Physical Science Research Council ERDF European Regional Development Fund FDR False discovery rate FIT Feed-in Tariff GHG Greenhouse has...

Pelenur, Marcos

2014-03-04T23:59:59.000Z

167

E-Print Network 3.0 - acute household accidental Sample Search...  

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

Evaluating the health benefits of transitions in household energy Summary: ; Household energy; Indoor air pollution; Intervention assessment; Kenya 1. Introduction Acute...

168

Total Energy - Data - U.S. Energy Information Administration (EIA)  

Gasoline and Diesel Fuel Update (EIA)

Electricity Flow, (Quadrillion Btu) Electricity Flow, (Quadrillion Btu) Electricity Flow diagram image Footnotes: 1 Blast furnace gas, propane gas, and other manufactured and waste gases derived from fossil fuels. 2 Batteries, chemicals, hydrogen, pitch, purchased steam, sulfur, miscellaneous technologies, and non-renewable waste (municipal solid waste from non-biogenic sources, and tire-derived fuels). 3 Data collection frame differences and nonsampling error. Derived for the diagram by subtracting the "T & D Losses" estimate from "T & D Losses and Unaccounted for" derived from Table 8.1. 4 Electric energy used in the operation of power plants. 5 Transmission and distribution losses (electricity losses that occur between the point of generation and delivery to the customer) are estimated

169

Total Energy - Data - U.S. Energy Information Administration (EIA)  

Gasoline and Diesel Fuel Update (EIA)

Petroleum Flow, (Million Barrels per Day) Petroleum Flow, (Million Barrels per Day) Petroleum Energy Flow diagram image Footnotes: 1 Unfinished oils, hydrogen/oxygenates/renewables/other hydrocarbons, and motor gasoline and aviation gasoline blending components. 2 Renewable fuels and oxygenate plant net production (0.972), net imports (1.164) and adjustments (0.122) minus stock change (0.019) and product supplied (0.001). 3 Finished petroleum products, liquefied petroleum gases, and pentanes plus. 4 Natural gas plant liquids. 5 Field production (2.183) and renewable fuels and oxygenate plant net production (-.019) minus refinery and blender net imputs (0.489). 6 Production minus refinery input. (s)= Less than 0.005. Notes: * Data are preliminary. * Values are derived from source data prior to rounding for publication.

170

ASSESSMENT OF HOUSEHOLD CARBON FOOTPRINT REDUCTION POTENTIALS  

E-Print Network [OSTI]

EnergyEfficiencyPotentialStudy. TechnicalReportEnergyEfficiency PotentialStudy. TechnicalReportEnergyEfficiency RenewableEnergyTechnologies Transportation AssessmentofHouseholdCarbonFootprintReductionPotentialsisthefinalreport

Masanet, Eric

2010-01-01T23:59:59.000Z

171

Buildings Energy Data Book: 2.9 Low-Income Housing  

Buildings Energy Data Book [EERE]

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

172

Retrofitting the domestic built environment: investigating household perspectives towards energy efficiency technologies and behaviour.  

E-Print Network [OSTI]

??Retrofitting the UK domestic built environment presents an excellent opportunity to improve its energy performance. However, retrofitting homes is a complex challenge conflated by multiple (more)

Pelenur, Marcos

2014-01-01T23:59:59.000Z

173

Automated Demand Response Approaches to Household Energy Management in a Smart Grid Environment.  

E-Print Network [OSTI]

??The advancement of renewable energy technologies and the deregulation of theelectricity market have seen the emergence of Demand response (DR) programs. Demand response is a (more)

Adika, Christopher Otieno

2014-01-01T23:59:59.000Z

174

Household actions can provide a behavioral wedge to rapidly reduce US carbon emissions  

Science Journals Connector (OSTI)

...ineffective in reducing household energy consumption. Mass media...10 years. The changes in household behavior outlined above result...European Union countries and Japan, where the household sector is less energy intensive. Analyses similar...

Thomas Dietz; Gerald T. Gardner; Jonathan Gilligan; Paul C. Stern; Michael P. Vandenbergh

2009-01-01T23:59:59.000Z

175

Understanding and Improving Household Energy Consumption and Carbon Emissions Policies - A System Dynamics Approach  

E-Print Network [OSTI]

? scale?. This covers any energy generation that is decentralized. Micro-generation technologies may take the form of solar photovoltaic (PV), micro-wind turbines, micro-hydro or even micro-combined heat and power (CHP). Micro-generation provides energy...

Oladokun, M.; Motawa, I.; Banfill, P.

2012-01-01T23:59:59.000Z

176

Estimating Total Energy Consumption and Emissions of China's Commercial and Office Buildings  

E-Print Network [OSTI]

18 Figure 6 Primary Energy Consumption by End-Use in24 Figure 7 Primary Energy Consumption by Fuel in Commercialbased on total primary energy consumption (source energy),

Fridley, David G.

2008-01-01T23:59:59.000Z

177

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

178

Retailers : a possible stepping stone for promoting energy efficiency in household appliances  

Science Journals Connector (OSTI)

The public support of energy efficiency generally targets manufacturers (support to R&D policies) and consumers (information campaign). This practice leaves out the retailers, who often have an essential role ...

Michel Colombier; Sophie Attali

1999-01-01T23:59:59.000Z

179

A cross-cultural analysis of household energy use behaviour in Japan and Norway  

Science Journals Connector (OSTI)

In this paper we compare and contrast the results of ethnographic investigations of energy use behaviour in Fukuoka, Japan and Oslo, Norway. These studies show significant differences in end use patterns for space heating, lighting and hot water use. We discuss how these patterns are related to cultural and economic factors. Our findings show that while energy intensive space heating and lighting habits have become an integral part of the presentation of the Norwegian home, Japanese space heat and light habits are more disciplined and less culturally significant. In Japan, the bathing routine is extremely important to the Japanese lifestyle and at the same time very energy intensive. Other energy intensive patterns are identified which do not have the same cultural significance, such as lax temperature setback in Norway and dish washing practices in Japan. The policy implications of these findings are discussed.

Harold Wilhite; Hidetoshi Nakagami; Takashi Masuda; Yukiko Yamaga; Hiroshi Haneda

1996-01-01T23:59:59.000Z

180

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

Note: This page contains sample records for the topic "household total energy" from the National Library of EnergyBeta (NLEBeta).
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We encourage you to perform a real-time search of NLEBeta
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181

Control of household refrigerators. Part 2: Alternate control approaches for improving temperature performance and reducing energy use  

SciTech Connect (OSTI)

In Part 1 it was shown that conventional control of household refrigerators is achieved by regulating the distribution of air in the freezer compartment to all other parts of the plant. In Part 2 three alternative approaches to the conventional control of a top-mount refrigerator are presented: variable temperature bandwidths, uncoupled compressor and evaporator fan, and the combination of these two. These allowed the plant to achieve near-ideal control with respect to improved temperature performance in each compartment. Automatic airflow dampers were used with the dual controllers to independently regulate refrigerator compartment temperature. Plant performance was simulated using a model that computes the refrigerant and airflow systems behavior. Together, these alternate configurations and approaches define new control algorithms that reveal the plant's optimal control model for improving performance and energy usage relative to conventional controllers. Results based on model simulations are dependent upon the model's accuracy and validity. However, the model validation studies cited here, though limited in scope, do show agreement between simulation and experimental data for the ambient temperatures and thermal load conditions considered. This suggests that these model results are reasonable, and representative of actual plant behavior under these conditions and configurations for a top-mount style refrigerator plant.

Graviss, K.J.; Collins, R.L.

1999-07-01T23:59:59.000Z

182

A multivariate analysis of the energy intensity of sprawl versus compact living in the U.S. for 2003  

E-Print Network [OSTI]

Household energy consumption Sprawl Compact living Energy impact We explore the energy intensity of sprawl versus compact living by analyzing the total energy requirements of U.S. households for the year 2003. The methods used are based on previous studies on energy cost of living. Total energy requirement

Vermont, University of

183

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

184

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

185

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

186

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

187

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

188

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

189

Table 16. Total Energy Consumption, Projected vs. Actual  

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

Total Energy Consumption, Projected vs. Actual" Total Energy Consumption, Projected vs. Actual" "Projected" " (quadrillion Btu)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011 "AEO 1994",88.02,89.53,90.72,91.73,92.71,93.61,94.56,95.73,96.69,97.69,98.89,100,100.79,101.7,102.7,103.6,104.3,105.23 "AEO 1995",,89.21,89.98,90.57,91.91,92.98,93.84,94.61,95.3,96.19,97.18,98.38,99.37,100.3,101.2,102.1,102.9,103.88 "AEO 1996",,,90.6,91.26,92.54,93.46,94.27,95.07,95.94,96.92,97.98,99.2,100.38,101.4,102.1,103.1,103.8,104.69,105.5 "AEO 1997",,,,92.64,93.58,95.13,96.59,97.85,98.79,99.9,101.2,102.4,103.4,104.7,105.8,106.6,107.2,107.9,108.6 "AEO 1998",,,,,94.68,96.71,98.61027527,99.81855774,101.254303,102.3907928,103.3935776,104.453476,105.8160553,107.2683716,108.5873566,109.8798981,111.0723877,112.166893,113.0926208

190

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

191

The Excitation Energy Dependence of the Total Kinetic Energy Release in 235U(n,f)  

E-Print Network [OSTI]

The total kinetic energy release in the neutron induced fission of $^{235}$U was measured (using white spectrum neutrons from LANSCE) for neutron energies from E$_{n}$ = 3.2 to 50 MeV. In this energy range the average post-neutron total kinetic energy release drops from 167.4 $\\pm$ 0.7 to 162.1 $\\pm$ 0.8 MeV, exhibiting a local dip near the second chance fission threshold. The values and the slope of the TKE vs. E$_{n}$ agree with previous measurements but do disagree (in magnitude) with systematics. The variances of the TKE distributions are larger than expected and apart from structure near the second chance fission threshold, are invariant for the neutron energy range from 11 to 50 MeV. We also report the dependence of the total excitation energy in fission, TXE, on neutron energy.

R. Yanez; L. Yao; J. King; W. Loveland; F. Tovesson; N. Fotiades

2014-03-18T23:59:59.000Z

192

Estimating Total Energy Consumption and Emissions of China's Commercial and Office Buildings  

E-Print Network [OSTI]

were used to calculate the energy mix in manufacturing,of Chinas total energy consumption mix. However, accuratelyof Chinas total energy consumption mix. However, accurately

Fridley, David G.

2008-01-01T23:59:59.000Z

193

Standby electricity consumption and saving potentials of Turkish households  

Science Journals Connector (OSTI)

Abstract The share of the residential sector currently accounts for about 25% of the national electricity consumption in Turkey. Due to increase in household income levels and decrease in the costs of appliances; significant increases in appliance ownerships and residential electricity consumption levels have been observed in recent years. Most domestic appliances continue consuming electricity when they are not performing their primary functions, i.e. at standby mode, which can constitute up 15% of the total household electricity consumption in some countries. Although the demand in Turkish residential electricity consumption is increasing, there are limited studies on the components of the residential electricity consumption and no studies specifically examining the extent and effects of standby electricity consumption using a surveying/measurement methodology. Thus, determining the share of standby electricity consumption in total home electricity use and the ways of reducing it are important issues in residential energy conservation strategies. In this study, surveys and standby power measurements are conducted at 260 households in Ankara, Turkey, to determine the amount, share, and saving potentials of the standby electricity consumption of Turkish homes. The survey is designed to gather information on the appliance properties, lights, electricity consumption behavior, economic and demographics of the occupants, and electricity bills. A total of 1746 appliances with standby power are measured in the surveyed homes. Using the survey and standby power measurements data, the standby, active, and lighting end-use electricity consumptions of the surveyed homes are determined. The average Turkish household standby power and standby electricity consumption are estimated as 22W and 95kWh/yr, respectively. It was also found that the standby electricity consumption constitutes 4% of the total electricity consumption in Turkish homes. Two scenarios are then applied to the surveyed homes to determine the potentials in reducing standby electricity consumption of the households.

Mustafa Cagri Sahin; Merih Aydinalp Koksal

2014-01-01T23:59:59.000Z

194

"Table A15. Selected Energy Operating Ratios for Total Energy Consumption for"  

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

Selected Energy Operating Ratios for Total Energy Consumption for" Selected Energy Operating Ratios for Total Energy Consumption for" " Heat, Power, and Electricity Generation by Census Region and Economic" " Characteristics of the Establishment, 1991" ,,,"Consumption","Major" " "," ","Consumption","per Dollar","Byproducts(b)","Fuel Oil(c)"," " " ","Consumption","per Dollar","of Value","as a Percent","as a Percent","RSE" " ","per Employee","of Value Added","of Shipments","of Consumption","of Natural Gas","Row" "Economic Characteristics(a)","(million Btu)","(thousand Btu)","(thousand Btu)","(percent)","(percent)","Factors"

195

"Table A45. Selected Energy Operating Ratios for Total Energy Consumption"  

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

5. Selected Energy Operating Ratios for Total Energy Consumption" 5. Selected Energy Operating Ratios for Total Energy Consumption" " for Heat, Power, and Electricity Generation by Industry Group," " Selected Industries, and Value of Shipment Categories, 1994" ,,,,,"Major" ,,,"Consumption","Consumption per","Byproducts(c)","Fuel Oil(d)" ,,"Consumption","per Dollar","Dollar of Value","as a Percent","as a Percent","RSE" "SIC",,"per Employee","of Value Added","of Shipments","of Consumption","of Natural Gas","Row" "Code(a)","Economic Characteristics(b)","(million Btu)","(thousand Btu)","(thousand Btu)","(percents)","(percents)","Factors"

196

"Table A46. Selected Energy Operating Ratios for Total Energy Consumption"  

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

Selected Energy Operating Ratios for Total Energy Consumption" Selected Energy Operating Ratios for Total Energy Consumption" " for Heat, Power, and Electricity Generation by Industry Group," " Selected Industries, and Employment Size Categories, 1994" ,,,,,"Major" ,,,"Consumption","Consumption per","Byproducts(c)","Fuel Oil(d)" ,,"Consumption","per Dollar","Dollar of Value","as a Percent","as a Percent","RSE" "SIC",,"per Employee","of Value Added","of Shipments","of Consumption","of Natural Gas","Row" "Code(a)","Economic Characteristics(b)","(million Btu)","(thousand Btu)","(thousand Btu)","(percents)","(percents)","Factors"

197

"Table A48. Selected Energy Operating Ratios for Total Energy Consumption for"  

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

8. Selected Energy Operating Ratios for Total Energy Consumption for" 8. Selected Energy Operating Ratios for Total Energy Consumption for" " Heat, Power, and Electricity Generation by Census Region, Census Division, and Economic" " Characteristics of the Establishment, 1994" ,,,"Consumption","Major" " "," ","Consumption","per Dollar","Byproducts(b)","Fuel Oil(c)"," " " ","Consumption","per Dollar","of Value","as a Percent","as a Percent","RSE" " ","per Employee","of Value Added","of Shipments","of Consumption","of Natural Gas","Row"

198

"Table A8. Selected Energy Operating Ratios for Total Energy Consumption for"  

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

A8. Selected Energy Operating Ratios for Total Energy Consumption for" A8. Selected Energy Operating Ratios for Total Energy Consumption for" " Heat, Power, and Electricity Generation by Census Region, Industry Group, and" " Selected Industries, 1991" ,,,,,"Major" ,,,,"Consumption","Byproducts(b)" ,,,"Consumption","per Dollar","as a","Fuel Oil(c) as" ,,"Consumption","per Dollar","of Value","Percent of","a Percent of","RSE" "SIC"," ","per Employee","of Value Added","of Shipments","Consumsption","Natural Gas","Row" "Code(a)","Industry Groups and Industry","(million Btu)","(thousand Btu)","(thousand Btu)","(PERCENT)","(percent)","Factors"

199

"Table A51. Selected Energy Operating Ratios for Total Energy Consumption for"  

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

1. Selected Energy Operating Ratios for Total Energy Consumption for" 1. Selected Energy Operating Ratios for Total Energy Consumption for" " Heat, Power, and Electricity Generation by Census Region and Economic" " Characteristics of the Establishment, 1991 " ,,,,,"Major" ,,,"Consumption","Consumption per","Byproducts(c)","Fuel Oil(d)" ,,"Consumption","per Dollar","Dollar of Value","as a Percent","as a Percent","RSE" "SIC",,"per Employee","of Value Added","of Shipments","of Consumption","of Natural Gas","Row" "Code(a)","Economic Characteristics(b)","(million Btu)","(thousand Btu)","(thousand Btu)","(percent)","(percent)","Factors"

200

"Table A47. Selected Energy Operating Ratios for Total Energy Consumption for"  

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

7. Selected Energy Operating Ratios for Total Energy Consumption for" 7. Selected Energy Operating Ratios for Total Energy Consumption for" " Heat, Power, and Electricity Generation by Census Region, Census Division, Industry Group, and" " Selected Industries, 1994" ,,,,,"Major" ,,,,"Consumption","Byproducts(b)" ,,,"Consumption","per Dollar","as a","Fuel Oil(c) as" ,,"Consumption","per Dollar","of Value","Percent of","a Percent of","RSE" "SIC"," ","per Employee","of Value Added","of Shipments","Consumption","Natural Gas","Row" "Code(a)","Industry Group and Industry","(million Btu)","(thousand Btu)","(thousand Btu)","(percents)","(percents)","Factors"

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


201

"Table A50. Selected Energy Operating Ratios for Total Energy Consumption for"  

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

0. Selected Energy Operating Ratios for Total Energy Consumption for" 0. Selected Energy Operating Ratios for Total Energy Consumption for" " Heat, Power, and Electricity Generation by Industry Group," " Selected Industries, and Economic Characteristics of the" " Establishment, 1991 (Continued)" ,,,,,"Major" ,,,"Consumption","Consumption per","Byproducts(c)","Fuel Oil(d)" ,,"Consumption","per Dollar","Dollar of Value","as a Percent of","as a Percent","RSE" "SIC",,"per Employee","of Value Added","of Shipments","of Consumption","of Natural Gas","Row" "Code(a)","Economic Characteristics(b)","(million Btu)","(thousand Btu)","(thousand Btu)","(Percent)","(percent)","Factors"

202

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

203

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

204

Table 18. Total Delivered Commercial Energy Consumption, Projected vs. Actual  

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

Total Delivered Commercial Energy Consumption, Projected vs. Actual Total Delivered Commercial Energy Consumption, Projected vs. Actual Projected (quadrillion Btu) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 AEO 1994 6.8 6.9 6.9 7.0 7.1 7.1 7.2 7.2 7.3 7.3 7.4 7.4 7.4 7.5 7.5 7.5 7.5 7.6 AEO 1995 6.9 6.9 7.0 7.0 7.0 7.1 7.1 7.1 7.1 7.1 7.2 7.2 7.2 7.2 7.3 7.3 7.3 AEO 1996 7.1 7.2 7.2 7.3 7.3 7.4 7.4 7.5 7.6 7.6 7.7 7.7 7.8 7.9 8.0 8.0 8.1 AEO 1997 7.4 7.4 7.4 7.5 7.5 7.6 7.7 7.7 7.8 7.8 7.9 7.9 8.0 8.1 8.1 8.2 AEO 1998 7.5 7.6 7.7 7.8 7.9 8.0 8.0 8.1 8.2 8.3 8.4 8.4 8.5 8.6 8.7 AEO 1999 7.4 7.8 7.9 8.0 8.1 8.2 8.2 8.3 8.4 8.5 8.6 8.7 8.8 8.9 AEO 2000 7.7 7.8 7.9 8.0 8.1 8.2 8.3 8.4 8.5 8.5 8.7 8.7 8.8 AEO 2001 7.8 8.1 8.3 8.6 8.7 8.9 9.0 9.2 9.3 9.5 9.6 9.7 AEO 2002 8.2 8.4 8.7 8.9 9.0 9.2 9.4 9.6 9.7 9.9 10.1

205

Table 16. Total Energy Consumption, Projected vs. Actual Projected  

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

Total Energy Consumption, Projected vs. Actual Total Energy Consumption, Projected vs. Actual Projected (quadrillion Btu) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 AEO 1994 88.0 89.5 90.7 91.7 92.7 93.6 94.6 95.7 96.7 97.7 98.9 100.0 100.8 101.7 102.7 103.6 104.3 105.2 AEO 1995 89.2 90.0 90.6 91.9 93.0 93.8 94.6 95.3 96.2 97.2 98.4 99.4 100.3 101.2 102.1 102.9 103.9 AEO 1996 90.6 91.3 92.5 93.5 94.3 95.1 95.9 96.9 98.0 99.2 100.4 101.4 102.1 103.1 103.8 104.7 105.5 AEO 1997 92.6 93.6 95.1 96.6 97.9 98.8 99.9 101.2 102.4 103.4 104.7 105.8 106.6 107.2 107.9 108.6 AEO 1998 94.7 96.7 98.6 99.8 101.3 102.4 103.4 104.5 105.8 107.3 108.6 109.9 111.1 112.2 113.1 AEO 1999 94.6 97.0 99.2 100.9 102.0 102.8 103.6 104.7 106.0 107.2 108.5 109.7 110.8 111.8

206

Table 19. Total Delivered Industrial Energy Consumption, Projected vs. Actual  

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

Total Delivered Industrial Energy Consumption, Projected vs. Actual Total Delivered Industrial Energy Consumption, Projected vs. Actual Projected (quadrillion Btu) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 AEO 1994 25.4 25.9 26.3 26.7 27.0 27.1 26.8 26.6 26.9 27.2 27.7 28.1 28.3 28.7 29.1 29.4 29.7 30.0 AEO 1995 26.2 26.3 26.5 27.0 27.3 26.9 26.6 26.8 27.1 27.5 27.9 28.2 28.4 28.7 29.0 29.3 29.6 AEO 1996 26.5 26.6 27.3 27.5 26.9 26.5 26.7 26.9 27.2 27.6 27.9 28.2 28.3 28.5 28.7 28.9 29.2 AEO 1997 26.2 26.5 26.9 26.7 26.6 26.8 27.1 27.4 27.8 28.0 28.4 28.7 28.9 29.0 29.2 29.4 AEO 1998 27.2 27.5 27.2 26.9 27.1 27.5 27.7 27.9 28.3 28.7 29.0 29.3 29.7 29.9 30.1 AEO 1999 26.7 26.4 26.4 26.8 27.1 27.3 27.5 27.9 28.3 28.6 28.9 29.2 29.5 29.7 AEO 2000 25.8 25.5 25.7 26.0 26.5 26.9 27.4 27.8 28.1 28.3 28.5 28.8 29.0

207

Table 17. Total Delivered Residential Energy Consumption, Projected vs. Actual  

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

Total Delivered Residential Energy Consumption, Projected vs. Actual Total Delivered Residential Energy Consumption, Projected vs. Actual Projected (quadrillion Btu) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 AEO 1994 10.3 10.4 10.4 10.4 10.4 10.4 10.4 10.4 10.4 10.4 10.4 10.5 10.5 10.5 10.5 10.5 10.6 10.6 AEO 1995 11.0 10.8 10.8 10.8 10.8 10.8 10.8 10.7 10.7 10.7 10.7 10.7 10.7 10.7 10.8 10.8 10.9 AEO 1996 10.4 10.7 10.7 10.7 10.8 10.8 10.9 10.9 11.0 11.2 11.2 11.3 11.4 11.5 11.6 11.7 11.8 AEO 1997 11.1 10.9 11.1 11.1 11.2 11.2 11.2 11.3 11.4 11.5 11.5 11.6 11.7 11.8 11.9 12.0 AEO 1998 10.7 11.1 11.2 11.4 11.5 11.5 11.6 11.7 11.8 11.9 11.9 12.1 12.1 12.2 12.3 AEO 1999 10.5 11.1 11.3 11.3 11.4 11.5 11.5 11.6 11.6 11.7 11.8 11.9 12.0 12.1 AEO 2000 10.7 10.9 11.0 11.1 11.2 11.3 11.4 11.5 11.6 11.7 11.8 11.9 12.0

208

Table 20. Total Delivered Transportation Energy Consumption, Projected vs. Actual  

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

Total Delivered Transportation Energy Consumption, Projected vs. Actual Total Delivered Transportation Energy Consumption, Projected vs. Actual Projected (quadrillion Btu) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 AEO 1994 23.6 24.1 24.5 24.7 25.1 25.4 25.7 26.2 26.5 26.9 27.2 27.6 27.9 28.3 28.6 28.9 29.2 29.5 AEO 1995 23.3 24.0 24.2 24.7 25.1 25.5 25.9 26.2 26.5 26.9 27.3 27.7 28.0 28.3 28.5 28.7 28.9 AEO 1996 23.9 24.1 24.5 24.8 25.3 25.7 26.0 26.4 26.7 27.1 27.5 27.8 28.1 28.4 28.6 28.9 29.1 AEO 1997 24.7 25.3 25.9 26.4 27.0 27.5 28.0 28.5 28.9 29.4 29.8 30.3 30.6 30.9 31.1 31.3 AEO 1998 25.3 25.9 26.7 27.1 27.7 28.3 28.8 29.4 30.0 30.6 31.2 31.7 32.3 32.8 33.1 AEO 1999 25.4 26.0 27.0 27.6 28.2 28.8 29.4 30.0 30.6 31.2 31.7 32.2 32.8 33.1 AEO 2000 26.2 26.8 27.4 28.0 28.5 29.1 29.7 30.3 30.9 31.4 31.9 32.5 32.9

209

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

210

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

211

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

Gasoline and Diesel Fuel Update (EIA)

all comparisons reported in the text are statistically significant, based on a standard test made at the 0.05 significance level. These tests were made using the actual RSE's...

212

Estimating Total Energy Consumption and Emissions of China's Commercial and Office Buildings  

E-Print Network [OSTI]

of Central Government Buildings. Available at: http://Energy Commission, PIER Building End-Use Energy Efficiencythe total lifecycle of a building such as petroleum and

Fridley, David G.

2008-01-01T23:59:59.000Z

213

An Adaptive Tree Code for Computing Total Potential Energy in Classical Molecular Systems  

E-Print Network [OSTI]

An Adaptive Tree Code for Computing Total Potential Energy in Classical Molecular Systems Zhong, 2000 Abstract A tree code algorithm is presented for rapid computation of the total potential energy are presented for a variety of systems. Keywords: adaptive tree code; total potential energy; nonbonded

Duan, Zhong-Hui

214

THE USE OF TRUST REGIONS IN KOHN-SHAM TOTAL ENERGY MINIMIZATION  

E-Print Network [OSTI]

-consistent and the Kohn-Sham (KS) total energy function associated with the system reaches the global minimum. It has longTHE USE OF TRUST REGIONS IN KOHN-SHAM TOTAL ENERGY MINIMIZATION CHAO YANG , JUAN C. MEZA , AND LIN system, is viewed in this paper as an optimization procedure that minimizes the Kohn- Sham total energy

Geddes, Cameron Guy Robinson

215

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

216

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

217

Total China Investment Co Ltd | Open Energy Information  

Open Energy Info (EERE)

Total China Investment Co Ltd Total China Investment Co Ltd Jump to: navigation, search Name Total (China) Investment Co. Ltd. Place Beijing, China Zip 100004 Product Total has been present in China for about 30 years through its activities of Exploration & Production, Gas & Power, Refining & Marketing, and Chemicals. Coordinates 39.90601°, 116.387909° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":39.90601,"lon":116.387909,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

218

Households and Pension  

Science Journals Connector (OSTI)

This chapter deals with two economic issues. First, we examine Japans household structure. In the previous chapter ( Chapter 10 ...), we recognized the importance of the ...

Mitsuhiko Iyoda

2010-01-01T23:59:59.000Z

219

Property:Building/TotalFloorArea | Open Energy Information  

Open Energy Info (EERE)

Property Property Edit with form History Facebook icon Twitter icon » Property:Building/TotalFloorArea Jump to: navigation, search This is a property of type Number. Total floor area (BRA), m2 Pages using the property "Building/TotalFloorArea" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 19,657 + Sweden Building 05K0002 + 7,160 + Sweden Building 05K0003 + 4,855 + Sweden Building 05K0004 + 25,650 + Sweden Building 05K0005 + 2,260 + Sweden Building 05K0006 + 13,048 + Sweden Building 05K0007 + 24,155 + Sweden Building 05K0008 + 7,800 + Sweden Building 05K0009 + 34,755 + Sweden Building 05K0010 + 437 + Sweden Building 05K0011 + 15,310 + Sweden Building 05K0012 + 22,565 + Sweden Building 05K0013 + 19,551 +

220

Property:RenewableFuelStandard/Total | Open Energy Information  

Open Energy Info (EERE)

Total Total Jump to: navigation, search This is a property of type Number. Pages using the property "RenewableFuelStandard/Total" Showing 15 pages using this property. R Renewable Fuel Standard Schedule + 13.95 + Renewable Fuel Standard Schedule + 26 + Renewable Fuel Standard Schedule + 15.2 + Renewable Fuel Standard Schedule + 28 + Renewable Fuel Standard Schedule + 16.55 + Renewable Fuel Standard Schedule + 30 + Renewable Fuel Standard Schedule + 18.15 + Renewable Fuel Standard Schedule + 9 + Renewable Fuel Standard Schedule + 33 + Renewable Fuel Standard Schedule + 20.5 + Renewable Fuel Standard Schedule + 11.1 + Renewable Fuel Standard Schedule + 36 + Renewable Fuel Standard Schedule + 22.25 + Renewable Fuel Standard Schedule + 12.95 + Renewable Fuel Standard Schedule + 24 +

Note: This page contains sample records for the topic "household total energy" 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

"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"

222

Property:Building/FloorAreaTotal | Open Energy Information  

Open Energy Info (EERE)

FloorAreaTotal FloorAreaTotal Jump to: navigation, search This is a property of type Number. Total Pages using the property "Building/FloorAreaTotal" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 19,657 + Sweden Building 05K0002 + 7,160 + Sweden Building 05K0003 + 4,454 + Sweden Building 05K0004 + 25,650 + Sweden Building 05K0005 + 2,260 + Sweden Building 05K0006 + 14,348 + Sweden Building 05K0007 + 24,155 + Sweden Building 05K0008 + 7,800 + Sweden Building 05K0009 + 34,755 + Sweden Building 05K0010 + 437 + Sweden Building 05K0011 + 15,300 + Sweden Building 05K0012 + 22,565 + Sweden Building 05K0013 + 19,551 + Sweden Building 05K0014 + 1,338.3 + Sweden Building 05K0015 + 1,550 + Sweden Building 05K0016 + 2,546 +

223

Property:Building/SPElectrtyUsePercTotal | Open Energy Information  

Open Energy Info (EERE)

SPElectrtyUsePercTotal SPElectrtyUsePercTotal Jump to: navigation, search This is a property of type String. Total Pages using the property "Building/SPElectrtyUsePercTotal" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 100.0 + Sweden Building 05K0002 + 100.0 + Sweden Building 05K0003 + 100.0 + Sweden Building 05K0004 + 100.0 + Sweden Building 05K0005 + 100.0 + Sweden Building 05K0006 + 100.0 + Sweden Building 05K0007 + 100.0 + Sweden Building 05K0008 + 100.0 + Sweden Building 05K0009 + 100.0 + Sweden Building 05K0010 + 100.0 + Sweden Building 05K0011 + 100.0 + Sweden Building 05K0012 + 100.0 + Sweden Building 05K0013 + 100.0 + Sweden Building 05K0014 + 100.0 + Sweden Building 05K0015 + 100.0 + Sweden Building 05K0016 + 100.0 +

224

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

225

char_household2001.pdf  

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

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

226

ac_household2001.pdf  

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

1a. Air Conditioning by South Census Region, 1a. Air Conditioning by South Census Region, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total U.S. South Census Region RSE Row Factors Total Census Division South Atlantic East South Central West South Central 0.5 0.8 1.2 1.3 1.4 Households With Electric Air-Conditioning Equipment ...................... 82.9 37.2 19.3 6.4 11.5 1.5 Air Conditioners Not Used ........................... 2.1 0.4 Q Q Q 28.2 Households Using Electric Air-Conditioning 1 ........................................ 80.8 36.9 19.0 6.4 11.5 1.6 Type of Electric Air-Conditioning Used Central Air-Conditioning 2 ............................ 57.5 30.4 16.1 5.0 9.2 2.8 Without a Heat Pump ................................ 46.2 22.1 10.4 3.4 8.3 5.6 With a Heat Pump

227

ac_household2001.pdf  

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

9a. Air Conditioning by Northeast Census Region, 9a. Air Conditioning by Northeast Census Region, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total U.S. Northeast Census Region RSE Row Factors Total Census Division Middle Atlantic New England 0.5 1.0 1.2 1.8 Households With Electric Air-Conditioning Equipment ...................... 82.9 14.5 11.3 3.2 3.3 Air Conditioners Not Used ........................... 2.1 0.3 0.3 Q 28.3 Households Using Electric Air-Conditioning 1 ........................................ 80.8 14.2 11.1 3.2 3.4 Type of Electric Air-Conditioning Used Central Air-Conditioning 2 ............................ 57.5 5.7 4.9 0.8 8.9 Without a Heat Pump ................................ 46.2 5.2 4.5 0.7 9.2 With a Heat Pump .....................................

228

AEO2011: Total Energy Supply, Disposition, and Price Summary | OpenEI  

Open Energy Info (EERE)

Total Energy Supply, Disposition, and Price Summary Total Energy Supply, Disposition, and Price Summary Dataset Summary Description This dataset comes from the Energy Information Administration (EIA), and is part of the 2011 Annual Energy Outlook Report (AEO2011). This dataset is table 1, and contains only the reference case. The dataset uses quadrillion BTUs, and quantifies the energy prices using U.S. dollars. The data is broken down into total production, imports, exports, consumption, and prices for energy types. Source EIA Date Released April 26th, 2011 (3 years ago) Date Updated Unknown Keywords 2011 AEO consumption EIA export import production reference case total energy Data application/vnd.ms-excel icon AEO2011: Total Energy Supply, Disposition, and Price Summary - Reference Case (xls, 112.8 KiB) Quality Metrics

229

IEP - Water-Energy Interface: Total Maximum Daily Load Page  

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

Total Maximum Daily Loads (TMDLs) Total Maximum Daily Loads (TMDLs) The overall goal of the Clean Water Act is to "restore and maintain the chemical, physical, and biological integrity of the Nation’s waters." In 1999, EPA proposed changes to Section 303(d), to establish Total Maximum Daily Loads (TMDLs) for watersheds that do not meet this goal. The TMDL is the highest amount of a given pollutant that is permissible in that body of water over a given period of time. TMDLs include both waste load allocation (WLA) for point sources and load allocations for non-point sources. In Appalachia, acid mine drainage (AMD) is the single most damaging non-point source. There is also particular concern of the atmospheric deposition of airborne sulfur, nitrogen, and mercury compounds. States are currently in the process of developing comprehensive lists of impaired waters and establishing TMDLs for those waters. EPA has recently proposed a final rule that will require states to develop TMDLs and implement plans for improving water quality within the next 10 years. Under the new rule, TMDL credits could be traded within a watershed.

230

"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"

231

Toward understanding the exchange-correlation energy and total-energy density functionals  

Science Journals Connector (OSTI)

If an accurate ground-state electron density ?0 for a system is known, it is shown from calculations on atoms that a strikingly good estimate for the total electronic energy of atoms is provided by the formula E[?0]=tsumi?i-(1-1/N)J[?0], where N is the number of electrons, J[?0] is the classical Coulomb repulsion energy for ?0, and the ?i are the Kohn-Sham orbital energies determined by the Zhao-Morrison-Parr procedure [Phys. Rev. A 50, 2138 (1994)] for implementation of the Levy-constrained search determination of the Kohn-Sham kinetic energy. The surprising accuracy of this formula is attributed to the fact that the exchange-correlation functional is equal to -J/N plus a functional that behaves as if it were approximately homogeneous, of degree 1 in the electron density. A corresponding exact formula is given, and various approximate models are constructed.

Robert G. Parr and Swapan K. Ghosh

1995-05-01T23:59:59.000Z

232

Table A10. Total Inputs of Energy for Heat, Power, and Electricity...  

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

0. Total Inputs of Energy for Heat, Power, and Electricity Generation" " by Fuel Type, Industry Group, Selected Industries, and End Use, 1994:" " Part 2" " (Estimates in Trillion...

233

A Constrained Optimization Algorithm for Total Energy Minimization in Electronic Structure Calculation  

E-Print Network [OSTI]

Functionals for Electronic Structure Calculations. J. Comp.Minimization in Electronic Structure Calculation ? ChaoKey words: electronic structure calculation, total energy

Yang, Chao; Meza, Juan C.; Wang, Lin-Wang

2005-01-01T23:59:59.000Z

234

Modal and Nonmodal Symmetric Perturbations. Part II: Nonmodal Growths Measured by Total Perturbation Energy  

Science Journals Connector (OSTI)

Maximum nonmodal growths of total perturbation energy are computed for symmetric perturbations constructed from the normal modes presented in Part I. The results show that the maximum nonmodal growths are larger than the energy growth produced by ...

Qin Xu; Ting Lei; Shouting Gao

2007-06-01T23:59:59.000Z

235

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

236

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

237

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

238

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

239

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

240

Towards sustainable consumption: do green households have smaller ecological footprints?  

Science Journals Connector (OSTI)

The need for households in rich countries to develop more sustainable consumption patterns is high on the political agenda. An increased awareness of environmental issues among the general public is often presented as an important prerequisite for this change. This article describes how the study team compared the ecological footprints of ''green'' and ''ordinary'' households. These footprint calculations are based on a number of consumption categories that have severe environmental consequences, such as energy and material use in the home, and transport. The comparison is based on a survey of 404 households in the city of Stavanger, where 66 respondents were members of the Environmental Home Guard in Norway. The analysis suggests that, even if the green households have a smaller ecological footprint per household member, this is not caused by their participation in the Home Guard. It merely reflects the fact that green households are larger than ordinary households.

Erling Holden

2004-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "household total energy" 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

Japan's Residential Energy Demand Outlook to 2030 Considering Energy Efficiency Standards "Top-Runner Approach"  

E-Print Network [OSTI]

Total Energy Source Demand Coal, Oil, Gas, Heat, ElectricityEnergy Source Demand per Household Coal, Oil, Gas, Heat,ton of oil equivalent Considerable increases in demand for

Komiyama, Ryoichi

2008-01-01T23:59:59.000Z

242

Total electron and proton energy input during auroral substorms: Remote sensing with IMAGE-FUV  

E-Print Network [OSTI]

, it is found that the most critical factor is the assumption made on the energy of the auroral protonsTotal electron and proton energy input during auroral substorms: Remote sensing with IMAGE-FUV B and proton energy fluxes. The proton energy flux is derived from the Lyman a measurements on the basis

California at Berkeley, University of

243

Increased energy prices: energy savings and equity aspects. Final report  

SciTech Connect (OSTI)

A mathematical model has been developed which approximates the reduction in a household's total energy consumption in response to higher energy prices and different rebate schemes. This model is based on the assumption that energy consumption is a function of a household's real income, prices of different commodities and energy intensities. The amount of energy saved and the change in real expenditure of a household has been calculated for four tax rates; 50%, 100%, 224% and 400%, and five rebate schemes; one regressive, two progressive, one income distribution preserving and the flat per capita rebate. The results indicate that, for a given tax rate, the choice of rebate scheme does not significantly affect the amount of energy conserved by the households. However, the effect of different rebate schemes on a household's real expenditure could be dramatically different.

Herendeen, R.A.

1983-06-01T23:59:59.000Z

244

"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"

245

Table A14. Total First Use (formerly Primary Consumption) of Energy for All P  

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

4. Total First Use (formerly Primary Consumption) of Energy for All Purposes" 4. Total First Use (formerly Primary Consumption) of Energy for All Purposes" " by Value of Shipment Categories, Industry Group, and Selected Industries, 1994" " (Estimates in Trillion Btu)" ,,,," Value of Shipments and Receipts(b)" ,,,," "," (million dollars)" ,,,,,,,,,"RSE" "SIC"," "," "," "," "," "," "," ",500,"Row"," "," "," ",," "," "," "," " "Code(a)","Industry Group and Industry","Total","Under 20","20-49","50-99","100-249","250-499","and Over","Factors"," "," "," "," "," "," "," "," ",," "

246

Table A45. Total Inputs of Energy for Heat, Power, and Electricity Generation  

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

Total Inputs of Energy for Heat, Power, and Electricity Generation" Total Inputs of Energy for Heat, Power, and Electricity Generation" " by Enclosed Floorspace, Percent Conditioned Floorspace, and Presence of Computer" " Controls for Building Environment, 1991" " (Estimates in Trillion Btu)" ,,"Presence of Computer Controls" ,," for Buildings Environment",,"RSE" "Enclosed Floorspace and"," ","--------------","--------------","Row" "Percent Conditioned Floorspace","Total","Present","Not Present","Factors" " "," " "RSE Column Factors:",0.8,1.3,0.9 "ALL SQUARE FEET CATEGORIES" "Approximate Conditioned Floorspace"

247

Table A30. Total Primary Consumption of Energy for All Purposes by Value of  

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

0. Total Primary Consumption of Energy for All Purposes by Value of" 0. Total Primary Consumption of Energy for All Purposes by Value of" "Shipment Categories, Industry Group, and Selected Industries, 1991" " (Estimates in Trillion Btu)" ,,,," Value of Shipments and Receipts(b)" ,,,," ","(million dollars)" ,,,"-","-","-","-","-","-","RSE" "SIC"," "," "," "," "," "," "," ",500,"Row"," "," "," ",," "," "," "," " "Code(a)","Industry Groups and Industry","Total","Under 20","20-49","50-99","100-249","250-499","and Over","Factors"," "," "," "," "," "," "," "," ",," "

248

Table A31. Total Inputs of Energy for Heat, Power, and Electricity Generation  

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

Total Inputs of Energy for Heat, Power, and Electricity Generation" Total Inputs of Energy for Heat, Power, and Electricity Generation" " by Value of Shipment Categories, Industry Group, and Selected Industries, 1991" " (Continued)" " (Estimates in Trillion Btu)",,,,"Value of Shipments and Receipts(b)" ,,,," (million dollars)" ,,,"-","-","-","-","-","-","RSE" "SIC"," "," "," "," "," "," "," ",500,"Row" "Code(a)","Industry Groups and Industry","Total","Under 20","20-49","50-99","100-249","250-499","and Over","Factors"

249

"Table A11. Total Primary Consumption of Combustible Energy for Nonfuel"  

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

1. Total Primary Consumption of Combustible Energy for Nonfuel" 1. Total Primary Consumption of Combustible Energy for Nonfuel" " Purposes by Census Region and Economic Characteristics of the Establishment," 1991 " (Estimates in Btu or Physical Units)" " "," "," "," ","Natural"," "," ","Coke"," "," " " ","Total","Residual","Distillate","Gas(c)"," ","Coal","and Breeze","Other(d)","RSE" " ","(trillion","Fuel Oil","Fuel Oil(b)","(billion","LPG","(1000","(1000","(trillion","Row"

250

Table 21. Total Transportation Energy Consumption, Projected vs. Actual  

Gasoline and Diesel Fuel Update (EIA)

Transportation Energy Consumption, Projected vs. Actual Transportation Energy Consumption, Projected vs. Actual (quadrillion Btu) 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 AEO 1982 18.6 18.2 17.7 17.3 17.0 16.9 AEO 1983 19.8 20.1 20.4 20.4 20.5 20.5 20.7 AEO 1984 19.2 19.0 19.0 19.0 19.1 19.2 20.1 AEO 1985 20.0 19.8 20.0 20.0 20.0 20.1 20.3 AEO 1986 20.5 20.8 20.8 20.6 20.7 20.3 21.0 AEO 1987 21.3 21.5 21.6 21.7 21.8 22.0 22.0 22.0 21.9 22.3 AEO 1989* 21.8 22.2 22.4 22.4 22.5 22.5 22.5 22.5 22.6 22.7 22.8 23.0 23.2 AEO 1990 22.0 22.4 23.2 24.3 25.5 AEO 1991 22.1 21.6 21.9 22.1 22.3 22.5 22.8 23.1 23.4 23.8 24.1 24.5 24.8 25.1 25.4 25.7 26.0 26.3 26.6 26.9 AEO 1992 21.7 22.0 22.5 22.9 23.2 23.4 23.6 23.9 24.1 24.4 24.8 25.1 25.4 25.7 26.0 26.3 26.6 26.9 27.1 AEO 1993 22.5 22.8 23.4 23.9 24.3 24.7 25.1 25.4 25.7 26.1 26.5 26.8 27.2 27.6 27.9 28.1 28.4 28.7 AEO 1994 23.6

251

Table 17. Total Energy Consumption, Projected vs. Actual  

Gasoline and Diesel Fuel Update (EIA)

Energy Consumption, Projected vs. Actual Energy Consumption, Projected vs. Actual (quadrillion Btu) 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 AEO 1982 79.1 79.6 79.9 80.8 82.1 83.3 AEO 1983 78.0 79.5 81.0 82.4 83.9 84.6 89.0 AEO 1984 78.5 79.4 81.2 83.1 85.1 86.4 93.0 AEO 1985 77.6 78.5 79.8 81.2 82.7 83.3 84.2 85.0 85.7 86.3 87.2 AEO 1986 77.0 78.8 79.8 80.7 81.5 82.9 83.8 84.6 85.3 86.0 86.6 87.4 88.3 89.4 90.2 AEO 1987 78.9 80.0 82.0 82.8 83.9 85.1 86.2 87.1 87.9 92.5 AEO 1989* 82.2 83.8 84.5 85.4 86.2 87.1 87.8 88.7 89.5 90.4 91.4 92.4 93.5 AEO 1990 84.2 85.4 91.9 97.4 102.8 AEO 1991 84.4 85.0 86.0 87.0 87.9 89.1 90.4 91.8 93.1 94.3 95.6 97.1 98.4 99.4 100.3 101.4 102.5 103.6 104.7 105.8 AEO 1992 84.7 87.0 88.0 89.2 90.5 91.4 92.4 93.4 94.5 95.6 96.9 98.0 99.0 100.0 101.2 102.2 103.2 104.3 105.2 AEO 1993 87.0 88.3 89.8 91.4 92.7 94.0 95.3 96.3 97.5 98.6

252

Table 20. Total Industrial Energy Consumption, Projected vs. Actual  

Gasoline and Diesel Fuel Update (EIA)

Industrial Energy Consumption, Projected vs. Actual Industrial Energy Consumption, Projected vs. Actual (quadrillion Btu) 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 AEO 1982 24.0 24.1 24.4 24.9 25.5 26.1 AEO 1983 23.2 23.6 23.9 24.4 24.9 25.0 25.4 AEO 1984 24.1 24.5 25.4 25.5 27.1 27.4 28.7 AEO 1985 23.2 23.6 23.9 24.4 24.8 24.8 24.4 AEO 1986 22.2 22.8 23.1 23.4 23.4 23.6 22.8 AEO 1987 22.4 22.8 23.7 24.0 24.3 24.6 24.6 24.7 24.9 22.6 AEO 1989* 23.6 24.0 24.1 24.3 24.5 24.3 24.3 24.5 24.6 24.8 24.9 24.4 24.1 AEO 1990 25.0 25.4 27.1 27.3 28.6 AEO 1991 24.6 24.5 24.8 24.8 25.0 25.3 25.7 26.2 26.5 26.1 25.9 26.2 26.4 26.6 26.7 27.0 27.2 27.4 27.7 28.0 AEO 1992 24.6 25.3 25.4 25.6 26.1 26.3 26.5 26.5 26.0 25.6 25.8 26.0 26.1 26.2 26.4 26.7 26.9 27.2 27.3 AEO 1993 25.5 25.9 26.2 26.8 27.1 27.5 27.8 27.4 27.1 27.4 27.6 27.8 28.0 28.2 28.4 28.7 28.9 29.1 AEO 1994 25.4 25.9

253

Table 18. Total Residential Energy Consumption, Projected vs. Actual  

Gasoline and Diesel Fuel Update (EIA)

Residential Energy Consumption, Projected vs. Actual Residential Energy Consumption, Projected vs. Actual (quadrillion Btu) 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 AEO 1982 10.1 10.1 10.1 10.1 10.2 10.2 AEO 1983 9.8 9.9 10.0 10.1 10.2 10.1 10.0 AEO 1984 9.9 9.9 10.0 10.2 10.3 10.3 10.5 AEO 1985 9.8 10.0 10.1 10.3 10.6 10.6 10.9 AEO 1986 9.6 9.8 10.0 10.3 10.4 10.8 10.9 AEO 1987 9.9 10.2 10.3 10.3 10.4 10.5 10.5 10.5 10.5 10.6 AEO 1989* 10.3 10.5 10.4 10.5 10.5 10.5 10.5 10.5 10.5 10.5 10.5 10.5 10.5 AEO 1990 10.4 10.7 10.8 11.0 11.3 AEO 1991 10.2 10.7 10.7 10.8 10.8 10.8 10.9 10.9 10.9 11.0 11.0 11.0 11.1 11.2 11.2 11.3 11.4 11.4 11.5 11.6 AEO 1992 10.6 11.1 11.1 11.1 11.1 11.1 11.2 11.2 11.3 11.3 11.4 11.5 11.5 11.6 11.7 11.8 11.8 11.9 12.0 AEO 1993 10.7 10.9 11.0 11.0 11.0 11.1 11.1 11.1 11.1 11.2 11.2 11.2 11.2 11.3 11.3 11.4 11.4 11.5 AEO 1994 10.3 10.4 10.4 10.4

254

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

255

Table 19. Total Commercial Energy Consumption, Projected vs. Actual  

Gasoline and Diesel Fuel Update (EIA)

Commercial Energy Consumption, Projected vs. Actual Commercial Energy Consumption, Projected vs. Actual (quadrillion Btu) 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 AEO 1982 6.6 6.7 6.8 6.8 6.8 6.9 AEO 1983 6.4 6.6 6.8 6.9 7.0 7.1 7.2 AEO 1984 6.2 6.4 6.5 6.7 6.8 6.9 7.3 AEO 1985 5.9 6.1 6.2 6.3 6.4 6.5 6.7 AEO 1986 6.2 6.3 6.4 6.4 6.5 7.1 7.4 AEO 1987 6.1 6.1 6.3 6.4 6.6 6.7 6.8 6.9 6.9 7.3 AEO 1989* 6.6 6.7 6.9 7.0 7.0 7.1 7.2 7.3 7.3 7.4 7.5 7.6 7.7 AEO 1990 6.6 6.8 7.1 7.4 7.8 AEO 1991 6.7 6.9 7.0 7.1 7.1 7.2 7.3 7.4 7.5 7.6 7.7 7.8 7.9 8.0 8.1 8.2 8.3 8.4 8.6 8.7 AEO 1992 6.8 7.1 7.2 7.3 7.3 7.4 7.5 7.6 7.7 7.8 7.9 8.0 8.1 8.2 8.3 8.4 8.5 8.6 8.7 AEO 1993 7.2 7.3 7.4 7.4 7.5 7.6 7.7 7.7 7.8 7.9 7.9 8.0 8.0 8.1 8.1 8.1 8.2 8.2 AEO 1994 6.8 6.9 6.9 7.0 7.1 7.1 7.2 7.2 7.3 7.3 7.4 7.4 7.4 7.5 7.5 7.5 7.5 AEO 1995 6.94 6.9 7.0 7.0 7.0 7.1 7.1 7.1 7.1 7.1 7.2 7.2 7.2 7.2 7.3 7.3 AEO 1996 7.1 7.2 7.2 7.3 7.3 7.4 7.4 7.5 7.6 7.6 7.7 7.7 7.8 7.9 8.0

256

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

257

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

258

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

259

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

260

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

Note: This page contains sample records for the topic "household total energy" 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

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

262

Table A54. Number of Establishments by Total Inputs of Energy for Heat, Powe  

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

Number of Establishments by Total Inputs of Energy for Heat, Power, and Electricity Generation," Number of Establishments by Total Inputs of Energy for Heat, Power, and Electricity Generation," " by Industry Group, Selected Industries, and" " Presence of General Technologies, 1994: Part 2" ,," "," ",," "," ",," "," "," "," " ,,,,"Computer Control" ,," "," ","of Processes"," "," ",," "," ",," " ,," ","Computer Control","or Major",,,"One or More"," ","RSE" "SIC"," ",,"of Building","Energy-Using","Waste Heat"," Adjustable-Speed","General Technologies","None","Row"

263

Economic theory and women's household status: The case of Japan  

Science Journals Connector (OSTI)

Economic development disadvantages wives. Conventional microeconomic theory predicts this. As household incomes rise, wives have incentives to specialize in intangible household production. This may raise total household production according to the theory of comparative advantage, but disproportionately favors husbands in distribution of the gains according to the marginal productivity theory of distribution. Wives may become better off in absolute terms but more dependent financially on their husbands and lose power within the household. Historically, Japanese gender roles became highly specialized and wives legal status declined, although other Meiji-era features protected wives. Policies to improve women's status should address the precise economic problem involved.

Barbara J. Redman

2008-01-01T23:59:59.000Z

264

"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

265

Energy consumption and environmental pollution: a stochastic model  

Science Journals Connector (OSTI)

......indicated that total energy consumption in sugar beet production...pollution. Although energy consumption increased sugar beet yield...and found that hybrid and electric car technologies exhibit (efficiency...ergy efficiency, affects consumption choice by Swedish households......

Charles S. Tapiero

2009-07-01T23:59:59.000Z

266

Table A50. Total Inputs of Energy for Heat, Power, and Electricity Generatio  

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

A50. Total Inputs of Energy for Heat, Power, and Electricity Generation" A50. Total Inputs of Energy for Heat, Power, and Electricity Generation" " by Census Region, Industry Group, Selected Industries, and Type of" " Energy-Management Program, 1994" " (Estimates in Trillion Btu)" ,,,," Census Region",,,"RSE" "SIC",,,,,,,"Row" "Code(a)","Industry Group and Industry","Total","Northeast","Midwest","South","West","Factors" ,"RSE Column Factors:",0.7,1.2,1.1,0.9,1.2 "20-39","ALL INDUSTRY GROUPS" ,"Participation in One or More of the Following Types of Programs",12605,1209,3303,6386,1706,2.9

267

Table A20. Total First Use (formerly Primary Consumption) of Energy for All P  

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

Total First Use (formerly Primary Consumption) of Energy for All Purposes by Census" Total First Use (formerly Primary Consumption) of Energy for All Purposes by Census" " Region, Census Division, and Economic Characteristics of the Establishment, 1994" " (Estimates in Btu or Physical Units)" ,,,,,,,,"Coke",,"Shipments" " "," ","Net","Residual","Distillate","Natural Gas(e)"," ","Coal","and Breeze"," ","of Energy Sources","RSE" " ","Total(b)","Electricity(c)","Fuel Oil","Fuel Oil(d)","(billion","LPG","(1000","(1000","Other(f)","Produced Onsite(g)","Row"

268

Table A41. Total Inputs of Energy for Heat, Power, and Electricity  

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

A41. Total Inputs of Energy for Heat, Power, and Electricity" A41. Total Inputs of Energy for Heat, Power, and Electricity" " Generation by Census Region, Industry Group, Selected Industries, and Type of" " Energy Management Program, 1991" " (Estimates in Trillion Btu)" ,,," Census Region",,,,"RSE" "SIC","Industry Groups",," -------------------------------------------",,,,"Row" "Code(a)","and Industry","Total","Northeast","Midwest","South","West","Factors" ,"RSE Column Factors:",0.7,1.3,1,0.9,1.2 "20-39","ALL INDUSTRY GROUPS" ,"Participation in One or More of the Following Types of Programs",10743,1150,2819,5309,1464,2.6,,,"/WIR{D}~"

269

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

270

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

271

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

272

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

273

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

274

Household portfolios in Japan  

Science Journals Connector (OSTI)

I provide a detailed description and in-depth analysis of household portfolios in Japan. (1) It is shown that the share of equities in financial wealth and the stock market participation of Japanese households decreased throughout the 1990s. (2) Using survey data, age-related variations in the share of stocks in financial wealth are analyzed. The equity share and stock market participation increase with age among young households, peaking when people reach their 50s, and then stabilizing. However, the share of equities conditional on ownership exhibits no significant age-related pattern, implying that age-related patterns are primarily explained by the decision to hold stocks. A similar mechanism operates to that found in previous studies of Western countries. (3) Owner-occupied housing has a significantly positive effect on stock market participation and on the share of stocks in financial wealth.

Tokuo Iwaisako

2009-01-01T23:59:59.000Z

275

AEO2011:Total Energy Supply, Disposition, and Price Summary | OpenEI  

Open Energy Info (EERE)

Total Energy Supply, Disposition, and Price Summary Total Energy Supply, Disposition, and Price Summary Dataset Summary Description This dataset comes from the Energy Information Administration (EIA), and is part of the 2011 Annual Energy Outlook Report (AEO2011). This dataset is table 1, and contains only the reference case. The dataset uses quadrillion Btu and the U.S. Dollar. The data is broken down into production, imports, exports, consumption and price. Source EIA Date Released April 26th, 2011 (3 years ago) Date Updated Unknown Keywords 2011 AEO consumption disposition energy exports imports Supply Data application/vnd.ms-excel icon AEO2011:Total Energy Supply, Disposition, and Price Summary- Reference Case (xls, 112.8 KiB) Quality Metrics Level of Review Peer Reviewed Comment Temporal and Spatial Coverage

276

Estimating Total Energy Consumption and Emissions of China's Commercial and Office Buildings  

SciTech Connect (OSTI)

Buildings represent an increasingly important component of China's total energy consumption mix. However, accurately assessing the total volume of energy consumed in buildings is difficult owing to deficiencies in China's statistical collection system and a lack of national surveys. Official statistics suggest that buildings account for about 19% of China's total energy consumption, while others estimate the proportion at 23%, rising to 30% over the next few years. In addition to operational energy, buildings embody the energy used in the in the mining, extraction, harvesting, processing, manufacturing and transport of building materials as well as the energy used in the construction and decommissioning of buildings. This embodied energy, along with a building's operational energy, constitutes the building's life-cycle energy and emissions footprint. This report first provides a review of international studies on commercial building life-cycle energy use from which data are derived to develop an assessment of Chinese commercial building life-cycle energy use, then examines in detail two cases for the development of office building operational energy consumption to 2020. Finally, the energy and emissions implications of the two cases are presented.

Fridley, David; Fridley, David G.; Zheng, Nina; Zhou, Nan

2008-03-01T23:59:59.000Z

277

Ab initio total energy study of brucite, diaspore and hypothetical hydrous wadsleyite  

Science Journals Connector (OSTI)

Ab initio total energy calculations based on the local density approximation (LDA) and the generalised gradient approximation (GGA) of density functional theory have been performed for brucite, Mg(OH)2, diaspore,...

B. Winkler; V. Milman; B. Hennion; M. C. Payne

1995-10-01T23:59:59.000Z

278

E-Print Network 3.0 - ab-initio total energy Sample Search Results  

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

ab-initio total energy Page: << < 1 2 3 4 5 > >> 1 INSTITUTE OF PHYSICS PUBLISHING MEASUREMENT SCIENCE AND TECHNOLOGY Meas. Sci. Technol. 16 (2005) 296301 doi:10.10880957-0233...

279

"Keeping Up" or "Keeping Afloat"? : how American households accumulate wealth  

E-Print Network [OSTI]

having a Black or Hispanic household head, and experiencingBlack households, Hispanic households, poor households, etc.that Black- and Hispanic- headed households appear to be at

Lundy, Jeffrey Dalton

2012-01-01T23:59:59.000Z

280

"Table A22. Total Quantity of Purchased Energy Sources by Census Region,"  

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

2. Total Quantity of Purchased Energy Sources by Census Region," 2. Total Quantity of Purchased Energy Sources by Census Region," " Industry Group, and Selected Industries, 1991" " (Estimates in Btu or Physical Units)" ,,,,,,"Natural",,,"Coke" " "," ","Total","Electricity","Residual","Distillate","Gas(c)"," ","Coal","and Breeze"," ","RSE" "SIC"," ","(trillion","(million","Fuel Oil","Fuel Oil(b)","(billion","LPG","(1000","(1000","Other(d)","Row" "Code(a)","Industry Groups and Industry","Btu)","kWh)","(1000 bbls)","(1000 bbls)","cu ft)","(1000 bbls)","short tons)","short tons)","(trillion Btu)","Factors"

Note: This page contains sample records for the topic "household total energy" 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

Table A9. Total Primary Consumption of Energy for All Purposes by Census  

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

A9. Total Primary Consumption of Energy for All Purposes by Census" A9. Total Primary Consumption of Energy for All Purposes by Census" " Region and Economic Characteristics of the Establishment, 1991" " (Estimates in Btu or Physical Units)" ,,,,,,,,"Coke" " "," ","Net","Residual","Distillate","Natural Gas(d)"," ","Coal","and Breeze"," ","RSE" " ","Total","Electricity(b)","Fuel Oil","Fuel Oil(c)","(billion","LPG","(1000","(1000","Other(e)","Row" "Economic Characteristics(a)","(trillion Btu)","(million kWh)","(1000 bbls)","(1000 bbls)","(cu ft)","(1000 bbls)","short tons)","short tons)","(trillion Btu)","Factors"

282

Table A56. Number of Establishments by Total Inputs of Energy for Heat, Powe  

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

Number of Establishments by Total Inputs of Energy for Heat, Power, and Electricity Generation," Number of Establishments by Total Inputs of Energy for Heat, Power, and Electricity Generation," " by Industry Group, Selected Industries, and" " Presence of Industry-Specific Technologies for Selected Industries, 1994: Part 2" ,,,"RSE" "SIC",,,"Row" "Code(a)","Industry Group and Industry","Total(b)","Factors" ,"RSE Column Factors:",1 20,"FOOD and KINDRED PRODUCTS" ,"Industry-Specific Technologies" ,"One or More Industry-Specific Technologies Present",2353,9 ," Infrared Heating",607,13 ," Microwave Drying",127,21 ," Closed-Cycle Heat Pump System Used to Recover Heat",786,19

283

Table A17. Total First Use (formerly Primary Consumption) of Energy for All P  

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

Total First Use (formerly Primary Consumption) of Energy for All Purposes" Total First Use (formerly Primary Consumption) of Energy for All Purposes" " by Employment Size Categories, Industry Group, and Selected Industries, 1994" " (Estimates in Trillion Btu)" ,,,," "," Employment Size(b)" ,,,,,,,,,"RSE" "SIC"," "," "," "," "," "," "," ",1000,"Row" "Code(a)","Industry Group and Industry","Total","Under 50","50-99","100-249","250-499","500-999","and Over","Factors" ,"RSE Column Factors:",0.6,1.5,1.5,1,0.9,0.9,0.9 , 20,"Food and Kindred Products",1193,119,207,265,285,195,122,6

284

Table A15. Total Inputs of Energy for Heat, Power, and Electricity Generation  

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

Total Inputs of Energy for Heat, Power, and Electricity Generation" Total Inputs of Energy for Heat, Power, and Electricity Generation" " by Value of Shipment Categories, Industry Group, and Selected Industries, 1994" " (Estimates in Trillion Btu)" ,,,," Value of Shipments and Receipts(b)" ,,,," "," (million dollars)" ,,,,,,,,,"RSE" "SIC"," "," "," "," "," "," "," ",500,"Row" "Code(a)","Industry Group and Industry","Total","Under 20","20-49","50-99","100-249","250-499","and Over","Factors" ,"RSE Column Factors:",0.6,1.3,1,1,0.9,1.2,1.2

285

U.S. Department of Energy Releases Revised Total System Life Cycle Cost  

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

Releases Revised Total System Life Cycle Releases Revised Total System Life Cycle Cost Estimate and Fee Adequacy Report for Yucca Mountain Project U.S. Department of Energy Releases Revised Total System Life Cycle Cost Estimate and Fee Adequacy Report for Yucca Mountain Project August 5, 2008 - 2:40pm Addthis WASHINGTON, DC -The U.S. Department of Energy (DOE) today released a revised estimate of the total system life cycle cost for a repository at Yucca Mountain, Nevada. The 2007 total system life cycle cost estimate includes the cost to research, construct and operate Yucca Mountain during a period of 150 years, from the beginning of the program in 1983 through closure and decommissioning in 2133. The new cost estimate of $79.3 billion, when updated to 2007 dollars comes to $96.2 billion, a 38 percent

286

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

287

Benchmark quality total atomization energies of small polyatomic Jan M. L. Martin  

E-Print Network [OSTI]

Benchmark quality total atomization energies of small polyatomic molecules Jan M. L. Martin Successive coupled-cluster CCSD T calculations in basis sets of spdf, spdfg, and spdfgh quality, combined with separate Schwartz-type extrapolations A B/(l 1/2) of the self-consistent field SCF and correlation energies

Martin, Jan M.L.

288

Table A33. Total Primary Consumption of Energy for All Purposes by Employment  

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

Primary Consumption of Energy for All Purposes by Employment" Primary Consumption of Energy for All Purposes by Employment" " Size Categories, Industry Group, and Selected Industries, 1991 (Continued)" " (Estimates in Trillion Btu)" ,,,,,"Employment Size" ,,,"-","-","-","-","-","-","RSE" "SIC"," "," "," "," "," "," ",,500,"Row" "Code(a)","Industry Groups and Industry","Total","Under 20","20-49","50-99","100-249","250-499","and Over","Factors"," "," "," "," "," "," "," "

289

Low-energy positron scattering from methanol and ethanol: Total cross sections  

Science Journals Connector (OSTI)

We report total cross sections for positron scattering from two primary alcohols, methanol (CH3OH) and ethanol (C2H5OH). The energy range of the present study is 0.140eV. The ethanol measurement appears to be original while for methanol we compare our data to the only previous result from Kimura and colleagues [Adv. Chem. Phys. 111, 537 (2000)], with a significant discrepancy between them being found at the lower energies. Positronium formation threshold energies for both species, deduced from the present respective total cross section data sets, are found to be consistent with those expected on the basis of their known ionization energies. There are currently no theoretical results against which we can compare our total cross sections.

Antonio Zecca, Luca Chiari, A. Sarkar, Kate L. Nixon, and Michael J. Brunger

2008-08-05T23:59:59.000Z

290

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

E-Print Network [OSTI]

be damaged when corrosive chemicals are put down the drain. Burning hazardous wastes simply distributes themHousehold 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

de Lijser, Peter

291

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

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

0 Home Appliances Usage Indicators by Number of Household Members, 2005 Total... 111.1 30.0 34.8 18.4...

292

Non-CFC vacuum alternatives for the energy-efficient insulation of household refrigerators: Design and use  

SciTech Connect (OSTI)

Energy efficiency, environmental issues, and market incentives all encourage government and industry to continue work on thin-profile vacuum insulations for domestic refrigerators and freezers (R/Fs). Vacuum insulations promise significant improvement in thermal savings over current insulations; the technical objective of one design is an R-value of better than 10 (hr-ft{sup 2}-F/Btu) in 0.1 in. thickness. If performance is improved by a factor of 10 over that of CFC-blown insulating foams, the new insulations (made without CFCs or other potentially troublesome fill gases) will change the design and improve the efficiency of refrigerators. Such changes will meet the conservation, regulatory, and market drivers now strong in developed countries and likely to increase in developing countries. Prototypes of various designs have been tested in the laboratory and in factories, and results to date confirm the good thermal performance of these thin-profile alternatives. The next step is to resolve issues of reliability and cost effectiveness. 34 refs., 4 figs.

Potter, T.F.; Benson, D.K.

1991-01-01T23:59:59.000Z

293

Table A55. Number of Establishments by Total Inputs of Energy for Heat, Powe  

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

Number of Establishments by Total Inputs of Energy for Heat, Power, and Electricity Generation," Number of Establishments by Total Inputs of Energy for Heat, Power, and Electricity Generation," " by Industry Group, Selected Industries, and" " Presence of Cogeneration Technologies, 1994: Part 2" ,,,"Steam Turbines",,,,"Steam Turbines" ,," ","Supplied by Either","Conventional",,,"Supplied by","One or More",," " " "," ",,"Conventional","Combustion ","Combined-Cycle","Internal Combustion","Heat Recovered from","Cogeneration",,"RSE" "SIC"," ",,"or Fluidized","Turbines with","Combustion","Engines with","High-Temperature","Technologies","None","Row"

294

A Total Quality Management (TQM) Approach for Energy Savings Through Employee Awareness and Building Upgrades to Improve Energy Efficiency  

E-Print Network [OSTI]

A TOTAL QUALIn' MANAGEMENT (TQM) APPROACH FOR ENERGY SAVINGS THROUGH EMPLOYEE AWARENESS AND BUILDING UPGRADES TO IMPROVE ENERGY EFFICIENCY Daniel H. Stewart, Principal Engineer, Facilities Department, Rh6oe-Poulenc. Inc., Cranbury, NJ...) approach depends on the input from the end-users, clients, employees, power companies, various consultants and site operation management. This paper discusses the energy efficiency projects that are currently in progress at Rhone Poulenc's Corporate...

Stewart, D. H.

295

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

296

Table A32. Total Consumption of Offsite-Produced Energy for Heat, Power, and  

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

Consumption of Offsite-Produced Energy for Heat, Power, and" Consumption of Offsite-Produced Energy for Heat, Power, and" " Electricity Generation by Value of Shipment Categories, Industry Group, and" " Selected Industries, 1991" " (Estimates in Trillion Btu)" ,,,,"Value of Shipments and Receipts(b)" ,,,," (million dollars)" ,," ","-","-","-","-","-","-","RSE" ," "," "," ",,,,,500,"Row" "Code(a)","Industry Groups and Industry","Total","Under 20","20-49","50-99","100-249","250-499","and Over","Factors"," "," "," "," "," "

297

Total electron scattering cross sections for methanol and ethanol at intermediate energies  

Science Journals Connector (OSTI)

Absolute total cross section (TCS) measurements of electron scattering from gaseous methanol and ethanol molecules are reported for impact energies from 60 to 500 eV, using the linear transmission method. The attenuation of intensity of a collimated electron beam through the target volume is used to determine the absolute TCS for a given impact energy, using the BeerLambert law to first approximation. Besides these experimental measurements, we have also determined TCS using the additivity rule.

D G M Silva; T Tejo; J Muse; D Romero; M A Khakoo; M C A Lopes

2010-01-01T23:59:59.000Z

298

Table A52. Total Inputs of Energy for Heat, Power, and Electricity Generatio  

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

2. Total Inputs of Energy for Heat, Power, and Electricity Generation by Employment Size" 2. Total Inputs of Energy for Heat, Power, and Electricity Generation by Employment Size" " Categories and Presence of General Technologies and Cogeneration Technologies, 1994" " (Estimates in Trillion Btu)" ,,,,"Employment Size(a)" ,,,,,,,,"RSE" ,,,,,,,"1000 and","Row" "General/Cogeneration Technologies","Total","Under 50","50-99","100-249","250-499","500-999","Over","Factors" "RSE Column Factors:",0.5,2,2.1,1,0.7,0.7,0.9 "One or More General Technologies Present",14601,387,781,2054,2728,3189,5462,3.1 " Computer Control of Building Environment (b)",5079,64,116,510,802,1227,2361,5

299

Table A1. Total First Use (formerly Primary Consumption) of Energy for All Pu  

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

2" 2" " (Estimates in Trillion Btu)" " "," "," "," "," "," "," "," "," "," "," ",," " " "," "," ",," "," ",," "," ",," ","Shipments","RSE" "SIC"," ",,"Net","Residual","Distillate",," ",,"Coke and"," ","of Energy Sources","Row" "Code(a)","Industry Group and Industry","Total(b)","Electricity(c)","Fuel Oil","Fuel Oil(d)","Natural Gas(e)","LPG","Coal","Breeze","Other(f)","Produced Onsite(g)","Factors"

300

Accelerating the convergence of the total energy evaluation in density functional theory calculations  

E-Print Network [OSTI]

Accelerating the convergence of the total energy evaluation in density functional theory.1063/1.2821101 I. INTRODUCTION Density functional theory DFT ,1,2 one of the most widely used first functional theory OO-DFT B. Zhou and Y. A. Wang, J. Chem. Phys. 124, 081107 2006 is that the second

Wang, Yan Alexander

Note: This page contains sample records for the topic "household total energy" 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

Total cross section of neutron-proton scattering at low energies in quark-gluon model  

E-Print Network [OSTI]

We show that analysis of nonrelativistic neutron-proton scattering in a framework of relativistic QCD based quark model can give important information about QCD vacuum structure. In this model we describe total cross section of neutron-proton scattering at kinetic energies of projectile neutron from 1 eV up to 1 MeV.

V. A. Abramovsky; N. V. Radchenko

2011-07-30T23:59:59.000Z

302

Table A1. Total First Use (formerly Primary Consumption) of Energy for All Pu  

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

1 " 1 " " (Estimates in Btu or Physical Units)" " "," "," "," "," "," "," "," "," "," "," ",," " " "," "," ",," "," ",," "," ","Coke and"," ","Shipments"," " " "," ",,"Net","Residual","Distillate","Natural Gas(e)"," ","Coal","Breeze"," ","of Energy Sources","RSE" "SIC"," ","Total(b)","Electricity(c)","Fuel Oil","Fuel Oil(d)","(billion","LPG","(1000","(1000","Other(f)","Produced Onsite(g)","Row"

303

Income inequality and carbon dioxide emissions: The case of Chinese urban households  

Science Journals Connector (OSTI)

This paper draws on Chinese survey data to investigate variations in carbon dioxide emissions across households with different income levels. Rich households generate more emissions per capita than poor households via both their direct energy consumption and their higher expenditure on goods and services that use energy as an intermediate input. An econometric analysis confirms a positive relationship between emissions and income and establishes a slightly increasing marginal propensity to emit (MPE) over the relevant income range. The redistribution of income from rich to poor households is therefore shown to reduce aggregate household emissions, suggesting that the twin pursuits of reducing inequality and emissions can be achieved in tandem.

Jane Golley; Xin Meng

2012-01-01T23:59:59.000Z

304

Measurement of the total energy of an isolated system by an internal observer  

E-Print Network [OSTI]

We consider the situation in which an observer internal to an isolated system wants to measure the total energy of the isolated system (this includes his own energy, that of the measuring device and clocks used, etc...). We show that he can do this in an arbitrarily short time, as measured by his own clock. This measurement is not subjected to a time-energy uncertainty relation. The properties of such measurements are discussed in detail with particular emphasis on the relation between the duration of the measurement as measured by internal clocks versus external clocks.

S. Massar; S. Popescu

2004-12-10T23:59:59.000Z

305

Household Vehicles Energy Consumption 1991  

Gasoline and Diesel Fuel Update (EIA)

all comparisons reported in the text are statistically significant, based on a standard test made at the 0.05 significance level. No adjustments were made for simultaneous...

306

Household Vehicles Energy Consumption 1991  

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

Protection Agency (EPA) certification files (CERT files) containing laboratory test results of MPG. When the vehicle characteristic was missing from the questionnaire, but...

307

Household Vehicles Energy Consumption 1994  

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

Christy Hall 202-586-1068 chall@eia.doe.gov Public Use Data, Computer Nanno Smith 202-586-5841 nsmith@eia.doe.gov Systems Design Detailed Statistical Tables Vicky...

308

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

309

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

310

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

311

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

312

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

313

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

314

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

315

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

316

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

317

"Table 21. Total Energy Related Carbon Dioxide Emissions, Projected vs. Actual"  

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

Total Energy Related Carbon Dioxide Emissions, Projected vs. Actual" Total Energy Related Carbon Dioxide Emissions, Projected vs. Actual" "Projected" " (million metric tons)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011 "AEO 1994",5060,5129.666667,5184.666667,5239.666667,5287.333333,5335,5379,5437.666667,5481.666667,5529.333333,5599,5657.666667,5694.333333,5738.333333,5797,5874,5925.333333,5984 "AEO 1995",,5137,5173.666667,5188.333333,5261.666667,5309.333333,5360.666667,5393.666667,5441.333333,5489,5551.333333,5621,5679.666667,5727.333333,5775,5841,5888.666667,5943.666667 "AEO 1996",,,5181.817301,5223.645142,5294.776326,5354.687297,5416.802205,5463.67395,5525.288005,5588.52771,5660.226888,5734.87972,5812.398031,5879.320068,5924.814575,5981.291626,6029.640422,6086.804077,6142.120972

318

Correlation Of Surface Heat Loss And Total Energy Production For Geothermal  

Open Energy Info (EERE)

source source History View New Pages Recent Changes All Special Pages Semantic Search/Querying Get Involved Help Apps Datasets Community Login | Sign Up Search Page Edit History Facebook icon Twitter icon » Correlation Of Surface Heat Loss And Total Energy Production For Geothermal Systems Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Conference Paper: Correlation Of Surface Heat Loss And Total Energy Production For Geothermal Systems Details Activities (1) Areas (1) Regions (0) Abstract: Geothermal systems lose their heat by a site-specific combination of conduction (heat flow) and advection (surface discharge). The conductive loss at or near the surface (shallow heat flow) is a primary signature and indication of the strength of a geothermal system. Using a database of

319

"Table A32. Total Quantity of Purchased Energy Sources by Census Region,"  

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

Quantity of Purchased Energy Sources by Census Region," Quantity of Purchased Energy Sources by Census Region," " Census Division, Industry Group, and Selected Industries, 1994" " (Estimates in Btu or Physical Units)" ,,,,,,"Natural",,,"Coke" " "," ","Total","Electricity","Residual","Distillate","Gas(c)"," ","Coal","and Breeze"," ","RSE" "SIC"," ","(trillion","(million","Fuel Oil","Fuel Oil(b)","(billion","LPG","(1000","(1000","Other(d)","Row" "Code(a)","Industry Group and Industry","Btu)","kWh)","(1000 bbl)","(1000 bbl)","cu ft)","(1000 bbl)","short tons)","short tons)","(trillion Btu)","Factors"

320

Total energy and band structure of the 3d, 4d, and 5d metals  

Science Journals Connector (OSTI)

We performed total-energy calculations by the scalar-relativistic augmented-plane-wave method in the local-density and muffin-tin approximations for all 3d, 4d, and 5d transition metals in the fcc and bcc structures. These calculations predict the correct equilibrium structure and give good agreement with experiment and other calculations for lattice constants and bulk moduli.

M. Sigalas; D. A. Papaconstantopoulos; N. C. Bacalis

1992-03-15T23:59:59.000Z

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


321

Household electricity consumption and CO2 emissions in the Netherlands: A model-based analysis  

Science Journals Connector (OSTI)

Abstract Twenty percent of the total energy consumption in the Netherlands comes from household electricity consumption. This comes from household electric appliances whose number has grown in recent years. The paper explores the effect of smart meter introduction, appliance efficiency and consumer behaviour on reducing electricity consumption in the Netherlands. It does so by combining two perspectives: a sociotechnical approach and a bottom up simulation approach. The range of scenarios explored through simulation in the paper provides an understanding of the interplay between efficiency, smart meter diffusion and consumer behaviour. The results show their effect on electricity consumption and suggest that further effort is required to control and reduce it. Insights from the paper suggest that future studies should disaggregate with respect to a number of factors.

George Papachristos

2015-01-01T23:59:59.000Z

322

Asset Pricing with Countercyclical Household Consumption Risk  

E-Print Network [OSTI]

1 Asset Pricing with Countercyclical Household Consumption Risk George M. Constantinides that shocks to household consumption growth are negatively skewed, persistent, and countercyclical and play that drives the conditional cross-sectional moments of household consumption growth. The estimated model

Sadeh, Norman M.

323

Sorting through the many total-energy-cycle pathways possible with early plug-in hybrids.  

SciTech Connect (OSTI)

Using the 'total energy cycle' methodology, we compare U.S. near term (to {approx}2015) alternative pathways for converting energy to light-duty vehicle kilometers of travel (VKT) in plug-in hybrids (PHEVs), hybrids (HEVs), and conventional vehicles (CVs). For PHEVs, we present total energy-per-unit-of-VKT information two ways (1) energy from the grid during charge depletion (CD); (2) energy from stored on-board fossil fuel when charge sustaining (CS). We examine 'incremental sources of supply of liquid fuel such as (a) oil sands from Canada, (b) Fischer-Tropsch diesel via natural gas imported by LNG tanker, and (c) ethanol from cellulosic biomass. We compare such fuel pathways to various possible power converters producing electricity, including (i) new coal boilers, (ii) new integrated, gasified coal combined cycle (IGCC), (iii) existing natural gas fueled combined cycle (NGCC), (iv) existing natural gas combustion turbines, (v) wood-to-electricity, and (vi) wind/solar. We simulate a fuel cell HEV and also consider the possibility of a plug-in hybrid fuel cell vehicle (FCV). For the simulated FCV our results address the merits of converting some fuels to hydrogen to power the fuel cell vs. conversion of those same fuels to electricity to charge the PHEV battery. The investigation is confined to a U.S. compact sized car (i.e. a world passenger car). Where most other studies have focused on emissions (greenhouse gases and conventional air pollutants), this study focuses on identification of the pathway providing the most vehicle kilometers from each of five feedstocks examined. The GREET 1.7 fuel cycle model and the new GREET 2.7 vehicle cycle model were used as the foundation for this study. Total energy, energy by fuel type, total greenhouse gases (GHGs), volatile organic compounds (VOC), carbon monoxide (CO), nitrogen oxides (NO{sub x}), fine particulate (PM2.5) and sulfur oxides (SO{sub x}) values are presented. We also isolate the PHEV emissions contribution from varying kWh storage capability of battery packs in HEVs and PHEVs from {approx}16 to 64 km of charge depleting distance. Sensitivity analysis is conducted with respect to the effect of replacing the battery once during the vehicle's life. The paper includes one appendix that examines several recent studies of interactions of PHEVs with patterns of electric generation and one that provides definitions, acronyms, and fuel consumption estimation steps.

Gaines, L.; Burnham, A.; Rousseau, A.; Santini, D.; Energy Systems

2008-01-01T23:59:59.000Z

324

Table ET1. Primary Energy, Electricity, and Total Energy Price and Expenditure Estimates, Selected Years, 1970-2011, United States  

Gasoline and Diesel Fuel Update (EIA)

ET1. Primary Energy, Electricity, and Total Energy Price and Expenditure Estimates, Selected Years, 1970-2011, United States ET1. Primary Energy, Electricity, and Total Energy Price and Expenditure Estimates, Selected Years, 1970-2011, United States Year Primary Energy Electric Power Sector h,j Retail Electricity Total Energy g,h,i Coal Coal Coke Natural Gas a Petroleum Nuclear Fuel Biomass Total g,h,i,j Coking Coal Steam Coal Total Exports Imports Distillate Fuel Oil Jet Fuel b LPG c Motor Gasoline d Residual Fuel Oil Other e Total Wood and Waste f,g Prices in Dollars per Million Btu 1970 0.45 0.36 0.38 1.27 0.93 0.59 1.16 0.73 1.43 2.85 0.42 1.38 1.71 0.18 1.29 1.08 0.32 4.98 1.65 1975 1.65 0.90 1.03 2.37 3.47 1.18 2.60 2.05 2.96 4.65 1.93 2.94 3.35 0.24 1.50 2.19 0.97 8.61 3.33 1980 2.10 1.38 1.46 2.54 3.19 2.86 6.70 6.36 5.64 9.84 3.88 7.04 7.40 0.43 2.26 4.57 1.77 13.95 6.89 1985 2.03 1.67 1.69 2.76 2.99 4.61 7.22 5.91 6.63 9.01 4.30 R 7.62 R 7.64 0.71 2.47 4.93 1.91 19.05

325

More efficient household electricity use  

SciTech Connect (OSTI)

The energy efficiency of electric appliances has increased markedly in OECD countries, according to data provided by utilities, appliance associations, appliance manufacturers, and independent analyses of each country we reviewed (US, Sweden, Norway, Holland, Japan, Germany, UK). These improvements have, in part, offset increases in electricity demand due to increasing saturation of appliances. However, we see evidence that the efficiency of new devices has hit a temporary plateau: Appliances sold in 1988, while far more efficient than similar ones sold in the early 1970s, may not be significantly more efficient than those sold in 1987. The reason for this plateau, according to manufacturers we interviewed, is that the simple energy-saving features have been incorporated; more sophisticated efficiency improvements are economically justified by five to ten year paybacks, but unattractive to consumers in most countries who appear to demand paybacks of less than three years. Manufacturers see features other than efficiency --- such as number of storage compartments and automatic ice-makers --- as more likely to boost sales, market share, or profits. If this efficiency plateau'' proves lasting, then electricity use for appliance could begin to grow again as larger and more fancy models appear in households. 38 refs., 10 figs., 1 tab.

Schipper, L.; Hawk, D.V.

1989-12-01T23:59:59.000Z

326

Buildings Energy Data Book: 2.1 Residential Sector Energy Consumption  

Buildings Energy Data Book [EERE]

4 4 Ownership (1) Owned 54.9 104.5 40.3 78% Rented 77.4 71.7 28.4 22% Public Housing 75.7 62.7 28.7 2% Not Public Housing 77.7 73.0 28.4 19% 100% Note(s): Source(s): 1) Energy consumption per square foot was 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 2005 Residential Delivered Energy Consumption Intensities, by Ownership of Unit Per Square Per Household Per Household Percent of Foot (thousand Btu) (million Btu) Members (million Btu) Total Consumption

327

The Household Market for Electric Vehicles: Testing the Hybrid Household Hypothesis -- A Reflexively Designed Survey of New-Car-Buying Multi-Vehicle California Households  

E-Print Network [OSTI]

EV,then we expect 13.3 to 15.2% of all light-duty vehicle sales,EV marketpotential for smaller and shorter range velucles represented by our sampleis about 7%of annual, newhght duty vehicle sales.EV body styles" EVs ICEVs Total PAGE 66 THE HOUSEHOLD MA RKET FOR ELECTRIC VEHICLES percent mandatein the year 2003will dependon sales

Turrentine, Thomas; Kurani, Kenneth S.

2001-01-01T23:59:59.000Z

328

THE DESIRE TO ACQUIRE: FORECASTING THE EVOLUTION OF HOUSEHOLD  

E-Print Network [OSTI]

energy-using devices in the average U.S. household that used over 4,700 kWh of electricity, natural gas.46]. The cost of these devices was also statistically significant. Keywords: electricity use; energy efficiency the Canadian Industrial Energy End Use Data and Analysis (CIEEDAC) for their financial support made possible

329

Total Neutron Cross Section of Xe135 as a Function of Energy  

Science Journals Connector (OSTI)

The total neutron cross section of Xe135 as a function of energy has been remeasured at Oak Ridge National Laboratory under more favorable conditions than obtained in earlier measurements. A sample thickness of 2.51018 atoms of Xe135 gas per cm2 was procured from the gases generated in a homogeneous reactor. A mechanical time-of-flight chopper was used to select neutrons in the energy range from 0.01 ev to several thousand ev. The number of Xe135 atoms in the sample was determined by means of mass spectrometer measurements on the long-lived daughter, Cs135. The data of the low-energy resonance were fitted to the single-level Breit-Wigner formula, taking into account Doppler corrections, equally well with the following two sets of parameters: statistical weight factor g=38; resonance energy ?0=0.084720.00027 ev; neutron width at energy ?0, ?n0=0.034770.00021 ev; capture width, ??=0.0833030.00062 ev; for g=58, ?0=0.084150.00028 ev; ?n0=0.020570.00012 ev; ?a=0.094930.00071 ev. The errors quoted are the standard deviations derived from the statistics of the measurements. Systematic errors are discussed in the body of the paper. No evidence for resonances at energies greater than 0.085 ev was observed. The results described are interpreted in terms of recent considerations on the statistics of the properties of nuclear energy levels.

E. C. Smith, G. S. Pawlicki, P. E. F. Thurlow, G. W. Parker, W. J. Martin, G. E. Creek, P. M. Lantz, and S. Bernstein

1959-09-15T23:59:59.000Z

330

"Table 20. Total Delivered Transportation Energy Consumption, Projected vs. Actual"  

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

Total Delivered Transportation Energy Consumption, Projected vs. Actual" Total Delivered Transportation Energy Consumption, Projected vs. Actual" "Projected" " (quadrillion Btu)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011 "AEO 1994",23.62,24.08,24.45,24.72,25.06,25.38,25.74,26.16,26.49,26.85,27.23,27.55,27.91,28.26,28.61,28.92,29.18,29.5 "AEO 1995",,23.26,24.01,24.18,24.69,25.11,25.5,25.86,26.15,26.5,26.88,27.28,27.66,27.99,28.25,28.51,28.72,28.94 "AEO 1996",,,23.89674759,24.08507919,24.47502899,24.84881783,25.25887871,25.65527534,26.040205,26.38586426,26.72540092,27.0748024,27.47158241,27.80837631,28.11616135,28.3992157,28.62907982,28.85912895,29.09081459 "AEO 1997",,,,24.68686867,25.34906006,25.87225533,26.437994,27.03513145,27.52499771,27.96490097,28.45482063,28.92999458,29.38239861,29.84147453,30.26097488,30.59760475,30.85550499,31.10873222,31.31938744

331

"Table 19. Total Delivered Industrial Energy Consumption, Projected vs. Actual"  

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

Total Delivered Industrial Energy Consumption, Projected vs. Actual" Total Delivered Industrial Energy Consumption, Projected vs. Actual" "Projected" " (quadrillion Btu)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011 "AEO 1994",25.43,25.904,26.303,26.659,26.974,27.062,26.755,26.598,26.908,27.228,27.668,28.068,28.348,28.668,29.068,29.398,29.688,30.008 "AEO 1995",,26.164,26.293,26.499,27.044,27.252,26.855,26.578,26.798,27.098,27.458,27.878,28.158,28.448,28.728,29.038,29.298,29.608 "AEO 1996",,,26.54702756,26.62236823,27.31312376,27.47668697,26.90313339,26.47577946,26.67685979,26.928811,27.23795407,27.58448499,27.91057103,28.15050595,28.30145734,28.518,28.73702901,28.93001263,29.15872662 "AEO 1997",,,,26.21291769,26.45981795,26.88483478,26.67847443,26.55107968,26.78246968,27.07367604,27.44749539,27.75711339,28.02446072,28.39156621,28.69999783,28.87316602,29.01207631,29.19475644,29.37683575

332

"Table 18. Total Delivered Commercial Energy Consumption, Projected vs. Actual"  

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

Total Delivered Commercial Energy Consumption, Projected vs. Actual" Total Delivered Commercial Energy Consumption, Projected vs. Actual" "Projected" " (quadrillion Btu)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011 "AEO 1994",6.82,6.87,6.94,7,7.06,7.13,7.16,7.22,7.27,7.32,7.36,7.38,7.41,7.45,7.47,7.5,7.51,7.55 "AEO 1995",,6.94,6.9,6.95,6.99,7.02,7.05,7.08,7.09,7.11,7.13,7.15,7.17,7.19,7.22,7.26,7.3,7.34 "AEO 1996",,,7.059859276,7.17492485,7.228339195,7.28186655,7.336973667,7.387932777,7.442782879,7.501244545,7.561584473,7.623688221,7.684037209,7.749266148,7.815915108,7.884147644,7.950204372,8.016282082,8.085801125 "AEO 1997",,,,7.401538849,7.353548527,7.420701504,7.48336792,7.540113449,7.603093624,7.663851738,7.723834991,7.783358574,7.838726044,7.89124918,7.947964668,8.008976936,8.067288399,8.130317688,8.197405815

333

Nuclear Physics A 772 (2006) 113137 Total prompt energy release in the neutron-induced  

E-Print Network [OSTI]

This study addresses, for the first time, the total prompt energy release and its components for the fission of 235U, 238U, and 239Pu as a function of the kinetic energy of the neutron inducing the fission. The components are extracted from experimental measurements, where they exist, together with model-dependent calculation, interpolation, and extrapolation. While the components display clear dependencies upon the incident neutron energy, their sums display only weak, yet definite, energy dependencies. Also addressed is the total prompt energy deposition in fission for the same three systems. Results are presented in equation form. New measurements are recommended as a consequence of this study.

D. G. Madland

2006-01-01T23:59:59.000Z

334

Reduced Total Energy Requirements For The Original Alcubierre and Natario Warp Drive Spacetimes-The Role Of Warp Factors.  

E-Print Network [OSTI]

Reduced Total Energy Requirements For The Original Alcubierre and Natario Warp Drive Spacetimes Alcubierre and Natario themselves the Warp Drive violates all the known energy conditions because the stress energy momentum tensor(the right side of the Einstein Field Equations) for the Einstein tensor G00

Boyer, Edmond

335

Household equipment of Canadians -- features of the 1993 stock and the 1994 and 1995 purchases: Analysis report  

SciTech Connect (OSTI)

This report reviews the results of three surveys that collected information on household equipment: The 1994 and 1995 Household Equipment Surveys and the 1993 Survey of Household Energy Use. The goal of the report is to highlight the features of energy-consuming equipment bought by Canadian households in 1994 and 1995 in comparison to those owned by households in 1993. Results are presented by type of equipment: Refrigerators, stoves, dishwashers, freezers, automatic washers, automatic dryers, air conditioning systems, heating systems, and water heaters. Appendices include information on survey methodology and a copy of the survey questionnaire.

Not Available

1997-01-01T23:59:59.000Z

336

Ventilation Behavior and Household Characteristics in NewCalifornia Houses  

SciTech Connect (OSTI)

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

337

Estimating Total Energy Consumption and Emissions of China's Commercial and Office Buildings  

E-Print Network [OSTI]

material intensity, energy intensity of materials, buildingtypes manufacturing energy intensity (how much energy itthe manufacturing energy intensity of each type of building

Fridley, David G.

2008-01-01T23:59:59.000Z

338

TOTAL Full-TOTAL Full-  

E-Print Network [OSTI]

Conducting - Orchestral 6 . . 6 5 1 . 6 5 . . 5 Conducting - Wind Ensemble 3 . . 3 2 . . 2 . 1 . 1 Early- X TOTAL Full- Part- X TOTAL Alternative Energy 6 . . 6 11 . . 11 13 2 . 15 Biomedical Engineering 52 English 71 . 4 75 70 . 4 74 72 . 3 75 Geosciences 9 . 1 10 15 . . 15 19 . . 19 History 37 1 2 40 28 3 3 34

Portman, Douglas

339

Parametric analysis of total costs and energy efficiency of 2G enzymatic ethanol production  

Science Journals Connector (OSTI)

Abstract This paper presents an analysis of total costs (TPC) and energy efficiency of enzymatic ethanol production. The analysis is parametrized with respect to plant capacity and polysaccharides content (pc) of lignocellulosic feedstock. The feedstock is based on wheat straw whose price is proportional to its pc ranging from new straw with high pc and high cost to agro-wastes with limited pc but lower cost. The plant flowsheet was built using a conventional biochemical platform with co-saccharification and fermentation (SHF) technologies. A parametric analysis of TPC as a function of plant capacity (1002100ton DB/day) and pc (i.e. feedstock price) (80% (75 USD/ton DB)35% (6 USD/ton DB)) was performed with Net Present Value (NPV) techniques. Current data from Mexican economics and the agro-industrial sector were used as an illustrative case. A quasi-linear section of the TCP surface was identified delimited by (3001100ton DB/day) and (8055% pc) with increments no larger than 21% of the minimum TPC obtained (0.99 USD/l etOH for 2100ton DB/day and 80% pc). Major cost contributions are detailed and quantified for boundary cases of this surface. Energy consumption and production were also calculated for all the plant capacity and feedstock pc cases, taking into consideration the Maximum Energy Recovery (MER) obtained from a Pinch analysis. The end-use energy index eer was less than 0.82 for all cases, thus stressing the need to use process equipment with lower energy requirements. TPC are compared against previously published results for SHF technology between 500 and 2100ton DB/day plant capacities. These values were updated and normalized with respect to feedstock and enzyme costs employed in this work. Differences among TPC and recently published normalized results are within a 5% range, thus confirming the dependence of TPC from feedstock and enzyme prices, regardless of flowsheet technology and economic conditions.

A. Sanchez; V. Sevilla-Gitrn; G. Magaa; L. Gutierrez

2013-01-01T23:59:59.000Z

340

Characteristics RSE Column Factor: Households with Children Households...  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

... 6.1 0.8 2.7 2.6 Q Q Q Q Q Q Q 23.2 Race of Householder White ... 54.8 14.4 27.6 12.8 83.7 3.2 6.7 7.2...

Note: This page contains sample records for the topic "household total energy" 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

Physical activity of adults in households with and without children  

E-Print Network [OSTI]

whites, fewer Hispanics, and higher household incomes thanWhites, fewer Hispanics, and higher household incomes thanWhites, fewer Hispanics, and higher household incomes than

Candelaria, Jeanette Irene

2010-01-01T23:59:59.000Z

342

The Hawthorne effect and energy awareness  

Science Journals Connector (OSTI)

...rented* Average household size* Average...Indian, Asian, Hispanic, Pacific Islander, other)* Total households (block, tract...American, Asian, Hispanic/Latino, White...answer) *Only households in the treatment...

Daniel Schwartz; Baruch Fischhoff; Tamar Krishnamurti; Fallaw Sowell

2013-01-01T23:59:59.000Z

343

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

344

Household environmental monitoring a strategy to help homeowners reduce their environmental impact  

Science Journals Connector (OSTI)

A group of 20 households was established to study whether we can motivate environmentally sustainable behaviour by providing homeowners with a clear picture of their impact, tangible reasons for improvement, and tailored solutions to follow. Reports for each household compared heating fuel, electricity, water, vehicle fuel/waste generation within the group and recommended cost-effective measures to reduce consumption. On average, 26% of the recommended measures were implemented, resulting in an estimated greenhouse gas reduction of about 2 tonnes per household. Wide variations were found between households, demonstrating the potential to reduce environmental impact through lifestyle, conservation, and energy conscious retrofits.

Jane Thompson; Magda Goemans; Peter C. Goemans; Andrzej Wisniowski

2008-01-01T23:59:59.000Z

345

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

346

Total energy loss to fast ablator-ions and target capacitance of direct-drive implosions on OMEGA  

E-Print Network [OSTI]

Energetics, Rochester, New York 14623, USA 3 Los Alamos National Laboratory, Los Alamos, New Mexico 87545Total energy loss to fast ablator-ions and target capacitance of direct-drive implosions on OMEGA N 19, 093101 (2012) Target normal sheath acceleration sheath fields for arbitrary electron energy

347

The World Distribution of Household Wealth  

E-Print Network [OSTI]

Japan is not a remote prospect. In summary, it is clear that householdJapan Korea, South New Zealand Norway Spain Sweden Switzerland United Kingdom United States Year Unit share of top 2002 household

DAVIES, JAMES B; Shorrocks, Anthony; Sandstrom, Susanna; WOLFF, EDWARD N

2007-01-01T23:59:59.000Z

348

To appear in the Proceedings of The Second International Conference on Energy Efficiency in Household Appliances, Naples (Italy), September 2000. Also published  

E-Print Network [OSTI]

California homes. Total standby power in the homes ranged from 14­169 W, with an average of 67 W of thousands of appliances, but few measurements of total standby power consumption in individual homes. To our electricity consumption in individual homes and the likely impact of policies aimed at reduction. We report

Kammen, Daniel M.

349

Study of energy tax and rebate schemes: energy conservation and the question of equity  

SciTech Connect (OSTI)

Taxing all kinds of primary energy at the wellhead on a $/Btu basis is suggested. This aims at inducing energy conservation throughout the economic system. To reduce the financial pressure of the tax on consumers, especially the poor, tax revenues could be rebated to households. It has been attempted to design an equitable rebate scheme. A mathematical model was developed that approximates the reduction in a household's total energy consumption in response to higher energy prices and different rebate schemes. This model is based on the assumption that energy consumption is a function of a household's real income, prices of different commodities, and energy intensities. The amount of energy saved and the change in real expenditure of a household was calculated for four tax rates; 50%, 100%, 224% and 400%, and five rebate schemes; one regressive, two progressive, one income distribution preserving and the flat per-capita rebate. The results indicate that, for a given tax rate, the choice of rebate scheme does not significantly affect the amount of energy conserved by the households. However, the effectof different rebate schemes on a household's real expenditure could be dramatically different.

Fazel Sarjui, F.

1983-01-01T23:59:59.000Z

350

Trip rate comparison of workplace and household surveys  

E-Print Network [OSTI]

Available vs. Trip Rate) 14 El Paso Household Survey (Household Income vs. Trip Rate) . 15 El Paso Workplace Survey (Household Income vs. Trip Rate) . 52 52 53 53 54 54 16 BPA Household Survey (Household Size vs. Trip Rate) . . 17 BPA Workplace... Survey (Household Size vs. Trip Rate) . . 56 56 18 BPA Household Survey (No. of Employees vs. Trip Rate) . . 19 BPA Workplace Survey (No. of Employees vs. Trip Rate) . . 20 BPA Household Survey (Vehicles Available vs. Trip Rate) . . 21 BPA Workplace...

Endres, Stephen Michael

2012-06-07T23:59:59.000Z

351

Beryllium and Graphite High-Accuracy Total Cross-Section Measurements in the Energy Range from 24 to 900 keV  

E-Print Network [OSTI]

Beryllium and Graphite High-Accuracy Total Cross-Section Measurements in the Energy Range from 24 new measurements of the carbon and beryllium neutron total cross section in the energy range of 24 the measurement of the energy-dependent total cross section st ~Ei ! by applying Eq. ~1! for every TOF channel i

Danon, Yaron

352

"Table B29. Primary Space-Heating Energy Sources, Total Floorspace for Non-Mall Buildings, 2003"  

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

9. Primary Space-Heating Energy Sources, Total Floorspace for Non-Mall Buildings, 2003" 9. Primary Space-Heating Energy Sources, Total Floorspace for Non-Mall Buildings, 2003" ,"Total Floorspace (million square feet)" ,"All Buildings*","Buildings with Space Heating","Primary Space-Heating Energy Source Used a" ,,,"Electricity","Natural Gas","Fuel Oil","District Heat" "All Buildings* ...............",64783,60028,15996,32970,3818,4907 "Building Floorspace" "(Square Feet)" "1,001 to 5,000 ...............",6789,5668,1779,2672,484,"Q" "5,001 to 10,000 ..............",6585,5786,1686,3068,428,"Q" "10,001 to 25,000 .............",11535,10387,3366,5807,536,"Q" "25,001 to 50,000 .............",8668,8060,2264,4974,300,325

353

Estimating broad-brush rebound effects for household energy consumption in the EU 28 countries and Norway: some policy implications of Odyssee data  

Science Journals Connector (OSTI)

Abstract Currently there is a strong policy commitment in European Union (EU) and Organisation for Economic Co-operation and Development (OECD) countries to increase the energy efficiency of residential buildings, and it is widely assumed that this will naturally and automatically reduce domestic energy consumption. However, other factors such as fuel prices, wages, attitudes and lifestyles also influence energy consumption. This paper calculates broad-brush rebound effects based on changes in energy efficiency and energy consumption in each of the 28EU countries plus Norway, for the years 20002011. In doing so, it tests how well the assumption of energy efficiency leading to energy reduction stands up to scrutiny in these lands. It uses the EUs Odyssee database for efficiency and consumption figures and a commonly employed econometric definition of the rebound effect as an energy-efficiency elasticity. Most older EU lands show rebound effects in the expected range of 050%. However, the range for newer EU countries is 100550%, suggesting that energy efficiency increases are not a good predictor of energy consumption. A more in-depth look at one country, Germany, suggests these results underestimate the rebound effect significantly. This also identifies research needs for specific energy consumption determinants in each country, to find more precisely what is driving consumption levels.

Ray Galvin

2014-01-01T23:59:59.000Z

354

Energy Consumption, Efficiency, Conservation, and Greenhouse Gas Mitigation in Japan's Building Sector  

E-Print Network [OSTI]

comparison o f energy consumption i n housing (1998) (Trends i n household energy consumption (Jyukankyo Research4) Average (N=2976) Energy consumption [GJ / household-year

2006-01-01T23:59:59.000Z

355

FY 2007 Total System Life Cycle Cost, Pub 2008 | Department of Energy  

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

FY 2007 Total System Life Cycle Cost, Pub 2008 FY 2007 Total System Life Cycle Cost, Pub 2008 FY 2007 Total System Life Cycle Cost, Pub 2008 The Analysis of the Total System Life Cycle Cost (TSLCC) of the Civilian Radioactive Waste Management Program presents the Office of Civilian Radioactive Waste Management's (OCRWM) May 2007 total system cost estimate for the disposal of the Nation's spent nuclear fuel (SNF) and high-level radioactive waste (HLW). The TSLCC analysis provides a basis for assessing the adequacy of the Nuclear Waste Fund (NWF) Fee as required by Section 302 of the Nuclear Waste Policy Act of 1982 (NWPA), as amended. In addition, the TSLCC analysis provides a basis for the calculation of the Government's share of disposal costs for government-owned and managed SNF and HLW. The TSLCC estimate includes both historical costs and

356

Total fission cross section of {sup 181}Ta and {sup 208}Pb induced by protons at relativistic energies  

SciTech Connect (OSTI)

Total fission cross section induced by protons in {sup 181}Ta and {sup 208}Pb at energies in the range of 300 to 1000 A MeV have been measured at GSI (Germany) using the inverse kinematics technique. A dedicated setup with high efficiency made it possible to determine these cross sections with high accuracy. The new data seed light in the controversial results obtained so far and contribute to the understanding of the fission process at high excitation energies. (authors)

Ayyad, Y.; Benlliure, J.; Casarejos, E. [Group GENP, Dpto. Fisica de Particulas, Universidade de Santiago de Compostela, 15782 Santiago de Compostela (Spain); Schmidt, K. H. [GSI, Planckstrasse 1, 64941, Darmstadt (Germany); Jurado, B. [Universite Bordeaux I, CNRS/IN2 P3, CENBG, BP 120, F-33175 Gradignan (France); Kelic-Heil, A. [GSI, Planckstrasse 1, 64941, Darmstadt (Germany); Pol, H. A. [Group GENP, Dpto. Fisica de Particulas, Universidade de Santiago de Compostela, 15782 Santiago de Compostela (Spain); Ricciardi, M. V.; Pleskac, R. [GSI, Planckstrasse 1, 64941, Darmstadt (Germany); Enqvist, T. [CUPP Project, P.O. Box 22, FI-86801, Pyhsalmi (Finland); Rejmund, F. [Grand Accelerateur National D Ions Lourds, BP 55027, F-14076 Caen Cedex 05 (France); Giot, L. [Subatech - Ecole des Mines de Nantes (France); Henzl, V. [Massachusetts Inst. of Technology, 77, Massachusetts Ave, Cambridge, MA 02139 (United States); Lukic, S. [Karlsruhe Inst. of Technology, D-76021 Karlsruhe (Germany); Ngoc, S. N. [Dept. of Nuclear Physics, Inst. of Physics, National Centre for Natural Science and Technology, NgiaDo-TuLiem, Hanoi (Viet Nam); Boudard, A. [DSM/IRFU/CEA, 91191 Gif-sur-Ivette (France); Universite Louis Pasteur, Strasbourg (France); Leray, S. [DSM/IRFU/CEA, 91191 Gif-sur-Ivette (France); Fernandez, M. [Entro de Investigaciones Energticas Medioambientales Y Tecnolgicas, Madrid (Spain); Kurtukian, T. [Universite Bordeaux I, CNRS/IN2 P3, CENBG, BP 120, F-33175 Gradignan (France); Nadtochy, P. [Omsk State Univ., Dept. of Theoretical Physics, RU-644077 Omsk (Russian Federation); Schmitt, C. [Grand Accelerateur National D'Ions Lourds, BP 55027, F-14076 Caen Cedex 05 (France); Henzlova, D. [Los Alamos National Laboratory, Safeguards Science and Technology Group N-1, Los Alamos, NM 87545 (United States); Paradela, C. [Group GENP, Dpto. Fisica de Particulas, Universidade de Santiago de Compostela, 15782 Santiago de Compostela (Spain); Bacquias, A. [DSM/IRFU/CEA, 91191 Gif-sur-Ivette (France); Universite Louis Pasteur, Strasbourg (France); Loureiro, D. P. [Group GENP, Dpto. Fisica de Particulas, Universidade de Santiago de Compostela, 15782 Santiago de Compostela (Spain); Foehr, V. [GSI, Planckstrasse 1, 64941, Darmstadt (Germany); Tarrio, D. [Group GENP, Dpto. Fisica de Particulas, Universidade de Santiago de Compostela, 15782 Santiago de Compostela (Spain); Kezzar, K. [DSM/IRFU/CEA, 91191 Gif-sur-Ivette (France)

2011-07-01T23:59:59.000Z

357

Table A37. Total Inputs of Energy for Heat, Power, and Electricity  

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

2" 2" " (Estimates in Trillion Btu)" ,,,,,,,"Coal" ,,,,"Distillate",,,"(excluding" ,,,,"Fuel Oil",,,"Coal Coke",,"RSE" ,,"Net","Residual","and Diesel",,,"and",,"Row" "End-Use Categories","Total","Electricity(a)","Fuel Oil","Fuel(b)","Natural Gas(c)","LPG","Breeze)","Other(d)","Factors" "Total United States" "RSE Column Factors:","NF",0.4,1.6,1.5,0.7,1,1.6,"NF" "TOTAL INPUTS",15027,2370,414,139,5506,105,1184,5309,3 "Boiler Fuel","--","W",296,40,2098,18,859,"--",3.6

358

Table A11. Total Inputs of Energy for Heat, Power, and Electricity Generatio  

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

2" 2" " (Estimates in Trillion Btu)" ,,,,,,,"Coal" ,,,,"Distillate",,,"(excluding" ,,,,"Fuel Oil",,,"Coal Coke",,"RSE" ,,"Net","Residual","and Diesel",,,"and",,"Row" "End-Use Categories","Total","Electricity(a)","Fuel Oil","Fuel(b)","Natural Gas(c)","LPG","Breeze)","Other(d)","Factors" ,"Total United States" "RSE Column Factors:"," NF",0.5,1.3,1.4,0.8,1.2,1.2," NF" "TOTAL INPUTS",16515,2656,441,152,6141,99,1198,5828,2.7 "Indirect Uses-Boiler Fuel"," --",28,313,42,2396,15,875," --",4

359

Effect of window type, size and orientation on the total energy demand for a building in Indian climatic conditions  

Science Journals Connector (OSTI)

Windows in a building allow daylight to enter a building space but simultaneously they also result in heat gains and losses affecting energy balance. This requires an optimisation of window area from the point of view of total energy demand viz., for lighting and cooling/heating. This paper is devoted to this kind of study for Indian climatic conditions, which are characterised by six climatic zones varying from extreme cold to hot, dry and humid conditions. Different types of windows have been considered because the optimised size will also depend on the thermo-optical parameters like heat transfer coefficient (U-value), solar heat gain coefficient (g), visual (?), and total transmittance (T) of the glazing in the window. It is observed that in a non-insulated building, cooling/heating energy demand far exceeds lighting energy demand, making the optimisation of window area a futile exercise from the point of view of total energy demand. Only for buildings with U-value below 0.6 W/m²K can optimisation be achieved. The optimised window area and the corresponding specific energy consumption have been calculated for different climates in India, for different orientations, and for three different advanced window systems.

Inderjeet Singh; N.K. Bansal

2004-01-01T23:59:59.000Z

360

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

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

Note: This page contains sample records for the topic "household total energy" 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

Property:Building/SPPurchasedEngyPerAreaKwhM2ElctrtyTotal | Open Energy  

Open Energy Info (EERE)

ElctrtyTotal ElctrtyTotal Jump to: navigation, search This is a property of type String. Electricity, total Pages using the property "Building/SPPurchasedEngyPerAreaKwhM2ElctrtyTotal" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 71.2214478303 + Sweden Building 05K0002 + 95.9357541899 + Sweden Building 05K0003 + 72.2496632241 + Sweden Building 05K0004 + 65.8830409357 + Sweden Building 05K0005 + 54.2477876106 + Sweden Building 05K0006 + 58.7608028994 + Sweden Building 05K0007 + 61.5607534672 + Sweden Building 05K0008 + 40.3846153846 + Sweden Building 05K0009 + 56.4810818587 + Sweden Building 05K0010 + 152.219679634 + Sweden Building 05K0011 + 25.5555555556 + Sweden Building 05K0012 + 35.8807888323 + Sweden Building 05K0013 + 61.3267863536 +

362

Total Facility Control - Applying New Intelligent Technologies to Energy Efficient Green Buildings  

E-Print Network [OSTI]

lighting, co-generation stations, and much more. This paper will discuss some of the basic concepts, architectures, and technologies that are being used today to implement a Total Facility Control model....

Bernstein, R.

2010-01-01T23:59:59.000Z

363

Table A36. Total Inputs of Energy for Heat, Power, and Electricity  

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

"Net","Residual","and Diesel",,,"and",,"Row" "Code(a)","End-Use Categories","Total","Electricity(b)","Fuel Oil","Fuel(c)","Natural Gas(d)","LPG","Breeze)","Other(e)","Factors" ,...

364

Table A10. Total Inputs of Energy for Heat, Power, and Electricity...  

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

,,,"Net","Residual","and Diesel",,,"Coal Coke",,"RSE" "SIC",,"Total","Electricity(b)","Fuel Oil","Fuel(c)","Natural Gas(d)","LPG","and Breeze)","Other(e)","Row"...

365

Table A11. Total Inputs of Energy for Heat, Power, and Electricity Generatio  

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

1" 1" " (Estimates in Btu or Physical Units)" ,,,,"Distillate",,,"Coal" ,,,,"Fuel Oil",,,"(excluding" ,,"Net","Residual","and Diesel",,,"Coal Coke",,"RSE" ,"Total","Electricity(a)","Fuel Oil","Fuel(b)","Natural Gas(c)","LPG","and Breeze)","Other(d)","Row" "End-Use Categories","(trillion Btu)","(million kWh)","(1000 bbls)","(1000 bbls)","(billion cu ft)","(1000 bbls)","(1000 short tons)","(trillion Btu)","Factors" ,,,,,,,,,,, ,"Total United States"

366

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

367

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

368

Energy Consumption, Efficiency, Conservation, and Greenhouse Gas Mitigation in Japan's Building Sector  

E-Print Network [OSTI]

from household energy consumption i n Japan increased b y 20is that household energy consumption i n Japan has notfrom a l l households i n Japan, through 2050 (with energy-

2006-01-01T23:59:59.000Z

369

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.

370

Property:Building/SPPurchasedEngyNrmlYrMwhYrElctrtyTotal | Open Energy  

Open Energy Info (EERE)

Property Property Edit with form History Facebook icon Twitter icon » Property:Building/SPPurchasedEngyNrmlYrMwhYrElctrtyTotal Jump to: navigation, search This is a property of type String. Electricity, total Pages using the property "Building/SPPurchasedEngyNrmlYrMwhYrElctrtyTotal" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 1400.0 + Sweden Building 05K0002 + 686.9 + Sweden Building 05K0003 + 321.8 + Sweden Building 05K0004 + 1689.9 + Sweden Building 05K0005 + 122.6 + Sweden Building 05K0006 + 843.1 + Sweden Building 05K0007 + 1487.0 + Sweden Building 05K0008 + 315.0 + Sweden Building 05K0009 + 1963.0 + Sweden Building 05K0010 + 66.52 + Sweden Building 05K0011 + 391.0 + Sweden Building 05K0012 + 809.65 +

371

Metering Campaign on All Cooking End-Uses in 100 Households  

Science Journals Connector (OSTI)

This paper presents the findings of an experimental study performed in 100 French households on the end-use power demand and energy consumption of domestic appliances focusing on cooking appliances [1].

Olivier Sidler

2001-01-01T23:59:59.000Z

372

Table A1. Total Primary Consumption of Energy for All Purposes by Census  

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

1 " 1 " " (Estimates in Btu or Physical Units)" " "," "," "," "," "," "," "," "," "," "," "," " " "," "," ",," "," ",," "," ","Coke and"," "," " " "," ",,"Net","Residual","Distillate","Natural Gas(d)"," ","Coal","Breeze"," ","RSE" "SIC"," ","Total","Electricity(b)","Fuel Oil","Fuel Oil(c)","(billion","LPG","(1000","(1000","Other(e)","Row"

373

Table A4. Total Inputs of Energy for Heat, Power, and Electricity Generation  

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

2" 2" " (Estimates in Trillion Btu)" " "," "," "," "," "," "," "," "," "," "," "," " " "," "," "," "," "," "," "," "," "," "," ","RSE" "SIC"," "," ","Net","Residual","Distillate"," "," "," ","Coke"," ","Row" "Code(a)","Industry Groups and Industry","Total","Electricity(b)","Fuel Oil","Fuel Oil(c)","Natural Gas(d)","LPG","Coal","and Breeze","Other(e)","Factors"

374

Property:Building/SPPurchasedEngyNrmlYrMwhYrTotal | Open Energy Information  

Open Energy Info (EERE)

SPPurchasedEngyNrmlYrMwhYrTotal SPPurchasedEngyNrmlYrMwhYrTotal Jump to: navigation, search This is a property of type String. Total Pages using the property "Building/SPPurchasedEngyNrmlYrMwhYrTotal" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 4355.0 + Sweden Building 05K0002 + 1530.1 + Sweden Building 05K0003 + 872.1 + Sweden Building 05K0004 + 4466.9 + Sweden Building 05K0005 + 768.6 + Sweden Building 05K0006 + 3031.1 + Sweden Building 05K0007 + 3479.0 + Sweden Building 05K0008 + 1336.0 + Sweden Building 05K0009 + 4876.0 + Sweden Building 05K0010 + 131.52 + Sweden Building 05K0011 + 1501.0 + Sweden Building 05K0012 + 2405.65 + Sweden Building 05K0013 + 3436.6002445 + Sweden Building 05K0014 + 389.66 + Sweden Building 05K0015 + 270.0 +

375

Property:Building/SPPurchasedEngyForPeriodMwhYrTotal | Open Energy  

Open Energy Info (EERE)

SPPurchasedEngyForPeriodMwhYrTotal SPPurchasedEngyForPeriodMwhYrTotal Jump to: navigation, search This is a property of type String. Total Pages using the property "Building/SPPurchasedEngyForPeriodMwhYrTotal" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 4228.0 + Sweden Building 05K0002 + 1501.1 + Sweden Building 05K0003 + 847.1 + Sweden Building 05K0004 + 4360.9 + Sweden Building 05K0005 + 727.6 + Sweden Building 05K0006 + 2915.1 + Sweden Building 05K0007 + 3385.0 + Sweden Building 05K0008 + 1282.0 + Sweden Building 05K0009 + 4739.0 + Sweden Building 05K0010 + 127.52 + Sweden Building 05K0011 + 1436.0 + Sweden Building 05K0012 + 2334.65 + Sweden Building 05K0013 + 3323.0 + Sweden Building 05K0014 + 381.66 + Sweden Building 05K0015 + 257.0 +

376

Property:Building/SPPurchasedEngyForPeriodMwhYrElctrtyTotal | Open Energy  

Open Energy Info (EERE)

SPPurchasedEngyForPeriodMwhYrElctrtyTotal SPPurchasedEngyForPeriodMwhYrElctrtyTotal Jump to: navigation, search This is a property of type String. Electricity, total Pages using the property "Building/SPPurchasedEngyForPeriodMwhYrElctrtyTotal" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 1399.0 + Sweden Building 05K0002 + 686.9 + Sweden Building 05K0003 + 321.8 + Sweden Building 05K0004 + 1689.9 + Sweden Building 05K0005 + 122.6 + Sweden Building 05K0006 + 843.1 + Sweden Building 05K0007 + 1487.0 + Sweden Building 05K0008 + 315.0 + Sweden Building 05K0009 + 1963.0 + Sweden Building 05K0010 + 66.52 + Sweden Building 05K0011 + 391.0 + Sweden Building 05K0012 + 809.65 + Sweden Building 05K0013 + 1199.0 + Sweden Building 05K0014 + 227.66 +

377

Bounds on the Solar Antineutrino total Flux and Energy spectrum from the SK experiment  

E-Print Network [OSTI]

A search for inverse beta decay electron antineutrinos has been carried out using the 825 days sample of solar data obtained at SK. The absence of a significant signal, that is, contributions to the total SK background and their angular variations has set upper bounds on a) the absolute flux of solar antineutrinos originated from ${}^8 B$ neutrinos $\\Phi_{\\bar{\

E. Torrente-Lujan

1999-11-23T23:59:59.000Z

378

Table A1. Total Primary Consumption of Energy for All Purposes by Census  

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

2" 2" " (Estimates in Trillion Btu)" " "," "," "," "," "," "," "," "," "," "," "," " " "," ",," "," "," "," "," "," "," "," ","RSE" "SIC"," ",,"Net","Residual","Distillate "," "," "," ","Coke"," ","Row" "Code(a)","Industry Groups and Industry"," Total","Electricity(b)","Fuel Oil","Fuel Oil(c)","Natural Gas(d)","LPG","Coal","and Breeze","Other(e)","Factors"

379

Isotopic Mo Neutron Total Cross Section Measurements in the Energy Range 1 to 620 keV  

Science Journals Connector (OSTI)

Abstract A series of new total cross section measurements for the stable molybdenum isotopes of 92,94,95,96,98,100Mo covering the energy range between 1 keV and 620 keV was performed at the Gaerttner LINAC Center at Rensselaer Polytechnic Institute. New high-accuracy resonance parameters were extracted from an analysis of the data using the multilevel R-matrix Bayesian code SAMMY. In the unresolved resonance region, average resonance parameters and fits to the total cross sections were obtained using the Bayesian Hauser-Feshbach statistical model code FITACS.

R. Bahran; D. Barry; G. Leinweber; M. Rapp; R. Block; A. Daskalakis; B. McDermott; S. Piela; E. Blain; Y. Danon

2014-01-01T23:59:59.000Z

380

Arsenic Removal from Groundwater by Household Sand Filters:? Comparative Field Study, Model Calculations, and Health Benefits  

Science Journals Connector (OSTI)

Arsenic Removal from Groundwater by Household Sand Filters:? Comparative Field Study, Model Calculations, and Health Benefits ... Simultaneously, raw groundwater from the same households and additional 31 tubewells was sampled to investigate arsenic coprecipitation with hydrous ferric iron from solution, i.e., without contact to sand surfaces. ... Concentra tions of total Fe, Mn, Na, K, Mg, and Ca were quantified by atomic absorption spectroscopy (Shimadzu AA-6800, Kyoto, Japan). ...

Michael Berg; Samuel Luzi; Pham Thi Kim Trang; Pham Hung Viet; Walter Giger; Doris Stben

2006-07-19T23:59:59.000Z

Note: This page contains sample records for the topic "household total energy" 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

Chemical Characterization and Source Apportionment of Household Fine Particulate Matter in Rural, Peri-urban, and Urban West Africa  

Science Journals Connector (OSTI)

In addition to households own fuel, HAP in urban households is affected by the extent of biomass use in the neighborhood, and by traffic-related sources. ... The elemental concentrations of the samples were quantified by energy dispersive X-ray fluorescence (ED-XRF) using a Shimadzu EDX-700HS spectrometer (Shimadzu Corp., Japan) at the Institute of Astronomy, Geophysics and Atmospheric Science, University of Sao Paulo, Brazil. ...

Zheng Zhou; Kathie L. Dionisio; Thiago G. Verissimo; Americo S. Kerr; Brent Coull; Stephen Howie; Raphael E. Arku; Petros Koutrakis; John D. Spengler; Kimberly Fornace; Allison F. Hughes; Jose Vallarino; Samuel Agyei-Mensah; Majid Ezzati

2013-12-18T23:59:59.000Z

382

Total and Peak Energy Consumption Minimization of Building HVAC Systems Using Model Predictive Control  

E-Print Network [OSTI]

inputs. The idea of modeling building thermal behavior usingThe detail of building thermal modeling is pre- sented in [Modeling and optimal control algorithm design for hvac systems in energy efficient buildings,

Maasoumy, Mehdi; Sangiovanni-Vincentelli, Alberto

2012-01-01T23:59:59.000Z

383

Estimating Total Energy Consumption and Emissions of China's Commercial and Office Buildings  

E-Print Network [OSTI]

rate of technology penetration and rate of intensity change,energy. In addition, the penetration rate of each end-use isinstalled base (i.e. penetration rate) for each end-use set

Fridley, David G.

2008-01-01T23:59:59.000Z

384

Asymptotic High Energy Total Cross Sections and Theories with Extra Dimensions  

E-Print Network [OSTI]

The rate at which cross sections grow with energy is sensitive to the presence of extra dimensions in a rather model-independent fashion. We examine how rates would be expected to grow if there are more spatial dimensions than 3 which appear at some energy scale, making connections with black hole physics and string theory. We also review what is known about the corresponding generalization of the Froissart-Martin bound and the experimental status of high energy hadronic cross sections which appear to saturate it up to the experimentally accessible limit of 100 TeV. We discuss how extra dimensions can be searched for in high energy cross section data and find no room for large extra dimensions in present data. Any apparent signatures of extra dimensions at the LHC may have to be interpreted as due to some other form of new physics.

J. Swain; A. Widom; Y. Srivastava

2014-10-05T23:59:59.000Z

385

Estimating Total Energy Consumption and Emissions of China's Commercial and Office Buildings  

E-Print Network [OSTI]

of energy consumed from coal, coke, liquid fuels, naturalwas expressed in terms of coal equivalency. 2.1.8.1 Tnational fuel inputs of coal, natural gas and petroleum were

Fridley, David G.

2008-01-01T23:59:59.000Z

386

Property:Building/SPBreakdownOfElctrcityUseKwhM2Total | Open Energy  

Open Energy Info (EERE)

SPBreakdownOfElctrcityUseKwhM2Total" SPBreakdownOfElctrcityUseKwhM2Total" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 71.4577086539 + Sweden Building 05K0002 + 110.926946534 + Sweden Building 05K0003 + 72.9096074806 + Sweden Building 05K0004 + 66.0248923654 + Sweden Building 05K0005 + 54.8654809632 + Sweden Building 05K0006 + 65.291976787 + Sweden Building 05K0007 + 65.5403331042 + Sweden Building 05K0008 + 41.6418235453 + Sweden Building 05K0009 + 56.5413268466 + Sweden Building 05K0010 + 150.269021739 + Sweden Building 05K0011 + 27.5018481341 + Sweden Building 05K0012 + 37.9937990385 + Sweden Building 05K0013 + 68.8990371973 + Sweden Building 05K0014 + 166.794253904 + Sweden Building 05K0015 + 71.0813662687 + Sweden Building 05K0016 + 38.5267410327 +

387

Property:Building/SPPurchasedEngyPerAreaKwhM2Total | Open Energy  

Open Energy Info (EERE)

SPPurchasedEngyPerAreaKwhM2Total" SPPurchasedEngyPerAreaKwhM2Total" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 221.549575215 + Sweden Building 05K0002 + 213.701117318 + Sweden Building 05K0003 + 195.801526718 + Sweden Building 05K0004 + 174.148148148 + Sweden Building 05K0005 + 340.088495575 + Sweden Building 05K0006 + 211.255924171 + Sweden Building 05K0007 + 144.028151521 + Sweden Building 05K0008 + 171.282051282 + Sweden Building 05K0009 + 140.296360236 + Sweden Building 05K0010 + 300.961098398 + Sweden Building 05K0011 + 98.1045751634 + Sweden Building 05K0012 + 106.609793929 + Sweden Building 05K0013 + 175.776187637 + Sweden Building 05K0014 + 291.160427408 + Sweden Building 05K0015 + 174.193548387 + Sweden Building 05K0016 + 145.793794187 +

388

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

389

Table A4. Total Inputs of Energy for Heat, Power, and Electricity Generation  

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

1 " 1 " " (Estimates in Btu or Physical Units)" " "," "," "," "," "," "," "," "," ","Coke"," "," " " "," "," ","Net","Residual","Distillate","Natural Gas(d)"," ","Coal","and Breeze"," ","RSE" "SIC"," ","Total","Electricity(b)","Fuel Oil","Fuel Oil(c)","(billion","LPG","(1000","(1000","Other(e)","Row" "Code(a)","Industry Groups and Industry","(trillion Btu)","(million kWh)","(1000 bbls)","(1000 bbls)","cu ft)","(1000 bbls)","short tons)","short tons)","(trillion Btu)","Factors"

390

Table A37. Total Inputs of Energy for Heat, Power, and Electricity  

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

1",,,,,,,"Coal" 1",,,,,,,"Coal" " (Estimates in Btu or Physical Units)",,,,,,,"(excluding" ,,,,"Distillate",,,"Coal Coke" ,,"Net",,"Fuel Oil",,,"and" ,,"Electricity(a)","Residual","and Diesel","Natural Gas",,"Breeze)",,"RSE" ,"Total","(million","Fuel Oil","Fuel","(billion","LPG","(1000 short","Other","Row" "End-Use Categories","(trillion Btu)","kWh)","(1000 bbls)","(1000 bbls)","cu ft)","(1000 bbls)","tons)","(trillion Btu)","Factors"

391

Table A36. Total Inputs of Energy for Heat, Power, and Electricity  

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

,,,,,,,,"Coal" ,,,,,,,,"Coal" " Part 1",,,,,,,,"(excluding" " (Estimates in Btu or Physical Units)",,,,,"Distillate",,,"Coal Coke" ,,,,,"Fuel Oil",,,"and" ,,,"Net","Residual","and Diesel","Natural Gas",,"Breeze)",,"RSE" "SIC",,"Total","Electricity(b)","Fuel Oil","Fuel","(billion","LPG","(1000 Short","Other","Row" "Code(a)","End-Use Categories","(trillion Btu)","(million kWh)","(1000 bbls)","(1000 bbls)","cu ft)","(1000 bbls)","tons)","(trillion Btu)","Factors",

392

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

SciTech Connect (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

393

Total energy study of the microscopic structure and electronic properties of tetragonal perovskite SrTiO{sub 3}  

SciTech Connect (OSTI)

To study the structural and electronic properties of cubic perovskite SrTiO{sub 3} and its stress-induced tetragonal phase, we have performed total energy calculations and studied the effect of oxygen vacancies on the electronic properties of tetragonal perovskite SrTiO{sub 3}. The method used was the relativistic full-potential linearized augmented plane wave (FLAPW) method. To obtain the geometry that minimizes the total energy, we relaxed the internal atomic sites of the tetragonal cell. As a result of this procedure, we have found that the titanium atoms move toward the plane of the vacancy by 0.03 , and the apical oxygen atoms move to the same plane by approximately 0.14 . These results are discussed in comparison with experimental data.

Rubio-Ponce, A. [Departamento de Ciencias Bsicas, Universidad Autnoma Metropolitana-Azcapotzalco, Av. San Pablo 180, 02200 Mxico, D.F. (Mexico); Olgun, D. [Departamento de Fsica, Centro de Investigacin y de Estudios Avanzados del Instituto Politcnico Nacional, A.P. 14740, Mxico, D.F. (Mexico)

2014-05-15T23:59:59.000Z

394

What People Do with Consumption Feedback: A Long-Term Living Lab Study of a Home Energy Management System  

Science Journals Connector (OSTI)

......to seven households over a period...edition of the Energy Efficiency Action Plan...Consumption. Energy Efficiency in Household Appliances...Council on energy efficiency and repealing...Standards-Households in the informations......

Tobias Schwartz; Gunnar Stevens; Timo Jakobi; Sebastian Denef; Leonardo Ramirez; Volker Wulf; Dave Randall

2014-04-01T23:59:59.000Z

395

High energy Gamma-Ray Bursts as a result of the collapse and total annihilation of neutralino clumps  

E-Print Network [OSTI]

Rare astrophysical events - cosmological gamma-ray bursts with energies over GeV - are considered as an origin of information about some SUSY parameters. The model of generation of the powerful gamma-ray bursts is proposed. According to this model the gamma-ray burst represents as a result of the collapse and the total annihilation of the neutralino clump. About 80 % of the clump mass radiates during about 100 second at the final stage of annihilation. The annihilation spectrum and its characteristic energies are calculated in the framework of Split Higgsino model.

R. S. Pasechnik; V. A. Beylin; V. I. Kuksa; G. M. Vereshkov

2006-02-20T23:59:59.000Z

396

"Table A33. Total Quantity of Purchased Energy Sources by Census Region, Census Division,"  

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

Quantity of Purchased Energy Sources by Census Region, Census Division," Quantity of Purchased Energy Sources by Census Region, Census Division," " and Economic Characteristics of the Establishment, 1994" " (Estimates in Btu or Physical Units)" ,,,,,"Natural",,,"Coke" " ","Total","Electricity","Residual","Distillate","Gas(c)"," ","Coal","and Breeze","Other(d)","RSE" " ","(trillion","(million","Fuel Oil","Fuel Oil(b)","(billion","LPG","(1000 ","(1000","(trillion","Row" "Economic Characteristics(a)","Btu)","kWh)","(1000 bbl)","(1000 bbl)","cu ft)","(1000 bbl)","short tons)","short tons)","Btu)","Factors"

397

Total Space Heat-  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

Buildings Energy Consumption Survey: Energy End-Use Consumption Tables Total Space Heat- ing Cool- ing Venti- lation Water Heat- ing Light- ing Cook- ing Refrig- eration...

398

"State","Fossil Fuels",,,,,,"Nuclear Electric Power",,"Renewable Energy",,,,,,"Total Energy Production"  

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

P2. Energy Production Estimates in Trillion Btu, 2011 " P2. Energy Production Estimates in Trillion Btu, 2011 " "State","Fossil Fuels",,,,,,"Nuclear Electric Power",,"Renewable Energy",,,,,,"Total Energy Production" ,"Coal a",,"Natural Gas b",,"Crude Oil c",,,,"Biofuels d",,"Other e",,"Total" ,"Trillion Btu" "Alabama",468.671,,226.821,,48.569,,411.822,,0,,245.307,,245.307,,1401.191 "Alaska",33.524,,404.72,,1188.008,,0,,0,,15.68,,15.68,,1641.933 "Arizona",174.841,,0.171,,0.215,,327.292,,7.784,,107.433,,115.217,,617.734 "Arkansas",2.985,,1090.87,,34.087,,148.531,,0,,113.532,,113.532,,1390.004 "California",0,,279.71,,1123.408,,383.644,,25.004,,812.786,,837.791,,2624.553

399

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

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

8 - Vehicles by HH Comp EIA ","Table A18. U.S. Vehicles by Household Composition1 (EIA), 2001 8 - Vehicles by HH Comp EIA ","Table A18. U.S. Vehicles by Household Composition1 (EIA), 2001 (Million Vehicles)" "Std Errors for A18","Relative Standard Errors for Table A18. U.S. Vehicles by Household Composition1 (EIA), 2001 (Percent)" "N Cells for A18","Number of Sample Cases Contributing to Estimates in Table A18. U.S. Vehicles by Household Composition1 (EIA), 2001" " Page A-1 of A-N" "Table A18. U.S. Vehicles by Household Composition1 (EIA), 2001 (Million Vehicles)" "2001 Household and Vehicle Characteristics","Households With Children",,,,"Households Without Children" ,"Total","Age of Oldest Child",,,"Total","One Adult--Age of Householder",,,"Two or More Adults--Age of Householder"

400

Material and Energy Dependence of Services and Its Implications for Climate Change  

Science Journals Connector (OSTI)

By decomposing the CO2 emissions embodied in material goods and services, this study quantitatively analyzes the implications of energy and materials consumption in services for the change in indirect CO2 emissions by household consumers in Japan. ... In contrast to p?kl, this indicator is independent of the total expenditure of households and thus allows the structure of supply chain CO2 emission by each segment to be compared from year to year. ...

Keisuke Nansai; Shigemi Kagawa; Sangwon Suh; Minoru Fujii; Rokuta Inaba; Seiji Hashimoto

2009-05-07T23:59:59.000Z

Note: This page contains sample records for the topic "household total energy" 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

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

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

3 Household Characteristics by Household Income, 2005" 3 Household Characteristics by Household Income, 2005" " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ,"Housing Units (millions)" ,,"Less than $20,000","$20,000 to $39,999","$40,000 to $59,999","$60,000 to $79,999","$80,000 or More" "Household Characteristics" "Total",111.1,26.7,28.8,20.6,13.1,22,16.6,38.6 "Household Size" "1 Person",30,13.5,8.5,4.3,2,1.8,5.9,13.1 "2 Persons",34.8,6,8.8,7.3,4.4,8.4,3.5,8.4 "3 Persons",18.4,3.1,4.7,3.4,2.5,4.6,2,5.8 "4 Persons",15.9,2.2,3.5,3.3,2.7,4.3,2.2,5.1

402

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

E-Print Network [OSTI]

efficiency standards. Total energy consumption (TEC) is thusarrived as follows, Total Energy Consumption = ? Stock(i) *Retirement) And total energy consumption for a particular

Lin, Jiang

2006-01-01T23:59:59.000Z

403

Projections up for total energy demand by IEA nations in 1990  

SciTech Connect (OSTI)

The author reviews the most recent IEA projections for energy demand to the year 2000 in IEA countries. These show that the expectations for 1990 are now higher than estimates made last year. Production of solid fuels is expected to increase from 814 million toe in 1983 to 1044 million toe in 1990 and 1345 million toe by 2000. Nearly all the increase is expected in the US, Canada and Australia.

Vielvoye, R.

1985-06-17T23:59:59.000Z

404

Estimate the fraction of the total transported energy (in the form of gasoline) in the Trans-Alaska Pipeline that is consumed in pumping.  

E-Print Network [OSTI]

Estimate the fraction of the total transported energy (in the form of gasoline) in the Trans m). So we can toss this out. Now estimate the energy content of gasoline: Many of you tried figuring

Nimmo, Francis

405

Electron induced dissociation of trimethyl (methylcyclopentadienyl) platinum (IV): Total cross section as a function of incident electron energy  

SciTech Connect (OSTI)

The total cross section has been measured for the electron induced dissociation of trimethyl (methylcyclopentadienyl) platinum (IV) [MeCpPt(IV)Me{sub 3}], a Pt precursor often used in focused electron beam induced processing (FEBIP), for incident electron energies ranging between 3-3 keV. Measurements were performed for the precursor in the adsorbed state under ultrahigh vacuum conditions. The techniques used in this study were temperature programmed desorption, x-ray photoelectron spectroscopy and mass spectrometry. Two surfaces were used in these experiments, amorphous carbon overlayers containing embedded Pt atoms (a:C-Pt), formed by the electron decomposition of the Pt precursor, and atomically clean Au. The results from these three experiments revealed a comparatively low total cross section at 8 eV (4.2+-0.3x10{sup -17} cm{sup 2} on the a:C-Pt and 1.4+-0.1x10{sup -17} cm{sup 2} on the Au) that increases with increasing incident electron energy, reaching a maximum at around 150 eV (4.1+-0.5x10{sup -16} cm{sup 2} on the a:C-Pt and 2.3+-0.2x10{sup -16} cm{sup 2} on the clean Au), before decreasing at higher incident electron energies, up to 3000 eV. Differences in the measured cross sections between Au and a:C-Pt surfaces demonstrate that the substrate can influence the reaction cross section of adsorbed species. Temperature programmed desorption was also used to measure the adsorption energy of MeCpPt(IV)Me{sub 3}, which was found to depend on both the substrate and the adsorbate coverage. The work in this paper demonstrates that surface science techniques can be used to quantitatively determine the total cross section of adsorbed FEBIP precursors for electron induced dissociation as a function of incident electron energy. These total cross section values are necessary to obtain quantitatively accurate information from FEBIP models and to compare the reaction efficiencies of different precursors on a quantitative basis.

Dorp, W. F. van [Department of Physics and Astronomy, Laboratory of Surface Modification, Rutgers, State University of New Jersey, Piscataway, New Jersey 08854-8019 (United States); Charged Particle Optics Group, Faculty of Applied Sciences, Delft University of Technology, Lorentzweg 1, 2628 CJ Delft (Netherlands); Wnuk, J. D.; Gorham, J. M.; Fairbrother, D. H. [Department of Chemistry, Johns Hopkins University, Baltimore, Maryland 21218 (United States); Madey, T. E. [Department of Physics and Astronomy, Laboratory of Surface Modification, Rutgers, The State University of New Jersey, Piscataway, New Jersey 08854-8019 (United States); Hagen, C. W. [Charged Particle Optics Group, Faculty of Applied Sciences, Delft University of Technology, Lorentzweg 1, 2628 CJ Delft (Netherlands)

2009-10-01T23:59:59.000Z

406

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

Open Energy Info (EERE)

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

407

Household Light Makes Global Heat: High Black Carbon Emissions From Kerosene Wick Lamps  

Science Journals Connector (OSTI)

(3) Lighting is another component of this household energy challenge, with millions of households still relying on simple liquid-fueled lamps, but little is known of the associated environmental and health impacts. ... For laboratory tests, CO2 and CO concentrations were measured in real-time with a Li-COR 6252 (Li-COR Biosciences, Lincoln, NE) and Horiba AIA-220 (Horiba, Kyoto, Japan) nondispersive infrared (NDIR) analyzer, respectively. ...

Nicholas L. Lam; Yanju Chen; Cheryl Weyant; Chandra Venkataraman; Pankaj Sadavarte; Michael A. Johnson; Kirk R. Smith; Benjamin T. Brem; Joseph Arineitwe; Justin E. Ellis; Tami C. Bond

2012-11-19T23:59:59.000Z

408

Small modular HTGR nuclear power plant concept to meet the total energy needs of the developing nations  

SciTech Connect (OSTI)

In this paper, a small modular High-Temperature Gas-Cooled Reactor (HTGR) is described that can support the total energy needs of the developing nations by supplying electrical power, process steam, low-grade heat for desalination, and hydrogen production. Major features of the nuclear power plant concept, currently under development by GA Technologies Inc. (GA), are discussed with emphasis on (1) plant simplicity, (2) inherent safety, (3) ease of operation, (4) design and licensing standardization, and (5) acceptable power generation economics.

McDonald, C.F.

1983-09-26T23:59:59.000Z

409

Household Vehicles Energy Use: Latest Data & Trends  

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

for a period of 1 year. VMT was calculated using (1) a regression method developed by Oak Ridge National Laboratories, Center for Transportation Analysis (2) two odometer...

410

Household Vehicles Energy Use: Latest Data & Trends  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

a NHTS sample vehicle having the following attributes: Volkswagen, Sirocco, 1990, Automobile. Toggling of model years, by a single year increase followed by a single year...

411

Household Vehicles Energy Consumption 1994 - Appendix C  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

Protection Agency (EPA) certification files (CERT files) containing laboratory test results of MPG. When the vehicle characteristic was missing from the questionnaire, but...

412

Household Vehicles Energy Use: Latest Data & Trends  

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

80, 85, 86, 88, and 600 and 10 CFR Part 474. GREET MODEL Of course, there are other conversion factors available, depending on the various fuel-specific factors. For the...

413

Environmental Communication Aimed at Household Energy Conservation  

Science Journals Connector (OSTI)

The first commitment period of the Kyoto Protocol started in 2008. Japan is required to cut down on greenhouse...2) emissions in Japan have been showing a tendency to increase ... report of the Ministry of the En...

Chizuru Nishio

2010-01-01T23:59:59.000Z

414

Skylarks trade size and energy content in weed seeds to maximize total ingested lipid biomass  

Science Journals Connector (OSTI)

Abstract The trade-off between forage quality and quantity has been particularly studied in herbivore organisms, but much less for seed eating animals, in particular seed-eating birds which constitute the bulk of wintering passerines in European farmlands. The skylark is one of the commonest farmland birds in winter, mainly feeding on seeds. We focus on weed seeds for conservation and management purposes. Weed seeds form the bulk of the diet of skylarks during winter period, and although this is still a matter for discussion, weed seed predation by granivorous has been suggested as an alternative to herbicides used to regulate weed populations in arable crops. Our objectives were to identify whether weed seed traits govern foraging decisions of skylarks, and to characterize key seed traits with respect to size, which is related to searching and handling time, and lipid content, which is essential for migratory birds. We combined a single-offer experiment and a multiple-offer one to test for feeding preferences of the birds by estimating seed intake on weed seed species differing in their seed size and seed lipid content. Our results showed (1) a selective preference for smaller seeds above a threshold of seed size or seed size difference in the pair and, (2) a significant effect of seed lipid biomass suggesting a trade-off between foraging for smaller seeds and selecting seeds rich in lipids. Skylarks foraging decision thus seems to be mainly based on seed size, that is presumably a proxy for weed seed energy content. However, there are clearly many possible combinations of morphological and physiological traits that must play crucial role in the plantbird interaction such as toxic compound or seed coat.

Sabrina Gaba; Claire Collas; Thibaut Powolny; Franois Bretagnolle; Vincent Bretagnolle

2014-01-01T23:59:59.000Z

415

Measurement of low-energy Na^+ -- Na total collision rate in an ion--neutral hybrid trap  

E-Print Network [OSTI]

We present measurements of the total elastic and resonant charge-exchange ion-atom collision rate coefficient $k_\\mathrm{ia}$ of cold sodium (\\ce{Na}) with optically-dark low energy \\ce{Na+} ions in a hybrid ion-neutral trap. To determine $k_\\mathrm{ia}$, we measured the trap loading and loss from both a \\ce{Na} magneto-optical trap (MOT) and a linear radio frequency quadrupole Paul trap. We found the total rate coefficient to be $7.4 \\pm 1.9 \\times 10^{-8}$ cm$^3$/s for the type I \\ce{Na} MOT immersed within an $\\approx 140$ K ion cloud and $1.10 \\pm 0.25 \\times 10^{-7}$ cm$^3$/s for the type II \\ce{Na} MOT within an $\\approx 1070$ K ion cloud. Our measurements show excellent agreement with previously reported theoretical fully quantal \\textit{ab initio} calculations. In the process of determining the total rate coefficient, we demonstrate that a MOT can be used to probe an optically dark ion cloud's spatial distribution within a hybrid trap.

Goodman, D S; Kwolek, J M; Blmel, R; Narducci, F A; Smith, W W

2014-01-01T23:59:59.000Z

416

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

417

Consumers' preference for renewable energy in the southwest USA  

Science Journals Connector (OSTI)

The southwestern part of the US has abundant supply of renewable energy resources but little is known about the consumers' preferences for renewable energy in this region. This paper investigates households' willingness to pay for a renewable energy program in a southwestern state, New Mexico (NM). Using the contingent valuation method, we provide different scenarios that include provision of 10% and 20% of renewable energy supply, to elicit households' willingness to pay (WTP) for the renewable energy. We estimate the WTP for specific shares of renewable energy in the total energy mix as it is a key factor in affecting the price of the energy portfolio in the market. The survey design also allows us to check the scope sensitivity of renewable energy which can help guide the future renewable energy policy. We hope results from this study will offer useful insights to energy regulators and utility companies and help them increase the share of renewable energy supply.

Pallab Mozumder; William F. Vsquez; Achla Marathe

2011-01-01T23:59:59.000Z

418

A comparative evaluation of household preferences for solar photovoltaic standalone and mini-grid system: An empirical study in a costal village of Indian Sundarban  

Science Journals Connector (OSTI)

Solar PhotoVoltaic (SPV) based systems have been widely accepted technology for rural electrification in developing countries. The standalone SPV home lighting system has increasingly been popular among rural households, while SPV mini-grid supply system is being promoted for rural electrification schemes. This study uses data from household survey to explore the impact of household characteristics on the preference for electrical energy from SPV systems. Econometric evidence shows heterogeneity in behavioural pattern for these two SPV systems. The flexibility in use and cost of systems might explain this difference. Household characteristics such as monthly household income, household size, occupational status of household head, number of room and type of house significantly influence households decision for SPV standalone home lighting systems. For SPV mini-grid supply households income and monthly expenditure on kerosene are significant predictors. The result reported in this paper might be a valuable input for policy makers to frame right policy mix with regard to provide subsidy on rural electrification programmes.

Amit K. Bhandari; Chinmoy Jana

2010-01-01T23:59:59.000Z

419

Nevada: Kingston Creek Hydro Project Powers 100 Households  

Broader source: Energy.gov [DOE]

Hydropower project produces enough electricity to annually power nearly 100 typical American households.

420

The Total Energy Content  

Science Journals Connector (OSTI)

The important message of RG theory [1] is that we have to attribute a specific symmetry to the continuous or infinite solid. Also, magnets with long range magnetic order show properties of an infinite system. Usi...

Dr. Ulrich Kbler; Dr. Andreas Hoser

2010-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "household total energy" 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

Tips: Heating and Cooling | Department of Energy  

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

Tips: Heating and Cooling Tips: Heating and Cooling Tips: Heating and Cooling May 30, 2012 - 7:38pm Addthis Household Heating Systems: Although several different types of fuels are available to heat our homes, more than half of us use natural gas. | Source: Buildings Energy Data Book 2010, 2.1.1 Residential Primary Energy Consumption, by Year and Fuel Type (Quadrillion Btu and Percent of Total). Household Heating Systems: Although several different types of fuels are available to heat our homes, more than half of us use natural gas. | Source: Buildings Energy Data Book 2010, 2.1.1 Residential Primary Energy Consumption, by Year and Fuel Type (Quadrillion Btu and Percent of Total). Heating and cooling your home uses more energy and costs more money than any other system in your home -- typically making up about 54% of your

422

Total and partial capture cross sections in reactions with deformed nuclei at energies near and below the Coulomb barrier  

SciTech Connect (OSTI)

Within the quantum diffusion approach, the capture of a projectile nucleus by a target nucleus is studied at bombarding energies above and below the Coulomb barrier. The effects of deformation of interacting nuclei and neutron transfer between them on the total and partial capture cross sections and the mean angular momentum of the captured system are studied. The results obtained for the {sup 16}O + {sup 112}Cd, {sup 152}Sm, and {sup 184}W; {sup 19}F +{sup 175}Lu; {sup 28}Si +{sup 94,100}Mo and {sup 154}Sm; {sup 40}Ca +{sup 96}Zr; {sup 48}Ca+ {sup 90}Zr; and {sup 64}Ni +{sup 58,64}Ni, {sup 92,96}Zr, and {sup 100}Mo reactions are in good agreement with available experimental data.

Kuzyakin, R. A., E-mail: rkuzyakin@theor.jinr.ru; Sargsyan, V. V.; Adamian, G. G.; Antonenko, N. V. [Joint Institute for Nuclear Research (Russian Federation)

2013-06-15T23:59:59.000Z

423

Total energy cycle assessment of electric and conventional vehicles: an energy and environmental analysis. Volume 2: appendices A-D to technical report  

SciTech Connect (OSTI)

This report compares the energy use, oil use and emissions of electric vehicles (EVs) with those of conventional, gasoline- powered vehicles (CVs) over the total life cycle of the vehicles. The various stages included in the vehicles` life cycles include vehicle manufacture, fuel production, and vehicle operation. Disposal is not included. An inventory of the air emissions associated with each stage of the life cycle is estimated. Water pollutants and solid wastes are reported for individual processes, but no comprehensive inventory is developed. Volume II contains additional details on the vehicle, utility, and materials analyses and discusses several details of the methodology.

NONE

1998-01-01T23:59:59.000Z

424

Total energy cycle assessment of electric and conventional vehicles: an energy and environmental analysis. Volume 4: peer review comments on technical report  

SciTech Connect (OSTI)

This report compares the energy use, oil use and emissions of electric vehicles (EVs) with those of conventional, gasoline-powered vehicles (CVs) over the total life cycle of the vehicles. The various stages included in the vehicles` life cycles include vehicle manufacture, fuel production, and vehicle operation. Disposal is not included. An inventory of the air emissions associated with each stage of the life cycle is estimated. Water pollutants and solid wastes are reported for individual processes, but no comprehensive inventory is developed. Volume IV includes copies of all the external peer review comments on the report distributed for review in July 1997.

NONE

1998-01-01T23:59:59.000Z

425

Green Computing Wanted: Electricity Consumptions in the IT Industry and by Household Computers in Five Major Chinese Cities  

Science Journals Connector (OSTI)

Exhausted energy consumption becomes a world-wide issue nowadays. Computing contributes a large portion of energy consumption. The concept of green computing has been popularized. Along with the rapid development of China, energy issue becomes more and ... Keywords: energy/electricity consumption, IT industry, household computers, energy efficiency, green computing

Luyang Wang; Tao Wang

2011-08-01T23:59:59.000Z

426

Environmental attitudes and household consumption: an ambiguous relationship  

Science Journals Connector (OSTI)

This article analyses the relationship between environmental attitudes and energy use in the home and for transport by Norwegian households. Quantitative surveys were used to find statistical correlations, and qualitative analyses to reveal mechanisms that influence the ability to behave in an environmentally friendly way. Three theses about attitudes, mechanisms and household consumption are presented. Firstly, a desire to project an environmentally friendly image has little influence on energy use in the home and for transport. Secondly, a sense of powerlessness prevents people from translating positive environmental attitudes into low energy use in the home and for everyday transport. Thirdly, a desire to self-indulge prevents people from translating positive environmental attitudes into low energy use for long distance leisure travel. These results have important implications for environmental policy. Public information and awareness campaigns can give consumers information on how to behave in an environmentally responsible way, but tend only to influence categories of consumption with little environmental impact. Structural change can be used to mitigate the effect of the sense of powerlessness and encourage environmentally friendly behaviour, but the desire to self-indulge is much more difficult to deal with.

Erling Holden; Kristin Linnerud

2010-01-01T23:59:59.000Z

427

Evolution of the household vehicle fleet: Anticipating fleet composition, PHEV adoption and GHG emissions in Austin, Texas  

Science Journals Connector (OSTI)

In todays world of volatile fuel prices and climate concerns, there is little study on the relationship between vehicle ownership patterns and attitudes toward vehicle cost (including fuel prices and feebates) and vehicle technologies. This work provides new data on ownership decisions and owner preferences under various scenarios, coupled with calibrated models to microsimulate Austins personal-fleet evolution. Opinion survey results suggest that most Austinites (63%, population-corrected share) support a feebate policy to favor more fuel efficient vehicles. Top purchase criteria are price, type/class, and fuel economy. Most (56%) respondents also indicated that they would consider purchasing a Plug-in Hybrid Electric Vehicle (PHEV) if it were to cost $6000 more than its conventional, gasoline-powered counterpart. And many respond strongly to signals on the external (health and climate) costs of a vehicles emissions, more strongly than they respond to information on fuel cost savings. Twenty five-year simulations of Austins household vehicle fleet suggest that, under all scenarios modeled, Austins vehicle usage levels (measured in total vehicle miles traveled or VMT) are predicted to increase overall, along with average vehicle ownership levels (both per household and per capita). Under a feebate, HEVs, \\{PHEVs\\} and Smart Cars are estimated to represent 25% of the fleets VMT by simulation year 25; this scenario is predicted to raise total regional VMT slightly (just 2.32%, by simulation year 25), relative to the trend scenario, while reducing CO2 emissions only slightly (by 5.62%, relative to trend). Doubling the trend-case gas price to $5/gallon is simulated to reduce the year-25 vehicle use levels by 24% and CO2 emissions by 30% (relative to trend). Two- and three-vehicle households are simulated to be the highest adopters of \\{HEVs\\} and \\{PHEVs\\} across all scenarios. The combined share of vans, pickup trucks, sport utility vehicles (SUVs), and cross-over utility vehicles (CUVs) is lowest under the feebate scenario, at 35% (versus 47% in Austins current household fleet). Feebate-policy receipts are forecasted to exceed rebates in each simulation year. In the longer term, gas price dynamics, tax incentives, feebates and purchase prices along with new technologies, government-industry partnerships, and more accurate information on range and recharging times (which increase customer confidence in EV technologies) should have added effects on energy dependence and greenhouse gas emissions.

Sashank Musti; Kara M. Kockelman

2011-01-01T23:59:59.000Z

428

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

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

429

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

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

430

Structure in the energy dependence of the proton total reaction cross section for C and Si in the energy region 20-40 MeV  

Science Journals Connector (OSTI)

Measurements of proton total reaction cross sections for Be9, C12, O16, and Si28 have been made in the energy range between 20-44 MeV. The cross sections show irregular energy variation for C12 at about 23.8 and 25.9 MeV, and for Si28 at 30.3 and 33.5 MeV; irregularities were not observed clearly for Be9 or O16.NUCLEAR REACTIONS Be9, C12, O16, Si28: 20MeV

I. laus; D. J. Margaziotis; R. F. Carlson; W. T. H. van Oers; J. Reginald Richardson

1975-09-01T23:59:59.000Z

431

Drivers of Future Energy Demand  

Gasoline and Diesel Fuel Update (EIA)

trends - Household income migration urbanization * Policy: China Energy Outlook - Air pollution - Climate change 4 (1) Industrial energy intensity: The energy intensity of...

432

Enhanced naphthenic refrigeration oils for household refrigerator systems  

SciTech Connect (OSTI)

Due to industry concerns about the successful employment of hydrofluorocarbon-immiscible hydrocarbon oils in refrigeration systems, enhanced naphthenic refrigeration oils have been developed. These products have been designed to be more dispersible with hydrofluorocarbon (HFC) refrigerants, such as R-134a, in order to facilitate lubricant return to the compressor and to ensure proper energy efficiency of the system. Bench tests and system performance evaluations indicate the feasibility of these oils for use in household refrigeration applications. Results of these evaluations are compared with those obtained with polyol esters and typical naphthenic mineral oils employed in chlorofluorocarbon (CFC) and hydrochlorofluorocarbon (HCFC) refrigeration applications.

Reyes-Gavilan, J.L.; Flak, G.T.; Tritcak, T.R. [Witco Corp., Oakland, NJ (United States); Barbour, C.B. [Americold, Cullman, AL (United States)

1997-12-31T23:59:59.000Z

433

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

434

Intra-hour forecasting with a total sky imager at the UC San Diego solar energy testbed  

E-Print Network [OSTI]

solener.2011.02.014, Solar Energy. Lave, M. , Kleissl, J. ,smoothing. Submitted to Solar Energy. Linke, F. , 1922.24th European Photovoltaic Solar Energy Conference, Hamburg,

2011-01-01T23:59:59.000Z

435

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

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

5.17. U.S. Number of Households by Vehicle Fuel Expenditures, 1994 (Continued) (Million Households) 1993 Household and 1994 Vehicle Characteristics RSE Column Factor: All...

436

Using census aggregates to proxy for household characteristics: an application to vehicle ownership  

E-Print Network [OSTI]

Instead, Asian and Hispanic households were undersampled byhousehold Age of the householder/Average age of residents Hispanichousehold Age of the householder/Average age of residents Hispanic

Adjemian, Michael; Williams, Jeffrey

2009-01-01T23:59:59.000Z

437

"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

438

"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

439

Transferring 2001 National Household Travel Survey  

SciTech Connect (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

440

"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

Note: This page contains sample records for the topic "household total energy" 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

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

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

442

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

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

443

Opportunities to reduce greenhouse gas emissions from households in Nigeria  

Science Journals Connector (OSTI)

Efforts to mitigate climate threats should not exclude the household as the household is a major driver of greenhouse gas (GHG) emissions through its consumption...2) emissions from kerosene combustion for lighting

O. Adeoti; S. O. Osho

2012-02-01T23:59:59.000Z

444

Household Wealth in a Cross-Country Perspective  

Science Journals Connector (OSTI)

This paper provides a comparative analysis of household wealth in the United States, the United Kingdom, Japan, France, Germany, Spain, and Italy. ... wealth, looking at the instruments in which households invest...

Laura Bartiloro; Massimo Coletta

2012-01-01T23:59:59.000Z

445

Control of household refrigerators. Part 1: Modeling temperature control performance  

SciTech Connect (OSTI)

Commercial household refrigerators use simple, cost-effective, temperature controllers to obtain acceptable control. A manually adjusted airflow damper regulates the freezer compartment temperature while a thermostat controls operation of the compressor and evaporator fan to regulate refrigerator compartment temperature. Dual compartment temperature control can be achieved with automatic airflow dampers that function independently of the compressor and evaporator fan thermostat, resulting in improved temperature control quality and energy consumption. Under dual control, freezer temperature is controlled by the thermostat while the damper controls refrigerator temperature by regulating airflow circulation. A simulation model is presented that analyzes a household refrigerator configured with a conventional thermostat and both manual and automatic dampers. The model provides a new paradigm for investigating refrigerator systems and temperature control performance relative to the extensive verification testing that is typically done by manufacturers. The effects of each type of control and damper configuration are compared with respect to energy usage, control quality, and ambient temperature shift criteria. The results indicate that the appropriate control configuration can have significant effects and can improve plant performance.

Graviss, K.J.; Collins, R.L.

1999-07-01T23:59:59.000Z

446

Combined iterative reconstruction and image-domain decomposition for dual energy CT using total-variation regularization  

SciTech Connect (OSTI)

Purpose: Dual-energy CT (DECT) is being increasingly used for its capability of material decomposition and energy-selective imaging. A generic problem of DECT, however, is that the decomposition process is unstable in the sense that the relative magnitude of decomposed signals is reduced due to signal cancellation while the image noise is accumulating from the two CT images of independent scans. Direct image decomposition, therefore, leads to severe degradation of signal-to-noise ratio on the resultant images. Existing noise suppression techniques are typically implemented in DECT with the procedures of reconstruction and decomposition performed independently, which do not explore the statistical properties of decomposed images during the reconstruction for noise reduction. In this work, the authors propose an iterative approach that combines the reconstruction and the signal decomposition procedures to minimize the DECT image noise without noticeable loss of resolution. Methods: The proposed algorithm is formulated as an optimization problem, which balances the data fidelity and total variation of decomposed images in one framework, and the decomposition step is carried out iteratively together with reconstruction. The noise in the CT images from the proposed algorithm becomes well correlated even though the noise of the raw projections is independent on the two CT scans. Due to this feature, the proposed algorithm avoids noise accumulation during the decomposition process. The authors evaluate the method performance on noise suppression and spatial resolution using phantom studies and compare the algorithm with conventional denoising approaches as well as combined iterative reconstruction methods with different forms of regularization. Results: On the Catphan600 phantom, the proposed method outperforms the existing denoising methods on preserving spatial resolution at the same level of noise suppression, i.e., a reduction of noise standard deviation by one order of magnitude. This improvement is mainly attributed to the high noise correlation in the CT images reconstructed by the proposed algorithm. Iterative reconstruction using different regularization, including quadratic orq-generalized Gaussian Markov random field regularization, achieves similar noise suppression from high noise correlation. However, the proposed TV regularization obtains a better edge preserving performance. Studies of electron density measurement also show that our method reduces the average estimation error from 9.5% to 7.1%. On the anthropomorphic head phantom, the proposed method suppresses the noise standard deviation of the decomposed images by a factor of ?14 without blurring the fine structures in the sinus area. Conclusions: The authors propose a practical method for DECT imaging reconstruction, which combines the image reconstruction and material decomposition into one optimization framework. Compared to the existing approaches, our method achieves a superior performance on DECT imaging with respect to decomposition accuracy, noise reduction, and spatial resolution.

Dong, Xue; Niu, Tianye; Zhu, Lei, E-mail: leizhu@gatech.edu [Nuclear and Radiological Engineering and Medical Physics Programs, The George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332 (United States)] [Nuclear and Radiological Engineering and Medical Physics Programs, The George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332 (United States)

2014-05-15T23:59:59.000Z

447

Home Prices and Household Callan Windsor, Jarkko Jskel and  

E-Print Network [OSTI]

Research Discussion Paper Home Prices and Household Spending Callan Windsor, Jarkko Jääskelä. ISSN 1320-7729 (Print) ISSN 1448-5109 (Online) #12;Home Prices and Household Spending Callan Windsor Abstract This paper explores the positive relationship between home prices and household spending

448

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)

449

Handling Frame Problems When Address-Based Sampling Is Used for In-Person Household Surveys  

Science Journals Connector (OSTI)

......use as the sampling frame for household surveys. This subset includes...However, around 90 percent of households with PO box addresses also have...recent growth, new construction, Hispanic households, non-English-speaking households......

Graham Kalton; Jennifer Kali; Richard Sigman

2014-09-01T23:59:59.000Z

450

Energy for 500 Million Homes: Drivers and Outlook for Residential Energy Consumption in China  

E-Print Network [OSTI]

Japan by 2020. 12 of 17 Because of their large share in household energyJapan in 2000 which was 4560 kWh/household (IEEJ, 2003). In developed countries, the energy

Zhou, Nan

2010-01-01T23:59:59.000Z

451

Relationship Between Surface Free Energy and Total Work of Fracture of Asphalt Binder and Asphalt Binder-Aggregate Interfaces  

E-Print Network [OSTI]

is the surface free energy of the asphalt binder and the aggregate. Surface free energy, which is a thermodynamic material property, is directly related to the adhesive bond energy between the asphalt binder and the aggregate as well as the cohesive bond energy...

Howson, Jonathan Embrey

2012-10-19T23:59:59.000Z

452

E-Print Network 3.0 - assessing household solid Sample Search...  

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

of Groundwater Contamination from Household Wastewater... 12;Glossary Household Wastewater Treatment These terms may help you make more accurate assessments......

453

Greenhouse Gas Emissions from the Consumption of Electric and Electronic Equipment by Norwegian Households  

Science Journals Connector (OSTI)

Greenhouse Gas Emissions from the Consumption of Electric and Electronic Equipment by Norwegian Households ... Conventional wisdom holds that large appliances, in particular washers, dryers, refrigerators and freezers, dominate residential energy consumption apart from heat, hot water and light. ... (16) It excludes lighting, all professional equipment, space heating, hot water, garden or car equipment, fire alarms, and air conditioning. ...

Edgar G. Hertwich; Charlotte Roux

2011-08-30T23:59:59.000Z

454

Stranded Vehicles: How Gasoline Taxes Change the Value of Households' Vehicle Assets  

E-Print Network [OSTI]

Stranded Vehicles: How Gasoline Taxes Change the Value of Households' Vehicle Assets Meghan Busse pollution caused by the burning of fossil fuels. Argu- ments against energy taxes, and gasoline taxes more incidence of the tax. We study the effect of a gasoline tax using changes in vehicle values. We construct

Rothman, Daniel

455

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

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

3a. Housing Unit Characteristics by Household Income, 3a. Housing Unit Characteristics by Household Income, Million U.S. Households, 2001 Housing Unit 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 Census Region and Division Northeast ...................................... 20.3 3.3 4.2 4.9 7.8 2.6 6.8 6.4 New England .............................. 5.4 0.8 1.1 1.3 2.3 0.6 1.6 9.9 Middle Atlantic ............................ 14.8 2.6 3.2 3.5 5.6 2.0 5.2 7.7 Midwest ......................................... 24.5 3.7 5.2 6.8 8.9 2.8 7.4 5.8 East North Central ......................

456

ESTIMATE OF THE TOTAL MECHANICAL FEEDBACK ENERGY FROM GALAXY CLUSTER-CENTERED BLACK HOLES: IMPLICATIONS FOR BLACK HOLE EVOLUTION, CLUSTER GAS FRACTION, AND ENTROPY  

SciTech Connect (OSTI)

The total feedback energy injected into hot gas in galaxy clusters by central black holes can be estimated by comparing the potential energy of observed cluster gas profiles with the potential energy of non-radiating, feedback-free hot gas atmospheres resulting from gravitational collapse in clusters of the same total mass. Feedback energy from cluster-centered black holes expands the cluster gas, lowering the gas-to-dark-matter mass ratio below the cosmic value. Feedback energy is unnecessarily delivered by radio-emitting jets to distant gas far beyond the cooling radius where the cooling time equals the cluster lifetime. For clusters of mass (4-11) x 10{sup 14} M{sub sun}, estimates of the total feedback energy, (1-3) x 10{sup 63} erg, far exceed feedback energies estimated from observations of X-ray cavities and shocks in the cluster gas, energies gained from supernovae, and energies lost from cluster gas by radiation. The time-averaged mean feedback luminosity is comparable to those of powerful quasars, implying that some significant fraction of this energy may arise from the spin of the black hole. The universal entropy profile in feedback-free gaseous atmospheres in Navarro-Frenk-White cluster halos can be recovered by multiplying the observed gas entropy profile of any relaxed cluster by a factor involving the gas fraction profile. While the feedback energy and associated mass outflow in the clusters we consider far exceed that necessary to stop cooling inflow, the time-averaged mass outflow at the cooling radius almost exactly balances the mass that cools within this radius, an essential condition to shut down cluster cooling flows.

Mathews, William G.; Guo Fulai, E-mail: mathews@ucolick.org [University of California Observatories/Lick Observatory, Department of Astronomy and Astrophysics, University of California, Santa Cruz, CA 95064 (United States)

2011-09-10T23:59:59.000Z

457

Residential Energy Consumption Survey (RECS) - Analysis & Projections -  

Gasoline and Diesel Fuel Update (EIA)

Share of energy used by appliances and consumer electronics increases in Share of energy used by appliances and consumer electronics increases in U.S. homes RECS 2009 - Release date: March 28, 2011 Over the past three decades, the share of residential electricity used by appliances and electronics in U.S. homes has nearly doubled from 17 percent to 31 percent, growing from 1.77 quadrillion Btu (quads) to 3.25 quads. This rise has occurred while Federal energy efficiency standards were enacted on every major appliance, overall household energy consumption actually decreased from 10.58 quads to 10.55 quads, and energy use per household fell 31 percent. Federal energy efficiency standards have greatly reduced consumption for home heating Total energy use in all U.S. homes occupied as primary residences decreased slightly from 10.58 quads in 1978 to 10.55 quads in 2005 as reported by the

458

Bis(4-methylanilinium) and bis(4-iodoanilinium) pentamolybdates from laboratory X-ray powder data and total energy minimization  

Science Journals Connector (OSTI)

The crystal structures of bis(4-methylanilinium) and bis(4-iodoanilinium) pentamolybdates were determined using laboratory X-ray data and refined by total energy minimization methods. The obtained structures present alternating organic cation and inorganic polyanion layers bound by weak bonding (apart from ionic interactions).

Oszajca, M.

2013-10-31T23:59:59.000Z

459

Effects of Forest Management on Total Biomass Production and CO2 Emissions from use of Energy Biomass of Norway Spruce and Scots Pine  

Science Journals Connector (OSTI)

The aim of this study was to analyze the effects of forest management on the total biomass production (t ha-1a-1) and CO2 emissions (kg CO2 MWh-1) from use of energy biomass of Norway spruce and Scots pine grown ...

Johanna Routa; Seppo Kellomki; Harri Strandman

2012-09-01T23:59:59.000Z

460

Total Imports  

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

Data Series: Imports - Total Imports - Crude Oil Imports - Crude Oil, Commercial Imports - by SPR Imports - into SPR by Others Imports - Total Products Imports - Total Motor Gasoline Imports - Finished Motor Gasoline Imports - Reformulated Gasoline Imports - Reformulated Gasoline Blended w/ Fuel Ethanol Imports - Other Reformulated Gasoline Imports - Conventional Gasoline Imports - Conv. Gasoline Blended w/ Fuel Ethanol Imports - Conv. Gasoline Blended w/ Fuel Ethanol, Ed55 & Ed55 Imports - Other Conventional Gasoline Imports - Motor Gasoline Blend. Components Imports - Motor Gasoline Blend. Components, RBOB Imports - Motor Gasoline Blend. Components, RBOB w/ Ether Imports - Motor Gasoline Blend. Components, RBOB w/ Alcohol Imports - Motor Gasoline Blend. Components, CBOB Imports - Motor Gasoline Blend. Components, GTAB Imports - Motor Gasoline Blend. Components, Other Imports - Fuel Ethanol Imports - Kerosene-Type Jet Fuel Imports - Distillate Fuel Oil Imports - Distillate F.O., 15 ppm Sulfur and Under Imports - Distillate F.O., > 15 ppm to 500 ppm Sulfur Imports - Distillate F.O., > 500 ppm to 2000 ppm Sulfur Imports - Distillate F.O., > 2000 ppm Sulfur Imports - Residual Fuel Oil Imports - Propane/Propylene Imports - Other Other Oils Imports - Kerosene Imports - NGPLs/LRGs (Excluding Propane/Propylene) Exports - Total Crude Oil and Products Exports - Crude Oil Exports - Products Exports - Finished Motor Gasoline Exports - Kerosene-Type Jet Fuel Exports - Distillate Fuel Oil Exports - Residual Fuel Oil Exports - Propane/Propylene Exports - Other Oils Net Imports - Total Crude Oil and Products Net Imports - Crude Oil Net Imports - Petroleum Products Period: Weekly 4-Week Avg.

Note: This page contains sample records for the topic "household total energy" 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

Buildings Energy Data Book: 2.9 Low-Income Housing  

Buildings Energy Data Book [EERE]

Program Definitions DOE Weatherization: Department of Energy's Weatherization Assistance Program DOE Weatherization Eligible Households: Households with incomes at or below 125% of the Federal poverty level, which varies by family size; however, a State may instead elect to use the LIHEAP income standard if its State LIHEAP income standard is at least 125% of the Federal poverty level. Data listed in this chapter include previously weatherized units. DOE Weatherization Eligible Households are a subset of Federally Eligible Households. DOE Weatherization Recipient Households: Households that have received weatherization under DOE Weatherization funding. Federally Eligible Households: Households with incomes below the Federal maximum standard of 150% to 200% of the poverty

462

Global Potential of Energy Efficiency Standards and Labeling Programs  

E-Print Network [OSTI]

and Energy Use in Japan: Household Equipment and EnergyHousehold (Electrified), 1999-2000 Average standby power (W/home) Austria Belgium Canada Denmark Finland France Germany Iceland Ireland Italy Japan

McNeil, Michael A

2008-01-01T23:59:59.000Z

463

Buildings Energy Data Book: 2.1 Residential Sector Energy Consumption  

Buildings Energy Data Book [EERE]

2 2 Year Built (1) Prior to 1950 74.5 114.9 46.8 24% 1950 to 1969 66.0 96.6 38.1 23% 1970 to 1979 59.4 83.4 33.5 15% 1980 to 1989 51.9 81.4 32.3 14% 1990 to 1999 48.2 94.4 33.7 16% 2000 to 2005 44.7 94.7 34.3 8% Average 58.7 95.0 40.0 Note(s): Source(s): 1) Energy consumption per square foot was 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. 2005 Residential Delivered Energy Consumption Intensities, by Vintage Per Square Per Household Per Household

464

Buildings Energy Data Book: 2.9 Low-Income Housing  

Buildings Energy Data Book [EERE]

7 7 Residential Energy Burdens, by Weatherization Eligibility and Year (1) 1987 Mean Mean Mean Mean Mdn Mean Mean Mdn Mean Group Indvdl Group Indvdl Indvdl Group Indvdl Indvdl Group Total U.S. Households 4.0% 6.8% 3.2% 6.1% 3.5% 2.4% 7.2% 4.4% 3.2% Federally Eligible 13.0% 14.4% 10.1% 12.1% 7.9% 7.7% 13.8% 9.6% 10.0% Federally Ineligible 4.0% 3.5% N.A. 3.0% 2.6% 2.0% 3.6% 3.1% 2.6% Below 125% Poverty Line 13.0% N.A. N.A. N.A. N.A. N.A. N.A. N.A. N.A. Note(s): Source(s): 1990 FY 2000 (2) FY 2009 (3) 1) Energy burden can be defined broadly as the burden placed on household incomes by the cost of energy, or the ratio of energy expenditures to income for a household. DOE Weatherization primarily uses mean individual burden and mean group burden since these statistics provide data on how an "average" individual household fares against an "average" group of households (that is, how burdens are

465

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

SciTech Connect (OSTI)

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

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

1990-02-01T23:59:59.000Z

466

Confronting earthquake risk in Japanare private households underinsured?  

Science Journals Connector (OSTI)

Despite the fact that Japan is an earthquake-prone country and Japanese ... risk averse, less than half of Japanese households are insured against earthquake risk. Based on...

Franz Waldenberger

2013-03-01T23:59:59.000Z

467

Salmon consumption at the household level in Japan.  

E-Print Network [OSTI]

??The primary purpose of this study is to investigate the salmon demand of Japanese households. The specific goals are to illuminate the substitutional relationship between (more)

Kikuchi, Akihiro

1987-01-01T23:59:59.000Z

468

Consumer perspectives on household hazardous waste management in Japan  

Science Journals Connector (OSTI)

We give an overview of the management systems of household hazardous waste (HHW) in Japan and discuss the management systems and their...

Misuzu Asari; Shin-ichi Sakai

2011-02-01T23:59:59.000Z

469

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.

470

Hadronic Total Cross Sections (R) in E+E- Interactions: Data from DOE laboratory experiments as compiled in data reviews by the Durham High Energy Physics Database Group  

DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

A comprehensive compilation of experimental data on total hadronic cross sections, and R ratios, in e+e- interactions is presented. Published data from the Novosibirsk, Orsay, Frascati, SLAC, CORNELL, DESY, KEK and CERN e+e- colliders on both exclusive and inclusive final particle states are included from threshold energies to the highest LEP energies. The data are presented in tabular form supplemented by compilation plots of different exclusive final particle states and of different energy regions. (Taken from abstract of paper, A Compilation of Data on Hadronic Total Cross Sections in E+E- Interactions, M.R. Whalley, Journal of Physics G (Nuclear and Particle Physics), Volume 29, Number 12A, 2003). The Durham High Energy Physics (HEP) Database Group makes these data, extracted from papers and data reviews, available in one place in an easy-to-access format. The data are also included in the Durham HEP Reaction Data Database, which can be searched at http://hepdata.cedar.ac.uk/reaction

Whalley, M.R.

471

Northern Virginia Residents Improve Their Homes' Energy With...  

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

Boost The Northern Virginia Home Energy Makeover Contest logo. The Local Energy Alliance Program (LEAP) awarded energy efficiency funding to three households as part of the...

472

"YEAR","MONTH","STATE","UTILITY CODE","UTILITY NAME","RESIDENTIAL PHOTOVOLTAIC ELECTRIC ENERGY SOLD BACK (MWh)","COMMERCIAL PHOTOVOLTAIC ELECTRIC ENERGY SOLD BACK (MWh)","INDUSTRIAL PHOTOVOLTAIC ELECTRIC ENERGY SOLD BACK (MWh)","TRANSPORTATION PHOTOVOLTAIC ELECTRIC ENERGY SOLD BACK (MWh)","TOTAL PHOTOVOLTAIC ELECTRIC ENERGY SOLD BACK (MWh)","RESIDENTIAL PHOTOVOLTAIC INSTALLED NET METERING CAPACITY (MW)","COMMERCIAL PHOTOVOLTAIC INSTALLED NET METERING CAPACITY (MW)","INDUSTRIAL PHOTOVOLTAIC INSTALLED NET METERING CAPACITY (MW)","TRANSPORTATION PHOTOVOLTAIC INSTALLED NET METERING CAPACITY (MW)","TOTAL PHOTOVOLTAIC INSTALLED NET METERING CAPACITY (MW)","RESIDENTIAL PHOTOVOLTAIC NET METERING CUSTOMER COUNT","COMMERCIAL PHOTOVOLTAIC NET METERING CUSTOMER COUNT","INDUSTRIAL PHOTOVOLTAIC NET METERING CUSTOMER COUNT","TRANSPORTATIONPHOTOVOLTAIC NET METERING CUSTOMER COUNT","TOTAL PHOTOVOLTAIC NET METERING CUSTOMER COUNT","RESIDENTIAL WIND ELECTRIC ENERGY SOLD BACK (MWh)","COMMERCIAL WIND ELECTRIC ENERGY SOLD BACK (MWh)","INDUSTRIAL WIND ELECTRIC ENERGY SOLD BACK (MWh)","TRANSPORTATION WIND ELECTRIC ENERGY SOLD BACK (MWh)","TOTAL WIND ELECTRIC ENERGY SOLD BACK (MWh)","RESIDENTIAL WIND INSTALLED NET METERING CAPACITY (MW)","COMMERCIAL WIND INSTALLED NET METERING CAPACITY (MW)","INDUSTRIAL WIND INSTALLED NET METERING CAPACITY (MW)","TRANSPORTATION WIND INSTALLED NET METERING CAPACITY (MW)","TOTAL WIND INSTALLED NET METERING CAPACITY (MW)","RESIDENTIAL WIND NET METERING CUSTOMER COUNT","COMMERCIAL WIND NET METERING CUSTOMER COUNT","INDUSTRIAL WIND NET METERING CUSTOMER COUNT","TRANSPORTATION WIND NET METERING CUSTOMER COUNT","TOTAL WIND NET METERING CUSTOMER COUNT","RESIDENTIAL OTHER ELECTRIC ENERGY SOLD BACK (MWh)","COMMERCIAL OTHER ELECTRIC ENERGY SOLD BACK (MWh)","INDUSTRIAL OTHER ELECTRIC ENERGY SOLD BACK (MWh)","TRANSPORTATION OTHER ELECTRIC ENERGY SOLD BACK (MWh)","TOTAL OTHER ELECTRIC ENERGY SOLD BACK (MWh)","RESIDENTIAL OTHER INSTALLED NET METERING CAPACITY (MW)","COMMERCIAL OTHER INSTALLED NET METERING CAPACITY (MW)","INDUSTRIAL OTHER INSTALLED NET METERING CAPACITY (MW)","TRANSPORTATION OTHER INSTALLED NET METERING CAPACITY (MW)","TOTAL OTHER INSTALLED NET METERING CAPACITY (MW)","RESIDENTIAL OTHER NET METERING CUSTOMER COUNT","COMMERCIAL OTHER NET METERING CUSTOMER COUNT","INDUSTRIAL OTHER NET METERING CUSTOMER COUNT","TRANSPORTATION OTHER NET METERING CUSTOMER COUNT","TOTAL OTHER NET METERING CUSTOMER COUNT","RESIDENTIAL TOTAL ENERGY SOLD BACK TO THE UTILITY (MWh)","COMMERCIAL TOTAL ELECTRIC ENERGY SOLD BACK (MWh)","INDUSTRIAL TOTAL ELECTRIC ENERGY SOLD BACK (MWh)","TRANSPORTATION TOTAL ELECTRIC ENERGY SOLD BACK (MWh)","TOTAL ELECTRIC ENERGY SOLD BACK (MWh)","RESIDENTIAL TOTAL INSTALLED NET METERING CAPACITY (MW)","COMMERCIAL TOTAL INSTALLED NET METERING CAPACITY (MW)","INDUSTRIAL TOTAL INSTALLED NET METERING CAPACITY (MW)","TRANSPORTATION TOTAL INSTALLED NET METERING CAPACITY (MW)","TOTAL INSTALLED NET METERING CAPACITY (MW)","RESIDENTIAL TOTAL NET METERING CUSTOMER COUNT","COMMERCIAL TOTAL NET METERING CUSTOMER COUNT","INDUSTRIAL TOTAL NET METERING CUSTOMER COUNT","TRANSPORTATION TOTAL NET METERING CUSTOMER COUNT","TOTAL NET METERING CUSTOMER COUNT","RESIDENTIAL ELECTRIC ENERGY SOLD BACK TO THE UTILITY FOR ALL STATES SERVED(MWh)","COMMERCIAL ELECTRIC ENERGY SOLD BACK TO THE UTILITY FOR ALL STATES SERVED(MWh)","INDUSTRIAL ELECTRIC ENERGY SOLD BACK TO THE UTILITY FOR ALL STATES SERVED(MWh)","TRANSPORTATION ELECTRIC ENERGY SOLD BACK TO THE UTILITY FOR ALL STATES SERVED(MWh)","TOTAL ELECTRIC ENERGY SOLD BACK TO THE UTILITYFOR ALL STATES SERVED(MWh)","RESIDENTIAL INSTALLED NET METERING CAPACITY FOR ALL STATES SERVED(MW)","COMMERCIAL INSTALLED NET METERING CAPACITY FOR ALL STATES SERVED(MW)","INDUSTRIAL INSTALLED NET METERING CAPACITY FOR ALL STATES SERVED(MW)","TRANSPORTATION INSTALLED NET METERING CAPACITY FOR ALL STATES SERVED(MW)","INSTALLED NET METERING CAPACITY FOR ALL STATES SERVED(MW)","RESIDENTIAL NET METERING CUSTOMER COUNT FOR ALL STATES SERVED","COMMERCIAL NET METERING CUSTOMER COUNT FOR ALL STATES SERVED","INDUSTRIAL NET METERING CUSTOMER COUNT FOR ALL STATES SERVED","TRANSPORTATION NET METERING CUSTOMER COUNT FOR ALL STATES SERVED","NET METERING CUSTOMER COUNT FOR ALL STATES SERVED"  

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

TRANSPORTATIONPHOTOVOLTAIC NET METERING CUSTOMER COUNT","TOTAL PHOTOVOLTAIC NET METERING CUSTOMER COUNT","RESIDENTIAL WIND ELECTRIC ENERGY SOLD BACK (MWh)","COMMERCIAL WIND ELECTRIC ENERGY SOLD BACK (MWh)","INDUSTRIAL WIND ELECTRIC ENERGY SOLD BACK (MWh)","TRANSPORTATION WIND ELECTRIC ENERGY SOLD BACK (MWh)","TOTAL WIND ELECTRIC ENERGY SOLD BACK (MWh)","RESIDENTIAL WIND INSTALLED NET METERING CAPACITY (MW)","COMMERCIAL WIND INSTALLED NET METERING CAPACITY (MW)","INDUSTRIAL WIND INSTALLED NET METERING CAPACITY (MW)","TRANSPORTATION WIND INSTALLED NET METERING CAPACITY (MW)","TOTAL WIND INSTALLED NET METERING CAPACITY (MW)","RESIDENTIAL WIND NET METERING CUSTOMER COUNT","COMMERCIAL WIND NET METERING CUSTOMER COUNT","INDUSTRIAL WIND NET METERING CUSTOMER COUNT","TRANSPORTATION WIND NET METERING CUSTOMER COUNT","TOTAL WIND NET METERING CUSTOMER COUNT","RESIDENTIAL OTHER ELECTRIC ENERGY SOLD BACK (MWh)","COMMERCIAL OTHER ELECTRIC ENERGY SOLD BACK (MWh)","INDUSTRIAL OTHER ELECTRIC ENERGY SOLD BACK (MWh)","TRANSPORTATION OTHER ELECTRIC ENERGY SOLD BACK (MWh)","TOTAL OTHER ELECTRIC ENERGY SOLD BACK (MWh)","RESIDENTIAL OTHER INSTALLED NET METERING CAPACITY (MW)","COMMERCIAL OTHER INSTALLED NET METERING CAPACITY (MW)","INDUSTRIAL OTHER INSTALLED NET METERING CAPACITY (MW)","TRANSPORTATION OTHER INSTALLED NET METERING CAPACITY (MW)","TOTAL OTHER INSTALLED NET METERING CAPACITY (MW)","RESIDENTIAL OTHER NET METERING CUSTOMER COUNT","COMMERCIAL OTHER NET METERING CUSTOMER COUNT","INDUSTRIAL OTHER NET METERING CUSTOMER COUNT","TRANSPORTATION OTHER NET METERING CUSTOMER COUNT","TOTAL OTHER NET METERING CUSTOMER COUNT","RESIDENTIAL TOTAL ENERGY SOLD BACK TO THE UTILITY (MWh)","COMMERCIAL TOTAL ELECTRIC ENERGY SOLD BACK (MWh)","INDUSTRIAL TOTAL ELECTRIC ENERGY SOLD BACK (MWh)","TRANSPORTATION TOTAL ELECTRIC ENERGY SOLD BACK (MWh)","TOTAL ELECTRIC ENERGY SOLD BACK (MWh)","RESIDENTIAL TOTAL INSTALLED NET METERING CAPACITY (MW)","COMMERCIAL TOTAL INSTALLED NET METERING CAPACITY (MW)","INDUSTRIAL TOTAL INSTALLED NET METERING CAPACITY (MW)","TRANSPORTATION TOTAL INSTALLED NET METERING CAPACITY (MW)","TOTAL INSTALLED NET METERING CAPACITY (MW)","RESIDENTIAL TOTAL NET METERING CUSTOMER COUNT","COMMERCIAL TOTAL NET METERING CUSTOMER COUNT","INDUSTRIAL TOTAL NET METERING CUSTOMER COUNT","TRANSPORTATION TOTAL NET METERING CUSTOMER COUNT","TOTAL NET METERING CUSTOMER COUNT","RESIDENTIAL ELECTRIC ENERGY SOLD BACK TO THE UTILITY FOR ALL STATES SERVED(MWh)","COMMERCIAL ELECTRIC ENERGY SOLD BACK TO THE UTILITY FOR ALL STATES SERVED(MWh)","INDUSTRIAL ELECTRIC ENERGY SOLD BACK TO THE UTILITY FOR ALL STATES SERVED(MWh)","TRANSPORTATION ELECTRIC ENERGY SOLD BACK TO THE UTILITY FOR ALL STATES SERVED(MWh)","TOTAL ELECTRIC ENERGY SOLD BACK TO THE UTILITYFOR ALL STATES SERVED(MWh)","RESIDENTIAL INSTALLED NET METERING CAPACITY FOR ALL STATES SERVED(MW)","COMMERCIAL INSTALLED NET METERING CAPACITY FOR ALL STATES SERVED(MW)","INDUSTRIAL INSTALLED NET METERING CAPACITY FOR ALL STATES SERVED(MW)","TRANSPORTATION INSTALLED NET METERING CAPACITY FOR ALL STATES SERVED(MW)","INSTALLED NET METERING CAPACITY FOR ALL STATES SERVED(MW)","RESIDENTIAL NET METERING CUSTOMER COUNT FOR ALL STATES SERVED","COMMERCIAL NET METERING CUSTOMER COUNT FOR ALL STATES SERVED","INDUSTRIAL NET METERING CUSTOMER COUNT FOR ALL STATES SERVED","TRANSPORTATION NET METERING CUSTOMER COUNT FOR ALL STATES SERVED","NET METERING CUSTOMER COUNT FOR ALL STATES SERVED"

473

Space Heating Scenarios for Ontario: a Demonstration of the Statistics Canada Household Model  

Science Journals Connector (OSTI)

ABSTRACT This paper describes the analytical and simulation capabilities of the currently implemented version of the household model developed by the Structural Analysis Division, Statistics Canada. The household model, as described in A Design Framework for Long Term Energy Economic Analysis of Dwelling Related Demand [1], is a simulation framework and related data base of the Canadian housing stocks, residential construction, and end-use energy consumption in the residential sector. The purpose of the model is to provide an analytical tool for evaluating a variety of residential energy conservation strategies including insulation retrofitting and the introduction of new building standards, the possibilities for fuel substitution afforded by equipment retrofitting, and the impact of new technologies for space conditioning with respect to impacts on residential energy requirements and construction materials over time. The simulation results for Ontario that are presented in the paper are for demonstration purposes only and do not constitute a forecast. The choice of Ontario was arbitrary; similar calculations can be performed for other provinces, for Canada as a whole, and for selected subprovincial regions. At the time of preparation of this paper, the population and household formation block at the national level, the housing stock block, and the space heating part of the space conditioning block are implemented. Therefore simulation results are limited to these areas.

R.H.H. Moll; K.H. Dickinson

1982-01-01T23:59:59.000Z

474

Inefficient subsidy in Nigerian oil sector; implications for revenue generation and household welfare in Nigeria  

Science Journals Connector (OSTI)

Subsidy exists when consumers are assisted by the government to pay less than the prevailing market price of a given commodity. In respect of fuel subsidy, it means that consumers would pay below the market price per litre of petroleum product. This paper is aim at analysing the effects of the increase in energy prices on the social welfare of Nigerian households and comparing the consequences with the condition in which in concurrence with increase in energy prices, the government undertakes transfer payments to Nigerian households in order to protect their social welfare status. An analytical reasoning model was adopted and within the framework of this model the effects of increase in energy price on social welfare is discussed. Decrease in energy subsidies and a shift towards market prices will result in a lower budget deficit for the government and powerfully harness one of the main causes of inflation. However, if the elimination of subsidies be accompanied by transfer payments to households, the result is increase in the government budget deficit which in its turn will enhance inflation thus very negatively affecting social welfare.

Benjamin Anabori Mmadu; David Chuks Akan

2013-01-01T23:59:59.000Z

475

Intra-Household Inequality in Transitional Russia Ekaterina Kalugina  

E-Print Network [OSTI]

1 Intra-Household Inequality in Transitional Russia Ekaterina Kalugina Natalia Radtchenko Catherine and satisfaction. Using two different subjective questions of the Russian data RLMS (Russia Longitudinal Monitoring and social changes in Russia, we investigate the dynamics of household behavior. Keywords: subjective data

Paris-Sud XI, Université de

476

Controlling Households' Drilling Fever in France: an economic modeling approach  

E-Print Network [OSTI]

to generate environmental benefits through reducing water use, has produced economic incentives for households; France; households; domestic boreholes; tube well; water pricing. Author-produced version Fourth World negative environmental impact of water price increase in the drinking water sector. Using primary data

Boyer, Edmond

477

Exploring alternative symmetry breaking mechanisms at the LHC with 7, 8 and 10 TeV total energy  

E-Print Network [OSTI]

In view of the annnouncement that in 2012 the LHC will run at 8 TeV, we study the possibility of detecting signals of alternative mechanisms of ElectroWeak Symmetry Breaking, described phenomenologically by unitarized models, at energies lower than 14 TeV. A complete calculation with six fermions in the final state is performed using the PHANTOM event generator. Our results indicate that at 8 TeV some of the scenarios with TeV scale resonances are likely to be identified while models with no resonances or with very heavy ones will be inaccessible, unless the available luminosity will be much higher than expected.

Alessandro Ballestrero; Diogo Buarque Franzosi; Ezio Maina

2012-03-13T23:59:59.000Z

478

Assimilation and differences between the settlement patterns of individual immigrants and immigrant households  

Science Journals Connector (OSTI)

...delineate directions for future household-scale investigations of...Categorization: Individuals or Households? The concentration on the...individual bodies. Of course, household structure and geographic context...children compared with non-Hispanic white children hinge on such...

Mark Ellis; Richard Wright

2005-01-01T23:59:59.000Z

479

Efficient Use of Commercial Lists in U.S. Household Sampling  

Science Journals Connector (OSTI)

......educational attainment, Hispanic ethnicity, household income, and home tenure...on the two persons in the household as well as the Hispanic ethnicity status of the head of household (assuming that the Hispanic ethnicity status of persons......

Richard Valliant; Frost Hubbard; Sunghee Lee; Chiungwen Chang

2014-06-01T23:59:59.000Z

480

A theoretical and simulation-based examination of household vehicle choice through an adoption perspective  

E-Print Network [OSTI]

=2 Senior h =3 Table 17: Japan household income distributionto 2005 Japan Census (millions of households)). CHAPTER 5.same shifts of household dynamics as Japan (i.e. lower birth

Liu, Jenny Hsing-I

2010-01-01T23:59:59.000Z

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