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1

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...

2

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

3

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.

4

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

5

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

6

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

7

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

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

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...

10

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

11

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

12

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

13

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...

14

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...

15

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

16

The impact of retirement on household consumption in Japan  

Science Journals Connector (OSTI)

Using monthly data from the Japanese Family Income and Expenditure Survey, we examine the impact of retirement on household consumption. We find little evidence of an immediate change in consumption at retirement, on average, in Japan. However, we find a decrease in consumption at retirement for low income households that is concentrated in food and work-related consumption. The availability of substantial retirement bonuses to a large share of Japanese retirees may help smooth consumption at retirement. We find that those households that are more likely to receive such bonuses experience a short-run consumption increase at retirement. However, among households that are less likely to receive a retirement bonus, we find that consumption decreases at retirement.

Melvin Stephens Jr.; Takashi Unayama

2012-01-01T23:59:59.000Z

17

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

18

Smoothing consumption across households and time : essays in development economics  

E-Print Network [OSTI]

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

Kinnan, Cynthia Georgia

2010-01-01T23:59:59.000Z

19

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

20

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

Note: This page contains sample records for the topic "baseline household consumption" 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

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

22

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.

23

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

24

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.

25

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

26

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

27

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

28

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

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

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

29

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

30

Baseline projections of transportation energy consumption by mode: 1981 update  

SciTech Connect (OSTI)

A comprehensive set of activity and energy-demand projections for each of the major transportation modes and submodes is presented. Projections are developed for a business-as-usual scenario, which provides a benchmark for assessing the effects of potential conservation strategies. This baseline scenario assumes a continuation of present trends, including fuel-efficiency improvements likely to result from current efforts of vehicle manufacturers. Because of anticipated changes in fuel efficiency, fuel price, modal shifts, and a lower-than-historic rate of economic growth, projected growth rates in transportation activity and energy consumption depart from historic patterns. The text discusses the factors responsible for this departure, documents the assumptions and methodologies used to develop the modal projections, and compares the projections with other efforts.

Millar, M; Bunch, J; Vyas, A; Kaplan, M; Knorr, R; Mendiratta, V; Saricks, C

1982-04-01T23:59:59.000Z

31

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

32

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

33

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

34

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...

35

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

36

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

37

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

38

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

39

The causes of Japan's lost decade: The role of household consumption  

Science Journals Connector (OSTI)

In this paper, I analyze the causes of the prolonged slowdown of the Japanese economy in the 1990s and find that the stagnation of investment, especially private fixed investment, was the primary culprit. I then investigate the causes of the stagnation of household consumption during the 1990s and find that the stagnation of household disposable income, the decline in household wealth, and increased uncertainty about the future are among the contributing factors. Finally, I consider whether demand side factors or supply side factors were more important as causes of the prolonged slowdown of the Japanese economy in the 1990s and conclude that the former (especially misguided government policies) were probably more important.

Charles Yuji Horioka

2006-01-01T23:59:59.000Z

40

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

Note: This page contains sample records for the topic "baseline household consumption" 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

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

42

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

43

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

44

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

45

Collecting program planning and evaluation data from low-income, minority households: A case study baseline survey  

SciTech Connect (OSTI)

As part of the Wisconsin Demand Side Demonstrations (WDSD) collaborative effort, Wisconsin Electric Power Company (WEPCo) is implementing a direct-install lighting program in two minority low-income communities in Milwaukee, Wisconsin. One of the communities has a very high proportion of Hispanic residents, many of whom speak only Spanish, while the other is a predominantly African-American neighborhood. This demonstration is designed to test the use of community based organizations (CBOs) to contact, market and recruit program participants. As a matter of policy WDSD requires that all programs be evaluated and that whenever feasible, baseline studies be conducted. This paper describes the methods used to conduct the baseline studies in these neighborhoods. The methods are important for evaluators because they demonstrate a very effective way of surveying a hard to reach population. They may also be useful for marketers and program staff who may find the approach useful for working with similar populations. The methods presented in this paper resulted in a 94% completion rate for a baseline survey that averaged twenty-two minutes. The survey probed household activities, appliance mix, appliance use, and community social activities. The paper demonstrates what can be achieved in minority communities when resources located in the neighborhoods are mobilized to obtain market, program or evaluation information.

Hall, N. [RCG/Hagler, Bailly, Inc., Madison, WI (United States); Wintersberger, J. [Wisconsin Electric Power Co., Milwaukee, WI (United States); Reed, J.; Maggiore, A.; Pinkowski, C. [Wisconsin Demand Side Demonstration, Inc., Madison, WI (United States)

1994-11-01T23:59:59.000Z

46

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

47

On the consumption insurance effects of long-term care insurance in Japan: Evidence from micro-level household data  

Science Journals Connector (OSTI)

Using micro-level household data in the 2001 Comprehensive Survey of the Living Conditions of the People on Health and Welfare compiled by the Japanese Ministry of Health, Labor and Welfare, this paper examines how having a household member in need of long-term nursing care can result in welfare losses measured in terms of consumption. In so doing, this study evaluates the role of the public long-term care insurance scheme implemented in Japan in April 2000. The results indicate that when households include a disabled family member, household consumption net of long-term care costs do not decrease as much as before the introduction of long-term care insurance. Further, when compared with the surveys conducted in 1998, the adverse effects on consumption net of long-term care costs have become much weaker. These findings suggest that the introduction of social insurance in 2000 helped Japanese households to reduce the welfare losses associated with a disabled family member.

Yasushi Iwamoto; Miki Kohara; Makoto Saito

2010-01-01T23:59:59.000Z

48

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

49

Household activities through various lenses: crossing surveys, diaries and electric consumption  

E-Print Network [OSTI]

comparison between electricity consumption and behavioralU.S. residential electricity consumption Energy Policy, 42(of the residential electricity consumption. Energy Policy,

Durand-Daubin, Mathieu

2013-01-01T23:59:59.000Z

50

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

E-Print Network [OSTI]

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

Segtnan, Ida Lund

2011-01-01T23:59:59.000Z

51

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

52

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

53

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

54

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

55

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

56

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.

57

Modelling household electricity consumption.  

E-Print Network [OSTI]

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

de la Rue, Philip Martin

2010-01-01T23:59:59.000Z

58

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

59

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

60

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

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


61

Assumptions to the Annual Energy Outlook - 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

62

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

63

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...

64

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...

65

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...

66

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

67

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

68

Tanzania Roads Evaluation - Baseline | Data.gov  

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

Tanzania Roads Evaluation - Baseline Tanzania Roads Evaluation - Baseline Agriculture Community Menu DATA APPS EVENTS DEVELOPER STATISTICS COLLABORATE ABOUT Agriculture You are here Data.gov » Communities » Agriculture » Data Tanzania Roads Evaluation - Baseline Dataset Summary Description Baseline survey for impact evaluation of MCC's roads improvement investments in Tanzania. The evaluation will examine the project's household- and community-level effects on local standards of living along the roads. For the evaluation of major roads on the mainland, Economic Development Initiatives conducted a survey of 3,000 households in 200 communities in 2009. For the Pemba rural roads evaluation, Economic Development Initiatives conducted a survey on 570 households in the treatment group and 630 households in the comparison group.

69

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

70

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

71

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

72

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

73

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

74

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

75

Energy Intensity Baselining and Tracking Guidance  

Broader source: Energy.gov [DOE]

The Energy Intensity Baselining and Tracking Guidance for the Better Buildings, Better Plants Program helps companies meet the programs reporting requirements by describing the steps necessary to develop an energy consumption and energy intensity baseline and calculating consumption and intensity changes over time.

76

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

77

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

78

US SoAtl GA Site Consumption  

Gasoline and Diesel Fuel Update (EIA)

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

79

US SoAtl GA Site Consumption  

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

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

80

US ENC IL Site Consumption  

Gasoline and Diesel Fuel Update (EIA)

IL IL Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US ENC IL Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 2,000 4,000 6,000 8,000 10,000 12,000 US ENC IL Site Consumption kilowatthours $0 $250 $500 $750 $1,000 $1,250 $1,500 US ENC IL Expenditures dollars ELECTRICITY ONLY average per household * Illinois households use 129 million Btu of energy per home, 44% more than the U.S. average. * High consumption, combined with low costs for heating fuels compared to states with a similar climate, result in Illinois households spending 2% more for energy than the U.S. average. * Less reliance on electricity for heating, as well as cool summers keeps average site electricity consumption in the state low relative to other parts of the U.S.

Note: This page contains sample records for the topic "baseline household consumption" 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

US ENC IL Site Consumption  

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

IL IL Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US ENC IL Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 2,000 4,000 6,000 8,000 10,000 12,000 US ENC IL Site Consumption kilowatthours $0 $250 $500 $750 $1,000 $1,250 $1,500 US ENC IL Expenditures dollars ELECTRICITY ONLY average per household * Illinois households use 129 million Btu of energy per home, 44% more than the U.S. average. * High consumption, combined with low costs for heating fuels compared to states with a similar climate, result in Illinois households spending 2% more for energy than the U.S. average. * Less reliance on electricity for heating, as well as cool summers keeps average site electricity consumption in the state low relative to other parts of the U.S.

82

US ENC MI Site Consumption  

Gasoline and Diesel Fuel Update (EIA)

MI MI Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US ENC MI Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 2,000 4,000 6,000 8,000 10,000 12,000 US ENC MI Site Consumption kilowatthours $0 $250 $500 $750 $1,000 $1,250 $1,500 US ENC MI Expenditures dollars ELECTRICITY ONLY average per household * Michigan households use 123 million Btu of energy per home, 38% more than the U.S. average. * High consumption, combined with low costs for heating fuels compared to states with a similar climate, result in Michigan households spending 6% more for energy than the U.S. average. * Less reliance on electricity for heating, as well as cool summers keeps average site electricity consumption in the state low relative to other parts of the U.S.

83

US ENC MI Site Consumption  

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

MI MI Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US ENC MI Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 2,000 4,000 6,000 8,000 10,000 12,000 US ENC MI Site Consumption kilowatthours $0 $250 $500 $750 $1,000 $1,250 $1,500 US ENC MI Expenditures dollars ELECTRICITY ONLY average per household * Michigan households use 123 million Btu of energy per home, 38% more than the U.S. average. * High consumption, combined with low costs for heating fuels compared to states with a similar climate, result in Michigan households spending 6% more for energy than the U.S. average. * Less reliance on electricity for heating, as well as cool summers keeps average site electricity consumption in the state low relative to other parts of the U.S.

84

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

85

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...

86

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

87

US ENC WI Site Consumption  

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

120 120 US ENC WI Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US ENC WI Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 2,000 4,000 6,000 8,000 10,000 12,000 US ENC WI Site Consumption kilowatthours $0 $300 $600 $900 $1,200 $1,500 US ENC WI Expenditures dollars ELECTRICITY ONLY average per household * Wisconsin households use 103 million Btu of energy per home, 15% more than the U.S. average. * Lower electricity and natural gas rates compared to states with a similar climate, such as New York, result in households spending 5% less for energy than the U.S. average. * Less reliance on electricity for heating, as well as cool summers, keeps average site electricity consumption in the state low relative to other parts of the U.S.

88

US ENC WI Site Consumption  

Gasoline and Diesel Fuel Update (EIA)

120 120 US ENC WI Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US ENC WI Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 2,000 4,000 6,000 8,000 10,000 12,000 US ENC WI Site Consumption kilowatthours $0 $300 $600 $900 $1,200 $1,500 US ENC WI Expenditures dollars ELECTRICITY ONLY average per household * Wisconsin households use 103 million Btu of energy per home, 15% more than the U.S. average. * Lower electricity and natural gas rates compared to states with a similar climate, such as New York, result in households spending 5% less for energy than the U.S. average. * Less reliance on electricity for heating, as well as cool summers, keeps average site electricity consumption in the state low relative to other parts of the U.S.

89

US WSC TX Site Consumption  

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

WSC TX WSC TX Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US WSC TX Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 4,000 8,000 12,000 16,000 US WSC TX Site Consumption kilowatthours $0 $500 $1,000 $1,500 $2,000 US WSC TX Expenditures dollars ELECTRICITY ONLY average per household * Texas households consume an average of 77 million Btu per year, about 14% less than the U.S. average. * Average electricity consumption per Texas home is 26% higher than the national average, but similar to the amount used in neighboring states. * The average annual electricity cost per Texas household is $1,801, among the highest in the nation, although similar to other warm weather states like Florida. * Texas homes are typically newer, yet smaller in size, than homes in other parts of

90

US WSC TX Site Consumption  

Gasoline and Diesel Fuel Update (EIA)

WSC TX WSC TX Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US WSC TX Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 4,000 8,000 12,000 16,000 US WSC TX Site Consumption kilowatthours $0 $500 $1,000 $1,500 $2,000 US WSC TX Expenditures dollars ELECTRICITY ONLY average per household * Texas households consume an average of 77 million Btu per year, about 14% less than the U.S. average. * Average electricity consumption per Texas home is 26% higher than the national average, but similar to the amount used in neighboring states. * The average annual electricity cost per Texas household is $1,801, among the highest in the nation, although similar to other warm weather states like Florida. * Texas homes are typically newer, yet smaller in size, than homes in other parts of

91

US ESC TN Site Consumption  

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

ESC TN ESC TN Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US ESC TN Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 4,000 8,000 12,000 16,000 US ESC TN Site Consumption kilowatthours $0 $400 $800 $1,200 $1,600 US ESC TN Expenditures dollars ELECTRICITY ONLY average per household * Tennessee households consume an average of 79 million Btu per year, about 12% less than the U.S. average. * Average electricity consumption for Tennessee households is 33% higher than the national average and among the highest in the nation, but spending for electricity is closer to average due to relatively low electricity prices. * Tennessee homes are typically newer, yet smaller in size, than homes in other parts of the country.

92

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

93

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.

94

2003 Commercial Buildings Energy Consumption - What is an RSE  

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

Home > Households, Buildings & Industry > Commercial Buildings Energy Consumption Survey (CBECS) > 2003 Detailed Tables > What is an RSE? What is an RSE? The estimates in the...

95

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

96

Public perceptions of energy consumption and savings  

E-Print Network [OSTI]

Public perceptions of energy consumption and savings Shahzeen Z. Attaria,1 , Michael L. De consumption and savings for a variety of household, transportation, and recycling activities. When asked, with 98% of US emissions attributed to energy consumption (2). According to Pacala and Socolow (3

Kammen, Daniel M.

97

US WNC MO Site Consumption  

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

WNC MO WNC MO Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US WNC MO Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 3,000 6,000 9,000 12,000 15,000 US WNC MO Site Consumption kilowatthours $0 $300 $600 $900 $1,200 $1,500 US WNC MO Expenditures dollars ELECTRICITY ONLY average per household * Missouri households consume an average of 100 million Btu per year, 12% more than the U.S. average. * Average household energy costs in Missouri are slightly less than the national average, primarily due to historically lower residential electricity prices in the state. * Missouri homes are typically larger than homes in other states and are more likely to be attached or detached single-family housing units.

98

US Mnt(N) CO Site Consumption  

Gasoline and Diesel Fuel Update (EIA)

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

99

US Mnt(N) CO Site Consumption  

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

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

100

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

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


101

HOUSEHOLD 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

102

Consumption & Efficiency - Data - U.S. Energy Information Administration  

Gasoline and Diesel Fuel Update (EIA)

Consumption & Efficiency Consumption & Efficiency Glossary › FAQS › Overview Data Residential Energy Consumption Survey Data Commercial Energy Consumption Survey Data Manufacturing Energy Consumption Survey Data Vehicle Energy Consumption Survey Data Energy Intensity Consumption Summaries Average cost of fossil-fuels for electricity generation All Consumption & Efficiency Data Reports Analysis & Projections All Sectors Commercial Buildings Efficiency Manufacturing Projections Residential Transportation All Reports Find statistics on energy consumption and efficiency across all fuel sources. + EXPAND ALL Residential Energy Consumption Survey Data Household characteristics Release Date: March 28, 2011 Survey data for occupied primary housing units. Residential Energy Consumption Survey (RECS)

103

US SoAtl VA Site Consumption  

Gasoline and Diesel Fuel Update (EIA)

SoAtl VA SoAtl VA Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US SoAtl VA Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 4,000 8,000 12,000 16,000 US SoAtl VA Site Consumption kilowatthours $0 $300 $600 $900 $1,200 $1,500 $1,800 US SoAtl VA Expenditures dollars ELECTRICITY ONLY average per household * Virginia households consume an average of 86 million Btu per year, about 4% less than the U.S. average. * Average electricity consumption and costs are higher for Virginia households than the national average, but similar to those in neighboring states where electricity is the most common heating fuel. * Virginia homes are typically newer and larger than homes in other parts of the country. CONSUMPTION BY END USE

104

US Mnt(S) AZ Site Consumption  

Gasoline and Diesel Fuel Update (EIA)

Mnt(S) AZ Mnt(S) AZ Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US Mnt(S) AZ Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 3,000 6,000 9,000 12,000 15,000 US Mnt(S) AZ Site Consumption kilowatthours $0 $500 $1,000 $1,500 $2,000 US Mnt(S) AZ Expenditures dollars ELECTRICITY ONLY average per household * Arizona households use 66 million Btu of energy per home, 26% less than the U.S. average. * The combination of lower than average site consumption of all energy, but above average electricity which is relatively expensive, results in Arizona households spending 3% less for energy than the U.S. average. * More reliance on air conditioning keeps average site electricity consumption in the state high relative to other parts of the U.S.

105

US SoAtl VA Site Consumption  

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

SoAtl VA SoAtl VA Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US SoAtl VA Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 4,000 8,000 12,000 16,000 US SoAtl VA Site Consumption kilowatthours $0 $300 $600 $900 $1,200 $1,500 $1,800 US SoAtl VA Expenditures dollars ELECTRICITY ONLY average per household * Virginia households consume an average of 86 million Btu per year, about 4% less than the U.S. average. * Average electricity consumption and costs are higher for Virginia households than the national average, but similar to those in neighboring states where electricity is the most common heating fuel. * Virginia homes are typically newer and larger than homes in other parts of the country. CONSUMPTION BY END USE

106

US Mnt(S) AZ Site Consumption  

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

Mnt(S) AZ Mnt(S) AZ Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US Mnt(S) AZ Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 3,000 6,000 9,000 12,000 15,000 US Mnt(S) AZ Site Consumption kilowatthours $0 $500 $1,000 $1,500 $2,000 US Mnt(S) AZ Expenditures dollars ELECTRICITY ONLY average per household * Arizona households use 66 million Btu of energy per home, 26% less than the U.S. average. * The combination of lower than average site consumption of all energy, but above average electricity which is relatively expensive, results in Arizona households spending 3% less for energy than the U.S. average. * More reliance on air conditioning keeps average site electricity consumption in the state high relative to other parts of the U.S.

107

2001 Residential Energy Consumption Survey Answers to Frequently Asked Questions  

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

D (2001) -- Household Bottled Gas (LPG or Propane) Usage Form D (2001) -- Household Bottled Gas (LPG or Propane) Usage Form OMB No. 1905-0092, Expiring February 29, 2004 2001 Residential Energy Consumption Survey Answers to Frequently Asked Questions About the Household Bottled Gas (LPG or Propane) 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

108

Methods to Develop Energy Baselines for California's  

E-Print Network [OSTI]

and implement land use and transportation policies designed to reduce energy consumption and its negative Program, Transportation Research Office Phone: 9163271315 Email: dgallagh@energy.state.ca.us DrMethods to Develop Energy Baselines for California's Regions Transportation Energy Research PIER

109

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

110

US NE MA Site Consumption  

Gasoline and Diesel Fuel Update (EIA)

NE MA NE MA Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 $3,000 US NE MA Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 2,000 4,000 6,000 8,000 10,000 12,000 US NE MA Site Consumption kilowatthours $0 $250 $500 $750 $1,000 $1,250 $1,500 US NE MA Expenditures dollars ELECTRICITY ONLY average per household * Massachusetts households use 109 million Btu of energy per home, 22% more than the U.S. average. * The higher than average site consumption results in households spending 22% more for energy than the U.S. average. * Less reliance on electricity for heating, as well as cool summers, keeps average site electricity consumption in the state low relative to other parts of the U.S. However, spending on electricity is closer to the national average due to higher

111

US NE MA Site Consumption  

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

NE MA NE MA Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 $3,000 US NE MA Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 2,000 4,000 6,000 8,000 10,000 12,000 US NE MA Site Consumption kilowatthours $0 $250 $500 $750 $1,000 $1,250 $1,500 US NE MA Expenditures dollars ELECTRICITY ONLY average per household * Massachusetts households use 109 million Btu of energy per home, 22% more than the U.S. average. * The higher than average site consumption results in households spending 22% more for energy than the U.S. average. * Less reliance on electricity for heating, as well as cool summers, keeps average site electricity consumption in the state low relative to other parts of the U.S. However, spending on electricity is closer to the national average due to higher

112

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

113

Baseline Rd. Colorado Ave.  

E-Print Network [OSTI]

Baseline Rd. Broadway Broadway Colorado Ave. Arapahoe Ave. Canyon Blvd. 28thSt. 9thSt. 6thSt. 13th Pearl St. Euclid FolsomSt. N Baseline Rd. Broadway Broadway Colorado Ave. Arapahoe Ave. Canyon Blvd. 28://www.banjobilly.com JUNE 12-13, 2009 JILA/CHEMISTRY & BIOCHEMISTRY, UNIVERSITY OF COLORADO, BOULDER A CELEBRATION OF 40

Lineberger, W. Carl

114

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

115

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

116

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

117

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

118

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

119

Experimental results of a household automatic icemaker in a refrigerator/freezer  

SciTech Connect (OSTI)

This paper describes the performance test results of an automatic icemaker refrigerator under various modes of icemaker operation. The tests were conducted on a 20-ft{sup 3} (0.566-m{sup 3}) household refrigerator that had a single forced convection evaporator and was charged with R-12. The focus of the research was to ascertain the effect of icemaker operation on the refrigerator`s daily energy consumption. Thus, three different types of tests were conducted, depending upon the icemaker`s operating mode. In the first test type, the baseline, the automatic icemaker was turned off and no ice was made. In the second test type, the ice-making mode (test A), the icemaker was turned on and ice was continuously made. Compared to the baseline, additional power was intermittently consumed by a mold heater that melts the ice cubes` interface with the tray, a solenoid valve that supplies water to the icemaker tray, and a motor that rotates the ejector blades to press the crescent-shaped ice cubes out of the mold and unload them into an ice bin. In the third test type, the failure mode (test B), the water supply was manually disconnected but the icemaker was left turned on. Even though no ice was made, additional power was still consumed by the mold heater, the solenoid valve, and the motorized ejector. In tests A and B, the energy consumed by the icemaker`s components increases the cooling load, which raises the compressor power consumption. The present study shows that at the AHAM-specified test conditions, uninterrupted icemaking increased the daily energy consumption by 22.5% to 27.2%.

Haider, I.; Feng, H.; Radermacher, R. [Univ. of Maryland, College Park, MD (United States). Center for Environmental Energy Engineering

1996-12-31T23:59:59.000Z

120

Transportation Baseline Schedule  

SciTech Connect (OSTI)

The 1999 National Transportation Program - Transportation Baseline Report presents data that form a baseline to enable analysis and planning for future Department of Energy (DOE) Environmental Management (EM) waste/material transportation. The companion 1999 Transportation Barriers Analysis analyzes the data and identifies existing and potential problems that may prevent or delay transportation activities based on the data presented. The 1999 Transportation Baseline Schedule (this report) uses the same data to provide an overview of the transportation activities of DOE EM waste/materials. This report can be used to identify areas where stakeholder interface is needed, and to communicate to stakeholders the quantity/schedule of shipments going through their area. Potential bottlenecks in the transportation system can be identified; the number of packages needed, and the capacity needed at receiving facilities can be planned. This report offers a visualization of baseline DOE EM transportation activities for the 11 major sites and the Geologic Repository Disposal site (GRD).

Fawcett, Ricky Lee; John, Mark Earl

2000-01-01T23:59:59.000Z

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


121

Household Vehicles Energy 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 *...

122

"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

123

Journal: Ecological Applications1 Carbon, nitrogen, and phosphorus fluxes in household ecosystems in the3  

E-Print Network [OSTI]

#12;1 Journal: Ecological Applications1 2 Carbon, nitrogen, and phosphorus fluxes in household Resources Center, Saint Paul, MN 551089 3 University of Minnesota, Department of Ecology, Evolution with several29 components of household activities including air and motor vehicle travel, food consumption,30

Minnesota, University of

124

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

125

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

126

Pervasive Externalities at the Population, Consumption, and Environment Nexus  

Science Journals Connector (OSTI)

...size and n* the average family size of the...equilibrium, the average of all the households...hand, nor is wood fuel easily accessible...recede. The relative prices of alternative...denoted by X: the average consumption level of...N is large, the effect of household hs choice...

Partha S. Dasgupta; Paul R. Ehrlich

2013-04-19T23:59:59.000Z

127

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

128

Energy Consumption  

Science Journals Connector (OSTI)

We investigated the relationship between electrical power consumption per capita and GDP per capita in 130 countries using the data reported by World Bank. We found that an electrical power consumption per capita...

Aki-Hiro Sato

2014-01-01T23:59:59.000Z

129

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

130

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

131

Energy Information Administration - Transportation Energy Consumption by  

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

Energy Consumption Energy Consumption Transportation Energy Consumption Surveys energy used by vehicles EIA conducts numerous energy-related surveys and other information programs. In general, the surveys can be divided into two broad groups: supply surveys, directed to the suppliers and marketers of specific energy sources, that measure the quantities of specific fuels produced for and/or supplied to the market; and consumption surveys, which gather information on the types of energy used by consumer groups along with the consumer characteristics that are associated with energy use. In the transportation sector, EIA's core consumption survey was the Residential Transportation Energy Consumption Survey. RTECS belongs to the consumption group because it collects information directly from the consumer, the household. For roughly a decade, EIA fielded the RTECS--data were first collected in 1983. This survey, fielded for the last time in 1994, was a triennial survey of energy use and expenditures, vehicle miles-traveled (VMT), and vehicle characteristics for household vehicles. For the 1994 survey, a national sample of more than 3,000 households that own or use some 5,500 vehicles provided data.

132

Transportation Baseline Report  

SciTech Connect (OSTI)

The National Transportation Program 1999 Transportation Baseline Report presents data that form a baseline to enable analysis and planning for future Department of Energy (DOE) Environmental Management (EM) waste and materials transportation. In addition, this Report provides a summary overview of DOEs projected quantities of waste and materials for transportation. Data presented in this report were gathered as a part of the IPABS Spring 1999 update of the EM Corporate Database and are current as of July 30, 1999. These data were input and compiled using the Analysis and Visualization System (AVS) which is used to update all stream-level components of the EM Corporate Database, as well as TSD System and programmatic risk (disposition barrier) information. Project (PBS) and site-level IPABS data are being collected through the Interim Data Management System (IDMS). The data are presented in appendices to this report.

Fawcett, Ricky Lee; Kramer, George Leroy Jr.

1999-12-01T23:59:59.000Z

133

US MidAtl PA Site Consumption  

Gasoline and Diesel Fuel Update (EIA)

MidAtl PA MidAtl PA Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 $3,000 US MidAtl PA Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 2,000 4,000 6,000 8,000 10,000 12,000 US MidAtl PA Site Consumption kilowatthours $0 $250 $500 $750 $1,000 $1,250 $1,500 US MidAtl PA Expenditures dollars ELECTRICITY ONLY average per household * Pennsylvania households consume an average of 96 million Btu per year, 8% more than the U.S. average. Pennsylvania residents also spend 16% more than the average U.S. households for energy consumed in their homes. * Average electricity consumption in Pennsylvania homes is 10,402 kWh per year, which is lower than the national average, but 58% more than New York households and 17% more than New Jersey residents.

134

US MidAtl PA Site Consumption  

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

MidAtl PA MidAtl PA Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 $3,000 US MidAtl PA Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 2,000 4,000 6,000 8,000 10,000 12,000 US MidAtl PA Site Consumption kilowatthours $0 $250 $500 $750 $1,000 $1,250 $1,500 US MidAtl PA Expenditures dollars ELECTRICITY ONLY average per household * Pennsylvania households consume an average of 96 million Btu per year, 8% more than the U.S. average. Pennsylvania residents also spend 16% more than the average U.S. households for energy consumed in their homes. * Average electricity consumption in Pennsylvania homes is 10,402 kWh per year, which is lower than the national average, but 58% more than New York households and 17% more than New Jersey residents.

135

Residential Lighting End-Use Consumption  

Broader source: Energy.gov [DOE]

The U.S. DOE Residential Lighting End-Use Consumption Study aims to improve the understanding of lighting energy usage in U.S. residential dwellings using a regional estimation framework. The framework allows for the estimation of lamp usage and energy consumption 1) nationally and by region of the United States, 2) by certain household characteristics, 3) by location within the home, 4) by certain lamp characteristics, and 5) by certain categorical cross-classifications.

136

Regional Energy Baseline  

E-Print Network [OSTI]

ESL-TR-11-09-02 REGIONAL ENERGY BASELINE (1960 ~ 2009) 0 100 200 300 400 500 600 700 800 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 To tal En erg y U se pe r C ap ita (M MB tu) Year Total Energy... Use per Capita (1960-2009) US SEEC 12-States TX Hyojin Kim Juan-Carlos Baltazar, Ph.D. Jeff S. Haberl, Ph.D., P.E. September 2011 ENERGY SYSTEMS LABORATORY Texas Engineering Experiment Station Texas A&M University...

Kim, H.; Baltazar, J.C.; Haberl, J.

137

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

138

Survey Consumption  

Gasoline and Diesel Fuel Update (EIA)

fsidentoi fsidentoi Survey Consumption and 'Expenditures, April 1981 March 1982 Energy Information Administration Wasningtoa D '" N """"*"""*"Nlwr. . *'.;***** -. Mik>. I This publication is available from ihe your COr : 20585 Residential Energy Consumption Survey: Consum ption and Expendi tures, April 1981 Through March 1982 Part 2: Regional Data Prepared by: Bruce Egan This report was prepared by the Energy Information Administra tion, the independent statistical

139

Residential Energy Consumption Survey (RECS) - Data - U.S. Energy  

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

1997 RECS Survey Data 2009 | 2005 | 2001 | 1997 | 1993 | Previous 1997 RECS Survey Data 2009 | 2005 | 2001 | 1997 | 1993 | Previous Housing Characteristics Consumption & Expenditures Microdata Methodology Housing Characteristics Tables Table Titles (Released: February 2004) Entire Section Percents Tables: HC1 Housing Unit Characteristics, Million U.S. Households PDF PDF NOTE: As of 10/31/01, numbers in the "Housing Units" TABLES section for stub item: "Number of Floors in Apartment Buildings" were REVISED. These numbers will differ from the numbers in the published report. Tables: HC2 Household Characteristics, Million U.S. Households PDF PDF Tables: HC3 Space Heating, Million U.S. Households PDF PDF Tables: HC4 Air-Conditioning, Million U.S. Households PDF PDF Tables: HC5 Appliances, Million U.S. Households PDF PDF

140

Residential Energy Consumption Survey (RECS) - Data - U.S. Energy  

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

3 RECS Survey Data 2009 | 2005 | 2001 | 1997 | 1993 | Previous 3 RECS Survey Data 2009 | 2005 | 2001 | 1997 | 1993 | Previous Housing Characteristics Consumption & Expenditures Microdata Methodology Housing Characteristics Tables Topical Sections Entire Section All Detailed Tables PDF Tables: HC1 Household Characteristics, Million U.S. Households Presents data relating to location, type, ownership, age, size, construction, and householder demographic and income characteristics. PDF Tables: HC2 Space Heating, Million U.S. Households Presents data describing the types of heating fuel and equipment used for main and secondary heating purposes. PDF Tables: HC3 Air-Conditioning, Million U.S. Households Presents data describing selected household characteristics including location, number of rooms and area cooled and air-conditioning usage. PDF

Note: This page contains sample records for the topic "baseline household consumption" 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

Guidance for Developing Baseline and Annual Water Use | Department of  

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

Guidance for Developing Baseline and Annual Water Use Guidance for Developing Baseline and Annual Water Use Guidance for Developing Baseline and Annual Water Use Potable water use intensity is defined as annual potable water use divided by total gross square footage of facility space (gal/ft2). The facility gross square footage is the same value used for energy use intensity reduction goals. Executive Order (E.O.) 13423 requires Federal agencies to develop a potable water use intensity baseline for fiscal year (FY) 2007. Agencies must report total potable water consumption and gross facility square footage against that baseline. To avoid additional reporting requirements, E.O. 13423 does not require agencies to report square footage of irrigated turf or landscape. Potable water used for landscape irrigation must be reported in total potable water

142

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

143

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

144

Re-baselining Report  

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

008 008 DOE/NETL-2008/1308 Re-baselining APS, CS & FC GRPA R&D Goals Impact of Cost Escalation on Power System R&D Goals Disclaimer This report was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference therein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or

145

Tobacco Consumption  

Science Journals Connector (OSTI)

Tobacco consumption is the use of tobacco products in different forms such as , , , water-pipes or tobacco products. Cigarettes and tobacco products containing tobacco are highly engineered so as to creat...

Martina Ptschke-Langer

2008-01-01T23:59:59.000Z

146

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

147

Alcohol Consumption and the Risk for Prostate Cancer in the European Prospective Investigation into Cancer and Nutrition  

Science Journals Connector (OSTI)

...Communications Alcohol Consumption and the Risk for...Welfare and Sports; World Cancer Research...association of alcohol consumption at recruitment...and nonalcohol energy intake. Overall, neither alcohol consumption at baseline nor...

Sabine Rohrmann; Jakob Linseisen; Timothy J. Key; Majken K. Jensen; Kim Overvad; Nina Fns Johnsen; Anne Tjnneland; Rudolf Kaaks; Manuela M. Bergmann; Cornelia Weikert; Androniki Naska; Antonia Trichopoulou; Dimitrios Trichopoulos; Valeria Pala; Carlotta Sacerdote; Domenico Palli; Rosario Tumino; H. Bas Bueno-de-Mesquita; Alina Vrieling; Carlos A. Gonzlez; Nerea Larraaga; Carmen Navarro; Aurelio Barricarte; J. Ramon Quiros; Carmen Martnez-Garca; Gran Hallmans; Pr Stattin; Jonas Manjer; Elisabet Wirflt; Sheila Bingham; Key-Tee Khaw; Lars Egevad; Pietro Ferrari; Mazda Jenab; and Elio Riboli

2008-05-01T23:59:59.000Z

148

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...

149

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

150

US MidAtl NY Site Consumption  

Gasoline and Diesel Fuel Update (EIA)

MidAtl NY MidAtl NY Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 $3,000 US MidAtl NY Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 2,000 4,000 6,000 8,000 10,000 12,000 US MidAtl NY Site Consumption kilowatthours $0 $250 $500 $750 $1,000 $1,250 $1,500 US MidAtl NY Expenditures dollars ELECTRICITY ONLY average per household * New York households consume an average of 103 million Btu per year, 15% more than the U.S. average. * Electricity consumption in New York homes is much lower than the U.S. average, because many households use other fuels for major energy end uses like space heating, water heating, and cooking. Electricity costs are closer to the national average due to higher than average electricity prices in the state.

151

US MidAtl NY Site Consumption  

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

MidAtl NY MidAtl NY Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 $3,000 US MidAtl NY Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 2,000 4,000 6,000 8,000 10,000 12,000 US MidAtl NY Site Consumption kilowatthours $0 $250 $500 $750 $1,000 $1,250 $1,500 US MidAtl NY Expenditures dollars ELECTRICITY ONLY average per household * New York households consume an average of 103 million Btu per year, 15% more than the U.S. average. * Electricity consumption in New York homes is much lower than the U.S. average, because many households use other fuels for major energy end uses like space heating, water heating, and cooking. Electricity costs are closer to the national average due to higher than average electricity prices in the state.

152

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

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

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

153

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

154

CONSUMPTION AND CHANGES IN HOME ENERGY COSTS: HOW PREVALENT IS THE `HEAT OR EAT' DECISION?  

E-Print Network [OSTI]

CONSUMPTION AND CHANGES IN HOME ENERGY COSTS: HOW PREVALENT IS THE `HEAT OR EAT' DECISION?· Julie how household consumption responds to changes in home energy outlays over the course of the year. We specify Euler equations describing nondurable and food consumption and then rely on changes in energy

Sadoulet, Elisabeth

155

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

156

Residential Energy Consumption Survey (RECS) - Data - U.S. Energy  

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

2001 RECS Survey Data 2009 | 2005 | 2001 | 1997 | 1993 | Previous 2001 RECS Survey Data 2009 | 2005 | 2001 | 1997 | 1993 | Previous Housing Characteristics Consumption & Expenditures Microdata Methodology Housing Characteristics Tables + EXPAND ALL Tables HC1: Housing Unit Characteristics, Million U.S. Households PDF (all tables) Climate Zone PDF Year of Construction PDF Household Income PDF Type of Owner-Occupied Housing Unit PDF Four Most Populated States PDF Urban/Rural Location PDF Northeast Census Region PDF Midwest Census Region PDF South Census Region PDF West Census Region PDF Tables HC2: Household Characteristics, Million U.S. Households PDF (all tables) Climate Zone PDF Year of Construction PDF Household Income PDF Type of Housing Unit PDF Type of Owner-Occupied Housing Unit PDF Type of Rented Housing Unit PDF

157

char_household2001.pdf  

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

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

158

char_household2001.pdf  

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

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

159

char_household2001.pdf  

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

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

160

char_household2001.pdf  

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

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

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


161

char_household2001.pdf  

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

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

162

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

163

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

164

Table 5.3. U.S. per Vehicle Miles Traveled, Vehicle Fuel Consumption...  

Gasoline and Diesel Fuel Update (EIA)

Consumption (gallons) Expenditures (dollars) 1.8 1.0 1.0 1.0 0.5 Race of Householder White ... 138.6 11.5 581 670 19.8 1.4 Black...

165

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...

166

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

167

ARM - Baseline Change Request Guidelines  

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

DocumentsBaseline Change Request Guidelines DocumentsBaseline Change Request Guidelines Page Contents Introduction Submit a BCR BCR Process Flowchart Baseline Change Request Guidelines Introduction Baseline Change Requests (BCR) are used by the ARM Infrastructure as a process to provide configuration control and for formally requesting and documenting changes within the ARM Infrastructure. Configuration Control: BCRs are required for changes to instruments, data systems, data processes, datastreams, measurement methods, and facilities. They help ensure that all aspects of the ARM Infrastructure are consulted prior to implementing changes. Seemingly minor changes can have significant repercussions throughout the Facility and therefore, NO change to an operational instrument, computer, facility, or other system can or will be

168

Who is eating seafood? On an annual basis, results from the survey screener showed that 65% of U.S. households purchased  

E-Print Network [OSTI]

Who is eating seafood? On an annual basis, results from the survey screener showed that 65% of U.S. households purchased seafood for at-home consumption at least once in the previous year while 83% of households purchased seafood in a restaurant during the same period. As shown in Figures 1a-c, retail seafood

169

Consumption Behavior in Investment/Consumption Problems  

Science Journals Connector (OSTI)

In this chapter we study the consumption behavior of an agent in the dynamic framework of consumption/investment decision making that allows the presence of a subsistence consumption level and the possibility of ...

E. L. Presman

1997-01-01T23:59:59.000Z

170

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

171

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

172

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

173

9 - Chinese healthcare system reforms and household saving patterns: some stylised facts  

Science Journals Connector (OSTI)

Abstract: This chapter aims to evaluate the relationship between one of the recent healthcare reforms in the Peoples Republic of China and household decisions both in terms of out-of-pocket expenditure and saving. Evidence on the results achieved by reforms of the health insurance sector in terms of reducing out-of-pocket medical expenditure is still uncertain and contradictory, and very little is known about the effect of these measures on the consumption and saving behaviour of the Chinese population. To shed light on this issue we use data collected by Chinese Household Income Project surveys (CHIPs), through a series of questionnaire-based interviews conducted in urban areas in 1995 and 2002. Our descriptive analysis suggests that there is a positive relationship between public health insurance coverage and household saving. This empirical evidence suggests that public insurance coverage is ineffective as a source of protection against income losses and might induce households to save more.

Vincenzo Atella; Agar Brugiavini; Hao Chen; Noemi Pace

2014-01-01T23:59:59.000Z

174

Evaluation of the soft measures' effects on ambient water quality improvement and household and industry economies  

Science Journals Connector (OSTI)

Abstract Various ecological footprint calculators, carbon footprint calculators and water footprint calculators have been developed in recent years. The basic concepts of ecological behaviour record notebooks and of carbon dioxide emission calculators have been developed since the late 20th century. The first carbon dioxide emission calculator was developed in 1991. Likewise, water pollutant discharge calculators have been developed to estimate the effects of soft measures introduced into households to reduce pollutant discharge since 2004. The soft measures which have been developed in Japan may consist of a wider framework, household sustainable consumption, which has been developed in Europe, and can be referred to cleaner consumption. In this research, summarisation of the short history of ecological behaviour record notebooks and ecological footprint calculators in Japan since the 1980s was conducted, and the soft measures in households to reduce pollutant discharge were evaluated for their effects on ambient water quality improvement as well as household and industry economies. Effects of the soft measures on related industry economies were investigated using an InputOutput Tableanalysis and the effects of the imported goods were evaluated with an import effect matrix, which was developed in this research. The effects of the soft measures on household expenditures were estimated to be a decrease by 2.5% or USD 285 person?1year?1 in 20032006. The results show that the soft measures positively affect the chemical fibre industry and significantly affect the detergent industry. Analysis of the import effect matrix proved that the six industries were tightly related through extensive amounts of imported goods. The soft measures in households may lead to household sustainable consumption and thus reduce disadvantageous human impacts on water environments. The effects of the measures introduced to improve the environment should be qualitatively and quantitatively evaluated to avoid redundant concerns and discord between the environment and the economy, which may be worried when the relationship is not well understood.

Yoshiaki Tsuzuki

2014-01-01T23:59:59.000Z

175

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.

176

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

177

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

178

Water Flows in the Spanish Economy: Agri-Food Sectors, Trade and Households Diets in an Input-Output Framework  

Science Journals Connector (OSTI)

Water Flows in the Spanish Economy: Agri-Food Sectors, Trade and Households Diets in an Input-Output Framework ... So although we use the information from a SAM, since we leave as exogenous accounts the household consumption and foreign trade; it is not a traditional SAM analysis, but more an extended input-output analysis. ... The countries concerned are France, Germany, Portugal, Italy, UK, Netherlands, U.S., Belgium, China, and Japan. ...

Ignacio Cazcarro; Rosa Duarte; Julio Snchez-Chliz

2012-05-21T23:59:59.000Z

179

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

180

homeoffice_household2001.pdf  

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

0a. Home Office Equipment by Midwest Census Region, 0a. Home Office Equipment by Midwest Census Region, Million U.S. Households, 2001 Home Office Equipment RSE Column Factor: Total U.S. Midwest Census Region RSE Row Factors Total Census Division East North Central West North Central 0.5 1.0 1.2 1.6 Total .............................................................. 107.0 24.5 17.1 7.4 NE Households Using Office Equipment ......................................... 96.2 22.4 15.7 6.7 1.3 Personal Computers 1 ................................. 60.0 14.1 9.9 4.2 3.7 Number of Desktop PCs 1 ................................................................ 45.1 10.4 7.2 3.2 3.7 2 or more ................................................... 9.1 2.3 1.6 0.7 10.1 Number of Laptop PCs 1 ................................................................

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


181

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

182

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

183

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

184

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

185

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

186

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

187

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

188

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

189

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

190

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

191

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

Gasoline and Diesel Fuel Update (EIA)

What's new in our home energy use? What's new in our home energy use? RECS 2009 - Release date: March 28, 2011 First results from EIA's 2009 Residential Energy Consumption Survey (RECS) The 2009 RECS collected home energy characteristics data from over 12,000 U.S. households. This report highlights findings from the survey, with details presented in the Household Energy Characteristics tables. How we use energy in our homes has changed substantially over the past three decades. Over this period U.S. homes on average have become larger, have fewer occupants, and are more energy-efficient. In 2005, energy use per household was 95 million British thermal units (Btu) of energy compared with 138 million Btu per household in 1978, a drop of 31 percent. Did You Know? Over 50 million U.S. homes have three or more televisions.

192

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

193

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

194

Functional Testing Protocols for Commercial Building Efficiency Baseline Modeling Software  

E-Print Network [OSTI]

Commercial Building Efficiency Baseline Modeling SoftwareCommercial Building Efficiency Baseline Modeling Software ETCommercial Building Energy Baseline Modeling

Jump, David

2014-01-01T23:59:59.000Z

195

Operational energy consumption and GHG emissions in residential sector in urban China : an empirical study in Jinan  

E-Print Network [OSTI]

Driven by rapid urbanization and increasing household incomes, residential energy consumption in urban China has been growing steadily in the past decade, posing critical energy and greenhouse gas emission challenges. ...

Zhang, Jiyang, M.C.P. Massachusetts Institute of Technology

2010-01-01T23:59:59.000Z

196

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

197

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

198

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

199

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

200

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

Note: This page contains sample records for the topic "baseline household consumption" 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

Externality of Consumption  

Science Journals Connector (OSTI)

Externalities of consumption exist if one individual's consumption of agood or service has positive... utility of another person. Apositive externality increases ...

2008-01-01T23:59:59.000Z

202

Environmental Baseline File: National Transportation  

SciTech Connect (OSTI)

This Environmental Baseline File summarizes and consolidates information related to the national-level transportation of commercial spent nuclear fuel. Topics address include: shipmnents of commercial spent nuclear fuel based on mostly truck and mostly rail shipping scenarios; transportation routing for commercial spent nuclear fuel sites and DOE sites; radionuclide inventories for various shipping container capacities; transportation routing; populations along transportation routes; urbanized area population densities; the impacts of historical, reasonably foreseeable, and general transportation; state-level food transfer factors; Federal Guidance Report No. 11 and 12 radionuclide dose conversion factors; and national average atmospheric conditions.

NONE

1999-05-22T23:59:59.000Z

203

Prospective Cohort Study of Green Tea Consumption and Colorectal Cancer Risk in Women  

Science Journals Connector (OSTI)

...ratio, intakes of total energy and red meat, and family...of CRC associated with green tea consumption, the...01 0.004 Years of green tea consumption , 1-23...and intakes of total energy, vegetables, fruits...of CRC associated with green tea consumption at baseline...

Gong Yang; Xiao-Ou Shu; Honglan Li; Wong-Ho Chow; Bu-Tian Ji; Xianglan Zhang; Yu-Tang Gao; and Wei Zheng

2007-06-01T23:59:59.000Z

204

A Consumption-Based GHG Inventory for the U.S. State of Oregon  

Science Journals Connector (OSTI)

A Consumption-Based GHG Inventory for the U.S. State of Oregon ... Many U.S. states conduct greenhouse gas (GHG) inventories to inform their climate change planning efforts. ... Accordingly, a consumption-based perspective opens new opportunities for many states and their local government partners to reduce GHG emissions, such as initiatives to advance lower-carbon public sector or household consumption, that are well within their sphere of influence. ...

Peter Erickson; David Allaway; Michael Lazarus; Elizabeth A. Stanton

2012-03-22T23:59:59.000Z

205

appl_household2001.pdf  

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

9a. Appliances by Northeast Census Region, 9a. Appliances by Northeast Census Region, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total U.S. Northeast Census Region RSE Row Factors Total Census Division Middle Atlantic New England 0.5 1.0 1.3 1.6 Total .............................................................. 107.0 20.3 14.8 5.4 NE Kitchen Appliances Cooking Appliances Oven ......................................................... 101.7 19.6 14.5 5.2 1.1 1 .............................................................. 95.2 18.2 13.3 4.9 1.1 2 or More ................................................. 6.5 1.4 1.1 0.3 11.7 Most Used Oven ...................................... 101.7 19.6 14.5 5.2 1.1 Electric .....................................................

206

spaceheat_household2001.pdf  

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

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

207

spaceheat_household2001.pdf  

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

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

208

spaceheat_household2001.pdf  

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

0a. Space Heating by Midwest Census Region, 0a. Space Heating by Midwest Census Region, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total U.S. Midwest Census Region RSE Row Factors Total Census Division East North Central West North Central 0.5 1.0 1.2 1.6 Total .............................................................. 107.0 24.5 17.1 7.4 NE Heat Home .................................................... 106.0 24.5 17.1 7.4 NE Do Not Heat Home ....................................... 1.0 Q Q Q 19.8 No Heating Equipment ................................ 0.5 Q Q Q 39.2 Have Equipment But Do Not Use It ............................................... 0.4 Q Q Q 38.4 Main Heating Fuel and Equipment (Have and Use Equipment) ........................... 106.0 24.5 17.1 7.4 NE Natural Gas

209

spaceheat_household2001.pdf  

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

2a. Space Heating by West Census Region, 2a. Space Heating by West Census Region, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total U.S. West Census Region RSE Row Factors Total Census Division Mountain Pacific 0.6 1.0 1.6 1.2 Total .............................................................. 107.0 23.3 6.7 16.6 NE Heat Home .................................................... 106.0 22.6 6.7 15.9 NE Do Not Heat Home ....................................... 1.0 0.7 Q 0.7 10.6 No Heating Equipment ................................ 0.5 0.4 Q 0.4 18.1 Have Equipment But Do Not Use It ............................................... 0.4 0.2 Q 0.2 27.5 Main Heating Fuel and Equipment (Have and Use Equipment) ........................... 106.0 22.6 6.7 15.9 NE Natural Gas .................................................

210

appl_household2001.pdf  

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

2a. Appliances by West Census Region, 2a. Appliances by West Census Region, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total U.S. West Census Region RSE Row Factors Total Census Division Mountain Pacific 0.5 1.0 1.7 1.2 Total .............................................................. 107.0 23.3 6.7 16.6 NE Kitchen Appliances Cooking Appliances Oven ......................................................... 101.7 22.1 6.6 15.5 1.1 1 .............................................................. 95.2 20.9 6.4 14.5 1.1 2 or More ................................................. 6.5 1.2 0.2 1.0 14.6 Most Used Oven ...................................... 101.7 22.1 6.6 15.5 1.1 Electric .....................................................

211

Electricity Consumption Electricity Consumption EIA Electricity Consumption Estimates  

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

Consumption Consumption Electricity Consumption EIA Electricity Consumption Estimates (million kWh) National Petroleum Council Assumption: The definition of electricity con- sumption and sales used in the NPC 1999 study is the equivalent ofwhat EIA calls "sales by utilities" plus "retail wheeling by power marketers." This A nn u al Gro wth total could also be called "sales through the distribution grid," 2o 99 99 to Sales by Utilities -012% #N/A Two other categories of electricity consumption tracked by EIA cover on site Retail Wheeling Sales by generation for host use. The first, "nonutility onsite direct use," covers the Power Marketen 212.25% #N/A traditional generation/cogeneration facilities owned by industrial or large All Sales Through Distribution

212

Population, Consumption & the Environment  

E-Print Network [OSTI]

12/11/2009 1 Population, Consumption & the Environment Alex de Sherbinin Center for International of carbon in 2001 · The ecological footprint, a composite measure of consumption measured in hectares kind of consumption is bad for the environment? 2. How are population dynamics and consumption linked

Columbia University

213

Housing as basis for sustainable consumption  

Science Journals Connector (OSTI)

An important element in the discussion regarding sustainable development in our part of the world is directed towards the large growth in private consumption, and the clash of interests that arises between this growth and sustainable development requirements. A considerable part of private consumption can be related to our houses and the living situations of which they are part. It is of considerable interest to obtain more knowledge about the variations in patterns and volumes of consumption between different living situations, as well as to explore the important factors behind these variations. The acquisition of this type of empirical knowledge is an important aim in the present study. It is based on the superior thesis that it is possible through land use and housing planning to achieve substantial changes in living situations and thus contribute to a development in a direction of ''sustainable production and consumption''. The article first sums up the state-of-art regarding research on relations between physical planning, household consumption and environment. A theoretical framework and the methods applied in a Norwegian research project acquiring new empirical knowledge into these relations are also presented. The project was intended to be finished by the end of year 2000. Parts of the investigations are, however, completed and the material has been analysed. Two different types of urban structure, Oslo and a small rural town, are included in the investigations. The article presents some of the findings and relates them to former research.

Karl Georg Hoyer; Erling Holden

2001-01-01T23:59:59.000Z

214

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...

215

State-dependent effects of fiscal policy in Japan: Do rule-of-thumb households increase the effects of fiscal policy?  

Science Journals Connector (OSTI)

Abstract This study empirically investigates whether macroeconomic effects of fiscal policy are affected by the existence of rule-of-thumb households in Japan. Motivated by existing theoretical formulations, we estimate a consumption function as extended to a Markov switching model and divide the sample period into two parts depending on the share of rule-of-thumb (ROT) households. Subsequently, we estimate a Vector Autoregression (VAR) model to investigate the effects of two types of fiscal policy shock: unanticipated and anticipated. The results are subjected to robustness checks and reveal that the share of ROT households rises after large negative shocks (i.e., oil shock, economic bubble burst, Lehman shock), and then (unanticipated) fiscal policy shock stimulates private consumption more effectively in the high ROT households period.

Hiroshi Morita

2015-01-01T23:59:59.000Z

216

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

Gasoline and Diesel Fuel Update (EIA)

EIA household energy use data now includes detail on 16 States EIA household energy use data now includes detail on 16 States RECS 2009 - Release date: March 28, 2011 EIA is releasing new benchmark estimates for home energy use for the year 2009 that include detailed data for 16 States, 12 more than in past EIA residential energy surveys. EIA has conducted the Residential Energy Consumption Survey (RECS) since 1978 to provide data on home energy characteristics, end uses of energy, and expenses for the four Census Regions and nine Divisions. In 1997, EIA produced additional tabulations for the four most populous States (California, New York, Texas, and Florida). A threefold increase in the number of households included in the 2009 RECS offers more accuracy and coverage for understanding energy usage for all estimated States, Regions and Divisions.

217

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

218

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

219

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

220

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

Note: This page contains sample records for the topic "baseline household consumption" 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

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

222

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

223

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

224

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

225

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

226

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

227

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

228

California Baseline Energy Demands to 2050 for Advanced Energy Pathways  

E-Print Network [OSTI]

residential electricity consumption include disaggregationfor annual residential electricity consumption through 2050.Saturation and unit electricity consumption are projected

McCarthy, Ryan; Yang, Christopher; Ogden, Joan M.

2008-01-01T23:59:59.000Z

229

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

230

Raw Garlic Consumption as a Protective Factor for Lung Cancer, a Population-Based CaseControl Study in a Chinese Population  

Science Journals Connector (OSTI)

...crystalline silica and ionizing radiation, air pollution, coal-related pollution, and indoor emissions from household combustion...questionnaire contains information such as basic demographic and social economic status, weekly raw garlic consumption (never, 2 times/week...

Zi-Yi Jin; Ming Wu; Ren-Qiang Han; Xiao-Feng Zhang; Xu-Shan Wang; Ai-Ming Liu; Jin-Yi Zhou; Qing-Yi Lu; Zuo-Feng Zhang; and Jin-Kou Zhao

2013-07-01T23:59:59.000Z

231

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.

232

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

233

Hazard Baseline Downgrade Effluent Treatment Facility  

SciTech Connect (OSTI)

This Hazard Baseline Downgrade reviews the Effluent Treatment Facility, in accordance with Department of Energy Order 5480.23, WSRC11Q Facility Safety Document Manual, DOE-STD-1027-92, and DOE-EM-STD-5502-94. It provides a baseline grouping based on the chemical and radiological hazards associated with the facility. The Determination of the baseline grouping for ETF will aid in establishing the appropriate set of standards for the facility.

Blanchard, A.

1998-10-21T23:59:59.000Z

234

Energy Intensity Baselining and Tracking Guidance  

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

Learn more at betterbuildings.energy.gov Energy Intensity Baselining and Tracking Guidance i Preface The U.S. Department of Energy's (DOE) Better Buildings, Better Plants Program...

235

Methodology for reconstruction of historical food consumption estimates  

SciTech Connect (OSTI)

This report was written to provide the food consumption methodology to be used in the Hanford Environmental Dose Reconstruction (HDER) Project beyond Phase I (which ended in July 1990). In Phase I (Callaway 1992), baseline food consumption estimates (grams per day) for 10 primary food types in the original 10-county study region were derived from the 1977--1978 National Food Consumption Survey (USDA 1983). The baseline estimates were multiplied by the 1945:1977 ratios to produce consumption estimates for 1945. This ratio backcasting method used in Phase I to project consumption estimates from 1977 back to 1945 will be refined using additional USDA data to improve and document the acceptability of the ratios for deriving backcast consumption estimates. The number of food types and population groups will be expanded to provide more disaggregated estimates of food consumption. Food consumption estimates will be developed for 1945, 1951, and 1957. A database of individual diets will be created from which daily diets will be randomly selected for use in the dose model to calculate doses for reference individuals.

Anderson, D.M.

1992-05-01T23:59:59.000Z

236

" Column: Energy-Consumption Ratios;"  

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

" Level: National Data; " " Row: Values of Shipments within NAICS Codes;" " Column: Energy-Consumption Ratios;" " Unit: Varies." ,,,,"Consumption" ,,,"Consumption","per...

237

Correlated income shocks and excess smoothness of consumption  

Science Journals Connector (OSTI)

Abstract In the literature, econometricians typically assume that household income is the sum of a random walk permanent component and a transitory component, with uncorrelated permanent and transitory shocks. Using data on realized individual incomes and individual expectations of future incomes from the Survey of Italian Households? Income and Wealth, I find that permanent and transitory shocks are negatively correlated. Relaxing the assumption of no correlation between the shocks, I explore the effects of correlated income shocks on the estimated consumption insurance against permanent and transitory shocks, and consumption smoothness using a life-cycle model with self-insurance calibrated to U.S. data. Negatively correlated income shocks result in smoother consumption, and upward-biased estimates of the insurance against transitory (and permanent when borrowing constraints are not tight) income shocks. While the life-cycle model with negatively correlated shocks fits well the sensitivity of consumption to current income shocks observed in U.S. data, it falls short of explaining the sensitivity of consumption to income shocks cumulated over a longer horizon.

Dmytro Hryshko

2014-01-01T23:59:59.000Z

238

Dynamic energy-consumption indicators for domestic appliances: environment, behaviour and design  

Science Journals Connector (OSTI)

The literature concerning the application of information-feedback methods for saving energy in the home is reviewed. Particular attention is given to electronic feedback via smart meters and displays, or energy-consumption indicators (ECI). Previous studies have not focused on individual appliances, but this paper presents the findings of a UK field study involving 44 households which considered domestic cooking: it compares the effectiveness of providing paper-based energy-use/saving information with electronic feedback of energy-consumption via \\{ECIs\\} designed specifically for this investigation. Twelve Control Group households were monitored for a period of at least 12 months and this revealed an average daily consumption for electric cooking of 1.30kWh. Subsequently across a minimum monitoring period of 2 months, 14 out of 31 households achieved energy savings of greater than 10% and six of these achieved savings of greater than 20%. The average reduction for households employing an ECI was 15%, whereas those given antecedent information alone reduced their electricity consumption, on average, by only 3%. The associated behavioural changes and the importance of providing regular feedback during use are identified. It is recommended that further attention be given to optimising the design and assessing the use of energy-consumption indicators in the home, in order to maximise the associated energy-saving potential.

G. Wood; M. Newborough

2003-01-01T23:59:59.000Z

239

Field usage and its impact on energy consumption of refrigerator/freezers  

SciTech Connect (OSTI)

This study investigated the effect of door openings and kitchen environment on the energy consumption of nine household refrigerator/freezers (R/Fs) in the field. The factors under consideration include fresh food and freezer door openings, length of door openings, ambient kitchen temperature, and kitchen relative humidity (RH). Average daily energy consumption for the nine units ranged from 1.7 to 5.3 kWh/day. Energy consumption was found to correlate with kitchen temperature and the number of door openings. No dependence on kitchen relative humidity was found. In general, the magnitude of the door opening component of energy consumption was higher for the more efficient units.

Gage, C.L. [Environmental Protection Agency, Research Triangle Park, NC (United States). Air Pollution Prevention and Control Div.

1995-12-31T23:59:59.000Z

240

CSV File Documentation: Consumption  

Gasoline and Diesel Fuel Update (EIA)

Consumption Consumption The State Energy Data System (SEDS) comma-separated value (CSV) files contain consumption estimates shown in the tables located on the SEDS website. There are four files that contain estimates for all states and years. Consumption in Physical Units contains the consumption estimates in physical units for all states; Consumption in Btu contains the consumption estimates in billion British thermal units (Btu) for all states. There are two data files for thermal conversion factors: the CSV file contains all of the conversion factors used to convert data between physical units and Btu for all states and the United States, and the Excel file shows the state-level conversion factors for coal and natural gas in six Excel spreadsheets. Zip files are also available for the large data files. In addition, there is a CSV file for each state, named

Note: This page contains sample records for the topic "baseline household consumption" 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

Energy consumption testing of innovative refrigerator-freezers  

SciTech Connect (OSTI)

The high ambient temperature of the Canadian Standards Association (CSA) and the AHAM/DOE Refrigerator-Freezer Energy Consumption Standards is intended to compensate for the lack of door openings and other heat loads. Recently published results by Meier and Jansky (1993) indicate labeled consumption overpredicting typical field consumption by 15%. In-house field studies on conventional models showed labeled consumption overpredicting by about 22%. The Refrigerator-Freezer Technology Assessment (RFTA) test was developed to more accurately predict field consumption. This test has ambient temperature and humidity, door openings, and condensation control set at levels intended to typify Canadian household conditions. It also assesses consumption at exactly defined compartment rating temperatures. Ten conventional and energy-efficient production models were laboratory tested. The RFTA results were about 30% lower than labeled. Similarly, the four innovative refrigerator-freezer models, when field tested, also had an average of 30% lower consumption than labeled. Thus, the results of the limited testing suggest that the RFTA test may be a more accurate predictor of field use. Further testing with a larger sample is recommended. Experimental results also indicated that some innovative models could save up to 50% of the energy consumption compared with similar conventional units. The technologies that contributed to this performance included dual compressors, more efficient compressors and fan motors, off-state refrigerant control valve, fuzzy logic control, and thicker insulation. The larger savings were on limited production models, for which additional production engineering is required for full marketability.

Wong, M.T.; Howell, B.T.; Jones, W.R. [Ontario Hydro Technologies, Toronto, Ontario (Canada); Long, D.L. [Statistical Solutions, Mississauga, Ontario (Canada)

1995-12-31T23:59:59.000Z

242

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)

243

Analysis of household refrigerators for different testing standards  

SciTech Connect (OSTI)

This study highlights the salient differences among various testing standards for household refrigerator-freezers and proposes a methodology for predicting the performance of a single evaporator-based vapor-compression refrigeration system (either refrigerator or freezer) from one test standard (where the test data are available-the reference case) to another (the alternative case). The standards studied during this investigation include the Australian-New Zealand Standard (ANZS), the International Standard (ISO), the American National Standard (ANSI), the Japanese Industrial Standard (JIS), and the Chinese National Standard (CNS). A simple analysis in conjunction with the BICYCLE model (Bansal and Rice 1993) is used to calculate the energy consumption of two refrigerator cabinets from the reference case to the alternative cases. The proposed analysis includes the effect of door openings (as required by the JIS) as well as defrost heaters. The analytical results are found to agree reasonably well with the experimental observations for translating energy consumption information from one standard to another.

Bansal, P.K. [Univ. of Auckland (New Zealand). Dept. of Mechanical Engineering; McGill, I. [Fischer and Paykel Ltd., Auckland (New Zealand)

1995-08-01T23:59:59.000Z

244

DOE/EIA-0207/3 Residential Energy Consumption Survey: Conservation  

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

3 3 Residential Energy Consumption Survey: Conservation February 1980 U.S. Department of Energy Energy Information Adminstration Assistant Administrater for Program Development Other NEICS Reports Preliminary Conservation Tables from the National Interim Energy Consumption Survey, August 1979, DOE/EIA-0193/P Characteristics of the Housing Stocks and Households: Preliminary Findings from the National Interim Energy Consumption Survey, October 1979, DOETllA-0199/P The above reports are available from the following address; U.S. Department of Energy Technical Information Center Attn:; EIA Coordinator P.O. Box 62 Oak Ridge, TN 37830 Residential Energy Consumption Survey; Characteristics of the Housing Stock and Households, DOE/EIA-0207/2, GPO Stock No,, 061-003-00093-2; $4.25

245

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

246

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

247

Consumption conundrums unravelled  

E-Print Network [OSTI]

attire of the early nineteenth century.57 Household goods too show strong trends. Before 1750, tea-making paraphernalia (tongs, tea kettle, teapot, caddy, tea tray, tea board, tea) was not stolen on any scale. At this point probate inventories suggest...

Horrell, Sara; Humphries, Jane; Sneath, Ken

2014-01-01T23:59:59.000Z

248

Modeling energy consumption of residential furnaces and boilers in U.S. homes  

E-Print Network [OSTI]

ENERGY CONSUMPTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . .ENERGY CONSUMPTION . . . . . . . . . . . . . . . . . . . . . . . . . .28 ENERGY CONSUMPTION

Lutz, James; Dunham-Whitehead, Camilla; Lekov, Alex; McMahon, James

2004-01-01T23:59:59.000Z

249

consumption | OpenEI  

Open Energy Info (EERE)

consumption consumption Dataset Summary Description This dataset is from the report Operational water consumption and withdrawal factors for electricity generating technologies: a review of existing literature (J. Macknick, R. Newmark, G. Heath and K.C. Hallett) and provides estimates of operational water withdrawal and water consumption factors for electricity generating technologies in the United States. Estimates of water factors were collected from published primary literature and were not modified except for unit conversions. Source National Renewable Energy Laboratory Date Released August 28th, 2012 (2 years ago) Date Updated Unknown Keywords coal consumption csp factors geothermal PV renewable energy technologies Water wind withdrawal Data application/vnd.openxmlformats-officedocument.spreadsheetml.sheet icon Operational water consumption and withdrawal factors for electricity generating technologies (xlsx, 32.3 KiB)

250

Public perceptions of energy consumption and savings  

Science Journals Connector (OSTI)

...divided into household operations, transportation...production. Household operations include electricity...used by household operations?___ What...dryer A portable heater A room air-conditioner...to "warm wash, cold rinse...include caulking and weather stripping to seal...

Shahzeen Z. Attari; Michael L. DeKay; Cliff I. Davidson; Wndi Bruine de Bruin

2010-01-01T23:59:59.000Z

251

Reduces electric energy consumption  

E-Print Network [OSTI]

consumption · Reduces nonhazardous solid waste and wastewater generation · Potential annual savings, and recycling. Alcoa provides the packaging, automotive, aerospace, and construction markets with a variety

252

Transportation Energy Consumption Surveys  

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

Energy Consumption (RTECS) - U.S. Energy Information Administration (EIA) U.S. Energy Information Administration - EIA - Independent Statistics and Analysis Sources & Uses...

253

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...

254

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

255

Baseline for beached marine debris on Sand Island, Midway Atoll  

Science Journals Connector (OSTI)

Baseline measurements were made of the amount and weight of beached marine debris on Sand Island, Midway Atoll, June 2008July 2010. On 23 surveys, 32,696 total debris objects (identifiable items and pieces) were collected; total weight was 740.4kg. Seventy-two percent of the total was pieces; 91% of the pieces were made of plastic materials. Pieces were composed primarily of polyethylene and polypropylene. Identifiable items were 28% of the total; 88% of the identifiable items were in the fishing/aquaculture/shipping-related and beverage/household products-related categories. Identifiable items were lowest during AprilAugust, while pieces were at their lowest during JuneAugust. Sites facing the North Pacific Gyre received the most debris and proportionately more pieces. More debris tended to be found on Sand Island when the Subtropical Convergence Zone was closer to the Atoll. This information can be used for potential mitigation and to understand the impacts of large-scale events such as the 2011 Japanese tsunami.

Christine A. Ribic; Seba B. Sheavly; John Klavitter

2012-01-01T23:59:59.000Z

256

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

257

Baseline Wind Energy Facility | Open Energy Information  

Open Energy Info (EERE)

Baseline Wind Energy Facility Baseline Wind Energy Facility Jump to: navigation, search Name Baseline Wind Energy Facility Facility Baseline Wind Energy Facility Sector Wind energy Facility Type Commercial Scale Wind Facility Status Proposed Owner First Wind Developer First Wind Location Gilliam County OR Coordinates 45.626863°, -120.162885° 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":45.626863,"lon":-120.162885,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

258

Optimizing Medium Baseline Reactor Neutrino Experiments  

E-Print Network [OSTI]

10 years from now medium baseline reactor neutrino experiments will attempt to determine the neutrino mass hierarchy from the observed antineutrino spectra. In this letter we present the results of more than four million detailed simulations of such experiments, studying the dependence of the probability of successfully determining the hierarchy upon the analysis method, the neutrino mass matrix parameters, reactor flux models and, in particular, combinations of baselines. We show that the strong dependence of the hierarchy determination upon mass differences and flux models found by Qian et al. results from a spurious dependence of the Fourier analysis upon the high energy tail of the reactor spectrum which can be removed by using a weighted Fourier transform. Such experiments necessarily use flux from multiple reactors at distinct baselines, smearing the oscillation signal and thus impeding the determination of the hierarchy. Using the results of our simulations, we determine the optimal baselines and corre...

Ciuffoli, Emilio; Zhang, Xinmin

2013-01-01T23:59:59.000Z

259

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

260

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

Note: This page contains sample records for the topic "baseline household consumption" 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

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

262

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

263

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

264

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

265

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

266

Energy Information Administration - Energy Efficiency, energy consumption  

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

Efficiency Efficiency Energy Efficiency energy consumption savings households, buildings, industry & vehicles The Energy Efficiency Page reflects EIA's information on energy efficiency and related information. This site provides an in depth discussion of the concept of energy efficiency and how it is measured, measurement, summaries of formal user meetings on energy efficiency data and measurement, as well as analysis of greenhouse gas emissions as related to energy use and energy efficiency. At the site you will find links to other sources of information, and via a listserv all interested analysts can share ideas, data, and ask for assistance on methodological problems associated with energy use, energy efficiency, and greenhouse gas issues. Contact: Behjat.Hojjati@eia.doe.gov

267

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

Gasoline and Diesel Fuel Update (EIA)

How does EIA estimate energy consumption and end uses in U.S. homes? How does EIA estimate energy consumption and end uses in U.S. homes? RECS 2009 - Release date: March 28, 2011 EIA administers the Residential Energy Consumption Survey (RECS) to a nationally representative sample of housing units. Specially trained interviewers collect energy characteristics on the housing unit, usage patterns, and household demographics. This information is combined with data from energy suppliers to these homes to estimate energy costs and usage for heating, cooling, appliances and other end uses â€" information critical to meeting future energy demand and improving efficiency and building design. RECS uses a multi-stage area probability design to select sample methodology figure A multi-stage area probability design ensures the selection

268

Residential Energy Consumption for Water Heating (2005) | OpenEI  

Open Energy Info (EERE)

for Water Heating (2005) for Water Heating (2005) Dataset Summary Description Provides total and average annual residential energy consumption for water heating in U.S. households in 2005, measured in both physical units and Btus. The data is presented for numerous categories including: Census Region and Climate Zone; Housing Unit Characteristics (type, year of construction, size, income, race, age); and Water Heater and Water-using Appliance Characteristics (size, age, frequency of use, EnergyStar rating). Source EIA Date Released September 01st, 2008 (6 years ago) Date Updated January 01st, 2009 (5 years ago) Keywords Energy Consumption Residential Water Heating Data application/vnd.ms-excel icon 2005_Consumption.for_.Water_.Heating.Phys_.Units_EIA.Sep_.2008.xls (xls, 67.6 KiB)

269

Table A4. Residential sector key indicators and consumption  

Gasoline and Diesel Fuel Update (EIA)

3 3 U.S. Energy Information Administration | Annual Energy Outlook 2013 Reference case Table A4. Residential sector key indicators and consumption (quadrillion Btu per year, unless otherwise noted) Energy Information Administration / Annual Energy Outlook 2013 Table A4. Residential sector key indicators and consumption (quadrillion Btu per year, unless otherwise noted) Key indicators and consumption Reference case Annual growth 2011-2040 (percent) 2010 2011 2020 2025 2030 2035 2040 Key indicators Households (millions) Single-family ....................................................... 82.85 83.56 91.25 95.37 99.34 103.03 106.77 0.8% Multifamily ........................................................... 25.78 26.07 29.82 32.05 34.54 37.05 39.53 1.4%

270

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

271

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

272

OpenEI - consumption  

Open Energy Info (EERE)

91/0 en Operational water 91/0 en Operational water consumption and withdrawal factors for electricity generating technologies http://en.openei.org/datasets/node/969 This dataset is from the report Operational water consumption and withdrawal factors for electricity generating technologies: a review of existing literature (J. Macknick, R. Newmark, G. Heath and K.C. Hallett) and provides estimates of operational water withdrawal and water consumption factors for electricity generating technologies in the United States. Estimates of water factors were collected from published primary literature and were not modified except for unit conversions.

License

273

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......

274

Compilation and Application of Japanese Inventories for Energy Consumption and Air Pollutant Emissions Using Input?Output Tables  

Science Journals Connector (OSTI)

Graduate School of Energy Science, Kyoto University, Gokasho, Uji, Kyoto 611-0011, Japan ... Next, for each of the 400 sectors (the 399 sectors of the consolidated Input?Output Table plus the consumption expenditure of households sector, which is one of the final demand sectors), various statistics and source materials were used to estimate gross consumptions, expressed as a physical amount for each sector, of 6 coal-based fuels, 12 petroleum-based fuels, 3 natural gas-based fuels, and 5 other fuels. ... LPG. LPG for automobile and household use is more expensive than that used by industry, because of its higher tax rate and less efficient mode of supply. ...

Keisuke Nansai; Yuichi Moriguchi; Susumu Tohno

2003-04-04T23:59:59.000Z

275

Reduction of Water Consumption  

E-Print Network [OSTI]

Cooling systems using water evaporation to dissipate waste heat, will require one pound of water per 1,000 Btu. To reduce water consumption, a combination of "DRY" and "WET" cooling elements is the only practical answer. This paper reviews...

Adler, J.

276

Fuel Consumption and Emissions  

Science Journals Connector (OSTI)

Calculating fuel consumption and emissions is a typical offline analysis ... simulations or real trajectory data) and the engine speed (as obtained from gear-shift schemes ... as input and is parameterized by veh...

Martin Treiber; Arne Kesting

2013-01-01T23:59:59.000Z

277

Spermatophore consumption in a cephalopod  

Science Journals Connector (OSTI)

...Animal behaviour 1001 14 70 Spermatophore consumption in a cephalopod Benjamin J. Wegener...provide evidence of ejaculate and sperm consumption in a cephalopod. Through labelling...combination of female spermatophore consumption and short-term external sperm storage...

2013-01-01T23:59:59.000Z

278

Food consumption trends and drivers  

Science Journals Connector (OSTI)

...original work is properly cited. Food consumption trends and drivers John Kearney...Government policy. A picture of food consumption (availability) trends and projections...largely responsible for these observed consumption trends are the subject of this review...

2010-01-01T23:59:59.000Z

279

Residential Energy Consumption Survey (RECS) - U.S. Energy Information  

Gasoline and Diesel Fuel Update (EIA)

About the RECS About the RECS RECS Survey Forms RECS Maps RECS Terminology Archived Reports State fact sheets Arizona household graph See state fact sheets › 2009 RECS Features Heating and cooling no longer majority of U.S. home energy use March 7, 2013 Newer U.S. homes are 30% larger but consume about as much energy as older homes February 12, 2013 Where does RECS square footage data come from? July 11, 2012 RECS data show decreased energy consumption per household June 6, 2012 The impact of increasing home size on energy demand April 19, 2012 Did you know that air conditioning is in nearly 100 million U.S. homes? August 19, 2011 See more > graph of U.S. electricity end use, as explained in the article text U.S. electricity sales have decreased in four of the past five years

280

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

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

About the RECS About the RECS RECS Survey Forms RECS Maps RECS Terminology Archived Reports State fact sheets Arizona household graph See state fact sheets › 2009 RECS Features Heating and cooling no longer majority of U.S. home energy use March 7, 2013 Newer U.S. homes are 30% larger but consume about as much energy as older homes February 12, 2013 Where does RECS square footage data come from? July 11, 2012 RECS data show decreased energy consumption per household June 6, 2012 The impact of increasing home size on energy demand April 19, 2012 Did you know that air conditioning is in nearly 100 million U.S. homes? August 19, 2011 See more > graph of U.S. electricity end use, as explained in the article text U.S. electricity sales have decreased in four of the past five years

Note: This page contains sample records for the topic "baseline household consumption" 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

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

Gasoline and Diesel Fuel Update (EIA)

About the RECS About the RECS RECS Survey Forms RECS Maps RECS Terminology Archived Reports State fact sheets Arizona household graph See state fact sheets › 2009 RECS Features Heating and cooling no longer majority of U.S. home energy use March 7, 2013 Newer U.S. homes are 30% larger but consume about as much energy as older homes February 12, 2013 Where does RECS square footage data come from? July 11, 2012 RECS data show decreased energy consumption per household June 6, 2012 The impact of increasing home size on energy demand April 19, 2012 Did you know that air conditioning is in nearly 100 million U.S. homes? August 19, 2011 See more > graph of U.S. electricity end use, as explained in the article text U.S. electricity sales have decreased in four of the past five years

282

Rice consumption in China  

E-Print Network [OSTI]

RICE CONSUMPTION IN CHINA A Thesis by JIN LAN Submitted to the Office of Graduate Studies of Texas ASM University in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE August 1989 Major Subject: Agricultural... Economics RICE CONSUMPTION IN CHINA A Thesis by JIN LAN Approved as to style and content by: E, We ey F. Peterson (Chair of Committee) James E. Christiansen (Member) Carl Shaf (Member) Daniel I. Padberg (Head of Department) August 1989...

Lan, Jin

2012-06-07T23:59:59.000Z

283

Impact of Nighttime Shut Down on the Prediction Accuracy of Monthly Regression Models for Energy Consumption in Commercial Buildings  

E-Print Network [OSTI]

Regression models of measured energy use in buildings are widely used as baseline models to determine retrofit savings from measured energy consumption. It is less expensive to determine savings from monthly utility bills when they are available...

Wang, J.; Claridge, D. E.

1998-01-01T23:59:59.000Z

284

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

SciTech Connect (OSTI)

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

Not Available

1991-10-01T23:59:59.000Z

285

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

SciTech Connect (OSTI)

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

Not Available

1991-10-01T23:59:59.000Z

286

EA-1943: Proposed Long Baseline Neutrino Experiment (LBNE) at...  

Energy Savers [EERE]

943: Proposed Long Baseline Neutrino Experiment (LBNE) at Fermilab, Batavia, Illinois EA-1943: Proposed Long Baseline Neutrino Experiment (LBNE) at Fermilab, Batavia, Illinois...

287

Simple Indicator To Identify the Environmental Soundness of Growth of Consumption and Technology:? Eco-velocity of Consumption  

Science Journals Connector (OSTI)

Research Center for Material Cycles and Waste Management, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki 305-8506, Japan, Faculty of Economics, Kyushu University, 6-19-1 Hakozaki, Higashi-ku, Fukuoka, 812-8581, Japan, and Department of Bioproducts and Biosystems Engineering, College of Food, Agriculture and Natural Resources Sciences, University of Minnesota, 2004 Folwell Avenue, St. Paul, MN 55108, and Institute of Environmental Sciences (CML), Leiden University, P.O. ... Eq 8 thus determined Dt where Yt denotes the quantity of goods and services provided to households as measured in monetary units and Pt is the aggregate CO2 emissions due to Yt. ... The linked IOT defines electricity, petroleum fuels (gasoline, diesel, kerosene, liquid petroleum gas, etc.), and city gas as three separate sectors (commodities) but with no further breakdown of quantitative consumption or the uses to which the respective energy carriers are put, either nationally or at the household level. ...

Keisuke Nansai; Shigemi Kagawa; Sangwon Suh; Rokuta Inaba; Yuichi Moriguchi

2007-01-19T23:59:59.000Z

288

Buildings Energy Data Book: 2.1 Residential Sector Energy Consumption  

Buildings Energy Data Book [EERE]

3 3 Building Type Pre-1995 1995-2005 Pre-1995 1995-2005 Pre-1995 1995-2005 Single-Family 38.4 44.9 102.7 106.2 38.5 35.5 Detached 37.9 44.7 104.5 107.8 38.8 35.4 Attached 43.8 55.5 86.9 85.1 34.2 37.6 Multi-Family 63.8 58.7 58.3 49.2 27.2 24.3 2 to 4 units 69.0 55.1 70.7 59.4 29.5 25.0 5 or more units 61.5 59.6 53.6 47.2 26.3 24.2 Mobile Homes 82.4 57.1 69.6 74.5 29.7 25.2 Note(s): Source(s): 2005 Residential Delivered Energy Consumption Intensities, by Principal Building Type and Vintage Per Square Foot (thousand Btu) (1) Per Household (million Btu) Per Household Member (million Btu) 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

289

Waste management project technical baseline description  

SciTech Connect (OSTI)

A systems engineering approach has been taken to describe the technical baseline under which the Waste Management Project is currently operating. The document contains a mission analysis, function analysis, requirement analysis, interface definitions, alternative analysis, system definition, documentation requirements, implementation definitions, and discussion of uncertainties facing the Project.

Sederburg, J.P.

1997-08-13T23:59:59.000Z

290

Electrochemistry Diagnostics of Baseline and New Materials  

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

9.35 mgcm 2 for treated 8.32 mgcm 2 for pristine 7.44 mgcm 2 for ABR baseline (SAFT) Cycling 4xC12 and 50xC3 (210 mAhg) * Evaluated electrochemical behavior of carbon...

291

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

292

Voluntary electricity conservation of households after the Great East Japan Earthquake: A stated preference analysis  

Science Journals Connector (OSTI)

Abstract This paper examines the voluntary electricity-saving awareness of households after the Great East Japan Earthquake and the subsequent accident at the Fukushima nuclear power station. We conduct a conjoint analysis of consumer stated preferences for the settings of air conditioners, refrigerators, and the standby power of electrical appliances, based on a web questionnaire survey administered in the areas supplied by the Tokyo Electric Power Company (TEPCO) and Kansai Electric Power Company (KEPCO). The main findings of this paper are as follows. First, we observe awareness of voluntary electricity conservation among the households in both the TEPCO and KEPCO areas after the disasters. Second, awareness of voluntary power saving is higher in the TEPCO area, which has been directly affected by the electric power shortages, in comparison with the KEPCO area, where there was no such direct impact. Third, if power prices are to be further raised, the consumer responses to the price changes would be small in both areas. Furthermore, we show that the potential voluntary reduction in electric power consumption of a household in the TEPCO area is 26% more than that in the KEPCO area during the summer peak periods.

Makoto Tanaka; Takanori Ida

2013-01-01T23:59:59.000Z

293

Rising household diesel consumption in the United States: A cause for concern? Evidence on asymmetric pricing  

Science Journals Connector (OSTI)

Papers in the literature have thus far overlooked the projected increase in U.S. diesel car share when looking at asymmetries in petroleum pricing. This paper addresses this issue by comparing retail gasoline and diesel prices in order to see whether they rise faster than they fall given the price of their upstream input, crude oil. This phenomenon has been termed in the literature as Rockets and Feathers. We apply the threshold vector error correction model (TVECM) of Hansen and Seo (2002) which has not yet been applied in the literature. We account for the 2008 structural break to crude oil and petroleum prices by splitting the sample using evidence from the recent structural break unit root test of Kim and Perron (2009). Both markets seem to price symmetrically before the 2008 break, but we find evidence of asymmetric pricing after 2008 in diesel prices, and not in gasoline prices. Given that the diesel market is small relative to the gasoline market and therefore more open to price exploitation, the ongoing cost increases associated with the policy of switching to Ultra Low Sulphur diesel (ULSD) from 2006 to 2010 could be at the heart of this asymmetry. With this in mind, the U.S. Federal Trade Commission should monitor diesel prices as the market share grows, in order to ensure that consumers are not adversely affected.

Jack Fosten

2012-01-01T23:59:59.000Z

294

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

E-Print Network [OSTI]

or unusually high heating oil prices in Massachusetts versusgas, and home heating oil prices averaged over the previousgas than in heating oil prices. There is a strong seasonal

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

2005-01-01T23:59:59.000Z

295

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

E-Print Network [OSTI]

exceeds 0.93. For heating oil prices, the lowest correlationfor weather and heating oil prices. 6. Estimation resultsor unusually high heating oil prices in Massachusetts versus

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

2005-01-01T23:59:59.000Z

296

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

E-Print Network [OSTI]

the Effects of Electricity Price Changes on Californiafacing typical electricity prices in Massachusetts or aand maximum electricity price), these high expenditure

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

2005-01-01T23:59:59.000Z

297

Understanding Socio-Economic Driving Factors of Indonesian Households Electricity Consumption in Two Urban Areas  

Science Journals Connector (OSTI)

Indonesia is one of the most diverse countries in the world in terms of its society. Therefore, there are several different characteristics in daily practices, including in consuming electricity. In order to unde...

Muhammad Ery Wijaya; Tetsuo Tezuka

2012-01-01T23:59:59.000Z

298

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

E-Print Network [OSTI]

oil prices show a similar increase in the later years of the sample, but show a much less pronounced seasonal cycle

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

2005-01-01T23:59:59.000Z

299

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

300

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

Note: This page contains sample records for the topic "baseline household consumption" 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

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

302

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

303

Office Buildings - Energy Consumption  

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

Energy Consumption Energy Consumption Office buildings consumed more than 17 percent of the total energy used by the commercial buildings sector (Table 4). At least half of total energy, electricity, and natural gas consumed by office buildings was consumed by administrative or professional office buildings (Figure 2). Table 4. Energy Consumed by Office Buildings for Major Fuels, 2003 All Buildings Total Energy Consumption (trillion Btu) Number of Buildings (thousand) Total Floorspace (million sq. ft.) Sum of Major Fuels Electricity Natural Gas Fuel Oil District Heat All Buildings 4,859 71,658 6,523 3,559 2,100 228 636 All Non-Mall Buildings 4,645 64,783 5,820 3,037 1,928 222 634 All Office Buildings 824 12,208 1,134 719 269 18 128 Type of Office Building

304

Carbon, Land, and Water Footprint Accounts for the European Union: Consumption, Production, and Displacements through International Trade  

Science Journals Connector (OSTI)

Industrial Ecology Programme and Department of Energy and Process Engineering, Norwegian University of Science and Technology (NTNU), Trondheim, Norway ... On the global level, the accounting for emissions embodied in trade increases the already high carbon footprints of Europe, Japan, South Korea, and the United States. ... On a global level, 72% of greenhouse gas emissions are related to household consumption, 10% to government consumption, and 18% to investments. ...

Kjartan Steen-Olsen; Jan Weinzettel; Gemma Cranston; A. Ertug Ercin; Edgar G. Hertwich

2012-09-26T23:59:59.000Z

305

Pomona Loop Baseline Performance Testing.PDF  

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

Pomona Loop Baseline Performance Testing Summary Pomona Loop Baseline Performance Testing Summary The U.S. Department of Energy's Field Operations Program sponsors the Urban and Freeway Pomona Loop range testing in Southern California. The testing is performed by one of the Program's testing partners, Southern California Edison. The vehicles are tested on local city streets (Urban Loop) and four highways (Freeway Loop). The Urban Loop is 19.3 miles long, ranging in elevation from 900 to 1500 feet, with approximately 50 stop signs and traffic lights. The Freeway Loop is 37.2 miles long, ranging in elevation from 700 to 1150 feet, and consists of four connected freeways shaped like a rectangle. When a vehicle is Pomona Loop tested, eight range tests are performed, with four tests on the Urban Loop and four on the Freeway Loop. The range tests are performed

306

Baseline Microstructural Characterization of Outer 3013 Containers  

SciTech Connect (OSTI)

Three DOE Standard 3013 outer storage containers were examined to characterize the microstructure of the type 316L stainless steel material of construction. Two of the containers were closure-welded yielding production-quality outer 3013 containers; the third examined container was not closed. Optical metallography and Knoop microhardness measurements were performed to establish a baseline characterization that will support future destructive examinations of 3013 outer containers in the storage inventory. Metallography revealed the microstructural features typical of this austenitic stainless steel as it is formed and welded. The grains were equiaxed with evident annealing twins. Flow lines were prominent in the forming directions of the cylindrical body and flat lids and bottom caps. No adverse indications were seen. Microhardness values, although widely varying, were consistent with annealed austenitic stainless steel. The data gathered as part of this characterization will be used as a baseline for the destructive examination of 3013 containers removed from the storage inventory.

Zapp, Phillip E.; Dunn, Kerry A

2005-07-31T23:59:59.000Z

307

2005 Residential Energy Consumption Survey  

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

D (2005) - Household Propane (Bottled Gas or LPG) Usage Form D (2005) - Household Propane (Bottled Gas or LPG) Usage Form OMB No. 1905-0092, Expiring May 31, 2008 Household Propane (Bottled Gas or LPG) Usage Form Service Address: If the customer account number is not shown on the label, please enter it here. STEP 1 Customer Account: __/__/__/__/__/__/__/__/__/__/__/__/__/__/__/ STEP 2 Now, please turn the page and answer the seven questions for the household identified above. Completed forms are due by March 4, 2006. If you have any questions, please call (toll-free) 1-NNN-NNN-NNNN. Ask for the Supplier Survey Specialist. This report is mandatory under Public Law 93-275, as amended. See the enclosed Answers to Frequently Asked Questions for more details concerning confidentiality

308

2005 Residential Energy Consumption Survey  

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

F (2005) - Household Natural Gas Usage Form F (2005) - Household Natural Gas Usage Form OMB No. 1905-0092, Expiring May 31, 2008 Household Natural Gas Usage Form Service Address: If the customer account number is not shown above, please enter it here. STEP 1 Customer Account: __/__/__/__/__/__/__/__/__/__/__/__/__/__/__/ STEP 2 Now, please turn the page and provide the requested information for the household identified above. Completed forms are due by March 4, 2006. If you have any questions, please call (toll-free) 1-NNN-NNN-NNNN. Ask for the Supplier Survey Specialist. This report is mandatory under Public Law 93-275, as amended. See the enclosed Answers to Frequently Asked Questions for more details concerning confidentiality and sanctions. Use the enclosed self-addressed envelope and return the completed form to:

309

2005 Residential Energy Consumption Survey  

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

G (2005) - Household Fuel Oil or Kerosene Usage Form G (2005) - Household Fuel Oil or Kerosene Usage Form OMB No. 1905-0092, Expiring May 31, 2008 Household Fuel Oil or Kerosene Usage Form Service Address: If the customer account number is not shown on the label, please enter it here. STEP 1 Customer Account: __/__/__/__/__/__/__/__/__/__/__/__/__/__/__/ STEP 2 Now, please turn the page and answer the seven questions for the household identified above. Completed forms are due by March 4, 2006. If you have any questions, please call (toll-free) 1-NNN-NNN-NNNN. Ask for the Supplier Survey Specialist. This report is mandatory under Public Law 93-275, as amended. See the enclosed Answers to Frequently Asked Questions for more details concerning confidentiality and sanctions.

310

2005 Residential Energy Consumption Survey  

Gasoline and Diesel Fuel Update (EIA)

in gallons, of this household's storage tank(s)? Enter the capacity for the two largest tanks (if there is more than one) in the boxes below. If the capacity is not known, write...

311

The Very Long Baseline ArrayThe Very Long Baseline Array Brought to you by the National Radio  

E-Print Network [OSTI]

The Very Long Baseline ArrayThe Very Long Baseline Array Brought to you by the National Radio Los Alamos, NM Pie Town, NM Kitt Peak, AZ Owens Valley, CA Brewster, WA Mauna Kea, HI #12;· weighs 240 gravitational lenses #12;www.www.nraonrao..eduedu #12;The Very Long Baseline ArrayThe Very Long Baseline Array

Groppi, Christopher

312

Natural Gas Consumption  

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

Lease Fuel Consumption Plant Fuel Consumption Pipeline & Distribution Use Volumes Delivered to Consumers Volumes Delivered to Residential Volumes Delivered to Commercial Consumers Volumes Delivered to Industrial Consumers Volumes Delivered to Vehicle Fuel Consumers Volumes Delivered to Electric Power Consumers Period: Monthly Annual Lease Fuel Consumption Plant Fuel Consumption Pipeline & Distribution Use Volumes Delivered to Consumers Volumes Delivered to Residential Volumes Delivered to Commercial Consumers Volumes Delivered to Industrial Consumers Volumes Delivered to Vehicle Fuel Consumers Volumes Delivered to Electric Power Consumers Period: Monthly Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: Data Series Area 2007 2008 2009 2010 2011 2012 View History U.S. 23,103,793 23,277,008 22,910,078 24,086,797 24,477,425 25,533,448 1949-2012 Alabama 418,512 404,157 454,456 534,779 598,514 666,738 1997-2012 Alaska 369,967 341,888 342,261 333,312 335,458 343,110 1997-2012

313

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

314

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

315

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

316

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

317

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

318

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

Science Journals Connector (OSTI)

......Figure 10. Providing Energy Feedback on multiple...checked their current energy consumption before...commercial breaks. The integration of the HEMS into...important factor for sustainable use. To an extent...provides significant challenge to householders...monitoring of their energy usage in situations......

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

2014-04-01T23:59:59.000Z

319

Residential Energy Consumption Survey (RECS) - U.S. Energy Information  

Gasoline and Diesel Fuel Update (EIA)

About the RECS About the RECS RECS Survey Forms RECS Maps RECS Terminology Archived Reports State fact sheets Arizona household graph See state fact sheets › graph of U.S. electricity end use, as explained in the article text U.S. electricity sales have decreased in four of the past five years December 20, 2013 Gas furnace efficiency has large implications for residential natural gas use December 5, 2013 EIA publishes state fact sheets on residential energy consumption and characteristics August 19, 2013 All 48 related articles › Other End Use Surveys Commercial Buildings - CBECS Manufacturing - MECS Transportation About the RECS EIA administers the Residential Energy Consumption Survey (RECS) to a nationally representative sample of housing units. Specially trained interviewers collect energy characteristics on the housing unit, usage

320

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

Gasoline and Diesel Fuel Update (EIA)

The impact of increasing home size on energy demand The impact of increasing home size on energy demand RECS 2009 - Release date: April 19, 2012 Homes built since 1990 are on average 27% larger than homes built in earlier decades, a significant trend because most energy end-uses are correlated with the size of the home. As square footage increases, the burden on heating and cooling equipment rises, lighting requirements increase, and the likelihood that the household uses more than one refrigerator increases. Square footage typically stays fixed over the life of a home and it is a characteristic that is expensive, even impractical to alter to reduce energy consumption. According to results from EIA's 2009 Residential Energy Consumption Survey (RECS), the stock of homes built in the 1970s and 1980s averages less than

Note: This page contains sample records for the topic "baseline household consumption" 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

Baselines for Greenhouse Gas Reductions: Problems, Precedents, Solutions |  

Open Energy Info (EERE)

Baselines for Greenhouse Gas Reductions: Problems, Precedents, Solutions Baselines for Greenhouse Gas Reductions: Problems, Precedents, Solutions Jump to: navigation, search Tool Summary Name: Baselines for Greenhouse Gas Reductions: Problems, Precedents, Solutions Agency/Company /Organization: World Bank Sector: Energy Topics: Baseline projection, GHG inventory, Pathways analysis Resource Type: Publications, Lessons learned/best practices Website: www.p2pays.org/ref/22/21739.pdf References: Baselines for Greenhouse Gas Reductions: Problems, Precedents, Solutions[1] Summary "Rigor in baselines It's important to establish the right degree of rigor in baselining. Overly lax baselines will threaten the system's credibility and usefulness, and shift rents from high quality providers to low quality providers of offsets. Overly stringent baselines will discourage valid projects and

322

Mexico - Greenhouse Gas Emissions Baselines and Reduction Potentials from  

Open Energy Info (EERE)

Greenhouse Gas Emissions Baselines and Reduction Potentials from Greenhouse Gas Emissions Baselines and Reduction Potentials from Buildings Jump to: navigation, search Name Mexico - Greenhouse Gas Emissions Baselines and Reduction Potentials from Buildings Agency/Company /Organization United Nations Environment Programme Sector Energy Focus Area Buildings Topics Baseline projection, GHG inventory, Pathways analysis, Background analysis Resource Type Publications Website http://www.unep.org/sbci/pdfs/ Country Mexico Central America References Greenhouse Emissions Baselines and Reduction Potentials for Buildings[1] Mexico - Greenhouse Gas Emissions Baselines and Reduction Potentials from Buildings Screenshot "This report represents the first comprehensive description of the factors that determine the present and future impacts of residential and commercial

323

Data Center Power Consumption  

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

Center Power Consumption Center Power Consumption A new look at a growing problem Fact - Data center power density up 10x in the last 10 years 2.1 kW/rack (1992); 14 kW/rack (2007) Racks are not fully populated due to power/cooling constraints Fact - Increasing processor power Moore's law Fact - Energy cost going up 3 yr. energy cost equivalent to acquisition cost Fact - Iterative power life cycle Takes as much energy to cool computers as it takes to power them. Fact - Over-provisioning Most data centers are over-provisioned with cooling and still have hot spots November 2007 SubZero Engineering An Industry at the Crossroads Conflict between scaling IT demands and energy efficiency Server Efficiency is improving year after year Performance/Watt doubles every 2 years Power Density is Going Up

324

101. Natural Gas Consumption  

Gasoline and Diesel Fuel Update (EIA)

1. Natural Gas Consumption 1. Natural Gas Consumption in the United States, 1930-1996 (Million Cubic Feet) Table Year Lease and Plant Fuel Pipeline Fuel Delivered to Consumers Total Consumption Residential Commercial Industrial Vehicle Fuel Electric Utilities Total 1930 ....................... 648,025 NA 295,700 80,707 721,782 NA 120,290 1,218,479 1,866,504 1931 ....................... 509,077 NA 294,406 86,491 593,644 NA 138,343 1,112,884 1,621,961 1932 ....................... 477,562 NA 298,520 87,367 531,831 NA 107,239 1,024,957 1,502,519 1933 ....................... 442,879 NA 283,197 85,577 590,865 NA 102,601 1,062,240 1,505,119 1934 ....................... 502,352 NA 288,236 91,261 703,053 NA 127,896 1,210,446 1,712,798 1935 ....................... 524,926 NA 313,498 100,187 790,563 NA 125,239 1,329,487 1,854,413 1936 ....................... 557,404 NA 343,346

325

Residential Energy Consumption Survey:  

Gasoline and Diesel Fuel Update (EIA)

E/EIA-0262/2 E/EIA-0262/2 Residential Energy Consumption Survey: 1978-1980 Consumption and Expenditures Part II: Regional Data May 1981 U.S. Department of Energy Energy Information Administration Assistant Administrator for Program Development Office of the Consumption Data System Residential and Commercial Data Systems Division -T8-aa * N uojssaooy 'SOS^-m (£03) ao£ 5925 'uofSfAfQ s^onpojj aa^ndmoo - aojAaag T BU T3gN am rcoj? aig^IT^^ '(adBx Q-naugBH) TOO/T8-JQ/30Q 30^703 OQ ' d jo :moaj ajqBfT^A^ 3J^ sjaodaa aAoqe aqa jo 's-TZTOO-eoo-Tgo 'ON ^ois odo 'g^zo-via/aoQ 'TBST Sujpjjng rXaAang uojidmnsuoo XSaaug sSu-ppjprig ON ^oo^s OdO '^/ZOZO-Via/aOQ *086T aunr '6L6I ?sn§ny og aunf ' jo suja^Bd uoj^dmnsuoo :XaAjng uo^^dmnsuoQ XSaaug OS '9$ '6-ieTOO- 00-T90 OdD 'S/ZOZO-Via/aOa C

326

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

327

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

328

Econometric model of the joint production and consumption of residential space heat  

SciTech Connect (OSTI)

This study models the production and comsumption of residential space heat, a nonmarket good. Production reflects capital investment decisions of households; consumption reflects final demand decisions given the existing capital stock. In the model, the production relationship is represented by a translog cost equation and an anergy factor share equation. Consumption is represented by a log-linear demand equation. This system of three equations - cost, fuel share, and final demand - is estimated simultaneously. Results are presented for two cross-sections of households surveyed in 1973 and 1981. Estimates of own-price and cross-price elasticities of factor demand are of the correct sign, and less than one in magnitude. The price elasticity of final demand is about -0.4; the income elasticity of final demand is less than 0.1. Short-run and long-run elasticities of demand for energy are about -0.3 and -0.6, respectively. These results suggest that price-induced decreases in the use of energy for space heat are attributable equally to changes in final demand and to energy conservation, the substitution of capital for energy in the production of space heat. The model is used to simulate the behavior of poor and nonpoor households during a period of rising energy prices. This simulation illustrates the greater impact of rising prices on poor households.

Klein, Y.L.

1985-12-01T23:59:59.000Z

329

Document Number Q0029500 Baseline Risk Assessment Update 4.0 Baseline Risk Assessment Update  

Office of Legacy Management (LM)

Baseline Risk Assessment Update Baseline Risk Assessment Update 4.0 Baseline Risk Assessment Update This section updates the human health and the ecological risk assessments that were originally presented in the 1998 RI (DOE 1998a). The impacts on the 1998 risk assessments are summarized in Section 2.9. 4.1 Human Health Risk Assessment Several activities completed since 1998 have contributed to changes in surface water and ground water concentrations. Activities that have impacted, or likely impacted surface water and ground water concentrations are Millsite Excavation (Section 2.1) Remediation of Soil and Sediment Along Montezuma Creek (Section 2.3) Millsite Dewatering and Treatment (Section 2.5) PRB Treatability Study (Section 2.6) Surface water and ground water monitoring data have been used to refine the list of COCs

330

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

331

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

332

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

333

NETL - Bituminous Baseline Performance and Cost Interactive Tool | Open  

Open Energy Info (EERE)

NETL - Bituminous Baseline Performance and Cost Interactive Tool NETL - Bituminous Baseline Performance and Cost Interactive Tool Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Bituminous Baseline Performance and Cost Interactive Tool Agency/Company /Organization: National Energy Technology Laboratory Sector: Energy Topics: Baseline projection, GHG inventory Resource Type: Software/modeling tools Website: www.netl.doe.gov/energy-analyses/refshelf/results.asp?ptype=Models/Too References: Bituminous Baseline Performance and Cost Interactive Tool [1] Bituminous Baseline Performance and Cost Interactive Tool The Bituminous Baseline Performance and Cost Interactive Tool illustrates key data from the Cost and Performance Baseline for Fossil Energy Plants - Bituminous Coal and Natural Gas to Electricity report. The tool provides an

334

California Baseline Energy Demands to 2050 for Advanced Energy Pathways  

E-Print Network [OSTI]

ED2, September. CEC (2005b) Energy demand forecast methodsCalifornia Baseline Energy Demands to 2050 for Advancedof a baseline scenario for energy demand in California for a

McCarthy, Ryan; Yang, Christopher; Ogden, Joan M.

2008-01-01T23:59:59.000Z

335

Greenhouse Gas Emissions Driven by the Transportation of Goods Associated with French Consumption  

Science Journals Connector (OSTI)

By product, transport of coal and coke and intermediate goods make the largest contribution to overall freight transport emissions associated with French household consumption. ... Finally, improving rail and inland water transportation infrastructure between northern European countries and France also serves the purpose of improving trade-relations and economic efficiency within Europe. ... per capita footprints were 1 ton CO2 equiv./yr in African countries to ?30ton CO2 equiv./yr in Luxembourg and the USA. ...

Troy R. Hawkins; Sbastien M. R. Dente

2010-10-01T23:59:59.000Z

336

Energy baseline and energy efficiency resource opportunities for the Forest Products Laboratory, Madison, Wisconsin  

SciTech Connect (OSTI)

This report provides recommendations to improve the energy use efficiency at the Forest Products Laboratory in Madison, Wisconsin. The assessment focuses upon the four largest buildings and central heating plant at the facility comprising a total of approximately 287,000 square feet. The analysis is comprehensive in nature, intended primarily to determine what if any energy efficiency improvements are warranted based upon the potential for cost-effective energy savings. Because of this breadth, not all opportunities are developed in detail; however, baseline energy consumption data and energy savings concepts are described to provide a foundation for detailed investigation and project design where warranted.

Mazzucchi, R.P. [SBW Consulting Co., Bellevue, WA (US); Richman, E.E.; Parker, G.B. [Pacific Northwest Lab., Richland, WA (US)

1993-08-01T23:59:59.000Z

337

Examining Uncertainty in Demand Response Baseline Models and  

E-Print Network [OSTI]

LBNL-5096E Examining Uncertainty in Demand Response Baseline Models and Variability in Automated of California. #12;Examining Uncertainty in Demand Response Baseline Models and Variability in Automated.e. dynamic prices). Using a regression-based baseline model, we define several Demand Response (DR

338

US Biofuels Baseline and impact of extending the  

E-Print Network [OSTI]

June 2011 US Biofuels Baseline and impact of extending the $0.45 ethanol blenders baseline projections for agricultural and biofuel markets.1 That baseline assumed current biofuel policy for cellulosic biofuels was assumed to expire at the end of 2012. This report compares a slightly modified

Noble, James S.

339

"Table HC7.10 Home Appliances Usage Indicators by Household...  

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

0 Home Appliances Usage Indicators by Household Income, 2005" " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1"...

340

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...

Note: This page contains sample records for the topic "baseline household consumption" 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

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

E-Print Network [OSTI]

of household refrigerators and freezers 2 . Therefore, thesales of the refrigerators and freezers are about 20.6for household refrigerators and freezers has been updated

Lin, Jiang

2006-01-01T23:59:59.000Z

342

Modeling households decisions on reconstruction of houses damaged by earthquakesJapanese case study  

Science Journals Connector (OSTI)

In this study, households decisions on reconstruction of damaged houses were modeled, using questionnaire data in Japan. Characteristics of households decisions were investigated using parameter estimation resu...

H. Sakakibara; H. Murakami; S. Esaki; D. Mori; H. Nakata

2008-02-01T23:59:59.000Z

343

ENERGY CONSUMPTION SURVEY  

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

5 RESIDENTIAL TRANSPORTATION 5 RESIDENTIAL TRANSPORTATION ENERGY CONSUMPTION SURVEY Prepared for: UNITED STATES DEPARTMENT OF ENERGY ENERGY INFORMATION ADMINISTRATION OFFICE OF ENERGY MARKETS AND END USE ENERGY END USE DIVISION RESIDENTIAL AND COMMERCIAL BRANCH WASHINGTON, DC 20585 Prepared by: THE ORKAND CORPORATION 8484 GEORGIA AVENUE SILVER SPRING, MD 20910 October 1986 Contract Number DE-AC01-84EI19658 TABLE OF CONTENTS FRONT MATTER Index to Program Descriptions........................................... vi List of Exhibits ....................................................... viii Acronyms and Abbreviations ............................................. ix SECTION 1: GENERAL INFORMATION ........................................ 1-1 1.1. Summary ....................................................... 1-1

344

Indexes of Consumption and Production  

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

Figure on manufacturing production indexes and purchased energy consumption Figure on manufacturing production indexes and purchased energy consumption Source: Energy Information Administration and Federal Reserve Board. History of Shipments This chart presents indices of 14 years (1980-1994) of historical data of manufacturing production indexes and Purchased (Offsite-Produced) Energy consumption, using 1992 as the base year (1992 = 100). Indexing both energy consumption and production best illustrates the trends in output and consumption. Taken separately, these two indices track the relative growth rates within the specified industry. Taken together, they reveal trends in energy efficiency. For example, a steady increase in output, coupled with a decline in energy consumption, represents energy efficiency gains. Likewise, steadily rising energy consumption with a corresponding decline in output illustrates energy efficiency losses.

345

Manufacturing Consumption of Energy 1991--Combined Consumption and Fuel  

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

< < Welcome to the U.S. Energy Information Administration's Manufacturing Web Site. If you are having trouble, call 202-586-8800 for help. Return to Energy Information Administration Home Page. Home > Energy Users > Manufacturing > Consumption and Fuel Switching Manufacturing Consumption of Energy 1991 (Combined Consumption and Fuel Switching) Overview Full Report Tables & Spreadsheets This report presents national-level estimates about energy use and consumption in the manufacturing sector as well as manufacturers' fuel-switching capability. Contact: Stephanie.battle@eia.doe.gov Stephanie Battle Director, Energy Consumption Division Phone: (202) 586-7237 Fax: (202) 586-0018 URL: http://www.eia.gov/emeu/mecs/mecs91/consumption/mecs1a.html File Last Modified: May 25, 1996

346

Griffiss AFB integrated resource assessment. Volume 2, Electric baseline detail  

SciTech Connect (OSTI)

The US Air Force Air Combat Command has tasked the Pacific Northwest Laboratory (PNL) as the lead laboratory supporting the US Department of Energy (DOE) Federal Energy Management Program`s (FEMP) mission to identify, evaluate, and assist in acquiring all cost-effective energy projects at Griffiss Air Force Base (AFB). This is a model program PNL is designing for federal customers served by the Niagara Mohawk Power Company (Niagara Mohawk). It will (1) identify and evaluate all electric cost-effective energy projects; (2) develop a schedule at each installation for project acquisition considering project type, size, timing, and capital requirements, as well as energy and dollar savings; and (3) secure 100% of the financing required to implement electric energy efficiency projects from Niagara Mohawk and have Niagara Mohawk procure the necessary contractors to perform detailed audits and install the technologies. This report documents the assessment of baseline energy use at one of Niagara Mohawk`s primary federal facilities, Griffiss AFB, an Air Combat Command facility located near Rome, New York. It is a companion report to Volume 1, the Executive Summary, and Volume 3, the Electric Resource Assessment. The analysis examines the characteristics of electric, gas, oil, propane, coal, and purchased thermal capacity use for fiscal year (FY) 1990. The results include energy-use intensities for the facilities at Griffiss AFB by building type and electric energy end use. A complete electric energy consumption reconciliation is presented that accounts for the distribution of all major electric energy uses and losses among buildings, utilities, and central systems.

Dixon, D.R.; Armstrong, P.R.; Keller, J.M.

1993-02-01T23:59:59.000Z

347

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

348

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

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

in gallons, of this household's storage tank(s)? Enter the capacity for the two largest tanks (if there is more than one) in the boxes below. If the capacity is not known, write...

349

Fact #614: March 15, 2010 Average Age of Household Vehicles  

Broader source: Energy.gov [DOE]

The average age of household vehicles has increased from 6.6 years in 1977 to 9.2 years in 2009. Pickup trucks have the oldest average age in every year listed. Sport utility vehicles (SUVs), first...

350

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

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

or More","NA","NA",93.75,96.42857143,91.27516779,97.46835443 "Race of Householder1" " White",88.61111111,"NA",91.54929577,91.68704156,90.27093596,92.77845777 " Black...

351

Fact #748: October 8, 2012 Components of Household Expenditures...  

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

but then declined until about 2004 when gasoline and motor oil expenditures began to rise again. The share of household expenditures on gasoline and oil was exactly the same...

352

Householder Symposium on Numerical Linear Algebra June 1721, 2002  

E-Print Network [OSTI]

for discussions. This year's symposium is held at Peebles Hotel Hydro in the small town of Peebles (populationHouseholder Symposium on Numerical Linear Algebra June 17­21, 2002 Peebles Hotel Hydro, Scotland

Higham, Nicholas J.

353

Pentek metal coating removal system: Baseline report  

SciTech Connect (OSTI)

The Pentek coating removal technology was tested and is being evaluated at Florida International University (FIU) as a baseline technology. In conjunction with FIU`s evaluation of efficiency and cost, this report covers evaluation conducted for safety and health issues. It is a commercially available technology and has been used for various projects at locations throughout the country. The Pentek coating removal system consisted of the ROTO-PEEN Scaler, CORNER-CUTTER{reg_sign}, and VAC-PAC{reg_sign}. They are designed to remove coatings from steel, concrete, brick, and wood. The Scaler uses 3M Roto Peen tungsten carbide cutters while the CORNER-CUTTER{reg_sign} uses solid needles for descaling activities. These hand tools are used with the VAC-PAC{reg_sign} vacuum system to capture dust and debris as removal of the coating takes place. The safety and health evaluation during the testing demonstration focused on two main areas of exposure: dust and noise. Dust exposure minimal, but noise exposure was significant. Further testing for each exposure is recommended because of the environment where the testing demonstration took place. It is feasible that the dust and noise levels will be higher in an enclosed operating environment of different construction. In addition, other areas of concern found were arm-hand vibration, whole-body, ergonomics, heat stress, tripping hazards, electrical hazards, machine guarding, and lockout/tagout.

NONE

1997-07-31T23:59:59.000Z

354

LTC vacuum blasting machine (concrete): Baseline report  

SciTech Connect (OSTI)

The LTC shot blast technology was tested and is being evaluated at Florida International University (FIU) as a baseline technology. In conjunction with FIU`s evaluation of efficiency and cost, this report covers the evaluation conducted for safety and health issues. It is a commercially available technology and has been used for various projects at locations throughout the country. The LTC 1073 Vacuum Blasting Machine uses a high-capacity, direct-pressure blasting system which incorporates a continuous feed for the blast media. The blast media cleans the surface within the contained brush area of the blast. It incorporates a vacuum system which removes dust and debris from the surface as it is blasted. The safety and health evaluation during the testing demonstration focused on two main areas of exposure: dust and noise. Dust exposure during maintenance activities was minimal, but due to mechanical difficulties dust monitoring could not be conducted during operation. Noise exposure was significant. Further testing for each of these exposures is recommended because of the outdoor environment where the testing demonstration took place. This may cause the results to be inaccurate. It is feasible that the dust and noise levels will be higher in an enclosed environment. In addition, other safety and health issues found were ergonomics, heat stress, tripping hazards, electrical hazards, lockout/tagout, and arm-hand vibration.

NONE

1997-07-31T23:59:59.000Z

355

LTC vacuum blasting machine (metal): Baseline report  

SciTech Connect (OSTI)

The LTC coating removal technology was tested and is being evaluated at Florida International University (FIU) as a baseline technology. In conjunction with evaluation of efficiency and cost, this report covers the evaluation conducted for safety and health issues. It is a commercially available technology and has been used for various projects at locations throughout the country. The LTC coating removal system consisted of several hand tools, a Roto Peen scaler, and a needlegun. They are designed to remove coatings from steel, concrete, brick, and wood. These hand tools are used with the LTC PTC-6 vacuum system to capture dust and debris as removal of the coating takes place. The safety and health evaluation during the testing demonstration focused on two main areas of exposure: dust and noise. The dust exposure was minimal but noise exposure was significant. Further testing for each exposure is recommended because of the environment where the testing demonstration took place. It is feasible that the dust and noise levels will be higher in an enclosed operating environment of different construction. In addition, other areas of concern found were arm-hand vibration, whole-body vibration, ergonomics, heat stress, tripping hazards, electrical hazards, machine guarding, and lockout/tagout.

NONE

1997-07-31T23:59:59.000Z

356

The LBNO long-baseline oscillation sensitivities with two conventional neutrino beams at different baselines  

E-Print Network [OSTI]

The proposed Long Baseline Neutrino Observatory (LBNO) initially consists of $\\sim 20$ kton liquid double phase TPC complemented by a magnetised iron calorimeter, to be installed at the Pyh\\"asalmi mine, at a distance of 2300 km from CERN. The conventional neutrino beam is produced by 400 GeV protons accelerated at the SPS accelerator delivering 700 kW of power. The long baseline provides a unique opportunity to study neutrino flavour oscillations over their 1st and 2nd oscillation maxima exploring the $L/E$ behaviour, and distinguishing effects arising from $\\delta_{CP}$ and matter. In this paper we show how this comprehensive physics case can be further enhanced and complemented if a neutrino beam produced at the Protvino IHEP accelerator complex, at a distance of 1160 km, and with modest power of 450 kW is aimed towards the same far detectors. We show that the coupling of two independent sub-MW conventional neutrino and antineutrino beams at different baselines from CERN and Protvino will allow to measure ...

:,; Agostino, L; Aittola, M; Alekou, A; Andrieu, B; Antoniou, F; Asfandiyarov, R; Autiero, D; Bsida, O; Balik, A; Ballett, P; Bandac, I; Banerjee, D; Bartmann, W; Bay, F; Biskup, B; Blebea-Apostu, A M; Blondel, A; Bogomilov, M; Bolognesi, S; Borriello, E; Brancus, I; Bravar, A; Buizza-Avanzini, M; Caiulo, D; Calin, M; Calviani, M; Campanelli, M; Cantini, C; Cata-Danil, G; Chakraborty, S; Charitonidis, N; Chaussard, L; Chesneanu, D; Chipesiu, F; Crivelli, P; Dawson, J; De Bonis, I; Declais, Y; Sanchez, P Del Amo; Delbart, A; Di Luise, S; Duchesneau, D; Dumarchez, J; Efthymiopoulos, I; Eliseev, A; Emery, S; Enqvist, T; Enqvist, K; Epprecht, L; Erykalov, A N; Esanu, T; Franco, D; Friend, M; Galymov, V; Gavrilov, G; Gendotti, A; Giganti, C; Gilardoni, S; Goddard, B; Gomoiu, C M; Gornushkin, Y A; Gorodetzky, P; Haesler, A; Hasegawa, T; Horikawa, S; Huitu, K; Izmaylov, A; Jipa, A; Kainulainen, K; Karadzhov, Y; Khabibullin, M; Khotjantsev, A; Kopylov, A N; Korzenev, A; Kosyanenko, S; Kryn, D; Kudenko, Y; Kuusiniemi, P; Lazanu, I; Lazaridis, C; Levy, J -M; Loo, K; Maalampi, J; Margineanu, R M; Marteau, J; Martin-Mari, C; Matveev, V; Mazzucato, E; Mefodiev, A; Mineev, O; Mirizzi, A; Mitrica, B; Murphy, S; Nakadaira, T; Narita, S; Nesterenko, D A; Nguyen, K; Nikolics, K; Noah, E; Novikov, Yu; Oprima, A; Osborne, J; Ovsyannikova, T; Papaphilippou, Y; Pascoli, S; Patzak, T; Pectu, M; Pennacchio, E; Periale, L; Pessard, H; Popov, B; Ravonel, M; Rayner, M; Resnati, F; Ristea, O; Robert, A; Rubbia, A; Rummukainen, K; Saftoiu, A; Sakashita, K; Sanchez-Galan, F; Sarkamo, J; Saviano, N; Scantamburlo, E; Sergiampietri, F; Sgalaberna, D; Shaposhnikova, E; Slupecki, M; Smargianaki, D; Stanca, D; Steerenberg, R; Sterian, A R; Sterian, P; Stoica, S; Strabel, C; Suhonen, J; Suvorov, V; Toma, G; Tonazzo, A; Trzaska, W H; Tsenov, R; Tuominen, K; Valram, M; Vankova-Kirilova, G; Vannucci, F; Vasseur, G; Velotti, F; Velten, P; Venturi, V; Viant, T; Vihonen, S; Vincke, H; Vorobyev, A; Weber, A; Wu, S; Yershov, N; Zambelli, L; Zito, M

2014-01-01T23:59:59.000Z

357

Energy Consumption | OpenEI  

Open Energy Info (EERE)

Consumption Consumption Dataset Summary Description This dataset contains hourly load profile data for 16 commercial building types (based off the DOE commercial reference building models) and residential buildings (based off the Building America House Simulation Protocols). This dataset also includes the Residential Energy Consumption Survey (RECS) for statistical references of building types by location. Source Commercial and Residential Reference Building Models Date Released April 18th, 2013 (9 months ago) Date Updated July 02nd, 2013 (7 months ago) Keywords building building demand building load Commercial data demand Energy Consumption energy data hourly kWh load profiles Residential Data Quality Metrics Level of Review Some Review Comment Temporal and Spatial Coverage

358

Manufacturing Consumption of Energy 1994  

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

Detailed Tables 28 Energy Information AdministrationManufacturing Consumption of Energy 1994 1. In previous MECS, the term "primary energy" was used to denote the "first use" of...

359

Manufacturing Consumption of Energy 1994  

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

1 Energy Information AdministrationManufacturing Consumption of Energy 1994 Introduction The market for natural gas has been changing for quite some time. As part of natural gas...

360

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

Note: This page contains sample records for the topic "baseline household consumption" 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

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

362

South Africa - Greenhouse Gas Emission Baselines and Reduction Potentials  

Open Energy Info (EERE)

Africa - Greenhouse Gas Emission Baselines and Reduction Potentials Africa - Greenhouse Gas Emission Baselines and Reduction Potentials from Buildings Jump to: navigation, search Name South Africa - Greenhouse Gas Emission Baselines and Reduction Potentials from Buildings Agency/Company /Organization United Nations Environment Programme Sector Energy Focus Area Buildings Topics Baseline projection, GHG inventory, Pathways analysis, Background analysis Resource Type Publications Website http://www.unep.org/sbci/pdfs/ Country South Africa UN Region Southern Africa References South Africa - Greenhouse Gas Emission Baselines and Reduction Potentials from Buildings[1] South Africa - Greenhouse Gas Emission Baselines and Reduction Potentials from Buildings Screenshot "This report aims to provide: a summary quantification of the influence of buildings on climate

363

Buildings Energy Data Book: 2.1 Residential Sector Energy Consumption  

Buildings Energy Data Book [EERE]

1 1 Type (1) Single-Family: 55.4 106.6 39.4 80.5% Detached 55.0 108.4 39.8 73.9% Attached 60.5 89.3 36.1 6.6% Multi-Family: 78.3 64.1 29.7 14.9% 2 to 4 units 94.3 85.0 35.2 6.3% 5 or more units 69.8 54.4 26.7 8.6% Mobile Homes 74.6 70.4 28.5 4.6% All Housing Types 58.7 95.0 37.0 100% 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 Housing Type

364

1993 baseline solid waste management system description  

SciTech Connect (OSTI)

Pacific Northwest Laboratory has prepared this report under the direction of Westinghouse Hanford Company. The report provides an integrated description of the system planned for managing Hanford`s solid low-level waste, low-level mixed waste, transuranic waste, and transuranic mixed waste. The primary purpose of this document is to illustrate a collective view of the key functions planned at the Hanford Site to handle existing waste inventories, as well as solid wastes that will be generated in the future. By viewing this system as a whole rather than as individual projects, key facility interactions and requirements are identified and a better understanding of the overall system may be gained. The system is described so as to form a basis for modeling the system at various levels of detail. Model results provide insight into issues such as facility capacity requirements, alternative system operating strategies, and impacts of system changes (ie., startup dates). This description of the planned Hanford solid waste processing system: defines a baseline system configuration; identifies the entering waste streams to be managed within the system; identifies basic system functions and waste flows; and highlights system constraints. This system description will evolve and be revised as issues are resolved, planning decisions are made, additional data are collected, and assumptions are tested and changed. Out of necessity, this document will also be revised and updated so that a documented system description, which reflects current system planning, is always available for use by engineers and managers. It does not provide any results generated from the many alternatives that will be modeled in the course of analyzing solid waste disposal options; such results will be provided in separate documents.

Armacost, L.L.; Fowler, R.A.; Konynenbelt, H.S.

1994-02-01T23:59:59.000Z

365

UNFCCC-Consolidated baseline and monitoring methodology for landfill...  

Open Energy Info (EERE)

TOOL Name: UNFCCC-Consolidated baseline and monitoring methodology for landfill gas project activities AgencyCompany Organization: United Nations Framework Convention on...

366

U.S. Department of Energy Performance Baseline Guide  

Broader source: Directives, Delegations, and Requirements [Office of Management (MA)]

The guide supports DOE O 413.3A and identifies key performance baseline development processes and practices. Does not cancel other directives.

2008-09-12T23:59:59.000Z

367

South Africa - Greenhouse Gas Emission Baselines and Reduction...  

Open Energy Info (EERE)

Potentials from Buildings Jump to: navigation, search Name South Africa - Greenhouse Gas Emission Baselines and Reduction Potentials from Buildings AgencyCompany Organization...

368

Ethiopia-National Greenhouse Gas Emissions Baseline Scenarios...  

Open Energy Info (EERE)

Website http:www.ens.dksitesens.dk Program Start 2011 Country Ethiopia Eastern Africa References National Greenhouse Gas Emissions Baseline Scenarios: Learning from...

369

World energy consumption  

SciTech Connect (OSTI)

Historical and projected world energy consumption information is displayed. The information is presented by region and fuel type, and includes a world total. Measurements are in quadrillion Btu. Sources of the information contained in the table are: (1) history--Energy Information Administration (EIA), International Energy Annual 1992, DOE/EIA-0219(92); (2) projections--EIA, World Energy Projections System, 1994. Country amounts include an adjustment to account for electricity trade. Regions or country groups are shown as follows: (1) Organization for Economic Cooperation and Development (OECD), US (not including US territories), which are included in other (ECD), Canada, Japan, OECD Europe, United Kingdom, France, Germany, Italy, Netherlands, other Europe, and other OECD; (2) Eurasia--China, former Soviet Union, eastern Europe; (3) rest of world--Organization of Petroleum Exporting Countries (OPEC) and other countries not included in any other group. Fuel types include oil, natural gas, coal, nuclear, and other. Other includes hydroelectricity, geothermal, solar, biomass, wind, and other renewable sources.

NONE

1995-12-01T23:59:59.000Z

370

Electricity Consumption | OpenEI  

Open Energy Info (EERE)

Consumption Consumption Dataset Summary Description Total annual electricity consumption by country, 1980 to 2009 (billion kilowatthours). Compiled by Energy Information Administration (EIA). Source EIA Date Released Unknown Date Updated Unknown Keywords EIA Electricity Electricity Consumption world Data text/csv icon total_electricity_net_consumption_1980_2009billion_kwh.csv (csv, 50.7 KiB) Quality Metrics Level of Review Peer Reviewed Comment Temporal and Spatial Coverage Frequency Time Period 1980 - 2009 License License Other or unspecified, see optional comment below Comment Rate this dataset Usefulness of the metadata Average vote Your vote Usefulness of the dataset Average vote Your vote Ease of access Average vote Your vote Overall rating Average vote Your vote Comments Login or register to post comments

371

Biofuels Consumption | OpenEI  

Open Energy Info (EERE)

Biofuels Consumption Biofuels Consumption Dataset Summary Description Total annual biofuels consumption and production data by country was compiled by the Energy Information Administration (EIA). Data is presented as thousand barrels per day. Source EIA Date Released Unknown Date Updated Unknown Keywords Biofuels Biofuels Consumption EIA world Data text/csv icon total_biofuels_production_2000_2010thousand_barrels_per_day.csv (csv, 9.3 KiB) text/csv icon total_biofuels_consumption_2000_2010thousand_barrels_per_day.csv (csv, 9.3 KiB) Quality Metrics Level of Review Peer Reviewed Comment Temporal and Spatial Coverage Frequency Time Period 2000 - 2010 License License Other or unspecified, see optional comment below Comment Rate this dataset Usefulness of the metadata Average vote Your vote

372

Coal consumption | OpenEI  

Open Energy Info (EERE)

consumption consumption Dataset Summary Description Total annual coal consumption by country, 1980 to 2009 (available as Quadrillion Btu). Compiled by Energy Information Administration (EIA). Source EIA Date Released Unknown Date Updated Unknown Keywords coal Coal consumption EIA world Data text/csv icon total_coal_consumption_1980_2009quadrillion_btu.csv (csv, 38.3 KiB) Quality Metrics Level of Review Peer Reviewed Comment Temporal and Spatial Coverage Frequency Time Period 1980 - 2009 License License Other or unspecified, see optional comment below Comment Rate this dataset Usefulness of the metadata Average vote Your vote Usefulness of the dataset Average vote Your vote Ease of access Average vote Your vote Overall rating Average vote Your vote Comments Login or register to post comments

373

Manufacturing Consumption of Energy 1994  

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

(MECS) > MECS 1994 Combined Consumption and Fuel Switching (MECS) > MECS 1994 Combined Consumption and Fuel Switching Manufacturing Energy Consumption Survey 1994 (Combined Consumption and Fuel Switching) Manufacturing Energy Consumption Logo Full Report - (file size 5.4 MB) pages:531 Selected Sections (PDF format) Contents (file size 56 kilobytes, 10 pages). Overview (file size 597 kilobytes, 11 pages). Chapters 1-3 (file size 265 kilobytes, 9 pages). Chapter 4 (file size 1,070 kilobytes, 15 pages). Appendix A - Detailed Tables Tables A1 - A8 (file size 1,031 kilobytes, 139 pages). Tables A9 - A23 (file size 746 kilobytes, 119 pages). Tables A24 - A29 (file size 485 kilobytes, 84 pages). Tables A30 - A44 (file size 338 kilobytes, 39 pages). Appendix B (file size 194 kilobytes, 24 pages). Appendix C (file size 116 kilobytes, 16 pages).

374

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

SciTech Connect (OSTI)

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

Poyer, D. A.; Decision and Information Sciences

2001-05-31T23:59:59.000Z

375

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.

376

Spent Nuclear Fuel Project technical baseline document. Fiscal year 1995: Volume 1, Baseline description  

SciTech Connect (OSTI)

This document is a revision to WHC-SD-SNF-SD-002, and is issued to support the individual projects that make up the Spent Nuclear Fuel Project in the lower-tier functions, requirements, interfaces, and technical baseline items. It presents results of engineering analyses since Sept. 1994. The mission of the SNFP on the Hanford site is to provide safety, economic, environmentally sound management of Hanford SNF in a manner that stages it to final disposition. This particularly involves K Basin fuel, although other SNF is involved also.

Womack, J.C. [Westinghouse Hanford Co., Richland, WA (United States); Cramond, R. [TRW (United States); Paedon, R.J. [SAIC (United States)] [and others

1995-03-13T23:59:59.000Z

377

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

378

Cape Canaveral Air Force Station integrated resource assessment. Volume 2, Baseline detail  

SciTech Connect (OSTI)

The US Air Force (USAF) has tasked the Pacific Northwest Laboratory (PNL), in support of the US Department of Energy (DOE) Federal Energy Management Program (FEMP), to assess energy use at Cape Canaveral Air Force Station (AFS). The information obtained from this assessment will be used in identifying energy resource opportunities to reduce overall energy consumption by the station. The primary focus of this report is to assess the current baseline energy consumption at Cape Canaveral AFS. It is A companion report to Volume 1, the Executive Summary, and Volume 3, the Resource Assessment. This assessment requires that information be obtained and characterized for buildings, utilities, energy sources, energy uses, and load profiles to be used to improve the current energy system on the station. The characteristics of electricity, diesel fuel, No. 2 fuel oil, and motor vehicle gasoline (MOGAS) are analyzed for on-base facilities. The assessment examines basic regional information used to determine energy-use intensity (EUI) values for Cape Canaveral AFS facilities by building, fuel type, and energy end use. It also provides a summary of electricity consumption from Florida Power and Light Company (FPL) metered data for 1985--1991. Load profile information obtained from FPL data is presented for the North, South, and Titan Substations for the four seasons of the year, including weekdays and weekends.

Wahlstrom, R.R.; McMordie, K.L.; Parker, S.A.; King, D.A.; Sandusky, W.F.

1993-12-01T23:59:59.000Z

379

Patrick Air Force Base integrated resource assessment. Volume 2, Baseline detail  

SciTech Connect (OSTI)

The US Air Force has tasked the Pacific Northwest Laboratory (PNL), in support of the US Department of Energy (DOE) Federal Energy Management Program (FEMP), to assess energy use at Patrick Air Force Base (AFB). The information obtained from this assessment will be used in identifying energy resource opportunities to reduce overall energy consumption on the base. The primary focus of this report is to assess the current baseline energy consumption at Patrick AFB. It is a comparison report to Volume 1, the Executive Summary, and Volume 3, the Resource Assessment. This assessment requires that information be obtained and characterized for buildings, utilities, energy sources, energy uses, and load profile information to be used to improve the characterization of energy use on the base. The characteristics of electricity, natural gas, and No. 2 fuel oil are analyzed for on-base facilities and housing. The assessment examines basic regional information used to determine energy-use intensity (EUI) values for Patrick AFB facilities by building, fuel type, and energy end use. It also provides a summary of electricity consumption from Florida Power and Light Company (FPL) metered data for 1985-1991. Load profile information obtained from FPL data is presented for the north and south substations for the four seasons of the year, including weekdays and weekends.

Wahlstrom, R.R.; King, D.A.; Parker, S.A.; Sandusky, W.F.

1993-08-01T23:59:59.000Z

380

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

Gasoline and Diesel Fuel Update (EIA)

All Reports & Publications All Reports & Publications Search By: Go Pick a date range: From: To: Go graph of U.S. electricity end use, as explained in the article text U.S. electricity sales have decreased in four of the past five years December 20, 2013 Gas furnace efficiency has large implications for residential natural gas use December 5, 2013 EIA publishes state fact sheets on residential energy consumption and characteristics August 19, 2013 All 48 related articles › ResidentialAvailable formats PDF Modeling Distributed Generation in the Buildings Sectors Released: August 29, 2013 This report focuses on how EIA models residential and commercial sector distributed generation, including combined heat and power, for the Annual Energy Outlook. State Fact Sheets on Household Energy Use

Note: This page contains sample records for the topic "baseline household consumption" 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

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

Gasoline and Diesel Fuel Update (EIA)

Air conditioning in nearly 100 million U.S. homes Air conditioning in nearly 100 million U.S. homes RECS 2009 - Release date: August 19, 2011 line chart:air conditioning in U.S. figure dataExcept in the temperate climate regions along the West coast, air conditioners (AC) are now standard equipment in most U.S. homes (Figure 1). As recently as 1993, only 68% of all occupied housing units had AC. The latest results from the 2009 Residential Energy Consumption Survey (RECS) show that 87 percent of U.S. households are now equipped with AC. This growth occurred among all housing types and in every Census region. Wider use has coincided with much improved energy efficiency standards for AC equipment, a population shift to hotter and more humid regions, and a housing boom during which average housing sizes increased.

382

Fact Sheet: Gas Prices and Oil Consumption Would Increase Without Biofuels  

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

Fact Sheet: Gas Prices and Oil Consumption Would Increase Without Fact Sheet: Gas Prices and Oil Consumption Would Increase Without Biofuels Fact Sheet: Gas Prices and Oil Consumption Would Increase Without Biofuels June 11, 2008 - 1:30pm Addthis Secretary of Energy Samuel W. Bodman and Secretary of Agriculture Edward T. Schafer sent a letter on June 11, 2008 to Senator Jeff Bingaman addressing a number of questions related to biofuels, food, and gasoline and diesel prices. Read the letter. Without Biofuels, Gas Prices Would Increase $.20 to $.35 per Gallon. The U.S. Department of Energy (DOE) estimates that gasoline prices would be between 20 cents to 35 cents per gallon higher without ethanol1, a first-generation biofuel. For a typical household, that means saving about $150 to $300 per year. For the U.S. overall, this saves gas expenditures of $28 billion to

383

Fact Sheet: Gas Prices and Oil Consumption Would Increase Without Biofuels  

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

Gas Prices and Oil Consumption Would Increase Without Gas Prices and Oil Consumption Would Increase Without Biofuels Fact Sheet: Gas Prices and Oil Consumption Would Increase Without Biofuels June 11, 2008 - 1:30pm Addthis Secretary of Energy Samuel W. Bodman and Secretary of Agriculture Edward T. Schafer sent a letter on June 11, 2008 to Senator Jeff Bingaman addressing a number of questions related to biofuels, food, and gasoline and diesel prices. Read the letter. Without Biofuels, Gas Prices Would Increase $.20 to $.35 per Gallon. The U.S. Department of Energy (DOE) estimates that gasoline prices would be between 20 cents to 35 cents per gallon higher without ethanol1, a first-generation biofuel. For a typical household, that means saving about $150 to $300 per year. For the U.S. overall, this saves gas expenditures of $28 billion to

384

Michigan Tech University Keweenaw Research Center Ecological Baseline Report  

E-Print Network [OSTI]

Michigan Tech University Keweenaw Research Center Ecological Baseline Report Lac La Belle Wetland;Michigan Tech University Keweenaw Research Center Ecological Baseline Report MDEQ Permit 06-31-0002-P 1 number 06-31-0002-P) to fill in 2.3 acres of wetland to expand a vehicle test course near the Michigan

385

An Adaptive Kalman Filter for Removing Baseline Wandering in ECG  

E-Print Network [OSTI]

An Adaptive Kalman Filter for Removing Baseline Wandering in ECG Signals MA Mneimneh, EE Yaz, MT misleads ECG anno- tators from accurate identification of the ECG features. Previous work that deals with baseline wandering re- moval requires the identification of the QRS complex or other ECG features prior

Povinelli, Richard J.

386

DOETEIAO32l/2 Residential Energy Consumption Survey; Consumption  

Gasoline and Diesel Fuel Update (EIA)

General information about EIA data on energy consumption may be obtained from Wray Smith, Director, Office of Energy Markets and End Use (202- 252-1617); Lynda T. Carlson,...

387

UNFCCC-Consolidated baseline and monitoring methodology for landfill gas  

Open Energy Info (EERE)

UNFCCC-Consolidated baseline and monitoring methodology for landfill gas UNFCCC-Consolidated baseline and monitoring methodology for landfill gas project activities Jump to: navigation, search Tool Summary LAUNCH TOOL Name: UNFCCC-Consolidated baseline and monitoring methodology for landfill gas project activities Agency/Company /Organization: United Nations Framework Convention on Climate Change (UNFCCC) Sector: Climate, Energy Focus Area: Renewable Energy, Non-renewable Energy, - Landfill Gas Topics: Baseline projection, GHG inventory Resource Type: Guide/manual Website: cdm.unfccc.int/public_inputs/meth/acm0001/index.html Cost: Free Language: English References: UNFCCC-Consolidated baseline and monitoring methodology for landfill gas project activities[1] This article is a stub. You can help OpenEI by expanding it. References

388

Brazil-Danish Government Baseline Workstream | Open Energy Information  

Open Energy Info (EERE)

Brazil-Danish Government Baseline Workstream Brazil-Danish Government Baseline Workstream Jump to: navigation, search Name Brazil-Danish Government Baseline Workstream Agency/Company /Organization Danish Government Partner Danish Ministry for Climate, Energy, and Building; The Danish Energy Agency Sector Energy Topics Implementation, Low emission development planning Program Start 2011 Country Brazil South America References Denmark[1] Overview Progress and Outcomes Capacity building needs identified are lessons learned, challenges and gaps, including those that may be common between countries, and aspects of good practice for assumptions, methodologies and other aspects of baseline setting. References ↑ "Denmark" Retrieved from "http://en.openei.org/w/index.php?title=Brazil-Danish_Government_Baseline_Workstream&oldid=699917"

389

Vietnam-Danish Government Baseline Workstream | Open Energy Information  

Open Energy Info (EERE)

Vietnam-Danish Government Baseline Workstream Vietnam-Danish Government Baseline Workstream Jump to: navigation, search Name Vietnam-Danish Government Baseline Workstream Agency/Company /Organization Danish Government Partner Danish Ministry for Climate, Energy, and Building; The Danish Energy Agency Sector Energy Topics Implementation, Low emission development planning Program Start 2011 Country Vietnam South-Eastern Asia References Denmark[1] Overview Progress and Outcomes Capacity building needs identified are lessons learned, challenges and gaps, including those that may be common between countries, and aspects of good practice for assumptions, methodologies and other aspects of baseline setting. References ↑ "Denmark" Retrieved from "http://en.openei.org/w/index.php?title=Vietnam-Danish_Government_Baseline_Workstream&oldid=699935"

390

Chile-Danish Government Baseline Workstream | Open Energy Information  

Open Energy Info (EERE)

Chile-Danish Government Baseline Workstream Chile-Danish Government Baseline Workstream Jump to: navigation, search Name Chile-Danish Government Baseline Workstream Agency/Company /Organization Danish Government Partner Danish Ministry for Climate, Energy, and Building; The Danish Energy Agency Sector Energy Topics Implementation, Low emission development planning Program Start 2011 Country Chile South America References Denmark[1] Overview Progress and Outcomes Capacity building needs identified are lessons learned, challenges and gaps, including those that may be common between countries, and aspects of good practice for assumptions, methodologies and other aspects of baseline setting. References ↑ "Denmark" Retrieved from "http://en.openei.org/w/index.php?title=Chile-Danish_Government_Baseline_Workstream&oldid=699919"

391

Kenya-Danish Government Baseline Workstream | Open Energy Information  

Open Energy Info (EERE)

Kenya-Danish Government Baseline Workstream Kenya-Danish Government Baseline Workstream Jump to: navigation, search Name Kenya-Danish Government Baseline Workstream Agency/Company /Organization Danish Government Partner Danish Ministry for Climate, Energy, and Building; The Danish Energy Agency Sector Energy Topics Implementation, Low emission development planning Program Start 2011 Country Kenya Eastern Africa References Denmark[1] Overview Progress and Outcomes Capacity building needs identified are lessons learned, challenges and gaps, including those that may be common between countries, and aspects of good practice for assumptions, methodologies and other aspects of baseline setting. References ↑ "Denmark" Retrieved from "http://en.openei.org/w/index.php?title=Kenya-Danish_Government_Baseline_Workstream&oldid=699929"

392

South Africa-Danish Government Baseline Workstream | Open Energy  

Open Energy Info (EERE)

Danish Government Baseline Workstream Danish Government Baseline Workstream Jump to: navigation, search Name South Africa-Danish Government Baseline Workstream Agency/Company /Organization Danish Government Partner Danish Ministry for Climate, Energy, and Building; The Danish Energy Agency Sector Energy Topics Implementation, Low emission development planning Program Start 2011 Country South Africa Southern Africa References Denmark[1] Overview Progress and Outcomes Capacity building needs identified are lessons learned, challenges and gaps, including those that may be common between countries, and aspects of good practice for assumptions, methodologies and other aspects of baseline setting. References ↑ "Denmark" Retrieved from "http://en.openei.org/w/index.php?title=South_Africa-Danish_Government_Baseline_Workstream&oldid=699933"

393

Thailand-Danish Government Baseline Workstream | Open Energy Information  

Open Energy Info (EERE)

Thailand-Danish Government Baseline Workstream Thailand-Danish Government Baseline Workstream Jump to: navigation, search Name Thailand-Danish Government Baseline Workstream Agency/Company /Organization Danish Government Partner Danish Ministry for Climate, Energy, and Building; The Danish Energy Agency Sector Energy Topics Implementation, Low emission development planning Program Start 2011 Country Thailand South-Eastern Asia References Denmark[1] Overview Progress and Outcomes Capacity building needs identified are lessons learned, challenges and gaps, including those that may be common between countries, and aspects of good practice for assumptions, methodologies and other aspects of baseline setting. References ↑ "Denmark" Retrieved from "http://en.openei.org/w/index.php?title=Thailand-Danish_Government_Baseline_Workstream&oldid=699937

394

Mexico-Danish Government Baseline Workstream | Open Energy Information  

Open Energy Info (EERE)

Mexico-Danish Government Baseline Workstream Mexico-Danish Government Baseline Workstream Jump to: navigation, search Name Mexico-Danish Government Baseline Workstream Agency/Company /Organization Danish Government Partner Danish Ministry for Climate, Energy, and Building; The Danish Energy Agency Sector Energy Topics Implementation, Low emission development planning Program Start 2011 Country Mexico Central America References Denmark[1] Overview Progress and Outcomes Capacity building needs identified are lessons learned, challenges and gaps, including those that may be common between countries, and aspects of good practice for assumptions, methodologies and other aspects of baseline setting. References ↑ "Denmark" Retrieved from "http://en.openei.org/w/index.php?title=Mexico-Danish_Government_Baseline_Workstream&oldid=699931

395

China-Danish Government Baseline Workstream | Open Energy Information  

Open Energy Info (EERE)

China-Danish Government Baseline Workstream China-Danish Government Baseline Workstream Jump to: navigation, search Name China-Danish Government Baseline Workstream Agency/Company /Organization Danish Government Partner Danish Ministry for Climate, Energy, and Building; The Danish Energy Agency Sector Energy Topics Implementation, Low emission development planning Program Start 2011 Country China Eastern Asia References Denmark[1] Overview Progress and Outcomes Capacity building needs identified are lessons learned, challenges and gaps, including those that may be common between countries, and aspects of good practice for assumptions, methodologies and other aspects of baseline setting. References ↑ "Denmark" Retrieved from "http://en.openei.org/w/index.php?title=China-Danish_Government_Baseline_Workstream&oldid=699921"

396

India-Danish Government Baseline Workstream | Open Energy Information  

Open Energy Info (EERE)

India-Danish Government Baseline Workstream India-Danish Government Baseline Workstream Jump to: navigation, search Name India-Danish Government Baseline Workstream Agency/Company /Organization Danish Government Partner Danish Ministry for Climate, Energy, and Building; The Danish Energy Agency Sector Energy Topics Implementation, Low emission development planning Program Start 2011 Country India Southern Asia References Denmark[1] Overview Progress and Outcomes Capacity building needs identified are lessons learned, challenges and gaps, including those that may be common between countries, and aspects of good practice for assumptions, methodologies and other aspects of baseline setting. References ↑ "Denmark" Retrieved from "http://en.openei.org/w/index.php?title=India-Danish_Government_Baseline_Workstream&oldid=699927"

397

Advances in Household Appliances- A Review  

SciTech Connect (OSTI)

An overview of options and potential barriers and risks for reducing the energy consumption, peak demand, and emissions for seven key energy consuming residential products (refrigerator-freezers, dishwashers, clothes washers, clothes dryers, electric ovens, gas ovens and microwave ovens) is presented. The paper primarily concentrates on the potential energy savings from the use of advanced technologies in appliances for the U.S. market. The significance and usefulness of each technology was evaluated in order to prioritize the R&D needs to improve energy efficiency of appliances in view of energy savings, cost, and complexity. The paper provides a snapshot of the future R&D needs for each of the technologies along with the associated barriers. Although significant energy savings may be achieved, one of the major barriers in most cases is high first cost. One way of addressing this issue and promoting the introduction of new technologies is to level the playing field for all manufacturers by establishing Minimum Energy Performance Standards (MEPS) which are not cost prohibitive and promoting energy efficient products through incentives to both manufacturers and consumers.

Bansal, Pradeep [ORNL; Vineyard, Edward Allan [ORNL; Abdelaziz, Omar [ORNL

2011-01-01T23:59:59.000Z

398

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

399

An exploratory study of Spanish households' WEEE disposal behaviour  

Science Journals Connector (OSTI)

This paper presents the findings of an exploratory study based on a survey of 1,537 households in Spain. The questionnaire included 23 key questions regarding the number of appliances in use, previous appliances lifetimes, reasons for buying each new appliance and end-of-life handling of discarded appliances. The distribution of the households along a number of relevant factors was analysed and a prototypical household was identified. A non-parametric analysis of the duration of each type of appliance has also been carried out and it was found that television sets are the most durable of the appliances considered. Survival rates for irons fall more rapidly than for microwaves. Moreover, television sets are the most durable of the appliances considered. Replacement rates of personal computers rapidly increase after approximately six to eight years. Finally, a statistical analysis of the respondents motivations for recycling the appliances considered in this study was carried out.

Ester Gutiérrez; Belarmino Adenso-Díaz; Sebastián Lozano; Plácido Moreno

2011-01-01T23:59:59.000Z

400

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

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

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

Note: This page contains sample records for the topic "baseline household consumption" 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

Fuel Consumption | ornl.gov  

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

Fuel Consumption, CO2 Emissions, And A Simple Connection To the Vehicle Fuel Consumption, CO2 Emissions, And A Simple Connection To the Vehicle Road Load Equation Jan 15 2014 11:30 AM - 12:30 PM Glen E. Johnson Tennessee Tech University, Cookeville Energy and Transportation Science Division Seminar National Transportation Research Center, Room C-04 CONTACT : Email: Andreas Malikopoulos Phone:865.382.7827 Add to Calendar SHARE Ambitious goals have been set to reduce fuel consumption and CO2 emissions over the next generation. Starting from first principles, we will derive relations to connect fuel consumption and carbon dioxide emissions to a vehicle's road load equation. The model suggests approaches to facilitate achievement of future fuel and emissions targets. About the speaker: Dr. Johnson is a 1973 Mechanical Engineering graduate of Worcester

402

Manufacturing Consumption of Energy 1994  

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

energy data used in this report do not reflect adjustments for losses in electricity generation or transmission. energy data used in this report do not reflect adjustments for losses in electricity generation or transmission. 1 The manufacturing sector is composed of establishments classified in Standard Industrial Classification 20 through 39 of the U.S. economy as defined 2 by the Office of Management and Budget. The manufacturing sector is a part of the industrial sector, which also includes mining; construction; and agriculture, forestry, and fishing. The EIA also conducts energy consumption surveys in the residential, commercial buildings, and residential transportation sectors: the Residential Energy 3 Consumption Survey (RECS); the Commercial Buildings Energy Consumption Survey (CBECS); and, until recently, the Residential Transportation Energy Consumption Survey (RTECS).

403

All Consumption Tables.vp  

Gasoline and Diesel Fuel Update (EIA)

17 17 Table C12. Total Energy Consumption, Gross Domestic Product (GDP), Energy Consumption per Real Dollar of GDP, Ranked by State, 2011 Rank Total Energy Consumption Gross Domestic Product (GDP) Energy Consumption per Real Dollar of GDP State Trillion Btu State Billion Chained (2005) Dollars State Thousand Btu per Chained (2005) Dollar 1 Texas 12,206.6 California 1,735.4 Louisiana 19.7 2 California 7,858.4 Texas 1,149.9 Wyoming 17.5 3 Florida 4,217.1 New York 1,016.4 North Dakota 15.4 4 Louisiana 4,055.3 Florida 661.1 Alaska 14.3 5 Illinois 3,977.8 Illinois 582.1 Mississippi 13.8 6 Ohio 3,827.6 Pennsylvania 500.4 Kentucky 13.5

404

Energy Consumption in Access Networks  

Science Journals Connector (OSTI)

We present a comparison of energy consumption of access networks. We consider passive optical networks, fiber to the node, point-to-point optical systems and WiMAX. Optical access...

Baliga, Jayant; Ayre, Robert; Sorin, Wayne V; Hinton, Kerry; Tucker, Rodney S

405

The Wealth-Consumption Ratio  

E-Print Network [OSTI]

We derive new estimates of total wealth, the returns on total wealth, and the wealth effect on consumption. We estimate the prices of aggregate risk from bond yields and stock returns using a no-arbitrage model. Using these ...

Verdelhan, Adrien Frederic

406

Progressive consumption : strategic sustainable excess  

E-Print Network [OSTI]

Trends in the marketplace show that urban dwellers are increasingly supporting locally produced foods. This thesis argues for an architecture that responds to our cultures consumptive behaviors. Addressing the effects of ...

Bonham, Daniel J. (Daniel Joseph MacLeod)

2007-01-01T23:59:59.000Z

407

Energy consumption of building 39  

E-Print Network [OSTI]

The MIT community has embarked on an initiative to the reduce energy consumption and in accordance with the Kyoto Protocol. This thesis seeks to further expand our understanding of how the MIT campus consumes energy and ...

Hopeman, Lisa Maria

2007-01-01T23:59:59.000Z

408

Energy Consumption Profile for Energy  

E-Print Network [OSTI]

317 Chapter 12 Energy Consumption Profile for Energy Harvested WSNs T. V. Prabhakar, R Venkatesha.............................................................................................318 12.2 Energy Harvesting ...................................................................................318 12.2.1 Motivations for Energy Harvesting...............................................319 12

Langendoen, Koen

409

Manufacturing Consumption of Energy 1994  

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

S Y M n i 1 y 2 i (W i ) (W i 1) , Energy Information Administration, Manufacturing Energy Consumption Survey: Methodological Report 1985. Although this report describes 44...

410

Optimal consumption strategies under model uncertainty  

E-Print Network [OSTI]

Optimal consumption strategies under model uncertainty Christian Burgert, Ludger R of finding optimal consumption strategies in an incomplete semimartingale market model under model uncertainty. The quality of a consumption strategy is measured by not only one probability measure

Rüschendorf, Ludger

411

Exploring Chinas Materialization Process with Economic Transition: Analysis of Raw Material Consumption and Its Socioeconomic Drivers  

Science Journals Connector (OSTI)

Understanding the key drivers behind Chinas mass consumption of raw materials is thus crucial for developing sustainable resource management and providing valuable insights into how other emerging economies may be aiming to accomplish a low resource-dependent future. ... Of these two influencing factors, urbanization is the predominant driving force behind increasing RMC, characterized by the rapid increase in urbanization-related investment, notably in the construction sector (e.g., infrastructure, real estate), and rises in urban household consumption. ... Environmental sustainability can only be achieved by timely technol. ...

Heming Wang; Xin Tian; Hiroki Tanikawa; Miao Chang; Seiji Hashimoto; Yuichi Moriguchi; Zhongwu Lu

2014-04-10T23:59:59.000Z

412

OpenEI - Electricity Consumption  

Open Energy Info (EERE)

Annual Electricity Annual Electricity Consumption (1980 - 2009) http://en.openei.org/datasets/node/877 Total annual electricity consumption by country, 1980 to 2009 (billion kilowatthours). Compiled by Energy Information Administration (EIA). License

Type of License:  Other (please specify below)
Source of data

413

Manufacturing consumption of energy 1991  

SciTech Connect (OSTI)

This report provides estimates on energy consumption in the manufacturing sector of the US economy. These estimates are based on data from the 1991 Manufacturing Energy Consumption Survey (MECS). This survey--administered by the Energy End Use and Integrated Statistics Division, Office of Energy Markets and End Use, Energy Information Administration (EIA)--is the most comprehensive source of national-level data on energy-related information for the manufacturing industries.

Not Available

1994-12-01T23:59:59.000Z

414

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

415

Household solid waste characteristics and management in Chittagong, Bangladesh  

SciTech Connect (OSTI)

Solid waste management (SWM) is a multidimensional challenge faced by urban authorities, especially in developing countries like Bangladesh. We investigated per capita waste generation by residents, its composition, and the households' attitudes towards waste management at Rahman Nagar Residential Area, Chittagong, Bangladesh. The study involved a structured questionnaire and encompassed 75 households from five different socioeconomic groups (SEGs): low (LSEG), lower middle (LMSEG), middle (MSEG), upper middle (UMSEG) and high (HSEG). Wastes, collected from all of the groups of households, were segregated and weighed. Waste generation was 1.3 kg/household/day and 0.25 kg/person/day. Household solid waste (HSW) was comprised of nine categories of wastes with vegetable/food waste being the largest component (62%). Vegetable/food waste generation increased from the HSEG (47%) to the LSEG (88%). By weight, 66% of the waste was compostable in nature. The generation of HSW was positively correlated with family size (r{sub xy} = 0.236, p < 0.05), education level (r{sub xy} = 0.244, p < 0.05) and monthly income (r{sub xy} = 0.671, p < 0.01) of the households. Municipal authorities are usually the responsible agencies for solid waste collection and disposal, but the magnitude of the problem is well beyond the ability of any municipal government to tackle. Hence dwellers were found to take the service from the local waste management initiative. Of the respondents, an impressive 44% were willing to pay US$0.3 to US$0.4 per month to waste collectors and it is recommended that service charge be based on the volume of waste generated by households. Almost a quarter (22.7%) of the respondents preferred 12-1 pm as the time period for their waste to be collected. This study adequately shows that household solid waste can be converted from burden to resource through segregation at the source, since people are aware of their role in this direction provided a mechanism to assist them in this pursuit exists and the burden is distributed according to the amount of waste generated.

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

2008-07-01T23:59:59.000Z

416

Commercial Buildings Energy Consumption and Expenditures 1992...  

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

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

417

Demonstrating Fuel Consumption and Emissions Reductions with...  

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

Fuel Consumption and Emissions Reductions with Next Generation Model-Based Diesel Engine Control Demonstrating Fuel Consumption and Emissions Reductions with Next Generation...

418

New York: Weatherizing Westbeth Reduces Energy Consumption |...  

Energy Savers [EERE]

York: Weatherizing Westbeth Reduces Energy Consumption New York: Weatherizing Westbeth Reduces Energy Consumption August 21, 2013 - 12:00am Addthis The New York State Homes and...

419

Energy Information Administration - Commercial Energy Consumption...  

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

8A. Natural Gas Consumption and Conditional Energy Intensity by Census Division for All Buildings, 2003: Part 2 Total Natural Gas Consumption (billion cubic feet) Total Floorspace...

420

Energy Information Administration - Commercial Energy Consumption...  

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

2A. Natural Gas Consumption and Conditional Energy Intensity by Year Constructed for All Buildings, 2003 Total Natural Gas Consumption (billion cubic feet) Total Floorspace of...

Note: This page contains sample records for the topic "baseline household consumption" 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

Energy Information Administration - Commercial Energy Consumption...  

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

0A. Natural Gas Consumption and Conditional Energy Intensity by Climate Zonea for All Buildings, 2003 Total Natural Gas Consumption (billion cubic feet) Total Floorspace of...

422

Energy Information Administration - Commercial Energy Consumption...  

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

7A. Natural Gas Consumption and Conditional Energy Intensity by Census Division for All Buildings, 2003: Part 1 Total Natural Gas Consumption (billion cubic feet) Total Floorspace...

423

Energy Information Administration - Commercial Energy Consumption...  

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

Table C22. Electricity Consumption and Conditional Energy Intensity by Year Constructed for Non-Mall Buildings, 2003 Total Electricity Consumption (billion kWh) Total Floorspace...

424

Energy Information Administration - Commercial Energy Consumption...  

Gasoline and Diesel Fuel Update (EIA)

5A. Electricity Consumption and Conditional Energy Intensity by Census Region for All Buildings, 2003 Total Electricity Consumption (billion kWh) Total Floorspace of Buildings...

425

Energy Information Administration - Commercial Energy Consumption...  

Gasoline and Diesel Fuel Update (EIA)

5A. Natural Gas Consumption and Conditional Energy Intensity by Census Region for All Buildings, 2003 Total Natural Gas Consumption (billion cubic feet) Total Floorspace of...

426

Energy Information Administration - Commercial Energy Consumption...  

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

7A. Electricity Consumption and Conditional Energy Intensity by Census Division for All Buildings, 2003: Part 1 Total Electricity Consumption (billion kWh) Total Floorspace of...

427

Energy Information Administration - Commercial Energy Consumption...  

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

2A. Electricity Consumption and Conditional Energy Intensity by Year Constructed for All Buildings, 2003 Total Electricity Consumption (billion kWh) Total Floorspace of Buildings...

428

Energy Information Administration - Commercial Energy Consumption...  

Gasoline and Diesel Fuel Update (EIA)

A. Consumption and Gross Energy Intensity by Year Constructed for Sum of Major Fuels for All Buildings, 2003 Sum of Major Fuel Consumption (trillion Btu) Total Floorspace of...

429

Energy Information Administration - Commercial Energy Consumption...  

Gasoline and Diesel Fuel Update (EIA)

8A. Electricity Consumption and Conditional Energy Intensity by Census Division for All Buildings, 2003: Part 2 Total Electricity Consumption (billion kWh) Total Floorspace of...

430

Energy Information Administration - Commercial Energy Consumption...  

Gasoline and Diesel Fuel Update (EIA)

A. Consumption and Gross Energy Intensity by Climate Zonea for All Buildings, 2003 Sum of Major Fuel Consumption (trillion Btu) Total Floorspace of Buildings (million square feet)...

431

Energy Information Administration - Commercial Energy Consumption...  

Gasoline and Diesel Fuel Update (EIA)

0. Consumption and Gross Energy Intensity by Climate Zonea for Non-Mall Buildings, 2003 Sum of Major Fuel Consumption (trillion Btu) Total Floorspace of Buildings (million square...

432

Energy Information Administration - Commercial Energy Consumption...  

Gasoline and Diesel Fuel Update (EIA)

9A. Natural Gas Consumption and Conditional Energy Intensity by Census Division for All Buildings, 2003: Part 3 Total Natural Gas Consumption (billion cubic feet) Total Floorspace...

433

Energy Information Administration - Commercial Energy Consumption...  

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

9A. Electricity Consumption and Conditional Energy Intensity by Census Division for All Buildings, 2003: Part 3 Total Electricity Consumption (billion kWh) Total Floorspace of...

434

Energy Information Administration - Commercial Energy Consumption...  

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

0A. Electricity Consumption and Conditional Energy Intensity by Climate Zonea for All Buildings, 2003 Total Electricity Consumption (billion kWh) Total Floorspace of Buildings...

435

Energy Information Administration - Transportation Energy Consumption...  

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

Energy Consumption Transportation Energy Consumption Surveys energy used by vehicles EIA conducts numerous energy-related surveys and other information programs. In general, the...

436

Buildings Energy Data Book: 4.4 Legislation Affecting Energy Consumption of Federal Buildings and Facilities  

Buildings Energy Data Book [EERE]

1 1 Energy Policy Act of 2005, Provisions Affecting Energy Consumption in Federal Buildings Source(s): Energy Management Requirements - Amended reduction goals set by the National Energy Conservation Policy Act, and requires increasing percentage reductions in energy consumption through FY 2015, with a final energy consumption reduction goal of 20 percent savings in FY 2015, as compared to the baseline energy consumption of Federal buildings in FY 2003. (These goals were superseded by Section 431 of the Energy Independence and Security Act of 2007.) [Section 102] Energy Use Measurement and Accountability - Requires that all Federal buildings be metered to measure electricity use by 2012. [Section 103] Procurement of Energy Efficient Products - Requires all Federal agencies to procure ENERGY STAR qualified products, for product

437

Table 5.1. U.S. Number of Vehicles, Vehicle-Miles, Motor Fuel Consumption  

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

. U.S. Number of Vehicles, Vehicle-Miles, Motor Fuel Consumption . U.S. Number of Vehicles, Vehicle-Miles, Motor Fuel Consumption and Expenditures, 1994 1993 Household and 1994 Vehicle Characteristics RSE Column Factor: Number of Vehicles Vehicle-Miles Traveled Motor Fuel Consumption Motor Fuel Expenditures RSE Row Factor: (million) (percent) (billion) (percent) (billion gallons) (gallon percent) (quadril- lion Btu) (billion dollars) (percent) 0.9 0.8 1.1 1.0 1.1 1.0 1.1 1.1 1.0 Household Characteristics Total .................................................... 156.8 100.0 1,793 100.0 90.6 100.0 11.2 104.7 100.0 2.8 Census Region and Division Northeast ........................................... 26.6 17.0 299 16.7 14.5 16.0 1.8 17.2 16.4 5.7 New England ................................... 7.6 4.8 84 4.7 4.1 4.5 0.5 4.8 4.6 13.8 Middle Atlantic

438

The Impact of Using Derived Fuel Consumption Maps to Predict...  

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

The Impact of Using Derived Fuel Consumption Maps to Predict Fuel Consumption The Impact of Using Derived Fuel Consumption Maps to Predict Fuel Consumption Poster presented at the...

439

Information architecture. Volume 2, Part 1: Baseline analysis summary  

SciTech Connect (OSTI)

The Department of Energy (DOE) Information Architecture, Volume 2, Baseline Analysis, is a collaborative and logical next-step effort in the processes required to produce a Departmentwide information architecture. The baseline analysis serves a diverse audience of program management and technical personnel and provides an organized way to examine the Department`s existing or de facto information architecture. A companion document to Volume 1, The Foundations, it furnishes the rationale for establishing a Departmentwide information architecture. This volume, consisting of the Baseline Analysis Summary (part 1), Baseline Analysis (part 2), and Reference Data (part 3), is of interest to readers who wish to understand how the Department`s current information architecture technologies are employed. The analysis identifies how and where current technologies support business areas, programs, sites, and corporate systems.

NONE

1996-12-01T23:59:59.000Z

440

Establish Employee Commuting Behavior Baseline for Greenhouse Gas Profile |  

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

Establish Employee Commuting Behavior Baseline for Greenhouse Gas Establish Employee Commuting Behavior Baseline for Greenhouse Gas Profile Establish Employee Commuting Behavior Baseline for Greenhouse Gas Profile October 7, 2013 - 1:49pm Addthis YOU ARE HERE Step 2 For evaluating a greenhouse gas (GHG) profile, once employee commuting survey data are collected and priority worksites have been identified, the survey responses should be analyzed for each major worksite to establish a behavior baseline. Depending on the agency's size and where it places accountability for GHG commuting emissions reduction goals, it may be to most appropriate to have individual programs or operating units assess their own employee commute data. Exceptions should be made when programs share facilities. For example, at a headquarters office building, a single program may take

Note: This page contains sample records for the topic "baseline household consumption" 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

The Travel Behavior of Immigrants and Race/Ethnicity Groups: An Analysis of the 2001 National Household Transportation Survey  

E-Print Network [OSTI]

the average household size for Hispanic respondents isper year, while households of black and Hispanic respondentsHispanic versus settled and native born residents. Vehicle ownership is highly correlated with mode choice as households

Handy, Susan L; Tal, Gil

2005-01-01T23:59:59.000Z

442

2003 Commercial Buildings Energy Consumption - What is an RSE  

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

Home > Households, Buildings & Industry > Commercial Buildings Energy Consumption Survey (CBECS) > 2003 Detailed Tables > What is an RSE? What is an RSE? The estimates in the Commercial Buildings Energy Consumption Survey (CBECS) are based on data reported by representatives of a statistically-designed subset of the entire commercial building population in the United States, or a "sample". Consequently, the estimates differ from the true population values. However, the sample design permits us to estimate the sampling error in each value. It is important to understand: CBECS estimates should not be considered as finite point estimates, but as estimates with some associated error in each direction. The standard error is a measure of the reliability or precision of the survey statistic. The value for the standard error can be used to construct confidence intervals and to perform hypothesis tests by standard statistical methods. Relative Standard Error (RSE) is defined as the standard error (square root of the variance) of a survey estimate, divided by the survey estimate and multiplied by 100.

443

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...

444

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

445

Alcohol consumption, Lewis phenotypes, and risk of ischemic heart disease  

SciTech Connect (OSTI)

The authors have previously found an increased risk of ischemic heart disease (IHD) in men with the Lewis phenotype Le(a[minus]b[minus]) and suggested that the Lewis blood group has a close genetic relation with insulin resistance. The authors have investigated whether any conventional risk factors explain the increased risk in Le(a[minus]b[minus]) men. 3,383 men aged 53-75 years were examined in 1985-86, and morbidity and mortality during the next 4 years were recorded. At baseline, the authors excluded 343 men with a history of myocardial infarction, angina pectoris, intermittent claudication, or stroke. The potential risk factors examined were alcohol consumption, physical activity, tobacco smoking, serum cotinine, serum lipids, body-mass index, blood pressure, prevalence of hypertension and non-insulin-dependent diabetes mellitus, and social class. In 280 (9.6%) men with Le(a[minus]b[minus]), alcohol was the only risk factor significantly associated with risk of IHD. There was a significant inverse dose-effect relation between alcohol consumption and risk; trend tests, with adjustment for age, were significant for fatal IHD (p=0.02), all IHD (p=0.03), and all causes of death (p=0.02). In 2649 (90.4%) men with other phenotypes, there was a limited negative association with alcohol consumption. In Le(a[minus]b[minus]) men, a group genetically at high risk of IHD, alcohol consumption seems to be especially protective. The authors suggest that alcohol consumption may modify insulin resistance in Le(a[minus]b[minus]) men.

Hein, H.O.; Suadicani, P.; Gyntelberg, F. (Rigshospitalet State Univ. Hospital, Copenhagen (Denmark). Epidemiological Research Unit); Sorenson, H. (Rigshospitalet State Univ. Hospital, Copenhagen (Denmark). Dept. of Chemical Immunology); Hein, H.O. (Univ. of Copenhagen (Denmark). Dept. of Internal Medicine)

1993-02-13T23:59:59.000Z

446

Household Segmentation in Food Insecurity and Soil Improving Practices in Ghana  

E-Print Network [OSTI]

secure household, and households farming medium quality soil increase the probability of adopting soil improving practices. Application of chemical fertilizers, commercial seeds, and pesticides, along with operating under a seasonal lease tenure...

Nata, Jifar T

2013-08-09T23:59:59.000Z

447

Logistic regression models for predicting trip reporting accuracy in GPS-enhanced household travel surveys  

E-Print Network [OSTI]

This thesis presents a methodology for conducting logistic regression modeling of trip and household information obtained from household travel surveys and vehicle trip information obtained from global positioning systems (GPS) to better understand...

Forrest, Timothy Lee

2007-04-25T23:59:59.000Z

448

Fact #747: October 1, 2012 Behind Housing, Transportation is the Top Household Expenditure  

Broader source: Energy.gov [DOE]

Except for housing, transportation was the largest single expenditure for the average American household in 2010. The average household spends more on transportation in a year than on food. Vehicle...

449

Fact #727: May 14, 2012 Nearly Twenty Percent of Households Own Three or More Vehicles  

Broader source: Energy.gov [DOE]

Household vehicle ownership has changed over the last six decades. In 1960, over twenty percent of households did not own a vehicle, but by 2010, that number fell to less than 10%. The number of...

450

Fact #729: May 28, 2012 Secondary Household Vehicles Travel Fewer Miles  

Broader source: Energy.gov [DOE]

When a household has more than one vehicle, the secondary vehicles travel fewer miles than the primary vehicle. In a two-vehicle household, the second vehicle travels less than half of the miles...

451

A Comparison of Household Budget Allocation Patterns Between Hispanic Americans and Non-Hispanic White Americans  

Science Journals Connector (OSTI)

The budget allocation patterns of Hispanic versus non-Hispanic White households are examined. Annual household expenditure data from 1980 to 1992 are ... Index (1990). The sample includes 588 Hispanic and 8,444 n...

Jessie X. Fan; Virginia Solis Zuiker

1998-06-01T23:59:59.000Z

452

The household production function approach to valuing climate: the case of Japan  

Science Journals Connector (OSTI)

In fact ours is not the first attempt to use the household production function technique empirically to estimate the ... climate and the impact of climate change on households. But our analysis uses repeated cros...

David Maddison; Katrin Rehdanz; Daiju Narita

2013-01-01T23:59:59.000Z

453

Understanding the Effect of Baseline Modeling Implementation Choices on  

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

Understanding the Effect of Baseline Modeling Implementation Choices on Understanding the Effect of Baseline Modeling Implementation Choices on Analysis of Demand Response Performance Title Understanding the Effect of Baseline Modeling Implementation Choices on Analysis of Demand Response Performance Publication Type Conference Paper LBNL Report Number LBNL-5560E Year of Publication 2013 Authors Addy, Nathan, Johanna L. Mathieu, Sila Kiliccote, and Duncan S. Callaway Conference Name ASME 2013 International Mechanical Engineering Congress & Exposition Conference Location Houston, TX Keywords market sectors, technologies Abstract Accurate evaluation of the performance of buildings participating in Demand Response (DR) programs is critical to the adoption and improvement of these programs. Typically, we calculate load sheds during DR events by comparing observed electric demand against counterfactual predictions made using statistical baseline models. Many baseline models exist and these models can produce different shed calculations. Moreover, modelers implementing the same baseline model can make different modeling implementation choices, which may affect shed estimates. In this work, using real data, we analyze the effect of different modeling implementation choices on shed predictions. We focused on five issues: weather data source, resolution of data, methods for determining when buildings are occupied, methods for aligning building data with temperature data, and methods for power outage filtering. Results indicate sensitivity to the weather data source and data filtration methods as well as an immediate potential for automation of methods to choose building occupied modes.

454

Phase Characteristics of the ALMA 3 km Baseline Data  

E-Print Network [OSTI]

We present the phase characteristics study of the Atacama Large Millimeter/submillimeter Array (ALMA) long (up to 3 km) baseline, which is the longest baseline tested so far using ALMA. The data consist of long time-scale (10 - 20 minutes) measurements on a strong point source (i.e., bright quasar) at various frequency bands (bands 3, 6, and 7, which correspond to the frequencies of about 88 GHz, 232 GHz, and 336 GHz). Water vapor radiometer (WVR) phase correction works well even at long baselines, and the efficiency is better at higher PWV (>1 mm) condition, consistent with the past studies. We calculate the spatial structure function of phase fluctuation, and display that the phase fluctuation (i.e., rms phase) increases as a function of baseline length, and some data sets show turn-over around several hundred meters to 1 km and being almost constant at longer baselines. This is the first millimeter/submillimeter structure function at this long baseline length, and to show the turn-over of the structure fun...

Matsushita, Satoki; Kawabe, Ryohei; Fomalont, Ed; Barkats, Denis; Corder, Stuartt

2014-01-01T23:59:59.000Z

455

The CRAF/Cassini mission: Baseline plan and status  

Science Journals Connector (OSTI)

Mission spacecraft and power subsystem design considerations for the Comet Rendezvous Asteroid Flyby (CRAF)/Cassini (Saturn Orbiter) Project encompass scientific/performance and environmental/safety considerations. Based on the previous experience with the Galileo and Voyager spacecraft a CRAF/Cassini baseline design has been proposed that seeks to optimize mission performance and reliability while achieving a level of environmental safety commensurate with previous RTG?powered missions. Concurrently in support of NASAs satisfaction of National Environmental Policy Act (NEPA) requirements alternative designs capable of mitigating any significant environmental impacts associated with the baseline design are being identified. A comparison of the baseline and alternative designs will be reported in a publicly available Environmental Impact Statement (EIS) scheduled for release in draft form this Spring. The baseline design supporting these impact determinations and alternative comparisons currently rely for CRAF on a Venus?Venus?Earth gravity assist trajectory to the comet Tempel 2 and for Cassini on a Venus?Earth?Jupiter gravity assist trajectory to Saturn. The spacecraft involved in this baseline make use of a common cylindrical core design comprised of virtually identical subsystems and of a host of certain mission?specific instruments. Due to the low solar intensity at the rendezvous distances associated with both missions and the past success associated with RTG use on deep space missions three Radioisotope Thermoelectric Generators (RTGs) have been selected as the baseline power source.

Reed E. Wilcox; Dougals S. Abraham; C. Perry Bankston; Sandra M. Dawson; John W. Klein; Philip C. Knocke; Paul D. Sutton

1992-01-01T23:59:59.000Z

456

Today in Energy - commercial consumption & efficiency  

Reports and Publications (EIA)

Short, timely articles with graphs about recent commercial consumption and efficiency issues and trends.

2028-01-01T23:59:59.000Z

457

Frequency and longitudinal trends of household care product use Rebecca E. Moran a  

E-Print Network [OSTI]

SUPERB Indoor environment d-limonene a b s t r a c t The use of household cleaning products and air, frequencies of use of eight types of household cleaning products and air fresheners and the performance. Introduction Household care products, such as cleaning products and air fresheners, are frequently used

Leistikow, Bruce N.

458

OpenEI - Energy Consumption  

Open Energy Info (EERE)

Commercial and Commercial and Residential Hourly Load Profiles for all TMY3 Locations in the United States http://en.openei.org/datasets/node/961 This dataset contains hourly load profile data for 16 commercial building types (based off the DOE commercial reference building models) and residential buildings (based off the Building America House Simulation Protocols).  This dataset also includes the consumption/residential/">Residential Energy Consumption Survey (RECS) for statistical references of building types

459

Fuel consumption model for FREFLO  

E-Print Network [OSTI]

above, Biggs and Akcelik (1985) proposed a model of the following form: f = fsito + &Pr + z[apr)o o (5) where, Po = total drag power P, = inertia power a = instantaneous acceleration 8, = fuel consumption per unit power 8, = fuel consumption per... that is additional to S, P, . This component is expressed as SzaP, , where &z is considered to be a secondary efficiency parameter that relates fuel to the product of inertia power and acceleration rate, for positive accelerations. This term allows for the effects...

Rao, Kethireddipalli Srinivas

1992-01-01T23:59:59.000Z

460

The Hispanic Americans Baseline Alcohol Survey (HABLAS): Rates and predictors of DUI across Hispanic national groups  

Science Journals Connector (OSTI)

This paper examines rates of self-reported driving under the influence (DUI) of alcohol and 12-month and lifetime DUI arrest rates among Mexican Americans, Puerto Ricans, Cuban Americans and South/Central Americans in the U.S. population. Using a multistage cluster sample design, a total of 5224 individuals 18 years of age and older were selected from the household population in five metropolitan areas of the U.S.: Miami, New York, Philadelphia, Houston and Los Angeles. The survey weighted response rate was 76%. Among men, 21% of Mexican Americans, 19.9% of South/Central Americans, 11.6% of Puerto Ricans and 6.9% of Cuban Americans reported DUI. Rates were lower among women, ranging from 9.7% for Mexican Americans to 1.3% for Cuban Americans. Mexican American men had the highest 12-month arrest rate (1.6%) and the highest lifetime arrest rate (11.2%). Drinkers who reported DUI were heavier drinkers than those not reporting DUI according to a variety of indicators. However, most DUI incidents involved non-alcohol-dependent drivers. Mexican Americans and South Central/Americans, men, younger drivers, those with less than high school education, those with higher income and higher alcohol consumption were more likely to report DUI and DUI arrests. These findings show that Hispanic national groups in the U.S. are diverse regarding drinking and DUI-related experiences.

Raul Caetano; Suhasini Ramisetty-Mikler; Lori A. Rodriguez

2008-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "baseline household consumption" 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

Rail Transit and Energy Consumption  

Science Journals Connector (OSTI)

...Transit and Energy Consumption In a recent issue...D.C. 20418 The Diesel's Advantages It...p. 517). The diesel car, while it has...Other types of engine can be made to meet...catalysts by using leaded fuel because it is 3 to...politically unpopular. The diesel car requires no add-on...

CHARLES A. LAVE

1977-09-02T23:59:59.000Z

462

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

463

Do households smooth expenditure over anticipated income changes? Evidence from bonus payments to public employees in Japan  

Science Journals Connector (OSTI)

This paper provides new evidence of consumers reaction to an anticipated sizable change in income. Until FY2002, Japanese public employees received predictable large bonus payments three times a fiscal year (in June, December, and March), but the March bonus was abolished in FY2003. We compare the seasonal patterns of public employees expenditure before and after the reform of the bonus payment schedule. Contrary to the prediction of the life cycle/permanent income hypothesis (LC/PIH), we find evidence that monthly patterns of household expenditure were significantly affected by the anticipated large change in income pattern. However, at closer inspection, this excess sensitivity of expenditure is observed only for expenditure subcategories of some durability, i.e., durables and semi-durables. Thus, while the LC/PIH does not appear to hold for expenditure (which we observe here), it may still hold for consumption.

Masahiro Hori; Satoshi Shimizutani

2012-01-01T23:59:59.000Z

464

State Residential Energy Consumption Shares  

Gasoline and Diesel Fuel Update (EIA)

This next slide shows what fuels are used in the residential market. When a This next slide shows what fuels are used in the residential market. When a energy supply event happens, particularly severe winter weather, it is this sector that the government becomes most concerned about. As you can see, natural gas is very important to the residential sector not only in DC, MD and VA but in the United States as well. DC residents use more natural gas for home heating than do MD and VA. While residents use heating oil in all three states, this fuel plays an important role in MD and VA. Note: kerosene is included in the distillate category because it is an important fuel to rural households in MD and VA. MD and VA rely more on electricity than DC. Both MD and VA use propane as well. While there are some similarities in this chart, it is interesting to note

465

California Baseline Energy Demands to 2050 for Advanced Energy Pathways  

E-Print Network [OSTI]

these trends lead to declining natural gas consumption byNatural gas demand has been rising in California and this trendnatural gas demands regionally, to account for variability in energy usage trends

McCarthy, Ryan; Yang, Christopher; Ogden, Joan M.

2008-01-01T23:59:59.000Z

466

Multi-baseline interferometric synthetic aperture radar applications and error analysis  

E-Print Network [OSTI]

In this thesis, we deal primarily with the multi-baseline SAR configuration utilizing three satellites. Two applications of InSAR, multi-baseline height retrieval and multi-baseline compensation of CCD's slope biasing ...

Chua, Song Liang

2007-01-01T23:59:59.000Z

467

UK Electricity Consumption and Number of Meters at MLSOA level (2008) |  

Open Energy Info (EERE)

8) 8) Dataset Summary Description The UK Department of Energy and Climate Change (DECC) releases annual statistics on domestic and non-domestic electricity and gas consumption (and number of meters) at the Middle Layer Super Output Authority (MLSOA) and Intermediate Geography Zone (IGZ) level (there are over 950 of these subregions throughout England, Scotland and Wales). Both MLSOAs (England and Wales) and IGZs (Scotland) include a minimum of approximately 2,000 households. The electricity consumption data data is split by ordinary electricity and economy7 electricity usage. All data in this set are classified as UK National Statistics. Related socio-economic data for MLSOA and IGZ levels can be accessed: http://decc.gov.uk/assets/decc/Statistics/regional/mlsoa2008/181-mlsoa-i...

468

Residential Lighting End-Use Consumption Study: Estimation Framework and Initial Estimates  

SciTech Connect (OSTI)

The U.S. DOE Residential Lighting End-Use Consumption Study is an initiative of the U.S. Department of Energys (DOEs) Solid-State Lighting Program that aims to improve the understanding of lighting energy usage in residential dwellings. The study has developed a regional estimation framework within a national sample design that allows for the estimation of lamp usage and energy consumption 1) nationally and by region of the United States, 2) by certain household characteristics, 3) by location within the home, 4) by certain lamp characteristics, and 5) by certain categorical cross-classifications (e.g., by dwelling type AND lamp type or fixture type AND control type).

Gifford, Will R.; Goldberg, Miriam L.; Tanimoto, Paulo M.; Celnicker, Dane R.; Poplawski, Michael E.

2012-12-01T23:59:59.000Z

469

User-needs study for the 1993 residential energy consumption survey  

SciTech Connect (OSTI)

During 1992, the Energy Information Administration (EIA) conducted a user-needs study for the 1993 Residential Energy Consumption Survey (RECS). Every 3 years, the RECS collects information on energy consumption and expenditures for various classes of households and residential buildings. The RECS is the only source of such information within EIA, and one of only a few sources of such information anywhere. EIA sent letters to more than 750 persons, received responses from 56, and held 15 meetings with users. Written responses were also solicited by notices published in the April 14, 1992 Federal Register and in several energy-related publications. To ensure that the 1993 RECS meets current information needs, EIA made a specific effort to get input from policy makers and persons needing data for forecasting efforts. These particular needs relate mainly to development of the National Energy Modeling System and new energy legislation being considered at the time of the user needs survey.

Not Available

1993-09-24T23:59:59.000Z

470

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

471

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

472

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.

473

Fermilab | Recovery Act | Long-baseline neutrino research  

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

Long-baseline neutrino research Long-baseline neutrino research The proposed long-baseline neutrino project will place a particle detector at great depth underground to study neutrinos from an intense beam generated several states away. Researchers from six American laboratories and more than two dozen universities, most in the United States, have proposed plans to generate an intense beam of neutrinos at Fermilab and to place the detector in the Homestake Gold Mine near Lead, South Dakota. It would be the world's deepest underground laboratory, hosting experiments as deep as 8,000 feet underground. Neutrinos are the most abundant but perhaps least understood particles in our galaxy. Scientists hope to observe the neutrinos changing from one type to another as they travel. Studying a neutrino beam at two locations a

474

Develop baseline computational model for proactive welding stress  

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

Develop baseline computational model for proactive welding stress Develop baseline computational model for proactive welding stress management to suppress helium induced cracking during weld repair Develop baseline computational model for proactive welding stress management to suppress helium induced cracking during weld repair There are over 100 nuclear power plants operating in the U.S., which generate approximately 20% of the nation's electricity. These plants range from 15 to 40 years old. Extending the service lives of the current fleet of nuclear power plants beyond 60 years is imperative to allow for the environmentally-sustainable energy infrastructure being developed and matured. Welding repair of irradiated nuclear reactor materials (such as austenitic stainless steels) is especially challenging because of the

475

Functional Testing Protocols for Commercial Building Efficiency Baseline Modeling Software  

SciTech Connect (OSTI)

This document describes procedures for testing and validating proprietary baseline energy modeling software accuracy in predicting energy use over the period of interest, such as a month or a year. The procedures are designed according to the methodology used for public domain baselining software in another LBNL report that was (like the present report) prepared for Pacific Gas and Electric Company: ?Commercial Building Energy Baseline Modeling Software: Performance Metrics and Method Testing with Open Source Models and Implications for Proprietary Software Testing Protocols? (referred to here as the ?Model Analysis Report?). The test procedure focuses on the quality of the software?s predictions rather than on the specific algorithms used to predict energy use. In this way the software vendor is not required to divulge or share proprietary information about how their software works, while enabling stakeholders to assess its performance.

Jump, David; Price, Phillip N.; Granderson, Jessica; Sohn, Michael

2013-09-06T23:59:59.000Z

476

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

SciTech Connect (OSTI)

The purpose of this research is to estimate individual fuel prices within the residential sector. The data from four US Department of Energy, Energy Information Administration, residential energy consumption surveys were used to estimate the models. For a number of important fuel types - fuel oil, natural gas, and liquefied petroleum gas - the estimation presents a problem because these fuels are not used by all households. Estimates obtained by using only data in which observed fuel prices are present would be biased. A correction for this self-selection bias is needed for estimating prices of these fuels. A literature search identified no past studies on application of the selectivity model for estimating prices of residential fuel oil/kerosine, natural gas, and liquefied petroleum gas. This report describes selectivity models that utilize the Dubin/McFadden correction method for estimating prices of residential fuel oil/kerosine, natural gas, and liquefied petroleum gas in the Northeast, Midwest, South, and West census regions. Statistically significant explanatory variables are identified and discussed in each of the models. This new application of the selectivity model should be of interest to energy policy makers, researchers, and academicians.

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

1994-08-01T23:59:59.000Z

477

Long-term behaviour of baled household waste  

Science Journals Connector (OSTI)

This study was carried out at the laboratory scale (approximately 15 l) and using real baled waste of industrial dimensions (about 1 m3), in order to assess the long-term behaviour of baled household waste. The laboratory assays were carried out with real household waste which was fractioned on site, reconstituted in the laboratory and then compacted into 15 l airtight containers (unless stated otherwise). These containers were incubated under different experimental conditions at a constant temperature (28C). Three assays were conducted over 34 months and two others over 27 months. For the assays incubated in conditions simulating those of real baled waste (confined medium, with no aeration or water flow), a very low microbial activity was observed. The assay incubated in the same conditions but with slight aeration during the first three months in order to simulate imperfectly airtight wrapping, revealed biodegradation which started in a significant manner after 800 days of incubation. The evolution of two real wrapped bales each containing 900 kg of household waste was monitored over 8 months. These bales were produced industrially, one in July 97 and the other in July 98 at the incinerator plant at Agde (France). The bales were then stored outside at the laboratory location and their evolution was monitored mainly by biogas analysis and temperature measurement. No methane formation was observed, revealing the absence of anaerobic biodegradation, thus confirming the laboratory assays.

Fabian Robles-Mart??nez; Rmy Gourdon

2000-01-01T23:59:59.000Z

478

Etalon-induced Baseline Drift And Correction In Atom Flux Sensors...  

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

Etalon-induced Baseline Drift And Correction In Atom Flux Sensors Based On Atomic Absorption Spectroscopy. Etalon-induced Baseline Drift And Correction In Atom Flux Sensors Based...

479

Manufacturing Consumption of Energy 1994  

Gasoline and Diesel Fuel Update (EIA)

Energy Information Administration/Manufacturing Consumption of Energy 1994 Energy Information Administration/Manufacturing Consumption of Energy 1994 Introduction The market for natural gas has been changing for quite some time. As part of natural gas restructuring, gas pipelines were opened to multiple users. Manufacturers or their representatives could go directly to the wellhead to purchase their natural gas, arrange the transportation, and have the natural gas delivered either by the local distribution company or directly through a connecting pipeline. More recently, the electricity markets have been undergoing change. When Congress passed the Energy Policy Act of 1992, requirements were included not only to open access to the ownership of electricity generation, but also to open access to the transmission lines so that wholesale trade in electricity would be possible. Now several States, including California and

480

All Consumption Tables.vp  

Gasoline and Diesel Fuel Update (EIA)

6 6 State Energy Data 2011: Consumption Table C11. Energy Consumption by Source, Ranked by State, 2011 Rank Coal Natural Gas a Petroleum b Retail Electricity Sales State Trillion Btu State Trillion Btu State Trillion Btu State Trillion Btu 1 Texas 1,695.2 Texas 3,756.9 Texas 5,934.3 Texas 1,283.1 2 Indiana 1,333.4 California 2,196.6 California 3,511.4 California 893.7 3 Ohio 1,222.6 Louisiana 1,502.9 Louisiana 1,925.7 Florida 768.0 4 Pennsylvania 1,213.0 New York 1,246.9 Florida 1,680.3 Ohio 528.0 5 Illinois 1,052.2 Florida 1,236.6 New York 1,304.0 Pennsylvania 507.6 6 Kentucky 1,010.6 Pennsylvania 998.6 Pennsylvania 1,255.6 New York 491.5

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


481

Manufacturing Consumption of Energy 1994  

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

Manufacturing Manufacturing Energy Consumption Survey Forms Form EIA-846A (4-6-95) U.S. Department of Commerce Bureau of the Census Acting as Collecting and Compiling Agent For 1994 MANUFACTURING ENERGY CONSUMPTION SURVEY Public reporting burden for this collection of information is estimated to average 9 hours per response, including the time of reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden, to the Energy Information Administration, Office of Statistical Standards, EI-73, 1707 H-Street, NW, Washington, DC 20585; and to the Office of Information and Regulatory Affairs, Office of

482

Manufacturing Consumption of Energy 1994  

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

2(94) 2(94) Distribution Category UC-950 Manufacturing Consumption of Energy 1994 December 1997 Energy Information Administration Office of Energy Markets and End Use U.S. Department of Energy Washington, DC 20585 This report was prepared by the Energy Information Administration, the independent statistical and analytical agency within the U.S. Department of Energy. The information contained herein should be attributed to the Energy Information Administration and should not be construed as advocating or reflecting any policy position of the Department of Energy or any other organization. ii Energy Information Administration/Manufacturing Consumption of Energy 1994 Contacts This publication was prepared by the Energy Information Administration (EIA) under the general direction of W. Calvin

483

Manufacturing consumption of energy 1994  

SciTech Connect (OSTI)

This report provides estimates on energy consumption in the manufacturing sector of the U.S. economy based on data from the Manufacturing Energy Consumption Survey. The sample used in this report represented about 250,000 of the largest manufacturing establishments which account for approximately 98 percent of U.S. economic output from manufacturing, and an expected similar proportion of manufacturing energy use. The amount of energy use was collected for all operations of each establishment surveyed. Highlights of the report include profiles for the four major energy-consuming industries (petroleum refining, chemical, paper, and primary metal industries), and an analysis of the effects of changes in the natural gas and electricity markets on the manufacturing sector. Seven appendices are included to provide detailed background information. 10 figs., 51 tabs.

NONE

1997-12-01T23:59:59.000Z

484

Manufacturing Consumption of Energy 1994  

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

E E U.S. Census Regions and Divisions 489 Energy Information Administration/Manufacturing Consumption of Energy 1994 Source: U.S. Department of Commerce, Bureau of the Census, Statistical Abstract of the United States,1996 (Washington, DC, October 1996), Figure 1. Appendix E U.S. Census Regions and Divisions Appendix F Descriptions of Major Industrial Groups and Selected Industries Executive Office of the President, Office of Management and Budget, Standard Industrial Classification Manual, 1987, pp. 67-263. 54 493 Energy Information Administration/Manufacturing Consumption of Energy 1994 Appendix F Descriptions of Major Industrial Groups and Selected Industries This appendix contains descriptions of industrial groups and selected industries taken from the Standard Industrial

485

All Consumption Tables.vp  

Gasoline and Diesel Fuel Update (EIA)

4) 4) June 2007 State Energy Consumption Estimates 1960 Through 2004 2004 Consumption Summary Tables Table S1. Energy Consumption Estimates by Source and End-Use Sector, 2004 (Trillion Btu) State Total Energy b Sources End-Use Sectors a Coal Natural Gas c Petroleum Nuclear Electric Power Hydro- electric Power d Biomass e Other f Net Interstate Flow of Electricity/Losses g Residential Commercial Industrial b Transportation Alabama 2,159.7 853.9 404.0 638.5 329.9 106.5 185.0 0.1 -358.2 393.7 270.2 1,001.1 494.7 Alaska 779.1 14.1 411.8 334.8 0.0 15.0 3.3 0.1 0.0 56.4 63.4 393.4 266.0 Arizona 1,436.6 425.4 354.9 562.8 293.1 69.9 8.7 3.6 -281.7 368.5 326.0 231.2 511.0 Arkansas 1,135.9 270.2 228.9 388.3 161.1 36.5 76.0 0.6 -25.7 218.3 154.7 473.9 288.9 California 8,364.6 68.9 2,474.2 3,787.8 315.6 342.2

486

All Consumption Tables.vp  

Gasoline and Diesel Fuel Update (EIA)

9) 9) June 2011 State Energy Consumption Estimates 1960 Through 2009 2009 Consumption Summary Tables Table C1. Energy Consumption Overview: Estimates by Energy Source and End-Use Sector, 2009 (Trillion Btu) State Total Energy b Sources End-Use Sectors a Fossil Fuels Nuclear Electric Power Renewable Energy e Net Interstate Flow of Electricity/ Losses f Net Electricity Imports Residential Commercial Industrial b Transportation Coal Natural Gas c Petroleum d Total Alabama 1,906.8 631.0 473.9 583.9 1,688.8 415.4 272.9 -470.3 0.0 383.2 266.0 788.5 469.2 Alaska 630.4 14.5 344.0 255.7 614.1 0.0 16.3 0.0 (s) 53.4 61.0 325.4 190.6 Arizona 1,454.3 413.3 376.7 520.8 1,310.8 320.7 103.5 -279.9 -0.8 400.8 352.1 207.8 493.6 Arkansas 1,054.8 264.1 248.1 343.1 855.3 158.7 126.5 -85.7 0.0 226.3 167.0 372.5

487

All Consumption Tables.vp  

Gasoline and Diesel Fuel Update (EIA)

3. Energy Consumption per Capita by End-Use Sector, Ranked by State, 2011 3. Energy Consumption per Capita by End-Use Sector, Ranked by State, 2011 Rank Residential Sector Commercial Sector Industrial Sector Transportation Sector Total Consumption State Million Btu State Million Btu State Million Btu State Million Btu State Million Btu 1 North Dakota 99.8 District of Columbia 193.1 Louisiana 585.8 Alaska 277.3 Wyoming 974.7 2 West Virginia 90.9 Wyoming 119.2 Wyoming 568.2 Wyoming 200.7 Louisiana 886.5 3 Missouri 89.4 North Dakota 106.9 Alaska 435.7 North Dakota 172.8 Alaska 881.3 4 Tennessee 87.8 Alaska 94.1 North Dakota 388.9 Louisiana 158.0 North Dakota 768.4 5 Kentucky 87.4 Montana 78.4 Iowa 243.4 Oklahoma 122.3 Iowa 493.6

488

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

E-Print Network [OSTI]

to overtake the US in energy consumption and GHG emissionsto overtake the US in energy consumption and greenhouse

Lin, Jiang

2006-01-01T23:59:59.000Z

489

Buildings Energy Data Book: 2.1 Residential Sector Energy Consumption  

Buildings Energy Data Book [EERE]

0 0 Region (1) Northeast 73.5 122.2 47.7 24% New England 77.0 129.4 55.3 7% Middle Atlantic 72.2 119.7 45.3 17% Midwest 58.9 113.5 46.0 28% East North Central 61.1 117.7 47.3 20% West North Central 54.0 104.1 42.9 8% South 51.5 79.8 31.6 31% South Atlantic 47.4 76.1 30.4 16% East South Central 56.6 87.3 36.1 6% West South Central 56.6 82.4 31.4 9% West 56.6 77.4 28.1 18% Mountain 54.4 89.8 33.7 6% Pacific 58.0 71.8 25.7 11% U.S. Average 58.7 94.9 37.0 100% 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.

490

Essays on aggregate and individual consumption fluctuations  

E-Print Network [OSTI]

This thesis consists of three essays on aggregate and individual consumption fluctuations. Chapter 1 develops a quantitative model to explore aggregate and individual consumption dynamics when the income process exhibits ...

Hwang, Youngjin

2006-01-01T23:59:59.000Z

491

Reduced Energy Consumption for Melting in Foundries  

E-Print Network [OSTI]

Reduced Energy Consumption for Melting in Foundries Ph.D. Thesis by Søren Skov-Hansen Supervisor-melted, and hence reduce the energy consumption for melting in foundries. Traditional gating systems are known

492

Energy Information Administration - Commercial Energy Consumption...  

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

A. Consumption and Gross Energy Intensity by Census Region for Sum of Major Fuels for All Buildings, 2003 Sum of Major Fuel Consumption (trillion Btu) Total Floorspace of Buildings...

493

Energy Information Administration - Commercial Energy Consumption...  

Gasoline and Diesel Fuel Update (EIA)

C3. Consumption and Gross Energy Intensity for Sum of Major Fuels for Non-Mall Buildings, 2003 All Buildings* Sum of Major Fuel Consumption Number of Buildings (thousand)...

494

Energy Information Administration - Commercial Energy Consumption...  

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

C7A. Consumption and Gross Energy Intensity by Census Division for Sum of Major Fuels for All Buildings, 2003: Part 1 Sum of Major Fuel Consumption (trillion Btu) Total Floorspace...

495

Energy Information Administration - Commercial Energy Consumption...  

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

. Consumption and Gross Energy Intensity by Census Region for Sum of Major Fuels for Non-Mall Buildings, 2003 Sum of Major Fuel Consumption (trillion Btu) Total Floorspace of...

496

Energy Information Administration - Commercial Energy Consumption...  

Gasoline and Diesel Fuel Update (EIA)

A. Consumption and Gross Energy Intensity by Census Division for Sum of Major Fuels for All Buildings, 2003: Part 3 Sum of Major Fuel Consumption (trillion Btu) Total Floorspace of...

497

Energy Information Administration - Commercial Energy Consumption...  

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

. Consumption and Gross Energy Intensity by Year Constructed for Sum of Major Fuels for Non-Mall Buildings, 2003 Sum of Major Fuel Consumption (trillion Btu) Total Floorspace of...

498

Energy Information Administration - Commercial Energy Consumption...  

Gasoline and Diesel Fuel Update (EIA)

C3A. Consumption and Gross Energy Intensity for Sum of Major Fuels for All Buildings, 2003 All Buildings Sum of Major Fuel Consumption Number of Buildings (thousand) Floorspace...

499

Energy Information Administration - Commercial Energy Consumption...  

Gasoline and Diesel Fuel Update (EIA)

Table C8A. Consumption and Gross Energy Intensity by Census Division for Sum of Major Fuels for All Buildings, 2003: Part 2 Sum of Major Fuel Consumption (trillion Btu) Total...

500

Technical Baseline Summary Description for the Tank Farm Contractor  

SciTech Connect (OSTI)

This document is a revision of the document titled above, summarizing the technical baseline of the Tank Farm Contractor. It is one of several documents prepared by CH2M HILL Hanford Group, Inc. to support the U.S. Department of Energy Office of River Protection Tank Waste Retrieval and Disposal Mission at Hanford.

TEDESCHI, A.R.

2000-04-21T23:59:59.000Z