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Sample records for household total energy

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

    Energy Information Administration (EIA) (indexed site)

    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....

  2. Household Vehicles Energy Consumption 1991

    Energy Information Administration (EIA) (indexed site)

    or commercial trucks (See Table 1). Energy Information AdministrationHousehold Vehicles Energy Consumption 1991 5 The 1991 RTECS count includes vehicles that were owned or used...

  3. Household Vehicles Energy Consumption 1991

    Energy Information Administration (EIA) (indexed site)

    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...

  4. Household Vehicles Energy Consumption 1991

    Energy Information Administration (EIA) (indexed site)

    16.8 17.4 18.6 18.9 1.7 2.2 0.6 1.5 Energy Information AdministrationHousehold Vehicles Energy Consumption 1991 15 Vehicle Miles Traveled per Vehicle (Thousand) . . . . . . . . ....

  5. Strategies for Collecting Household Energy Data | Department...

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Collecting Household Energy Data Strategies for Collecting Household Energy Data Better Buildings Neighborhood Program Data and Evaluation Peer Exchange Call: Strategies for ...

  6. Household Vehicles Energy Use Cover Page

    Energy Information Administration (EIA) (indexed site)

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

  7. Household vehicles energy consumption 1994

    SciTech Connect

    1997-08-01

    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.

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

    Gasoline and Diesel Fuel Update

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

  9. Energy Information Administration/Household Vehicles Energy Consumptio...

    Energy Information Administration (EIA) (indexed site)

    , Energy Information AdministrationHousehold Vehicles Energy Consumption 1994 ix Household Vehicles Energy Consumption 1994 presents statistics about energy-related...

  10. Household energy consumption and expenditures, 1990

    SciTech Connect

    Not Available

    1993-03-02

    This report, Household Energy Consumption and Expenditures 1990, is based upon data from the 1990 Residential Energy Consumption Survey (RECS). Focusing on energy end-use consumption and expenditures of households, the 1990 RECS is the eighth in a series conducted since 1978 by the Energy Information Administration (EIA). Over 5,000 households were surveyed, providing information on their housing units, housing characteristics, energy consumption and expenditures, stock of energy-consuming appliances, and energy-related behavior. The information provided represents the characteristics and energy consumption of 94 million households nationwide.

  11. Strategies for Collecting Household Energy Data

    Energy.gov [DOE]

    Better Buildings Neighborhood Program Data and Evaluation Peer Exchange Call: Strategies for Collecting Household Energy Data, Call Slides and Discussion Summary, July 19, 2012.

  12. Determinants of Household Use of Selected Energy Star Appliances - Energy

    Gasoline and Diesel Fuel Update

    Information Administration Determinants of Household Use of Selected Energy Star Appliances Release date: May 25, 2016 Introduction According to the 2009 Residential Energy Consumption Survey (RECS), household appliances1accounted for 35% of U.S. household energy consumption, up from 24% in 1993. Thus, improvements in the energy performance of residential appliances as well as increases in the use of more efficient appliances can be effective in reducing household energy consumption and

  13. Household energy consumption and expenditures 1993

    SciTech Connect

    1995-10-05

    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.

  14. Microsoft Word - Household Energy Use CA

    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

  15. Household energy consumption and expenditures, 1987

    SciTech Connect

    Not Available

    1989-10-10

    Household Energy Consumption and Expenditures 1987, Part 1: National Data is the second publication in a series from the 1987 Residential Energy Consumption Survey (RECS). It is prepared by the Energy End Use Division (EEUD) of the Office of Energy Markets and End Use (EMEU), Energy Information Administration (EIA). The EIA collects and publishes comprehensive data on energy consumption in occupied housing units in the residential sector through the RECS. 15 figs., 50 tabs.

  16. Household Vehicles Energy Consumption 1991

    Energy Information Administration (EIA) (indexed site)

    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...

  17. Household Vehicles Energy Consumption 1991

    Energy Information Administration (EIA) (indexed site)

    selected tabulations were produced using two different software programs, Table Producing Language (TPL) and Statistical Analysis System (SAS). Energy Information Administration...

  18. Household Vehicles Energy Consumption 1991

    Energy Information Administration (EIA) (indexed site)

    for 1994, will continue the 3-year cycle. The RTECS, a subsample of the Residential Energy Consumption Survey (RECS), is an integral part of a series of surveys designed by...

  19. Household Energy Consumption Segmentation Using Hourly Data

    SciTech Connect

    Kwac, J; Flora, J; Rajagopal, R

    2014-01-01

    The increasing US deployment of residential advanced metering infrastructure (AMI) has made hourly energy consumption data widely available. Using CA smart meter data, we investigate a household electricity segmentation methodology that uses an encoding system with a pre-processed load shape dictionary. Structured approaches using features derived from the encoded data drive five sample program and policy relevant energy lifestyle segmentation strategies. We also ensure that the methodologies developed scale to large data sets.

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

    Energy Saver

    Competition Helps Kids Learn About Energy and Save Their Households Some Money Competition Helps Kids Learn About Energy and Save Their Households Some Money May 21, 2013 - 2:40pm ...

  1. Parallel Total Energy

    Energy Science and Technology Software Center

    2004-10-21

    This is a total energy electronic structure code using Local Density Approximation (LDA) of the density funtional theory. It uses the plane wave as the wave function basis set. It can sue both the norm conserving pseudopotentials and the ultra soft pseudopotentials. It can relax the atomic positions according to the total energy. It is a parallel code using MP1.

  2. Next Generation Household Refrigerator | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Next Generation Household Refrigerator Next Generation Household Refrigerator Embraco's high efficiency, oil-free linear compressor.
    Credit: Whirlpool Embraco's high ...

  3. Household energy consumption and expenditures, 1990. [Contains Glossary

    SciTech Connect

    Not Available

    1993-03-02

    This report, Household Energy Consumption and Expenditures 1990, is based upon data from the 1990 Residential Energy Consumption Survey (RECS). Focusing on energy end-use consumption and expenditures of households, the 1990 RECS is the eighth in a series conducted since 1978 by the Energy Information Administration (EIA). Over 5,000 households were surveyed, providing information on their housing units, housing characteristics, energy consumption and expenditures, stock of energy-consuming appliances, and energy-related behavior. The information provided represents the characteristics and energy consumption of 94 million households nationwide.

  4. Household energy consumption and expenditures 1987

    SciTech Connect

    Not Available

    1990-01-22

    This report is the third in the series of reports presenting data from the 1987 Residential Energy Consumption Survey (RECS). The 1987 RECS, seventh in a series of national surveys of households and their energy suppliers, provides baseline information on household energy use in the United States. Data from the seven RECS and its companion survey, the Residential Transportation Energy Consumption Survey (RTECS), are made available to the public in published reports such as this one, and on public use data files. This report presents data for the four Census regions and nine Census divisions on the consumption of and expenditures for electricity, natural gas, fuel oil and kerosene (as a single category), and liquefied petroleum gas (LPG). Data are also presented on consumption of wood at the Census region level. The emphasis in this report is on graphic depiction of the data. Data from previous RECS surveys are provided in the graphics, which indicate the regional trends in consumption, expenditures, and uses of energy. These graphs present data for the United States and each Census division. 12 figs., 71 tabs.

  5. Barriers to household investment in residential energy conservation: preliminary assessment

    SciTech Connect

    Hoffman, W.L.

    1982-12-01

    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)

  6. Household and environmental characteristics related to household energy-consumption change: A human ecological approach

    SciTech Connect

    Guerin, D.A.

    1988-01-01

    This study focused on the family household as an organism and on its interaction with the three environments of the human ecosystem (natural, behavioral, and constructed) as these influence energy consumption and energy-consumption change. A secondary statistical analysis of data from the US Department of Energy Residential Energy Consumption Surveys (RECS) was completed. The 1980 and 1983 RECS were used as the data base. Longitudinal data, including household, environmental, and energy-consumption measures, were available for over 800 households. The households were selected from a national sample of owner-occupied housing units surveyed in both years. Results showed a significant( p = <.05) relationship between the dependent-variable energy-consumption change and the predictor variables heating degree days, addition of insulation, addition of a wood-burning stove, year the housing unit was built, and weighted number of appliances. A significant (p = <.05) relationship was found between the criterion variable energy-consumption change and the discriminating variables of age of the head of the household, cooling degree days, heating degree days, year the housing unit was built, and number of stories in the housing unit.

  7. Projecting household energy consumption within a conditional demand framework

    SciTech Connect

    Teotia, A.; Poyer, D.

    1991-01-01

    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).

  8. Projecting household energy consumption within a conditional demand framework

    SciTech Connect

    Teotia, A.; Poyer, D.

    1991-12-31

    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).

  9. Household energy use in non-OPEC developing countries

    SciTech Connect

    Fernandez, J.C.

    1980-05-01

    Energy use in the residential sector in India, Brazil, Mexico, the Republic of Korea, the Sudan, Pakistan, Malaysia, and Guatemala is presented. Whenever possible, information is included on the commercial fuels (oil, gas, coal, and electricity) and on what are termed noncommercial fuels (firewood, animal dung, and crop residues). Of special interest are the differences in the consumption patterns of urban and rural areas, and of households at different income levels. Where the data allow, the effect of household size on energy consumption is discussed. Section II is an overview of the data for all eight countries. Section III examines those areas (India, Brazil, Mexico City) for which data exist on the actual quantity of energy consumed by households. Korea, the Sudan, and Pakistan, which collect data on household expenditures on fuels, are discussed in Section IV. The patterns of ownership of energy-using durables in Malaysia and Guatemala are discussed in Section V. (MCW)

  10. Household Vehicles Energy Use: Latest Data & Trends

    Energy Information Administration (EIA) (indexed site)

    (EERE) program in the U.S. Department of Energy (DOE), Transportation Energy Data Book: Edition 24. Note: * a recession year. Estimates are displayed as rounded values....

  11. Household Vehicles Energy Consumption 1994 - Appendix C

    Energy Information Administration (EIA) (indexed site)

    discusses several issues relating to the quality of the Residential Transportation Energy Consumption Survey (RTECS) data and to the interpretation of conclusions based on...

  12. Household Vehicles Energy Use: Latest Data & Trends

    Energy Information Administration (EIA) (indexed site)

    E : C H R O N O L O G Y O F W O R L D O I L M A R K E T E V E N T S ENERGY INFORMATION ADMINISTRATIONHOUSEHOLD VEHICLES ENERGY USE: LATEST DATA & TRENDS 177 APPENDIX E A P P E N D...

  13. 2009 Total Energy Production by State | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Total Energy Production by State 2009 Total Energy Production by State 2009 Total Energy Production by State...

  14. Household Vehicles Energy Use: Latest Data & Trends

    Energy Information Administration (EIA) (indexed site)

    Federal Highway Administration. Accessed on the world-wide web at http:www.fhwa.dot.govenvironmentcmaqpgsamaq03cmaq1fig3.htm on July 11, 2005. ENERGY INFORMATION...

  15. Microsoft Word - Household Energy Use CA

    Gasoline and Diesel Fuel Update

    ... None Yes Yes No No 0% 20% 40% 60% 80% 100% US CA No Car CAR IS PARKED WITHIN 20 FT OF ELECTRICAL OUTLET More highlights from RECS on housing characteristics and energy-related ...

  16. Comparison of energy expenditures by elderly and non-elderly households: 1975 and 1985

    SciTech Connect

    Siler, A.

    1980-05-01

    The relative position of the elderly in the population is examined and their characteristic use of energy in relation to the total population and their non-elderly counterparts is observed. The 1985 projections are based on demographic, economic, and socio-economic, and energy data assumptions contained in the 1978 Annual Report to Congress. The model used for estimating household energy expenditure is MATH/CHRDS - Micro-Analysis of Transfers to Households/Comprehensive Human Resources Data System. Characteristics used include households disposable income, poverty status, location by DOE region and Standard Metropolitan Statistical Area (SMSA), and race and sex of the household head as well as age. Energy use by fuel type will be identified for total home fuels, including electricity, natural gas, bottled gas and fuel oil, and for all fuels, where gasoline use is also included. Throughout the analysis, both income and expenditure-dollar amounts for 1975 and 1985 are expressed in constant 1978 dollars. Two appendices contain statistical information.

  17. Solar total energy project Shenandoah

    SciTech Connect

    1980-01-10

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

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

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Money | Department of Energy Competition Helps Kids Learn About Energy and Save Their Households Some Money Competition Helps Kids Learn About Energy and Save Their Households Some Money May 21, 2013 - 2:40pm Addthis Students can register now to save energy and win prizes with the Home Energy Challenge. Students can register now to save energy and win prizes with the Home Energy Challenge. Eric Barendsen Energy Technology Program Specialist, Office of Energy Efficiency and Renewable Energy

  19. Forum on Enhancing the Delivery of Energy Efficiency to Middle Income Households: Discussion Summary

    SciTech Connect

    none,

    2012-09-20

    Summarizes discussions and recommendations from a forum for practitioners and policymakers aiming to strengthen residential energy efficiency program design and delivery for middle income households.

  20. Total Energy Facilities Biomass Facility | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Energy Facilities Biomass Facility Jump to: navigation, search Name Total Energy Facilities Biomass Facility Facility Total Energy Facilities Sector Biomass Facility Type...

  1. Total Eolica | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Eolica Jump to: navigation, search Name: Total Eolica Place: Spain Product: Project developer References: Total Eolica1 This article is a stub. You can help OpenEI by expanding...

  2. EPA Webinar: Bringing Energy Efficiency and Renewable Housing to Low-Income Households

    Energy.gov [DOE]

    Hosted by the U.S. Environmental Protection Agency, this webinar will explore the topic of linking and leveraging energy efficiency and renewable energy programs for limited-income households, including the need to coordinate with other energy assistance programs.

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

    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 ...

  4. Delivering Energy Efficiency to Middle Income Single Family Households

    SciTech Connect

    none,

    2011-12-01

    Provides state and local policymakers with information on successful approaches to the design and implementation of residential efficiency programs for households ineligible for low-income programs.

  5. Energy-efficient housing alternatives: a predictive model of factors affecting household perceptions

    SciTech Connect

    Schreckengost, R.L.

    1985-01-01

    The major purpose of this investigation was to assess the impact of household socio-economic factors, dwelling characteristics, energy conservation behavior, and energy attitudes on the perceptions of energy-efficient housing alternatives. Perceptions of passive solar, active solar, earth sheltered, and retrofitted housing were examined. Data used were from the Southern Regional Research Project, S-141, Housing for Low and Moderate Income Families. Responses from 1804 households living in seven southern states were analyzed. A conceptual model was proposed to test the hypothesized relationships which were examined by path analysis. Perceptions of energy efficient housing alternatives were found to be a function of selected household and dwelling characteristics, energy attitude, household economic factors, and household conservation behavior. Age and education of the respondent, family size, housing-income ratio, utility income ratio, energy attitude, and size of the dwelling unit were found to have direct and indirect effects on perceptions of energy-efficient housing alternatives. Energy conservation behavior made a significant direct impact with behavioral energy conservation changes having the most profound influence. Conservation behavior was influenced by selected household and dwelling characteristics, energy attitude, and household economic factors.

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

    Energy.gov [DOE]

    Anyone who has decided to save energy at home knows that the entire household needs to be involved if you really want to see savings. Some people—be they roommates, spouses, children, or maybe even...

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

    SciTech Connect

    Zimring, Mark; Fuller, Merrian

    2011-01-24

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

  8. TENESOL formerly known as TOTAL ENERGIE | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    search Name: TENESOL (formerly known as TOTAL ENERGIE) Place: la Tour de Salvagny, France Zip: 69890 Sector: Solar Product: Makes polycrystalline silicon modules, and PV-based...

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

    Energy.gov [DOE] (indexed site)

    Presentation by Sunita Satyapal at the Total Energy USA 2012 meeting in Houston, Texas, on November 27, 2012. National Fuel Cell and Hydrogen Energy Overview (4.73 MB) More ...

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

    SciTech Connect

    Figueroa, M.J.; Sathaye, J.

    1993-08-01

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

  11. Household Vehicles Energy Use: Latest Data and Trends

    Reports and Publications

    2005-01-01

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

  12. Table 2.5 Household Energy Consumption and Expenditures by End Use, Selected Years, 1978-2005

    Energy Information Administration (EIA) (indexed site)

    5 Household 1 Energy Consumption and Expenditures by End Use, Selected Years, 1978-2005 Year Space Heating Air Conditioning Water Heating Appliances, 2 Electronics, and Lighting Natural Gas Elec- tricity 3 Fuel Oil 4 LPG 5 Total Electricity 3 Natural Gas Elec- tricity 3 Fuel Oil 4 LPG 5 Total Natural Gas Elec- tricity 3 LPG 5 Total Consumption (quadrillion Btu)<//td> 1978 4.26 0.40 2.05 0.23 6.94 0.31 1.04 0.29 0.14 0.06 1.53 0.28 1.46 0.03 1.77 1980 3.41 .27 1.30 .23 5.21 .36 1.15 .30 .22

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

    Energy Information Administration (EIA) (indexed site)

    Total Energy Glossary › FAQS › Overview Data Monthly Annual Analysis & Projections Major Topics Most popular Annual Monthly Projections Recurring U.S. States All reports Browse by Tag Alphabetical Frequency Tag Cloud Current Issues & Trends See more › U.S. energy production, consumption has changed significantly since 1908 liquid fuelsproductioncrude oilconsumptioncoalrenewable Weekly Energy Snapshots provides a weekly recap of EIA data visualizations

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

    SciTech Connect

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

    1992-10-01

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

  15. Total..........................................................

    Energy Information Administration (EIA) (indexed site)

    0.9 Q Q Q Heat Pump......7.7 0.3 Q Q Steam or Hot Water System......Census Division Total West Energy Information Administration ...

  16. Total..........................................................

    Energy Information Administration (EIA) (indexed site)

    0.9 Q Q Q Heat Pump......6.2 3.8 2.4 Steam or Hot Water System......Census Division Total Northeast Energy Information ...

  17. Emissions from small-scale energy production using co-combustion of biofuel and the dry fraction of household waste

    SciTech Connect

    Hedman, Bjoern . E-mail: bjorn.hedman@chem.umu.se; Burvall, Jan; Nilsson, Calle; Marklund, Stellan

    2005-07-01

    In sparsely populated rural areas, recycling of household waste might not always be the most environmentally advantageous solution due to the total amount of transport involved. In this study, an alternative approach to recycling has been tested using efficient small-scale biofuel boilers for co-combustion of biofuel and high-energy waste. The dry combustible fraction of source-sorted household waste was mixed with the energy crop reed canary-grass (Phalaris Arundinacea L.), and combusted in both a 5-kW pilot scale reactor and a biofuel boiler with 140-180 kW output capacity, in the form of pellets and briquettes, respectively. The chlorine content of the waste fraction was 0.2%, most of which originated from plastics. The HCl emissions exceeded levels stipulated in new EU-directives, but levels of equal magnitude were also generated from combustion of the pure biofuel. Addition of waste to the biofuel did not give any apparent increase in emissions of organic compounds. Dioxin levels were close to stipulated limits. With further refinement of combustion equipment, small-scale co-combustion systems have the potential to comply with emission regulations.

  18. Achieving Total Employee Engagement in Energy Efficiency

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Raytheon Employee Engagement in Energy Conservation Department of Energy August 5, 2010 Steve Fugarazzo Raytheon Company Enterprise Energy Team Copyright © 2007 Raytheon Company. All rights reserved. Customer Success Is Our Mission is a trademark of Raytheon Company. Page 2 8/9/2010 Presentation Overview  Company Background  Communication & Outreach Initiatives - Internal Partnerships - Energy Champions - Energy Citizens - Energy Awareness Events & Contests Page 3 8/9/2010

  19. Achieving Total Employee Engagement in Energy Efficiency

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Raytheon Employee Engagement in Energy Conservation Department of Energy August 5, 2010 ... and Safety (EHS) - Earth Day events, employee contests Human Resources - New ...

  20. Trends in Commercial Buildings--Total Primary Energy Detail

    Energy Information Administration (EIA) (indexed site)

    Energy Consumption and Graph Total Primary Energy Consumption Graph Detail and Data Table 1979 to 1992 primary consumption trend with 95% confidence ranges 1979 to 1992 primary...

  1. Trends in Commercial Buildings--Total Site Energy Detail

    Energy Information Administration (EIA) (indexed site)

    Energy Consumption and Graph Total Site Energy Consumption Graph Detail and Data Table 1979 to 1992 site consumption trend with 95% confidence ranges 1979 to 1992 site...

  2. ,"Total Fuel Oil Consumption (trillion Btu)",,,,,"Fuel Oil Energy...

    Energy Information Administration (EIA) (indexed site)

    A. Fuel Oil Consumption (Btu) and Energy Intensities by End Use for All Buildings, 2003" ,"Total Fuel Oil Consumption (trillion Btu)",,,,,"Fuel Oil Energy Intensity (thousand Btu...

  3. A Method for Modeling Household Occupant Behavior to Simulate Residential Energy Consumption

    SciTech Connect

    Johnson, Brandon J; Starke, Michael R; Abdelaziz, Omar; Jackson, Roderick K; Tolbert, Leon M

    2014-01-01

    This paper presents a statistical method for modeling the behavior of household occupants to estimate residential energy consumption. Using data gathered by the U.S. Census Bureau in the American Time Use Survey (ATUS), actions carried out by survey respondents are categorized into ten distinct activities. These activities are defined to correspond to the major energy consuming loads commonly found within the residential sector. Next, time varying minute resolution Markov chain based statistical models of different occupant types are developed. Using these behavioral models, individual occupants are simulated to show how an occupant interacts with the major residential energy consuming loads throughout the day. From these simulations, the minimum number of occupants, and consequently the minimum number of multiple occupant households, needing to be simulated to produce a statistically accurate representation of aggregate residential behavior can be determined. Finally, future work will involve the use of these occupant models along side residential load models to produce a high-resolution energy consumption profile and estimate the potential for demand response from residential loads.

  4. Household energy conservation attitudes and behaviors in the Northwest: Tracking changes between 1983 and 1985

    SciTech Connect

    Fang, J.M.; Hattrup, M.P.; Nordi, R.T.; Shankle, S.A.; Ivey, D.L.

    1987-05-01

    Pacific Northwest Laboratory (PNL) has analyzed the changes in consumer energy conservation attitudes and behaviors in the Pacific Northwest between 1983 and 1985. The information was collected through stratified random telephone surveys on 2000 and 1058 households, respectively, for 1983 and 1985 in the Bonneville Power Administration (BPA) service area in Idaho, Oregon, Washington and Western Montana. This report covers four topic areas and tests two hypotheses. The topics are as follows: consumer perceptions and attitudes of energy use and conservation in the home; consumer perceptions of energy institutions and other entities; past and intended conservation actions and investments; and segmentation of homeowners into market prospect groups. The hypotheses tested are as follows: (1) There has been no change in the size and psychographic make-up of the original three market segments found in the 1983 survey analysis; and (2) image profiles of institutions with respect to familiarity, overall impression, and believability as sources of energy conservation information remain unchanged since 1983.

  5. Compare All CBECS Activities: Total Energy Use

    Energy Information Administration (EIA) (indexed site)

    are more likely to contain specialized, high energy-consuming equipment-food service (cooking and ventilation equipment), inpatient health care (medical equipment), and food sales...

  6. EQUUS Total Return Inc | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Jump to: navigation, search Name: EQUUS Total Return Inc Place: Houston, Texas Product: A business development company and VC investor that trades as a closed-end fund. EQUUS is...

  7. Survey of Recipients of WAP Services Assessment of Household Budget and Energy Behaviors Pre to Post Weatherization DOE

    SciTech Connect

    Tonn, Bruce Edward; Rose, Erin M.; Hawkins, Beth A.

    2015-10-01

    This report presents results from the national survey of weatherization recipients. This research was one component of the retrospective and Recovery Act evaluations of the U.S. Department of Energy s Weatherization Assistance Program. Survey respondents were randomly selected from a nationally representative sample of weatherization recipients. The respondents and a comparison group were surveyed just prior to receiving their energy audits and then again approximately 18 months post-weatherization. This report focuses on budget issues faced by WAP households pre- and post-weatherization, whether household energy behaviors changed from pre- to post, the effectiveness of approaches to client energy education, and use and knowledge about thermostats.

  8. spaceheat_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral ... RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral ...

  9. Achieving Total Employee Engagement in Energy Efficiency | Department...

    Energy.gov [DOE] (indexed site)

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

  10. char_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    9a. Household Characteristics by Northeast Census Region, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total U.S. Northeast Census Region RSE Row Factors Total Census Division Middle Atlantic New England 0.5 1.0 1.2 1.5 Total .............................................................. 107.0 20.3 14.8 5.4 NE Household Size 1 Person ...................................................... 28.2 6.0 4.4 1.6 3.5 2 Persons

  11. ASSESSMENT OF HOUSEHOLD CARBON FOOTPRINT REDUCTION POTENTIALS

    SciTech Connect

    Kramer, Klaas Jan; Homan, Greg; Brown, Rich; Worrell, Ernst; Masanet, Eric

    2009-04-15

    The term ?household carbon footprint? refers to the total annual carbon emissions associated with household consumption of energy, goods, and services. In this project, Lawrence Berkeley National Laboratory developed a carbon footprint modeling framework that characterizes the key underlying technologies and processes that contribute to household carbon footprints in California and the United States. The approach breaks down the carbon footprint by 35 different household fuel end uses and 32 different supply chain fuel end uses. This level of end use detail allows energy and policy analysts to better understand the underlying technologies and processes contributing to the carbon footprint of California households. The modeling framework was applied to estimate the annual home energy and supply chain carbon footprints of a prototypical California household. A preliminary assessment of parameter uncertainty associated with key model input data was also conducted. To illustrate the policy-relevance of this modeling framework, a case study was conducted that analyzed the achievable carbon footprint reductions associated with the adoption of energy efficient household and supply chain technologies.

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

    Annual Energy Outlook

    with the decomposition of energy changes into separate effects. 5Factors such as conservation effort and consumer responses to change in energy prices may also influence changes ...

  13. Table 21. Total Energy Related Carbon Dioxide Emissions, Projected...

    Energy Information Administration (EIA) (indexed site)

    Total Energy Related Carbon Dioxide Emissions, Projected vs. Actual Projected (million metric tons) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 ...

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

    Energy Information Administration (EIA) (indexed site)

    Total Energy Related Carbon Dioxide Emissions, Projected vs. Actual" "Projected" " (million metric tons)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,200...

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

    Energy Information Administration (EIA) (indexed site)

    ... Division, Form EIA-846, '1991" "Manufacturing Energy Consumption Survey,' and Bureau of the Census, Industry" "Division, data files for the '1991 Annual Survey of Manufactures.'"

  16. char_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    2001 2 HC2-12a. Household Characteristics by West Census Region, Million U.S. Households, 2001 2 These data are from the 2001 Residential Energy Consumption Survey ...

  17. Total....................................................................

    Energy Information Administration (EIA) (indexed site)

    14.7 7.4 12.5 12.5 18.9 18.6 17.3 9.2 Household Size 1 Person.......................................................... 30.0 4.6 2.5 3.7 3.2 5.4 5.5 3.7 1.6 2 Persons......................................................... 34.8 4.3 1.9 4.4 4.1 5.9 5.3 5.5 3.4 3 Persons......................................................... 18.4 2.5 1.3 1.7 1.9 2.9 3.5 2.8 1.6 4 Persons......................................................... 15.9 1.9 0.8 1.5 1.6 3.0 2.5 3.1 1.4 5

  18. Total..........................................................

    Annual Energy Outlook

    Living Space Characteristics Detached Attached Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Table HC3.2 ...

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

    Office of Energy Efficiency and Renewable Energy (EERE)

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

  20. Total

    Energy Information Administration (EIA) (indexed site)

    Product: Total Crude Oil Liquefied Petroleum Gases PropanePropylene Normal ButaneButylene Other Liquids Oxygenates Fuel Ethanol MTBE Other Oxygenates Biomass-based Diesel Fuel ...

  1. Total

    Gasoline and Diesel Fuel Update

    of photovoltaic module shipments, 2015 (peak kilowatts) Source Disposition Source: U.S. Energy Information Administration, Form EIA-63B, 'Annual Photovoltaic CellModule ...

  2. Total............................................................

    Energy Information Administration (EIA) (indexed site)

    Total................................................................... 111.1 2,033 1,618 1,031 791 630 401 Total Floorspace (Square Feet) Fewer than 500............................................... 3.2 357 336 113 188 177 59 500 to 999....................................................... 23.8 733 667 308 343 312 144 1,000 to 1,499................................................. 20.8 1,157 1,086 625 435 409 235 1,500 to 1,999................................................. 15.4 1,592

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

    SciTech Connect

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

    1998-05-01

    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.

  4. Total-energy and pressure calculations for random substitutional alloys

    SciTech Connect

    Johnson, D.D. ); Nicholson, D.M. ); Pinski, F.J. ); Gyoerffy, B.L. ); Stocks, G.M. )

    1990-05-15

    We present the details and the derivation of density-functional-based expressions for the total energy and pressure for random substitutional alloys (RSA) using the Korringa-Kohn-Rostoker Green's-function approach in combination with the coherent-potential approximation (CPA) to treat the configurational averaging. This includes algebraic cancellation of various electronic core contributions to the total energy and pressure, as in ordered-solid muffin-tin-potential calculations. Thus, within the CPA, total-energy and pressure calculations for RSA have the same foundation and have been found to have the same accuracy as those obtained in similar calculations for ordered solids. Results of our calculations for the impurity formation energy, and for the bulk moduli, the lattice parameters, and the energy of mixing as a function of concentration in fcc Cu{sub {ital c}}Zn{sub 1{minus}{ital c}} alloys show that this generalized density-functional theory will be useful in studying alloy phase stability.

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

    SciTech Connect

    Henderson, L.J. ); Poyer, D.A.; Teotia, A.P.S. . Energy Systems Div.)

    1992-09-01

    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.

  6. Total...........................................................

    Energy Information Administration (EIA) (indexed site)

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

  7. char_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    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

  8. char_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    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

  9. char_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    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

  10. Total

    Energy Information Administration (EIA) (indexed site)

    Total floor- space 1 Heated floor- space 2 Total floor- space 1 Cooled floor- space 2 Total floor- space 1 Lit floor- space 2 All buildings 87,093 80,078 70,053 79,294 60,998 83,569 68,729 Building floorspace (square feet) 1,001 to 5,000 8,041 6,699 5,833 6,124 4,916 7,130 5,590 5,001 to 10,000 8,900 7,590 6,316 7,304 5,327 8,152 6,288 10,001 to 25,000 14,105 12,744 10,540 12,357 8,840 13,250 10,251 25,001 to 50,000 11,917 10,911 9,638 10,813 7,968 11,542 9,329 50,001 to 100,000 13,918 13,114

  11. Total...................................................................

    Energy Information Administration (EIA) (indexed site)

    2,033 1,618 1,031 791 630 401 Total Floorspace (Square Feet) Fewer than 500............................................... 3.2 357 336 113 188 177 59 500 to 999....................................................... 23.8 733 667 308 343 312 144 1,000 to 1,499................................................. 20.8 1,157 1,086 625 435 409 235 1,500 to 1,999................................................. 15.4 1,592 1,441 906 595 539 339 2,000 to

  12. Total..........................................................................

    Energy Information Administration (EIA) (indexed site)

    . 111.1 20.6 15.1 5.5 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 0.9 0.5 0.4 500 to 999........................................................... 23.8 4.6 3.6 1.1 1,000 to 1,499..................................................... 20.8 2.8 2.2 0.6 1,500 to 1,999..................................................... 15.4 1.9 1.4 0.5 2,000 to 2,499..................................................... 12.2 2.3 1.7 0.5 2,500 to

  13. Total..........................................................................

    Energy Information Administration (EIA) (indexed site)

    5.6 17.7 7.9 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 0.5 0.3 Q 500 to 999........................................................... 23.8 3.9 2.4 1.5 1,000 to 1,499..................................................... 20.8 4.4 3.2 1.2 1,500 to 1,999..................................................... 15.4 3.5 2.4 1.1 2,000 to 2,499..................................................... 12.2 3.2 2.1 1.1 2,500 to

  14. Total..........................................................................

    Energy Information Administration (EIA) (indexed site)

    0.7 21.7 6.9 12.1 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 0.9 0.6 Q Q 500 to 999........................................................... 23.8 9.0 4.2 1.5 3.2 1,000 to 1,499..................................................... 20.8 8.6 4.7 1.5 2.5 1,500 to 1,999..................................................... 15.4 6.0 2.9 1.2 1.9 2,000 to 2,499..................................................... 12.2 4.1 2.1 0.7

  15. Total..........................................................................

    Energy Information Administration (EIA) (indexed site)

    4.2 7.6 16.6 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 1.0 0.2 0.8 500 to 999........................................................... 23.8 6.3 1.4 4.9 1,000 to 1,499..................................................... 20.8 5.0 1.6 3.4 1,500 to 1,999..................................................... 15.4 4.0 1.4 2.6 2,000 to 2,499..................................................... 12.2 2.6 0.9 1.7 2,500 to

  16. Total................................................

    Energy Information Administration (EIA) (indexed site)

    .. 111.1 86.6 2,522 1,970 1,310 1,812 1,475 821 1,055 944 554 Total Floorspace (Square Feet) Fewer than 500............................. 3.2 0.9 261 336 162 Q Q Q 334 260 Q 500 to 999.................................... 23.8 9.4 670 683 320 705 666 274 811 721 363 1,000 to 1,499.............................. 20.8 15.0 1,121 1,083 622 1,129 1,052 535 1,228 1,090 676 1,500 to 1,999.............................. 15.4 14.4 1,574 1,450 945 1,628 1,327 629 1,712 1,489 808 2,000 to

  17. Total..........................................................

    Energy Information Administration (EIA) (indexed site)

    .. 111.1 24.5 1,090 902 341 872 780 441 Total Floorspace (Square Feet) Fewer than 500...................................... 3.1 2.3 403 360 165 366 348 93 500 to 999.............................................. 22.2 14.4 763 660 277 730 646 303 1,000 to 1,499........................................ 19.1 5.8 1,223 1,130 496 1,187 1,086 696 1,500 to 1,999........................................ 14.4 1.0 1,700 1,422 412 1,698 1,544 1,348 2,000 to 2,499........................................ 12.7

  18. Total...................................................................

    Energy Information Administration (EIA) (indexed site)

    Floorspace (Square Feet) Total Floorspace 1 Fewer than 500............................................ 3.2 0.4 Q 0.6 1.7 0.4 500 to 999................................................... 23.8 4.8 1.4 4.2 10.2 3.2 1,000 to 1,499............................................. 20.8 10.6 1.8 1.8 4.0 2.6 1,500 to 1,999............................................. 15.4 12.4 1.5 0.5 0.5 0.4 2,000 to 2,499............................................. 12.2 10.7 1.0 0.2 Q Q 2,500 to

  19. Total.........................................................................

    Energy Information Administration (EIA) (indexed site)

    Floorspace (Square Feet) Total Floorspace 2 Fewer than 500.................................................. 3.2 Q 0.8 0.9 0.8 0.5 500 to 999.......................................................... 23.8 1.5 5.4 5.5 6.1 5.3 1,000 to 1,499.................................................... 20.8 1.4 4.0 5.2 5.0 5.2 1,500 to 1,999.................................................... 15.4 1.4 3.1 3.5 3.6 3.8 2,000 to 2,499.................................................... 12.2 1.4 3.2 3.0 2.3 2.3

  20. Total..........................................................................

    Energy Information Administration (EIA) (indexed site)

    25.6 40.7 24.2 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 0.9 0.5 0.9 1.0 500 to 999........................................................... 23.8 4.6 3.9 9.0 6.3 1,000 to 1,499..................................................... 20.8 2.8 4.4 8.6 5.0 1,500 to 1,999..................................................... 15.4 1.9 3.5 6.0 4.0 2,000 to 2,499..................................................... 12.2 2.3 3.2 4.1

  1. Total..........................................................................

    Energy Information Administration (EIA) (indexed site)

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

  2. Total...........................................................

    Energy Information Administration (EIA) (indexed site)

    14.7 7.4 12.5 12.5 18.9 18.6 17.3 9.2 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500.................................... 3.2 0.7 Q 0.3 0.3 0.7 0.6 0.3 Q 500 to 999........................................... 23.8 2.7 1.4 2.2 2.8 5.5 5.1 3.0 1.1 1,000 to 1,499..................................... 20.8 2.3 1.4 2.4 2.5 3.5 3.5 3.6 1.6 1,500 to 1,999..................................... 15.4 1.8 1.4 2.2 2.0 2.4 2.4 2.1 1.2 2,000 to 2,499..................................... 12.2 1.4 0.9

  3. Total...........................................................

    Energy Information Administration (EIA) (indexed site)

    26.7 28.8 20.6 13.1 22.0 16.6 38.6 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................... 3.2 1.9 0.9 Q Q Q 1.3 2.3 500 to 999........................................... 23.8 10.5 7.3 3.3 1.4 1.2 6.6 12.9 1,000 to 1,499..................................... 20.8 5.8 7.0 3.8 2.2 2.0 3.9 8.9 1,500 to 1,999..................................... 15.4 3.1 4.2 3.4 2.0 2.7 1.9 5.0 2,000 to 2,499..................................... 12.2 1.7 2.7 2.9 1.8 3.2 1.1 2.8

  4. char_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    4a. Household Characteristics by Type of Housing Unit, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total Type of Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Homes Two to Four Units Five or More Units 0.4 0.5 1.6 1.4 2.0 Total ............................................... 107.0 73.7 9.5 17.0 6.8 4.3 Household Size 1 Person ....................................... 28.2 15.0 3.3 7.9 1.9 5.9 2 Persons

  5. char_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    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

  6. char_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    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

  7. char_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    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 --

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

    Energy Information Administration (EIA) (indexed site)

    Total Energy Consumption, Projected vs. Actual" "Projected" " (quadrillion Btu)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013 "AEO 1994",88.02,89.53,90.72,91.73,92.71,93.61,94.56,95.73,96.69,97.69,98.89,100,100.79,101.7,102.7,103.6,104.3,105.23 "AEO 1995",,89.21,89.98,90.57,91.91,92.98,93.84,94.61,95.3,96.19,97.18,98.38,99.37,100.3,101.2,102.1,102.9,103.88 "AEO

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

    Energy Information Administration (EIA) (indexed site)

    Total Energy Consumption, Projected vs. Actual Projected (quadrillion Btu) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 AEO 1994 88.0 89.5 90.7 91.7 92.7 93.6 94.6 95.7 96.7 97.7 98.9 100.0 100.8 101.7 102.7 103.6 104.3 105.2 AEO 1995 89.2 90.0 90.6 91.9 93.0 93.8 94.6 95.3 96.2 97.2 98.4 99.4 100.3 101.2 102.1 102.9 103.9 AEO 1996 90.6 91.3 92.5 93.5 94.3 95.1 95.9 96.9 98.0 99.2 100.4 101.4 102.1 103.1 103.8 104.7 105.5 106.5 107.2

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

    Energy Information Administration (EIA) (indexed site)

    Total Delivered Residential Energy Consumption, Projected vs. Actual Projected (quadrillion Btu) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 AEO 1994 10.3 10.4 10.4 10.4 10.4 10.4 10.4 10.4 10.4 10.4 10.4 10.5 10.5 10.5 10.5 10.5 10.6 10.6 AEO 1995 11.0 10.8 10.8 10.8 10.8 10.8 10.8 10.7 10.7 10.7 10.7 10.7 10.7 10.7 10.8 10.8 10.9 AEO 1996 10.4 10.7 10.7 10.7 10.8 10.8 10.9 10.9 11.0 11.2 11.2 11.3 11.4 11.5 11.6 11.7 11.8 12.0 12.1

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

    Energy Information Administration (EIA) (indexed site)

    Total Delivered Commercial Energy Consumption, Projected vs. Actual Projected (quadrillion Btu) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 AEO 1994 6.8 6.9 6.9 7.0 7.1 7.1 7.2 7.2 7.3 7.3 7.4 7.4 7.4 7.5 7.5 7.5 7.5 7.6 AEO 1995 6.9 6.9 7.0 7.0 7.0 7.1 7.1 7.1 7.1 7.1 7.2 7.2 7.2 7.2 7.3 7.3 7.3 AEO 1996 7.1 7.2 7.2 7.3 7.3 7.4 7.4 7.5 7.6 7.6 7.7 7.7 7.8 7.9 8.0 8.0 8.1 8.2 8.2 AEO 1997 7.4 7.4 7.4 7.5 7.5 7.6 7.7 7.7 7.8 7.8 7.9 7.9

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

    Energy Information Administration (EIA) (indexed site)

    Total Delivered Industrial Energy Consumption, Projected vs. Actual Projected (quadrillion Btu) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 AEO 1994 25.4 25.9 26.3 26.7 27.0 27.1 26.8 26.6 26.9 27.2 27.7 28.1 28.3 28.7 29.1 29.4 29.7 30.0 AEO 1995 26.2 26.3 26.5 27.0 27.3 26.9 26.6 26.8 27.1 27.5 27.9 28.2 28.4 28.7 29.0 29.3 29.6 AEO 1996 26.5 26.6 27.3 27.5 26.9 26.5 26.7 26.9 27.2 27.6 27.9 28.2 28.3 28.5 28.7 28.9 29.2 29.4 29.6

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

    Energy Information Administration (EIA) (indexed site)

    Total Delivered Transportation Energy Consumption, Projected vs. Actual Projected (quadrillion Btu) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 AEO 1994 23.6 24.1 24.5 24.7 25.1 25.4 25.7 26.2 26.5 26.9 27.2 27.6 27.9 28.3 28.6 28.9 29.2 29.5 AEO 1995 23.3 24.0 24.2 24.7 25.1 25.5 25.9 26.2 26.5 26.9 27.3 27.7 28.0 28.3 28.5 28.7 28.9 AEO 1996 23.9 24.1 24.5 24.8 25.3 25.7 26.0 26.4 26.7 27.1 27.5 27.8 28.1 28.4 28.6 28.9 29.1 29.3

  14. Delaware Total Electric Power Industry Net Generation, by Energy...

    Energy Information Administration (EIA) (indexed site)

    ...e","-","-","-","-","-" "Other","-","-",11,6,"-" "Total",7182,8534,7524,4842,5628 " " "s Value is less than 0.5 of the table metric, but value is included in any associated total.

  15. Total China Investment Co Ltd | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    China Investment Co Ltd Jump to: navigation, search Name: Total (China) Investment Co. Ltd. Place: Beijing, China Zip: 100004 Product: Total has been present in China for about 30...

  16. ac_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    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

  17. appl_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    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

  18. ac_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    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

  19. ac_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    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

  20. ac_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    2a. Air Conditioning by West Census Region, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total U.S. West Census Region RSE Row Factors Total Census Division Mountain Pacific 0.4 1.2 1.7 1.4 Households With Electric Air-Conditioning Equipment ...................... 82.9 10.7 3.4 7.2 7.1 Air Conditioners Not Used ........................... 2.1 1.1 0.2 0.9 15.5 Households Using Electric Air-Conditioning 1 ........................................ 80.8 9.6 3.2

  1. Table 2.4 Household Energy Consumption by Census Region, Selected...

    Energy Information Administration (EIA) (indexed site)

    ... NANot available. 2See Appendix C for map of Census regions. Notes: * Data are estimates, and are for major energy sources only. * For years not shown, there are no data available. ...

  2. Total Agroindustria Canavieira S A | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Agroindustria Canavieira S A Jump to: navigation, search Name: Total Agroindustria Canavieira SA Place: Bambui, Minas Gerais, Brazil Product: Ethanol producer in Minas Gerais,...

  3. Utah Total Electric Power Industry Net Summer Capacity, by Energy...

    Energy Information Administration (EIA) (indexed site)

    Utah" "Energy Source",2006,2007,2008,2009,2010 "Fossil",6398,6830,6819,6897,6969 " ... " Other Gases","-","-","-","-","-" "Nuclear","-","-","-","-","-" ...

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

    Energy Information Administration (EIA) (indexed site)

    8. Selected Energy Operating Ratios for Total Energy Consumption for" " Heat, Power, and Electricity Generation by Census Region, Census Division, and Economic" " Characteristics of the Establishment, 1994" ,,,"Consumption","Major" " "," ","Consumption","per Dollar","Byproducts(b)","Fuel Oil(c)"," " " ","Consumption","per Dollar","of

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

    Energy Information Administration (EIA) (indexed site)

    0. Selected Energy Operating Ratios for Total Energy Consumption for" " Heat, Power, and Electricity Generation by Industry Group," " Selected Industries, and Economic Characteristics of the" " Establishment, 1991 (Continued)" ,,,,,"Major" ,,,"Consumption","Consumption per","Byproducts(c)","Fuel Oil(d)" ,,"Consumption","per Dollar","Dollar of Value","as a Percent

  6. "Table A28. Total Expenditures for Purchased Energy Sources...

    Energy Information Administration (EIA) (indexed site)

    ... Division, Form EIA-846, '1991" "Manufacturing Energy Consumption Survey,' and Bureau of the Census, Industry" "Division, data files for the '1991 Annual Survey of Manufactures.'

  7. ,"Total Fuel Oil Consumption (trillion Btu)",,,,,"Fuel Oil Energy...

    Energy Information Administration (EIA) (indexed site)

    in this table do not include enclosed malls and strip malls. In the 1999 CBECS, total fuel oil consumption in malls was not statistically significant. (*)Value rounds to zero...

  8. Property:Building/SPElectrtyUsePercTotal | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    PElectrtyUsePercTotal" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 100.0 + Sweden Building 05K0002 + 100.0 + Sweden Building 05K0003 +...

  9. AEO2011:Total Energy Supply, Disposition, and Price Summary ...

    OpenEI (Open Energy Information) [EERE & EIA]

    case. The dataset uses quadrillion Btu and the U.S. Dollar. The data is broken down into production, imports, exports, consumption and price. Data and Resources AEO2011:Total...

  10. Property:RenewableFuelStandard/Total | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Property Edit with form History Facebook icon Twitter icon Property:RenewableFuelStandardTotal Jump to: navigation, search This is a property of type Number. Pages using the...

  11. Fact #565: April 6, 2009 Household Gasoline Expenditures by Income |

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Department of Energy 5: April 6, 2009 Household Gasoline Expenditures by Income Fact #565: April 6, 2009 Household Gasoline Expenditures by Income In the annual Consumer Expenditure Survey, household incomes are grouped into five equal parts called quintiles (each quintile is 20%). Households in the second and third quintiles consistently have a higher share of spending on gasoline each year than households in the other quintiles. Household Gasoline Expenditures by Income Quintile Bar graph

  12. Household magnets

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Household magnets Chances are very good that you have experimented with magnets. People have been fascinated with magnetism for thousands of years. As familiar to us as they may be, magnets still have some surprises for us. Here is a small collection of some of our favorite magnet experiments. What happens when we break a magnet in half? Radio Shack sells cheap ceramic magnets in several shapes. Get a ring shaped magnet and break it with pliers or a tap with a hammer. Try to put it back

  13. Iowa Total Electric Power Industry Net Summer Capacity, by Energy...

    Energy Information Administration (EIA) (indexed site)

    Iowa" "Energy Source",2006,2007,2008,2009,2010 "Fossil",9496,10391,10340,10467,10263 " Coal",6097,6967,6928,7107,6956 " Petroleum",1027,1023,1017,1014,1007 " Natural ...

  14. Maine Total Electric Power Industry Net Summer Capacity, by Energy...

    Energy Information Administration (EIA) (indexed site)

    Maine" "Energy Source",2006,2007,2008,2009,2010 "Fossil",2770,2751,2761,2738,2738 " Coal",85,85,85,85,85 " Petroleum",1030,1031,1031,1008,1008 " Natural Gas",1655,1636,1645,1645,16...

  15. Michigan Total Electric Power Industry Net Generation, by Energy...

    Energy Information Administration (EIA) (indexed site)

    Michigan" "Energy Source",2006,2007,2008,2009,2010 "Fossil",80004,84933,80179,75869,78535 " Coal",67780,70811,69855,66848,65604 " Petroleum",402,699,458,399,382 " Natural ...

  16. Texas Total Electric Power Industry Net Summer Capacity, by Energy...

    Energy Information Administration (EIA) (indexed site)

    Texas" "Energy Source",2006,2007,2008,2009,2010 "Fossil",92088,91494,91450,87547,92136 " ... " Other Gases",287,308,187,184,306 "Nuclear",4860,4860,4927,4927,4966 ...

  17. Ohio Total Electric Power Industry Net Summer Capacity, by Energy...

    Energy Information Administration (EIA) (indexed site)

    Ohio" "Energy Source",2006,2007,2008,2009,2010 "Fossil",31582,31418,31154,31189,30705 " ... " Other Gases",100,100,100,100,123 "Nuclear",2120,2124,2124,2134,2134 ...

  18. Property:Geothermal/TotalProjectCost | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Churchill Co., NV Geothermal Project + 14,571,873 + A Demonstration System for Capturing Geothermal Energy from Mine Waters beneath Butte, MT Geothermal Project + 2,155,497 + A...

  19. Vermont Total Electric Power Industry Net Generation, by Energy...

    Energy Information Administration (EIA) (indexed site)

    Vermont" "Energy Source",2006,2007,2008,2009,2010 "Fossil",9,10,7,7,8 " Coal","-","-","-","-","-" " Petroleum",7,8,4,2,5 " Natural Gas",2,2,3,4,4 " Other Gases","-","-","-","-","-" ...

  20. Nebraska Total Electric Power Industry Net Generation, by Energy...

    Energy Information Administration (EIA) (indexed site)

    Nebraska" "Energy Source",2006,2007,2008,2009,2010 "Fossil",21461,20776,22273,23684,23769 " Coal",20683,19630,21480,23350,23363 " Petroleum",19,36,35,23,31 " Natural ...

  1. Oregon Total Electric Power Industry Net Generation, by Energy...

    Energy Information Administration (EIA) (indexed site)

    Oregon" "Energy Source",2006,2007,2008,2009,2010 "Fossil",13621,19224,21446,19338,19781 " Coal",2371,4352,4044,3197,4126 " Petroleum",12,14,15,8,3 " Natural Gas",11239,14858,17387,...

  2. Nevada Total Electric Power Industry Net Generation, by Energy...

    Energy Information Administration (EIA) (indexed site)

    Nevada" "Energy Source",2006,2007,2008,2009,2010 "Fossil",28459,29370,31801,33436,30702 " Coal",7254,7091,7812,7540,6997 " Petroleum",17,11,14,16,11 " Natural Gas",21184,22263,2397...

  3. Utah Total Electric Power Industry Net Generation, by Energy...

    Energy Information Administration (EIA) (indexed site)

    Utah" "Energy Source",2006,2007,2008,2009,2010 "Fossil",40306,44634,45466,42034,40599 " Coal",36856,37171,38020,35526,34057 " Petroleum",62,39,44,36,50 " Natural ...

  4. Oklahoma Total Electric Power Industry Net Generation, by Energy...

    Energy Information Administration (EIA) (indexed site)

    Oklahoma" "Energy Source",2006,2007,2008,2009,2010 "Fossil",68093,67765,70122,68700,65435 " Coal",35032,34438,36315,34059,31475 " Petroleum",64,160,23,9,18 " Natural ...

  5. Ohio Total Electric Power Industry Net Generation, by Energy...

    Energy Information Administration (EIA) (indexed site)

    Ohio" "Energy Source",2006,2007,2008,2009,2010 "Fossil",137494,138543,134878,119712,126652 " Coal",133400,133131,130694,113712,117828 " Petroleum",1355,1148,1438,1312,1442 " ...

  6. Idaho Total Electric Power Industry Net Summer Capacity, by Energy...

    Energy Information Administration (EIA) (indexed site)

    Idaho" "Energy Source",2006,2007,2008,2009,2010 "Fossil",667,667,828,834,834 " Coal",17,17,17,17,17 " Petroleum",5,5,5,5,5 " Natural Gas",645,645,805,812,812 " Other ...

  7. Colorado Total Electric Power Industry Net Generation, by Energy...

    Energy Information Administration (EIA) (indexed site)

    Colorado" "Energy Source",2006,2007,2008,2009,2010 "Fossil",48211,50980,48334,45490,45639 " Coal",36269,35936,34828,31636,34559 " Petroleum",21,28,19,13,17 " Natural ...

  8. Kentucky Total Electric Power Industry Net Generation, by Energy...

    Energy Information Administration (EIA) (indexed site)

    Kentucky" "Energy Source",2006,2007,2008,2009,2010 "Fossil",95720,95075,95478,86937,95182 " Coal",91198,90483,91621,84038,91054 " Petroleum",3341,2791,2874,2016,2285 " Natural ...

  9. Delaware Total Electric Power Industry Net Generation, by Energy...

    Energy Information Administration (EIA) (indexed site)

    Delaware" "Energy Source",2006,2007,2008,2009,2010 "Fossil",7182,8486,7350,4710,5489 " Coal",4969,5622,5267,2848,2568 " Petroleum",132,241,219,258,56 " Natural ...

  10. Indiana Total Electric Power Industry Net Generation, by Energy...

    Energy Information Administration (EIA) (indexed site)

    Indiana" "Energy Source",2006,2007,2008,2009,2010 "Fossil",129345,129576,128206,114118,121101 " Coal",123645,122803,122036,108312,112328 " Petroleum",148,170,178,157,155 " Natural ...

  11. Idaho Total Electric Power Industry Net Generation, by Energy...

    Energy Information Administration (EIA) (indexed site)

    Idaho" "Energy Source",2006,2007,2008,2009,2010 "Fossil",1381,1741,1790,1726,1778 " Coal",82,84,90,83,88 " Petroleum","s","s","s","s","s" " Natural Gas",1298,1657,1700,1644,1689 " ...

  12. Florida Total Electric Power Industry Net Generation, by Energy...

    Energy Information Administration (EIA) (indexed site)

    Florida" "Energy Source",2006,2007,2008,2009,2010 "Fossil",184530,188433,180167,181553,197662 " Coal",65423,67908,64823,54003,59897 " Petroleum",22904,20203,11971,9221,9122 " ...

  13. Hawaii Total Electric Power Industry Net Generation, by Energy...

    Energy Information Administration (EIA) (indexed site)

    Hawaii" "Energy Source",2006,2007,2008,2009,2010 "Fossil",10646,10538,10356,9812,9655 " Coal",1549,1579,1648,1500,1546 " Petroleum",9054,8914,8670,8289,8087 " Natural ...

  14. Illinois Total Electric Power Industry Net Generation, by Energy...

    Energy Information Administration (EIA) (indexed site)

    Illinois" "Energy Source",2006,2007,2008,2009,2010 "Fossil",97212,103072,101101,94662,99605 " Coal",91649,95265,96644,89967,93611 " Petroleum",136,132,143,113,110 " Natural ...

  15. Georgia Total Electric Power Industry Net Generation, by Energy...

    Energy Information Administration (EIA) (indexed site)

    Georgia" "Energy Source",2006,2007,2008,2009,2010 "Fossil",100299,107165,99661,90634,97823 " Coal",86504,90298,85491,69478,73298 " Petroleum",834,788,742,650,641 " Natural ...

  16. Kansas Total Electric Power Industry Net Generation, by Energy...

    Energy Information Administration (EIA) (indexed site)

    Kansas" "Energy Source",2006,2007,2008,2009,2010 "Fossil",35172,38590,36363,35033,34895 " Coal",33281,36250,34003,32243,32505 " Petroleum",51,207,130,121,103 " Natural ...

  17. Iowa Total Electric Power Industry Net Generation, by Energy...

    Energy Information Administration (EIA) (indexed site)

    Iowa" "Energy Source",2006,2007,2008,2009,2010 "Fossil",37014,41388,42734,38621,42749 " Coal",34405,37986,40410,37351,41283 " Petroleum",208,312,161,85,154 " Natural ...

  18. Washington Total Electric Power Industry Net Generation, by Energy...

    Energy Information Administration (EIA) (indexed site)

    Washington" "Energy Source",2006,2007,2008,2009,2010 "Fossil",14255,16215,18879,19747,19211 " Coal",6373,8557,8762,7478,8527 " Petroleum",38,37,35,54,32 " Natural ...

  19. Wisconsin Total Electric Power Industry Net Generation, by Energy...

    Energy Information Administration (EIA) (indexed site)

    Wisconsin" "Energy Source",2006,2007,2008,2009,2010 "Fossil",46352,47530,47881,43477,46384 " Coal",40116,40028,41706,37280,40169 " Petroleum",877,1013,931,712,718 " Natural ...

  20. Virginia Total Electric Power Industry Net Generation, by Energy...

    Energy Information Administration (EIA) (indexed site)

    Virginia" "Energy Source",2006,2007,2008,2009,2010 "Fossil",42343,48422,42242,38888,43751 " Coal",34288,35421,31776,25599,25459 " Petroleum",839,2097,1150,1088,1293 " Natural ...

  1. New Mexico Total Electric Power Industry Net Generation, by Energy...

    Energy Information Administration (EIA) (indexed site)

    Mexico" "Energy Source",2006,2007,2008,2009,2010 "Fossil",35790,34308,35033,37823,34180 " Coal",29859,27604,27014,29117,25618 " Petroleum",41,44,53,45,50 " Natural ...

  2. New York Total Electric Power Industry Net Generation, by Energy...

    Energy Information Administration (EIA) (indexed site)

    York" "Energy Source",2006,2007,2008,2009,2010 "Fossil",69880,75234,66756,57187,64503 " Coal",20968,21406,19154,12759,13583 " Petroleum",6778,8195,3745,2648,2005 " Natural ...

  3. Wyoming Total Electric Power Industry Net Generation, by Energy...

    Energy Information Administration (EIA) (indexed site)

    Wyoming" "Energy Source",2006,2007,2008,2009,2010 "Fossil",43749,44080,44635,42777,43781 " Coal",42892,43127,43808,41954,42987 " Petroleum",46,47,44,50,56 " Natural ...

  4. New Jersey Total Electric Power Industry Net Generation, by Energy...

    Energy Information Administration (EIA) (indexed site)

    Jersey" "Energy Source",2006,2007,2008,2009,2010 "Fossil",26910,29576,30264,26173,31662 " Coal",10862,10211,9028,5100,6418 " Petroleum",270,453,325,278,235 " Natural ...

  5. ac_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    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

  6. char_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    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

  7. char_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    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

  8. char_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    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

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

    Energy Information Administration (EIA) (indexed site)

    5. Selected Energy Operating Ratios for Total Energy Consumption" " for Heat, Power, and Electricity Generation by Industry Group," " Selected Industries, and Value of Shipment Categories, 1994" ,,,,,"Major" ,,,"Consumption","Consumption per","Byproducts(c)","Fuel Oil(d)" ,,"Consumption","per Dollar","Dollar of Value","as a Percent","as a Percent","RSE"

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

    Energy Information Administration (EIA) (indexed site)

    Selected Energy Operating Ratios for Total Energy Consumption" " for Heat, Power, and Electricity Generation by Industry Group," " Selected Industries, and Employment Size Categories, 1994" ,,,,,"Major" ,,,"Consumption","Consumption per","Byproducts(c)","Fuel Oil(d)" ,,"Consumption","per Dollar","Dollar of Value","as a Percent","as a Percent","RSE"

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

    Energy Information Administration (EIA) (indexed site)

    7. Selected Energy Operating Ratios for Total Energy Consumption for" " Heat, Power, and Electricity Generation by Census Region, Census Division, Industry Group, and" " Selected Industries, 1994" ,,,,,"Major" ,,,,"Consumption","Byproducts(b)" ,,,"Consumption","per Dollar","as a","Fuel Oil(c) as" ,,"Consumption","per Dollar","of Value","Percent of","a

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

    Energy Information Administration (EIA) (indexed site)

    1. Selected Energy Operating Ratios for Total Energy Consumption for" " Heat, Power, and Electricity Generation by Census Region and Economic" " Characteristics of the Establishment, 1991 " ,,,,,"Major" ,,,"Consumption","Consumption per","Byproducts(c)","Fuel Oil(d)" ,,"Consumption","per Dollar","Dollar of Value","as a Percent","as a Percent","RSE"

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

    Energy Information Administration (EIA) (indexed site)

    A8. Selected Energy Operating Ratios for Total Energy Consumption for" " Heat, Power, and Electricity Generation by Census Region, Industry Group, and" " Selected Industries, 1991" ,,,,,"Major" ,,,,"Consumption","Byproducts(b)" ,,,"Consumption","per Dollar","as a","Fuel Oil(c) as" ,,"Consumption","per Dollar","of Value","Percent of","a Percent

  14. homeoffice_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    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

  15. homeoffice_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    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

  16. homeoffice_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    2a. Home Office Equipment by West Census Region, Million U.S. Households, 2001 Home Office Equipment RSE Column Factor: Total U.S. West Census Region RSE Row Factors Total Census Division Mountain Pacific 0.5 1.0 1.6 1.2 Total .............................................................. 107.0 23.3 6.7 16.6 NE Households Using Office Equipment ......................................... 96.2 21.4 6.2 15.2 1.0 Personal Computers 1 ................................. 60.0 14.3 4.0 10.4 3.7 Number of

  17. homeoffice_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    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

  18. Tennessee Total Electric Power Industry Net Generation, by Energy Source

    Energy Information Administration (EIA) (indexed site)

    Tennessee" "Energy Source",2006,2007,2008,2009,2010 "Fossil",61336,61205,57753,42242,46203 " Coal",60498,60237,57058,41633,43670 " Petroleum",160,232,216,187,217 " Natural Gas",664,722,467,409,2302 " Other Gases",14,13,12,12,13 "Nuclear",24679,28700,27030,26962,27739 "Renewables",8559,5910,6611,11162,9125 "Pumped Storage",-668,-704,-739,-650,-721 "Other",5,3,8,1,3

  19. Texas Total Electric Power Industry Net Generation, by Energy Source

    Energy Information Administration (EIA) (indexed site)

    Texas" "Energy Source",2006,2007,2008,2009,2010 "Fossil",349849,351720,344813,333227,341054 " Coal",146391,147279,147132,139107,150173 " Petroleum",1789,1309,1034,1405,708 " Natural Gas",197870,199531,193247,189066,186882 " Other Gases",3798,3601,3401,3649,3291 "Nuclear",41264,40955,40727,41498,41335 "Renewables",8480,11932,18679,22133,28967 "Pumped

  20. Pennsylvania Total Electric Power Industry Net Generation, by Energy Source

    Energy Information Administration (EIA) (indexed site)

    Pennsylvania" "Energy Source",2006,2007,2008,2009,2010 "Fossil",138173,143909,137862,136047,145210 " Coal",122558,122693,117583,105475,110369 " Petroleum",1518,1484,938,915,571 " Natural Gas",13542,19198,18731,29215,33718 " Other Gases",554,534,610,443,552 "Nuclear",75298,77376,78658,77328,77828 "Renewables",5317,4782,5353,6035,6577 "Pumped Storage",-698,-723,-354,-731,-708

  1. Louisiana Total Electric Power Industry Net Generation, by Energy Source

    Energy Information Administration (EIA) (indexed site)

    Louisiana" "Energy Source",2006,2007,2008,2009,2010 "Fossil",69795,71028,72850,70155,80110 " Coal",24395,23051,24100,23067,23924 " Petroleum",1872,2251,2305,1858,3281 " Natural Gas",41933,43915,45344,44003,51344 " Other Gases",1595,1811,1101,1227,1561 "Nuclear",16735,17078,15371,16782,18639 "Renewables",3676,3807,3774,3600,3577 "Pumped

  2. Maine Total Electric Power Industry Net Generation, by Energy Source

    Energy Information Administration (EIA) (indexed site)

    Maine" "Energy Source",2006,2007,2008,2009,2010 "Fossil",8214,7869,8264,7861,8733 " Coal",321,376,352,72,87 " Petroleum",595,818,533,433,272 " Natural Gas",7298,6675,7380,7355,8374 " Other Gases","-","-","-","-","-" "Nuclear","-","-","-","-","-" "Renewables",8246,7945,8515,8150,7963 "Pumped

  3. Maryland Total Electric Power Industry Net Generation, by Energy Source

    Energy Information Administration (EIA) (indexed site)

    Maryland" "Energy Source",2006,2007,2008,2009,2010 "Fossil",32091,33303,29810,26529,27102 " Coal",29408,29699,27218,24162,23668 " Petroleum",581,985,406,330,322 " Natural Gas",1770,2241,1848,1768,2897 " Other Gases",332,378,338,269,215 "Nuclear",13830,14353,14679,14550,13994 "Renewables",2730,2256,2587,2440,2241 "Pumped Storage","-","-","-","-","-"

  4. Massachusetts Total Electric Power Industry Net Generation, by Energy Source

    Energy Information Administration (EIA) (indexed site)

    Massachusetts" "Energy Source",2006,2007,2008,2009,2010 "Fossil",36773,40001,34251,30913,34183 " Coal",11138,12024,10629,9028,8306 " Petroleum",2328,3052,2108,897,296 " Natural Gas",23307,24925,21514,20988,25582 " Other Gases","-","-","-","-","-" "Nuclear",5830,5120,5869,5396,5918 "Renewables",2791,2038,2411,2430,2270 "Pumped

  5. Minnesota Total Electric Power Industry Net Generation, by Energy Source

    Energy Information Administration (EIA) (indexed site)

    Minnesota" "Energy Source",2006,2007,2008,2009,2010 "Fossil",36125,36463,34879,32263,32454 " Coal",33070,32190,31755,29327,28083 " Petroleum",494,405,232,65,31 " Natural Gas",2561,3842,2866,2846,4341 " Other Gases","-",26,27,24,"-" "Nuclear",13183,13103,12997,12393,13478 "Renewables",3631,4586,6578,7546,7480 "Pumped

  6. Mississippi Total Electric Power Industry Net Generation, by Energy Source

    Energy Information Administration (EIA) (indexed site)

    Mississippi" "Energy Source",2006,2007,2008,2009,2010 "Fossil",34254,39184,37408,36266,43331 " Coal",18105,17407,16683,12958,13629 " Petroleum",399,399,76,17,81 " Natural Gas",15706,21335,20607,23267,29619 " Other Gases",44,42,40,25,2 "Nuclear",10419,9359,9397,10999,9643 "Renewables",1541,1493,1391,1424,1504 "Pumped Storage","-","-","-","-","-"

  7. Missouri Total Electric Power Industry Net Generation, by Energy Source

    Energy Information Administration (EIA) (indexed site)

    Missouri" "Energy Source",2006,2007,2008,2009,2010 "Fossil",81245,80127,78788,75122,79870 " Coal",77450,75084,73532,71611,75047 " Petroleum",61,60,57,88,126 " Natural Gas",3729,4979,5196,3416,4690 " Other Gases",5,3,3,7,7 "Nuclear",10117,9372,9379,10247,8996 "Renewables",223,1234,2293,2391,2527 "Pumped Storage",48,383,545,567,888 "Other",54,37,24,27,32

  8. Montana Total Electric Power Industry Net Generation, by Energy Source

    Energy Information Administration (EIA) (indexed site)

    Montana" "Energy Source",2006,2007,2008,2009,2010 "Fossil",17583,18960,18822,16181,19068 " Coal",17085,18357,18332,15611,18601 " Petroleum",419,479,419,490,409 " Natural Gas",68,106,66,78,57 " Other Gases",11,19,6,1,2 "Nuclear","-","-","-","-","-" "Renewables",10661,9971,10704,10422,10442 "Pumped

  9. Alabama Total Electric Power Industry Net Generation, by Energy Source

    Energy Information Administration (EIA) (indexed site)

    Alabama" "Energy Source",2006,2007,2008,2009,2010 "Fossil",97827,101561,97376,87580,102762 " Coal",78109,77994,74605,55609,63050 " Petroleum",180,157,204,219,200 " Natural Gas",19407,23232,22363,31617,39235 " Other Gases",131,178,204,135,277 "Nuclear",31911,34325,38993,39716,37941 "Renewables",11136,7937,9493,15585,11081 "Pumped

  10. Alaska Total Electric Power Industry Net Generation, by Energy Source

    Energy Information Administration (EIA) (indexed site)

    Alaska" "Energy Source",2006,2007,2008,2009,2010 "Fossil",5443,5519,5598,5365,5308 " Coal",617,641,618,631,620 " Petroleum",768,1010,978,1157,937 " Natural Gas",4058,3868,4002,3577,3750 " Other Gases","-","-","-","-","-" "Nuclear","-","-","-","-","-" "Renewables",1231,1302,1177,1337,1452 "Pumped

  11. Arizona Total Electric Power Industry Net Generation, by Energy Source

    Energy Information Administration (EIA) (indexed site)

    Arizona" "Energy Source",2006,2007,2008,2009,2010 "Fossil",73385,79794,82715,74509,73386 " Coal",40443,41275,43840,39707,43644 " Petroleum",73,49,52,63,66 " Natural Gas",32869,38469,38822,34739,29676 " Other Gases","-","-","-","-","-" "Nuclear",24012,26782,29250,30662,31200 "Renewables",6846,6639,7400,6630,6941 "Pumped Storage",149,125,95,169,209

  12. Arkansas Total Electric Power Industry Net Generation, by Energy Source

    Energy Information Administration (EIA) (indexed site)

    Arkansas" "Energy Source",2006,2007,2008,2009,2010 "Fossil",33626,34203,34639,36385,40667 " Coal",24183,25744,26115,25075,28152 " Petroleum",161,94,64,88,45 " Natural Gas",9282,8364,8461,11221,12469 " Other Gases","-","-","-","-","-" "Nuclear",15233,15486,14168,15170,15023 "Renewables",3273,4860,6173,5778,5283 "Pumped Storage",15,30,48,100,-1

  13. California Total Electric Power Industry Net Generation, by Energy Source

    Energy Information Administration (EIA) (indexed site)

    California" "Energy Source",2006,2007,2008,2009,2010 "Fossil",112317,122151,125699,118679,112376 " Coal",2235,2298,2280,2050,2100 " Petroleum",2368,2334,1742,1543,1059 " Natural Gas",105691,115700,119992,113463,107522 " Other Gases",2022,1818,1685,1623,1695 "Nuclear",31959,35792,32482,31764,32201 "Renewables",71963,52173,48912,53428,58881 "Pumped Storage",96,310,321,153,-171

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

    Energy Information Administration (EIA) (indexed site)

    ... '1994" "Manufacturing Energy Consumption Survey', and Bureau of the Census, Industry" "Division, data files for the '1994 Annual Survey of Manufactures.'" "Table A53. Total ...

  15. ac_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    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

  16. U.S. Department of Energy Releases Revised Total System Life...

    Energy Saver

    U.S. Department of Energy Releases Revised Total System Life Cycle Cost Estimate and Fee Adequacy Report ... U.S. Department of Energy Awards Contracts for Waste Storage Canisters for ...

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

    Energy Information Administration (EIA) (indexed site)

    National Research Council, Effectiveness and Impact of Corporate Average Fuel Economy (CAFE) Standards (Washington, DC: National Academy of Sciences, 2002), p. 85. 4 8.3 million...

  18. appl_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    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

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

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Estimate and Fee Adequacy Report for Yucca Mountain Project | Department of Energy Revised Total System Life Cycle Cost Estimate and Fee Adequacy Report for Yucca Mountain Project U.S. Department of Energy Releases Revised Total System Life Cycle Cost Estimate and Fee Adequacy Report for Yucca Mountain Project August 5, 2008 - 2:40pm Addthis WASHINGTON, DC -The U.S. Department of Energy (DOE) today released a revised estimate of the total system life cycle cost for a repository at Yucca

  20. homeoffice_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral ... 29.1 5.3 22.7 3.8 1 Below 150 percent of poverty line or 60 percent of median State income

  1. char_household2001.pdf

    Annual Energy Outlook

    RSE Row Factors New York California Texas Florida 0.4 1.1 1.0 1.5 1.5 Total ... RSE Row Factors New York California Texas Florida 0.4 1.1 1.0 1.5 1.5 Household Owns or ...

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

    SciTech Connect

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

    2008-03-01

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

  3. ac_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    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

  4. ac_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    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

  5. ac_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    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

  6. DOE Selects Projects Totaling $12.4 Million Aimed at Increasing Domestic Energy Production While Enhancing Environmental Protection

    Office of Energy Efficiency and Renewable Energy (EERE)

    A total of 11 research projects that will help find ways to extract more energy from unconventional oil and gas resources while reducing environmental risks have been selected totaling $12.4 million by DOE's Office of Fossil Energy.

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

    Energy Information Administration (EIA) (indexed site)

    2. Total Quantity of Purchased Energy Sources by Census Region," " Industry Group, and Selected Industries, 1991" " (Estimates in Btu or Physical Units)" ,,,,,,"Natural",,,"Coke" " "," ","Total","Electricity","Residual","Distillate","Gas(c)"," ","Coal","and Breeze"," ","RSE" "SIC","

  8. appl_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    0a. Appliances by Midwest Census Region, Million U.S. Households, 2001 Appliance Types and 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 1.5 Total .............................................................. 107.0 24.5 17.1 7.4 NE Kitchen Appliances Cooking Appliances Oven ......................................................... 101.7 23.8 16.6 7.2 NE 1

  9. appl_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    1a. Appliances by South Census Region, Million U.S. Households, 2001 Appliance Types and 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 1.4 1.5 Total .............................................................. 107.0 38.9 20.3 6.8 11.8 NE Kitchen Appliances Cooking Appliances Oven ......................................................... 101.7 36.2 19.4 6.4 10.3 1.5 1

  10. appl_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    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

  11. spaceheat_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    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

  12. homeoffice_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    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

  13. ac_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    a. Air Conditioning by Climate Zone, Million U.S. Households, 2001 Air Conditioning 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 2.1 1.0 0.9 1.5 1.0 Total Households With Air-Conditioning ........................... 82.9 5.4 20.9 20.2 14.2 22.1 8.1 Air Conditioners Not Used ............ 2.1 Q 0.4 0.3 0.8 0.4 23.2

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

    Energy Information Administration (EIA) (indexed site)

    Total First Use (formerly Primary Consumption) of Energy for All Purposes by Census" " Region, Census Division, and Economic Characteristics of the Establishment, 1994" " (Estimates in Btu or Physical Units)" ,,,,,,,,"Coke",,"Shipments" " "," ","Net","Residual","Distillate","Natural Gas(e)"," ","Coal","and Breeze"," ","of Energy

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

    Energy Information Administration (EIA) (indexed site)

    A41. Total Inputs of Energy for Heat, Power, and Electricity" " Generation by Census Region, Industry Group, Selected Industries, and Type of" " Energy Management Program, 1991" " (Estimates in Trillion Btu)" ,,," Census Region",,,,"RSE" "SIC","Industry Groups",," -------------------------------------------",,,,"Row" "Code(a)","and

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

    Energy Information Administration (EIA) (indexed site)

    A50. Total Inputs of Energy for Heat, Power, and Electricity Generation" " by Census Region, Industry Group, Selected Industries, and Type of" " Energy-Management Program, 1994" " (Estimates in Trillion Btu)" ,,,," Census Region",,,"RSE" "SIC",,,,,,,"Row" "Code(a)","Industry Group and

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

    SciTech Connect

    Herendeen, R.A.

    1983-06-01

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

  18. appl_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    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

  19. appl_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

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

  20. appl_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    6a. Appliances by Type of Rented Housing Unit, Million U.S. Households, 2001 Appliance Types and 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 Kitchen Appliances Cooking Appliances Oven ........................................... 33.4 10.1 7.3 14.9 1.1

  1. appl_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    8a. Appliances by Urban/Rural Location, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total Urban/Rural Location 1 RSE Row Factors City Town Suburbs Rural 0.5 0.9 1.4 1.2 1.3 Total .............................................................. 107.0 49.9 18.0 21.2 17.9 4.1 Kitchen Appliances Cooking Appliances Oven ......................................................... 101.7 47.5 17.5 19.9 16.8 4.2 1

  2. spaceheat_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    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

  3. spaceheat_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    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

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

    Energy Information Administration (EIA) (indexed site)

    A9. Total Primary Consumption of Energy for All Purposes by Census" " Region and Economic Characteristics of the Establishment, 1991" " (Estimates in Btu or Physical Units)" ,,,,,,,,"Coke" " "," ","Net","Residual","Distillate","Natural Gas(d)"," ","Coal","and Breeze"," ","RSE" " ","Total","Electricity(b)","Fuel

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

    Energy Information Administration (EIA) (indexed site)

    Total First Use (formerly Primary Consumption) of Energy for All Purposes" " by Employment Size Categories, Industry Group, and Selected Industries, 1994" " (Estimates in Trillion Btu)" ,,,," "," Employment Size(b)" ,,,,,,,,,"RSE" "SIC"," "," "," "," "," "," "," ",1000,"Row" "Code(a)","Industry Group and

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

    Energy Information Administration (EIA) (indexed site)

    Total Inputs of Energy for Heat, Power, and Electricity Generation" " by Value of Shipment Categories, Industry Group, and Selected Industries, 1991" " (Continued)" " (Estimates in Trillion Btu)",,,,"Value of Shipments and Receipts(b)" ,,,," (million dollars)" ,,,"-","-","-","-","-","-","RSE" "SIC"," "," "," "," ","

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

    Energy Information Administration (EIA) (indexed site)

    Total Inputs of Energy for Heat, Power, and Electricity Generation" " by Enclosed Floorspace, Percent Conditioned Floorspace, and Presence of Computer" " Controls for Building Environment, 1991" " (Estimates in Trillion Btu)" ,,"Presence of Computer Controls" ,," for Buildings Environment",,"RSE" "Enclosed Floorspace and"," ","--------------","--------------","Row" "Percent

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

    Energy Information Administration (EIA) (indexed site)

    Number of Establishments by Total Inputs of Energy for Heat, Power, and Electricity Generation," " by Industry Group, Selected Industries, and" " Presence of Cogeneration Technologies, 1994: Part 2" ,,,"Steam Turbines",,,,"Steam Turbines" ,," ","Supplied by Either","Conventional",,,"Supplied by","One or More",," " " "," ",,"Conventional","Combustion

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

    Energy Information Administration (EIA) (indexed site)

    4. Total Expenditures for Purchased Energy Sources by Census Region," " Industry Group, and Selected Industries, 1991" " (Estimates in Million Dollars)" ,,,,,,,,,,,"RSE" "SIC"," "," "," ","Residual","Distillate ","Natural"," "," ","Coke"," ","Row" "Code(a)","Industry Groupsc and

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

    Energy Information Administration (EIA) (indexed site)

    Quantity of Purchased Energy Sources by Census Region," " Census Division, Industry Group, and Selected Industries, 1994" " (Estimates in Btu or Physical Units)" ,,,,,,"Natural",,,"Coke" " "," ","Total","Electricity","Residual","Distillate","Gas(c)"," ","Coal","and Breeze"," ","RSE" "SIC","

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

    Energy Information Administration (EIA) (indexed site)

    6. Total Expenditures for Purchased Energy Sources by Census Region," " Census Division, Industry Group, and Selected Industries, 1994" " (Estimates in Million Dollars)" ,,,,,,,,,,,"RSE" "SIC"," "," "," ","Residual","Distillate ","Natural"," "," ","Coke"," ","Row" "Code(a)","Industry Group and

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

    Energy Information Administration (EIA) (indexed site)

    7. Total Expenditures for Purchased Energy Sources by Census Region," " Census Division, and Economic Characteristics of the Establishment, 1994" " (Estimates in Million Dollars)" " "," "," "," ",," "," "," "," "," ","RSE" " "," "," ","Residual","Distillate","Natural"," ","

  13. Households to pay more than expected to stay warm this winter

    Energy Information Administration (EIA) (indexed site)

    Households to pay more than expected to stay warm this winter Following a colder-than-expected November, U.S. households are forecast to consume more heating fuels than previously expected....resulting in higher heating bills. Homeowners that rely on natural gas will see their total winter expenses rise nearly 13 percent from last winter....while users of electric heat will see a 2.6 percent increase in costs. That's the latest forecast from the U.S. Energy Information Administration. Propane

  14. Total reaction cross sections in CEM and MCNP6 at intermediate energies

    SciTech Connect

    Kerby, Leslie M.; Mashnik, Stepan G.

    2015-05-14

    Accurate total reaction cross section models are important to achieving reliable predictions from spallation and transport codes. The latest version of the Cascade Exciton Model (CEM) as incorporated in the code CEM03.03, and the Monte Carlo N-Particle transport code (MCNP6), both developed at Los Alamos National Laboratory (LANL), each use such cross sections. Having accurate total reaction cross section models in the intermediate energy region (50 MeV to 5 GeV) is very important for different applications, including analysis of space environments, use in medical physics, and accelerator design, to name just a few. The current inverse cross sections used in the preequilibrium and evaporation stages of CEM are based on the Dostrovsky et al. model, published in 1959. Better cross section models are now available. Implementing better cross section models in CEM and MCNP6 should yield improved predictions for particle spectra and total production cross sections, among other results.

  15. The contribution of low-energy protons to the total on-orbit SEU rate

    DOE PAGES [OSTI]

    Dodds, Nathaniel Anson; Martinez, Marino J.; Dodd, Paul E.; Shaneyfelt, Marty R.; Sexton, Frederick W.; Black, Jeffrey D.; Lee, David S.; Swanson, Scot E.; Bhuva, B. L.; Warren, K. M.; et al

    2015-11-10

    Low- and high-energy proton experimental data and error rate predictions are presented for many bulk Si and SOI circuits from the 20-90 nm technology nodes to quantify how much low-energy protons (LEPs) can contribute to the total on-orbit single-event upset (SEU) rate. Every effort was made to predict LEP error rates that are conservatively high; even secondary protons generated in the spacecraft shielding have been included in the analysis. Across all the environments and circuits investigated, and when operating within 10% of the nominal operating voltage, LEPs were found to increase the total SEU rate to up to 4.3 timesmore » as high as it would have been in the absence of LEPs. Therefore, the best approach to account for LEP effects may be to calculate the total error rate from high-energy protons and heavy ions, and then multiply it by a safety margin of 5. If that error rate can be tolerated then our findings suggest that it is justified to waive LEP tests in certain situations. Trends were observed in the LEP angular responses of the circuits tested. As a result, grazing angles were the worst case for the SOI circuits, whereas the worst-case angle was at or near normal incidence for the bulk circuits.« less

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

    SciTech Connect

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

    2008-01-01

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

  17. Framework for Evaluating the Total Value Proposition of Clean Energy Technologies

    SciTech Connect

    Pater, J. E.

    2006-02-01

    Conventional valuation techniques fail to include many of the financial advantages of clean energy technologies. By omitting benefits associated with risk management, emissions reductions, policy incentives, resource use, corporate social responsibility, and societal economic benefits, investors and firms sacrifice opportunities for new revenue streams and avoided costs. In an effort to identify some of these externalities, this analysis develops a total value proposition for clean energy technologies. It incorporates a series of values under each of the above categories, describing the opportunities for recapturing investments throughout the value chain. The framework may be used to create comparable value propositions for clean energy technologies supporting investment decisions, project siting, and marketing strategies. It can also be useful in policy-making decisions.

  18. Average Neutron Total Cross Sections in the Unresolved Energy Range From ORELA High Resolutio Transmission Measurements

    SciTech Connect

    Derrien, H

    2004-05-27

    Average values of the neutron total cross sections of {sup 233}U, {sup 235}U, {sup 238}U, and {sup 239}Pu have been obtained in the unresolved resonance energy range from high-resolution transmission measurements performed at ORELA in the past two decades. The cross sections were generated by correcting the effective total cross sections for the self-shielding effects due to the resonance structure of the data. The self-shielding factors were found by calculating the effective and true cross sections with the computer code SAMMY for the same Doppler and resolution conditions as for the transmission measurements, using an appropriate set of resonance parameters. Our results are compared to results of previous measurements and to the current ENDF/B-VI data.

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

    Energy Information Administration (EIA) (indexed site)

    4. Total First Use (formerly Primary Consumption) of Energy for All Purposes" " by Value of Shipment Categories, Industry Group, and Selected Industries, 1994" " (Estimates in Trillion Btu)" ,,,," Value of Shipments and Receipts(b)" ,,,," "," (million dollars)" ,,,,,,,,,"RSE" "SIC"," "," "," "," "," "," "," ",500,"Row"," ","

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

    Energy Information Administration (EIA) (indexed site)

    Total Inputs of Energy for Heat, Power, and Electricity Generation" " by Value of Shipment Categories, Industry Group, and Selected Industries, 1994" " (Estimates in Trillion Btu)" ,,,," Value of Shipments and Receipts(b)" ,,,," "," (million dollars)" ,,,,,,,,,"RSE" "SIC"," "," "," "," "," "," "," ",500,"Row" "Code(a)","Industry

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

    Energy Information Administration (EIA) (indexed site)

    0. Total Primary Consumption of Energy for All Purposes by Value of" "Shipment Categories, Industry Group, and Selected Industries, 1991" " (Estimates in Trillion Btu)" ,,,," Value of Shipments and Receipts(b)" ,,,," ","(million dollars)" ,,,"-","-","-","-","-","-","RSE" "SIC"," "," "," "," "," ","

  2. Table A34. Total Inputs of Energy for Heat, Power, and Electricity Generation

    Energy Information Administration (EIA) (indexed site)

    Total Inputs of Energy for Heat, Power, and Electricity Generation" " by Employment Size Categories, Industry Group, and Selected Industries, 1991" " (Continued)" " (Estimates in Trillion Btu)" ,,,,,"Employment Size" ,,,"-","-","-","-","-","-","RSE" "SIC"," "," "," "," "," "," ",,"1,000","Row"

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

    Energy Information Administration (EIA) (indexed site)

    0. Total Inputs of Energy for Heat, Power, and Electricity Generation" " by Fuel Type, Industry Group, Selected Industries, and End Use, 1994:" " Part 2" " (Estimates in Trillion Btu)" ,,,,,"Distillate",,,"Coal" ,,,,,"Fuel Oil",,,"(excluding",,"RSE" "SIC",,,"Net","Residual","and Diesel",,,"Coal Coke",,"Row" "Code(a)","End-Use

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

    Energy Information Administration (EIA) (indexed site)

    Number of Establishments by Total Inputs of Energy for Heat, Power, and Electricity Generation," " by Industry Group, Selected Industries, and" " Presence of General Technologies, 1994: Part 2" ,," "," ",," "," ",," "," "," "," " ,,,,"Computer Control" ,," "," ","of Processes"," "," ",," "," ",," "

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

    Energy Information Administration (EIA) (indexed site)

    Total Delivered Industrial Energy Consumption, Projected vs. Actual" "Projected" " (quadrillion Btu)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013 "AEO 1994",25.43,25.904,26.303,26.659,26.974,27.062,26.755,26.598,26.908,27.228,27.668,28.068,28.348,28.668,29.068,29.398,29.688,30.008 "AEO

  6. Fact #618: April 12, 2010 Vehicles per Household and Other Demographic

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Statistics | Department of Energy 8: April 12, 2010 Vehicles per Household and Other Demographic Statistics Fact #618: April 12, 2010 Vehicles per Household and Other Demographic Statistics Since 1969, the number of vehicles per household has increased by 66% and the number of vehicles per licensed driver has increased by 47%. The number of workers per household has changed the least of the statistics shown here. There has been a decline in the number of persons per household from 1969 to

  7. ac_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    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

  8. Total reaction cross sections in CEM and MCNP6 at intermediate energies

    DOE PAGES [OSTI]

    Kerby, Leslie M.; Mashnik, Stepan G.

    2015-05-14

    Accurate total reaction cross section models are important to achieving reliable predictions from spallation and transport codes. The latest version of the Cascade Exciton Model (CEM) as incorporated in the code CEM03.03, and the Monte Carlo N-Particle transport code (MCNP6), both developed at Los Alamos National Laboratory (LANL), each use such cross sections. Having accurate total reaction cross section models in the intermediate energy region (50 MeV to 5 GeV) is very important for different applications, including analysis of space environments, use in medical physics, and accelerator design, to name just a few. The current inverse cross sections used inmore » the preequilibrium and evaporation stages of CEM are based on the Dostrovsky et al. model, published in 1959. Better cross section models are now available. Implementing better cross section models in CEM and MCNP6 should yield improved predictions for particle spectra and total production cross sections, among other results.« less

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

    Gasoline and Diesel Fuel Update

    U.S. Energy Information Administration (EIA) RECS data show decreased energy consumption per household RECS 2009 - Release date: June 6, 2012 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

  10. Try This: Household Magnets

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Household Magnets Household Magnets Chances are very good that you have experimented with magnets. People have been fascinated with magnetism for thousands of years. As familiar to us as they may be, magnets still have some surprises for us. Here is a small collection of some of our favorite magnet experiments. What happens when we break a magnet in half? Radio Shack sells cheap ceramic magnets in several shapes. Get a ring shaped magnet and break it with pliers or a tap with a hammer. Try to

  11. Development of a Total Energy, Environment and Asset Management (TE2AM tm) Curriculum

    SciTech Connect

    2012-12-31

    The University of Wisconsin Department of Engineering Professional Development (EPD) has completed the sponsored project entitled, Development of a Total Energy, Environment and Asset Management (TE2AM™) Curriculum. The project involved the development of a structured professional development program to improve the knowledge, skills, capabilities, and competencies of engineers and operators of commercial buildings. TE2AM™ advances a radically different approach to commercial building design, operation, maintenance, and end-­‐of-­‐life disposition. By employing asset management principles to the lifecycle of a commercial building, owners and occupants will realize improved building performance, reduced energy consumption and positive environmental impacts. Through our commercialization plan, we intend to offer TE2AM™ courses and certificates to the professional community and continuously improve TE2AM™ course materials. The TE2AM™ project supports the DOE Strategic Theme 1 -­‐ Energy Security; and will further advance the DOE Strategic Goal 1.4 Energy Productivity. Through participation in the TE2AM™ curriculum, engineers and operators of commercial buildings will be eligible for a professional certificate; denoting the completion of a prescribed series of learning activities. The project involved a comprehensive, rigorous approach to curriculum development, and accomplished the following goals: 1. Identify, analyze and prioritize key learning needs of engineers, architects and technical professionals as operators of commercial buildings. 2. Design and develop TE2AM™ curricula and instructional strategies to meet learning needs of the target learning community. 3. Establish partnerships with the sponsor and key stakeholders to enhance the development and delivery of learning programs. 4. Successfully commercialize and sustain the training and certificate programs for a substantial time following the term of the award. The project team was

  12. Household Vehicles Energy Consumption 1991

    Energy Information Administration (EIA) (indexed site)

    a comparison between the 1991 and previous years RTECS designs; (2) the sample design; (3) the data-collection procedures; (4) the Vehicle Identification Number (VIN); (5)...

  13. Household Vehicles Energy Consumption 1994

    Energy Information Administration (EIA) (indexed site)

    DC, October 1995), Table DL-1B. 5. "Chained dollars" is a measure used to express real prices. Real prices are those that have been adjusted to remove the effect of changes...

  14. Household Vehicles Energy Consumption 1991

    Energy Information Administration (EIA) (indexed site)

    production vehicles in order to assess compliance with Corporate Average Fuel Economy (CAFE) standards. The EPA Composite MPG is based on the assumption of a "typical" vehicle-use...

  15. Household Vehicles Energy Consumption 1991

    Energy Information Administration (EIA) (indexed site)

    more fuel-efficient vehicles, and the implementation of Corporate Average Fuel Economy (CAFE) 6 standards. Figure 13. Average Fuel Efficiency of All Vehicles, by Model Year 6...

  16. Household Vehicles Energy Consumption 1991

    Energy Information Administration (EIA) (indexed site)

    Matching: A model-based procedure used to impute for item nonresponse. This method uses logistic models to compute predicted means that are used to statistically match each...

  17. Household Vehicles Energy Consumption 1991

    Energy Information Administration (EIA) (indexed site)

    were imputed as disposed vehicles. To impute vehicle stock changes in the 1991 RTECS, logistic regression equations were used to compute a predicted probability (or propensity)...

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

    Energy Information Administration (EIA) (indexed site)

    Total Delivered Residential Energy Consumption, Projected vs. Actual" "Projected" " (quadrillion Btu)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013 "AEO 1994",10.31,10.36,10.36,10.37,10.38,10.4,10.4,10.41,10.43,10.43,10.44,10.45,10.46,10.49,10.51,10.53,10.56,10.6 "AEO 1995",,10.96,10.8,10.81,10.81,10.79,10.77,10.75,10.73,10.72,10.7,10.7,10.69,10.7,10.72,10.75,10.8,10.85 "AEO

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

    Energy Information Administration (EIA) (indexed site)

    Total Delivered Commercial Energy Consumption, Projected vs. Actual" "Projected" " (quadrillion Btu)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013 "AEO 1994",6.82,6.87,6.94,7,7.06,7.13,7.16,7.22,7.27,7.32,7.36,7.38,7.41,7.45,7.47,7.5,7.51,7.55 "AEO 1995",,6.94,6.9,6.95,6.99,7.02,7.05,7.08,7.09,7.11,7.13,7.15,7.17,7.19,7.22,7.26,7.3,7.34 "AEO

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

    Energy Information Administration (EIA) (indexed site)

    Total Delivered Transportation Energy Consumption, Projected vs. Actual" "Projected" " (quadrillion Btu)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013 "AEO 1994",23.62,24.08,24.45,24.72,25.06,25.38,25.74,26.16,26.49,26.85,27.23,27.55,27.91,28.26,28.61,28.92,29.18,29.5 "AEO 1995",,23.26,24.01,24.18,24.69,25.11,25.5,25.86,26.15,26.5,26.88,27.28,27.66,27.99,28.25,28.51,28.72,28.94 "AEO

  1. appl_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    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

  2. appl_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    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

  3. spaceheat_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

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

  4. spaceheat_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    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

  5. Energy Information Administration - Energy Efficiency, energy...

    Energy Information Administration (EIA) (indexed site)

    Efficiency Energy Efficiency energy consumption savings households, buildings, industry & vehicles The Energy Efficiency Page reflects EIA's information on energy efficiency and...

  6. Total energy cycle assessment of electric and conventional vehicles: an energy and environmental analysis. Volume 1: technical report

    SciTech Connect

    Cuenca, R.; Formento, J.; Gaines, L.; Marr, B.; Santini, D.; Wang, M.; Adelman, S.; Kline, D.; Mark, J.; Ohi, J.; Rau, N.; Freeman, S.; Humphreys, K.; Placet, M.

    1998-01-01

    This report compares the energy use, oil use and emissions of electric vehicles (EVs) with those of conventional, gasoline-powered vehicles (CVs) over the total life cycle of the vehicles. The various stages included in the vehicles` life cycles include vehicle manufacture, fuel production, and vehicle operation. Disposal is not included. An inventory of the air emissions associated with each stage of the life cycle is estimated. Water pollutants and solid wastes are reported for individual processes, but no comprehensive inventory is developed. Volume I contains the major results, a discussion of the conceptual framework of the study, and summaries of the vehicle, utility, fuel production, and manufacturing analyses. It also contains summaries of comments provided by external peer reviewers and brief responses to these comments.

  7. usage_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    Usage Indicators by South Census Region, Million U.S. Households, 2001 5 HC6-12a. Usage Indicators by West Census Region, Million U.S. Households, 2001 5 These data are from the ...

  8. homeoffice_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    Home Office Equipment by South Census Region, Million U.S. Households, 2001 1 HC7-12a. Home Office Equipment by West Census Region, Million U.S. Households, 2001 1 These data are ...

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

    Energy Information Administration (EIA) (indexed site)

    Percent of Households with Vehicles, Selected Survey Years " ,"Survey Years" ,1983,1985,1988,1991,1994,2001 "Total",85.5450237,89.00343643,88.75545852,89.42917548,87.25590956,92.08...

  10. Home Heating Systems | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Heat & Cool » Home Heating Systems Home Heating Systems Household Heating Systems: Although several different types of fuels are available to heat our homes, nearly half of us use natural gas. | Source: Buildings Energy Data Book 2011, 2.1.1 Residential Primary Energy Consumption, by Year and Fuel Type (Quadrillion Btu and Percent of Total). Household Heating Systems: Although several different types of fuels are available to heat our homes, nearly half of us use natural gas. | Source:

  11. ac_household2001.pdf

    Annual Energy Outlook

    ... those households were treated as if the fuel was electricity. 3 The 2001 RECS reported ... Notes: * To obtain the RSE percentage for any table cell, multiply the corresponding ...

  12. "Table B29. Primary Space-Heating Energy Sources, Total Floorspace...

    Energy Information Administration (EIA) (indexed site)

    ... ......",2853,2734,"Q",339,"Q",2165 "Propane ......",7076,6790,1323,1947,930,"Q" "Other ......",1401,1399,"Q",713,"Q","Q" "Energy End Uses ...

  13. Table A13. Total Consumption of Offsite-Produced Energy for...

    Energy Information Administration (EIA) (indexed site)

    ... Statistics Division, Form EIA-846, '1991" "Manufacturing Energy Consumption Survey,' and Bureau of the Census, Industry" "Division, data files for the '1991 Annual Survey of

  14. Table A26. Total Quantity of Purchased Energy Sources by Census...

    Energy Information Administration (EIA) (indexed site)

    ... Division, Form EIA-846, '1991" "Manufacturing Energy Consumption Survey,' and Bureau of the Census, Industry" "Division, data files for the '1991 Annual Survey of Manufactures.'

  15. Property:Building/SPPurchasedEngyNrmlYrMwhYrTotal | Open Energy...

    OpenEI (Open Energy Information) [EERE & EIA]

    dEngyNrmlYrMwhYrTotal" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 4355.0 + Sweden Building 05K0002 + 1530.1 + Sweden Building 05K0003...

  16. Property:Building/SPPurchasedEngyPerAreaKwhM2Total | Open Energy...

    OpenEI (Open Energy Information) [EERE & EIA]

    EngyPerAreaKwhM2Total" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 221.549575215 + Sweden Building 05K0002 + 213.701117318 + Sweden...

  17. Property:Building/SPPurchasedEngyForPeriodMwhYrTotal | Open Energy...

    OpenEI (Open Energy Information) [EERE & EIA]

    gyForPeriodMwhYrTotal" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 4228.0 + Sweden Building 05K0002 + 1501.1 + Sweden Building 05K0003...

  18. Buildings Energy Data Book: 2.3 Residential Sector Expenditures

    Buildings Energy Data Book

    2 2005 Household Energy Expenditures, by Vintage ($2010) | Year | Prior to 1950 887 | 22% 1950 to 1969 771 | 22% 1970 to 1979 736 | 16% 1980 to 1989 741 | 16% 1990 to 1999 752 | 16% 2000 to 2005 777 | 9% | Average 780 | Total 100% Note(s): Source(s): 1.24 2,003 1) Energy expenditures per square foot were calculated using estimates of average heated floor space per household. According to the 2005 Residential Energy Consumption Survey (RECS), the average heated floor space per household in the

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

    Reports and Publications

    2004-01-01

    Entails how people live, the factors that cause the most differences in home lifestyle, including energy use in geographic location, socioeconomics and household income.

  20. Buildings Energy Data Book: 2.3 Residential Sector Expenditures

    Buildings Energy Data Book

    5 2005 Households and Energy Expenditures, by Income Level ($2010) Energy Expenditures by Household Income Households (millions) Household Less than $10,000 9.9 9% $10,000 to $14,999 8.5 8% $15,000 to $19,999 8.4 8% $20,000 to $29,999 15.1 14% $30,000 to $39,999 13.6 12% $40,000 to $49,999 11.0 10% $50,000 to $74,999 19.8 18% $75,000 to $99,999 10.6 10% $100,000 or more 14.2 13% Total 111.1 100% Note(s): Source(s): 7% 1) See Table 2.3.15 for more on energy burdens. 2) A household is defined as a

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

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Transportation, 1984-2010 | Department of Energy 8: October 8, 2012 Components of Household Expenditures on Transportation, 1984-2010 Fact #748: October 8, 2012 Components of Household Expenditures on Transportation, 1984-2010 The overall share of annual household expenditures for transportation was lower in 2010 than it was in 1984, reaching its lowest point in 2009 at 15.5%. In the early to mid-1980s when oil prices were high, gasoline and motor oil made up a larger share of transportation

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

    Energy Information Administration (EIA) (indexed site)

    2" " (Estimates in Trillion Btu)" ,,,,,,,"Coal" ,,,,"Distillate",,,"(excluding" ,,,,"Fuel Oil",,,"Coal Coke",,"RSE" ,,"Net","Residual","and Diesel",,,"and",,"Row" "End-Use Categories","Total","Electricity(a)","Fuel Oil","Fuel(b)","Natural

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

    Energy Information Administration (EIA) (indexed site)

    2" " (Estimates in Trillion Btu)" ,,,,,,,"Coal" ,,,,"Distillate",,,"(excluding" ,,,,"Fuel Oil",,,"Coal Coke",,"RSE" ,,"Net","Residual","and Diesel",,,"and",,"Row" "End-Use Categories","Total","Electricity(a)","Fuel Oil","Fuel(b)","Natural

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

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Department of Energy 9: May 28, 2012 Secondary Household Vehicles Travel Fewer Miles Fact #729: May 28, 2012 Secondary Household Vehicles Travel Fewer Miles 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 that the primary vehicle travels in a day. In a six-vehicle household, the sixth vehicle travels fewer than five miles a day. Daily Vehicle

  5. FAST NEUTRON SPECTROMETER USING SPACED SEMICONDUCTORS FOR MEASURING TOTAL ENERGY OF NEUTRONS CAPTURED

    DOEpatents

    Love, T.A.; Murray, R.B.

    1964-04-14

    A fast neutron spectrometer was designed, which utilizes a pair of opposed detectors having a layer of /sup 6/LiF between to produce alpha and T pair for each neutron captured to provide signals, which, when combined, constitute a measure of neutron energy. (AEC)

  6. Buildings Energy Data Book: 2.9 Low-Income Housing

    Buildings Energy Data Book

    0 2005 Average Energy Expenditures per Household Member and per Square Foot, by Weatherization Eligibility ($2010) Members/ Hhold Hhold Total U.S. Households 780 2.6 0.86 Federally Eligible 617 2.7 1.10 Federally Ineligible 844 2.5 0.82 Below 100% Poverty Line 603 2.7 1.14 Source(s): 1,442 EIA, 2005 Residential Energy Consumption Survey: Household Energy Consumption and Expenditures Tables, Oct. 2008, Table US1 part2; EIA, Annual Energy Review 2010, Oct. 2011, Appendix D, p. 353 for price

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

    Energy Information Administration (EIA) (indexed site)

    1" " (Estimates in Btu or Physical Units)" ,,,,,"Distillate",,,"Coal" ,,,,,"Fuel Oil",,,"(excluding" ,,,"Net","Residual","and Diesel",,,"Coal Coke",,"RSE" "SIC",,"Total","Electricity(b)","Fuel Oil","Fuel(c)","Natural Gas(d)","LPG","and Breeze)","Other(e)","Row" "Code(a)","End-Use

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

    Energy Information Administration (EIA) (indexed site)

    1" " (Estimates in Btu or Physical Units)" ,,,,"Distillate",,,"Coal" ,,,,"Fuel Oil",,,"(excluding" ,,"Net","Residual","and Diesel",,,"Coal Coke",,"RSE" ,"Total","Electricity(a)","Fuel Oil","Fuel(b)","Natural Gas(c)","LPG","and Breeze)","Other(d)","Row" "End-Use Categories","(trillion

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

    Energy Information Administration (EIA) (indexed site)

    ,,,,,,,,"Coal" " Part 1",,,,,,,,"(excluding" " (Estimates in Btu or Physical Units)",,,,,"Distillate",,,"Coal Coke" ,,,,,"Fuel Oil",,,"and" ,,,"Net","Residual","and Diesel","Natural Gas",,"Breeze)",,"RSE" "SIC",,"Total","Electricity(b)","Fuel Oil","Fuel","(billion","LPG","(1000

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

    Energy Information Administration (EIA) (indexed site)

    " Part 2" " (Estimates in Trillion Btu)",,,,,,,,"Coal" ,,,,,"Distillate",,,"(excluding" ,,,,,"Fuel Oil",,,"Coal Coke",,"RSE" "SIC",,,"Net","Residual","and Diesel",,,"and",,"Row" "Code(a)","End-Use Categories","Total","Electricity(b)","Fuel Oil","Fuel(c)","Natural

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

    Energy Information Administration (EIA) (indexed site)

    1",,,,,,,"Coal" " (Estimates in Btu or Physical Units)",,,,,,,"(excluding" ,,,,"Distillate",,,"Coal Coke" ,,"Net",,"Fuel Oil",,,"and" ,,"Electricity(a)","Residual","and Diesel","Natural Gas",,"Breeze)",,"RSE" ,"Total","(million","Fuel Oil","Fuel","(billion","LPG","(1000

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

    SciTech Connect

    Rubio-Ponce, A.; Olgun, D.

    2014-05-15

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

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

    Energy Information Administration (EIA) (indexed site)

    Consumption of Offsite-Produced Energy for Heat, Power, and" " Electricity Generation by Value of Shipment Categories, Industry Group, and" " Selected Industries, 1991" " (Estimates in Trillion Btu)" ,,,,"Value of Shipments and Receipts(b)" ,,,," (million dollars)" ,," ","-","-","-","-","-","-","RSE" ," "," ","

  14. Shared Solar Projects Powering Households Throughout America...

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Shared Solar Projects Powering Households Throughout America Shared Solar Projects Powering Households Throughout America January 31, 2014 - 2:30pm Addthis Shared solar projects ...

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

    Energy Information Administration (EIA) (indexed site)

    Quantity of Purchased Energy Sources by Census Region, Census Division," " and Economic Characteristics of the Establishment, 1994" " (Estimates in Btu or Physical Units)" ,,,,,"Natural",,,"Coke" " ","Total","Electricity","Residual","Distillate","Gas(c)"," ","Coal","and Breeze","Other(d)","RSE" "

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

    Energy Information Administration (EIA) (indexed site)

    Primary Consumption of Energy for All Purposes by Employment" " Size Categories, Industry Group, and Selected Industries, 1991 (Continued)" " (Estimates in Trillion Btu)" ,,,,,"Employment Size" ,,,"-","-","-","-","-","-","RSE" "SIC"," "," "," "," "," "," ",,500,"Row" "Code(a)","Industry Groups and

  17. Pennsylvania Total Electric Power Industry Net Summer Capacity, by Energy Source

    Energy Information Administration (EIA) (indexed site)

    Pennsylvania" "Energy Source",2006,2007,2008,2009,2010 "Fossil",32893,32751,32654,32663,32530 " Coal",18771,18581,18513,18539,18481 " Petroleum",4664,4660,4540,4533,4534 " Natural Gas",9349,9410,9507,9491,9415 " Other Gases",110,100,94,101,100 "Nuclear",9234,9305,9337,9455,9540 "Renewables",1365,1529,1619,1971,1984 "Pumped Storage",1513,1521,1521,1521,1521

  18. Minnesota Total Electric Power Industry Net Summer Capacity, by Energy Source

    Energy Information Administration (EIA) (indexed site)

    Minnesota" "Energy Source",2006,2007,2008,2009,2010 "Fossil",9714,9550,10548,10752,10519 " Coal",5444,5207,5235,4826,4789 " Petroleum",746,764,782,801,795 " Natural Gas",3524,3579,4531,5126,4936 " Other Gases","-","-","-","-","-" "Nuclear",1668,1668,1668,1668,1594 "Renewables",1259,1658,2008,2192,2588 "Pumped

  19. Alabama Total Electric Power Industry Net Summer Capacity, by Energy Source

    Energy Information Administration (EIA) (indexed site)

    Alabama" "Energy Source",2006,2007,2008,2009,2010 "Fossil",21804,21784,22372,22540,23519 " Coal",11557,11544,11506,11486,11441 " Petroleum",43,43,43,43,43 " Natural Gas",10104,10098,10724,10912,11936 " Other Gases",100,100,100,100,100 "Nuclear",5008,4985,4985,4985,5043 "Renewables",3852,3846,3865,3863,3855 "Pumped Storage","-","-","-","-","-"

  20. Alaska Total Electric Power Industry Net Summer Capacity, by Energy Source

    Energy Information Administration (EIA) (indexed site)

    Alaska" "Energy Source",2006,2007,2008,2009,2010 "Fossil",1485,1561,1593,1591,1618 " Coal",105,105,112,111,111 " Petroleum",575,622,643,644,663 " Natural Gas",805,834,838,836,845 " Other Gases","-","-","-","-","-" "Nuclear","-","-","-","-","-" "Renewables",400,400,403,422,422 "Pumped

  1. Arizona Total Electric Power Industry Net Summer Capacity, by Energy Source

    Energy Information Administration (EIA) (indexed site)

    Arizona" "Energy Source",2006,2007,2008,2009,2010 "Fossil",18784,18756,18942,19351,19338 " Coal",5830,5818,5818,6227,6233 " Petroleum",90,93,93,93,93 " Natural Gas",12864,12845,13031,13031,13012 " Other Gases","-","-","-","-","-" "Nuclear",3872,3872,3942,3942,3937 "Renewables",2736,2736,2762,2826,2901 "Pumped Storage",216,216,216,216,216

  2. Arkansas Total Electric Power Industry Net Summer Capacity, by Energy Source

    Energy Information Administration (EIA) (indexed site)

    Arkansas" "Energy Source",2006,2007,2008,2009,2010 "Fossil",10965,11807,11756,11753,12451 " Coal",3846,3846,3861,3864,4535 " Petroleum",23,22,22,22,22 " Natural Gas",7096,7939,7873,7867,7894 " Other Gases","-","-","-","-","-" "Nuclear",1824,1838,1839,1835,1835 "Renewables",1691,1623,1643,1659,1667 "Pumped Storage",28,28,28,28,28

  3. California Total Electric Power Industry Net Summer Capacity, by Energy Source

    Energy Information Administration (EIA) (indexed site)

    California" "Energy Source",2006,2007,2008,2009,2010 "Fossil",39351,39961,39950,41443,42654 " Coal",389,389,367,367,374 " Petroleum",789,754,752,734,701 " Natural Gas",38001,38556,38635,40146,41370 " Other Gases",171,262,197,197,209 "Nuclear",4390,4390,4390,4390,4390 "Renewables",15776,15774,15945,16295,16460 "Pumped Storage",3688,3688,3813,3813,3813 "Other",8,"-",7,7,11

  4. An estimation of the total atmospheric pollution in the city of Thessaloniki using solar energy data

    SciTech Connect

    Sahsamanoglou, H.S.; Makrogiannis, T.I.; Meletis, H. )

    1991-01-01

    The atmospheric mass over the city of Thessaloniki is characterized by a generally increased pollution due to solid particles in the lower atmosphere. This conclusion has been reached after a comparison between values of total solar radiation, taken in the city center during clear sky days, and values predicted by the model of D.F. Heermann et al. for corresponding days. Pollution varies between a minimum value which is constant over the year and independent of weather situations (pollution background), and a maximum value. The minimum pollution causes an attenuation of solar radiation about 15%, compared to the values given by the above model. The atmospheric pollution in the city, during a usual day with clear sky, causes an attenuation varying between 10% in the summer and 20% in the winter, when compared to the constant background of the pollution. During the most unfavorable days with clear sky, the percentages are 30% in the summer and 40% in the winter.

  5. Buildings Energy Data Book: 5.4 Water Heaters

    Buildings Energy Data Book

    1 Water Heater Stock for Residential Buildings, By Fuel Type Electric Natural Gas Fuel Oil Propane/LPG Other 0.2 0.2% Total (1) Note(s): Souce(s): According to RECS, 1.1 million households did not use hot water.The total only includes those households that used hot water. EIA, Residential Energy Consumption Survey 2005, Table HC 2.8, June 2008. 4.0 3.6% 4.0 3.6% 110.0 100.0% Households in 2005 (millions) Percent 43.1 39.2% 58.7 53.4%

  6. Issues in International Energy Consumption Analysis: Canadian Energy Demand

    Reports and Publications

    2015-01-01

    The residential sector is one of the main end-use sectors in Canada accounting for 16.7% of total end-use site energy consumption in 2009 (computed from NRCan 2012. pp, 4-5). In this year, the residential sector accounted for 54.5% of buildings total site energy consumption. Between 1990 and 2009, Canadian household energy consumption grew by less than 11%. Nonetheless, households contributed to 14.6% of total energy-related greenhouse gas emissions in Canada in 2009 (computed from NRCan 2012). This is the U.S. Energy Information Administrations second study to help provide a better understanding of the factors impacting residential energy consumption and intensity in North America (mainly the United States and Canada) by using similar methodology for analyses in both countries.

  7. A Glance at China’s Household Consumption

    SciTech Connect

    Shui, Bin

    2009-10-01

    Known for its scale, China is the most populous country with the world’s third largest economy. In the context of rising living standards, a relatively lower share of household consumption in its GDP, a strong domestic market and globalization, China is witnessing an unavoidable increase in household consumption, related energy consumption and carbon emissions. Chinese policy decision makers and researchers are well aware of these challenges and keen to promote green lifestyles. China has developed a series of energy policies and programs, and launched a wide-range social marketing activities to promote energy conservation.

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

    SciTech Connect

    Fazel Sarjui, F.

    1983-01-01

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

  9. ,"Total Natural Gas Consumption

    Energy Information Administration (EIA) (indexed site)

    Gas Consumption (billion cubic feet)",,,,,"Natural Gas Energy Intensity (cubic feetsquare foot)" ,"Total ","Space Heating","Water Heating","Cook- ing","Other","Total ","Space...

  10. Residential Network Members Impact More Than 42,000 Households | Department

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    of Energy Impact More Than 42,000 Households Residential Network Members Impact More Than 42,000 Households Photo of a row of townhomes. Eligible Better Buildings Residential Network members reported completing 27,563 home energy upgrades during 2013 as part of the Residential Network's first reporting cycle. In addition, 13 Better Buildings Neighborhood Program partners completed 12,166 home energy upgrades, and six Home Performance with ENERGY STAR® Sponsors completed 2,540 home energy

  11. ,"Total Fuel Oil Consumption

    Energy Information Administration (EIA) (indexed site)

    0. Fuel Oil Consumption (gallons) and Energy Intensities by End Use for Non-Mall Buildings, 2003" ,"Total Fuel Oil Consumption (million gallons)",,,,,"Fuel Oil Energy Intensity...

  12. Total Space Heat-

    Gasoline and Diesel Fuel Update

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

  13. ,"Total Fuel Oil Consumption

    Energy Information Administration (EIA) (indexed site)

    A. Fuel Oil Consumption (gallons) and Energy Intensities by End Use for All Buildings, 2003" ,"Total Fuel Oil Consumption (million gallons)",,,,,"Fuel Oil Energy Intensity...

  14. Ventilation Behavior and Household Characteristics in NewCalifornia Houses

    SciTech Connect

    Price, Phillip N.; Sherman, Max H.

    2006-02-01

    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.

  15. Colossal Magnetoresistive Manganite Based Fast Bolometric X-ray Sensors for Total Energy Measurements of Free Electron Lasers

    SciTech Connect

    Yong, G J; Kolagani, R M; Adhikari, S; Mundle, R M; Cox, D W; Davidson III, A L; Liang, Y; Drury, O B; Hau-Riege, S P; Gardner, C; Ables, E; Bionta, R M; Friedrich, S

    2008-12-17

    Bolometric detectors based on epitaxial thin films of rare earth perovskite manganites have been proposed as total energy monitors for X-ray pulses at the Linac Coherent Light Source free electron laser. We demonstrate such a detector scheme based on epitaxial thin films of the perovskite manganese oxide material Nd{sub 0.67}Sr{sub x0.33}MnO{sub 3}, grown by pulsed laser deposition on buffered silicon substrates. The substrate and sensor materials are chosen to meet the conflicting requirements of radiation hardness, sensitivity, speed and linearity over a dynamic range of three orders of magnitude. The key challenge in the material development is the integration of the sensor material with Si. Si is required to withstand the free electron laser pulse impact and to achieve a readout speed three orders of magnitude faster than conventional cryoradiometers for compatibility with the Linac Coherent Light Source pulse rate. We discuss sensor material development and the photoresponse of prototype devices. This Linac Coherent Light Source total energy monitor represents the first practical application of manganite materials as bolometric sensors.

  16. Buildings and Energy in the 1980s

    Energy Information Administration (EIA) (indexed site)

    No. PB83-199554, 220. Residential Energy Consumption Survey: Household Transportation Panel Monthly Gas Purchases and Vehicle and Household Characteristics, 679-981; Order...

  17. Buildings and Energy in the 1980s

    Energy Information Administration (EIA) (indexed site)

    conducted in two stages: (1) A Household (RECS)Building (CBECS) Survey and an Energy Suppliers Survey. The HouseholdBuilding Characteristics Survey consists of personal...

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

    SciTech Connect

    Brian C. O'Neill

    2006-08-09

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

  19. Fission Fragment Mass Distributions and Total Kinetic Energy Release of 235-Uranium and 238-Uranium in Neutron-Induced Fission at Intermediate and Fast Neutron Energies

    SciTech Connect

    Duke, Dana Lynn

    2015-11-12

    This Ph.D. dissertation describes a measurement of the change in mass distributions and average total kinetic energy (TKE) release with increasing incident neutron energy for fission of 235U and 238U. Although fission was discovered over seventy-five years ago, open questions remain about the physics of the fission process. The energy of the incident neutron, En, changes the division of energy release in the resulting fission fragments, however, the details of energy partitioning remain ambiguous because the nucleus is a many-body quantum system. Creating a full theoretical model is difficult and experimental data to validate existing models are lacking. Additional fission measurements will lead to higher-quality models of the fission process, therefore improving applications such as the development of next-generation nuclear reactors and defense. This work also paves the way for precision experiments such as the Time Projection Chamber (TPC) for fission cross section measurements and the Spectrometer for Ion Determination in Fission (SPIDER) for precision mass yields.

  20. Fact #614: March 15, 2010 Average Age of Household Vehicles | Department of

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Energy 4: March 15, 2010 Average Age of Household Vehicles Fact #614: March 15, 2010 Average Age of Household Vehicles 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 reported in the 1995 survey, have the youngest average age. Average Vehicle Age by Vehicle Type Graph showing the average vehicle age by type (car, van, pickup, SUV, all household

  1. ac_household2001.pdf

    Annual Energy Outlook

    RSE Row Factors New York California Texas Florida 0.4 1.1 1.7 1.2 1.2 Households With ... RSE Row Factors New York California Texas Florida 0.4 1.1 1.7 1.2 1.2 Pays for Electricity ...

  2. Short-Term Energy Outlook

    Annual Energy Outlook

    Thank

    Overview U.S. Territories: American Samoa | Guam | Northern Mariana Islands | Puerto Rico | U.S. Virgin Islands More State Data & Analysis by Source Petroleum Natural Gas Electricity Coal Renewable & Alternative Fuels Nuclear Environment Total Energy Summary Reports Household Energy Use State Electricity Summaries State Renewable Electricity Statistics Natural Gas Summary Statistics Today In Energy In 2015, U.S. coal production, consumption, and employment fell by more than 10%

  3. Environmental assessment of air quality, noise and cooling tower drift from the Jersey City Total Energy Demonstration

    SciTech Connect

    Davis, W.T.; Kolb, J.O.

    1980-06-01

    This assessment covers three specific effects from the operation of the Total Energy (TE) demonstration: (1) air quality from combustion emissions of 600 kW diesel engines and auxiliary boilers fueled with No. 2 distillate oil, (2) noise levels from TE equipment operation, (3) cooling tower drift from two, 2220 gpm, forced-draft cooling towers. For the air quality study, measurements were performed to determine both the combustion emission rates and ground-level air quality at the Demonstration site. Stack analysis of NO/sub x/, SO/sub 2/, CO, particulates, and total hydrocarbons characterized emission rates over a range of operating conditions. Ground-level air quality was monitored during two six-week periods during the summer and winter of 1977. The noise study was performed by measuring sound levels in db(A) in the area within approximately 60 m of the CEB. The noise survey investigated the effects on noise distribution of different wind conditions, time of day or night, and condition of doors - open or closed - near the diesel engines in the CEB. In the cooling tower study, drift emission characteristics were measured to quantify the drift emission before and after cleaning of the tower internals to reduce fallout of large drift droplets in the vicinity of the CEB.

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

    SciTech Connect

    1998-01-01

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

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

    SciTech Connect

    1998-01-01

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

  6. Saving Water Saves Energy

    SciTech Connect

    McMahon, James E.; Whitehead, Camilla Dunham; Biermayer, Peter

    2006-06-15

    Hot water use in households, for showers and baths as wellas for washing clothes and dishes, is a major driver of household energyconsumption. Other household uses of water (such as irrigatinglandscaping) require additional energy in other sectors to transport andtreat the water before use, and to treat wastewater. In California, 19percent of total electricity for all sectors combined and 32 percent ofnatural gas consumption is related to water. There is a criticalinterdependence between energy and water systems: thermal power plantsrequire cooling water, and water pumping and treatment require energy.Energy efficiency can be increased by a number of means, includingmore-efficient appliances (e.g., clothes washers or dishwashers that useless total water and less heated water), water-conserving plumbingfixtures and fittings (e.g., showerheads, faucets, toilets) and changesin consumer behavior (e.g., lower temperature set points for storagewater heaters, shorter showers). Water- and energy-conserving activitiescan help offset the stress imposed on limited water (and energy) suppliesfrom increasing population in some areas, particularly in drought years,or increased consumption (e.g., some new shower systems) as a result ofincreased wealth. This paper explores the connections between householdwater use and energy, and suggests options for increased efficiencies inboth individual technologies and systems. Studies indicate that urbanwater use can be reduced cost-effectively by up to 30 percent withcommercially available products. The energy savings associated with watersavings may represent a large additional and largely untappedcost-effective opportunity.

  7. Household heating bills expected to be lower this winter

    Energy Information Administration (EIA) (indexed site)

    Household heating bills expected to be lower this winter U.S. consumers are expected to pay less this winter on their home heating bills because of lower oil and natural gas prices and projected milder temperatures than last winter. In its new forecast, the U.S. Energy Information Administration said households that rely on heating oil which are mainly located in the Northeast will pay the lowest heating expenditures in 9 years down 25% from last winter as consumers are expected to save about

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

    Energy Information Administration (EIA) (indexed site)

    3a. Housing Unit Characteristics by Household Income, Million U.S. Households, 2001 Housing Unit Characteristics RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral Assist- ance 1 RSE Row Factors Less than $14,999 $15,000 to $29,999 $30,000 to $49,999 $50,000 or More 0.6 1.3 1.1 1.0 0.9 1.4 1.0 Total ............................................... 107.0 18.7 22.9 27.1 38.3 15.0 33.8 3.3 Census Region and Division Northeast

  9. Appliance Commitment for Household Load Scheduling

    SciTech Connect

    Du, Pengwei; Lu, Ning

    2011-06-30

    This paper presents a novel appliance commitment algorithm that schedules thermostatically-controlled household loads based on price and consumption forecasts considering users comfort settings to meet an optimization objective such as minimum payment or maximum comfort. The formulation of an appliance commitment problem was described in the paper using an electrical water heater load as an example. The thermal dynamics of heating and coasting of the water heater load was modeled by physical models; random hot water consumption was modeled with statistical methods. The models were used to predict the appliance operation over the scheduling time horizon. User comfort was transformed to a set of linear constraints. Then, a novel linear, sequential, optimization process was used to solve the appliance commitment problem. The simulation results demonstrate that the algorithm is fast, robust, and flexible. The algorithm can be used in home/building energy-management systems to help household owners or building managers to automatically create optimal load operation schedules based on different cost and comfort settings and compare cost/benefits among schedules.

  10. New York Household Travel Patterns: A Comparison Analysis

    SciTech Connect

    Hu, Patricia S; Reuscher, Tim

    2007-05-01

    In 1969, the U. S. Department of Transportation began collecting detailed data on personal travel to address various transportation planning issues. These issues range from assessing transportation investment programs to developing new technologies to alleviate congestion. This 1969 survey was the birth of the Nationwide Personal Transportation Survey (NPTS). The survey was conducted again in 1977, 1983, 1990 and 1995. Longer-distance travel was collected in 1977 and 1995. In 2001, the survey was renamed to the National Household Travel Survey (NHTS) and collected both daily and longer-distance trips in one survey. In addition to the number of sample households that the national NPTS/NHTS survey allotted to New York State (NYS), the state procured an additional sample of households in both the 1995 and 2001 surveys. In the 1995 survey, NYS procured an addition sample of more than 9,000 households, increasing the final NY NPTS sample size to a total of 11,004 households. Again in 2001, NYS procured 12,000 additional sample households, increasing the final New York NHTS sample size to a total of 13,423 households with usable data. These additional sample households allowed NYS to address transportation planning issues pertinent to geographic areas significantly smaller than for what the national NPTS and NHTS data are intended. Specifically, these larger sample sizes enable detailed analysis of twelve individual Metropolitan Planning Organizations (MPOs). Furthermore, they allowed NYS to address trends in travel behavior over time. In this report, travel data for the entire NYS were compared to those of the rest of the country with respect to personal travel behavior and key travel determinants. The influence of New York City (NYC) data on the comparisons of the state of New York to the rest of the country was also examined. Moreover, the analysis examined the relationship between population density and travel patterns, and the similarities and differences among New

  11. Junior Energy | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    York Zip: 10003 Product: New York-based organization working with schools to teach children about practical ways to save energy in their own households and neighborhoods....

  12. Energy Saver Blog | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Home cooling accounts for 6 percent of the average household's energy use. To help you save money by saving energy, our experts are answering your home cooling questions. |...

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

    SciTech Connect

    Dong, Xue; Niu, Tianye; Zhu, Lei

    2014-05-15

    Purpose: Dual-energy CT (DECT) is being increasingly used for its capability of material decomposition and energy-selective imaging. A generic problem of DECT, however, is that the decomposition process is unstable in the sense that the relative magnitude of decomposed signals is reduced due to signal cancellation while the image noise is accumulating from the two CT images of independent scans. Direct image decomposition, therefore, leads to severe degradation of signal-to-noise ratio on the resultant images. Existing noise suppression techniques are typically implemented in DECT with the procedures of reconstruction and decomposition performed independently, which do not explore the statistical properties of decomposed images during the reconstruction for noise reduction. In this work, the authors propose an iterative approach that combines the reconstruction and the signal decomposition procedures to minimize the DECT image noise without noticeable loss of resolution. Methods: The proposed algorithm is formulated as an optimization problem, which balances the data fidelity and total variation of decomposed images in one framework, and the decomposition step is carried out iteratively together with reconstruction. The noise in the CT images from the proposed algorithm becomes well correlated even though the noise of the raw projections is independent on the two CT scans. Due to this feature, the proposed algorithm avoids noise accumulation during the decomposition process. The authors evaluate the method performance on noise suppression and spatial resolution using phantom studies and compare the algorithm with conventional denoising approaches as well as combined iterative reconstruction methods with different forms of regularization. Results: On the Catphan600 phantom, the proposed method outperforms the existing denoising methods on preserving spatial resolution at the same level of noise suppression, i.e., a reduction of noise standard deviation by one order

  14. Household Vehicles Energy Use: Latest Data & Trends

    Energy Information Administration (EIA) (indexed site)

    Laboratory (ORNL), Engineering Science Technology Division, Center for Transportation Analysis. For 1,262 vehicles, the work conducted by ORNL did not result in a viable annual VMT...

  15. Household Vehicles Energy Use: Latest Data & Trends

    Energy Information Administration (EIA) (indexed site)

    fuel, diesel motor fuel, electric, and natural gas, excluding propane because NHTSA's CAFE program does not track these vehicles. See Gasoline, Gasohol, Unleaded Gasoline, Leaded...

  16. Household Vehicles Energy Use: Latest Data & Trends

    Energy Information Administration (EIA) (indexed site)

    vehicle type, and vehicle model year. "600" - represents a "match" based on EIA expert analysis using subject matter experience, in conjunction with past RTECS. Additionally,...

  17. Household Vehicles Energy Use: Latest Data & Trends

    Energy Information Administration (EIA) (indexed site)

    C : Q U A L I T Y O F T H E D ATA APPENDIX C A P P E N D I X C QUALITY OF THE DATA INTRODUCTION This section discusses several issues relating to the quality of the National...

  18. DOE/EIA-032171(84) Energy Information Administration Residential...

    Gasoline and Diesel Fuel Update

    it was used to screen households for participation in the Household Transportation Panel. 190 1984 RECS: Consumption and Expenditures, National Data Energy Information...

  19. DOE/EIA-0516(85) Energy Information Administration Manufacturing...

    Energy Information Administration (EIA) (indexed site)

    Order No. PB83- 199554HAA Residential Energy Consumption Survey: HouseholdTransportation Panel Monthly Gas Purchases and Vehicle and Household Characteristics, 6179-9181 * Order...

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

    SciTech Connect

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

    2005-05-31

    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.

  1. Buildings Energy Data Book: 2.1 Residential Sector Energy Consumption

    Buildings Energy Data Book

    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

  2. Search results | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    with household appliances, transportation, and their own bodies. However, the nature of energy, energy transformations, and energy conservation are poorly understood, even...

  3. Total Imports

    Energy Information Administration (EIA) (indexed site)

    Data Series: Imports - Total Imports - Crude Oil Imports - Crude Oil, Commercial Imports - by SPR Imports - into SPR by Others Imports - Total Products Imports - Total Motor Gasoline Imports - Finished Motor Gasoline Imports - Reformulated Gasoline Imports - Reformulated Gasoline Blended w/ Fuel Ethanol Imports - Other Reformulated Gasoline Imports - Conventional Gasoline Imports - Conv. Gasoline Blended w/ Fuel Ethanol Imports - Conv. Gasoline Blended w/ Fuel Ethanol, Ed55 & < Imports -

  4. Household heating bills expected to be higher than last winter, mainly driven by colder weather

    Energy Information Administration (EIA) (indexed site)

    Household heating bills expected to be higher than last winter, mainly driven by colder weather U.S. households are expected to pay higher heating bills this winter compared to last winter mainly because the weather is forecast to be colder than the relatively mild weather seen last winter and fuel prices are forecast to be higher. In its new forecast, the U.S. Energy Information Administration said households using heating oil will see a 38% jump in their heating fuel expenditures while propane

  5. Fact #616: March 29, 2010 Household Vehicle-Miles of Travel by Trip Purpose

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    | Department of Energy 6: March 29, 2010 Household Vehicle-Miles of Travel by Trip Purpose Fact #616: March 29, 2010 Household Vehicle-Miles of Travel by Trip Purpose In 2009, getting to and from work accounted for about 27% of household vehicle-miles of travel (VMT). Work-related business was 8.4% of VMT in 2001, but declined to 6.7% in 2009, possibly due to advancements in computing technology making it possible for more business to be handled electronically. VMT for shopping was almost

  6. homeoffice_household2001.pdf

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    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 ......

  7. Loan Programs for Low- and Moderate-Income Households | Department...

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Programs for Low- and Moderate-Income Households Loan Programs for Low- and Moderate-Income Households Better Buildings Residential Network Multifamily and Low-Income Housing Peer ...

  8. Kingston Creek Hydro Project Powers 100 Households | Department...

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Kingston Creek Hydro Project Powers 100 Households Kingston Creek Hydro Project Powers 100 Households August 21, 2013 - 12:00am Addthis Nevada-based contracting firm Nevada ...

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

    OpenEI (Open Energy Information) [EERE & EIA]

    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...

  10. Total Space Heat-

    Gasoline and Diesel Fuel Update

    Survey: Energy End-Use Consumption Tables Total Space Heat- ing Cool- ing Venti- lation Water Heat- ing Light- ing Cook- ing Refrig- eration Office Equip- ment Com- puters Other...

  11. Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total"

    Energy Information Administration (EIA) (indexed site)

    West Virginia" ,"Full service providers",,,,,"Other providers",, "Item","Investor Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total" "Number of entities",5,2,"NA",2,"NA","NA","NA"," " "Number of retail

  12. Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total"

    Energy Information Administration (EIA) (indexed site)

    Alaska" ,"Full service providers",,,,,"Other providers",, "Item","Investor Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total" "Number of entities",17,34,"NA",19,"NA","NA","NA"," " "Number of retail

  13. Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total"

    Energy Information Administration (EIA) (indexed site)

    District of Columbia" ,"Full service providers",,,,,"Other providers",, "Item","Investor Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total" "Number of entities",3,"NA","NA","NA","NA",26,1," " "Number of retail

  14. Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total"

    Energy Information Administration (EIA) (indexed site)

    Hawaii" ,"Full service providers",,,,,"Other providers",, "Item","Investor Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total" "Number of entities",14,"NA","NA",1,2,"NA","NA"," " "Number of retail

  15. Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total"

    Energy Information Administration (EIA) (indexed site)

    Indiana" ,"Full service providers",,,,,"Other providers",, "Item","Investor Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total" "Number of entities",7,72,"NA",39,"NA","NA","NA"," " "Number of retail

  16. Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total"

    Energy Information Administration (EIA) (indexed site)

    Iowa" ,"Full service providers",,,,,"Other providers",, "Item","Investor Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total" "Number of entities",3,137,"NA",42,"NA","NA","NA"," " "Number of retail

  17. Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total"

    Energy Information Administration (EIA) (indexed site)

    Louisiana" ,"Full service providers",,,,,"Other providers",, "Item","Investor Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total" "Number of entities",7,22,"NA",12,"NA","NA","NA"," " "Number of retail

  18. Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total"

    Energy Information Administration (EIA) (indexed site)

    Missouri" ,"Full service providers",,,,,"Other providers",, "Item","Investor Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total" "Number of entities",5,86,"NA",42,"NA","NA","NA"," " "Number of retail

  19. Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total"

    Energy Information Administration (EIA) (indexed site)

    Nebraska" ,"Full service providers",,,,,"Other providers",, "Item","Investor Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total" "Number of entities","NA",148,1,10,"NA","NA","NA"," " "Number of retail

  20. Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total"

    Energy Information Administration (EIA) (indexed site)

    Carolina" ,"Full service providers",,,,,"Other providers",, "Item","Investor Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total" "Number of entities",4,22,"NA",21,"NA","NA","NA"," " "Number of retail

  1. Mitigating Carbon Emissions: the Potential of Improving Efficiencyof Household Appliances in China

    SciTech Connect

    Lin, Jiang

    2006-07-10

    China is already the second's largest energy consumer in the world after the United States, and its demand for energy is expected to continue to grow rapidly in the foreseeable future, due to its fast economic growth and its low level of energy use per capita. From 2001 to 2005, the growth rate of energy consumption in China has exceeded the growth rate of its economy (NBS, 2006), raising serious concerns about the consequences of such energy use on local environment and global climate. It is widely expected that China is likely to overtake the US in energy consumption and greenhouse gas (GHG) emissions during the first half of the 21st century. Therefore, there is considerable interest in the international community in searching for options that may help China slow down its growth in energy consumption and GHG emissions through improving energy efficiency and adopting more environmentally friendly fuel supplies such as renewable energy. This study examines the energy saving potential of three major residential energy end uses: household refrigeration, air-conditioning, and water heating. China is already the largest consumer market in the world for household appliances, and increasingly the global production base for consumer appliances. Sales of household refrigerators, room air-conditioners, and water heaters are growing rapidly due to rising incomes and booming housing market. At the same time, the energy use of Chinese appliances is relatively inefficient compared to similar products in the developed economies. Therefore, the potential for energy savings through improving appliance efficiency is substantial. This study focuses particularly on the impact of more stringent energy efficiency standards for household appliances, given that such policies are found to be very effective in improving the efficiency of household appliances, and are well established both in China and around world (CLASP, 2006).

  2. GTZ Global Energy Program | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    to households, SME and public utility institutions. Key products include access to modern energy services and promotion of new technologies. References "GTZ projects"...

  3. Stepped-anneal and total helium/hydrogen measurements in high-energy proton-irradiated tungsten

    SciTech Connect

    Oliver, B.M.; Hamilton, M.L.; Garner, F.A.; Sommer, W.F.; Maloy, S.A.; Ferguson, P.D.

    1998-12-31

    To provide structural material design data for the Accelerator Production of Tritium (APT) project, a 1 mA, 800 MeV proton beam at the Los Alamos Neutron Science Center (LANSCE) was used to irradiate a large number of metal samples, including a tungsten target similar to that being considered as the neutron source for the tritium production. The maximum proton fluence to the tungsten target was {approximately} 10{sup 21} protons/cm{sup 2}. An unavoidable byproduct of spallation reactions is the formation of large amounts of hydrogen and helium. Postulated accident scenarios for APT involving the use of tungsten rods clad with Alloy 718, raise concerns as to the amount and rate of release of these gases due to temperatures increases from afterheat accumulation, with the major concern being pressurizing and possibly failure of the cladding. To address these issues, portions of the LANSCE tungsten rods were subjected to temperature histories calculated as likely to occur, and the time-dependent evolution of helium and hydrogen gases was measured. Stepped-anneal and total helium/hydrogen measurements were conducted on multiple samples of the tungsten material. Helium measurements were conducted at Pacific Northwest National Laboratory (PNNL) using a high-sensitivity magnetic-sector isotope-dilution helium analysis system. Stepped-anneal measurements were conducted at temperatures from {approximately} 25 C to {approximately} 1,600 C in {approximately} 100 C steps. Total helium measurements were conducted by rapid vaporization after completion of the stepped-anneal process, and are compared with Monte Carlo calculations performed at Los Alamos National Laboratory (LANL) using the LAHET code system. Hydrogen measurements were conducted between {approximately} 750 C and {approximately} 1,200 C using a high-temperature furnace that had been extensively modified for the application. Hydrogen detection was accomplished by periodic sampling of the furnace gas using a separate

  4. Crafty Gifts for the Energy Conscious

    Energy.gov [DOE]

    Check out these homemade gifts that can help your loved ones be energy efficient in their households.

  5. Hadronic Total Cross Sections (R) in E+E- Interactions: Data from DOE laboratory experiments as compiled in data reviews by the Durham High Energy Physics Database Group

    DOE Data Explorer

    Whalley, M. R.

    A comprehensive compilation of experimental data on total hadronic cross sections, and R ratios, in e+e- interactions is presented. Published data from the Novosibirsk, Orsay, Frascati, SLAC, CORNELL, DESY, KEK and CERN e+e- colliders on both exclusive and inclusive final particle states are included from threshold energies to the highest LEP energies. The data are presented in tabular form supplemented by compilation plots of different exclusive final particle states and of different energy regions. (Taken from abstract of paper, A Compilation of Data on Hadronic Total Cross Sections in E+E- Interactions, M.R. Whalley, Journal of Physics G (Nuclear and Particle Physics), Volume 29, Number 12A, 2003). The Durham High Energy Physics (HEP) Database Group makes these data, extracted from papers and data reviews, available in one place in an easy-to-access format. The data are also included in the Durham HEP Reaction Data Database, which can be searched at http://hepdata.cedar.ac.uk/reaction

  6. Total Space Heating Water Heating Cook-

    Annual Energy Outlook

    Commercial Buildings Energy Consumption Survey: Energy End-Use Consumption Tables Total Space Heating Water Heating Cook- ing Other Total Space Heating Water Heating Cook- ing...

  7. Total Space Heating Water Heating Cook-

    Gasoline and Diesel Fuel Update

    Energy Consumption Survey: Energy End-Use Consumption Tables Total Space Heating Water Heating Cook- ing Other Total Space Heating Water Heating Cook- ing Other All...

  8. Search results | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    counted and priced. They measure and evaluate energy use and cost of representative household and school electrical items. http:energy.goveereeducationdownloads...

  9. appl_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    RSE Row Factors New York California Texas Florida 0.4 1.2 1.1 1.4 1.3 Total ... RSE Row Factors New York California Texas Florida 0.4 1.2 1.1 1.4 1.3 Age of Refrigerator ...

  10. spaceheat_household2001.pdf

    Gasoline and Diesel Fuel Update

    RSE Row Factors New York California Texas Florida 0.5 1.1 1.0 1.2 1.6 Total ... RSE Row Factors New York California Texas Florida 0.5 1.1 1.0 1.2 1.6 Age of Main Heating ...

  11. Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total"

    Energy Information Administration (EIA) (indexed site)

    Vermont" ,"Full service providers",,,,,"Other providers",, "Item","Investor Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total" "Number of entities",2,14,"NA",2,1,"NA","NA"," " "Number of retail customers",258928,54912,"NA",49378,1,"NA","NA",363219 "Retail

  12. Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total"

    Energy Information Administration (EIA) (indexed site)

    Virginia" ,"Full service providers",,,,,"Other providers",, "Item","Investor Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total" "Number of entities",3,16,"NA",13,"NA",1,1," " "Number of retail customers",2934456,166751,"NA",629034,"NA",20,"NA",3730261 "Retail sales

  13. Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total"

    Energy Information Administration (EIA) (indexed site)

    Washington" ,"Full service providers",,,,,"Other providers",, "Item","Investor Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total" "Number of entities",4,41,2,18,1,3,1," " "Number of retail customers",1460672,1669068,10,167371,1,17,"NA",3297139 "Retail sales

  14. Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total"

    Energy Information Administration (EIA) (indexed site)

    Wisconsin" ,"Full service providers",,,,,"Other providers",, "Item","Investor Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total" "Number of entities",13,82,"NA",24,2,"NA","NA"," " "Number of retail customers",2439647,282258,"NA",260892,2,"NA","NA",2982799

  15. Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total"

    Energy Information Administration (EIA) (indexed site)

    Wyoming" ,"Full service providers",,,,,"Other providers",, "Item","Investor Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total" "Number of entities",5,13,1,18,"NA","NA","NA"," " "Number of retail customers",198292,36318,5,99606,"NA","NA","NA",334221 "Retail

  16. Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total"

    Energy Information Administration (EIA) (indexed site)

    United States" ,"Full service providers",,,,,"Other providers",, "Item","Investor Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total" "Number of entities",256,1948,6,810,144,188,67," " "Number of retail customers",93329397,21335809,40029,19096482,656,13411030,"NA",147213403 "Retail sales

  17. Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total"

    Energy Information Administration (EIA) (indexed site)

    Arizona" ,"Full service providers",,,,,"Other providers",, "Item","Investor Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total" "Number of entities",23,29,3,9,11,"NA","NA"," " "Number of retail customers",1675038,1078638,16690,187629,12,"NA","NA",2958007 "Retail sales

  18. Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total"

    Energy Information Administration (EIA) (indexed site)

    California" ,"Full service providers",,,,,"Other providers",, "Item","Investor Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total" "Number of entities",29,41,2,4,65,17,3," " "Number of retail customers",11676056,3110257,2197,16506,69,185755,"NA",14990840 "Retail sales

  19. Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total"

    Energy Information Administration (EIA) (indexed site)

    Colorado" ,"Full service providers",,,,,"Other providers",, "Item","Investor Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total" "Number of entities",10,29,1,28,7,"NA","NA"," " "Number of retail customers",1500660,428854,13,632335,7,"NA","NA",2561869 "Retail sales

  20. Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total"

    Energy Information Administration (EIA) (indexed site)

    Connecticut" ,"Full service providers",,,,,"Other providers",, "Item","Investor Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total" "Number of entities",7,8,"NA","NA",3,35,2," " "Number of retail customers",948486,71741,"NA","NA",3,597272,"NA",1617502 "Retail sales

  1. Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total"

    Energy Information Administration (EIA) (indexed site)

    Delaware" ,"Full service providers",,,,,"Other providers",, "Item","Investor Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total" "Number of entities",2,9,"NA",1,1,27,1," " "Number of retail customers",267434,66283,"NA",88026,1,38537,"NA",460281 "Retail sales

  2. Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total"

    Energy Information Administration (EIA) (indexed site)

    Georgia" ,"Full service providers",,,,,"Other providers",, "Item","Investor Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total" "Number of entities",2,53,"NA",42,1,"NA","NA"," " "Number of retail customers",2410042,333203,"NA",1966788,31,"NA","NA",4710064

  3. Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total"

    Energy Information Administration (EIA) (indexed site)

    Idaho" ,"Full service providers",,,,,"Other providers",, "Item","Investor Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total" "Number of entities",3,11,2,17,"NA","NA","NA"," " "Number of retail customers",693393,43895,1,84578,"NA","NA","NA",821867 "Retail

  4. Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total"

    Energy Information Administration (EIA) (indexed site)

    Illinois" ,"Full service providers",,,,,"Other providers",, "Item","Investor Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total" "Number of entities",4,41,"NA",26,2,53,3," " "Number of retail customers",1911129,270483,"NA",301219,318,3268220,"NA",5751369 "Retail sales

  5. Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total"

    Energy Information Administration (EIA) (indexed site)

    Kansas" ,"Full service providers",,,,,"Other providers",, "Item","Investor Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total" "Number of entities",4,118,1,29,"NA","NA","NA"," " "Number of retail customers",953679,235288,4,292717,"NA","NA","NA",1481688 "Retail

  6. Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total"

    Energy Information Administration (EIA) (indexed site)

    Kentucky" ,"Full service providers",,,,,"Other providers",, "Item","Investor Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total" "Number of entities",5,30,1,24,2,"NA","NA"," " "Number of retail customers",1220619,210206,17,813201,4,"NA","NA",2244047 "Retail sales

  7. Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total"

    Energy Information Administration (EIA) (indexed site)

    Maine" ,"Full service providers",,,,,"Other providers",, "Item","Investor Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total" "Number of entities",2,4,"NA",2,1,32,6," " "Number of retail customers",39,10603,"NA",2535,1,788335,"NA",801513 "Retail sales

  8. Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total"

    Energy Information Administration (EIA) (indexed site)

    Maryland" ,"Full service providers",,,,,"Other providers",, "Item","Investor Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total" "Number of entities",10,5,"NA",3,8,52,5," " "Number of retail customers",1638979,28808,"NA",208447,8,610640,"NA",2486882 "Retail sales

  9. Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total"

    Energy Information Administration (EIA) (indexed site)

    Massachusetts" ,"Full service providers",,,,,"Other providers",, "Item","Investor Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total" "Number of entities",13,40,"NA","NA",27,40,5," " "Number of retail customers",2182382,399857,"NA","NA",40,544399,"NA",3126678 "Retail

  10. Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total"

    Energy Information Administration (EIA) (indexed site)

    Michigan" ,"Full service providers",,,,,"Other providers",, "Item","Investor Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total" "Number of entities",8,41,"NA",10,2,12,3," " "Number of retail customers",4177118,306315,"NA",318985,2,6419,"NA",4808839 "Retail sales

  11. Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total"

    Energy Information Administration (EIA) (indexed site)

    Mississippi" ,"Full service providers",,,,,"Other providers",, "Item","Investor Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total" "Number of entities",2,23,1,25,"NA","NA","NA"," " "Number of retail customers",628656,134500,7,741758,"NA","NA","NA",1504921

  12. Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total"

    Energy Information Administration (EIA) (indexed site)

    Montana" ,"Full service providers",,,,,"Other providers",, "Item","Investor Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total" "Number of entities",5,1,3,29,"NA",2,1," " "Number of retail customers",377770,983,20971,197627,"NA",419,"NA",597770 "Retail sales

  13. Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total"

    Energy Information Administration (EIA) (indexed site)

    Hampshire" ,"Full service providers",,,,,"Other providers",, "Item","Investor Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total" "Number of entities",3,5,"NA",1,"NA",20,4," " "Number of retail customers",496060,12226,"NA",78794,"NA",128985,"NA",716065 "Retail sales

  14. Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total"

    Energy Information Administration (EIA) (indexed site)

    Jersey" ,"Full service providers",,,,,"Other providers",, "Item","Investor Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total" "Number of entities",17,9,"NA",1,35,58,4," " "Number of retail customers",3270179,55120,"NA",11581,39,649669,"NA",3986588 "Retail sales

  15. Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total"

    Energy Information Administration (EIA) (indexed site)

    York" ,"Full service providers",,,,,"Other providers",, "Item","Investor Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total" "Number of entities",19,48,"NA",4,5,69,9," " "Number of retail customers",5052054,1270394,"NA",18139,15,1751992,"NA",8092594 "Retail sales

  16. Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total"

    Energy Information Administration (EIA) (indexed site)

    Dakota" ,"Full service providers",,,,,"Other providers",, "Item","Investor Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total" "Number of entities",3,12,1,21,"NA","NA","NA"," " "Number of retail customers",238608,11023,21,186997,"NA","NA","NA",436649 "Retail

  17. Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total"

    Energy Information Administration (EIA) (indexed site)

    Ohio" ,"Full service providers",,,,,"Other providers",, "Item","Investor Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total" "Number of entities",10,85,"NA",25,6,52,6," " "Number of retail customers",2143362,375117,"NA",383167,12,2618989,"NA",5520647 "Retail sales

  18. Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total"

    Energy Information Administration (EIA) (indexed site)

    Oklahoma" ,"Full service providers",,,,,"Other providers",, "Item","Investor Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total" "Number of entities",3,62,1,31,"NA","NA","NA"," " "Number of retail customers",1291253,204450,1,508162,"NA","NA","NA",2003866

  19. Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total"

    Energy Information Administration (EIA) (indexed site)

    Oregon" ,"Full service providers",,,,,"Other providers",, "Item","Investor Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total" "Number of entities",8,18,1,19,"NA",4,3," " "Number of retail customers",1421279,294747,1,203211,"NA",484,"NA",1919722 "Retail sales

  20. Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total"

    Energy Information Administration (EIA) (indexed site)

    Pennsylvania" ,"Full service providers",,,,,"Other providers",, "Item","Investor Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total" "Number of entities",15,35,"NA",13,5,73,10," " "Number of retail customers",3554206,83922,"NA",219570,5,2146096,"NA",6003799 "Retail sales

  1. Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total"

    Energy Information Administration (EIA) (indexed site)

    Rhode Island" ,"Full service providers",,,,,"Other providers",, "Item","Investor Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total" "Number of entities",2,1,"NA","NA","NA",17,1," " "Number of retail customers",462381,4658,"NA","NA","NA",32071,"NA",499110

  2. Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total"

    Energy Information Administration (EIA) (indexed site)

    Dakota" ,"Full service providers",,,,,"Other providers",, "Item","Investor Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total" "Number of entities",6,36,1,31,"NA","NA","NA"," " "Number of retail customers",243148,60553,22,154530,"NA","NA","NA",458253 "Retail

  3. Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total"

    Energy Information Administration (EIA) (indexed site)

    Tennessee" ,"Full service providers",,,,,"Other providers",, "Item","Investor Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total" "Number of entities",3,61,1,26,1,"NA","NA"," " "Number of retail customers",47264,2213496,23,969214,1,"NA","NA",3229998 "Retail sales

  4. Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total"

    Energy Information Administration (EIA) (indexed site)

    Texas" ,"Full service providers",,,,,"Other providers",, "Item","Investor Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total" "Number of entities",89,72,"NA",68,13,"NA","NA"," " "Number of retail customers",7744205,1849743,"NA",2076859,50,"NA","NA",11670857

  5. Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total"

    Energy Information Administration (EIA) (indexed site)

    Utah" ,"Full service providers",,,,,"Other providers",, "Item","Investor Owned","Public","Federal","Cooperative","Non-utility","Energy","Delivery","Total" "Number of entities",1,40,1,9,1,"NA","NA"," " "Number of retail customers",835233,244217,7,48538,1,"NA","NA",1127996 "Retail sales

  6. EERE Success Story-Kingston Creek Hydro Project Powers 100 Households |

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Department of Energy Kingston Creek Hydro Project Powers 100 Households EERE Success Story-Kingston Creek Hydro Project Powers 100 Households August 21, 2013 - 12:00am Addthis Nevada-based contracting firm Nevada Controls, LLC used a low-interest loan from the Nevada State Office of Energy's Revolving Loan Fund to help construct a hydropower project in the small Nevada town of Kingston. The Kingston Creek Project-benefitting the Young Brothers Ranch-is a 175-kilowatt hydro generation plant

  7. Measurement of the 240Pu/239Pu mass ratio using a transition-edge-sensor microcalorimeter for total decay energy spectroscopy

    DOE PAGES [OSTI]

    Hoover, Andrew S.; Bond, Evelyn M.; Croce, Mark P.; Holesinger, Terry G.; Kunde, Gerd J.; Rabin, Michael W.; Wolfsberg, Laura E.; Bennett, Douglas A.; Hays-Wehle, James P.; Schmidt, Dan R.; et al

    2015-02-27

    In this study, we have developed a new category of sensor for measurement of the 240Pu/239Pu mass ratio from aqueous solution samples with advantages over existing methods. Aqueous solution plutonium samples were evaporated and encapsulated inside of a gold foil absorber, and a superconducting transition-edge-sensor microcalorimeter detector was used to measure the total reaction energy (Q-value) of nuclear decays via heat generated when the energy is thermalized. Since all of the decay energy is contained in the absorber, we measure a single spectral peak for each isotope, resulting in a simple spectral analysis problem with minimal peak overlap. We foundmore » that mechanical kneading of the absorber dramatically improves spectral quality by reducing the size of radioactive inclusions within the absorber to scales below 50 nm such that decay products primarily interact with atoms of the host material. Due to the low noise performance of the microcalorimeter detector, energy resolution values of 1 keV fwhm (full width at half-maximum) at 5.5 MeV have been achieved, an order of magnitude improvement over α-spectroscopy with conventional silicon detectors. We measured the 240Pu/239Pu mass ratio of two samples and confirmed the results by comparison to mass spectrometry values. These results have implications for future measurements of trace samples of nuclear material.« less

  8. Measurement of the 240Pu/239Pu mass ratio using a transition-edge-sensor microcalorimeter for total decay energy spectroscopy

    SciTech Connect

    Hoover, Andrew S.; Bond, Evelyn M.; Croce, Mark P.; Holesinger, Terry G.; Kunde, Gerd J.; Rabin, Michael W.; Wolfsberg, Laura E.; Bennett, Douglas A.; Hays-Wehle, James P.; Schmidt, Dan R.; Swetz, Daniel; Ullom, Joel N.

    2015-02-27

    In this study, we have developed a new category of sensor for measurement of the 240Pu/239Pu mass ratio from aqueous solution samples with advantages over existing methods. Aqueous solution plutonium samples were evaporated and encapsulated inside of a gold foil absorber, and a superconducting transition-edge-sensor microcalorimeter detector was used to measure the total reaction energy (Q-value) of nuclear decays via heat generated when the energy is thermalized. Since all of the decay energy is contained in the absorber, we measure a single spectral peak for each isotope, resulting in a simple spectral analysis problem with minimal peak overlap. We found that mechanical kneading of the absorber dramatically improves spectral quality by reducing the size of radioactive inclusions within the absorber to scales below 50 nm such that decay products primarily interact with atoms of the host material. Due to the low noise performance of the microcalorimeter detector, energy resolution values of 1 keV fwhm (full width at half-maximum) at 5.5 MeV have been achieved, an order of magnitude improvement over α-spectroscopy with conventional silicon detectors. We measured the 240Pu/239Pu mass ratio of two samples and confirmed the results by comparison to mass spectrometry values. These results have implications for future measurements of trace samples of nuclear material.

  9. Buildings Energy Data Book: 2.2 Residential Sector Characteristics

    Buildings Energy Data Book

    6 Residential Heated Floorspace, as of 2005 (Percent of Total Households) Floorspace (SF) Fewer than 500 6% 500 to 999 26% 1,000 to 1,499 24% 1,500 to 1,999 16% 2,000 to 2,499 9% 2,500 to 2,999 7% 3,000 or more 11% Total 100% Source(s): EIA, 2005 Residential Energy Consumption Survey, Oct. 2008, Table HC1-3.

  10. Transferring 2001 National Household Travel Survey

    SciTech Connect

    Hu, Patricia S; Reuscher, Tim; Schmoyer, Richard L; Chin, Shih-Miao

    2007-05-01

    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

  11. Total Energy Outcome City Pilot

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Results should include a working policy that requires; 1) benchmarking of all public and ... Additional Funding: No other funding has been utilized Budget History 090112- FY2013 ...

  12. Comparison of approaches to Total Quality Management. Including an examination of the Department of Energy`s position on quality management

    SciTech Connect

    Bennett, C.T.

    1994-03-01

    This paper presents a comparison of several qualitatively different approaches to Total Quality Management (TQM). The continuum ranges from management approaches that are primarily standards -- with specific guidelines, but few theoretical concepts -- to approaches that are primarily philosophical, with few specific guidelines. The approaches to TQM discussed in this paper include the International Organization for Standardization (ISO) 9000 Standard, the Malcolm Baldrige National Quality Award, Senge`s the Learning Organization, Watkins and Marsick`s approach to organizational learning, Covey`s Seven Habits of Highly Successful People, and Deming`s Fourteen Points for Management. Some of these approaches (Deming and ISO 9000) are then compared to the DOE`s official position on quality management and conduct of operations (DOE Orders 5700.6C and 5480.19). Using a tabular format, it is shown that while 5700.6C (Quality Assurance) maps well to many of the current approaches to TQM, DOE`s principle guide to management Order 5419.80 (Conduct of Operations) has many significant conflicts with some of the modern approaches to continuous quality improvement.

  13. Residential Energy Consumption Survey: Housing Characteristics...

    Gasoline and Diesel Fuel Update

    either air or liquid as the working fluid. It does not refer :<: passive collection of solar thermal energy. Fuel Oil Paid by Household: The household paid directly to the fuel...

  14. Lincoln Electric System (Residential)- 2015 Sustainable Energy Program

    Energy.gov [DOE]

    Lincoln Electric System (LES) offers several rebates to residential customers who are interested in upgrading to energy efficient household equipment.

  15. 2014 Renewable Energy Markets (REM) Conference

    Energy.gov [DOE]

    Renewable Energy Markets (REM) is the clean energy industry's most important annual event focused on the states, businesses, organizations, and households that choose clean, renewable electricity...

  16. IMAT SpA | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    33074 Sector: Renewable Energy, Solar Product: Italy-based company specializing in manufacturing of components for household refrigeration. Their main renewable energy focus is...

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

    Gasoline and Diesel Fuel Update

    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 ...

  18. Buildings Energy Data Book: 2.1 Residential Sector Energy Consumption

    Buildings Energy Data Book

    9 Northeast Midwest South West National Space Heating 70.3 56.6 20.4 23.8 38.7 Space Cooling 3.6 5.6 13.9 4.0 7.9 Water Heating 21.1 20.4 15.8 21.2 19.0 Refrigerator 5.4 7.0 6.6 5.7 6.3 Other Appliances & Lighting 23.0 25.9 25.0 24.1 24.7 Total (1) 79.9 77.4 95.0 Note(s): Source(s): 2005 Delivered Energy End-Uses for an Average Household, by Region (Million Btu per Household) 122.2 113.5 1) Due to rounding, sums do not add up to totals. EIA, 2005 Residential Energy Consumption Survey, Oct.

  19. Average household expected to save $675 at the pump in 2015

    Energy Information Administration (EIA) (indexed site)

    Average household expected to save $675 at the pump in 2015 Although retail gasoline prices have risen in recent weeks U.S. consumers are still expected to save about $675 per household in motor fuel costs this year. In its new monthly forecast, the U.S. Energy Information Administration says the average pump price for regular grade gasoline in 2015 will be $2.43 per gallon. That's about 93 cents lower than last year's average. The savings for consumers will be even bigger during the

  20. Household-level dynamics of food waste production and related beliefs, attitudes, and behaviours in Guelph, Ontario

    SciTech Connect

    Parizeau, Kate; Massow, Mike von; Martin, Ralph

    2015-01-15

    Highlights: • We combined household waste stream weights with survey data. • We examine relationships between waste and food-related practices and beliefs. • Families and large households produced more total waste, but less waste per capita. • Food awareness and waste awareness were related to reduced food waste. • Convenience lifestyles were differentially associated with food waste. - Abstract: It has been estimated that Canadians waste $27 billion of food annually, and that half of that waste occurs at the household level (Gooch et al., 2010). There are social, environmental, and economic implications for this scale of food waste, and source separation of organic waste is an increasingly common municipal intervention. There is relatively little research that assesses the dynamics of household food waste (particularly in Canada). The purpose of this study is to combine observations of organic, recyclable, and garbage waste production rates to survey results of food waste-related beliefs, attitudes, and behaviours at the household level in the mid-sized municipality of Guelph, Ontario. Waste weights and surveys were obtained from 68 households in the summer of 2013. The results of this study indicate multiple relationships between food waste production and household shopping practices, food preparation behaviours, household waste management practices, and food-related attitudes, beliefs, and lifestyles. Notably, we observed that food awareness, waste awareness, family lifestyles, and convenience lifestyles were related to food waste production. We conclude that it is important to understand the diversity of factors that can influence food wasting behaviours at the household level in order to design waste management systems and policies to reduce food waste.

  1. The changing character of household waste in the Czech Republic between 1999 and 2009 as a function of home heating methods

    SciTech Connect

    Doležalová, Markéta; Benešová, Libuše; Závodská, Anita

    2013-09-15

    Highlights: • The character of household waste in the three different types of households were assesed. • The quantity, density and composition of household waste were determined. • The physicochemical characteristics were determined. • The changing character of household waste during past 10 years was described. • The potential of energy recovery of household waste in Czech republic was assesed. - Abstract: The authors of this paper report on the changing character of household waste, in the Czech Republic between 1999 and 2009 in households differentiated by their heating methods. The data presented are the result of two projects, financed by the Czech Ministry of Environment, which were undertaken during this time period with the aim of focusing on the waste characterisation and complete analysis of the physicochemical properties of the household waste. In the Czech Republic, the composition of household waste varies significantly between different types of households based on the methods of home heating employed. For the purposes of these studies, the types of homes were divided into three categories – urban, mixed and rural. Some of the biggest differences were found in the quantities of certain subsample categories, especially fine residue (matter smaller than 20 mm), between urban households with central heating and rural households that primarily employ solid fuel such coal or wood. The use of these solid fuels increases the fraction of the finer categories because of the higher presence of ash. Heating values of the residual household waste from the three categories varied very significantly, ranging from 6.8 MJ/kg to 14.2 MJ/kg in 1999 and from 6.8 MJ/kg to 10.5 MJ/kg in 2009 depending on the type of household and season. The same factors affect moisture of residual household waste which varied from 23.2% to 33.3%. The chemical parameters also varied significantly, especially in the quantities of Tl, As, Cr, Zn, Fe and Mn, which were higher in

  2. Nepal-GTZ Energy Efficiency Program | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    1 GTZ is working with Nepal on integration of EE as part of the national energy strategy, development of EE measures for households. References "GTZ projects" Retrieved...

  3. Pakistan-GTZ Renewable Energy and Energy Efficiency Promotion...

    OpenEI (Open Energy Information) [EERE & EIA]

    is working with Pakistan on improvement of energy service supply to households and enterprises through RE use and EE. References "GTZ projects" Retrieved from "http:...

  4. Energy Trust of Oregon Inc | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Product: Gives grants for the implementation of efficiency improvements and renewable energy sources at a household and utility-scale level. Coordinates: 45.511795,...

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

    SciTech Connect

    Letschert, Virginie; McNeil, Michael A.

    2009-03-23

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

  6. Search results | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Students learn how electrical usage is counted and priced. They measure and evaluate energy use and cost of representative household and school electrical items. http:...

  7. Search results | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    an abstract concept that is very familiar to students from personal experiences with household appliances, transportation, and their own bodies. However, the nature of energy,...

  8. The importance of China's household sector for black carbon emissions - article no. L12708

    SciTech Connect

    Streets, D.G.; Aunan, K.

    2005-06-30

    The combustion of coal and biofuels in Chinese households is a large source of black carbon (BC), representing about 10-15% of total global emissions during the past two decades, depending on the year. How the Chinese household sector develops during the next 50 years will have an important bearing on future aerosol concentrations, because the range of possible outcomes (about 550 Gg yr{sup -1}) is greater than total BC emissions in either the United States or Europe (each about 400-500 Gg yr{sup -1}). In some Intergovernmental Panel on Climate Change scenarios biofuels persist in rural China for at least the next 50 years, whereas in other scenarios a transition to cleaner fuels and technologies effectively mitigates BC emissions. This paper discusses measures and policies that would help this transition and also raises the possibility of including BC emission reductions as a post-Kyoto option for China and other developing countries.

  9. Buildings Energy Data Book: 2.3 Residential Sector Expenditures

    Buildings Energy Data Book

    0 2005 Energy End-Use Expenditures for an Average Household, by Region ($2010) Northeast Midwest South West National Space Heating 1,050 721 371 352 575 Air-Conditioning 199 175 456 262 311 Water Heating 373 294 313 318 320 Refrigerators 194 145 146 154 157 Other Appliances and Lighting 827 665 715 716 725 Total (1) 2,554 1,975 1,970 1,655 2,003 Note(s): 1) Due to rounding, end-uses do not sum to totals. Source(s): EIA, 2005 Residential Energy Consumption Survey, Oct. 2008, Table US-15; EIA,

  10. Loan Programs for Low- and Moderate-Income Households

    Energy.gov [DOE]

    Better Buildings Residential Network Multifamily and Low-Income Housing Peer Exchange Call Series: Loan Programs for Low- and Moderate-Income Households, March 13, 2014.

  11. Table 8.4a Consumption for Electricity Generation by Energy Source: Total (All Sectors), 1949-2011 (Sum of Tables 8.4b and 8.4c; Billion Btu)

    Energy Information Administration (EIA) (indexed site)

    a Consumption for Electricity Generation by Energy Source: Total (All Sectors), 1949-2011 (Sum of Tables 8.4b and 8.4c; Billion Btu) Year Fossil Fuels Nuclear Electric Power 5 Renewable Energy Other 9 Electricity Net Imports 10 Total Coal 1 Petroleum 2 Natural Gas 3 Other Gases 4 Total Conventional Hydroelectric Power 5 Biomass Geo- thermal 5 Solar/PV 5,8 Wind 5 Total Wood 6 Waste 7 1949 1,995,055 414,632 569,375 NA 2,979,062 0 1,424,722 5,803 NA NA NA NA 1,430,525 NA 5,420 4,415,007 1950

  12. U.S. Energy Department, Pay-Television Industry and Energy Efficiency

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Groups Announce Set-Top Box Energy Conservation Agreement; Will Cut Energy Use for 90 Million U.S. Households, Save Consumers Billions | Department of Energy Department, Pay-Television Industry and Energy Efficiency Groups Announce Set-Top Box Energy Conservation Agreement; Will Cut Energy Use for 90 Million U.S. Households, Save Consumers Billions U.S. Energy Department, Pay-Television Industry and Energy Efficiency Groups Announce Set-Top Box Energy Conservation Agreement; Will Cut Energy

  13. Residential Sector Demand Module of the National Energy Modeling...

    Gasoline and Diesel Fuel Update

    Stoves Geothermal Heat Pump Natural Gas Heat Pump Variables: HSYSSHR 2001,eg,b,r Benchmarking Data from Short-Term Energy Outlook Definition: Household energy consumption by...

  14. Property-Assessed Clean Energy (PACE) Financing Resources | Department...

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    ... PACE on community adoption rates of energy efficiency improvements and per household energy consumption, and various program design strategies, and effectiveness of PACE relative ...

  15. Appliance Standby Power and Energy Consumption in South African...

    OpenEI (Open Energy Information) [EERE & EIA]

    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...

  16. Analysis of changes in residential energy consumption, 1973-1980

    SciTech Connect

    King, M.J.; Belzer, D.B.; Callaway, J.M.; Adams, R.C.

    1982-09-01

    The progress of energy conservation in the residential sector since the 1973 to 1974 Arab oil embargo is assessed. To accomplish this goal, the reduction in residential energy use per household since 1973 is disaggregated into six possible factors. The factors considered were: (1) building shell efficiencies, (2) geographic distribution of households, (3) appliance efficiency, (4) size of dwelling units, (5) fuel switching, and (6) consumer attitudes. The most important factor identified was improved building shell efficiency, although the impact of appliance efficiency is growing rapidly. Due to data limitations, PNL was not able to quantify the effects of two factors (size of dwelling units and fuel switching) within the framework of this study. The total amount of the energy reduction explained ranged from 18 to 46% over the years 1974 to 1980.

  17. Barge Truck Total

    Annual Energy Outlook

    Barge Truck Total delivered cost per short ton Shipments with transportation rates over total shipments Total delivered cost per short ton Shipments with transportation rates over...

  18. Energy Intensity Indicators: Residential Source Energy Consumption

    Energy.gov [DOE]

    Figure R1 below reports as index numbers over the period 1970 through 2011: 1) the number of U.S. households, 2) the average size of those housing units, 3) residential source energy consumption, 4...

  19. Minority energy assessment report

    SciTech Connect

    Teotia, A.P.S.; Poyer, D.A.; Lampley, L.; Anderson, J.L.

    1992-12-01

    The purpose of this research is to project household energy consumption, energy expenditure, and energy expenditure as share of income for five population groups from 1991 to 2009. The approach uses the Minority Energy Assessment Model (MEAM), developed by Argonne National Laboratory for the US Department of Energy's Office of Minority Economic Impact. The MEAM provides a framework that can be used to forecast regional energy consumption and energy expenditure for majority, black, Hispanic, poor, and nonpoor households. The forecasts of key macroeconomic and energy variables used as exogenous variables in the MEAM were obtained from the Data Resources, Inc., Macromodel and Energy Model. Generally, the projections of household energy consumption, expenditure, and energy expenditure as share of income vary across population groups and census regions.

  20. Table HC6.2 Living Space Characteristics by Number of Household Members, 2005

    Energy Information Administration (EIA) (indexed site)

    2 Living Space Characteristics by Number of Household Members, 2005 Total...................................................................... 111.1 30.0 34.8 18.4 15.9 12.0 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500............................................... 3.2 1.7 0.8 0.4 0.3 Q 500 to 999....................................................... 23.8 10.2 6.4 3.4 2.3 1.5 1,000 to 1,499................................................. 20.8 5.5 6.3 3.0 3.3 2.6 1,500 to

  1. Tax Credits, Rebates & Savings | Department of Energy

    Energy.gov [DOE] (indexed site)

    The New Jersey Comfort Partners program is a free of charge, direct installation energy efficiency assistance program available to most New Jersey households with significant...

  2. NREL: Energy Systems Integration - Systems Integration

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    High-level system integration New distribution scenarios such as household DC systems and residential-scale generation and storage integrated with home energy management systems. ...

  3. Tax Credits, Rebates & Savings | Department of Energy

    Energy.gov [DOE] (indexed site)

    rental apartment owners. The program is designed to offer rebates on some of the most energy intensive household... Eligibility: Multifamily Residential Savings Category:...

  4. Lincoln Electric System (Residential)- Sustainable Energy Program

    Office of Energy Efficiency and Renewable Energy (EERE)

    Lincoln Electric System (LES) offers several rebates to their residential customers who are interested in upgrading to energy efficient household equipment. 

  5. Laboratory Testing of Demand-Response Enabled Household Appliances

    SciTech Connect

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

    2013-10-01

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

  6. Laboratory Testing of Demand-Response Enabled Household Appliances

    SciTech Connect

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

    2013-10-01

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

  7. Perceptions of risk among households in two Australian coastal communities

    SciTech Connect

    Elrick-Barr, Carmen E.; Smith, Timothy F.; Thomsen, Dana C.; Preston, Benjamin L.

    2015-04-20

    There is limited knowledge of risk perceptions in coastal communities despite their vulnerability to a range of risks including the impacts of climate change. A survey of 400 households in two Australian coastal communities, combined with semi-structured interviews, provides insight into household perceptions of the relative importance of climatic and non-climatic risks and the subsequent risk priorities that may inform household adaptive action. In contrast to previous research, the results demonstrated that geographic location and household characteristics might not affect perceptions of vulnerability to environmental hazards. However, past experience was a significant influence, raising the priority of environmental concerns. Overall, the results highlight the priority concerns of coastal households (from finance, to health and environment) and suggest to increase the profile of climate issues in coastal communities climate change strategies need to better demonstrate links between climate vulnerability and other household concerns. Moreover, promoting generic capacities in isolation from understanding the context in which households construe climate risks is unlikely to yield the changes required to decrease the vulnerability of coastal communities.

  8. Perceptions of risk among households in two Australian coastal communities

    DOE PAGES [OSTI]

    Elrick-Barr, Carmen E.; Smith, Timothy F.; Thomsen, Dana C.; Preston, Benjamin L.

    2015-04-20

    There is limited knowledge of risk perceptions in coastal communities despite their vulnerability to a range of risks including the impacts of climate change. A survey of 400 households in two Australian coastal communities, combined with semi-structured interviews, provides insight into household perceptions of the relative importance of climatic and non-climatic risks and the subsequent risk priorities that may inform household adaptive action. In contrast to previous research, the results demonstrated that geographic location and household characteristics might not affect perceptions of vulnerability to environmental hazards. However, past experience was a significant influence, raising the priority of environmental concerns. Overall,more » the results highlight the priority concerns of coastal households (from finance, to health and environment) and suggest to increase the profile of climate issues in coastal communities climate change strategies need to better demonstrate links between climate vulnerability and other household concerns. Moreover, promoting generic capacities in isolation from understanding the context in which households construe climate risks is unlikely to yield the changes required to decrease the vulnerability of coastal communities.« less

  9. Reconstructing householder vectors from Tall-Skinny QR

    DOE PAGES [OSTI]

    Ballard, Grey Malone; Demmel, James; Grigori, Laura; Jacquelin, Mathias; Knight, Nicholas; Nguyen, Hong Diep

    2015-08-05

    The Tall-Skinny QR (TSQR) algorithm is more communication efficient than the standard Householder algorithm for QR decomposition of matrices with many more rows than columns. However, TSQR produces a different representation of the orthogonal factor and therefore requires more software development to support the new representation. Further, implicitly applying the orthogonal factor to the trailing matrix in the context of factoring a square matrix is more complicated and costly than with the Householder representation. We show how to perform TSQR and then reconstruct the Householder vector representation with the same asymptotic communication efficiency and little extra computational cost. We demonstratemore » the high performance and numerical stability of this algorithm both theoretically and empirically. The new Householder reconstruction algorithm allows us to design more efficient parallel QR algorithms, with significantly lower latency cost compared to Householder QR and lower bandwidth and latency costs compared with Communication-Avoiding QR (CAQR) algorithm. Experiments on supercomputers demonstrate the benefits of the communication cost improvements: in particular, our experiments show substantial improvements over tuned library implementations for tall-and-skinny matrices. Furthermore, we also provide algorithmic improvements to the Householder QR and CAQR algorithms, and we investigate several alternatives to the Householder reconstruction algorithm that sacrifice guarantees on numerical stability in some cases in order to obtain higher performance.« less

  10. Reconstructing householder vectors from Tall-Skinny QR

    SciTech Connect

    Ballard, Grey Malone; Demmel, James; Grigori, Laura; Jacquelin, Mathias; Knight, Nicholas; Nguyen, Hong Diep

    2015-08-05

    The Tall-Skinny QR (TSQR) algorithm is more communication efficient than the standard Householder algorithm for QR decomposition of matrices with many more rows than columns. However, TSQR produces a different representation of the orthogonal factor and therefore requires more software development to support the new representation. Further, implicitly applying the orthogonal factor to the trailing matrix in the context of factoring a square matrix is more complicated and costly than with the Householder representation. We show how to perform TSQR and then reconstruct the Householder vector representation with the same asymptotic communication efficiency and little extra computational cost. We demonstrate the high performance and numerical stability of this algorithm both theoretically and empirically. The new Householder reconstruction algorithm allows us to design more efficient parallel QR algorithms, with significantly lower latency cost compared to Householder QR and lower bandwidth and latency costs compared with Communication-Avoiding QR (CAQR) algorithm. Experiments on supercomputers demonstrate the benefits of the communication cost improvements: in particular, our experiments show substantial improvements over tuned library implementations for tall-and-skinny matrices. Furthermore, we also provide algorithmic improvements to the Householder QR and CAQR algorithms, and we investigate several alternatives to the Householder reconstruction algorithm that sacrifice guarantees on numerical stability in some cases in order to obtain higher performance.

  11. Special Topics on Energy Use in Household Transportation

    Energy Information Administration (EIA) (indexed site)

    compare your estimate of your car's mpg to the average of everyone else who takes the test. (Released 04112000; Updated Yearly for Fuel Economies and Weekly for Fuel Prices)...

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

    Gasoline and Diesel Fuel Update

    ... 9.6 5.0 100 4.4 6.2 4.5 0.8 6.8 4.5 Income Relative to Poverty Line Below 100 Percent... 11.4 6.0 116 5.1 5.6...

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

    Annual Energy Outlook

    11.5 0.8 1.0 0.9 0.8 0.7 0.8 0.7 1.6 1.4 0.8 0.5 0.2 0.1 0.7 0.4 Income Relative to Poverty Line Below 100 Percent... 13.3 0.3 0.4 0.4 0.6...

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

    Annual Energy Outlook

    ... 6.5 1.5 15.4 957 1,031 Income Relative to Poverty Line Below 100 Percent... 7.9 1.4 14.7 942 937...

  15. Determinants of Household Use of Selected Energy Star Appliances

    Gasoline and Diesel Fuel Update

    Restructuring by State Map. State: 51 items, 51 with data. Alabama is 0. Value is in the Not Active range, Alabama Deregulation: NO Retail Choice: NO Click for more information (State Restructuring Activities: None since 10/2000), Detail for AL. Arkansas is 9. Value is in the Suspended range, Arkansas Deregulation: SUSPENDED Retail Choice: NO Click for more information (State Restructuring Activities: None since 03/2003), Detail for AR. Arizona is 9. Value is in the Suspended range, Arizona

  16. Fact #618: April 12, 2010 Vehicles per Household and Other Demographic...

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    per Household and Other Demographic Statistics Fact 618: April 12, 2010 Vehicles per Household and Other Demographic Statistics Since 1969, the number of vehicles per ...

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

    Energy Information Administration (EIA) (indexed site)

    ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ... for 2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ...

  18. "Table HC7.12 Home Electronics Usage Indicators by Household...

    Energy Information Administration (EIA) (indexed site)

    ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ... for 2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ...

  19. Total Crude by Pipeline

    Energy Information Administration (EIA) (indexed site)

    Product: Total Crude by All Transport Methods Domestic Crude by All Transport Methods Foreign Crude by All Transport Methods Total Crude by Pipeline Domestic Crude by Pipeline Foreign Crude by Pipeline Total Crude by Tanker Domestic Crude by Tanker Foreign Crude by Tanker Total Crude by Barge Domestic Crude by Barge Foreign Crude by Barge Total Crude by Tank Cars (Rail) Domestic Crude by Tank Cars (Rail) Foreign Crude by Tank Cars (Rail) Total Crude by Trucks Domestic Crude by Trucks Foreign

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

    SciTech Connect

    Eisenberg, Joel Fred

    2008-06-01

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

  1. Neutron Total Cross Sections of {sup 235}U From Transmission Measurements in the Energy Range 2 keV to 300 keV and Statistical Model Analysis of the Data

    SciTech Connect

    Derrien, H.; Harvey, J.A.; Larson, N.M.; Leal, L.C.; Wright, R.Q.

    2000-05-01

    The average {sup 235}U neutron total cross sections were obtained in the energy range 2 keV to 330 keV from high-resolution transmission measurements of a 0.033 atom/b sample.1 The experimental data were corrected for the contribution of isotope impurities and for resonance self-shielding effects in the sample. The results are in very good agreement with the experimental data of Poenitz et al.4 in the energy range 40 keV to 330 keV and are the only available accurate experimental data in the energy range 2 keV to 40 keV. ENDF/B-VI evaluated data are 1.7% larger. The SAMMY/FITACS code 2 was used for a statistical model analysis of the total cross section, selected fission cross sections and data in the energy range 2 keV to 200 keV. SAMMY/FITACS is an extended version of SAMMY which allows consistent analysis of the experimental data in the resolved and unresolved resonance region. The Reich-Moore resonance parameters were obtained 3 from a SAMMY Bayesian fits of high resolution experimental neutron transmission and partial cross section data below 2.25 keV, and the corresponding average parameters and covariance data were used in the present work as input for the statistical model analysis of the high energy range of the experimental data. The result of the analysis shows that the average resonance parameters obtained from the analysis of the unresolved resonance region are consistent with those obtained in the resolved energy region. Another important result is that ENDF/B-VI capture cross section could be too small by more than 10% in the energy range 10 keV to 200 keV.

  2. NEUTRON TOTAL CROSS SECTIONS OF 235U FROM TRANSMISSION MEASUREMENTS IN THE ENERGY RANGE 2 keV to 300 keV AND STATISTICAL MODEL ANALYSIS OF THE DATA

    SciTech Connect

    Derrien, H.

    2000-05-22

    The average {sup 235}U neutron total cross sections were obtained in the energy range 2 keV to 330 keV from high-resolution transmission measurements of a 0.033 atom/b sample. The experimental data were corrected for the contribution of isotope impurities and for resonance self-shielding effects in the sample. The results are in very good agreement with the experimental data of Poenitz et al. in the energy range 40 keV to 330 keV and are the only available accurate experimental data in the energy range 2 keV to 40 keV. ENDF/B-VI evaluated data are 1.7% larger. The SAMMY/FITACS code was used for a statistical model analysis of the total cross section, selected fission cross sections and {alpha} data in the energy range 2 keV to 200 keV. SAMMY/FITACS is an extended version of SAMMY which allows consistent analysis of the experimental data in the resolved and unresolved resonance region. The Reich-Moore resonance parameters were obtained from a SAMMY Bayesian fits of high resolution experimental neutron transmission and partial cross section data below 2.25 keV, and the corresponding average parameters and covariance data were used in the present work as input for the statistical model analysis of the high energy range of the experimental data. The result of the analysis shows that the average resonance parameters obtained from the analysis of the unresolved resonance region are consistent with those obtained in the resolved energy region. Another important result is that ENDF/B-VI capture cross section could be too small by more than 10% in the energy range 10 keV to 200 keV.

  3. Household waste disposal in Mekelle city, Northern Ethiopia

    SciTech Connect

    Tadesse, Tewodros Ruijs, Arjan; Hagos, Fitsum

    2008-07-01

    In many cities of developing countries, such as Mekelle (Ethiopia), waste management is poor and solid wastes are dumped along roadsides and into open areas, endangering health and attracting vermin. The effects of demographic factors, economic and social status, waste and environmental attributes on household solid waste disposal are investigated using data from household survey. Household level data are then analyzed using multinomial logit estimation to determine the factors that affect household waste disposal decision making. Results show that demographic features such as age, education and household size have an insignificant impact over the choice of alternative waste disposal means, whereas the supply of waste facilities significantly affects waste disposal choice. Inadequate supply of waste containers and longer distance to these containers increase the probability of waste dumping in open areas and roadsides relative to the use of communal containers. Higher household income decreases the probability of using open areas and roadsides as waste destinations relative to communal containers. Measures to make the process of waste disposal less costly and ensuring well functioning institutional waste management would improve proper waste disposal.

  4. Advances in Household Appliances- A Review

    SciTech Connect

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

    2011-01-01

    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.

  5. Monthly energy review, September 1995

    SciTech Connect

    1995-09-25

    An ``energy snapshot`` article is included on housing characteristics in 1993 (survey of 7,111 households). The rest of the document is divided into: energy overview, energy consumption, petroleum, natural gas, oil and gas resource development, coal, electricity, nuclear energy, energy prices, international energy, and appendices (conversion factors, CO2 emission factors from coal, index, glossary).

  6. Table HC6.10 Home Appliances Usage Indicators by Number of Household Members, 2005

    Energy Information Administration (EIA) (indexed site)

    0 Home Appliances Usage Indicators by Number of Household Members, 2005 Total.............................................................................. 111.1 30.0 34.8 18.4 15.9 12.0 Cooking Appliances Frequency of Hot Meals Cooked 3 or More Times A Day........................................... 8.2 1.4 1.9 1.4 1.0 2.4 2 Times A Day........................................................ 24.6 4.3 7.6 4.3 4.8 3.7 Once a Day............................................................ 42.3 9.9

  7. Table HC6.12 Home Electronics Usage Indicators by Number of Household Members, 2005

    Energy Information Administration (EIA) (indexed site)

    2 Home Electronics Usage Indicators by Number of Household Members, 2005 Total................................................................................ 111.1 30.0 34.8 18.4 15.9 12.0 Personal Computers Do Not Use a Personal Computer............................. 35.5 16.3 9.4 4.0 2.7 3.2 Use a Personal Computer.......................................... 75.6 13.8 25.4 14.4 13.2 8.8 Most-Used Personal Computer Type of PC Desk-top Model.....................................................

  8. Table HC6.7 Air-Conditioning Usage Indicators by Number of Household Members, 2005

    Energy Information Administration (EIA) (indexed site)

    7 Air-Conditioning Usage Indicators by Number of Household Members, 2005 Total........................................................................ 111.1 30.0 34.8 18.4 15.9 12.0 Do Not Have Cooling Equipment.......................... 17.8 5.4 5.3 2.7 2.5 2.0 Have Cooling Equipment...................................... 93.3 24.6 29.6 15.7 13.4 10.0 Use Cooling Equipment....................................... 91.4 24.0 29.1 15.5 13.2 9.7 Have Equipment But Do Not Use it......................

  9. Table HC6.9 Home Appliances Characteristics by Number of Household Members, 2005

    Energy Information Administration (EIA) (indexed site)

    HC6.9 Home Appliances Characteristics by Number of Household Members, 2005 Total U.S.............................................................. 111.1 30.0 34.8 18.4 15.9 12.0 Cooking Appliances Conventional Ovens Use an Oven.................................................. 109.6 29.5 34.4 18.2 15.7 11.8 1................................................................. 103.3 28.4 32.0 17.3 14.7 11.0 2 or More.................................................... 6.2 1.1 2.5 1.0 0.9 0.8 Do Not

  10. Buildings Energy Data Book: 2.3 Residential Sector Expenditures

    Buildings Energy Data Book

    3 2005 Average Household Expenditures, by Census Region ($2010) Item Energy (1) Shelter (2) Food Telephone, water and other public services Household supplies, furnishings and equipment (3) Transportation (4) Healthcare Education Personal taxes (5) Other expenditures Average Annual Income Note(s): Source(s): 1) Average household energy expenditures are calculated from the Residential Energy Consumption Survey (RECS), while average expenditures for other categories are calculated from the

  11. Buildings Energy Data Book: 2.3 Residential Sector Expenditures

    Buildings Energy Data Book

    4 2005 Average Household Expenditures as Percent of Annual Income, by Census Region ($2010) Item Energy (1) Shelter (2) Food Telephone, water and other public services Household supplies, furnishings and equipment (3) Transportation (4) Healthcare Education Personal taxes (5) Average Annual Expenditures Average Annual Income Note(s): Source(s): 1) Average household energy expenditures are calculated from the Residential Energy Consumption Survey (RECS), while average expenditures for other

  12. PVT -- A photovoltaic/thermal concentrator total energy system: Final phase 1 project report. Building opportunities in the U.S. for photovoltaics (PV:BONUS) Two

    SciTech Connect

    1998-12-31

    United Solar completed its Phase 1 report and its proposal for Phase 2 of the PVBONUS Two program at the end of March 1998. At the same time, it also completed and submitted a proposal to the California Energy Commission PIER program for additional funding to cost-share development and testing of a pre-production model of the PVT-14. It was unsuccessful in both of these proposed efforts. While waiting for the proposal decisions, work continued in April and May to analyze the system design and component decisions described below. This document is a final summation report on the Phase 1 effort of the PVBONUS Two program that describes the key technical issues that United Solar and its subcontractor, Industrial Solar Technology Corporation, worked on in preparation of a Phase 2 award. The decisions described were ones that will guide the design and fabrication of a pre-production prototype of a 1500:1 mirrored concentrator with gallium arsenide cells when United solar resumes its development work. The material below is organized by citing the key components that underwent a design review, what the company considered, what was decided, the name of the expected supplier, if not to be produced in-house, and some information about expected costs. The cost figures given are usually budgetary estimates, not the result of firm quotations or extensive analysis.

  13. Energy

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Sandia Energy Energy Search Icon Sandia Home Locations Contact Us Employee Locator Energy & Climate Secure & Sustainable Energy Future Stationary Power Energy Conversion Efficiency ...

  14. Energy

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    3 - Sandia Energy Energy Search Icon Sandia Home Locations Contact Us Employee Locator Energy & Climate Secure & Sustainable Energy Future Stationary Power Energy Conversion ...

  15. Energy

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    2 - Sandia Energy Energy Search Icon Sandia Home Locations Contact Us Employee Locator Energy & Climate Secure & Sustainable Energy Future Stationary Power Energy Conversion ...

  16. Equity implications of utility energy conservation programs

    SciTech Connect

    Sutherland, R.J.

    1994-03-15

    This paper uses the Residential Energy Consumption Survey undertaken by the Energy Information Administration in 1990 to estimate the statistical association between household income and participation in electric utility energy conservation programs and the association between participation and the electricity consumption. The results indicate that utility rebates, energy audits, load management programs and other conservation measures tend to be undertaken at greater frequency by high income households than by low income households. Participants in conservation programs tend to occupy relatively new and energy efficient residences and undertake conservation measures other than utility programs, which suggests that utility sponsored programs are substitutes for other conservation investments. Electricity consumption during 1990 is not significantly less for households participating in utility programs than for nonparticipants, which also implies that utility conservation programs are displacing other conservation investments. Apparently, utility programs are not avoiding costs of new construction and instead are transferring wealth, particularly to high income participating households.

  17. U.S. Energy Information Administration (EIA) - Ap

    Energy Information Administration (EIA) (indexed site)

    cost of fossil-fuels for electricity generation All consumption & efficiency data reports ... Residential Energy Consumption Survey Household end use consumption of ...

  18. Watt Does It Cost To Use It? | Department of Energy

    Office of Environmental Management (EM)

    Summary Students learn how electrical usage is counted and priced. They measure and evaluate energy use and cost of representative household and school electrical items. Curriculum ...

  19. Energy Department Announces Winners of Housing Innovation Awards...

    Energy Saver

    building technologies and design to new and older homes and helping households save money. ... communities across the country save money and energy and are leading the way to ...

  20. Saving Energy and Money with Appliance and Equipment Standards...

    Energy Saver

    ... Today, a typical household saves about 247 per year Saving Energy and Money with Appliance and Equipment Standards in the United States BUILDING TECHNOLOGIES OFFICE Photo credit ...

  1. Assumption to the Annual Energy Outlook 2014 - Residential Demand...

    Annual Energy Outlook

    oil, liquefied petroleum gas, natural gas, kerosene, electricity, wood, geothermal, and solar energy. The module's output includes number of households, equipment stock, average...

  2. DHCD- Multifamily Energy Efficiency and Housing Affordability Program

    Office of Energy Efficiency and Renewable Energy (EERE)

    Maryland Department of Housing and Community Development (DHCD) provides several programs to increase energy efficiency of multifamily homes of low and moderate income households. These affordable...

  3. DOE/EIA-0321/HRIf Residential Energy Consumption Survey. Consumption

    Annual Energy Outlook

    purchase diaries from a subset of respondents composing a Household Transportation Panel and is reported separately. Residential Energy Consumption Survey: Consumption and...

  4. Energy Savings Week: How Lighting Standards Are Saving You Money...

    Energy Saver

    Standards Are Saving You Money Lighting accounts for about 11% of home electricity use (or 7% energy use). Lighting efficiency standards are expected to save households almost ...

  5. How are coastal households responding to climate change?

    DOE PAGES [OSTI]

    Elrick-Barr, Carmen E.; Smith, Timothy F.; Preston, Benjamin L.; Thomsen, Dana C.; Baum, Scott

    2016-06-13

    In Australia, shared responsibility is a concept advocated to promote collective climate change adaptation by multiple actors and institutions. However, a shared response is often promoted in the absence of information regarding actions currently taken; in particular, there is limited knowledge regarding action occurring at the household scale. To address this gap, we examine household actions taken to address climate change and associated hazards in two Australian coastal communities. Mixed methods research is conducted to answer three questions: (1) what actions are currently taken (mitigation, actions to lobby for change or adaptation to climate impacts)? (2) why are these actionsmore » taken (e.g. are they consistent with capacity, experience, perceptions of risk); and (3) what are the implications for adaptation? We find that households are predominantly mitigating greenhouse gas emissions and that impact orientated adaptive actions are limited. Coping strategies are considered sufficient to mange climate risks, proving a disincentive for additional adaptive action. Influencing factors differ, but generally, risk perception and climate change belief are associated with action. Furthermore, the likelihood of more action is a function of homeownership and a tendency to plan ahead. Addressing factors that support or constrain household adaptive decision-making and action, from the physical (e.g. homeownership) to the social (e.g. skills in planning and a culture of adapting to change) will be critical in increasing household participation in adaptation.« less

  6. Total quality management implementation guidelines

    SciTech Connect

    Not Available

    1993-12-01

    These Guidelines were designed by the Energy Quality Council to help managers and supervisors in the Department of Energy Complex bring Total Quality Management to their organizations. Because the Department is composed of a rich mixture of diverse organizations, each with its own distinctive culture and quality history, these Guidelines are intended to be adapted by users to meet the particular needs of their organizations. For example, for organizations that are well along on their quality journeys and may already have achieved quality results, these Guidelines will provide a consistent methodology and terminology reference to foster their alignment with the overall Energy quality initiative. For organizations that are just beginning their quality journeys, these Guidelines will serve as a startup manual on quality principles applied in the Energy context.

  7. International Energy Outlook 2014

    Gasoline and Diesel Fuel Update

    Household heating bills expected to be higher than last winter, mainly driven by colder weather U.S. households are expected to pay higher heating bills this winter compared to last winter mainly because the weather is forecast to be colder than the relatively mild weather seen last winter and fuel prices are forecast to be higher. In its new forecast, the U.S. Energy Information Administration said households using heating oil will see a 38% jump in their heating fuel expenditures while propane

  8. ,"Total District Heat Consumption (trillion Btu)",,,,,"District...

    Energy Information Administration (EIA) (indexed site)

    Heat Consumption (trillion Btu)",,,,,"District Heat Energy Intensity (thousand Btusquare foot)" ,"Total ","Space Heating","Water Heating","Cook- ing","Other","Total ","Space...

  9. ,"Total Natural Gas Consumption (trillion Btu)",,,,,"Natural...

    Energy Information Administration (EIA) (indexed site)

    Gas Consumption (trillion Btu)",,,,,"Natural Gas Energy Intensity (thousand Btusquare foot)" ,"Total ","Space Heating","Water Heating","Cook- ing","Other","Total ","Space...

  10. Buildings Energy Data Book: 2.1 Residential Sector Energy Consumption

    Buildings Energy Data Book

    2 Delivered Energy Consumption Intensities of Public Multi-Family Buildings, by Fuel and Region (Million Btu/Household) Region Electricity Natural Gas Fuel Oil Total Northeast 21.2 34.9 36.2 54.7 Midwest 16.6 36.6 N.A. 51.8 South 39.4 20.0 N.A. 48.5 West 16.6 19.3 N.A. 34.8 National Average 24.6 32.2 51.0

  11. Modeling patterns of hot water use in households

    SciTech Connect

    Lutz, J.D.; Liu, Xiaomin; McMahon, J.E.

    1996-11-01

    This report presents a detailed model of hot water use patterns in individual household. The model improves upon an existing model by including the effects of four conditions that were previously unaccounted for: the absence of a clothes washer; the absence of a dishwasher; a household consisting of seniors only; and a household that does not pay for its own hot water use. Although these four conditions can significantly affect residential hot water use, and have been noted in other studies, this is the first time that they have been incorporated into a detailed model. This model allows detailed evaluation of the impact of potential efficiency standards for water heaters and other market transformation policies. 21 refs., 3 figs., 10 tabs.

  12. Modeling patterns of hot water use in households

    SciTech Connect

    Lutz, James D.; Liu, Xiaomin; McMahon, James E.; Dunham, Camilla; Shown, Leslie J.; McCure, Quandra T.

    1996-01-01

    This report presents a detailed model of hot water use patterns in individual households. The model improves upon an existing model by including the effects of four conditions that were previously unaccounted for: the absence of a clothes washer; the absence of a dishwasher; a household consisting of seniors only; and a household that does not pay for its own hot water use. Although these four conditions can significantly affect residential hot water use, and have been noted in other studies, this is the first time that they have been incorporated into a detailed model. This model allows detailed evaluation of the impact of potential efficiency standards for water heaters and other market transformation policies.

  13. Small Town Energy Program (STEP) Final Report revised

    SciTech Connect

    Wilson, Charles T.

    2014-01-02

    University Park, Maryland (“UP”) is a small town of 2,540 residents, 919 homes, 2 churches, 1 school, 1 town hall, and 1 breakthrough community energy efficiency initiative: the Small Town Energy Program (“STEP”). STEP was developed with a mission to “create a model community energy transformation program that serves as a roadmap for other small towns across the U.S.” STEP first launched in January 2011 in UP and expanded in July 2012 to the neighboring communities of Hyattsville, Riverdale Park, and College Heights Estates, MD. STEP, which concluded in July 2013, was generously supported by a grant from the U.S. Department of Energy (DOE). The STEP model was designed for replication in other resource-constrained small towns similar to University Park - a sector largely neglected to date in federal and state energy efficiency programs. STEP provided a full suite of activities for replication, including: energy audits and retrofits for residential buildings, financial incentives, a community-based social marketing backbone and local community delivery partners. STEP also included the highly innovative use of an “Energy Coach” who worked one-on-one with clients throughout the program. Please see www.smalltownenergy.org for more information. In less than three years, STEP achieved the following results in University Park: • 30% of community households participated voluntarily in STEP; • 25% of homes received a Home Performance with ENERGY STAR assessment; • 16% of households made energy efficiency improvements to their home; • 64% of households proceeded with an upgrade after their assessment; • 9 Full Time Equivalent jobs were created or retained, and 39 contractors worked on STEP over the course of the project. Estimated Energy Savings - Program Totals kWh Electricity 204,407 Therms Natural Gas 24,800 Gallons of Oil 2,581 Total Estimated MMBTU Saved (Source Energy) 5,474 Total Estimated Annual Energy Cost Savings $61,343 STEP clients who

  14. ,"Total Fuel Oil Expenditures

    Energy Information Administration (EIA) (indexed site)

    . Fuel Oil Expenditures by Census Region for Non-Mall Buildings, 2003" ,"Total Fuel Oil Expenditures (million dollars)",,,,"Fuel Oil Expenditures (dollars)" ,,,,,"per...

  15. ,"Total Fuel Oil Expenditures

    Energy Information Administration (EIA) (indexed site)

    4. Fuel Oil Expenditures by Census Region, 1999" ,"Total Fuel Oil Expenditures (million dollars)",,,,"Fuel Oil Expenditures (dollars)" ,,,,,"per Gallon",,,,"per Square Foot"...

  16. ,"Total Fuel Oil Expenditures

    Energy Information Administration (EIA) (indexed site)

    A. Fuel Oil Expenditures by Census Region for All Buildings, 2003" ,"Total Fuel Oil Expenditures (million dollars)",,,,"Fuel Oil Expenditures (dollars)" ,,,,,"per Gallon",,,,"per...

  17. Total Space Heat-

    Gasoline and Diesel Fuel Update

    Revised: December, 2008 Total Space Heat- ing Cool- ing Venti- lation Water Heat- ing Light- ing Cook- ing Refrig- eration Office Equip- ment Com- puters Other All Buildings...

  18. Total Space Heat-

    Gasoline and Diesel Fuel Update

    Released: September, 2008 Total Space Heat- ing Cool- ing Venti- lation Water Heat- ing Light- ing Cook- ing Refrig- eration Office Equip- ment Com- puters Other All Buildings*...

  19. Status of not-in-kind refrigeration technologies for household space conditioning, water heating and food refrigeration

    SciTech Connect

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

    2012-07-19

    This paper presents a review of the next generation not-in-kind technologies to replace conventional vapor compression refrigeration technology for household applications. Such technologies are sought to provide energy savings or other environmental benefits for space conditioning, water heating and refrigeration for domestic use. These alternative technologies include: thermoacoustic refrigeration, thermoelectric refrigeration, thermotunneling, magnetic refrigeration, Stirling cycle refrigeration, pulse tube refrigeration, Malone cycle refrigeration, absorption refrigeration, adsorption refrigeration, and compressor driven metal hydride heat pumps. Furthermore, heat pump water heating and integrated heat pump systems are also discussed due to their significant energy saving potential for water heating and space conditioning in households. The paper provides a snapshot of the future R&D needs for each of the technologies along with the associated barriers. Both thermoelectric and magnetic technologies look relatively attractive due to recent developments in the materials and prototypes being manufactured.

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

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    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 ...