Sample records for bottom-up energy end-use

  1. China's energy and emissions outlook to 2050: Perspectives from bottom-up energy end-use model

    E-Print Network [OSTI]

    Zhou, Nan

    2014-01-01T23:59:59.000Z

    Implications for Chinese energy demand and imports in 2020.for China to reduce energy demand and emissions. Thisand physical drivers of energy demand and thereby help

  2. China's energy and emissions outlook to 2050: Perspectives from bottom-up energy end-use model

    E-Print Network [OSTI]

    Zhou, Nan

    2014-01-01T23:59:59.000Z

    Development Plan for Renewable Energy in China. Availabledevelopment-plan-for-renewable-energy.pdf Tu, J. , Jaccard,further expansion of renewable and nuclear power capacity.

  3. Implications of maximizing China's technical potential for residential end-use energy efficiency: A 2030 outlook from the bottom-up

    E-Print Network [OSTI]

    Khanna, Nina

    2014-01-01T23:59:59.000Z

    4 3. Basis for Residential Energy Demandand the subsequent energy demand and CO 2 emissionsa smaller share of total energy demand followed by space

  4. Implications of maximizing China's technical potential for residential end-use energy efficiency: A 2030 outlook from the bottom-up

    E-Print Network [OSTI]

    Khanna, Nina

    2014-01-01T23:59:59.000Z

    of electric and gas water heaters, both of which areMEPS revisions. For gas water heaters, the energy factor isDOE 2010). For electric water heaters, continued efficiency

  5. Bottom-Up Energy Analysis System - Methodology and Results

    E-Print Network [OSTI]

    McNeil, Michael A.

    2013-01-01T23:59:59.000Z

    TSL 4 TSL 4 TSL 4 TSL 4 Group End Use Water HeatersWater HeatersWater Heaters Water Heaters Water Heaters Water Heaters

  6. Bottom-Up Energy Analysis System (BUENAS) | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to:EzfeedflagBiomass ConversionsSouthbyBoston Heights, Ohio: Energy ResourcesBothell,

  7. Bottom-Up Energy Analysis System (BUENAS) | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to:EzfeedflagBiomass ConversionsSouthbyBoston Heights, Ohio: Energy ResourcesBothell,(Redirected

  8. Bottom-Up Energy Analysis System - Methodology and Results

    E-Print Network [OSTI]

    McNeil, Michael A.

    2013-01-01T23:59:59.000Z

    et al. , TV Energy Consumption Trends and Energy-Efficiencyet al. , Fan Energy Consumption Trends and Energy-EfficiencyEnergy Consumption can change over time according to usage trends.

  9. Bottom-Up Energy Analysis System - Methodology and Results

    E-Print Network [OSTI]

    McNeil, Michael A.

    2013-01-01T23:59:59.000Z

    LEGEND Baseline Unit Energy  Consumption Data or Assumptionof baseline unit energy consumption data is given in Table5 – Sources of Unit Energy Consumption Data Product Boilers

  10. Bottom-Up Energy Analysis System - Methodology and Results

    E-Print Network [OSTI]

    McNeil, Michael A.

    2013-01-01T23:59:59.000Z

    MEX RUS USA ZAF Baseline Unit Energy Consumption – AnnualRUS A USA ZAF A Target Unit Energy Consumption – Unit energy

  11. Bottom-Up Energy Analysis System - Methodology and Results

    E-Print Network [OSTI]

    McNeil, Michael A.

    2013-01-01T23:59:59.000Z

    Energy Agency, World Energy Outlook 2006. 2006, OECD. ILO,by the trend of IEA’s World Energy Outlook (WEO) 2006 [71],to trends in the World Energy Outlook [71]. The projection

  12. Bottom-Up Energy Analysis System - Methodology and Results

    E-Print Network [OSTI]

    McNeil, Michael A.

    2013-01-01T23:59:59.000Z

    Case (EFF) energy demand and Business as Usual (BAU) energyAnnual unit energy consumption in Business As Usual ScenarioM.A. , et al. , Business Case for Energy Efficiency in

  13. Bottom-Up Energy Analysis System - Methodology and Results

    E-Print Network [OSTI]

    McNeil, Michael A.

    2013-01-01T23:59:59.000Z

    South Africa China India Indonesia Total without China Total including China EnergySouth Africa and the United States. Chinese appliance energy

  14. Bottoms Up

    E-Print Network [OSTI]

    Hacker, Randi; Boyd, David

    2011-03-30T23:59:59.000Z

    Broadcast Transcript: "Bottoms up!" Or, "gan bei," as they say here in China. But what are you drinking? It could either be the authentic 144-proof sorghum-based liquor Moutai, or a clever counterfeit. Moutai has been dubbed the "national wine...

  15. Representing energy technologies in top-down economic models using bottom-up information

    E-Print Network [OSTI]

    McFarland, James R.; Reilly, John M.; Herzog, Howard J.

    This paper uses bottom-up engineering information as a basis for modeling new technologies within the MIT Emissions Prediction and Policy Analysis (EPPA) model, a computable general equilibrium model of the world economy. ...

  16. Energy efficiency and the cost of GHG abatement: A comparison of bottom-up and hybrid models for the US

    E-Print Network [OSTI]

    Energy efficiency and the cost of GHG abatement: A comparison of bottom-up and hybrid models energy­economy models. Using the CIMS hybrid model, we conducted simulations for comparison with the Mc February 2011 Accepted 16 August 2011 Available online 17 September 2011 Keywords: Energy efficiency

  17. Two Paths to Transforming Markets through Public Sector Energy Efficiency: Bottom Up versus Top Down

    E-Print Network [OSTI]

    Van Wie McGrory, Laura; Coleman, Philip; Fridley, David; Harris, Jeffrey; Villasenor Franco, Edgar

    2006-01-01T23:59:59.000Z

    public sector buildings in four provinces to develop a baseline of equipment usage and energy consumption;

  18. India Energy Outlook: End Use Demand in India to 2020

    SciTech Connect (OSTI)

    de la Rue du Can, Stephane; McNeil, Michael; Sathaye, Jayant

    2009-03-30T23:59:59.000Z

    Integrated economic models have been used to project both baseline and mitigation greenhouse gas emissions scenarios at the country and the global level. Results of these scenarios are typically presented at the sectoral level such as industry, transport, and buildings without further disaggregation. Recently, a keen interest has emerged on constructing bottom up scenarios where technical energy saving potentials can be displayed in detail (IEA, 2006b; IPCC, 2007; McKinsey, 2007). Analysts interested in particular technologies and policies, require detailed information to understand specific mitigation options in relation to business-as-usual trends. However, the limit of information available for developing countries often poses a problem. In this report, we have focus on analyzing energy use in India in greater detail. Results shown for the residential and transport sectors are taken from a previous report (de la Rue du Can, 2008). A complete picture of energy use with disaggregated levels is drawn to understand how energy is used in India and to offer the possibility to put in perspective the different sources of end use energy consumption. For each sector, drivers of energy and technology are indentified. Trends are then analyzed and used to project future growth. Results of this report provide valuable inputs to the elaboration of realistic energy efficiency scenarios.

  19. Two Paths to Transforming Markets through Public Sector Energy Efficiency: Bottom Up versus Top Down

    E-Print Network [OSTI]

    agencies, reduced demand on capacity-constrained electric utility systems, increased energy system energy-efficiency strategies in the public sector. Several years of pursuing a top-down (federally led federal government is leading to an intergovernmental initiative with strong support at the federal level

  20. Bottom Up and Country Led: A New Framework for Climate Action | Open Energy

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualProperty EditCalifornia: EnergyAvignon,BelcherBlundell 1FortInformationJV

  1. Assessment of Historic Trend in Mobility and Energy Use in India Transportation Sector Using Bottom-up Approach

    SciTech Connect (OSTI)

    Zhou, Nan; McNeil, Michael A.

    2009-05-01T23:59:59.000Z

    Transportation mobility in India has increased significantly in the past decades. From 1970 to 2000, motorized mobility (passenger-km) has risen by 888%, compared with an 88% population growth (Singh,2006). This contributed to many energy and environmental issues, and an energy strategy incorporates efficiency improvement and other measures needs to be designed. Unfortunately, existing energy data do not provide information on driving forces behind energy use and sometime show large inconsistencies. Many previous studies address only a single transportation mode such as passenger road travel; did not include comprehensive data collection or analysis has yet been done, or lack detail on energy demand by each mode and fuel mix. The current study will fill a considerable gap in current efforts, develop a data base on all transport modes including passenger air and water, and freight in order to facilitate the development of energy scenarios and assess significance of technology potential in a global climate change model. An extensive literature review and data collection has been done to establish the database with breakdown of mobility, intensity, distance, and fuel mix of all transportation modes. Energy consumption was estimated and compared with aggregated transport consumption reported in IEA India transportation energy data. Different scenarios were estimated based on different assumptions on freight road mobility. Based on the bottom-up analysis, we estimated that the energy consumption from 1990 to 2000 increased at an annual growth rate of 7% for the mid-range road freight growth case and 12% for the high road freight growth case corresponding to the scenarios in mobility, while the IEA data only shows a 1.7% growth rate in those years.

  2. Healthcare Energy End-Use Monitoring

    SciTech Connect (OSTI)

    Sheppy, M.; Pless, S.; Kung, F.

    2014-08-01T23:59:59.000Z

    NREL partnered with two hospitals (MGH and SUNY UMU) to collect data on the energy used for multiple thermal and electrical end-use categories, including preheat, heating, and reheat; humidification; service water heating; cooling; fans; pumps; lighting; and select plug and process loads. Additional data from medical office buildings were provided for an analysis focused on plug loads. Facility managers, energy managers, and engineers in the healthcare sector will be able to use these results to more effectively prioritize and refine the scope of investments in new metering and energy audits.

  3. Bottom-up Representation of Industrial Energy Efficiency Technologies in Integrated Assessment Models for the Cement Sector

    SciTech Connect (OSTI)

    Sathaye, J.; Xu, T.; Galitsky, C.

    2010-08-15T23:59:59.000Z

    Adoption of efficient end-use technologies is one of the key measures for reducing greenhouse gas (GHG) emissions. How to effectively analyze and manage the costs associated with GHG reductions becomes extremely important for the industry and policy makers around the world. Energy-climate (EC) models are often used for analyzing the costs of reducing GHG emissions for various emission-reduction measures, because an accurate estimation of these costs is critical for identifying and choosing optimal emission reduction measures, and for developing related policy options to accelerate market adoption and technology implementation. However, accuracies of assessing of GHG-emission reduction costs by taking into account the adoption of energy efficiency technologies will depend on how well these end-use technologies are represented in integrated assessment models (IAM) and other energy-climate models.

  4. Energy End-Use Intensities in Commercial Buildings1992 -- Overview/End-Use

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40CoalLease(Billion2,128 2,469DecadeOriginand Tables End-Use1995 End-Use

  5. Canadian Industrial Energy End-use Data and Analysis

    E-Print Network [OSTI]

    CIEEDAC Canadian Industrial Energy End-use Data and Analysis Centre Prospectus and Business Plan as part clearinghouse, part depository, and part analysis centre for energy data on the Canadian EXECUTIVE SUMMARY CIEEDAC ii Executive Summary 1. Background The Canadian Industrial Energy End-use Data

  6. Healthcare Energy End-Use Monitoring

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels DataDepartment of Energy Your Density Isn't YourTransport(Fact Sheet), GeothermalGridHYDROGEN TO THEHudson Hazle

  7. Comparison of Bottom-Up and Top-Down Forecasts: Vision Industry Energy Forecasts with ITEMS and NEMS 

    E-Print Network [OSTI]

    Roop, J. M.; Dahowski, R. T

    2000-01-01T23:59:59.000Z

    of the Department of Energy's Office of Industrial Technologies, EIA extracted energy use infonnation from the Annual Energy Outlook (AEO) - 2000 (8) for each of the seven # The Pacific Northwest National Laboratory is operated by Battelle Memorial Institute... Energy Technology Conference, Houston, Texas, pp.115-124. 7. U.S. Department of Energy. 1994. Manufacturing Consumption ofEnergy, J99J. DOEIEIA-0512(91). Washington, D. C. 8. U.S. Department of Energy. 1999. Annual Energy Outlook. 2000...

  8. Comparison of Bottom-Up and Top-Down Forecasts: Vision Industry Energy Forecasts with ITEMS and NEMS

    E-Print Network [OSTI]

    Roop, J. M.; Dahowski, R. T

    Comparisons are made of energy forecasts using results from the Industrial module of the National Energy Modeling System (NEMS) and an industrial economic-engineering model called the Industrial Technology and Energy Modeling System (ITEMS), a model...

  9. Bottom-up Representation of Industrial Energy Efficiency Technologies in Integrated Assessment Models for the Cement Sector

    E-Print Network [OSTI]

    Sathaye, J.

    2011-01-01T23:59:59.000Z

    energy-efficiency technology costs and improvementon behavioral responses, technology costs, energy savings,is to characterize technology costs and potentials for

  10. Bottom-up Representation of Industrial Energy Efficiency Technologies in Integrated Assessment Models for the Cement Sector

    E-Print Network [OSTI]

    Sathaye, J.

    2011-01-01T23:59:59.000Z

    EIA) Manufacturing Energy Consumption Survey (MECS) ModelEIA), 2005. 2002 Manufacturing Energy Consumption Survey onSurvey (MECS), such as crosscutting technologies like process controls, building controls, waste heat recovery or adjustable speed drives (EIA

  11. Assessment of Historic Trend in Mobility and Energy Use in India Transportation Sector Using Bottom-up Approach

    E-Print Network [OSTI]

    Zhou, Nan

    2010-01-01T23:59:59.000Z

    consumption reported in IEA India transportation energyin mobility, while the IEA data only shows a 1.7% growthWB, 2004). According to the IEA energy balance for India,

  12. 1999 Commercial Buildings Characteristics--Energy Sources and End Uses

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National and Regional Data; Row: NAICS8) Distribution Category UC-950 Cost and Quality of Fuels for Electric Utility PlantsEnd-Use

  13. Energy End-Use Intensities in Commercial Buildings 1992

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40CoalLease(Billion2,128 2,469DecadeOriginand Tables End-Use

  14. Development of Bottom-up Representation of Industrial Energy Efficiency Technologies in Integrated Assessment Models for the Iron and Steel Sector

    SciTech Connect (OSTI)

    Xu, T.T.; Sathaye, J.; Galitsky, C.

    2010-09-30T23:59:59.000Z

    Adoption of efficient end-use technologies is one of the key measures for reducing greenhouse gas (GHG) emissions. With the working of energy programs and policies on carbon regulation, how to effectively analyze and manage the costs associated with GHG reductions become extremely important for the industry and policy makers around the world. Energy-climate (EC) models are often used for analyzing the costs of reducing GHG emissions (e.g., carbon emission) for various emission-reduction measures, because an accurate estimation of these costs is critical for identifying and choosing optimal emission reduction measures, and for developing related policy options to accelerate market adoption and technology implementation. However, accuracies of assessing of GHG-emission reduction costs by taking into account the adoption of energy efficiency technologies will depend on how well these end-use technologies are represented in integrated assessment models (IAM) and other energy-climate models. In this report, we first conduct brief overview on different representations of end-use technologies (mitigation measures) in various energy-climate models, followed by problem statements, and a description of the basic concepts of quantifying the cost of conserved energy including integrating non-regrets options. A non-regrets option is defined as a GHG reduction option that is cost effective, without considering their additional benefits related to reducing GHG emissions. Based upon these, we develop information on costs of mitigation measures and technological change. These serve as the basis for collating the data on energy savings and costs for their future use in integrated assessment models. In addition to descriptions of the iron and steel making processes, and the mitigation measures identified in this study, the report includes tabulated databases on costs of measure implementation, energy savings, carbon-emission reduction, and lifetimes. The cost curve data on mitigation measures are available over time, which allows an estimation of technological change over a decade-long historical period. In particular, the report will describe new treatment of technological change in energy-climate modeling for this industry sector, i.e., assessing the changes in costs and energy-savings potentials via comparing 1994 and 2002 conservation supply curves. In this study, we compared the same set of mitigation measures for both 1994 and 2002 -- no additional mitigation measure for year 2002 was included due to unavailability of such data. Therefore, the estimated potentials in total energy savings and carbon reduction would most likely be more conservative for year 2002 in this study. Based upon the cost curves, the rate of change in the savings potential at a given cost can be evaluated and be used to estimate future rates of change that can be the input for energy-climate models. Through characterizing energy-efficiency technology costs and improvement potentials, we have developed and presented energy cost curves for energy efficiency measures applicable to the U.S. iron and steel industry for the years 1994 and 2002. The cost curves can change significantly under various scenarios: the baseline year, discount rate, energy intensity, production, industry structure (e.g., integrated versus secondary steel making and number of plants), efficiency (or mitigation) measures, share of iron and steel production to which the individual measures can be applied, and inclusion of other non-energy benefits. Inclusion of other non-energy benefits from implementing mitigation measures can reduce the costs of conserved energy significantly. In addition, costs of conserved energy (CCE) for individual mitigation measures increase with the increases in discount rates, resulting in a general increase in total cost of mitigation measures for implementation and operation with a higher discount rate. In 1994, integrated steel mills in the U.S. produced 55.

  15. End use energy consumption data base: transportation sector

    SciTech Connect (OSTI)

    Hooker, J.N.; Rose, A.B.; Greene, D.L.

    1980-02-01T23:59:59.000Z

    The transportation fuel and energy use estimates developed a Oak Ridge National Laboratory (ORNL) for the End Use Energy Consumption Data Base are documented. The total data base contains estimates of energy use in the United States broken down into many categories within all sectors of the economy: agriculture, mining, construction, manufacturing, commerce, the household, electric utilities, and transportation. The transportation data provided by ORNL generally cover each of the 10 years from 1967 through 1976 (occasionally 1977 and 1978), with omissions in some models. The estimtes are broken down by mode of transport, fuel, region and State, sector of the economy providing transportation, and by the use to which it is put, and, in the case of automobile and bus travel, by the income of the traveler. Fuel types include natural gas, motor and aviation gasoline, residual and diesel oil, liuqefied propane, liquefied butane, and naphtha- and kerosene-type jet engine fuels. Electricity use is also estimated. The mode, fuel, sector, and use categories themselves subsume one, two, or three levels of subcategories, resulting in a very detailed categorization and definitive accounting.

  16. Healthcare Energy End-Use Monitoring | Department of Energy

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742Energy ChinaofSchaefer To:Department of Energy Completing theWhiz!NREL partnered with two

  17. Enzyme Design From the Bottom Up: An Active Nickel Electrocatalyst...

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

    Enzyme Design From the Bottom Up: An Active Nickel Electrocatalyst with a Structured Peptide Outer Coordination Sphere. Enzyme Design From the Bottom Up: An Active Nickel...

  18. ENERGY CONSERVATION: POLICY ISSUES AND END-USE SCENARIOS OF SAVINGS POTENTIAL PT.2

    E-Print Network [OSTI]

    Authors, Various

    2011-01-01T23:59:59.000Z

    4.50 Foreign LBL 7896 ENERGY CONSERVATION: POLICY ISSUES ANDBarriers to Industrial Energy Conservation 2) The Process ofs·------------- 6. END-USE ENERGY CONSERVATION DATA BASE AND

  19. Bottom-up Representation of Industrial Energy Efficiency Technologies in Integrated Assessment Models for the U.S. Pulp and Paper Sector

    E-Print Network [OSTI]

    Xu, Tengfang

    2014-01-01T23:59:59.000Z

    Sixth Annual Industrial Energy Technology Conference, VolumeBNL). 2001. The Energy Technology Systems AnalysisKramer Environmental Energy Technologies Division July 2012

  20. Development of Bottom-up Representation of Industrial Energy Efficiency Technologies in Integrated Assessment Models for the Iron and Steel Sector

    E-Print Network [OSTI]

    Xu, T.T.

    2011-01-01T23:59:59.000Z

    Maintenance Energy monitoring and management systemMaintenance Energy monitoring and management system AppliedMaintenance Energy monitoring and management system

  1. Development of Bottom-up Representation of Industrial Energy Efficiency Technologies in Integrated Assessment Models for the Iron and Steel Sector

    E-Print Network [OSTI]

    Xu, T.T.

    2011-01-01T23:59:59.000Z

    EIA) Manufacturing Energy Consumption Survey (MECS) ModelEIA), 2005. 2002 Manufacturing Energy Consumption Survey onEIA), 2009. 2006 Manufacturing Energy Consumption Survey on

  2. India Energy Outlook: End Use Demand in India to 2020

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2009-01-01T23:59:59.000Z

    Institute, “Curbing Global Energy Demand Growth: The Energyup Assessment of Energy Demand in India Transportationa profound effect on energy demand. Policy analysts wishing

  3. India Energy Outlook: End Use Demand in India to 2020

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2009-01-01T23:59:59.000Z

    11% oil, 6% coal, and traditional energy. A survey conductedand Renewable Energy Ministry of Coal Ministry of Commerce &in Figure 10, coal represents the largest energy product

  4. India Energy Outlook: End Use Demand in India to 2020

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2009-01-01T23:59:59.000Z

    patterns of energy consumption, trends in saturation and1 shows the trend in total primary energy consumption overvalue added – energy consumption. This trend can be observed

  5. India Energy Outlook: End Use Demand in India to 2020

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2009-01-01T23:59:59.000Z

    U.S. DOE, 2006, “Buildings Energy Data Book 2006”, Septembersame period (US Buildings Energy Data Book). Over the next

  6. India Energy Outlook: End Use Demand in India to 2020

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2009-01-01T23:59:59.000Z

    nuclear hydro Energy output Own Uses Transmission and distribution loses Electricity delivered Primary factor The Agriculture

  7. India Energy Outlook: End Use Demand in India to 2020

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2009-01-01T23:59:59.000Z

    input Coal gas oil nuclear hydro Energy output Own Uses Transmission and distribution loses Electricity delivered Primary factor The Agriculture

  8. Energy End-Use Intensities in Commercial Buildings

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40Coal Stocks at1,066,688Electricity Use as an Indicator of U.S.U.S.U.S. Energy/2

  9. Energy End-Use Intensities in Commercial Buildings 1989

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40Coal Stocks at1,066,688Electricity Use as an Indicator of U.S.U.S.U.S. Energy/29

  10. Residential Lighting End-Use Consumption | Department of Energy

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn April 23, 2014, an OHASeptemberAssessments |FossilThisDepartmentDepartment ofThe U.S.

  11. Engineer End Uses for Maximum Efficiency | Department of Energy

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels DataDepartment of Energy Your Density Isn't Your Destiny:RevisedAdvisoryStandard |inHVACEnforcementEngaging Students in2

  12. Energy End-Use Intensities in Commercial Buildings 1989 -- Executive

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40CoalLease(Billion2,128 2,469DecadeOrigin

  13. Energy Information Administration - Table 2. End Uses of Fuel Consumption,

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40CoalLease(Billion2,128 2,469DecadeOriginand2003Offsite-ProducedExpenditures1998

  14. Nanowires As Building Blocks for Bottom-Up Nanotechnology

    E-Print Network [OSTI]

    Wang, Zhong L.

    #12;Nanowires As Building Blocks for Bottom-Up Nanotechnology The field of nanotechnology/or combinations of function in an integrated nanosystem. To enable this bottom-up approach for nanotechnology-dimensional (1D) nanostruc- tures at the forefront of nanoscience and nanotechnology. NWs and NBs are typi- cally

  15. Energy End-Use Intensities in Commercial Buildings 1995 - Index Page

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40CoalLease(Billion2,128 2,469DecadeOriginand Tables End-Use1995 End-Use Data

  16. Bottom-Up Top-Down 3D Human Pose Estimation Integrating Bottom-Up and Top-Down Approach from Monocular Image

    E-Print Network [OSTI]

    Takiguchi, Tetsuya

    Bottom-Up Top-Down 3 3D Human Pose Estimation Integrating Bottom-Up and Top-Down Approach from and Technology, Kobe University 2 Organization of Advanced Science and Technology 1 3 HOG 3 Bottom-up Top-down 2 3 x web [1] HOG [2] 3 3D Bottom-Up Top-Down Bottom-Up Top-Down 3.1 Bottom-Up HOG z 3 x x = Rz + (1

  17. End-use energy consumption estimates for US commercial buildings, 1989

    SciTech Connect (OSTI)

    Belzer, D.B.; Wrench, L.E.; Marsh, T.L. [Pacific Northwest Lab., Richland, WA (United States)

    1993-11-01T23:59:59.000Z

    An accurate picture of how energy is used in the nation`s stock of commercial buildings can serve a variety of program planning and policy needs within the Department of Energy, by utilities, and other groups seeking to improve the efficiency of energy use in the building sector. This report describes an estimation of energy consumption by end use based upon data from the 1989 Commercial Building Energy Consumption Survey (CBECS). The methodology used in the study combines elements of engineering simulations and statistical analysis to estimate end-use intensities for heating, cooling, ventilation, lighting, refrigeration, hot water, cooking, and miscellaneous equipment. Billing data for electricity and natural gas were first decomposed into weather and nonweather dependent loads. Subsequently, Statistical Adjusted Engineering (SAE) models were estimated by building type with annual data. The SAE models used variables such as building size, vintage, climate region, weekly operating hours, and employee density to adjust the engineering model predicted loads to the observed consumption. End-use consumption by fuel was estimated for each of the 5,876 buildings in the 1989 CBECS. The report displays the summary results for eleven separate building types as well as for the total US commercial building stock.

  18. Energy Conservation: Policy Issues and End-Use Scenarios of Savings Potential -- Part 3, Policy Barriers and Investment Decisions in Industry

    E-Print Network [OSTI]

    Benenson, Peter

    2011-01-01T23:59:59.000Z

    CONAES) and FEA End Use Energy Consumption Data Base: 1978).and FEA End Use Energy Consumption Data Base: 1978). (3)CONAES) and FEA End Use Energy Consumption Data Base: 1978).

  19. " Row: End Uses;" " Column: Energy Sources, including Net Electricity;"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocksa. Appliances byA49. Total Inputs of Energy182 End Uses8 End1.

  20. " Row: End Uses;" " Column: Energy Sources, including Net Electricity;"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocksa. Appliances byA49. Total Inputs of Energy182 End Uses8

  1. " Row: End Uses;" " Column: Energy Sources, including Net Electricity;"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocksa. Appliances byA49. Total Inputs of Energy182 End Uses85 End

  2. " Row: End Uses;" " Column: Energy Sources, including Net Electricity;"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocksa. Appliances byA49. Total Inputs of Energy182 End Uses85 End6

  3. " Row: End Uses;" " Column: Energy Sources, including Net Electricity;"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocksa. Appliances byA49. Total Inputs of Energy182 End Uses85 End65

  4. " Row: End Uses;" " Column: Energy Sources, including Net Electricity;"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocksa. Appliances byA49. Total Inputs of Energy182 End Uses85

  5. " Row: End Uses;" " Column: Energy Sources, including Net Electricity;"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocksa. Appliances byA49. Total Inputs of Energy182 End Uses855 End

  6. " Row: End Uses;" " Column: Energy Sources, including Net Electricity;"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocksa. Appliances byA49. Total Inputs of Energy182 End Uses855 End6

  7. Table E9. Total End-Use Energy Expenditure Estimates, 2012

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Energy I I' a(STEO)U.S. CoalInputsTotal Stocks4.E9. Total End-Use

  8. Large CO2 reductions via offshore wind power matched to inherent storage in energy end-uses

    E-Print Network [OSTI]

    Jacobson, Mark

    Large CO2 reductions via offshore wind power matched to inherent storage in energy end-uses Willett develop methods for assessing offshore wind resources, using a model of the vertical structure offshore wind power matched to inherent storage in energy end- uses, Geophys. Res. Lett., 34, L02817, doi

  9. Energy End-Use Intensities in Commercial Buildings 1989 data -- Publication

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40CoalLease(Billion2,128 2,469DecadeOriginand Tables End-Use Intensities

  10. Energy Demand: Limits on the Response to Higher Energy Prices in the End-Use Sectors (released in AEO2007)

    Reports and Publications (EIA)

    2007-01-01T23:59:59.000Z

    Energy consumption in the end-use demand sectorsresidential, commercial, industrial, and transportationgenerally shows only limited change when energy prices increase. Several factors that limit the sensitivity of end-use energy demand to price signals are common across the end-use sectors. For example, because energy generally is consumed in long-lived capital equipment, short-run consumer responses to changes in energy prices are limited to reductions in the use of energy services or, in a few cases, fuel switching; and because energy services affect such critical lifestyle areas as personal comfort, medical services, and travel, end-use consumers often are willing to absorb price increases rather than cut back on energy use, especially when they are uncertain whether price increases will be long-lasting. Manufacturers, on the other hand, often are able to pass along higher energy costs, especially in cases where energy inputs are a relatively minor component of production costs. In economic terms, short-run energy demand typically is inelastic, and long-run energy demand is less inelastic or moderately elastic at best.

  11. The Value of End-Use Energy Efficiency in Mitigation of U.S. Carbon Emissions

    SciTech Connect (OSTI)

    Kyle, G. Page; Smith, Steven J.; Clarke, Leon E.; Kim, Son H.; Wise, Marshall A.

    2007-11-27T23:59:59.000Z

    This report documents a scenario analysis exploring the value of advanced technologies in the U.S. buildings, industrial, and transportation sectors in stabilizing atmospheric greenhouse gas concentrations. The analysis was conducted by staff members of Pacific Northwest National Laboratory (PNNL), working at the Joint Global Change Research Institute (JGCRI) in support of the strategic planning process of the U.S. Department of Energy (U.S. DOE) Office of Energy Efficiency and Renewable Energy (EERE). The conceptual framework for the analysis is an integration of detailed buildings, industrial, and transportation modules into MiniCAM, a global integrated assessment model. The analysis is based on three technology scenarios, which differ in their assumed rates of deployment of new or presently available energy-saving technologies in the end-use sectors. These technology scenarios are explored with no carbon policy, and under two CO2 stabilization policies, in which an economic price on carbon is applied such that emissions follow prescribed trajectories leading to long-term stabilization of CO2 at roughly 450 and 550 parts per million by volume (ppmv). The costs of meeting the emissions targets prescribed by these policies are examined, and compared between technology scenarios. Relative to the reference technology scenario, advanced technologies in all three sectors reduce costs by 50% and 85% for the 450 and 550 ppmv policies, respectively. The 450 ppmv policy is more stringent and imposes higher costs than the 550 ppmv policy; as a result, the magnitude of the economic value of energy efficiency is four times greater for the 450 ppmv policy than the 550 ppmv policy. While they substantially reduce the costs of meeting emissions requirements, advanced end-use technologies do not lead to greenhouse gas stabilization without a carbon policy. This is due mostly to the effects of increasing service demands over time, the high consumption of fossil fuels in the electricity sector, and the use of unconventional feedstocks in the liquid fuel refining sector. Of the three end-use sectors, advanced transportation technologies have the greatest potential to reduce costs of meeting carbon policy requirements. Services in the buildings and industrial sectors can often be supplied by technologies that consume low-emissions fuels such as biomass or, in policy cases, electricity. Passenger transportation, in contrast, is especially unresponsive to climate policies, as the fuel costs are small compared to the time value of transportation and vehicle capital and operating costs. Delaying the transition from reference to advanced technologies by 15 years increases the costs of meeting 450 ppmv stabilization emissions requirements by 21%, but the costs are still 39% lower than the costs assuming reference technology. The report provides a detailed description of the end-use technology scenarios and provides a thorough analysis of the results. Assumptions are documented in the Appendix.

  12. Development of an Energy Savings Benchmark for All Residential End-Uses: Preprint

    SciTech Connect (OSTI)

    Hendron, R.; Anderson, R.; Christensen, C.; Eastment, M.; Reeves, P.

    2004-08-01T23:59:59.000Z

    To track progress toward aggressive multi-year whole-house energy savings goals of 40-70% and onsite power production of up to 30%, the U.S. Department of Energy (DOE) Residential Buildings Program and the National Renewable Energy Laboratory (NREL) developed the Building America Research Benchmark in 2003. The Benchmark is generally consistent with mid-1990s standard practice, as reflected in the Home Energy Rating System (HERS) Technical Guidelines, with additional definitions that allow the analyst to evaluate all residential end-uses, an extension of the traditional HERS rating approach that focuses on space conditioning and hot water. A series of user profiles, intended to represent the behavior of a''standard'' set of occupants, was created for use in conjunction with the Benchmark. Finally, a set of tools was developed by NREL and other Building America partners to help analysts compare whole-house energy use for a Prototype house to the Benchmark in a fair and consistent manner.

  13. Bottom-up graphene nanoribbon field-effect transistors

    SciTech Connect (OSTI)

    Bennett, Patrick B. [Applied Science and Technology, University of California, Berkeley, California 94720 (United States) [Applied Science and Technology, University of California, Berkeley, California 94720 (United States); Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, California 94720 (United States); Pedramrazi, Zahra [Department of Physics, University of California, Berkeley, California 94720 (United States)] [Department of Physics, University of California, Berkeley, California 94720 (United States); Madani, Ali [Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, California 94720 (United States)] [Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, California 94720 (United States); Chen, Yen-Chia; Crommie, Michael F. [Department of Physics, University of California, Berkeley, California 94720 (United States) [Department of Physics, University of California, Berkeley, California 94720 (United States); Materials Sciences Division, Lawrence Berkeley National Laboratories, Berkeley, California 94720 (United States); Oteyza, Dimas G. de [Department of Physics, University of California, Berkeley, California 94720 (United States) [Department of Physics, University of California, Berkeley, California 94720 (United States); Centro de Física de Materiales CSIC/UPV-EHU-Materials Physics Center, San Sebastián E-20018 (Spain); Chen, Chen [Department of Chemistry, University of California, Berkeley, California 94720 (United States)] [Department of Chemistry, University of California, Berkeley, California 94720 (United States); Fischer, Felix R. [Department of Chemistry, University of California, Berkeley, California 94720 (United States) [Department of Chemistry, University of California, Berkeley, California 94720 (United States); Materials Sciences Division, Lawrence Berkeley National Laboratories, Berkeley, California 94720 (United States); Bokor, Jeffrey, E-mail: jbokor@eecs.berkeley.edu [Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, California 94720 (United States) [Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, California 94720 (United States); Materials Sciences Division, Lawrence Berkeley National Laboratories, Berkeley, California 94720 (United States)

    2013-12-16T23:59:59.000Z

    Recently developed processes have enabled bottom-up chemical synthesis of graphene nanoribbons (GNRs) with precise atomic structure. These GNRs are ideal candidates for electronic devices because of their uniformity, extremely narrow width below 1?nm, atomically perfect edge structure, and desirable electronic properties. Here, we demonstrate nano-scale chemically synthesized GNR field-effect transistors, made possible by development of a reliable layer transfer process. We observe strong environmental sensitivity and unique transport behavior characteristic of sub-1?nm width GNRs.

  14. Estimates of Energy Consumption by Building Type and End Use at U.S. Army Installations

    E-Print Network [OSTI]

    Konopacki, S.J.

    2010-01-01T23:59:59.000Z

    4. Figure 5-5. 1993 Electricity Consumption Estimates by EndkWh/ft ) 1993 Electricity Consumption Estimates by End Useof Total) 1993 Electricity Consumption Estimates by End Use

  15. A Bottom-Up Approach to SUSY Analyses

    SciTech Connect (OSTI)

    Horn, Claus; /SLAC

    2011-11-11T23:59:59.000Z

    This paper proposes a new way to do event generation and analysis in searches for new physics at the LHC. An abstract notation is used to describe the new particles on a level which better corresponds to detector resolution of LHC experiments. In this way the SUSY discovery space can be decomposed into a small number of eigenmodes each with only a few parameters, which allows to investigate the SUSY parameter space in a model-independent way. By focusing on the experimental observables for each process investigated the Bottom-Up Approach allows to systematically study the boarders of the experimental efficiencies and thus to extend the sensitivity for new physics.

  16. A Bottom-Up Approach to SUSY Analyses

    E-Print Network [OSTI]

    Claus Horn

    2009-06-02T23:59:59.000Z

    This paper proposes a new way to do event generation and analysis in searches for new physics at the LHC. An abstract notation is used to describe the new particles on a level which better corresponds to detector resolution of LHC experiments. In this way the SUSY discovery space can be decomposed into a small number of eigenmodes each with only a few parameters, which allows to investigate the SUSY parameter space in a model-independent way. By focusing on the experimental observables for each process investigated the Bottom-Up Approach allows to systematically study the boarders of the experimental efficiencies and thus to extend the sensitivity for new physics.

  17. Public Health Benefits of End-Use Electrical Energy Efficiency in California: An Exploratory Study

    SciTech Connect (OSTI)

    McKone, Thomas E.; Lobscheid, A.B.

    2006-06-01T23:59:59.000Z

    This study assesses for California how increasing end-use electrical energy efficiency from installing residential insulation impacts exposures and disease burden from power-plant pollutant emissions. Installation of fiberglass attic insulation in the nearly 3 million electricity-heated homes throughout California is used as a case study. The pollutants nitrous oxides (NO{sub x}), sulfur dioxide (SO{sub 2}), fine particulate matter (PM2.5), benzo(a)pyrene, benzene, and naphthalene are selected for the assessment. Exposure is characterized separately for rural and urban environments using the CalTOX model, which is a key input to the US Environmental Protection Agency (EPA) Tool for the Reduction and Assessment of Chemicals and other environmental Impacts (TRACI). The output of CalTOX provides for urban and rural populations emissions-to-intake factors, which are expressed as an individual intake fraction (iFi). The typical iFi from power plant emissions are on the order of 10{sup -13} (g intake per g emitted) in urban and rural regions. The cumulative (rural and urban) product of emissions, population, and iFi is combined with toxic effects factors to determine human damage factors (HDFs). HDF are expressed as disability adjusted life years (DALYs) per kilogram pollutant emitted. The HDF approach is applied to the insulation case study. Upgrading existing residential insulation to US Department of Energy (DOE) recommended levels eliminates over the assmned 50-year lifetime of the insulation an estimated 1000 DALYs from power-plant emissions per million tonne (Mt) of insulation installed, mostly from the elimination of PM2.5 emissions. In comparison, the estimated burden from the manufacture of this insulation in DALYs per Mt is roughly four orders of magnitude lower than that avoided.

  18. An integrated top-down and bottom-up proteomic approach to characteriz...

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

    Publications An integrated top-down and bottom-up proteomic approach to characterize the antigen binding fragment of antibodies. An integrated top-down and bottom-up proteomic...

  19. Service Report Energy Information Administration Office of Energy Markets and End Use

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. AverageForecastEnergy

  20. Table C1. Energy Consumption Overview: Estimates by Energy Source and End-Use Sector, 2012

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Energy I I' a(STEO)U.S. Coal Stocks at Manufacturing:: Total U.S..

  1. Bottom-up, social innovation for addressing climate change Noam Bergman, University of Oxford

    E-Print Network [OSTI]

    1 Bottom-up, social innovation for addressing climate change Noam Bergman, University of Oxford and practice in the area of bottom-up, social innovation could yield benefits if integrated into wider employing new technical solutions, we identify these as warranting more research, policy and support. Bottom-up

  2. Energy Information Administration - Energy Efficiency, Table 6b-End Uses of

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40CoalLease(Billion2,128 2,469DecadeOriginand2003

  3. Energy Information Administration - Energy Efficiency-Table 6a- End uses of

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40CoalLease(Billion2,128 2,469DecadeOriginand2003Offsite-Produced Fuelof Energyfuel

  4. Energy Information Administration - Energy Efficiency-Table 6a- End uses of

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40CoalLease(Billion2,128 2,469DecadeOriginand2003Offsite-Produced Fuelof

  5. A bottom-up engineering estimate of the aggregate heating andcooling loads of the entire U.S. building stock

    SciTech Connect (OSTI)

    Huang, Yu Joe; Brodrick, Jim

    2000-08-01T23:59:59.000Z

    A recently completed project for the U.S. Department of Energy's (DOE) Office of Building Equipment combined DOE-2 results for a large set of prototypical commercial and residential buildings with data from the Energy Information Administration (EIA) residential and commercial energy consumption surveys (RECS, CBECS) to estimate the total heating and cooling loads in U.S. buildings attributable to different shell components such as windows, roofs, walls, etc., internal processes, and space-conditioning systems. This information is useful for estimating the national conservation potentials for DOE's research and market transformation activities in building energy efficiency. The prototypical building descriptions and DOE-2 input files were developed from 1986 to 1992 to provide benchmark hourly building loads for the Gas Research Institute (GRI) and include 112 single-family, 66 multi-family, and 481 commercial building prototypes. The DOE study consisted of two distinct tasks : (1) perform DOE-2 simulations for the prototypical buildings and develop methods to extract the heating and cooling loads attributable to the different building components; and (2) estimate the number of buildings or floor area represented by each prototypical building based on EIA survey information. These building stock data were then multiplied by the simulated component loads to derive aggregated totals by region, vintage, and building type. The heating and cooling energy consumption of the national building stock estimated by this bottom-up engineering approach was found to agree reasonably well with estimates from other sources, although significant differences were found for certain end-uses. The main added value from this study, however, is the insight it provides about the contributing factors behind this energy consumption, and what energy savings can be expected from efficiency improvements for different building components by region, vintage, and building type.

  6. 2 Large CO2 reductions via offshore wind power matched to inherent 3 storage in energy end-uses

    E-Print Network [OSTI]

    Firestone, Jeremy

    2 Large CO2 reductions via offshore wind power matched to inherent 3 storage in energy end-uses 4] We develop methods for assessing offshore wind 9 resources, using a model of the vertical structure. Dhanju, R. W. 26 Garvine, and M. Z. Jacobson (2007), Large CO2 reductions via 27 offshore wind power

  7. Architectures built using bottom-up self-assembly of nanoelectronic devices will need to tolerate defect rates that

    E-Print Network [OSTI]

    Sorin, Daniel J.

    in the lithography process, the high energy associated with shorter wavelengths and the accuracy needed to fabricate1 Abstract Architectures built using bottom-up self-assembly of nanoelectronic devices will need isolation. Simulations show that, for a fail-stop model of node failure, the broadcast connects all nodes

  8. Architectures built using bottom-up self-assembly of nanoelectronic devices will need to tolerate defect rates that

    E-Print Network [OSTI]

    Dwyer, Chris

    in the lithography process, the high energy associated with shorter wavelengths and the accuracy needed to fabricateAbstract Architectures built using bottom-up self-assembly of nanoelectronic devices will need isolation. Simulations show that, for a fail-stop model of node failure, the broadcast connects all nodes

  9. ENERGY CONSERVATION: POLICY ISSUES AND END-USE SCENARIOS OF SAVINGS POTENTIAL PT.1

    E-Print Network [OSTI]

    Authors, Various

    2011-01-01T23:59:59.000Z

    savings due to energy conservation. This report was done4.50 Foreign LBL 7896 ENERGY CONSERVATION: POLICY ISSUES ANDBarriere to Industrial Energy Conservation 2) The Process of

  10. Public Health Benefits of End-Use Electrical Energy Efficiency in California: An Exploratory Study

    E-Print Network [OSTI]

    McKone, Thomas E.

    2011-01-01T23:59:59.000Z

    IECC: International Energy Conservation Code iFi: individualmeet the International Energy Conservation Code (IECC 2000)meet the International Energy Conservation Code (IECe) 2000

  11. INTERNATIONAL RESIDENTIAL ENERGY END USE DATA: ANALYSIS OF HISTORICAL AND PRESENT DAY STRUCTURE AND DYNAMICS

    E-Print Network [OSTI]

    Schipper, Lee

    2013-01-01T23:59:59.000Z

    J. , 1979. niske Hoejsko1e. Energi og Husholdninger. Lyngby:Ministry of Housing), 16) Energi NM (A Bi11 of Swedish

  12. A new bottom-up search method for determining all maximal efficient ...

    E-Print Network [OSTI]

    Ta Van Tu

    2014-11-04T23:59:59.000Z

    Nov 4, 2014 ... Abstract: Bottom-up search methods for determining the efficient set of a multiple objective linear programming (MOLP) problem have a ...

  13. An integrated top-down and bottom-up proteomic approach to characteriz...

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

    approach to characterize the antigen binding fragment of antibodies. An integrated top-down and bottom-up proteomic approach to characterize the antigen binding fragment of...

  14. art bottom-up methods: Topics by E-print Network

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

    liquor Moutai, or a clever counterfeit. Moutai has been dubbed the "national wine... Hacker, Randi; Boyd, David 2011-03-30 2 introduction videogame stimuli bottom-up...

  15. Mesoscale regulation comes from the bottom-up: intertidal interactions between consumers

    E-Print Network [OSTI]

    Nielsen, Karina J.

    REPORT Mesoscale regulation comes from the bottom-up: intertidal interactions between consumers variation in nutrient supply to shift community structure over mesoscales. Keywords Macroalgae, upwelling

  16. Control Limits for Building Energy End Use Based on Engineering Judgment, Frequency Analysis, and Quantile Regression

    SciTech Connect (OSTI)

    Henze, G. P.; Pless, S.; Petersen, A.; Long, N.; Scambos, A. T.

    2014-02-01T23:59:59.000Z

    Approaches are needed to continuously characterize the energy performance of commercial buildings to allow for (1) timely response to excess energy use by building operators; and (2) building occupants to develop energy awareness and to actively engage in reducing energy use. Energy information systems, often involving graphical dashboards, are gaining popularity in presenting energy performance metrics to occupants and operators in a (near) real-time fashion. Such an energy information system, called Building Agent, has been developed at NREL and incorporates a dashboard for public display. Each building is, by virtue of its purpose, location, and construction, unique. Thus, assessing building energy performance is possible only in a relative sense, as comparison of absolute energy use out of context is not meaningful. In some cases, performance can be judged relative to average performance of comparable buildings. However, in cases of high-performance building designs, such as NREL's Research Support Facility (RSF) discussed in this report, relative performance is meaningful only when compared to historical performance of the facility or to a theoretical maximum performance of the facility as estimated through detailed building energy modeling.

  17. ENERGY CONSERVATION: POLICY ISSUES AND END-USE SCENARIOS OF SAVINGS POTENTIAL PT.2

    E-Print Network [OSTI]

    Authors, Various

    2011-01-01T23:59:59.000Z

    Comprehensive Studies of Solid Waste Disposal," Chapter6 ofSystems for Municipal Solid Waste A Technical/EconomicDerivatives from Municipal Solid Waste. In Energy from Solid

  18. Healthcare Energy: Using End-Use Data to Inform Decisions | Department of

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742Energy ChinaofSchaefer To:Department of Energy Completing theWhiz!NRELEnergy See below

  19. Service Report Enwgy Information Administration Office of Energy Markets and End Use

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. AverageForecastEnergyEnwgy

  20. Manufacturing Consumption of Energy 1994 - Derived measures of end-use

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade EnergyTennesseeYearUnderground Storage1 Energy Informationeialogo

  1. Assessment of U.S. Electric End-Use Energy Efficiency Potential

    SciTech Connect (OSTI)

    Gellings, Clark W.; Wikler, Greg; Ghosh, Debyani

    2006-11-15T23:59:59.000Z

    Demand-side management holds significant potential to reduce growth in U.S. energy consumption and peak demand, and in a cost-effective manner. But significant policy interventions will be required to achieve these benefits. (author)

  2. Energy End-Use Intensities in Commercial Buildings 1992 - Index Page

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40Coal Stocks at1,066,688Electricity Use as an Indicator of U.S.U.S.U.S. Energy/292

  3. Table C4. Total End-Use Energy Consumption Estimates, 2012

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Energy I I' a(STEO)U.S. Coal Stocks at Manufacturing:: TotalC4. Total

  4. Table E2. Total End-Use Energy Price Estimates, 2012

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Energy I I' a(STEO)U.S. CoalInputsTotal Stocks4. Electric Power6.E2.

  5. "Table B25. Energy End Uses, Floorspace for Non-Mall Buildings, 2003"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocksa. AppliancesTotal"1" "Shell Storage1.2.5.

  6. Level: National and Regional Data; Row: End Uses; Column: Energy Sources, including Net Demand for Electricity;

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade EnergyTennesseeYear Jan Next MECS will be fielded in 2015 Table 8.4337

  7. Level: National and Regional Data; Row: End Uses; Column: Energy Sources, including Net Demand for Electricity;

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade EnergyTennesseeYear Jan Next MECS will be fielded in 2015 Table 8.4337

  8. Level: National and Regional Data; Row: End Uses; Column: Energy Sources, including Net Electricity;

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade EnergyTennesseeYear Jan Next MECS will be fielded in 2015 Table

  9. Level: National and Regional Data; Row: End Uses; Column: Energy Sources, including Net Electricity;

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade EnergyTennesseeYear Jan Next MECS will be fielded in 2015 Table6 End

  10. Letter Report on Testing of Distributed Energy Resource, Microgrid, and End-Use

    E-Print Network [OSTI]

    the same support to the grid. Figure 1 indicates that 1 MW of storage (provided by a battery or ramping as an Enabling Technology. Subtask 8.2: Use of Hydrogen for Energy Storage Under this subtask, HNEI evaluated the use of hydrogen as part of an integrated storage system with emphasis on the use of hydrogen

  11. Understanding Superconducting Magnetic Energy Storage (SMES) technology, applications, and economics, for end-use workshop

    SciTech Connect (OSTI)

    Ferraro, R.J. [Ferraro, Oliver, and Associates, Inc., Knoxville, TN (United States); McConnell, B.W. [Oak Ridge National Lab., TN (United States)

    1993-06-01T23:59:59.000Z

    The overall objective of this project was to determine the state-of-the-art and to what extent existing SMES is a viable option in meeting the needs of utilities and their customers for improving electric service power quality. By defining and analyzing SMES electrical/mechanical performance characteristics, and comparing SMES application benefits with competitive stored energy systems, industry will be able to determine SMES unique applications and potential market penetration. Building on this information base, it would also be possible to evaluate the impact of high temperature superconductors (77 K and 20-35 K) on SMES technology applications. The authors of this report constructed a network of industry contacts and research consultants that were used to collect, update, and analyze ongoing SMES R&D and marketing activities in industries, utilities, and equipment manufacturers. These key resources were utilized to assemble performance characteristics on existing SMES, battery, capacitor, flywheel, and high temperature superconductor (HTS) stored energy technologies. From this information, preliminary stored energy system comparisons were accomplished. In this way, the electric load needs would be readily comparable to the potential solutions and applications offered by each aforementioned energy storage technology.

  12. Level: National Data; Row: End Uses within NAICS Codes; Column: Energy Sources, including Net Electricity;

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40Coal StocksProved Reserves (Billion Cubic Feet)Wellhead0 Capability to.54 End1

  13. Level: National Data; Row: End Uses within NAICS Codes; Column: Energy Sources, including Net Electricity;

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40Coal StocksProved Reserves (Billion Cubic Feet)Wellhead0 Capability to.54 End12

  14. CBECS 1989 - Energy End-use Intensities in Commercial Buildings -- Detailed

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40CoalLease(Billion2,128 2,469 2,321 2,590 1,550 1,460 1977-2013164 167

  15. The evolution of carbon dioxide emissions from energy use in industrialized countries: an end-use analysis

    SciTech Connect (OSTI)

    Schipper, L.; Ting, M.; Khrushch, M.; Unander, F.; Monahan, P.; Golove, W.

    1996-08-01T23:59:59.000Z

    There has been much attention drawn to plans for reductions or restraint in future C02 emissions, yet little analysis of the recent history of those emissions by end use or economic activity. Understanding the components of C02 emissions, particularly those related to combustion of fossil fuels, is important for judging the likely success of plans for dealing with future emissions. Knowing how fuel switching, changes in economic activity and its structure, or changes in energy-use efficiency affected emissions in the past, we can better judge both the realism of national proposals to restrain future emissions and the outcome as well. This study presents a first step in that analysis. The organization of this paper is as follows. We present a brief background and summarize previous work analyzing changes in energy use using the factorial method. We then describe our data sources and method. We then present a series of summary results, including a comparison of C02 emissions in 1991 by end use or sector. We show both aggregate change and change broken down by factor, highlighting briefly the main components of change. We then present detailed results, sector by sector. Next we highlight recent trends. Finally, we integrate our results, discussing -the most important factors driving change - evolution in economic structure, changes in energy intensities, and shifts in the fuel mix. We discuss briefly some of the likely causes of these changes - long- term technological changes, effects of rising incomes, the impact of overall changes in energy prices, as well as changes in the relative prices of energy forms.

  16. Top-down modification of bottom-up processes: selective grazing reduces macroalgal nitrogen uptake

    E-Print Network [OSTI]

    Bracken, MES; Stachowicz, J J

    2007-01-01T23:59:59.000Z

    flow and clear plastic tops to maximize light penetration.RC, Kohrs DG, Alberte RS (1996) Top-down im- pact through aSer Published January 25 Top-down modification of bottom-up

  17. When Top-Down Meets Bottom-Up: Auditory Training Enhances VerbalMemory in Schizophrenia

    E-Print Network [OSTI]

    Vinogradov, Sophia

    2009-01-01T23:59:59.000Z

    September 10, 2009 When Top-Down Meets Bottom-Up: Auditorynot only the higher order or ‘‘top-down’’ processes of cog-representations as well as ‘‘top-down’’ attention and

  18. Bottom-Up and Top-Down Processes in Emotion Generation: Common and Distinct Neural Mechanisms

    E-Print Network [OSTI]

    Ochsner, Kevin N.

    Emotions are generally thought to arise through the interaction of bottom-up and top-down processes. However, prior work has not delineated their relative contributions. In a sample of 20 females, we used functional magnetic ...

  19. Some recent advances in the bottom-up holographic approach to QCD

    SciTech Connect (OSTI)

    Afonin, S. S. [Saint Petersburg State University, 1 ul. Ulyanovskaya, St. Petersburg, 198504 (Russian Federation)

    2014-07-23T23:59:59.000Z

    We give a brief report on our recent results in the bottom-up holographic approach to QCD. The holographic description of the heavy vector quarkonia and generalization of the Soft Wall model are discussed.

  20. Assembly of a Molecular Needle, from the Bottom Up

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office511041cloth DocumentationProductsAlternativeOperational Management »EnergyHubs | Department of

  1. Assembly of a Molecular Needle, from the Bottom Up

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office511041cloth DocumentationProductsAlternativeOperational Management »EnergyHubs | Department ofAssembly of

  2. Assembly of a Molecular Needle, from the Bottom Up

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office511041cloth DocumentationProductsAlternativeOperational Management »EnergyHubs | Department ofAssembly

  3. Assembly of a Molecular Needle, from the Bottom Up

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office511041cloth DocumentationProductsAlternativeOperational Management »EnergyHubs | Department

  4. Assembly of a Molecular Needle, from the Bottom Up

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625govInstrumentstdmadapInactiveVisiting the TWP TWPAlumni AlumniFederalAshley Boyle AdministrativeAssembly of a

  5. Energy Conservation: Policy Issues and End-Use Scenarios of Savings Potential -- Part 4, Energy Efficient Recreational Travel

    E-Print Network [OSTI]

    Cornwall, B.

    2011-01-01T23:59:59.000Z

    Recreation Planning for Energy Conservation. Ecology, VolumeRecreation Planning for Energy Conservation. Inter- nationalMicrofiche, LBL 7896 ENERGY CONSERVATION: POLICY ISSUES AND

  6. The $m$'bottom-up parton system with two momentum scales

    E-Print Network [OSTI]

    Khachatryan, Vladimir; Hemmick, Thomas K

    2015-01-01T23:59:59.000Z

    One possible evolutionary scenario of the dense gluon system produced in an ultrarelativistic heavy ion collision is the bottom-up thermalization scenario, which describes the dynamics of the system shortly after the collision via the decay of originally produced hard gluons to soft ones through QCD branching processes. The soft gluons form a thermal bath that subsequently reaches thermalization and/or equilibration. There is a scaling solution to the bottom-up problem that interpolates between its early stage, which has a highly anisotropic gluon distribution, and its final stage of equilibration which occurs later. Such a solution depends on a single parameter, the so called momentum asymmetry parameter $\\delta$. With this scaling solution, the bottom-up scenario gets modified and the evolving parton system, referred to as the $m$'bottom-up parton system throughout this paper, is described by this modification. The time evolution of the system in the original bottom-up ansatz is driven by the saturation sca...

  7. Bottom-up isotropization in classical-statistical lattice gauge theory

    E-Print Network [OSTI]

    J. Berges; S. Scheffler; D. Sexty

    2008-01-11T23:59:59.000Z

    We compute nonequilibrium dynamics for classical-statistical SU(2) pure gauge theory on a lattice. We consider anisotropic initial conditions with high occupation numbers in the transverse plane on a characteristic scale ~ Q_s. This is used to investigate the very early stages of the thermalization process in the context of heavy-ion collisions. We find Weibel or "primary" instabilities with growth rates similar to those obtained from previous treatments employing anisotropic distributions of hard modes (particles) in the weak coupling limit. We observe "secondary" growth rates for higher-momentum modes reaching substantially larger values and we analyse them in terms of resummed loop diagrams beyond the hard-loop approximation. We find that a coarse grained pressure isotropizes "bottom-up" with a characteristic inverse rate of gamma^{-1} ~ 1 - 2 fm/c for coarse graining momentum scales of p energy density for RHIC of epsilon = 30 GeV/fm^3. The nonequilibrium spatial Wilson loop is found to exhibit an area law and to become isotropic on a similar time scale.

  8. Energy Implications of Minienvironment in Clean Spaces: A Case Study on Minienvironment Energy End-use and Performance

    E-Print Network [OSTI]

    Xu, Tengfang

    2005-01-01T23:59:59.000Z

    supported by the Assistant Secretary for Energy Efficiencyand Renewable Energy, Office of Building Technology, State,of the U.S. Department of Energy under Contract No. DE-AC02-

  9. Integrated estimation of commercial sector end-use load shapes and energy use intensities in the PG&E service area

    SciTech Connect (OSTI)

    Akbari, H.; Eto, J.; Konopacki, S.; Afzal, A.; Heinemeier, K.; Rainer, L.

    1993-12-01T23:59:59.000Z

    This project represents a unique research effort to address the commercial sector end-use energy forecasting data needs of the Pacific Gas and Electric Company (PG&E) and the California Energy Commission (CEC). The object of the project was to develop an updated set of commercial sector end-use energy use intensity (EUI) data that has been fully reconciled with measured data. The research was conducted in two stages. First, we developed reconciled electricity end-use EUIs and load shapes for each of the 11 building types in the inland and coastal regions of the PG&E service territory using information collected in 1986. Second, we developed procedures to translate these results into a consistent set of commercial sector forecasting model inputs recognizing the separate modeling conventions used by PG&E and CEC. EUIs have been developed for: II commercial building types; up to 10 end uses; up to 3 fuel types; 2 and 5 subservice territory forecasting regions (as specified by the PG&E and CEC forecasting models, respectively); and up to 2 distinct vintages corresponding to the period prior to and immediately following the adoption of the first generation of California building and equipment standards. For the electricity end uses, 36 sets of daily load shapes have been developed representing average weekday, average weekend, and peak weekday electricity use for each month of the year by building type for both the inland and coastal climate zones.

  10. An integrated top-down and bottom-up strategy for characterization protein isoforms and modifications

    SciTech Connect (OSTI)

    Wu, Si; Tolic, Nikola; Tian, Zhixin; Robinson, Errol W.; Pasa-Tolic, Ljiljana

    2011-04-15T23:59:59.000Z

    Bottom-up and top-down strategies are two commonly used methods for mass spectrometry (MS) based protein identification; each method has its own advantages and disadvantages. In this chapter, we describe an integrated top-down and bottom-up approach facilitated by concurrent liquid chromatography-mass spectrometry (LC-MS) analysis and fraction collection for comprehensive high-throughput intact protein profiling. The approach employs a high resolution reversed phase (RP) LC separation coupled with LC eluent fraction collection and concurrent on-line MS with a high field (12 Tesla) Fourier-transform ion cyclotron resonance (FTICR) mass spectrometer. Protein elusion profiles and tentative modified protein identification are made using detected intact protein mass in conjunction with bottom-up protein identifications from the enzymatic digestion and analysis of corresponding LC fractions. Specific proteins of biological interest are incorporated into a target ion list for subsequent off-line gas-phase fragmentation that uses an aliquot of the original collected LC fraction, an aliquot of which was also used for bottom-up analysis.

  11. A bottom-up analysis of including aviation within theEU's Emissions Trading Scheme

    E-Print Network [OSTI]

    Watson, Andrew

    A bottom-up analysis of including aviation within theEU's Emissions Trading Scheme Alice Bows-up analysis of including aviation within the EU's Emissions Trading Scheme Alice Bows & Kevin Anderson Tyndall's emissions trading scheme. Results indicate that unless the scheme adopts both an early baseline year

  12. TOP-DOWN/BOTTOM-UP APPROACH FOR DEVELOPING SUSTAINABLE DEVELOPMENT INDICATORS FOR MINING

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    1 TOP-DOWN/BOTTOM-UP APPROACH FOR DEVELOPING SUSTAINABLE DEVELOPMENT INDICATORS FOR MINING: APPLICATION TO THE ARLIT URANIUM MINES (NIGER) A. Chamareta)b) , M. O'Connor a) and G. Récoché b) a indicators for assessing impacts and performances of mining sites thus appears necessary to inform

  13. Bottom-up and top-down emotion generation: implications for emotion regulation

    E-Print Network [OSTI]

    Gross, James J.

    Bottom-up and top-down emotion generation: implications for emotion regulation Kateri McRae,1, The University of Denver, Denver, CO 80209 and 2 Stanford University, Stanford, CA, USA Emotion regulation plays a crucial role in adaptive functioning and mounting evidence suggests that some emotion regulation

  14. Top-down and bottom-up diversity cascades in detrital vs. living food webs

    E-Print Network [OSTI]

    Dyer, Lee

    REPORT Top-down and bottom-up diversity cascades in detrital vs. living food webs Lee A. Dyer1 for maintaining diversity in biotic communities, but the indirect (ÔcascadingÕ) effects of top-down and bottom in decomposer food webs. We measured effects of top predators and plant resources on the diversity of endophytic

  15. Top-down versus bottom-up learning in cognitive skill acquisition

    E-Print Network [OSTI]

    Varela, Carlos

    Top-down versus bottom-up learning in cognitive skill acquisition Action editor: Vasant Honavar Ron between implicit and explicit processes during skill learning, in terms of top-down learning (that is learning that takes into account both implicit and explicit processes and both top-down and bottom

  16. End-use taxes: Current EIA practices

    SciTech Connect (OSTI)

    Not Available

    1994-08-17T23:59:59.000Z

    There are inconsistencies in the EIA published end-use price data with respect to Federal, state, and local government sales and excise taxes; some publications include end-use taxes and others do not. The reason for including these taxes in end-use energy prices is to provide consistent and accurate information on the total cost of energy purchased by the final consumer. Preliminary estimates are made of the effect on prices (bias) reported in SEPER (State Energy Price and Expenditure Report) resulting from the inconsistent treatment of taxes. EIA has undertaken several actions to enhance the reporting of end-use energy prices.

  17. Power applications of high-temperature superconductivity: Variable speed motors, current switches, and energy storage for end use

    SciTech Connect (OSTI)

    Hawsey, R.A. [Oak Ridge National Lab., TN (United States); Banerjee, B.B.; Grant, P.M. [Electric Power Research Inst., Palo Alto, CA (United States)

    1996-08-01T23:59:59.000Z

    The objective of this project is to conduct joint research and development activities related to certain electric power applications of high-temperature superconductivity (HTS). The new superconductors may allow development of an energy-efficient switch to control current to variable speed motors, superconducting magnetic energy storage (SMES) systems, and other power conversion equipment. Motor types that were considered include induction, permanent magnet, and superconducting ac motors. Because it is impractical to experimentally alter certain key design elements in radial-gap motors, experiments were conducted on an axial field superconducting motor prototype using 4 NbTi magnets. Superconducting magnetic energy storage technology with 0.25--5 kWh stored energy was studied as a viable solution to short duration voltage sag problems on the customer side of the electric meter. The technical performance characteristics of the device wee assembled, along with competing technologies such as active power line conditioners with storage, battery-based uninterruptible power supplies, and supercapacitors, and the market potential for SMES was defined. Four reports were prepared summarizing the results of the project.

  18. Level: National Data; Row: End Uses within NAICS Codes; Column: Energy Sources, including Net Demand for Electricity;

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40Coal StocksProved Reserves (Billion Cubic Feet)Wellhead0 Capability to.5

  19. Level: National Data; Row: End Uses within NAICS Codes; Column: Energy Sources, including Net Demand for Electricity;

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40Coal StocksProved Reserves (Billion Cubic Feet)Wellhead0 Capability to.54 End

  20. TOP-DOWN AND BOTTOM-UP EFFECTS IN A DETRITAL FOOD WEB: THE PITCHER PLANT INQUILINE COMMUNITY AS A MODEL FOOD WEB

    E-Print Network [OSTI]

    Notre Dame, University of

    TOP-DOWN AND BOTTOM-UP EFFECTS IN A DETRITAL FOOD WEB: THE PITCHER PLANT INQUILINE COMMUNITY;TOP-DOWN AND BOTTOM-UP EFFECTS IN A DETRITAL FOOD WEB: THE PITCHER PLANT INQUILINE COMMUNITY that regulate food web dynamics. Both top-down and bottom-up forces affect populations within a food web

  1. Energy Conservation Policy Issues and End-Use Scenarios of Savings Potential--Part 5. Energy Efficient Buildings: The Cause of Litigation Against Energy Conservation Building Codes

    E-Print Network [OSTI]

    Benenson, P.

    2011-01-01T23:59:59.000Z

    LITIGATION AGAINST ENERGY CONSERVATION BUILDING CODES I TWO-OF LITIGATION AGAINST ENERGY CONSERVATION BUILDING CODESDIFFERENT PURPOSES OF ENERGY CONSERVATION BUILDING CODES B.

  2. Energy Conservation Policy Issues and End-Use Scenarios of Savings Potential--Part 5. Energy Efficient Buildings: The Cause of Litigation Against Energy Conservation Building Codes

    E-Print Network [OSTI]

    Benenson, P.

    2011-01-01T23:59:59.000Z

    Impact Evaluation of New York State Energy Code (ASHRAE 90-N.Y. , N.Y. : New York State Energy Research and DevelopmentJ. "New York Puts Together Its Own State Energy Policy and

  3. Energy Conservation Policy Issues and End-Use Scenarios of Savings Potential--Part 5. Energy Efficient Buildings: The Cause of Litigation Against Energy Conservation Building Codes

    E-Print Network [OSTI]

    Benenson, P.

    2011-01-01T23:59:59.000Z

    could be persuaded that energy efficient design is a "good"energy savings (Cochran 1978:4). More efficient techniques would include improved conservation methods or passive solar designs.

  4. Energy Conservation Policy Issues and End-Use Scenarios of Savings Potential--Part 5. Energy Efficient Buildings: The Cause of Litigation Against Energy Conservation Building Codes

    E-Print Network [OSTI]

    Benenson, P.

    2011-01-01T23:59:59.000Z

    C. RECOMMENDATIONS MAKE CODES TRULY PERFORMANCE BASED WORKENERGY CONSERVATION BUILDING CODES I TWO-WEEK LOAN COPY I iENERGY CONSERVATION BUILDING CODES INTRODUCTION DIFFERENT

  5. A Top-down and Bottom-up look at Emissions Abatement in Germany in response to the EU ETS

    E-Print Network [OSTI]

    Feilhauer, Stephan M. (Stephan Marvin)

    2008-01-01T23:59:59.000Z

    This paper uses top-down trend analysis and a bottom-up power sector model to define upper and lower boundaries on abatement in Germany in the first phase of the EU Emissions Trading Scheme (2005-2007). Long-term trend ...

  6. Teaching application-orientated mathematics and developing didactic from the bottom up Regina Puscher and Rdiger Vernay

    E-Print Network [OSTI]

    Spagnolo, Filippo

    261 Teaching application-orientated mathematics and developing didactic from the bottom up Regina the possibilities of didactic development from the bottom, from the work of practising teachers, and illustrate of the MUED the latest developements in math-didactics can be discussed from the view of schoolteachers

  7. Top-Down versus Bottom-Up Learning in Skill Acquisition Ron Sun (rsun@cecs.missouri.edu)

    E-Print Network [OSTI]

    Varela, Carlos

    Top-Down versus Bottom-Up Learning in Skill Acquisition Ron Sun (rsun@cecs.missouri.edu) Xi Zhang This paper studies the interaction between implicit and explicit processes in skill learning, in terms of top of skill learning that takes into account both im- plicit and explicit processes and both top

  8. A Bottom-Up Approach to Verification of Hybrid Model-Based Hierarchical Controllers with application to Underwater Vehicles

    E-Print Network [OSTI]

    Kumar, Ratnesh

    A Bottom-Up Approach to Verification of Hybrid Model-Based Hierarchical Controllers with application to Underwater Vehicles M. O'Connor, S. Tangirala, R. Kumar, S. Bhattacharyya, M. Sznaier and L.E. Holloway Abstract -- We present a systematic method of verification for a hierarchical hybrid system

  9. www.sciencemag.org SCIENCE VOL 313 22 SEPTEMBER 2006 1737 Top-Down Vs. Bottom-Up

    E-Print Network [OSTI]

    Edwards, Matthew

    for nutrients or pri- mary production in nearshore kelp forests and despite evidence to the contrary [e.g., (9www.sciencemag.org SCIENCE VOL 313 22 SEPTEMBER 2006 1737 Top-Down Vs. Bottom-Up Effects in Kelp Forests IN THEIR REPORT "STRONG TOP-DOWN CON- trol in southern California kelp forest ecosystems" (26 May

  10. A Bottom up Approach to on-Road CO2 Emissions Estimates: Improved Spatial Accuracy and Applications for Regional Planning

    E-Print Network [OSTI]

    Hutyra, Lucy R.

    component of vehicle greenhouse gas (GHG) emissions is CO2 generated by the combustion of motor gasoline and diesel fuel. CO2 emissions contribute to global climate change,2 but the United States has yetA Bottom up Approach to on-Road CO2 Emissions Estimates: Improved Spatial Accuracy and Applications

  11. Representing energy technologies in top-down economic models using bottom-up information

    E-Print Network [OSTI]

    example (e.g., a 500 megawatt coal fired power plant, or a 1-MW wind turbine). The technologies production may be treated as a single sector with capital, labor, material, and fuel inputs. Continuous

  12. An integrated top-down and bottom-up proteomic approach to characterize the antigen binding fragment of antibodies

    SciTech Connect (OSTI)

    Dekker, Leendert J.; Wu, Si; vanDuijn, Martijn M.; Tolic, Nikola; Stingl, Christoph; Zhao, Rui; Luider, Theo N.; Pasa-Tolic, Ljiljana

    2014-05-31T23:59:59.000Z

    We have previously shown that different individuals exposed to the same antigen produce antibodies with identical mutations in their complementarity determining regions (CDR), suggesting that CDR tryptic peptides can serve as biomarkers for disease diagnosis and prognosis. Complete Fabs derived from disease specific antibodies have even higher potential; they could potentially be used for disease treatment and are required to identify the antigens towards which the antibodies are directed. However, complete Fab sequence characterization via LC-MS analysis of tryptic peptides (i.e. bottom-up) has proven to be impractical for mixtures of antibodies. To tackle this challenge, we have developed an integrated bottom-up and top-down MS approach, employing 2D chromatography coupled with Fourier transform mass spectrometry (FTMS), and applied this approach for full characterization of the variable parts of two pharmaceutical monoclonal antibodies with sensitivity comparable to the bottom-up standard. These efforts represent an essential step towards the identification of disease specific antibodies in patient samples with potentially significant clinical impact.

  13. Benchmarking Non-Hardware Balance-of-System (Soft) Costs for U.S. Photovoltaic Systems, Using a Bottom-Up Approach and Installer Survey - Second Edition

    SciTech Connect (OSTI)

    Friedman, B.; Ardani, K.; Feldman, D.; Citron, R.; Margolis, R.; Zuboy, J.

    2013-10-01T23:59:59.000Z

    This report presents results from the second U.S. Department of Energy (DOE) sponsored, bottom-up data-collection and analysis of non-hardware balance-of-system costs -- often referred to as 'business process' or 'soft' costs -- for U.S. residential and commercial photovoltaic (PV) systems. In service to DOE's SunShot Initiative, annual expenditure and labor-hour-productivity data are analyzed to benchmark 2012 soft costs related to (1) customer acquisition and system design (2) permitting, inspection, and interconnection (PII). We also include an in-depth analysis of costs related to financing, overhead, and profit. Soft costs are both a major challenge and a major opportunity for reducing PV system prices and stimulating SunShot-level PV deployment in the United States. The data and analysis in this series of benchmarking reports are a step toward the more detailed understanding of PV soft costs required to track and accelerate these price reductions.

  14. " Row: End Uses;"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocksa. Appliances byA49. Total Inputs of Energy182 End Uses of4

  15. " Row: End Uses;"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocksa. Appliances byA49. Total Inputs of Energy182 End Uses of47

  16. " Row: End Uses;"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocksa. Appliances byA49. Total Inputs of Energy182 End Uses of478

  17. " Row: End Uses;"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocksa. Appliances byA49. Total Inputs of Energy182 End Uses of4787

  18. " Row: End Uses;"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocksa. Appliances byA49. Total Inputs of Energy182 End Uses of47878

  19. " Row: End Uses;"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocksa. Appliances byA49. Total Inputs of Energy182 End Uses

  20. " Row: End Uses;"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocksa. Appliances byA49. Total Inputs of Energy182 End Uses8 End

  1. Biomass Resource Allocation among Competing End Uses

    SciTech Connect (OSTI)

    Newes, E.; Bush, B.; Inman, D.; Lin, Y.; Mai, T.; Martinez, A.; Mulcahy, D.; Short, W.; Simpkins, T.; Uriarte, C.; Peck, C.

    2012-05-01T23:59:59.000Z

    The Biomass Scenario Model (BSM) is a system dynamics model developed by the U.S. Department of Energy as a tool to better understand the interaction of complex policies and their potential effects on the biofuels industry in the United States. However, it does not currently have the capability to account for allocation of biomass resources among the various end uses, which limits its utilization in analysis of policies that target biomass uses outside the biofuels industry. This report provides a more holistic understanding of the dynamics surrounding the allocation of biomass among uses that include traditional use, wood pellet exports, bio-based products and bioproducts, biopower, and biofuels by (1) highlighting the methods used in existing models' treatments of competition for biomass resources; (2) identifying coverage and gaps in industry data regarding the competing end uses; and (3) exploring options for developing models of biomass allocation that could be integrated with the BSM to actively exchange and incorporate relevant information.

  2. Exurbia from the bottom-up: Confronting empirical challenges to characterizing a complex system

    E-Print Network [OSTI]

    Illinois at Chicago, University of

    (Hansen et al., 2005), and material and energy flows such as carbon sequestration (Pickett et al., 2001

  3. A Bottom-Up Cost Analysis of a High Concentration PV Module ...

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

    France 13-15 April 2015 2 Analysis Disclaimer DISCLAIMER AGREEMENT These manufacturing cost model results ("Data") are provided by the National Renewable Energy Laboratory...

  4. Energy Conservation: Policy Issues and End-Use Scenarios of Savings Potential -- Part 3, Policy Barriers and Investment Decisions in Industry

    E-Print Network [OSTI]

    Benenson, Peter

    2011-01-01T23:59:59.000Z

    Ct3_ 3.of 6 UC-95c ENERGY CONSERVATION: POLICY ISSUES ANDBARRIERS TO INDUSTRIAL ENERGY CONSERVATION I. II. III.. IV.II. RETROFIT OF ENERGY CONSERVATION EQUIPMENT A. CONCEPT

  5. Humans Strengthen Bottom-Up Effects and Weaken Trophic Cascades in a Terrestrial Food Web

    E-Print Network [OSTI]

    Hebblewhite, Mark

    of Canada, Shell Canada, the Institute for Sustainable Energy, Environment and Economy, the Canadian.pone.0064311 Editor: Jon Moen, Umea University, Sweden Received December 31, 2012; Accepted April 11, 2013 Association, Alberta Tourism, Parks and Recreation, Alberta Sustainable Resource Development, Alberta

  6. The Bottom-Up Approach forThermoelectric Nanocomposites, plusƒ |

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels DataDepartment of Energy Your Density Isn'tOriginEducationVideoStrategic| DepartmentDepartment ofTankTest(EAP)Summer 2011JuneBooming

  7. A new class of high ZT doped bulk nanothermoelectrics through bottom-up

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels DataDepartment of Energy Your Density Isn't Your Destiny: The Future of1 A Strategic Framework for SMRA View from the Bridge -

  8. Residential HVAC Data, Assumptions and Methodology for End-Use Forecasting with EPRI-REEPS 2.1

    E-Print Network [OSTI]

    Johnson, F.X.

    2010-01-01T23:59:59.000Z

    modeling framework of the Residential End-Use Energy Plamiing System (REEPS) developed for the Electric

  9. Bottom-up Representation of Industrial Energy Efficiency Technologies in Integrated Assessment Models for the Cement Sector

    E-Print Network [OSTI]

    Sathaye, J.

    2011-01-01T23:59:59.000Z

    10 References Anonymous. 1994. Cement Plant Modernization inCentral Europe, World Cement (November): 35-38 Bösche, A.Variable Speed Drives in Cement Plants, World Cement 6 24

  10. Bottom-up Representation of Industrial Energy Efficiency Technologies in Integrated Assessment Models for the Cement Sector

    E-Print Network [OSTI]

    Sathaye, J.

    2011-01-01T23:59:59.000Z

    wet and dry kilns, and modern control systems now find widermodern systems use so- called 'fuzzy logic' or expert control,modern preheater. 6.0 Finish Grinding Process Control and Management – Grinding Mills. Control systems

  11. Bottom-up Representation of Industrial Energy Efficiency Technologies in Integrated Assessment Models for the Cement Sector

    E-Print Network [OSTI]

    Sathaye, J.

    2011-01-01T23:59:59.000Z

    system that runs a steam turbine system (bottom cycle).This report focuses on the steam turbine system since these

  12. Bottom-up Representation of Industrial Energy Efficiency Technologies in Integrated Assessment Models for the Cement Sector

    E-Print Network [OSTI]

    Sathaye, J.

    2011-01-01T23:59:59.000Z

    Technology Support Unit (ETSU), 1988. “High Level Control ofCircle Industries and SIRA (ETSU, 1988). The LINKman system

  13. Assessment of Historic Trend in Mobility and Energy Use in India Transportation Sector Using Bottom-up Approach

    E-Print Network [OSTI]

    Zhou, Nan

    2010-01-01T23:59:59.000Z

    IEA Motor Gasoline IEA Heavy Fuel Oil Total Rail Fuel UseEstimated Electric IEA Heavy Fuel Oil J 1,500 P J 60 P Total

  14. Bottom-up Representation of Industrial Energy Efficiency Technologies in Integrated Assessment Models for the Cement Sector

    E-Print Network [OSTI]

    Sathaye, J.

    2011-01-01T23:59:59.000Z

    use of the wastes (e.g. incineration with or without energyefficiency of use (e.g. incineration with or without heat

  15. Bottom-up Representation of Industrial Energy Efficiency Technologies in Integrated Assessment Models for the Cement Sector

    E-Print Network [OSTI]

    Sathaye, J.

    2011-01-01T23:59:59.000Z

    d) heat recovery for cogeneration (d) conversion to dryd) heat recovery for cogeneration (d) conversion from dry tod) heat recovery for cogeneration (d) conversion from dry to

  16. " Row: End Uses within NAICS Codes;"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocksa. Appliances byA49. Total Inputs of Energy182 End Uses of Fuel

  17. " Row: End Uses within NAICS Codes;"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocksa. Appliances byA49. Total Inputs of Energy182 End Uses of

  18. " Row: End Uses within NAICS Codes;"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocksa. Appliances byA49. Total Inputs of Energy182 End Uses of4 End

  19. Realizing Building End-Use Efficiency with Ermerging Technologies

    Office of Energy Efficiency and Renewable Energy (EERE)

    Information about the implementation of emerging technologies to maximize end-use efficiency in buildings.

  20. End-Use Load and Consumer Assessment Program: Characterizing residential thermal performance from high resolution end-use data

    SciTech Connect (OSTI)

    Miller, N.E.; Pearson, E.W.; Stokes, G.M.; Pratt, R.G.; Williamson, M.A.

    1991-01-01T23:59:59.000Z

    The Bonneville Power Administration (Bonneville) began the End-Use Load and Consumer Assessment Program (ELCAP) in 1983. Prior to beginning the ELCAP, there was an abundance of information regarding total power consumption for residential structures in the Pacific Northwest and limited information regarding power consumption by various end uses. The purpose of ELCAP is to collect actual end-use load data from both residential and commercial buildings in the region. This report presents the methodology used in several statistical modeling studies carried out on the ELCAP data between 1986 and 1989. These studies involve the thermal characterization of homes and comparisons of building techniques and conservation measures by residential and commercial consumers within the Bonneville service area of the Pacific Northwest. Each data gathering technique was successful in extracting a specific set of consumer-related energy use information. The analytical techniques used in these studies are compiled in this methodology report and are to be used in conjunction with Volume 2 -- Analysis. This should facilitate ease of reference use during future analyses. It is anticipated that the data gathered on participating consumers could potentially be used to aid in decisions regarding the management of the Northwest's electrical energy resources. 7 refs., 6 figs., 2 tabs.

  1. 1999 Commercial Buildings Characteristics--End-Use Equipment

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National and Regional Data; Row: NAICS8) Distribution Category UC-950 Cost and Quality of Fuels for Electric Utility PlantsEnd-Use Equipment

  2. Bottom-Up Strategic Planning

    E-Print Network [OSTI]

    Williams, Jeff; Dearie, Tammy; Schottlaender, Brian E.C.

    2013-01-01T23:59:59.000Z

    and every Libraries staff classification. The Working Groupone additional Libraries staff member of any classification.

  3. Assessment of Supply Chain Energy Efficiency Potentials: A U.S. Case Study

    SciTech Connect (OSTI)

    Masanet, Eric; Kramer, Klaas Jan; Homan, Gregory; Brown, Richard; Worrell, Ernst

    2009-01-01T23:59:59.000Z

    This paper summarizes a modeling framework that characterizes the key underlying technologies and processes that contribute to the supply chain energy use and greenhouse gas (GHG) emissions of a variety of goods and services purchased by U.S. consumers. The framework couples an input-output supply chain modeling approach with"bottom-up" fuel end use models for individual IO sectors. This fuel end use modeling detail allows energy and policy analysts to better understand the underlying technologies and processes contributing to the supply chain energy and GHG"footprints" of goods and services. To illustrate the policy-relevance of thisapproach, a case study was conducted to estimate achievable household GHG footprint reductions associated with the adoption of best practice energy-efficient supply chain technologies.

  4. Office Buildings - End-Use Equipment

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5 Tables July 1996 Energy Information Administration Office ofthroughYear Jan Feb Mar Apr May Jun Jul Aug SepDecade

  5. Estimate of Cost-Effective Potential for Minimum Efficiency Performance Standards in 13 Major World Economies Energy Savings, Environmental and Financial Impacts

    E-Print Network [OSTI]

    Letschert, Virginie E.

    2013-01-01T23:59:59.000Z

    Retail Data Brazil – International Energy Initiative Life-business as usual Brazil Bottom-Up Energy Analysis Systemfor setting energy efficiency standards in Brazil:The case

  6. Ohio Natural Gas Consumption by End Use

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5 Tables July 1996 Energy Information Administration Office ofthroughYear Jan Feb Mar Apr May Jun Jul AugFeet)Foot)83,839

  7. Oklahoma Natural Gas Consumption by End Use

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5 Tables July 1996 Energy Information Administration Office ofthroughYear Jan Feb Mar Apr May Jun Jul9ThousandFeet)41

  8. Oregon Natural Gas Consumption by End Use

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5 Tables July 1996 Energy Information Administration Office ofthroughYear Jan Feb Mar Apr MayYear Jan Feb Mar Apr MayYear Jan Feb

  9. Pennsylvania Natural Gas Consumption by End Use

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5 Tables July 1996 Energy Information Administration Office ofthroughYear Jan Feb Mar Apr MayYear JanProduction 1980 198188,970

  10. Biomass Resource Allocation among Competing End Uses

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office511041clothAdvanced Materials Advanced Materials Find Find More

  11. Iowa Natural Gas Consumption by End Use

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Building FloorspaceThousandWithdrawals0.0Decade Year-0 Year-1 Year-2

  12. Kansas Natural Gas Consumption by End Use

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Building FloorspaceThousandWithdrawals0.0Decade Year-0Base7 3Increases20096NA

  13. Kentucky Natural Gas Consumption by End Use

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto China (Million Cubic Feet) Kenai, AKExtensionsNov-14 Dec-1424,371

  14. Louisiana Natural Gas Consumption by End Use

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto China (Million Cubic Feet) 3 0 0 0 1569 0 0 0Sales (Billion99Year

  15. Maine Natural Gas Consumption by End Use

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto China (Million Cubic Feet) 3 0 07,755,432 7,466,375:Decade

  16. Maryland Natural Gas Consumption by End Use

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto China (Million Cubic Feet) 3 00.0 0.0 0.0 0.0 0.0 0.0Nov-14Year

  17. Massachusetts Natural Gas Consumption by End Use

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto China (Million Cubic Feet) 3 00.0 0.04,000

  18. Michigan Natural Gas Consumption by End Use

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto China (Million Cubic Feet) 3 00.0Feet)YearFeet)2009

  19. Minnesota Natural Gas Consumption by End Use

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto China (Million Cubic Feet) 3Exportspercontinues, with theMay6549,029

  20. Mississippi Natural Gas Consumption by End Use

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto China (Million Cubic Feet)CommercialperSales (BillionDecade31,473

  1. Missouri Natural Gas Consumption by End Use

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto China (Million CubicCubic Feet)Same 2011 2012 2013 View2009

  2. Montana Natural Gas Consumption by End Use

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto China (Million CubicCubic32,876 10,889 11,5022009 2010 2011

  3. Tennessee Natural Gas Consumption by End Use

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122Commercial ConsumersThousandCubic Feet)4. U.S. VehicleNov-14 Dec-14Year Jan

  4. Texas Natural Gas Consumption by End Use

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122Commercial ConsumersThousandCubicSeparation 7,559Nov-14 Dec-14 Jan-15Year

  5. Alabama Natural Gas Consumption by End Use

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National and Regional Data; Row: NAICS8) Distribution Category UC-950 Cost and Quality of Fuels forA 6 J 9 U B u o f l dIncreases4 1657,237

  6. Alaska Natural Gas Consumption by End Use

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National and Regional Data; Row: NAICS8) Distribution Category UC-950 Cost and Quality of Fuels forA 6 J 9 U B uYear JanSales (Billion0 0 07,022

  7. End-Use Taxes: Current EIA Practices

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40Coal Stocks at1,066,688Electricity Use as an Indicator of U.S. Economic

  8. Arizona Natural Gas Consumption by End Use

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40CoalLease(Billion CubicPotentialNov-14 Dec-14Decade Year-0 Year-1 Year-221,635

  9. Arkansas Natural Gas Consumption by End Use

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40CoalLease(Billion CubicPotentialNov-14Sales (Billion Cubic Feet) Arkansas1

  10. California Natural Gas Consumption by End Use

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40CoalLease(Billion2,128 2,469 2,321 2,590 1,550Increases (Billion1 -5 2 7

  11. Colorado Natural Gas Consumption by End Use

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40CoalLease(Billion2,128 2,469 2,321Spain (Million CubicSales (Billion 044,086

  12. Connecticut Natural Gas Consumption by End Use

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40CoalLease(Billion2,128 2,469 2,321Spain,606,602andDecade Year-0207 164

  13. Delaware Natural Gas Consumption by End Use

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40CoalLease(Billion2,128 2,469Decade Year-0 Year-1 Year-2(MillionCubic200917

  14. Washington Natural Gas Consumption by End Use

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122Commercial602 1,397 125 Q 69 (Million Cubic58 810 0 0349,980Warehouse2009Year

  15. Wisconsin Natural Gas Consumption by End Use

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122Commercial602 1,397 125 Q 69 (Million Cubic58(MillionYear Jan 201151 -18 -29

  16. Wyoming Natural Gas Consumption by End Use

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122Commercial602 1,397 125 Q 69 (MillionAdjustments (Billion Cubic2009 2010

  17. Utah Natural Gas Consumption by End Use

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17 34 44Year Jan FebIncreases (Billion Cubic Feet) Utah

  18. Vermont Natural Gas Consumption by End Use

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17 34 44Year Jan FebIncreases (BillionThousand27,262

  19. Virginia Natural Gas Consumption by End Use

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17 34 44Year Jan FebIncreasesCommercialFeet) New2009 201058YearNA

  20. Florida Natural Gas Consumption by End Use

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40CoalLease(Billion2,12803 Table A1.Gas ProvedCommercialNov-14 Dec-1483,632 88,561

  1. Georgia Natural Gas Consumption by End Use

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40CoalLease(Billion2,12803 Table A1.GasYear JanPrice Data59.2Year Jan Feb Mar

  2. Hawaii Natural Gas Consumption by End Use

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40CoalLease(Billion2,12803 Table A1.GasYearperHOW TO OBTAIN EIACubicDecade227 251

  3. Idaho Natural Gas Consumption by End Use

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40CoalLease(Billion2,12803 Table A1.GasYearperHOWYear-Month Week2009 2010Year

  4. Illinois Natural Gas Consumption by End Use

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40CoalLease(Billion2,12803 TableTotal Consumption (Million381 -260 74 127

  5. Indiana Natural Gas Consumption by End Use

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40CoalLease(Billion2,12803 TableTotal Consumptionper Thousand Cubic4 15.873,318

  6. Nebraska Natural Gas Consumption by End Use

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40CoalLease(Billion2,12803andYear Janthrough2,869,9601. Natural5,19580 1417,001

  7. Nevada Natural Gas Consumption by End Use

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40CoalLease(Billion2,12803andYearWithdrawals (MillionYearNA 24,057 25,124 21,417 NA

  8. ,"New Mexico Natural Gas Consumption by End Use"

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

    ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","New Mexico Natural Gas Consumption by End Use",6,"Monthly","12015","1151989" ,"Release...

  9. Analysis of PG E's residential end-use metered data to improve electricity demand forecasts

    SciTech Connect (OSTI)

    Eto, J.H.; Moezzi, M.M.

    1992-06-01T23:59:59.000Z

    It is generally acknowledged that improvements to end-use load shape and peak demand forecasts for electricity are limited primarily by the absence of reliable end-use data. In this report we analyze recent end-use metered data collected by the Pacific Gas and Electric Company from more than 700 residential customers to develop new inputs for the load shape and peak demand electricity forecasting models used by the Pacific Gas and Electric Company and the California Energy Commission. Hourly load shapes are normalized to facilitate separate accounting (by the models) of annual energy use and the distribution of that energy use over the hours of the day. Cooling electricity consumption by central air-conditioning is represented analytically as a function of climate. Limited analysis of annual energy use, including unit energy consumption (UEC), and of the allocation of energy use to seasons and system peak days, is also presented.

  10. Commercial equipment loads: End-Use Load and Consumer Assessment Program (ELCAP)

    SciTech Connect (OSTI)

    Pratt, R.G.; Williamson, M.A.; Richman, E.E.; Miller, N.E.

    1990-07-01T23:59:59.000Z

    The Office of Energy Resources of the Bonneville Power Administration is generally responsible for the agency's power and conservation resource planning. As associated responsibility which supports a variety of office functions is the analysis of historical trends in and determinants of energy consumption. The Office of Energy Resources' End-Use Research Section operates a comprehensive data collection program to provide pertinent information to support demand-side planning, load forecasting, and demand-side program development and delivery. Part of this on-going program is known as the End-Use Load and Consumer Assessment Program (ELCAP), an effort designed to collect electricity usage data through direct monitoring of end-use loads in buildings. This program is conducted for Bonneville by the Pacific Northwest Laboratory. This report provides detailed information on electricity consumption of miscellaneous equipment from the commercial portion of ELCAP. Miscellaneous equipment includes all commercial end-uses except heating, ventilating, air conditioning, and central lighting systems. Some examples of end-uses covered in this report are office equipment, computers, task lighting, refrigeration, and food preparation. Electricity consumption estimates, in kilowatt-hours per square food per year, are provided for each end-use by building type. The following types of buildings are covered: office, retail, restaurant, grocery, warehouse, school, university, and hotel/motel. 6 refs., 35 figs., 12 tabs.

  11. Monitoring of Electrical End-Use Loads in Commercial Buildings

    E-Print Network [OSTI]

    Martinez, M.; Alereza, T.; Mort, D.

    1988-01-01T23:59:59.000Z

    Southern California Edison is currently conducting a program to collect end-use metered data from commercial buildings in its service area. The data will provide actual measurements of end-use loads and will be used in research and in designing...

  12. Residential Appliance Data, Assumptions and Methodology for End-Use Forecasting with EPRI-REEPS 2.1

    E-Print Network [OSTI]

    was developed by the Electric Power Research Institute (McMenamin et al. 1992). In this modeling framework the modeling framework of the Residential End-Use Energy Planning System (REEPS) developed for the Electric provided by the Appliance Model in the Residential End-Use Energy Planning System (REEPS), which

  13. Residential Behavioral Savings: An Analysis of Principal Electricity End Uses in British Columbia

    E-Print Network [OSTI]

    Tiedemann, Kenneth Mr.

    2013-01-01T23:59:59.000Z

    of residential end use electricity consumption for Britishresidential electricity consumption by end use Apply theresidential end use electricity consumption using a

  14. Towards a Very Low Energy Building Stock: Modeling the U.S. Commercial Building Sector to Support Policy and Innovation Planning

    E-Print Network [OSTI]

    Coffey, Brian

    2010-01-01T23:59:59.000Z

    World Energy Outlook (IEA 2008), the bottom up models supporting IPCC “economic mitigation potentials” (IPCC 2007), the buildings chapter of the US assessment

  15. Development of Bottom-up Representation of Industrial Energy Efficiency Technologies in Integrated Assessment Models for the Iron and Steel Sector

    E-Print Network [OSTI]

    Xu, T.T.

    2011-01-01T23:59:59.000Z

    or 74% of the rolling sludges and oils (1.68 PJ). Bethlehemassuming 7.5% in oil recovery sludges and 90% in oils,Europe. Along with the oil recovery sludges, there are also

  16. Development of Bottom-up Representation of Industrial Energy Efficiency Technologies in Integrated Assessment Models for the Iron and Steel Sector

    E-Print Network [OSTI]

    Xu, T.T.

    2011-01-01T23:59:59.000Z

    1994) at $2.8/t. Automated monitoring and targeting system.an automated monitoring and targeting system at a cold stripComputer-based Monitoring and Targeting on a Rolling Mill,”

  17. Development of Bottom-up Representation of Industrial Energy Efficiency Technologies in Integrated Assessment Models for the Iron and Steel Sector

    E-Print Network [OSTI]

    Xu, T.T.

    2011-01-01T23:59:59.000Z

    International 6(1): 19-29. ETSU, 1992. “Reduction of CostsProfile 33, Harwell, UK: ETSU Farla, J.C.M. , E. Worrell, L.sites (Farla et al. , 1998; ETSU, 1992). We estimate the

  18. Development of Bottom-up Representation of Industrial Energy Efficiency Technologies in Integrated Assessment Models for the Iron and Steel Sector

    E-Print Network [OSTI]

    Xu, T.T.

    2011-01-01T23:59:59.000Z

    around 8-9% for good coking coal (IISI, 1982). Dryingof steam coal and coking coal to be $15/t (IEA, 1995). This

  19. Development of Bottom-up Representation of Industrial Energy Efficiency Technologies in Integrated Assessment Models for the Iron and Steel Sector

    E-Print Network [OSTI]

    Xu, T.T.

    2011-01-01T23:59:59.000Z

    Improved Product Quality,” Ironmaking and Steel making 18(pound Investment,” Ironmaking and Steel making,” Anonymous,Oil Through Sintering," Ironmaking and Steel making Dawson,

  20. Development of Bottom-up Representation of Industrial Energy Efficiency Technologies in Integrated Assessment Models for the Iron and Steel Sector

    E-Print Network [OSTI]

    Xu, T.T.

    2011-01-01T23:59:59.000Z

    We assume minimal investment costs for good housekeeping0.002 GJ/t sinter. No investment costs are assumed for this1990). We assume an investment cost of $0.3/t hot metal, to

  1. Development of Bottom-up Representation of Industrial Energy Efficiency Technologies in Integrated Assessment Models for the Iron and Steel Sector

    E-Print Network [OSTI]

    Xu, T.T.

    2011-01-01T23:59:59.000Z

    Assessment of Electric Steel making Through the Year 2000,by Injection Technology” Steel Times, October 1994 pp.391-Hanes, C. , 1999. USS/Kobe Steel, Personal communication,

  2. GridLAB-D Technical Support Document: Residential End-Use Module Version 1.0

    SciTech Connect (OSTI)

    Taylor, Zachary T.; Gowri, Krishnan; Katipamula, Srinivas

    2008-07-31T23:59:59.000Z

    1.0 Introduction The residential module implements the following end uses and characteristics to simulate the power demand in a single family home: • Water heater • Lights • Dishwasher • Range • Microwave • Refrigerator • Internal gains (plug loads) • House (heating/cooling loads) The house model considers the following four major heat gains/losses that contribute to the building heating/cooling load: 1. Conduction through exterior walls, roof and fenestration (based on envelope UA) 2. Air infiltration (based on specified air change rate) 3. Solar radiation (based on CLTD model and using tmy data) 4. Internal gains from lighting, people, equipment and other end use objects. The Equivalent Thermal Parameter (ETP) approach is used to model the residential loads and energy consumption. The following sections describe the modeling assumptions for each of the above end uses and the details of power demand calculations in the residential module.

  3. India Energy Outlook: End Use Demand in India to 2020

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2009-01-01T23:59:59.000Z

    rural, k=Kerosene m=rural, k=biogas m =urban, k=LPG m=urban,k=LPG k=wood k=kerosene k=biogas k=electricity k=electricity

  4. India Energy Outlook: End Use Demand in India to 2020

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2009-01-01T23:59:59.000Z

    Ministry of Chemical and Petrochemical (MoCP), 2005. “AnnualMinistry of Chemical and Petrochemical Ministry of Petroleumpotential. 3.3.2.6 Petrochemicals and Chemicals India ranks

  5. India Energy Outlook: End Use Demand in India to 2020

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2009-01-01T23:59:59.000Z

    Efficiency in Electricity Consumption", HWWA Discussionconsumption. Even electricity consumption, which isData Adjustment Electricity consumption from farmers is un-

  6. India Energy Outlook: End Use Demand in India to 2020

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2009-01-01T23:59:59.000Z

    5% of its reserve is coking coal used by the steel industry.imports around 70% of coking coal annually. More recently,

  7. India Energy Outlook: End Use Demand in India to 2020

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2009-01-01T23:59:59.000Z

    Diesel, 18% Primary Electricity Diesel, 49% Electricty,51% Electricty Data Adjustment Electricity consumption from

  8. India Energy Outlook: End Use Demand in India to 2020

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2009-01-01T23:59:59.000Z

    Activity, 2005-06 8India's GDP, with 54% in 2005-06 (MOSPI, 2007b) and is alsoby Economic Activity, 2005-06 GDP Share AAGR (billion of GDP

  9. India Energy Outlook: End Use Demand in India to 2020

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2009-01-01T23:59:59.000Z

    of 43% of total oil consumption. The residential sectorrepresenting 63% and oil consumption representing the rest.the diesel and fuel oil consumption are included, the total

  10. India Energy Outlook: End Use Demand in India to 2020

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2009-01-01T23:59:59.000Z

    T&D) technical and commercial losses are substantial,losses. T&D losses include technical loses and commercial

  11. Distribution Infrastructure and End Use | Department of Energy

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE: Alternative FuelsNovember 13, 2014ContributingDOEDepartment ofOff-Gas fromDistributedDistribution

  12. Engineer End Uses for Maximum Efficiency | Department of Energy

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page onYouTube YouTube Note: Since the YouTube|6721 FederalTexas Energyof 2005 atDepartment ofLLC

  13. Alternative Strategies for Low Pressure End Uses | Department of Energy

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page onYouTube YouTube Note: Since the YouTube platform is alwaysISOSource Heat PumpAllegations of

  14. Optimizing U.S. Mitigation Strategies for the Light-Duty Transportation Sector: What We Learn from a Bottom-Up Model

    E-Print Network [OSTI]

    Yeh, Sonia; Farrell, Alexander E.; Plevin, Richard J; Sanstad, Alan; Weyant, John

    2008-01-01T23:59:59.000Z

    leg/leginx.asp 4. EIA Annual Energy Outlook 2007 with22, (4), 10. EIA Annual Energy Outlook 2006 with Projectionsto the Annual Energy Outlook 2007. Transportation Demand

  15. Optimizing U.S. Mitigation Strategies for the Light-Duty Transportation Sector: What We Learn from a Bottom-Up Model

    E-Print Network [OSTI]

    Yeh, Sonia; Farrell, Alexander E.; Plevin, Richard J; Sanstad, Alan; Weyant, John

    2008-01-01T23:59:59.000Z

    2005; Energy Information Administration, U.S. Department of0383(2007); Energy Information Administration: 2007. http://0383(2006); Energy Information Administration: Washington,

  16. Industrial Steam Power Cycles Final End-Use Classification

    E-Print Network [OSTI]

    Waterland, A. F.

    1983-01-01T23:59:59.000Z

    Final end uses of steam include two major classifications: those uses that condense the steam against heat transfer surfaces to provide heat to an item of process or service equipment; and those that require a mass flow of steam for stripping...

  17. A bottom-up engineering estimate of the aggregate heating and cooling loads of the entire U.S. building stock

    E-Print Network [OSTI]

    Huang, Yu Joe; Brodrick, Jim

    2000-01-01T23:59:59.000Z

    EIA). 1996a. "Annual Energy Outlook 1995", DOE/EIA-0383(95).EIA). 1996b. "Annual Energy Outlook 1997", DOE/EIA-0383(97).CBECS, and the Annual Energy Outlook) and the Gas Research

  18. Optimizing U.S. Mitigation Strategies for the Light-Duty Transportation Sector: What We Learn from a Bottom-Up Model

    E-Print Network [OSTI]

    Yeh, Sonia; Farrell, Alexander E.; Plevin, Richard J; Sanstad, Alan; Weyant, John

    2008-01-01T23:59:59.000Z

    Delhi, India, 2007. (16) EIA. Emissions of Greenhouse Gasesglobalwarming/leg/leginx.asp 4. EIA Annual Energy Outlookto 2030. Report #DOE/EIA-0383(2007); Energy Information

  19. Electricity end-use efficiency: Experience with technologies, markets, and policies throughout the world

    SciTech Connect (OSTI)

    Levine, M.D.; Koomey, J.; Price, L. [Lawrence Berkeley Lab., CA (United States); Geller, H.; Nadel, S. [American Council for an Energy-Efficient Economy, Washington, DC (United States)

    1992-03-01T23:59:59.000Z

    In its August meeting in Geneva, the Energy and Industry Subcommittee (EIS) of the Policy Response Panel of the Intergovernmental Panel on Climate Change (IPCC) identified a series of reports to be produced. One of these reports was to be a synthesis of available information on global electricity end-use efficiency, with emphasis on developing nations. The report will be reviewed by the IPCC and approved prior to the UN Conference on Environment and Development (UNCED), Brazil, June 1992. A draft outline for the report was submitted for review at the November 1991 meeting of the EIS. This outline, which was accepted by the EIS, identified three main topics to be addressed in the report: status of available technologies for increasing electricity end-use efficiency; review of factors currently limiting application of end-use efficiency technologies; and review of policies available to increase electricity end-use efficiency. The United States delegation to the EIS agreed to make arrangements for the writing of the report.

  20. Optimizing U.S. Mitigation Strategies for the Light-Duty Transportation Sector: What We Learn from a Bottom-Up Model

    E-Print Network [OSTI]

    Yeh, Sonia; Farrell, Alexander E.; Plevin, Richard J; Sanstad, Alan; Weyant, John

    2008-01-01T23:59:59.000Z

    vehicles: The case of natural gas vehicles. Energy PolicyCNG: dedicated natural gas vehicles; LPG: liquefiedvehicles using low- GHG fuels such as compressed natural gas,

  1. Analysis of PG&E`s residential end-use metered data to improve electricity demand forecasts

    SciTech Connect (OSTI)

    Eto, J.H.; Moezzi, M.M.

    1992-06-01T23:59:59.000Z

    It is generally acknowledged that improvements to end-use load shape and peak demand forecasts for electricity are limited primarily by the absence of reliable end-use data. In this report we analyze recent end-use metered data collected by the Pacific Gas and Electric Company from more than 700 residential customers to develop new inputs for the load shape and peak demand electricity forecasting models used by the Pacific Gas and Electric Company and the California Energy Commission. Hourly load shapes are normalized to facilitate separate accounting (by the models) of annual energy use and the distribution of that energy use over the hours of the day. Cooling electricity consumption by central air-conditioning is represented analytically as a function of climate. Limited analysis of annual energy use, including unit energy consumption (UEC), and of the allocation of energy use to seasons and system peak days, is also presented.

  2. Residential applliance data, assumptions and methodology for end-use forecasting with EPRI-REEPS 2.1

    SciTech Connect (OSTI)

    Hwang, R.J,; Johnson, F.X.; Brown, R.E.; Hanford, J.W.; Kommey, J.G.

    1994-05-01T23:59:59.000Z

    This report details the data, assumptions and methodology for end-use forecasting of appliance energy use in the US residential sector. Our analysis uses the modeling framework provided by the Appliance Model in the Residential End-Use Energy Planning System (REEPS), which was developed by the Electric Power Research Institute. In this modeling framework, appliances include essentially all residential end-uses other than space conditioning end-uses. We have defined a distinct appliance model for each end-use based on a common modeling framework provided in the REEPS software. This report details our development of the following appliance models: refrigerator, freezer, dryer, water heater, clothes washer, dishwasher, lighting, cooking and miscellaneous. Taken together, appliances account for approximately 70% of electricity consumption and 30% of natural gas consumption in the US residential sector. Appliances are thus important to those residential sector policies or programs aimed at improving the efficiency of electricity and natural gas consumption. This report is primarily methodological in nature, taking the reader through the entire process of developing the baseline for residential appliance end-uses. Analysis steps documented in this report include: gathering technology and market data for each appliance end-use and specific technologies within those end-uses, developing cost data for the various technologies, and specifying decision models to forecast future purchase decisions by households. Our implementation of the REEPS 2.1 modeling framework draws on the extensive technology, cost and market data assembled by LBL for the purpose of analyzing federal energy conservation standards. The resulting residential appliance forecasting model offers a flexible and accurate tool for analyzing the effect of policies at the national level.

  3. Table 5.1 End Uses of Fuel Consumption, 2010;

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API Gravity Period:Dakota"Dakota"Nevada"Washington" "megawatthours" "Item",5.1 End Uses of

  4. Table 5.2 End Uses of Fuel Consumption, 2010;

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API Gravity Period:Dakota"Dakota"Nevada"Washington" "megawatthours" "Item",5.1 End Uses of2

  5. Table 5.3 End Uses of Fuel Consumption, 2010;

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API Gravity Period:Dakota"Dakota"Nevada"Washington" "megawatthours" "Item",5.1 End Uses

  6. Table 5.4 End Uses of Fuel Consumption, 2010;

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API Gravity Period:Dakota"Dakota"Nevada"Washington" "megawatthours" "Item",5.1 End Uses4

  7. Table 5.5 End Uses of Fuel Consumption, 2010;

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API Gravity Period:Dakota"Dakota"Nevada"Washington" "megawatthours" "Item",5.1 End Uses45

  8. Table 5.6 End Uses of Fuel Consumption, 2010;

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API Gravity Period:Dakota"Dakota"Nevada"Washington" "megawatthours" "Item",5.1 End Uses456

  9. Table 5.7 End Uses of Fuel Consumption, 2010;

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API Gravity Period:Dakota"Dakota"Nevada"Washington" "megawatthours" "Item",5.1 End Uses4567

  10. Ris Energy Report 4 Interaction between supply and end-use 4 8 Interaction between supply and end-use

    E-Print Network [OSTI]

    the introduction of more distributed generation and intermittent renewables. Using the Nordic power market for increasing flexibility on the demand side. Demand response on the Nordic Power Mar- ket Nord Pool, the Nordic), is open until two hours before delivery. In addition to these two markets, the Nordic transmission system

  11. IMPACTS OF GREENHOUSE GAS AND PARTICULATE EMISSIONS FROM WOODFUEL PRODUCTION AND END-USE IN SUB-SAHARAN AFRICA

    E-Print Network [OSTI]

    Kammen, Daniel M.

    the pollution associated with production, distribution and end-use of common household fuels and assess. At the household level, energy is derived primarily from solid biomass fuels burned in simple stoves with poor & African Center for Technology Studies, Nairobi, Kenya ABSTRACT: Household energy in sub-Saharan Africa

  12. GIS-based energy consumption mapping 

    E-Print Network [OSTI]

    Balta, Chrysi

    2014-11-27T23:59:59.000Z

    This project aims to provide a methodology to map energy consumption of the housing stock at a city level and visualise and evaluate different retrofitting scenarios. It is based on an engineering, bottom-up approach. It makes use...

  13. Industrial Geospatial Analysis Tool for Energy Evaluation 

    E-Print Network [OSTI]

    Alkadi, N.; Starke, M.; Ma, O.; Nimbalkar, S.; Cox, D.; Dowling, K.; Johnson, B.; Khan, S.

    2013-01-01T23:59:59.000Z

    . The tool applies statistical modeling to multiple datasets and provides information at the geospatial resolution of zip code using bottom up approaches. Within each zip code, the current version of the tool estimates electrical energy consumption...

  14. End-Use Load and Consumer Assessment Program: Characterizing residential thermal performance from high resolution end-use data

    SciTech Connect (OSTI)

    Miller, N.E.; Williamson, M.A.; Bailey, S.A.; Pratt, R.G.; Stokes, G.M.; Sandusky, W.F.; Pearson, E.W.; Roberts, J.S.

    1991-06-01T23:59:59.000Z

    This document is part of a two-volume set describing a series of thermal analyses of the residential buildings monitored under the End-Use Load and Consumer Assessment Program. Volume 1 describes in detail the thermal analysis methodology employed. Volume 2 presents the results of applying the methodology in a series of four distinct analyses: (1) an analysis of the first monitored heating season, 1985--1986; (2) an analysis of the second monitored heating season, (3) a comparison of first- and second-year analyses showing changes in residential consumption with changes in weather and evaluating the ability of the analytical technique to discriminate those changes; and (4) a continuation of the previous analyses evaluating the effects of foundation type and heating system type on the results.

  15. Comparative Analysis of Modeling Studies on China's Future Energy and Emissions Outlook

    E-Print Network [OSTI]

    Zheng, Nina

    2010-01-01T23:59:59.000Z

    International Energy Agency (IEA). 2009. World EnergyChina-specific section of the IEA World Energy Outlook 2009.while LBNL, McKinsey and IEA all employed bottom-up modeling

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

    SciTech Connect (OSTI)

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

    2012-12-01T23:59:59.000Z

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

  17. Technology data characterizing lighting in commercial buildings: Application to end-use forecasting with commend 4.0

    SciTech Connect (OSTI)

    Sezgen, A.O.; Huang, Y.J.; Atkinson, B.A.; Eto, J.H.; Koomey, J.G.

    1994-05-01T23:59:59.000Z

    End-use forecasting models typically utilize technology tradeoff curves to represent technology options available to consumers. A tradeoff curve, in general terms, is a functional form which relates efficiency to capital cost. Each end-use is modeled by a single tradeoff curve. This type of representation is satisfactory in the analysis of many policy options. On the other hand, for policies addressing individual technology options or groups of technology options, because individual technology options are accessible to the analyst, representation in such reduced form is not satisfactory. To address this and other analysis needs, the Electric Power Research Institute (EPRI) has enhanced its Commercial End-Use Planning System (COMMEND) to allow modeling of specific lighting and space conditioning (HVAC) technology options. This report characterizes the present commercial floorstock in terms of lighting technologies and develops cost-efficiency data for these lighting technologies. This report also characterizes the interactions between the lighting and space conditioning end uses in commercial buildings in the US In general, lighting energy reductions increase the heating and decrease the cooling requirements. The net change in a building`s energy requirements, however, depends on the building characteristics, operating conditions, and the climate. Lighting/HVAC interactions data were generated through computer simulations using the DOE-2 building energy analysis program.

  18. Residential and Transport Energy Use in India: Past Trend and Future Outlook

    SciTech Connect (OSTI)

    de la Rue du Can, Stephane; Letschert, Virginie; McNeil, Michael; Zhou, Nan; Sathaye, Jayant

    2009-03-31T23:59:59.000Z

    The main contribution of this report is to characterize the underlying residential and transport sector end use energy consumption in India. Each sector was analyzed in detail. End-use sector-level information regarding adoption of particular technologies was used as a key input in a bottom-up modeling approach. The report looks at energy used over the period 1990 to 2005 and develops a baseline scenario to 2020. Moreover, the intent of this report is also to highlight available sources of data in India for the residential and transport sectors. The analysis as performed in this way reveals several interesting features of energy use in India. In the residential sector, an analysis of patterns of energy use and particular end uses shows that biomass (wood), which has traditionally been the main source of primary energy used in households, will stabilize in absolute terms. Meanwhile, due to the forces of urbanization and increased use of commercial fuels, the relative significance of biomass will be greatly diminished by 2020. At the same time, per household residential electricity consumption will likely quadruple in the 20 years between 2000 and 2020. In fact, primary electricity use will increase more rapidly than any other major fuel -- even more than oil, in spite of the fact that transport is the most rapidly growing sector. The growth in electricity demand implies that chronic outages are to be expected unless drastic improvements are made both to the efficiency of the power infrastructure and to electric end uses and industrial processes. In the transport sector, the rapid growth in personal vehicle sales indicates strong energy growth in that area. Energy use by cars is expected to grow at an annual growth rate of 11percent, increasing demand for oil considerably. In addition, oil consumption used for freight transport will also continue to increase .

  19. Vehicle Technologies Office: Biofuels End-Use Research | Department of

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn AprilA group current C3EDepartmentDepartment ofConstruction|(EVSE)Each year,Energy

  20. " Row: End Uses within NAICS Codes;"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocksa. Appliances byA49. Total Inputs of Energy18 Number441. End

  1. " Row: End Uses within NAICS Codes;"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocksa. Appliances byA49. Total Inputs of Energy18 Number441. End2.

  2. " Row: End Uses within NAICS Codes;"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocksa. Appliances byA49. Total Inputs of Energy18 Number441.

  3. " Row: End Uses within NAICS Codes;"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocksa. Appliances byA49. Total Inputs of Energy18 Number441.4. End

  4. " Row: End Uses within NAICS Codes;"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocksa. Appliances byA49. Total Inputs of Energy18 Number441.4. End1

  5. " Row: End Uses within NAICS Codes;"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocksa. Appliances byA49. Total Inputs of Energy18 Number441.4.

  6. " Row: End Uses within NAICS Codes;"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocksa. Appliances byA49. Total Inputs of Energy18 Number441.4.3 End

  7. " Row: End Uses within NAICS Codes;"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocksa. Appliances byA49. Total Inputs of Energy18 Number441.4.3

  8. " Row: End Uses within NAICS Codes;"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocksa. Appliances byA49. Total Inputs of Energy18 Number441.4.31

  9. " Row: End Uses within NAICS Codes;"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocksa. Appliances byA49. Total Inputs of Energy18 Number441.4.312

  10. " Row: End Uses within NAICS Codes;"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocksa. Appliances byA49. Total Inputs of Energy18 Number441.4.3123

  11. " Row: End Uses within NAICS Codes;"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocksa. Appliances byA49. Total Inputs of Energy18 Number441.4.31234

  12. " Row: End Uses within NAICS Codes;"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocksa. Appliances byA49. Total Inputs of Energy18

  13. North Carolina Natural Gas Consumption by End Use

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5 Tables July 1996 Energy Information Administration Office ofthrough 1996) inThousandWithdrawals (MillionNine8 2.415Decade

  14. End-use matching for solar industrial process heat. Final report

    SciTech Connect (OSTI)

    Brown, K.C.; Hooker, D.W.; Rabl, A.; Stadjuhar, S.A.; West, R.E.

    1980-01-01T23:59:59.000Z

    Because of the large energy demand of industry (37% of US demand) and the wide spectrum of temperatures at which heat is required, the industrial sector appears to be very suitable for the matching of solar thermal technology with industrial process heat (IPH) requirements. A methodology for end-use matching has been devised, complete with required data bases and an evaluation program PROSYS/ECONMAT. Six cities in the United States were selected for an analysis of solar applications to IPH. Typical process heat requirements for 70% of the industrial plants in each city were identified and evaluated in conjunction with meteorological and economic data for each site to determine lowest-cost solar systems for each application. The flexibility and scope of PROSYS/ECONMAT is shown in a variety of sensitivity studies that expand the results of the six-city analysis. Case studies of two industrial plants were performed to evaluate the end-use matching procedure; these results are reported.

  15. U.S. Adjusted Sales of Kerosene by End Use

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2,EHSS A-Zandofpoint motional%^ U N C L AKerosene by

  16. U.S. Natural Gas Consumption by End Use

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2,EHSSCoal ProductionLiquefied NaturalYear Jan

  17. Average End Use Breakdown: Massachusetts General Hospital Gray Building

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels DataDepartment of Energy Your Density Isn't Your Destiny: The FutureComments fromof Energy Automation WorldofAutotune

  18. New York Natural Gas Consumption by End Use

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5 Tables July 1996 Energy Information Administration Office ofthrough 1996) inThousand CubicFeet)perFeet) New2 1,033116,717

  19. North Dakota Natural Gas Consumption by End Use

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5 Tables July 1996 Energy Information Administration Office ofthrough 1996)McGuire"Feet) EstimatedProduction 4 12 73 95,581

  20. Rhode Island Natural Gas Consumption by End Use

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122Commercial ConsumersThousand CubicCubic Feet) Yeara

  1. South Carolina Natural Gas Consumption by End Use

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122Commercial ConsumersThousand CubicCubicIndia (Million2,116 3,110IIF2009Decade20,213

  2. South Dakota Natural Gas Consumption by End Use

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122Commercial ConsumersThousand CubicCubicIndiaFeet)6 0.6 0.7 0.6 0.6Decade7,530

  3. District of Columbia Natural Gas Consumption by End Use

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40CoalLease(Billion2,128 2,469Decade Year-0CubicCubic Feet) Year

  4. U.S. Sales of Kerosene by End Use

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40Coal Stocks at Commercial and InstitutionalArea: U.S. East

  5. West Virginia Natural Gas Consumption by End Use

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122Commercial602 1,397 125 Q 69 (Million Cubic58 810YearDecade Year-0 Year-1

  6. New Hampshire Natural Gas Consumption by End Use

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40CoalLease(Billion2,12803andYearWithdrawalsYear Jan Feb Mar Apr8 0.8Decade4,662

  7. New Jersey Natural Gas Consumption by End Use

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40CoalLease(Billion2,12803andYearWithdrawalsYear Jan1 0.2 0.1 0.1 0.22009Year

  8. New Mexico Natural Gas Consumption by End Use

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40CoalLease(Billion2,12803andYearWithdrawalsYearFeet) NewNov-14 Dec-14

  9. Driving Biofuels End Use: BETO/VTO Collaborations

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels DataDepartment of Energy Your Density Isn't Your Destiny:Revised Finding of No53197E TDrew Bittner About Us Drew Bittner -DriveDriving

  10. Residential sector end-use forecasting with EPRI-Reeps 2.1: Summary input assumptions and results

    SciTech Connect (OSTI)

    Koomey, J.G.; Brown, R.E.; Richey, R. [and others

    1995-12-01T23:59:59.000Z

    This paper describes current and projected future energy use by end-use and fuel for the U.S. residential sector, and assesses which end-uses are growing most rapidly over time. The inputs to this forecast are based on a multi-year data compilation effort funded by the U.S. Department of Energy. We use the Electric Power Research Institute`s (EPRI`s) REEPS model, as reconfigured to reflect the latest end-use technology data. Residential primary energy use is expected to grow 0.3% per year between 1995 and 2010, while electricity demand is projected to grow at about 0.7% per year over this period. The number of households is expected to grow at about 0.8% per year, which implies that the overall primary energy intensity per household of the residential sector is declining, and the electricity intensity per household is remaining roughly constant over the forecast period. These relatively low growth rates are dependent on the assumed growth rate for miscellaneous electricity, which is the single largest contributor to demand growth in many recent forecasts.

  11. Current Status and Future Scenarios of Residential Building Energy Consumption in China

    SciTech Connect (OSTI)

    Zhou, Nan; Nishida, Masaru; Gao, Weijun

    2008-12-01T23:59:59.000Z

    China's rapid economic expansion has propelled it into the ranks of the largest energy consuming nation in the world, with energy demand growth continuing at a pace commensurate with its economic growth. Even though the rapid growth is largely attributable to heavy industry, this in turn is driven by rapid urbanization process, by construction materials and equipment produced for use in buildings. Residential energy is mostly used in urban areas, where rising incomes have allowed acquisition of home appliances, as well as increased use of heating in southern China. The urban population is expected to grow by 20 million every year, accompanied by construction of 2 billion square meters of buildings every year through 2020. Thus residential energy use is very likely to continue its very rapid growth. Understanding the underlying drivers of this growth helps to identify the key areas to analyze energy efficiency potential, appropriate policies to reduce energy use, as well as to understand future energy in the building sector. This paper provides a detailed, bottom-up analysis of residential building energy consumption in China using data from a wide variety of sources and a modeling effort that relies on a very detailed characterization of China's energy demand. It assesses the current energy situation with consideration of end use, intensity, and efficiency etc, and forecast the future outlook for the critical period extending to 2020, based on assumptions of likely patterns of economic activity, availability of energy services, technology improvement and energy intensities.

  12. Comparative Analysis of Modeling Studies on China's Future Energy and Emissions Outlook

    SciTech Connect (OSTI)

    Zheng, Nina; Zhou, Nan; Fridley, David

    2010-09-01T23:59:59.000Z

    The past decade has seen the development of various scenarios describing long-term patterns of future Greenhouse Gas (GHG) emissions, with each new approach adding insights to our understanding of the changing dynamics of energy consumption and aggregate future energy trends. With the recent growing focus on China's energy use and emission mitigation potential, a range of Chinese outlook models have been developed across different institutions including in China's Energy Research Institute's 2050 China Energy and CO2 Emissions Report, McKinsey & Co's China's Green Revolution report, the UK Sussex Energy Group and Tyndall Centre's China's Energy Transition report, and the China-specific section of the IEA World Energy Outlook 2009. At the same time, the China Energy Group at Lawrence Berkeley National Laboratory (LBNL) has developed a bottom-up, end-use energy model for China with scenario analysis of energy and emission pathways out to 2050. A robust and credible energy and emission model will play a key role in informing policymakers by assessing efficiency policy impacts and understanding the dynamics of future energy consumption and energy saving and emission reduction potential. This is especially true for developing countries such as China, where uncertainties are greater while the economy continues to undergo rapid growth and industrialization. A slightly different assumption or storyline could result in significant discrepancies among different model results. Therefore, it is necessary to understand the key models in terms of their scope, methodologies, key driver assumptions and the associated findings. A comparative analysis of LBNL's energy end-use model scenarios with the five above studies was thus conducted to examine similarities and divergences in methodologies, scenario storylines, macroeconomic drivers and assumptions as well as aggregate energy and emission scenario results. Besides directly tracing different energy and CO{sub 2} savings potential back to the underlying strategies and combination of efficiency and abatement policy instruments represented by each scenario, this analysis also had other important but often overlooked findings.

  13. Residential Sector End-Use Forecasting with EPRI-REEPS 2.1: Summary Input Assumptions and Results

    E-Print Network [OSTI]

    Koomey, Jonathan G.

    2010-01-01T23:59:59.000Z

    End-Use Forecasting with EPRI-REEPS 2.1. Lawrence BerkeleyEnd-Use Forecasting with EPRI-REEPS 2.1. Lawrence BerkeleyPower Research Institute. EPRI Research Project Meier, Alan

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

    SciTech Connect (OSTI)

    Zhou, Nan; McNeil, Michael A.; Levine, Mark

    2009-06-01T23:59:59.000Z

    China's rapid economic expansion has propelled it to the rank of the largest energy consuming nation in the world, with energy demand growth continuing at a pace commensurate with its economic growth. The urban population is expected to grow by 20 million every year, accompanied by construction of 2 billion square meters of buildings every year through 2020. Thus residential energy use is very likely to continue its very rapid growth. Understanding the underlying drivers of this growth helps to identify the key areas to analyze energy efficiency potential, appropriate policies to reduce energy use, as well as to understand future energy in the building sector. This paper provides a detailed, bottom-up analysis of residential building energy consumption in China using data from a wide variety of sources and a modelling effort that relies on a very detailed characterization of China's energy demand. It assesses the current energy situation with consideration of end use, intensity, and efficiency etc, and forecast the future outlook for the critical period extending to 2020, based on assumptions of likely patterns of economic activity, availability of energy services, technology improvement and energy intensities. From this analysis, we can conclude that Chinese residential energy consumption will more than double by 2020, from 6.6 EJ in 2000 to 15.9 EJ in 2020. This increase will be driven primarily by urbanization, in combination with increases in living standards. In the urban and higher income Chinese households of the future, most major appliances will be common, and heated and cooled areas will grow on average. These shifts will offset the relatively modest efficiency gains expected according to current government plans and policies already in place. Therefore, levelling and reduction of growth in residential energy demand in China will require a new set of more aggressive efficiency policies.

  15. Public Health Benefits of End-Use Electrical Energy Efficiency in California: An Exploratory Study

    E-Print Network [OSTI]

    McKone, Thomas E.

    2011-01-01T23:59:59.000Z

    2004 Database of California Power Plants/' Located at:generation from California power plants. A-2a) Emissionthat includes all power plants in California that are one-

  16. Public Health Benefits of End-Use Electrical Energy Efficiency in California: An Exploratory Study

    E-Print Network [OSTI]

    McKone, Thomas E.

    2011-01-01T23:59:59.000Z

    more S02 and NOx than natural gas combustion, the result isSteam turbine Diesel Natural Gas Combustion or gas turbineand gas turbine Natural gas Combustion or gas turbine Steam

  17. ENERGY CONSERVATION: POLICY ISSUES AND END-USE SCENARIOS OF SAVINGS POTENTIAL PT.1

    E-Print Network [OSTI]

    Authors, Various

    2011-01-01T23:59:59.000Z

    water consumption and solar water heaters with efficientsolar water heating systems with efficent electrical backup heaters

  18. Public Health Benefits of End-Use Electrical Energy Efficiency in California: An Exploratory Study

    E-Print Network [OSTI]

    McKone, Thomas E.

    2011-01-01T23:59:59.000Z

    and NOx than natural gas combustion, the result is higherturbine Diesel Natural Gas Combustion or gas turbine Steamand gas turbine Nahual Gas Combustion or gas turbine Steam

  19. Public Health Benefits of End-Use Electrical Energy Efficiency in California: An Exploratory Study

    E-Print Network [OSTI]

    McKone, Thomas E.

    2011-01-01T23:59:59.000Z

    Because distillate oil combustion emits much more S02 andSan Mateo Distillate Oil Combustion Turbine Santa BarbaraTECHNOLOGY Distillate Oil Combustion Turbine COGEN COUNTY

  20. ENERGY CONSERVATION: POLICY ISSUES AND END-USE SCENARIOS OF SAVINGS POTENTIAL PT.2

    E-Print Network [OSTI]

    Authors, Various

    2011-01-01T23:59:59.000Z

    Recovery Direct Combustion Pyrolysis (Oil) Note: Col. 3 =Oil) Source Separation *Million BTU/ton MSW **Direct Combustionto Elec (Oil) Source Separation(2) *D.C. Direct Combustion

  1. ENERGY CONSERVATION: POLICY ISSUES AND END-USE SCENARIOS OF SAVINGS POTENTIAL PT.1

    E-Print Network [OSTI]

    Authors, Various

    2011-01-01T23:59:59.000Z

    consumption and solar water heaters with efficient backups;solar water heating systems with efficent electrical backup heaters

  2. Public Health Benefits of End-Use Electrical Energy Efficiency in California: An Exploratory Study

    E-Print Network [OSTI]

    McKone, Thomas E.

    2011-01-01T23:59:59.000Z

    Cogen Cogen Natural Gas Landfill Gas Tulare Tulare Woodwasteand wood waste, landfill gas, and mlmicipal solid waste andscf digester gas, or Btu/ scf landfill gas. HVs are given in

  3. Public Health Benefits of End-Use Electrical Energy Efficiency in California: An Exploratory Study

    E-Print Network [OSTI]

    McKone, Thomas E.

    2011-01-01T23:59:59.000Z

    Woodwaste Natural Gas Steam Turbine Cogen Sierra Tulare GasGas Turbine Combined Cycle Steam Turbine Cogen Not Cogen NotNot Cogen Cogen Cogen Kern Steam Turbine Steam Turbne Lassen

  4. INTERNATIONAL RESIDENTIAL ENERGY END USE DATA: ANALYSIS OF HISTORICAL AND PRESENT DAY STRUCTURE AND DYNAMICS

    E-Print Network [OSTI]

    Schipper, Lee

    2013-01-01T23:59:59.000Z

    heat includes all fuels except district heating. Only forSweden, and Germany had district heating. The Swedish/Germandistrict-heated share are given in parenthesis. For France the figures refers only to central heating.

  5. ENERGY CONSERVATION: POLICY ISSUES AND END-USE SCENARIOS OF SAVINGS POTENTIAL PT.2

    E-Print Network [OSTI]

    Authors, Various

    2011-01-01T23:59:59.000Z

    of Waste Landfilled and Landfill Closure Dates For The Lostradeoffs between landfill and com- bined programs ofare the tradeoffs between landfill and com- bined resource

  6. Public Health Benefits of End-Use Electrical Energy Efficiency in California: An Exploratory Study

    E-Print Network [OSTI]

    McKone, Thomas E.

    2011-01-01T23:59:59.000Z

    Cogen Cogen Natural Gas Landfill Gas Tulare Tulare Woodwasteas agricultural and wood waste, landfill gas, and mlmicipalscf digester gas, or Btu/ scf landfill gas. HVs are given in

  7. Public Health Benefits of End-Use Electrical Energy Efficiency in California: An Exploratory Study

    E-Print Network [OSTI]

    McKone, Thomas E.

    2011-01-01T23:59:59.000Z

    j designates the plant generating electricity from apowered electricity generating plants in a) urban and b)from electricity generating plants in California. Exposure

  8. Estimates of Energy Consumption by Building Type and End Use at U.S. Army Installations

    E-Print Network [OSTI]

    Konopacki, S.J.

    2010-01-01T23:59:59.000Z

    A C EUIs (cooling, ventilation, and gas heating). The annualCooling kWh/ft Ventilation kWh/ft Heating kBtu/ft CoolingMiscellaneous DOE-2 Ventilation kWh/ft Heating kBtu/ft EDA

  9. Public Health Benefits of End-Use Electrical Energy Efficiency in California: An Exploratory Study

    E-Print Network [OSTI]

    McKone, Thomas E.

    2011-01-01T23:59:59.000Z

    Tulare Gas Fueled Reciprocating Cogen Engine Gas TurbineGas Turbine Combined Cycle Steam Turbine Cogen Not Cogen NotGas Kern Natural Gas/Eor Gas Turbine Kern Ag. & Woodwaste

  10. Public Health Benefits of End-Use Electrical Energy Efficiency in California: An Exploratory Study

    E-Print Network [OSTI]

    McKone, Thomas E.

    2011-01-01T23:59:59.000Z

    Woodwaste Woodwaste Agricultural Waste Not Cogen Cogen Cogenfuels, such as agricultural and wood waste, landfill gas,

  11. Public Health Benefits of End-Use Electrical Energy Efficiency in California: An Exploratory Study

    E-Print Network [OSTI]

    McKone, Thomas E.

    2011-01-01T23:59:59.000Z

    Gas Sonoma Internal Combustion Engine Internal Combustionwhich report internal combustion (IC) engines as technologygas, internal combustion, or reciprocating engines. 3.9 i

  12. Public Health Benefits of End-Use Electrical Energy Efficiency in California: An Exploratory Study

    E-Print Network [OSTI]

    McKone, Thomas E.

    2011-01-01T23:59:59.000Z

    Spi- Sonora Woodwaste Natural Gas Steam Turbine Cogen SierraCogen Not Cogen Cogen Natural Gas Landfill Gas Tulare TulareMidsun Partners Sekr Cogen Natural Gas Natural Gas o Cogen o

  13. Public Health Benefits of End-Use Electrical Energy Efficiency in California: An Exploratory Study

    E-Print Network [OSTI]

    McKone, Thomas E.

    2011-01-01T23:59:59.000Z

    Cogen Cogen Kern Steam Turbine Steam Turbne Lassen Lassen b)a g 0.70-0.80 j i gas turbine Steam turbine or boiler 0.15-engme h WTE o n III gas turbine steam htrbine or boile! Ie

  14. Public Health Benefits of End-Use Electrical Energy Efficiency in California: An Exploratory Study

    E-Print Network [OSTI]

    McKone, Thomas E.

    2011-01-01T23:59:59.000Z

    either multiple cyclone, scrubber, ESP, or baghouse); Pc,either multiple cyclone, scrubber, ESP, or baghouses); PC,either multiple cyclone, scrubber, ESP, or baghouse) and PC,

  15. ENERGY CONSERVATION: POLICY ISSUES AND END-USE SCENARIOS OF SAVINGS POTENTIAL PT.2

    E-Print Network [OSTI]

    Authors, Various

    2011-01-01T23:59:59.000Z

    Works Department. General Electric Company Solid Wasteavailable in MSW (General Electric 1975: Determining thein MSW (%) Source: General Electric 1975, Lidstrum 1974,

  16. Public Health Benefits of End-Use Electrical Energy Efficiency in California: An Exploratory Study

    E-Print Network [OSTI]

    McKone, Thomas E.

    2011-01-01T23:59:59.000Z

    coal-powered electricity generating plants located in rural counties (primarily the Mohave coal power plant).power plant efficiencies assumed in the estimates. Because value ranges for efficiencies of coal- powered

  17. Public Health Benefits of End-Use Electrical Energy Efficiency in California: An Exploratory Study

    E-Print Network [OSTI]

    McKone, Thomas E.

    2011-01-01T23:59:59.000Z

    Arco Oxford Occidental Of Elk Hills Inc. Lost Hills BerryRiver Cogen Sycamore Cogen Elk Hills PRIMARY FUEL TECHNOLOGY

  18. Public Health Benefits of End-Use Electrical Energy Efficiency in California: An Exploratory Study

    E-Print Network [OSTI]

    McKone, Thomas E.

    2011-01-01T23:59:59.000Z

    from electricity generation from California power plants. A-electricity generation capacity comes from coal-fired power plants (

  19. Public Health Benefits of End-Use Electrical Energy Efficiency in California: An Exploratory Study

    E-Print Network [OSTI]

    McKone, Thomas E.

    2011-01-01T23:59:59.000Z

    bed and bubbling bed FBe. b Average of all boiler typesbed and bubbling bed FBe. , Because diesel is a distillate

  20. Public Health Benefits of End-Use Electrical Energy Efficiency in California: An Exploratory Study

    E-Print Network [OSTI]

    McKone, Thomas E.

    2011-01-01T23:59:59.000Z

    Cogen Engine Gas Turbine Gas Turbine Combined Cycle SteamCycle Cogeneration Steam To Dow Gas Combustion Turbine GasTurbine Gas Turbine Cogen Contra Costa Mobile Gt Natural Gas

  1. ENERGY CONSERVATION: POLICY ISSUES AND END-USE SCENARIOS OF SAVINGS POTENTIAL PT.1

    E-Print Network [OSTI]

    Authors, Various

    2011-01-01T23:59:59.000Z

    RDSF), pyrolysis and incineration. Landfilling is one of theRDSF, pyrolysis and incineration--is more economically

  2. ENERGY CONSERVATION: POLICY ISSUES AND END-USE SCENARIOS OF SAVINGS POTENTIAL PT.2

    E-Print Network [OSTI]

    Authors, Various

    2011-01-01T23:59:59.000Z

    $(Thousands) b Process: Incineration RDSF Generation OilCosts $/ton(2) a Process: Incineration RDSF Generation Oilprocessing tech- niques. Incineration is clearly the most

  3. Public Health Benefits of End-Use Electrical Energy Efficiency in California: An Exploratory Study

    E-Print Network [OSTI]

    McKone, Thomas E.

    2011-01-01T23:59:59.000Z

    plants relying on enhanced oil recovery (EOR), and NOx andAgency EOR: enhanced oil recovery EP A: US EnvironmentalGas Steam Turbine/Enhanced Oil Recovery Internal Combustion

  4. INTERNATIONAL RESIDENTIAL ENERGY END USE DATA: ANALYSIS OF HISTORICAL AND PRESENT DAY STRUCTURE AND DYNAMICS

    E-Print Network [OSTI]

    Schipper, Lee

    2013-01-01T23:59:59.000Z

    all fuels except district heating. Only for Germany andSweden, and Germany had district heating. The Swedish/German

  5. Public Health Benefits of End-Use Electrical Energy Efficiency in California: An Exploratory Study

    E-Print Network [OSTI]

    McKone, Thomas E.

    2011-01-01T23:59:59.000Z

    Phase Ii Landfill Gas Sonoma Internal Combustion EngineInternal Combustion Engine Sonoma Landfill Gas Sonoma a)which report internal combustion (IC) engines as technology

  6. ENERGY CONSERVATION: POLICY ISSUES AND END-USE SCENARIOS OF SAVINGS POTENTIAL PT.2

    E-Print Network [OSTI]

    Authors, Various

    2011-01-01T23:59:59.000Z

    Efficiency** Process Process BTU/Ton of MSW Input* RDSF1 - Col. 2; Col. 4 = Col. 3/11.4 Million BTU/per ton of MSWfor RDSF and 9.1 Million BTU/ton for direct combustion and

  7. Public Health Benefits of End-Use Electrical Energy Efficiency in California: An Exploratory Study

    E-Print Network [OSTI]

    McKone, Thomas E.

    2011-01-01T23:59:59.000Z

    ~Mwe: conversion factor from Btu to MWe-y ( 3.345 x 10- MWe-insulation R-values [fe-hr OF I Btu] for electricity heatedspecific fuel, expressed as Btu/lb coal, Btu/ gal oil, Btu/

  8. Public Health Benefits of End-Use Electrical Energy Efficiency in California: An Exploratory Study

    E-Print Network [OSTI]

    McKone, Thomas E.

    2011-01-01T23:59:59.000Z

    location, whether or not cogeneration technologies are used,in rural regions use cogeneration technologies and thisof coal- powered cogeneration plants are not provided by the

  9. Table B19. Energy End Uses, Number of Buildings and Floorspace, 1999

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality", 2013,Iowa"Dakota" ,"FullWestQuantity of2". Summary5.9.

  10. Residential HVAC Data, Assumptions and Methodology for End-Use Forecasting with EPRI-REEPS 2.1

    E-Print Network [OSTI]

    Johnson, F.X.

    2010-01-01T23:59:59.000Z

    Administration. April. EPRI. 1982. Residential End-UseInstitute. EA-2512. July. EPRI. 1990. REEPS 2.0 HVAC ModelInstitute. October 11. EPRI, Electric Power Research

  11. Residential HVAC Data, Assumptions and Methodology for End-Use Forecasting with EPRI-REEPS 2.1

    E-Print Network [OSTI]

    Johnson, F.X.

    2010-01-01T23:59:59.000Z

    technologies. The heating technologies are: natural gasThe combination of a heating technology, cooling technologyCharacteristics End-Use Heating Technology Efficiency Units

  12. Residential Sector End-Use Forecasting with EPRI-REEPS 2.1: Summary Input Assumptions and Results

    E-Print Network [OSTI]

    Koomey, Jonathan G.

    2010-01-01T23:59:59.000Z

    Natural Gas Oil Lighting 0-1 hrs 1-2 his 2-3 hrs Usage levelNatural gas Oil Dishwasher End-Use Lighting 0-1 hrs 1-2 hrs UsageNatural gas Oil Dishwasher End-Use Lighting 0-1 hrs 1-2 hrs Usage

  13. Evaluating Energy Efficiency Policies with Energy-Economy Models

    SciTech Connect (OSTI)

    Mundaca, Luis; Neij, Lena; Worrell, Ernst; McNeil, Michael A.

    2010-08-01T23:59:59.000Z

    The growing complexities of energy systems, environmental problems and technology markets are driving and testing most energy-economy models to their limits. To further advance bottom-up models from a multidisciplinary energy efficiency policy evaluation perspective, we review and critically analyse bottom-up energy-economy models and corresponding evaluation studies on energy efficiency policies to induce technological change. We use the household sector as a case study. Our analysis focuses on decision frameworks for technology choice, type of evaluation being carried out, treatment of market and behavioural failures, evaluated policy instruments, and key determinants used to mimic policy instruments. Although the review confirms criticism related to energy-economy models (e.g. unrealistic representation of decision-making by consumers when choosing technologies), they provide valuable guidance for policy evaluation related to energy efficiency. Different areas to further advance models remain open, particularly related to modelling issues, techno-economic and environmental aspects, behavioural determinants, and policy considerations.

  14. Financing end-use solar technologies in a restructured electricity industry: Comparing the cost of public policies

    SciTech Connect (OSTI)

    Jones, E.; Eto, J.

    1997-09-01T23:59:59.000Z

    Renewable energy technologies are capital intensive. Successful public policies for promoting renewable energy must address the significant resources needed to finance them. Public policies to support financing for renewable energy technologies must pay special attention to interactions with federal, state, and local taxes. These interactions are important because they can dramatically increase or decrease the effectiveness of a policy, and they determine the total cost of a policy to society as a whole. This report describes a comparative analysis of the cost of public policies to support financing for two end-use solar technologies: residential solar domestic hot water heating (SDHW) and residential rooftop photovoltaic (PV) systems. The analysis focuses on the cost of the technologies under five different ownership and financing scenarios. Four scenarios involve leasing the technologies to homeowners in return for a payment that is determined by the financing requirements of each form of ownership. For each scenario, the authors examine nine public policies that might be used to lower the cost of these technologies: investment tax credits (federal and state), production tax credits (federal and state), production incentives, low-interest loans, grants (taxable and two types of nontaxable), direct customer payments, property and sales tax reductions, and accelerated depreciation.

  15. Target Allocation Methodology for China's Provinces: Energy Intensity in the 12th FIve-Year Plan

    SciTech Connect (OSTI)

    Ohshita, Stephanie; Price, Lynn

    2011-03-21T23:59:59.000Z

    Experience with China's 20% energy intensity improvement target during the 11th Five-Year Plan (FYP) (2006-2010) has shown the challenges of rapidly setting targets and implementing measures to meet them. For the 12th FYP (2011-2015), there is an urgent need for a more scientific methodology to allocate targets among the provinces and to track physical and economic indicators of energy and carbon saving progress. This report provides a sectoral methodology for allocating a national energy intensity target - expressed as percent change in energy per unit gross domestic product (GDP) - among China's provinces in the 12th FYP. Drawing on international experience - especially the European Union (EU) Triptych approach for allocating Kyoto carbon targets among EU member states - the methodology here makes important modifications to the EU approach to address an energy intensity rather than a CO{sub 2} emissions target, and for the wider variation in provincial energy and economic structure in China. The methodology combines top-down national target projections and bottom-up provincial and sectoral projections of energy and GDP to determine target allocation of energy intensity targets. Total primary energy consumption is separated into three end-use sectors - industrial, residential, and other energy. Sectoral indicators are used to differentiate the potential for energy saving among the provinces. This sectoral methodology is utilized to allocate provincial-level targets for a national target of 20% energy intensity improvement during the 12th FYP; the official target is determined by the National Development and Reform Commission. Energy and GDP projections used in the allocations were compared with other models, and several allocation scenarios were run to test sensitivity. The resulting allocations for the 12th FYP offer insight on past performance and offer somewhat different distributions of provincial targets compared to the 11th FYP. Recommendations for reporting and monitoring progress on the targets, and methodology improvements, are included.

  16. America's Bottom-Up Climate Change Mitigation Policy

    E-Print Network [OSTI]

    Lutsey, Nicholas P.; Sperling, Dan

    2008-01-01T23:59:59.000Z

    and developing emissions trading mechanisms to connect andand development of emissions trading or cap-and-tradesector market-based emissions trading system in the Western

  17. America's Bottom-Up Climate Change Mitigation Policy

    E-Print Network [OSTI]

    Lutsey, Nicholas P.; Sperling, Dan

    2008-01-01T23:59:59.000Z

    large conventional hydroelectric power, municipal solidconventional large hydroelectric power). To quantify thelarge conventional hydroelectric power is not included (this

  18. Introduction Within the context of a "bottom-up" ap-

    E-Print Network [OSTI]

    Yang, Peidong

    )substrate(Figure1a).4 A similar level of growth control can be achieved for GaN (Figure 1b) and Si 2 by adjusting the initial nano- cluster density on the substrates. In addi- tion, we have also the use of metalorganic chemical vapor deposition (MOCVD) and appropriate substrate selec- tion to control

  19. Assembly of a Molecular Needle, from the Bottom Up

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

    representation of the EscJ monomer, showing two domains. Top right: Arc-shaped EscJ tetramer. Bottom left: Interface between domain 1 of two EscJ monomers, colored green and...

  20. The application of a hybrid energy-economy model to a key developing country China

    E-Print Network [OSTI]

    The application of a hybrid energy-economy model to a key developing country ­ China JianJun Tu, a hybrid (bottom-up/top-down) energy- economy model, to test how different policy packages could, Vancouver, V5A 1S6, Canada E-mail (Jaccard): Jaccard@sfu.ca Energy security, local air pollution and GHG

  1. 1980 survey and evaluation of utility conservation, load management, and solar end-use projects. Volume 3: utility load management projects. Final report

    SciTech Connect (OSTI)

    Not Available

    1982-01-01T23:59:59.000Z

    The results of the 1980 survey of electric utility-sponsored energy conservation, load management, and end-use solar energy conversion projects are described. The work is an expansion of a previous survey and evaluation and has been jointly sponsored by EPRI and DOE through the Oak Ridge National Laboratory. There are three volumes and a summary document. Each volume presents the results of an extensive survey to determine electric utility involvement in customer-side projects related to the particular technology (i.e., conservation, solar, or load management), selected descriptions of utility projects and results, and first-level technical and economic evaluations.

  2. July 11 Public Meeting: Physical Characterization of Grid-Connected Commercial And Residential Building End-Use Equipment And Appliances

    Broader source: Energy.gov [DOE]

    These documents contain the three slide decks presented at the public meeting on the Physical Characterization of Grid-Connected Commercial and Residential Buildings End-Use Equipment and Appliances, held on July 11, 2014 in Washington, DC.

  3. Public Interest Energy Research (PIER) Program INTERIM REPORT

    E-Print Network [OSTI]

    Public Interest Energy Research (PIER) Program INTERIM REPORT SOLAR REFLECTANCES OF ROOFS: · Buildings EndUse Energy Efficiency · Energy Innovations Small Grants · EnergyRelated Environmental/Agricultural/Water EndUse Energy Efficiency · Renewable Energy Technologies · Transportation Solar Reflectances

  4. U.S. Energy Information Administration (EIA) - Sector

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

    Commercial Sector Energy Demand On This Page End-use efficiency... Growth in electricity use... Core technologies... Improved interconnection... End-use efficiency improvements...

  5. Modelling the Energy Demand of Households in a Combined

    E-Print Network [OSTI]

    Steininger, Karl W.

    . Emissions from passenger transport, households'electricity and heat consumption are growing rapidly despite demand analysis for electricity (e.g. Larsen and Nesbakken, 2004; Holtedahl and Joutz, 2004Modelling the Energy Demand of Households in a Combined Top Down/Bottom Up Approach Kurt Kratena

  6. Improving behavioral realism in hybrid energy-economy models using discrete choice

    E-Print Network [OSTI]

    Improving behavioral realism in hybrid energy-economy models using discrete choice studies Abstract Hybrid energy-economy models combine top-down and bottom-up approaches to explore behaviorally models to inform key behavioral parameters in CIMS, a hybrid model. The discrete choice models

  7. Residential Behavioral Savings: An Analysis of Principal Electricity End Uses in British Columbia

    E-Print Network [OSTI]

    Tiedemann, Kenneth Mr.

    2013-01-01T23:59:59.000Z

    Fowlie. 2007. Demand-Side Management and Energy Efficiencyand building shells. Demand side management programs have

  8. End-use electrification in the residential sector : a general equilibrium analysis of technology advancements

    E-Print Network [OSTI]

    Madan, Tanvir Singh

    2012-01-01T23:59:59.000Z

    The residential sector in the U.S. is responsible for about 20% of the country's primary energy use (EIA, 2011). Studies estimate that efficiency improvements in this sector can reduce household energy consumption by over ...

  9. Energy Conservation: Policy Issues and End-Use Scenarios of Savings Potential -- Part 4, Energy Efficient Recreational Travel

    E-Print Network [OSTI]

    Cornwall, B.

    2011-01-01T23:59:59.000Z

    arrive by car (Booz, Allen & Hamilton 1974:27). SuchD.C. October. f of Booz, Allen & Hamilton Sensitivity of the

  10. Robust ASR front-end using spectral-based and discriminant features: experiments on the Aurora tasks

    E-Print Network [OSTI]

    Dupont, Stéphane

    Robust ASR front-end using spectral-based and discriminant features: experiments on the Aurora was tested on the set of speech corpora used for the "Aurora" evaluation. Using the feature stream generated and server side ASR processing, a standartization initiative called "Aurora" was initiated within European

  11. Control Policy: End-User and End-Use Based Part 744--page 1 Export Administration Regulations October 1, 2001

    E-Print Network [OSTI]

    Bernstein, Daniel

    of items subject to the EAR to defined nuclear, missile, chemical and biological weapons, and nuclear nuclear, missile, chemical, or biological end- uses regardless of whether that support involves the export items for certain aircraft and vessels. In addition, these sections include license review standards

  12. Table 3. Top Five Retailers of Electricity, with End Use Sectors...

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

    3,"Colorado River Comm of Nevada","Public",1886849,0,1102253,784596,0 4,"Shell Energy North America (US), L.P.","Investor-Owned",1020000,0,0,1020000,0 5,"Wells Rural...

  13. ,"U.S. Adjusted Distillate Fuel Oil and Kerosene Sales by End Use"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National and Regional Data; Row: NAICS Codes; Column: Energy Sources andPlant Liquids,+ LeasePrice SoldPlantGross

  14. ,"U.S. Distillate Fuel Oil and Kerosene Sales by End Use"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National and Regional Data; Row: NAICS Codes; Column: Energy Sources andPlant Liquids,+ LeasePrice SoldPlantGrossDistillateReserves+

  15. ,"U.S. Natural Gas Consumption by End Use"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National and Regional Data; Row: NAICS Codes; Column: Energy Sources andPlant Liquids,+ LeasePriceExpectedOther

  16. ,"U.S. Natural Gas Consumption by End Use"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventional Gasoline Sales to End Users, Total

  17. U.S. Adjusted Distillate Fuel Oil and Kerosene Sales by End Use

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2,EHSS A-Zandofpoint motional%^ U N C L A SDistillate

  18. U.S. Adjusted Sales of Distillate Fuel Oil by End Use

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2,EHSS A-Zandofpoint motional%^ U N C L A

  19. U.S. Adjusted Sales of Residual Fuel Oil by End Use

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2,EHSS A-Zandofpoint motional%^ U N C L AKerosene

  20. U.S. Distillate Fuel Oil and Kerosene Sales by End Use

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2,EHSS A-Zandofpoint motional%^602SWPA

  1. ,"U.S. Adjusted Sales of Distillate Fuel Oil by End Use"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National and Regional Data; Row: NAICS Codes; Column: Energy Sources andPlant Liquids,+ LeasePrice SoldPlantGrossDistillate Fuel Oil by End

  2. ,"U.S. Adjusted Sales of Residual Fuel Oil by End Use"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National and Regional Data; Row: NAICS Codes; Column: Energy Sources andPlant Liquids,+ LeasePrice SoldPlantGrossDistillate Fuel Oil by

  3. ,"U.S. Total Sales of Residual Fuel Oil by End Use"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National and Regional Data; Row: NAICS Codes; Column: Energy SourcesRefinery, Bulk Terminal, and Natural Gas Plant StocksPetroleum ProductSales

  4. Distribution Category UC-98 Consumption End-Use A Comparison of Measures

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001)gasoline353/06) 2Yonthly Energy :

  5. Table 3. Top five retailers of electricity, with end use sectors, 2013

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14Total Delivered Residentialtight oilU.S.

  6. Table 3. Top five retailers of electricity, with end use sectors, 2013

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14Total Delivered Residentialtight oilU.S.Arkansas"

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

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    % 2 of the GHG emissions. That is to say that some efforts in demand side management should have In France in 2008, the buildings (housing stock) are responsible for 27% 1 of the final energy demand and 16 points that allow to build-up a relevant load curve. This will lead us to step down at the appliance

  8. Refining and end use study of coal liquids. Quarterly report, January--March 1996

    SciTech Connect (OSTI)

    NONE

    1996-09-01T23:59:59.000Z

    Bechtel, with Southwest Research Institute, Amoco Oil R&D, and the M. W. Kellogg Co. as subcontractors, initiated a study on November 1, 1993, for the US Department of Energy`s (DOE`s) Pittsburgh Energy Technology Center (PETC) to determine the most cost effective and suitable combination of existing petroleum refinery processes needed to make specification transportation fuels or blending stocks, from direct and indirect coal liquefaction product liquids. A key objective is to determine the most desirable ways of integrating coal liquefaction liquids into existing petroleum refineries to produce transportation fuels meeting current and future, e.g. year 2000, Clean Air Act Amendment (CAAA) standards. An integral part of the above objectives is to test the fuels or blends produced and compare them with established ASTM fuels. The comparison will include engine tests to ascertain compliance of the fuels produced with CAAA and other applicable fuel quality and performance standards. The final part of the project includes a detailed economic evaluation of the cost of processing the coal liquids to their optimum products. The cost analyses is for the incremental processing cost; in other words, the feed is priced at zero dollars. The study reflects costs for operations using state of the art refinery technology; no capital costs for building new refineries is considered. Some modifications to the existing refinery may be required. Economy of scale dictates the minimum amount of feedstock that should be processed. The major efforts conducted during the first quarter of 1996 were in the areas of: DL2 light distillate hydrotreating; and DL2 heave distillate catalytic cracking.

  9. Microsoft Word - Major end uses front page v2 2015-03-31.docx

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOEThe Bonneville PowerCherries 82981-1cnHighandSWPA / SPRA / USACE LMI-EFRC Kick-Off Meeting10, Market1Closure2

  10. Microsoft Word - Major end uses front page v2 2015-03-31.docx

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOEThe Bonneville PowerCherries 82981-1cnHighandSWPA / SPRA / USACE LMI-EFRC Kick-Off Meeting10, Market1Closure23

  11. Microsoft Word - Major end uses front page v2 2015-03-31.docx

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOEThe Bonneville PowerCherries 82981-1cnHighandSWPA / SPRA / USACE LMI-EFRC Kick-Off Meeting10, Market1Closure234

  12. Microsoft Word - Major end uses front page v2 2015-03-31.docx

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOEThe Bonneville PowerCherries 82981-1cnHighandSWPA / SPRA / USACE LMI-EFRC Kick-Off Meeting10, Market1Closure2345

  13. U.S. Sales of Distillate Fuel Oil by End Use

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40Coal Stocks at Commercial and InstitutionalArea: U.S. East Coast502Propane,Area:

  14. U.S. Sales of Residual Fuel Oil by End Use

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40Coal Stocks at Commercial and InstitutionalArea: U.S. EastArea: U.S. East Coast

  15. Microsoft Word - Major end uses front page v2 2015-03-31.docx

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17 3400,Information Administration2 U.S.and Winter Fuels8 11 1

  16. An Assessment of Interval Data and Their Potential Application to Residential Electricity End-Use Modeling

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001)gasoline prices4 OilU.S. Offshore U.S.:7)An Assessment

  17. Renewable Electricity Futures Study. Volume 3: End-Use Electricity Demand

    SciTech Connect (OSTI)

    Hostick, D.; Belzer, D.B.; Hadley, S.W.; Markel, T.; Marnay, C.; Kintner-Meyer, M.

    2012-06-01T23:59:59.000Z

    The Renewable Electricity Futures (RE Futures) Study investigated the challenges and impacts of achieving very high renewable electricity generation levels in the contiguous United States by 2050. The analysis focused on the sufficiency of the geographically diverse U.S. renewable resources to meet electricity demand over future decades, the hourly operational characteristics of the U.S. grid with high levels of variable wind and solar generation, and the potential implications of deploying high levels of renewables in the future. RE Futures focused on technical aspects of high penetration of renewable electricity; it did not focus on how to achieve such a future through policy or other measures. Given the inherent uncertainties involved with analyzing alternative long-term energy futures as well as the multiple pathways that might be taken to achieve higher levels of renewable electricity supply, RE Futures explored a range of scenarios to investigate and compare the impacts of renewable electricity penetration levels (30%-90%), future technology performance improvements, potential constraints to renewable electricity development, and future electricity demand growth assumptions. RE Futures was led by the National Renewable Energy Laboratory (NREL) and the Massachusetts Institute of Technology (MIT).

  18. Agenda for Public Meeting on the Physical Characterization of Grid-Connected Commercial and Residential Buildings End-Use Equipment and Appliances

    Broader source: Energy.gov [DOE]

    Download the agenda below for the July 11 Public Meeting on the Physical Characterization of Grid-Connected Commercial and  Residential Buildings End-Use Equipment and Appliances.

  19. How many people actually see the price signal? Quantifying market failures in the end use of energy

    E-Print Network [OSTI]

    Meier, Alan; Eide, Anita

    2007-01-01T23:59:59.000Z

    landlords select the water heaters but their tenants mustin a high efficiency water heater. Another example is in thefamily home select the water heater and pay for the water

  20. How many people actually see the price signal? Quantifying market failures in the end use of energy

    E-Print Network [OSTI]

    Meier, Alan; Eide, Anita

    2007-01-01T23:59:59.000Z

    as the project manager. The IEA and the authors gratefullyand the United States. The IEA report is scheduled forpresents part of a larger IEA study that will be published

  1. How many people actually see the price signal? Quantifying market failures in the end use of energy

    E-Print Network [OSTI]

    Meier, Alan; Eide, Anita

    2007-01-01T23:59:59.000Z

    family home select the water heater and pay for the waterlandlords select the water heaters but their tenants mustin a high efficiency water heater. Another example is in the

  2. The Boom of Electricity Demand in the Residential Sector in the Developing World and the Potential for Energy Efficiency

    SciTech Connect (OSTI)

    Letschert, Virginie; McNeil, Michael A.

    2008-05-13T23:59:59.000Z

    With the emergence of China as the world's largest energy consumer, the awareness of developing country energy consumption has risen. According to common economic scenarios, the rest of the developing world will probably see an economic expansion as well. With this growth will surely come continued rapid growth in energy demand. This paper explores the dynamics of that demand growth for electricity in the residential sector and the realistic potential for coping with it through efficiency. In 2000, only 66% of developing world households had access to electricity. Appliance ownership rates remain low, but with better access to electricity and a higher income one can expect that households will see their electricity consumption rise significantly. This paper forecasts developing country appliance growth using econometric modeling. Products considered explicitly - refrigerators, air conditioners, lighting, washing machines, fans, televisions, stand-by power, water heating and space heating - represent the bulk of household electricity consumption in developing countries. The resulting diffusion model determines the trend and dynamics of demand growth at a level of detail not accessible by models of a more aggregate nature. In addition, the paper presents scenarios for reducing residential consumption through cost-effective and/or best practice efficiency measures defined at the product level. The research takes advantage of an analytical framework developed by LBNL (BUENAS) which integrates end use technology parameters into demand forecasting and stock accounting to produce detailed efficiency scenarios, which allows for a realistic assessment of efficiency opportunities at the national or regional level. The past decades have seen some of the developing world moving towards a standard of living previously reserved for industrialized countries. Rapid economic development, combined with large populations has led to first China and now India to emerging as 'energy giants', a phenomenon that is expected to continue, accelerate and spread to other countries. This paper explores the potential for slowing energy consumption and greenhouse gas emissions in the residential sector in developing countries and evaluates the potential of energy savings and emissions mitigation through market transformation programs such as, but not limited to Energy Efficiency Standards and Labeling (EES&L). The bottom-up methodology used allows one to identify which end uses and regions have the greatest potential for savings.

  3. Measured electric hot water standby and demand loads from Pacific Northwest homes. End-Use Load and Consumer Assessment Program

    SciTech Connect (OSTI)

    Pratt, R.G.; Ross, B.A.

    1991-11-01T23:59:59.000Z

    The Bonneville Power Administration began the End-Use Load and Consumer Assessment Program (ELCAP) in 1983 to obtain metered hourly end-use consumption data for a large sample of new and existing residential and commercial buildings in the Pacific Northwest. Loads and load shapes from the first 3 years of data fro each of several ELCAP residential studies representing various segments of the housing population have been summarized by Pratt et al. The analysis reported here uses the ELCAP data to investigate in much greater detail the relationship of key occupant and tank characteristics to the consumption of electricity for water heating. The hourly data collected provides opportunities to understand electricity consumption for heating water and to examine assumptions about water heating that are critical to load forecasting and conservation resource assessments. Specific objectives of this analysis are to: (A) determine the current baseline for standby heat losses by determining the standby heat loss of each hot water tank in the sample, (B) examine key assumptions affecting standby heat losses such as hot water temperatures and tank sizes and locations, (C) estimate, where possible, impacts on standby heat losses by conservation measures such as insulating tank wraps, pipe wraps, anticonvection valves or traps, and insulating bottom boards, (D) estimate the EF-factors used by the federal efficiency standards and the nominal R-values of the tanks in the sample, (E) develop estimates of demand for hot water for each home in the sample by subtracting the standby load from the total hot water load, (F) examine the relationship between the ages and number of occupants and the hot water demand, (G) place the standby and demand components of water heating electricity consumption in perspective with the total hot water load and load shape.

  4. ENERGY EFFICIENCY TECHNOLOGY ROADMAP

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

    renewable generation, grid supply, energy storage, distribution, communication, demand control, and end uses. Workshop findings are pending as of March 2013. Lawrence...

  5. Residential Sector End-Use Forecasting with EPRI-REEPS 2.1: Summary Input Assumptions and Results

    E-Print Network [OSTI]

    Koomey, Jonathan G.

    2010-01-01T23:59:59.000Z

    US DOE. 1995a. Annual Energy Outlook 1995, with ProjectionsAdministration (ELA) 1995 Annual Energy Outlook (AEO); 1990of Energy's Annual Energy Outlook ( US DOE 1995a). A l l

  6. 2014-04-30 Public Meeting Agenda: Physical Characterization of Smart and Grid-Connected Commercial and Residential Buildings End-Use Equipment and Appliances

    Broader source: Energy.gov [DOE]

    This document is the agenda for the Physical Characterization of Smart and Grid-Connected Commercial and Residential Buildings End-Use Equipment and Appliances public meeting being held on April 30, 2014.

  7. 2014-04-30 Public Meeting Presentation Slides: Physical Characterization of Smart and Grid-Connected Commercial and Residential Buildings End-Use Equipment and Appliances

    Broader source: Energy.gov [DOE]

    These documents contain slide decks presented at the Physical Characterization of Smart and Grid-Connected Commercial and Residential Buildings End-Use Equipment and Appliances public meeting held on April 30, 2014.

  8. Residential HVAC Data, Assumptions and Methodology for End-Use Forecasting with EPRI-REEPS 2.1

    E-Print Network [OSTI]

    Johnson, F.X.

    2010-01-01T23:59:59.000Z

    assessing future trends in energy consumption at the end-usedetermine the basic trend of energy consumption and are used

  9. RESIDENTIAL SECTOR END-USE FORECASTING WITH EPRI-REEPS 2.1: SUMMARY INPUT ASSUMPTIONS AND RESULTS

    E-Print Network [OSTI]

    of Energy. We use the Electric Power Research Institute's (EPRI's) REEPS model, as reconfigured to reflect was supported by the Assistant Secretary for Energy Efficiency and Renewable Energy, Office of Building ....................................................................................................1 2. OVERVIEW OF THE REEPS MODEL..............................................................1

  10. Residential HVAC Data, Assumptions and Methodology for End-Use Forecasting with EPRI-REEPS 2.1

    E-Print Network [OSTI]

    Johnson, F.X.

    2010-01-01T23:59:59.000Z

    Dubin, Rivers Associates. EIA. 1989. Housing CharacteristicsU.S. Dept. of Energy, Washington, DC. DOE/EIA- 0314(87).May. EIA. 1990. Energy Consumption and Conservation

  11. Residential HVAC Data, Assumptions and Methodology for End-Use Forecasting with EPRI-REEPS 2.1

    E-Print Network [OSTI]

    Johnson, F.X.

    2010-01-01T23:59:59.000Z

    equipment (EIA 1993), and a compilation of utility surveySurvey (RECS) conducted by the Energy Information Administration (EIAMay. EIA. 1993. 1990 Residential Energy Consumption Survey (

  12. Energy Data Sourcebook for the U.S. Residential Sector

    E-Print Network [OSTI]

    Wenzel, T.P.

    2010-01-01T23:59:59.000Z

    1987b). 2.1. Unit Energy Consumptions Data on end-use unitresidential sector energy consumption data, and typicallyNational Interim Energy Consumption Survey Data, prepared

  13. Energy Conservation Policy Issues and End-Use Scenarios of Savings Potential--Part 5. Energy Efficient Buildings: The Cause of Litigation Against Energy Conservation Building Codes

    E-Print Network [OSTI]

    Benenson, P.

    2011-01-01T23:59:59.000Z

    methods or passive solar designs. C. CASES REVIEWEDmany proposed designs, such as passive solar plans. At the

  14. Energy Conservation Policy Issues and End-Use Scenarios of Savings Potential--Part 5. Energy Efficient Buildings: The Cause of Litigation Against Energy Conservation Building Codes

    E-Print Network [OSTI]

    Benenson, P.

    2011-01-01T23:59:59.000Z

    for mortgage payments (Booz-Allen and Hamilton 1977). SuchREFERENCES Booz-Allen and Hamilton, Inc. Methodology to

  15. High-Energy Astrophysics and Cosmology

    E-Print Network [OSTI]

    John Ellis

    2002-10-26T23:59:59.000Z

    Interfaces between high-energy physics, astrophysics and cosmology are reviewed, with particular emphasis on the important roles played by high-energy cosmic-ray physics. These include the understanding of atmospheric neutrinos, the search for massive cold dark matter particles and possible tests of models of quantum gravity. In return, experiments at the LHC may be useful for refining models of ultra-high-energy cosmic rays, and thereby contributing indirectly to understanding their origin. Only future experiments will be able to tell whether these are due to some bottom-up astrophysical mechanism or some top-down cosmological mechanism.

  16. Methodology for Modeling Building Energy Performance across the Commercial Sector

    SciTech Connect (OSTI)

    Griffith, B.; Long, N.; Torcellini, P.; Judkoff, R.; Crawley, D.; Ryan, J.

    2008-03-01T23:59:59.000Z

    This report uses EnergyPlus simulations of each building in the 2003 Commercial Buildings Energy Consumption Survey (CBECS) to document and demonstrate bottom-up methods of modeling the entire U.S. commercial buildings sector (EIA 2006). The ability to use a whole-building simulation tool to model the entire sector is of interest because the energy models enable us to answer subsequent 'what-if' questions that involve technologies and practices related to energy. This report documents how the whole-building models were generated from the building characteristics in 2003 CBECS and compares the simulation results to the survey data for energy use.

  17. China Energy Databook - Rev. 4

    E-Print Network [OSTI]

    Sinton Editor, J.E.

    2010-01-01T23:59:59.000Z

    1992 12. End Use Electricity Consumption by Sector, 1992 13.Sources) Per Capita Electricity Consumption, 1990 EnergyUrban Rural 2. Electricity Consumption Shares Year Urban TWh

  18. Residential HVAC Data, Assumptions and Methodology for End-Use Forecasting with EPRI-REEPS 2.1

    E-Print Network [OSTI]

    Johnson, F.X.

    2010-01-01T23:59:59.000Z

    Manufactured Home Room Heating Market Shares". Lawrenceset based on the market share of heating equipment in newMarket for Energy Efficiency in Residential Appliances Including Heating and

  19. Residential Sector End-Use Forecasting with EPRI-REEPS 2.1: Summary Input Assumptions and Results

    E-Print Network [OSTI]

    Koomey, Jonathan G.

    2010-01-01T23:59:59.000Z

    $/household 10e3 Site Energy Prices Electricity ElectricityAverage electricity price Average household disposableAverage price of electricity Average household disposable

  20. Alternative Strategies for Low-Pressure End Uses; Industrial Technologies Program (ITP) Compressed Air Tip Sheet #11 (Fact Sheet)

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels DataDepartment of Energy Your Density Isn't Your Destiny: The Future of1Albuquerque, NM -Alicia Moulton AboutDepartment of Energy1 *

  1. Opportunities for Energy Efficiency and Demand Response in the California Cement Industry

    E-Print Network [OSTI]

    Olsen, Daniel

    2012-01-01T23:59:59.000Z

    Opportunities for Energy  Efficiency and Demand Response in Agricultural/Water End?Use Energy Efficiency Program.    i 1   4.0   Energy Efficiency and Demand Response 

  2. Quantifying the Effect of the Principal-Agent Problem on US Residential Energy Use

    E-Print Network [OSTI]

    Murtishaw, Scott; Sathaye, Jayant

    2006-01-01T23:59:59.000Z

    of housing and energy consumption data. Our research hashousing and end use energy consumption data available. Theunits are MFRs. Energy consumption data were taken from the

  3. ResPoNSe: modeling the wide variability of residential energy consumption.

    E-Print Network [OSTI]

    Peffer, Therese; Burke, William; Auslander, David

    2010-01-01T23:59:59.000Z

    affect appliance energy consumption. For example, differentStates, 2005 Residential Energy Consumption Survey: HousingModeling of End-Use Energy Consumption in the Residential

  4. TECHNOLOGY DATA CHARACTERIZING LIGHTING IN COMMERCIAL BUILDINGS: APPLICATION TO END-USE FORECASTING WITH COMMEND 4.0

    E-Print Network [OSTI]

    LBL-34243 UC - 1600 TECHNOLOGY DATA CHARACTERIZING LIGHTING IN COMMERCIAL BUILDINGS: APPLICATION Technologies, and the Office of Environmental Analysis, Office of Policy, Planning, and Analysis of the U.S. Department of Energy under Contract No. DE-AC03-76SF00098. #12;Technology Data Characterizing Lighting

  5. Energy Use in China: Sectoral Trends and Future Outlook

    SciTech Connect (OSTI)

    Zhou, Nan; McNeil, Michael A.; Fridley, David; Lin, Jiang; Price,Lynn; de la Rue du Can, Stephane; Sathaye, Jayant; Levine, Mark

    2007-10-04T23:59:59.000Z

    This report provides a detailed, bottom-up analysis ofenergy consumption in China. It recalibrates official Chinese governmentstatistics by reallocating primary energy into categories more commonlyused in international comparisons. It also provides an analysis of trendsin sectoral energy consumption over the past decades. Finally, itassesses the future outlook for the critical period extending to 2020,based on assumptions of likely patterns of economic activity,availability of energy services, and energy intensities. The followingare some highlights of the study's findings: * A reallocation of sectorenergy consumption from the 2000 official Chinese government statisticsfinds that: * Buildings account for 25 percent of primary energy, insteadof 19 percent * Industry accounts for 61 percent of energy instead of 69percent * Industrial energy made a large and unexpected leap between2000-2005, growing by an astonishing 50 percent in the 3 years between2002 and 2005. * Energy consumption in the iron and steel industry was 40percent higher than predicted * Energy consumption in the cement industrywas 54 percent higher than predicted * Overall energy intensity in theindustrial sector grew between 2000 and 2003. This is largely due tointernal shifts towards the most energy-intensive sub-sectors, an effectwhich more than counterbalances the impact of efficiency increases. *Industry accounted for 63 percent of total primary energy consumption in2005 - it is expected to continue to dominate energy consumption through2020, dropping only to 60 percent by that year. * Even assuming thatgrowth rates in 2005-2020 will return to the levels of 2000-2003,industrial energy will grow from 42 EJ in 2005 to 72 EJ in 2020. * Thepercentage of transport energy used to carry passengers (instead offreight) will double from 37 percent to 52 percent between 2000 to 2020,.Much of this increase is due to private car ownership, which willincrease by a factor of 15 from 5.1 million in 2000 to 77 million in2020. * Residential appliance ownership will show signs of saturation inurban households. The increase in residential energy consumption will belargely driven by urbanization, since rural homes will continue to havelow consumption levels. In urban households, the size of appliances willincrease, but its effect will be moderated by efficiency improvements,partially driven by government standards. * Commercial energy increaseswill be driven both by increases in floor space and by increases inpenetration of major end uses such as heating and cooling. Theseincreases will be moderated somewhat, however, by technology changes,such as increased use of heat pumps. * China's Medium- and Long-TermDevelopment plan drafted by the central government and published in 2004calls for a quadrupling of GDP in the period from 2000-2020 with only adoubling in energy consumption during the same period. A bottom-upanalysis with likely efficiency improvements finds that energyconsumption will likely exceed the goal by 26.12 EJ, or 28 percent.Achievements of these goals will there fore require a more aggressivepolicy of encouraging energy efficiency.

  6. National Energy Efficiency Evaluation, Measurement and Verification (EM&V) Standard: Scoping Study of Issues and Implementation Requirements

    SciTech Connect (OSTI)

    Schiller Consulting, Inc.; Schiller, Steven R.; Goldman, Charles A.; Galawish, Elsia

    2011-02-04T23:59:59.000Z

    This report is a scoping study that identifies issues associated with developing a national evaluation, measurement and verification (EM&V) standard for end-use, non-transportation, energy efficiency activities. The objectives of this study are to identify the scope of such a standard and define EM&V requirements and issues that will need to be addressed in a standard. To explore these issues, we provide and discuss: (1) a set of definitions applicable to an EM&V standard; (2) a literature review of existing guidelines, standards, and 'initiatives' relating to EM&V standards as well as a review of 'bottom-up' versus 'top-down' evaluation approaches; (3) a summary of EM&V related provisions of two recent federal legislative proposals (Congressman Waxman's and Markey's American Clean Energy and Security Act of 2009 and Senator Bingaman's American Clean Energy Leadership Act of 2009) that include national efficiency resource requirements; (4) an annotated list of issues that that are likely to be central to, and need to be considered when, developing a national EM&V standard; and (5) a discussion of the implications of such issues. There are three primary reasons for developing a national efficiency EM&V standard. First, some policy makers, regulators and practitioners believe that a national standard would streamline EM&V implementation, reduce costs and complexity, and improve comparability of results across jurisdictions; although there are benefits associated with each jurisdiction setting its own EM&V requirements based on their specific portfolio and evaluation budgets and objectives. Secondly, if energy efficiency is determined by the US Environmental Protection Agency to be a Best Available Control Technology (BACT) for avoiding criteria pollutant and/or greenhouse gas emissions, then a standard can be required for documenting the emission reductions resulting from efficiency actions. The third reason for a national EM&V standard is that such a standard is likely to be required as a result of future federal energy legislation that includes end-use energy efficiency, either as a stand-alone energy-efficiency resource standard (EERS) or as part of a clean energy or renewable energy standard. This study is focused primarily on this third reason and thus explores issues associated with a national EM&V standard if energy efficiency is a qualifying resource in federal clean energy legislation. Developing a national EM&V standard is likely to be a lengthy process; this study focuses on the critical first step of identifying the issues that must be addressed in a future standard. Perhaps the most fundamental of these issues is 'how good is good enough?' This has always been the fundamental issue of EM&V for energy efficiency and is a result of the counter-factual nature of efficiency. Counter-factual in that savings are not measured, but estimated to varying degrees of accuracy by comparing energy consumption after a project (program) is implemented with what is assumed to have been the consumption of energy in the absence of the project (program). Therefore, the how good is good enough question is a short version of asking how certain does one have to be of the energy savings estimate that results from EM&V activities and is that level of certainty properly balanced against the amount of effort (resources, time, money) that is utilized to obtain that level of certainty. The implication is that not only should energy efficiency investments be cost-effective, but EM&V investments should consider risk management principles and thus also balance the costs and value of information derived from EM&V (EM&V should also be cost-effective).

  7. Public Interest Energy Research (PIER) Program FINAL PROJECT REPORT

    E-Print Network [OSTI]

    PHOTOVOLTAICS ROOFING SYSTEM Prepared for: California Energy Commission Prepared by: United Solar Ovonics&D program areas: · Buildings EndUse Energy Efficiency · Energy Innovations Small Grants · Energy · Industrial/Agricultural/Water EndUse Energy Efficiency · Renewable Energy Technologies · Transportation

  8. April 30 Public Meeting: Physical Characterization of Smart and Grid-Connected Commercial and Residential Building End-Use Equipment and Appliances

    Broader source: Energy.gov [DOE]

    These documents contain slide decks presented at the Physical Characterization of Smart and Grid-Connected Commercial and Residential Buildings End-Use Equipment and Appliances public meeting held on April 30, 2014. The first document includes the first presentation from the meeting: DOE Vision and Objectives. The second document includes all other presentations from the meeting: Terminology and Definitions; End-User and Grid Services; Physical Characterization Framework; Value, Benefits & Metrics.

  9. China Energy Databook - Rev. 4

    E-Print Network [OSTI]

    Sinton Editor, J.E.

    2010-01-01T23:59:59.000Z

    continued growth of its coal- dominated energy system, Chinasectoral end use from coal China Energy Databook IX-3 (TableAND EXPORTS Net Energy Exports Coal Imports and Exports by

  10. Engineer End Uses for Maximum Efficiency; Industrial Technologies Program (ITP) Compressed Air Tip Sheet #10 (Fact Sheet)

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels DataDepartment of Energy Your Density Isn't Your Destiny:RevisedAdvisoryStandard |inHVACEnforcementEngaging Students in20 * August 2004

  11. Estimates of U.S. Commercial Building Electricity Intensity Trends: Issues Related to End-Use and Supply Surveys

    SciTech Connect (OSTI)

    Belzer, David B.

    2004-09-04T23:59:59.000Z

    This report examines measurement issues related to the amount of electricity used by the commercial sector in the U.S. and the implications for historical trends of commercial building electricity intensity (kWh/sq. ft. of floor space). The report compares two (Energy Information Administration) sources of data related to commercial buildings: the Commercial Building Energy Consumption Survey (CBECS) and the reporting by utilities of sales to commercial customers (survey Form-861). Over past two decades these sources suggest significantly different trend rates of growth of electricity intensity, with the supply (utility)-based estimate growing much faster than that based only upon the CBECS. The report undertakes various data adjustments in an attempt to rationalize the differences between these two sources. These adjustments deal with: 1) periodic reclassifications of industrial vs. commercial electricity usage at the state level and 2) the amount of electricity used by non-enclosed equipment (non-building use) that is classified as commercial electricity sales. In part, after applying these adjustments, there is a good correspondence between the two sources over the the past four CBECS (beginning with 1992). However, as yet, there is no satisfactory explanation of the differences between the two sources for longer periods that include the 1980s.

  12. China Energy and Emissions Paths to 2030

    SciTech Connect (OSTI)

    Fridley, David; Zheng, Nina; Zhou, Nan; Ke, Jing; Hasanbeigi, Ali; Morrow, Bill; Price, Lynn

    2011-01-14T23:59:59.000Z

    After over two decades of staggering economic growth and soaring energy demand, China has started taking serious actions to reduce its economic energy and carbon intensity by setting short and medium-term intensity reduction targets, renewable generation targets and various supporting policies and programs. In better understanding how further policies and actions can be taken to shape China's future energy and emissions trajectory, it is important to first identify where the largest opportunities for efficiency gains and emission reduction lie from sectoral and end-use perspectives. Besides contextualizing China's progress towards reaching the highest possible efficiency levels through the adoption of the most advanced technologies from a bottom-up perspective, the actual economic costs and benefits of adopting efficiency measures are also assessed in this study. This study presents two modeling methodologies that evaluate both the technical and economic potential of raising China's efficiency levels to the technical maximum across sectors and the subsequent carbon and energy emission implications through 2030. The technical savings potential by efficiency measure and remaining gap for improvements are identified by comparing a reference scenario in which China continues the current pace of with a Max Tech scenario in which the highest technically feasible efficiencies and advanced technologies are adopted irrespective of costs. In addition, from an economic perspective, a cost analysis of selected measures in the key industries of cement and iron and steel help quantify the actual costs and benefits of achieving the highest efficiency levels through the development of cost of conserved energy curves for the sectors. The results of this study show that total annual energy savings potential of over one billion tonne of coal equivalent exists beyond the expected reference pathway under Max Tech pathway in 2030. CO2 emissions will also peak earlier under Max Tech, though the 2020s is a likely turning point for both emission trajectories. Both emission pathways must meet all announced and planned policies, targets and non-fossil generation targets, or an even wider efficiency gap will exist. The savings potential under Max Tech varies by sector, but the industrial sector appears to hold the largest energy savings and emission reduction potential. The primary source of savings is from electricity rather than fuel, and electricity savings are magnified by power sector decarbonization through increasing renewable generation and coal generation efficiency improvement. In order to achieve the maximum energy savings and emission reduction potential, efficiency improvements and technology switching must be undertaken across demand sectors as well as in the growing power sector. From an economic perspective, the cost of conserved energy analysis indicates that nearly all measures for the iron and steel and cement industry are cost-effective. All 23 efficiency measures analyzed for the cement industry are cost-effective, with combined CO2 emission reduction potential of 448 Mt CO2. All of the electricity savings measures in the iron and steel industry are cost-effective, but the cost-effective savings potential for fuel savings measures is slightly lower than total technical savings potential. The total potential savings from these measures confirm the magnitude of savings in the scenario models, and illustrate the remaining efficiency gap in the cement and iron and steel industries.

  13. Manufacturing consumption of energy 1991

    SciTech Connect (OSTI)

    Not Available

    1994-12-01T23:59:59.000Z

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

  14. Opportunities for Energy Efficiency and Open Automated Demand Response in Wastewater Treatment Facilities in California -- Phase I Report

    E-Print Network [OSTI]

    Lekov, Alex

    2010-01-01T23:59:59.000Z

    Processing Industry Energy Efficiency Initiative, CaliforniaK. (2004). Bringing Energy Efficiency to the Water andAgricultural/Water End-Use Energy Efficiency Program. Lyco

  15. Energy Efficiency Program Impact Evaluation Guide

    Office of Energy Efficiency and Renewable Energy (EERE)

    This Energy Efficiency Program Impact Evaluation Guide describes and provides guidance on approaches for determining and documenting energy and non-energy benefits resulting from end-use energy efficiency programs and portfolios of programs.

  16. Annual review of energy and the environment

    SciTech Connect (OSTI)

    Hollander, J.M. (Univ. of California at Berkeley, CA (US)); Socolow, R.H. (Princeton Univ., PA (US)); Sternlight, D.

    1991-01-01T23:59:59.000Z

    This book is organized under the following headings: Energy end use and conservation; Energy resources and technologies; Risks and impacts of energy production and use; Energy policy; International and regional topics.

  17. Use of Building Automation System Trend Data for Inputs Generation in Bottom-Up Simulation Calibration

    E-Print Network [OSTI]

    Zibin, N. F.; Zmeureanu, R. G.; Love, J. A.

    2013-01-01T23:59:59.000Z

    for analysis and use in simulation is very large. This paper explores automating the process of generating inputs from Building Automation System (BAS) trend data for use in building simulation software. A proof-of-concept prototype called the Automatic...

  18. Bottom-up, decision support system development : a wetlandsalinity management application in California's San Joaquin Valley

    SciTech Connect (OSTI)

    Quinn, Nigel W.T.

    2006-05-10T23:59:59.000Z

    Seasonally managed wetlands in the Grasslands Basin ofCalifornia's San Joaquin Valley provide food and shelter for migratorywildfowl during winter months and sport for waterfowl hunters during theannual duck season. Surface water supply to these wetland contain saltwhich, when drained to the San Joaquin River during the annual drawdownperiod, negatively impacts downstream agricultural riparian waterdiverters. Recent environmental regulation, limiting discharges salinityto the San Joaquin River and primarily targeting agricultural non-pointsources, now addresses return flows from seasonally managed wetlands.Real-time water quality management has been advocated as a means ofmatching wetland return flows to the assimilative capacity of the SanJoaquin River. Past attempts to build environmental monitoring anddecision support systems to implement this concept have failed forreasons that are discussed in this paper. These reasons are discussed inthe context of more general challenges facing the successfulimplementation of environmental monitoring, modelling and decisionsupport systems. The paper then provides details of a current researchand development project which will ultimately provide wetland managerswith the means of matching salt exports with the available assimilativecapacity of the San Joaquin River, when fully implemented. Manipulationof the traditional wetland drawdown comes at a potential cost to thesustainability of optimal wetland moist soil plant habitat in thesewetlands - hence the project provides appropriate data and a feedback andresponse mechanism for wetland managers to balance improvements to SanJoaquin River quality with internally-generated information on the healthof the wetland resource. The author concludes the paper by arguing thatthe architecture of the current project decision support system, whencoupled with recent advances in environmental data acquisition, dataprocessing and information dissemination technology, holds significantpromise to address some of the problems described earlier in the paperthat have limited past efforts to improve Basin water qualitymanagement.

  19. Bottom-Up Self-Organization of Unpredictable Demand and Supply under Decentralized Power Management

    E-Print Network [OSTI]

    Wedde, Horst F.

    level of granularity, with short-term power balance fluctuation, in terms of a peak demand and supply, distributed power production at lower voltage levels (through wind turbines or solar panels) is considered, as this depends on external environmental conditions (e.g. solar and wind power). In Electrical Engineering

  20. [Re]constructing Finite Flavour Groups: Horizontal Symmetry Scans from the Bottom-Up

    E-Print Network [OSTI]

    Jim Talbert

    2015-01-07T23:59:59.000Z

    We present a novel procedure for identifying discrete, leptonic flavour symmetries, given a class of unitary mixing matrices. By creating explicit 3D representations for generators of residual symmetries in both the charged lepton and neutrino sector, we reconstruct large(r) non-abelian flavour groups using the GAP language for computational finite algebra. We use experimental data to construct only those generators that yield acceptable (or preferable) mixing patterns. Such an approach is advantageous because it 1) can reproduce known groups from other 'top-down' scans while elucidating their origins from residuals, 2) find new previously unconsidered groups, and 3) serve as a powerful model building tool for theorists wishing to explore exotic flavour scenarios. We test our procedure on a generalization of the canonical tri-bimaximal (TBM) form.

  1. Top-down modification of bottom-up processes: selective grazing reduces macroalgal nitrogen uptake

    E-Print Network [OSTI]

    Bracken, MES; Stachowicz, J J

    2007-01-01T23:59:59.000Z

    morphology associated with kelp crab Pugettia productauptake SA:V (cm 2 ml –1 ) kelp crab grazing simulatedmenziesii. Influences of kelp crab Pugettia producta grazing

  2. Top-down modification of bottom-up processes: selective grazing reduces macroalgal nitrogen uptake

    E-Print Network [OSTI]

    Bracken, MES; Stachowicz, J J

    2007-01-01T23:59:59.000Z

    the kelp’s subsequent ability to acquire nutrients. Becauseof nutrient enhancement on the inter- tidal kelp Hedophyllumkelps and other large, dominant macrophytes. In our study, Pugettia producta reduced the biomass- specific nutrient-

  3. An integrated top-down and bottom-up strategy for broadly characterizi...

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

    employs high resolution reversed phase (RP) LC separations coupled on-line with a 12T Fourier transform ion cyclotron resonance (FTICR) spectrometer to profile and tentatively...

  4. Top-Down, Bottom-Up, or Both? Toward an Integrative Perspective on Operations Strategy Formation

    E-Print Network [OSTI]

    Kim, Yoon Hee; Sting, Fabian J.; Loch, Christopher H.

    2014-09-16T23:59:59.000Z

    and process ? Car components: axles, gearboxes, shaft drives ? Metalworking and assembly ? Power controllers (electrical and electronics) for machine tools ? Engineering and assembly ? SME, two manager-owners ? Medical kits for ambulances... . MEDICAL is a family-owned firm—a “small or medium-sized enterprise” (SME)—that develops and manufactures medical devices for ambulances and homes; it has a total of some 800 employees. The heads of manufacturing and technology and of sales are members...

  5. Peace Corps Volunteers and the Boundaries of Bottom-up Development

    E-Print Network [OSTI]

    Schuckman, Hugh Erik

    2012-01-01T23:59:59.000Z

    Andrea Matles, ed. Mongolia: A Country Study. Washington,Organizational Literature JICA Mongolia Office. "Baasan ".DC, 1985. ———. "Peace Corps Mongolia Annual Report 2011." (

  6. Energy Information Administration - Commercial Energy Consumption...

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

    104 306 3,611 Fuel Oil ... 5 1,864 403 179 1,993 District Heat ... 67 5,576 83 636 7,279 Energy End Uses...

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

    E-Print Network [OSTI]

    Fridley, David G.

    2008-01-01T23:59:59.000Z

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

  8. 3-D Characterization of the Structure of Paper and Paperboard and Their Application to Optimize Drying and Water Removal Processes and End-Use Applications

    SciTech Connect (OSTI)

    Shri Ramaswamy, University of Minnesota; B.V. Ramarao, State University of New York

    2004-08-29T23:59:59.000Z

    The three dimensional structure of paper materials plays a critical role in the paper manufacturing process especially via its impact on the transport properties for fluids. Dewatering of the wet web, pressing and drying will benefit from knowledge of the relationships between the web structure and its transport coefficients. The structure of the pore space within a paper sheet is imaged in serial sections using x-ray micro computed tomography. The three dimensional structure is reconstructed from these sections using digital image processing techniques. The structure is then analyzed by measuring traditional descriptors for the pore space such as specific surface area and porosity. A sequence of microtomographs was imaged at approximately 2 ?m intervals and the three-dimensional pore-fiber structure was reconstructed. The pore size distributions for both in-plane as well as transverse pores were measured. Significant differences in the in-plane (XY) and the transverse directions in pore characteristics are found and may help partly explain the different liquid and vapor transport properties in the in-plane and transverse directions. Results with varying sheet structures compare favorably with conventional mercury intrusion porosimetry data. Interestingly, the transverse pore structure appears to be more open with larger pore size distribution compared to the in plane pore structure. This may help explain the differences in liquid and vapor transport through the in plane and transverse structures during the paper manufacturing process and during end-use application. Comparison of Z-directional structural details of hand sheet and commercially made fine paper samples show a distinct difference in pore size distribution both in the in-plane and transverse direction. Method presented here may provide a useful tool to the papermaker to truly engineer the structure of paper and board tailored to specific end-use applications. The difference in surface structure between the top and bottom sides of the porous material, i.e. "two-sidedness" due to processing and raw material characteristics may lead to differences in end-use performance. The measurements of surface structure characteristics include thickness distribution, surface volume distribution, contact fraction distribution and surface pit distribution. This complements our earlier method to analyze the bulk structure and Z-D structure of porous materials. As one would expect, the surface structure characteristics will be critically dependent on the quality and resolution of the images. This presents a useful tool to characterize and engineer the surface structure of porous materials such as paper and board tailored to specific end-use applications. This will also help troubleshoot problems related to manufacturing and end-use applications. This study attempted to identify the optimal resolution through a comparison between 3D images obtained by monochromatic synchrotron radiation X-?CT in phase contrast mode (resolution ? 1 ?m) and polychromatic radiation X-?CT in absorption mode (res. ? 5 ?m). It was found that both resolutions have the ability to show the expected trends when comparing different paper samples. The low resolution technique shows fewer details resulting in lower specific surface area, larger pore channels, characterized as hydraulic radii, and lower tortuosities, where differences between samples and principal directions are more difficult to detect. The disadvantages of the high resolution images are high cost and limited availability of hard x-ray beam time as well as the small size of the sample volumes imaged. The results show that the low resolution images can be used for comparative studies, whereas the high resolution images may be better suited for fundamental research on the paper structure and its influence on paper properties, as one gets more accurate physical measurements. In addition, pore space diffusion model has been developed to simulate simultaneous diffusion in heterogeneous porous materials such as paper containing cellu

  9. China Energy Group - Sustainable Growth Through Energy Efficiency

    E-Print Network [OSTI]

    2006-01-01T23:59:59.000Z

    full end-use model of China’s energy economy for 2020.Assessed ways for China to meet its goal of reducing energyCenter (BSDC) Beijing University China Academy of Building

  10. Monthly energy review, March 1993

    SciTech Connect (OSTI)

    Not Available

    1993-03-26T23:59:59.000Z

    Contains summary data on petroleum, natural gas, coal, electricity, and nuclear energy relative to consumption, distribution, end-use, generation, imports, supply and demand, production, prices, global aspects, and international energy.

  11. Energy Conservation: Policy Issues and End-Use Scenarios of Savings Potential -- Part 3, Policy Barriers and Investment Decisions in Industry

    E-Print Network [OSTI]

    Benenson, Peter

    2011-01-01T23:59:59.000Z

    TECHNOLOGY, AND ECONOMIC EVALUATION DEPARTMENTS CONSTRUCTIONchannels. The Economic Evaluation and the Operations andinformation, banks for economic evaluations, etc. ). This

  12. Representation of Energy Use in the Food Products Industry 

    E-Print Network [OSTI]

    Elliott, N. R.

    2007-01-01T23:59:59.000Z

    Traditional representations of energy in the manufacturing sector have tended to represent energy end-uses rather than actual energy service demands. While this representation if quite adequate for understanding how energy is used today...

  13. INTERNATIONAL COMPARISON OF RESIDENTIAL ENERGY USE: INDICATORS OF RESIDENTIAL ENERGY USE AND EFFICIENCY PART ONE: THE DATA BASE

    E-Print Network [OSTI]

    Schipper, L.

    2013-01-01T23:59:59.000Z

    the housing and energy consumption data is a detailed studyConventions 6 All energy consumption data refer energy,Italian residential energy consumption data by end use. Unt

  14. Renewable Energy in Rangan Banerjee

    E-Print Network [OSTI]

    Banerjee, Rangan

    ENERGY END USE ACTIVITIES (ENERGY SERVICES) COAL, OIL, SOLAR, GAS POWER PLANT, REFINERIES REFINED OIL;Characteristics of Renewables Large, Inexhaustible source -Solar energy intercepted by earth 1.8*1011 MW Clean #12;Renewable Energy Options Wind Solar Small Hydro Biomass Tidal Energy Wave Energy Ocean Thermal

  15. Monthly energy review, March 1993. [Contains Glossary

    SciTech Connect (OSTI)

    Not Available

    1993-03-26T23:59:59.000Z

    Contains summary data on petroleum, natural gas, coal, electricity, and nuclear energy relative to consumption, distribution, end-use, generation, imports, supply and demand, production, prices, global aspects, and international energy.

  16. Monthly energy review, November 1992

    SciTech Connect (OSTI)

    Not Available

    1992-11-24T23:59:59.000Z

    Contains summary data on petroleum, natural gas, coal, electricity, and nuclear energy relative to consumption, distribution, end-use, generation, imports, supply and demand, production, prices, global aspects, and international markets.

  17. Monthly energy review, February 1993

    SciTech Connect (OSTI)

    Not Available

    1993-02-24T23:59:59.000Z

    Contains summary data on petroleum, natural gas, coal, electricity, and nuclear energy relative to consumption, distribution, end-use, generation, imports, supply and demand, production, prices, global aspects, and international markets.

  18. Towards increased policy relevance in energy modeling

    SciTech Connect (OSTI)

    Worrell, Ernst; Ramesohl, Stephan; Boyd, Gale

    2003-07-29T23:59:59.000Z

    Historically, most energy models were reasonably equipped to assess the impact of a subsidy or change in taxation, but are often insufficient to assess the impact of more innovative policy instruments. We evaluate the models used to assess future energy use, focusing on industrial energy use. We explore approaches to engineering-economic analysis that could help improve the realism and policy relevance of engineering-economic modeling frameworks. We also explore solutions to strengthen the policy usefulness of engineering-economic analysis that can be built from a framework of multi-disciplinary cooperation. We focus on the so-called ''engineering-economic'' (or ''bottom-up'') models, as they include the amount of detail that is commonly needed to model policy scenarios. We identify research priorities for the modeling framework, technology representation in models, policy evaluation and modeling of decision-making behavior.

  19. Energy Research and Development Division FINAL PROJECT REPORT

    E-Print Network [OSTI]

    Energy Research and Development Division FINAL PROJECT REPORT SMART GRID ROADMAP and Development Division funding efforts are focused on the following RD&D program areas: · Buildings EndUse Energy Efficiency · Renewable Energy Technologies · Transportation The Smart Grid Roadmap

  20. Public Interest Energy Research (PIER) Program FINAL PROJECT REPORT

    E-Print Network [OSTI]

    TO THE CALIFORNIA SMART GRID OF 2020 FOR PUBLICLY OWNED UTILITIES Prepared for: California Energy Integration · Environmentally Preferred Advanced Generation · Industrial/Agricultural/Water EndUse Energy Efficiency · Renewable Energy Technologies · Transportation Defining the Pathway to the California Smart

  1. Improved Analysis Methods for Retrofit Savings and Energy Accounting (ERAP #227)

    E-Print Network [OSTI]

    Claridge, D. E.; Haberl, J. S.; Kissock, J. K.; Ruch, D. K.; Katipamula, S.; Chen, L.; Wang, J.

    1990-01-01T23:59:59.000Z

    an end-use data base for commercial and institutional buildings to facilitate the comparison and exchange of building energy use information....

  2. Public Interest Energy Research (PIER) Program INTERIM PROJECT REPORT

    E-Print Network [OSTI]

    for the Smart Grid Information Assurance and Security Technology Assessment project (Contract Number 50008027 Generation · Industrial/Agricultural/Water EndUse Energy Efficiency · Renewable Energy Technologies

  3. Representation of Energy Use in the Food Products Industry

    E-Print Network [OSTI]

    Elliott, N. R.

    2007-01-01T23:59:59.000Z

    such as combined heat and power (CHP). This paper discusses the differences between energy end-uses and service demands, proposes an approach for approximating service demands and discusses the ramifications of this alternative representation to energy modeling...

  4. Energy Data Sourcebook for the U.S. Residential Sector

    E-Print Network [OSTI]

    Wenzel, T.P.

    2010-01-01T23:59:59.000Z

    J.E. 1986. The LBL Residential Energy Model. LawrenceInc. MEANS. 1992. Residential Cost Data: 11th Annual EditionInstitute. 1989. Residential End-Use Energy Consumption: A

  5. U.S. Energy Information Administration (EIA) - Pub

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

    and their impacts on end-use energy demand In 2010, the residential and commercial buildings sectors used 20.4 quadrillion Btu of delivered energy, or 28 percent of total U.S....

  6. Sectoral trends in global energy use and greenhouse gas emissions

    E-Print Network [OSTI]

    2006-01-01T23:59:59.000Z

    Agency (IEA), 2004c. CO2 emissions from fuel combustion,12. Global Energy-Related CO2 Emissions by End-Use Sector,2030. Energy-Related CO2 Emissions (GtC) Transport Buildings

  7. Monthly energy review, February 1993. [Contains Glossary

    SciTech Connect (OSTI)

    Not Available

    1993-02-24T23:59:59.000Z

    Contains summary data on petroleum, natural gas, coal, electricity, and nuclear energy relative to consumption, distribution, end-use, generation, imports, supply and demand, production, prices, global aspects, and international markets.

  8. Monthly energy review, November 1992. [Contains Glossary

    SciTech Connect (OSTI)

    Not Available

    1992-11-24T23:59:59.000Z

    Contains summary data on petroleum, natural gas, coal, electricity, and nuclear energy relative to consumption, distribution, end-use, generation, imports, supply and demand, production, prices, global aspects, and international markets.

  9. International energy outlook 2006

    SciTech Connect (OSTI)

    NONE

    2006-06-15T23:59:59.000Z

    This report presents international energy projections through 2030, prepared by the Energy Information Administration. After a chapter entitled 'Highlights', the report begins with a review of world energy and economic outlook, followed by energy consumption by end-use sector. The next chapter is on world oil markets. Natural gas, world coal market and electricity consumption and supply are then discussed. The final chapter covers energy-related carbon dioxide emissions.

  10. International Review of the Development and Implementation of Energy Efficiency Standards and Labeling Programs

    E-Print Network [OSTI]

    Zhou, Nan

    2013-01-01T23:59:59.000Z

    end-use and direct energy consumption data resources forof sales or energy consumption data on the regional level.used, and energy consumption and expenditure data for major

  11. Energy Audit Practices in China: National and Local Experiences and Issues

    E-Print Network [OSTI]

    Shen, Bo

    2011-01-01T23:59:59.000Z

    factor to standard coal of energy source i; n—Number ofin standard coal equivalent) ? sectoral energy consumptiontable (standard coal) End-use energy consumption by P303-5

  12. Current Status and Future Scenarios of Residential Building Energy Consumption in China

    E-Print Network [OSTI]

    Zhou, Nan

    2010-01-01T23:59:59.000Z

    LPG is a major energy source, while coal and electricity arethe total residential energy and coal is the dominant fuel.1 Residential Energy consumption by End-use Coal Renewables

  13. Quantifying the potential impact of energy efficiency and low carbon policies for China

    E-Print Network [OSTI]

    Zhou, Nan

    2014-01-01T23:59:59.000Z

    of China’s future energy demand and serves as the basis foraddresses end-use energy demand characteristics includingeconomic growth and energy demand. Because this model is an

  14. High-Energy Permanent Magnets for Hybrid Vehicles and Alternative Energy Uses

    SciTech Connect (OSTI)

    Hadjipanayis, George C. [University of Delaware] [University of Delaware; McCallum, William R. [Ames Laboratory] [Ames Laboratory; Sellmyer, David J. [University of Nebraska, Lincoln] [University of Nebraska, Lincoln; Harris, Vincent [Northeastern University] [Northeastern University; Carpenter, Everett E. [Virginia Commonwealth University] [Virginia Commonwealth University; Liu, Jinfang [Electron Energy Corporation] [Electron Energy Corporation

    2013-12-17T23:59:59.000Z

    The report summarizes research undertaken by a multidisciplinary team aimed at the development of the next generation high-energy permanent magnets. The principal approach was relied on bottom-up fabrication of anisotropic nanocomposite magnets. Our efforts resulted in further development of the theoretical concept and fabrication principles for the nanocomposites and in synthesis of a range of rare-earth-based hard magnetic nanoparticles. Even though we did not make a breakthrough in the assembly of these hard magnetic particles with separately prepared Fe(Co) nanoparticles and did not obtain a compact nanocomposite magnet, our performed research will help to direct the future efforts, in particular, towards nano-assembly via coating, when the two phases which made the nanocomposite are first organized in core-shell-structured particles. Two other approaches were to synthesize (discover) new materials for the traditional singe-material magnets and the nanocomposite magnets. Integrated theoretical and experimental efforts lead to a significant advance in nanocluster synthesis technique and yielded novel rare-earth-free nanostructured and nanocomposite materials. Examination of fifteen R-Fe-X alloy systems (R = rare earth), which have not been explored earlier due to various synthesis difficulties reveal several new ferromagnetic compounds. The research has made major progress in bottom-up manufacturing of rare-earth-containing nanocomposite magnets with superior energy density and open new directions in development of higher-energy-density magnets that do not contain rare earths. The advance in the scientific knowledge and technology made in the course of the project has been reported in 50 peer-reviewed journal articles and numerous presentations at scientific meetings.

  15. Achieving Energy Savings Through Residential Energy Use Behavior

    E-Print Network [OSTI]

    Office PIER Buildings End-use Energy Efficiency Research Program www.energy.ca.gov/research/buildings May and purchasing decisions, are important factors in achieving energy savings in buildings. However, little efficiency programs for the residential sector? Technologies such as smart meters and home area networks

  16. Energy Reduction in California Pipeline Operations

    E-Print Network [OSTI]

    technologies that can help California's industrial sectors reduce their energy consumption, their water use. In addition to significant baseline energy consumption, more energy is often required by pipelines Energy Commission Public Interest Energy Research Program Industrial/Agriculture/Water EndUse Phone

  17. Energy Information Administration - Commercial Energy Consumption Survey-

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40CoalLease(Billion2,128 2,469DecadeOriginand Tables End-Use1995 End-Use2003

  18. OIKOS 89: 524540. Copenhagen 2000 Assessing top-down and bottom-up control in a litter-based soil

    E-Print Network [OSTI]

    Jost, Christian

    of a temperate deciduous forest. During two consecutive years, we estimated the abundances of macroinvertebrate abundance increases when its food supply increases. Top-down control is demon- strated by an increase-level chain should be so efficiently preyed upon that any additional unit of biomass they might produce

  19. ISDA 2010, Montpellier, June 28-30, 2010 1 COMBINING TOP-DOWN AND BOTTOM-UP

    E-Print Network [OSTI]

    Boyer, Edmond

    efficiency and on the other tried to fine-tune inputs (of nutrients, agrochemicals, manure, etc) to societal

  20. With or Against the People? The Impact of a Bottom-Up Approach on Tax Morale and the Shadow Economy

    E-Print Network [OSTI]

    Torgler, Benno; Schneider, Friedrich; Schaltegger, Christoph A.

    2007-01-01T23:59:59.000Z

    Corruption and the Shadow Economy: An Empirical Analysis,Journal of Political Economy Feld, L. P. , Kirchgässner,G. 2001. The Political Economy of Direct Legislation: Direct

  1. Teacher self-efficacy in Cape Town : a bottom up approach to enhancing the quality of education

    E-Print Network [OSTI]

    Kim, YeSeul

    2011-01-01T23:59:59.000Z

    Personal teacher self-efficacy (PTE), or the belief in one's own ability to overcome a particular challenge, often acts as a catalyst for teachers to improve the effectiveness of their teaching. Gaining PTE can translate ...

  2. Bottom-up and top-down controls of walleye pollock (Theragra chalcogramma) on the Eastern Bering Sea shelf

    E-Print Network [OSTI]

    Ladd, Carol

    . Furthermore, a dome-shaped relationship between pollock survival and summer wind mixing at the early juvenile- erate levels of wind mixing, but a decrease in feeding success at high levels of wind mixing. Top-to- recruit survival could be accounted for by predation mortality at the early juvenile stage (age-1

  3. California spiny lobsters and benthic community structure in Southern California: top-down and bottom-up interactions

    E-Print Network [OSTI]

    Hovel, Kevin; Lowe, Christopher

    2010-01-01T23:59:59.000Z

    in southern California kelp forests Supported by Sea Grantof benthic communities in kelp forest and seagrass habitat.movement, and home range among kelp forest, surfgrass, and

  4. Efficient Bottom-Up Image Segmentation Using Region Competition and the Mumford-Shah Model for Color and Textured Images

    E-Print Network [OSTI]

    curves usually introduce high computational loads, and techniques must be used to ensure that no pixels to solve PDEs. The computa- tional load of curve evolution is thus greatly reduced. The proposed m@ece.utk.edu Abstract Curve evolution implementations [3][23] [25] of the Mumford-Shah functional [16] are of broad

  5. A bottom up approach to on-road CO2 emissions estimates: improved spatial accuracy and applications for regional

    E-Print Network [OSTI]

    Wing, Ian Sue

    's Global Warming Solutions Act.3 Both policies set emissions reduction targets for power plants and other Type: Article Date Submitted by the Author: 11-Jan-2013 Complete List of Authors: Gately, Conor; Boston their own abatement initiatives such as the Regional Greenhouse Gas Initiative (RGGI) and California

  6. An Extended Model for the Evolution of Prebiotic Homochirality: A Bottom-Up Approach to the Origin of Life

    E-Print Network [OSTI]

    Marcelo Gleiser; Sara Imari Walker

    2008-02-20T23:59:59.000Z

    A generalized autocatalytic model for chiral polymerization is investigated in detail. Apart from enantiomeric cross-inhibition, the model allows for the autogenic (non-catalytic) formation of left and right-handed monomers from a substrate with reaction rates $\\epsilon_L$ and $\\epsilon_R$, respectively. The spatiotemporal evolution of the net chiral asymmetry is studied for models with several values of the maximum polymer length, N. For N=2, we study the validity of the adiabatic approximation often cited in the literature. We show that the approximation obtains the correct equilibrium values of the net chirality, but fails to reproduce the short time behavior. We show also that the autogenic term in the full N=2 model behaves as a control parameter in a chiral symmetry- breaking phase transition leading to full homochirality from racemic initial conditions. We study the dynamics of the N -> infinity model with symmetric ($\\epsilon_L = \\epsilon_R$) autogenic formation, showing that it only achieves homochirality for $\\epsilon development of homochirality in prebiotic Earth and possible experimental verification of our findings.

  7. California spiny lobsters and benthic community structure in Southern California: top-down and bottom-up interactions

    E-Print Network [OSTI]

    Hovel, Kevin; Lowe, Christopher

    2010-01-01T23:59:59.000Z

    annual conference Location: Ventura, CA Title: Ecology and88th annual meeting, Ventura, CA: Hovel and Lowe: Californiaannual conferences, Ventura, CA (Nov. 2008) and Monterey,

  8. A New, Stochastic, Energy Model of the U.S. is Under Construction: SEDS and Its Industrial Structure

    E-Print Network [OSTI]

    Roop, J. M.

    -duty vehicles and heavy-duty vehicles. The industrial sector is currently modeled as a single sector, using the latest Manufacturing Energy Consumption Survey (MECS) to calibrate energy consumption to end-use energy categories: boilers, process heating...

  9. Ris Energy Report 7 This Ris Energy Report, the seventh of a series that began

    E-Print Network [OSTI]

    #12;#12;#12;#12;#12;3 1 Risø Energy Report 7 This Risø Energy Report, the seventh of a series. This report presents state-of-the-art and development per- spectives for energy supply technologies, new energy sys- tems, end-use energy efficiency improvements and new pol- icy measures. It also includes

  10. SUSTAINABLE DEVELOPMENT IN KAZAKHASTAN: USING OIL AND GAS PRODUCTION BY-PRODUCT SULFUR FOR COST-EFFECTIVE SECONDARY END-USE PRODUCTS.

    SciTech Connect (OSTI)

    KALB, P.D.; VAGIN, S.; BEALL, P.W.; LEVINTOV, B.L.

    2004-09-25T23:59:59.000Z

    The Republic of Kazakhstan is continuing to develop its extensive petroleum reserves in the Tengiz region of the northeastern part of the Caspian Sea. Large quantities of by-product sulfur are being produced as a result of the removal of hydrogen sulfide from the oil and gas produced in the region. Lack of local markets and economic considerations limit the traditional outlets for by-product sulfur and the buildup of excess sulfur is a becoming a potential economic and environmental liability. Thus, new applications for re-use of by-product sulfur that will benefit regional economies including construction, paving and waste treatment are being developed. One promising application involves the cleanup and treatment of mercury at a Kazakhstan chemical plant. During 19 years of operation at the Pavlodar Khimprom chlor-alkali production facility, over 900 tons of mercury was lost to the soil surrounding and beneath the buildings. The Institute of Metallurgy and Ore Benefication (Almaty) is leading a team to develop and demonstrate a vacuum-assisted thermal process to extract the mercury from the soil and concentrate it as pure, elemental mercury, which will then be treated using the Sulfur Polymer Stabilization/Solidification (SPSS) process. The use of locally produced sulfur will recycle a low-value industrial by-product to treat hazardous waste and render it safe for return to the environment, thereby helping to solve two problems at once. SPSS chemically stabilizes mercury to mercuric sulfide, which has a low vapor pressure and low solubility, and then physically encapsulates the material in a durable, monolithic solid sulfur polymer matrix. Thus, mercury is placed in a solid form very much like stable cinnabar, the form in which it is found in nature. Previous research and development has shown that the process can successfully encapsulate up to 33 wt% mercury in the solid form, while still meeting very strict regulatory standards for leachable mercury (0.025 mg/l in the Toxicity Characteristic Leaching Procedure). The research and development to deploy Kazakhstan recycled sulfur for secondary applications described in this paper is being conducted with support from the International Science and Technology Center (ISTC) and the U.S. Department of Energy Initiatives for Proliferation Prevention (DOE IPP).

  11. Current and future industrial energy service characterizations

    SciTech Connect (OSTI)

    Krawiec, F.; Thomas, T.; Jackson, F.; Limaye, D.R.; Isser, S.; Karnofsky, K.; Davis, T.D.

    1980-10-01T23:59:59.000Z

    Current and future energy demands, end uses, and cost used to characterize typical applications and resultant services in the industrial sector of the United States and 15 selected states are examined. A review and evaluation of existing industrial energy data bases was undertaken to assess their potential for supporting SERI research on: (1) market suitability analysis, (2) market development, (3) end-use matching, (3) industrial applications case studies, and (4) identification of cost and performance goals for solar systems and typical information requirements for industrial energy end use. In reviewing existing industrial energy data bases, the level of detail, disaggregation, and primary sources of information were examined. The focus was on fuels and electric energy used for heat and power purchased by the manufacturing subsector and listed by 2-, 3-, and 4-digit SIC, primary fuel, and end use. Projections of state level energy prices to 1990 are developed using the energy intensity approach. The effects of federal and state industrial energy conservation programs on future industrial sector demands were assessed. Future end-use energy requirements were developed for each 4-digit SIC industry and were grouped as follows: (1) hot water, (2) steam (212 to 300/sup 0/F, each 100/sup 0/F interval from 300 to 1000/sup 0/F, and greater than 1000/sup 0/F), and (3) hot air (100/sup 0/F intervals). Volume I details the activities performed in this effort.

  12. Public Interest Energy Research (PIER) Program FINAL PROJECT REPORT

    E-Print Network [OSTI]

    /Agricultural/Water End-Use Energy Efficiency Renewable Energy Technologies Transportation Sitras® Static Energy StoragePublic Interest Energy Research (PIER) Program FINAL PROJECT REPORT SITRAS® STATIC ENERGY STORAGE System Demonstration Program is the interim and final report for the Static Energy Storage Project

  13. Impacts of Temperature Variation on Energy Demand in Buildings (released in AEO2005)

    Reports and Publications (EIA)

    2005-01-01T23:59:59.000Z

    In the residential and commercial sectors, heating and cooling account for more than 40% of end-use energy demand. As a result, energy consumption in those sectors can vary significantly from year to year, depending on yearly average temperatures.

  14. Improving the Contribution of Economic Models in Evaluating Industrial Energy Efficiency Improvements 

    E-Print Network [OSTI]

    Laitner, J. A.

    2007-01-01T23:59:59.000Z

    Traditional representation of improved end-use efficiency in the manufacturing sector has tended to assume “a net cost” perspective. In other words, the assumption for many models is that any change within the energy end-use patterns must imply a...

  15. Report: An Updated Annual Energy Outlook 2009 Reference Case...

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

    9. Energy-Related Carbon Dioxide Emissions by End Use" " (million metric tons carbon dioxide equivalent, unless otherwise noted)" ,2006,2007,2008,2009,2010,2011,2012,2013,2014,2015...

  16. A Fresh Look at Weather Impact on Peak Electricity Demand and Energy Use of Buildings Using 30-Year Actual Weather Data

    E-Print Network [OSTI]

    Hong, Tianzhen

    2014-01-01T23:59:59.000Z

    more than 40% of end-use energy demand. It is important toin terms of building energy supply and demand. Additionally,to evaluate energy performance and demand response. Accurate

  17. Energy Research and Development Division FINAL PROJECT REPORT

    E-Print Network [OSTI]

    the aircraft off the ground for each mission. i #12;PREFACE The California Energy Commission Energy Research/Agricultural/Water End-Use Energy Efficiency · Renewable Energy Technologies · Transportation California AutonomousEnergy Research and Development Division FINAL PROJECT REPORT CALIFORNIA AUTONOMOUS UNMANNED AERIAL

  18. Energy Research and Development Division FINAL PROJECT REPORT

    E-Print Network [OSTI]

    Franco Program Area Lead Energy-Related Environmental Research Linda Spiegel Office Manager Energy on the following RD&D program areas: · Buildings EndUse Energy Efficiency · Energy Innovations Small Grants Energy Research and Development Division FINAL PROJECT REPORT AIRQUALITY IMPACTS OF HEAT

  19. Energy Efficiency Supporting Policy and Heat Pumping Technology in Japan

    E-Print Network [OSTI]

    Oak Ridge National Laboratory

    % improvement energy consumption per real GDP of Japan> Ref: METI/ Energy Data Modeling Centre, comprehensive energy statistics *Total consumption of primary energy (tons in crude oil equivalent) / real GDP heating , 25% Cooling, 2% Water heating, 29% Power, etc., 36% cooking , 8% Energy consumption by end- use

  20. New Technology Demonstration Program FEMPFederal Energy Management Program

    E-Print Network [OSTI]

    Efficiency and Renewable Energy, Federal Energy Management Program, of the U.S. Department of Energy under federal facilities, the fastest growing end-use of electric energy is found in concentrations of computing to their agency mission will present a serious challenge to meeting the aggressive new energy efficiency goals