National Library of Energy BETA

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

    2014-01-01

    China's Future Energy and Emissions Outlook. Berkeley, CA:Energy Agency), 2009. World Energy Outlook 2009. Paris: OECDAgency (IEA)’s World Energy Outlook (WEO) 2009, which set

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

    E-Print Network [OSTI]

    Zhou, Nan

    2014-01-01

    Studies on China's Future Energy and Emissions Outlook.Institute. IEA (International Energy Agency), 2009.World Energy Outlook 2009. Paris: OECD Publishing. Li, J. ,

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

    E-Print Network [OSTI]

    Zhou, Nan

    2014-01-01

    Energy Agency), 2009. World Energy Outlook 2009. Paris: OECDEnergy Agency (IEA)’s World Energy Outlook (WEO) 2009, whichresults are taken from World Energy Outlook 2009. As seen in

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

    E-Print Network [OSTI]

    Zhou, Nan

    2014-01-01

    Environment Institute. IEA (International Energy Agency),GR 4. IND +25% HI P CIS IEA Ref 5. COM +25% FA LBNL Lowest4% OI EI GR ERI Low Carbon AIS IEA 450 ERI Accel. Low Carbon

  5. 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

    2014-01-01

    Levine. 2012. “China's Energy and Emissions Outlook to 2050:on China’s Future Energy and Emissions Outlook. LBNL-4032E.Energy Demand Outlook

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

    SciTech Connect (OSTI)

    McNeil, Michael A.; Letschert, Virginie E.; Stephane, de la Rue du Can; Ke, Jing

    2012-06-15

    The main objective of the development of BUENAS is to provide a global model with sufficient detail and accuracy for technical assessment of policy measures such as energy efficiency standards and labeling (EES&L) programs. In most countries where energy efficiency policies exist, the initial emphasis is on household appliances and lighting. Often, equipment used in commercial buildings, particularly heating, air conditioning and ventilation (HVAC) is also covered by EES&L programs. In the industrial sector, standards and labeling generally covers electric motors and distribution transformers, although a few more types of industrial equipment are covered by some programs, and there is a trend toward including more of them. In order to make a comprehensive estimate of the total potential impacts, development of the model prioritized coverage of as many end uses commonly targeted by EES&L programs as possible, for as many countries as possible.

  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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION JEnvironmental JumpInformationBio-GasIllinois:EnergyIdahoTechnology Venture

  8. 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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION JEnvironmental JumpInformationBio-GasIllinois:EnergyIdahoTechnology Venture(Redirected from

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

    E-Print Network [OSTI]

    McNeil, Michael A.

    2013-01-01

    consumer energy expenditures. Direct rebound effects referimpact on estimates of energy demand and savings. ReboundRebound effects’ refers to the increase in usage of energy

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

    E-Print Network [OSTI]

    McNeil, Michael A.

    2013-01-01

    Developing the World's best Energy-Efficient Appliances.Annual unit energy consumption in Best Practice ScenarioConsumption - EFF Unit Energy Consumption - Best Practice BP

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

    E-Print Network [OSTI]

    McNeil, Michael A.

    2013-01-01

    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

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

    E-Print Network [OSTI]

    McNeil, Michael A.

    2013-01-01

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

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

    E-Print Network [OSTI]

    McNeil, Michael A.

    2013-01-01

    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

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

    E-Print Network [OSTI]

    McNeil, Michael A.

    2013-01-01

    2011. 2011. EIA, International Energy Outlook 2010. 2010.EIA, International Energy Outlook 2008. 2008. McNeil, M.A. ,Energy Agency, World Energy Outlook 2006. 2006, OECD. ILO,

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

    E-Print Network [OSTI]

    McNeil, Michael A.

    2013-01-01

    effect in TSL 5 Useful Energy from Ecodesign, EfficiencyAUS assumed equal to US Useful energy from Ecodesign study,regions. In addition, useful energy consumption 2 for

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

    E-Print Network [OSTI]

    McNeil, Michael A.

    2013-01-01

    Products: The Case of India. Energy Policy, 2008. 36(9): p.in India, in 5th International Conference on EnergyIndia Indonesia Total without China Total including China Energy

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

    E-Print Network [OSTI]

    McNeil, Michael A.

    2013-01-01

    diffusion and industrial motor energy. GDP growth rates areenergy consumption in Best Practice Scenario Best practice efficiency definitions Product class market shares Industrial electric motorsenergy demand sectors. The LBNL China appliance model (including industrial motors

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

    E-Print Network [OSTI]

    take energy and other prices as exogenous and, therefore, may overestimate the potential penetrationRepresenting energy technologies in top-down economic models using bottom-up information J.R. Mc 02139, USA c Laboratory for Energy and the Environment, M.I.T., Cambridge, MA 02139, USA Available

  19. 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. ...

  20. 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 February 2011 Accepted 16 August 2011 Available online 17 September 2011 Keywords: Energy efficiency that a large potential for profitable energy efficiency exists in the US, and that substantial greenhouse gas

  1. Healthcare Energy End-Use Monitoring

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

    Healthcare Energy End-Use Monitoring Michael Sheppy, Shanti Pless, and Feitau Kung National Renewable Energy Laboratory Technical Report NRELTP-5500-61064 August 2014 NREL is a...

  2. 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

    2006-01-01

    of a national energy-efficient purchasing program. Thesenational energy- efficiency endorsement labeling program. 5.a program to promote energy-efficient purchasing by national

  3. 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

    2006-01-01

    energy-efficient products currently on the Ministry of Financefinance sectors should support resource conservation activities and comprehensive utilization, and adopt energy-Finance and the National Development and Reform Commission on the Issuance of “Implementation of Government Energy

  4. 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

    2006-01-01

    public sector energy spending reached roughly US$10 billion and that figure has been rising as total built space

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

    E-Print Network [OSTI]

    Zhou, Nan

    2014-01-01

    demand-side Total electricity demand efficiency programs608 GW in 2050 Total electricity demand reaches 7,764 TWh innearly one-third of all electricity demand. Under AIS, the

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

    E-Print Network [OSTI]

    Zhou, Nan

    2014-01-01

    is the rapid expansion of nuclear generation, whichfurther expansion of renewable and nuclear power capacity.further expansion of renewable and nuclear power capacity.

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

    E-Print Network [OSTI]

    Zhou, Nan

    2014-01-01

    management Installed capacity of wind, solar, and biomassand policies Installed capacity of wind, solar, and biomass

  8. Healthcare Energy End-Use Monitoring

    Office of Energy Efficiency and Renewable Energy (EERE)

    This report describes the NREL partnership with two hospitals (MGH and SUNY UMU) to collect data on the energy used for multiple thermal and electrical end-use categories, which can be used to more effectively prioritize and refine the scope of investments in new metering and energy audits.

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

    SciTech Connect (OSTI)

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

    2009-03-30

    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.

  10. 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.

    2010-08-15

    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.

  11. Healthcare Energy End-Use Monitoring

    SciTech Connect (OSTI)

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

    2014-08-01

    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.

  12. Energy End-Use Intensities in Commercial Buildings

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

    Estimates The end-use estimates had two main sources: the 1989 Commercial Buildings Energy Consumption Survey (CBECS) and the Facility Energy Decision Screening (FEDS) system....

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

    E-Print Network [OSTI]

    Sathaye, J.

    2011-01-01

    de Beer, 1997. "Energy Efficient Technologies in Industry -Tracking Industrial Energy Efficiency and CO2 Emissions.and L. Price. 1999. Energy Efficiency and Carbon Dioxide

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

    E-Print Network [OSTI]

    Zhou, Nan

    2010-01-01

    institute TERI. (2001) TERI Energy Data Directory & Yearbookdesigned. Unfortunately, existing energy data do not provideIndia transportation energy data. Different scenarios were

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

    E-Print Network [OSTI]

    Zhou, Nan

    2010-01-01

    reported in IEA India transportation energy data. DifferentKeywords: India, transport, energy demand, decomposition,balance for India, transport energy consumption represents

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

    E-Print Network [OSTI]

    Sathaye, J.

    2011-01-01

    mill throughput and saving energy. Advanced Grindingstudy, for which cost and energy-savings data on mitigationfor collating the data on energy savings and costs for their

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

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2009-01-01

    N ATIONAL L ABORATORY India Energy Outlook: End Use DemandTables Figures Figure 1. India Primary Energy Supply by fuel33 Table 15. India Industry Energy Intensities (GJ/

  18. 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

    2000-01-01

    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...

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

    E-Print Network [OSTI]

    Sathaye, J.

    2011-01-01

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

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

    E-Print Network [OSTI]

    Sathaye, J.

    2011-01-01

    Energy and Carbon Reduction . 9   3.1   Cost of Conserved Energy Curves – with and without Other Benefits . 9   3.2   Calculationenergy conservation is generally reduced when productivity benefits associated with labor and material cost savings are included in the calculationenergy benefits are excluded from calculation. Changes in cost

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

    E-Print Network [OSTI]

    Zhou, Nan

    2010-01-01

    consumption. As in the statistic from India Ministry ofTransport In India Ministry of Statistics (MOS), India. (Statistics 4.2 Comparison with IEA data The energy consumption estimates described above were compared with IEA India

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

    E-Print Network [OSTI]

    Zhou, Nan

    2010-01-01

    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,

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

    E-Print Network [OSTI]

    Sathaye, J.

    2011-01-01

    M. , 1990. “Waste Gas Heat Recovery in Cement Plants” EnergyAdvanced Concepts of Waste Heat Recovery in Cement Plants”process Optimize heat recovery of Wet Increased product

  4. Enduse Global Emissions Mitigation Scenarios (EGEMS): A New Generation of Energy Efficiency Policy Planning Models

    E-Print Network [OSTI]

    McNeil, Michael A.

    2010-01-01

    and J. Sathaye (2009). India Energy Outlook: End Use Demandand Transport Energy Use in India: Past Trends and Futureenergy demand, forecasting, end use, bottom-up, China, India,

  5. Energy end-use intensities in commercial buildings

    SciTech Connect (OSTI)

    Not Available

    1994-09-01

    This report examines energy intensities in commercial buildings for nine end uses: space heating, cooling, ventilation, lighting, water heating, cooking, refrigeration, office equipment, and other. The objective of this analysis was to increase understanding of how energy is used in commercial buildings and to identify targets for greater energy efficiency which could moderate future growth in demand. The source of data for the analysis is the 1989 Commercial Buildings Energy Consumption survey (CBECS), which collected detailed data on energy-related characteristics and energy consumption for a nationally representative sample of approximately 6,000 commercial buildings. The analysis used 1989 CBECS data because the 1992 CBECS data were not yet available at the time the study was initiated. The CBECS data were fed into the Facility Energy Decision Screening (FEDS) system, a building energy simulation program developed by the US Department of Energy`s Pacific Northwest Laboratory, to derive engineering estimates of end-use consumption for each building in the sample. The FEDS estimates were then statistically adjusted to match the total energy consumption for each building. This is the Energy Information Administration`s (EIA) first report on energy end-use consumption in commercial buildings. This report is part of an effort to address customer requests for more information on how energy is used in buildings, which was an overall theme of the 1992 user needs study. The end-use data presented in this report were not available for publication in Commercial Buildings Energy Consumption and Expenditures 1989 (DOE/EIA-0318(89), Washington, DC, April 1992). However, subsequent reports on end-use energy consumption will be part of the Commercial Buildings Energy Consumption and Expenditures series, beginning with a 1992 data report to be published in early 1995.

  6. United States Industrial Sector Energy End Use Analysis

    SciTech Connect (OSTI)

    Shehabi, Arman; Morrow, William R.; Masanet, Eric

    2012-05-11

    The United States Department of Energy’s (DOE) Energy Information Administration (EIA) conducts the Manufacturing Energy Consumption Survey (MECS) to provide detailed data on energy consumption in the manufacturing sector. The survey is a sample of approximately 15,000 manufacturing establishments selected from the Economic Census - Manufacturing Sector. MECS provides statistics on the consumption of energy by end uses (e.g., boilers, process, electric drives, etc.) disaggregated by North American Industry Classification System (NAICS) categories. The manufacturing sector (NAICS Sector 31-33) consists of all manufacturing establishments in the 50 States and the District of Columbia. According to the NAICS, the manufacturing sector comprises establishments engaged in the mechanical, physical, or chemical transformation of materials, substances, or components into new products. The establishments are physical facilities such as plants, factories, or mills. For many of the sectors in the MECS datasets, information is missing because the reported energy use is less than 0.5 units or BTUs, or is withheld to avoid disclosing data for individual establishments, or is withheld because the standard error is greater than 50%. We infer what the missing information likely are using several approximations techniques. First, much of the missing data can be easily calculated by adding or subtracting other values reported by MECS. If this is not possible (e.g. two data are missing), we look at historic MECS reports to help identify the breakdown of energy use in the past and assume it remained the same for the current MECS. Lastly, if historic data is also missing, we assume that 3 digit NAICS classifications predict energy use in their 4, 5, or 6 digit NAICS sub-classifications, or vice versa. Along with addressing data gaps, end use energy is disaggregated beyond the specified MECS allocations using additional industry specific energy consumption data. The result is a completed table of energy end use by sector with mechanical drives broken down by pumps, fans, compressed air, and drives.

  7. Energy End-Use Intensities in Commercial Buildings1992 -- Overview/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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet)DecadeYear Jan Feb Mar Apr May Jun Jul1998,(Million CubicEnd1995 End-Use

  8. 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.

    2010-09-30

    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.

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

    Energy Savers [EERE]

    Using End-Use Data to Inform Decisions Healthcare Energy: Using End-Use Data to Inform Decisions The Building Technologies Office conducted a healthcare energy end-use monitoring...

  10. Energy End-Use Intensities in Commercial Buildings

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

    as buildings of the 1980's. In this section, intensities are based upon the entire building stock, not just those buildings using a particular fuel for a given end use. This...

  11. United States Industrial Sector Energy End Use Analysis

    E-Print Network [OSTI]

    Shehabi, Arman

    2014-01-01

    by end uses (e.g. , boilers, process, electric drives,MECS 2002, and MECS 1998 data. Indirect Uses-Boiler FuelConventional Boiler Use CHP and/or Cogeneration Process

  12. 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.

    2011-01-01

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

  13. 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.

    2011-01-01

    Using an Advanced Energy Management System,” Best Practiceincludes site energy management systems for optimal energyvariety of such energy management systems exist (Worrell et

  14. 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.

    2011-01-01

    production and hence saving energy consumed in coke making (for collating the data on energy savings and costs for theircan result in significant energy savings and carbon-emission

  15. Modeling of End-Use Energy Profile: An Appliance-Data-Driven Stochastic Approach

    E-Print Network [OSTI]

    Kang, Zhaoyi; Jin, Ming; Spanos, Costas J

    2014-01-01

    Demand side management: Demand response, intelligent energydesigning building demand-response system [5]. The Bottom-up

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

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet)DecadeYear Jan Feb Mar Apr May Jun Jul1998,(Million CubicEnd Use:‹Home

  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.

    2011-01-01

    Energy and Carbon Reduction 3.1 Calculation of cost ofCalculation of cost of carbon reduction related to energyweighted fuel cost in our calculation based on energy data

  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.

    2011-01-01

    Thermal Energy of Rolling Mill Waste Oil Through Sintering,"It is possible to use waste oils (especially from coldwaste recovery), or 74% of the rolling sludges and oils (

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

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2009-01-01

    Crises & Climate Challenges - 30 Years of Energy Use in IEACountries”, IEA/OECD, Paris, France. International Energy2006a. “World Energy Outlook”, IEA/OECD, Paris, France.

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

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2009-01-01

    for cooking and lighting. Biomass energy consumption willused in an economy, biomass energy consumption is certainlyby a large share of biomass energy use representing 50% of

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

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2009-01-01

    7 Figure 3. Energy Consumption in the Agriculture Sector (13 Figure 6. Energy Consumption in the ServiceFinal and Primary Energy Consumption in the Industry Sector,

  2. Energy End-Use Intensities in Commercial Buildings1995 -- Overview...

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

    by the Commercial Buildings Energy Consumption Survey (CBECS) and (2) building energy simulations provided by the Facility Energy Decision Screening (FEDS) system. The...

  3. Energy End-Use Intensities in Commercial Buildings1995 -- Tables

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

    model using survey data from the 1995 commercial buildings energy consumption survey and building energy simulations provided by the Facility Energy Decision Screening system....

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

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2009-01-01

    same activities that require energy today will continue toaccounting of how energy is consumed today. For each sector,

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

    E-Print Network [OSTI]

    Letter Report on Testing of Distributed Energy Resource, Microgrid, and End-Use Efficiency of Distributed Energy Resource, Microgrid, and End Use Efficiency Technologies (Task 8) This completes Under Cooperative Agreement No. DE-FC26-06NT42847 Hawai`i Distributed Energy Resource Technologies

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

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2009-01-01

    Tables Figures Figure 1. India Primary Energy Supply by fuel7 Figure 2. Final and Primary Energy (including biomass) by19 Figure 10. Final and Primary Energy Consumption in the

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

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2009-01-01

    2002, “TEDDY: TERI’s energy data directory and yearbook2006. “TEDDY: TERI’s energy data directory and yearbookU.S. DOE, 2006, “Buildings Energy Data Book 2006”, September

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

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2009-01-01

    gas oil nuclear hydro Energy output Own Uses Transmissiongas oil nuclear hydro Energy output Own Uses Transmissionenergy equivalence of electricity generated from hydro or

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

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2009-01-01

    pumps in India”, Renewable and Sustainable Energy Reviews,Renewable Energy (MNES), 2008. “Annual Report 2007-08”. Government of India.

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

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2009-01-01

    Statistics and Programme Implementation published a condensed version of statics related to energy production and consumption (

  11. Canadian Industrial Energy End-use Data and Analysis

    E-Print Network [OSTI]

    in Canadian Oil Refineries, 1990, 1994 to the current year Detailed reports on energy consumption, an initiative begun in October, 1991, is to expand and improve the existing knowledge on energy consumption data on energy consumption, on the characteristics of energy using equipment and buildings

  12. Energy End-Use Intensities in Commercial Buildings

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

    Active Solar: As an energy source, energy from the sun collected and stored using mechanical pumps or fans to circulate heat-laden fluids or air between solar collectors and the...

  13. Energy End-Use Intensities in Commercial Buildings

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

    2. Energy Use in Commercial Buildings The purpose of this section is to provide an overview of how energy was used in commercial buildings. Focusing on 1989 buildings, the section...

  14. Canadian Industrial Energy End-use Data and Analysis

    E-Print Network [OSTI]

    technologies. CIEEDAC is responsible for the industrial energy data under this initiative. The Centre operates as part clearinghouse, part depository, and part analysis centre for energy data on the Canadian

  15. Energy End-Use Intensities in Commercial Buildings

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

    Intensities The purpose of this section is to provide information on how energy was used for space conditioning--heating, cooling, and ventilation--in commercial...

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

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2009-01-01

    Petroleum pricing in India: balancing efficiency andand Tables Figures Figure 1. India Primary Energy Supply by28 Table 13. India, US and France Farm Machinery

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

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2009-01-01

    Past Trend and Future Outlook",LBNL forthcoming. de la Rue2006. “Building up India: Outlook for India’s real estate”,2006a. “World Energy Outlook”, IEA/OECD, Paris, France.

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

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2009-01-01

    of oil use for the need of LPG and kerosene for cooking andSector PJ Fuel Oil Diesel Oil LPG Electricity Source: CEA,PJ) PJ fuel oil diesel LPG electricity Energy consumption is

  19. 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 Fuels DataEnergy Webinar:IAbout Us|of EnergySmall-

  20. Engineer End Uses for Maximum Efficiency | 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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustmentsShirleyEnergyTher i n cEnergyNatural GasDepartmentApril 13, 2010|Earned Value (EV)

  1. Canadian Industrial Energy End-use Data and Analysis

    E-Print Network [OSTI]

    Resources Canada's National Energy Use Database (NEUD) initiative. The primary goal of the NEUD to further analyze specific data- related issues. In terms of its database role, the Centre focuses-to-date documentation of the various databases; houses a specialized library of published reports; and maintains

  2. Efficient Multi-Level Modeling and Monitoring of End-use Energy Profile in Commercial Buildings

    E-Print Network [OSTI]

    Kang, Zhaoyi

    2015-01-01

    buildings”. In: Energy Efficiency 5.2 (2012), pp. 149–162. [Sys- tems for Energy-Efficiency in Buildings. ACM. 2011, pp.Efficient Multi-Level Modeling and Monitoring of End-use

  3. 1999 Commercial Buildings Characteristics--Energy Sources and End Uses

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet)Decade Year-0ProvedDecade Year-0Cubic Monthly ActualActivitiesEnergy Sources

  4. Alternative Strategies for Low Pressure End Uses | 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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustmentsShirleyEnergyTher i n c i p a l De p u t y AEfficiency Rebate ProgramsAlpena<fuelalternative

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

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

    Assembly of a Molecular Needle, from the Bottom Up Print Many pathogenic bacteria use a specialized secretion system to inject virulence proteins directly into the cells they...

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

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

    Needle, from the Bottom Up Print Wednesday, 21 December 2005 00:00 Many pathogenic bacteria use a specialized secretion system to inject virulence proteins directly into the...

  7. 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

  8. The Bottom-Up Freezing: An Approach to Neural Engineering

    E-Print Network [OSTI]

    Ghorbani, Ali

    The Bottom-Up Freezing: An Approach to Neural Engineering Ali Farzan and Ali A. Ghorbani Faculty of the proposed method is to reduce the size of the network by freezing any node that does not actively presents a new pruning method. The proposed method, which we call Bottom-Up Freezing (BUF), alters

  9. 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

    2011-01-01

    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).

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

    E-Print Network [OSTI]

    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

  11. Bottom-up graphene nanoribbon field-effect transistors

    SciTech Connect (OSTI)

    Bennett, Patrick B.; Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, California 94720 ; Pedramrazi, Zahra; Madani, Ali; Chen, Yen-Chia; Crommie, Michael F.; Materials Sciences Division, Lawrence Berkeley National Laboratories, Berkeley, California 94720 ; Oteyza, Dimas G. de; Centro de Física de Materiales CSIC Chen, Chen; Fischer, Felix R.; Materials Sciences Division, Lawrence Berkeley National Laboratories, Berkeley, California 94720 ; Bokor, Jeffrey; Materials Sciences Division, Lawrence Berkeley National Laboratories, Berkeley, California 94720

    2013-12-16

    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.

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

    Reports and Publications (EIA)

    2007-01-01

    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.

  13. 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.

    2007-11-27

    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.

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

    E-Print Network [OSTI]

    Konopacki, S.J.

    2010-01-01

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

    SciTech Connect (OSTI)

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

    2006-06-01

    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.

  16. 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 by matching the winds of the 14 Middle-Atlantic Bight (MAB) to energy demand in the 15 adjacent states] We develop methods for assessing offshore wind 9 resources, using a model of the vertical structure

  17. End-use Breakdown: The Building Energy Modeling Blog | 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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustmentsShirleyEnergyTher i n cEnergy (AZ,Local GovernmentofVoltageEnergyEnergyWell, theRSS

  18. 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

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

    E-Print Network [OSTI]

    McNeil, Michael A.

    2013-01-01

    Kaya, Y. , Impact of Carbon Dioxide Emissions on GNP Growth:savings and carbon dioxide emissions mitigation. Finalentering the stock. Carbon dioxide emissions are calculated

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

    E-Print Network [OSTI]

    McNeil, Michael A.

    2013-01-01

    year data forecasted according to trends in the World Energyyear data, and scaling by the trend of IEA’s World Energyenergy consumption data (from IEA) and divided by GDPVA IND from the World

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

    E-Print Network [OSTI]

    McNeil, Michael A.

    2013-01-01

    Product Class Units Electric kWh/yr USA Gas Storage GJ/yr USA Gas Storage GJ/yr CAN Gas Storage Gas Instantaneous Gas Instantaneous GJ/yr

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

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet)DecadeYear Jan Feb Mar Apr May Jun2003 Detailed Tables 0.20032003energy per

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

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet)DecadeYear Jan Feb Mar Apr May Jun2003 Detailed Tablesof Energy for alloffuel

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

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet)DecadeYear Jan Feb Mar Apr May Jun2003 Detailed Tablesof Energy for

  5. Service Report Energy Information Administration Office of Energy Markets and 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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet) Wyoming963 1.969 1.979 1.988 1.996 2.003 1990-2016November 2000 OverviewEnergy

  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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page|Monthly","10/2015","1/15/1981" ,"DataWorking17.2 116.9 107.6 104.9612. End Uses of348

  7. " 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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page|Monthly","10/2015","1/15/1981" ,"DataWorking17.2 116.9 107.6 104.9612. End Uses of3482. End

  8. " 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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page|Monthly","10/2015","1/15/1981" ,"DataWorking17.2 116.9 107.6 104.9612. End Uses of3482. End5

  9. " 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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page|Monthly","10/2015","1/15/1981" ,"DataWorking17.2 116.9 107.6 104.9612. End Uses of3482.

  10. " 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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page|Monthly","10/2015","1/15/1981" ,"DataWorking17.2 116.9 107.6 104.9612. End Uses of3482.5 End

  11. " 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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page|Monthly","10/2015","1/15/1981" ,"DataWorking17.2 116.9 107.6 104.9612. End Uses of3482.5

  12. " 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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page|Monthly","10/2015","1/15/1981" ,"DataWorking17.2 116.9 107.6 104.9612. End Uses of3482.55

  13. " 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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page|Monthly","10/2015","1/15/1981" ,"DataWorking17.2 116.9 107.6 104.9612. End Uses of3482.556

  14. Level: National Data; Row: End Uses within NAICS Codes; 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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet) Wyoming963Residential Consumers (Number of33 2,297 809 245 15504 End Uses of1

  15. Level: National Data; Row: End Uses within NAICS Codes; 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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet) Wyoming963Residential Consumers (Number of33 2,297 809 245 15504 End Uses of12

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

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet)DecadeYear Jan Feb Mar Apr May Jun Jul1998,(Million CubicEnd Use:‹Homeand

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

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet)DecadeYear Jan Feb Mar Apr May Jun Jul1998,(Million CubicEnd1995 End-Use Data

  18. 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

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

    E-Print Network [OSTI]

    McKone, Thomas E.

    2011-01-01

    resources (DEER) Update Shldy (Energy Commission, 2001). Asfor Energy Efficiency Resources (DEER) Update Study" (Final

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

    E-Print Network [OSTI]

    Authors, Various

    2011-01-01

    Potential Alternative Fuels Derivatives from Municipal Solid Waste. In EnergyPotential Energy Savings -- Source Separation Table 15. Comparative Energy Savings For Newsprint Recovery and MSW Fuel

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

    E-Print Network [OSTI]

    Authors, Various

    2011-01-01

    in the resource stream where energy recovery from materialsMSW Derived Energy Table 10. Recyclables in the Waste Stream

  2. Food supplementation leads to bottom-up and top-down foodhostparasite interactions

    E-Print Network [OSTI]

    Zanette, Liana

    Food supplementation leads to bottom-up and top-down food­host­parasite interactions Liana Zanette1 `bottom-up' effects because we previously found that food supplemented sparrows better eluded nest results to the contrary. Food supplemented sparrows were parasitized as often as non-food supplemented

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

    E-Print Network [OSTI]

    McKone, Thomas E.

    2011-01-01

    for coal, natural gas, oil, and waste-to-energy (WTE) firedcoal, natural gas, oil and waste-to-energy fired electricitytype (coal, oil, natural gas, or waste-to-energy, or WTE),

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

    E-Print Network [OSTI]

    Konopacki, S.J.

    2010-01-01

    Summer Study on Energy Efficiency in Buildings, Volume 10,Summer Study on Energy Efficiency in Buildings, V o l 10, ppSummer Study on Energy Efficiency in Buildings, Volume 3, p.

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

    E-Print Network [OSTI]

    Schipper, Lee

    2013-01-01

    growth in the residential demand for energy, particularlydemand for energy. In Griffinps epic study (1) the author was forced to model residential

  6. America's Bottom-Up Climate Change Mitigation Policy

    E-Print Network [OSTI]

    Lutsey, Nicholas P.; Sperling, Dan

    2008-01-01

    domestic ‘‘push’’. Energy Policy 35, 1282–1291. Bergerson,N. Lutsey, D. Sperling / Energy Policy 36 (2008) 673–685Lutsey, D. Sperling / Energy Policy 36 (2008) 673–685 U.S.

  7. 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.

    2014-02-01

    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.

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

    E-Print Network [OSTI]

    Konopacki, S.J.

    2010-01-01

    of existing building and energy use data and obtain energydata; IFS building inventory data, building prototypes,Inventory The IFS building inventory data included building

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

    E-Print Network [OSTI]

    potential renewable, distributed energy resource, and micro-grid technology initiatives. Specific activities renewable generation technologies. The more energy storage available on the grid, the more intermittent renewables such as wind and solar that can be added to the grid. Currently grids use backup power generators

  10. America's Bottom-Up Climate Change Mitigation Policy

    E-Print Network [OSTI]

    Lutsey, Nicholas P.; Sperling, Dan

    2008-01-01

    develop renewable energy credit-tracking and trading systemenergy and emissions technologies, and development of emissions trading

  11. Energy balances in the production and end-use of methanol derived from coal

    SciTech Connect (OSTI)

    1980-12-10

    Analysis is performed for three combinations of fuels, specifically: net petroleum gain (petroleum only); net premium fuel gain (natural gas and petroleum); and net energy gain (includes all fuels; does not include free energy from sun). The base case selected for evaluation was that of an energy-efficient coal-to-methanol plant located in Montana/Wyoming and using the Lurgi conversion process. The following variations of the base coal-methanol case are also analyzed: gasoline from coal with methanol as an intermediate step (Mobil-M); and methanol from coal (Texaco gasification process). For each process, computations are made for the product methanol as a replacement for unleaded gasoline in a conventional spark ignition engine and as a chemical feedstock. For the purpose of the energy analysis, computations are made for three situations regarding mileage of methanol/ gasoline compared to that of regular unleaded gasoline: mileage of the two fuels equal, mileage 4 percent better with gasohol, and mileage 4 percent worse with gasohol. The standard methodology described for the base case applies to all of the variations.

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

    SciTech Connect (OSTI)

    Ferraro, R.J.; McConnell, B.W.

    1993-06-01

    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.

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

    E-Print Network [OSTI]

    Bracken, MES; Stachowicz, J J

    2007-01-01

    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

  14. 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 on Google Bookmark EERE: AlternativeMonthly","10/2015"Monthly","10/2015" ,"Release7CubicthroughtheSeptember 24,4,630.22Primary Consumption6.9. Energy

  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.

    1996-08-01

    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. End-Use Sector Flowchart

    Broader source: Energy.gov [DOE]

    This system of energy intensity indicators for total energy covers the economy as a whole and each of the major end-use sectors—transportation, industry, commercial and residential—identified in Figure 1. By clicking on any of the boxes with the word "Sector" in the title will reveal the more detailed structure within that sector.

  17. Formation and Film Characteristics of Dual Damascene Interconnects by Bottom-up Electroless Cu Plating

    SciTech Connect (OSTI)

    Shingubara, S. [Kansai University, Dept. of Mechanical Engineering, Suita 3-3-35, Osaka (Japan); Wang, Z. [Shaanxi Normal University, School of Chemistry and Materials Science (China)

    2006-02-07

    Bottom-up filling of Cu in a dual damascene interconnection structure was achieved through electroless plating alone. The addition of inhibitor molecules to the electroless Cu plating solution was investigated, and showed that sulfopropyl sulfonate (SPS) was highly effective in promoting bottom-up filling. Bottom-up filling was enhanced by shrinkage of the hole diameter, suggesting that the diffusion flux of SPS molecules to the bottom of the holes was suppressed. Thus, Cu deposition rate near the hole bottom was larger than that outside the hole, leading to bottom-up filling. The salient feature of electroless plating technology is the lack of overgrowth or bump formation after hole filling, which is a serious problem in electroplating technology. Problems such as increased resistance due to inclusion of SPS molecules and pattern size dependence affected applicability of this method. A two-step electroless plating using different concentrations of inhibitor molecules was effective for filling a dual damascene structure without voiding, and may provide a practical solution for ULSI interconnections.

  18. Statistical Evaluation of a Bottom-Up Clustering for Single Particle Molecular Images

    E-Print Network [OSTI]

    Stephan, Frank

    structures are solved. Under low dose conditions to minimize radiation damage? molecular images are usually i m o n o h a r a ' ~ ~Kiyoshi Asai1 yukio0cbrc.j p asaimcbrc .j p ' Computational Biology Research by bottom-up clustering, a hierarchical algorithm, using simulated protein images with a low signal- to

  19. 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

  20. 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

  1. 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

  2. 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

  3. Growing Artificial Societies: Social Science from the Bottom Up. By Joshua M. Epstein and Robert Axtell.

    E-Print Network [OSTI]

    Tesfatsion, Leigh

    Growing Artificial Societies: Social Science from the Bottom Up. By Joshua M. Epstein and Robert be passed in modified form to descendants. Such an artificial society can grow itself over time, with large) and a vision level that helps it search for sugar. Any sugar collected by an agent in excess of its metabolic

  4. A Bottom-up Merging Algorithm for Chinese Unknown Word Extraction

    E-Print Network [OSTI]

    A Bottom-up Merging Algorithm for Chinese Unknown Word Extraction Wei-Yun Ma Institute, Academia Sinica kchen@iis.sinica.edu.tw Abstract Statistical methods for extracting Chinese unknown words of characters with no delimiters to mark word boundaries. Therefore the initial step for Chinese processing

  5. 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

    2011-04-15

    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.

  6. End-use taxes: Current EIA practices

    SciTech Connect (OSTI)

    Not Available

    1994-08-17

    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.

  7. Top-down and bottom-up definitions of human failure events in human reliability analysis

    SciTech Connect (OSTI)

    Boring, Ronald Laurids

    2014-10-01

    In the probabilistic risk assessments (PRAs) used in the nuclear industry, human failure events (HFEs) are determined as a subset of hardware failures, namely those hardware failures that could be triggered by human action or inaction. This approach is top-down, starting with hardware faults and deducing human contributions to those faults. Elsewhere, more traditionally human factors driven approaches would tend to look at opportunities for human errors first in a task analysis and then identify which of those errors is risk significant. The intersection of top-down and bottom-up approaches to defining HFEs has not been carefully studied. Ideally, both approaches should arrive at the same set of HFEs. This question is crucial, however, as human reliability analysis (HRA) methods are generalized to new domains like oil and gas. The HFEs used in nuclear PRAs tend to be top-down—defined as a subset of the PRA—whereas the HFEs used in petroleum quantitative risk assessments (QRAs) often tend to be bottom-up—derived from a task analysis conducted by human factors experts. The marriage of these approaches is necessary in order to ensure that HRA methods developed for top-down HFEs are also sufficient for bottom-up applications.

  8. Piezoresistive characterization of bottom-up, n-type silicon microwires undergoing bend deformation

    SciTech Connect (OSTI)

    McClarty, Megan M.; Oliver, Derek R. E-mail: Derek.Oliver@umanitoba.ca; Bruce, Jared P.; Freund, Michael S. E-mail: Derek.Oliver@umanitoba.ca

    2015-01-12

    The piezoresistance of silicon has been studied over the past few decades in order to characterize the material's unique electromechanical properties and investigate their wider applicability. While bulk and top-down (etched) micro- and nano-wires have been studied extensively, less work exists regarding bottom-up grown microwires. A facile method is presented for characterizing the piezoresistance of released, phosphorus-doped silicon microwires that have been grown, bottom-up, via a chemical vapour deposition, vapour-liquid-solid process. The method uses conductive tungsten probes to simultaneously make electrical measurements via direct ohmic contact and apply mechanical strain via bend deformation. These microwires display piezoresistive coefficients within an order of magnitude of those expected for bulk n-type silicon; however, they show an anomalous response at degenerate doping concentrations (?10{sup 20?}cm{sup ?3}) when compared to lower doping concentrations (?10{sup 17?}cm{sup ?3}), with a stronger piezoresistive coefficient exhibited for the more highly doped wires. This response is postulated to be due to the different growth mechanism of bottom-up microwires as compared to top-down.

  9. Level: National Data; Row: End Uses within NAICS Codes; 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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet) Wyoming963Residential Consumers (Number of33 2,297 809 245 15504 End Uses of

  10. 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

    2007-01-01

    investment, behaviour, energy price, consumers Abstract “suggest that raising energy prices—such as in the form ofconsumers actually “see” energy prices and are therefore

  11. Beam-deposited platinum as versatile catalyst for bottom-up silicon nanowire synthesis

    SciTech Connect (OSTI)

    Hibst, N.; Strehle, S. [Institute of Electron Devices and Circuits, Ulm University, Albert-Einstein-Allee 45, 89081 Ulm (Germany); Knittel, P.; Kranz, C.; Mizaikoff, B. [Institute of Analytical and Bioanalytical Chemistry, Ulm University, Albert-Einstein-Allee 11, 89081 Ulm (Germany)

    2014-10-13

    The controlled localized bottom-up synthesis of silicon nanowires on arbitrarily shaped surfaces is still a persisting challenge for functional device assembly. In order to address this issue, electron beam and focused ion beam-assisted catalyst deposition have been investigated with respect to platinum expected to form a PtSi alloy catalyst for a subsequent bottom-up nanowire synthesis. The effective implementation of pure platinum nanoparticles or thin films for silicon nanowire growth has been demonstrated recently. Beam-deposited platinum contains significant quantities of amorphous carbon due to the organic precursor and gallium ions for a focused ion beam-based deposition process. Nevertheless, silicon nanowires could be grown on various substrates regardless of the platinum purity. Additionally, p-type doping could be realized with diborane whereas n-type doping suppressed a nanowire growth. The rational utilization of this beam-assisted approach enables us to control the localized synthesis of single silicon nanowires at planar surfaces but succeeded also in single nanowire growth at the three-dimensional apex of an atomic force microscopy tip. Therefore, this catalyst deposition method appears to be a unique extension of current technologies to assemble complex nanowire-based devices.

  12. Europe from the bottom up: A statistical examination of the central and northern European lithosphereasthenosphere boundary from comparing seismological

    E-Print Network [OSTI]

    Jones, Alan G.

    Europe from the bottom up: A statistical examination of the central and northern European: Lithosphere­asthenosphere boundary (LAB) Europe Seismology Magnetotellurics The Lithosphere, between the delineation of the LAB for Europe based on seismological and electromagnetic observations. We

  13. 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: Alternative Fuels Data Center Home PageMonthly","10/2015"4,"Ames City of",6,1,"OmahaEnergy Sources and End Uses Topics: Energy Sources and End Uses End-UseA 6 J 9 U B u o f l53DecadeVehicle

  14. 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: Alternative Fuels Data Center Home PageMonthly","10/2015"4,"Ames City of",6,1,"OmahaEnergy Sources and End Uses Topics: Energy Sources and End Uses End-UseA 6 J 9 U BEstimatedSales (Billion342,261

  15. Arizona 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 PageMonthly","10/2015"4,"Ames City of",6,1,"OmahaEnergy Sources and End Uses Topics: Energy Sources and End Uses End-UseA 6 J 9Cubic Feet) Oil1369,739 330,914

  16. Arkansas 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 PageMonthly","10/2015"4,"Ames City of",6,1,"OmahaEnergy Sources and End Uses Topics: Energy Sources and End Uses End-UseA 6 J 9CubicFeet)

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

    E-Print Network [OSTI]

    Ardani, Kristen

    2014-01-01

    and Utility-Scale Photovoltaic System Prices in the UnitedSoft) Costs for U.S. Photovoltaic Systems Using a Bottom-UpSoft) Costs for U.S. Photovoltaic Systems Using a Bottom-Up

  18. 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

  19. 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)

    1996-08-01

    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.

  20. End Use and Fuel Certification

    Broader source: Energy.gov [DOE]

    Breakout Session 2: Frontiers and Horizons Session 2–B: End Use and Fuel Certification John Eichberger, Vice President of Government Relations, National Association for Convenience Stores

  1. 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

  2. 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)

    2008-01-01

    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 ...

  3. A bottom-up method to develop pollution abatement cost curves for coal-fired utility boilers

    E-Print Network [OSTI]

    Barlaz, Morton A.

    costs depend, in part, on a complex combination of coal type, coal composition, boiler design, plantA bottom-up method to develop pollution abatement cost curves for coal-fired utility boilers. The Coal Utility Environmental Cost (CUECost) model is used to estimate retrofit costs for five different

  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.

    2011-01-01

    OF ENERGY CONSERVATION BUILDING CODES B. COST CALCULATIONScost calculations carries weight in California because the state EnergyCOST CALCULATIONS AS A BASIS FOR CODES Even small improvements in conservation design save energy, and

  5. 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.

    2011-01-01

    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

  6. 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

    2006-01-01

    Comision Nacional para el Ahorro del Energía, CONAE), thefund Fideicomiso para el Ahorro de Energía Eléctrica (FIDE)—

  7. 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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION J APPENDIX ECoop IncIowaWisconsin:Pontiac BiomassInformationSystems Inc

  8. 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.

    2013-10-01

    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.

  9. 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.

    2012-05-01

    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.

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

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

    Analysis Center Greg Smestad Sol Ideas Technology Development, Solar Energy Materials and Solar Cells Journal Hohyun Lee University of Santa Clara Alfred Hicks and Kendra Palmer...

  11. The drastic outcomes from voting alliances in three-party bottom-up democratic voting (1990 $\\rightarrow$ 2013)

    E-Print Network [OSTI]

    Galam, Serge

    2013-01-01

    The drastic effect of local alliances in three-party competition is investigated in democratic hierarchical bottom-up voting. The results are obtained analytically using a model which extends a sociophysics frame introduced in 1986 \\cite{psy} and 1990 \\cite{lebo} to study two-party systems and the spontaneous formation of democratic dictatorship. It is worth stressing that the 1990 paper was published in the Journal of Statistical Physics, the first paper of its kind in the journal. It was shown how a minority in power can preserve its leadership using bottom-up democratic elections. However such a bias holds only down to some critical value of minimum support. The results were used latter to explain the sudden collapse of European communist parties in the nineties. The extension to three-party competition reveals the mechanisms by which a very small minority party can get a substantial representation at higher levels of the hierarchy when the other two competing parties are big. Additional surprising results...

  12. 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: Alternative Fuels Data Center Home PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal, Nuclear,DecadeYear Jan FebElements)Feet) Decade8 45YearYearEnd-Use

  13. 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 Data Center Home Page on Delicious RankADVANCEDInstallers/ContractorsPhotovoltaics »TanklessResearchEnergy2Fall 2011 TheMarch

  14. 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

    2011-01-01

    on Nu- clear and Alternative Energy Systems ( CONAES) andCommittee on Nuclear and Alternative Energy Systems (CONAES)on Nu- clear and Alternative Energy Systems (CONAES) and FEA

  15. Conservative and dissipative force field for simulation of coarse-grained alkane molecules: A bottom-up approach

    SciTech Connect (OSTI)

    Trément, Sébastien; Rousseau, Bernard, E-mail: bernard.rousseau@u-psud.fr [Laboratoire de Chimie-Physique, UMR 8000 CNRS, Université Paris-Sud, Orsay (France)] [Laboratoire de Chimie-Physique, UMR 8000 CNRS, Université Paris-Sud, Orsay (France); Schnell, Benoît; Petitjean, Laurent; Couty, Marc [Manufacture Française des Pneumatiques MICHELIN, Centre de Ladoux, 23 place des Carmes, 63000 Clermont-Ferrand (France)] [Manufacture Française des Pneumatiques MICHELIN, Centre de Ladoux, 23 place des Carmes, 63000 Clermont-Ferrand (France)

    2014-04-07

    We apply operational procedures available in the literature to the construction of coarse-grained conservative and friction forces for use in dissipative particle dynamics (DPD) simulations. The full procedure rely on a bottom-up approach: large molecular dynamics trajectories of n-pentane and n-decane modeled with an anisotropic united atom model serve as input for the force field generation. As a consequence, the coarse-grained model is expected to reproduce at least semi-quantitatively structural and dynamical properties of the underlying atomistic model. Two different coarse-graining levels are studied, corresponding to five and ten carbon atoms per DPD bead. The influence of the coarse-graining level on the generated force fields contributions, namely, the conservative and the friction part, is discussed. It is shown that the coarse-grained model of n-pentane correctly reproduces self-diffusion and viscosity coefficients of real n-pentane, while the fully coarse-grained model for n-decane at ambient temperature over-predicts diffusion by a factor of 2. However, when the n-pentane coarse-grained model is used as a building block for larger molecule (e.g., n-decane as a two blobs model), a much better agreement with experimental data is obtained, suggesting that the force field constructed is transferable to large macro-molecular systems.

  16. Philippine Marine Fisheries Catches: A Bottom-up Reconstruction, 1950-2010, Palomares, MLD and Pauly, D (eds.) Reconstructed marine fisheries catches of the Philippines, 1950-2010101

    E-Print Network [OSTI]

    Pauly, Daniel

    Philippine Marine Fisheries Catches: A Bottom-up Reconstruction, 1950-2010, Palomares, MLD.L.D. Palomares and D. Pauly Sea Around Us, Fisheries Centre, University of British Columbia, 2202 Main Mall, Vancouver BC, V6T 1Z4; Email: m.palomares@fisheries.ubc.ca; d.pauly@fisheries.ubc.ca Abstract

  17. Philippine Marine Fisheries Catches: A Bottom-up Reconstruction, 1950-2010, Palomares, MLD and Pauly, D (eds.) Philippine marine fisheries 1011

    E-Print Network [OSTI]

    Pauly, Daniel

    Philippine Marine Fisheries Catches: A Bottom-up Reconstruction, 1950-2010, Palomares, MLD and Pauly, D (eds.) 1 Philippine marine fisheries 1011 M.L.D. Palomares1 , V.A. Parducho2 , M. Bimbao2 , E, Vancouver BC, V6T 1Z4; Email: m.palomares@fisheries.ubc.ca 2 FishBase Information and Research Group, Inc

  18. Preliminary CBECS End-Use Estimates

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

    For the past three CBECS (1989, 1992, and 1995), we used a statistically-adjusted engineering (SAE) methodology to estimate end-use consumption. The core of the SAE methodology...

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

    E-Print Network [OSTI]

    Sathaye, J.

    2011-01-01

    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

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

    E-Print Network [OSTI]

    Sathaye, J.

    2011-01-01

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

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

    E-Print Network [OSTI]

    Sathaye, J.

    2011-01-01

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

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

    E-Print Network [OSTI]

    Sathaye, J.

    2011-01-01

    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

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

    E-Print Network [OSTI]

    Sathaye, J.

    2011-01-01

    one or more additives (fly ash, pozzolans, granulated blastblending materials are fly ash and granulated blast furnaceslag. Not all slag and fly ash is suitable for cement

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

    E-Print Network [OSTI]

    Zhou, Nan

    2010-01-01

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

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

    E-Print Network [OSTI]

    Sathaye, J.

    2011-01-01

    2 Cogeneration systems can either be direct gas turbinesCogeneration. Waste gas discharged from the kiln exit gases, the clinker cooler system,

  6. " 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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page|Monthly","10/2015","1/15/1981" ,"DataWorking17.2 116.9 107.6 104.9612. End Uses of34 End3.

  7. " 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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page|Monthly","10/2015","1/15/1981" ,"DataWorking17.2 116.9 107.6 104.9612. End Uses of34 End3.7

  8. " 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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page|Monthly","10/2015","1/15/1981" ,"DataWorking17.2 116.9 107.6 104.9612. End Uses of34 End3.78

  9. " 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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page|Monthly","10/2015","1/15/1981" ,"DataWorking17.2 116.9 107.6 104.9612. End Uses of34

  10. " 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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page|Monthly","10/2015","1/15/1981" ,"DataWorking17.2 116.9 107.6 104.9612. End Uses of348 End

  11. " 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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page|Monthly","10/2015","1/15/1981" ,"DataWorking17.2 116.9 107.6 104.9612. End Uses of348 End7

  12. " 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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page|Monthly","10/2015","1/15/1981" ,"DataWorking17.2 116.9 107.6 104.9612. End Uses of348 End78

  13. 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.

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

    E-Print Network [OSTI]

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

    1988-01-01

    custom-designed to facilitate collection and validation of the end-use load data. For example, the Load Profile Viewer is a PC-based software program for reviewing and validating the end-use load data....

  15. Engineer End Uses for Maximum Efficiency; Industrial Technologies...

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

    specified by the manufacturer, and the air going to all end uses should be free of condensate to maximize tool life and effectiveness. 6 End uses having similar air requirements...

  16. Bottom-Up Strategic Planning

    E-Print Network [OSTI]

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

    2013-01-01

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

  17. Bottom-Up Strategic Planning

    E-Print Network [OSTI]

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

    2013-01-01

    and Hiram Davis, “Strategic-Planning as a Catalyst forD. Hensley, “A New Strategic-Planning Model for Academic-Academic Libraries: Should Strategic Planning Be Renewed? ,”

  18. Enduse Global Emissions Mitigation Scenarios (EGEMS): A New Generation of Energy Efficiency Policy Planning Models

    E-Print Network [OSTI]

    McNeil, Michael A.

    2010-01-01

    driver for the energy demand forecast. The basic assumptionglobal bottom-up energy demand forecasts, and a frameworkin modelling energy demand is to forecast activity. Activity

  19. Constructing Ordered Sensitized Heterojunctions: Bottom-Up Electrochemical Synthesis of p-Type Semiconductors in Oriented n-TiO2 Nanotube Arrays

    SciTech Connect (OSTI)

    Wang, Q.; Zhu, K.; Neale, N. R.; Frank. A. J.

    2009-01-01

    Fabrication of efficient semiconductor-sensitized bulk heterojunction solar cells requires the complete filling of the pore system of one semiconductor (host) material with nanoscale dimensions (<100 nm) with a different semiconductor (guest) material. Because of the small pore size and electrical conductivity of the host material, it is challenging to employ electrochemical approaches to fill the entire pore network. Typically, during the electrochemical deposition process, the guest material blocks the pores of the host, precluding complete pore filling. We describe a general synthetic strategy for spatially controlling the growth of p-type semiconductors in the nanopores of electrically conducting n-type materials. As an illustration of this strategy, we report on the facile electrochemical deposition of p-CuInSe{sub 2} in nanoporous anatase n-TiO{sub 2} oriented nanotube arrays and nanoparticle films. We show that by controlling the ambipolar diffusion length the p-type semiconductors can be deposited from the bottom-up, resulting in complete pore filling.

  20. Delaware 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 PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal, Nuclear, Electric andHousehold Vehicles Energy Usei9)Year Jan FebYear

  1. Idaho 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 PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal, Nuclear, ElectricRhodeFeet)CubicCitygateC : Q U A L I T Y O387

  2. Illinois 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 PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal, Nuclear, ElectricRhodeFeet)CubicCitygateC : Q UYear Jan Feb956,068

  3. Indiana 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 PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal, Nuclear, ElectricRhodeFeet)CubicCitygateC : (MillionSame4 15.8Year

  4. Iowa 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 PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal, Nuclear,Decade Year-0 Year-1 Year-2 Year-3 Year-45)Decade Year-0315,186

  5. Kansas 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 PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal, Nuclear,Decade Year-0 Year-1 Year-2Decade Year-0DecreasesYear Jan Feb

  6. Kentucky 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 PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal, Nuclear,Decade Year-0 Year-1Decade Year-0 Year-1Cubic0 0SalesYear Jan

  7. Louisiana 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 PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal, Nuclear,Decade Year-0 Year-1Decade2,9191,189,744 1,354,641 1,420,264

  8. Maine 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 PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal, Nuclear,Decade Year-03.82 4.235,382 6,358 8,483 11,08220110,334 77,575

  9. Maryland 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 PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal, Nuclear,Decade Year-03.82 4.235,382 6,358 (Million Cubic S196,510 212,020

  10. Massachusetts 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 PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal, Nuclear,Decade Year-03.82 4.235,382Year Jan Feb Mar Apr May2395,852

  11. Michigan 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 PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal, Nuclear,Decade Year-03.82 4.235,382Year52 55 59 7135,340 746,748 776,466

  12. Minnesota 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 PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal, Nuclear,Decade Year-03.82 4.235,382Year526)Midwest Region9 1,010Year

  13. Mississippi 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 PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal, Nuclear,Decade Year-03.82 (Million Cubic Feet)118Decade Year-0

  14. Missouri 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 PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal, Nuclear,Decade Year-03.82 (Million (MillionFeet)117 94 90 8207264,867

  15. Montana 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 PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal, Nuclear,Decade Year-03.82 (Millionand PlantDecade4)New0 0 0 2 075,802

  16. California 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 PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal, Nuclear, Electric and Alternate FuelsSales (Billion Cubic5 2 7 -5

  17. Colorado 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 PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal, Nuclear, Electric and AlternateYear Jan523,726 501,350 466,680 443,750

  18. Connecticut 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 PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal, Nuclear, Electric and AlternateYear(Million42Year Jan Feb Mar Apr May

  19. Florida 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 PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal, Nuclear, ElectricRhode Island2009 20103 PC'sIncreases (Billion

  20. Georgia 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 PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal, Nuclear, ElectricRhodeFeet) Decade Year-0TobagoCommercialDecade462,799

  1. Hawaii 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 PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal, Nuclear, ElectricRhodeFeet)Cubic Feet)Cubic Feet)Decade2,607

  2. Nebraska 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 PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal, Nuclear,Decade Year-03.823,172 3,009165,360 165,928 209,4390 14 21Year

  3. Nevada 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 PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal, Nuclear,Decade Year-03.823,172Year Jan Feb Mar Apr-348,719Decade75,468

  4. 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: Alternative Fuels Data Center Home PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal, Nuclear,DecadeYear JanNew Field Discoveries (Billion Cubic740,925 784,293

  5. 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: Alternative Fuels Data Center Home PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal, Nuclear,DecadeYear JanNew FieldDecade Year-0Year Jan33 1,032659,305

  6. 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: Alternative Fuels Data Center Home PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal, Nuclear,DecadeYear JanNew FieldDecadeYear Jan Feb Mar16,78924248,864

  7. 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: Alternative Fuels Data Center Home PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal, Nuclear,DecadeYear JanNewMajor CharacteristicsStorage 690 39

  8. Tennessee 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 PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal, Nuclear,DecadeYearbyWithdrawalsHome6,672 7,2060 0 1216,945 257,443 264,231

  9. Texas 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 PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal, Nuclear,DecadeYearbyWithdrawalsHome6,672 7,2060Year0 0NewSales

  10. Utah 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 PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal,Demand Module of theCubicEstimation Results forExtensions44 1,045Year

  11. Vermont 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 PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal,Demand Module of theCubicEstimation ResultsYear JanYearDay)Year Jan Feb

  12. Virginia 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 PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal,Demand Module of theCubicEstimation ResultsYearYear JanSalesYear Jan

  13. Washington 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 PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal,Demand Module of theCubicEstimation10,428 285,726 264,589 264,540 318,292

  14. Wisconsin 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 PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal,Demand Module of6,090 7,163 10,532 14,881 23,209DecadeFeet)087,066

  15. 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.

    2013-01-01

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

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

    E-Print Network [OSTI]

    Tiedemann, Kenneth Mr.

    2013-01-01

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

  17. 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

    2008-01-01

    22, (4), 10. EIA Annual Energy Outlook 2006 with Projections4. EIA Annual Energy Outlook 2007 with Projections to 2030.to the Annual Energy Outlook 2007. Transportation Demand

  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

    2008-01-01

    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

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

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    domestic end-uses, the development of plug-in hybrid and electric vehicles, the increase of heat pumps heating systems such as heat pumps in new building or which will replace old installed fossil fuels based influences: · best building insulation which will reduce the energy needs for heating and cooling; · new

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

    SciTech Connect (OSTI)

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

    2008-07-31

    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.

  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.

    2011-01-01

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

  2. 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

    2014-01-01

    black liquor evaporation Lime kiln modifications Extended black liquor evaporation Lime kiln modifications Teriary effluents ClO2 filtrate heating Lime kiln oxygen enrichement

  3. 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.

    2011-01-01

    Bremen,” La Revue de Metallurgie-CIT 93(10): 1219-1226.Blast Furnaces,” La Revue de Metallurgie-CIT 92(3): 375-380.a Sinter Plant,” Revue de Metallurgie-CIT 3 92 pp. 329-335 (

  4. 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.

    2011-01-01

    Foamy slag Oxy-fuel burners Eccentric Bottom Tapping (EBT)combustion air for the burners and to generate high pressureNew Concept for Using Oxy-Fuel Burners and Oxygen Lances to

  5. 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.

    2011-01-01

    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,”

  6. 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.

    2011-01-01

    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

  7. 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

    2014-01-01

    Opportunities for the Pulp and Paper Industry (LBNL-2268E).in the U.S. Pulp and Paper Industry. Lawrence BerkeleyManagement in the Pulp and Paper Industry. Buehler, E. and

  8. 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

    2014-01-01

    the U.S. Pulp and Paper Industry. Lawrence Berkeley NationalProfile of the Pulp and Paper Industry, 2 nd Edition. Officefor the Pulp and Paper Industry (No. LBNL-2268E). Berkeley,

  9. 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.

    2011-01-01

    CASTING .Progress in Continuous Casting. ” International Energykg/thm Adopt continuous casting Reduced dust emissions and

  10. 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.

    2011-01-01

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

  11. 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

    2014-01-01

    heat recovery Implement efficient control systems for the machine steam  and condensate Heat Recovery Blowdown Steam Recovery Steam trap maintenance Automatic Steam Trap Monitoring Leak Repair Condensate Heat Recovery Blowdown Steam Recovery Steam trap maintenance Automatic Steam Trap Monitoring Leak Repair Condensate 

  12. 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

    2014-01-01

    screen out thick chips, boiler maintenance, steam trapSteam Production and Efficiency Boiler maintenance Improved of black liquor in recovery boiler High temperature video 

  13. 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.

    2011-01-01

    intensity of 2.6 GJ/t sinter. Sinter plant heat recovery.Heat recovery at the sinter plant is a means for improvingbuilding controls, waste heat recovery or adjustable speed

  14. 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.

    2011-01-01

    Variable speed drive coke oven gas compressors Coke dryVariable speed drive coke oven gas compressors Coke drythe waste heat from the coke oven gas to dry the coal used

  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.

    2011-01-01

    intensity of 2.6 GJ/t sinter. Sinter plant heat recovery.Heat recovery at the sinter plant is a means for improvinghave a positive effect on the heat recovery equipment. These

  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.

    2011-01-01

    costs. Waste heat recovery from cooling water. Waste heatrolling mill Waste heat recovery from cooling water Generalmill Waste heat recovery from cooling water Integrated Cold

  17. 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

    2014-01-01

    building controls, waste heat recovery or adjustable speedMill Identifies Heat Recovery Projects and Operationsgroundwood pulping ?Super Heat recovery in thermomechanical 

  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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page|Monthly","10/2015","1/15/1981" ,"DataWorking17.2 116.9 107.6 104.9612. End Uses of3 End Uses

  19. Refining and End Use Study of Coal Liquids

    SciTech Connect (OSTI)

    1997-10-01

    This report summarizes revisions to the design basis for the linear programing refining model that is being used in the Refining and End Use Study of Coal Liquids. This revision primarily reflects the addition of data for the upgrading of direct coal liquids.

  20. Industrial Steam Power Cycles Final End-Use Classification 

    E-Print Network [OSTI]

    Waterland, A. F.

    1983-01-01

    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...

  1. End-use Breakdown: The Building Energy Modeling Blog

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

    class"field-items">

    The AEC Technology Symposium and Hackathon brings together software developers that work in and...

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

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2009-01-01

    2006. “All India Electricity Statistics, General Review2005, “Industrial Statistics of India: Status and Issues”,is reported in India’s national statistics for this sector,

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

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2009-01-01

    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

    2009-01-01

    Efficiency in Electricity Consumption", HWWA Discussionelectricity includes electricity consumption plus thedistribution. Total electricity consumption represents 1,654

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

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2009-01-01

    Technology for Indian Pulp and Paper Industry” Newsletter ofwith 13% and the pulp and paper industry with 9%. Similarly,and Paper The Indian pulp and paper industry is the sixth

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

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2009-01-01

    2005a. “Statistics of the Indian Paper Industry: Directoryof Indian Paper Industry”. Volume II. Saharanpur, India. de2005. “The Indian Paper Industry: Towards Sustainability”,

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

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2009-01-01

    and 6 million diesel irrigation pump sets in operation (rural areas, pump sets are installed to provide irrigation

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

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2009-01-01

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

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

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2009-01-01

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

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

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2009-01-01

    photovoltaic water pumping systems since 1993- 94. About 7,000 pump set were installed with a capacity

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

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2009-01-01

    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

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

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2009-01-01

    first electricity distribution and transmission (T&D)Own Uses Transmission and distribution losses ElectricityOwn Uses Transmission and distribution loses Electricity

  13. Energy End-Use Intensities in Commercial Buildings

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

    lighting intensities per lighted square foot-hour (Figure 23). * Food service and health care buildings had the highest water-heating intensities per square foot--more than...

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

    Energy Savers [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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page on DeliciousMathematics AndBeryllium Disease |Records Management Field OfficerPaylor, Director ofDepartment of

  15. Energy End-Use Intensities in Commercial Buildings

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet) Wyoming963 1.969Central RegionReportingElectricity Glossary › FAQS ›1

  16. Energy End-Use Intensities in Commercial Buildings 1989

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet) Wyoming963 1.969Central RegionReportingElectricity Glossary › FAQS ›19

  17. Energy End-Use Intensities in Commercial Buildings 1992

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet)DecadeYear Jan Feb Mar Apr May Jun Jul1998,(Million CubicEnd

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

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet)DecadeYear Jan Feb Mar Apr May Jun2003 Detailed Tablesof1998 and 2002 2

  19. REFINING AND END USE STUDY OF COAL LIQUIDS

    SciTech Connect (OSTI)

    Unknown

    2002-01-01

    This document summarizes all of the work conducted as part of the Refining and End Use Study of Coal Liquids. There were several distinct objectives set, as the study developed over time: (1) Demonstration of a Refinery Accepting Coal Liquids; (2) Emissions Screening of Indirect Diesel; (3) Biomass Gasification F-T Modeling; and (4) Updated Gas to Liquids (GTL) Baseline Design/Economic Study.

  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

    2008-01-01

    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. 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)

    1992-03-01

    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.

  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.

    1994-05-01

    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. " 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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page|Monthly","10/2015","1/15/1981" ,"DataWorking17.2 116.9 107.6 104.9612. End Uses of Fuel

  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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page|Monthly","10/2015","1/15/1981" ,"DataWorking17.2 116.9 107.6 104.9612. End Uses of Fuel3.

  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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page|Monthly","10/2015","1/15/1981" ,"DataWorking17.2 116.9 107.6 104.9612. End Uses of Fuel3.4.

  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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page|Monthly","10/2015","1/15/1981" ,"DataWorking17.2 116.9 107.6 104.9612. End Uses of Fuel3.4.1

  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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page|Monthly","10/2015","1/15/1981" ,"DataWorking17.2 116.9 107.6 104.9612. End Uses of

  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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page|Monthly","10/2015","1/15/1981" ,"DataWorking17.2 116.9 107.6 104.9612. End Uses of3 End

  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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page|Monthly","10/2015","1/15/1981" ,"DataWorking17.2 116.9 107.6 104.9612. End Uses of3 End1 End

  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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page|Monthly","10/2015","1/15/1981" ,"DataWorking17.2 116.9 107.6 104.9612. End Uses of3 End1

  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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page|Monthly","10/2015","1/15/1981" ,"DataWorking17.2 116.9 107.6 104.9612. End Uses of3 End13

  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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page|Monthly","10/2015","1/15/1981" ,"DataWorking17.2 116.9 107.6 104.9612. End Uses of3 End134

  13. " 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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page|Monthly","10/2015","1/15/1981" ,"DataWorking17.2 116.9 107.6 104.9612. End Uses of3 End1341

  14. " 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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page|Monthly","10/2015","1/15/1981" ,"DataWorking17.2 116.9 107.6 104.9612. End Uses of3 End13412

  15. " 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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page|Monthly","10/2015","1/15/1981" ,"DataWorking17.2 116.9 107.6 104.9612. End Uses of3

  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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page|Monthly","10/2015","1/15/1981" ,"DataWorking17.2 116.9 107.6 104.9612. End Uses of34 End

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

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet)Decade Year-0 Year-1 Year-2Feet)Thousand7,Year Jan995 1555.3 End Uses of Fuel

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

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet)Decade Year-0 Year-1 Year-2Feet)Thousand7,Year Jan995 1555.3 End Uses of

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

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet)Decade Year-0 Year-1 Year-2Feet)Thousand7,Year Jan995 1555.3 End Uses of5 End

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

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet)Decade Year-0 Year-1 Year-2Feet)Thousand7,Year Jan995 1555.3 End Uses of5

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

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet)Decade Year-0 Year-1 Year-2Feet)Thousand7,Year Jan995 1555.3 End Uses of57

  2. Table 5.8 End Uses of Fuel Consumption, 2010;

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet)Decade Year-0 Year-1 Year-2Feet)Thousand7,Year Jan995 1555.3 End Uses of578

  3. Renewable Electricity Futures Study Volume 3: End-Use Electricity Demand

    Broader source: Energy.gov [DOE]

    This volume details the end-use electricity demand and efficiency assumptions. The projection of electricity demand is an important consideration in determining the extent to which a predominantly renewable electricity future is feasible. Any scenario regarding future electricity use must consider many factors, including technological, sociological, demographic, political, and economic changes (e.g., the introduction of new energy-using devices; gains in energy efficiency and process improvements; changes in energy prices, income, and user behavior; population growth; and the potential for carbon mitigation).

  4. Detailed End Use Load Modeling for Distribution System Analysis

    SciTech Connect (OSTI)

    Schneider, Kevin P.; Fuller, Jason C.

    2010-04-09

    The field of distribution system analysis has made significant advances in the past ten years. It is now standard practice when performing a power flow simulation to use an algorithm that is capable of unbalanced per-phase analysis. Recent work has also focused on examining the need for time-series simulations instead of examining a single time period, i.e., peak loading. One area that still requires a significant amount of work is the proper modeling of end use loads. Currently it is common practice to use a simple load model consisting of a combination of constant power, constant impedance, and constant current elements. While this simple form of end use load modeling is sufficient for a single point in time, the exact model values are difficult to determine and it is inadequate for some time-series simulations. This paper will examine how to improve simple time invariant load models as well as develop multi-state time variant models.

  5. Bottom-Up Argumentation Francesca Toni1

    E-Print Network [OSTI]

    Toni, Francesca

    be fixed?). Others may be serendipitous (e.g. while discussing the recent tsunami in Japan one may end up debating pros and cons of nuclear power stations). While it is acknowledged (e.g. in [11

  6. Bottom-Up Propositionalization Stefan Kramer1

    E-Print Network [OSTI]

    Frank, Eibe

    - gorithms. This transformation requires the construction of features that capture relational properties would be 'o-s-c', meaning "an oxygen atom with a single bond to a sulfur atom with a single bond

  7. 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.

    2012-12-01

    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).

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

    E-Print Network [OSTI]

    Zheng, Nina

    2010-01-01

    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

  9. The Reality and Future Scenarios of Commercial Building Energy Consumption in China

    E-Print Network [OSTI]

    Zhou, Nan

    2008-01-01

    Wang Qingyi, 2005, 2005 energy data for Fiscal and EconomicStatistics in Japan, The Energy Data and Modeling Center,of the current energy data. The bottom-up approach allows

  10. Policy modeling for industrial energy use

    E-Print Network [OSTI]

    2003-01-01

    Energy Outlook 2002. The IEA produces every year the WEO.For the 2002 WEO a combined ‘top- down’ and ‘bottom-up’for OECD. The new WEO is the result of collaboration of two

  11. GIS-based energy consumption mapping 

    E-Print Network [OSTI]

    Balta, Chrysi

    2014-11-27

    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 ...

  12. Technology data characterizing water heating in commercial buildings: Application to end-use forecasting

    SciTech Connect (OSTI)

    Sezgen, O.; Koomey, J.G.

    1995-12-01

    Commercial-sector conservation analyses have traditionally focused on lighting and space conditioning because of their relatively-large shares of electricity and fuel consumption in commercial buildings. In this report we focus on water heating, which is one of the neglected end uses in the commercial sector. The share of the water-heating end use in commercial-sector electricity consumption is 3%, which corresponds to 0.3 quadrillion Btu (quads) of primary energy consumption. Water heating accounts for 15% of commercial-sector fuel use, which corresponds to 1.6 quads of primary energy consumption. Although smaller in absolute size than the savings associated with lighting and space conditioning, the potential cost-effective energy savings from water heaters are large enough in percentage terms to warrant closer attention. In addition, water heating is much more important in particular building types than in the commercial sector as a whole. Fuel consumption for water heating is highest in lodging establishments, hospitals, and restaurants (0.27, 0.22, and 0.19 quads, respectively); water heating`s share of fuel consumption for these building types is 35%, 18% and 32%, respectively. At the Lawrence Berkeley National Laboratory, we have developed and refined a base-year data set characterizing water heating technologies in commercial buildings as well as a modeling framework. We present the data and modeling framework in this report. The present commercial floorstock is characterized in terms of water heating requirements and technology saturations. Cost-efficiency data for water heating technologies are also developed. These data are intended to support models used for forecasting energy use of water heating in the commercial sector.

  13. 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

    2009-03-31

    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 .

  14. District of Columbia 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 PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal, Nuclear, Electric andHousehold VehiclesVehicleYear Jan Feb Mar AprYear

  15. Gulf of Mexico 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 PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal, Nuclear, ElectricRhodeFeet)Cubic Feet) Decade(Million(Million--

  16. New Hampshire 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 PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal, Nuclear,Decade Year-03.823,172Year Jan Feb (MillionDecade59,950 60,378

  17. New Jersey 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 PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal, Nuclear,Decade Year-03.823,172Year JanDecade Year-0 Year-129620,790

  18. New Mexico 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 PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal, Nuclear,Decade Year-03.823,172YearDecade Year-0 Year-1 Year-2

  19. 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: Alternative Fuels Data Center Home PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal, Nuclear,DecadeYear Jan Feb Mar Apr May Jun JulFeet) NewSales1

  20. 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: Alternative Fuels Data Center Home PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal, Nuclear,DecadeYear Jan Feb Mar Apr721,507 836,698 867,922247,047 304,148

  1. 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: Alternative Fuels Data Center Home PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal, Nuclear,DecadeYear Jan Feb MarFeet) EstimatedSales

  2. Rhode Island 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 PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal, Nuclear,DecadeYearby the(Dollars1.840 2.318 3.1195) Model8)32392,743

  3. South 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: Alternative Fuels Data Center Home PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal, Nuclear,DecadeYearby the(Dollars1.840YearDecadeThousandDecade

  4. South 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: Alternative Fuels Data Center Home PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal, Nuclear,DecadeYearbyWithdrawals (MillionYear Jan Feb Mar Apr May Jun

  5. West Virginia 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 PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal,Demand Module of theCubicEstimation10,428 (Million20Decade Year-009,652

  6. 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.

    1995-12-01

    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.

  7. Biogas end-use in the European community

    SciTech Connect (OSTI)

    Constant, M.; Naveau, H.; Nyns, E.J. ); Ferrero, G.L.

    1989-01-01

    In Europe over the past few years the generation of biogas for energy and environmental purposes has been gaining in importance. Industrial wastewaters, cattle manure, sewage sludges, urban wastes, crop residues, algae and aquatic biomass are all typical of the materials being utilized. In contrast to the extensive inventory of biomethanation processes which has been carried out within the EEC, until recently a detailed, up-to-date investigation of the end-sues of biogas had not been undertaken. To supply the necessary information, the Commission of the European Communities and the Belgian Science Policy Office jointly entrusted a study to the Unit of Bioengineering at the Catholic University of Louvain, Belgium. This book is record of the study and has the following key features: it gives a broad overview of the ongoing use of biogas in Europe; it summarizes available data on storage, purification and engines using biogas; it draws several conclusions concerning the technical and economic viability of the processes; it discusses the problems of using biogas; and it outlines recommendations and future R and D and demonstration projects in the field.

  8. ficient thermal energy, leading to a different STP (27). Similar temperature-dependent be-

    E-Print Network [OSTI]

    Savrasov, Sergej Y.

    ficient thermal energy, leading to a different STP (27). Similar temperature-dependent be- havior a bottom-up paradigm for spintronics manufacturing. Different conjugated molecules and QDs should provide

  9. ,"U.S. Distillate Fuel Oil and Kerosene Sales by End Use"

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

    Distillate Fuel Oil and Kerosene Sales by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for"...

  10. Estimating home energy decision parameters for a hybrid energyYeconomy policy model

    E-Print Network [OSTI]

    , household energy demand, hybrid energy model, bottom-up energy model 1. Introduction: energy a variety of energyYeconomy models are available to forecast the effectiveness of energy and envi- ronmentEstimating home energy decision parameters for a hybrid energyYeconomy policy model Mark Jaccard

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

    SciTech Connect (OSTI)

    Zhou, Nan; Nishida, Masaru; Gao, Weijun

    2008-12-01

    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

    2010-09-01

    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. ,"South 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: Alternative Fuels Data Center Home PageMonthly","10/2015"4,"Ames City of",6,1,"Omaha Public PowerOECD/IEA - 2008Wellhead PriceConsumption by End Use" ,"ClickConsumption by End Use"

  14. ,"South 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: Alternative Fuels Data Center Home PageMonthly","10/2015"4,"Ames City of",6,1,"Omaha Public PowerOECD/IEA - 2008Wellhead PriceConsumption by End Use"Summary"Consumption by End Use"

  15. Inventory of China's Energy-Related CO2 Emissions in 2008

    E-Print Network [OSTI]

    Fridley, David

    2011-01-01

    Energy End-Use Sectors Full End-Use Sector Name Farming, Forestry, Animal Husbandry, Fishery & Water

  16. Wood stove use in the end-use load and consumer assessment program residential base sample

    SciTech Connect (OSTI)

    LeBaron, B.A.

    1988-11-01

    This report examines wood heating in the End-Use Load and Consumer Assessment Program (ELCAP) Residential Base Sample during the 1985/1986 heating season. The goals of this study were to assess the frequency of wood burning in homes having wood burning equipment and to estimate the quantity of electrical space heat displaced by it use. 15 refs., 18 figs., 6 tabs.

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

    SciTech Connect (OSTI)

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

    2009-06-01

    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.

  18. ,"Massachusetts 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 PageMonthly","10/2015"4,"Ames City of",6,1,"Omaha Public PowerOECD/IEA - 2008 © OECD/IEA - 2008LNGUndergroundDryAnnual",2014Consumption by End Use"

  19. ,"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: Alternative Fuels Data Center Home PageMonthly","10/2015"4,"Ames City of",6,1,"Omaha Public PowerOECD/IEA - 2008Wellhead Price (Dollars per Thousand Cubic Feet)"Consumption by End Use"

  20. ,"Rhode Island 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 PageMonthly","10/2015"4,"Ames City of",6,1,"Omaha Public PowerOECD/IEA - 2008Wellhead PriceConsumption by End Use" ,"Click worksheet name or tab at

  1. ,"West Virginia 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 PageMonthly","10/2015"4,"Ames City of",6,1,"Omaha Public PowerOECD/IEA -Annual",2014Proved Reserves, WetGas,Consumption by End Use" ,"Click

  2. ,"Colorado 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 PageMonthly","10/2015"4,"Ames City of",6,1,"Omaha Public PowerOECD/IEA - 2008 © OECD/IEA - 2008LNG Storage NetConsumption by End Use" ,"Click worksheet

  3. ,"Connecticut 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 PageMonthly","10/2015"4,"Ames City of",6,1,"Omaha Public PowerOECD/IEA - 2008 © OECD/IEA - 2008LNG Storage NetConsumptionConsumption by End Use"

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

    E-Print Network [OSTI]

    Konopacki, S.J.

    2010-01-01

    Annual Weather Statistics (HDH = Heating Degree Hours, C DH = Cooling Degree Hours, L E H = Latent Enthalpy Hours)

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

    E-Print Network [OSTI]

    Authors, Various

    2011-01-01

    D.C. : U.S. Agency Solid Waste Management. EnvironmentalCRRA California State Solid Waste Management Board 1977aBay Area Solid Waste Management Project - Sacramento,

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

    E-Print Network [OSTI]

    Authors, Various

    2011-01-01

    of Waste Landfilled and Landfill Closure Dates For The Loswaste landfilled and landfill closure dates the Los Angeles

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

    E-Print Network [OSTI]

    Authors, Various

    2011-01-01

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

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

    E-Print Network [OSTI]

    Konopacki, S.J.

    2010-01-01

    Dix Bvr Brg Bng~ Plk Bhn Lwd Iwn Sll Yma Bis Shn Hood EndBvr Brg Bng Plk Bhn HVAC Lwd Iwn SII Non-HVAC Yma Bis ShnGWh). Dix Bvr Brg Bng Plk Bhn Lwd Iwn Sll Y m a Bis Shn Hood

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

    E-Print Network [OSTI]

    McKone, Thomas E.

    2011-01-01

    Hanford Woodwaste Steam Turbine, Cfb Fresno Petroleum Coke,Woodwaste MSW Steam Turbine, Cfb Riverside Corona Landfill

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

    E-Print Network [OSTI]

    Schipper, Lee

    2013-01-01

    PJ Elec. , TI/h City Gas,PJ LPG,PJ Oil ,PJ Coal,PJ GERMANYPJ Nat .Gas,PJ City Gas,PJ LPG, PJ Oil ,PJ Coal,PJ 3B6g I IJapan). \\\\fe have separated LPG from oil totals in some

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

    E-Print Network [OSTI]

    McKone, Thomas E.

    2011-01-01

    impact assessment. In Life cycle assessment: Analysis by anRebitzer, G. (2004). Life cycle assessment Part 2: CurrentHealth Response in Life Cycle Assessment Using EDI0s and

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

    E-Print Network [OSTI]

    McKone, Thomas E.

    2011-01-01

    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

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

    E-Print Network [OSTI]

    McKone, Thomas E.

    2011-01-01

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

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

    E-Print Network [OSTI]

    McKone, Thomas E.

    2011-01-01

    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-

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

    E-Print Network [OSTI]

    McKone, Thomas E.

    2011-01-01

    Gas Natural Gas a) Urban power plants (continued) PLANTNAMELandfill Gas Landfill Guadalupe Power Plant WatsonvilleGas Natural Gas b) rural power plants (continued) PLANTNAME

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

    E-Print Network [OSTI]

    McKone, Thomas E.

    2011-01-01

    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

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

    E-Print Network [OSTI]

    Schipper, Lee

    2013-01-01

    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.

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

    E-Print Network [OSTI]

    McKone, Thomas E.

    2011-01-01

    Location: State/County Fuel Type: Coal, natural a oil WTELocation: State/County Fuel Type: Coal, natural gas, oil,Location: State/County Fuel Type: Coal, natural gas, oil,

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

    E-Print Network [OSTI]

    Konopacki, S.J.

    2010-01-01

    Maintenance Hospital Residential Warehouse Miscellaneous Non-Building Utility PumpMaintenance Hospital Residential Warehouse Miscellaneous Non-Building Utility Pump

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

    E-Print Network [OSTI]

    McKone, Thomas E.

    2011-01-01

    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

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

    E-Print Network [OSTI]

    McKone, Thomas E.

    2011-01-01

    Gas Turbine Gas Turbine Combined Cycle Steam Turbine CogenEastridge Sunrise Ii Combined Cycle Expansion Midway-Sunset0.33-0.39 a CHP/cogen/ Combined cycle O.4 b c 0.58-0.84 d

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

    E-Print Network [OSTI]

    Konopacki, S.J.

    2010-01-01

    Bragg Fort Benning Fort Polk Fort Benjamin Harrison FortEstimated H V A C EUIs at Fort Polk Table 5-6. Annual DOE-2Electricity Use at Fort Polk [GWh/yr] Table 5-18. Annual E D

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

    E-Print Network [OSTI]

    Schipper, Lee

    2013-01-01

    ELECTRICITY PRICES Nominal and Real Prices ( UScents/kWh) YEAR ! *CANADA* *JAPAN* *W GERMANY*electricity are considerably lower than these averages, particularly in W Germany and UKe All price

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

    E-Print Network [OSTI]

    McKone, Thomas E.

    2011-01-01

    Efficiency Improvements at Coal-Fired Power Plants." Locatedcapacity comes from coal-fired power plants (including coalCalifornia is the Mohave coal-fired power plants located in

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

    E-Print Network [OSTI]

    McKone, Thomas E.

    2011-01-01

    primarily the Mohave coal power plant). By comparison, LevyImprovements at Coal-Fired Power Plants." Located at:capacity comes from coal-fired power plants (including coal

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

    E-Print Network [OSTI]

    McKone, Thomas E.

    2011-01-01

    Reciprocating Cogen Engine Gas Turbine Gas Turbine Combinedturbine Steam turbine Reciprocating engines WTE Digester gasturbine Steam turbine Reciprocating engine WTE Digester gas

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

    E-Print Network [OSTI]

    McKone, Thomas E.

    2011-01-01

    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

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

    E-Print Network [OSTI]

    McKone, Thomas E.

    2011-01-01

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

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

    E-Print Network [OSTI]

    Authors, Various

    2011-01-01

    Housekeeping, New Plant Construction, Waste Heat Recovery,Construction were arrayed against subsector characteristics for the steel and chemical subsectors; attributes associated with Waste

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

    E-Print Network [OSTI]

    McKone, Thomas E.

    2011-01-01

    of coal- powered cogeneration plants are not provided by theheat and power Cogen: cogeneration plant CTD: characteristiccycle, cogeneration cycles and combined cycle plants)

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

    E-Print Network [OSTI]

    McKone, Thomas E.

    2011-01-01

    impact assessment. In Life cycle assessment: Analysis by anRebitzer, G. (2004). Life cycle assessment Part 2: CurrentEnvironmental management-life cycle assessment- principles

  12. "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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page|Monthly","10/2015","1/15/1981"0. Total Consumption of LPG, Distillate6. Total1.6.

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

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet) Wyoming963 1.969Central RegionReportingElectricity Glossary › FAQS ›192

  14. 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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet) Wyoming963Residential Consumers (Number of33 2,297 809 245 1550473 Number

  15. 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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet) Wyoming963Residential Consumers (Number of33 2,297 809 245 1550473 Number Next

  16. 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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet) Wyoming963Residential Consumers (Number of33 2,297 809 245 1550473 Number Next5

  17. 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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet) Wyoming963Residential Consumers (Number of33 2,297 809 245 1550473 Number Next56

  18. 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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet) Wyoming963Residential2, 2014 MEMORANDUM FOR: JOHNThousand

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

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet)Decade Year-0ProvedDecade2,948 2,724per ThousandLease0 0and164 167 200Tables

  20. Service Report Enwgy Information Administration Office of Energy Markets and 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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet) Wyoming963 1.969 1.979 1.988 1.996 2.003 1990-2016November 2000

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

    SciTech Connect (OSTI)

    Jones, E.; Eto, J.

    1997-09-01

    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.

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

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

    found across many different species of bacteria possessing TTSSs. Most importantly, the self-association ("multimerization") of proteins in this family has been shown to be one...

  3. America's Bottom-Up Climate Change Mitigation Policy

    E-Print Network [OSTI]

    Lutsey, Nicholas P.; Sperling, Dan

    2008-01-01

    and developing emissions trading mechanisms to connect andand development of emissions trading or cap-and-tradesector market-based emissions trading system in the Western

  4. Top down or bottom up? Volcanic architecture, climate,

    E-Print Network [OSTI]

    Geist, Dennis

    .5 Ma) Kauai (4.5 Ma) Hawaii (images from Porder & Vitousek) (images by A. Jefferson) #12;Volcano Island Hawaii Cascades Easter Island Azores Madeira Canary Galapagos Samoa Cape Verde #12;Time 0 >5 Ma "Conventional conceptual model" because of early work in Hawaii Modified from Gingerich and Oki 2000 (Oahu

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

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

    The injected proteins, by mimicking host-cell mechanisms, can then subvert normal cellular function. The type III secretion system (TTSS) is a sophisticated protein complex...

  6. America's Bottom-Up Climate Change Mitigation Policy

    E-Print Network [OSTI]

    Lutsey, Nicholas P.; Sperling, Dan

    2008-01-01

    large conventional hydroelectric power, municipal solidconventional large hydroelectric power). To quantify theby states that large hydroelectric is not counted toward the

  7. America's Bottom-Up Climate Change Mitigation Policy

    E-Print Network [OSTI]

    Lutsey, Nicholas P.; Sperling, Dan

    2008-01-01

    large conventional hydroelectric power, municipal solidconventional large hydroelectric power). To quantify thelarge conventional hydroelectric power is not included (this

  8. 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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 OutreachProductswsicloudwsiclouddenDVA N C E D B L O O DBiomass and Biofuels Biomass andPostdoctoralYourAssembly

  9. 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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 OutreachProductswsicloudwsiclouddenDVA N C E D B L O O DBiomass and Biofuels Biomass

  10. 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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 OutreachProductswsicloudwsiclouddenDVA N C E D B L O O DBiomass and Biofuels BiomassAssembly of a Molecular

  11. 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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 OutreachProductswsicloudwsiclouddenDVA N C E D B L O O DBiomass and Biofuels BiomassAssembly of a

  12. 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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room News Publications TraditionalWithAntiferromagneticInexpensive 2- toArthurAshley CadbyAssembly

  13. Hierarchical Three-Dimensional Microbattery Electrodes Combining Bottom-Up

    Office of Scientific and Technical Information (OSTI)

    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 Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of NaturalDukeWakefieldSulfate Reducing(Journal Article)lasers (Journal Article) |different|

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

    E-Print Network [OSTI]

    Tiedemann, Kenneth Mr.

    2013-01-01

    Summer Study on Energy Efficiency in Buildings, Washington ,Summer Study on Energy Efficiency in Buildings, Washington,

  15. 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

    1982-01-01

    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.

  16. 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.

  17. Target Allocation Methodology for China's Provinces: Energy Intensity in the 12th FIve-Year Plan

    SciTech Connect (OSTI)

    Ohshita, Stephanie; Price, Lynn

    2011-03-21

    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.

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

    E-Print Network [OSTI]

    Zhou, Nan

    2010-01-01

    Energy Intensity by End-use Urban enduse intensity Spaceenergy efficiency improvement. 7 of 17 Table 3 End Use Saturations and Intensities Saturation, % Urban Space

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

    E-Print Network [OSTI]

    Zhou, Nan

    2010-01-01

    energy efficiency improvement. 7 of 17 Table 3 End Use Saturations and Intensities Saturation, % Urban

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

    E-Print Network [OSTI]

    Zhou, Nan

    2010-01-01

    Energy Intensity by End-use Assumptions Urban enduse intensity SpaceEnergy Consumption by Fuel Table 3 End Use Saturations and Intensities Saturation, % Urban Space

  1. Evaluating Energy Efficiency Policies with Energy-Economy Models

    SciTech Connect (OSTI)

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

    2010-08-01

    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.

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

    E-Print Network [OSTI]

    Tiedemann, Kenneth Mr.

    2013-01-01

    Fowlie. 2007. Demand-Side Management and Energy Efficiencyand building shells. Demand side management programs have

  3. California Baseline Energy Demands to 2050 for Advanced Energy Pathways

    E-Print Network [OSTI]

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

    2008-01-01

    End use energy consumption per square-foot and floorspaceof floorspace and energy consumption per square-foot, for 10

  4. Analyzing California's GHG Reduction Paths using CA-TIMES Energy System Model

    E-Print Network [OSTI]

    California at Davis, University of

    Analyzing California's GHG Reduction Paths using CA-TIMES Energy System Model Christopher Yang@ucdavis.edu NextSTEPS (Sustainable Transportation Energy Pathways) #12;CA-TIMES Model Overview · CA-TIMES is a bottom-up, linear optimization model of California's energy sectors ­ Technology and resources details

  5. End-use electrification in the residential sector : a general equilibrium analysis of technology advancements

    E-Print Network [OSTI]

    Madan, Tanvir Singh

    2012-01-01

    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 ...

  6. Table 3. Top five retailers of electricity, with end use sectors...

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

    Energy LLC - (MT)","Investor-Owned",5964495,2409714,3095129,459652,0 2,"PPL EnergyPlus LLC","Investor-Owned",2219237,0,125451,2093786,0 3,"Flathead Electric Coop...

  7. The use of negotiated agreements to improve efficiency of end-use appliances: First results from the European experience

    SciTech Connect (OSTI)

    Bertoldi, P.; Bowie, R.; Hagen, L.

    1998-07-01

    The European Union is pursuing measures to improve end-use equipment efficiency through a variety of policy instruments, in particular for domestic appliances. One of the most effective methods to achieve market transformation is through minimum efficiency performance standards (MEPS). However, after the difficulties and controversy following the adoption of legislation for MEPS for domestic refrigerators/freezers, a new policy instrument, i.e. negotiated agreements by manufacturers, has been investigated and tested for two type of appliances: domestic washing machines and TVs and VCRs. Based on the positive experience of the above two agreements, other products (e.g. dryers, dishwasher, electric water heaters, etc.) will be the subject of future negotiated agreements. Based on the results of the two negotiated agreements, this paper describes the energy efficiency potential, the procedures, and the advantages and disadvantages of negotiated agreements compared to legislated mandatory for MEPS, as developed in the European context. The paper concludes that negotiated agreements are a viable policy option, which allow flexibility in the implementation of the efficiency targets and therefore the adoption of cost-effective solutions for manufacturers. In addition, negotiated agreements can be implemented more quickly compared to mandatory MEPS and they allow a closer monitoring of the results. The main question asked in the paper is whether the negotiated agreements can deliver the results in the long term compared to what could be achieved through legislation. The European experience indicates that this instrument can deliver the results and that it offer a number of advantages compared to MEPS.

  8. Energy Use in China: Sectoral Trends and Future Outlook

    E-Print Network [OSTI]

    2008-01-01

    Energy Intensity by End-use Assumptions Urban enduse intensity Spaceenergy efficiency improvement. Table 7 End Use Saturations and Intensities Saturation, % Urban Rural Space

  9. Table 3. Top five retailers of electricity, with end use sectors...

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

    Ohio" "megawatthours" ,"Entity","Type of provider","All sectors","Residential","Commercial","Industrial","Transportation" 1,"First Energy Solutions Corp.","Investor-owned",49437270...

  10. Table 3. Top five retailers of electricity, with end use sectors...

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

    Carolina" "megawatthours" ,"Entity","Type of provider","All sectors","Residential","Commercial","Industrial","Transportation" 1,"Duke Energy Carolinas, LLC","Investor-owned",553018...

  11. Table 3. Top five retailers of electricity, with end use sectors...

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

    NewEnergy, Inc","Investor-owned",4346122,183554,3460337,680584,21647 " ","Total sales, top five providers",,42520476,22426188,15836198,4089313,168777 " ","Percent of total state...

  12. Table 3. Top five retailers of electricity, with end use sectors...

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

    5,"Midwest Energy Inc","Cooperative",1465542,320197,365898,779447,0 " ","Total sales, top five providers",,29387627,10230485,12148409,7008733,0 " ","Percent of total state...

  13. Table 3. Top five retailers of electricity, with end use sectors...

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

    5,"Lower Valley Energy Inc","Cooperative",669848,398716,236467,34665,0 " ","Total sales, top five providers",,15008067,2126255,3300520,9581292,0 " ","Percent of total state...

  14. Table 3. Top five retailers of electricity, with end use sectors...

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

    Energy Northeast LLC","Investor-owned",433689,2146,862,109190,321491 " ","Total sales, top five providers",,9211781,1800472,6711814,378004,321491 " ","Percent of total state...

  15. Table 3. Top five retailers of electricity, with end use sectors...

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

    4,"Connexus Energy","Cooperative",2001218,1181107,682415,137696,0 5,"Total sales, top five providers","Cooperative",1859499,931254,50650,877595,0 " ","Percent of total state...

  16. Table 3. Top five retailers of electricity, with end use sectors...

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

    NewEnergy, Inc","Investor-owned",4695050,0,3692011,857925,145114 5,"Total sales, top five providers","Investor-owned",3689844,2775192,664586,250066,0 " ","Percent of total...

  17. Table 3. Top five retailers of electricity, with end use sectors...

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

    Energy Services, Inc.","Investor-owned",11441899,6021716,5420183,0,0 5,"Total sales, top five providers","Investor-owned",9958632,5474417,2804396,1666670,13149 " ","Percent of...

  18. Table 3. Top five retailers of electricity, with end use sectors...

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

    NewEnergy, Inc","Investor-owned",587269,0,443918,143351,0 5,"Total sales, top five providers","Investor-owned",548868,0,509045,39823,0 " ","Percent of total state...

  19. Table 3. Top five retailers of electricity, with end use sectors...

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

    Electric Utilities Corp","Investor-owned",9154327,7469000,1587178,98149,0 5,"PPL EnergyPlus LLC","Investor-owned",9048664,1235909,3987959,3824796,0 " ","Total sales, top five...

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

    E-Print Network [OSTI]

    Cornwall, B.

    2011-01-01

    2 reveals that the primary sources of information for the "are the primary sources of information, transit operatorssource of information on "where to go" (Natonal Advertising Corporation 1972:8). PRIMARY

  1. 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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page| Open Energy Informationmonthly gasoline price toStocks 2009CubicAnalysisYear

  2. 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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page| Open Energy Informationmonthly gasoline price toStocks 2009CubicAnalysisYearArkansas"

  3. Refining and end use study of coal liquids. Quarterly report, July-- September 1995

    SciTech Connect (OSTI)

    NONE

    1995-12-31

    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.

  4. Refining and end use study of coal liquids. Quarterly report, April--June 1996

    SciTech Connect (OSTI)

    NONE

    1997-12-31

    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 U.S. 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. This 47-month study, with an approved budget of $4.4 million dollars, is being performed under DOE Contract Number DE-AC22-93PC91029. 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.

  5. ,"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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page| Open Energy Informationmonthly gasoline price to fall to $3.43U.S.longec 188 U.S.1Sales

  6. ,"Nevada 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 PageMonthly","10/2015"4,"Ames City of",6,1,"Omaha Public PowerOECD/IEA - 2008 © OECD/IEA -LiquidsAnnual",2014LNG Storageb. Historical Net Energy

  7. China Energy Databook - Rev. 4

    E-Print Network [OSTI]

    Sinton Editor, J.E.

    2010-01-01

    Consumption: Commercial and Biomass Energy, 1979 and 1987;Consumption: Commercial and Biomass Energy Energy IntensityEnd Use, Commercial and Biomass Energy Shares of Total

  8. Renewable Electricity Futures Study. Volume 3. End-Use Electricity Demand

    SciTech Connect (OSTI)

    Hostick, Donna; Belzer, David B.; Hadley, Stanton W.; Markel, Tony; Marnay, Chris; Kintner-Meyer, Michael

    2012-06-15

    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). Learn more at the RE Futures website. http://www.nrel.gov/analysis/re_futures/

  9. 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.

    2012-06-01

    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).

  10. 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.

  11. National Energy Efficiency Evaluation, Measurement and Verification (EM&V) Standard: Scoping Study of Issues and Implementation Requirements

    E-Print Network [OSTI]

    Schiller, Steven R.

    2011-01-01

    on Energy End-Use Efficiency and Energy Services (EMEES)on Energy End-Use Efficiency and Energy Services (EMEES)types of energy efficiency and energy conservation measures

  12. Target Allocation Methodology for China's Provinces: Energy Intensity in the 12th FIve-Year Plan

    E-Print Network [OSTI]

    Ohshita, Stephanie

    2011-01-01

    Targets Residential Energy Other Energy Energy saving EnergyEnergy saving Energy growth rates goals based on growthEcon Trend Analysis & Equal Savings Energy End- Use Sectors

  13. 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

    2007-01-01

    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

  14. Level: National Data; Row: End Uses within NAICS Codes; 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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet) Wyoming963Residential Consumers (Number of33 2,297 809 245 1550

  15. 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.

    2008-05-13

    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.

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

    E-Print Network [OSTI]

    Koomey, Jonathan G.

    2010-01-01

    data. Residential primary energy use is expected to growmat the overall primary energy intensity per household ofby Stock Equipment (Primary Energy, Trillion Btu) Table B .

  17. Development of an End-Use Sector-Based Low-Carbon Indicator System for Cities in China

    E-Print Network [OSTI]

    Price, Lynn

    2014-01-01

    Summer Study on Energy Efficiency in Buildings Proceedings”Summer Study on Energy Efficiency in Buildings Proceedings”Study on Energy Efficiency in Buildings, held in Asilomar

  18. 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.

  19. 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.

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

    E-Print Network [OSTI]

    Koomey, Jonathan G.

    2010-01-01

    US DOE. 1995a. Annual Energy Outlook 1995, with ProjectionsELA) 1995 Annual Energy Outlook (AEO); 1990 Residentialof Energy's Annual Energy Outlook ( US DOE 1995a). A l l

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

    E-Print Network [OSTI]

    Koomey, Jonathan G.

    2010-01-01

    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

  2. Assessment of China's Energy-Saving and Emission-Reduction Accomplishments and Opportunities During the 11th Five Year Plan

    E-Print Network [OSTI]

    Levine, Mark D.

    2010-01-01

    National Action Plan for Energy Efficiency: Model Energy-Efficiency Programregular national surveys of energy end-use to assess programregular national surveys of energy end-use to assess program

  3. Commercial Buildings Energy Consumption and Expenditures 1992

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

    Distribution Category UC-950 Commercial Buildings Energy Consumption and Expenditures 1992 April 1995 Energy Information Adminstration Office of Energy Markets and End Use U.S....

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

    E-Print Network [OSTI]

    Zhou, Nan

    2010-01-01

    energy demand. It assesses the current energy situation with consideration of end use, intensity, and efficiency etc, and forecastenergy demand. It assesses the current energy situation with consideration of end use, intensity, and efficiency etc, and forecast

  5. Enduse Global Emissions Mitigation Scenarios (EGEMS): A New Generation of Energy Efficiency Policy Planning Models

    E-Print Network [OSTI]

    McNeil, Michael A.

    2010-01-01

    2007). International Energy Outlook 2007, Energy InformationJ. Sathaye (2009). India Energy Outlook: End Use Demand inEnergy’s International Energy Outlook 2007 (USEIA, 2007). It

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

    E-Print Network [OSTI]

    Kammen, Daniel M.

    resources like Gabon, Nigeria, and Angola, biomass constitutes the majority of national energy consumption-SAHARAN AFRICA Robert Bailis1 , David Pennise2 , Majid Ezzati3 , Daniel M. Kammen1,4 , Evans Kituyi5 1 Energy & African Center for Technology Studies, Nairobi, Kenya ABSTRACT: Household energy in sub-Saharan Africa

  7. Understanding Manufacturing Energy and Carbon Footprints, October 2012

    Broader source: Energy.gov [DOE]

    The Manufacturing Energy and Carbon Footprints provide a mapping of energy use and carbon emissions from energy supply to end use

  8. Energy Data Sourcebook for the U.S. Residential Sector

    E-Print Network [OSTI]

    Wenzel, T.P.

    2010-01-01

    1987b). 2.1. Unit Energy Consumptions Data on end-use unitresidential sector energy consumption data, and typicallyNational Interim Energy Consumption Survey Data, prepared

  9. Energy Intensity Changes by Sector, 1985-2011 - Alternative Measures...

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

    to different definitions of energy use. Source energy attributes all the energy used for electricity generation and transmission to the specific end-use sector, addition to the...

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

    E-Print Network [OSTI]

    Fridley, David G.

    2008-01-01

    Table 12 Projected Primary Energy Savings between ReferenceEnergy (Primary Energy) .18 Figure 6 Primary Energy Consumption by End-Use in

  11. Assessment of Energy Use in Multibuilding Facilities

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

    CBECS asked for district steam or district hot water piped into the building. Source: Energy Information Administration, Office of Energy Markets and End Use, 1979, 1983, 1986 and...

  12. Buildings and Energy in the 1980s

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

    Air Conditioning: See Energy End Use, Cooling. Authorization Form: A form signed by the respondent authorizing energy supplier companies that serve the building to release...

  13. Healthcare Energy: Spotlight on Medical Equipment

    Broader source: Energy.gov [DOE]

    The Building Technologies Office conducted a healthcare energy end-use monitoring project for two sites. Read details about large medical imaging equipment energy results.

  14. Healthcare Energy: Spotlight on Chiller Plants

    Broader source: Energy.gov [DOE]

    The Building Technologies Office conducted a healthcare energy end-use monitoring project for two sites. Read details about the chiller plant energy results.

  15. Review of Evaluation, Measurement and Verification Approaches Used to Estimate the Load Impacts and Effectiveness of Energy Efficiency Programs

    E-Print Network [OSTI]

    Messenger, Mike

    2010-01-01

    Consortium for Energy Efficiency Energy efficiency (end-use,Weatherization, and Energy Efficiency and Conservation BlockInstitute for Energy Efficiency and the California Public

  16. High-Energy Astrophysics and Cosmology

    E-Print Network [OSTI]

    John Ellis

    2002-10-26

    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.

  17. Refining and end use study of coal liquids. Second quarter 1995 technical progress report, April--June 1995

    SciTech Connect (OSTI)

    NONE

    1995-12-01

    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 U.S. 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. This 47-month study, with an approved budget of $4.4 million dollars, is being performed under DOE Contract Number DE-AC22-93PC91029. 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.

  18. 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.

  19. 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.

    2008-03-01

    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.

  20. China Energy Databook - Rev. 4

    E-Print Network [OSTI]

    Sinton Editor, J.E.

    2010-01-01

    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

  1. Refining and end use study of coal liquids. Sixth quarterly technical progress report, December 19, 1994--March 26, 1995

    SciTech Connect (OSTI)

    NONE

    1995-08-01

    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 U.S. 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. This 47-month study, with an approved budget of $4.4 million dollars, is being performed under DOE Contract Number DE-AC22-93PC91029. 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.

  2. Estimates of U.S. Commercial Building Electricity Intensity Trends: Issues Related to End-Use and Supply Surveys

    SciTech Connect (OSTI)

    Belzer, David B.

    2004-09-04

    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.

  3. Bottom-up, decision support system development : a wetlandsalinity management application in California's San Joaquin Valley

    SciTech Connect (OSTI)

    Quinn, Nigel W.T.

    2006-05-10

    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.

  4. A hierarchical bottom-up, equation-based optimization design methodology

    E-Print Network [OSTI]

    Sanchez, William R

    2007-01-01

    We have implemented a segment of an RF transmitter signal chain in discrete components using bipolar transistors. We formulated both a broadband amplifier and mixer as mathematical programs (MP) and extracted Pareto-optimal ...

  5. Stress corrosion cracking of steel Stressed-Out Metals: Predicting their Response from the Bottom Up

    E-Print Network [OSTI]

    Simons, Jack

    Stress corrosion cracking of steel Stressed-Out Metals: Predicting their Response from the Bottom;Shocked Iron Ground state bcc undergoes a martensitic phase transformation to hcp at ~13 GPa

  6. Organizing and financing interstellar space projects - A bottom-up approach

    E-Print Network [OSTI]

    Ceyssens, Frederik; Wouters, Kristof; Ceyssens, Pieter-Jan; Wen, Lianggong

    2011-01-01

    The development and deployment of interstellar missions will without doubt require orders of magnitude more resources than needed for current or past megaprojects (Apollo, Iter, LHC,...). Question is how enough resources for such gigaprojects can be found. In this contribution different scenarios will be explored assuming limited, moderate economic growth throughout the next centuries, i.e. without human population and productivity continuing to grow exponentially, and without extreme events such as economic collapse or singularity. In such a world, which is not unlike the current situation, gigascale space projects face a combination of inhibiting factors: the enormous cost threshold, the need for risky and costly development of often quite application specific technology, the relatively little benefit with respect to the costs for the sponsors, the time span of at least a few generations and the absence of a sense of urgency. It will be argued that the best chance of getting an interstellar project started ...

  7. Bottom-up soft-lithographic fabrication of three-dimensional multilayer polymer integrated optical microdevices

    E-Print Network [OSTI]

    Huang, Yanyi

    is limited by the size of the devices. Stacking PLCs to make three-dimensional (3D) structures will effi- ciently increase the density of photonic circuits. Several polymer 3D integrated optical devices have been alternate fabrication methods to generate 3D multilayer structures.10,11 In this letter, we describe

  8. 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.

    2013-01-01

    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...

  9. 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

  10. ORIGINAL ARTICLE Bottom-up influences of voice continuity in focusing selective

    E-Print Network [OSTI]

    Shinn-Cunningham, Barbara

    00426-014-0555-7) contains supplementary material, which is available to authorized users. S. Bressler Á Psychological Research DOI 10.1007/s00426-014-0555-7 #12;stream is attended is it segregated from a sound

  11. Bottom-up model of adsorption and transport in multiscale porous media

    E-Print Network [OSTI]

    Ulm, Franz-Josef

    We develop a model of transport in multiscale porous media which accounts for adsorption in the different porosity scales. This model employs statistical mechanics to upscale molecular simulation and describe adsorption ...

  12. From atoms to cities : A bottom-up analysis of infrastructure materials and systems

    E-Print Network [OSTI]

    Abdolhosseini Qomi, Mohammad Javad

    2015-01-01

    Civil infrastructure is and continues to be the backbone of our society to meet our needs in housing, transportation, water and electricity supply, and so on. However, its functions are recently revisited in response to ...

  13. BUCS -A Bottom-Up Cache Structure for Networked Storage Servers Ming Zhang and Qing Yang

    E-Print Network [OSTI]

    Yang, Qing "Ken"

    interconnects such as PCI bus have not kept pace with these improvements. As a result, it has become the major of system interconnects by replacing PCI with PCI-X, PCI Express, or InfiniBand [1]. The Infini

  14. Peace Corps Volunteers and the Boundaries of Bottom-up Development

    E-Print Network [OSTI]

    Schuckman, Hugh Erik

    2012-01-01

    the level of practical classroom management skills in theage-differentiated classroom management, both skill sets areplanning and varied classroom management techniques. But

  15. 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.

    2014-09-16

    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...

  16. Peace Corps Volunteers and the Boundaries of Bottom-up Development

    E-Print Network [OSTI]

    Schuckman, Hugh Erik

    2012-01-01

    to have the most basic training modules such as instructionswelcome. Having basic training modules pre- packaged wouldmodules were already completed, however, the Peace Corps training

  17. BottomUp Propositionalization Stefan Kramer 1 and Eibe Frank 2

    E-Print Network [OSTI]

    Frank, Eibe

    ­ gorithms. This transformation requires the construction of features that capture relational properties. An example of a fragment would be 'o­s­c', meaning ``an oxygen atom with a single bond to a sulfur atom

  18. [Re]constructing Finite Flavour Groups: Horizontal Symmetry Scans from the Bottom-Up

    E-Print Network [OSTI]

    Jim Talbert

    2015-01-07

    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.

  19. Peace Corps Volunteers and the Boundaries of Bottom-up Development

    E-Print Network [OSTI]

    Schuckman, Hugh Erik

    2012-01-01

    and the Us Peace Corps." [Pamphlet] (1989). ———. "Looking atarchival resources such as pamphlets, reports, internalwild. They brought now pamphlets, brochures, movies, or any

  20. 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 Data Center Home Page on Delicious Rank EERE:Financing ToolInternationalReportOffice | DepartmentVery1, in:QuarterlyA SolarAA View fromsynthesis

  1. Bottoms Up. [report on the Defense Department] (Journal Article) | SciTech

    Office of Scientific and Technical Information (OSTI)

    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 Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of NaturalDukeWakefieldSulfate Reducing Bacteria (Technical Report) | SciTechReport)(TechnicalArticle) | SciTech

  2. Renewable Energy and Efficiency Modeling Analysis Partnership: An Analysis of How Different Energy Models Addressed a Common High Renewable Energy Penetration Scenario in 2025

    E-Print Network [OSTI]

    Blair, N.

    2010-01-01

    system benefits charges for renewable energy Table 2.benefit charges for renewables RPS Policy Assumptions • Renewable Energybenefit) gy y • Characteristics of the renewable and end-use energy

  3. Opportunities for Energy Efficiency and Demand Response in the California Cement Industry

    E-Print Network [OSTI]

    Olsen, Daniel

    2012-01-01

    Opportunities for Energy  Efficiency and Demand Response in Agricultural/Water End?Use Energy Efficiency Program.    i 1   4.0   Energy Efficiency and Demand Response 

  4. ResPoNSe: modeling the wide variability of residential energy consumption.

    E-Print Network [OSTI]

    Peffer, Therese; Burke, William; Auslander, David

    2010-01-01

    affect appliance energy consumption. For example, differentStates, 2005 Residential Energy Consumption Survey: HousingModeling of End-Use Energy Consumption in the Residential

  5. Quantifying the Effect of the Principal-Agent Problem on US Residential Energy Use

    E-Print Network [OSTI]

    Murtishaw, Scott; Sathaye, Jayant

    2006-01-01

    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

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

    E-Print Network [OSTI]

    Fridley, David G.

    2008-01-01

    from the Long-Range Energy Alternatives Planning (LEAP) end-using the Long-Range Energy Alternatives Planning (LEAP)Energy Modeling. 10 Reference and Alternative

  7. 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

    2011-02-04

    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).

  8. 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

  9. Global Potential of Energy Efficiency Standards and Labeling Programs

    E-Print Network [OSTI]

    McNeil, Michael A

    2008-01-01

    characterize global energy consumption and its consequencesconsumption for specific end-uses. Energy demand in the commercial sector represents 11% of total global

  10. Linking Continuous Energy Management and Open Automated Demand Response

    E-Print Network [OSTI]

    Piette, Mary Ann

    2009-01-01

    end-uses and whole building energy performance metrics. Theperformance metrics associated with each of the domains. For example, whole-building energy

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

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

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

  12. 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

    2007-10-04

    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.

  13. Opportunities for Energy Efficiency and Open Automated Demand Response in Wastewater Treatment Facilities in California -- Phase I Report

    E-Print Network [OSTI]

    Lekov, Alex

    2010-01-01

    Processing Industry Energy Efficiency Initiative, CaliforniaK. (2004). Bringing Energy Efficiency to the Water andAgricultural/Water End-Use Energy Efficiency Program. Lyco

  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

    2010-01-01

    Fuller, J. (2003). Energy Efficient Alternative for theAgricultural/Water End-Use Energy Efficiency Program. LycoWastewater Industry Energy Efficiency: A Research Roadmap,

  15. Evolution of the U.S. Energy Service Company Industry: Market Size and Project Performance from 1990-2008

    E-Print Network [OSTI]

    Goldman, Charles A.

    2013-01-01

    and end-use sector energy prices to projects using marketproject costs and energy prices across time to account forinvolve escalating future energy prices. Because practices

  16. U.S. Renewable Energy Policy and Industry

    SciTech Connect (OSTI)

    Zhou, Ella

    2015-10-01

    From 2005 to 2014, wind and solar power generation has seen an almost tenfold increase in the United States. Such rapid development is the result of a variety of federal and state, top-down and bottom-up drivers, as well as the macro-environment of cost-reduction globally and early adoption in Europe. This presentation, prepared for a meeting with China National Renewable Energy Center and National Energy Administration (of China), is a summary of some of the key drivers for renewable energy deployment in the United States.

  17. 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

    2004-08-29

    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

  18. China Energy Group - Sustainable Growth Through Energy Efficiency

    E-Print Network [OSTI]

    2006-01-01

    end-use model of China’s energy economy for 2020. Assessedto meet its goal of reducing energy intensity by 20% in fiveCommission (BDRC) Beijing Energy Efficiency Center (BECon)

  19. China Energy and Emissions Paths to 2030

    SciTech Connect (OSTI)

    Fridley, David; Zheng, Nina; Zhou, Nan; Ke, Jing; Hasanbeigi, Ali; Morrow, Bill; Price, Lynn

    2011-01-14

    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.

  20. 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.