National Library of Energy BETA

Sample records for xx xx household

  1. DOE O XXX.X DRAFT XX-XX-XX

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

    DOE O XXX.X DRAFT XX-XX-XX 4 DOE O XXX.X DRAFT XX-XX-XX DOE O XXX.X 3 DRAFT XX-XX-XX DOE O XXX.X Appendix A DRAFT XX-XX-XX A- 1 (and A-2) DOE O XXX.X Attachment 1 DRAFT XX-XX-XX Page 1 (and Page 2) Appendix E DOE O 251.1C E- 6 1-15-09 DOE O XXX.X Attachment 2 DRAFT XX-XX-XX Page 1 (and Page 2) draftDOE O XXX.XdraftDOE O XXX.Xu.s. Department of EnergyORDER draft DOE O XXX.X draft DOE O XXX.X Washington, DC Approved: XX-XX-XXXX SUBJECT: title PURPOSE. (Define the program or subject matter and its

  2. CAP XX Pty Ltd | Open Energy Information

    Open Energy Info (EERE)

    Zip: NSW 2066 Product: Australia-based designer and manufacturer of high power density supercapacitors. References: CAP-XX Pty Ltd1 This article is a stub. You can help...

  3. WEATHERIZATION PROGRAM NOTICE 16-XX EFFECTIVE DATE:

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

    WEATHERIZATION PROGRAM NOTICE 16-XX EFFECTIVE DATE: SUBJECT: WEATHERIZATION OF RENTAL UNITS - Applicable to single family and multifamily dwellings PURPOSE: To provide Grantees with updated guidance on weatherizing rental units in the Weatherization Assistance Program (WAP). DOE has answered specific questions from Grantees related to the weatherization of rental units, whether single family building or multifamily dwellings, over a number of years. However, the responses to these questions have

  4. RELAP5-3D V. 4.X.X

    Energy Science and Technology Software Center (OSTI)

    000191MLTPL01 NON-NRC FUNDED RELAP5-3D VERSION 4.x.x SOFTWARE REACTOR EXCURSION AND LEAK ANALYSIS PACKAGE - THREE DIMENSIONAL

  5. WEATHERIZATION PROGRAM NOTICE 16-XX EFFECTIVE DATE: SUBJECT: MULTIFAMILY WEATHERIZATION

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

    6-XX EFFECTIVE DATE: SUBJECT: MULTIFAMILY WEATHERIZATION PURPOSE: To provide Grantees with consolidated guidance on previously issued Weatherization Program Notices (WPNs) on weatherizing multifamily buildings in the Weatherization Assistance Program (WAP). This supersedes WPN 10-7 and WPN 11-9 SCOPE: The provisions of this guidance apply to Grantees applying for financial assistance under the Department of Energy (DOE) WAP. LEGAL AUTHORITY: Title IV, Energy Conservation and Production Act, as

  6. DOE G 441.1-XX Control and Release of Property with Residual...

    Office of Environmental Management (EM)

    April 4, 2002 FROM: STEPHEN M. SMITH, DEPUTY DIRECTOR OFFICE OF CORPORATE SOLUTIONS, ME-80 TO: DIRECTIVES POINTS OF CONTACT SUBJECT: DRAFT DOE G 441.1-XX, CONTROL AND RELEASE OF ...

  7. Long-distance entanglement and quantum teleportation in XX spin chains

    SciTech Connect (OSTI)

    Campos Venuti, L.; Giampaolo, S. M.; Illuminati, F.; Zanardi, P.

    2007-11-15

    Isotropic XX models of one-dimensional spin-1/2 chains are investigated with the aim to elucidate the formal structure and the physical properties that allow these systems to act as channels for long-distance, high-fidelity quantum teleportation. We introduce two types of models: (i) open, dimerized XX chains, and (ii) open XX chains with small end bonds. For both models we obtain the exact expressions for the end-to-end correlations and the scaling of the energy gap with the length of the chain. We determine the end-to-end concurrence and show that model (i) supports true long-distance entanglement at zero temperature, while model (ii) supports 'quasi-long-distance' entanglement that slowly falls off with the size of the chain. Due to the different scalings of the gaps, respectively exponential for model (i) and algebraic in model (ii), we demonstrate that the latter allows for efficient qubit teleportation with high fidelity in sufficiently long chains even at moderately low temperatures.

  8. XX 08

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

    to protect the area from further damage. Northwest ratepayers will absorb the costs in electric rates, and BPA is offering a reward of up to 25,000 for information that leads...

  9. SF6432-EI (xx-xx-xx) Educational Institutions

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

    operations in flight or afloat, which are Control : SF 6432-EI Title: Standard Terms & Conditions for Educational Institutions Owner: Procurement Policy & Quality Dept Release...

  10. SF6432-EI (xx-xx-xx) Educational Institutions

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

    laboratory procedures, loading or Control : SF 6432-EI Title: Standard Terms & Conditions for Educational Institutions Owner: Procurement Policy Department Release Date:...

  11. SF6432-EI (xx-xx-xx) Educational Institutions

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

    ... prior to any attempts to enter a government site as shown ... premises are subject to search. (e) Contractor shall ... Control : SF 6432-EI Title: Standard Terms & Conditions for ...

  12. SF 6432-TM (xx-xx-xx) Time Material

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

    Department Release Date: 11/17/15 Page 1 of 25 Printed copies of this document are uncontrolled. Retrieve latest version electronically. SANDIA CORPORATION SF 6432-TM (11/2015) Section II STANDARD TERMS AND CONDITIONS FOR TIME AND MATERIALS LABOR- HOUR CONTRACTS THE FOLLOWING CLAUSES APPLY TO THIS CONTRACT AS INDICATED UNLESS SPECIFICALLY DELETED, OR EXCEPT TO THE EXTENT THEY ARE SPECIFICALLY IDENTIFIED AS BEING CHANGED SUPPLEMENTED OR AMENDED IN WRITING ISSUED BY THE SANDIA CONTRACTING

  13. SF6432-EI (xx-xx-xx) Educational Institutions

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

    Department Release Date: 11/17/15 Page 1 of 25 Printed copies of this document are uncontrolled. Retrieve latest version electronically. SANDIA CORPORATION SF 6432-El (11/2015) SECTION II STANDARD TERMS AND CONDITIONS FOR ALL COST-REIMBURSEMENT OR ORDERING AGREEMENTS WITH EDUCATIONAL INSTITUTIONS THE FOLLOWING CLAUSES APPLY TO THIS CONTRACT AS INDICATED UNLESS SPECIFICALLY DELETED, OR EXCEPT TO THE EXTENT THEY ARE SPECIFICALLY SUPPLEMENTED OR AMENDED IN WRITING IN THE COVER PAGE OR SECTION I.

  14. SF 6432-TM (xx-xx-xx) Time Material

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

    costs are consistent with subparagraph (3) below. Control : SF 6432-TM Title: Standard Terms and Conditions for Time and Materials Labor-Hour Contracts Owner: Procurement Policy &...

  15. SF 6432-TM (xx-xx-xx) Time Material

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

    costs are comprised of indirect costs, including Control : SF 6432-TM Title: Standard Terms and Conditions for Time and Materials Labor-Hour Contracts Owner: Procurement Policy...

  16. SF 6432-TM (xx-xx-xx) Time Material

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

    SCR and SDR (if one is identified in the contract,) within 72 hours of the Contractor's learning of the situation. The Contractor shall cooperate with Sandia and provide...

  17. SF6432-EI (xx-xx-xx) Educational Institutions

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

    ... prior to any attempts to enter a government site as shown ... premises are subject to search. (e) Contractor will ... SF 6432-EI Title: Standard Terms & Conditions for ...

  18. SF 6432-TM (xx-xx-xx) Time Material

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

    ... as those materials which enter directly into the end ... SF 6432-TM Title: Standard Terms and Conditions for Time and ... premises are subject to search. (e) Contractor shall ...

  19. SF6432-EI (xx-xx-xx) Educational Institutions

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

    ... SF 6432-EI Title: Standard Terms & Conditions for ... Any Contractor personnel who will enter a government site to ... premises are subject to search. (e) Contractor shall ...

  20. SF 6432-TM (xx-xx-xx) Time Material

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

    ... as those materials which enter directly into the end ... Control : SF 6432-TM Title: Standard Terms and Conditions ... premises are subject to search. (e) Contractor will ...

  1. SF 6432-TM (xx-xx-xx) Time Material

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

    ... National Fire Protection Association (NFPA), Standard of Mechanical Engineers (ASME), ... APPLY TO CONTRACTS AT ANY VALUE FAR 52.203-99 Prohibition of Contracting with Entities ...

  2. SF6432-EI (xx-xx-xx) Educational Institutions

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

    ... National Fire Protection Association (NFPA), Standard of Mechanical Engineers (ASME), ... APPLY TO CONTRACTS OF ANY VALUE FAR 52.203-99 Prohibition on Contracting with Entities ...

  3. Energy levels, oscillator strengths, and radiative rates for Si-like Zn XVII, Ga XVIII, Ge XIX, and As XX

    SciTech Connect (OSTI)

    Abou El-Maaref, A.; Allam, S.H.; El-Sherbini, Th.M.

    2014-01-15

    The energy levels, oscillator strengths, line strengths, and transition probabilities for transitions among the terms belonging to the 3s{sup 2}3p{sup 2}, 3s3p{sup 3}, 3s{sup 2}3p3d, 3s{sup 2}3p4s, 3s{sup 2}3p4p and 3s{sup 2}3p4d configurations of silicon-like ions (Zn XVII, Ga XVIII, Ge XIX, and As XX) have been calculated using the configuration-interaction code CIV3. The calculations have been carried out in the intermediate coupling scheme using the BreitPauli Hamiltonian. The present calculations have been compared with the available experimental data and other theoretical calculations. Most of our calculations of energy levels and oscillator strengths (in length form) show good agreement with both experimental and theoretical data. Lifetimes of the excited levels have also been calculated. -- Highlights: We have calculated the fine-structure energy levels of Si-like Zn, Ga, Ge and As. The calculations are performed using the configuration interaction method (CIV3). We have calculated the oscillator strengths, line strengths and transition rates. The wavelengths of the transitions are listed in this article. We also have made comparisons between our data and other calculations.

  4. A :netao '?X,S vrtttcn (XX-x-162) to ;,r+ allison dascrllltnPr a m?neral 7m~rM o

    Office of Legacy Management (LM)

    A :netao '?X,S vrtttcn (XX-x-162) to ;,r+ allison dascrllltnPr a m?neral 7m~rM of metallurKic.%l, fabrication, and nhysicnf stuJles whtch owht to be carried out as lntcnsively as -loseible stnrtinr: imiaedintely, in order to Tmvide information for the desicn of efficient methods of using atomic noxer. This nrescnt memo becomes more snecific in q entionini: lines of vmr!: which the idetholis and iinterlals Section believes to bc of lnortence. It also tells names of neonle and olaces where useful

  5. Microsoft Word - xx xx 13 Midway pole replacement news release...

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

    local utilities. The public meeting is: Wednesday, Feb. 20, 2013 4 p.m. to 7 p.m. Moxee City Hall 255 W. Seattle Ave. Moxee, WA 98936 Because there will not be a formal...

  6. Form Reclearance Approval Expires: XX/XX/XXXX

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

    collection of information unless the form displays a valid OMB number. U.S. Department of Energy U.S. Energy Information Administration Washington, DC 20585 Form EIA-858 Uranium...

  7. Non-Ideal p-n junction Diode of Sb{sub x}Se{sub 1-x}(x = 0.4, 0.5, 0.6, 0.7) Thin Films

    SciTech Connect (OSTI)

    Mustafa, Falah I.; Gupta, Shikha; Goyal, N.; Tripathi, S. K.

    2011-12-12

    We have made diodes consisting of the same alloy i.e. Sb{sub x}Se{sub 1-x}(x = 0.4, 0.5, 0.6 and 0.7), but change the concentration of Sb metal from 40% to 70% atomic weight percentage. It is observed from the Hall measurements that the nature of charge carriers have changed from p- to n-type at x = 0.6 for Sb{sub x}Se{sub 1-x}. We have measured I-V characteristics of four p-n junction diodes i.e. p-Sb{sub 2}Se{sub 3}/n-Sb{sub 3}Se{sub 2}, p-Sb{sub 2}Se{sub 3}/n-Sb{sub 7}Se{sub 3}, p-SbSe/n-Sb{sub 3}Se{sub 2}, p-SbSe/n-Sb{sub 7}Se{sub 3}. From the I-V plots we have calculated the parameters as built-in voltage (V{sub bi}), forward resistance (R{sub f}), ideal factor (n), saturation current (I{sub o}), breakdown current (I{sub Bd}) and breakdown voltage (V{sub Bd}).

  8. Slide 1

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

    16XX 071620XX-0826XX 071620XX-0728XX 072820XX-0802XX 080220XX-0804XX JUN XX JUL XX AUG XX SEP X Page 3 Assessing Schedule Position (Float Analysis) Activity...

  9. OMB No. XXXX-XXXX Expiration Date: XX/XX/XXXX

    Gasoline and Diesel Fuel Update (EIA)

    Product Code Input Production Stocks End of Week Oxygenates, Renewable Fuels, and Hydrocarbon Gas Liquids*: 003 Hydrocarbon Gas Liquids* 242 Consumer and Export Grade Propane...

  10. OMB No. XXXX-XXXX Expiration Date: XX/XX/XXXX

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

    888 Total 999 Pipeline stocks must be greater than or equal to stocks in tanks and underground storage in Part 7. Finished Motor Gasoline Pipeline Stocks + Gulf Coast (PADD 3)...

  11. OMB No. XXXX-XXXX Expiration Date: XX/XX/XXXX

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

    per Stream Day Quantity Used As Fuel or Feedstock Trucks Atmospheric Crude Oil Distillation Capacity PART 5. ATMOSPHERIC CRUDE OIL DISTILLATION CAPACITY AS OF JANUARY 1 1...

  12. OMB No. XXXX-XXXX Expiration Date: XX/XX/XXXX

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

    same, only complete the physical address. For the PC Electronic Data Reporting Option (PEDRO) software, call (202) 586-9659. (See Form instructions, pg 1.) Comments: Identify any...

  13. OMB No. XXXX-XXXX Expiration Date: XX/XX/XXXX

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

    PART 1. RESPONDENT IDENTIFICATION DATA For the PC Electronic Data Reporting Option (PEDRO) software, call (202) 586-9659. (See Form instructions, pg 1.) OOG.SURVEYS@eia.doe.gov...

  14. OMB No. XXXX-XXX Expiration Date: XX/XX/XXXX

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

    BARGE, AND RAIL MOVEMENTS ACTIVITY SUMMARY For the PC Electronic Data Reporting Option (PEDRO) software, call (202) 586-9659. (See Form instructions, pg 1) Mailing Address of...

  15. OMB No. XXXX-XXXX Expiration Date: XX/XX/XXXX

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

    OF THE MONTH (Barrels per Calendar Day) For the PC Electronic Data Reporting Option (PEDRO) software, call (202) 586-9659. (See Form instructions, pg 1.) Mailing Address of...

  16. OMB No. XXXX-XXXX Expiration Date: XX/XX/XXXX

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

    same, only complete the physical address. For the PC Electronic Data Reporting Option (PEDRO) software, call (202) 586-9659. (See Form instructions, pg 1) Month A completed form...

  17. OMB No. XXXX-XXXX Expiration Date: XX/XX/XXXX

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

    using one of the following methods: For the PC Electronic Data Reporting Option (PEDRO) software, call (202) 586-9659. (See Form instructions, pg 1) Enter barrels to the...

  18. OMB No. XXXX-XXXX Expiration Date: XX/XX/XXXX

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

    day following the end of the report month. For the PC Electronic Data Reporting Option (PEDRO) software, call (202) 586-9659. (See Form instructions, pg 1.) Month Forms may be...

  19. OMB No. XXXX-XXXX Expiration Date: XX/XX/XXXX

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

    comment from another, press ALT+ENTER.) For the PC Electronic Data Reporting Option (PEDRO) software, call (202) 586-9659. (See Form instructions, pg 1.) Forms may be submitted...

  20. Microsoft Word - xx xx 13 Bill Drummond sworn in as administrator...

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

    and executive management to the agency. Before joining BPA, Drummond had managed Western Montana Electric Generating and Transmission Cooperative in Missoula, Mont., for...

  1. ANL-78-XX-95 Energy Level Structure and Transition Probabilities

    Office of Scientific and Technical Information (OSTI)

    III. Treatment of Experimental Data 8 Fig. 2. Crystal-field Parameters for Ln 3+ :LaCl 3 and Ln 3+ :LaF 3 13 IV. Energy Level Correlations - Survey of Experimental Data 14 1. f 2 ...

  2. Microsoft Word - XX 15 BPA moving forward with Hooper Springs...

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

    CONTACT: Doug Johnson, 503-230-5840503-230-5131 BPA selects final path for its Hooper Springs Transmission project Portland, Ore. - The Bonneville Power Administration has decided...

  3. Microsoft Word - XX 13 Public scoping Walla Walla Basin Spring...

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

    existing adult holding and spawning facility on the South Fork Walla Walla River near Milton-Freewater in Umatilla County, Ore. This is the latest project in an ongoing...

  4. Microsoft Word - XX 13 Science and education grants offered by...

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

    gotoEducationGrants . BPA's education program provides free presentations and information to K-12 schools in our region to help students achieve energy literacy, and to...

  5. Microsoft Word - XX 13 IG report statement 10-2013

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

    particularly against those who raise concerns. As we move forward to rebuild our human resource capabilities, all of us at BPA will continue to serve our core mission by...

  6. Microsoft Word - XX 13 Colville Tribe to celebrate opening of...

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

    will significantly boost the availability of chinook salmon for the tribe and for sport fishing in the Columbia River as well as reintroduce spring chinook to the Okanogan...

  7. NAP-XX Defense Programs Business Requirements and Processes Manual

    National Nuclear Security Administration (NNSA)

    Programs http://nnsa.energy.gov printed copies are uncontrolled SUPPLEMENTAL DIRECTIVE Approved: 2-25-16 DEFENSE PROGRAMS BUSINESS PROCESS SYSTEM (DPBPS) NATIONAL NUCLEAR SECURITY ADMINISTRATION Office of Defense Programs NNSA SD 452.3-1A THIS PAGE INTENTIONALLY LEFT BLANK NNSA SD 452.3-1A 1 2-25-16 DEFENSE PROGRAMS BUSINESS PROCESS SYSTEM 1. PURPOSE. This supplemental directive (SD) establishes the Defense Programs Business Process System (DPBPS) Portal as the mechanism for implementing DOE

  8. Microsoft Word - XX 14 Delwiche and Andrews appointments FINAL...

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

    for BPA's power planning and scheduling functions; generation asset management; power contracts and rates; power purchases and acquisitions; and business relationships with...

  9. Microsoft Word - XX 13 Coyote Creek land acquisition provides...

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

    Wingert, 503-230-4140 or 503-230-5131 Rare wet prairie, wildlife corridor protected by land acquisition in Willamette Valley Portland, Ore. - Building upon a well-established...

  10. Microsoft Word - XX 13 HRD dep adm release (3).doc

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

    capital management function and ensure it has high performing compliance and governance functions. First, Brian E. Carter, currently the CivilianHuman Resources Officer for the...

  11. Household magnets

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

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

  12. Microsoft Word - XX 14 Connolly named VP Gen - Asset Mgmt FINAL...

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

    0 14 BONNEVILLE POWER ADMINISTRATION FOR IMMEDIATE RELEASE Monday, Oct. 6, 2014 CONTACT: Doug Johnson, 503-230-5840503-230-5131 Kieran Connolly named BPA vice president of...

  13. THE ANGLO-AUSTRALIAN PLANET SEARCH. XX. A SOLITARY ICE-GIANT PLANET ORBITING HD 102365

    SciTech Connect (OSTI)

    Tinney, C. G.; Wittenmyer, Robert A.; Bailey, Jeremy; Butler, R. Paul; Jones, Hugh R. A.; O'Toole, Simon; Carter, Brad D.

    2011-02-01

    We present 12 years of precision Doppler data for the very nearby G3 star HD 102365, which reveals the presence of a Neptune-like planet with a 16.0 M{sub Earth} minimum mass in a 122.1 day orbit. Very few 'Super Earth' planets have been discovered to date in orbits this large and those that have been found reside in multiple systems of between three and six planets. HD 102365 b, in contrast, appears to orbit its star in splendid isolation. Analysis of the residuals to our Keplerian fit for HD 102365 b indicates that there are no other planets with minimum mass above 0.3 M{sub Jup} orbiting within 5 AU and no other 'Super Earths' more massive than 10 M{sub Earth} orbiting at periods shorter than 50 days. At periods of less than 20 days these limits drop to as low as 6 M{sub Earth}. There are now 32 exoplanets known with minimum mass below 20 M{sub Earth}, and interestingly the period distributions of these low-mass planets seem to be similar whether they orbit M-, K-, or G-type dwarfs.

  14. SECTION L … ATTACHMENT xx … KEY PERSONNEL AND CRITICAL WORK AREA PERSONNEL RESUME ELEMENTS

    National Nuclear Security Administration (NNSA)

    2] Attachment L-3a KEY PERSONNEL RESUME ELEMENTS 1. Name of Offeror: 2. Name of Key Person: 3. Proposed Position: 4. Duties and Responsibilities in Proposed Position including elements of SOW assigned: 5. Chronological Work History: Start with current position and work backwards. A. Name and Address of Firm: B. Position(s) Held: C. Dates of Employment: D. General Summary of Responsibilities: Provide a concise description of major duties and responsibilities for each job relevant to the proposed

  15. Microsoft PowerPoint - xxDraft SEIS PUBLIC MEETING PRESENTATION 9 sep 2014 [Compatibility Mode]

    National Nuclear Security Administration (NNSA)

    Public Hearings on Draft SEIS September 9-10, 2014 National Nuclear Security Administration (NNSA) Department of Energy (DOE) 1 Supplemental Environmental Impact Statement (SEIS) for the Production of Tritium in a Commercial Light Water Reactor Background * NNSA is the federal agency responsible for providing the nation with nuclear weapons and ensuring those weapons remain safe and reliable * Tritium is a radioactive isotope of hydrogen and is an essential component of every weapon in the

  16. SECTION L … ATTACHMENT xx … KEY PERSONNEL AND CRITICAL WORK...

    National Nuclear Security Administration (NNSA)

    the proposed duties and responsibilities of the proposed position. 8. Professional credentials that are relevant to the individual's proposed position. 9. Signed 3-Year Letter of ...

  17. Microsoft Word - xx 13 Treasury Payment Oct 2013 Final Oct 4...

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

    to Energy Northwest projects. Energy Northwest develops, owns and operates a diverse mix of electricity generating resources, including the Northwest's only nuclear generating...

  18. A :netao '?X,S vrtttcn (XX-x-162) to ;,r+ allison dascrllltnPr...

    Office of Legacy Management (LM)

    XeJuction an& nurification methods for the metal should be sou&t ano the 12 usefulnas? oiL:stillation should be Determined. Sneddiw' s work on' 9e reduct.Zoa and- : castin? 2nd ...

  19. Microsoft Word - XX 14 15 minute scheduling release FINAL.docx

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

    with abundant clean energy resources, led by the hydropower system," said John Prescott, president and CEO of PNGC Power. "BPA has been proactive in taking steps to increase...

  20. Microsoft PowerPoint - xxDraft SEIS PUBLIC MEETING PRESENTATION...

    National Nuclear Security Administration (NNSA)

    Zircaloy Tritium Getter Nickel Plate Lithium Aluminate Pellets Zircaloy Liner Lithium Aluminate Pellets Ceramic material containing Lithium-6, the active ingredient that transmutes ...

  1. Microsoft Word - NRAP-TRS-III-0XX-2016_A Users Guide to DFNGen...

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

    ... A User's Guide to DFNGen 12 The second group of options involves saving DFNGen files. 11 The File>Save command will save the current data set using the current file name and ...

  2. Microsoft Word - XX 13 New book reveals drama behind your light...

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

    evolving environmental values and building out the regional power grid. Filled with spectacular photographs, it tells the stories vividly through the lens of BPA, the federal...

  3. Microsoft Word - XX 15 Jensen named BPA general counsel (3) FINAL...

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

    in creating national guidelines for power marketing administrations in states where marijuana sales are lawful under state statutes. She also instituted new processes that enable...

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

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

    logo printer-friendly version logo for Portable Document Format file Household Vehicles Energy Consumption 1994 August 1997 Release Next Update: EIA has discontinued this series....

  5. Building Interoperability

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

    Page 3 20XX-XX-XX Market Place Needs - Data Fatigue Carbon Emissions Alternative Energy Demand Response Distributed Power IAQ Personal UI Mobile Cloud IT Convergence Charging...

  6. Appendix A, Sample Register REGISTER XY CONTRACTING OFFICE Initiation

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

    Number Solicitation Number Business Instrument Number 08302011 XX REQ- 11XX12345 DE-SOL- XX12345 DE- XY12345 AmendmentModification REQ- 11XX12345.000 Modification 001...

  7. Draft DOE P 226

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

    Extension of DOE N XXX.X (Title) Synopsis Summary Background: The Office of XXXXXXXXXXXX (XX) is requesting a 1-year extension to DOE N XXX.X, (Title), dated XX-XX-XX. The Notice ...

  8. appl_household2001.pdf

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

    Appliances Tables (Million U.S. Households; 60 pages, 240 kb) Contents Pages HC5-1a. Appliances by Climate Zone, Million U.S. Households, 2001 5 HC5-2a. Appliances by Year of Construction, Million U.S. Households, 2001 5 HC5-3a. Appliances by Household Income, Million U.S. Households, 2001 5 HC5-4a. Appliances by Type of Housing Unit, Million U.S. Households, 2001 5 HC5-5a. Appliances by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 5 HC5-6a. Appliances by Type of Rented

  9. Experimental investigation of factors limiting slow axis beam quality in 9xx nm high power broad area diode lasers

    SciTech Connect (OSTI)

    Winterfeldt, M. Crump, P.; Wenzel, H.; Erbert, G.; Trnkle, G.

    2014-08-14

    GaAs-based broad-area diode lasers are needed with improved lateral beam parameter product (BPP{sub lat}) at high power. An experimental study of the factors limiting BPP{sub lat} is therefore presented, using extreme double-asymmetric (EDAS) vertical structures emitting at 910?nm. Continuous wave, pulsed and polarization-resolved measurements are presented and compared to thermal simulation. The importance of thermal and packaging-induced effects is determined by comparing junction -up and -down devices. Process factors are clarified by comparing diodes with and without index-guiding trenches. We show that in all cases studied, BPP{sub lat} is limited by a non-thermal BPP ground-level and a thermal BPP, which depends linearly on self-heating. Measurements as a function of pulse width confirm that self-heating rather than bias-level dominates. Diodes without trenches show low BPP ground-level, and a thermal BPP which depends strongly on mounting, due to changes in the temperature profile. The additional lateral guiding in diodes with trenches strongly increases the BPP ground-level, but optically isolates the stripe from the device edges, suppressing the influence of the thermal profile, leading to a BPP-slope that is low and independent of mounting. Trenches are also shown to initiate strain fields that cause parasitic TM-polarized emission with large BPP{sub lat}, whose influence on total BPP{sub lat} remains small, provided the overall polarization purity is >95%.

  10. Microsoft Word - NRAP-TRS-III-0XX-2016_A Users Guide to DFNGen 2016.final.docx

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

    A User's Guide to DFNGen 28 January 2016 Office of Fossil Energy NRAP-TRS-III-001-2016 Disclaimer This report was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents

  11. housingunit_household2001.pdf

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

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

  12. appl_household2001.pdf

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

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

  13. ac_household2001.pdf

    Gasoline and Diesel Fuel Update (EIA)

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

  14. spaceheat_household2001.pdf

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

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

  15. Household Vehicles Energy Consumption 1991

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

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

  16. Household Vehicles Energy Consumption 1991

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

    logo printer-friendly version logo for Portable Document Format file Household Vehicles Energy Consumption 1991 December 1993 Release Next Update: August 1997. Based on the 1991...

  17. Household vehicles energy consumption 1994

    SciTech Connect (OSTI)

    1997-08-01

    Household Vehicles Energy Consumption 1994 reports on the results of the 1994 Residential Transportation Energy Consumption Survey (RTECS). The RTECS is a national sample survey that has been conducted every 3 years since 1985. For the 1994 survey, more than 3,000 households that own or use some 6,000 vehicles provided information to describe vehicle stock, vehicle-miles traveled, energy end-use consumption, and energy expenditures for personal vehicles. The survey results represent the characteristics of the 84.9 million households that used or had access to vehicles in 1994 nationwide. (An additional 12 million households neither owned or had access to vehicles during the survey year.) To be included in then RTECS survey, vehicles must be either owned or used by household members on a regular basis for personal transportation, or owned by a company rather than a household, but kept at home, regularly available for the use of household members. Most vehicles included in the RTECS are classified as {open_quotes}light-duty vehicles{close_quotes} (weighing less than 8,500 pounds). However, the RTECS also includes a very small number of {open_quotes}other{close_quotes} vehicles, such as motor homes and larger trucks that are available for personal use.

  18. Next Generation Household Refrigerator | Department of Energy

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

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

  19. Household Vehicles Energy Use Cover Page

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

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

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

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

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

  1. ac_household2001.pdf

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

    0a. Air Conditioning by Midwest Census Region, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total U.S. Midwest Census Region RSE Row Factors Total Census Division East North Central West North Central 0.5 1.0 1.2 1.4 Households With Electric Air-Conditioning Equipment ...................... 82.9 20.5 13.6 6.8 2.2 Air Conditioners Not Used ........................... 2.1 0.3 Q Q 27.5 Households Using Electric Air-Conditioning 1

  2. ac_household2001.pdf

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

    1a. Air Conditioning by South Census Region, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total U.S. South Census Region RSE Row Factors Total Census Division South Atlantic East South Central West South Central 0.5 0.8 1.2 1.3 1.4 Households With Electric Air-Conditioning Equipment ...................... 82.9 37.2 19.3 6.4 11.5 1.5 Air Conditioners Not Used ........................... 2.1 0.4 Q Q Q 28.2 Households Using Electric Air-Conditioning 1

  3. ac_household2001.pdf

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

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

  4. ac_household2001.pdf

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

    4a. Air Conditioning by Type of Housing Unit, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total Type of Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.4 0.6 1.5 1.4 1.8 Households With Electric Air-Conditioning Equipment ........ 82.9 58.7 6.5 12.4 5.3 4.9 Air Conditioners Not Used ............ 2.1 1.1 Q 0.6 Q 21.8 Households Using Electric Air-Conditioning 1

  5. ac_household2001.pdf

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

    8a. Air Conditioning by Urban/Rural Location, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total Urban/Rural Location 1 RSE Row Factors City Town Suburbs Rural 0.5 0.8 1.4 1.3 1.4 Households With Electric Air-Conditioning Equipment ...................... 82.9 36.8 13.6 18.9 13.6 4.3 Air Conditioners Not Used ........................... 2.1 1.2 0.2 0.4 0.3 21.4 Households Using Electric Air-Conditioning 2 ........................................ 80.8 35.6 13.4

  6. ac_household2001.pdf

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

    9a. Air Conditioning by Northeast Census Region, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total U.S. Northeast Census Region RSE Row Factors Total Census Division Middle Atlantic New England 0.5 1.0 1.2 1.8 Households With Electric Air-Conditioning Equipment ...................... 82.9 14.5 11.3 3.2 3.3 Air Conditioners Not Used ........................... 2.1 0.3 0.3 Q 28.3 Households Using Electric Air-Conditioning 1

  7. MEMORANDUM FOR:

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

    xx-xx-xxxx Expires: xx-xx-xxxx SUBJECT: EXTENSION OF DOE N XXX.X, (Title) Effective immediately, DOE N XXX.X, (Title), dated XX-XX-XX, is extended to XX-XX-XXXX, or until superseded. The requirements of DOE N XXX.X (state where the requirements will be incorporated, i.e., an Order, rule, etc.). If you need additional information, contact (name) at (phone number). BY ORDER OF THE SECRETARY OF ENERGY: NAME Deputy Secretary AVAILABLE ONLINE AT: INITIATED BY: www.directives.doe.gov Office of

  8. Household Vehicles Energy Consumption 1991

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

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

  9. homeoffice_household2001.pdf

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

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

  10. char_household2001.pdf

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

    RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral ... Income Relative to Poverty Line Below 100 Percent ...... 15.0 13.2 1.8 Q ...

  11. char_household2001.pdf

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

    Contact: Stephanie J. Battles, Survey Manager (stephanie.battles@eia.doe.gov) World Wide Web: http:www.eia.doe.govemeuconsumption Table HC2-1a. Household Characteristics by ...

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

    Gasoline and Diesel Fuel Update (EIA)

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

  13. ac_household2001.pdf

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

    2a. Air Conditioning by Year of Construction, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total Year of Construction RSE Row Factors 1990 to 2001 1 1980 to 1989 1970 to 1979 1960 to 1969 1950 to 1959 1949 or Before 0.4 1.6 1.2 1.1 1.2 1.1 0.9 Households With Electric Air-Conditioning Equipment ........ 82.9 13.6 16.0 14.7 10.4 10.5 17.6 4.7 Air Conditioners Not Used ............ 2.1 Q 0.3 0.5 0.3 0.4 0.5 27.2 Households Using Electric Air-Conditioning 2

  14. ac_household2001.pdf

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

    5a. Air Conditioning by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total Owner- Occupied Units Type of Owner-Occupied Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.5 0.5 1.5 1.4 1.8 Households With Electric Air-Conditioning Equipment ........ 59.5 58.7 6.5 12.4 5.3 5.2 Air Conditioners Not Used ............ 1.2 1.1 Q 0.6 Q 23.3 Households Using

  15. ac_household2001.pdf

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

    6a. Air Conditioning by Type of Rented Housing Unit, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total Rented Units Type of Rented Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.8 0.5 1.4 1.2 1.6 Households With Electric Air-Conditioning Equipment ........ 23.4 58.7 6.5 12.4 5.3 6.1 Air Conditioners Not Used ............ 0.9 1.1 Q 0.6 Q 23.0 Households Using Electric Air-Conditioning

  16. homeoffice_household2001.pdf

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

    0a. Home Office Equipment by Midwest Census Region, Million U.S. Households, 2001 Home Office Equipment RSE Column Factor: Total U.S. Midwest Census Region RSE Row Factors Total Census Division East North Central West North Central 0.5 1.0 1.2 1.6 Total .............................................................. 107.0 24.5 17.1 7.4 NE Households Using Office Equipment ......................................... 96.2 22.4 15.7 6.7 1.3 Personal Computers 1 ................................. 60.0

  17. homeoffice_household2001.pdf

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

    1a. Home Office Equipment by South Census Region, Million U.S. Households, 2001 Home Office Equipment RSE Column Factor: Total U.S. South Census Region RSE Row Factors Total Census Division South Atlantic East South Central West South Central 0.5 0.8 1.2 1.3 1.6 Total .............................................................. 107.0 38.9 20.3 6.8 11.8 NE Households Using Office Equipment ......................................... 96.2 34.6 18.4 6.0 10.1 1.2 Personal Computers 1

  18. homeoffice_household2001.pdf

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

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

  19. homeoffice_household2001.pdf

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

    9a. Home Office Equipment by Northeast Census Region, Million U.S. Households, 2001 Home Office Equipment RSE Column Factor: Total U.S. Northeast Census Region RSE Row Factors Total Census Division Middle Atlantic New England 0.5 1.1 1.4 1.2 Total .............................................................. 107.0 20.3 14.8 5.4 NE Households Using Office Equipment ......................................... 96.2 17.9 12.8 5.0 1.3 Personal Computers 1 ................................. 60.0 10.9

  20. Chapter 1

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

    ... The Office of Xxxxxxxxxx has scheduled a (Event Type, i.e., holiday party) on (Month Day, Year) at the Forrestal Building in Rm. xx-xxx from x:xx to x:xx ampm. I am therefore ...

  1. 71-100-01d

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

    DUKE UNIVERSITY FREE ELECTRON LASER LABORATORY LaSalle Street Extension, Duke University, Durham, NC 27708 Matthew admin 1282009 660-2694 XX-XX-XXX-XX C C D D H H K L 25 26 5004 ...

  2. homeoffice_household2001.pdf

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

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

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

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

    Household Expenditures on Transportation, 1984-2010 Fact 748: October 8, 2012 Components of Household Expenditures on Transportation, 1984-2010 The overall share of annual household ...

  4. MEMORANDUM FOR:

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

    directives (is/are) canceled: DOE G, Title, dated XX-XX-XX (Author: email; phone number) DOE G, Title, dated XX-XX-XX (Author: email; phone number) Cancellation of these directives (this directive) does not relieve the Department or its contractors from complying with applicable Federal laws and regulations pertaining to the canceled directives. Inquiries should be addressed to the point(s) of contact listed with the directive(s). For information about the Departmental Directives Program,

  5. ac_household2001.pdf

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

    2001 Air Conditioning Characteristics RSE Column Factor: Total U.S. Four Most Populated States RSE Row Factors New York California Texas Florida 0.4 1.1 1.7 1.2 1.2 Households With Electric Air-Conditioning Equipment ...................... 82.9 4.9 6.0 7.4 6.2 2.4 Air Conditioners Not Used ........................... 2.1 0.1 0.8 Q 0.1 23.2 Households Using Electric Air-Conditioning 1 ........................................ 80.8 4.7 5.2 7.4 6.1 2.6 Type of Electric Air-Conditioning Used Central

  6. homeoffice_household2001.pdf

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

    2a. Home Office Equipment by Year of Construction, Million U.S. Households, 2001 Home Office Equipment RSE Column Factor: Total Year of Construction RSE Row Factors 1990 to 2001 1 1980 to 1989 1970 to 1979 1960 to 1969 1950 to 1959 1949 or Before 0.4 1.4 1.1 1.1 1.2 1.2 1.0 Total ............................................... 107.0 15.5 18.2 18.8 13.8 14.2 26.6 4.2 Households Using Office Equipment .......................... 96.2 14.9 16.7 17.0 12.2 13.0 22.4 4.4 Personal Computers 2

  7. appl_household2001.pdf

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

    2a. Appliances by West Census Region, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total U.S. West Census Region RSE Row Factors Total Census Division Mountain Pacific 0.5 1.0 1.7 1.2 Total .............................................................. 107.0 23.3 6.7 16.6 NE Kitchen Appliances Cooking Appliances Oven ......................................................... 101.7 22.1 6.6 15.5 1.1 1

  8. ASME N511-19XX, Standard for periodic in-service testing of nuclear air treatment, heating, ventilating and air conditioning systems

    SciTech Connect (OSTI)

    1997-08-01

    A draft version of the Standard is presented in this document. The Standard covers the requirements for periodic in-service testing of nuclear safety-related air treatment, heating, ventilating, and air conditioning systems in nuclear facilities. The Standard provides a basis for the development of test programs and does not include acceptance criteria, except in cases where the results of one test influence the performance of other tests. The Standard covers general inspection and test requirements, reference values, inspection and test requirements, generic tests, acceptance criteria, in-service test requirements, testing following an abnormal incident, corrective action requirements, and quality assurance. Mandatory appendices provide a visual inspection checklist and four test procedures. Non-mandatory appendices provide additional information and guidance on mounting frame pressure leak test procedure, corrective action, challenge gas substitute selection criteria, and test program development. 8 refs., 10 tabs.

  9. NON-NRC FUNDED RELAP5-3D VERSION 4.x.x SOFTWARE REACTOR EXCURSION AND LEAK ANALYSIS PACKAGE - THREE DIMENSIONAL

    SciTech Connect (OSTI)

    2012-03-26

    The RELAP5-3D Version 3.x code has been developed for best-estimate transient simulation of nuclear reactor coolant systems during postulated accidents. The code models the coupled behavior of the reactor coolant system and the core for loss-of-coolant accidents and operational transients such as anticipated transient without scram, loss of offsite power, loss of feedwater, and loss of flow. A generic modeling approach is used that permits simulating a variety of thermal hydraulic systems including pressurized water reactors, boiling water reactors, Soviet-designed reactors, heavy water reactors, gas-cooled reactors, liquid metal and molten salt cooled reactors, and even fusion reactors. Numerical models include multi-dimensional hydrodynamics, 1- and 2-D heat transfer in metal walls, 0-, 1-, 2-, and 3-D neutron kinetics, trips, and control systems. Secondary system components are included to permit modeling of plant controls, turbines, condensers, and secondary feedwater systems.

  10. NON-NRC FUNDED RELAP5-3D VERSION 4.x.x SOFTWARE REACTOR EXCURSION AND LEAK ANALYSIS PACKAGE - THREE DIMENSIONAL

    Energy Science and Technology Software Center (OSTI)

    2012-03-26

    The RELAP5-3D Version 3.x code has been developed for best-estimate transient simulation of nuclear reactor coolant systems during postulated accidents. The code models the coupled behavior of the reactor coolant system and the core for loss-of-coolant accidents and operational transients such as anticipated transient without scram, loss of offsite power, loss of feedwater, and loss of flow. A generic modeling approach is used that permits simulating a variety of thermal hydraulic systems including pressurized watermore » reactors, boiling water reactors, Soviet-designed reactors, heavy water reactors, gas-cooled reactors, liquid metal and molten salt cooled reactors, and even fusion reactors. Numerical models include multi-dimensional hydrodynamics, 1- and 2-D heat transfer in metal walls, 0-, 1-, 2-, and 3-D neutron kinetics, trips, and control systems. Secondary system components are included to permit modeling of plant controls, turbines, condensers, and secondary feedwater systems.« less

  11. appl_household2001.pdf

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

    0a. Appliances by Midwest Census Region, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total U.S. Midwest Census Region RSE Row Factors Total Census Division East North Central West North Central 0.5 1.0 1.2 1.5 Total .............................................................. 107.0 24.5 17.1 7.4 NE Kitchen Appliances Cooking Appliances Oven ......................................................... 101.7 23.8 16.6 7.2 NE 1

  12. appl_household2001.pdf

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

    1a. Appliances by South Census Region, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total U.S. South Census Region RSE Row Factors Total Census Division South Atlantic East South Central West South Central 0.5 0.8 1.1 1.4 1.5 Total .............................................................. 107.0 38.9 20.3 6.8 11.8 NE Kitchen Appliances Cooking Appliances Oven ......................................................... 101.7 36.2 19.4 6.4 10.3 1.5 1

  13. appl_household2001.pdf

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

    4a. Appliances by Type of Housing Unit, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total Type of Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.4 0.5 1.7 1.6 1.9 Total ............................................... 107.0 73.7 9.5 17.0 6.8 4.2 Kitchen Appliances Cooking Appliances Oven ........................................... 101.7 69.1 9.4 16.7 6.6 4.3 1

  14. appl_household2001.pdf

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

    5a. Appliances by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total Owner- Occupied Units Type of Owner-Occupied Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.3 0.4 2.1 3.1 1.3 Total ............................................... 72.7 63.2 2.1 1.8 5.7 6.7 Kitchen Appliances Cooking Appliances Oven ...........................................

  15. appl_household2001.pdf

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

    6a. Appliances by Type of Rented Housing Unit, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total Rented Units Type of Rented Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.5 0.8 1.1 0.9 2.5 Total ............................................... 34.3 10.5 7.4 15.2 1.1 6.9 Kitchen Appliances Cooking Appliances Oven ........................................... 33.4 10.1 7.3 14.9 1.1

  16. appl_household2001.pdf

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

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

  17. appl_household2001.pdf

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

    9a. Appliances by Northeast Census Region, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total U.S. Northeast Census Region RSE Row Factors Total Census Division Middle Atlantic New England 0.5 1.0 1.3 1.6 Total .............................................................. 107.0 20.3 14.8 5.4 NE Kitchen Appliances Cooking Appliances Oven ......................................................... 101.7 19.6 14.5 5.2 1.1 1

  18. homeoffice_household2001.pdf

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

    2001 Home Office Equipment RSE Column Factor: Total U.S. Four Most Populated States RSE Row Factors New York California Texas Florida 0.4 1.1 1.0 1.5 1.5 Total .............................................................. 107.0 7.1 12.3 7.7 6.3 NE Households Using Office Equipment ......................................... 96.2 6.2 11.4 6.7 5.9 1.7 Personal Computers 1 ................................. 60.0 3.4 7.9 4.1 3.8 4.4 Number of Desktop PCs 1

  19. spaceheat_household2001.pdf

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

    0a. Space Heating by Midwest Census Region, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total U.S. Midwest Census Region RSE Row Factors Total Census Division East North Central West North Central 0.5 1.0 1.2 1.6 Total .............................................................. 107.0 24.5 17.1 7.4 NE Heat Home .................................................... 106.0 24.5 17.1 7.4 NE Do Not Heat Home ....................................... 1.0 Q Q Q 19.8 No

  20. spaceheat_household2001.pdf

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

    1a. Space Heating by South Census Region, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total U.S. South Census Region RSE Row Factors Total Census Division South Atlantic East South Central West South Central 0.5 0.9 1.2 1.4 1.3 Total .............................................................. 107.0 38.9 20.3 6.8 11.8 NE Heat Home .................................................... 106.0 38.8 20.2 6.8 11.8 NE Do Not Heat Home

  1. spaceheat_household2001.pdf

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

    2a. Space Heating by West Census Region, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total U.S. West Census Region RSE Row Factors Total Census Division Mountain Pacific 0.6 1.0 1.6 1.2 Total .............................................................. 107.0 23.3 6.7 16.6 NE Heat Home .................................................... 106.0 22.6 6.7 15.9 NE Do Not Heat Home ....................................... 1.0 0.7 Q 0.7 10.6 No Heating Equipment

  2. spaceheat_household2001.pdf

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

    5a. Space Heating by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total Owner- Occupied Units Type of Owner-Occupied Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.4 0.4 1.9 3.0 1.3 Total ............................................... 72.7 63.2 2.1 1.8 5.7 6.7 Heat Home ..................................... 72.4 63.0 2.0 1.7 5.7 6.7 Do Not Heat Home

  3. spaceheat_household2001.pdf

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

    6a. Space Heating by Type of Rented Housing Unit, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total Rented Units Type of Rented Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.5 0.8 1.1 0.9 2.5 Total ............................................... 34.3 10.5 7.4 15.2 1.1 6.9 Heat Home ..................................... 33.7 10.4 7.4 14.8 1.1 6.9 Do Not Heat Home

  4. spaceheat_household2001.pdf

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

    8a. Space Heating by Urban/Rural Location, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total Urban/Rural Location 1 RSE Row Factors City Town Suburbs Rural 0.6 0.9 1.3 1.3 1.2 Total .............................................................. 107.0 49.9 18.0 21.2 17.9 4.3 Heat Home .................................................... 106.0 49.1 18.0 21.2 17.8 4.3 Do Not Heat Home ....................................... 1.0 0.7 0.1 0.1 0.1 25.8 No Heating

  5. spaceheat_household2001.pdf

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

    9a. Space Heating by Northeast Census Region, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total U.S. Northeast Census Region RSE Row Factors Total Census Division Middle Atlantic New England 0.5 1.0 1.2 1.7 Total .............................................................. 107.0 20.3 14.8 5.4 NE Heat Home .................................................... 106.0 20.1 14.7 5.4 NE Do Not Heat Home ....................................... 1.0 Q Q Q 19.9 No

  6. Household energy consumption and expenditures, 1990

    SciTech Connect (OSTI)

    Not Available

    1993-03-02

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

  7. appl_household2001.pdf

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

    a. Appliances by Climate Zone, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total Climate Zone 1 RSE Row Factors Fewer than 2,000 CDD and -- 2,000 CDD or More and Fewer than 4,000 HDD More than 7,000 HDD 5,500 to 7,000 HDD 4,000 to 5,499 HDD Fewer than 4,000 HDD 0.4 1.9 1.1 1.1 1.2 1.1 Total .................................................. 107.0 9.2 28.6 24.0 21.0 24.1 7.8 Kitchen Appliances Cooking Appliances Oven

  8. appl_household2001.pdf

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

    2a. Appliances by Year of Construction, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total Year of Construction RSE Row Factors 1990 to 2001 1 1980 to 1989 1970 to 1979 1960 to 1969 1950 to 1959 1949 or Before 0.4 1.5 1.2 1.1 1.2 1.1 0.9 Total ............................................... 107.0 15.5 18.2 18.8 13.8 14.2 26.6 4.2 Kitchen Appliances Cooking Appliances Oven ........................................... 101.7 14.3 17.2 17.8 12.9 13.7 25.9 4.2 1

  9. spaceheat_household2001.pdf

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

    2a. Space Heating by Year of Construction, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total Year of Construction RSE Row Factors 1990 to 2001 1 1980 to 1989 1970 to 1979 1960 to 1969 1950 to 1959 1949 or Before 0.5 1.5 1.1 1.1 1.1 1.1 0.9 Total ............................................... 107.0 15.5 18.2 18.8 13.8 14.2 26.6 4.3 Heat Home ..................................... 106.0 15.4 18.2 18.6 13.6 13.9 26.4 4.3 Do Not Heat Home ........................

  10. spaceheat_household2001.pdf

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

    4a. Space Heating by Type of Housing Unit, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total Type of Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.5 0.5 1.5 1.4 1.7 Total ............................................... 107.0 73.7 9.5 17.0 6.8 4.4 Heat Home ..................................... 106.0 73.4 9.4 16.4 6.8 4.5 Do Not Heat Home ........................ 1.0 0.3 Q 0.6 Q 19.0 No

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

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

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

  12. ASSESSMENT OF HOUSEHOLD CARBON FOOTPRINT REDUCTION POTENTIALS

    SciTech Connect (OSTI)

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

    2009-04-15

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

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

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

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

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

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

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

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

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

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

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

    Open Energy Info (EERE)

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

  17. Microsoft Word - Household Energy Use CA

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

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

  18. Microsoft Word - Household Energy Use CA

    Gasoline and Diesel Fuel Update (EIA)

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

  19. MEMORANDUM FOR:

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

    Washington, D.C. Approved: XX-XX-20XX Expires: XX-XX-20XX SUBJECT: TITLE 1 purpose . (Define the program or subject matter and its purpose/goals/objectives. Goals should be stated in simple, straightforward language that describes the results to be achieved by issuance of the Notice.) 2 CANCELLATION . DOE N XXX.X, Title, dated X-X-XX. (When the Notice replaces another directive currently in use, the canceled directive [i.e., Policy, Order, Notice, Manual, or Guide] is identified by number,

  20. Household energy consumption and expenditures 1993

    SciTech Connect (OSTI)

    1995-10-05

    This presents information about household end-use consumption of energy and expenditures for that energy. These data were collected in the 1993 Residential Energy Consumption Survey; more than 7,000 households were surveyed for information on their housing units, energy consumption and expenditures, stock of energy-consuming appliances, and energy-related behavior. The information represents all households nationwide (97 million). Key findings: National residential energy consumption was 10.0 quadrillion Btu in 1993, a 9% increase over 1990. Weather has a significant effect on energy consumption. Consumption of electricity for appliances is increasing. Houses that use electricity for space heating have lower overall energy expenditures than households that heat with other fuels. RECS collected data for the 4 most populous states: CA, FL, NY, TX.

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

    Gasoline and Diesel Fuel Update (EIA)

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

  2. Household Energy Consumption Segmentation Using Hourly Data

    SciTech Connect (OSTI)

    Kwac, J; Flora, J; Rajagopal, R

    2014-01-01

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

  3. Household energy consumption and expenditures, 1987

    SciTech Connect (OSTI)

    Not Available

    1989-10-10

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

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

    SciTech Connect (OSTI)

    Guerin, D.A.

    1988-01-01

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

  5. MEMORANDUM FOR:

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

    directive(s) (is/are) canceled: DOE (O, M, P, N), Title, dated XX-XX-XX (Author: email; phone number) DOE (O, M, P, N), Title, dated XX-XX-XX (Author: email; phone number) Cancellation of these directives (this directive) does not relieve the Department or its contractors from complying with applicable Federal laws and regulations pertaining to the canceled directives. Inquiries should be addressed to the point(s) of contact listed with the directive(s). For information about the Departmental

  6. Strategies for Collecting Household Energy Data | Department of Energy

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

    Collecting Household Energy Data Strategies for Collecting Household Energy Data Better Buildings Neighborhood Program Data and Evaluation Peer Exchange Call: Strategies for Collecting Household Energy Data, Call Slides and Discussion Summary, July 19, 2012. Call Slides and Discussion Summary (700.06 KB) More Documents & Publications Homeowner and Contractor Surveys Mastermind: Jim Mikel, Spirit Foundation Generating Energy Efficiency Project Leads and Allocating Leads to Contractors

  7. Household energy consumption and expenditures 1987

    SciTech Connect (OSTI)

    Not Available

    1990-01-22

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

  8. Appliance Commitment for Household Load Scheduling

    SciTech Connect (OSTI)

    Du, Pengwei; Lu, Ning

    2011-06-30

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

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

    SciTech Connect (OSTI)

    Not Available

    1993-03-02

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

  10. Delivering Energy Efficiency to Middle Income Single Family Households

    SciTech Connect (OSTI)

    none,

    2011-12-01

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

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

    SciTech Connect (OSTI)

    Hoffman, W.L.

    1982-12-01

    A general assessment of the range of barriers which impede household investments in weatherization and other energy efficiency improvements for their homes is provided. The relationship of similar factors to households' interest in receiving a free energy audits examined. Rates of return that underly household investments in major conservation improvements are assessed. A special analysis of household knowledge of economically attractive investments is provided that compares high payback improvements specified by the energy audit with the list of needed or desirable conservation improvements identified by respondents. (LEW)

  12. " Million U.S. Housing Units" ,,"2005 Household...

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

    8 Water Heating Characteristics by Household Income, 2005" " Million U.S. Housing Units" ... to 79,999","80,000 or More" "Water Heating Characteristics" ...

  13. RECS Propane Usage Form_v1 (Draft).xps

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

    Type of Fuel Sold was: PPropane BButane OOther Enter the Price per Unit of Measure XXX.XX X.XX (select one) P B O MMDDYY Page 1 of ...

  14. EERE Program Management Initiative (PMI) Brochure

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

    ... Program and Project Manager Performance Plans John Doe John Doe John Doe xxx-xx-xxxx EERExxxxxxxForrestalEE-xx EERE Program Management Initiative 8 December 2003 EERE Program ...

  15. The original of this document contains information which is subject...

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

    ... EPSs affected by the EPS Final Rule are in XXX XXXXXXXX XX XXXXX, XXXXX XXXXX, XXXXXXXX, ... products, Tektronix requests an additional XXX XX months to come into compliance with the ...

  16. DOE Acquisition Guide ...

    Energy Savers [EERE]

    ... handling of employee morale problems, etc. Planning: Adequate, quality, innovative, ... date Complete the 20XX Biennial Emergency Management Exercise. Ref: ...

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

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

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

    2015-04-20

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

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

    SciTech Connect (OSTI)

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

    2015-04-20

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

  19. Reconstructing householder vectors from Tall-Skinny QR

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

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

    2015-08-05

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

  20. Reconstructing householder vectors from Tall-Skinny QR

    SciTech Connect (OSTI)

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

    2015-08-05

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

  1. Projecting household energy consumption within a conditional demand framework

    SciTech Connect (OSTI)

    Teotia, A.; Poyer, D.

    1991-01-01

    Few models attempt to assess and project household energy consumption and expenditure by taking into account differential household choices correlated with such variables as race, ethnicity, income, and geographic location. The Minority Energy Assessment Model (MEAM), developed by Argonne National Laboratory (ANL) for the US Department of Energy (DOE), provides a framework to forecast the energy consumption and expenditure of majority, black, Hispanic, poor, and nonpoor households. Among other variables, household energy demand for each of these population groups in MEAM is affected by housing factors (such as home age, home ownership, home type, type of heating fuel, and installed central air conditioning unit), demographic factors (such as household members and urban/rural location), and climate factors (such as heating degree days and cooling degree days). The welfare implications of the revealed consumption patterns by households are also forecast. The paper provides an overview of the model methodology and its application in projecting household energy consumption under alternative energy scenarios developed by Data Resources, Inc., (DRI).

  2. Projecting household energy consumption within a conditional demand framework

    SciTech Connect (OSTI)

    Teotia, A.; Poyer, D.

    1991-12-31

    Few models attempt to assess and project household energy consumption and expenditure by taking into account differential household choices correlated with such variables as race, ethnicity, income, and geographic location. The Minority Energy Assessment Model (MEAM), developed by Argonne National Laboratory (ANL) for the US Department of Energy (DOE), provides a framework to forecast the energy consumption and expenditure of majority, black, Hispanic, poor, and nonpoor households. Among other variables, household energy demand for each of these population groups in MEAM is affected by housing factors (such as home age, home ownership, home type, type of heating fuel, and installed central air conditioning unit), demographic factors (such as household members and urban/rural location), and climate factors (such as heating degree days and cooling degree days). The welfare implications of the revealed consumption patterns by households are also forecast. The paper provides an overview of the model methodology and its application in projecting household energy consumption under alternative energy scenarios developed by Data Resources, Inc., (DRI).

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

  9. Transferring 2001 National Household Travel Survey

    SciTech Connect (OSTI)

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

    2007-05-01

    Policy makers rely on transportation statistics, including data on personal travel behavior, to formulate strategic transportation policies, and to improve the safety and efficiency of the U.S. transportation system. Data on personal travel trends are needed to examine the reliability, efficiency, capacity, and flexibility of the Nation's transportation system to meet current demands and to accommodate future demand. These data are also needed to assess the feasibility and efficiency of alternative congestion-mitigating technologies (e.g., high-speed rail, magnetically levitated trains, and intelligent vehicle and highway systems); to evaluate the merits of alternative transportation investment programs; and to assess the energy-use and air-quality impacts of various policies. To address these data needs, the U.S. Department of Transportation (USDOT) initiated an effort in 1969 to collect detailed data on personal travel. The 1969 survey was the first Nationwide Personal Transportation Survey (NPTS). The survey was conducted again in 1977, 1983, 1990, 1995, and 2001. Data on daily travel were collected in 1969, 1977, 1983, 1990 and 1995. In 2001, the survey was renamed the National Household Travel Survey (NHTS) and it collected both daily and long-distance trips. The 2001 survey was sponsored by three USDOT agencies: Federal Highway Administration (FHWA), Bureau of Transportation Statistics (BTS), and National Highway Traffic Safety Administration (NHTSA). The primary objective of the survey was to collect trip-based data on the nature and characteristics of personal travel so that the relationships between the characteristics of personal travel and the demographics of the traveler can be established. Commercial and institutional travel were not part of the survey. Due to the survey's design, data in the NHTS survey series were not recommended for estimating travel statistics for categories smaller than the combination of Census division (e.g., New England, Middle

  10. Ventilation Behavior and Household Characteristics in NewCalifornia Houses

    SciTech Connect (OSTI)

    Price, Phillip N.; Sherman, Max H.

    2006-02-01

    A survey was conducted to determine occupant use of windows and mechanical ventilation devices; barriers that inhibit their use; satisfaction with indoor air quality (IAQ); and the relationship between these factors. A questionnaire was mailed to a stratified random sample of 4,972 single-family detached homes built in 2003, and 1,448 responses were received. A convenience sample of 230 houses known to have mechanical ventilation systems resulted in another 67 completed interviews. Some results are: (1) Many houses are under-ventilated: depending on season, only 10-50% of houses meet the standard recommendation of 0.35 air changes per hour. (2) Local exhaust fans are under-utilized. For instance, about 30% of households rarely or never use their bathroom fan. (3) More than 95% of households report that indoor air quality is ''very'' or ''somewhat'' acceptable, although about 1/3 of households also report dustiness, dry air, or stagnant or humid air. (4) Except households where people cook several hours per week, there is no evidence that households with significant indoor pollutant sources get more ventilation. (5) Except households containing asthmatics, there is no evidence that health issues motivate ventilation behavior. (6) Security and energy saving are the two main reasons people close windows or keep them closed.

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

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

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

  12. Modeling patterns of hot water use in households

    SciTech Connect (OSTI)

    Lutz, J.D.; Liu, Xiaomin; McMahon, J.E.

    1996-11-01

    This report presents a detailed model of hot water use patterns in individual household. The model improves upon an existing model by including the effects of four conditions that were previously unaccounted for: the absence of a clothes washer; the absence of a dishwasher; a household consisting of seniors only; and a household that does not pay for its own hot water use. Although these four conditions can significantly affect residential hot water use, and have been noted in other studies, this is the first time that they have been incorporated into a detailed model. This model allows detailed evaluation of the impact of potential efficiency standards for water heaters and other market transformation policies. 21 refs., 3 figs., 10 tabs.

  13. Modeling patterns of hot water use in households

    SciTech Connect (OSTI)

    Lutz, James D.; Liu, Xiaomin; McMahon, James E.; Dunham, Camilla; Shown, Leslie J.; McCure, Quandra T.

    1996-01-01

    This report presents a detailed model of hot water use patterns in individual households. The model improves upon an existing model by including the effects of four conditions that were previously unaccounted for: the absence of a clothes washer; the absence of a dishwasher; a household consisting of seniors only; and a household that does not pay for its own hot water use. Although these four conditions can significantly affect residential hot water use, and have been noted in other studies, this is the first time that they have been incorporated into a detailed model. This model allows detailed evaluation of the impact of potential efficiency standards for water heaters and other market transformation policies.

  14. A Glance at China’s Household Consumption

    SciTech Connect (OSTI)

    Shui, Bin

    2009-10-01

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

  15. Shared Solar Projects Powering Households Throughout America | Department

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

    of Energy Shared Solar Projects Powering Households Throughout America Shared Solar Projects Powering Households Throughout America January 31, 2014 - 2:30pm Addthis Shared solar projects allow consumers to take advantage of solar energy’s myriad benefits, even though the system is not located on the consumer’s own rooftop. | Photo courtesy of the Vote Solar Initiative Shared solar projects allow consumers to take advantage of solar energy's myriad benefits, even though the system

  16. New York Household Travel Patterns: A Comparison Analysis

    SciTech Connect (OSTI)

    Hu, Patricia S; Reuscher, Tim

    2007-05-01

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

  17. Household heating bills expected to be lower this winter

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

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

  18. Heating oil and propane households bills to be lower this winter...

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

    Heating oil and propane households bills to be lower this winter despite recent cold spell Despite the recent cold weather, households that use heating oil or propane as their main ...

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

    Gasoline and Diesel Fuel Update (EIA)

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

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

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

    More Vehicles | Department of Energy 7: May 14, 2012 Nearly Twenty Percent of Households Own Three or More Vehicles Fact #727: May 14, 2012 Nearly Twenty Percent of Households Own Three or More Vehicles Household vehicle ownership has changed over the last six decades. In 1960, over twenty percent of households did not own a vehicle, but by 2010, that number fell to less than 10%. The number of households with three or more vehicles grew from 2% in 1960 to nearly 20% in 2010. Before 1990,

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

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

    Department of Energy 9: May 28, 2012 Secondary Household Vehicles Travel Fewer Miles Fact #729: May 28, 2012 Secondary Household Vehicles Travel Fewer Miles When a household has more than one vehicle, the secondary vehicles travel fewer miles than the primary vehicle. In a two-vehicle household, the second vehicle travels less than half of the miles that the primary vehicle travels in a day. In a six-vehicle household, the sixth vehicle travels fewer than five miles a day. Daily Vehicle

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

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

    Energy Programs for Low- and Moderate-Income Households Loan Programs for Low- and Moderate-Income Households Better Buildings Residential Network Multifamily and Low-Income Housing Peer Exchange Call Series: Loan Programs for Low- and Moderate-Income Households, March 13, 2014. Call Slides and Discussion Summary (919.64 KB) More Documents & Publications EcoHouse Program Overview Strengthening Relationships Between Energy Programs and Housing Programs Targeted Marketing and Program

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

    Reports and Publications (EIA)

    2004-01-01

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

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

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

    Energy 4: March 15, 2010 Average Age of Household Vehicles Fact #614: March 15, 2010 Average Age of Household Vehicles The average age of household vehicles has increased from 6.6 years in 1977 to 9.2 years in 2009. Pickup trucks have the oldest average age in every year listed. Sport utility vehicles (SUVs), first reported in the 1995 survey, have the youngest average age. Average Vehicle Age by Vehicle Type Graph showing the average vehicle age by type (car, van, pickup, SUV, all household

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

    SciTech Connect (OSTI)

    none,

    2012-09-20

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

  6. TO: INGRID KOLB

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

    (NOTE: Per Office of the Executive Secretariat procedures, please use Calibri, 12 point font for this action memorandum) TO: INGRID KOLB DIRECTOR OFFICE OF MANAGEMENT FROM: SECRETARIAL OFFICER'S NAME TITLE SUBJECT: DIRECTIVES CERTIFICATION STATEMENT DOE (number, title, dated xx-xx-xx) has been reviewed by my organization and deemed to be in compliance with related Departmental Directives, Secretarial Delegations, organizational structure, budget guidelines, regulations, standards, OMB guidance,

  7. Guide Title

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

    DOE G XXX.X-X xx-xx-20XX Guide Title [This Guide describes acceptable, but not mandatory means for complying with requirements. Guides are not requirements documents and are not to be construed as requirements in any audit or appraisal for compliance with associated rule or directives.] U.S. Department of Energy Office of Primary Interest FOREWORD (optional) THE FOREWORD SHOULD DESCRIBE THE DOE REQUIREMENTS, DIRECTIVES, OR RULES THAT MAY BE SATISFIED BY IMPLEMENTING THIS GUIDE. CONTENTS

  8. A material flow analysis on current electrical and electronic waste disposal from Hong Kong households

    SciTech Connect (OSTI)

    Lau, Winifred Ka-Yan; Chung, Shan-Shan; Zhang, Chan

    2013-03-15

    Highlights: ► Most household TWARC waste is sold directly to private e-waste collectors in HK. ► The current e-waste recycling network is popular with HK households. ► About 80% of household generated TWARC is exported overseas each year. ► Over 7000 tonnes/yr of household generated TWARC reach landfills. ► It is necessary to upgrade safety and awareness in HK’s e-waste recycling industry. - Abstract: A material flow study on five types of household electrical and electronic equipment, namely television, washing machine, air conditioner, refrigerator and personal computer (TWARC) was conducted to assist the Government of Hong Kong to establish an e-waste take-back system. This study is the first systematic attempt on identifying key TWARC waste disposal outlets and trade practices of key parties involved in Hong Kong. Results from two questionnaire surveys, on local households and private e-waste traders, were used to establish the material flow of household TWARC waste. The study revealed that the majority of obsolete TWARC were sold by households to private e-waste collectors and that the current e-waste collection network is efficient and popular with local households. However, about 65,000 tonnes/yr or 80% of household generated TWARC waste are being exported overseas by private e-waste traders, with some believed to be imported into developing countries where crude recycling methods are practiced. Should Hong Kong establish a formal recycling network with tight regulatory control on imports and exports, the potential risks of current e-waste recycling practices on e-waste recycling workers, local residents and the environment can be greatly reduced.

  9. No.","Financial and Activity Report (sheet 1 of 2) Version 1...

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

    Department of Defense--Military","(005-08) Department of Agriculture: ... ","(007-XX) Department of Defense--Military","(12-3504 2010 2011) Special ...

  10. No.","Financial and Activity Report (sheet 1 of 2) Version 1...

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

    Department of Defense--Military","(005-08) Department of Agriculture: ... ","(007-XX) Department of Defense--Military","(12-3540 2009 2010) State Child ...

  11. FEMP ESPC Project Development Resource Guide

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

    ... TO: All DOE ESPC IDIQ Contract Holders DATE: XX FROM: Contracting Officer Agency Contact Info SUBJECT: Notice of Opportunity (NOO) for Energy Savings Performance Contract (ESPC) ...

  12. Sample Contract Language for Construction Using Energy-Efficient...

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

    ... Method of Assessment - Random Sampling. (3) Performance Threshold - Up to 100 compliance, assuming life cycle cost efficient. Section H - Special Contract Requirements H-xx. ...

  13. Notice of Intent to Issue DOE N 314.1, DOE-Flex: DOE's Telework Program while Developing a Successor Order (5-6-11)

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

    2011-05-06

    This is to develop DOE N 3XX, which will establish the requirements and responsibilities for the Department's telework/flexiplace program.

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

    SciTech Connect (OSTI)

    Schreckengost, R.L.

    1985-01-01

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

  15. Laboratory Testing of Demand-Response Enabled Household Appliances

    SciTech Connect (OSTI)

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

    2013-10-01

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

  16. Laboratory Testing of Demand-Response Enabled Household Appliances

    SciTech Connect (OSTI)

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

    2013-10-01

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

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

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

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

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

    Broader source: Energy.gov [DOE]

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

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

    Broader source: Energy.gov [DOE]

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

  20. Table 2.5 Household Energy Consumption and Expenditures by End...

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

    5 Household 1 Energy Consumption and Expenditures by End Use, Selected Years, 1978-2005 Year Space ... 3 Fuel Oil 4 LPG 5 Total Electricity 3 Natural Gas Elec- tricity 3 ...

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

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

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

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

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

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

  3. A Mixed Nordic Experience: Implementing Competitive Retail Electricity Markets for Household Customers

    SciTech Connect (OSTI)

    Olsen, Ole Jess; Johnsen, Tor Arnt; Lewis, Philip

    2006-11-15

    Although the Nordic countries were among the first to develop competition in the electricity industry, it took a long time to make retail competition work. In Norway and Sweden a considerable number of households are actively using the market but very few households are active in Finland and Denmark. One problem has been institutional barriers involving metering, limited unbundling of distribution and supply, and limited access to reliable information on contracts and prices. (author)

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

    SciTech Connect (OSTI)

    Brian C. O'Neill

    2006-08-09

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

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

    SciTech Connect (OSTI)

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

    2005-05-31

    Residential household space heating energy use comprises close to half of all residential energy consumption. Currently, average space heating use by household is 43.9 Mbtu for a year. An average, however, does not reflect regional variation in heating practices, energy costs, or fuel type. Indeed, a national average does not capture regional or consumer group cost impacts from changing efficiency levels of heating equipment. The US Department of Energy sets energy standards for residential appliances in, what is called, a rulemaking process. The residential furnace and boiler efficiency rulemaking process investigates the costs and benefits of possible updates to the current minimum efficiency regulations. Lawrence Berkeley National Laboratory (LBNL) selected the sample used in the residential furnace and boiler efficiency rulemaking from publically available data representing United States residences. The sample represents 107 million households in the country. The data sample provides the household energy consumption and energy price inputs to the life-cycle cost analysis segment of the furnace and boiler rulemaking. This paper describes the choice of criteria to select the sample of houses used in the rulemaking process. The process of data extraction is detailed in the appendices and is easily duplicated. The life-cycle cost is calculated in two ways with a household marginal energy price and a national average energy price. The LCC results show that using an national average energy price produces higher LCC savings but does not reflect regional differences in energy price.

  6. InGaN Quantum Dot Fabrication using Quantum Size Controlled Photoelect...

    Office of Scientific and Technical Information (OSTI)

    X1 X-X" X-* X-* X- - -X-X XJ x-S' X- - -.* x- X-J* X- - -< X- -X- X- - X- -J- X- (tm) ' X-- - xjr x- - -X X-A * XJ x- - -.* X-X-X X---I* X-J* X->* X- X- - - ...

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

    SciTech Connect (OSTI)

    Figueroa, M.J.; Sathaye, J.

    1993-08-01

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

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

    SciTech Connect (OSTI)

    Zimring, Mark; Fuller, Merrian

    2011-01-24

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

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

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

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

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

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

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

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

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

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

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

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

    Drivers of U.S. Household Energy Consumption, 1980-2009 February 2015 Independent Statistics & Analysis www.eia.gov U.S. Department of Energy Washington, DC 20585 U.S. Energy Information Administration | Drivers of U.S. Household Energy Consumption, 1980-2009 i This report was prepared by the U.S. Energy Information Administration (EIA), the statistical and analytical agency within the U.S. Department of Energy. By law, EIA's data, analyses, and forecasts are independent of approval by any

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

    SciTech Connect (OSTI)

    Siler, A.

    1980-05-01

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

  14. A Multi Agent-Based Framework for Simulating Household PHEV Distribution and Electric Distribution Network Impact

    SciTech Connect (OSTI)

    Cui, Xiaohui; Liu, Cheng; Kim, Hoe Kyoung; Kao, Shih-Chieh; Tuttle, Mark A; Bhaduri, Budhendra L

    2011-01-01

    The variation of household attributes such as income, travel distance, age, household member, and education for different residential areas may generate different market penetration rates for plug-in hybrid electric vehicle (PHEV). Residential areas with higher PHEV ownership could increase peak electric demand locally and require utilities to upgrade the electric distribution infrastructure even though the capacity of the regional power grid is under-utilized. Estimating the future PHEV ownership distribution at the residential household level can help us understand the impact of PHEV fleet on power line congestion, transformer overload and other unforeseen problems at the local residential distribution network level. It can also help utilities manage the timing of recharging demand to maximize load factors and utilization of existing distribution resources. This paper presents a multi agent-based simulation framework for 1) modeling spatial distribution of PHEV ownership at local residential household level, 2) discovering PHEV hot zones where PHEV ownership may quickly increase in the near future, and 3) estimating the impacts of the increasing PHEV ownership on the local electric distribution network with different charging strategies. In this paper, we use Knox County, TN as a case study to show the simulation results of the agent-based model (ABM) framework. However, the framework can be easily applied to other local areas in the US.

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

    SciTech Connect (OSTI)

    Letschert, Virginie; McNeil, Michael A.

    2009-03-23

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

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

    SciTech Connect (OSTI)

    Lin, Jiang

    2006-07-10

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

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

    SciTech Connect (OSTI)

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

    2015-01-15

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

  18. Table 2.6 Household End Uses: Fuel Types, Appliances, and Electronics, Selected Years, 1978-2009

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

    6 Household End Uses: Fuel Types, Appliances, and Electronics, Selected Years, 1978-2009 Appliance Year Change 1978 1979 1980 1981 1982 1984 1987 1990 1993 1997 2001 2005 2009 1980 to 2009 Total Households (millions) 77 78 82 83 84 86 91 94 97 101 107 111 114 32 Percent of Households<//td> Space Heating - Main Fuel 1 Natural Gas 55 55 55 56 57 55 55 55 53 52 55 52 50 -5 Electricity 2 16 17 18 17 16 17 20 23 26 29 29 30 35 17 Liquefied Petroleum Gases 4 5 5 4 5 5 5 5 5 5 5 5 5 0 Distillate

  19. Characterization of household hazardous waste from Marin County, California, and New Orleans, Louisiana

    SciTech Connect (OSTI)

    Rathje, W.L.; Wilson, D.C.; Lambou, V.W.; Herndon, R.C.

    1987-09-01

    There is a growing concern that certain constituents of common household products, that are discarded in residential garbage, may be potentially harmful to human health and the environment by adversely affecting the quality of ground and surface water. A survey of hazardous wastes in residential garbage from Marin County, California, and New Orleans, Louisiana, was conducted in order to determine the amount and characteristics of such wastes that are entering municipal landfills. The results of the survey indicate that approximately 642 metric tons of hazardous waste are discarded per year for the New Orleans study area and approximately 259 metric tons are discarded per year for the Marin County study area. Even though the percent of hazardous household waste in the garbage discarded in both study areas was less than 1%, it represents a significant quantity of hazardous waste because of the large volume of garbage involved.

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

    SciTech Connect (OSTI)

    Streets, D.G.; Aunan, K.

    2005-06-30

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

  1. Evaluation of bulk paint worker exposure to solvents at household hazardous waste collection events

    SciTech Connect (OSTI)

    Cameron, M.

    1995-09-01

    In fiscal year 93/94, over 250 governmental agencies were involved in the collection of household hazardous wastes in the State of California. During that time, over 3,237,000 lbs. of oil based paint were collected in 9,640 drums. Most of this was in lab pack drums, which can only hold up to 20 one gallon cans. Cost for disposal of such drums is approximately $1000. In contrast, during the same year, 1,228,000 lbs. of flammable liquid were collected in 2,098 drums in bulk form. Incineration of bulked flammable liquids is approximately $135 per drum. Clearly, it is most cost effective to bulk flammable liquids at household hazardous waste events. Currently, this is the procedure used at most Temporary Household Hazardous Waste Collection Facilities (THHWCFs). THHWCFs are regulated by the Department of Toxic Substances Control (DTSC) under the new Permit-by Rule Regulations. These regulations specify certain requirements regarding traffic flow, emergency response notifications and prevention of exposure to the public. The regulations require that THHWCF operators bulk wastes only when the public is not present. [22 CCR, section 67450.4 (e) (2) (A)].Santa Clara County Environmental Health Department sponsors local THHWCF`s and does it`s own bulking. In order to save time and money, a variance from the regulation was requested and an employee monitoring program was initiated to determine actual exposure to workers. Results are presented.

  2. Identification of influencing municipal characteristics regarding household waste generation and their forecasting ability in Biscay

    SciTech Connect (OSTI)

    Oribe-Garcia, Iraia Kamara-Esteban, Oihane; Martin, Cristina; Macarulla-Arenaza, Ana M.; Alonso-Vicario, Ainhoa

    2015-05-15

    Highlights: • We have modelled household waste generation in Biscay municipalities. • We have identified relevant characteristics regarding household waste generation. • Factor models are used in order to identify the best subset of explicative variables. • Biscay’s municipalities are grouped by means of hierarchical clustering. - Abstract: The planning of waste management strategies needs tools to support decisions at all stages of the process. Accurate quantification of the waste to be generated is essential for both the daily management (short-term) and proper design of facilities (long-term). Designing without rigorous knowledge may have serious economic and environmental consequences. The present works aims at identifying relevant socio-economic features of municipalities regarding Household Waste (HW) generation by means of factor models. Factor models face two main drawbacks, data collection and identifying relevant explanatory variables within a heterogeneous group. Grouping similar characteristics observations within a group may favour the deduction of more robust models. The methodology followed has been tested with Biscay Province because it stands out for having very different municipalities ranging from very rural to urban ones. Two main models are developed, one for the overall province and a second one after clustering the municipalities. The results prove that relating municipalities with specific characteristics, improves the results in a very heterogeneous situation. The methodology has identified urban morphology, tourism activity, level of education and economic situation as the most influencing characteristics in HW generation.

  3. Household`s choices of efficiency levels for appliances: Using stated- and revealed-preference data to identify the importance of rebates and financing arrangements

    SciTech Connect (OSTI)

    Train, K.; Atherton, T.

    1994-11-01

    We examine customers` choice between standard and high-efficiency equipment, and the impact of utility incentives such as rebates and loans on this decision. Using data from interviews with 400 households, we identify the factors that customers consider in their choice of efficiency level for appliances and the relative importance of these factors. We build a model that describes customers` choices and can be used to predict choices in future situations under changes in the attributes of appliances and in the utility`s DSM and as part of the appliance-choice component of utilities` end-use forecasting systems. As examples, the model is used to predict the impacts of: doubling the size of rebates, replacing rebates with financing programs, and offering loans and rebates as alternative options for customers.

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

    SciTech Connect (OSTI)

    Eisenberg, Joel Fred

    2008-06-01

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

  5. Assessment of lead contamination in Bahrain environment. I. Analysis of household paint

    SciTech Connect (OSTI)

    Madany, I.M.; Ali, S.M.; Akhter, M.S.

    1987-01-01

    The analysis of lead in household paint collected from various old buildings in Bahrain is reported. The atomic absorption spectrophotometric method, both flame and flameless (graphite furnace) techniques, were used for the analysis. The concentrations of lead in paint were found in the range 200 to 5700 mg/kg, which are low compared to the limit of 0.5% in UK and 0.06% in USA. Nevertheless, these are hazardous. Recommendations are reported in order to avoid paint containing lead. 17 references, 1 table.

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

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

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

  7. Table HC6.11 Home Electronics Characteristics by Number of Household Members, 2005

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

    1 Home Electronics Characteristics by Number of Household Members, 2005 Total...................................................................... 111.1 30.0 34.8 18.4 15.9 12.0 Personal Computers Do Not Use a Personal Computer ................... 35.5 16.3 9.4 4.0 2.7 3.2 Use a Personal Computer................................ 75.6 13.8 25.4 14.4 13.2 8.8 Number of Desktop PCs 1.................................................................. 50.3 11.9 17.4 8.5 7.3 5.2

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

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

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

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

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

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

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

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

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

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

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

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

  12. WEEE and portable batteries in residual household waste: Quantification and characterisation of misplaced waste

    SciTech Connect (OSTI)

    Bigum, Marianne; Petersen, Claus; Scheutz, Charlotte

    2013-11-15

    Highlights: • We analyse 26.1 Mg of residual waste from 3129 Danish households. • We quantify and characterise misplaced WEEE and portable batteries. • We compare misplaced WEEE and batteries to collection through dedicated schemes. • Characterisation showed that primarily small WEEE and light sources are misplaced. • Significant amounts of misplaced batteries were discarded as built-in WEEE. - Abstract: A total of 26.1 Mg of residual waste from 3129 households in 12 Danish municipalities was analysed and revealed that 89.6 kg of Waste Electrical and Electronic Equipment (WEEE), 11 kg of batteries, 2.2 kg of toners and 16 kg of cables had been wrongfully discarded. This corresponds to a Danish household discarding 29 g of WEEE (7 items per year), 4 g of batteries (9 batteries per year), 1 g of toners and 7 g of unidentifiable cables on average per week, constituting 0.34% (w/w), 0.04% (w/w), 0.01% (w/w) and 0.09% (w/w), respectively, of residual waste. The study also found that misplaced WEEE and batteries in the residual waste constituted 16% and 39%, respectively, of what is being collected properly through the dedicated special waste collection schemes. This shows that a large amount of batteries are being discarded with the residual waste, whereas WEEE seems to be collected relatively successfully through the dedicated special waste collection schemes. Characterisation of the misplaced batteries showed that 20% (w/w) of the discarded batteries were discarded as part of WEEE (built-in). Primarily alkaline batteries, carbon zinc batteries and alkaline button cell batteries were found to be discarded with the residual household waste. Characterisation of WEEE showed that primarily small WEEE (WEEE directive categories 2, 5a, 6, 7 and 9) and light sources (WEEE directive category 5b) were misplaced. Electric tooth brushes, watches, clocks, headphones, flashlights, bicycle lights, and cables were items most frequently found. It is recommended that these

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

    SciTech Connect (OSTI)

    Dolealov, Markta; Beneov, Libue; Zvodsk, Anita

    2013-09-15

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

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

    SciTech Connect (OSTI)

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

    2014-01-01

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

  15. Recovery and separation of high-value plastics from discarded household appliances

    SciTech Connect (OSTI)

    Karvelas, D.E.; Jody, B.J.; Poykala, J.A. Jr.; Daniels, E.J.; Arman, B. |

    1996-03-01

    Argonne National Laboratory is conducting research to develop a cost- effective and environmentally acceptable process for the separation of high-value plastics from discarded household appliances. The process under development has separated individual high purity (greater than 99.5%) acrylonitrile-butadiene-styrene (ABS) and high- impact polystyrene (HIPS) from commingled plastics generated by appliance-shredding and metal-recovery operations. The process consists of size-reduction steps for the commingled plastics, followed by a series of gravity-separation techniques to separate plastic materials of different densities. Individual plastics of similar densities, such as ABS and HIPS, are further separated by using a chemical solution. By controlling the surface tension, the density, and the temperature of the chemical solution we are able to selectively float/separate plastics that have different surface energies. This separation technique has proven to be highly effective in recovering high-purity plastics materials from discarded household appliances. A conceptual design of a continuous process to recover high-value plastics from discarded appliances is also discussed. In addition to plastics separation research, Argonne National Laboratory is conducting research to develop cost-effective techniques for improving the mechanical properties of plastics recovered from appliances.

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

    SciTech Connect (OSTI)

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

    2015-10-01

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

  17. An Analysis of the Price Elasticity of Demand for Household Appliances

    SciTech Connect (OSTI)

    Fujita, Kimberly; Dale, Larry; Fujita, K. Sydny

    2008-01-25

    This report summarizes our study of the price elasticity of demand for home appliances, including refrigerators, clothes washers, and dishwashers. In the context of increasingly stringent appliance standards, we are interested in what kind of impact the increased manufacturing costs caused by higher efficiency requirements will have on appliance sales. We begin with a review of existing economics literature describing the impact of economic variables on the sale of durable goods.We then describe the market for home appliances and changes in this market over the past 20 years, performing regression analysis on the shipments of home appliances and relevant economic variables including changes to operating cost and household income. Based on our analysis, we conclude that the demand for home appliances is price inelastic.

  18. Table HC6.4 Space Heating Characteristics by Number of Household Members, 2005

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

    4 Space Heating Characteristics by Number of Household Members, 2005 Total..................................................................... 111.1 30.0 34.8 18.4 15.9 12.0 Do Not Have Space Heating Equipment............ 1.2 0.3 0.3 Q 0.2 0.2 Have Main Space Heating Equipment............... 109.8 29.7 34.5 18.2 15.6 11.8 Use Main Space Heating Equipment................. 109.1 29.5 34.4 18.1 15.5 11.6 Have Equipment But Do Not Use It................... 0.8 Q Q Q Q Q Main Heating Fuel and

  19. Table HC6.5 Space Heating Usage Indicators by Number of Household Members, 2005

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

    5 Space Heating Usage Indicators by Number of Household Members, 2005 Total U.S. Housing Units.................................. 111.1 30.0 34.8 18.4 15.9 12.0 Do Not Have Heating Equipment..................... 1.2 0.3 0.3 Q 0.2 0.2 Have Space Heating Equipment....................... 109.8 29.7 34.5 18.2 15.6 11.8 Use Space Heating Equipment........................ 109.1 29.5 34.4 18.1 15.5 11.6 Have But Do Not Use Equipment.................... 0.8 Q Q Q Q Q Space Heating Usage During 2005

  20. Particle and gas emissions from a simulated coal-burning household fire pit

    SciTech Connect (OSTI)

    Linwei Tian; Donald Lucas; Susan L. Fischer; S. C. Lee; S. Katharine Hammond; Catherine P. Koshland

    2008-04-01

    An open fire was assembled with firebricks to simulate the household fire pit used in rural China, and 15 different coals from this area were burned to measure the gaseous and particulate emissions. Particle size distribution was studied with a microorifice uniform-deposit impactor (MOUDI). Over 90% of the particulate mass was attributed to sub-micrometer particles. The carbon balance method was used to calculate the emission factors. Emission factors for four pollutants (particulate matter, CO{sub 2}, total hydrocarbons, and NOx) were 2-4 times higher for bituminous coals than for anthracites. In past inventories of carbonaceous emissions used for climate modeling, these two types of coal were not treated separately. The dramatic emission factor difference between the two types of coal warrants attention in the future development of emission inventories. 25 refs., 8 figs., 1 tab.

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

    SciTech Connect (OSTI)

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

    1987-05-01

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

  2. A Green Approach to SNF Reprocessing: Are Common Household Reagents the Answer?

    SciTech Connect (OSTI)

    Peper, Shane M.; McNamara, Bruce K.; O'Hara, Matthew J.; Douglas, Matthew

    2008-04-03

    It has been discovered that UO2, the principal component of spent nuclear fuel (SNF), can efficiently be dissolved at room temperature using a combination of common household reagents, namely hydrogen peroxide, baking soda, and ammonia. This rather serendipitous discovery opens up the possibility, for the first time, of considering a non-acidic process for recycling U from SNF. Albeit at the early stages of development, our unconventional dissolution approach possesses many attractive features that could make it a reality in the future. With dissolution byproducts of water and oxygen, our approach poses a minimal threat to the environment. Moreover, the use of common household reagents to afford actinide oxide dissolution suggests a certain degree of economic favorability. With the use of a “closed” digestion vessel as a reaction chamber, our approach has substantial versatility with the option of using either aqueous or gaseous reactant feeds or a combination of both. Our approach distinguishes itself from all existing reprocessing technologies in two important ways. First and foremost, it is an alkaline rather than an acidic process, using mild non-corrosive chemicals under ambient conditions to effect actinide separations. Secondly, it does not dissolve the entire SNF matrix, but rather selectively solubilizes U and other light actinides for subsequent separation, resulting in potentially faster head-end dissolution and fewer downstream separation steps. From a safeguards perspective, the use of oxidizing alkaline solutions to effect actinide separations also potentially offers a degree of inherent proliferation resistance, by allowing the U to be selectively removed from the remaining dissolver solution while keeping Pu grouped with the other minor actinides and fission products. This paper will describe the design and general experimental setup of a “closed” digestion vessel for performing uranium oxide dissolutions under alkaline conditions using

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

    SciTech Connect (OSTI)

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

    1992-10-01

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

  4. Metal to Insulator Transition on the N = 0 Landau Level in Graphene

    SciTech Connect (OSTI)

    Zhang, L.; Zhang, Y.; Khodas, M.; Valla, T.; Zaliznyak, I.A.

    2010-07-23

    The magnetotransport in single layer graphene has been experimentally investigated in magnetic fields up to 18 T as a function of temperature. A pronounced T dependence is observed for T {approx}< 50 K, which is either metallic, or insulating, depending on the filling factor {nu}. The metal-insulator transition (MIT) occurs at |{nu}{sub c}| {approx}0.65 and in the regime of the dissipative transport, where the longitudinal resistance R{sub xx} >1/2R{sub K}. The critical resistivity (R{sub xx} per square) is {rho}{sub xx}({nu}{sub c}) {approx} 1/2R{sub K} and is correlated with the appearance of zero plateau in Hall conductivity {sigma}{sub xy}({nu}) and peaks in {sigma}{sub xx}({nu}). This leads us to construct a universal low-T (n, B) phase diagram of this quantum phase transition.

  5. Slide 1

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

    XX7 - - - - - 30 (30) 228 February Summary 120 75 195 10 185 50 135 Contract Budget Base (CBB) Log Page 4 Undistributed Budget Parameters * Should be distributed within two...

  6. MAPPER - Sheet1

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

    .13 204.66 RSF - DRAWN OF INCHES mm mm IN REV D 1 INITIAL ISSUE x x.xxx x.xx SIDNEY W. BARNES RESEARCH LABORATORY DESCRIPTION DATE ZONE 11 - .0005 .013 DEPT. OF...

  7. Clearance of Real and Personal Property Under New DOE Radiation...

    Office of Environmental Management (EM)

    ... limits * Pre-approved limits included are: -radium-226 (or thorium 230) soil concentrations -radium 228 (or thorium-232) soil concentrations -surface guidelines in G 441.1-xx ...

  8. NREL Technology Partnership Participant Data Sheet

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

    by MRINREL, foreign nationals? If so, please provide the country of citizenship and immigration status (Green Card, H1B, F1Visa or etc.) of each foreign national. F12XX-E(012006)...

  9. Notification of Planned 230kV Outage at Potomac River Generating...

    Energy Savers [EERE]

    Subject: Notification of Planned 230kV Outage at Potomac River Generating Station To ... The next planned outage on 23106 high voltage circuit between xxxxxxx xx xxxx and ...

  10. DEACTIVATION COMPLETION AND TURNOVER Deactivation Completion...

    Office of Environmental Management (EM)

    ... records the stated condition will be placed in the space or system file folder. WP-xx-xxx Work Plans written to perform activities to support closeout of specific end-points or ...