National Library of Energy BETA

Sample records for derived estimates total

  1. Derived Annual Estimates

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

    74-1988 For Methodology Concerning the Derived Estimates Total Consumption of Offsite-Produced Energy for Heat and Power by Industry Group, 1974-1988 Total Energy *** Electricity...

  2. Total-derivative supersymmetry breaking

    SciTech Connect (OSTI)

    Haba, Naoyuki; Uekusa, Nobuhiro

    2010-05-15

    On an interval compactification in supersymmetric theory, boundary conditions for bulk fields must be treated carefully. If they are taken arbitrarily following the requirement that a theory is supersymmetric, the conditions could give redundant constraints on the theory. We construct a supersymmetric action integral on an interval by introducing brane interactions with which total-derivative terms under the supersymmetry transformation become zero due to a cancellation. The variational principle leads equations of motion and also boundary conditions for bulk fields, which determine boundary values of bulk fields. By estimating mass spectrum, spontaneous supersymmetry breaking in this simple setup can be realized in a new framework. This supersymmetry breaking does not induce a massless R axion, which is favorable for phenomenology. It is worth noting that fermions in hyper-multiplet, gauge bosons, and the fifth-dimensional component of gauge bosons can have zero-modes (while the other components are all massive as Kaluza-Klein modes), which fits the gauge-Higgs unification scenarios.

  3. Derived Annual Estimates of Manufacturing Energy Consumption...

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

    > Derived Annual Estimates - Executive Summary Derived Annual Estimates of Manufacturing Energy Consumption, 1974-1988 Figure showing Derived Estimates Executive Summary This...

  4. Cell Total Activity Final Estimate.xls

    Office of Legacy Management (LM)

    WSSRAP Cell Total Activity Final Estimate (calculated September 2002, Fleming) (Waste streams & occupied cell volumes from spreadsheet titled "cell waste volumes-8.23.02 with ...

  5. Estimation of Anisotoropy from Total Cross Section and Optical...

    Office of Scientific and Technical Information (OSTI)

    Conference: Estimation of Anisotoropy from Total Cross Section and Optical Model Citation Details In-Document Search Title: Estimation of Anisotoropy from Total Cross Section and ...

  6. Estimation of Anisotoropy from Total Cross Section and Optical Model

    Office of Scientific and Technical Information (OSTI)

    (Conference) | SciTech Connect Estimation of Anisotoropy from Total Cross Section and Optical Model Citation Details In-Document Search Title: Estimation of Anisotoropy from Total Cross Section and Optical Model Authors: Kawano, Toshihiko [1] + Show Author Affiliations Los Alamos National Laboratory Publication Date: 2013-06-03 OSTI Identifier: 1082234 Report Number(s): LA-UR-13-24025 DOE Contract Number: AC52-06NA25396 Resource Type: Conference Resource Relation: Conference: Working Party

  7. Derivative-free optimization for parameter estimation in computational...

    Office of Scientific and Technical Information (OSTI)

    Journal Article: Derivative-free optimization for parameter estimation in computational nuclear physics Citation Details ... RADIATION PHYSICS; 97 MATHEMATICS, COMPUTING, AND ...

  8. Derivative-free optimization for parameter estimation in computational...

    Office of Scientific and Technical Information (OSTI)

    nuclear physics Citation Details In-Document Search Title: Derivative-free optimization for parameter estimation in computational nuclear physics Authors: Wild, S ; ...

  9. Derived annual estimates of manufacturing energy consumption, 1974--1988

    SciTech Connect (OSTI)

    Not Available

    1992-08-05

    This report presents a complete series of annual estimates of purchased energy used by the manufacturing sector of the US economy, for the years 1974 to 1988. These estimates interpolate over gaps in the actual data collections, by deriving estimates for the missing years 1982--1984 and 1986--1987. For the purposes of this report, ``purchased`` energy is energy brought from offsite for use at manufacturing establishments, whether the energy is purchased from an energy vendor or procured from some other source. The actual data on purchased energy comes from two sources, the US Department of Commerce Bureau of the Census`s Annual Survey of Manufactures (ASM) and EIA`s Manufacturing Energy Consumption Survey (MECS). The ASM provides annual estimates for the years 1974 to 1981. However, in 1982 (and subsequent years) the scope of the ASM energy data was reduced to collect only electricity consumption and expenditures and total expenditures for other purchased energy. In 1985, EIA initiated the triennial MECS collecting complete energy data. The series equivalent to the ASM is referred to in the MECS as ``offsite-produced fuels.``

  10. Uncertainty estimates for derivatives and intercepts

    SciTech Connect (OSTI)

    Clark, E.L.

    1994-09-01

    Straight line least squares fits of experimental data are widely used in the analysis of test results to provide derivatives and intercepts. A method for evaluating the uncertainty in these parameters is described. The method utilizes conventional least squares results and is applicable to experiments where the independent variable is controlled, but not necessarily free of error. A Monte Carlo verification of the method is given.

  11. Derivative-free optimization for parameter estimation in computational

    Office of Scientific and Technical Information (OSTI)

    nuclear physics (Journal Article) | SciTech Connect Journal Article: Derivative-free optimization for parameter estimation in computational nuclear physics Citation Details In-Document Search Title: Derivative-free optimization for parameter estimation in computational nuclear physics Authors: Wild, S ; Sarich, J ; Schunck, N Publication Date: 2014-06-20 OSTI Identifier: 1177246 Report Number(s): LLNL-JRNL-656057 DOE Contract Number: DE-AC52-07NA27344 Resource Type: Journal Article Resource

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

    SciTech Connect (OSTI)

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

    2008-03-01

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

  13. Total

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

    Cell shipments Total Inventory, start-of-year 328,658 Manufactured during reporting year ... Table 5. Source and disposition of photovoltaic cell shipments, 2013 (peak kilowatts) ...

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

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

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

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

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

    14.7 7.4 12.5 12.5 18.9 18.6 17.3 9.2 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500...... 3.2 0.7 Q 0.3 0.3 0.7 0.6 0.3 Q 500 to ...

  16. Total

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

    Product: Total Crude Oil Liquefied Petroleum Gases Propane/Propylene Normal Butane/Butylene Other Liquids Oxygenates Fuel Ethanol MTBE Other Oxygenates Biomass-based Diesel Other Renewable Diesel Fuel Other Renewable Fuels Gasoline Blending Components Petroleum Products Finished Motor Gasoline Reformulated Gasoline Conventional Gasoline Kerosene-Type Jet Fuel Kerosene Distillate Fuel Oil Distillate Fuel Oil, 15 ppm Sulfur and Under Distillate Fuel Oil, Greater than 15 ppm to 500 ppm Sulfur

  17. Estimation of total cloud cover from solar radiation observations at Lake Rotorua, New Zealand

    SciTech Connect (OSTI)

    Luo, Liancong; Hamilton, David; Han, Boping

    2010-03-15

    The DYRESM-CAEDYM model is a valuable tool for simulating water temperature for biochemical studies in aquatic ecosystem. The model requires inputs of surface short-wave radiation and long-wave radiation or total cloud cover fraction (TC). Long-wave radiation is often not measured directly so a method to determine TC from commonly measured short-wave solar irradiance (E{sub 0}) and theoretical short-wave solar irradiance under a clear sky (E{sub c}) has broad application. A more than 17-year (15 November 1991 to 20 February 2009) hourly solar irradiance data set was used to estimate the peak solar irradiance for each ordinal date over one year, which was assumed to be representative of solar irradiance in the absence of cloud. Comparison between these daily observed values and the modelled clear-sky solar radiation over one year was in close agreement (Pearson correlation coefficient, r = 0.995 and root mean squared error, RMSE = 12.54 W m{sup -2}). The downloaded hourly cloudiness measurements from 15 November 1991 to 20 February 2009 was used to calculate the daily values for this period and then the calculated daily values over the 17 years were used to calculate the average values for each ordinal date over one year. A regression equation between (1 - E{sub 0}/E{sub c}) and TC produced a correlation coefficient value of 0.99 (p > 0.01, n = 71). The validation of this cloud cover estimation model was conducted with observed short-wave solar radiation and TC at two sites. Values of TC derived from the model at the Lake Rotorua site gave a reasonable prediction of the observed values (RMSE = 0.10, r = 0.86, p > 0.01, n = 61). The model was also tested at Queenstown (South Island of New Zealand) and it provided satisfactory results compared to the measurements (RMSE = 0.16, r = 0.67, p > 0.01, n = 61). Therefore the model's good performance and broad applicability will contribute to the DYRESM-CAEDYM accuracy of water temperature simulation when long-wave radiation is not available. (author)

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

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

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

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

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

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

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

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

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

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

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

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

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

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

    7.1 19.0 22.7 22.3 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 2.1 0.6 Q 0.4 500 to 999........................................................... 23.8 13.6 3.7 3.2 3.2 1,000 to 1,499..................................................... 20.8 9.5 3.7 3.4 4.2 1,500 to 1,999..................................................... 15.4 6.6 2.7 2.5 3.6 2,000 to 2,499..................................................... 12.2 5.0 2.1

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

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

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

  4. Total..........................................................

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

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

  5. Total...................................................................

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

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

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

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

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

  7. Total..........................................................................

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

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

  8. Total..........................................................................

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

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

  9. Total...........................................................

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

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

  10. Derived annual estimates of manufacturing energy consumption, 1974--1988. [Contains glossary

    SciTech Connect (OSTI)

    Not Available

    1992-08-05

    This report presents a complete series of annual estimates of purchased energy used by the manufacturing sector of the US economy, for the years 1974 to 1988. These estimates interpolate over gaps in the actual data collections, by deriving estimates for the missing years 1982--1984 and 1986--1987. For the purposes of this report, purchased'' energy is energy brought from offsite for use at manufacturing establishments, whether the energy is purchased from an energy vendor or procured from some other source. The actual data on purchased energy comes from two sources, the US Department of Commerce Bureau of the Census's Annual Survey of Manufactures (ASM) and EIA's Manufacturing Energy Consumption Survey (MECS). The ASM provides annual estimates for the years 1974 to 1981. However, in 1982 (and subsequent years) the scope of the ASM energy data was reduced to collect only electricity consumption and expenditures and total expenditures for other purchased energy. In 1985, EIA initiated the triennial MECS collecting complete energy data. The series equivalent to the ASM is referred to in the MECS as offsite-produced fuels.''

  11. Site Performance Measure Unit Lifecycle Total Estimate Pre-2016 Lifecycle Values

    Office of Environmental Management (EM)

    Management Guide Site Management Guide Site Management Guide (Blue Book) (Update 18, January 2016) PDF icon Site Management Guide (Blue Book) (Update 18, January 2016) More Documents & Publications 2014 ANNUAL SITE ENVIRONMENTAL REPORT (ASER) 2013 ANNUAL SITE ENVIRONMENTAL REPORT (ASER) 2011 Annual Site Environmental Report (ASER)

    Performance Measure Unit Lifecycle Total Estimate Pre-2016 Lifecycle Values 2016 Target 2017 Target Argonne National Laboratory-East TRU-RH Cubic meters 22 22

  12. Total Ozone Mapping Spectrometer (TOMS) Derived Data, Global Earth Coverage (GEC) from NASA's Earth Probe Satellite

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    This is data from an external datastream processed through the ARM External Data Center (XDC) at Brookhaven National Laboratory. The XDC identifies sources and acquires data, called "external data", to augment the data being generated within the ARM program. The external data acquired are usually converted from native format to either netCDF or HDF formats. The GEC collection contains global data derived from the Total Ozone Mapping Spectrometer (TOMS) instrument on the Earth Probe satellite, consisting of daily values of aerosol index, ozone and reflectivity remapped into a regular 1x1.25 deg grid. Data are available from July 25, 1996 - December 31, 2005, but have been updated or replaced as of September 2007. See the explanation on the ARM web site at http://www.arm.gov/xds/static/toms.stm and the information at the NASA/TOMS web site: http://toms.gsfc.nasa.gov/ (Registration required)

  13. Cancer risk estimates from radiation therapy for heterotopic ossification prophylaxis after total hip arthroplasty

    SciTech Connect (OSTI)

    Mazonakis, Michalis; Berris, Theoharris; Damilakis, John; Lyraraki, Efrossyni

    2013-10-15

    Purpose: Heterotopic ossification (HO) is a frequent complication following total hip arthroplasty. This study was conducted to calculate the radiation dose to organs-at-risk and estimate the probability of cancer induction from radiotherapy for HO prophylaxis.Methods: Hip irradiation for HO with a 6 MV photon beam was simulated with the aid of a Monte Carlo model. A realistic humanoid phantom representing an average adult patient was implemented in Monte Carlo environment for dosimetric calculations. The average out-of-field radiation dose to stomach, liver, lung, prostate, bladder, thyroid, breast, uterus, and ovary was calculated. The organ-equivalent-dose to colon, that was partly included within the treatment field, was also determined. Organ dose calculations were carried out using three different field sizes. The dependence of organ doses upon the block insertion into primary beam for shielding colon and prosthesis was investigated. The lifetime attributable risk for cancer development was estimated using organ, age, and gender-specific risk coefficients.Results: For a typical target dose of 7 Gy, organ doses varied from 1.0 to 741.1 mGy by the field dimensions and organ location relative to the field edge. Blocked field irradiations resulted in a dose range of 1.4146.3 mGy. The most probable detriment from open field treatment of male patients was colon cancer with a high risk of 564.3 10{sup ?5} to 837.4 10{sup ?5} depending upon the organ dose magnitude and the patient's age. The corresponding colon cancer risk for female patients was (372.2541.0) 10{sup ?5}. The probability of bladder cancer development was more than 113.7 10{sup ?5} and 110.3 10{sup ?5} for males and females, respectively. The cancer risk range to other individual organs was reduced to (0.00368.5) 10{sup ?5}.Conclusions: The risk for cancer induction from radiation therapy for HO prophylaxis after total hip arthroplasty varies considerably by the treatment parameters, organ site in respect to treatment volume and patient's gender and age. The presented risk estimates may be useful in the follow-up studies of irradiated patients.

  14. Steady state estimation of soil organic carbon using satellite-derived canopy leaf area index

    SciTech Connect (OSTI)

    Fang, Yilin; Liu, Chongxuan; Huang, Maoyi; Li, Hongyi; Leung, Lai-Yung R.

    2014-12-02

    Soil organic carbon (SOC) plays a key role in the global carbon cycle that is important for decadal-to-century climate prediction. Estimation of soil organic carbon stock using model-based methods typically requires spin-up (time marching transient simulation) of the carbon-nitrogen (CN) models by performing hundreds to thousands years long simulations until the carbon-nitrogen pools reach dynamic steady-state. This has become a bottleneck for global modeling and analysis, especially when testing new physical and/or chemical mechanisms and evaluating parameter sensitivity. Here we report a new numerical approach to estimate global soil carbon stock that can avoid the long term spin-up of the CN model. The approach uses canopy leaf area index (LAI) from satellite data and takes advantage of a reaction-based biogeochemical module NGBGC (Next Generation BioGeoChemical Module) that was recently developed and incorporated in version 4 of the Community Land Model (CLM4). Although NGBGC uses the same CN mechanisms as used in CLM4CN, it can be easily configured to run prognostic or steady state simulations. In this approach, monthly LAI from the multi-year Moderate Resolution Imaging Spectroradiometer (MODIS) data was used to calculate potential annual average gross primary production (GPP) and leaf carbon for the period of the atmospheric forcing. The calculated potential annual average GPP and leaf C are then used by NGBGC to calculate the steady-state distributions of carbon and nitrogen in different vegetation and soil pools by solving the steady-state reaction-network in NGBGC using the Newton-Raphson method. The new approach was applied at point and global scales and compared with SOC derived from long spin-up by running NGBGC in prognostic mode, and SOC from the empirical data of the Harmonized World Soil Database (HWSD). The steady-state solution is comparable to the spin-up value when the MODIS LAI is close to the LAI from the spin-up solution, and largely captured the variability of the HWSD SOC across the different dominant plant functional types (PFTs) at global scale. The numerical correlation between the calculated and HWSD SOC was, however, weak at both point and global scales, suggesting that the models used in describing biogeochemical processes in CLM needs improvements and/or HWSD needs updating as suggested by other studies. Besides SOC, the steady state solution also includes all other state variables simulated by a spin-up run, such as NPP, GPP, total vegetation C etc., which makes the developed approach a promising tool to efficiently estimate global SOC distribution and evaluate and compare different aspects simulated by different CN mechanisms in the model.

  15. Steady state estimation of soil organic carbon using satellite-derived canopy leaf area index

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

    Fang, Yilin; Liu, Chongxuan; Huang, Maoyi; Li, Hongyi; Leung, Lai-Yung R.

    2014-12-02

    Soil organic carbon (SOC) plays a key role in the global carbon cycle that is important for decadal-to-century climate prediction. Estimation of soil organic carbon stock using model-based methods typically requires spin-up (time marching transient simulation) of the carbon-nitrogen (CN) models by performing hundreds to thousands years long simulations until the carbon-nitrogen pools reach dynamic steady-state. This has become a bottleneck for global modeling and analysis, especially when testing new physical and/or chemical mechanisms and evaluating parameter sensitivity. Here we report a new numerical approach to estimate global soil carbon stock that can avoid the long term spin-up of themore » CN model. The approach uses canopy leaf area index (LAI) from satellite data and takes advantage of a reaction-based biogeochemical module NGBGC (Next Generation BioGeoChemical Module) that was recently developed and incorporated in version 4 of the Community Land Model (CLM4). Although NGBGC uses the same CN mechanisms as used in CLM4CN, it can be easily configured to run prognostic or steady state simulations. In this approach, monthly LAI from the multi-year Moderate Resolution Imaging Spectroradiometer (MODIS) data was used to calculate potential annual average gross primary production (GPP) and leaf carbon for the period of the atmospheric forcing. The calculated potential annual average GPP and leaf C are then used by NGBGC to calculate the steady-state distributions of carbon and nitrogen in different vegetation and soil pools by solving the steady-state reaction-network in NGBGC using the Newton-Raphson method. The new approach was applied at point and global scales and compared with SOC derived from long spin-up by running NGBGC in prognostic mode, and SOC from the empirical data of the Harmonized World Soil Database (HWSD). The steady-state solution is comparable to the spin-up value when the MODIS LAI is close to the LAI from the spin-up solution, and largely captured the variability of the HWSD SOC across the different dominant plant functional types (PFTs) at global scale. The numerical correlation between the calculated and HWSD SOC was, however, weak at both point and global scales, suggesting that the models used in describing biogeochemical processes in CLM needs improvements and/or HWSD needs updating as suggested by other studies. Besides SOC, the steady state solution also includes all other state variables simulated by a spin-up run, such as NPP, GPP, total vegetation C etc., which makes the developed approach a promising tool to efficiently estimate global SOC distribution and evaluate and compare different aspects simulated by different CN mechanisms in the model.« less

  16. Adjusting lidar-derived digital terrain models in coastal marshes based on estimated aboveground biomass density

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

    Medeiros, Stephen; Hagen, Scott; Weishampel, John; Angelo, James

    2015-03-25

    Digital elevation models (DEMs) derived from airborne lidar are traditionally unreliable in coastal salt marshes due to the inability of the laser to penetrate the dense grasses and reach the underlying soil. To that end, we present a novel processing methodology that uses ASTER Band 2 (visible red), an interferometric SAR (IfSAR) digital surface model, and lidar-derived canopy height to classify biomass density using both a three-class scheme (high, medium and low) and a two-class scheme (high and low). Elevation adjustments associated with these classes using both median and quartile approaches were applied to adjust lidar-derived elevation values closer tomore » true bare earth elevation. The performance of the method was tested on 229 elevation points in the lower Apalachicola River Marsh. The two-class quartile-based adjusted DEM produced the best results, reducing the RMS error in elevation from 0.65 m to 0.40 m, a 38% improvement. The raw mean errors for the lidar DEM and the adjusted DEM were 0.61 ± 0.24 m and 0.32 ± 0.24 m, respectively, thereby reducing the high bias by approximately 49%.« less

  17. Adjusting lidar-derived digital terrain models in coastal marshes based on estimated aboveground biomass density

    SciTech Connect (OSTI)

    Medeiros, Stephen; Hagen, Scott; Weishampel, John; Angelo, James

    2015-03-25

    Digital elevation models (DEMs) derived from airborne lidar are traditionally unreliable in coastal salt marshes due to the inability of the laser to penetrate the dense grasses and reach the underlying soil. To that end, we present a novel processing methodology that uses ASTER Band 2 (visible red), an interferometric SAR (IfSAR) digital surface model, and lidar-derived canopy height to classify biomass density using both a three-class scheme (high, medium and low) and a two-class scheme (high and low). Elevation adjustments associated with these classes using both median and quartile approaches were applied to adjust lidar-derived elevation values closer to true bare earth elevation. The performance of the method was tested on 229 elevation points in the lower Apalachicola River Marsh. The two-class quartile-based adjusted DEM produced the best results, reducing the RMS error in elevation from 0.65 m to 0.40 m, a 38% improvement. The raw mean errors for the lidar DEM and the adjusted DEM were 0.61 0.24 m and 0.32 0.24 m, respectively, thereby reducing the high bias by approximately 49%.

  18. Worldwide estimates and bibliography of net primary productivity derived from pre-1982 publications

    SciTech Connect (OSTI)

    Esser, G.; Lieth, H.F.H.; Scurlock, J.M.O.; Olson, R.J.

    1997-10-01

    An extensive compilation of more than 700 field estimates of net primary productivity of natural and agricultural ecosystems worldwide was synthesized in Germany in the 1970s and early 1980s. Although the Osnabrueck data set has not been updated since the 1980s, it represents a wealth of information for use in model development and validation. This report documents the development of this data set, its contents, and its recent availability on the Internet from the Oak Ridge National Laboratory Distributed Active Archive Center for Biogeochemical Dynamics. Caution is advised in using these data, which necessarily include assumptions and conversions that may not be universally applicable to all sites.

  19. Derived Annual Estimates

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

    robert.adler@eia.doe.gov Robert Adler Survey Manager Phone: 202-586-1134 Fax: (202) 586-0018 thomas.lorenz@eia.doe.gov Thomas Lorenz Operations Research Analyst Phone: 202-586-3442...

  20. Supercooled liquid water Estimation Tool

    Energy Science and Technology Software Center (OSTI)

    2012-05-04

    The Cloud Supercooled liquid water Estimation Tool (SEET) is a user driven Graphical User Interface (GUI) that estimates cloud supercooled liquid water (SLW) content in terms of vertical column and total mass from Moderate resolution Imaging Supercooled liquid water Estimation Tool Spectroradiometer (MODIS) spatially derived cloud products and realistic vertical cloud parameterizations that are user defined. It also contains functions for post-processing of the resulting data in tabular and graphical form.

  1. Table 8.6a Estimated Consumption of Combustible Fuels for Useful Thermal Output at Combined-Heat-and-Power Plants: Total (All Sectors), 1989-2011 (Sum of Tables 8.6b and 8.6c)

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

    a Estimated Consumption of Combustible Fuels for Useful Thermal Output at Combined-Heat-and-Power Plants: Total (All Sectors), 1989-2011 (Sum of Tables 8.6b and 8.6c) Year Coal 1 Petroleum Natural Gas 6 Other Gases 7 Biomass Other 10 Distillate Fuel Oil 2 Residual Fuel Oil 3 Other Liquids 4 Petroleum Coke 5 Total 5 Wood 8 Waste 9 Short Tons Barrels Short Tons Barrels Thousand Cubic Feet Billion Btu Billion Btu Billion Btu 1989 16,509,639 1,410,151 16,356,550 353,000 247,409 19,356,746

  2. Total Estimated Contract Cost: Performance Period Total Fee Paid

    Office of Environmental Management (EM)

    DE-AM09-05SR22405DE-AT30-07CC60011SL14 Contractor: Contract Number: Contract Type: Cost Plus Award Fee 357,223 597,797 894,699 EM Contractor Fee Site: Stanford Linear...

  3. Country Total

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

    Country Total Percent of U.S. total China 1,461,074 34 Republic of Korea 172,379 4 Taiwan 688,311 16 All others 1,966,263 46 Total 4,288,027 100 Note: All Others includes Canada, Czech Republic, Federal Republic of Germany, Malaysia, Mexico, Philippines and Singapore Source: U.S. Energy Information Administration, Form EIA-63B, 'Annual Photovoltaic Cell/Module Shipments Report.' Table 7 . Photovoltaic module import shipments by country, 2013 (peak kilowatts)

  4. Total Estimated Contract Cost: Performance Period

    Office of Environmental Management (EM)

    FY2012 Fee Information Minimum Fee Maximum Fee September 2015 Contract Number: Cost Plus Incentive Fee Contractor: 3,264,909,094 Contract Period: EM Contractor Fee s Idaho...

  5. Contractor: Contract Number: Contract Type: Total Estimated

    Office of Environmental Management (EM)

    886,608 Computer Sciences Corporation DE-AC06-04RL14383 895,358 899,230 907,583 Cost Plus Award Fee 134,100,336 8,221,404 Fee Available Contract Period: Fee Information...

  6. Notices Total Estimated Number of Annual

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

    (SAIG) allows eligible entities to securely exchange Title IV, Higher Education Act (HEA) assistance programs data electronically with the Department of Education processors. ...

  7. Summary Max Total Units

    Energy Savers [EERE]

    Summary Max Total Units *If All Splits, No Rack Units **If Only FW, AC Splits 1000 52 28 28 2000 87 59 35 3000 61 33 15 4000 61 33 15 Totals 261 153 93 ***Costs $1,957,500.00 $1,147,500.00 $697,500.00 Notes: added several refrigerants removed bins from analysis removed R-22 from list 1000lb, no Glycol, CO2 or ammonia Seawater R-404A only * includes seawater units ** no seawater units included *** Costs = (total units) X (estimate of $7500 per unit) 1000lb, air cooled split systems, fresh water

  8. State Total

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

    State Total Percent of U.S. total Alabama 1,652 0.0 Alaska 152 0.0 Arizona 912,975 19.9 Arkansas 2,724 0.1 California 2,239,983 48.8 Colorado 49,903 1.1 Connecticut 33,627 0.7 Delaware 3,080 0.1 District of Columbia 1,746 0.0 Florida 22,061 0.5 Georgia 99,713 2.2 Guam 39 0.0 Hawaii 126,595 2.8 Idaho 1,423 0.0 Illinois 8,176 0.2 Indiana 12,912 0.3 Iowa 4,480 0.1 Kansas 523 0.0 Kentucky 2,356 0.1 Louisiana 27,704 0.6 Maine 993 0.0 Maryland 30,528 0.7 Massachusetts 143,539 3.1 Michigan 3,416 0.1

  9. Barge Truck Total

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

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

  10. Weekly Coal Production Estimation Methodology

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

    Weekly Coal Production Estimation Methodology Step 1 (Estimate total amount of weekly U.S. coal production) U.S. coal production for the current week is estimated using a ratio ...

  11. ,"Total Natural Gas Consumption

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

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

  12. Estimating Methods

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

    1997-03-28

    Based on the project's scope, the purpose of the estimate, and the availability of estimating resources, the estimator can choose one or a combination of techniques when estimating an activity or project. Estimating methods, estimating indirect and direct costs, and other estimating considerations are discussed in this chapter.

  13. Total Space Heat-

    Gasoline and Diesel Fuel Update (EIA)

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

  14. ,"Total Fuel Oil Expenditures

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

    A. Fuel Oil Expenditures by Census Region for All Buildings, 2003" ,"Total Fuel Oil Expenditures (million dollars)",,,,"Fuel Oil Expenditures (dollars)" ,,,,,"per Gallon",,,,"per...

  15. ,"Total Fuel Oil Consumption

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

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

  16. Total Space Heat-

    Gasoline and Diesel Fuel Update (EIA)

    Revised: December, 2008 Total Space Heat- ing Cool- ing Venti- lation Water Heat- ing Light- ing Cook- ing Refrig- eration Office Equip- ment Com- puters Other All Buildings...

  17. Total Space Heat-

    Gasoline and Diesel Fuel Update (EIA)

    Released: September, 2008 Total Space Heat- ing Cool- ing Venti- lation Water Heat- ing Light- ing Cook- ing Refrig- eration Office Equip- ment Com- puters Other All Buildings*...

  18. ,"Total Fuel Oil Expenditures

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

    . Fuel Oil Expenditures by Census Region for Non-Mall Buildings, 2003" ,"Total Fuel Oil Expenditures (million dollars)",,,,"Fuel Oil Expenditures (dollars)" ,,,,,"per...

  19. ,"Total Fuel Oil Consumption

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

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

  20. ,"Total Fuel Oil Expenditures

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

    4. Fuel Oil Expenditures by Census Region, 1999" ,"Total Fuel Oil Expenditures (million dollars)",,,,"Fuel Oil Expenditures (dollars)" ,,,,,"per Gallon",,,,"per Square Foot"...

  1. Parallel Total Energy

    Energy Science and Technology Software Center (OSTI)

    2004-10-21

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

  2. Country/Continent Total

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

    peak kilowatts) Country/Continent Total Percent of U.S. total Africa 14,279 3.7 Asia/Australia 330,200 86.2 Europe 19,771 5.1 South/Central America 7,748 2.0 Canada 5,507 1.4 Mexico 5,747 1.5 Total 383,252 100.0 Table 8. Destination of photovoltaic module export shipments, 2013 Source: U.S. Energy Information Administration, Form EIA-63B, 'Annual Photovoltaic Cell/Module Shipments Report.'

  3. Estimation of Anisotoropy from Total Cross Section and Optical...

    Office of Scientific and Technical Information (OSTI)

    provided as a public service. Visit OSTI to utilize additional information resources in energy science and technology. A paper copy of this document is also available for sale to...

  4. Total Estimated Contract Cost: Contract Option Period: Maximum...

    Office of Environmental Management (EM)

    & Wilcox Conversion Services, LLC Contract Number: DE-AC30-11CC40015 Contract Type: Cost Plus Award Fee EM Contractor Fee September 2015 Site: Portsmouth Paducah Project Office...

  5. Total Estimated Contract Cost: Contract Option Period: Performance

    Office of Environmental Management (EM)

    Contractor: Bechtel National Inc. Contract Number: DE-AC27-01RV14136 Contract Type: Cost Plus Award Fee NA Maximum Fee 599,588,540 Fee Available 102,622,325 10,868,785,789...

  6. Total Estimated Contract Cost: Contract Option Period: Maximum...

    Office of Environmental Management (EM)

    LLC Contract Number: DE-AC30-11CC40015 Contract Type: Cost Plus Award Fee EM Contractor Fee December 2015 Site: Portsmouth Paducah Project Office Contract Name: Operation of DUF6

  7. Performance Measure Unit Lifecycle Total Estimate Pre-2016 Lifecycle Values

    Office of Environmental Management (EM)

    Audit of Costs Incurred Under the Department of Energy's International Nuclear Cooperation Program Interagency Agreements With the Department of State OAS-FS-15-09 February 2015 U.S. Department of Energy Office of Inspector General Office of Audits and Inspections Department of Energy Washington, DC 20585 February 24, 2015 MEMORADUM FOR THE ASSISTANT SECRETARY FOR NUCLEAR ENERGY AND THE ACTING DIRECTOR, OFFICE OF SCIENCE FROM: Rickey R. Hass Deputy Inspector General for Audits and Inspections

  8. Total Estimated Contract Cost: Contract Option Period: Maximum Fee

    Office of Environmental Management (EM)

    Definition and Scope Answer/Comment 1 What significant policy challenges are likely to remain unaddressed if we employ Title XIII's definition? The following points are not referencedd in EISA 1301. ・Power provider should also control the output fluctuation of renewable resources. ・The end user should have the choice of which form of power storage to be used. Certain types of energy conservation and storage could work better in different applications (e.g. not only electricity power but also

  9. Total Estimated Contract Cost: Contract Option Period: Performance

    Office of Environmental Management (EM)

    Performance Period Fee Earned FY2000 thru 2008 $102,622,325 FY2009 $12,259,719 FY2010 $35,789,418 FY2011 $24,126,240 FY2012 $24,995,209 FY2013 $6,340,762 FY2014 $16,285,867 FY2015 $35,931,000 $8,595,000 FY2016 $20,891,000 $8,810,000 FY2017 $24,849,000 FY2018 $99,100,000 FY2019 $129,700,000 Cumulative Fee $239,824,540 EM Contractor Fee March 2015 Site: Office of River Protection, Richland, WA Contract Name: Waste Treatment Plant Design, Construction Contract $750,000 Contractor: Bechtel National

  10. Total Estimated Contract Price: Contract Option Periods: Performance

    Office of Environmental Management (EM)

    Price: Contract Option Periods: Performance Period Fee Earned Base Period "A" $0 Base Period "B" Option 1 Option 2 Option 3 Cumulative Fee $0 $855,207 $142,771 $171,325 $175,563 $180,237 $185,312 Fee Available $44,562,457 Base Contract Period: November 21, 2016 to September 20, 2018 Fee Information Option Period 1 : September 21, 2018 to September 20, 2019 Option Period 2: September 21, 2019 to September 20, 2020 Option Period 3: September 21, 2020 to September 20, 2021

  11. Estimating Radiation Risk from Total Effective Dose Equivalent...

    National Nuclear Security Administration (NNSA)

    0 Tc 0.37 No. 1Tj 5.25 0 TD 0.098 Tc 0 Tw (No.) Tj 15.755 -13.5 TD 0.3to Tw ( ) Tj 5.25 0 TD F1 10.5 Tf -0.1925 Tc 0 5 Report 0 1Tj 5.25 0 TD 0.098 Tc 0 Tw 8No. 7 0 TD -0.IRRPC,

  12. Estimating Radiation Risk from Total Effective Dose Equivalent...

    National Nuclear Security Administration (NNSA)

    of Dose to the Public, DOE Report DOEEH-0070, July 1988. DOE, 1988b. Internal Dose Conversion Factors for Calculation of Dose to the Public, DOE Report DOEEH-0071, July 1988. ...

  13. Total Space Heat-

    Gasoline and Diesel Fuel Update (EIA)

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

  14. ARM - Measurement - Total carbon

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

    carbon ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Measurement : Total carbon The total concentration of carbon in all its organic and non-organic forms. Categories Aerosols, Atmospheric Carbon Instruments The above measurement is considered scientifically relevant for the following instruments. Refer to the datastream (netcdf) file headers of each instrument for a list of all available measurements, including

  15. Project Functions and Activities Definitions for Total Project Cost

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

    1997-03-28

    This chapter provides guidelines developed to define the obvious disparity of opinions and practices with regard to what exactly is included in total estimated cost (TEC) and total project cost (TPC).

  16. Total DOE/NNSA

    National Nuclear Security Administration (NNSA)

    8 Actuals 2009 Actuals 2010 Actuals 2011 Actuals 2012 Actuals 2013 Actuals 2014 Actuals 2015 Actuals Total DOE/NNSA 4,385 4,151 4,240 4,862 5,154 5,476 7,170 7,593 Total non-NNSA 3,925 4,017 4,005 3,821 3,875 3,974 3,826 3765 Total Facility 8,310 8,168 8,245 8,683 9,029 9,450 10,996 11,358 non-NNSA includes DOE offices and Strategic Parternship Projects (SPP) employees NNSA M&O Employee Reporting

  17. 21 briefing pages total

    Energy Savers [EERE]

    1 briefing pages total p. 1 Reservist Differential Briefing U.S. Office of Personnel Management December 11, 2009 p. 2 Agenda - Introduction of Speakers - Background - References/Tools - Overview of Reservist Differential Authority - Qualifying Active Duty Service and Military Orders - Understanding Military Leave and Earnings Statements p. 3 Background 5 U.S.C. 5538 (Section 751 of the Omnibus Appropriations Act, 2009, March 11, 2009) (Public Law 111-8) Law requires OPM to consult with DOD Law

  18. Total Sales of Kerosene

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

    End Use: Total Residential Commercial Industrial Farm All Other Period: Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: End Use Area 2009 2010 2011 2012 2013 2014 View History U.S. 269,010 305,508 187,656 81,102 79,674 137,928 1984-2014 East Coast (PADD 1) 198,762 237,397 142,189 63,075 61,327 106,995 1984-2014 New England (PADD 1A) 56,661 53,363 38,448 15,983 15,991 27,500 1984-2014 Connecticut 8,800 7,437

  19. Determination of Total Petroleum Hydrocarbons (TPH) Using Total Carbon Analysis

    SciTech Connect (OSTI)

    Ekechukwu, A.A.

    2002-05-10

    Several methods have been proposed to replace the Freon(TM)-extraction method to determine total petroleum hydrocarbon (TPH) content. For reasons of cost, sensitivity, precision, or simplicity, none of the replacement methods are feasible for analysis of radioactive samples at our facility. We have developed a method to measure total petroleum hydrocarbon content in aqueous sample matrixes using total organic carbon (total carbon) determination. The total carbon content (TC1) of the sample is measured using a total organic carbon analyzer. The sample is then contacted with a small volume of non-pokar solvent to extract the total petroleum hydrocarbons. The total carbon content of the resultant aqueous phase of the extracted sample (TC2) is measured. Total petroleum hydrocarbon content is calculated (TPH = TC1-TC2). The resultant data are consistent with results obtained using Freon(TM) extraction followed by infrared absorbance.

  20. Total Eolica | Open Energy Information

    Open Energy Info (EERE)

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

  1. Scaling properties of proton-nucleus total reaction cross sections

    SciTech Connect (OSTI)

    Abu-Ibrahim, Badawy; Kohama, Akihisa

    2010-05-15

    We study the scaling properties of proton-nucleus total reaction cross sections for stable nuclei and propose an approximate expression in proportion to Z{sup 2/3}sigma{sub pp}{sup total}+N{sup 2/3}sigma{sub pn}{sup total}. Based on this expression, we can derive a relation that enables us to predict a total reaction cross section for any stable nucleus within 10% uncertainty at most, using the empirical value of the total reaction cross section of a given nucleus.

  2. Total

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

    Fuel Kerosene Distillate Fuel Oil Distillate Fuel Oil, 15 ppm Sulfur and Under Distillate Fuel Oil, Greater than 15 ppm to 500 ppm Sulfur Distillate Fuel Oil, Greater than 500 ppm ...

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

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

    5 or More Units Mobile Homes Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Million U.S. Housing Units ...

  4. Total..............................................

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

    111.1 86.6 2,720 1,970 1,310 1,941 1,475 821 1,059 944 554 Census Region and Division Northeast.................................... 20.6 13.9 3,224 2,173 836 2,219 1,619 583 903 830 Q New England.......................... 5.5 3.6 3,365 2,154 313 2,634 1,826 Q 951 940 Q Middle Atlantic........................ 15.1 10.3 3,167 2,181 1,049 2,188 1,603 582 Q Q Q Midwest...................................... 25.6 21.0 2,823 2,239 1,624 2,356 1,669 1,336 1,081 961 778 East North

  5. Total........................................................

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

    111.1 24.5 1,090 902 341 872 780 441 Census Region and Division Northeast............................................. 20.6 6.7 1,247 1,032 Q 811 788 147 New England.................................... 5.5 1.9 1,365 1,127 Q 814 748 107 Middle Atlantic.................................. 15.1 4.8 1,182 978 Q 810 800 159 Midwest................................................ 25.6 4.6 1,349 1,133 506 895 810 346 East North Central............................ 17.7 3.2 1,483 1,239 560 968 842 351

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

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

    Q Table HC3.2 Living Space Characteristics by Owner-Occupied Housing Units, 2005 2 to 4 Units 5 or More Units Mobile Homes Million U.S. Housing Units Owner- Occupied Housing Units (millions) Type of Owner-Occupied Housing Unit Housing Units (millions) Single-Family Units Apartments in Buildings With-- Living Space Characteristics Detached Attached Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Table HC3.2 Living Space

  7. Total............................................................

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

  8. Total.............................................................

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

    26.7 28.8 20.6 13.1 22.0 16.6 38.6 Personal Computers Do Not Use a Personal Computer........... 35.5 17.1 10.8 4.2 1.8 1.6 10.3 20.6 Use a Personal Computer....................... 75.6 9.6 18.0 16.4 11.3 20.3 6.4 17.9 Most-Used Personal Computer Type of PC Desk-top Model.................................. 58.6 7.6 14.2 13.1 9.2 14.6 5.0 14.5 Laptop Model...................................... 16.9 2.0 3.8 3.3 2.1 5.7 1.3 3.5 Hours Turned on Per Week Less than 2 Hours..............................

  9. Total..............................................................

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

    ,171 1,618 1,031 845 630 401 Census Region and Division Northeast................................................... 20.6 2,334 1,664 562 911 649 220 New England.......................................... 5.5 2,472 1,680 265 1,057 719 113 Middle Atlantic........................................ 15.1 2,284 1,658 670 864 627 254 Midwest...................................................... 25.6 2,421 1,927 1,360 981 781 551 East North Central.................................. 17.7 2,483 1,926 1,269

  10. Total..............................................................

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

    Do Not Have Cooling Equipment................ 17.8 5.3 4.7 2.8 1.9 3.1 3.6 7.5 Have Cooling Equipment............................. 93.3 21.5 24.1 17.8 11.2 18.8 13.0 31.1 Use Cooling Equipment.............................. 91.4 21.0 23.5 17.4 11.0 18.6 12.6 30.3 Have Equipment But Do Not Use it............. 1.9 0.5 0.6 0.4 Q Q 0.5 0.8 Type of Air-Conditioning Equipment 1, 2 Central System.......................................... 65.9 11.0 16.5 13.5 8.7 16.1 6.4 17.2 Without a Heat

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

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

    20.6 25.6 40.7 24.2 Personal Computers Do Not Use a Personal Computer ........... 35.5 6.9 8.1 14.2 6.4 Use a Personal Computer......................... 75.6 13.7 17.5 26.6 17.8 Number of Desktop PCs 1.......................................................... 50.3 9.3 11.9 18.2 11.0 2.......................................................... 16.2 2.9 3.5 5.5 4.4 3 or More............................................. 9.0 1.5 2.1 2.9 2.5 Number of Laptop PCs

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

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

    0.7 21.7 6.9 12.1 Personal Computers Do Not Use a Personal Computer ........... 35.5 14.2 7.2 2.8 4.2 Use a Personal Computer......................... 75.6 26.6 14.5 4.1 7.9 Number of Desktop PCs 1.......................................................... 50.3 18.2 10.0 2.9 5.3 2.......................................................... 16.2 5.5 3.0 0.7 1.8 3 or More............................................. 9.0 2.9 1.5 0.5 0.8 Number of Laptop PCs

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

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

    26.7 28.8 20.6 13.1 22.0 16.6 38.6 Personal Computers Do Not Use a Personal Computer ........... 35.5 17.1 10.8 4.2 1.8 1.6 10.3 20.6 Use a Personal Computer......................... 75.6 9.6 18.0 16.4 11.3 20.3 6.4 17.9 Number of Desktop PCs 1.......................................................... 50.3 8.3 14.2 11.4 7.2 9.2 5.3 14.2 2.......................................................... 16.2 0.9 2.6 3.7 2.9 6.2 0.8 2.6 3 or More............................................. 9.0 0.4 1.2

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

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

    Do Not Have Cooling Equipment................. 17.8 5.3 4.7 2.8 1.9 3.1 3.6 7.5 Have Cooling Equipment.............................. 93.3 21.5 24.1 17.8 11.2 18.8 13.0 31.1 Use Cooling Equipment............................... 91.4 21.0 23.5 17.4 11.0 18.6 12.6 30.3 Have Equipment But Do Not Use it............. 1.9 0.5 0.6 0.4 Q Q 0.5 0.8 Air-Conditioning Equipment 1, 2 Central System............................................ 65.9 11.0 16.5 13.5 8.7 16.1 6.4 17.2 Without a Heat

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

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

    47.1 19.0 22.7 22.3 Personal Computers Do Not Use a Personal Computer ........... 35.5 16.9 6.5 4.6 7.6 Use a Personal Computer......................... 75.6 30.3 12.5 18.1 14.7 Number of Desktop PCs 1.......................................................... 50.3 21.1 8.3 10.7 10.1 2.......................................................... 16.2 6.2 2.8 4.1 3.0 3 or More............................................. 9.0 2.9 1.4 3.2 1.6 Number of Laptop PCs

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

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

    111.1 26.7 28.8 20.6 13.1 22.0 16.6 38.6 Do Not Have Space Heating Equipment....... 1.2 0.5 0.3 0.2 Q 0.2 0.3 0.6 Have Main Space Heating Equipment.......... 109.8 26.2 28.5 20.4 13.0 21.8 16.3 37.9 Use Main Space Heating Equipment............ 109.1 25.9 28.1 20.3 12.9 21.8 16.0 37.3 Have Equipment But Do Not Use It.............. 0.8 0.3 0.3 Q Q N 0.4 0.6 Main Heating Fuel and Equipment Natural Gas.................................................. 58.2 12.2 14.4 11.3 7.1 13.2 7.6 18.3 Central

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

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

    49.2 15.1 15.6 11.1 7.0 5.2 8.0 Have Cooling Equipment............................... 93.3 31.3 15.1 15.6 11.1 7.0 5.2 8.0 Use Cooling Equipment................................ 91.4 30.4 14.6 15.4 11.1 6.9 5.2 7.9 Have Equipment But Do Not Use it............... 1.9 1.0 0.5 Q Q Q Q Q Do Not Have Cooling Equipment................... 17.8 17.8 N N N N N N Air-Conditioning Equipment 1, 2 Central System............................................. 65.9 3.9 15.1 15.6 11.1 7.0 5.2 8.0 Without a Heat

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

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

    14.7 7.4 12.5 12.5 18.9 18.6 17.3 9.2 Do Not Have Space Heating Equipment........ 1.2 N Q Q 0.2 0.4 0.2 0.2 Q Have Main Space Heating Equipment........... 109.8 14.7 7.4 12.4 12.2 18.5 18.3 17.1 9.2 Use Main Space Heating Equipment............. 109.1 14.6 7.3 12.4 12.2 18.2 18.2 17.1 9.1 Have Equipment But Do Not Use It............... 0.8 Q Q Q Q 0.3 Q N Q Main Heating Fuel and Equipment Natural Gas................................................... 58.2 9.2 4.9 7.8 7.1 8.8 8.4 7.8 4.2 Central

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

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

    26.7 28.8 20.6 13.1 22.0 16.6 38.6 Cooking Appliances Frequency of Hot Meals Cooked 3 or More Times A Day.............................. 8.2 2.9 2.5 1.3 0.5 1.0 2.4 4.6 2 Times A Day........................................... 24.6 6.5 7.0 4.3 3.2 3.6 4.8 10.3 Once a Day................................................ 42.3 8.8 9.8 8.7 5.1 10.0 5.0 12.9 A Few Times Each Week........................... 27.2 5.6 7.2 4.7 3.3 6.3 3.2 7.5 About Once a Week................................... 3.9 1.1 1.1

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

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

    78.1 64.1 4.2 1.8 2.3 5.7 Do Not Have Cooling Equipment..................... 17.8 11.3 9.3 0.6 Q 0.4 0.9 Have Cooling Equipment................................. 93.3 66.8 54.7 3.6 1.7 1.9 4.8 Use Cooling Equipment.................................. 91.4 65.8 54.0 3.6 1.7 1.9 4.7 Have Equipment But Do Not Use it................. 1.9 1.1 0.8 Q N Q Q Type of Air-Conditioning Equipment 1, 2 Central System.............................................. 65.9 51.7 43.9 2.5 0.7 1.6 3.1 Without a Heat

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

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

    . 111.1 14.7 7.4 12.5 12.5 18.9 18.6 17.3 9.2 Do Not Have Cooling Equipment..................... 17.8 3.9 1.8 2.2 2.1 3.1 2.6 1.7 0.4 Have Cooling Equipment................................. 93.3 10.8 5.6 10.3 10.4 15.8 16.0 15.6 8.8 Use Cooling Equipment.................................. 91.4 10.6 5.5 10.3 10.3 15.3 15.7 15.3 8.6 Have Equipment But Do Not Use it................. 1.9 Q Q Q Q 0.6 0.4 0.3 Q Type of Air-Conditioning Equipment 1, 2 Central

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

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

    15.2 7.8 1.0 1.2 3.3 1.9 For Two Housing Units............................. 0.9 Q N Q 0.6 N Heat Pump.................................................. 9.2 7.4 0.3 Q 0.7 0.5 Portable Electric Heater............................... 1.6 0.8 Q Q Q 0.3 Other Equipment......................................... 1.9 0.7 Q Q 0.7 Q Fuel Oil........................................................... 7.7 5.5 0.4 0.8 0.9 0.2 Steam or Hot Water System........................ 4.7 2.9 Q 0.7 0.8 N For One Housing

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

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

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

  4. Total.......................................................................

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

    0.6 15.1 5.5 Personal Computers Do Not Use a Personal Computer ................... 35.5 6.9 5.3 1.6 Use a Personal Computer................................ 75.6 13.7 9.8 3.9 Number of Desktop PCs 1.................................................................. 50.3 9.3 6.8 2.5 2.................................................................. 16.2 2.9 1.9 1.0 3 or More..................................................... 9.0 1.5 1.1 0.4 Number of Laptop PCs

  5. Total.......................................................................

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

    5.6 17.7 7.9 Personal Computers Do Not Use a Personal Computer ................... 35.5 8.1 5.6 2.5 Use a Personal Computer................................ 75.6 17.5 12.1 5.4 Number of Desktop PCs 1.................................................................. 50.3 11.9 8.4 3.4 2.................................................................. 16.2 3.5 2.2 1.3 3 or More..................................................... 9.0 2.1 1.5 0.6 Number of Laptop PCs

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

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

    4.2 7.6 16.6 Personal Computers Do Not Use a Personal Computer ................... 35.5 6.4 2.2 4.2 Use a Personal Computer................................ 75.6 17.8 5.3 12.5 Number of Desktop PCs 1.................................................................. 50.3 11.0 3.4 7.6 2.................................................................. 16.2 4.4 1.3 3.1 3 or More..................................................... 9.0 2.5 0.7 1.8 Number of Laptop PCs

  7. Total........................................................................

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

    25.6 40.7 24.2 Do Not Have Space Heating Equipment............... 1.2 Q Q Q 0.7 Have Main Space Heating Equipment.................. 109.8 20.5 25.6 40.3 23.4 Use Main Space Heating Equipment.................... 109.1 20.5 25.6 40.1 22.9 Have Equipment But Do Not Use It...................... 0.8 N N Q 0.6 Main Heating Fuel and Equipment Natural Gas.......................................................... 58.2 11.4 18.4 13.6 14.7 Central Warm-Air Furnace................................ 44.7 6.1

  8. Total........................................................................

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

    15.1 5.5 Do Not Have Space Heating Equipment............... 1.2 Q Q Q Have Main Space Heating Equipment.................. 109.8 20.5 15.1 5.4 Use Main Space Heating Equipment.................... 109.1 20.5 15.1 5.4 Have Equipment But Do Not Use It...................... 0.8 N N N Main Heating Fuel and Equipment Natural Gas.......................................................... 58.2 11.4 9.1 2.3 Central Warm-Air Furnace................................ 44.7 6.1 5.3 0.8 For One Housing

  9. Total........................................................................

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

    5.6 17.7 7.9 Do Not Have Space Heating Equipment............... 1.2 Q Q N Have Main Space Heating Equipment.................. 109.8 25.6 17.7 7.9 Use Main Space Heating Equipment.................... 109.1 25.6 17.7 7.9 Have Equipment But Do Not Use It...................... 0.8 N N N Main Heating Fuel and Equipment Natural Gas.......................................................... 58.2 18.4 13.1 5.3 Central Warm-Air Furnace................................ 44.7 16.2 11.6 4.7 For One Housing

  10. Total........................................................................

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

    0.7 21.7 6.9 12.1 Do Not Have Space Heating Equipment............... 1.2 Q Q N Q Have Main Space Heating Equipment.................. 109.8 40.3 21.4 6.9 12.0 Use Main Space Heating Equipment.................... 109.1 40.1 21.2 6.9 12.0 Have Equipment But Do Not Use It...................... 0.8 Q Q N N Main Heating Fuel and Equipment Natural Gas.......................................................... 58.2 13.6 5.6 2.3 5.7 Central Warm-Air Furnace................................ 44.7 11.0 4.4

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

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

    4.2 7.6 16.6 Do Not Have Space Heating Equipment............... 1.2 0.7 Q 0.7 Have Main Space Heating Equipment.................. 109.8 23.4 7.5 16.0 Use Main Space Heating Equipment.................... 109.1 22.9 7.4 15.4 Have Equipment But Do Not Use It...................... 0.8 0.6 Q 0.5 Main Heating Fuel and Equipment Natural Gas.......................................................... 58.2 14.7 4.6 10.1 Central Warm-Air Furnace................................ 44.7 11.4 4.0 7.4 For One

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

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

    7.1 7.0 8.0 12.1 Do Not Have Space Heating Equipment............... 1.2 Q Q Q 0.2 Have Main Space Heating Equipment.................. 109.8 7.1 6.8 7.9 11.9 Use Main Space Heating Equipment.................... 109.1 7.1 6.6 7.9 11.4 Have Equipment But Do Not Use It...................... 0.8 N Q N 0.5 Main Heating Fuel and Equipment Natural Gas.......................................................... 58.2 3.8 0.4 3.8 8.4 Central Warm-Air Furnace................................ 44.7 1.8 Q 3.1 6.0

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

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

    7.1 19.0 22.7 22.3 Do Not Have Space Heating Equipment............... 1.2 0.7 Q 0.2 Q Have Main Space Heating Equipment.................. 109.8 46.3 18.9 22.5 22.1 Use Main Space Heating Equipment.................... 109.1 45.6 18.8 22.5 22.1 Have Equipment But Do Not Use It...................... 0.8 0.7 Q N N Main Heating Fuel and Equipment Natural Gas.......................................................... 58.2 27.0 11.9 14.9 4.3 Central Warm-Air Furnace................................ 44.7

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

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

    0.6 15.1 5.5 Do Not Have Cooling Equipment............................. 17.8 4.0 2.4 1.7 Have Cooling Equipment.......................................... 93.3 16.5 12.8 3.8 Use Cooling Equipment........................................... 91.4 16.3 12.6 3.7 Have Equipment But Do Not Use it.......................... 1.9 0.3 Q Q Air-Conditioning Equipment 1, 2 Central System........................................................ 65.9 6.0 5.2 0.8 Without a Heat

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

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

    4.2 7.6 16.6 Do Not Have Cooling Equipment............................. 17.8 10.3 3.1 7.3 Have Cooling Equipment.......................................... 93.3 13.9 4.5 9.4 Use Cooling Equipment........................................... 91.4 12.9 4.3 8.5 Have Equipment But Do Not Use it.......................... 1.9 1.0 Q 0.8 Air-Conditioning Equipment 1, 2 Central System........................................................ 65.9 10.5 3.9 6.5 Without a Heat

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

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

    Do Not Have Cooling Equipment............................... 17.8 4.0 2.1 1.4 10.3 Have Cooling Equipment............................................ 93.3 16.5 23.5 39.3 13.9 Use Cooling Equipment............................................. 91.4 16.3 23.4 38.9 12.9 Have Equipment But Do Not Use it............................ 1.9 0.3 Q 0.5 1.0 Type of Air-Conditioning Equipment 1, 2 Central System........................................................ 65.9 6.0 17.3 32.1 10.5 Without a Heat

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

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

    Cooking Appliances Frequency of Hot Meals Cooked 3 or More Times A Day......................................... 8.2 1.2 1.0 0.2 2 Times A Day...................................................... 24.6 4.0 2.7 1.2 Once a Day........................................................... 42.3 7.9 5.4 2.5 A Few Times Each Week...................................... 27.2 6.0 4.8 1.2 About Once a Week.............................................. 3.9 0.6 0.5 Q Less Than Once a

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

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

    Cooking Appliances Frequency of Hot Meals Cooked 3 or More Times A Day......................................... 8.2 1.4 1.0 0.4 2 Times A Day...................................................... 24.6 5.8 3.5 2.3 Once a Day........................................................... 42.3 10.7 7.8 2.9 A Few Times Each Week...................................... 27.2 5.6 4.0 1.6 About Once a Week.............................................. 3.9 0.9 0.6 0.3 Less Than Once a

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

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

    Do Not Have Cooling Equipment............................... 17.8 1.4 0.8 0.2 0.3 Have Cooling Equipment............................................ 93.3 39.3 20.9 6.7 11.8 Use Cooling Equipment............................................. 91.4 38.9 20.7 6.6 11.7 Have Equipment But Do Not Use it............................ 1.9 0.5 Q Q Q Type of Air-Conditioning Equipment 1, 2 Central System........................................................ 65.9 32.1 17.6 5.2 9.3 Without a Heat

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

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

    Cooking Appliances Frequency of Hot Meals Cooked 3 or More Times A Day......................................... 8.2 2.6 0.7 1.9 2 Times A Day...................................................... 24.6 6.6 2.0 4.6 Once a Day........................................................... 42.3 8.8 2.9 5.8 A Few Times Each Week...................................... 27.2 4.7 1.5 3.1 About Once a Week.............................................. 3.9 0.7 Q 0.6 Less Than Once a

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

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

    Do Not Have Cooling Equipment............................... 17.8 10.3 3.1 7.3 Have Cooling Equipment............................................ 93.3 13.9 4.5 9.4 Use Cooling Equipment............................................. 91.4 12.9 4.3 8.5 Have Equipment But Do Not Use it............................ 1.9 1.0 Q 0.8 Type of Air-Conditioning Equipment 1, 2 Central System........................................................ 65.9 10.5 3.9 6.5 Without a Heat

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

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

    Do Not Have Cooling Equipment............................... 17.8 8.5 2.7 2.6 4.0 Have Cooling Equipment............................................ 93.3 38.6 16.2 20.1 18.4 Use Cooling Equipment............................................. 91.4 37.8 15.9 19.8 18.0 Have Equipment But Do Not Use it............................ 1.9 0.9 0.3 0.3 0.4 Type of Air-Conditioning Equipment 1, 2 Central System........................................................ 65.9 25.8 10.9 16.6 12.5 Without a Heat

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

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

    111.1 7.1 7.0 8.0 12.1 Personal Computers Do Not Use a Personal Computer .......................... 35.5 3.0 2.0 2.7 3.1 Use a Personal Computer....................................... 75.6 4.2 5.0 5.3 9.0 Number of Desktop PCs 1......................................................................... 50.3 3.1 3.4 3.4 5.4 2......................................................................... 16.2 0.7 1.1 1.2 2.2 3 or More............................................................ 9.0 0.3

  4. Total.................................................................................

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

    7.1 7.0 8.0 12.1 Do Not Have Cooling Equipment................................... 17.8 1.8 Q Q 4.9 Have Cooling Equipment................................................ 93.3 5.3 7.0 7.8 7.2 Use Cooling Equipment................................................. 91.4 5.3 7.0 7.7 6.6 Have Equipment But Do Not Use it............................... 1.9 Q N Q 0.6 Air-Conditioning Equipment 1, 2 Central System.............................................................. 65.9 1.1 6.4 6.4 5.4 Without a

  5. Total....................................................................................

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

    25.6 40.7 24.2 Personal Computers Do Not Use a Personal Computer.................................. 35.5 6.9 8.1 14.2 6.4 Use a Personal Computer.............................................. 75.6 13.7 17.5 26.6 17.8 Most-Used Personal Computer Type of PC Desk-top Model......................................................... 58.6 10.4 14.1 20.5 13.7 Laptop Model............................................................. 16.9 3.3 3.4 6.1 4.1 Hours Turned on Per Week Less than 2

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

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

    5.6 17.7 7.9 Personal Computers Do Not Use a Personal Computer.................................. 35.5 8.1 5.6 2.5 Use a Personal Computer.............................................. 75.6 17.5 12.1 5.4 Most-Used Personal Computer Type of PC Desk-top Model......................................................... 58.6 14.1 10.0 4.0 Laptop Model............................................................. 16.9 3.4 2.1 1.3 Hours Turned on Per Week Less than 2

  7. Total....................................................................................

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

    Cooking Appliances Frequency of Hot Meals Cooked 3 or More Times A Day................................................. 8.2 3.0 1.6 0.3 1.1 2 Times A Day.............................................................. 24.6 8.3 4.2 1.3 2.7 Once a Day................................................................... 42.3 15.0 8.1 2.7 4.2 A Few Times Each Week............................................. 27.2 10.9 6.0 1.8 3.1 About Once a Week..................................................... 3.9

  8. Total....................................................................................

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

    Personal Computers Do Not Use a Personal Computer.................................. 35.5 14.2 7.2 2.8 4.2 Use a Personal Computer.............................................. 75.6 26.6 14.5 4.1 7.9 Most-Used Personal Computer Type of PC Desk-top Model......................................................... 58.6 20.5 11.0 3.4 6.1 Laptop Model............................................................. 16.9 6.1 3.5 0.7 1.9 Hours Turned on Per Week Less than 2

  9. Total....................................................................................

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

    4.2 7.6 16.6 Personal Computers Do Not Use a Personal Computer.................................. 35.5 6.4 2.2 4.2 Use a Personal Computer.............................................. 75.6 17.8 5.3 12.5 Most-Used Personal Computer Type of PC Desk-top Model......................................................... 58.6 13.7 4.2 9.5 Laptop Model............................................................. 16.9 4.1 1.1 3.0 Hours Turned on Per Week Less than 2

  10. Total....................................................................................

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

    Cooking Appliances Frequency of Hot Meals Cooked 3 or More Times A Day................................................. 8.2 3.7 1.6 1.4 1.5 2 Times A Day.............................................................. 24.6 10.8 4.1 4.3 5.5 Once a Day................................................................... 42.3 17.0 7.2 8.7 9.3 A Few Times Each Week............................................. 27.2 11.4 4.7 6.4 4.8 About Once a Week.....................................................

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

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

    111.1 47.1 19.0 22.7 22.3 Personal Computers Do Not Use a Personal Computer.................................. 35.5 16.9 6.5 4.6 7.6 Use a Personal Computer.............................................. 75.6 30.3 12.5 18.1 14.7 Most-Used Personal Computer Type of PC Desk-top Model......................................................... 58.6 22.9 9.8 14.1 11.9 Laptop Model............................................................. 16.9 7.4 2.7 4.0 2.9 Hours Turned on Per Week Less than 2

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

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

    ..... 111.1 7.1 7.0 8.0 12.1 Personal Computers Do Not Use a Personal Computer...................................... 35.5 3.0 2.0 2.7 3.1 Use a Personal Computer.................................................. 75.6 4.2 5.0 5.3 9.0 Most-Used Personal Computer Type of PC Desk-top Model............................................................. 58.6 3.2 3.9 4.0 6.7 Laptop Model................................................................. 16.9 1.0 1.1 1.3 2.4 Hours Turned on Per Week Less

  13. Total

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

    Administration, Form EIA-63B, 'Annual Photovoltaic CellModule Shipments Report.'rounding. ... Form EIA-63B, 'Annual Photovoltaic CellModule Shipments Report.' CellModule ...

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

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

    ... 41.8 2,603 2,199 1,654 941 795 598 1-Car Garage...... 9.5 2,064 1,664 1,039 775 624 390 2-Car Garage......

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

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

    ... Type of Glass in Windows Single-pane Glass...... 27.4 ... Q Q N Q N N Proportion of Windows Replaced All......

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

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

    ... Type of Glass in Windows Single-pane Glass......Q Q Q Q Proportion of Windows Replaced All......

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

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

    Air-Conditioning Equipment 1, 2 Central System...... 65.9 25.8 10.9 16.6 12.5 Without a Heat Pump......

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

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

    Air-Conditioning Equipment 1, 2 Central System...... 65.9 6.0 17.3 32.1 10.5 Without a Heat Pump......

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

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

    Air-Conditioning Equipment 1, 2 Central System...... 65.9 47.5 4.0 2.8 7.9 3.7 Without a Heat Pump...... 53.5 ...

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

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

    Air-Conditioning Equipment 1, 2 Central System...... 65.9 32.1 17.6 5.2 9.3 Without a Heat Pump......

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

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

    5.6 17.7 7.9 Do Not Have Cooling Equipment...... 17.8 2.1 1.8 0.3 Have Cooling Equipment...... 93.3 23.5 16.0 7.5 Use ...

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

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

    ... 111.1 20.6 15.1 5.5 Do Not Have Cooling Equipment...... 17.8 4.0 2.4 1.7 Have Cooling Equipment...... 93.3 ...

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

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

    33.0 8.0 3.4 5.9 14.4 1.2 Do Not Have Cooling Equipment...... 17.8 6.5 1.6 0.9 1.3 2.4 0.2 Have Cooling Equipment...... 93.3 26.5 6.5 2.5 ...

  4. Airborne aerosol in situ measurements during TCAP: A closure study of total scattering

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

    Kassianov, Evgueni; Sedlacek, Arthur; Berg, Larry K.; Pekour, Mikhail; Barnard, James; Chand, Duli; Flynn, Connor; Ovchinnikov, Mikhail; Schmid, Beat; Shilling, John; et al

    2015-07-31

    We present a framework for calculating the total scattering of both non-absorbing and absorbing aerosol at ambient conditions from aircraft data. Our framework is developed emphasizing the explicit use of chemical composition data for estimating the complex refractive index (RI) of particles, and thus obtaining improved ambient size spectra derived from Optical Particle Counter (OPC) measurements. The feasibility of our framework for improved calculations of total scattering is demonstrated using three types of data collected by the U.S. Department of Energy’s (DOE) aircraft during the Two-Column Aerosol Project (TCAP). Namely, these data types are: (1) size distributions measured by amore » suite of OPC’s; (2) chemical composition data measured by an Aerosol Mass Spectrometer and a Single Particle Soot Photometer; and (3) the dry total scattering coefficient measured by a integrating nephelometer and scattering enhancement factor measured with a humidification system. We demonstrate that good agreement (~10%) between the observed and calculated scattering can be obtained under ambient conditions (RH < 80%) by applying chemical composition data for the RI-based correction of the OPC-derived size spectra. We also demonstrate that ignoring the RI-based correction or using non-representative RI values can cause a substantial underestimation (~40%) or overestimation (~35%) of the calculated scattering, respectively.« less

  5. Airborne aerosol in situ measurements during TCAP: A closure study of total scattering

    SciTech Connect (OSTI)

    Kassianov, Evgueni; Sedlacek, Arthur; Berg, Larry K.; Pekour, Mikhail; Barnard, James; Chand, Duli; Flynn, Connor; Ovchinnikov, Mikhail; Schmid, Beat; Shilling, John; Tomlinson, Jason; Fast, Jerome

    2015-07-31

    We present a framework for calculating the total scattering of both non-absorbing and absorbing aerosol at ambient conditions from aircraft data. Our framework is developed emphasizing the explicit use of chemical composition data for estimating the complex refractive index (RI) of particles, and thus obtaining improved ambient size spectra derived from Optical Particle Counter (OPC) measurements. The feasibility of our framework for improved calculations of total scattering is demonstrated using three types of data collected by the U.S. Department of Energy’s (DOE) aircraft during the Two-Column Aerosol Project (TCAP). Namely, these data types are: (1) size distributions measured by a suite of OPC’s; (2) chemical composition data measured by an Aerosol Mass Spectrometer and a Single Particle Soot Photometer; and (3) the dry total scattering coefficient measured by a integrating nephelometer and scattering enhancement factor measured with a humidification system. We demonstrate that good agreement (~10%) between the observed and calculated scattering can be obtained under ambient conditions (RH < 80%) by applying chemical composition data for the RI-based correction of the OPC-derived size spectra. We also demonstrate that ignoring the RI-based correction or using non-representative RI values can cause a substantial underestimation (~40%) or overestimation (~35%) of the calculated scattering, respectively.

  6. Manufacturing Consumption of Energy 1994 - Derived measures of...

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

    eialogo Calculation of MECS Energy Measures Reported energy values were used to construct several derived values, which, in turn, were used to prepare the estimates appearing in...

  7. Apparatus and method for quantitatively evaluating total fissile and total fertile nuclide content in samples

    DOE Patents [OSTI]

    Caldwell, John T. (Los Alamos, NM); Kunz, Walter E. (Santa Fe, NM); Cates, Michael R. (Oak Ridge, TN); Franks, Larry A. (Santa Barbara, CA)

    1985-01-01

    Simultaneous photon and neutron interrogation of samples for the quantitative determination of total fissile nuclide and total fertile nuclide material present is made possible by the use of an electron accelerator. Prompt and delayed neutrons produced from resulting induced fissions are counted using a single detection system and allow the resolution of the contributions from each interrogating flux leading in turn to the quantitative determination sought. Detection limits for .sup.239 Pu are estimated to be about 3 mg using prompt fission neutrons and about 6 mg using delayed neutrons.

  8. Determination of Total Solids in Biomass and Total Dissolved...

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

    ... The published moisture loss on drying for sodium tartrate is 15.62% (84.38% total solids). 14.6 Sample size: Determined by sample matrix. 14.7 Sample storage: Samples should be ...

  9. Total least squares for anomalous change detection

    SciTech Connect (OSTI)

    Theiler, James P; Matsekh, Anna M

    2010-01-01

    A family of difference-based anomalous change detection algorithms is derived from a total least squares (TLSQ) framework. This provides an alternative to the well-known chronochrome algorithm, which is derived from ordinary least squares. In both cases, the most anomalous changes are identified with the pixels that exhibit the largest residuals with respect to the regression of the two images against each other. The family of TLSQ-based anomalous change detectors is shown to be equivalent to the subspace RX formulation for straight anomaly detection, but applied to the stacked space. However, this family is not invariant to linear coordinate transforms. On the other hand, whitened TLSQ is coordinate invariant, and furthermore it is shown to be equivalent to the optimized covariance equalization algorithm. What whitened TLSQ offers, in addition to connecting with a common language the derivations of two of the most popular anomalous change detection algorithms - chronochrome and covariance equalization - is a generalization of these algorithms with the potential for better performance.

  10. Estimates of Savings Achievable from Irrigation Controller

    SciTech Connect (OSTI)

    Williams, Alison; Fuchs, Heidi; Whitehead, Camilla Dunham

    2014-03-28

    This paper performs a literature review and meta-analysis of water savings from several types of advanced irrigation controllers: rain sensors (RS), weather-based irrigation controllers (WBIC), and soil moisture sensors (SMS).The purpose of this work is to derive average water savings per controller type, based to the extent possible on all available data. After a preliminary data scrubbing, we utilized a series of analytical filters to develop our best estimate of average savings. We applied filters to remove data that might bias the sample such as data self-reported by manufacturers, data resulting from studies focusing on high-water users, or data presented in a non-comparable format such as based on total household water use instead of outdoor water use. Because the resulting number of studies was too small to be statistically significant when broken down by controller type, this paper represents a survey and synthesis of available data rather than a definitive statement regarding whether the estimated water savings are representative.

  11. TotalView Training 2015

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

    TotalView Training 2015 TotalView Training 2015 NERSC will host an in-depth training course on TotalView, a graphical parallel debugger developed by Rogue Wave Software, on Thursday, March 26, 2015. This will be provided by Rogue Wave Software staff members. The training will include a lecture and demo sessions in the morning, followed by a hands-on parallel debugging session in the afternoon. Location This event will be presented online using WebEx technology and in person at NERSC Oakland

  12. ARM - Measurement - Total cloud water

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

    cloud water ARM Data Discovery Browse Data Comments? We would love to hear from you Send us a note below or call us at 1-888-ARM-DATA. Send Measurement : Total cloud water The...

  13. U.S. Total Exports

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

    CA Otay Mesa, CA Alamo, TX Clint, TX Del Rio, TX Eagle Pass, TX El Paso, TX Freeport, TX Hidalgo, TX Laredo, TX McAllen, TX Penitas, TX Rio Bravo, TX Rio Grande, TX Roma, TX Total ...

  14. Characteristics RSE Column Factor: Total

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

    and 1994 Vehicle Characteristics RSE Column Factor: Total 1993 Family Income Below Poverty Line Eli- gible for Fed- eral Assist- ance 1 RSE Row Factor: Less than 5,000 5,000...

  15. 2014 Total Electric Industry- Customers

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

    Customers (Data from forms EIA-861- schedules 4A, 4B, 4D, EIA-861S and EIA-861U) State Residential Commercial Industrial Transportation Total New England 6,243,013 862,269 28,017 8 ...

  16. "2014 Total Electric Industry- Customers"

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

    Customers" "(Data from forms EIA-861- schedules 4A, 4B, 4D, EIA-861S and EIA-861U)" "State","Residential","Commercial","Industrial","Transportation","Total" "New England",6243013,8...

  17. Award Number: Federal Non-Federal Federal Non-Federal Total

    Office of Environmental Management (EM)

    B - Budget Categories Catalog of Federal Domestic Assistance Number Grant Program Function or Activity Estimated Unobligated Funds e. Supplies i. Total Direct Charges (sum of...

  18. Total aerosol effect: forcing or radiative flux perturbation?

    SciTech Connect (OSTI)

    Lohmann, Ulrike; Storelvmo, Trude; Jones, Andy; Rotstayn, Leon; Menon, Surabi; Quaas, Johannes; Ekman, Annica; Koch, Dorothy; Ruedy, Reto

    2009-09-25

    Uncertainties in aerosol forcings, especially those associated with clouds, contribute to a large extent to uncertainties in the total anthropogenic forcing. The interaction of aerosols with clouds and radiation introduces feedbacks which can affect the rate of rain formation. Traditionally these feedbacks were not included in estimates of total aerosol forcing. Here we argue that they should be included because these feedbacks act quickly compared with the time scale of global warming. We show that for different forcing agents (aerosols and greenhouse gases) the radiative forcings as traditionally defined agree rather well with estimates from a method, here referred to as radiative flux perturbations (RFP), that takes these fast feedbacks and interactions into account. Thus we propose replacing the direct and indirect aerosol forcing in the IPCC forcing chart with RFP estimates. This implies that it is better to evaluate the total anthropogenic aerosol effect as a whole.

  19. Measurements and modeling of total solar irradiance in X-class solar flares

    SciTech Connect (OSTI)

    Moore, Christopher Samuel; Chamberlin, Phillip Clyde; Hock, Rachel

    2014-05-20

    The Total Irradiance Monitor (TIM) from NASA's SOlar Radiation and Climate Experiment can detect changes in the total solar irradiance (TSI) to a precision of 2 ppm, allowing observations of variations due to the largest X-class solar flares for the first time. Presented here is a robust algorithm for determining the radiative output in the TIM TSI measurements, in both the impulsive and gradual phases, for the four solar flares presented in Woods et al., as well as an additional flare measured on 2006 December 6. The radiative outputs for both phases of these five flares are then compared to the vacuum ultraviolet (VUV) irradiance output from the Flare Irradiance Spectral Model (FISM) in order to derive an empirical relationship between the FISM VUV model and the TIM TSI data output to estimate the TSI radiative output for eight other X-class flares. This model provides the basis for the bolometric energy estimates for the solar flares analyzed in the Emslie et al. study.

  20. CATEGORY Total Procurement Total Small Business Small Disadvantaged

    National Nuclear Security Administration (NNSA)

    CATEGORY Total Procurement Total Small Business Small Disadvantaged Business Woman Owned Small Business HubZone Small Business Veteran-Owned Small Business Service Disabled Veteran Owned Small Business FY 2013 Dollars Accomplished $1,049,087,940 $562,676,028 $136,485,766 $106,515,229 $12,080,258 $63,473,852 $28,080,960 FY 2013 % Accomplishment 54.40% 13.00% 10.20% 1.20% 6.60% 2.70% FY 2014 Dollars Accomplished $868,961,755 $443,711,175 $92,478,522 $88,633,031 $29,867,820 $43,719,452 $26,826,374

  1. Performance Period Total Fee Paid FY2001

    Office of Environmental Management (EM)

    FY2001 $4,547,400 FY2002 $4,871,000 FY2003 $6,177,902 FY2004 $8,743,007 FY2005 $13,134,189 FY2006 $7,489,704 FY2007 $9,090,924 FY2008 $10,045,072 FY2009 $12,504,247 FY2010 $17,590,414 FY2011 $17,558,710 FY2012 $14,528,770 Cumulative Fee Paid $126,281,339 Cost Plus Award Fee DE-AC29-01AL66444 Washington TRU Solutions LLC Contractor: Contract Number: Contract Type: $8,743,007 Contract Period: $1,813,482,000 Fee Information Maximum Fee $131,691,744 Total Estimated Contract Cost: $4,547,400

  2. Performance Period Total Fee Paid FY2008

    Office of Environmental Management (EM)

    FY2008 $87,580 FY2009 $87,580 FY2010 $171,763 FY2011 $1,339,286 FY 2012 $38,126 FY 2013 $42,265 Cumulative Fee Paid $1,766,600 $42,265 Cost Plus Incentive Fee/Cost Plus Fixed Fee $36,602,425 Contract Period: September 2007 - November 30, 2012 Target Fee $521,595 Total Estimated Contract Cost Contract Type: Maximum Fee $3,129,570 $175,160 $377,516 $1,439,287 Fee Available $175,160 $80,871 Accelerated Remediation Company (aRc) DE-AT30-07CC60013 Contractor: Contract Number: Minimum Fee $2,086,380

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

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

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

  4. Total Adjusted Sales of Kerosene

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

    End Use: Total Residential Commercial Industrial Farm All Other Period: Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: End Use Area 2009 2010 2011 2012 2013 2014 View History U.S. 269,010 305,508 187,656 81,102 79,674 137,928 1984-2014 East Coast (PADD 1) 198,762 237,397 142,189 63,075 61,327 106,995 1984-2014 New England (PADD 1A) 56,661 53,363 38,448 15,983 15,991 27,500 1984-2014 Connecticut 8,800 7,437

  5. Total Imports of Residual Fuel

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

    Sep-15 Oct-15 Nov-15 Dec-15 Jan-16 Feb-16 View History U.S. Total 7,281 4,217 5,941 6,842 9,010 5,030 1936-2016 PAD District 1 4,571 2,206 2,952 3,174 3,127 2,664 1981-2016 Connecticut 1995-2015 Delaware 678 85 1995-2015 Florida 351 299 932 836 858 649 1995-2016 Georgia 120 295 210 262 1995-2016 Maine 1995-2015 Maryland 1995-2015 Massachusetts 1995-2015 New Hampshire 1995-2015 New Jersey 1,575 400 1,131 1,712 1,283 843 1995-2016 New York 1,475 998 350 322 234 824 1995-2016 North Carolina

  6. Estimates of US biomass energy consumption 1992

    SciTech Connect (OSTI)

    Not Available

    1994-05-06

    This report is the seventh in a series of publications developed by the Energy Information Administration (EIA) to quantify the biomass-derived primary energy used by the US economy. It presents estimates of 1991 and 1992 consumption. The objective of this report is to provide updated estimates of biomass energy consumption for use by Congress, Federal and State agencies, biomass producers and end-use sectors, and the public at large.

  7. Cost Estimation Package

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

    1997-03-28

    This chapter focuses on the components (or elements) of the cost estimation package and their documentation.

  8. ARM - Measurement - Shortwave broadband total downwelling irradiance

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

    Measurement : Shortwave broadband total downwelling irradiance The total diffuse and direct radiant energy that comes from some continuous range of directions, at wavelengths ...

  9. Total Space Heating Water Heating Cook-

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

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

  10. Total Space Heating Water Heating Cook-

    Gasoline and Diesel Fuel Update (EIA)

    Released: September, 2008 Total Space Heating Water Heating Cook- ing Other Total Space Heating Water Heating Cook- ing Other All Buildings* ... 1,870 1,276...

  11. Total Space Heating Water Heating Cook-

    Gasoline and Diesel Fuel Update (EIA)

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

  12. Total Space Heating Water Heating Cook-

    Gasoline and Diesel Fuel Update (EIA)

    Released: September, 2008 Total Space Heating Water Heating Cook- ing Other Total Space Heating Water Heating Cook- ing Other All Buildings* ... 1,602 1,397...

  13. Total Space Heating Water Heating Cook-

    Gasoline and Diesel Fuel Update (EIA)

    Released: September, 2008 Total Space Heating Water Heating Cook- ing Other Total Space Heating Water Heating Cook- ing Other All Buildings ... 2,037...

  14. ,"West Virginia Natural Gas Total Consumption (MMcf)"

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

    Data for" ,"Data 1","West Virginia Natural Gas Total Consumption ... AM" "Back to Contents","Data 1: West Virginia Natural Gas Total Consumption (MMcf)" ...

  15. ,"New Mexico Natural Gas Total Consumption (MMcf)"

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

    Data for" ,"Data 1","New Mexico Natural Gas Total Consumption ... AM" "Back to Contents","Data 1: New Mexico Natural Gas Total Consumption (MMcf)" ...

  16. Estimated United States Transportation Energy Use 2005

    SciTech Connect (OSTI)

    Smith, C A; Simon, A J; Belles, R D

    2011-11-09

    A flow chart depicting energy flow in the transportation sector of the United States economy in 2005 has been constructed from publicly available data and estimates of national energy use patterns. Approximately 31,000 trillion British Thermal Units (trBTUs) of energy were used throughout the United States in transportation activities. Vehicles used in these activities include automobiles, motorcycles, trucks, buses, airplanes, rail, and ships. The transportation sector is powered primarily by petroleum-derived fuels (gasoline, diesel and jet fuel). Biomass-derived fuels, electricity and natural gas-derived fuels are also used. The flow patterns represent a comprehensive systems view of energy used within the transportation sector.

  17. Using Utility Load Data to Estimate Demand for Space Cooling and Potential for Shiftable Loads

    SciTech Connect (OSTI)

    Denholm, P.; Ong, S.; Booten, C.

    2012-05-01

    This paper describes a simple method to estimate hourly cooling demand from historical utility load data. It compares total hourly demand to demand on cool days and compares these estimates of total cooling demand to previous regional and national estimates. Load profiles generated from this method may be used to estimate the potential for aggregated demand response or load shifting via cold storage.

  18. FY 2007 Total System Life Cycle Cost, Pub 2008 | Department of Energy

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

    FY 2007 Total System Life Cycle Cost, Pub 2008 FY 2007 Total System Life Cycle Cost, Pub 2008 The Analysis of the Total System Life Cycle Cost (TSLCC) of the Civilian Radioactive Waste Management Program presents the Office of Civilian Radioactive Waste Management's (OCRWM) May 2007 total system cost estimate for the disposal of the Nation's spent nuclear fuel (SNF) and high-level radioactive waste (HLW). The TSLCC analysis provides a basis for assessing the adequacy of the Nuclear Waste Fund

  19. Apparatus and method for quantitatively evaluating total fissile and total fertile nuclide content in samples. [Patent application

    DOE Patents [OSTI]

    Caldwell, J.T.; Kunz, W.E.; Cates, M.R.; Franks, L.A.

    1982-07-07

    Simultaneous photon and neutron interrogation of samples for the quantitative determination of total fissile nuclide and total fertile nuclide material present is made possible by the use of an electron accelerator. Prompt and delayed neutrons produced from resulting induced fission are counted using a single detection system and allow the resolution of the contributions from each interrogating flux leading in turn to the quantitative determination sought. Detection limits for /sup 239/Pu are estimated to be about 3 mg using prompt fission neutrons and about 6 mg using delayed neutrons.

  20. Check Estimates and Independent Costs

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

    1997-03-28

    Check estimates and independent cost estimates (ICEs) are tools that can be used to validate a cost estimate. Estimate validation entails an objective review of the estimate to ensure that estimate criteria and requirements have been met and well documented, defensible estimate has been developed. This chapter describes check estimates and their procedures and various types of independent cost estimates.

  1. Table A39. Total Expenditures for Purchased Electricity and Steam

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

    9. Total Expenditures for Purchased Electricity and Steam" " by Type of Supplier, Census Region, Census Division, and" " Economic Characteristics of the Establishment, 1994" " (Estimates in Million Dollars)" ," Electricity",," Steam" ,,,,,"RSE" ,"Utility","Nonutility","Utility","Nonutility","Row" "Economic

  2. State Energy Production Estimates

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

    Energy Production Estimates 1960 Through 2012 2012 Summary Tables Table P1. Energy Production Estimates in Physical Units, 2012 Alabama 19,455 215,710 9,525 0 Alaska 2,052 351,259...

  3. Types of Cost Estimates

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

    1997-03-28

    The chapter describes the estimates required on government-managed projects for both general construction and environmental management.

  4. Derivative expansion of the effective action

    SciTech Connect (OSTI)

    Cheyette, O.

    1987-04-01

    This paper describes some methods for calculating derivative terms in the one loop effective action for a quantum field theory. The functional approach and background field method are first used to derive the general form of the one loop determinant. Then the determinant is expanded in powers of derivatives of the background fields. The form of this expansion is described for the simple case of an interacting scalar field, and then for the more complicated problem of a non-abelian gauge field. Finally, the expansion is applied to the task of calculating Higgs mass dependent effects in the Glashow-Weinberg-Salam model, and all terms which grow with the Higgs mass M/sub H/ are found in the one loop approximation. The result of this calculation is used to find the dependence of the gauge boson mass ratio rho on M/sub H/, and also to estimate the size of corrections to W and Z scattering theorems.

  5. Award Number: Federal Non-Federal Federal Non-Federal Total

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

    i. Total Direct Charges (sum of 6a-6h) Grant Program, Function or Activity Object Class ... Catalog of Federal Domestic Assistance Number Grant Program Function or Activity Estimated ...

  6. Population Estimates for Chum Salmon Spawning in the Mainstem Columbia River, 2002 Technical Report.

    SciTech Connect (OSTI)

    Rawding, Dan; Hillson, Todd D.

    2003-11-15

    Accurate and precise population estimates of chum salmon (Oncorhynchus keta) spawning in the mainstem Columbia River are needed to provide a basis for informed water allocation decisions, to determine the status of chum salmon listed under the Endangered Species Act, and to evaluate the contribution of the Duncan Creek re-introduction program to mainstem spawners. Currently, mark-recapture experiments using the Jolly-Seber model provide the only framework for this type of estimation. In 2002, a study was initiated to estimate mainstem Columbia River chum salmon populations using seining data collected while capturing broodstock as part of the Duncan Creek re-introduction. The five assumptions of the Jolly-Seber model were examined using hypothesis testing within a statistical framework, including goodness of fit tests and secondary experiments. We used POPAN 6, an integrated computer system for the analysis of capture-recapture data, to obtain maximum likelihood estimates of standard model parameters, derived estimates, and their precision. A more parsimonious final model was selected using Akaike Information Criteria. Final chum salmon escapement estimates and (standard error) from seining data for the Ives Island, Multnomah, and I-205 sites are 3,179 (150), 1,269 (216), and 3,468 (180), respectively. The Ives Island estimate is likely lower than the total escapement because only the largest two of four spawning sites were sampled. The accuracy and precision of these estimates would improve if seining was conducted twice per week instead of weekly, and by incorporating carcass recoveries into the analysis. Population estimates derived from seining mark-recapture data were compared to those obtained using the current mainstem Columbia River salmon escapement methodologies. The Jolly-Seber population estimate from carcass tagging in the Ives Island area was 4,232 adults with a standard error of 79. This population estimate appears reasonable and precise but batch marks and lack of secondary studies made it difficult to test Jolly-Seber assumptions, necessary for unbiased estimates. We recommend that individual tags be applied to carcasses to provide a statistical basis for goodness of fit tests and ultimately model selection. Secondary or double marks should be applied to assess tag loss and male and female chum salmon carcasses should be enumerated separately. Carcass tagging population estimates at the two other sites were biased low due to limited sampling. The Area-Under-the-Curve escapement estimates at all three sites were 36% to 76% of Jolly-Seber estimates. Area-Under-the Curve estimates are likely biased low because previous assumptions that observer efficiency is 100% and residence time is 10 days proved incorrect. If managers continue to rely on Area-Under-the-Curve to estimate mainstem Columbia River spawners, a methodology is provided to develop annual estimates of observer efficiency and residence time, and to incorporate uncertainty into the Area-Under-the-Curve escapement estimate.

  7. Estimating Uranium Partition Coefficients from Laboratory Adsorption Isotherms

    SciTech Connect (OSTI)

    Hull, L.C.; Grossman, C.; Fjeld, R.A.; Coates, J.T.; Elzerman, A.W.

    2002-05-10

    An estimated 330 metric tons of uranium have been buried in the radioactive waste Subsurface Disposal Area (SDA) at the Idaho National Engineering and Environmental Laboratory (INEEL). An assessment of uranium transport parameters is being performed to decrease the uncertainty in risk and dose predictions derived from computer simulations of uranium fate and transport to the underlying Snake River Plain Aquifer. Uranium adsorption isotherms have been measured in the laboratory and fit with a Freundlich isotherm. The Freundlich n parameter was statistically identical for 14 sediment samples. The Freundlich Kf for seven samples, where material properties have been measured, is correlated to sediment surface area. Based on these empirical observations, a model has been derived for adsorption of uranium on INEEL sedimentary materials using surface complexation theory. The model was then used to predict the range of adsorption conditions to be expected at the SDA. Adsorption in the deep vadose zone is predicted to be stronger than in near-surface sediments because the total dissolved carbonate decreases with depth.

  8. Estimating Uranium Partition Coefficients from Laboratory Adsorption Isotherms

    SciTech Connect (OSTI)

    Hull, Laurence Charles; Grossman, Christopher; Fjeld, R. A.; Coates, C.J.; Elzerman, A.

    2002-08-01

    An estimated 330 metric tons of uranium have been buried in the radioactive waste Subsurface Disposal Area (SDA) at the Idaho National Engineering and Environmental Laboratory (INEEL). An assessment of uranium transport parameters is being performed to decrease the uncertainty in risk and dose predictions derived from computer simulations of uranium fate and transport to the underlying Snake River Plain Aquifer. Uranium adsorption isotherms have been measured in the laboratory and fit with a Freundlich isotherm. The Freundlich n parameter was statistically identical for 14 sediment samples. The Freundlich Kf for seven samples, where material properties have been measured, is correlated to sediment surface area. Based on these empirical observations, a model has been derived for adsorption of uranium on INEEL sedimentary materials using surface complexation theory. The model was then used to predict the range of adsorption conditions to be expected at the SDA. Adsorption in the deep vadose zone is predicted to be stronger than in near-surface sediments because the total dissolved carbonate decreases with depth.

  9. Estimates of U.S. Biomass Energy Consumption 1992

    Reports and Publications (EIA)

    1994-01-01

    This report is the seventh in a series of publications developed by the Energy Information Administration (EIA) to quantify the biomass derived primary energy used by the U.S. economy. It presents estimates of 1991 and 1992 consumption.

  10. Total Space Heating Water Heating Cook-

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

    Tables Total Space Heating Water Heating Cook- ing Other Total Space Heating Water Heating Cook- ing Other All Buildings* ... 634 578 46 1 Q 116.4 106.3...

  11. Total System Performance Assessment Peer Review Panel

    Broader source: Energy.gov [DOE]

    Total System Performance Assessment (TSPA) Peer Review Panel for predicting the performance of a repository at Yucca Mountain.

  12. Million Cu. Feet Percent of National Total

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

    2 Alaska - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S2. Summary statistics for natural gas - Alaska, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 269 277 185 R 159 170 Production (million cubic feet) Gross Withdrawals From Gas Wells 127,417 112,268

  13. Million Cu. Feet Percent of National Total

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

    6 District of Columbia - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S9. Summary statistics for natural gas - District of Columbia, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells

  14. Million Cu. Feet Percent of National Total

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

    4 Massachusetts - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S23. Summary statistics for natural gas - Massachusetts, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0

  15. Million Cu. Feet Percent of National Total

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

    50 North Dakota - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S36. Summary statistics for natural gas - North Dakota, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 188 239 211 200 200 Production (million cubic feet) Gross Withdrawals From Gas Wells

  16. Million Cu. Feet Percent of National Total

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

    6 Washington - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S49. Summary statistics for natural gas - Washington, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil

  17. Total Activity Estimation - Quarry Area. QY-500-501-1.06.

    Office of Legacy Management (LM)

  18. Pushing schedule derivation method

    SciTech Connect (OSTI)

    Henriquez, B.

    1996-12-31

    The development of a Pushing Schedule Derivation Method has allowed the company to sustain the maximum production rate at CSH`s Coke Oven Battery, in spite of having single set oven machinery with a high failure index as well as a heat top tendency. The stated method provides for scheduled downtime of up to two hours for machinery maintenance purposes, periods of empty ovens for decarbonization and production loss recovery capability, while observing lower limits and uniformity of coking time.

  19. Reservoir Temperature Estimator

    Energy Science and Technology Software Center (OSTI)

    2014-12-08

    The Reservoir Temperature Estimator (RTEst) is a program that can be used to estimate deep geothermal reservoir temperature and chemical parameters such as CO2 fugacity based on the water chemistry of shallower, cooler reservoir fluids. This code uses the plugin features provided in The Geochemist’s Workbench (Bethke and Yeakel, 2011) and interfaces with the model-independent parameter estimation code Pest (Doherty, 2005) to provide for optimization of the estimated parameters based on the minimization of themore » weighted sum of squares of a set of saturation indexes from a user-provided mineral assemblage.« less

  20. Estimate of Geothermal Energy Resource in Major U.S. Sedimentary Basins (Presentation)

    SciTech Connect (OSTI)

    Porro, C.; Augustine, C.

    2012-04-01

    This study estimates the magnitude of geothermal energy from fifteen major known US sedimentary basins and ranks these basins relative to their potential. Because most sedimentary basins have been explored for oil and gas, well logs, temperatures at depth, and reservoir properties are known. This reduces exploration risk and allows development of geologic exploration models for each basin as well as a relative assessment of geologic risk elements for each play. The total available thermal resource for each basin was estimated using the volumetric heat-in-place method originally proposed by Muffler (USGS). Total sedimentary thickness maps, stratigraphic columns, cross sections, and temperature gradient Information were gathered for each basin from published articles, USGS reports, and state geological survey reports. When published data was insufficient, thermal gradients and reservoir properties were derived from oil and gas well logs obtained on oil and gas commission websites. Basin stratigraphy, structural history, and groundwater circulation patterns were studied in order to develop a model that estimates resource size and temperature distribution, and to qualitatively assess reservoir productivity.

  1. Estimate of the Geothermal Energy Resource in the Major Sedimentary Basins in the United States (Presentation)

    SciTech Connect (OSTI)

    Esposito, A.; Porro, C.; Augustine, C.; Roberts, B.

    2012-09-01

    Because most sedimentary basins have been explored for oil and gas, well logs, temperatures at depth, and reservoir properties such as depth to basement and formation thickness are well known. The availability of this data reduces exploration risk and allows development of geologic exploration models for each basin. This study estimates the magnitude of recoverable geothermal energy from 15 major known U.S. sedimentary basins and ranks these basins relative to their potential. The total available thermal resource for each basin was estimated using the volumetric heat-in-place method originally proposed by (Muffler, 1979). A qualitative recovery factor was determined for each basin based on data on flow volume, hydrothermal recharge, and vertical and horizontal permeability. Total sedimentary thickness maps, stratigraphic columns, cross sections, and temperature gradient information was gathered for each basin from published articles, USGS reports, and state geological survey reports. When published data were insufficient, thermal gradients and reservoir properties were derived from oil and gas well logs obtained on oil and gas commission databases. Basin stratigraphy, structural history, and groundwater circulation patterns were studied in order to develop a model that estimates resource size, temperature distribution, and a probable quantitative recovery factor.

  2. AN OVERVIEW OF TOOL FOR RESPONSE ACTION COST ESTIMATING (TRACE)

    SciTech Connect (OSTI)

    FERRIES SR; KLINK KL; OSTAPKOWICZ B

    2012-01-30

    Tools and techniques that provide improved performance and reduced costs are important to government programs, particularly in current times. An opportunity for improvement was identified for preparation of cost estimates used to support the evaluation of response action alternatives. As a result, CH2M HILL Plateau Remediation Company has developed Tool for Response Action Cost Estimating (TRACE). TRACE is a multi-page Microsoft Excel{reg_sign} workbook developed to introduce efficiencies into the timely and consistent production of cost estimates for response action alternatives. This tool combines costs derived from extensive site-specific runs of commercially available remediation cost models with site-specific and estimator-researched and derived costs, providing the best estimating sources available. TRACE also provides for common quantity and key parameter links across multiple alternatives, maximizing ease of updating estimates and performing sensitivity analyses, and ensuring consistency.

  3. Estimating Specialty Costs

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

    1997-03-28

    Specialty costs are those nonstandard, unusual costs that are not typically estimated. Costs for research and development (R&D) projects involving new technologies, costs associated with future regulations, and specialty equipment costs are examples of specialty costs. This chapter discusses those factors that are significant contributors to project specialty costs and methods of estimating costs for specialty projects.

  4. Energy and materials flows in the production of olefins and their derivatives

    SciTech Connect (OSTI)

    Gaines, L.L.; Shen, S.Y.

    1980-08-01

    Production of olefins and their derivatives uses almost 3.5% of the oil and gas consumed annually in the United States. It is estimated that their production requires an input energy of 2 Q, which is 50% of the energy used in the production of all petrochemicals. Substantial amounts of this energy could be recovered through recycling. For example, recycling of a single plastic product, polyester soft drink bottles, could have recovered about 0.014 Q in 1979. (About 1.4 Q is used to produce plastic derivatives of olefins). Petrochemical processes use fuels as feedstocks, as well as for process energy, and a portion of this energy is not foregone and can be recovered through combustion of the products. The energy foregone in the production of ethylene is estimated to be 7800 Btu/lb. The energy foregone in plastics production ranges from 12,100 Btu/lb for the new linear low-density polyethylene to 77,200 Btu/lb for nylon 66, which is about 60% of the total energy input for that product. Further investigation of the following areas could yield both material and energy savings in the olefins industry: (1) recycling of petrochemical products to recover energy in addition to that recoverable through combustion, (2) impact of feedstock substitution on utilization of available national resources, and (3) effective use of the heat embodied in process steam. This steam accounts for a major fraction of the industry's energy input.

  5. Total Natural Gas Underground Storage Capacity

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

    Storage Capacity Salt Caverns Storage Capacity Aquifers Storage Capacity Depleted Fields Storage Capacity Total Working Gas Capacity Working Gas Capacity of Salt Caverns Working...

  6. ARM - Measurement - Shortwave narrowband total downwelling irradiance

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

    Send Measurement : Shortwave narrowband total downwelling irradiance The rate at which radiant energy, in narrow bands of wavelengths shorter than approximately 4 mum, passes ...

  7. ARM - Measurement - Shortwave narrowband total upwelling irradiance

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

    Send Measurement : Shortwave narrowband total upwelling irradiance The rate at which radiant energy, in narrow bands of wavelengths shorter than approximately 4 mum, passes ...

  8. ARM - Measurement - Shortwave spectral total downwelling irradiance

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

    Send Measurement : Shortwave spectral total downwelling irradiance The rate at which radiant energy, at specrally-resolved wavelengths between 0.4 and 4 mum, is being emitted ...

  9. 2014 Total Electric Industry- Sales (Megawatthours

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

    EIA-861U)" "State","Residential","Commercial","Industrial","Transportation","Total" "New England",47211525,53107038,19107433,557463,119983459 "Connecticut",12777579,12893531,351479...

  10. Total Supplemental Supply of Natural Gas

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

    Product: Total Supplemental Supply Synthetic Propane-Air Refinery Gas Biomass Other Period: Monthly Annual Download Series History Download Series History Definitions, Sources & ...

  11. Million Cu. Feet Percent of National Total

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

    0 Alabama - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S1. Summary statistics for natural gas - Alabama, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 7,026 7,063 6,327 R 6,165 6,118 Production (million cubic feet) Gross Withdrawals From Gas Wells

  12. Million Cu. Feet Percent of National Total

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

    0 Colorado - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S6. Summary statistics for natural gas - Colorado, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 28,813 30,101 32,000 R 32,468 38,346 Production (million cubic feet) Gross Withdrawals From Gas

  13. Million Cu. Feet Percent of National Total

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

    8 Florida - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S10. Summary statistics for natural gas - Florida, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 17,182 16,459 19,742

  14. Million Cu. Feet Percent of National Total

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

    4 Hawaii - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S13. Summary statistics for natural gas - Hawaii, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0

  15. Million Cu. Feet Percent of National Total

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

    6 Idaho - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S14. Summary statistics for natural gas - Idaho, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0

  16. Million Cu. Feet Percent of National Total

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

    4 Kansas - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S18. Summary statistics for natural gas - Kansas, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 22,145 25,758 24,697 R 23,792 24,354 Production (million cubic feet) Gross Withdrawals From Gas Wells

  17. Million Cu. Feet Percent of National Total

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

    8 Louisiana - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S20. Summary statistics for natural gas - Louisiana, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 19,137 21,235 19,792 R 19,528 19,251 Production (million cubic feet) Gross Withdrawals From Gas

  18. Million Cu. Feet Percent of National Total

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

    4 New Mexico - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S33. Summary statistics for natural gas - New Mexico, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 44,748 32,302 28,206 R 27,073 27,957 Production (million cubic feet) Gross Withdrawals From

  19. Million Cu. Feet Percent of National Total

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

    6 Oregon - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S39. Summary statistics for natural gas - Oregon, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 26 24 27 R 26 28 Production (million cubic feet) Gross Withdrawals From Gas Wells 1,407 1,344 770 770

  20. Million Cu. Feet Percent of National Total

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

    Total Net Movements: - Industrial: Dry Production: Vehicle ... due to independent rounding. Prices are in nominal dollars. ... Annual Consumption per Consumer (thousand cubic feet) ...

  1. Million Cu. Feet Percent of National Total

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

    from Electric Power to Industrial for years 2002 through ... Totals may not add due to independent rounding. Prices are ... Annual Consumption per Consumer (thousand cubic feet) ...

  2. Cost Estimating Handbook for Environmental Restoration

    SciTech Connect (OSTI)

    1990-09-01

    Environmental restoration (ER) projects have presented the DOE and cost estimators with a number of properties that are not comparable to the normal estimating climate within DOE. These properties include: An entirely new set of specialized expressions and terminology. A higher than normal exposure to cost and schedule risk, as compared to most other DOE projects, due to changing regulations, public involvement, resource shortages, and scope of work. A higher than normal percentage of indirect costs to the total estimated cost due primarily to record keeping, special training, liability, and indemnification. More than one estimate for a project, particularly in the assessment phase, in order to provide input into the evaluation of alternatives for the cleanup action. While some aspects of existing guidance for cost estimators will be applicable to environmental restoration projects, some components of the present guidelines will have to be modified to reflect the unique elements of these projects. The purpose of this Handbook is to assist cost estimators in the preparation of environmental restoration estimates for Environmental Restoration and Waste Management (EM) projects undertaken by DOE. The DOE has, in recent years, seen a significant increase in the number, size, and frequency of environmental restoration projects that must be costed by the various DOE offices. The coming years will show the EM program to be the largest non-weapons program undertaken by DOE. These projects create new and unique estimating requirements since historical cost and estimating precedents are meager at best. It is anticipated that this Handbook will enhance the quality of cost data within DOE in several ways by providing: The basis for accurate, consistent, and traceable baselines. Sound methodologies, guidelines, and estimating formats. Sources of cost data/databases and estimating tools and techniques available at DOE cost professionals.

  3. Total-system performance assessment for Yucca Mountain - SNL second iteration (TSPA-1993); Volume 1

    SciTech Connect (OSTI)

    Wilson, M.L.; Gauthier, J.H.; Barnard, R.W.; Barr, G.E.; Dockery, H.A.; Dunn, E.; Eaton, R.R.; Guerin, D.C.; Lu, N.; Martinez, M.J.

    1994-04-01

    Sandia National Laboratories has completed the second iteration of the periodic total-system performance assessments (TSPA-93) for the Yucca Mountain Site Characterization Project (YMP). These analyses estimate the future behavior of a potential repository for high-level nuclear waste at the Yucca Mountain, Nevada, site under consideration by the Department of Energy. TSPA-93 builds upon previous efforts by emphasizing YMP concerns relating to site characterization, design, and regulatory compliance. Scenarios describing expected conditions (aqueous and gaseous transport of contaminants) and low-probability events (human-intrusion drilling and volcanic intrusion) are modeled. The hydrologic processes modeled include estimates of the perturbations to ambient conditions caused by heating of the repository resulting from radioactive decay of the waste. Hydrologic parameters and parameter probability distributions have been derived from available site data. Possible future climate changes are modeled by considering two separate groundwater infiltration conditions: {open_quotes}wet{close_quotes} with a mean flux of 10 mm/yr, and {open_quotes}dry{close_quotes} with a mean flux of 0.5 mm/yr. Two alternative waste-package designs and two alternative repository areal thermal power densities are investigated. One waste package is a thin-wall container emplaced in a vertical borehole, and the second is a container designed with corrosion-resistant and corrosion-allowance walls emplaced horizontally in the drift. Thermal power loadings of 57 kW/acre (the loading specified in the original repository conceptual design) and 114 kW/acre (a loading chosen to investigate effects of a {open_quotes}hot repository{close_quotes}) are considered. TSPA-93 incorporates significant new detailed process modeling, including two- and three-dimensional modeling of thermal effects, groundwater flow in the saturated-zone aquifers, and gas flow in the unsaturated zone.

  4. Building unbiased estimators from non-Gaussian likelihoods with application to shear estimation

    SciTech Connect (OSTI)

    Madhavacheril, Mathew S.; Sehgal, Neelima; McDonald, Patrick; Slosar, Ane E-mail: pvmcdonald@lbl.gov E-mail: anze@bnl.gov

    2015-01-01

    We develop a general framework for generating estimators of a given quantity which are unbiased to a given order in the difference between the true value of the underlying quantity and the fiducial position in theory space around which we expand the likelihood. We apply this formalism to rederive the optimal quadratic estimator and show how the replacement of the second derivative matrix with the Fisher matrix is a generic way of creating an unbiased estimator (assuming choice of the fiducial model is independent of data). Next we apply the approach to estimation of shear lensing, closely following the work of Bernstein and Armstrong (2014). Our first order estimator reduces to their estimator in the limit of zero shear, but it also naturally allows for the case of non-constant shear and the easy calculation of correlation functions or power spectra using standard methods. Both our first-order estimator and Bernstein and Armstrong's estimator exhibit a bias which is quadratic in true shear. Our third-order estimator is, at least in the realm of the toy problem of Bernstein and Armstrong, unbiased to 0.1% in relative shear errors ?g/g for shears up to |g|=0.2.

  5. Building unbiased estimators from non-gaussian likelihoods with application to shear estimation

    SciTech Connect (OSTI)

    Madhavacheril, Mathew S.; Slosar, Anze; McDonald, Patrick; Sehgal, Neelima

    2015-01-01

    We develop a general framework for generating estimators of a given quantity which are unbiased to a given order in the difference between the true value of the underlying quantity and the fiducial position in theory space around which we expand the likelihood. We apply this formalism to rederive the optimal quadratic estimator and show how the replacement of the second derivative matrix with the Fisher matrix is a generic way of creating an unbiased estimator (assuming choice of the fiducial model is independent of data). Next we apply the approach to estimation of shear lensing, closely following the work of Bernstein and Armstrong (2014). Our first order estimator reduces to their estimator in the limit of zero shear, but it also naturally allows for the case of non-constant shear and the easy calculation of correlation functions or power spectra using standard methods. Both our first-order estimator and Bernstein and Armstrongs estimator exhibit a bias which is quadratic in true shear. Our third-order estimator is, at least in the realm of the toy problem of Bernstein and Armstrong, unbiased to 0.1% in relative shear errors ?g/g for shears up to |g| = 0.2.

  6. Building unbiased estimators from non-gaussian likelihoods with application to shear estimation

    SciTech Connect (OSTI)

    Madhavacheril, Mathew S.; McDonald, Patrick; Sehgal, Neelima; Slosar, Anze

    2015-01-15

    We develop a general framework for generating estimators of a given quantity which are unbiased to a given order in the difference between the true value of the underlying quantity and the fiducial position in theory space around which we expand the likelihood. We apply this formalism to rederive the optimal quadratic estimator and show how the replacement of the second derivative matrix with the Fisher matrix is a generic way of creating an unbiased estimator (assuming choice of the fiducial model is independent of data). Next we apply the approach to estimation of shear lensing, closely following the work of Bernstein and Armstrong (2014). Our first order estimator reduces to their estimator in the limit of zero shear, but it also naturally allows for the case of non-constant shear and the easy calculation of correlation functions or power spectra using standard methods. Both our first-order estimator and Bernstein and Armstrongs estimator exhibit a bias which is quadratic in true shear. Our third-order estimator is, at least in the realm of the toy problem of Bernstein and Armstrong, unbiased to 0.1% in relative shear errors ?g/g for shears up to |g| = 0.2.

  7. Building unbiased estimators from non-gaussian likelihoods with application to shear estimation

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

    Madhavacheril, Mathew S.; McDonald, Patrick; Sehgal, Neelima; Slosar, Anze

    2015-01-15

    We develop a general framework for generating estimators of a given quantity which are unbiased to a given order in the difference between the true value of the underlying quantity and the fiducial position in theory space around which we expand the likelihood. We apply this formalism to rederive the optimal quadratic estimator and show how the replacement of the second derivative matrix with the Fisher matrix is a generic way of creating an unbiased estimator (assuming choice of the fiducial model is independent of data). Next we apply the approach to estimation of shear lensing, closely following the workmore » of Bernstein and Armstrong (2014). Our first order estimator reduces to their estimator in the limit of zero shear, but it also naturally allows for the case of non-constant shear and the easy calculation of correlation functions or power spectra using standard methods. Both our first-order estimator and Bernstein and Armstrong’s estimator exhibit a bias which is quadratic in true shear. Our third-order estimator is, at least in the realm of the toy problem of Bernstein and Armstrong, unbiased to 0.1% in relative shear errors Δg/g for shears up to |g| = 0.2.« less

  8. Algae Derived Biofuel

    SciTech Connect (OSTI)

    Jahan, Kauser

    2015-03-31

    One of the most promising fuel alternatives is algae biodiesel. Algae reproduce quickly, produce oils more efficiently than crop plants, and require relatively few nutrients for growth. These nutrients can potentially be derived from inexpensive waste sources such as flue gas and wastewater, providing a mutual benefit of helping to mitigate carbon dioxide waste. Algae can also be grown on land unsuitable for agricultural purposes, eliminating competition with food sources. This project focused on cultivating select algae species under various environmental conditions to optimize oil yield. Membrane studies were also conducted to transfer carbon di-oxide more efficiently. An LCA study was also conducted to investigate the energy intensive steps in algae cultivation.

  9. 2009 Total Energy Production by State | Department of Energy

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

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

  10. Cost Estimating Guide

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

    2011-05-09

    This Guide provides uniform guidance and best practices that describe the methods and procedures that could be used in all programs and projects at DOE for preparing cost estimates. No cancellations.

  11. Distribution System State Estimation

    Office of Scientific and Technical Information (OSTI)

    This Notice shall be affixed to any reproductions of these data in whole or in part. Executive Summary State estimation is a key enabler for any number of "smart grid" applications ...

  12. Cost Estimating Guide

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

    1997-03-28

    The objective of this Guide is to improve the quality of cost estimates and further strengthen the DOE program/project management system. The original 25 separate chapters and three appendices have been combined to create a single document.

  13. Cost Estimating Guide

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

    2011-05-09

    This Guide provides uniform guidance and best practices that describe the methods and procedures that could be used in all programs and projects at DOE for preparing cost estimates.

  14. Sulfur dioxide capture in the combustion of mixtures of lime, refuse-derived fuel, and coal

    SciTech Connect (OSTI)

    Churney, K.L.; Buckley, T.J. . Center for Chemical Technology)

    1990-06-01

    Chlorine and sulfur mass balance studies have been carried out in the combustion of mixtures of lime, refuse-derived fuel, and coal in the NIST multikilogram capacity batch combustor. The catalytic effect of manganese dioxide on the trapping of sulfur dioxide by lime was examined. Under our conditions, only 4% of the chlorine was trapped in the ash and no effect of manganese dioxide was observed. Between 42 and 14% of the total sulfur was trapped in the ash, depending upon the lime concentration. The effect of manganese dioxide on sulfur capture was not detectable. The temperature of the ash was estimated to be near 1200{degrees}C, which was in agreement with that calculated from sulfur dioxide capture thermodynamics. 10 refs., 12 figs., 10 tabs.

  15. ARM - Measurement - Shortwave broadband total upwelling irradiance

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

    Send Measurement : Shortwave broadband total upwelling irradiance The rate at which radiant energy, at a wavelength between 0.4 and 4 mum, is being emitted upwards into a ...

  16. "2014 Total Electric Industry- Revenue (Thousands Dollars)"

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

    EIA-861U)" "State","Residential","Commercial","Industrial","Transportation","Total" "New England",8414175.4,7806276.7,2262752.4,57837.4,18541041.8 "Connecticut",2523348.7,2004629.1...

  17. 2014 Total Electric Industry- Revenue (Thousands Dollars)

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

    Revenue (Thousands Dollars) (Data from forms EIA-861- schedules 4A-D, EIA-861S and EIA-861U) State Residential Commercial Industrial Transportation Total New England 8,414,175 ...

  18. Million Cu. Feet Percent of National Total

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

    8 Minnesota - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet ... Summary statistics for natural gas - Minnesota, 2010-2014 2010 2011 2012 2013 2014 ...

  19. EQUUS Total Return Inc | Open Energy Information

    Open Energy Info (EERE)

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

  20. Million Cu. Feet Percent of National Total

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

    Totals may not add due to independent rounding. Prices are ... 250,994 253,127 Industrial 9,332 9,088 8,833 8,497 8,156 Average Annual Consumption per Consumer (thousand cubic ...

  1. Million Cu. Feet Percent of National Total

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

    Notes: Totals may not add due to independent rounding. Prices ... 34,078 34,283 34,339 Industrial 102 94 97 95 92 Average Annual Consumption per Consumer (thousand cubic feet) ...

  2. Million Cu. Feet Percent of National Total

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

    as known volumes of natural gas that were the result of leaks, damage, accidents, migration, andor blow down. Notes: Totals may not add due to independent rounding. Prices are...

  3. TotalView Parallel Debugger at NERSC

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

    The performance of the GUI can be greatly improved if used in conjunction with free NX software. The TotalView documentation web page is a good resource for learning more...

  4. Million Cu. Feet Percent of National Total

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

    to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S11. ... 2,314 764 719 180 4,046 Supplemental Gas Supplies 732 701 660 642 635 Balancing Item ...

  5. Million Cu. Feet Percent of National Total

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

    to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S35. ... 3,762 7,315 10,303 Supplemental Gas Supplies 0 0 0 0 0 Balancing Item 65,897 -19,970 ...

  6. Million Cu. Feet Percent of National Total

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

    to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S7. ... 473 526 484 626 1,359 Supplemental Gas Supplies 0 0 0 0 0 Balancing Item -6,645 3,976 ...

  7. Million Cu. Feet Percent of National Total

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

    to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S31. ... 35 108 71 124 185 Supplemental Gas Supplies 0 0 0 0 0 Balancing Item -1,393 -3,726 ...

  8. Million Cu. Feet Percent of National Total

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

    to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S51. ... 92 87 100 89 138 Supplemental Gas Supplies 0 0 0 0 0 Balancing Item -2,885 -12,890 ...

  9. Million Cu. Feet Percent of National Total

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

    to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S8. ... 76 96 66 131 128 Supplemental Gas Supplies 1 0 * * 6 Balancing Item 3,249 7,362 ...

  10. Million Cu. Feet Percent of National Total

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

    to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S17. ... 1,844 980 2,403 2,701 Supplemental Gas Supplies 2 1 0 0 1 Balancing Item -1,989 -7,914 ...

  11. Million Cu. Feet Percent of National Total

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

    to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S32. ... 4,404 3,278 5,208 6,218 Supplemental Gas Supplies 457 392 139 255 530 Balancing Item ...

  12. Million Cu. Feet Percent of National Total

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

    to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S41. ... 698 436 457 645 879 Supplemental Gas Supplies 0 0 0 0 0 Balancing Item -1,269 1,045 ...

  13. Million Cu. Feet Percent of National Total

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

    to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S47. ... 0 LNG Storage 0 0 0 0 0 Supplemental Gas Supplies 1 2 3 3 5 Balancing Item -453 -1,711 ...

  14. Million Cu. Feet Percent of National Total

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

    to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S30. ... 195 154 146 210 211 Supplemental Gas Supplies 0 0 0 0 0 Balancing Item 17,590 4,622 ...

  15. Table 1.3 Primary Energy Consumption Estimates by Source, 1949...

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

    3 Primary Energy Consumption Estimates by Source, 1949-2011 (Quadrillion Btu) Year Fossil Fuels Nuclear Electric Power Renewable Energy 1 Electricity Net Imports 3 Total Coal Coal ...

  16. A METHOD FOR ESTIMATING GAS PRESSURE IN 3013 CONTAINERS USING AN ISP DATABASE QUERY

    SciTech Connect (OSTI)

    Friday, G; L. G. Peppers, L; D. K. Veirs, D

    2008-07-31

    The U.S. Department of Energy's Integrated Surveillance Program (ISP) is responsible for the storage and surveillance of plutonium-bearing material. During storage, plutonium-bearing material has the potential to generate hydrogen gas from the radiolysis of adsorbed water. The generation of hydrogen gas is a safety concern, especially when a container is breached within a glove box during destructive evaluation. To address this issue, the DOE established a standard (DOE, 2004) that sets the criteria for the stabilization and packaging of material for up to 50 years. The DOE has now packaged most of its excess plutonium for long-term storage in compliance with this standard. As part of this process, it is desirable to know within reasonable certainty the total maximum pressure of hydrogen and other gases within the 3013 container if safety issues and compliance with the DOE standards are to be attained. The principal goal of this investigation is to document the method and query used to estimate total (i.e. hydrogen and other gases) gas pressure within a 3013 container based on the material properties and estimated moisture content contained in the ISP database. Initial attempts to estimate hydrogen gas pressure in 3013 containers was based on G-values (hydrogen gas generation per energy input) derived from small scale samples. These maximum G-values were used to calculate worst case pressures based on container material weight, assay, wattage, moisture content, container age, and container volume. This paper documents a revised hydrogen pressure calculation that incorporates new surveillance results and includes a component for gases other than hydrogen. The calculation is produced by executing a query of the ISP database. An example of manual mathematical computations from the pressure equation is compared and evaluated with results from the query. Based on the destructive evaluation of 17 containers, the estimated mean absolute pressure was significantly higher (P<.01) than the mean GEST pressure. There was no significant difference (P>.10) between the mean pressures from DR and the calculation. The mean predicted absolute pressure was consistently higher than GEST by an average difference of 57 kPa (8 psi). The mean difference between the estimated pressure and digital radiography was 11 kPa (2 psi). Based on the initial results of destructive evaluation, the pressure query was found to provide a reasonably conservative estimate of the total pressure in 3013 containers whose material contained minimal moisture content.

  17. REQUESTS FOR RETIREMENT ESTIMATE

    Energy Savers [EERE]

    REQUEST FOR RETIREMENT ANNUITY ESTIMATE Instructions: Please read and answer the following questions thoroughly to include checking all applicable boxes. Unanswered questions may delay processing. Print and Fax back your request form to 202.586.6395 or drop request to GM-169. The request will be assigned to your servicing retirement specialist. They will confirm receipt of your request. SECTION A Request Submitted _____________________ ______________________ ________________________

  18. Total pressing Indonesian gas development, exports

    SciTech Connect (OSTI)

    Not Available

    1994-01-24

    Total is on track to become Indonesia's leading gas exporter by the turn of the century. Total's aggressive development of its Mahakam Delta acreage in East Kalimantan is intended to keep pace with growing liquefied natural gas demand, mainly from Japan but also increasingly from South Korea and Taiwan. A frantic scramble is under way among natural gas suppliers in the Pacific Rim region, particularly those with current LNG export facilities, to accommodate projections of soaring natural gas demand in the region. Accordingly, Total's Indonesian gas production goal is the centerpiece of a larger strategy to become a major player in the Far East Asia gas scene. Its goals also fall in line with Indonesia's. Facing flat or declining oil production while domestic oil demand continues to soar along with a rapidly growing economy, Indonesia is heeding some studies that project the country could become a net oil importer by the turn of the century. The paper describes Total's Far East strategy, the Mahakam acreage which it operates, the shift to gas development, added discoveries, future development, project spending levels, and LNG export capacity.

  19. Total internal reflection laser tools and methods

    DOE Patents [OSTI]

    Zediker, Mark S.; Faircloth, Brian O.; Kolachalam, Sharath K.; Grubb, Daryl L.

    2016-02-02

    There is provided high power laser tools and laser heads that utilize total internal reflection ("TIR") structures to direct the laser beam along a laser beam path within the TIR structure. The TIR structures may be a TIR prism having its hypotenuse as a TIR surface.

  20. Magnetic nanoparticle temperature estimation

    SciTech Connect (OSTI)

    Weaver, John B.; Rauwerdink, Adam M.; Hansen, Eric W.

    2009-05-15

    The authors present a method of measuring the temperature of magnetic nanoparticles that can be adapted to provide in vivo temperature maps. Many of the minimally invasive therapies that promise to reduce health care costs and improve patient outcomes heat tissue to very specific temperatures to be effective. Measurements are required because physiological cooling, primarily blood flow, makes the temperature difficult to predict a priori. The ratio of the fifth and third harmonics of the magnetization generated by magnetic nanoparticles in a sinusoidal field is used to generate a calibration curve and to subsequently estimate the temperature. The calibration curve is obtained by varying the amplitude of the sinusoidal field. The temperature can then be estimated from any subsequent measurement of the ratio. The accuracy was 0.3 deg. K between 20 and 50 deg. C using the current apparatus and half-second measurements. The method is independent of nanoparticle concentration and nanoparticle size distribution.

  1. Frustrated total internal reflection acoustic field sensor

    DOE Patents [OSTI]

    Kallman, Jeffrey S.

    2000-01-01

    A frustrated total internal reflection acoustic field sensor which allows the acquisition of the acoustic field over an entire plane, all at once. The sensor finds use in acoustic holography and acoustic diffraction tomography. For example, the sensor may be produced by a transparent plate with transparent support members tall enough to support one or more flexible membranes at an appropriate height for frustrated total internal reflection to occur. An acoustic wave causes the membrane to deflect away from its quiescent position and thus changes the amount of light that tunnels through the gap formed by the support members and into the membrane, and so changes the amount of light reflected by the membrane. The sensor(s) is illuminated by a uniform tight field, and the reflection from the sensor yields acoustic wave amplitude and phase information which can be picked up electronically or otherwise.

  2. Fractionated total body irradiation for metastatic neuroblastoma

    SciTech Connect (OSTI)

    Kun, L.E.; Casper, J.T.; Kline, R.W.; Piaskowski, V.D.

    1981-11-01

    Twelve patients over one year old with neuroblastoma (NBL) metastatic to bone and bone marrow entered a study of adjuvant low-dose, fractionated total body irradiation (TBI). Six children who achieved a ''complete clinical response'' following chemotherapy (cyclophosphamide and adriamycin) and surgical resection of the abdominal primary received TBI (10 rad/fraction to totals of 100-120 rad/10-12 fx/12-25 days). Two children received concurrent local irradiation for residual abdominal tumor. The intervals from cessation of chemotherapy to documented progression ranged from 2-16 months, not substatially different from patients receiving similar chemotherapy and surgery without TBI. Three additional children with progressive NBL received similar TBI (80-120 rad/8-12 fx) without objective response.

  3. Use of Cost Estimating Relationships

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

    1997-03-28

    Cost Estimating Relationships (CERs) are an important tool in an estimator's kit, and in many cases, they are the only tool. Thus, it is important to understand their limitations and characteristics. This chapter discusses considerations of which the estimator must be aware so the Cost Estimating Relationships can be properly used.

  4. Total Crude Oil and Petroleum Products Exports

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

    Exports Product: Total Crude Oil and Petroleum Products Crude Oil Natural Gas Plant Liquids and Liquefied Refinery Gases Pentanes Plus Liquefied Petroleum Gases Ethane/Ethylene Propane/Propylene Normal Butane/Butylene Isobutane/Isobutylene Other Liquids Hydrogen/Oxygenates/Renewables/Other Hydrocarbons Oxygenates (excl. Fuel Ethanol) Methyl Tertiary Butyl Ether (MTBE) Other Oxygenates Renewable Fuels (incl. Fuel Ethanol) Fuel Ethanol Biomass-Based Diesel Unfinished Oils Naphthas and Lighter

  5. Performance of internal covariance estimators for cosmic shear correlation functions

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

    Friedrich, O.; Seitz, S.; Eifler, T. F.; Gruen, D.

    2015-12-31

    Data re-sampling methods such as the delete-one jackknife are a common tool for estimating the covariance of large scale structure probes. In this paper we investigate the concepts of internal covariance estimation in the context of cosmic shear two-point statistics. We demonstrate how to use log-normal simulations of the convergence field and the corresponding shear field to carry out realistic tests of internal covariance estimators and find that most estimators such as jackknife or sub-sample covariance can reach a satisfactory compromise between bias and variance of the estimated covariance. In a forecast for the complete, 5-year DES survey we show that internally estimated covariance matrices can provide a large fraction of the true uncertainties on cosmological parameters in a 2D cosmic shear analysis. The volume inside contours of constant likelihood in themore » $$\\Omega_m$$-$$\\sigma_8$$ plane as measured with internally estimated covariance matrices is on average $$\\gtrsim 85\\%$$ of the volume derived from the true covariance matrix. The uncertainty on the parameter combination $$\\Sigma_8 \\sim \\sigma_8 \\Omega_m^{0.5}$$ derived from internally estimated covariances is $$\\sim 90\\%$$ of the true uncertainty.« less

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

    SciTech Connect (OSTI)

    Huang, Yu Joe; Brodrick, Jim

    2000-08-01

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

  7. Table 6a. Total Electricity Consumption per Effective Occupied...

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

    a. Total Electricity Consumption per Effective Occupied Square Foot, 1992 Building Characteristics All Buildings Using Electricity (thousand) Total Electricity Consumption...

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

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

    Total Expenditures for Purchased Energy Sources by Census Region" " and Economic ... "," ","Coke"," ","Row" "Economic Characteristics(a)","Total","Electricity...

  9. Total Acid Value Titration of Hydrotreated Biomass Fast Pyrolysis Oil: Determination of Carboxylic Acids and Phenolics with Multiple End-Point Detection

    SciTech Connect (OSTI)

    Christensen, E.; Alleman, T. L.; McCormick, R. L.

    2013-01-01

    Total acid value titration has long been used to estimate corrosive potential of petroleum crude oil and fuel oil products. The method commonly used for this measurement, ASTM D664, utilizes KOH in isopropanol as the titrant with potentiometric end point determination by pH sensing electrode and Ag/AgCl reference electrode with LiCl electrolyte. A natural application of the D664 method is titration of pyrolysis-derived bio-oil, which is a candidate for refinery upgrading to produce drop in fuels. Determining the total acid value of pyrolysis derived bio-oil has proven challenging and not necessarily amenable to the methodology employed for petroleum products due to the different nature of acids present. We presented an acid value titration for bio-oil products in our previous publication which also utilizes potentiometry using tetrabutylammonium hydroxide in place of KOH as the titrant and tetraethylammonium bromide in place of LiCl as the reference electrolyte to improve the detection of these types of acids. This method was shown to detect numerous end points in samples of bio-oil that were not detected by D664. These end points were attributed to carboxylic acids and phenolics based on the results of HPLC and GC-MS studies. Additional work has led to refinement of the method and it has been established that both carboxylic acids and phenolics can be determined accurately. Use of pH buffer calibration to determine half-neutralization potentials of acids in conjunction with the analysis of model compounds has allowed us to conclude that this titration method is suitable for the determination of total acid value of pyrolysis oil and can be used to differentiate and quantify weak acid species. The measurement of phenolics in bio-oil is subject to a relatively high limit of detection, which may limit the utility of titrimetric methodology for characterizing the acidic potential of pyrolysis oil and products.

  10. Emissions of nitrogen oxides from US urban areas: estimation from Ozone Monitoring Instrument retrievals for 2005-2014

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

    Lu, Z.; Streets, D. G.; de Foy, B.; Lamsal, L. N.; Duncan, B. N.; Xing, J.

    2015-05-28

    Satellite remote sensing of tropospheric nitrogen dioxide (NO2) can provide valuable information for estimating surface nitrogen oxides (NOx) emissions. Using an exponentially-modified Gaussian (EMG) method and taking into account the effect of wind on observed NO2 distributions, we estimate three-year moving-average emissions of summertime NOx from 35 US urban areas directly from NO2 retrievals of the Ozone Monitoring Instrument (OMI) during 2005–2014. Following the conclusions of previous studies that the EMG method provides robust and accurate emission estimates under strong-wind conditions, we derive top-down NOx emissions from each urban area by applying the EMG method to OMI data with windmore » speeds greater than 3–5 m s-1. Meanwhile, we find that OMI NO2 observations under weak-wind conditions (i.e., < 3 m s-1) are qualitatively better correlated with the surface NOx source strength in comparison to all-wind OMI maps; and therefore we use them to calculate the satellite-observed NO2 burdens of urban areas and compare with NOx emission estimates. The EMG results show that OMI-derived NOx emissions are highly correlated (R > 0.93) with weak-wind OMI NO2 burdens as well as bottom-up NOx emission estimates over 35 urban areas, implying a linear response of the OMI observations to surface emissions under weak-wind conditions. The simultaneous, EMG-obtained, effective NO2 lifetimes (~3.5 ± 1.3 h), however, are biased low in comparison to the summertime NO2 chemical lifetimes. In general, isolated urban areas with NOx emission intensities greater than ~ 2 Mg h-1 produce statistically significant weak-wind signals in three-year average OMI data. From 2005 to 2014, we estimate that total OMI-derived NOx emissions over all selected US urban areas decreased by 49%, consistent with reductions of 43, 47, 49, and 44% in the total bottom-up NOx emissions, the sum of weak-wind OMI NO2 columns, the total weak-wind OMI NO2 burdens, and the averaged NO2 concentrations, respectively, reflecting the success of NOx control programs for both mobile sources and power plants. The decrease rates of these NOx-related quantities are found to be faster (i.e., -6.8 to -9.3% yr-1) before 2010 and slower (i.e., -3.4 to -4.9% yr-1) after 2010. For individual urban areas, we calculate the R values of pair-wise trends among the OMI-derived and bottom-up NOx emissions, the weak-wind OMI NO2 burdens, and ground-based NO2 measurements; and high correlations are found for all urban areas (median R = 0.8), particularly large ones (R up to 0.97). The results of the current work indicate that using the EMG method and considering the wind effect, the OMI data allow for the estimation of NOx emissions from urban areas and the direct constraint of emission trends with reasonable accuracy.« less

  11. Automated Estimating System

    Energy Science and Technology Software Center (OSTI)

    1996-04-15

    AES6.1 is a PC software package developed to aid in the preparation and reporting of cost estimates. AES6.1 provides an easy means for entering and updating the detailed cost, schedule information, project work breakdown structure, and escalation information contained in a typical project cost estimate through the use of menus and formatted input screens. AES6.1 combines this information to calculate both unescalated and escalated cost for a project which can be reported at varying levelsmore » of detail. Following are the major modifications to AES6.0f: Contingency update was modified to provide greater flexibility for user updates, Schedule Update was modified to provide user ability to schedule Bills of Material at the WBS/Participant/Cost Code level, Schedule Plot was modified to graphically show schedule by WBS/Participant/Cost Code, All Fiscal Year reporting has been modified to use the new schedule format, The Schedule 1-B-7, Cost Schedule, and the WBS/Participant reprorts were modified to determine Phase of Work from the B/M Cost Code, Utility program was modified to allow selection by cost code and update cost code in the Global Schedule update, Generic summary and line item download were added to the utility program, and an option was added to all reports which allows the user to indicate where overhead is to be reported (bottom line or in body of report)« less

  12. Estimated recharge rates at the Hanford Site

    SciTech Connect (OSTI)

    Fayer, M.J.; Walters, T.B.

    1995-02-01

    The Ground-Water Surveillance Project monitors the distribution of contaminants in ground water at the Hanford Site for the U.S. Department of Energy. A subtask called {open_quotes}Water Budget at Hanford{close_quotes} was initiated in FY 1994. The objective of this subtask was to produce a defensible map of estimated recharge rates across the Hanford Site. Methods that have been used to estimate recharge rates at the Hanford Site include measurements (of drainage, water contents, and tracers) and computer modeling. For the simulations of 12 soil-vegetation combinations, the annual rates varied from 0.05 mm/yr for the Ephrata sandy loam with bunchgrass to 85.2 mm/yr for the same soil without vegetation. Water content data from the Grass Site in the 300 Area indicated that annual rates varied from 3.0 to 143.5 mm/yr during an 8-year period. The annual volume of estimated recharge was calculated to be 8.47 {times} 10{sup 9} L for the potential future Hanford Site (i.e., the portion of the current Site bounded by Highway 240 and the Columbia River). This total volume is similar to earlier estimates of natural recharge and is 2 to 10x higher than estimates of runoff and ground-water flow from higher elevations. Not only is the volume of natural recharge significant in comparison to other ground-water inputs, the distribution of estimated recharge is highly skewed to the disturbed sandy soils (i.e., the 200 Areas, where most contaminants originate). The lack of good estimates of the means and variances of the supporting data (i.e., the soil map, the vegetation/land use map, the model parameters) translates into large uncertainties in the recharge estimates. When combined, the significant quantity of estimated recharge, its high sensitivity to disturbance, and the unquantified uncertainty of the data and model parameters suggest that the defensibility of the recharge estimates should be improved.

  13. Total Adjusted Sales of Distillate Fuel Oil

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

    End Use: Total Residential Commercial Industrial Oil Company Farm Electric Power Railroad Vessel Bunkering On-Highway Military Off-Highway All Other Period: Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: End Use Area 2009 2010 2011 2012 2013 2014 View History U.S. 55,664,448 58,258,830 59,769,444 57,512,994 58,675,008 61,890,990 1984-2014 East Coast (PADD 1) 18,219,180 17,965,794 17,864,868 16,754,388

  14. Total Adjusted Sales of Residual Fuel Oil

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

    End Use: Total Commercial Industrial Oil Company Electric Power Vessel Bunkering Military All Other Period: Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: End Use Area 2009 2010 2011 2012 2013 2014 View History U.S. 7,835,436 8,203,062 7,068,306 5,668,530 4,883,466 3,942,750 1984-2014 East Coast (PADD 1) 3,339,162 3,359,265 2,667,576 1,906,700 1,699,418 1,393,068 1984-2014 New England (PADD 1A) 318,184

  15. Total Sales of Distillate Fuel Oil

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

    End Use: Total Residential Commercial Industrial Oil Company Farm Electric Power Railroad Vessel Bunkering On-Highway Military Off-Highway All Other Period: Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: End Use Area 2009 2010 2011 2012 2013 2014 View History U.S. 54,100,092 56,093,645 57,082,558 57,020,840 58,107,155 60,827,930 1984-2014 East Coast (PADD 1) 17,821,973 18,136,965 17,757,005 17,382,566

  16. Total Sales of Residual Fuel Oil

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

    End Use: Total Commercial Industrial Oil Company Electric Power Vessel Bunkering Military All Other Period: Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: End Use Area 2009 2010 2011 2012 2013 2014 View History U.S. 6,908,028 7,233,765 6,358,120 6,022,115 5,283,350 4,919,255 1984-2014 East Coast (PADD 1) 2,972,575 2,994,245 2,397,932 2,019,294 1,839,237 1,724,167 1984-2014 New England (PADD 1A) 281,895

  17. Improving Estimation Accuracy of Aggregate Queries on Data Cubes

    SciTech Connect (OSTI)

    Pourabbas, Elaheh; Shoshani, Arie

    2008-08-15

    In this paper, we investigate the problem of estimation of a target database from summary databases derived from a base data cube. We show that such estimates can be derived by choosing a primary database which uses a proxy database to estimate the results. This technique is common in statistics, but an important issue we are addressing is the accuracy of these estimates. Specifically, given multiple primary and multiple proxy databases, that share the same summary measure, the problem is how to select the primary and proxy databases that will generate the most accurate target database estimation possible. We propose an algorithmic approach for determining the steps to select or compute the source databases from multiple summary databases, which makes use of the principles of information entropy. We show that the source databases with the largest number of cells in common provide the more accurate estimates. We prove that this is consistent with maximizing the entropy. We provide some experimental results on the accuracy of the target database estimation in order to verify our results.

  18. Derivative

    National Nuclear Security Administration (NNSA)

    Robert C. Jones, Colleen M. Beck, and Barbara A. Holz Division of Earth and Ecosystem Sciences Cultural Resources Technical Report No.102 Desert Research Institute Las Vegas, ...

  19. Derivation of dose conversion factors for tritium

    SciTech Connect (OSTI)

    Killough, G. G.

    1982-03-01

    For a given intake mode (ingestion, inhalation, absorption through the skin), a dose conversion factor (DCF) is the committed dose equivalent to a specified organ of an individual per unit intake of a radionuclide. One also may consider the effective dose commitment per unit intake, which is a weighted average of organ-specific DCFs, with weights proportional to risks associated with stochastic radiation-induced fatal health effects, as defined by Publication 26 of the International Commission on Radiological Protection (ICRP). This report derives and tabulates organ-specific dose conversion factors and the effective dose commitment per unit intake of tritium. These factors are based on a steady-state model of hydrogen in the tissues of ICRP's Reference Man (ICRP Publication 23) and equilibrium of specific activities between body water and other tissues. The results differ by 27 to 33% from the estimate on which ICRP Publication 30 recommendations are based. The report also examines a dynamic model of tritium retention in body water, mineral bone, and two compartments representing organically-bound hydrogen. This model is compared with data from human subjects who were observed for extended periods. The manner of combining the dose conversion factors with measured or model-predicted levels of contamination in man's exposure media (air, drinking water, soil moisture) to estimate dose rate to an individual is briefly discussed.

  20. Total Ore Processing Integration and Management

    SciTech Connect (OSTI)

    Leslie Gertsch; Richard Gertsch

    2006-01-30

    This report outlines the technical progress achieved for project DE-FC26-03NT41785 (Total Ore Processing Integration and Management) during the period 01 July through 30 September of 2005. This ninth quarterly report discusses the activities of the project team during the period 1 July through 30 September 2005. Richard Gertsch's unexpected death due to natural causes while in Minnesota to work on this project has temporarily slowed progress. Statistical analysis of the Minntac Mine data set for late 2004 is continuing. Preliminary results raised several questions that could be amenable to further study. Detailed geotechnical characterization is being applied to improve the predictability of mill and agglomerator performance at Hibtac Mine.

  1. State Residential Commercial Industrial Transportation Total

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

    Sales (Megawatthours) (Data from forms EIA-861- schedules 4A, 4B, 4D, EIA-861S and EIA-861U) State Residential Commercial Industrial Transportation Total New England 47,211,525 53,107,038 19,107,433 557,463 119,983,459 Connecticut 12,777,579 12,893,531 3,514,798 168,552 29,354,460 Maine 4,660,605 3,984,570 3,357,486 0 12,002,661 Massachusetts 20,071,160 26,076,208 7,960,941 360,983 54,469,292 New Hampshire 4,510,487 4,464,530 1,969,064 0 10,944,081 Rhode Island 3,070,347 3,657,679 887,150 27,928

  2. Sol-gel derived sorbents

    DOE Patents [OSTI]

    Sigman, Michael E.; Dindal, Amy B.

    2003-11-11

    Described is a method for producing copolymerized sol-gel derived sorbent particles for the production of copolymerized sol-gel derived sorbent material. The method for producing copolymerized sol-gel derived sorbent particles comprises adding a basic solution to an aqueous metal alkoxide mixture for a pH.ltoreq.8 to hydrolyze the metal alkoxides. Then, allowing the mixture to react at room temperature for a precalculated period of time for the mixture to undergo an increased in viscosity to obtain a desired pore size and surface area. The copolymerized mixture is then added to an immiscible, nonpolar solvent that has been heated to a sufficient temperature wherein the copolymerized mixture forms a solid upon the addition. The solid is recovered from the mixture, and is ready for use in an active sampling trap or activated for use in a passive sampling trap.

  3. Magnetic cellulose-derivative structures

    DOE Patents [OSTI]

    Walsh, M.A.; Morris, R.S.

    1986-09-16

    Structures to serve as selective magnetic sorbents are formed by dissolving a cellulose derivative such as cellulose triacetate in a solvent containing magnetic particles. The resulting solution is sprayed as a fine mist into a chamber containing a liquid coagulant such as n-hexane in which the cellulose derivative is insoluble but in which the coagulant is soluble or miscible. On contact with the coagulant, the mist forms free-flowing porous magnetic microspheric structures. These structures act as containers for the ion-selective or organic-selective sorption agent of choice. Some sorption agents can be incorporated during the manufacture of the structure. 3 figs.

  4. Magnetic cellulose-derivative structures

    DOE Patents [OSTI]

    Walsh, Myles A. (Falmouth, MA); Morris, Robert S. (Fairhaven, MA)

    1986-09-16

    Structures to serve as selective magnetic sorbents are formed by dissolving a cellulose derivative such as cellulose triacetate in a solvent containing magnetic particles. The resulting solution is sprayed as a fine mist into a chamber containing a liquid coagulant such as n-hexane in which the cellulose derivative is insoluble but in which the coagulant is soluble or miscible. On contact with the coagulant, the mist forms free-flowing porous magnetic microspheric structures. These structures act as containers for the ion-selective or organic-selective sorption agent of choice. Some sorbtion agents can be incorporated during the manufacture of the structure.

  5. Cost Estimating, Analysis, and Standardization

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

    1984-11-02

    To establish policy and responsibilities for: (a) developing and reviewing project cost estimates; (b) preparing independent cost estimates and analysis; (c) standardizing cost estimating procedures; and (d) improving overall cost estimating and analytical techniques, cost data bases, cost and economic escalation models, and cost estimating systems. Cancels DOE O 5700.2B, dated 8-5-1983; DOE O 5700.8, dated 5-27-1981; and HQ 1130.1A, dated 12-30-1981. Canceled by DOE O 5700.2D, dated 6-12-1992

  6. Assessment of model estimates of land-atmosphere CO2 exchange...

    Office of Scientific and Technical Information (OSTI)

    comparisons against both observed CO2 fluxes derived from site-based eddy covariance measurements as well as regional-scale GPP estimates based on satellite remote-sensing data. ...

  7. Monitored Geologic Repository Life Cycle Cost Estimate Assumptions Document

    SciTech Connect (OSTI)

    R. Sweeney

    2000-03-08

    The purpose of this assumptions document is to provide general scope, strategy, technical basis, schedule and cost assumptions for the Monitored Geologic Repository (MGR) life cycle cost estimate and schedule update incorporating information from the Viability Assessment (VA), License Application Design Selection (LADS), 1999 Update to the Total System Life Cycle Cost (TSLCC) estimate and from other related and updated information. This document is intended to generally follow the assumptions outlined in the previous MGR cost estimates and as further prescribed by DOE guidance.

  8. MONITORED GEOLOGIC REPOSITORY LIFE CYCLE COST ESTIMATE ASSUMPTIONS DOCUMENT

    SciTech Connect (OSTI)

    R.E. Sweeney

    2001-02-08

    The purpose of this assumptions document is to provide general scope, strategy, technical basis, schedule and cost assumptions for the Monitored Geologic Repository (MGR) life cycle cost (LCC) estimate and schedule update incorporating information from the Viability Assessment (VA) , License Application Design Selection (LADS), 1999 Update to the Total System Life Cycle Cost (TSLCC) estimate and from other related and updated information. This document is intended to generally follow the assumptions outlined in the previous MGR cost estimates and as further prescribed by DOE guidance.

  9. TRENDS IN ESTIMATED MIXING DEPTH DAILY MAXIMUMS

    SciTech Connect (OSTI)

    Buckley, R; Amy DuPont, A; Robert Kurzeja, R; Matt Parker, M

    2007-11-12

    Mixing depth is an important quantity in the determination of air pollution concentrations. Fireweather forecasts depend strongly on estimates of the mixing depth as a means of determining the altitude and dilution (ventilation rates) of smoke plumes. The Savannah River United States Forest Service (USFS) routinely conducts prescribed fires at the Savannah River Site (SRS), a heavily wooded Department of Energy (DOE) facility located in southwest South Carolina. For many years, the Savannah River National Laboratory (SRNL) has provided forecasts of weather conditions in support of the fire program, including an estimated mixing depth using potential temperature and turbulence change with height at a given location. This paper examines trends in the average estimated mixing depth daily maximum at the SRS over an extended period of time (4.75 years) derived from numerical atmospheric simulations using two versions of the Regional Atmospheric Modeling System (RAMS). This allows for differences to be seen between the model versions, as well as trends on a multi-year time frame. In addition, comparisons of predicted mixing depth for individual days in which special balloon soundings were released are also discussed.

  10. Minnesota Natural Gas % of Total Residential Deliveries (Percent...

    Gasoline and Diesel Fuel Update (EIA)

    Minnesota Natural Gas % of Total Residential Deliveries (Percent) Decade Year-0 Year-1 ... Share of Total U.S. Natural Gas Residential Deliveries Minnesota Share of Total U.S. ...

  11. California Natural Gas % of Total Residential Deliveries (Percent...

    Gasoline and Diesel Fuel Update (EIA)

    California Natural Gas % of Total Residential Deliveries (Percent) Decade Year-0 Year-1 ... Share of Total U.S. Natural Gas Residential Deliveries California Share of Total U.S. ...

  12. Estimation of economic parameters of U.S. hydropower resources

    SciTech Connect (OSTI)

    Hall, Douglas G.; Hunt, Richard T.; Reeves, Kelly S.; Carroll, Greg R.

    2003-06-01

    Tools for estimating the cost of developing and operating and maintaining hydropower resources in the form of regression curves were developed based on historical plant data. Development costs that were addressed included: licensing, construction, and five types of environmental mitigation. It was found that the data for each type of cost correlated well with plant capacity. A tool for estimating the annual and monthly electric generation of hydropower resources was also developed. Additional tools were developed to estimate the cost of upgrading a turbine or a generator. The development and operation and maintenance cost estimating tools, and the generation estimating tool were applied to 2,155 U.S. hydropower sites representing a total potential capacity of 43,036 MW. The sites included totally undeveloped sites, dams without a hydroelectric plant, and hydroelectric plants that could be expanded to achieve greater capacity. Site characteristics and estimated costs and generation for each site were assembled in a database in Excel format that is also included within the EERE Library under the title, “Estimation of Economic Parameters of U.S. Hydropower Resources - INL Hydropower Resource Economics Database.”

  13. NREL: Building America Total Quality Management - 2015 Peer Review...

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

    NREL: Building America Total Quality Management - 2015 Peer Review NREL: Building America Total Quality Management - 2015 Peer Review Presenter: Stacey Rothgeb, NREL View the ...

  14. Table 6b. Relative Standard Errors for Total Electricity Consumption...

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

    b. Relative Standard Errors for Total Electricity Consumption per Effective Occupied Square Foot, 1992 Building Characteristics All Buildings Using Electricity (thousand) Total...

  15. ,"Total District Heat Consumption (trillion Btu)",,,,,"District...

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

    Heat Consumption (trillion Btu)",,,,,"District Heat Energy Intensity (thousand Btusquare foot)" ,"Total ","Space Heating","Water Heating","Cook- ing","Other","Total ","Space...

  16. ,"Total Natural Gas Consumption (trillion Btu)",,,,,"Natural...

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

    Gas Consumption (trillion Btu)",,,,,"Natural Gas Energy Intensity (thousand Btusquare foot)" ,"Total ","Space Heating","Water Heating","Cook- ing","Other","Total ","Space...

  17. Total Energy Facilities Biomass Facility | Open Energy Information

    Open Energy Info (EERE)

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

  18. Table 5a. Total District Heat Consumption per Effective Occupied...

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

    a. Total District Heat Consumption per Effective Occupied Square Foot, 1992 Building Characteristics All Buildings Using District Heat (thousand) Total District Heat Consumption...

  19. Webtrends Archives by Fiscal Year — EERE Totals

    Broader source: Energy.gov [DOE]

    Historical EERE office total reports include only Webtrends archives by fiscal year. EERE total reports dating after FY11 can be accessed in EERE's Google Analytics account.

  20. Minnesota Natural Gas Total Consumption (Million Cubic Feet)

    Gasoline and Diesel Fuel Update (EIA)

    Total Consumption (Million Cubic Feet) Minnesota Natural Gas Total Consumption (Million ... Referring Pages: Natural Gas Consumption Minnesota Natural Gas Consumption by End Use ...

  1. California Natural Gas Total Consumption (Million Cubic Feet...

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

    Total Consumption (Million Cubic Feet) California Natural Gas Total Consumption (Million ... Referring Pages: Natural Gas Consumption California Natural Gas Consumption by End Use ...

  2. Total Crude Oil and Petroleum Products Imports by Processing...

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

    Product: Total Crude Oil and Petroleum Products Crude Oil Total Products Other Liquids Unfinished Oils Naphthas and Lighter Kerosene and Light Gas Oils Heavy Gas Oils Residuum ...

  3. Total lymphoid irradiation for multiple sclerosis

    SciTech Connect (OSTI)

    Devereux, C.K.; Vidaver, R.; Hafstein, M.P.; Zito, G.; Troiano, R.; Dowling, P.C.; Cook, S.D.

    1988-01-01

    Although chemical immunosuppression has been shown to benefit patients with chronic progressive multiple sclerosis (MS), it appears that chemotherapy has an appreciable oncogenic potential in patients with multiple sclerosis. Accordingly, we developed a modified total lymphoid irradiation (TLI) regimen designed to reduce toxicity and applied it to a randomized double blind trial of TLI or sham irradiation in MS. Standard TLI regimens were modified to reduce dose to 1,980 rad, lowering the superior mantle margin to midway between the thyroid cartilage and angle of the mandible (to avert xerostomia) and the lower margin of the mantle field to the inferior margin of L1 (to reduce gastrointestinal toxicity by dividing abdominal radiation between mantle and inverted Y), limiting spinal cord dose to 1,000 rad by custom-made spine blocks in the mantle and upper 2 cm of inverted Y fields, and also protecting the left kidney even if part of the spleen were shielded. Clinical efficacy was documented by the less frequent functional scale deterioration of 20 TLI treated patients with chronic progressive MS compared to to 20 sham-irradiated progressive MS patients after 12 months (16% versus 55%, p less than 0.03), 18 months (28% versus 63%, p less than 0.03), and 24 months (44% versus 74%, N.S.). Therapeutic benefit during 3 years follow-up was related to the reduction in lymphocyte count 3 months post-irradiation (p less than 0.02). Toxicity was generally mild and transient, with no instance of xerostomia, pericarditis, herpes zoster, or need to terminate treatment in TLI patients. However, menopause was induced in 2 patients and staphylococcal pneumonia in one.

  4. Tetrahydroquinoline Derivatives as Potent and Selective Factor...

    Office of Scientific and Technical Information (OSTI)

    Tetrahydroquinoline Derivatives as Potent and Selective Factor XIa Inhibitors Citation Details In-Document Search Title: Tetrahydroquinoline Derivatives as Potent and Selective ...

  5. Robust and intelligent bearing estimation

    DOE Patents [OSTI]

    Claassen, John P.

    2000-01-01

    A method of bearing estimation comprising quadrature digital filtering of event observations, constructing a plurality of observation matrices each centered on a time-frequency interval, determining for each observation matrix a parameter such as degree of polarization, linearity of particle motion, degree of dyadicy, or signal-to-noise ratio, choosing observation matrices most likely to produce a set of best available bearing estimates, and estimating a bearing for each observation matrix of the chosen set.

  6. Survival Estimates for the Passage of Spring-Migrating Juvenile Salmonids through Snake and Columbia River Dams and Reservoirs, 2008.

    SciTech Connect (OSTI)

    Faulkner, James R.; Smith, Steven G.; Muir, William D.

    2009-06-23

    In 2008, the National Marine Fisheries Service completed the sixteenth year of a study to estimate survival and travel time of juvenile salmonids Oncorhynchus spp. passing through dams and reservoirs on the Snake and Columbia Rivers. All estimates were derived from detections of fish tagged with passive integrated transponder (PIT) tags. We PIT tagged and released a total of 18,565 hatchery steelhead O. mykiss, 15,991 wild steelhead, and 9,714 wild yearling Chinook salmon O. tshawytscha at Lower Granite Dam in the Snake River. In addition, we utilized fish PIT tagged by other agencies at traps and hatcheries upstream from the hydropower system and at sites within the hydropower system in both the Snake and Columbia Rivers. These included 122,061 yearling Chinook salmon tagged at Lower Granite Dam for evaluation of latent mortality related to passage through Snake River dams. PIT-tagged smolts were detected at interrogation facilities at Lower Granite, Little Goose, Lower Monumental, Ice Harbor, McNary, John Day, and Bonneville Dams and in the PIT-tag detector trawl operated in the Columbia River estuary. Survival estimates were calculated using a statistical model for tag-recapture data from single release groups (the single-release model). Primary research objectives in 2008 were to: (1) estimate reach survival and travel time in the Snake and Columbia Rivers throughout the migration period of yearling Chinook salmon and steelhead, (2) evaluate relationships between survival estimates and migration conditions, and (3) evaluate the survival estimation models under prevailing conditions. This report provides reach survival and travel time estimates for 2008 for PIT-tagged yearling Chinook salmon (hatchery and wild), hatchery sockeye salmon O. nerka, hatchery coho salmon O. kisutch, and steelhead (hatchery and wild) in the Snake and Columbia Rivers. Additional details on the methodology and statistical models used are provided in previous reports cited here. Survival and detection probabilities were estimated precisely for most of the 2008 yearling Chinook salmon and steelhead migrations. Hatchery and wild fish were combined in some of the analyses. For yearling Chinook salmon, overall percentages for combined release groups used in survival analyses in the Snake River were 80% hatchery-reared and 20% wild. For steelhead, the overall percentages were 65% hatchery-reared and 35% wild. Estimated survival from the tailrace of Lower Granite Dam to the tailrace of Little Goose Dam averaged 0.939 for yearling Chinook salmon and 0.935 for steelhead.

  7. Examples of Cost Estimation Packages

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

    1997-03-28

    Estimates can be performed in a variety of ways. Some of these are for projects for an undefined scope, a conventional construction project, or where there is a level of effort required to complete the work. Examples of cost estimation packages for these types of projects are described in this appendix.

  8. Table A26. Components of Total Electricity Demand by Census Region, Census Di

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

    Components of Total Electricity Demand by Census Region, Census Division, and" " Economic Characteristics of the Establishment, 1994" " (Estimates in Million Kilowatthours)" " "," "," "," ","Sales/"," ","RSE" " "," ","Transfers","Onsite","Transfers"," ","Row" "Economic

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

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

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

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

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

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

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

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

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

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

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

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

  13. FUZZY SUPERNOVA TEMPLATES. II. PARAMETER ESTIMATION

    SciTech Connect (OSTI)

    Rodney, Steven A.; Tonry, John L. E-mail: jt@ifa.hawaii.ed

    2010-05-20

    Wide-field surveys will soon be discovering Type Ia supernovae (SNe) at rates of several thousand per year. Spectroscopic follow-up can only scratch the surface for such enormous samples, so these extensive data sets will only be useful to the extent that they can be characterized by the survey photometry alone. In a companion paper we introduced the Supernova Ontology with Fuzzy Templates (SOFT) method for analyzing SNe using direct comparison to template light curves, and demonstrated its application for photometric SN classification. In this work we extend the SOFT method to derive estimates of redshift and luminosity distance for Type Ia SNe, using light curves from the Sloan Digital Sky Survey (SDSS) and Supernova Legacy Survey (SNLS) as a validation set. Redshifts determined by SOFT using light curves alone are consistent with spectroscopic redshifts, showing an rms scatter in the residuals of rms{sub z} = 0.051. SOFT can also derive simultaneous redshift and distance estimates, yielding results that are consistent with the currently favored {Lambda}CDM cosmological model. When SOFT is given spectroscopic information for SN classification and redshift priors, the rms scatter in Hubble diagram residuals is 0.18 mag for the SDSS data and 0.28 mag for the SNLS objects. Without access to any spectroscopic information, and even without any redshift priors from host galaxy photometry, SOFT can still measure reliable redshifts and distances, with an increase in the Hubble residuals to 0.37 mag for the combined SDSS and SNLS data set. Using Monte Carlo simulations, we predict that SOFT will be able to improve constraints on time-variable dark energy models by a factor of 2-3 with each new generation of large-scale SN surveys.

  14. Survival Estimates for the Passage of Juvenile Salmonids through Snake and Columbia River Dams and Reservoirs, 2002-2003 Annual Report.

    SciTech Connect (OSTI)

    Muir, William D.; Smith, Steven G.; Zabel, Richard W.

    2003-07-01

    In 2002, the National Marine Fisheries Service and the University of Washington completed the tenth year of a study to estimate survival and travel time of juvenile salmonids (Oncorhynchus spp.) passing through dams and reservoirs on the Snake and Columbia Rivers. All estimates were derived from detections of fish tagged with passive integrated transponder tags (PIT tags). We PIT tagged and released a total of 19,891 hatchery steelhead at Lower Granite Dam. In addition, we utilized fish PIT tagged by other agencies at traps and hatcheries upstream from the hydropower system and sites within the hydropower system. PIT-tagged smolts were detected at interrogation facilities at Lower Granite, Little Goose, Lower Monumental, McNary, John Day, and Bonneville Dams and in the PIT-tag detector trawl operated in the Columbia River estuary. Survival estimates were calculated using a statistical model for tag-recapture data from single release groups (the ''Single-Release Model''). Primary research objectives in 2002 were to (1) estimate reach and project survival and travel time in the Snake and Columbia Rivers throughout the migration period of yearling chinook salmon O. tshawytscha and steelhead O. mykiss; (2) evaluate relationships between survival estimates and migration conditions; and (3) evaluate the survival-estimation models under prevailing conditions. This report provides reach survival and travel time estimates for 2002 for PIT-tagged yearling chinook salmon (hatchery and wild), hatchery sockeye salmon O. nerka, hatchery coho salmon O. kisutch, and steelhead (hatchery and wild) in the Snake and Columbia Rivers. Results are reported primarily in the form of tables and figures; details on methodology and statistical models used are provided in previous reports cited here. Results for summer-migrating chinook salmon will be reported separately.

  15. Survival Estimates for the Passage of Spring-Migrating Juvenile Salmonids through Snake and Columbia River Dams and Reservoirs, 2005-2006 Annual Report.

    SciTech Connect (OSTI)

    Smith, Steven G.; Muir, William D.; Marsh, Douglas M.

    2006-05-01

    In 2005, the National Marine Fisheries Service and the University of Washington completed the thirteenth year of a study to estimate survival and travel time of juvenile salmonids Oncorhynchus spp. passing through dams and reservoirs on the Snake and Columbia Rivers. All estimates were derived from detections of fish tagged with passive integrated transponder tags (PIT tags). We PIT tagged and released a total of 18,439 hatchery steelhead, 5,315 wild steelhead, and 6,964 wild yearling Chinook salmon at Lower Granite Dam in the Snake River. In addition, we utilized fish PIT tagged by other agencies at traps and hatcheries upstream from the hydropower system and at sites within the hydropower system in both the Snake and Columbia Rivers. PIT-tagged smolts were detected at interrogation facilities at Lower Granite, Little Goose, Lower Monumental, Ice Harbor, McNary, John Day, and Bonneville Dams and in the PIT-tag detector trawl operated in the Columbia River estuary. Survival estimates were calculated using a statistical model for tag-recapture data from single release groups (the ''single-release model''). Primary research objectives in 2005 were: (1) Estimate reach survival and travel time in the Snake and Columbia Rivers throughout the migration period of yearling Chinook salmon O. tshawytscha and steelhead O. mykiss. (2) Evaluate relationships between survival estimates and migration conditions. (3) Evaluate the survival estimation models under prevailing conditions. This report provides reach survival and travel time estimates for 2005 for PIT-tagged yearling Chinook salmon (hatchery and wild), hatchery sockeye salmon O. nerka, hatchery coho salmon O. kisutch, and steelhead (hatchery and wild) in the Snake and Columbia Rivers. Additional details on the methodology and statistical models used are provided in previous reports cited here.

  16. Cloud properties derived from two lidars over the ARM SGP site

    SciTech Connect (OSTI)

    Dupont, Jean-Charles; Haeffelin, Martial; Morille, Y.; Comstock, Jennifer M.; Flynn, Connor J.; Long, Charles N.; Sivaraman, Chitra; Newsom, Rob K.

    2011-02-16

    [1] Active remote sensors such as lidars or radars can be used with other data to quantify the cloud properties at regional scale and at global scale (Dupont et al., 2009). Relative to radar, lidar remote sensing is sensitive to very thin and high clouds but has a significant limitation due to signal attenuation in the ability to precisely quantify the properties of clouds with a 20 cloud optical thickness larger than 3. In this study, 10-years of backscatter lidar signal data are analysed by a unique algorithm called STRucture of ATmosphere (STRAT, Morille et al., 2007). We apply the STRAT algorithm to data from both the collocated Micropulse lidar (MPL) and a Raman lidar (RL) at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site between 1998 and 2009. Raw backscatter lidar signal is processed and 25 corrections for detector deadtime, afterpulse, and overlap are applied. (Campbell et al.) The cloud properties for all levels of clouds are derived and distributions of cloud base height (CBH), top height (CTH), physical cloud thickness (CT), and optical thickness (COT) from local statistics are compared. The goal of this study is (1) to establish a climatology of macrophysical and optical properties for all levels of clouds observed over the ARM SGP site 30 and (2) to estimate the discrepancies induced by the two remote sensing systems (pulse energy, sampling, resolution, etc.). Our first results tend to show that the MPLs, which are the primary ARM lidars, have a distinctly limited range where all of these cloud properties are detectable, especially cloud top and cloud thickness, but even actual cloud base especially during summer daytime period. According to the comparisons between RL and MPL, almost 50% of situations show a signal to noise ratio too low (smaller than 3) for the MPL in order to detect clouds higher than 7km during daytime period in summer. Consequently, the MPLderived annual cycle of cirrus cloud base (top) altitude is biased low, especially for daylight periods, compared with those derived from the RL data, which detects 5 cloud base ranging from 7.5 km in winter to 9.5 km in summer (and tops ranging from 8.6 to 10.5 km). The optically thickest cirrus clouds (COT>0.3) reach 50% of the total population for the Raman lidar and only 20% for the Micropulse lidar due to the difference of pulse energy and the effect of solar irradiance contamination. A complementary study using the cloud fraction 10 derived from the Micropulse lidar for clouds below 5 km and from the Raman lidar for cloud above 5 km allows for better estimation of the total cloud fraction between the ground and the top of the atmosphere. This study presents the diurnal cycle of cloud fraction for each season in comparisons with the Long et al. (2006) cloud fraction calculation derived from radiative flux analysis.

  17. Binder enhanced refuse derived fuel

    DOE Patents [OSTI]

    Daugherty, Kenneth E.; Venables, Barney J.; Ohlsson, Oscar O.

    1996-01-01

    A refuse derived fuel (RDF) pellet having about 11% or more particulate calcium hydroxide which is utilized in a combustionable mixture. The pellets are used in a particulate fuel bring a mixture of 10% or more, on a heat equivalent basis, of the RDF pellet which contains calcium hydroxide as a binder, with 50% or more, on a heat equivalent basis, of a sulphur containing coal. Combustion of the mixture is effective to produce an effluent gas from the combustion zone having a reduced SO.sub.2 and polycyclic aromatic hydrocarbon content of effluent gas from similar combustion materials not containing the calcium hydroxide.

  18. Estimates of particulate mass in multi-canister overpacks

    SciTech Connect (OSTI)

    SLOUGHTER, J.P.

    1999-02-25

    High, best estimate, and low values are developed for particulate inventories within MCO baskets that have been loaded with freshly cleaned fuel assemblies and scrap. These per-basket estimates are then applied to all anticipated MCO payload configurations to identify which configurations are bounding for each type of particulate. Finally the resulting bounding and nominal values for residual particulates are combined with corresponding values [from other documents] for particulate that may be generated by corrosion of exposed uranium after the fuel has been cleaned. The resulting rounded nominal estimate for a typical MCO after 40 years of storage is 8 kg. The estimate for a bounding total particulate case MCO is that it may contain up to 64 kg of particulate after 40 years of storage.

  19. Estimates of Particulate Mass in Multi Canister Overpacks (MCO)

    SciTech Connect (OSTI)

    SLOUGHTER, J.P.

    2000-02-16

    High, best estimate, and low values are developed for particulate inventories within MCO baskets that have been loaded with freshly cleaned fuel assemblies and scrap. These per-basket estimates are then applied to all anticipated MCO payload configurations to identify which configurations are bounding for each type of particulate. Finally the resulting bounding and nominal values for residual particulates are combined with corresponding values [from other documents] for particulates that may be generated by corrosion of exposed uranium after the fuel has been cleaned. The resulting rounded nominal estimate for a typical MCO after 40 years of storage is 8 kg. The estimate for a bounding total particulate case MCO is that it may contain up to 64 kg of particulate after 40 years of storage.

  20. Isotopic Tracking of Hanford 300 Area Derived Uranium in the Columbia River

    SciTech Connect (OSTI)

    Christensen, John N.; Dresel, P. Evan; Conrad, Mark E.; Patton, Gregory W.; DePaolo, Donald J.

    2010-10-31

    Our objectives in this study are to quantify the discharge rate of uranium (U) to the Columbia River from the Hanford Site's 300 Area, and to follow that U down river to constrain its fate. Uranium from the Hanford Site has variable isotopic composition due to nuclear industrial processes carried out at the site. This characteristic makes it possible to use high-precision isotopic measurements of U in environmental samples to identify even trace levels of contaminant U, determine its sources, and estimate discharge rates. Our data on river water samples indicate that as much as 3.2 kg/day can enter the Columbia River from the 300 Area, which is only a small fraction of the total load of dissolved natural background U carried by the Columbia River. This very low-level of Hanford derived U can be discerned, despite dilution to < 1 percent of natural background U, 350 km downstream from the Hanford Site. These results indicate that isotopic methods can allow the amounts of U from the 300 Area of the Hanford Site entering the Columbia River to be measured accurately to ascertain whether they are an environmental concern, or are insignificant relative to natural uranium background in the Columbia River.

  1. Module: Estimating Historical Emissions from Deforestation |...

    Open Energy Info (EERE)

    Website: www.leafasia.orgtoolstechnical-guidance-series-estimating-historical Cost: Free Language: English Module: Estimating Historical Emissions from Deforestation Screenshot...

  2. Virginia Natural Gas % of Total Residential Deliveries (Percent...

    Gasoline and Diesel Fuel Update (EIA)

    % of Total Residential Deliveries (Percent) Virginia Natural Gas % of Total Residential Deliveries (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8...

  3. Washington Natural Gas % of Total Residential Deliveries (Percent...

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

    % of Total Residential Deliveries (Percent) Washington Natural Gas % of Total Residential Deliveries (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8...

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

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

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

  5. New Mexico Natural Gas % of Total Residential Deliveries (Percent...

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

    % of Total Residential Deliveries (Percent) New Mexico Natural Gas % of Total Residential Deliveries (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8...

  6. Connecticut Natural Gas % of Total Residential Deliveries (Percent...

    Gasoline and Diesel Fuel Update (EIA)

    % of Total Residential Deliveries (Percent) Connecticut Natural Gas % of Total Residential Deliveries (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7...

  7. Connecticut Natural Gas Total Consumption (Million Cubic Feet...

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

    Total Consumption (Million Cubic Feet) Connecticut Natural Gas Total Consumption (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9...

  8. Maine Natural Gas Total Consumption (Million Cubic Feet)

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

    Total Consumption (Million Cubic Feet) Maine Natural Gas Total Consumption (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's...

  9. Maine Natural Gas % of Total Residential Deliveries (Percent...

    Gasoline and Diesel Fuel Update (EIA)

    % of Total Residential Deliveries (Percent) Maine Natural Gas % of Total Residential Deliveries (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8...

  10. Total China Investment Co Ltd | Open Energy Information

    Open Energy Info (EERE)

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

  11. Kansas Natural Gas % of Total Residential Deliveries (Percent...

    Gasoline and Diesel Fuel Update (EIA)

    % of Total Residential Deliveries (Percent) Kansas Natural Gas % of Total Residential Deliveries (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8...

  12. Arizona Natural Gas Total Consumption (Million Cubic Feet)

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

    Total Consumption (Million Cubic Feet) Arizona Natural Gas Total Consumption (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9...

  13. Arizona Natural Gas % of Total Residential Deliveries (Percent...

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

    % of Total Residential Deliveries (Percent) Arizona Natural Gas % of Total Residential Deliveries (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8...

  14. ,"Total Crude Oil and Petroleum Products Net Receipts by Pipeline...

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

    Data for" ,"Data 1","Total Crude Oil and Petroleum Products Net Receipts by ... PM" "Back to Contents","Data 1: Total Crude Oil and Petroleum Products Net Receipts by ...

  15. Estimate Radiological Dose for Animals

    Energy Science and Technology Software Center (OSTI)

    1997-12-18

    Estimate Radiological dose for animals in ecological environment using open literature values for parameters such as body weight, plant and soil ingestion rate, rad. halflife, absorbed energy, biological halflife, gamma energy per decay, soil-to-plant transfer factor, ...etc

  16. NREL: Building America Total Quality Management - 2015 Peer Review |

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

    Department of Energy NREL: Building America Total Quality Management - 2015 Peer Review NREL: Building America Total Quality Management - 2015 Peer Review Presenter: Stacey Rothgeb, NREL View the Presentation PDF icon NREL: Building America Total Quality Management - 2015 Peer Review More Documents & Publications Home Performance with ENERGY STAR - 2014 BTO Peer Review NREL: Building America Total Quality Management - 2015 Peer Review R25 Polyisocyanurate Composite Insulation Material

  17. Estimates of Green potentials. Applications

    SciTech Connect (OSTI)

    Danchenko, V I

    2003-02-28

    Optimal Cartan-type covers by hyperbolic discs of carriers of Green {alpha}-potentials are obtained in a simply connected domain in the complex plane and estimates of the potentials outside the carriers are presented. These results are applied to problems on the separation of singularities of analytic and harmonic functions. For instance, uniform and integral estimates in terms of Green capacities of components of meromorphic functions are obtained.

  18. New Methodology for Estimating Fuel Economy by Vehicle Class

    SciTech Connect (OSTI)

    Chin, Shih-Miao; Dabbs, Kathryn; Hwang, Ho-Ling

    2011-01-01

    Office of Highway Policy Information to develop a new methodology to generate annual estimates of average fuel efficiency and number of motor vehicles registered by vehicle class for Table VM-1 of the Highway Statistics annual publication. This paper describes the new methodology developed under this effort and compares the results of the existing manual method and the new systematic approach. The methodology developed under this study takes a two-step approach. First, the preliminary fuel efficiency rates are estimated based on vehicle stock models for different classes of vehicles. Then, a reconciliation model is used to adjust the initial fuel consumption rates from the vehicle stock models and match the VMT information for each vehicle class and the reported total fuel consumption. This reconciliation model utilizes a systematic approach that produces documentable and reproducible results. The basic framework utilizes a mathematical programming formulation to minimize the deviations between the fuel economy estimates published in the previous year s Highway Statistics and the results from the vehicle stock models, subject to the constraint that fuel consumptions for different vehicle classes must sum to the total fuel consumption estimate published in Table MF-21 of the current year Highway Statistics. The results generated from this new approach provide a smoother time series for the fuel economies by vehicle class. It also utilizes the most up-to-date and best available data with sound econometric models to generate MPG estimates by vehicle class.

  19. GAO Cost Estimating and Assessment Guide Twelve Steps of a High-Quality Cost Estimating Process

    Energy Savers [EERE]

    GAO Cost Estimating and Assessment Guide Twelve Steps of a High-Quality Cost Estimating Process Step Description Associated task 1 Define estimate's purpose Determine estimate's purpose, required level of detail, and overall scope; Determine who will receive the estimate 2 Develop estimating plan Determine the cost estimating team and develop its master schedule; Determine who will do the independent cost estimate; Outline the cost estimating approach; Develop the estimate timeline 3 Define

  20. Development of surface mine cost estimating equations

    SciTech Connect (OSTI)

    Not Available

    1980-09-26

    Cost estimating equations were developed to determine capital and operating costs for five surface coal mine models in Central Appalachia, Northern Appalachia, Mid-West, Far-West, and Campbell County, Wyoming. Engineering equations were used to estimate equipment costs for the stripping function and for the coal loading and hauling function for the base case mine and for several mines with different annual production levels and/or different overburden removal requirements. Deferred costs were then determined through application of the base case depreciation schedules, and direct labor costs were easily established once the equipment quantities (and, hence, manpower requirements) were determined. The data points were then fit with appropriate functional forms, and these were then multiplied by appropriate adjustment factors so that the resulting equations yielded the model mine costs for initial and deferred capital and annual operating cost. (The validity of this scaling process is based on the assumption that total initial and deferred capital costs are proportional to the initial and deferred costs for the primary equipment types that were considered and that annual operating cost is proportional to the direct labor costs that were determined based on primary equipment quantities.) Initial capital costs ranged from $3,910,470 in Central Appalachia to $49,296,785; deferred capital costs ranged from $3,220,000 in Central Appalachia to $30,735,000 in Campbell County, Wyoming; and annual operating costs ranged from $2,924,148 in Central Appalachia to $32,708,591 in Campbell County, Wyoming. (DMC)

  1. Synchrophasor Measurement-Based Wind Plant Inertia Estimation: Preprint

    SciTech Connect (OSTI)

    Zhang, Y.; Bank, J.; Wan, Y. H.; Muljadi, E.; Corbus, D.

    2013-05-01

    The total inertia stored in all rotating masses that are connected to power systems, such as synchronous generations and induction motors, is an essential force that keeps the system stable after disturbances. To ensure bulk power system stability, there is a need to estimate the equivalent inertia available from a renewable generation plant. An equivalent inertia constant analogous to that of conventional rotating machines can be used to provide a readily understandable metric. This paper explores a method that utilizes synchrophasor measurements to estimate the equivalent inertia that a wind plant provides to the system.

  2. Weldon Spring historical dose estimate

    SciTech Connect (OSTI)

    Meshkov, N.; Benioff, P.; Wang, J.; Yuan, Y.

    1986-07-01

    This study was conducted to determine the estimated radiation doses that individuals in five nearby population groups and the general population in the surrounding area may have received as a consequence of activities at a uranium processing plant in Weldon Spring, Missouri. The study is retrospective and encompasses plant operations (1957-1966), cleanup (1967-1969), and maintenance (1969-1982). The dose estimates for members of the nearby population groups are as follows. Of the three periods considered, the largest doses to the general population in the surrounding area would have occurred during the plant operations period (1957-1966). Dose estimates for the cleanup (1967-1969) and maintenance (1969-1982) periods are negligible in comparison. Based on the monitoring data, if there was a person residing continually in a dwelling 1.2 km (0.75 mi) north of the plant, this person is estimated to have received an average of about 96 mrem/yr (ranging from 50 to 160 mrem/yr) above background during plant operations, whereas the dose to a nearby resident during later years is estimated to have been about 0.4 mrem/yr during cleanup and about 0.2 mrem/yr during the maintenance period. These values may be compared with the background dose in Missouri of 120 mrem/yr.

  3. THE IMPORTANCE OF PHYSICAL MODELS FOR DERIVING DUST MASSES AND GRAIN SIZE DISTRIBUTIONS IN SUPERNOVA EJECTA. I. RADIATIVELY HEATED DUST IN THE CRAB NEBULA

    SciTech Connect (OSTI)

    Temim, Tea; Dwek, Eli, E-mail: tea.temim@nasa.gov [Observational Cosmology Lab, Code 665, NASA Goddard Space Flight Center, Greenbelt, MD 20771 (United States)

    2013-09-01

    Recent far-infrared (IR) observations of supernova remnants (SNRs) have revealed significantly large amounts of newly condensed dust in their ejecta, comparable to the total mass of available refractory elements. The dust masses derived from these observations assume that all the grains of a given species radiate at the same temperature, regardless of the dust heating mechanism or grain radius. In this paper, we derive the dust mass in the ejecta of the Crab Nebula, using a physical model for the heating and radiation from the dust. We adopt a power-law distribution of grain sizes and two different dust compositions (silicates and amorphous carbon), and calculate the heating rate of each dust grain by the radiation from the pulsar wind nebula. We find that the grains attain a continuous range of temperatures, depending on their size and composition. The total mass derived from the best-fit models to the observed IR spectrum is 0.019-0.13 M{sub Sun }, depending on the assumed grain composition. We find that the power-law size distribution of dust grains is characterized by a power-law index of 3.5-4.0 and a maximum grain size larger than 0.1 {mu}m. The grain sizes and composition are consistent with what is expected for dust grains formed in a Type IIP supernova (SN). Our derived dust mass is at least a factor of two less than the mass reported in previous studies of the Crab Nebula that assumed more simplified two-temperature models. These models also require a larger mass of refractory elements to be locked up in dust than was likely available in the ejecta. The results of this study show that a physical model resulting in a realistic distribution of dust temperatures can constrain the dust properties and affect the derived dust masses. Our study may also have important implications for deriving grain properties and mass estimates in other SNRs and for the ultimate question of whether SNe are major sources of dust in the Galactic interstellar medium and in external galaxies.

  4. Preliminary assessment of the Velocity Pump Reaction Turbine as a geothermal total-flow expander

    SciTech Connect (OSTI)

    Demuth, O.J.

    1985-01-01

    A preliminary evaluation was made of the Velocity Pump Reaction Turbine (VPRT) as a total flow expander in a geothermal-electric conversion cycle. Values of geofluid effectiveness of VPRT systems were estimated for conditions consisting of: a 360/sup 0/F geothermal resource, 60/sup 0/F wet-bulb ambient temperature, zero and 0.003 mass concentrations of dissolved noncondensible gas in the geofluid, 100 and 120/sup 0/F condensing temperature, and engine efficiencies ranging from 0.4 to 1.0. Achievable engine efficiencies were estimated to range from 0.47 to 0.77, with plant geofluid effectivenss values ranging as high as 9.5 Watt hr/lbm geofluid. This value is competitive with magnitudes of geofluid effectiveness projected for advanced binary plants, and is on the order of 40% higher than estimates for dual-flash steam systems and other total flow systems reviewed. Because of its potentially high performance and relative simplicity, the VPRT system appears to warrant further investigation toward its use in a well-head geothermal plant. 13 refs., 5 figs.

  5. Preliminary assessment of the velocity pump reaction turbine as a geothermal total-flow expander

    SciTech Connect (OSTI)

    Demuth, O.J.

    1984-06-01

    A preliminary evaluation was made of the Velocity Pump Reaction Turbine (VPRT) as a total flow expander in a geothermal-electric conversion cycle. Values of geofluid effectiveness of VPRT systems were estimated for conditions consisting of: a 360/sup 0/ geothermal resource, 60/sup 0/F wet-bulb ambient temperature, zero and 0.003 mass concentrations of dissolved noncondensible gas in the geofluid, 100 and 120/sup 0/F condensing temperatures, and engine efficiencies ranging from 0.4 to 1.0. Achievable engine efficiencies were estimated to range from 0.47 to 0.77, with plant geofluid effectiveness values ranging as high as 9.5 Watt hr/lbm geofluid for the 360/sup 0/F resource temperature. This value is competitive with magnitudes of geofluid effectiveness projected for advanced binary plants, and is on the order of 40% higher than estimates for dual-flash steam and other total flow systems reviewed. Because of its potentially high performance and relative simplicity, the VPRT system appears to warrant further investigation toward its use in a well-head geothermal plant.

  6. A Survey of State-Level Cost and Benefit Estimates of Renewable Portfolio Standards

    Broader source: Energy.gov [DOE]

    This report surveys and summarizes existing state-level RPS cost and benefit estimates and examines the various methods used to calculate such estimates. The report relies largely upon data or results reported directly by electric utilities and state regulators. As such, the estimated costs and benefits itemized in this document do not result from the application of a standardized approach or the use of a consistent set of underlying assumptions. Because the reported values may differ from those derived through a more consistent analytical treatment, we do not provide an aggregate national estimate of RPS costs and benefits, nor do we attempt to quantify net RPS benefits at national or state levels.

  7. Percentage of Total Natural Gas Commercial Deliveries included in Prices

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

    City Gate Price Residential Price Percentage of Total Residential Deliveries included in Prices Commercial Price Percentage of Total Commercial Deliveries included in Prices Industrial Price Percentage of Total Industrial Deliveries included in Prices Electric Power Price Period: Monthly Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: Data Series Area Sep-15 Oct-15 Nov-15 Dec-15 Jan-16 Feb-16 View History U.S.

  8. Percentage of Total Natural Gas Industrial Deliveries included in Prices

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

    Pipeline and Distribution Use Price City Gate Price Residential Price Percentage of Total Residential Deliveries included in Prices Commercial Price Percentage of Total Commercial Deliveries included in Prices Industrial Price Percentage of Total Industrial Deliveries included in Prices Vehicle Fuel Price Electric Power Price Period: Monthly Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: Data Series Area 2010

  9. Percentage of Total Natural Gas Industrial Deliveries included in Prices

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

    City Gate Price Residential Price Percentage of Total Residential Deliveries included in Prices Commercial Price Percentage of Total Commercial Deliveries included in Prices Industrial Price Percentage of Total Industrial Deliveries included in Prices Electric Power Price Period: Monthly Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: Data Series Area Sep-15 Oct-15 Nov-15 Dec-15 Jan-16 Feb-16 View History U.S.

  10. Percentage of Total Natural Gas Residential Deliveries included in Prices

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

    City Gate Price Residential Price Percentage of Total Residential Deliveries included in Prices Commercial Price Percentage of Total Commercial Deliveries included in Prices Industrial Price Percentage of Total Industrial Deliveries included in Prices Electric Power Price Period: Monthly Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: Data Series Area Sep-15 Oct-15 Nov-15 Dec-15 Jan-16 Feb-16 View History U.S.

  11. Estimation of Energy Savings Resulting From the BestPractices Program, Fiscal Year 2002

    SciTech Connect (OSTI)

    Truett, LF

    2003-09-24

    Within the U.S. Department of Energy (DOE), the Office of Energy Efficiency and Renewable Energy (EERE) has a vision of a future with clean, abundant, reliable, and affordable energy. Within EERE, the Industrial Technologies Program (ITP), formerly the Office of Industrial Technologies, works in partnership with industry to increase energy efficiency, improve environmental performance, and boost productivity. The BestPractices (BP) Program, within ITP, works directly with industries to encourage energy efficiency. The purpose of the BP Program is to improve energy utilization and management practices in the industrial sector. The program targets distinct technology areas, including pumps, process heating, steam, compressed air, motors, and insulation. This targeting is accomplished with a variety of delivery channels, such as computer software, printed publications, Internet-based resources, technical training, technical assessments, and other technical assistance. A team of program evaluators from Oak Ridge National Laboratory (ORNL) was tasked to evaluate the fiscal year 2002 (FY02) energy savings of the program. The ORNL assessment enumerates levels of program activity for technology areas across delivery channels. In addition, several mechanisms that target multiple technology areas--e.g., Plant-wide Assessments (PWAs), the ''Energy Matters'' newsletter, and special events--are also evaluated for their impacts. When possible, the assessment relies on published reports and the Industrial Assessment Center (IAC) database for estimates of energy savings that result from particular actions. Data were also provided by ORNL, Lawrence Berkeley National Laboratory (LBNL) and Project Performance Corporation (PPC), the ITP Clearinghouse at Washington State University, the National Renewable Energy Laboratory (NREL), Energetics Inc., and the Industrial Technologies Program Office. The estimated energy savings in FY02 resulting from activities of the BP Program are almost 81.9 trillion Btu (0.0819 Quad), which is about 0.25% of the 32.5 Quads of energy consumed during FY02 by the industrial sector in the United States. The technology area with the largest estimated savings is steam, with 32% of the total energy savings. The delivery mechanism with the largest savings is that of software systems distribution, encompassing 44% of the total savings. Training results in an energy savings of 33%. Energy savings from PWAs and PWA replications equal 10%. Sources of overestimation of energy savings might derive from (1) a possible overlap of energy savings resulting from separate events (delivery channels) occurring in conjunction with one another (e.g., a training event and CTA at the same plant), and (2) a possible issue with the use of the average CTA value to assess savings for training and software distribution. Any overestimation attributable to these sources probably is outweighed by underestimations caused by the exclusion of savings resulting from general awareness workshops, data not submitted to the ITP Tracking Database, omission of savings attributable to web downloads of publications, use of BP products by participants over multiple years, and the continued utilization of equipment installed or replaced in previous years. Next steps in improving these energy savings estimates include continuing to enhance the design of the ITP Tracking Database and to improve reporting of program activities for the distribution of products and services; obtaining more detailed information on implementation rates and savings estimates for software training, tools, and assessments; continuing attempts to quantify savings based on Qualified Specialist activities; defining a methodology for assessing savings based on web downloads of publications; establishing a protocol for evaluating savings from other BP-sponsored events and activities; and continuing to refine the estimation methodology and reduction factors.

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

    Open Energy Info (EERE)

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

  13. Texas Natural Gas Gross Withdrawals Total Offshore (Million Cubic...

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

    Gross Withdrawals Total Offshore (Million Cubic Feet) Texas Natural Gas Gross Withdrawals ... Offshore Gross Withdrawals of Natural Gas Natural Gas Gross Withdrawals Texas Offshore ...

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

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

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

  15. Montana Total Maximum Daily Load Development Projects Wiki |...

    Open Energy Info (EERE)

    Wiki Jump to: navigation, search OpenEI Reference LibraryAdd to library Web Site: Montana Total Maximum Daily Load Development Projects Wiki Abstract Provides information on...

  16. ,"Motor Gasoline Sales to End Users, Total Refiner Sales Volumes...

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

    Sales to End Users, Total Refiner Sales Volumes",60,"Monthly","22016","1151983" ,"Release Date:","522016" ,"Next Release Date:","612016" ,"Excel File Name:","petconsrefmg...

  17. Total Agroindustria Canavieira S A | Open Energy Information

    Open Energy Info (EERE)

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

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

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

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

  19. ,"U.S. Total Refiner Petroleum Product Prices"

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

    NUSDPG","EMAEPPRPTGNUSDPG","EMAEPPRLPTGNUSDPG","EMAEPPRHPTGNUSDPG" "Date","U.S. Total Gasoline Retail Sales by Refiners (Dollars per Gallon)","U.S. Aviation Gasoline...

  20. Table 3a. Total Natural Gas Consumption per Effective Occupied...

    Gasoline and Diesel Fuel Update (EIA)

    3a. Natural Gas Consumption per Sq Ft Table 3a. Total Natural Gas Consumption per Effective Occupied Square Foot, 1992 Building Characteristics All Buildings Using Natural Gas...

  1. Real-space formulation of the electrostatic potential and total...

    Office of Scientific and Technical Information (OSTI)

    Journal Article: Real-space formulation of the electrostatic potential and total energy of solids Citation Details In-Document Search Title: Real-space formulation of the ...

  2. Table A19. Components of Total Electricity Demand by Census...

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

    Components of Total Electricity Demand by Census Region and" " Economic Characteristics of ...ansfers","Onsite","Transfers"," ","Row" "Economic Characteristics(a)","Purchases","In(b)",...

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

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

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

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

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

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

  5. ,"Crude Oil and Petroleum Products Total Stocks Stocks by Type...

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

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Crude Oil and Petroleum Products Total Stocks Stocks by Type",6,"Monthly","82015","1151956"...

  6. ,"Other States Total Natural Gas Gross Withdrawals and Production...

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

    Total Natural Gas Gross Withdrawals and Production" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for" ...

  7. $787 Million Total in Small Business Contract Funding Awarded...

    National Nuclear Security Administration (NNSA)

    787 Million Total in Small Business Contract Funding Awarded in FY2009 by DOE Programs in Oak Ridge | National Nuclear Security Administration Facebook Twitter Youtube Flickr RSS...

  8. ,"Conventional Gasoline Sales to End Users, Total Refiner Sales...

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

    Sales to End Users, Total Refiner Sales Volumes",60,"Monthly","22016","1151994" ,"Release Date:","522016" ,"Next Release Date:","612016" ,"Excel File Name:","petconsrefmg...

  9. Mandatory Photovoltaic System Cost Estimate

    Broader source: Energy.gov [DOE]

    If the customer has a ratio of estimated monthly kilowatt-hour (kWh) usage to line extension mileage that is less than or equal to 1,000, the utility must provide the comparison at no cost. If the...

  10. The estimation of N{sub 2}O emissions from municipal solid waste incineration facilities: The Korea case

    SciTech Connect (OSTI)

    Park, Sangwon; Choi, Jun-Ho; Park, Jinwon

    2011-08-15

    The greenhouse gases (GHGs) generated in municipal solid waste (MSW) incineration are carbon dioxide (CO{sub 2}), methane (CH{sub 4}), and nitrous oxide (N{sub 2}O). In South Korea case, the total of GHGs from the waste incineration facilities has been increasing at an annual rate 10%. In these view, waste incineration facilities should consider to reduce GHG emissions. This study is designed to estimate the N{sub 2}O emission factors from MSW incineration plants, and calculate the N{sub 2}O emissions based on these factors. The three MSW incinerators examined in this study were either stoker or both stoker and rotary kiln facilities. The N{sub 2}O concentrations from the MSW incinerators were measured using gas chromatography-electron capture detection (GC-ECD) equipment. The average of the N{sub 2}O emission factors for the M01 plant, M02 plant, and M03 plant are 71, 75, and 153 g-N{sub 2}O/ton-waste, respectively. These results showed a significant difference from the default values of the intergovernmental panel on climate change (IPCC), while approaching those values derived in Japan and Germany. Furthermore, comparing the results of this study to the Korea Energy Economics Institute (KEEI) (2007) data on waste incineration, N{sub 2}O emissions from MSW incineration comprised 19% of the total N{sub 2}O emissions.

  11. Deriving stellar inclination of slow rotators using stellar activity

    SciTech Connect (OSTI)

    Dumusque, X.

    2014-12-01

    Stellar inclination is an important parameter for many astrophysical studies. Although different techniques allow us to estimate stellar inclination for fast rotators, it becomes much more difficult when stars are rotating slower than ?2-2.5 km s{sup 1}. By using the new activity simulation SOAP 2.0 which can reproduce the photometric and spectroscopic variations induced by stellar activity, we are able to fit observations of solar-type stars and derive their inclination. For HD 189733, we estimate the stellar inclination to be i=84{sub ?20}{sup +6} deg, which implies a star-planet obliquity of ?=4{sub ?4}{sup +18} considering previous measurements of the spin-orbit angle. For ? Cen B, we derive an inclination of i=45{sub ?19}{sup +9}, which implies that the rotational spin of the star is not aligned with the orbital spin of the ? Cen binary system. In addition, assuming that ? Cen Bb is aligned with its host star, no transit would occur. The inclination of ? Cen B can be measured using 40 radial-velocity measurements, which is remarkable given that the projected rotational velocity of the star is smaller than 1.15 km s{sup 1}.

  12. A Total Cost of Ownership Model for Low Temperature PEM Fuel Cells in Combined Heat and Power and Backup Power Applications

    SciTech Connect (OSTI)

    University of California, Berkeley; Wei, Max; Lipman, Timothy; Mayyas, Ahmad; Chien, Joshua; Chan, Shuk Han; Gosselin, David; Breunig, Hanna; Stadler, Michael; McKone, Thomas; Beattie, Paul; Chong, Patricia; Colella, Whitney; James, Brian

    2014-06-23

    A total cost of ownership model is described for low temperature proton exchange membrane stationary fuel cell systems for combined heat and power (CHP) applications from 1-250kW and backup power applications from 1-50kW. System designs and functional specifications for these two applications were developed across the range of system power levels. Bottom-up cost estimates were made for balance of plant costs, and detailed direct cost estimates for key fuel cell stack components were derived using design-for-manufacturing-and-assembly techniques. The development of high throughput, automated processes achieving high yield are projected to reduce the cost for fuel cell stacks to the $300/kW level at an annual production volume of 100 MW. Several promising combinations of building types and geographical location in the U.S. were identified for installation of fuel cell CHP systems based on the LBNL modelling tool DER CAM. Life-cycle modelling and externality assessment were done for hotels and hospitals. Reduced electricity demand charges, heating credits and carbon credits can reduce the effective cost of electricity ($/kWhe) by 26-44percent in locations such as Minneapolis, where high carbon intensity electricity from the grid is displaces by a fuel cell system operating on reformate fuel. This project extends the scope of existing cost studies to include externalities and ancillary financial benefits and thus provides a more comprehensive picture of fuel cell system benefits, consistent with a policy and incentive environment that increasingly values these ancillary benefits. The project provides a critical, new modelling capacity and should aid a broad range of policy makers in assessing the integrated costs and benefits of fuel cell systems versus other distributed generation technologies.

  13. Cost estimate for muddy water palladium production facility at Mound

    SciTech Connect (OSTI)

    McAdams, R.K.

    1988-11-30

    An economic feasibility study was performed on the ''Muddy Water'' low-chlorine content palladium powder production process developed by Mound. The total capital investment and total operating costs (dollars per gram) were determined for production batch sizes of 1--10 kg in 1-kg increments. The report includes a brief description of the Muddy Water process, the process flow diagram, and material balances for the various production batch sizes. Two types of facilities were evaluated--one for production of new, ''virgin'' palladium powder, and one for recycling existing material. The total capital investment for virgin facilities ranged from $600,000 --$1.3 million for production batch sizes of 1--10 kg, respectively. The range for recycle facilities was $1--$2.3 million. The total operating cost for 100% acceptable powder production in the virgin facilities ranged from $23 per gram for a 1-kg production batch size to $8 per gram for a 10-kg batch size. Similarly for recycle facilities, the total operating cost ranged from $34 per gram to $5 per gram. The total operating cost versus product acceptability (ranging from 50%--100% acceptability) was also evaluated for both virgin and recycle facilities. Because production sizes studied vary widely and because scale-up factors are unknown for batch sizes greater than 1 kg, all costs are ''order-of-magnitude'' estimates. All costs reported are in 1987 dollars.

  14. Estimates and Recommendations for Coincidence Geometry (Technical...

    Office of Scientific and Technical Information (OSTI)

    Estimates and Recommendations for Coincidence Geometry Citation Details In-Document Search Title: Estimates and Recommendations for Coincidence Geometry You are accessing a...

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

  1. DERIVATION OF STOCHASTIC ACCELERATION MODEL CHARACTERISTICS FOR...

    Office of Scientific and Technical Information (OSTI)

    FOR SOLAR FLARES FROM RHESSI HARD X-RAY OBSERVATIONS Citation Details In-Document Search Title: DERIVATION OF STOCHASTIC ACCELERATION MODEL CHARACTERISTICS FOR SOLAR FLARES ...

  2. Proceedings of refuse-derived fuel (RDF)

    SciTech Connect (OSTI)

    Saltiel, C. )

    1991-01-01

    This book contains proceedings of Refuse-Derived Fuel (RDF)-Quality. Standards and Processing. Topics covered include: An Overview of RDF Processing Systems: Current Status, Design Features, and Future Trends. The Impact of Recycling and Pre-Combustion Processing of Municipal Solid Waste on Fuel Properties and Steam Combustion. The Changing Role of Standards in the Marketing of RDF. Refuse Derived Fuel Quality Requirements for Firing in Utility, Industrial or Dedicated Boilers. Refuse-Derived Fuel Moisture Effects on Boiler Performance and Operability. Refuse Derived Fuels: Technology, Processing, Quality and Combustion Experiences.

  3. Hydrogen from Bio-Derived Liquids (Presentation)

    Broader source: Energy.gov [DOE]

    Presented at the 2007 Bio-Derived Liquids to Hydrogen Distributed Reforming Working Group held November 6, 2007 in Laurel, Maryland.

  4. Cost Analysis of Bio-Derived Liquids Reforming (Presentation...

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

    Bio-Derived Liquids Reforming (Presentation) Cost Analysis of Bio-Derived Liquids Reforming (Presentation) Presented at the 2007 Bio-Derived Liquids to Hydrogen Distributed ...

  5. Estimating carbon dioxide emission factors for the California electric power sector

    SciTech Connect (OSTI)

    Marnay, Chris; Fisher, Diane; Murtishaw, Scott; Phadke, Amol; Price, Lynn; Sathaye, Jayant

    2002-08-01

    The California Climate Action Registry (''Registry'') was initially established in 2000 under Senate Bill 1771, and clarifying legislation (Senate Bill 527) was passed in September 2001. The Ernest Orlando Lawrence Berkeley National Laboratory (Berkeley Lab) has been asked to provide technical assistance to the California Energy Commission (CEC) in establishing methods for calculating average and marginal electricity emissions factors, both historic and current, as well as statewide and for sub-regions. This study is exploratory in nature. It illustrates the use of three possible approaches and is not a rigorous estimation of actual emissions factors. While the Registry will ultimately cover emissions of all greenhouse gases (GHGs), presently it is focusing on carbon dioxide (CO2). Thus, this study only considers CO2, which is by far the largest GHG emitted in the power sector. Associating CO2 emissions with electricity consumption encounters three major complications. First, electricity can be generated from a number of different primary energy sources, many of which are large sources of CO2 emissions (e.g., coal combustion) while others result in virtually no CO{sub 2} emissions (e.g., hydro). Second, the mix of generation resources used to meet loads may vary at different times of day or in different seasons. Third, electrical energy is transported over long distances by complex transmission and distribution systems, so the generation sources related to electricity usage can be difficult to trace and may occur far from the jurisdiction in which that energy is consumed. In other words, the emissions resulting from electricity consumption vary considerably depending on when and where it is used since this affects the generation sources providing the power. There is no practical way to identify where or how all the electricity used by a certain customer was generated, but by reviewing public sources of data the total emission burden of a customer's electricity supplier can b e found and an average emissions factor (AEF) calculated. These are useful for assigning a net emission burden to a facility. In addition, marginal emissions factors (MEFs) for estimating the effect of changing levels of usage can be calculated. MEFs are needed because emission rates at the margin are likely to diverge from the average. The overall objective of this task is to develop methods for estimating AEFs and MEFs that can provide an estimate of the combined net CO2 emissions from all generating facilities that provide electricity to California electricity customers. The method covers the historic period from 1990 to the present, with 1990 and 1999 used as test years. The factors derived take into account the location and time of consumption, direct contracts for power which may have certain atypical characteristics (e.g., ''green'' electricity from renewable resources), resource mixes of electricity providers, import and export of electricity from utility owned and other sources, and electricity from cogeneration. It is assumed that the factors developed in this way will diverge considerably from simple statewide AEF estimates based on standardized inventory estimates that use conventions inconsistent with the goals of this work. A notable example concerns the treatment of imports, which despite providing a significant share of California's electricity supply picture, are excluded from inventory estimates of emissions, which are based on geographical boundaries of the state.

  6. Step-by-step cost-estimation guide for residential earth-shelter construction

    SciTech Connect (OSTI)

    Not Available

    1980-01-01

    Designers and builders of earth-sheltered structures will find this guide to be a basic outline for estimating construction costs. It considers, besides the basic materials and costs of any construction project, the regional, experience, and other variables that affect underground construction costs. The guide format permits the user to tally individual estimates and derive a simple cost per square foot. Space is also provided to tally actual costs for comparison. (DCK)

  7. Guidelines for Estimating Unmetered Landscapting Water Use

    SciTech Connect (OSTI)

    None

    2010-07-30

    Guidance to help Federal agencies estimate unmetered landscaping water use as required by Executive Order 13514

  8. SECPOP90: Sector population, land fraction, and economic estimation program

    SciTech Connect (OSTI)

    Humphreys, S.L.; Rollstin, J.A.; Ridgely, J.N.

    1997-09-01

    In 1973 Mr. W. Athey of the Environmental Protection Agency wrote a computer program called SECPOP which calculated population estimates. Since that time, two things have changed which suggested the need for updating the original program - more recent population censuses and the widespread use of personal computers (PCs). The revised computer program uses the 1990 and 1992 Population Census information and runs on current PCs as {open_quotes}SECPOP90.{close_quotes} SECPOP90 consists of two parts: site and regional. The site provides population and economic data estimates for any location within the continental United States. Siting analysis is relatively fast running. The regional portion assesses site availability for different siting policy decisions; i.e., the impact of available sites given specific population density criteria within the continental United States. Regional analysis is slow. This report compares the SECPOP90 population estimates and the nuclear power reactor licensee-provided information. Although the source, and therefore the accuracy, of the licensee information is unknown, this comparison suggests SECPOP90 makes reasonable estimates. Given the total uncertainty in any current calculation of severe accidents, including the potential offsite consequences, the uncertainty within SECPOP90 population estimates is expected to be insignificant. 12 refs., 55 figs., 7 tabs.

  9. Summary and recommendations: Total fuel cycle assessment workshop

    SciTech Connect (OSTI)

    1995-08-01

    This report summarizes the activities of the Total Fuel Cycle Assessment Workshop held in Austin, Texas, during October 6--7, 1994. It also contains the proceedings from that workshop.

  10. Ultrasound image guided acetabular implant orientation during total hip replacement

    DOE Patents [OSTI]

    Chang, John; Haddad, Waleed; Kluiwstra, Jan-Ulco; Matthews, Dennis; Trauner, Kenneth

    2003-08-19

    A system for assisting in precise location of the acetabular implant during total hip replacement. The system uses ultrasound imaging for guiding the placement and orientation of the implant.

  11. Property:Building/SPElectrtyUsePercTotal | Open Energy Information

    Open Energy Info (EERE)

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

  12. Property:RenewableFuelStandard/Total | Open Energy Information

    Open Energy Info (EERE)

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

  13. Gathering total items count for pagination | OpenEI Community

    Open Energy Info (EERE)

    Gathering total items count for pagination Home > Groups > Utility Rate Hi I'm using the following base link plus some restrictions to sector, utility, and locations to poll for...

  14. ,"U.S. Total Crude Oil and Products Imports"

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

    10:54:24 PM" "Back to Contents","Data 1: U.S. Total Crude Oil and Products Imports" ...-NVM1","MTTIMUSVQ1","MTTIMUSYE1" "Date","U.S. Imports of Crude Oil and Petroleum Products ...

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

    Open Energy Info (EERE)

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

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

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

    6. Total Energy Consumption, Projected vs. Actual Projected (quadrillion Btu) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 ...

  17. Prisms with total internal reflection as solar reflectors

    DOE Patents [OSTI]

    Rabl, Arnulf; Rabl, Veronika

    1978-01-01

    An improved reflective wall for radiant energy collection and concentration devices is provided. The wall is comprised of a plurality of prisms whose frontal faces are adjacent and which reflect the desired radiation by total internal reflection.

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

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

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

  19. CIGNA Study Uncovers Relationship of Disabilities to Total Benefits Costs

    Broader source: Energy.gov [DOE]

    The findings of a new study reveal an interesting trend. Integrating disability programs with health care programs can potentially lower employers' total benefits costs and help disabled employees get back to work sooner and stay at work.

  20. ,"U.S. Total Natural Gas Underground Storage Capacity (MMcf)...

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

    ...dnavnghistn5290us2m.htm" ,"Source:","Energy Information Administration" ,"For Help, ... 1: U.S. Total Natural Gas Underground Storage Capacity (MMcf)" "Sourcekey","N5290US2" ...

  1. ,"U.S. Total Natural Gas Underground Storage Capacity (MMcf)...

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

    ...dnavnghistn5290us2a.htm" ,"Source:","Energy Information Administration" ,"For Help, ... 1: U.S. Total Natural Gas Underground Storage Capacity (MMcf)" "Sourcekey","N5290US2" ...

  2. AGA Producing Region Natural Gas Total Underground Storage Capacity...

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

    Storage Capacity (Million Cubic Feet) AGA Producing Region Natural Gas Total Underground Storage Capacity (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec...

  3. U.S. Total Shell Storage Capacity at Operable Refineries

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

    Product Area 2010 2011 2012 2013 2014 2015 View History Total 710,413 -- -- -- -- -- 1982-2015 Crude Oil 180,846 -- -- -- -- -- 1985-2015 Liquefied Petroleum Gases 33,842 -- -- -- ...

  4. Determination of ferrous and total iron in refractory spinels (Journal

    Office of Scientific and Technical Information (OSTI)

    Article) | SciTech Connect Determination of ferrous and total iron in refractory spinels Citation Details In-Document Search Title: Determination of ferrous and total iron in refractory spinels Accurate and precise determination of the redox state of iron (Fe) in spinels presents a significant challenge due to their refractory nature. The resultant extreme conditions needed to obtain complete dissolution generally oxidize some of the Fe(II) initially present and thus prevent the use of

  5. Emissions of nitrogen oxides from US urban areas: estimation from Ozone Monitoring Instrument retrievals for 2005-2014

    SciTech Connect (OSTI)

    Lu, Z.; Streets, D. G.; de Foy, B.; Lamsal, L. N.; Duncan, B. N.; Xing, J.

    2015-05-28

    Satellite remote sensing of tropospheric nitrogen dioxide (NO2) can provide valuable information for estimating surface nitrogen oxides (NOx) emissions. Using an exponentially-modified Gaussian (EMG) method and taking into account the effect of wind on observed NO2 distributions, we estimate three-year moving-average emissions of summertime NOx from 35 US urban areas directly from NO2 retrievals of the Ozone Monitoring Instrument (OMI) during 2005–2014. Following the conclusions of previous studies that the EMG method provides robust and accurate emission estimates under strong-wind conditions, we derive top-down NOx emissions from each urban area by applying the EMG method to OMI data with wind speeds greater than 3–5 m s-1. Meanwhile, we find that OMI NO2 observations under weak-wind conditions (i.e., < 3 m s-1) are qualitatively better correlated with the surface NOx source strength in comparison to all-wind OMI maps; and therefore we use them to calculate the satellite-observed NO2 burdens of urban areas and compare with NOx emission estimates. The EMG results show that OMI-derived NOx emissions are highly correlated (R > 0.93) with weak-wind OMI NO2 burdens as well as bottom-up NOx emission estimates over 35 urban areas, implying a linear response of the OMI observations to surface emissions under weak-wind conditions. The simultaneous, EMG-obtained, effective NO2 lifetimes (~3.5 ± 1.3 h), however, are biased low in comparison to the summertime NO2 chemical lifetimes. In general, isolated urban areas with NOx emission intensities greater than ~ 2 Mg h-1 produce statistically significant weak-wind signals in three-year average OMI data. From 2005 to 2014, we estimate that total OMI-derived NOx emissions over all selected US urban areas decreased by 49%, consistent with reductions of 43, 47, 49, and 44% in the total bottom-up NOx emissions, the sum of weak-wind OMI NO2 columns, the total weak-wind OMI NO2 burdens, and the averaged NO2 concentrations, respectively, reflecting the success of NOx control programs for both mobile sources and power plants. The decrease rates of these NOx-related quantities are found to be faster (i.e., -6.8 to -9.3% yr-1) before 2010 and slower (i.e., -3.4 to -4.9% yr-1) after 2010. For individual urban areas, we calculate the R values of pair-wise trends among the OMI-derived and bottom-up NOx emissions, the weak-wind OMI NO2 burdens, and ground-based NO2 measurements; and high correlations are found for all urban areas (median R = 0.8), particularly large ones (R up to 0.97). The results of the current work indicate that using the EMG method and considering the wind effect, the OMI data allow for the estimation of NOx emissions from urban areas and the direct constraint of emission trends with reasonable accuracy.

  6. Growing attraction of refuse-derived fuels

    SciTech Connect (OSTI)

    Singh, R.

    1981-09-08

    A review of Dr. Andrew Porteous' book, Refuse Derived Fuels is presented. The escalating price of fossil fuel, particularily oil, together with the high cost of handling and transporting refuse makes the idea of refuse-derived fuel production an attractive and economic proposition. Refuse-derived fuel production is discussed and the various manufacturing processes in the UK and the USA are described. The pyrolysis of refuse for the production of gas, oil or heat and the production of methane and ethyl alcohol or other possibilities for refuse conversion.

  7. Lower and upper estimates on the excitation threshold for breathers in discrete nonlinear Schroedinger lattices

    SciTech Connect (OSTI)

    Cuevas, J.; Palmero, F.

    2009-11-15

    We propose analytical lower and upper estimates on the excitation threshold for breathers (in the form of spatially localized and time periodic solutions) in discrete nonlinear Schroedinger (DNLS) lattices with power nonlinearity. The estimation, depending explicitly on the lattice parameters, is derived by a combination of a comparison argument on appropriate lower bounds depending on the frequency of each solution with a simple and justified heuristic argument. The numerical studies verify that the analytical estimates can be of particular usefulness, as a simple analytical detection of the activation energy for breathers in DNLS lattices.

  8. A statistical study of the macroepidemiology of air pollution and total mortality

    SciTech Connect (OSTI)

    Lipfert, F.W.; Malone, R.G.; Daum, M.L.; Mendell, N.R.; Yang, Chin-Chun

    1988-04-01

    A statistical analysis of spatial patterns of 1980 US urban total mortality (all causes) was performed, evaluating demographic, socioeconomic and air pollution factors as predictors. Specific mortality predictors included cigarette smoking, drinking water hardness, heating fuel use, and 1978-1982 annual concentrations of the following air pollutants: ozone, carbon monoxide, sulfate aerosol, particulate concentrations of lead, iron, cadmium, manganese, vanadium, as well as total and fine particle mass concentrations from the inhalable particulate network (dichotomous samplers). In addition, estimates of sulfur dioxide, oxides of nitrogen, and sulfate aerosol were made for each city using the ASTRAP long-range transport diffusion model, and entered into the analysis as independent variables. Because the number of cities with valid air quality and water hardness data varied considerably by pollutant, it was necessary to consider several different data sets, ranging from 48 to 952 cities. The relatively strong associations (ca. 5--10%) shown for 1980 pollution with 1980 total mortality are generally not confirmed by independent studies, for example, in Europe. In addition, the US studies did not find those pollutants with known adverse health effects at the concentrations in question (such as ozone or CO) to be associated with mortality. The question of causality vs. circumstantial association must therefore be regarded as still unresolved. 59 refs., 20 figs., 40 tabs.

  9. SCM Forcing Data Derived from NWP Analyses

    SciTech Connect (OSTI)

    Jakob, Christian

    2008-01-15

    Forcing data, suitable for use with single column models (SCMs) and cloud resolving models (CRMs), have been derived from NWP analyses for the ARM (Atmospheric Radiation Measurement) Tropical Western Pacific (TWP) sites of Manus Island and Nauru.

  10. Tax Credit for Forest Derived Biomass

    Broader source: Energy.gov [DOE]

    Forest-derived biomass includes tree tops, limbs, needles, leaves, and other woody debris leftover from activities such as timber harvesting, forest thinning, fire suppression, or forest health m...

  11. Casimir Energy Associated With Fractional Derivative Field

    SciTech Connect (OSTI)

    Lim, S. C.

    2007-04-28

    Casimir energy associated with fractional derivative scalar massless field at zero and positive temperature can be obtained using the regularization based on generalized Riemann zeta function of Epstein-Hurwitz type.

  12. 2007 Estimated International Energy Flows

    SciTech Connect (OSTI)

    Smith, C A; Belles, R D; Simon, A J

    2011-03-10

    An energy flow chart or 'atlas' for 136 countries has been constructed from data maintained by the International Energy Agency (IEA) and estimates of energy use patterns for the year 2007. Approximately 490 exajoules (460 quadrillion BTU) of primary energy are used in aggregate by these countries each year. While the basic structure of the energy system is consistent from country to country, patterns of resource use and consumption vary. Energy can be visualized as it flows from resources (i.e. coal, petroleum, natural gas) through transformations such as electricity generation to end uses (i.e. residential, commercial, industrial, transportation). These flow patterns are visualized in this atlas of 136 country-level energy flow charts.

  13. Characterization and Hydrodesulfurization Properties of Catalysts Derived

    Office of Scientific and Technical Information (OSTI)

    from Amorphous Metal-Boron Materials (Journal Article) | SciTech Connect Characterization and Hydrodesulfurization Properties of Catalysts Derived from Amorphous Metal-Boron Materials Citation Details In-Document Search Title: Characterization and Hydrodesulfurization Properties of Catalysts Derived from Amorphous Metal-Boron Materials Unsupported and silica-supported amorphous metal-boron materials (Ni-B, Mo-O-B, and Ni-Mo-O-B) were prepared by NaBH{sub 4} reduction of aqueous or

  14. The Federal Highway Administration Gasohol Consumption Estimation Model

    SciTech Connect (OSTI)

    Hwang, HL

    2003-08-28

    The Federal Highway Administration (FHWA) is responsible for estimating the portion of Federal highway funds attributable to each State. The process involves use of State-reported data (gallons) and a set of estimation models when accurate State data is unavailable. To ensure that the distribution of funds is equitable, FHWA periodically reviews the estimation models. Estimation of the use of gasohol is difficult because of State differences in the definition of gasohol, inability of many States to separate and report gasohol usage from other fuel types, changes in fuel composition in nonattainment areas to address concerns over the use of certain fuel additives, and the lack of a valid State-level surrogate data set for gasohol use. Under the sponsorship of FHWA, Oak Ridge National Laboratory (ORNL) reviewed the regression-based gasohol estimation model that has been in use for several years. Based on an analytical assessment of that model and an extensive review of potential data sets, ORNL developed an improved rule-based model. The new model uses data from Internal Revenue Service, Energy Information Administration, Environmental Protection Agency, Department of Energy, ORNL, and FHWA sources. The model basically consists of three parts: (1) development of a controlled total of national gasohol usage, (2) determination of reliable State gasohol consumption data, and (3) estimation of gasohol usage for all other States. The new model will be employed for the 2004 attribution process. FHWA is currently soliciting comments and inputs from interested parties. Relevant data, as identified, will be pursued and refinements will be made by the research team if warranted.

  15. U.S. Natural Gas % of Total Residential Deliveries (Percent)

    Gasoline and Diesel Fuel Update (EIA)

    Deliveries (Percent) U.S. Natural Gas % of Total Residential Deliveries (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 100 100 100 100 100 100 100 2000's 100 100 100 100 100 100 100 100 100 100 2010's 100 100 100 100 100 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016 Next Release Date: 5/31/2016 Referring Pages: Share of Total U.S. Natural Gas

  16. Properties of solar gravity mode signals in total irradiance observations

    SciTech Connect (OSTI)

    Kroll, R.J.; Chen, J.; Hill, H.A.

    1988-01-01

    Further evidence has been found that a significant fraction of the gravity mode power density in the total irradiance observations appears in sidebands of classified eigenfrequencies. These sidebands whose amplitudes vary from year to year are interpreted as harmonics of the rotational frequencies of the nonuniform solar surface. These findings are for non axisymmetric modes and corroborate the findings of Kroll, Hill and Chen for axisymmetric modes. It is demonstrated the the generation of the sidebands lifts the usual restriction on the parity of the eigenfunctions for modes detectable in total irradiance observations. 14 refs.

  17. Flow cytometric measurement of total DNA and incorporated halodeoxyuridine

    DOE Patents [OSTI]

    Dolbeare, Frank A.; Gray, Joe W.

    1986-01-01

    A method for the simultaneous flow cytometric measurement of the total DNA content and the level of DNA synthesis in normal and malignant cells is disclosed. The sensitivity of the method allows a study of cell cycle traverse rates for large scale cell populations as well as single cell measurements. A DNA stain such as propidium iodide is used as the probe for the measurement of total DNA content and a monoclonal antibody reactive with a DNA precursor such as bromodeoxyuridine (BrdU) is used as a probe for the measurement of BrdU uptake by the cells as a measure of DNA synthesis.

  18. Federal Offshore -- Gulf of Mexico Natural Gas Total Consumption (Million

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

    Cubic Feet) -- Gulf of Mexico Natural Gas Total Consumption (Million Cubic Feet) Federal Offshore -- Gulf of Mexico Natural Gas Total Consumption (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 0 2000's 0 0 109,277 98,372 90,025 78,139 102,242 115,528 102,389 103,976 2010's 108,490 101,217 93,985 95,207 93,855 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data.

  19. Estimating the potential of greenhouse gas mitigation in Kazakhstan

    SciTech Connect (OSTI)

    Monacrovich, E.; Pilifosova, O.; Danchuck, D.

    1996-09-01

    As part of the studies related to the obligations of the UN Framework Convention on Climate Change, the Republic of Kazakhstan started activities to inventory greenhouse gas (GHG) emissions and assess of GHG mitigation options, The objective of this paper is to present an estimate of the possibility of mitigating GHG emissions and determine the mitigation priorities. It presents a compilation of the possible options and their assessment in terms of major criteria and implementation feasibility. Taking into account the structure of GHG emissions in Kazakhstan in 1990, preliminary estimates of the potential for mitigation are presented for eight options for the energy sector and agriculture and forestry sector. The reference scenario prepared by expert assessments assumes a reduction of CO{sub 2} emissions in 1996-1998 by about 26% from the 1990 level due to general economic decline, but then emissions increase. It is estimated that the total potential for the mitigation of CO{sub 2} emissions for the year 2000 is 3% of the CO{sub 2} emissions in the reference scenario. The annual reduction in methane emissions due to the estimated options can amount to 5%-6% of the 1990 level. 10 refs., 1 fig., 4 tabs.

  20. Reassessing Wind Potential Estimates for India: Economic and Policy Implications

    SciTech Connect (OSTI)

    Phadke, Amol; Bharvirkar, Ranjit; Khangura, Jagmeet

    2011-09-15

    We assess developable on-shore wind potential in India at three different hub-heights and under two sensitivity scenarios – one with no farmland included, the other with all farmland included. Under the “no farmland included” case, the total wind potential in India ranges from 748 GW at 80m hub-height to 976 GW at 120m hub-height. Under the “all farmland included” case, the potential with a minimum capacity factor of 20 percent ranges from 984 GW to 1,549 GW. High quality wind energy sites, at 80m hub-height with a minimum capacity factor of 25 percent, have a potential between 253 GW (no farmland included) and 306 GW (all farmland included). Our estimates are more than 15 times the current official estimate of wind energy potential in India (estimated at 50m hub height) and are about one tenth of the official estimate of the wind energy potential in the US.

  1. Cost Model and Cost Estimating Software

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

    1997-03-28

    This chapter discusses a formalized methodology is basically a cost model, which forms the basis for estimating software.

  2. Estimating Waste Inventory and Waste Tank Characterization

    Broader source: Energy.gov [DOE]

    Summary Notes from 28 May 2008 Generic Technical Issue Discussion on Estimating Waste Inventory and Waste Tank Characterization

  3. Table 17. Estimated natural gas plant liquids and dry natural gas content of tot

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

    Estimated natural gas plant liquids and dry natural gas content of total natural gas proved reserves, 2014" "million barrels and billion cubic feet" ,"Total Wet Natural Gas Proved Reserves",,,,"Estimated content of proved reserves" " State and Subdivision",,2014,,,"Natural Gas Plant Liquids",,"Dry Natural Gas" ,,"billion cubic feet",,,"million barrels",,"billion cubic feet"

  4. BLE: Battery Life Estimator | Argonne National Laboratory

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

    BOE Reserve Class No 2001 Reserves 0.1 - 10 MBOE Basin Outline WY UT ID CO MT WA OR NV CANADA INDEX MAP ID Total Total Total Number Liquid Gas BOE of Reserves Reserves Reserves Fields (Mbbl) (MMcf) (Mbbl) Montana Thrust Belt 1 1 0 1 Basin 2001 Reserve Summary for Montana Thrust Belt Fields CANADA USA Montana Thrust Belt Oil & Gas Fields By 2001 BOE

    Gas Reserve Class No 2001 gas reserves Basin Outline WY UT ID CO MT WA OR NV CANADA INDEX MAP ID Total Total Total Number Liquid Gas BOE of

  5. New Methodology for Natural Gas Production Estimates

    Reports and Publications (EIA)

    2010-01-01

    A new methodology is implemented with the monthly natural gas production estimates from the EIA-914 survey this month. The estimates, to be released April 29, 2010, include revisions for all of 2009. The fundamental changes in the new process include the timeliness of the historical data used for estimation and the frequency of sample updates, both of which are improved.

  6. Characterization of ?-carrageenan and its derivative based green polymer electrolytes

    SciTech Connect (OSTI)

    Jumaah, Fatihah Najirah; Mobaraka, Nadhratun Naiim; Ahmad, Azizan; Ramli, Nazaruddin [School of Chemical Sciences and Food Technology, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600, Bangi, Selangor Darul Ehsan (Malaysia)

    2013-11-27

    The new types of green polymer electrolytes based on ?-carrageenan derivative have been prepared. ?-carrageenan act as precursor was reacted with monochloroacetic acid to produce carboxymethyl ?-carrageenan. The powders were characterized by Attenuated Total Reflection Fourier Transform infrared (ATR-FTIR) spectroscopy and {sup 1}H nuclear magnetic resonance (NMR) to confirm the substitution of targeted functional group in ?-carrageenan. The green polymer electrolyte based on ?-carrageenan and carboxymethyl ?-carrageenan was prepared by solution-casting technique. The films were characterized by electrochemical impedance spectroscopy to determine the ionic conductivity. The ionic conductivity ?-carrageenan film were higher than carboxymethyl ?-carrageenan which 4.87 10{sup ?6} S cm{sup ?1} and 2.19 10{sup ?8} S cm{sup ?1}, respectively.

  7. Photolysis and radiant flash pyrolysis of coal-derived wastes

    SciTech Connect (OSTI)

    Worman, J.J.; Worman, J.J.; Hawthorne, S.B.; Sears, R.E.

    1986-01-01

    It is attractive to think that coal-derived wastes could be converted to useful fuels by irradiation with solar energy. This would eliminate energy-intensive steps in the processing of coal gasification condensate water as well as provide an inexpensive alternate source of energy. Environmental concerns for the distribution of contaminants from biosludge would be minimized. This paper demonstrates that coal gasification condensate water in the presence of photoconductors and varying wavelengths of light can produce useful fuels in addition to lowering the total organic carbon content. Biosludge obtained from the processing of the condensate water can be irradiated in the solid state with a high-intensity xenon flash to give fuel-type products as identified by GC/MS. 13 refs., 2 figs., 4 tabs.

  8. A fresh look at coal-derived liquid fuels

    SciTech Connect (OSTI)

    Paul, A.D.

    2009-01-15

    35% of the world's energy comes from oil, and 96% of that oil is used for transportation. The current number of vehicles globally is estimated to be 700 million; that number is expected to double overall by 2030, and to triple in developing countries. Now consider that the US has 27% of the world's supply of coal yet only 2% of the oil. Coal-to-liquids technologies could bridge the gap between US fuel supply and demand. The advantages of coal-derived liquid fuels are discussed in this article compared to the challenges of alternative feedstocks of oil sands, oil shale and renewable sources. It is argued that pollutant emissions from coal-to-liquid facilities could be minimal because sulfur compounds will be removed, contaminants need to be removed for the FT process, and technologies are available for removing solid wastes and nitrogen oxides. If CO{sub 2} emissions for coal-derived liquid plants are captured and sequestered, overall emissions of CO{sub 2} would be equal or less than those from petroleum. Although coal liquefaction requires large volumes of water, most water used can be recycled. Converting coal to liquid fuels could, at least in the near term, bring a higher level of stability to world oil prices and the global economy and could serve as insurance for the US against price hikes from oil-producing countries. 7 figs.

  9. Device for measuring the total concentration of oxygen in gases

    DOE Patents [OSTI]

    Isaacs, Hugh S.; Romano, Anthony J.

    1977-01-01

    This invention provides a CO equilibrium in a device for measuring the total concentration of oxygen impurities in a fluid stream. To this end, the CO equilibrium is produced in an electrochemical measuring cell by the interaction of a carbon element in the cell with the chemically combined and uncombined oxygen in the fluid stream at an elevated temperature.

  10. "Table A10. Total Consumption of LPG, Distillate Fuel Oil...

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

    "Total",11681,21576,70668,"W",21384,80123,"W",315,0,9.3 "Employment Size" " Under 50",1824,6108,928,"W",5936,928,"Q","Q",0,37.1 " 50-99","W",2450,6052,573,"W",6052,"W","W",0,20.7 ...

  11. Broad Band Intra-Cavity Total Reflection Chemical Sensor

    DOE Patents [OSTI]

    Pipino, Andrew C. R.

    1998-11-10

    A broadband, ultrahigh-sensitivity chemical sensor is provided that allows etection through utilization of a small, extremely low-loss, monolithic optical cavity. The cavity is fabricated from highly transparent optical material in the shape of a regular polygon with one or more convex facets to form a stable resonator for ray trajectories sustained by total internal reflection. Optical radiation enters and exits the monolithic cavity by photon tunneling in which two totally reflecting surfaces are brought into close proximity. In the presence of absorbing material, the loss per pass is increased since the evanescent waves that exist exterior to the cavity at points where the circulating pulse is totally reflected, are absorbed. The decay rate of an injected pulse is determined by coupling out an infinitesimal fraction of the pulse to produce an intensity-versus-time decay curve. Since the change in the decay rate resulting from absorption is inversely proportional to the magnitude of absorption, a quantitative sensor of concentration or absorption cross-section with 1 part-per-million/pass or better sensitivity is obtained. The broadband nature of total internal reflection permits a single device to be used over a broad wavelength range. The absorption spectrum of the surrounding medium can thereby be obtained as a measurement of inverse decay time as a function of wavelength.

  12. Commercialization strategies for coal-derived transportation fuels

    SciTech Connect (OSTI)

    Tomlinson, G.; Gray, D.

    1992-12-31

    The objective of this paper is to analyze a program that can stimulate the development of a synthetic liquid transportation fuels from coal industry, by requiring that the products be bought at their true cost of production. These coal-derived liquids will then be assimulated into the nation`s fuel supply system. The cost of this program will be borne by increased cost of all fuels in the marketplace. The justification of the program is the assumption that, because of increasing demand, the world oil price (WOP) will increase to a level that will make coal-derived fuels economical in the relatively near future. However, as noted in the International Energy Outlook of 1990: ``Given current costs and Technologies, it is estimated the cost of crude oil would have to exceed $35 per barrel in 1989 dollars for at least four consecutive years for commercial production, in the range of 100,000 barrels per day, of synthetic liquids to occur. This delayed response of production to price increases reflects the planning and construction time required to complete a coal liquefaction plant``. This program is designed to reduce this time lag so that coal-derived fuels will be available when they are needed. This timely production capability of coal liquids may be able to limit future world oil prices to the actual cost of synthetic alternatives. In addition, the program is structured so that it will provide synthetic fuel producers with a cushion in the event that the WOP continues to remain low.

  13. Determining effective soil formation thermal properties from field data using a parameter estimation technique

    SciTech Connect (OSTI)

    Shonder, J.A.; Beck, J.V.

    1998-11-01

    A one-dimensional thermal model is derived to describe the temperature field around a vertical borehole heat exchanger (BHEx) for a geothermal heat pump. The inlet and outlet pipe flows are modeled as one, and an effective heat capacity is added to model the heat storage in the fluid and pipes. Parameter estimation techniques are then used to estimate various parameters associated with the model, including the thermal conductivity of the soil and of the grout which fills the borehole and surrounds the u-tube. The model is validated using test data from an experimental rig containing sand with known thermal conductivity. The estimates of the sand thermal conductivity derived from the model are found to be in good agreement with independent measurements.

  14. Determining Effective Soil Formation Thermal Properties From Field Data Using A Parameter Estimation Technique

    SciTech Connect (OSTI)

    Shonder, John A; Beck, Dr. James V.

    1999-01-01

    A one-dimensional thermal model is derived to describe the temperature field around a vertical borehole heat exchanger (BHEX) for a geothermal heat pump. The inlet and outlet pipe flows are modeled as one, and an effective heat capacity is added to model the heat storage in the fluid and pipes. Parameter estimation techniques are then used to estimate various parameters associated with the model, including the thermal conductivity of the soil and the grout that fills the borehole and surrounds the U-tube. The model is validated using test data from an experimental rig containing sand with known thermal conductivity. The estimates of the sand's thermal conductivity derived from the model are found to be in good agreement with independent measurements.

  15. Comparison of Historical Satellite-Based Estimates of Solar Radiation Resources with Recent Rotating Shadowband Radiometer Measurements: Preprint

    SciTech Connect (OSTI)

    Myers, D. R.

    2009-03-01

    The availability of rotating shadow band radiometer measurement data at several new stations provides an opportunity to compare historical satellite-based estimates of solar resources with measurements. We compare mean monthly daily total (MMDT) solar radiation data from eight years of NSRDB and 22 years of NASA hourly global horizontal and direct beam solar estimates with measured data from three stations, collected after the end of the available resource estimates.

  16. Tropical Africa: Land use, biomass, and carbon estimates for 1980

    SciTech Connect (OSTI)

    Brown, S.; Gaston, G.; Daniels, R.C.

    1996-06-01

    This document describes the contents of a digital database containing maximum potential aboveground biomass, land use, and estimated biomass and carbon data for 1980 and describes a methodology that may be used to extend this data set to 1990 and beyond based on population and land cover data. The biomass data and carbon estimates are for woody vegetation in Tropical Africa. These data were collected to reduce the uncertainty associated with the possible magnitude of historical releases of carbon from land use change. Tropical Africa is defined here as encompassing 22.7 x 10{sup 6} km{sup 2} of the earth`s land surface and includes those countries that for the most part are located in Tropical Africa. Countries bordering the Mediterranean Sea and in southern Africa (i.e., Egypt, Libya, Tunisia, Algeria, Morocco, South Africa, Lesotho, Swaziland, and Western Sahara) have maximum potential biomass and land cover information but do not have biomass or carbon estimate. The database was developed using the GRID module in the ARC/INFO{sup TM} geographic information system. Source data were obtained from the Food and Agriculture Organization (FAO), the U.S. National Geophysical Data Center, and a limited number of biomass-carbon density case studies. These data were used to derive the maximum potential and actual (ca. 1980) aboveground biomass-carbon values at regional and country levels. The land-use data provided were derived from a vegetation map originally produced for the FAO by the International Institute of Vegetation Mapping, Toulouse, France.

  17. A comparison of estimates of cost-effectiveness of alternative fuels and vehicles for reducing emissions

    SciTech Connect (OSTI)

    Hadder, G.R.

    1995-11-01

    The cost-effectiveness ratio (CER) is a measure of the monetary value of resources expended to obtain reductions in emissions of air pollutants. The CER can lead to selection of the most effective sequence of pollution reduction options. Derived with different methodologies and technical assumptions, CER estimates for alternative fuel vehicles (AFVs) have varied widely among pervious studies. In one of several explanations of LCER differences, this report uses a consistent basis for fuel price to re-estimate CERs for AFVs in reduction of emissions of criteria pollutants, toxics, and greenhouse gases. The re-estimated CERs for a given fuel type have considerable differences due to non-fuel costs and emissions reductions, but the CERs do provide an ordinal sense of cost-effectiveness. The category with CER less than $5,000 per ton includes compressed natural gas and ed Petroleum gas vehicles; and E85 flexible-fueled vehicles (with fuel mixture of 85 percent cellulose-derived ethanol in gasoline). The E85 system would be much less attractive if corn-derived ethanol were used. The CER for E85 (corn-derived) is higher with higher values placed on the reduction of gas emissions. CER estimates are relative to conventional vehicles fueled with Phase 1 California reformulated gasoline (RFG). The California Phase 2 RFG program will be implemented before significant market penetration by AFVs. CERs could be substantially greater if they are calculated incremental to the Phase 2 RFG program. Regression analysis suggests that different assumptions across studies can sometimes have predictable effects on the CER estimate of a particular AFV type. The relative differences in cost and emissions reduction assumptions can be large, and the effect of these differences on the CER estimate is often not predictable. Decomposition of CERs suggests that methodological differences can make large contributions to CER differences among studies.

  18. Robust bearing estimation for 3-component stations

    SciTech Connect (OSTI)

    CLAASSEN,JOHN P.

    2000-02-01

    A robust bearing estimation process for 3-component stations has been developed and explored. The method, called SEEC for Search, Estimate, Evaluate and Correct, intelligently exploits the inherent information in the arrival at every step of the process to achieve near-optimal results. In particular the approach uses a consistent framework to define the optimal time-frequency windows on which to make estimates, to make the bearing estimates themselves, to construct metrics helpful in choosing the better estimates or admitting that the bearing is immeasurable, and finally to apply bias corrections when calibration information is available to yield a single final estimate. The algorithm was applied to a small but challenging set of events in a seismically active region. It demonstrated remarkable utility by providing better estimates and insights than previously available. Various monitoring implications are noted from these findings.

  19. Robust Bearing Estimation for 3-Component Stations

    SciTech Connect (OSTI)

    Claassen, John P.

    1999-06-03

    A robust bearing estimation process for 3-component stations has been developed and explored. The method, called SEEC for Search, Estimate, Evaluate and Correct, intelligently exploits the in- herent information in the arrival at every step of the process to achieve near-optimal results. In particular, the approach uses a consistent framework to define the optimal time-frequency windows on which to make estimates, to make the bearing estimates themselves, to construct metrics helpful in choosing the better estimates or admitting that the bearing is immeasurable, andjinally to apply bias corrections when calibration information is available to yield a single final estimate. The method was applied to a small but challenging set of events in a seismically active region. The method demonstrated remarkable utility by providing better estimates and insights than previously available. Various monitoring implications are noted fiom these findings.

  20. Optimizing weak lensing mass estimates for cluster profile uncertainty

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

    Gruen, D.; Bernstein, G. M.; Lam, T. Y.; Seitz, S.

    2011-09-11

    Weak lensing measurements of cluster masses are necessary for calibrating mass-observable relations (MORs) to investigate the growth of structure and the properties of dark energy. However, the measured cluster shear signal varies at fixed mass M200m due to inherent ellipticity of background galaxies, intervening structures along the line of sight, and variations in the cluster structure due to scatter in concentrations, asphericity and substructure. We use N-body simulated halos to derive and evaluate a weak lensing circular aperture mass measurement Map that minimizes the mass estimate variance <(Map - M200m)2> in the presence of all these forms of variability. Dependingmore » on halo mass and observational conditions, the resulting mass estimator improves on Map filters optimized for circular NFW-profile clusters in the presence of uncorrelated large scale structure (LSS) about as much as the latter improve on an estimator that only minimizes the influence of shape noise. Optimizing for uncorrelated LSS while ignoring the variation of internal cluster structure puts too much weight on the profile near the cores of halos, and under some circumstances can even be worse than not accounting for LSS at all. As a result, we discuss the impact of variability in cluster structure and correlated structures on the design and performance of weak lensing surveys intended to calibrate cluster MORs.« less

  1. Second derivatives for approximate spin projection methods

    SciTech Connect (OSTI)

    Thompson, Lee M.; Hratchian, Hrant P.

    2015-02-07

    The use of broken-symmetry electronic structure methods is required in order to obtain correct behavior of electronically strained open-shell systems, such as transition states, biradicals, and transition metals. This approach often has issues with spin contamination, which can lead to significant errors in predicted energies, geometries, and properties. Approximate projection schemes are able to correct for spin contamination and can often yield improved results. To fully make use of these methods and to carry out exploration of the potential energy surface, it is desirable to develop an efficient second energy derivative theory. In this paper, we formulate the analytical second derivatives for the Yamaguchi approximate projection scheme, building on recent work that has yielded an efficient implementation of the analytical first derivatives.

  2. Reliability Estimates for Power Supplies

    SciTech Connect (OSTI)

    Lee C. Cadwallader; Peter I. Petersen

    2005-09-01

    Failure rates for large power supplies at a fusion facility are critical knowledge needed to estimate availability of the facility or to set priorties for repairs and spare components. A study of the "failure to operate on demand" and "failure to continue to operate" failure rates has been performed for the large power supplies at DIII-D, which provide power to the magnet coils, the neutral beam injectors, the electron cyclotron heating systems, and the fast wave systems. When one of the power supplies fails to operate, the research program has to be either temporarily changed or halted. If one of the power supplies for the toroidal or ohmic heating coils fails, the operations have to be suspended or the research is continued at de-rated parameters until a repair is completed. If one of the power supplies used in the auxiliary plasma heating systems fails the research is often temporarily changed until a repair is completed. The power supplies are operated remotely and repairs are only performed when the power supplies are off line, so that failure of a power supply does not cause any risk to personnel. The DIII-D Trouble Report database was used to determine the number of power supply faults (over 1,700 reports), and tokamak annual operations data supplied the number of shots, operating times, and power supply usage for the DIII-D operating campaigns between mid-1987 and 2004. Where possible, these power supply failure rates from DIII-D will be compared to similar work that has been performed for the Joint European Torus equipment. These independent data sets support validation of the fusion-specific failure rate values.

  3. Time and Resource Estimation Tool

    Energy Science and Technology Software Center (OSTI)

    2004-06-08

    RESTORE is a computer software tool that allows one to model a complex set of steps required to accomplish a goal (e.g., repair a ruptured natural gas pipeline and restore service to customers). However, the time necessary to complete step may be uncertain and may be affected by conditions, such as the weather, the time of day, the day of the week. Therefore, "nature" can influence which steps are taken and the time needed tomore » complete each step. In addition, the tool allows one to model the costs for each step, which also may be uncertain. RESTORE allows the user to estimate the time and cost, both of which may be uncertain, to achieve an intermediate stage of completion, as well as overall completion. The software also makes it possible to model parallel, competing groups of activities (i.e., parallel paths) so that progreSs at a ‘merge point’ can proceed before other competing activities are completed. For example, RESTORE permits one to model a workaround and a simultaneous complete repair to determine a probability distribution for the earliest time service can be restored to a critical customer. The tool identifies the ‘most active path’ through the network of tasks, which is extremely important information for assessing the most effective way to speed-up or slow-down progress. Unlike other project planning and risk analysis tools, RESTORE provides an intuitive, graphical, and object-oriented environment for structuring a model and setting its parameters.« less

  4. New Hampshire Natural Gas Total Consumption (Million Cubic Feet)

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

    Total Consumption (Million Cubic Feet) New Hampshire Natural Gas Total Consumption (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 20,848 19,127 20,313 2000's 24,950 23,398 24,901 54,147 61,172 70,484 62,549 62,132 71,179 59,950 2010's 60,378 69,978 72,032 54,028 57,017 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016 Next Release Date:

  5. New Jersey Natural Gas Total Consumption (Million Cubic Feet)

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

    Total Consumption (Million Cubic Feet) New Jersey Natural Gas Total Consumption (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 717,011 679,619 715,630 2000's 605,275 564,923 598,602 612,890 620,806 602,388 547,206 618,965 614,908 620,790 2010's 654,458 660,743 652,060 682,247 762,200 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016 Next

  6. New Mexico Natural Gas Total Consumption (Million Cubic Feet)

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

    Total Consumption (Million Cubic Feet) New Mexico Natural Gas Total Consumption (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 256,464 245,823 236,264 2000's 266,469 266,283 235,098 221,021 223,575 220,717 223,636 234,236 246,665 241,194 2010's 241,137 246,418 243,961 245,502 246,178 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016 Next

  7. New York Natural Gas Total Consumption (Million Cubic Feet)

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

    Total Consumption (Million Cubic Feet) New York Natural Gas Total Consumption (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 1,324,164 1,232,473 1,274,162 2000's 1,244,746 1,171,898 1,199,632 1,101,618 1,098,056 1,080,215 1,097,160 1,187,059 1,180,356 1,142,625 2010's 1,198,127 1,217,324 1,223,036 1,273,263 1,345,315 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data.

  8. North Carolina Natural Gas Total Consumption (Million Cubic Feet)

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

    Total Consumption (Million Cubic Feet) North Carolina Natural Gas Total Consumption (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 215,634 214,092 217,159 2000's 233,714 207,108 235,376 218,642 224,796 229,715 223,032 237,354 243,090 247,047 2010's 304,148 307,804 363,945 440,175 453,212 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016 Next

  9. North Dakota Natural Gas Total Consumption (Million Cubic Feet)

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

    Total Consumption (Million Cubic Feet) North Dakota Natural Gas Total Consumption (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 56,179 49,541 56,418 2000's 56,528 60,819 66,726 60,907 59,986 53,050 53,336 59,453 63,097 54,564 2010's 66,395 72,463 72,740 81,593 83,330 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016 Next Release Date:

  10. Ohio Natural Gas Total Consumption (Million Cubic Feet)

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

    Total Consumption (Million Cubic Feet) Ohio Natural Gas Total Consumption (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 897,693 811,384 841,966 2000's 890,962 804,243 830,955 848,388 825,753 825,961 742,359 806,350 792,247 740,925 2010's 784,293 823,548 842,959 912,403 1,000,231 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016 Next Release

  11. Oklahoma Natural Gas Total Consumption (Million Cubic Feet)

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

    Total Consumption (Million Cubic Feet) Oklahoma Natural Gas Total Consumption (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 567,050 575,855 538,329 2000's 538,563 491,458 508,298 540,103 538,576 582,536 624,400 658,379 687,989 659,305 2010's 675,727 655,919 691,661 658,569 640,607 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016 Next

  12. Oregon Natural Gas Total Consumption (Million Cubic Feet)

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

    Total Consumption (Million Cubic Feet) Oregon Natural Gas Total Consumption (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 185,069 229,403 235,009 2000's 224,888 229,665 202,164 212,556 234,997 232,562 222,608 251,927 268,484 248,864 2010's 239,325 199,419 215,830 240,418 220,076 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016 Next Release

  13. Pacific Region Natural Gas Total Underground Storage Capacity (Million

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

    Cubic Feet) Region Natural Gas Total Underground Storage Capacity (Million Cubic Feet) Pacific Region Natural Gas Total Underground Storage Capacity (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2014 676,176 676,176 676,176 676,176 676,176 676,176 676,176 676,176 676,176 676,176 676,176 676,176 2015 679,477 679,477 679,477 679,477 679,477 679,477 679,477 679,477 679,477 678,273 678,273 678,273 2016 678,273 678,273 - = No Data Reported; -- = Not Applicable; NA =

  14. Pennsylvania Natural Gas Total Consumption (Million Cubic Feet)

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

    Total Consumption (Million Cubic Feet) Pennsylvania Natural Gas Total Consumption (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 706,230 644,017 688,740 2000's 702,847 634,794 675,583 689,992 696,175 691,591 659,754 752,401 749,884 809,707 2010's 879,365 965,742 1,037,979 1,121,696 1,203,418 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016

  15. Alaska Natural Gas % of Total Residential Deliveries (Percent)

    Gasoline and Diesel Fuel Update (EIA)

    % of Total Residential Deliveries (Percent) Alaska Natural Gas % of Total Residential Deliveries (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 0.28 0.31 0.31 0.31 0.30 0.35 0.37 2000's 0.32 0.35 0.33 0.33 0.37 0.37 0.47 0.42 0.44 0.42 2010's 0.39 0.43 0.52 0.39 0.35 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016 Next Release Date: 5/31/2016

  16. Hawaii Natural Gas % of Total Residential Deliveries (Percent)

    Gasoline and Diesel Fuel Update (EIA)

    Foot) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2013 1,056 1,055 1,057 1,043 983 983 983 983 983 983 983 983 2014 947 946 947 947 947 947 951 978 990 968 974 962 2015 968 954 947 959 990 1,005 1,011 965 989 996 996 997 2016 998 1,004

    % of Total Residential Deliveries (Percent) Hawaii Natural Gas % of Total Residential Deliveries (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 0.01 0.01 0.01 0.01 0.01 0.01 0.01 2000's 0.01 0.01 0.01

  17. Idaho Natural Gas % of Total Residential Deliveries (Percent)

    Gasoline and Diesel Fuel Update (EIA)

    Foot) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2013 1,015 1,015 1,031 1,021 1,010 997 988 994 1,001 1,026 1,034 1,054 2014 1,048 1,036 1,030 1,022 1,006 993 984 996 1,005 1,019 1,046 1,039 2015 1,047 1,037 1,030 1,023 1,000 1,010 1,034 1,028 1,024 1,033 1,035 1,041 2016 1,034 1,038

    % of Total Residential Deliveries (Percent) Idaho Natural Gas % of Total Residential Deliveries (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 0.25

  18. Kentucky Natural Gas Total Consumption (Million Cubic Feet)

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

    Total Consumption (Million Cubic Feet) Kentucky Natural Gas Total Consumption (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 227,931 205,129 218,399 2000's 225,168 208,974 227,920 223,226 225,470 234,080 211,049 229,799 225,295 206,833 2010's 232,099 223,034 225,924 229,983 254,244 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016 Next

  19. Louisiana Natural Gas Total Consumption (Million Cubic Feet)

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

    Total Consumption (Million Cubic Feet) Louisiana Natural Gas Total Consumption (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 1,661,061 1,569,190 1,495,478 2000's 1,536,725 1,219,013 1,341,444 1,233,505 1,281,428 1,254,370 1,217,871 1,289,421 1,238,661 1,189,744 2010's 1,354,641 1,420,264 1,482,343 1,396,261 1,460,031 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company

  20. Maryland Natural Gas Total Consumption (Million Cubic Feet)

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

    Total Consumption (Million Cubic Feet) Maryland Natural Gas Total Consumption (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 212,017 188,552 196,350 2000's 212,133 178,376 196,276 197,024 194,725 202,509 182,294 201,053 196,067 196,510 2010's 212,020 193,986 208,946 197,356 207,527 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016 Next

  1. Massachusetts Natural Gas Total Consumption (Million Cubic Feet)

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

    Total Consumption (Million Cubic Feet) Massachusetts Natural Gas Total Consumption (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 402,629 358,846 344,790 2000's 343,314 349,103 393,194 403,991 372,532 378,068 370,664 408,704 406,719 395,852 2010's 432,297 449,194 416,350 421,001 418,526 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016 Next

  2. Michigan Natural Gas Total Consumption (Million Cubic Feet)

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

    Total Consumption (Million Cubic Feet) Michigan Natural Gas Total Consumption (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 994,342 876,444 951,143 2000's 963,136 906,001 966,354 924,819 916,629 913,827 803,336 798,126 779,602 735,340 2010's 746,748 776,466 790,642 814,635 850,974 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016 Next

  3. Midwest Region Natural Gas Total Underground Storage Capacity (Million

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

    Cubic Feet) Total Underground Storage Capacity (Million Cubic Feet) Midwest Region Natural Gas Total Underground Storage Capacity (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2014 2,721,231 2,721,231 2,721,231 2,721,231 2,721,231 2,721,231 2,721,231 2,721,231 2,721,231 2,723,336 2,725,497 2,725,535 2015 2,725,587 2,725,587 2,725,587 2,725,587 2,725,587 2,725,587 2,725,587 2,716,587 2,715,888 2,717,255 2,718,087 2,718,087 2016 2,718,087 2,718,087 - = No Data

  4. Mississippi Natural Gas Total Consumption (Million Cubic Feet)

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

    Total Consumption (Million Cubic Feet) Mississippi Natural Gas Total Consumption (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 255,475 241,342 306,733 2000's 300,652 332,589 343,890 265,842 282,051 301,663 307,305 364,067 355,006 364,323 2010's 438,733 433,538 494,016 420,594 412,979 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016 Next

  5. Missouri Natural Gas Total Consumption (Million Cubic Feet)

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

    Total Consumption (Million Cubic Feet) Missouri Natural Gas Total Consumption (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 283,294 258,652 265,798 2000's 284,763 283,793 275,629 262,529 263,945 268,040 252,697 272,536 296,058 264,867 2010's 280,181 272,583 255,875 276,967 296,605 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016 Next

  6. Montana Natural Gas Total Consumption (Million Cubic Feet)

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

    Total Consumption (Million Cubic Feet) Montana Natural Gas Total Consumption (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 59,851 59,840 62,129 2000's 67,955 65,051 69,532 68,473 66,829 68,355 73,879 73,822 76,422 75,802 2010's 72,025 78,217 73,399 79,670 78,010 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016 Next Release Date: 5/31/2016

  7. Nebraska Natural Gas Total Consumption (Million Cubic Feet)

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

    Total Consumption (Million Cubic Feet) Nebraska Natural Gas Total Consumption (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 132,221 130,730 121,487 2000's 126,962 121,984 120,333 118,922 115,011 119,070 129,885 150,808 171,005 163,474 2010's 168,944 171,777 158,757 173,376 172,749 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016 Next

  8. Nevada Natural Gas Total Consumption (Million Cubic Feet)

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

    Total Consumption (Million Cubic Feet) Nevada Natural Gas Total Consumption (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 132,128 148,539 154,689 2000's 189,170 176,835 176,596 185,846 214,984 227,149 249,608 254,406 264,596 275,468 2010's 259,251 249,971 273,502 272,965 252,097 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016 Next Release

  9. AGA Eastern Consuming Region Natural Gas Total Underground Storage Capacity

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

    (Million Cubic Feet) Total Underground Storage Capacity (Million Cubic Feet) AGA Eastern Consuming Region Natural Gas Total Underground Storage Capacity (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1994 4,737,921 4,727,501 4,727,501 4,727,501 4,727,501 4,727,501 4,727,501 4,727,501 4,727,446 4,727,446 4,727,446 4,727,509 1995 4,730,109 4,647,791 4,647,791 4,647,791 4,647,791 4,647,791 4,593,948 4,593,948 4,593,948 4,593,948 4,593,948 4,593,948 1996 4,593,948

  10. Alabama Natural Gas Total Consumption (Million Cubic Feet)

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

    Total Consumption (Million Cubic Feet) Alabama Natural Gas Total Consumption (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 324,158 329,134 337,270 2000's 353,614 332,693 379,343 350,345 382,367 353,156 391,093 418,512 404,157 454,456 2010's 534,779 598,514 666,712 615,407 634,678 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016 Next Release

  11. Alaska Natural Gas Total Consumption (Million Cubic Feet)

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

    Total Consumption (Million Cubic Feet) Alaska Natural Gas Total Consumption (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 425,393 434,871 422,816 2000's 427,288 408,960 419,131 414,234 406,319 432,972 373,850 369,967 341,888 342,261 2010's 333,312 335,458 343,110 332,298 327,428 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016 Next Release

  12. Flow cytometric measurement of total DNA and incorporated halodeoxyuridine

    DOE Patents [OSTI]

    Dolbeare, Frank A.; Gray, Joe W.

    1988-01-01

    A method for the simultaneous flow cytometric measurement of the total DNA content and the level of DNA synthesis in normal and malignant cells is disclosed. The sensitivity of the method allows a study of cell cycle traverse rates for large scale cell populations as well as single cell measurements. A DNA stain such as propidium iodide or Hoechst 33258 is used as the probe for the measurement of total DNA content and a monoclonal antibody reactive with a DNA precursor such as halodeoxy-uridine (HdU), more specifically bromodeoxyuridine (BrdU) is used as a probe for the measurement of HdU or BrdU uptake by the cells as a measure of DNA synthesis.

  13. Wyoming Natural Gas Total Consumption (Million Cubic Feet)

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

    Total Consumption (Million Cubic Feet) Wyoming Natural Gas Total Consumption (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 100,950 109,188 96,726 2000's 101,314 98,569 112,872 115,358 107,060 108,314 108,481 140,912 142,705 142,793 2010's 150,106 156,455 153,333 149,820 135,678 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016 Next Release

  14. Flow cytometric measurement of total DNA and incorporated halodeoxyuridine

    DOE Patents [OSTI]

    Dolbeare, F.A.; Gray, J.W.

    1983-10-18

    A method for the simultaneous flow cylometric measurement of total cellular DNA content and of the uptake of DNA precursors as a measure of DNA synthesis during various phases of the cell cycle in normal and malignant cells in vitro and in vivo is described. The method comprises reacting cells with labelled halodeoxyuridine (HdU), partially denaturing cellular DNA, adding to the reaction medium monoclonal antibodies (mabs) reactive with HdU, reacting the bound mabs with a second labelled antibody, incubating the mixture with a DNA stain, and measuring simultaneously the intensity of the DNA stain as a measure of the total cellular DNA and the HdU incorporated as a measure of DNA synthesis. (ACR)

  15. Rhode Island Natural Gas Total Consumption (Million Cubic Feet)

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

    Total Consumption (Million Cubic Feet) Rhode Island Natural Gas Total Consumption (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 117,707 130,751 118,001 2000's 88,419 95,607 87,805 78,456 72,609 80,764 77,204 87,972 89,256 92,743 2010's 94,110 100,455 95,476 85,537 88,673 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016 Next Release Date:

  16. South Carolina Natural Gas Total Consumption (Million Cubic Feet)

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

    Total Consumption (Million Cubic Feet) South Carolina Natural Gas Total Consumption (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 153,917 159,458 162,926 2000's 160,436 141,785 184,803 146,641 163,787 172,032 174,806 175,701 170,077 190,928 2010's 220,235 229,497 244,850 232,297 231,863 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016 Next

  17. South Central Region Natural Gas Total Underground Storage Capacity

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

    (Million Cubic Feet) Total Underground Storage Capacity (Million Cubic Feet) South Central Region Natural Gas Total Underground Storage Capacity (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2014 2,578,946 2,577,866 2,578,498 2,578,547 2,590,575 2,599,184 2,611,335 2,616,178 2,612,570 2,613,746 2,635,148 2,634,993 2015 2,631,717 2,630,903 2,631,616 2,631,673 2,631,673 2,631,444 2,631,444 2,631,444 2,636,984 2,637,895 2,637,895 2,640,224 2016 2,634,512 2,644,516 -

  18. South Dakota Natural Gas Total Consumption (Million Cubic Feet)

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

    Total Consumption (Million Cubic Feet) South Dakota Natural Gas Total Consumption (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 36,115 33,042 35,794 2000's 37,939 37,077 41,577 43,881 41,679 42,555 40,739 53,938 65,258 66,185 2010's 72,563 73,605 70,238 81,986 79,964 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016 Next Release Date:

  19. Tennessee Natural Gas Total Consumption (Million Cubic Feet)

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

    Total Consumption (Million Cubic Feet) Tennessee Natural Gas Total Consumption (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 282,395 279,070 278,841 2000's 270,658 255,990 255,515 257,315 231,133 230,338 221,626 221,118 229,935 216,945 2010's 257,443 264,231 277,127 279,441 303,996 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016 Next

  20. Texas Natural Gas Total Consumption (Million Cubic Feet)

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

    Total Consumption (Million Cubic Feet) Texas Natural Gas Total Consumption (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 4,116,722 4,205,459 4,009,689 2000's 4,421,777 4,252,152 4,303,831 4,050,632 3,908,243 3,503,636 3,432,236 3,516,706 3,546,804 3,387,341 2010's 3,574,398 3,693,905 3,850,331 4,021,851 4,088,445 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data.

  1. U.S. Natural Gas Total Liquids Extracted (Thousand Barrels)

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

    Total Liquids Extracted (Thousand Barrels) U.S. Natural Gas Total Liquids Extracted (Thousand Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 569,968 599,518 584,160 571,256 587,502 594,306 569,913 1990's 573,054 602,734 626,320 634,481 635,983 649,149 689,314 690,999 668,011 686,862 2000's 721,895 682,873 681,646 622,291 657,032 619,884 637,635 658,291 673,677 720,612 2010's 749,095 792,481 873,563 937,591 1,124,416 - = No Data Reported; -- = Not

  2. Utah Natural Gas Total Consumption (Million Cubic Feet)

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

    Total Consumption (Million Cubic Feet) Utah Natural Gas Total Consumption (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 165,253 169,776 159,889 2000's 164,557 159,299 163,379 154,125 155,891 160,275 187,399 219,700 224,188 214,220 2010's 219,213 222,227 223,039 247,285 242,457 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016 Next Release

  3. Vermont Natural Gas Total Consumption (Million Cubic Feet)

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

    Total Consumption (Million Cubic Feet) Vermont Natural Gas Total Consumption (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 8,061 7,735 8,033 2000's 10,426 7,919 8,367 8,400 8,685 8,372 8,056 8,867 8,624 8,638 2010's 8,443 8,611 8,191 9,602 10,678 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016 Next Release Date: 5/31/2016 Referring Pages:

  4. Virginia Natural Gas Total Consumption (Million Cubic Feet)

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

    Total Consumption (Million Cubic Feet) Virginia Natural Gas Total Consumption (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 248,960 260,332 276,793 2000's 268,770 237,853 258,202 262,970 277,434 299,746 274,175 319,913 299,364 319,134 2010's 375,421 373,444 410,106 418,506 419,615 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016 Next

  5. Washington Natural Gas Total Consumption (Million Cubic Feet)

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

    Total Consumption (Million Cubic Feet) Washington Natural Gas Total Consumption (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 256,366 290,229 287,302 2000's 286,653 312,114 233,716 249,599 262,485 264,754 263,395 272,613 298,140 310,428 2010's 285,726 264,589 264,540 318,292 307,021 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016 Next

  6. West Virginia Natural Gas Total Consumption (Million Cubic Feet)

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

    Total Consumption (Million Cubic Feet) West Virginia Natural Gas Total Consumption (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 159,504 142,860 139,961 2000's 147,854 141,090 146,455 126,986 122,267 117,136 113,084 115,974 111,480 109,652 2010's 113,179 115,361 129,753 142,082 150,766 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016 Next

  7. Wisconsin Natural Gas Total Consumption (Million Cubic Feet)

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

    Total Consumption (Million Cubic Feet) Wisconsin Natural Gas Total Consumption (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 400,651 368,022 380,560 2000's 393,601 359,784 385,310 394,711 383,316 410,250 372,462 398,370 409,377 387,066 2010's 372,898 393,734 402,656 442,544 462,627 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016 Next

  8. Total System Performance Assessment - License Application Methods and Approach

    SciTech Connect (OSTI)

    J. McNeish

    2003-12-08

    ''Total System Performance Assessment-License Application (TSPA-LA) Methods and Approach'' provides the top-level method and approach for conducting the TSPA-LA model development and analyses. The method and approach is responsive to the criteria set forth in Total System Performance Assessment Integration (TSPAI) Key Technical Issues (KTIs) identified in agreements with the U.S. Nuclear Regulatory Commission, the ''Yucca Mountain Review Plan'' (YMRP), ''Final Report'' (NRC 2003 [163274]), and the NRC final rule 10 CFR Part 63 (NRC 2002 [156605]). This introductory section provides an overview of the TSPA-LA, the projected TSPA-LA documentation structure, and the goals of the document. It also provides a brief discussion of the regulatory framework, the approach to risk management of the development and analysis of the model, and the overall organization of the document. The section closes with some important conventions that are used in this document.

  9. Total System Performance Assessment-License Application Methods and Approach

    SciTech Connect (OSTI)

    J. McNeish

    2002-09-13

    ''Total System Performance Assessment-License Application (TSPA-LA) Methods and Approach'' provides the top-level method and approach for conducting the TSPA-LA model development and analyses. The method and approach is responsive to the criteria set forth in Total System Performance Assessment Integration (TSPAI) Key Technical Issue (KTI) agreements, the ''Yucca Mountain Review Plan'' (CNWRA 2002 [158449]), and 10 CFR Part 63. This introductory section provides an overview of the TSPA-LA, the projected TSPA-LA documentation structure, and the goals of the document. It also provides a brief discussion of the regulatory framework, the approach to risk management of the development and analysis of the model, and the overall organization of the document. The section closes with some important conventions that are utilized in this document.

  10. Arkansas Natural Gas Total Consumption (Million Cubic Feet)

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

    Total Consumption (Million Cubic Feet) Arkansas Natural Gas Total Consumption (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 260,113 266,485 252,853 2000's 251,329 227,943 242,325 246,916 215,124 213,609 233,868 226,439 234,901 244,193 2010's 271,515 284,076 296,132 282,120 268,453 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016 Next

  11. Colorado Natural Gas Total Consumption (Million Cubic Feet)

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

    Total Consumption (Million Cubic Feet) Colorado Natural Gas Total Consumption (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 314,486 330,259 333,085 2000's 367,920 463,738 459,397 436,253 440,378 470,321 450,832 504,775 504,783 523,726 2010's 501,350 466,680 443,750 467,798 480,747 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016 Next

  12. Delaware Natural Gas Total Consumption (Million Cubic Feet)

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

    Total Consumption (Million Cubic Feet) Delaware Natural Gas Total Consumption (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 46,511 40,809 56,013 2000's 48,387 50,113 52,216 46,177 48,057 46,904 43,190 48,155 48,162 50,148 2010's 54,825 79,715 101,676 95,978 100,776 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016 Next Release Date:

  13. District of Columbia Natural Gas Total Consumption (Million Cubic Feet)

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

    Total Consumption (Million Cubic Feet) District of Columbia Natural Gas Total Consumption (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 34,105 30,409 32,281 2000's 33,468 29,802 32,898 32,814 32,227 32,085 29,049 32,966 31,880 33,177 2010's 33,251 32,862 28,561 32,743 34,057 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016 Next Release

  14. East Region Natural Gas Total Underground Storage Capacity (Million Cubic

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

    Feet) Total Underground Storage Capacity (Million Cubic Feet) East Region Natural Gas Total Underground Storage Capacity (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2014 2,200,169 2,200,169 2,200,169 2,200,169 2,200,169 2,200,169 2,200,169 2,200,169 2,200,169 2,200,169 2,200,169 2,200,169 2015 2,197,282 2,197,282 2,197,282 2,197,282 2,195,132 2,195,132 2,195,132 2,195,132 2,195,132 2,195,132 2,195,132 2,195,132 2016 2,195,132 2,195,132 - = No Data Reported; -- =

  15. Everett, MA Liquefied Natural Gas Total Imports (Million Cubic Feet)

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

    Total Imports (Million Cubic Feet) Everett, MA Liquefied Natural Gas Total Imports (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2013 2,583 2,728 2014 5,470 3,783 2,334 2,806 2,175 3,311 1,567 2,871 2,505 2,003 2015 7,729 7,623 5,521 1,673 2,557 7,133 8,237 2,563 2,653 1,541 2,452 2016 10,633 8,593 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016 Next Release Date:

  16. Florida Natural Gas Total Consumption (Million Cubic Feet)

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

    Total Consumption (Million Cubic Feet) Florida Natural Gas Total Consumption (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 522,116 503,844 559,366 2000's 541,847 543,143 689,337 689,986 734,178 778,209 891,611 917,244 942,699 1,055,340 2010's 1,158,452 1,217,689 1,328,463 1,225,676 1,231,957 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016

  17. Georgia Natural Gas Total Consumption (Million Cubic Feet)

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

    Total Consumption (Million Cubic Feet) Georgia Natural Gas Total Consumption (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 371,376 368,579 337,576 2000's 413,845 351,109 383,546 379,761 394,986 412,560 420,469 441,107 425,043 462,799 2010's 530,030 522,897 615,771 625,283 652,230 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016 Next Release

  18. Hawaii Natural Gas Total Consumption (Million Cubic Feet)

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

    Total Consumption (Million Cubic Feet) Hawaii Natural Gas Total Consumption (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 2,894 2,654 3,115 2000's 2,841 2,818 2,734 2,732 2,774 2,795 2,783 2,850 2,702 2,607 2010's 2,627 2,619 2,689 2,855 2,928 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016 Next Release Date: 5/31/2016 Referring Pages:

  19. Illinois Natural Gas Total Consumption (Million Cubic Feet)

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

    Total Consumption (Million Cubic Feet) Illinois Natural Gas Total Consumption (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 1,077,139 957,254 1,004,281 2000's 1,030,604 951,616 1,049,878 998,486 953,207 969,642 893,997 965,591 1,000,501 956,068 2010's 966,678 986,867 940,367 1,056,826 1,092,999 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date:

  20. Indiana Natural Gas Total Consumption (Million Cubic Feet)

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

    Total Consumption (Million Cubic Feet) Indiana Natural Gas Total Consumption (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 556,624 521,748 556,932 2000's 570,558 501,711 539,034 527,037 526,701 531,111 496,303 535,796 551,424 506,944 2010's 573,866 630,669 649,921 672,751 710,838 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016 Next Release