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 macros.xls") Waste Stream a Volume (cy) Mass (g) 2 Radiological Profile 3 Nuclide Activity (Ci) 4 Total % of Total U-238 U-234 U-235 Th-228 Th-230 Th-232 Ra-226 Ra-228 Rn-222 5 Activity if > 1% Raffinate Pits Work Zone (Ci) Raffinate processed through CSS Plant 1 159990 1.49E+11 Raffinate 6.12E+01 6.12E+01

  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. Total Estimated Contract Cost: Performance Period Total Fee Paid

    Office of Environmental Management (EM)

    Performance Period Total Fee Paid FY2008 $134,832 FY2009 $142,578 FY2010 $299,878 FY2011 $169,878 Cumulative Fee Paid $747,166 Contract Period: September 2007 - October 2012 $31,885,815 C/P/E Environmental Services, LLC DE-AM09-05SR22405/DE-AT30-07CC60011/SL14 Contractor: Contract Number: Contract Type: Cost Plus Award Fee $357,223 $597,797 $894,699 EM Contractor Fee Site: Stanford Linear Accelerator Center (SLAC) Contract Name: SLAC Environmental Remediation December 2012 $1,516,646 Fee

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

    Office of Environmental Management (EM)

    Measure Unit Lifecycle Total Estimate Pre-2016 Lifecycle Values 2016 Target 2017 Target Pu packaged for long-term disposition Number of Containers 5,089 5,089 5,089 5,089 eU ...

  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. 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 ...

  10. 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.``

  11. 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.

  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

    Gasoline and Diesel Fuel Update (EIA)

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

  14. Total

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

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

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

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

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

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

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

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

  17. 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

  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

    .. 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

  2. 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

  3. 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

  4. 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

  5. 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

  6. 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

  7. 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 999........................................... 23.8 2.7 1.4 2.2 2.8 5.5 5.1 3.0 1.1 1,000 to 1,499..................................... 20.8 2.3 1.4 2.4 2.5 3.5 3.5 3.6 1.6 1,500 to 1,999..................................... 15.4 1.8 1.4 2.2 2.0 2.4 2.4 2.1 1.2 2,000 to 2,499..................................... 12.2 1.4 0.9

  8. 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.''

  9. Superconvergence of the derivative patch recovery technique and a posteriorii error estimation

    SciTech Connect (OSTI)

    Zhang, Z.; Zhu, J.Z.

    1995-12-31

    The derivative patch recovery technique developed by Zienkiewicz and Zhu for the finite element method is analyzed. It is shown that, for one dimensional problems and two dimensional problems using tensor product elements, the patch recovery technique yields superconvergence recovery for the derivatives. Consequently, the error estimator based on the recovered derivative is asymptotically exact.

  10. 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)

  11. 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

  12. 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

  13. 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

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

    SciTech Connect (OSTI)

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

    1991-01-01

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

  15. 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

  16. 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%.

  17. 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.

  18. 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...

  19. 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.

  20. 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

  1. Total Imports

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

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

  2. Country Total

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

    Country Total Percent of U.S. total Canada 61,078 1% China 3,323,297 57% Germany 154,800 3% Japan 12,593 0% India 47,192 1% South Korea 251,105 4% All Others 2,008,612 34% Total 5,858,677 100% Table 7 . Photovoltaic module import shipments by country, 2014 (peak kilowatts) Note: All Others includes Cambodia, Czech Republic, Hong Kong, Malaysia, Mexico, Netherlands, Philippines, Singapore, Taiwan and Turkey Source: U.S. Energy Information Administration, Form EIA-63B, 'Annual Photovoltaic

  3. State Total

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

    State Total Percent of U.S. total Alabama 482 0.0% Alaska 81 0.0% Arizona 194,476 3.3% Arkansas 336 0.0% California 3,163,120 53.0% Colorado 47,240 0.8% Connecticut 50,745 0.9% Delaware 6,600 0.1% District of Columbia 751 0.0% Florida 18,593 0.3% Georgia 47,660 0.8% Hawaii 78,329 1.3% Illinois 5,795 0.1% Indiana 37,016 0.6% Iowa 14,281 0.2% Kansas 1,809 0.0% Kentucky 520 0.0% Louisiana 12,147 0.2% Maine 1,296 0.0% Maryland 63,077 1.1% Massachusetts 157,415 2.6% Michigan 4,210 0.1% Minnesota

  4. Summary Max Total Units

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

    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

  5. Notices Total Estimated Number of Annual

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

    ... 27 Dumont Street, Thursday, September 26, 2013, 5-8 p.m. Requests to speak at one or more public scoping meeting(s) should be received at the address for Brian Mills indicated ...

  6. 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...

  7. 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...

  8. Estimation of benchmark dose as the threshold levels of urinary cadmium, based on excretion of total protein, {beta} {sub 2}-microglobulin, and N-acetyl-{beta}-D-glucosaminidase in cadmium nonpolluted regions in Japan

    SciTech Connect (OSTI)

    Kobayashi, Etsuko . E-mail: ekoba@faculty.chiba-u.jp; Suwazono, Yasushi; Uetani, Mirei; Inaba, Takeya; Oishi, Mitsuhiro; Kido, Teruhiko; Nishijo, Muneko; Nakagawa, Hideaki; Nogawa, Koji

    2006-07-15

    Previously, we investigated the association between urinary cadmium (Cd) concentration and indicators of renal dysfunction, including total protein, {beta} {sub 2}-microglobulin ({beta} {sub 2}-MG), and N-acetyl-{beta}-D-glucosaminidase (NAG). In 2778 inhabitants {>=}50 years of age (1114 men, 1664 women) in three different Cd nonpolluted areas in Japan, we showed that a dose-response relationship existed between renal effects and Cd exposure in the general environment without any known Cd pollution. However, we could not estimate the threshold levels of urinary Cd at that time. In the present study, we estimated the threshold levels of urinary Cd as the benchmark dose low (BMDL) using the benchmark dose (BMD) approach. Urinary Cd excretion was divided into 10 categories, and an abnormality rate was calculated for each. Cut-off values for urinary substances were defined as corresponding to the 84% and 95% upper limit values of the target population who have not smoked. Then we calculated the BMD and BMDL using a log-logistic model. The values of BMD and BMDL for all urinary substances could be calculated. The BMDL for the 84% cut-off value of {beta} {sub 2}-MG, setting an abnormal value at 5%, was 2.4 {mu}g/g creatinine (cr) in men and 3.3 {mu}g/g cr in women. In conclusion, the present study demonstrated that the threshold level of urinary Cd could be estimated in people living in the general environment without any known Cd-pollution in Japan, and the value was inferred to be almost the same as that in Belgium, Sweden, and China.

  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

    Gasoline and Diesel Fuel Update (EIA)

    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 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...

  14. ,"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...

  15. ,"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"...

  16. 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...

  17. ,"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...

  18. ,"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...

  19. 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...

  20. 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*...

  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. U.S. Total Exports

    Gasoline and Diesel Fuel Update (EIA)

    Total to Chile Sabine Pass, LA Total to China Kenai, AK Sabine Pass, LA Total to Egypt ... Sabine Pass, LA Total to Russia Total to South Korea Freeport, TX Sabine Pass, LA Total ...

  3. 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...

  4. Site Performance Measure Unit Lifecycle Total Estimate Pre-2016...

    Office of Environmental Management (EM)

    Number of Release Sites 443 443 443 443 Brookhaven National Laboratory Nuclear Facility Completions Number of Facilities 1 1 2 2 Brookhaven National Laboratory Radioactive Facility ...

  5. 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

  6. 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. ...

  7. 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

  8. 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 $9,310,000 FY2017 $24,849,000 FY2018 $99,100,000 FY2019 $129,700,000 Cumulative Fee $240,324,540 $595,298,540 $12,259,719 $35,789,418 $38,554,240 $41,785,209 $16,698,762 $37,117,867 Maximum Fee $595,298,540 Fee Available $102,622,325 $10,921,302,346 Completion Contract:

  9. 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 EM Contractor Fee June 2015 Site: Office of River Protection, Richland, WA Contract Name: Hanford 222-S Laboratory Analysis and Testing Services Contractor: Wastren Advantage, Inc Contract Number: DE-EM0003722 Contract Type: Hybrid Contract with Award Fee Fee Available $44,562,457 Base Contract Period: November 21, 2016 to September 20,

  10. 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...

  11. 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...

  12. 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,

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

    Office of Scientific and Technical Information (OSTI)

    Resource Type: Conference Resource Relation: Conference: Working Party on Evaluation Cooperation ; 2013-05-22 - 2013-05-24 ; Paris, France Research Org: Los Alamos National ...

  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 Atmospheric Carbon, Aerosols 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. Independent Cost Estimate (ICE)

    Broader source: Energy.gov [DOE]

    Independent Cost Estimate (ICE). On August 8-12, the Office of Project Management Oversight and Assessments (PM) will conduct an ICE on the NNSA Albuquerque Complex Project (NACP) at Albuquerque, NM. This estimate will support the Critical Decision (CD) for establishing the performance baseline and approval to start construction (CD-2/3). This project is at CD-1, with a total project cost range of $183M to $251M.

  18. TOTAL WORKFORCE Males

    National Nuclear Security Administration (NNSA)

    76 Females Male Female Male Female Male Female Male Female Male Female 27 24 86 134 65 24 192 171 1189 423 PAY PLAN SES 96 EX 4 EJ/EK 60 EN 05 39 EN 04 159 EN 03 21 EN 00 8 NN (Engineering) 398 NQ (Prof/Tech/Admin) 1165 NU (Tech/Admin Support) 54 NV (Nuc Mat Courier) 325 GS 15 3 GS 14 1 GS 13 1 GS 10 1 Total includes 2318 permanent and 17 temporary employees. DIVERSITY 2335 1559 66.8% American Indian Alaska Native African American Asian American Pacific Islander Hispanic White 33.2% National

  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. U.S. Total Exports

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

    Barbados Total To Brazil Freeport, TX Sabine Pass, LA Total to Canada Eastport, ID Calais, ME Detroit, MI Marysville, MI Port Huron, MI Crosby, ND Portal, ND Sault St. Marie, MI St. Clair, MI Noyes, MN Warroad, MN Babb, MT Havre, MT Port of Morgan, MT Sherwood, ND Pittsburg, NH Buffalo, NY Grand Island, NY Massena, NY Niagara Falls, NY Waddington, NY Sumas, WA Sweetgrass, MT Total to Chile Sabine Pass, LA Total to China Kenai, AK Sabine Pass, LA Total to Egypt Freeport, TX Total to India

  1. 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...

  2. 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.

  3. 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

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

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

  5. 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

  6. 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

  7. 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

  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 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

  9. 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

  10. 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

  11. 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

  12. 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

  13. 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

  14. 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 37.8 3.4 2.2 7.0 3.1 With a Heat Pump....................................... 12.3 9.7 0.6 0.5 1.0 0.6 Window/Wall Units.......................................... 28.9 14.9 2.3 3.5 6.0 2.1 1 Unit........................................................... 14.5 6.6 1.0 1.6 4.2 1.2 2

  15. 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

  16. 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

  17. 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

  18. 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

  19. 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

  20. 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

  1. 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

  2. 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

  3. 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 Cooling Equipment........................................... 91.4 23.4 15.9 7.5 Have Equipment But Do Not Use it.......................... 1.9 Q Q Q Air-Conditioning Equipment 1, 2 Central System........................................................ 65.9 17.3 11.3 6.0 Without a Heat

  4. 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

  5. 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

  6. 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

  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 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

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

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

    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 Cooling Equipment............................................. 91.4 23.4 15.9 7.5 Have Equipment But Do Not Use it............................ 1.9 Q Q Q Type of Air-Conditioning Equipment 1, 2 Central System........................................................ 65.9 17.3 11.3 6.0 Without a Heat

  9. 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

  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 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

  11. 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

  12. 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

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

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

    20.6 25.6 40.7 24.2 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 Air-Conditioning Equipment 1, 2 Central System........................................................... 65.9 6.0 17.3 32.1 10.5

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

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

    0.7 21.7 6.9 12.1 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 Air-Conditioning Equipment 1, 2 Central System........................................................... 65.9 32.1 17.6 5.2 9.3 Without a

  15. 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

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

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

    7.1 19.0 22.7 22.3 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 Air-Conditioning Equipment 1, 2 Central System........................................................... 65.9 25.8 10.9 16.6 12.5

  17. 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

  18. 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

  19. 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

  20. 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

  1. 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

  2. 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.....................................................

  3. 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

  4. 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

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

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

    ... Basements Basement in Single-Family Homes and Apartments in 2-4 Unit Buildings ... Attics Attic in Single-Family Homes and Apartments in 2-4 Unit Buildings ...

  6. Total

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

    ... Climate region 3 Very coldCold 31,898 30,469 28,057 28,228 21,019 30,542 25,067 Mixed-humid 27,873 26,716 24,044 26,365 21,026 27,096 22,812 Mixed-dryHot-dry 12,037 10,484 7,628 ...

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

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

    Air-Conditioning Equipment 1, 2 Central System......Central Air-Conditioning...... 65.9 1.1 6.4 6.4 ...

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

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

    Income Relative to Poverty Line Below 100 Percent......1.3 1.2 0.8 0.4 1. Below 150 percent of poverty line or 60 percent of median State ...

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

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

    ... Below Poverty Line Eligible for Federal Assistance 1 80,000 or More 60,000 to 79,999 ... Below Poverty Line Eligible for Federal Assistance 1 80,000 or More 60,000 to 79,999 ...

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

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

    ... Table HC7.4 Space Heating Characteristics by Household Income, 2005 Below Poverty Line ... Below Poverty Line Eligible for Federal Assistance 1 80,000 or More Space Heating ...

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

    Gasoline and Diesel Fuel Update (EIA)

    ... Table HC7.7 Air-Conditioning Usage Indicators by Household Income, 2005 Below Poverty Line ... Table HC7.7 Air-Conditioning Usage Indicators by Household Income, 2005 Below Poverty Line ...

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

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

    ... Living Space Characteristics Below Poverty Line Eligible for Federal Assistance 1 Million ... Living Space Characteristics Below Poverty Line Eligible for Federal Assistance 1 Million ...

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

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

    ... Table HC7.12 Home Electronics Usage Indicators by Household Income, 2005 Below Poverty ... Table HC7.12 Home Electronics Usage Indicators by Household Income, 2005 Below Poverty ...

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

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

    ... Table HC7.10 Home Appliances Usage Indicators by Household Income, 2005 Below Poverty Line ... Below Poverty Line Eligible for Federal Assistance 1 40,000 to 59,999 60,000 to 79,999 ...

  15. Total

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

    1,001 to 5,000 2,777 8,041 10,232 2.9 786 56 5,001 to 10,000 1,229 8,900 9,225 7.2 965 62 10,001 to 25,000 884 14,105 14,189 16.0 994 65 25,001 to 50,000 332 11,917 11,327 35.9 1,052 72 50,001 to 100,000 199 13,918 12,345 69.9 1,127 80 100,001 to 200,000 90 12,415 11,310 137.9 1,098 89 200,001 to 500,000 38 10,724 10,356 284.2 1,035 99 Over 500,000 8 7,074 9,196 885.0 769 117 Principal building activity Education 389 12,239 10,885 31.5 1,124 53 Food sales 177 1,252 1,172 7.1 1,067 121 Food

  16. Total

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

    1,001 to 5,000 2,777 8,041 10,232 2.9 786 56 5,001 to 10,000 1,229 8,900 9,225 7.2 965 62 10,001 to 25,000 884 14,105 14,189 16.0 994 65 25,001 to 50,000 332 11,917 11,327 35.9 1,052 72 50,001 to 100,000 199 13,918 12,345 69.9 1,127 80 100,001 to 200,000 90 12,415 11,310 137.9 1,098 89 200,001 to 500,000 38 10,724 10,356 284.2 1,035 99 Over 500,000 8 7,074 9,196 885.0 769 117 Principal building activity Education 389 12,239 10,885 31.5 1,124 53 Food sales 177 1,252 1,172 7.1 1,067 121 Food

  17. Total

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

    1,001 to 5,000 2,777 8,041 10,232 2.9 786 56 5,001 to 10,000 1,229 8,900 9,225 7.2 965 62 10,001 to 25,000 884 14,105 14,189 16.0 994 65 25,001 to 50,000 332 11,917 11,327 35.9 1,052 72 50,001 to 100,000 199 13,918 12,345 69.9 1,127 80 100,001 to 200,000 90 12,415 11,310 137.9 1,098 89 200,001 to 500,000 38 10,724 10,356 284.2 1,035 99 Over 500,000 8 7,074 9,196 885.0 769 117 Principal building activity Education 389 12,239 10,885 31.5 1,124 53 Food sales 177 1,252 1,172 7.1 1,067 121 Food

  18. Total

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

    Median square feet per building (thousand) Median square feet per worker Median operating hours per week Median age of buildings (years) All buildings 5,557 87,093 88,182 5.0 1,029 50 32 Building floorspace (square feet) 1,001 to 5,000 2,777 8,041 10,232 2.8 821 49 37 5,001 to 10,000 1,229 8,900 9,225 7.0 1,167 50 31 10,001 to 25,000 884 14,105 14,189 15.0 1,444 56 32 25,001 to 50,000 332 11,917 11,327 35.0 1,461 60 29 50,001 to 100,000 199 13,918 12,345 67.0 1,442 60 26 100,001 to 200,000 90

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

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

    ... Housing Units (millions) UrbanRural Location (as Self-Reported) Living Space ... Housing Units (millions) UrbanRural Location (as Self-Reported) Living Space ...

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

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

    ... Housing Units (millions) UrbanRural Location (as Self-Reported) City Town Suburbs Rural ... Housing Units (millions) UrbanRural Location (as Self-Reported) City Town Suburbs Rural ...

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

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

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

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

    Gasoline and Diesel Fuel Update (EIA)

    Table HC4.2 Living Space Characteristics by Renter-Occupied Housing Units, 2005 2 to 4 Units 5 or More Units Mobile Homes Energy Information Administration 2005 Residential Energy ...

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

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

    ... Per Household Member Average Square Feet Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Table HC1.2.2 ...

  4. 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 ...

  5. 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......

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

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

    ... Average Square Feet per Apartment in a -- Apartments (millions) Major Outside Wall Construction Siding (Aluminum, Vinyl, Steel)...... 35.3 3.5 1,286 1,090 325 852 786 461 ...

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

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

    ... Type of Renter-Occupied Housing Unit Housing Units (millions) Single-Family Units ... At Home Behavior Home Used for Business Yes......

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

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

    ... Type of Owner-Occupied Housing Unit U.S. Housing Units (millions) Single-Family Units ... At Home Behavior Home Used for Business Yes......

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

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

    ... Housing Characteristics Tables Single-Family Units Detached Type of Housing Unit Table ... At Home Behavior Home Used for Business Yes......

  10. Table A32. Total Consumption of Offsite-Produced Energy for...

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

    Consumption of Offsite-Produced Energy for Heat, Power, and" " Electricity Generation by ... The derived estimates presented" "in this table represent the consumption of energy ...

  11. 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.

  12. 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

  13. 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...

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

    DOE Patents [OSTI]

    Caldwell, John T.; Kunz, Walter E.; Cates, Michael R.; Franks, Larry A.

    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.

  15. 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.

  16. 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.

  17. 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...

  18. 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 total concentration (mass/vol) of ice and liquid water particles in a cloud; this includes condensed water content (CWC). Categories Cloud Properties Instruments The above measurement is considered scientifically relevant for the following instruments. Refer to the datastream (netcdf) file headers of each instrument for a

  19. 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...

  20. 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.

  1. 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.

  2. 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

  3. Million Cu. Feet Percent of National Total

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

    0 New Hampshire - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle ...

  4. Total Number of Operable Refineries

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

    Data Series: Total Number of Operable Refineries Number of Operating Refineries Number of Idle Refineries Atmospheric Crude Oil Distillation Operable Capacity (B/CD) Atmospheric Crude Oil Distillation Operating Capacity (B/CD) Atmospheric Crude Oil Distillation Idle Capacity (B/CD) Atmospheric Crude Oil Distillation Operable Capacity (B/SD) Atmospheric Crude Oil Distillation Operating Capacity (B/SD) Atmospheric Crude Oil Distillation Idle Capacity (B/SD) Vacuum Distillation Downstream Charge

  5. Design Storm for Total Retention.pdf

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

    Title: Design Storm for "Total Retention" under Individual Permit, Poster, Individual ... International. Environmental Programs Design Storm for "Total Retention" under ...

  6. 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

  7. U.S. Total Imports

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

    St. Clair, MI International Falls, MN Noyes, MN Warroad, MN Babb, MT Havre, MT Port of Del Bonita, MT Port of Morgan, MT Sweetgrass, MT Whitlash, MT Portal, ND Sherwood, ND Pittsburg, NH Champlain, NY Grand Island, NY Massena, NY Niagara Falls, NY Waddington, NY Sumas, WA Highgate Springs, VT North Troy, VT U.S. Pipeline Total from Mexico Ogilby, CA Otay Mesa, CA Alamo, TX El Paso, TX Galvan Ranch, TX Hidalgo, TX McAllen, TX Penitas, TX LNG Imports from Algeria Cove Point, MD Everett, MA Lake

  8. Total Imports of Residual Fuel

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

    Jan-16 Feb-16 Mar-16 Apr-16 May-16 Jun-16 View History U.S. Total 9,010 5,030 8,596 6,340 4,707 8,092 1936-2016 PAD District 1 3,127 2,664 2,694 1,250 1,327 2,980 1981-2016 Connecticut 1995-2015 Delaware 280 1995-2016 Florida 858 649 800 200 531 499 1995-2016 Georgia 210 262 149 106 1995-2016 Maine 1995-2015 Maryland 84 1995-2016 Massachusetts 1995-2015 New Hampshire 1995-2015 New Jersey 1,283 843 1,073 734 355 1,984 1995-2016 New York 234 824 210 196 175 1995-2016 North Carolina 1995-2011

  9. Total quality management implementation guidelines

    SciTech Connect (OSTI)

    Not Available

    1993-12-01

    These Guidelines were designed by the Energy Quality Council to help managers and supervisors in the Department of Energy Complex bring Total Quality Management to their organizations. Because the Department is composed of a rich mixture of diverse organizations, each with its own distinctive culture and quality history, these Guidelines are intended to be adapted by users to meet the particular needs of their organizations. For example, for organizations that are well along on their quality journeys and may already have achieved quality results, these Guidelines will provide a consistent methodology and terminology reference to foster their alignment with the overall Energy quality initiative. For organizations that are just beginning their quality journeys, these Guidelines will serve as a startup manual on quality principles applied in the Energy context.

  10. Total Imports of Residual Fuel

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

    2010 2011 2012 2013 2014 2015 View History U.S. Total 133,646 119,888 93,672 82,173 63,294 68,265 1936-2015 PAD District 1 88,999 79,188 59,594 33,566 30,944 33,789 1981-2015 Connecticut 220 129 1995-2015 Delaware 748 1,704 510 1,604 2,479 1995-2015 Florida 15,713 11,654 10,589 8,331 5,055 7,013 1995-2015 Georgia 5,648 7,668 6,370 4,038 2,037 1,629 1995-2015 Maine 1,304 651 419 75 317 135 1995-2015 Maryland 3,638 1,779 1,238 433 938 539 1995-2015 Massachusetts 123 50 78 542 88 1995-2015 New

  11. 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

  12. Total quality management program planning

    SciTech Connect (OSTI)

    Thornton, P.T.; Spence, K.

    1994-05-01

    As government funding grows scarce, competition between the national laboratories is increasing dramatically. In this era of tougher competition, there is no for resistance to change. There must instead be a uniform commitment to improving the overall quality of our products (research and technology) and an increased focus on our customers` needs. There has been an ongoing effort to bring the principles of total quality management (TQM) to all Energy Systems employees to help them better prepare for future changes while responding to the pressures on federal budgets. The need exists for instituting a vigorous program of education and training to an understanding of the techniques needed to improve and initiate a change in organizational culture. The TQM facilitator is responsible for educating the work force on the benefits of self-managed work teams, designing a program of instruction for implementation, and thus getting TQM off the ground at the worker and first-line supervisory levels so that the benefits can flow back up. This program plan presents a conceptual model for TQM in the form of a hot air balloon. In this model, there are numerous factors which can individually and collectively impede the progress of TQM within the division and the Laboratory. When these factors are addressed and corrected, the benefits of TQM become more visible. As this occurs, it is hoped that workers and management alike will grasp the ``total quality`` concept as an acceptable agent for change and continual improvement. TQM can then rise to the occasion and take its rightful place as an integral and valid step in the Laboratory`s formula for survival.

  13. 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.

  14. 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.

  15. 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...

  16. 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...

  17. 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...

  18. 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...

  19. 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...

  20. ,"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)" ...

  1. ,"Total Crude Oil and Petroleum Products Exports"

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

    Data for" ,"Data 1","Total Crude Oil and Petroleum Products ... "Back to Contents","Data 1: Total Crude Oil and Petroleum Products Exports" ...

  2. ,"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)" ...

  3. ,"North Dakota Natural Gas Total Consumption (MMcf)"

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

    Data for" ,"Data 1","North Dakota Natural Gas Total Consumption ... 9:10:34 AM" "Back to Contents","Data 1: North Dakota Natural Gas Total Consumption ...

  4. ,"North Carolina Natural Gas Total Consumption (MMcf)"

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

    Data for" ,"Data 1","North Carolina Natural Gas Total Consumption ... 9:10:33 AM" "Back to Contents","Data 1: North Carolina Natural Gas Total Consumption ...

  5. 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.

  6. 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.

  7. Reference air kerma and kerma-area product as estimators of peak skin dose for fluoroscopically guided interventions

    SciTech Connect (OSTI)

    Kwon, Deukwoo; Little, Mark P.; Miller, Donald L.

    2011-07-15

    Purpose: To determine more accurate regression formulas for estimating peak skin dose (PSD) from reference air kerma (RAK) or kerma-area product (KAP). Methods: After grouping of the data from 21 procedures into 13 clinically similar groups, assessments were made of optimal clustering using the Bayesian information criterion to obtain the optimal linear regressions of (log-transformed) PSD vs RAK, PSD vs KAP, and PSD vs RAK and KAP. Results: Three clusters of clinical groups were optimal in regression of PSD vs RAK, seven clusters of clinical groups were optimal in regression of PSD vs KAP, and six clusters of clinical groups were optimal in regression of PSD vs RAK and KAP. Prediction of PSD using both RAK and KAP is significantly better than prediction of PSD with either RAK or KAP alone. The regression of PSD vs RAK provided better predictions of PSD than the regression of PSD vs KAP. The partial-pooling (clustered) method yields smaller mean squared errors compared with the complete-pooling method.Conclusion: PSD distributions for interventional radiology procedures are log-normal. Estimates of PSD derived from RAK and KAP jointly are most accurate, followed closely by estimates derived from RAK alone. Estimates of PSD derived from KAP alone are the least accurate. Using a stochastic search approach, it is possible to cluster together certain dissimilar types of procedures to minimize the total error sum of squares.

  8. 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

  9. " Level: National Data and Regional Totals...

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

    ... by" "petroleum refineries, rather than purchased ... ,,"Total United States" ,"RSE Column ... 324,"Petroleum and Coal ...

  10. 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.

  11. 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

  12. 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.

  13. 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...

  14. 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.

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

    Energy Savers [EERE]

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

  16. 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

  17. 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.

  18. 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.

  19. 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.

  20. 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...

  1. 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.

  2. 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

  3. 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

  4. Million Cu. Feet Percent of National Total

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

    0 Indiana - 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 S16. Summary statistics for natural gas - Indiana, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 620 914 819 R 921 895 Production (million cubic feet) Gross Withdrawals From Gas Wells 6,802 9,075

  5. 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

  6. Million Cu. Feet Percent of National Total

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

    6 Nebraska - 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 S29. Summary statistics for natural gas - Nebraska, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 276 322 270 R 357 310 Production (million cubic feet) Gross Withdrawals From Gas Wells 2,092 1,854

  7. 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

  8. 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.

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

    Office of Legacy Management (LM)

  10. 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.

  11. 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.

  12. 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

  13. 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.

  14. 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.

  15. 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

  16. Million Cu. Feet Percent of National Total

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

    6 Arkansas - 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 S4. Summary statistics for natural gas - Arkansas, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 7,397 8,388 8,538 R 9,843 10,150 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 California - 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 S5. Summary statistics for natural gas - California, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 1,580 1,308 1,423 R 1,335 1,118 Production (million cubic feet) Gross Withdrawals From Gas

  18. 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

  19. 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

  20. Million Cu. Feet Percent of National Total

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

    0 Georgia - 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 S11. Summary statistics for natural gas - Georgia, 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

  1. 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

  2. Million Cu. Feet Percent of National Total

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

    8 Illinois - 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 S15. Summary statistics for natural gas - Illinois, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 50 40 40 R 34 36 Production (million cubic feet) Gross Withdrawals From Gas Wells E 1,697 2,114

  3. Million Cu. Feet Percent of National Total

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

    2 Iowa - 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 S17. Summary statistics for natural gas - Iowa, 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 0

  4. 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

  5. Million Cu. Feet Percent of National Total

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

    6 Kentucky - 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 S19. Summary statistics for natural gas - Kentucky, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 17,670 14,632 17,936 R 19,494 19,256 Production (million cubic feet) Gross Withdrawals From Gas

  6. 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

  7. Million Cu. Feet Percent of National Total

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

    0 Maine - 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 S21. Summary statistics for natural gas - Maine, 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

  8. Million Cu. Feet Percent of National Total

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

    6 Michigan - 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 S24. Summary statistics for natural gas - Michigan, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 10,100 11,100 10,900 R 10,550 10,500 Production (million cubic feet) Gross Withdrawals From Gas

  9. Million Cu. Feet Percent of National Total

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

    0 Mississippi - 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 S26. Summary statistics for natural gas - Mississippi, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 1,979 5,732 1,669 R 1,967 1,645 Production (million cubic feet) Gross Withdrawals From Gas

  10. Million Cu. Feet Percent of National Total

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

    2 Missouri - 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 S27. Summary statistics for natural gas - Missouri, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 0 53 100 R 26 28 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 R 8 8 From

  11. Million Cu. Feet Percent of National Total

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

    4 Montana - 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 S28. Summary statistics for natural gas - Montana, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 6,059 6,477 6,240 5,754 5,754 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

    8 Nevada - 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 S30. Summary statistics for natural gas - Nevada, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 0 0 0 R 4 4 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 3 From Oil Wells

  13. 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

  14. Million Cu. Feet Percent of National Total

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

    6 New York - 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 S34. Summary statistics for natural gas - New York, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 6,736 6,157 7,176 R 6,902 7,119 Production (million cubic feet) Gross Withdrawals From Gas Wells

  15. Million Cu. Feet Percent of National Total

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

    2 Ohio - 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 S37. Summary statistics for natural gas - Ohio, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 34,931 46,717 35,104 R 32,664 32,967 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

    4 Oklahoma - 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 S38. Summary statistics for natural gas - Oklahoma, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 44,000 41,238 40,000 39,776 40,070 Production (million cubic feet) Gross Withdrawals From Gas

  17. 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

  18. Million Cu. Feet Percent of National Total

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

    8 Pennsylvania - 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 S40. Summary statistics for natural gas - Pennsylvania, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 44,500 54,347 55,136 R 53,762 70,400 Production (million cubic feet) Gross Withdrawals

  19. Million Cu. Feet Percent of National Total

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

    6 Tennessee - 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 S44. Summary statistics for natural gas - Tennessee, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 230 210 212 R 1,089 1,024 Production (million cubic feet) Gross Withdrawals From Gas Wells 5,144

  20. Million Cu. Feet Percent of National Total

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

    8 Texas - 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 S45. Summary statistics for natural gas - Texas, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 95,014 100,966 96,617 97,618 98,279 Production (million cubic feet) Gross Withdrawals From Gas Wells

  1. Million Cu. Feet Percent of National Total

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

    0 Utah - 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 S46. Summary statistics for natural gas - Utah, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 6,075 6,469 6,900 R 7,030 7,275 Production (million cubic feet) Gross Withdrawals From Gas Wells 328,135

  2. Million Cu. Feet Percent of National Total

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

    4 Virginia - 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 S48. Summary statistics for natural gas - Virginia, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 7,470 7,903 7,843 R 7,956 7,961 Production (million cubic feet) Gross Withdrawals From Gas Wells

  3. Million Cu. Feet Percent of National Total

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

    8 West Virginia - 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 S50. Summary statistics for natural gas - West Virginia, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 52,498 56,813 50,700 R 54,920 60,000 Production (million cubic feet) Gross Withdrawals

  4. 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.

  5. 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.

  6. Total-system performance assessment for Yucca Mountain - SNL second iteration (TSPA-1993); Volume 2

    SciTech Connect (OSTI)

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

    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.

  7. 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.

  8. 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.

  9. Budget estimates. Fiscal year 1998

    SciTech Connect (OSTI)

    1997-02-01

    The U.S. Congress has determined that the safe use of nuclear materials for peaceful purposes is a legitimate and important national goal. It has entrusted the Nuclear Regulatory Commission (NRC) with the primary Federal responsibility for achieving that goal. The NRC`s mission, therefore, is to regulate the Nation`s civilian use of byproduct, source, and special nuclear materials to ensure adequate protection of public health and safety, to promote the common defense and security, and to protect the environment. The NRC`s FY 1998 budget requests new budget authority of $481,300,000 to be funded by two appropriations - one is the NRC`s Salaraies and Expenses appropriation for $476,500,000, and the other is NRC`s Office of Inspector General appropriation for $4,800,000. Of the funds appropriated to the NRC`s Salaries and Expenses, $17,000,000, shall be derived from the Nuclear Waste Fund and $2,000,000 shall be derived from general funds. The proposed FY 1998 appropriation legislation would also exempt the $2,000,000 for regulatory reviews and other assistance provided to the Department of Energy from the requirement that the NRC collect 100 percent of its budget from fees. The sums appropriated to the NRC`s Salaries and Expenses and NRC`s Office of Inspector General shall be reduced by the amount of revenues received during FY 1998 from licensing fees, inspection services, and other services and collections, so as to result in a final FY 1998 appropriation for the NRC of an estimated $19,000,000 - the amount appropriated from the Nuclear Waste Fund and from general funds. Revenues derived from enforcement actions shall be deposited to miscellaneous receipts of the Treasury.

  10. 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.

  11. 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

  12. 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.

  13. 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.

  14. 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...

  15. Million Cu. Feet Percent of National Total

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

    Table S22. Summary statistics for natural gas - Maryland, 2010-2014 - continued -- Not applicable. < Percentage is less than 0.05 percent. E Estimated data. R Revised data. W ...

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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...

  2. Million Cu. Feet Percent of National Total

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

    -3,826 Total Supply 854,673 908,380 892,923 R 900,232 828,785 See footnotes at end of ... Gas Annual 165 Table S43. Summary statistics for natural gas - South Dakota, ...

  3. Total Ore Processing Integration and Management

    SciTech Connect (OSTI)

    Leslie Gertsch; Richard Gertsch

    2004-06-30

    This report outlines the technical progress achieved for project DE-FC26-03NT41785 (Total Ore Processing Integration and Management) during the period 01 April through 30 June of 2004.

  4. 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...

  5. 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...

  6. ARM - Measurement - Net broadband total irradiance

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

    govMeasurementsNet broadband total irradiance 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 : Net broadband total irradiance The difference between upwelling and downwelling, covering longwave and shortwave radiation. Categories Radiometric Instruments The above measurement is considered scientifically relevant for the following instruments. Refer to the datastream (netcdf) file headers of each

  7. ARM - Measurement - Shortwave broadband total downwelling irradiance

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

    downwelling irradiance 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 : Shortwave broadband total downwelling irradiance The total diffuse and direct radiant energy that comes from some continuous range of directions, at wavelengths between 0.4 and 4 {mu}m, that is being emitted downwards. Categories Radiometric Instruments The above measurement is considered scientifically relevant for the following

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

    SciTech Connect (OSTI)

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

    1990-05-15

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

  9. 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

  10. Parametric Hazard Function Estimation.

    Energy Science and Technology Software Center (OSTI)

    1999-09-13

    Version 00 Phaze performs statistical inference calculations on a hazard function (also called a failure rate or intensity function) based on reported failure times of components that are repaired and restored to service. Three parametric models are allowed: the exponential, linear, and Weibull hazard models. The inference includes estimation (maximum likelihood estimators and confidence regions) of the parameters and of the hazard function itself, testing of hypotheses such as increasing failure rate, and checking ofmore » the model assumptions.« less

  11. ARM - Measurement - Shortwave spectral total downwelling irradiance

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

    total downwelling irradiance 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 : Shortwave spectral total downwelling irradiance The rate at which radiant energy, at specrally-resolved wavelengths between 0.4 and 4 {mu}m, is being emitted upwards and downwards into a radiation field and transferred across a surface area (real or imaginary) in a hemisphere of directions. Categories Radiometric Instruments

  12. REQUESTS FOR RETIREMENT ESTIMATE

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

    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 _____________________ ______________________ ________________________

  13. 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.

  14. Million Cu. Feet Percent of National Total

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

    R 196 184 Total Supply 2,627 2,619 2,689 R 2,855 2,928 See footnotes at end of table. 0 ... Gas Annual 105 Table S13. Summary statistics for natural gas - Hawaii, 2010-2014 - ...

  15. The Leica TCRA1105 Reflectorless Total Station

    SciTech Connect (OSTI)

    Gaudreault, F.

    2005-09-06

    This poster provides an overview of SLAC's TCRA1105 reflectorless total station for the Alignment Engineering Group. This instrument has shown itself to be very useful for planning new construction and providing quick measurements to difficult to reach or inaccessible surfaces.

  16. 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.

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

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

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

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

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

    2. Total Inputs of Energy for Heat, Power, and Electricity Generation by Employment Size" " Categories and Presence of General Technologies and Cogeneration Technologies, 1994" " (Estimates in Trillion Btu)" ,,,,"Employment Size(a)" ,,,,,,,,"RSE" ,,,,,,,"1000 and","Row" "General/Cogeneration Technologies","Total","Under

  19. Country/Continent Total Percent of U.S. Total Africa/Europe

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

    peak kilowatts Country/Continent Total Percent of U.S. Total Africa/Europe 53,898 29% Asia/Australia 107,460 59% South/Central America 11,692 6% Canada 4,378 2% Mexico 5,556 3% Total 182,984 100% Table 8. Destination of photovoltaic module export shipments, 2014 Source: U.S. Energy Information Administration, Form EIA-63B, 'Annual Photovoltaic Cell/Module Shipments Report.'

  20. Total Natural Gas Gross Withdrawals (Summary)

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

    Pipeline and Distribution Use Price Citygate Price Residential Price Commercial Price Industrial Price Vehicle Fuel Price Electric Power Price Proved Reserves as of 12/31 Reserves Adjustments Reserves Revision Increases Reserves Revision Decreases Reserves Sales Reserves Acquisitions Reserves Extensions Reserves New Field Discoveries New Reservoir Discoveries in Old Fields Estimated Production Number of Producing Gas Wells Gross Withdrawals Gross Withdrawals From Gas Wells Gross Withdrawals From

  1. 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.

  2. State Energy Production Estimates

    Gasoline and Diesel Fuel Update (EIA)

    Production Estimates 1960 Through 2014 2014 Summary Tables U.S. Energy Information Administration | State Energy Data 2014: Production 1 Table P1. Energy Production Estimates in Physical Units, 2014 Alabama 16,377 181,054 9,828 0 Alaska 1,502 345,331 181,175 0 Arizona 8,051 106 56 1,044 Arkansas 94 1,123,678 6,845 0 California 0 252,718 204,269 4,462 Colorado 24,007 1,631,391 95,192 3,133 Connecticut 0 0 0 0 Delaware 0 0 0 0 District of Columbia 0 0 0 0 Florida 0 369 2,227 0 Georgia 0 0 0 2,517

  3. 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.

  4. 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.

  5. Total Crude Oil and Petroleum Products Exports

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

    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 Kerosene and

  6. ARM - Measurement - Shortwave broadband total net irradiance

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

    net irradiance 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 : Shortwave broadband total net irradiance The difference between upwelling and downwelling broadband shortwave radiation. Categories Radiometric 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

  7. ARM - Measurement - Shortwave narrowband total downwelling irradiance

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

    downwelling irradiance 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 : Shortwave narrowband total downwelling irradiance The rate at which radiant energy, in narrow bands of wavelengths shorter than approximately 4 {mu}m, passes through a horizontal unit area in a downward direction. Categories Radiometric Instruments The above measurement is considered scientifically relevant for the following

  8. ARM - Measurement - Shortwave narrowband total upwelling irradiance

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

    upwelling irradiance 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 : Shortwave narrowband total upwelling irradiance The rate at which radiant energy, in narrow bands of wavelengths shorter than approximately 4 {mu}m, passes through a horizontal unit area in an upward direction. Categories Radiometric Instruments The above measurement is considered scientifically relevant for the following instruments.

  9. 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

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

    SciTech Connect (OSTI)

    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 the $\\Omega_m$-$\\sigma_8$ 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.

  11. 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.

  12. 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.

  13. Robust Optical Richness Estimation with Reduced Scatter

    SciTech Connect (OSTI)

    Rykoff, E.S.; Koester, B.P.; Rozo, E.; Annis, J.; Evrard, A.E.; Hansen, S.M.; Hao, J.; Johnston, D.E.; McKay, T.A.; Wechsler, R.H.; /KIPAC, Menlo Park /SLAC

    2012-06-07

    Reducing the scatter between cluster mass and optical richness is a key goal for cluster cosmology from photometric catalogs. We consider various modifications to the red-sequence matched filter richness estimator of Rozo et al. (2009b), and evaluate their impact on the scatter in X-ray luminosity at fixed richness. Most significantly, we find that deeper luminosity cuts can reduce the recovered scatter, finding that {sigma}{sub ln L{sub X}|{lambda}} = 0.63 {+-} 0.02 for clusters with M{sub 500c} {approx}> 1.6 x 10{sup 14} h{sub 70}{sup -1} M{sub {circle_dot}}. The corresponding scatter in mass at fixed richness is {sigma}{sub ln M|{lambda}} {approx} 0.2-0.3 depending on the richness, comparable to that for total X-ray luminosity. We find that including blue galaxies in the richness estimate increases the scatter, as does weighting galaxies by their optical luminosity. We further demonstrate that our richness estimator is very robust. Specifically, the filter employed when estimating richness can be calibrated directly from the data, without requiring a-priori calibrations of the red-sequence. We also demonstrate that the recovered richness is robust to up to 50% uncertainties in the galaxy background, as well as to the choice of photometric filter employed, so long as the filters span the 4000 {angstrom} break of red-sequence galaxies. Consequently, our richness estimator can be used to compare richness estimates of different clusters, even if they do not share the same photometric data. Appendix A includes 'easy-bake' instructions for implementing our optimal richness estimator, and we are releasing an implementation of the code that works with SDSS data, as well as an augmented maxBCG catalog with the {lambda} richness measured for each cluster.

  14. 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...

  15. 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.

  16. Table 10. Total natural gas proved reserves, reserves changes, and production, w

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

    Total natural gas proved reserves, reserves changes, and production, wet after lease separation, 2014" "billion cubic feet" ,,"Changes in reserves during 2014" ,"Published",,,,,,,,"New Reservoir" ,"Proved",,"Revision","Revision",,,,"New Field","Discoveries","Estimated","Proved"

  17. 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

  18. 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.

  19. ARM - Measurement - Shortwave broadband total upwelling irradiance

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

    upwelling irradiance 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 : Shortwave broadband total upwelling irradiance The rate at which radiant energy, at a wavelength between 0.4 and 4 {mu}m, is being emitted upwards into a radiation field and transferred across a surface area (real or imaginary) in a hemisphere of directions. Categories Radiometric Instruments The above measurement is considered

  20. 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

  1. 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

  2. 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

  3. 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

  4. Total Ore Processing Integration and Management

    SciTech Connect (OSTI)

    Leslie 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 October through 31 December of 2005. Graphical analysis of blast patterns according to drill monitor data is continuing. Multiple linear regression analysis of 16 mine and mill variables (powder factor, two modeled size fractions, liberation index, predicted grind, total crude Fe, Satmagan Fe, sat ratio, DSC, geologic blend, ambient temperature, cobbing hours, feeder plugs, and percent feeder run time-of-mill time) indicates that December variations in plant performance are generally predictable (Figure 1). The outlier on December 28th coincides with low cobbing availability and equipment downtime. Mill productivity appeared to be most influenced, as usual, by ore quality as indicated by the liberation index--the higher the liberation index, the lower the throughput. The upcoming quarter will be concerned with wrapping up the work in progress, such as the detailed statistical analyses, and writing a final report. Hibtac Mine engineers are evaluating neural network software to determine its utility for modeling, and eventually predicting, mill throughput.

  5. 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.

  6. Total Supplemental Supply of Natural Gas

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

    Product: Total Supplemental Supply Synthetic Propane-Air Refinery Gas Biomass Other Period: Monthly Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: Product Area 2010 2011 2012 2013 2014 2015 View History U.S. 64,575 60,088 61,366 54,650 59,528 58,555 1980-2015 Alabama 0 0 0 0 0 1967-2014 Alaska 0 0 0 0 0 2004-2014 Arizona 0 0 0 0 0 1967-2014 Arkansas 0 0 0 0 0 1967-2014 Colorado 5,148 4,268 4,412 4,077 4,120

  7. 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.

  8. 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

  9. 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.

  10. 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, ...

  11. 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

  12. 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.

  13. 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.

  14. New York Natural Gas % of Total Residential Deliveries (Percent...

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

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

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

    Gasoline and Diesel Fuel Update (EIA)

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

  16. New Jersey Natural Gas % of Total Residential Deliveries (Percent...

    Gasoline and Diesel Fuel Update (EIA)

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

  17. 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. ...

  18. 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.

  19. 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.

  20. 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.”

  1. Magnetic cellulose-derivative structures

    DOE Patents [OSTI]

    Walsh, Myles A.; Morris, Robert 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 sorbtion agents can be incorporated during the manufacture of the structure.

  2. 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.

  3. ,"Crude Oil and Petroleum Products Total Stocks Stocks by Type...

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

    Data for" ,"Data 1","Crude Oil and Petroleum Products Total Stocks Stocks ... AM" "Back to Contents","Data 1: Crude Oil and Petroleum Products Total Stocks Stocks ...

  4. 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...

  5. ARM: GRAMS: data from the total solar broadband radiometer (TBBR...

    Office of Scientific and Technical Information (OSTI)

    solar broadband radiometer (TBBR) Title: ARM: GRAMS: data from the total solar broadband radiometer (TBBR) GRAMS: data from the total solar broadband radiometer (TBBR) Authors: ...

  6. ARM: GRAMS: calibration information for the total solar broadband...

    Office of Scientific and Technical Information (OSTI)

    solar broadband radiometer (TBBR) Title: ARM: GRAMS: calibration information for the total solar broadband radiometer (TBBR) GRAMS: calibration information for the total solar ...

  7. 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...

  8. 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...

  9. Webtrends Archives by Fiscal Year — EERE Totals

    Office of Energy Efficiency and Renewable Energy (EERE)

    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.

  10. New Jersey Natural Gas Total Consumption (Million Cubic Feet...

    Gasoline and Diesel Fuel Update (EIA)

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

  11. New York Natural Gas Total Consumption (Million Cubic Feet)

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

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

  12. New Mexico Natural Gas Total Consumption (Million Cubic Feet...

    Gasoline and Diesel Fuel Update (EIA)

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

  13. 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 ... Referring Pages: Natural Gas Consumption West Virginia Natural Gas Consumption by End Use ...

  14. 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 ... Referring Pages: Natural Gas Consumption Virginia Natural Gas Consumption by End Use ...

  15. 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 ...

  16. ,"Alaska (with Total Offshore) Natural Gas Liquids Lease Condensate...

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

    Data for" ,"Data 1","Alaska (with Total Offshore) Natural Gas Liquids Lease Condensate, ... to Contents","Data 1: Alaska (with Total Offshore) Natural Gas Liquids Lease Condensate, ...

  17. ,"Alaska (with Total Offshore) Coalbed Methane Proved Reserves...

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

    Data for" ,"Data 1","Alaska (with Total Offshore) Coalbed Methane Proved Reserves ... to Contents","Data 1: Alaska (with Total Offshore) Coalbed Methane Proved Reserves ...

  18. ,"Alaska (with Total Offshore) Natural Gas Plant Liquids, Expected...

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

    Data for" ,"Data 1","Alaska (with Total Offshore) Natural Gas Plant Liquids, Expected ... to Contents","Data 1: Alaska (with Total Offshore) Natural Gas Plant Liquids, Expected ...

  19. ,"Alaska (with Total Offshore) Shale Proved Reserves (Billion...

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

    Data for" ,"Data 1","Alaska (with Total Offshore) Shale Proved Reserves (Billion Cubic ... to Contents","Data 1: Alaska (with Total Offshore) Shale Proved Reserves (Billion Cubic ...

  20. Federal Offshore -- Gulf of Mexico Natural Gas Total Consumption...

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

    -- 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 ...

  1. ,"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...

  2. ,"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...

  3. 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 ... Referring Pages: Natural Gas Consumption North Carolina Natural Gas Consumption by End Use ...

  4. 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 ... Referring Pages: Natural Gas Consumption North Dakota Natural Gas Consumption by End Use ...

  5. 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 ...

  6. ARM: GRAMS: data from the total direct diffuse radiometer (TDDR...

    Office of Scientific and Technical Information (OSTI)

    direct diffuse radiometer (TDDR) Title: ARM: GRAMS: data from the total direct diffuse radiometer (TDDR) GRAMS: data from the total direct diffuse radiometer (TDDR) Authors: ...

  7. ,"Texas Natural Gas Gross Withdrawals Total Offshore (MMcf)"

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

    Data for" ,"Data 1","Texas Natural Gas Gross Withdrawals Total ... 7:03:02 AM" "Back to Contents","Data 1: Texas Natural Gas Gross Withdrawals Total ...

  8. 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.

  9. "Table A11. Total Primary Consumption of Combustible Energy for Nonfuel"

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

    1. Total Primary Consumption of Combustible Energy for Nonfuel" " Purposes by Census Region and Economic Characteristics of the Establishment," 1991 " (Estimates in Btu or Physical Units)" " "," "," "," ","Natural"," "," ","Coke"," "," " " ","Total","Residual","Distillate","Gas(c)"," ","Coal","and

  10. "Table A16. Components of Total Electricity Demand by Census Region, Industry"

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

    6. Components of Total Electricity Demand by Census Region, Industry" " Group, and Selected Industries, 1991" " (Estimates in Million Kilowatthours)" " "," "," "," "," "," "," "," " " "," "," "," "," ","Sales and/or"," ","RSE" "SIC"," "," ","Transfers","Total

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

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

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

  12. 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

  13. Redox Chemistry of Anthraquinone Derivatives Via Simulations...

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

    August 27, 2014, Research Highlights Redox Chemistry of Anthraquinone Derivatives Via ... S. Assary, Investigation of the Redox Chemistry of Anthraquinone Derivatives Using ...

  14. 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.

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

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

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

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

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

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

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

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

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

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

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

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

  19. "Table A38. Total Expenditures for Purchased Electricity, Steam, and Natural Gas"

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

    8. Total Expenditures for Purchased Electricity, Steam, and Natural Gas" " by Type of Supplier, Census Region, Census Division, Industry Group," " and Selected Industries, 1994" " (Estimates in Million Dollars)" ,," Electricity",," Steam" ,,,,,,"RSE" "SIC",,"Utility","Nonutility","Utility","Nonutility","Row" "Code(a)","Industry Group and

  20. "Table A46. Total Expenditures for Purchased Electricity, Steam, and Natural"

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

    6. Total Expenditures for Purchased Electricity, Steam, and Natural" " Gas by Type of Supplier, Census Region, Industry Group, and Selected Industries," 1991 " (Estimates in Million Dollars)" ,," Electricity",," Steam",," Natural Gas" ,,"-","-----------","-","-----------","-","------------","-","RSE"

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

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

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

  2. Table A19. Components of Total Electricity Demand by Census Region and

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

    Components of Total Electricity Demand by Census Region and" " Economic Characteristics of the Establishment, 1991" " (Estimates in Million Kilowatthours)" " "," "," "," ","Sales/"," ","RSE" " "," ","Transfers","Onsite","Transfers"," ","Row" "Economic

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

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

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

  4. Table A22. Total First Use (formerly Primary Consumption) of Combustible Ener

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

    First Use (formerly Primary Consumption) of Combustible Energy for Nonfuel" " Purposes by Census Region, Census Division, and Economic Characteristics of the Establishment," 1994 " (Estimates in Btu or Physical Units)" " "," "," "," ","Natural"," "," ","Coke"," "," " " ","Total","Residual","Distillate","Gas(c)","

  5. 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

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

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

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

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

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

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

  8. Table 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

  9. 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

  10. 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

  11. 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

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  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

    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. 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.

  18. 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.

  19. 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...

  20. 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.

  1. 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.

  2. 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...

  3. 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...

  4. 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...

  5. 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...

  6. North Carolina Natural Gas % of Total Residential Deliveries...

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

    % of Total Residential Deliveries (Percent) North Carolina 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. Washington Natural Gas Total Consumption (Million Cubic Feet...

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

    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...

  8. ,"U.S. Total Shell Storage Capacity at Operable Refineries"

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

    Data for" ,"Data 1","U.S. Total Shell Storage Capacity at Operable ... 9:47:20 AM" "Back to Contents","Data 1: U.S. Total Shell Storage Capacity at Operable ...

  9. 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...

  10. 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...

  11. 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...

  12. 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...

  13. 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 ...

  14. New Hampshire Natural Gas % of Total Residential Deliveries ...

    Gasoline and Diesel Fuel Update (EIA)

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

  15. ,"U.S. Total Imports Natural Gas Plant Processing"

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

    Data for" ,"Data 1","U.S. Total Imports Natural Gas Plant Processing",1,"Monthly"... "Back to Contents","Data 1: U.S. Total Imports Natural Gas Plant Processing" ...

  16. 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.

  17. 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 NREL: Building America Total Quality Management - 2015 Peer Review (2.43 MB) 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

  18. 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

  19. 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.

  20. 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.

  1. 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)

  2. 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.

  3. Alaska (with Total Offshore) Shale Production (Billion Cubic...

    Gasoline and Diesel Fuel Update (EIA)

    company data. Release Date: 11192015 Next Release Date: 12312016 Referring Pages: Shale Natural Gas Estimated Production Alaska Shale Gas Proved Reserves, Reserves Changes,...

  4. 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.

  5. 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.

  6. 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.

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

    Office of Energy Efficiency and Renewable Energy (EERE)

    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.

  8. 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

  9. Quick estimating for thermal conductivity

    SciTech Connect (OSTI)

    Sastri, S.R.S.; Rao, K.K. )

    1993-08-01

    Accurate values for thermal conductivity--an important engineering property used in heat transfer calculations of liquids--are not as readily available as those for other physical properties. Therefore, it often becomes necessary to use estimated data. A new estimating method combines ease of use with an accuracy that is generally better than existing procedures. The paper discusses how to select terms and testing correlations, then gives two examples of the use of the method for calculation of the thermal conductivity of propionic acid and chlorobenzene.

  10. 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 Jan-16 Feb-16 Mar-16 Apr-16 May-16 Jun-16 View History U.S.

  11. 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

  12. 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 Jan-16 Feb-16 Mar-16 Apr-16 May-16 Jun-16 View History U.S.

  13. 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 Jan-16 Feb-16 Mar-16 Apr-16 May-16 Jun-16 View History U.S.

  14. Estimation of Energy Savings Resulting From the BestPractices Program, Fiscal Year 2002

    SciTech Connect (OSTI)

    Truett, LF

    2003-09-24

    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.

  15. 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 ...

  16. Physisorption and Chemisorption Methods for Evaluating the Total...

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

    Physisorption and Chemisorption Methods for Evaluating the Total Surface Area and Active Surface Area of Two Types of Carbon Materials Physisorption and Chemisorption Methods for ...

  17. 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...

  18. 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...

  19. Alaska (with Total Offshore) Natural Gas Plant Liquids, Expected...

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

    Expected Future Production (Million Barrels) Alaska (with Total Offshore) Natural Gas Plant Liquids, Expected Future Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3...

  20. United States Total Electric Power Industry Net Summer Capacity...

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

    Total Electric Power Industry Net Summer Capacity, by Energy Source, 2006 - 2010" "(Megawatts)" "United ... Gases",2256,2313,1995,1932,2700 "Nuclear",100334,100266,100755,101004,10116...

  1. 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,...

  2. 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...

  3. ,"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...

  4. 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...

  5. ,"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...

  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. ,"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"...

  8. Table 17. Total Delivered Residential Energy Consumption, Projected...

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

    Total Delivered Residential Energy Consumption, Projected vs. Actual Projected (quadrillion Btu) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 ...

  9. "Table 17. Total Delivered Residential Energy Consumption, Projected...

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

    Total Delivered Residential Energy Consumption, Projected vs. Actual" "Projected" " (quadrillion Btu)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2...

  10. $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...

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

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

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

  12. 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...

  13. U.S. Total Imports of Residual Fuel

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

    Area: U.S. Total PAD District 1 Connecticut Delaware Florida Georgia Maine Maryland Massachusetts New Hampshire New Jersey New York North Carolina Pennsylvania Rhode Island South ...

  14. "Table 18. Total Delivered Commercial Energy Consumption, Projected...

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

    Total Delivered Commercial Energy Consumption, Projected vs. Actual" "Projected" " (quadrillion Btu)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,20...

  15. United States Total Electric Power Industry Net Generation, by...

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

    Total Electric Power Industry Net Generation, by Energy Source, 2006 - 2010" "(Thousand Megawatthours)" "United States" "Energy Source",2006,2007,2008,2009,2010 ...

  16. 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...

  17. 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.

  18. BLE: Battery Life Estimator | Argonne National Laboratory

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

    BLE: Battery Life Estimator BLE: Battery Life Estimator Argonne's Battery Life Estimator (BLE) software is a state-of-the-art tool kit for fitting battery aging data and for ...

  19. Incorporating Experimental Information in the Total Monte Carlo Methodology Using File Weights

    SciTech Connect (OSTI)

    Helgesson, P.; Sjöstrand, H.; Koning, A.J.; Rochman, D.; Alhassan, E.; Pomp, S.

    2015-01-15

    Some criticism has been directed towards the Total Monte Carlo method because experimental information has not been taken into account in a statistically well-founded manner. In this work, a Bayesian calibration method is implemented by assigning weights to the random nuclear data files and the method is illustratively applied to a few applications. In some considered cases, the estimated nuclear data uncertainties are significantly reduced and the central values are significantly shifted. The study suggests that the method can be applied both to estimate uncertainties in a more justified way and in the search for better central values. Some improvements are however necessary; for example, the treatment of outliers and cross-experimental correlations should be more rigorous and random files that are intended to be prior files should be generated.

  20. 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.

  1. "Table A28. Total Expenditures for Purchased Energy Sources by Census Region"

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

    Total Expenditures for Purchased Energy Sources by Census Region" " and Economic Characteristics of the Establishment, 1991" " (Estimates in Million Dollars)" " "," "," "," ",," "," "," "," "," ","RSE" " "," "," ","Residual","Distillate","Natural"," "," ","Coke","

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

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

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

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

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

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

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

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

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

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

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

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

  6. 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

  7. 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

  8. 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

  9. 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

  10. 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

  11. 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

  12. 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...

  13. Estimating Waste Inventory and Waste Tank Characterization |...

    Office of Environmental Management (EM)

    Estimating Waste Inventory and Waste Tank Characterization Estimating Waste Inventory and Waste Tank Characterization Summary Notes from 28 May 2008 Generic Technical Issue ...

  14. 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.

  15. 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}.

  16. Background estimation in experimental spectra

    SciTech Connect (OSTI)

    Fischer, R.; Hanson, K. M.; Los Alamos National Laboratory, MS P940, Los Alamos, New Mexico 87545 ; Dose, V.; Linden, W. von der

    2000-02-01

    A general probabilistic technique for estimating background contributions to measured spectra is presented. A Bayesian model is used to capture the defining characteristics of the problem, namely, that the background is smoother than the signal. The signal is allowed to have positive and/or negative components. The background is represented in terms of a cubic spline basis. A variable degree of smoothness of the background is attained by allowing the number of knots and the knot positions to be adaptively chosen on the basis of the data. The fully Bayesian approach taken provides a natural way to handle knot adaptivity and allows uncertainties in the background to be estimated. Our technique is demonstrated on a particle induced x-ray emission spectrum from a geological sample and an Auger spectrum from iron, which contains signals with both positive and negative components. (c) 2000 The American Physical Society.

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

    Office of Scientific and Technical Information (OSTI)

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

  18. 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.

  19. 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 ...

  20. Biomass Derivatives Competitive with Heating Oil Costs.

    Energy Savers [EERE]

    Biomass Derivatives Competitive with Heating Oil Costs Transportation fuel Heat or electricity * Data are from literature, except heating oil is adjusted from 2011 winter average * ...

  1. 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

  2. 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)

  3. Cell Shipments Total Inventory, Start-of-Year

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

    Cell Shipments Total Inventory, Start-of-Year 628,668 Manufactured and Purchased During Reporting Year 652,696 Imported During Reporting Year 233,377 Total Available for Shipment 1,514,740 Cells Assembled into Modules and Sold for Resale 1,129,525 Export Shipments 106,472 Total Shipments 1,235,997 Inventory, End-of-Year 278,744 Table 5. Source and disposition of photovoltaic cell shipments, 2014 (peak kilowatts) Source Disposition Source: U.S. Energy Information Administration, Form EIA-63B,

  4. Module Shipments Total Inventory, Start-of-Year

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

    Module Shipments Total Inventory, Start-of-Year 906,914 Manufactured During Reporting Year 726,915 Imported During Reporting Year 5,858,676 Purchased from U.S. OEM 33,951 Total Available for Shipment 7,526,456 U.S. Shipments and Sales for Resale 6,054,538 Export Shipments 182,985 Total Shipments 6,237,524 Inventory, End-of-Year 1,288,933 Table 6. Source and disposition of photovoltaic module shipments, 2014 (peak kilowatts) Source Disposition Source: U.S. Energy Information Administration, Form

  5. 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

  6. 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.

  7. ,"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...

  8. ,"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" ...

  9. ,"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" ...

  10. ,"U.S. Total Crude Oil and Products Imports"

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

    to Contents","Data 1: U.S. Total Crude Oil and Products Imports" "Sourcekey","MTTIMUS1... "Date","U.S. Imports of Crude Oil and Petroleum Products (Thousand ...

  11. ,"U.S. Total Crude Oil and Products Imports"

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

    to Contents","Data 1: U.S. Total Crude Oil and Products Imports" "Sourcekey","MTTIMUS2... "Date","U.S. Imports of Crude Oil and Petroleum Products (Thousand Barrels ...

  12. "Table A48. Total Expenditures for Purchased Electricity,...

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

    ...teristics(a)","Supplier(b)","Supplier(c)","Supplier(b)","Supplier(c)","Supplier(b)","Pipelines","Supplier(d)","Factors"," " ,"Total United States" "RSE Column Factors:",0.4,2.7,1.5...

  13. Lower 48 States Total Natural Gas Underground Storage Capacity...

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

    Lower 48 States Total Natural Gas Underground Storage Capacity (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2012 8,842,950 8,854,720 8,854,720 ...

  14. 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...

  15. 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...

  16. 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...

  17. Table A1. Total First Use (formerly Primary Consumption) of...

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

    ... Manufacturing Industries"," W ",613,0," W ",2," W ",0,0," W ",0,28.1 ,"Total",1947,98827,2220,2397,500,6887,13448,1627,728,48,8.2 ,,"West South Central Census Division" ...

  18. Table A1. Total First Use (formerly Primary Consumption) of...

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

    ... Manufacturing Industries"," W ",2,0," W ",2," W ",0,0," W ",0,28.1 ,"Total",1947,337,14,14,515,26,320,40,728,48,8.3 ,,"West South Central Census Division" ,"RSE Column ...

  19. 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...

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

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

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

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

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

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

  2. 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.

  3. 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 ...

  4. 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. National Fuel Cell and Hydrogen Energy Overview (4.73 MB) More ...

  5. 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.

  6. 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.

  7. 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 +...

  8. Alabama Natural Gas Percentage Total Industrial Deliveries (Percent...

    Gasoline and Diesel Fuel Update (EIA)

    Industrial Deliveries (Percent) Alabama Natural Gas Percentage Total Industrial Deliveries (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9...

  9. 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.

  10. " Level: National Data and Regional Totals;"

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

    0 Capability to Switch Coal to Alternative Energy Sources, 2002; " " Level: National Data and Regional Totals;" " Row: NAICS Codes, Value of Shipments and Employment Sizes;" " Column: Energy Sources;" " Unit: Thousand Short Tons." ,,"Coal",,,"Alternative Energy Sources(b)" ,,,,,,,,,,,"RSE" "NAICS"," ","Total","

  11. " Level: National Data and Regional Totals;"

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

    2 Capability to Switch Natural Gas to Alternative Energy Sources, 2002;" " Level: National Data and Regional Totals;" " Row: NAICS Codes, Value of Shipments and Employment Sizes;" " Column: Energy Sources;" " Unit: Billion Cubic Feet." ,,"Natural Gas",,,"Alternative Energy Sources(b)" ,,,,,,,,,,"Coal Coke",,"RSE" "NAICS"," ","Total","

  12. " Level: National Data and Regional Totals;"

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

    4 Capability to Switch Residual Fuel Oil to Alternative Energy Sources, 2002;" " Level: National Data and Regional Totals;" " Row: NAICS Codes, Value of Shipments and Employment Sizes;" " Column: Energy Sources;" " Unit: Thousand Barrels." ,,"Residual Fuel Oil",,,"Alternative Energy Sources(b)" ,,,,,,,,,,"Coal Coke",,"RSE" "NAICS"," ","Total","

  13. " Level: National Data and Regional Totals;"

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

    6 Capability to Switch Electricity to Alternative Energy Sources, 2002; " " Level: National Data and Regional Totals;" " Row: NAICS Codes, Value of Shipments and Employment Sizes;" " Column: Energy Sources;" " Unit: Million Kilowatthours." ,,"Electricity Receipts",,,"Alternative Energy Sources(b)" ,,,,,,,,,,"Coal Coke",,"RSE" "NAICS"," ","Total","

  14. " Level: National Data and Regional Totals;"

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

    8 Capability to Switch Distillate Fuel Oil to Alternative Energy Sources, 2002; " " Level: National Data and Regional Totals;" " Row: NAICS Codes, Value of Shipments and Employment Sizes;" " Column: Energy Sources;" " Unit: Thousand Barrels." ,,"Distillate Fuel Oil",,,"Alternative Energy Sources(b)" ,,,,,,,,,,"Coal Coke",,"RSE" "NAICS"," ","Total","

  15. " Level: National Data and Regional Totals;"

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

    0 Capability to Switch Coal to Alternative Energy Sources, 2006; " " Level: National Data and Regional Totals;" " Row: NAICS Codes, Value of Shipments and Employment Sizes;" " Column: Energy Sources;" " Unit: Thousand Short Tons." ,,"Coal",,,"Alternative Energy Sources(b)" "NAICS"," ","Total","

  16. " Level: National Data and Regional Totals;"

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

    2 Capability to Switch Natural Gas to Alternative Energy Sources, 2006;" " Level: National Data and Regional Totals;" " Row: NAICS Codes, Value of Shipments and Employment Sizes;" " Column: Energy Sources;" " Unit: Billion Cubic Feet." ,,"Natural Gas",,,"Alternative Energy Sources(b)" ,,,,,,,,,,"Coal Coke" "NAICS"," ","Total","

  17. " Level: National Data and Regional Totals;"

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

    4 Capability to Switch Residual Fuel Oil to Alternative Energy Sources, 2006;" " Level: National Data and Regional Totals;" " Row: NAICS Codes, Value of Shipments and Employment Sizes;" " Column: Energy Sources;" " Unit: Thousand Barrels." ,,"Residual Fuel Oil",,,"Alternative Energy Sources(b)" ,,,,,,,,,,"Coal Coke" "NAICS"," ","Total","

  18. " Level: National Data and Regional Totals;"

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

    8 Capability to Switch Distillate Fuel Oil to Alternative Energy Sources, 2006; " " Level: National Data and Regional Totals;" " Row: NAICS Codes, Value of Shipments and Employment Sizes;" " Column: Energy Sources;" " Unit: Thousand Barrels." ,,"Distillate Fuel Oil",,,"Alternative Energy Sources(b)" ,,,,,,,,,,"Coal Coke" "NAICS"," ","Total","

  19. Physisorption and Chemisorption Methods for Evaluating the Total Surface

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

    Area and Active Surface Area of Two Types of Carbon Materials | Department of Energy Physisorption and Chemisorption Methods for Evaluating the Total Surface Area and Active Surface Area of Two Types of Carbon Materials Physisorption and Chemisorption Methods for Evaluating the Total Surface Area and Active Surface Area of Two Types of Carbon Materials TSA is a gross indicator of soot reactivity and does not always correlate well with the real reactivity. This research shows that a more

  20. 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