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1

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

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

Total Stocks Stocks by Type" Total Stocks Stocks by Type" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Crude Oil and Petroleum Products Total Stocks Stocks by Type",6,"Monthly","9/2013","1/15/1956" ,"Release Date:","11/27/2013" ,"Next Release Date:","Last Week of December 2013" ,"Excel File Name:","pet_stoc_typ_a_ep00_sae_mbbl_m.xls" ,"Available from Web Page:","http://www.eia.gov/dnav/pet/pet_stoc_typ_a_ep00_sae_mbbl_m.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.gov"

2

Crude Oil and Petroleum Products Total Stocks Stocks by Type  

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

Product: Crude Oil and Petroleum Products Crude Oil All Oils (Excluding Crude Oil) Pentanes Plus Liquefied Petroleum Gases Ethane/Ethylene Propane/Propylene Normal Butane/Butylene Isobutane/Butylene Other Hydrocarbons Oxygenates (excluding Fuel Ethanol) MTBE Other Oxygenates Renewables (including Fuel Ethanol) Fuel Ethanol Renewable Diesel Fuel Other Renewable Fuels Unfinished Oils Unfinished Oils, Naphthas & Lighter Unfinished Oils, Kerosene & Light Gas Unfinished Oils, Heavy Gas Oils Residuum Motor Gasoline Blending Comp. (MGBC) MGBC - Reformulated MGBC - Reformulated, RBOB MGBC - Reformulated, RBOB w/ Alcohol MGBC - Reformulated, RBOB w/ Ether MGBC - Reformulated, GTAB MGBC - Conventional MGBC - Conventional, CBOB MGBC - Conventional, GTAB MGBC - Conventional Other Aviation Gasoline Blending Comp. Finished Motor Gasoline Reformulated Gasoline Reformulated Gasoline Blended w/ Fuel Ethanol Reformulated Gasoline, Other Conventional Gasoline Conventional Gasoline Blended Fuel Ethanol Conventional Gasoline Blended Fuel Ethanol, Ed55 and Lower Conventional Other Gasoline Finished Aviation Gasoline Kerosene-Type Jet Fuel Kerosene Distillate Fuel Oil Distillate F.O., 15 ppm Sulfur and under Distillate F.O., Greater than 15 to 500 ppm Sulfur Distillate F.O., Greater 500 ppm Sulfur Residual Fuel Oil Residual F.O., than 1.00% Sulfur Petrochemical Feedstocks Naphtha for Petro. Feedstock Use Other Oils for Petro. Feedstock Use Special Naphthas Lubricants Waxes Petroleum Coke Asphalt and Road Oil Miscellaneous Products Period-Unit: Monthly-Thousand Barrels Annual-Thousand Barrels

3

U.S. Propane Total Stocks  

Gasoline and Diesel Fuel Update (EIA)

9 9 Notes: U.S. inventories of propane benefited from a late pre-season build that pushed inventories to over 65 million barrels by early November 2000, the second highest peak pre-heating season level since 1986. Although propane inventories were expected to remain within the normal range for the duration of the 2000-01 heating season, cold weather in November and December, along with recently high natural gas prices that discouraged propane production from gas processing, resulted in stocks falling below the normal range by the end of December. However, if the weather remains seasonally normal, and the recent decline in natural gas prices holds, EIA expects the propane inventory drawdown to slow. This is reflected in the data for January 19, which showed a draw of only 2.1 million barrels, compared to more than twice that

4

Low Total OECD Oil Stocks* Keep Market Balance Tight  

Gasoline and Diesel Fuel Update (EIA)

5 5 Notes: This chart illustrates why EIA sees crude oil prices staying relatively high. It shows global inventories, as measured by OECD petroleum stocks. EIA sees a tenuous supply/demand balance over the remainder of 2001. Global inventories remain low, and need to recover to more adequate levels of forward demand coverage in order to avoid continued price volatility. The most recent data show OECD inventories remaining at very low levels. Low inventories increase the potential for price volatility throughout 2001. Inventories are a good measure of the supply/demand balance that affects prices. A large over-supply (production greater than demand) will put downward pressure on prices, while under-supply will push prices upward. OECD inventories illustrate the changes in the world petroleum

5

Type II Transformation -Regeneration 2 Media -1 Liter Solution Substance []stock/MW Final Add ( )  

E-Print Network [OSTI]

Type II Transformation - Regeneration 2 Media - 1 Liter Solution Substance []stock/MW Final Add. bialaphos stock 10mg/ml 1mg/L 100ul/L Pour into 100x25mm Petri dishes in hood. 1L=30 plates. Dry plates lids

Raizada, Manish N.

6

Contractor: Contract Number: Contract Type: Total Estimated  

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

Number: Number: Contract Type: Total Estimated Contract Cost: Performance Period Total Fee Earned FY2008 $2,550,203 FY2009 $39,646,446 FY2010 $64,874,187 FY2011 $66,253,207 FY2012 $41,492,503 FY2013 $0 FY2014 FY2015 FY2016 FY2017 FY2018 Cumulative Fee Earned $214,816,546 Fee Available $2,550,203 Minimum Fee $77,931,569 $69,660,249 Savannah River Nuclear Solutions LLC $458,687,779 $0 Maximum Fee Fee Information $88,851,963 EM Contractor Fee Site: Savannah River Site Office, Aiken, SC Contract Name: Management & Operating Contract September 2013 DE-AC09-08SR22470

7

RICOH FT MODELS PRODUCT ASU STOCK # FT 3013/3213/3513/3713 TONER TYPE 320 CP502006  

E-Print Network [OSTI]

RICOH FT MODELS PRODUCT ASU STOCK # FT 3013/3213/3513/3713 TONER TYPE 320 CP502006 DEVELOPER TYPE 310 CP502027 FT 3113/3313 TONER TYPE 310 CP502005 DEVELOPER TYPE 310 CP502027 FT 3320 TONER TYPE 3300 CP502025 DEVELOPER TYPE 3300 CP502026 FT 4415/4418/4421/4220/4222/4215 TONER TYPE 410 CP502028

Rhoads, James

8

Type II Transformation -Callus Initiation Media N6 1-100-25 +Ag Solution Substance []stock/MW Final Add ()  

E-Print Network [OSTI]

Type II Transformation - Callus Initiation Media N6 1-100-25 +Ag Solution Substance []stock25mm Petri Dishes in hood. 1L=30 plates. Dry lids on in hood 3days in darkness or quick cool upside

Raizada, Manish N.

9

U.S. Total Stocks of Crude Oil and Petroleum Products  

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

Area: U.S. PADD 1 New England Central Atlantic Lower Atlantic PADD 2 Cushing, Oklahoma PADD 3 PADD 4 PADD 5 PADD's 4 & 5 Period: Weekly Monthly Annual Area: U.S. PADD 1 New England Central Atlantic Lower Atlantic PADD 2 Cushing, Oklahoma PADD 3 PADD 4 PADD 5 PADD's 4 & 5 Period: Weekly Monthly Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: Product Area 11/08/13 11/15/13 11/22/13 11/29/13 12/06/13 12/13/13 View History Total Crude Oil and Petroleum Products (Incl. SPR) 1,806,930 1,795,196 1,793,557 1,786,470 1,781,747 1,769,150 1990-2013 Total Crude Oil and Petroleum Products (Excl. SPR) 1,110,961 1,099,227 1,097,588 1,090,501 1,085,778 1,073,181 1990-2013 Crude Oil (Including SPR) 1,084,057 1,084,432 1,087,385 1,081,800 1,071,215 1,068,274 1982-2013 Commercial Crude Oil

10

Total OECD Oil Stocks*  

Gasoline and Diesel Fuel Update (EIA)

6 6 Notes: The most recent data show OECD inventories remaining at very low levels. EIA expects inventories to remain low through the coming year. This increases the potential for price volatility through the rest of the winter, and into the next gasoline season. Inventories are a good measure of the supply/demand balance that affects prices. A large over-supply (production greater than demand) will put downward pressure on prices, while under-supply will push prices upward. As global oil production changed relative to demand, the world moved from a period of over-supply in 1998 to one of under-supply in 1999 and 2000. OECD inventories illustrate the changes in the world petroleum balance. OECD inventories rose to high levels during 1997 and 1998 when production exceeded demand and prices dropped to around $10 per barrel in

11

Total OECD Oil Stocks*  

Gasoline and Diesel Fuel Update (EIA)

The most recent data show OECD inventories remaining at very low The most recent data show OECD inventories remaining at very low levels. EIA expects inventories to remain low through the coming year. This increases the potential for price volatility through the winter, and even extending to the next gasoline season. Inventories are a good measure of the supply/demand balance that effects prices. A large over-supply (production greater than demand) will put downward pressure on prices, while under-supply will push prices upward. As global oil production changed relative to demand, the world moved from a period of over-supply in 1998 to one of under-supply in 1999 and 2000. OECD inventories illustrate the changes in the world petroleum balance. OECD inventories rose to high levels during 1997 and 1998 when production exceeded demand and prices dropped to around $10 per barrel in

12

Total OECD Oil Stocks*  

Gasoline and Diesel Fuel Update (EIA)

9 9 Notes: The most recent data show OECD inventories remaining at very low levels. EIA expects inventories to remain low through the coming year. This increases the potential for price volatility through the winter, and even extending to the next gasoline season. Inventories are a good measure of the supply/demand balance that effects prices. A large over-supply (production greater than demand) will put downward pressure on prices, while under-supply will push prices upward. As global oil production changed relative to demand, the world moved from a period of over-supply in 1998 to one of under-supply in 1999 and 2000. OECD inventories illustrate the changes in the world petroleum balance. OECD inventories rose to high levels during 1997 and 1998 when production exceeded demand and prices dropped to around $10 per barrel in

13

Total OECD Oil Stocks*  

Gasoline and Diesel Fuel Update (EIA)

7 7 Notes: As global production changed relative to demand, the world moved from a period of "over supply" in 1998 to one of "under supply" in 1999 and 2000. Inventories are a good means of seeing the imbalance between petroleum production and demand. For example, when production exceeds demand, inventories rise. A large over supply will put downward pressure on prices, while under supply will cause prices to rise. OECD inventories illustrate the changes in the world petroleum balance. OECD inventories rose to high levels during 1997 and 1998 when production exceeded demand and prices dropped to around $10 per barrel in December 1998. However, when demand exceeded production in 1999 and early 2000, inventories fell to the low levels seen above, and prices rose to $35 per

14

Total  

Gasoline and Diesel Fuel Update (EIA)

Total Total .............. 16,164,874 5,967,376 22,132,249 2,972,552 280,370 167,519 18,711,808 1993 Total .............. 16,691,139 6,034,504 22,725,642 3,103,014 413,971 226,743 18,981,915 1994 Total .............. 17,351,060 6,229,645 23,580,706 3,230,667 412,178 228,336 19,709,525 1995 Total .............. 17,282,032 6,461,596 23,743,628 3,565,023 388,392 283,739 19,506,474 1996 Total .............. 17,680,777 6,370,888 24,051,665 3,510,330 518,425 272,117 19,750,793 Alabama Total......... 570,907 11,394 582,301 22,601 27,006 1,853 530,841 Onshore ................ 209,839 11,394 221,233 22,601 16,762 1,593 180,277 State Offshore....... 209,013 0 209,013 0 10,244 260 198,509 Federal Offshore... 152,055 0 152,055 0 0 0 152,055 Alaska Total ............ 183,747 3,189,837 3,373,584 2,885,686 0 7,070 480,828 Onshore ................ 64,751 3,182,782

15

Total............................................................  

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

Total................................................................... Total................................................................... 111.1 2,033 1,618 1,031 791 630 401 Total Floorspace (Square Feet) Fewer than 500............................................... 3.2 357 336 113 188 177 59 500 to 999....................................................... 23.8 733 667 308 343 312 144 1,000 to 1,499................................................. 20.8 1,157 1,086 625 435 409 235 1,500 to 1,999................................................. 15.4 1,592 1,441 906 595 539 339 2,000 to 2,499................................................. 12.2 2,052 1,733 1,072 765 646 400 2,500 to 2,999................................................. 10.3 2,523 2,010 1,346 939 748 501 3,000 to 3,499................................................. 6.7 3,020 2,185 1,401 1,177 851 546

16

Total...................................................................  

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

Single-Family Units Single-Family Units Detached Type of Housing Unit Table HC2.7 Air Conditioning Usage Indicators by Type of Housing Unit, 2005 Million U.S. Housing Units Air Conditioning Usage Indicators Attached 2 to 4 Units 5 or More Units Mobile Homes Apartments in Buildings With-- Housing Units (millions) Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Single-Family Units Detached Type of Housing Unit Table HC2.7 Air Conditioning Usage Indicators by Type of Housing Unit, 2005 Million U.S. Housing Units Air Conditioning Usage Indicators Attached 2 to 4 Units 5 or More Units Mobile Homes Apartments in Buildings With-- Housing Units (millions) At Home Behavior Home Used for Business

17

Total...................  

Gasoline and Diesel Fuel Update (EIA)

4,690,065 52,331,397 2,802,751 4,409,699 7,526,898 209,616 1993 Total................... 4,956,445 52,535,411 2,861,569 4,464,906 7,981,433 209,666 1994 Total................... 4,847,702 53,392,557 2,895,013 4,533,905 8,167,033 202,940 1995 Total................... 4,850,318 54,322,179 3,031,077 4,636,500 8,579,585 209,398 1996 Total................... 5,241,414 55,263,673 3,158,244 4,720,227 8,870,422 206,049 Alabama ...................... 56,522 766,322 29,000 62,064 201,414 2,512 Alaska.......................... 16,179 81,348 27,315 12,732 75,616 202 Arizona ........................ 27,709 689,597 28,987 49,693 26,979 534 Arkansas ..................... 46,289 539,952 31,006 67,293 141,300 1,488 California ..................... 473,310 8,969,308 235,068 408,294 693,539 36,613 Colorado...................... 110,924 1,147,743

18

Type II Transformation -Callus Selection Media N6 2-0-0+3mg/L Bialaphos Solution Substance []stock/MW Final Add ()  

E-Print Network [OSTI]

Type II Transformation - Callus Selection Media N6 2-0-0+3mg/L Bialaphos Solution Substance []stock in hood. 1L=30 plates. Dry lids on in hood 3days or quick cool upside down, tilted on lid for 1-2 hours

Raizada, Manish N.

19

Total...........................................................  

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

Q Q Million U.S. Housing Units Renter- Occupied Housing Units (millions) Type of Renter-Occupied Housing Unit U.S. Housing Units (millions Single-Family Units Apartments in Buildings With-- Living Space Characteristics Detached Attached 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 Consumption Survey: Preliminary Housing Characteristics Tables Million U.S. Housing Units Renter- Occupied Housing Units (millions) Type of Renter-Occupied Housing Unit U.S. Housing Units (millions Single-Family Units Apartments in Buildings With-- Living Space Characteristics Detached Attached Table HC4.2 Living Space Characteristics by Renter-Occupied Housing Units, 2005

20

Total...........................................................  

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

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

Note: This page contains sample records for the topic "type total stocks" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


21

Total....................................................................................  

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

Personal Computers 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 Hours..................................................... 13.6 5.0 2.6 1.0 1.3 2 to 15 Hours............................................................. 29.1 10.3 5.9 1.6 2.9 16 to 40 Hours........................................................... 13.5 4.1 2.3 0.6 1.2 41 to 167 Hours.........................................................

22

Total....................................................................................  

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

4.2 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 Hours..................................................... 13.6 2.9 0.9 2.0 2 to 15 Hours............................................................. 29.1 6.6 2.0 4.6 16 to 40 Hours........................................................... 13.5 3.4 0.9 2.5 41 to 167 Hours......................................................... 6.3

23

Total.............................................................................  

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

Do Not Have Cooling Equipment............................... 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 Pump............................................. 53.5 16.2 10.6 5.6 With a Heat Pump................................................. 12.3 1.1 0.8 0.4 Window/Wall Units.................................................. 28.9 6.6 4.9 1.7 1 Unit..................................................................... 14.5 4.1 2.9 1.2 2 Units...................................................................

24

Total....................................................................................  

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

5.6 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 Hours..................................................... 13.6 3.4 2.5 0.9 2 to 15 Hours............................................................. 29.1 7.0 4.8 2.3 16 to 40 Hours........................................................... 13.5 2.8 2.1 0.7 41 to 167 Hours......................................................... 6.3

25

Total.......................................................................  

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

4.2 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 1.................................................................. 22.5 5.4 1.5 3.9 2.................................................................. 4.0 1.1 0.3 0.8 3 or More..................................................... 0.7 0.3 Q Q Type of Monitor Used on Most-Used PC Desk-top CRT (Standard Monitor)...........................

26

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 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 Type of Air-Conditioning Equipment 1, 2 Central System.......................................................... 65.9 6.0 5.2 0.8 Without a Heat Pump.............................................. 53.5 5.5 4.8 0.7 With a Heat Pump................................................... 12.3 0.5 0.4 Q Window/Wall Units.................................................... 28.9 10.7 7.6 3.1 1 Unit.......................................................................

27

Total.............................................................................  

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

Do Not Have Cooling Equipment............................... 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 Pump............................................. 53.5 8.7 3.2 5.5 With a Heat Pump................................................. 12.3 1.7 0.7 1.0 Window/Wall Units.................................................. 28.9 3.6 0.6 3.0 1 Unit..................................................................... 14.5 2.9 0.5 2.4 2 Units...................................................................

28

Total.............................................................................  

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

Do Not Have Cooling Equipment............................... 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 Pump............................................. 53.5 23.2 10.9 3.8 8.4 With a Heat Pump................................................. 12.3 9.0 6.7 1.4 0.9 Window/Wall Units.................................................. 28.9 8.0 3.4 1.7 2.9 1 Unit.....................................................................

29

Total..........................................................................  

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

7.1 7.1 19.0 22.7 22.3 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 2.1 0.6 Q 0.4 500 to 999........................................................... 23.8 13.6 3.7 3.2 3.2 1,000 to 1,499..................................................... 20.8 9.5 3.7 3.4 4.2 1,500 to 1,999..................................................... 15.4 6.6 2.7 2.5 3.6 2,000 to 2,499..................................................... 12.2 5.0 2.1 2.8 2.4 2,500 to 2,999..................................................... 10.3 3.7 1.8 2.8 2.1 3,000 to 3,499..................................................... 6.7 2.0 1.4 1.7 1.6 3,500 to 3,999..................................................... 5.2 1.6 0.8 1.5 1.4 4,000 or More.....................................................

30

Total..........................................................................  

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

0.7 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 1.3 2,500 to 2,999..................................................... 10.3 3.0 1.8 0.5 0.7 3,000 to 3,499..................................................... 6.7 2.1 1.2 0.5 0.4 3,500 to 3,999..................................................... 5.2 1.5 0.8 0.3 0.4 4,000 or More.....................................................

31

Total..........................................................................  

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

25.6 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 2.6 2,500 to 2,999..................................................... 10.3 2.2 2.7 3.0 2.4 3,000 to 3,499..................................................... 6.7 1.6 2.1 2.1 0.9 3,500 to 3,999..................................................... 5.2 1.1 1.7 1.5 0.9 4,000 or More.....................................................

32

Total..........................................................................  

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

4.2 4.2 7.6 16.6 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 1.0 0.2 0.8 500 to 999........................................................... 23.8 6.3 1.4 4.9 1,000 to 1,499..................................................... 20.8 5.0 1.6 3.4 1,500 to 1,999..................................................... 15.4 4.0 1.4 2.6 2,000 to 2,499..................................................... 12.2 2.6 0.9 1.7 2,500 to 2,999..................................................... 10.3 2.4 0.9 1.4 3,000 to 3,499..................................................... 6.7 0.9 0.3 0.6 3,500 to 3,999..................................................... 5.2 0.9 0.4 0.5 4,000 or More.....................................................

33

Total.........................................................................  

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

Floorspace (Square Feet) 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 2,500 to 2,999.................................................... 10.3 1.5 2.3 2.7 2.1 1.7 3,000 to 3,499.................................................... 6.7 1.0 2.0 1.7 1.0 1.0 3,500 to 3,999.................................................... 5.2 0.8 1.5 1.5 0.7 0.7 4,000 or More.....................................................

34

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 2,999..................................................... 10.3 2.2 1.7 0.6 3,000 to 3,499..................................................... 6.7 1.6 1.0 0.6 3,500 to 3,999..................................................... 5.2 1.1 0.9 0.3 4,000 or More.....................................................

35

Total..........................................................................  

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

7.1 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 2,500 to 2,999..................................................... 10.3 0.5 0.5 0.4 1.1 3,000 to 3,499..................................................... 6.7 0.3 Q 0.4 0.3 3,500 to 3,999..................................................... 5.2 Q Q Q Q 4,000 or More.....................................................

36

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 0.4 2,139 1,598 Q Q Q Q 2,500 to 2,999........................................ 10.1 Q Q Q Q Q Q Q 3,000 or More......................................... 29.6 0.3 Q Q Q Q Q Q Heated Floorspace (Square Feet) None...................................................... 3.6 1.8 1,048 0 Q 827 0 407 Fewer than 500......................................

37

Total...................................................................  

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

2,033 2,033 1,618 1,031 791 630 401 Total Floorspace (Square Feet) Fewer than 500............................................... 3.2 357 336 113 188 177 59 500 to 999....................................................... 23.8 733 667 308 343 312 144 1,000 to 1,499................................................. 20.8 1,157 1,086 625 435 409 235 1,500 to 1,999................................................. 15.4 1,592 1,441 906 595 539 339 2,000 to 2,499................................................. 12.2 2,052 1,733 1,072 765 646 400 2,500 to 2,999................................................. 10.3 2,523 2,010 1,346 939 748 501 3,000 to 3,499................................................. 6.7 3,020 2,185 1,401 1,177 851 546 3,500 to 3,999................................................. 5.2 3,549 2,509 1,508

38

Total...........................................................  

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

26.7 26.7 28.8 20.6 13.1 22.0 16.6 38.6 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................... 3.2 1.9 0.9 Q Q Q 1.3 2.3 500 to 999........................................... 23.8 10.5 7.3 3.3 1.4 1.2 6.6 12.9 1,000 to 1,499..................................... 20.8 5.8 7.0 3.8 2.2 2.0 3.9 8.9 1,500 to 1,999..................................... 15.4 3.1 4.2 3.4 2.0 2.7 1.9 5.0 2,000 to 2,499..................................... 12.2 1.7 2.7 2.9 1.8 3.2 1.1 2.8 2,500 to 2,999..................................... 10.3 1.2 2.2 2.3 1.7 2.9 0.6 2.0 3,000 to 3,499..................................... 6.7 0.9 1.4 1.5 1.0 1.9 0.4 1.4 3,500 to 3,999..................................... 5.2 0.8 1.2 1.0 0.8 1.5 0.4 1.3 4,000 or More...................................... 13.3 0.9 1.9 2.2 2.0 6.4 0.6 1.9 Heated Floorspace

39

Total...........................................................  

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

14.7 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 1.8 1.4 2.2 2.1 1.6 0.8 2,500 to 2,999..................................... 10.3 1.6 0.9 1.1 1.1 1.5 1.5 1.7 0.8 3,000 to 3,499..................................... 6.7 1.0 0.5 0.8 0.8 1.2 0.8 0.9 0.8 3,500 to 3,999..................................... 5.2 1.1 0.3 0.7 0.7 0.4 0.5 1.0 0.5 4,000 or More...................................... 13.3

40

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 2,499.............................. 12.2 11.9 2,039 1,731 1,055 2,143 1,813 1,152 Q Q Q 2,500 to 2,999.............................. 10.3 10.1 2,519 2,004 1,357 2,492 2,103 1,096 Q Q Q 3,000 or 3,499.............................. 6.7 6.6 3,014 2,175 1,438 3,047 2,079 1,108 N N N 3,500 to 3,999.............................. 5.2 5.1 3,549 2,505 1,518 Q Q Q N N N 4,000 or More...............................

Note: This page contains sample records for the topic "type total stocks" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
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41

U.S. Total Stocks  

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

Crude Oil and Petroleum Products Crude Oil and Petroleum Products 1,665,345 1,736,739 1,776,375 1,794,099 1,750,087 1,807,777 1956-2012 Crude Oil 983,046 1,027,663 1,051,795 1,059,975 1,026,630 1,060,764 1913-2012 All Oils (Excluding Crude Oil) 682,299 709,076 724,580 734,124 723,457 747,013 1993-2012 Pentanes Plus 10,278 13,775 10,481 12,510 17,596 12,739 1981-2012 Liquefied Petroleum Gases 95,592 113,134 102,147 108,272 111,778 140,529 1967-2012 Ethane/Ethylene 14,869 27,591 20,970 24,323 22,892 35,396 1967-2012 Propane/Propylene 52,007 55,408 50,140 49,241 54,978 67,991 1967-2012 Normal Butane/Butylene 21,862 23,031 24,149 27,652 26,779 28,574 1981-2012 Isobutane/Butylene 6,854 7,104 6,888 7,056 7,129 8,568 1981-2012 Other Hydrocarbons 29 20 41 42 2009-2012

42

U.S. Total Stocks  

Gasoline and Diesel Fuel Update (EIA)

Reserve Non-SPR Refinery Tank Farms and Pipelines Leases Alaskan in Transit Bulk Terminal Pipeline Natural Gas Processing Plant Download Series History Download Series History...

43

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 than 2 Hours......................................................... 13.6 0.7 0.9 0.9 1.4 2 to 15 Hours................................................................. 29.1 1.7 2.1 1.9 3.4 16 to 40 Hours............................................................... 13.5 0.9 0.9 0.9 1.8 41 to 167 Hours.............................................................

44

Total....................................................................................  

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

25.6 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 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 Hours..................................................... 13.6 2.4 3.4 5.0 2.9 2 to 15 Hours............................................................. 29.1 5.2 7.0 10.3 6.6 16 to 40 Hours........................................................... 13.5 3.1 2.8 4.1 3.4 41 to 167 Hours.........................................................

45

Total..................................................................  

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

33.0 33.0 8.0 3.4 5.9 14.4 1.2 Do Not Have Cooling Equipment..................... 17.8 6.5 1.6 0.9 1.3 2.4 0.2 Have Cooling Equipment................................. 93.3 26.5 6.5 2.5 4.6 12.0 1.0 Use Cooling Equipment.................................. 91.4 25.7 6.3 2.5 4.4 11.7 0.8 Have Equipment But Do Not Use it................. 1.9 0.8 Q Q 0.2 0.3 Q Type of Air-Conditioning Equipment 1, 2 Central System.............................................. 65.9 14.1 3.6 1.5 2.1 6.4 0.6 Without a Heat Pump.................................. 53.5 12.4 3.1 1.3 1.8 5.7 0.6 With a Heat Pump....................................... 12.3 1.7 0.6 Q 0.3 0.6 Q Window/Wall Units....................................... 28.9 12.4 2.9 1.0 2.5 5.6 0.4 1 Unit.......................................................... 14.5 7.3 1.2 0.5 1.4 3.9 0.2 2 Units.........................................................

46

Total...............................................................  

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

26.7 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 1.3 1.2 5.0 0.3 1.1 Number of Laptop PCs 1.......................................................... 22.5 2.2 4.6 4.5 2.9 8.3 1.4 4.0 2.......................................................... 4.0 Q 0.4 0.6 0.4 2.4 Q 0.5 3 or More............................................. 0.7 Q Q Q Q 0.4 Q Q Type of Monitor Used on Most-Used PC Desk-top

47

Total...............................................................  

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

20.6 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 1.......................................................... 22.5 4.7 4.6 7.7 5.4 2.......................................................... 4.0 0.6 0.9 1.5 1.1 3 or More............................................. 0.7 Q Q Q 0.3 Type of Monitor Used on Most-Used PC Desk-top CRT (Standard Monitor)................... 45.0 7.9 11.4 15.4 10.2 Flat-panel LCD.................................

48

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 Hours..................................................... 13.6 5.7 1.8 2.9 3.2 2 to 15 Hours............................................................. 29.1 11.9 5.1 6.5 5.7 16 to 40 Hours........................................................... 13.5 5.5 2.5 3.3 2.2 41 to 167 Hours.........................................................

49

Total...............................................................  

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

47.1 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 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 1.......................................................... 22.5 9.1 3.6 6.0 3.8 2.......................................................... 4.0 1.5 0.6 1.3 0.7 3 or More............................................. 0.7 0.3 Q Q Q Type of Monitor Used on Most-Used PC Desk-top CRT (Standard Monitor)................... 45.0 17.7 7.5 10.2 9.6 Flat-panel LCD.................................

50

Total...............................................................  

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

0.7 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 1.......................................................... 22.5 7.7 4.3 1.1 2.4 2.......................................................... 4.0 1.5 0.9 Q 0.4 3 or More............................................. 0.7 Q Q Q Q Type of Monitor Used on Most-Used PC Desk-top CRT (Standard Monitor)................... 45.0 15.4 7.9 2.8 4.8 Flat-panel LCD.................................

51

Total.............................................................................  

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

Do Not Have Cooling Equipment............................... 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 Pump............................................. 53.5 21.2 9.7 13.7 8.9 With a Heat Pump................................................. 12.3 4.6 1.2 2.8 3.6 Window/Wall Units.................................................. 28.9 13.4 5.6 3.9 6.1 1 Unit.....................................................................

52

Total..................................................................  

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

78.1 78.1 64.1 4.2 1.8 2.3 5.7 Do Not Have Cooling Equipment..................... 17.8 11.3 9.3 0.6 Q 0.4 0.9 Have Cooling Equipment................................. 93.3 66.8 54.7 3.6 1.7 1.9 4.8 Use Cooling Equipment.................................. 91.4 65.8 54.0 3.6 1.7 1.9 4.7 Have Equipment But Do Not Use it................. 1.9 1.1 0.8 Q N Q Q Type of Air-Conditioning Equipment 1, 2 Central System.............................................. 65.9 51.7 43.9 2.5 0.7 1.6 3.1 Without a Heat Pump.................................. 53.5 41.1 34.8 2.1 0.5 1.2 2.6 With a Heat Pump....................................... 12.3 10.6 9.1 0.4 Q 0.3 0.6 Window/Wall Units....................................... 28.9 16.5 12.0 1.3 1.0 0.4 1.7 1 Unit.......................................................... 14.5 7.2 5.4 0.5 0.2 Q 0.9 2 Units.........................................................

53

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 System.............................................. 65.9 3.7 2.6 6.1 6.8 11.2 13.2 13.9 8.2 Without a Heat Pump.................................. 53.5 3.6 2.3 5.5 5.8 9.5 10.1 10.3 6.4 With a Heat Pump....................................... 12.3 Q 0.3 0.6 1.0 1.7 3.1 3.6 1.7 Window/Wall Units....................................... 28.9 7.3 3.2 4.5 3.7 4.8 3.0 1.9 0.7 1 Unit..........................................................

54

Total..............................................................  

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

Do Not Have Cooling Equipment................ Do Not Have Cooling Equipment................ 17.8 5.3 4.7 2.8 1.9 3.1 3.6 7.5 Have Cooling Equipment............................. 93.3 21.5 24.1 17.8 11.2 18.8 13.0 31.1 Use Cooling Equipment.............................. 91.4 21.0 23.5 17.4 11.0 18.6 12.6 30.3 Have Equipment But Do Not Use it............. 1.9 0.5 0.6 0.4 Q Q 0.5 0.8 Type of Air-Conditioning Equipment 1, 2 Central System.......................................... 65.9 11.0 16.5 13.5 8.7 16.1 6.4 17.2 Without a Heat Pump.............................. 53.5 9.4 13.6 10.7 7.1 12.7 5.4 14.5 With a Heat Pump................................... 12.3 1.7 2.8 2.8 1.6 3.4 1.0 2.7 Window/Wall Units................................... 28.9 10.5 8.1 4.5 2.7 3.1 6.7 14.1 1 Unit...................................................... 14.5 5.8 4.3 2.0 1.1 1.3 3.4 7.4 2 Units....................................................

55

U.S. Crude Oil and Petroleum Products Stocks by Type  

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

Product: Crude Oil and Petroleum Products Crude Oil All Oils (Excluding Crude Oil) Pentanes Plus Liquefied Petroleum Gases Ethane/Ethylene Ethylene Propane/Propylene Propylene (Nonfuel Use) Normal Butane/Butylene Refinery Grade Butane Isobutane/Butylene Other Hydrocarbons Oxygenates (excluding Fuel Ethanol) MTBE Other Oxygenates Renewables (including Fuel Ethanol) Fuel Ethanol Renewable Diesel Fuel Other Renewable Fuels Unfinished Oils Unfinished Oils, Naphthas & Lighter Unfinished Oils, Kerosene & Light Gas Unfinished Oils, Heavy Gas Oils Residuum Motor Gasoline Blending Comp. (MGBC) MGBC - Reformulated MGBC - Reformulated, RBOB MGBC - Reformulated, RBOB w/ Alcohol MGBC - Reformulated, RBOB w/ Ether MGBC - Reformulated, GTAB MGBC - Conventional MGBC - Conventional, CBOB MGBC - Conventional, GTAB MGBC - Conventional Other Aviation Gasoline Blending Comp. Finished Motor Gasoline Reformulated Gasoline Reformulated Gasoline Blended w/ Fuel Ethanol Reformulated Gasoline, Other Conventional Gasoline Conventional Gasoline Blended Fuel Ethanol Conventional Gasoline Blended Fuel Ethanol, Ed55 and Lower Conventional Other Gasoline Finished Aviation Gasoline Kerosene-Type Jet Fuel Kerosene Distillate Fuel Oil Distillate F.O., 15 ppm Sulfur and under Distillate F.O., Greater than 15 to 500 ppm Sulfur Distillate F.O., Greater 500 ppm Sulfur Residual Fuel Oil Residual F.O., than 1.00% Sulfur Petrochemical Feedstocks Naphtha for Petro. Feedstock Use Other Oils for Petro. Feedstock Use Special Naphthas Lubricants Waxes Petroleum Coke Asphalt and Road Oil Miscellaneous Products

56

Persistent collective trend in stock markets  

Science Journals Connector (OSTI)

Empirical evidence is given for a significant difference in the collective trend of the share prices during the stock index rising and falling periods. Data on the Dow Jones Industrial Average and its stock components are studied between 1991 and 2008. Pearson-type correlations are computed between the stocks and averaged over stock pairs and time. The results indicate a general trend: whenever the stock index is falling the stock prices are changing in a more correlated manner than in case the stock index is ascending. A thorough statistical analysis of the data shows that the observed difference is significant, suggesting a constant fear factor among stockholders.

Emeric Balogh; Ingve Simonsen; Bálint Zs. Nagy; Zoltán Néda

2010-12-13T23:59:59.000Z

57

A Viscosity Approach to Total Variation Flows of Non-Divergence Type  

E-Print Network [OSTI]

A Viscosity Approach to Total Variation Flows of Non-Divergence Type Norbert Poz´ar Graduate School, we will introduce a notion of viscosity solutions for a class of singular nonlinear parabolic viscosity theory does not apply is the unboundedness of the operator on the right-hand side of (5) at u = 0

Ishii, Hitoshi

58

Global distribution of total cloud cover and cloud type amounts over the ocean  

SciTech Connect (OSTI)

This is the fourth of a series of atlases to result from a study of the global cloud distribution from ground-based observations. The first two atlases (NCAR/TN-201+STR and NCAR/TN-241+STR) described the frequency of occurrence of each cloud type and the co-occurrence of different types, but included no information about cloud amounts. The third atlas (NCAR/TN-273+STR) described, for the land areas of the earth, the average total cloud cover and the amounts of each cloud type, and their geographical, diurnal, seasonal, and interannual variations, as well as the average base heights of the low clouds. The present atlas does the same for the ocean areas of the earth.

Warren, S.G.; Hahn, C.J.; London, J.; Chervin, R.M.; Jenne, R.L. (Washington Univ., Seattle, WA (USA). Dept. of Atmospheric Sciences; Colorado Univ., Boulder, CO (USA). Cooperative Inst. for Research in Environmental Sciences; Colorado Univ., Boulder, CO (USA). Dept. of Astrophysical, Planetary, and Atmospheric Sciences; National Center for Atmospheric Research, Boulder, CO (USA))

1988-12-01T23:59:59.000Z

59

Aluminium in-use stocks in the state of Connecticut  

Science Journals Connector (OSTI)

The in-use stock of aluminium in the State of Connecticut, USA, has been established by an extensive “bottom-up” study. For year 2000, the results are a total stock of 1.2–1.4 Tg Al, or 360–400 kg Al per capita. The per capita stock amount is similar to that derived in a recent study in Japan. Infrastructure & buildings contains nearly 60% of the total stock, and transportation vehicles nearly 40%. The aluminium in equipment of various kinds amounts to only about 2% of the total, and packaging stock is less than 1%.

Korinti Recalde; Jinlong Wang; T.E. Graedel

2008-01-01T23:59:59.000Z

60

U.S. Total Propane (Consumer Grade) Prices by Sales Type  

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

Area: U.S. East Coast (PADD 1) New England (PADD 1A) Central Atlantic (PADD 1B) Lower Atlantic (PADD 1C) Midwest (PADD 2) Gulf Coast (PADD 3) Rocky Mountain (PADD 4) West Coast (PADD 5) Period: Monthly Annual Area: U.S. East Coast (PADD 1) New England (PADD 1A) Central Atlantic (PADD 1B) Lower Atlantic (PADD 1C) Midwest (PADD 2) Gulf Coast (PADD 3) Rocky Mountain (PADD 4) West Coast (PADD 5) Period: Monthly Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: Sales Type Area Apr-13 May-13 Jun-13 Jul-13 Aug-13 Sep-13 View History Sales to End Users, Average - - - - - - 1993-2013 Residential - - - - - - 1993-2013 Commercial/Institutional - - - - - - 1993-2013 Industrial - - - - - - 1993-2013 Through Retail Outlets - - - - - - 1993-2013 Petro-Chemical - - - - - - 1994-2013 Other End Users - - - - - - 1993-2013 Sales for Resale

Note: This page contains sample records for the topic "type total stocks" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


61

Cooperative Extension Instruction Public Service Research Total Type Major Unit Department CNT Amount CNT Amount CNT Amount CNT Amount CNT Amount  

E-Print Network [OSTI]

Cooperative Extension Instruction Public Service Research Total Type Major Unit Department CNT Service Research Total Type Major Unit Department CNT Amount CNT Amount CNT Amount CNT Amount CNT Amount $16,000 2 $37,966 CENTER APPLIED GENETIC TECH- RI 1 $158,070 1 $158,070 CENTER FOR FOOD SAFETY

Arnold, Jonathan

62

Effect of window type, size and orientation on the total energy demand for a building in Indian climatic conditions  

Science Journals Connector (OSTI)

Windows in a building allow daylight to enter a building space but simultaneously they also result in heat gains and losses affecting energy balance. This requires an optimisation of window area from the point of view of total energy demand viz., for lighting and cooling/heating. This paper is devoted to this kind of study for Indian climatic conditions, which are characterised by six climatic zones varying from extreme cold to hot, dry and humid conditions. Different types of windows have been considered because the optimised size will also depend on the thermo-optical parameters like heat transfer coefficient (U-value), solar heat gain coefficient (g), visual (?), and total transmittance (T) of the glazing in the window. It is observed that in a non-insulated building, cooling/heating energy demand far exceeds lighting energy demand, making the optimisation of window area a futile exercise from the point of view of total energy demand. Only for buildings with U-value below 0.6 W/m²K can optimisation be achieved. The optimised window area and the corresponding specific energy consumption have been calculated for different climates in India, for different orientations, and for three different advanced window systems.

Inderjeet Singh; N.K. Bansal

2004-01-01T23:59:59.000Z

63

Low Gasoline Stocks Indicate Increased Odds of Spring Volatility  

Gasoline and Diesel Fuel Update (EIA)

We cannot just focus on distillate. Gasoline will likely be our next We cannot just focus on distillate. Gasoline will likely be our next major concern. Gasoline stock levels have fallen well below the typical band for this time of year, primarily for the same reason distillate stocks fell to low levels -- namely relatively low production due to low margins. At the end of January, total gasoline inventories were almost 13 million barrels (6%) below the low end of the normal band. While gasoline stocks are generally not as important a supply source to the gasoline market this time of year as are distillate stocks to the distillate market, gasoline stocks still are needed. Gasoline stocks are usually used to help meet gasoline demand during February and March as refiners go through maintenance and turnarounds, but we do not have the

64

stocked inventory.PDF  

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

08 08 AUDIT REPORT STOCKED INVENTORY AT THE SAVANNAH RIVER SITE U.S. DEPARTMENT OF ENERGY OFFICE OF INSPECTOR GENERAL OFFICE OF AUDIT SERVICES JUNE 2001 MEMORANDUM FOR THE SECRETARY FROM: Gregory H. Friedman (Signed) Inspector General SUBJECT: INFORMATION: Audit Report on "Stocked Inventory at the Savannah River Site" BACKGROUND The Department of Energy's (Department) management and operating contractor at the Savannah River Site, Westinghouse Savannah River Company (Westinghouse), is responsible for managing the majority of the Department's missions and associated stocked inventory at the site. As of March 2001, Westinghouse maintained about

65

North Atlantic Oscillation influence and weather types associated with winter total and extreme precipitation events in Spain  

Science Journals Connector (OSTI)

An analysis of winter intensity and frequency of precipitation is presented, based on 102 daily precipitation stations over Spain and the Balearic Islands for the 1997–2006 decade. Precipitation stations have been merged in the eight different regions which compose the analyzed area by the use of an EOF analysis. NAO influence on the intensity and frequency of precipitation of each region is described in terms of mean precipitation, mean rain frequency, the number of extreme events, changes in the precipitation distribution and the prevalent synoptic configuration. Results indicate a non-stationary response; NAO signal being more evident in mid–late winter. Strong regional differences in the response to NAO are also found, which vary according to the specific character of the precipitation under analysis. Thus, NAO exerts a clear effect on the intensity of total and extreme precipitation rates in northern and westernmost Spanish regions, whereas the frequency of precipitation is clearly affected by NAO in central and southwestern areas. While the correlation between NAO and precipitation is negative for most of the analyzed area, two regions reveal positive responses to NAO in total precipitation occurrence and intensity for specific months. Further analyses reveal asymmetric responses to opposite phases of NAO in the precipitation distributions of some regions. The complex regional relationship between NAO and precipitation is also revealed through the modulation of the former in the preferred Circulation Weather Types associated to precipitation in each region. This spatially non-homogeneous NAO signal stresses the need of caution when employing Iberian precipitation as a proxy for NAO.

S. Queralt; E. Hernández; D. Barriopedro; D. Gallego; P. Ribera; C. Casanova

2009-01-01T23:59:59.000Z

66

Monitoring of Total Type II Pyrethroid Pesticides in Citrus Oils and Water by Converting to a Common Product 3-Phenoxybenzoic Acid  

E-Print Network [OSTI]

Monitoring of Total Type II Pyrethroid Pesticides in Citrus Oils and Water by Converting to a Common Product 3-Phenoxybenzoic Acid Mark R. McCoy, Zheng Yang, Xun Fu,§ Ki Chang Ahn, Shirley J. Gee an alternative method that converts the type II pyrethroids to a common chemical product, 3-phenoxybenzoic acid

Hammock, Bruce D.

67

Value-Added Stock Loan Participation Program | Department of Energy  

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

Value-Added Stock Loan Participation Program Value-Added Stock Loan Participation Program Value-Added Stock Loan Participation Program < Back Eligibility Agricultural Savings Category Bioenergy Solar Buying & Making Electricity Wind Maximum Rebate RFA provides up to 45% of the loan up to $40,000 of loan principal Program Info Start Date 1994 State Minnesota Program Type State Loan Program Provider Minnesota Department of Agriculture The Value-Added Stock Loan Participation Program was created in 1994 and is designed to help farmers finance the purchase of stock in certain types of cooperative, limited liability company, or limited liability partnership that will produce a "value-added agricultural product." This may include wind energy and anaerobic-digestion cooperatives if they meet the

68

Distillate Stocks Expected  

Gasoline and Diesel Fuel Update (EIA)

4 4 Notes: So let's get to what you want to know. What do we expect this upcoming winter? When EIA's demand forecast is combined with its outlook for production and net imports, distillate stocks are projected to remain towards the lower end of the normal range. We are forecasting about an 11 million barrel build between the end of July 2001 and the end of November 2001, slightly more than the average over the past 5 years (10 million barrels), but less than the average of the last 10 years (15 ½ million barrels). If, however, economic incentives are high enough, distillate stocks could build more, resulting in a higher distillate stock level heading into the winter. Of course, the reverse is true as well, if for example, the distillate fuel refining spread declines substantially. Since 1994,

69

PAD District III Stocks  

Gasoline and Diesel Fuel Update (EIA)

4 4 Notes: PADD 3 (the Gulf Coast) inventories, at the end of July, stood at 33.5 million barrels and are well above the normal range for this time of year. Since we have a few months more to go until the beginning of the heating season, there is still time for the plentiful stocks in the Gulf Coast to find their way up into the Midwest. Thus, even though propane stocks in the Midwest are low, this could easily not be the case by the beginning of the heating season. One slight area of concern, however, is that the Texas Eastern Pipeline (TET) is experiencing brine problems due to heavy rains and record stock builds. To help alleviate the problem, some chemical companies are shifting their propane out of TET to other storage facilities. At this time we don't feel that this will negatively affect the propane market this

70

Property:StockSymbol | Open Energy Information  

Open Energy Info (EERE)

StockSymbol StockSymbol Jump to: navigation, search This is a property of type String. Pages using the property "StockSymbol" Showing 25 pages using this property. (previous 25) (next 25) A A.O. Smith + AOS + AAON + AAON + Alterra Power + MGMXF + Ameresco, Inc. + AMRC + Applied Materials + AMAT + Archer Daniels Midland + ADM + Autodesk + ADSK + C China Integrated Energy + CBEH + E EEMAP, Inc. + N/A + EnerNOC + ENOC + Evergreen Solar, Inc. + ESLR + ExxonMobil + XOM + G General Electric + GE + Geothermal Resources Council + Geothermal Resources Council + Goodwill Instrument + TPE 2423 + GreenShift Corporation + GERS.OB + Gulfsands Petroleum + AIM:GPX + H Helix Wind Corp. + HLXW + I ICF International + NASDAQ:ICFI + J Johnson Controls + JCI + M Molycorp Inc. + MCP +

71

The effect of the Fukushima nuclear accident on stock prices of electric power utilities in Japan  

Science Journals Connector (OSTI)

The purpose of this study is to investigate the effect of the accident at the Fukushima Daiichi nuclear power station, which is owned by Tokyo Electric Power Co. (TEPCO), on the stock prices of the other electric power utilities in Japan. Because the other utilities were not directly damaged by the Fukushima nuclear accident, their stock price responses should reflect the change in investor perceptions on risk and return associated with nuclear power generation. Our first finding is that the stock prices of utilities that own nuclear power plants declined more sharply after the accident than did the stock prices of other electric power utilities. In contrast, investors did not seem to care about the risk that may arise from the use of the same type of nuclear power reactors as those at the Fukushima Daiichi station. We also observe an increase of both systematic and total risks in the post-Fukushima period, indicating that negative market reactions are not merely caused by one-time losses but by structural changes in society and regulation that could increase the costs of operating a nuclear power plant.

Shingo Kawashima; Fumiko Takeda

2012-01-01T23:59:59.000Z

72

Use of naphthenic base stocks in engine oil formulations  

SciTech Connect (OSTI)

The use of naphthenic base stocks in the formulation of engine oils has always been restricted due to certain physico-chemical properties (i.e. low oxidation stability, high volatility, great variation of the viscosity with the temperature) as well as the limited availability of this type of base oil in many parts of the world. This paper summarizes the experimental results followed in the development of a crankcase engine oil formulation SAE 40, API SF/CC with maximum usage of a naphthenic base stock MVIN-170 combined with HVI stocks and conventional additive technologies. The physico-chemical characterization of the MVIN-170 base stock, a conventional processed napthenic oil that Maraven (affiliate of PDVSA) commercializes from Isla Refinery of Curazao, is presented and compared with other napthenic oils coming from other crude sources of processes and with parafinic base stocks of equivalent viscosity.

Josefina, V.C.M.; Armando, I.R.

1988-01-01T23:59:59.000Z

73

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 & Ed55 Imports - Other Conventional Gasoline Imports - Motor Gasoline Blend. Components Imports - Motor Gasoline Blend. Components, RBOB Imports - Motor Gasoline Blend. Components, RBOB w/ Ether Imports - Motor Gasoline Blend. Components, RBOB w/ Alcohol Imports - Motor Gasoline Blend. Components, CBOB Imports - Motor Gasoline Blend. Components, GTAB Imports - Motor Gasoline Blend. Components, Other Imports - Fuel Ethanol Imports - Kerosene-Type Jet Fuel Imports - Distillate Fuel Oil Imports - Distillate F.O., 15 ppm Sulfur and Under Imports - Distillate F.O., > 15 ppm to 500 ppm Sulfur Imports - Distillate F.O., > 500 ppm to 2000 ppm Sulfur Imports - Distillate F.O., > 2000 ppm Sulfur Imports - Residual Fuel Oil Imports - Propane/Propylene Imports - Other Other Oils Imports - Kerosene Imports - NGPLs/LRGs (Excluding Propane/Propylene) Exports - Total Crude Oil and Products Exports - Crude Oil Exports - Products Exports - Finished Motor Gasoline Exports - Kerosene-Type Jet Fuel Exports - Distillate Fuel Oil Exports - Residual Fuel Oil Exports - Propane/Propylene Exports - Other Oils Net Imports - Total Crude Oil and Products Net Imports - Crude Oil Net Imports - Petroleum Products Period: Weekly 4-Week Avg.

74

Stocking Rate Decisions  

E-Print Network [OSTI]

to predict potential forage shortfalls, determine the im- pact of the decision on finances and other ranch re- sources, and make any necessary adjustments before the forage resource is harmed or financial problems occur. Through adequate planning and periodic... rates with limited knowledge of future forage and market conditions. But they can use past records, experience and range surveys to make realistic projections of forage and market conditions (Figure 3). Then, the planned stock- ing rate should...

White, Larry D.; McGinty, Allan

1999-02-15T23:59:59.000Z

75

Jim Stock | Department of Energy  

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

Jim Stock Jim Stock About Us Jim Stock - Member - White House Council of Economic Advisers James H. Stock is a member of the Council of Economic Advisers and is responsible for offering the President objective advice on the formulation of economic policy. Stock was previously the Chief Economist for the Council of Economic Advisers. He is on leave from Harvard University where he is the Harold Hitchings Burbank Professor of Political Economy in the Department of Economics, with a dual appointment in the Harvard Kennedy School. Dr. Stock served as Chair of the Harvard Economics Department from 2006 to 2009 and has been a professor at Harvard continuously since 1983, with the exception of a two-year appointment at UC Berkeley from 1990 to 1991. His research focuses on macroeconomic forecasting, monetary policy, and

76

Stocks, bonds and the  

Science Journals Connector (OSTI)

In this paper, we investigate the relative performance of stocks and bonds for various investment horizons on the French market. We use a new matched block bootstrap approach to take account of estimation risk. Furthermore, in the light of non-normality of returns, we use two different risk approaches as inputs in portfolio optimization: the traditional variance, and a downside risk measure, the semi-variance. Our results suggest that an investor should avoid bonds in the long run due to the time diversification effect.

Gilles Sanfilippo

2003-01-01T23:59:59.000Z

77

EQUUS Total Return Inc | Open Energy Information  

Open Energy Info (EERE)

EQUUS Total Return Inc EQUUS Total Return Inc 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 managed by MCC Global NV, a Frankfurt stock exchange listed management and merchant banking group. Coordinates 29.76045°, -95.369784° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":29.76045,"lon":-95.369784,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

78

Table 38. Coal Stocks at Coke Plants by Census Division  

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

Coal Stocks at Coke Plants by Census Division Coal Stocks at Coke Plants by Census Division (thousand short tons) U.S. Energy Information Administration | Quarterly Coal Report, April - June 2013 Table 38. Coal Stocks at Coke Plants by Census Division (thousand short tons) U.S. Energy Information Administration | Quarterly Coal Report, April - June 2013 Census Division June 30, 2013 March 31, 2013 June 30, 2012 Percent Change (June 30) 2013 versus 2012 Middle Atlantic w w w w East North Central 1,313 1,177 1,326 -1.0 South Atlantic w w w w East South Central w w w w U.S. Total 2,500 2,207 2,295 8.9 w = Data withheld to avoid disclosure. Note: Total may not equal sum of components because of independent rounding. Source: U.S. Energy Information Administration (EIA), Form EIA-5, 'Quarterly Coal Consumption and Quality Report - Coke Plants.'

79

On the performance of the base-stock inventory system under a compound Erlang demand distribution  

Science Journals Connector (OSTI)

Abstract In this paper, we propose a new method for determining the optimal base-stock level in a single echelon inventory system where the demand is a compound Erlang process and the lead-time is constant. The demand inter-arrival follows an Erlang distribution and the demand size follows a Gamma distribution. The stock is controlled according to a continuous review base-stock policy where unfilled demands are backordered. The optimal base-stock level is derived based on a minimization of the total expected inventory cost. A numerical investigation is conducted to analyze the performance of the inventory system with respect to the different system parameters and also to show the outperformance of the approach that is based on the compound Erlang demand assumption as compared to the classical Newsboy approach. This work allows insights to be gained on stock control related issues for both slow and fast moving stock keeping units.

S. Saidane; M.Z. Babai; M.S. Aguir; O. Korbaa

2013-01-01T23:59:59.000Z

80

Towards a Very Low Energy Building Stock: Modeling the US Commercial Building Sector  

E-Print Network [OSTI]

area and energy use intensity by fuel type and end use), based on historical data and user-defined scenarios for future projections. In addition to supporting the interactive exploration of building stock targeting very low future energy consumption in the building stock. Model use has highlighted the scale

Note: This page contains sample records for the topic "type total stocks" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


81

Standing crop dynamics under simulated short-duration grazing at four stocking rates  

E-Print Network [OSTI]

separation for stocking rate main factor for total forage during 1982, averaged across replications and grazing cycles. 86 Table 40. Statistical model and alpha significance probabilities for the percentages of organic matter (OM), crude protein (CP...

Casco, Jose Francisco

2012-06-07T23:59:59.000Z

82

Quantum Brownian motion model for stock markets  

E-Print Network [OSTI]

We investigate the relevance between quantum open systems and stock markets. A Quantum Brownian motion model is proposed for studying the interaction between the Brownian system and the reservoir, i.e., the stock index and the entire stock market. Based on the model, we investigate the Shanghai Stock Exchange of China from perspective of quantum statistics, and thereby examine the behaviors of the stock index violating the efficient market hypothesis, such as fat-tail phenomena and non-Markovian features. Our interdisciplinary works thus help to discovery the underlying quantum characteristics of stock markets and develop new research fields of econophysics.

Meng, Xiangyi; Guo, Hong

2014-01-01T23:59:59.000Z

83

Stocking Rate: The Key Grazing Management Decision  

E-Print Network [OSTI]

Stocking rate is the most important grazing management decision a rancher makes. This publication covers all the factors involved in determining an appropriate stocking rate, including rainfall and forage production, range condition, and the forage...

Lyons, Robert K.; Machen, Richard V.

2001-07-19T23:59:59.000Z

84

Privacy Threats in Online Stock Quotes  

Science Journals Connector (OSTI)

Stock traders reveal information about their pending trades by their selection of stock performance data to retrieve from the web. Potentially malicious quote publishers have access to this information, and ca...

Peter Williams

2008-01-01T23:59:59.000Z

85

Essays on macroeconomic risks and stock prices  

E-Print Network [OSTI]

In this thesis, I study the relationship between macroeconomic risks and asset prices. In the first chapter, I establish that inflation risk is priced in the cross-section of stock returns: stocks that have low returns ...

Duarte, Fernando Manuel

2011-01-01T23:59:59.000Z

86

Islamic Finance Bulletin Conventional Stock Markets 2  

E-Print Network [OSTI]

by about 6 percent. There were signs of revival in the Tunisian economy after Qatar extended a USD 1- lar increased from oil importers, and as #12;StockMarkets Table 2: Evolution of Islamic Stock Markets

Meju, Max

87

Outlook of the World Steel Cycle Based on the Stock and Flow Dynamics  

Science Journals Connector (OSTI)

The material flows are dependent on various factors, such as economic parameters (GDP, metal price, energy price, etc.) and technological restrictions (ore grade, energy intensity, etc.) (7). ... Compared with eq 9, the variable t is replaced with per capita GDP, and stock is handled in per capita values as well (therefore, here Ssat, which denotes total stock, was replaced with ssat, which denotes per capita stock). ... that the world demand for iron ore (primary iron) depends not on the vol. of GDP but on the variation of GDP, as already reported. ...

Hiroki Hatayama; Ichiro Daigo; Yasunari Matsuno; Yoshihiro Adachi

2010-07-22T23:59:59.000Z

88

The effects of stocking density on two Tilapia species raised in an intensive culture system  

E-Print Network [OSTI]

. , SUNY College of Environmental Science and Forestry Chairman of Advisory Committee: Dr. Robert R. Stickney ~Tile ia auras and T. mossambica fry were stocked in a flowing system at varying stocking densities (5, 10, 20, 30, 40, 50, and 60 fish/tank... in 60 liters of water) in an intensive tank culture system. The fish were maintained for 101 days on commercial pelleted feed. In terms of length increase, weight gain, condition, total yi. eld, and food conversion rates, T. sures performed...

Henderson-Arzapalo, Anne

1979-01-01T23:59:59.000Z

89

Moving Toward the Circular Economy: The Role of Stocks in the Chinese Steel Cycle  

Science Journals Connector (OSTI)

(15, 16) Another common approach is to correlate the flows of steel consumption to external GDP projections, e.g., in the World Energy Model(17) or as in a publication by Das and Kandpal. ... Future demand for the total in-use stock S1(t) is determined by multiplying population estimates P(t) with a scenario-specific set of per-capita stocks ci(t) for all product categories: ...

Stefan Pauliuk; Tao Wang; Daniel B. Müller

2011-11-17T23:59:59.000Z

90

Low Stocks Mean Tight Markets  

Gasoline and Diesel Fuel Update (EIA)

6 6 Notes: Like those for other petroleum products, gasoline inventories have been running below normal. As of the latest weekly data, stocks are about 5% lower than the low end of the normal range for this time of year. Behind all of the low product inventories are low crude oil inventories. Recall that the crude market tightened in 1999 when OPEC cut back production. Demand was greater than supply and inventories were used to make up the difference. They have not yet recovered. Crude oil inventories are running about 7% below the low end of the normal range for this time of year. After last week's very large stock draw, it appears inventories are the lowest that they have been since December 1975. The U.S. inventory data will be an important price barometer to

91

Determination of Total Biodiesel Fatty Acid Methyl, Ethyl Esters, and Hydrocarbon Types in Diesel Fuels by Supercritical Fluid Chromatography-Flame Ionization Detection  

Science Journals Connector (OSTI)

......Research and Engineering, Paulsboro...determining total biodiesel methyl and...in diesel fuels by supercritical...mixture. Introduction The proposed use of biodiesel esters derived...as diesel fuel blending...of Total Biodiesel Fatty Acid...in Diesel Fuels by Supercritical...Research and Engineering, Paulsboro......

John W. Diehl; Frank P. DiSanzo

92

TOTAL Full-TOTAL Full-  

E-Print Network [OSTI]

Conducting - Orchestral 6 . . 6 5 1 . 6 5 . . 5 Conducting - Wind Ensemble 3 . . 3 2 . . 2 . 1 . 1 Early- X TOTAL Full- Part- X TOTAL Alternative Energy 6 . . 6 11 . . 11 13 2 . 15 Biomedical Engineering 52 English 71 . 4 75 70 . 4 74 72 . 3 75 Geosciences 9 . 1 10 15 . . 15 19 . . 19 History 37 1 2 40 28 3 3 34

Portman, Douglas

93

Distillate Stocks Expected to Remain Low  

Gasoline and Diesel Fuel Update (EIA)

5 5 Notes: When EIA's demand forecast is combined with its outlook for production and net imports, distillate stocks are projected to remain low for the rest of the year. - Stocks are beginning at very low levels. The September 1 distillate fuel stock level (112 million barrels) is nearly 20% less than last year, and about 15% below the 10 year average for end of August levels. - But stocks on the East Coast, at 39.8 million barrels, are 39% behind year-ago levels, and about a similar percentage below end-of-August 10-year average levels. Over the last 10 years, the average stock build from the end of August through the end of November has been about 10 million barrels. We are forecasting about a 12 million barrel build, which does not reach the normal band. Forecast stocks peak at the end of November at 127 million

94

Shandong Jinjing Science Technology Stock Co Ltd | Open Energy Information  

Open Energy Info (EERE)

Shandong Jinjing Science Technology Stock Co Ltd Shandong Jinjing Science Technology Stock Co Ltd Jump to: navigation, search Name Shandong Jinjing Science & Technology Stock Co Ltd Place Zibo, Shandong Province, China Zip 255200 Sector Solar Product Zibo-based glass producer. The firm makes low-iron super white glass for use in solar modules. Coordinates 36.799999°, 118.050003° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":36.799999,"lon":118.050003,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

95

Determination of Total Biodiesel Fatty Acid Methyl, Ethyl Esters, and Hydrocarbon Types in Diesel Fuels by Supercritical Fluid Chromatography-Flame Ionization Detection  

Science Journals Connector (OSTI)

......Determination of Total Biodiesel Fatty Acid Methyl...vortex mixer. This process produced solutions ranging...D5186 indicated that the biodiesel esters were not eluted...0%. For further evaluation, the quantitative analysis...determination of the biodiesel ester components by......

John W. Diehl; Frank P. DiSanzo

96

Bachelor Project StockHome -Web Application  

E-Print Network [OSTI]

Bachelor Project StockHome - Web Application User interface for a financial analysis tool Gilad and assisting us during dark times. Last but not least, I would like to thank my friends who spent those long . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 iii #12;Gilad Geron StockHome - Web Application A Technologies 31 A.1 Ruby

Lanza, Michele

97

TRAWLING AND THE STOCKS OF FISH  

Science Journals Connector (OSTI)

... before the Royal Society of Arts on January 27 on “Trawling and the Stocks of Fish”, Dr. E. S. Russell, director of fishery investigations, Ministry of Agriculture ... manner the problems which will confront us after the War in connexion with the national fish stocks of Great Britain and those of our near neighbours. In a summary of ...

1943-03-20T23:59:59.000Z

98

Systematic analysis of group identification in stock markets  

Science Journals Connector (OSTI)

We propose improved methods to identify stock groups using the correlation matrix of stock price changes. By filtering out the marketwide effect and the random noise, we construct the correlation matrix of stock groups in which nontrivial high correlations between stocks are found. Using the filtered correlation matrix, we successfully identify the multiple stock groups without any extra knowledge of the stocks by the optimization of the matrix representation and the percolation approach to the correlation-based network of stocks. These methods drastically reduce the ambiguities while finding stock groups using the eigenvectors of the correlation matrix.

Dong-Hee Kim and Hawoong Jeong

2005-10-25T23:59:59.000Z

99

Wuhan Linuo Solar Energy Group Stock Co Ltd | Open Energy Information  

Open Energy Info (EERE)

Solar Energy Group Stock Co Ltd Solar Energy Group Stock Co Ltd Jump to: navigation, search Name Wuhan Linuo Solar Energy Group Stock Co Ltd Place Wuhan, Hubei Province, China Zip 430015 Sector Solar Product String representation "Develop, manufa ... istry painting." is too long. Coordinates 30.572399°, 114.279121° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":30.572399,"lon":114.279121,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

100

Time-phased safety stocks planning and its financial impacts: Empirical evidence based on European econometric data  

Science Journals Connector (OSTI)

Abstract This paper explores the rationale for planning time-phased safety stocks. We assert that a single safety stock vector for the entire planning horizon (typically based on stationary demand forecast errors and stationary replenishment lead times) may be insufficient for hedging against uncertainties. We argue that planning time-phased safety stocks is prudent when faced with non-stationary demand and/or non-stationary supply. We scrutinize particularly whenever non-stationarity is due to heteroscedastic demand and resulting heteroscedastic demand forecast errors. Consequently, an empirical evidence on a wide basis is provided that such errors for manufactured products are highly heteroscedastic. To test the phenomenon and to estimate its impact at stock keeping unit level, we have conducted an econometric analysis using the EUROSTAT data from 1985 onwards. Specifically, we analyze new industrial orders across various industries and types of goods manufactured in the five largest European economies by using \\{EViews\\} 7.0. To demonstrate which inventory savings can accrue when safety stock levels are deliberately planned to vary in accordance with the observed heteroscedasticity, we estimate potential safety stock savings reusing the same data sets. Our findings indicate that one realization of non-stationarity, i.e., heteroscedastic demand, is indeed pervasive in the European industry. Thus, recognition of this demand nature may add to effective inventory management policies: reducing unnecessary safety stocks, improving service, or both relative to a single-valued safety stock regimen.

Martin Stößlein; John Jack Kanet; Mike Gorman; Stefan Minner

2014-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "type total stocks" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


101

Political Risk and Stock Market Development  

Science Journals Connector (OSTI)

This article examines empirically the relationship between political instability and stock market development in a small capital market (the Greek capital market). We measure socio-political instability by con...

Costas Siriopoulos; Dimitrios Asteriou

1998-01-01T23:59:59.000Z

102

Credit Conditions and Stock Return Predictability  

E-Print Network [OSTI]

This dissertation examines stock return predictability with aggregate credit conditions. The aggregate credit conditions are empirically measured by credit standards (Standards) derived from the Federal Reserve Board's Senior Loan Officer Opinion...

Park, Heungju

2012-10-19T23:59:59.000Z

103

Skewness in individual stocks at different investment  

Science Journals Connector (OSTI)

This paper examines the (a)symmetry of several individual stock returns at different investment horizons: daily, weekly and monthly. While some asymmetries are observed in daily returns, they disappear almost completely in weekly and monthly returns. The explanation for this fact lies in the convergence to normality that takes place when the investment horizon increases. These features allow one to question several financial models; in particular, they question the preference for positive skewness as a factor for investments in stock markets.

Amado Peiró

2002-01-01T23:59:59.000Z

104

An evaluation of total body electrical conductivity to estimate body composition of largemouth bass  

E-Print Network [OSTI]

Information about body composition of fish is important for the assessment and management of fish stocks. Measurement of total body electrical conductivity (TOBEC) recently has been used to estimate the body composition of several fish species in a...

Barziza, Daniel Eugene

2012-06-07T23:59:59.000Z

105

Naphthenic/paraffinic hydrocarbons of residual lube stock from West Siberian crudes  

SciTech Connect (OSTI)

The lube stocks from West Siberian crudes are characterized by high contents of aromatic hydrocarbons and by high viscosity indexes of the naphthenic/paraffinic and aromatic hydrocarbons. Mass spectrometric analysis showed that isoparaffins account for one-third of the total naphthenic/paraffinic hydrocarbons. The study showed that the naphthenic/paraffinic hydrocarbons of the residual lube stock from West Siberia crudes, even with a variation of molecular weight over broad limits, are relatively uniform in composition. They consist mainly of isoparaffinic and monocyclic and noncondensed naphthenic structures.

Detusheva, E.P.; Bogdanov, Sh.K.; Khramtsova, L.P.; Nekrasova, A.V.; Shkol'nikov, V.M.

1983-03-01T23:59:59.000Z

106

Total Petroleum Systems and Assessment Units (AU)  

E-Print Network [OSTI]

Total Petroleum Systems (TPS) and Assessment Units (AU) Field type Surface water Groundwater X X X X X X X X AU 00000003 Oil/ Gas X X X X X X X X Total X X X X X X X Total Petroleum Systems (TPS) and Assessment Units (AU) Field type Total undiscovered petroleum (MMBO or BCFG) Water per oil

Torgersen, Christian

107

Contractor: Contract Number: Contract Type: Total Estimated  

Energy Savers [EERE]

Services Support Contract Fee Information Contract Period: Cost Plus Award Fee 3,311,479,516 September 2014 May 2009 - May 2019 Mission Support Alliance, LLC DE-AC06-09RL14728...

108

U.S. Crude Oil Stocks  

Gasoline and Diesel Fuel Update (EIA)

5 5 Notes: U.S. crude oil stocks stood at about 289 million barrels on September 8, according to EIA's latest survey. This puts them about 24 million barrels below the level seen at the same time last year. Current market conditions do not suggest much improvement in the near term. We probably ended last month (August 2000) with the lowest level for end-of-August crude oil stocks (289 million barrels) in the United States since 1976, when crude oil inputs to refineries were about 2 million barrels per day less than today. However, by EIA data, we have seen (at least slightly) lower crude stocks in recent months, including an end-December 1999 level of 284 million barrels. The American Petroleum Institute (API), which also surveys petroleum supply and demand

109

Production smoothing and buffer stock reduction for two-stage production and inventory systems  

Science Journals Connector (OSTI)

This paper deals with the problem of developing an effective push-type ordering system which can decrease the variations of production ordering and inventory levels, while taking into account forecasted error, the difference between forecasted values and the backlog quantity, in which the shortage of safety stock of component parts causes a discrepancy between production ordering and actual production levels. The ordering system is developed on the basis of an idea which combines safety stock and the weight of the feedback quantity of actual and forecasted term-end inventory levels. Some results of numerical analysis show the effects of safety stock of the component parts and the feedback control parameter of each production stage, the autocorrelation coefficient of product demand upon the amplifications of production ordering and inventory levels.

Kazuyoshi Ishii; Shusaku Hiraki

2000-01-01T23:59:59.000Z

110

Summary Max Total Units  

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

Max Total Units 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 Refrig Voltage Cond Unit IF-CU Combos 2 4 5 28 References Refrig Voltage C-U type Compressor HP R-404A 208/1/60 Hermetic SA 2.5 R-507 230/1/60 Hermetic MA 2.5 208/3/60 SemiHerm SA 1.5 230/3/60 SemiHerm MA 1.5 SemiHerm HA 1.5 1000lb, remote rack systems, fresh water Refrig/system Voltage Combos 12 2 24 References Refrig/system Voltage IF only

111

Supply/Demand Forecasts Begin to Show Stock Rebuilding  

Gasoline and Diesel Fuel Update (EIA)

9 9 Notes: During 1999, we saw stock draws during the summer months, when we normally see stock builds, and very large stock draws during the winter of 1999/2000. Normally, crude oil production exceeds product demand in the spring and summer, and stocks build. These stocks are subsequently drawn down during the fourth and first quarters (dark blue areas). When the market is in balance, the stock builds equal the draws. During 2000, stocks have gradually built, but following the large stock draws of 1999, inventories needed to have been built more to get back to normal levels. As we look ahead using EIA's base case assumptions for OPEC production, non-OPEC production, and demand, we expect a more seasonal pattern for the next 3 quarters. But since we are beginning the year with

112

Rangeland Drought Management for Texans: Stocking Rate and Grazing Management  

E-Print Network [OSTI]

This publication explains how stocking rates and grazing management decisions can help a ranch survive a drought. To deal with drought, a rancher must monitor forage supply and demand; use a conservative stocking rate and keep it flexible...

Hart, Charles R.; Carpenter, Bruce B.

2001-05-03T23:59:59.000Z

113

Predicting stock returns and assessing prediction performance  

Science Journals Connector (OSTI)

......found that in the USA, 47% of investments were made by households with an average annual turnover of over 75% of stocks held...effects in data from the USA, the UK, France, Germany and Japan, and conclude that data snooping is not a major problem......

Rose Baker; Alexander Belgorodskiy

2007-10-01T23:59:59.000Z

114

Wild oil prices, but brave stock markets! The case of GCC stock markets  

Science Journals Connector (OSTI)

Using a vector autoregression (VAR) analysis, this paper investigates the effect of the sharp increase in oil prices on stock market returns for five Gulf ... to 24 May, 2005. During this period oil price has bee...

Bashar Abu Zarour

115

Market Maker Inventories and Stock Prices Terrence Hendershott  

E-Print Network [OSTI]

complement past returns when predicting return reversals. A portfolio long high-inventory/low-return stocks and short low-inventory/high-return stocks yields 1.05% over the following 5 days. Order imbalancesMarket Maker Inventories and Stock Prices Terrence Hendershott U.C. Berkeley Mark S. Seasholes U

Kearns, Michael

116

Assessment of the eel stock in Sweden, spring 2012  

E-Print Network [OSTI]

Assessment of the eel stock in Sweden, spring 2012 Aqua reports 2012:9 First post-evaluation of the Swedish Eel Management Plan Willem Dekker #12;Assessment of the eel stock in Sweden, spring 2012 First: Dekker, W. (2012). Assessment of the eel stock in Sweden, spring 2012. First post

117

Compare All CBECS Activities: Total Energy Use  

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

Total Energy Use Total Energy Use Compare Activities by ... Total Energy Use Total Major Fuel Consumption by Building Type Commercial buildings in the U.S. used a total of approximately 5.7 quadrillion Btu of all major fuels (electricity, natural gas, fuel oil, and district steam or hot water) in 1999. Office buildings used the most total energy of all the building types, which was not a surprise since they were the most common commercial building type and had an above average energy intensity. Figure showing total major fuel consumption by building type. If you need assistance viewing this page, please call 202-586-8800. Major Fuel Consumption per Building by Building Type Because there were relatively few inpatient health care buildings and they tend to be large, energy intensive buildings, their energy consumption per building was far above that of any other building type.

118

Barge Truck Total  

Annual Energy Outlook 2013 [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...

119

Oil price shocks and stock market returns: New evidence from the United States and China  

Science Journals Connector (OSTI)

Abstract This study examines the time-varying correlations between oil prices shocks of different types (supply-side, aggregate demand and oil-market specific demand as per Kilian (2009) who highlighted that “Not all oil shocks are alike”) and stock market returns, using a Scalar-BEKK model. For this study we consider the aggregate stock market indices from two countries, China and the US, reflecting the most important developing and developed financial markets in the world. In addition to the whole market, we also consider correlations from key selected industrial sectors, namely Metals & Mining, Oil & Gas, Retail, Technology and Banking. The sample period runs from 1995 until 2013. We highlight several key points: (i) correlations between oil price shocks and stock returns are clearly and systematically time-varying; (ii) oil shocks of different types show substantial variation in their impact upon stock market returns; (iii) these effects differ widely across industrial sectors; and finally (iv) China is seemingly more resilient to oil price shocks than the US.

David C. Broadstock; George Filis

2014-01-01T23:59:59.000Z

120

Tebian Electric Apparatus Stock Co Ltd TBEA | Open Energy Information  

Open Energy Info (EERE)

Tebian Electric Apparatus Stock Co Ltd TBEA Tebian Electric Apparatus Stock Co Ltd TBEA Jump to: navigation, search Name Tebian Electric Apparatus Stock Co Ltd (TBEA) Place Changji, Xinjiang Autonomous Region, China Zip 831100 Sector Solar Product TBEA makes transformer products and aluminium foil, and also solar energy equipment. References Tebian Electric Apparatus Stock Co Ltd (TBEA)[1] LinkedIn Connections CrunchBase Profile No CrunchBase profile. Create one now! This article is a stub. You can help OpenEI by expanding it. Tebian Electric Apparatus Stock Co Ltd (TBEA) is a company located in Changji, Xinjiang Autonomous Region, China . References ↑ "Tebian Electric Apparatus Stock Co Ltd (TBEA)" Retrieved from "http://en.openei.org/w/index.php?title=Tebian_Electric_Apparatus_Stock_Co_Ltd_TBEA&oldid=352059

Note: This page contains sample records for the topic "type total stocks" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


121

Proposed Fidelity Option Line-Up Tier Fund Type Fund Category/Asset Class Proposed Investment Option  

E-Print Network [OSTI]

Proposed Fidelity Option Line-Up Tier Fund Type Fund Category/Asset Class Proposed Investment Vanguard Inflation Protected Securities U.S. Large Cap Stock Index Fund Vanguard S&P 500 Index Fund U.S. Small/Mid Cap Stock Index Fund Vanguard Extended Market Index Fund International Stock Index Fund

122

NATIONAL ENERGY POLICY Taking Stock A  

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

Taking Stock Taking Stock A merica's current energy challeng- es can be met with rapidly im- proving technology, dedicated leadership, and a comprehensive approach to our energy needs. Our challenge is clear-we must use tech- nology to reduce demand for energy, re- pair and maintain our energy infrastruc- ture, and increase energy supply. Today, the United States remains the world's undisput- ed technological leader; but recent events have demonstrated that we have yet to inte- grate 21st-century technology into an ener- gy plan that is focused on wise energy use, production, efficiency, and conservation. Prices today for gasoline, heating oil, and natural gas are dramatically higher than they were only a year ago. In Califor- nia, homeowners, farmers, and businesses face soaring electricity prices, rolling

123

Transfer Entropy Analysis of the Stock Market  

E-Print Network [OSTI]

In terms of transfer entropy, we investigated the strength and the direction of information transfer in the US stock market. Through the directionality of the information transfer, the more influential company between the correlated ones can be found and also the market leading companies are selected. Our entropy analysis shows that the companies related with energy industries such as oil, gas, and electricity influence the whole market.

Baek, S K; Kwon, O; Moon, H T; Baek, Seung Ki; Jung, Woo-Sung; Kwon, Okyu; Moon, Hie-Tae

2005-01-01T23:59:59.000Z

124

total energy | OpenEI  

Open Energy Info (EERE)

total energy total energy Dataset Summary Description This dataset comes from the Energy Information Administration (EIA), and is part of the 2011 Annual Energy Outlook Report (AEO2011). This dataset is table 1, and contains only the reference case. The dataset uses quadrillion BTUs, and quantifies the energy prices using U.S. dollars. The data is broken down into total production, imports, exports, consumption, and prices for energy types. Source EIA Date Released April 26th, 2011 (3 years ago) Date Updated Unknown Keywords 2011 AEO consumption EIA export import production reference case total energy Data application/vnd.ms-excel icon AEO2011: Total Energy Supply, Disposition, and Price Summary - Reference Case (xls, 112.8 KiB) Quality Metrics Level of Review Peer Reviewed

125

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

SciTech Connect (OSTI)

This paper describes the origin, structure and continuing development of a model of time varying energy consumption in the US commercial building stock. The model is based on a flexible structure that disaggregates the stock into various categories (e.g. by building type, climate, vintage and life-cycle stage) and assigns attributes to each of these (e.g. floor area and energy use intensity by fuel type and end use), based on historical data and user-defined scenarios for future projections. In addition to supporting the interactive exploration of building stock dynamics, the model has been used to study the likely outcomes of specific policy and innovation scenarios targeting very low future energy consumption in the building stock. Model use has highlighted the scale of the challenge of meeting targets stated by various government and professional bodies, and the importance of considering both new construction and existing buildings.

Coffey, Brian; Borgeson, Sam; Selkowitz, Stephen; Apte, Josh; Mathew, Paul; Haves, Philip

2009-07-01T23:59:59.000Z

126

Last-Minute Energy Saving Stocking Stuffers | Department of Energy  

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

Last-Minute Energy Saving Stocking Stuffers Last-Minute Energy Saving Stocking Stuffers Last-Minute Energy Saving Stocking Stuffers December 23, 2013 - 12:13pm Addthis There are all sorts of small energy-efficient presents available for stuffing stockings this year. | Photo courtesy of ©iStockphoto.com/DNY59 There are all sorts of small energy-efficient presents available for stuffing stockings this year. | Photo courtesy of ©iStockphoto.com/DNY59 Christina Stowers Communications Specialist in the Office of Weatherization and Intergovernmental Program How can I participate? Keep an eye out for these small, energy saving gifts as you do your last minute shopping this year. Looking for some last minute stocking stuffers to complement the holiday gifts you've purchased for your loved ones? We covered a few

127

Low Distillate Stocks Set Stage for Price Volatility  

Gasoline and Diesel Fuel Update (EIA)

Along with the recent rise in crude oil prices, low stocks of Along with the recent rise in crude oil prices, low stocks of distillate fuels left markets in a vulnerable position. As we went into our two biggest distillate demand months, January and February, U.S. distillate stocks were very low -- particularly on the East and Gulf Coasts. The East Coast is the primary heating oil region, and it depends heavily on production from the Gulf Coast as well. Distillate stocks in the U.S. and Europe were in surplus supply as recently as October, but distillate stocks did not build as they usually do during the late fall, and declined more sharply than usual in December. December stocks closed well below the normal range. The unusual drawdown, in contrast to the more normal building pattern, resulted in distillate inventory levels about 3 million barrels lower than the very low

128

Distillate Stocks Are Important Part of Northeast Winter Supply  

Gasoline and Diesel Fuel Update (EIA)

1 of 15 1 of 15 Notes: Why do stocks matter in the Northeast? Stocks are normally an important part of PADD 1 winter distillate supply. Over the last 5 years, they provided about 15% of supply during the peak winter months of January and February. One of the biggest stock draws we have seen was in January 1994, when a prolonged severe cold spell required 666 MB/D of stocks, covering almost 36% of demand for that month. PADD 1 refineries meet about 25% of demand during January and February, and other PADDs -- mostly PADD 3 -- supply 45-50% of the regionÂ’s needs. Imports generally supply about as much as stocks during the peak months, with most of the product coming from Canada, the Virgin Islands and Venezuela. Percentages do not tell the whole story. Stocks supply close to 300

129

Status of the eel stock in Sweden in 2011  

E-Print Network [OSTI]

Status of the eel stock in Sweden in 2011 Willem Dekker Håkan Wickström Jan Andersson Aqua reports of the eel stock in Sweden in 2011 By Willem Dekker, Håkan Wickström & Jan Andersson October 2011 SLU: Dekker, W., Wickström, H. & Andersson, J. (2011). Status of the eel stock in Sweden in 2011. Aqua reports

130

Automatic stock market trading based on Technical Analysis.  

E-Print Network [OSTI]

?? The theory of technical analysis suggests that future stock price developement can be foretold by analyzing historical price fluctuations and identifying repetitive patterns. A… (more)

Larsen, Fredrik

2007-01-01T23:59:59.000Z

131

Uncertainty of forest carbon stock changes – implications to the total uncertainty of GHG inventory of Finland  

Science Journals Connector (OSTI)

Uncertainty analysis facilitates identification of the most important categories affecting greenhouse gas (GHG) inventory uncertainty and helps in prioritisation of ... . This paper presents an uncertainty analys...

S. Monni; M. Peltoniemi; T. Palosuo; A. Lehtonen; R. Mäkipää…

2007-04-01T23:59:59.000Z

132

Buildings","Total  

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

L1. Floorspace Lit by Lighting Type for Non-Mall Buildings, 1995" L1. Floorspace Lit by Lighting Type for Non-Mall Buildings, 1995" ,"Floorspace (million square feet)" ,"Total (Lit or Unlit) in All Buildings","Total (Lit or Unlit) in Buildings With Any Lighting","Lighted Area Only","Area Lit by Each Type of Light" ,,,,"Incan- descent","Standard Fluor-escent","Compact Fluor- escent","High Intensity Discharge","Halogen" "All Buildings*",54068,51570,45773,6746,34910,1161,3725,779 "Building Floorspace" "(Square Feet)" "1,001 to 5,000",6272,5718,4824,986,3767,50,22,54 "5,001 to 10,000",7299,6667,5728,1240,4341,61,169,45 "10,001 to 25,000",10829,10350,8544,1495,6442,154,553,"Q"

133

Buildings","Total  

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

L2. Floorspace Lit by Lighting Types (Non-Mall Buildings), 1999" L2. Floorspace Lit by Lighting Types (Non-Mall Buildings), 1999" ,"Floorspace (million square feet)" ,"Total (Lit or Unlit) in All Buildings","Total (Lit or Unlit) in Buildings With Any Lighting","Lighted Area Only","Area Lit by Each Type of Light" ,,,,"Incan- descent","Standard Fluor-escent","Compact Fluor- escent","High Intensity Discharge","Halogen" "All Buildings* ...............",61707,58693,49779,6496,37150,3058,5343,1913 "Building Floorspace" "(Square Feet)" "1,001 to 5,000 ...............",6750,5836,4878,757,3838,231,109,162 "5,001 to 10,000 ..............",7940,7166,5369,1044,4073,288,160,109 "10,001 to 25,000 .............",10534,9773,7783,1312,5712,358,633,232

134

Buildings","Total  

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

L3. Floorspace Lit by Lighting Type (Non-Mall Buildings), 2003" L3. Floorspace Lit by Lighting Type (Non-Mall Buildings), 2003" ,"Floorspace (million square feet)" ,"Total (Lit or Unlit) in All Buildings","Total (Lit or Unlit) in Buildings With Any Lighting","Lighted Area Only","Area Lit by Each Type of Light" ,,,,"Incan- descent","Standard Fluor-escent","Compact Fluor- escent","High Intensity Discharge","Halogen" "All Buildings* ...............",64783,62060,51342,5556,37918,4004,4950,2403 "Building Floorspace" "(Square Feet)" "1,001 to 5,000 ...............",6789,6038,4826,678,3932,206,76,124 "5,001 to 10,000 ..............",6585,6090,4974,739,3829,192,238,248 "10,001 to 25,000 .............",11535,11229,8618,1197,6525,454,506,289

135

Recent Trends in Crude Oil Stock Levels  

Gasoline and Diesel Fuel Update (EIA)

J J J J J J J J J J J J J J J J J J J J J J J J J J J J J J J J J 0 280 300 320 340 360 380 400 420 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 Average Range: 1993-1995 Recent Trends in Crude Oil Stock Levels by Aileen A. Bohn Energy Information Administration (EIA) data for March 1996 primary inventories of crude oil were the lowest recorded in almost 20 years. Crude oil inventories, which were generally on a downward trend since the beginning of 1995, fell below the average range in July 1995 and have yet to recover (Figure FE1). On September 27, 1996, crude oil stocks registered 303 million barrels, compared to a normal range of nearly 311 to 332 million barrels for September. 1 Low crude oil inventories can cause price volatility in crude oil markets. 2 When inventories are low, refiners resort to

136

Oil, economic growth and strategic petroleum stocks  

Science Journals Connector (OSTI)

Abstract An examination of over 40 years of data reveals that oil price shocks are invariably followed by 2–3 years of weak economic growth and weak economic growth is almost always preceded by an oil price shock. This paper reviews why the price-inelastic demand and supply of oil cause oil price shocks and why oil price shocks reduce economic growth through dislocations of labor and capital. This paper also reviews the current state of oil-supply security noting that previous episodes of supply instability appear to have become chronic conditions. While new unconventional oil production technologies have revitalized North American oil production, there are significant barriers to a world-wide uptake of these technologies. Strategic petroleum stocks could provide a large measure of protection to the world economy during an oil supply disruption if they are used promptly and in sufficient volume to prevent large oil-price spikes. Despite the large volume of world-wide emergency reserves, their effectiveness in protecting world economies is not assured. Strategic oil stocks have not been used in sufficient quantity or soon enough to avoid the economic downturns that followed past oil supply outages. In addition, the growth of U.S. oil production has reduced the ability of the U.S. Strategic Petroleum Reserve to protect the economy following a future oil supply disruption. The policy implications of these findings are discussed.

Carmine Difiglio

2014-01-01T23:59:59.000Z

137

Table 2. U.S. Biodiesel Production, Sales, and Stocks  

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

U.S. Biodiesel Production, Sales, and Stocks U.S. Biodiesel Production, Sales, and Stocks (million gallons) Period 2011 January 35 22 9 17 4 February 40 27 13 17 1 March 60 41 17 19 2 April 71 47 22 21 2 May 77 50 27 23 2 June 81 62 24 19 (4)

138

Fish Stocks Rainer Froese, IFM-GEOMAR, Kiel, Germany  

E-Print Network [OSTI]

Fish Stocks Rainer Froese, IFM-GEOMAR, Kiel, Germany Daniel Pauly, University of British Columbia and consisting of four elements (species names, location, time, and source). Catches The fish (or other aquatic organisms) of a given stock killed during a certain period by the operation of fishing gear. This definition

Pauly, Daniel

139

Petrale Sole Stock Assessment Review (STAR) Panel Report  

E-Print Network [OSTI]

constituted a major uncertainty in the assessment (Figure 1), as did the appropriate natural mortality ratePetrale Sole Stock Assessment Review (STAR) Panel Report Hotel Deca, Seattle, Washington 20-24 June Leipzig PFMC Groundfish Advisory Subpanel (GAP) Stock Assessment Team (STAT) Melissa Haltuch NMFS

140

UCSF FOUNDATION DONATION OF SECURITIES: STOCKS AND MUTAL FUNDS  

E-Print Network [OSTI]

-over- UCSF FOUNDATION DONATION OF SECURITIES: STOCKS AND MUTAL FUNDS GIFT TO CURRENT ACCOUNT Thank you for your interest in making a gift of stocks or mutual fund shares to the UCSF Foundation. We Foundation of your donation. Broker Instructions -- Credit to: State Street Bank & Trust, DTC #997, UCSF

Yamamoto, Keith

Note: This page contains sample records for the topic "type total stocks" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


141

UCSF FOUNDATION DONATION OF SECURITIES: STOCKS AND MUTAL FUNDS  

E-Print Network [OSTI]

-over- UCSF FOUNDATION DONATION OF SECURITIES: STOCKS AND MUTAL FUNDS GIFT TO ENDOWMENT ACCOUNT Thank you for your interest in making a gift of stocks or mutual funds shares to the UCSF Foundation. We to notify UCSF Foundation of your donation. · Broker Instructions -- Credit to: State Street Bank & Trust

Yamamoto, Keith

142

"Why Are Some Firms More Innovative? Knowledge Inputs, Knowledge Stocks,  

E-Print Network [OSTI]

"Why Are Some Firms More Innovative? Knowledge Inputs, Knowledge Stocks, and the Role of Global, Exporting, Knowledge and Technological Change Abstract Why do some firms create more knowledge than others stock of knowledge. But there is very little empirical evidence on production functions for new ideas

Sadoulet, Elisabeth

143

Detecting Stock Market Manipulation using Supervised Learning Algorithms  

E-Print Network [OSTI]

suspicious transactions in relation to market manipulation in stock market. We use a case studyDetecting Stock Market Manipulation using Supervised Learning Algorithms Koosha Golmohammadi, Osmar,Chile ddiaz@unegocios.cl Abstract-- Market manipulation remains the biggest concern of investors in today

Zaiane, Osmar R.

144

Distillate Stocks Are Important Part of East Coast Winter Supply  

Gasoline and Diesel Fuel Update (EIA)

Stocks are normally an important part of East Coast winter Stocks are normally an important part of East Coast winter distillate supply, since they are the nearest source when anything unexpected occurs, and they supply a significant portion of demand during the peak heating season. Over the last 10 years, stocks have provided about 15% of supply during the peak winter months of January and February. On average, stocks supply the East Coast with about 260 thousand barrels per day in January and 280 in February. Those supplies represent draws of about 8 million barrels in one month. In addition, East Coast refineries meet about 25% of demand during January and February, and other regions -- mostly the Gulf Coast -- supply 40-50% of the region's needs. Imports generally supply about as much as stocks during the peak

145

Recovery May Require Holding Stocks Level in February and March  

Gasoline and Diesel Fuel Update (EIA)

have dropped back as new supplies are appearing, but we still have dropped back as new supplies are appearing, but we still have nearly a month of winter ahead of us. Stocks cannot drop much farther. February 4 stock levels were just above the lowest month-end levels ever seen for PADD 1, which occurred in April 1996. For stocks to recover to the low end of the normal range, they would have to stay level in February in March, when normally they would be used to meet demand. Keeping stocks level would require finding supply to substitute for the average stock drops of 290 thousand barrels per day (8 million barrels) in February and 210 thousand barrels per day (6 million barrels) in March. If all of that supply were to come from imports, we would have to see distillate imports into PADD 1 double from their average levels of 7

146

Distillate Stocks Are Important Part of East Coast Winter Supply  

Gasoline and Diesel Fuel Update (EIA)

5 5 Notes: Stocks are important in the Northeast because they are the nearest source of supply when anything unexpected occurs, and they supply a significant portion of demand during the peak heating season. Stocks are normally an important part of East Coast winter distillate supply. Over the last 10 years, they provided about 15% of supply during the peak winter months of January and February. One of the biggest stock draws we have seen was in January 1994, when a prolonged severe cold spell required 666,000 barrels per day of stocks, covering almost 36% of demand for that month. On average, stocks supply the East Coast with about 260,000 barrels per day on average in January and 280,000 barrels per day in February. Those supplies represent draws of about 8 million barrels in one month.

147

Distillate Stocks Are Important Part of East Coast Winter Supply  

Gasoline and Diesel Fuel Update (EIA)

8 8 Notes: Why do stocks matter in the Northeast? They are the nearest source of supply when anything unexpected occurs, and they supply a significant portion of demand during the peak heating season. Stocks are normally an important part of PADD 1 winter distillate supply. Over the last 10 years, they provided about 15% of supply during the peak winter months of January and February. One of the biggest stock draws we have seen was in January 1994, when a prolonged severe cold spell required 666 MB/D of stocks, covering almost 36% of demand for that month. Stocks supply the East Coast with about 260 MB/D on average in January and 280 MB/D in February. Those supplies represent draws of about 8 million barrels in one month. PADD 1 refineries meet about 25% of demand during January and

148

Distillate Stocks Are Important Part of Northeast Winter Supply  

Gasoline and Diesel Fuel Update (EIA)

The weather alone was not enough to cause the price spike. The low The weather alone was not enough to cause the price spike. The low stocks left the area vulnerable to sudden changes in the market, such as the weather change. Why do stocks matter in the Northeast? Stocks are normally an important part of PADD 1 winter distillate supply. Over the last 5 years, PADD 1 stocks provided about 15% of supply during the peak winter months of January and February. They are the closest source of supply to the consumer. PADD 1 depends on about 60% of its supply from distant sources such as the Gulf Coast or imports, which can take several weeks to travel to the Northeast. Even product from East Coast refineries, if capacity is available, may take a week before it is produced and delivered to the regions needing new supply. Thus, stocks must be able

149

On the stock control performance of intermittent demand estimators  

Science Journals Connector (OSTI)

The purpose of this paper is to assess the empirical stock control performance of intermittent demand estimation procedures. The forecasting methods considered are the simple moving average, single exponential smoothing, Croston's method and a new method recently developed by the authors of this paper. We first discuss the nature of the empirical demand data set (3000 stock keeping units) and we specify the stock control model to be used for experimentation purposes. Performance measures are then selected to report customer service level and stock volume differences. The out-of-sample empirical comparison results demonstrate the superior stock control performance of the new intermittent demand forecasting method and enable insights to be gained into the empirical utility of the other estimators.

Aris A. Syntetos; John E. Boylan

2006-01-01T23:59:59.000Z

150

Variations of Total Domination  

Science Journals Connector (OSTI)

The study of locating–dominating sets in graphs was pioneered by Slater [186, 187...], and this concept was later extended to total domination in graphs. A locating–total dominating set, abbreviated LTD-set, in G

Michael A. Henning; Anders Yeo

2013-01-01T23:59:59.000Z

151

,"U.S. Refinery, Bulk Terminal, and Natural Gas Plant Stocks...  

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

Stocks at Refineries, Bulk Terminals, and Natural Gas Plants (Thousand Barrels)","U.S. Gasoline Blending Components Stocks at Refineries, Bulk Terminals, and Natural Gas Plants...

152

Total Crude by Pipeline  

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

Product: Total Crude by All Transport Methods Domestic Crude by All Transport Methods Foreign Crude by All Transport Methods Total Crude by Pipeline Domestic Crude by Pipeline Foreign Crude by Pipeline Total Crude by Tanker Domestic Crude by Tanker Foreign Crude by Tanker Total Crude by Barge Domestic Crude by Barge Foreign Crude by Barge Total Crude by Tank Cars (Rail) Domestic Crude by Tank Cars (Rail) Foreign Crude by Tank Cars (Rail) Total Crude by Trucks Domestic Crude by Trucks Foreign Crude by Trucks Period: Product: Total Crude by All Transport Methods Domestic Crude by All Transport Methods Foreign Crude by All Transport Methods Total Crude by Pipeline Domestic Crude by Pipeline Foreign Crude by Pipeline Total Crude by Tanker Domestic Crude by Tanker Foreign Crude by Tanker Total Crude by Barge Domestic Crude by Barge Foreign Crude by Barge Total Crude by Tank Cars (Rail) Domestic Crude by Tank Cars (Rail) Foreign Crude by Tank Cars (Rail) Total Crude by Trucks Domestic Crude by Trucks Foreign Crude by Trucks Period: Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: Product Area 2007 2008 2009 2010 2011 2012 View

153

Modeling Metal Stocks and Flows: A Review of Dynamic Material Flow Analysis Methods  

Science Journals Connector (OSTI)

Remote sensing methods are used by Takahashi et al.,(86) who analyze in-use copper stocks using satellite nighttime light observation data. ... McMillan et al.(54) quantify the sensitivity of the lifetime distribution, recycling rate, and metallic recovery by using the Fourier Amplitude Sensitivity Test method, which provides a measure of input sensitivity defined as the fraction of total model variance. ... Yano, J.; Hirai, Y.; Okamoto, K.; Sakai, S.Dynamic flow analysis of current and future end-of-life vehicles generation and lead content in automobile shredder residue J. Mater. ...

Esther Müller; Lorenz M. Hilty; Rolf Widmer; Mathias Schluep; Martin Faulstich

2014-01-17T23:59:59.000Z

154

Total Space Heat-  

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

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...

155

Weblog Analysis for Predicting Correlations in Stock Price Evolutions Milad Kharratzadeh1  

E-Print Network [OSTI]

method which combines information from the weblog data and histor- ical stock prices. Through simulation strategies based on company sec- tors or historical stock prices. This suggests that the method- ology has evolution of stock prices and whether this is complementary to the information embedded in historical stock

Coates, Mark

156

Trading Puts and CDS on Stocks with Short Sale Ban Sophie Xiaoyan Ni and Jun Pan  

E-Print Network [OSTI]

not perform differently from the middle group. Within the sample of banned stocks with CDS traded and using in banned stocks and the trading of options and CDS. Within the sample of banned stocks with exchange traded options, stocks whose put-call ratios are in the top quintile underperform the middle group by 2.13% and 4

Gabrieli, John

157

Distillate Stocks Are Important Part of East Coast Winter Supply  

Gasoline and Diesel Fuel Update (EIA)

7 7 Notes: Stocks are normally an important part of East Coast winter distillate supply, since they are the nearest source when anything unexpected occurs, and they supply a significant portion of demand during the peak heating season. Over the last 10 years, stocks have provided about 15% of supply during the peak winter months of January and February. On average, stocks supply the East Coast with about 260 MB/D in January and 280 MB/D in February. Those supplies represent draws of about 8 million barrels in one month. In addition, East Coast refineries meet about 25% of demand during January and February, and other regions -- mostly the Gulf Coast -- supply 40-50% of the region's needs. Imports generally supply about as much as stocks during the peak months,

158

Distillate Stocks Are Important Part of East Coast Winter Supply  

Gasoline and Diesel Fuel Update (EIA)

6 6 Notes: Stocks are normally an important part of East Coast winter distillate supply, since they are the nearest source when anything unexpected occurs, and they supply a significant portion of demand during the peak heating season. Over the last 10 years, stocks have provided about 15% of supply during the peak winter months of January and February. On average, stocks supply the East Coast with about 260 thousand barrels per day in January and 280 in February. Those supplies represent draws of about 8 million barrels in one month. In addition, East Coast refineries meet about 25% of demand during January and February, and other regions -- mostly the Gulf Coast -- supply 40-50% of the region's needs. Imports generally supply about as much as stocks during the peak

159

PADD 1 (East Coast) Heating Oil Stocks Low  

Gasoline and Diesel Fuel Update (EIA)

5 5 Notes: The East Coast (PADD 1) is the primary heating oil region, and it depends heavily on production from the Gulf Coast (PADD 3) as well. The biggest decline in U.S. stocks has taken place in the heating oil markets of PADD 1 (East Coast), which consumed 86 percent of the nationÂ’s heating oil in 1998. It also is the region with the largest volume of heating oil stocks. PADD 1 was down over 8.4 million barrels on January 21 from the 5-year average stock level for end of January PADD 3, which supplies PADD 1, was down 4.6 million barrels from its 5-year January ending levels. During the week ending January 21, weather in New England was nearly 20% colder than normal for this time of year. This cold weather on top of low stocks was pushing prices up, with

160

Table 2. U.S. Biodiesel Production, Sales, and Stocks  

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

U.S. Biodiesel Production, Sales, and Stocks" U.S. Biodiesel Production, Sales, and Stocks" "(million gallons)" "Period","B100 Production",,"Sales of B100",,"Sales of B100 Included in Biodiesel Blends",,"Ending Stocks of B100",,"B100 Stock Change" 2011 "January",35.355469,,21.760435,,9.397668,,16.705962,,3.900173 "February",40.342355,,27.263997,,13.027514,,17.367083,,0.661121 "March",59.59017,,40.879532,,16.804541,,19.178192,,1.811109 "April",71.0517,,47.320311,,21.819273,,21.000047,,1.821855 "May",77.196652,,49.520679,,27.20637,,23.448551,,2.448504 "June",81.39104,,61.776718,,23.965853,,19.302451,,-4.1461 "July",91.679738,,65.997152,,22.388332,,22.956565,,3.654114

Note: This page contains sample records for the topic "type total stocks" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


161

The More Important Price Indicator This Year is Low Stocks  

Gasoline and Diesel Fuel Update (EIA)

6 of 6 6 of 6 Notes: Crude prices this year at the beginning of the second quarter are likely to be higher -- not lower -- as a result of the current shortfall in crude oil production relative to demand on top of low stocks. OECD stocks of crude oil and products plunged steeply in 1999. By year end, they were below the low levels at end December 1996 -- OPEC's stated target. This does not take into consideration the growth in demand that these stocks must help supply. EIA expects OECD stocks to stay very low throughout the year 2000. The projection shows end March levels remain well below those seen at the end of the first quarter 1996. The build during the summer will not be adequate to make up for the draws, resulting in a net draw of over 300 thousand barrels in an already tight market.

162

Forecasting Volatility in Stock Market Using GARCH Models  

E-Print Network [OSTI]

Forecasting volatility has held the attention of academics and practitioners all over the world. The objective for this master's thesis is to predict the volatility in stock market by using generalized autoregressive ...

Yang, Xiaorong

2008-01-01T23:59:59.000Z

163

The impact of political risk for testing Taiwan's stock market  

Science Journals Connector (OSTI)

This paper examines the vital role of political risk in stock trading. In Taiwan, the Kuomintang (KMT) Government has always been stable, since 1949, but the Progressive Party (DPP) has replaced KMI, and made huge impacts. I adopt the weighted attribute-adjustment methodology to measure the political risk variables, construct a multifactor model to link the political risk induced by Taiwan's first governmental change in May 1999, and analyse its influence on Taiwan's stock market trading. The results show that the political risk induced by governmental change resulted in a crisis of illiquidity in Taiwan's stock market. After the governmental change, the worsening situation in the domestic economy and the populace's lack of faith in the government were the key factors resulting in a serious shrinkage in Taiwan's stock trading.

Lie-Huey Wang

2003-01-01T23:59:59.000Z

164

Stock, Energy and Currency Effects on the Asymmetric Wheat Market  

Science Journals Connector (OSTI)

The purpose of this paper is to explore the effects of financial and currency indicators on wheat futures prices. The results suggest that the stock market, and particularly the S&P 500, positively influence the ...

Nikolaos Sariannidis

2011-05-01T23:59:59.000Z

165

Revised Propane Stock Levels for 6/7/13  

Gasoline and Diesel Fuel Update (EIA)

Revised Propane Stock Levels for 6713 Release Date: June 19, 2013 Following the release of the Weekly Petroleum Status Report (WPSR) for the week ended June 7, 2013, EIA...

166

Advisory on the reporting error in the combined propane stocks...  

Gasoline and Diesel Fuel Update (EIA)

Advisory on the reporting error in the combined propane stocks for PADDs 4 and 5 Release Date: June 12, 2013 The U.S. Energy Information Administration issued the following...

167

NONLINEARITY AND MARKET EFFICIENCY IN GCC STOCK MARKETS  

E-Print Network [OSTI]

): Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and the United Arab Emirates (UAE), using three robust and highly regarded nonlinearity tests. In addition, the Efficient Market Hypothesis (EMH) was tested in this dissertation for the GCC stock markets using...

Alharbi, Abdullah M. H.

2009-07-31T23:59:59.000Z

168

Distillate Stocks Are Important Part of East Coast Winter Supply  

Gasoline and Diesel Fuel Update (EIA)

9 9 Notes: Stocks are normally an important part of East Coast winter distillate supply, since they are the nearest source when anything unexpected occurs, and they supply a significant portion of demand during the peak heating season. Over the last 10 years, stocks have provided about 15% of supply during the peak winter months of January and February. On average, stocks supply the East Coast with about 260 thousand barrels per day in January and 280 in February. Those supplies represent draws of about 8 million barrels in one month. In addition, East Coast refineries meet about 25% of demand during January and February, and other regions -- mostly the Gulf Coast -- supply 40-50% of the region's needs. Imports generally supply about as much as stocks during the peak

169

Performance Period Total Fee Paid  

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

Period Period Total Fee Paid 4/29/2012 - 9/30/2012 $418,348 10/1/2012 - 9/30/2013 $0 10/1/2013 - 9/30/2014 $0 10/1/2014 - 9/30/2015 $0 10/1/2015 - 9/30/2016 $0 Cumulative Fee Paid $418,348 Contract Type: Cost Plus Award Fee Contract Period: $116,769,139 November 2011 - September 2016 $475,395 $0 Fee Information Total Estimated Contract Cost $1,141,623 $1,140,948 $1,140,948 $5,039,862 $1,140,948 Maximum Fee $5,039,862 Minimum Fee Fee Available Portage, Inc. DE-DT0002936 EM Contractor Fee Site: MOAB Uranium Mill Tailings - MOAB, UT Contract Name: MOAB Uranium Mill Tailings Remedial Action Contract September 2013 Contractor: Contract Number:

170

UPDATING THE FREIGHT TRUCK STOCK ADJUSTMENT MODEL: 1997 VEHICLE INVENTORY AND USE SURVEY DATA  

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

36 36 UPDATING THE FREIGHT TRUCK STOCK ADJUSTMENT MODEL: 1997 VEHICLE INVENTORY AND USE SURVEY DATA Stacy C. Davis November 2000 Prepared for the Energy Information Administration U.S. Department of Energy Prepared by the OAK RIDGE NATIONAL LABORATORY Oak Ridge, Tennessee 37831-6073 managed by UT-BATTELLE, LLC for the U.S. DEPARTMENT OF ENERGY under Contract No. DE-AC05-00OR22725 Updating the FTSAM: 1997 VIUS Data iii TABLE OF CONTENTS ABSTRACT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 OBJECTIVE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 VIUS DATA PREPARATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Table 1. Share of Trucks by Fuel Type and Truck Size -

171

21 briefing pages total  

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

briefing pages total p. 1 briefing pages total p. 1 Reservist Differential Briefing U.S. Office of Personnel Management December 11, 2009 p. 2 Agenda - Introduction of Speakers - Background - References/Tools - Overview of Reservist Differential Authority - Qualifying Active Duty Service and Military Orders - Understanding Military Leave and Earnings Statements p. 3 Background 5 U.S.C. 5538 (Section 751 of the Omnibus Appropriations Act, 2009, March 11, 2009) (Public Law 111-8) Law requires OPM to consult with DOD Law effective first day of first pay period on or after March 11, 2009 (March 15 for most executive branch employees) Number of affected employees unclear p. 4 Next Steps

172

Stock option fraud detection and an analysis for its reasons: Arabic Republic of Egypt case  

Science Journals Connector (OSTI)

This paper investigates how stock option turned from an incentive for good management to a tool of management fraud. The objective of this paper is accomplished through studying the stock option phenomenon in the Arab Republic of Egypt (ARE). Stock option grants data are obtained from all firms that have stock option grants and listed in the Egyptian stock market. The empirical study covers the period from 2006 through 2009. Detecting stock option fraud and distinguishing between control and fraud firms was done through calculating the cumulative abnormal returns before and after stock option grants. Results of this research reveal that the incidence of stock option fraud is higher in unscheduled option grants compared to scheduled ones. These results strongly support that the reason of stock option fraud in ARE is dating games rather than news announcements manipulation.

Zakia M. Alaa Eldeen; Ahmed F. Elbayoumi

2013-01-01T23:59:59.000Z

173

"ENDING STOCKS OF CRUDE OIL (excluding SPR)"  

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

ENDING STOCKS OF CRUDE OIL (excluding SPR)" ENDING STOCKS OF CRUDE OIL (excluding SPR)" "Sourcekey","WCESTP11","WCESTP11","WCESTP21","WCESTP21","WCESTP31","WCESTP31","WCESTP41","WCESTP41","WCESTP51","WCESTP51","WCESTUS1","WCESTUS1" "Date","Weekly East Coast (PADD 1) Ending Stocks excluding SPR of Crude Oil (Thousand Barrels)","Weekly East Coast (PADD 1) Ending Stocks excluding SPR of Crude Oil (Thousand Barrels)","Weekly Midwest (PADD 2) Ending Stocks excluding SPR of Crude Oil (Thousand Barrels)","Weekly Midwest (PADD 2) Ending Stocks excluding SPR of Crude Oil (Thousand Barrels)","Weekly Gulf Coast (PADD 3) Ending Stocks excluding SPR of Crude Oil (Thousand Barrels)","Weekly Gulf Coast (PADD 3) Ending Stocks excluding SPR of Crude Oil (Thousand Barrels)","Weekly Rocky Mountain (PADD 4) Ending Stocks excluding SPR of Crude Oil (Thousand Barrels)","Weekly Rocky Mountain (PADD 4) Ending Stocks excluding SPR of Crude Oil (Thousand Barrels)","Weekly West Coast (PADD 5) Ending Stocks excluding SPR of Crude Oil (Thousand Barrels)","Weekly West Coast (PADD 5) Ending Stocks excluding SPR of Crude Oil (Thousand Barrels)","Weekly U.S. Ending Stocks excluding SPR of Crude Oil (Thousand Barrels)","Weekly U.S. Ending Stocks excluding SPR of Crude Oil (Thousand Barrels)"

174

Barge Truck Total  

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

Barge 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 total shipments Year (nominal) (real) (real) (percent) (nominal) (real) (real) (percent) 2008 $6.26 $5.77 $36.50 15.8% 42.3% $6.12 $5.64 $36.36 15.5% 22.2% 2009 $6.23 $5.67 $52.71 10.8% 94.8% $4.90 $4.46 $33.18 13.5% 25.1% 2010 $6.41 $5.77 $50.83 11.4% 96.8% $6.20 $5.59 $36.26 15.4% 38.9% Annual Percent Change First to Last Year 1.2% 0.0% 18.0% - - 0.7% -0.4% -0.1% - - Latest 2 Years 2.9% 1.7% -3.6% - - 26.6% 25.2% 9.3% - - - = No data reported or value not applicable STB Data Source: The Surface Transportation Board's 900-Byte Carload Waybill Sample EIA Data Source: Form EIA-923 Power Plant Operations Report

175

Total Precipitable Water  

SciTech Connect (OSTI)

The simulation was performed on 64K cores of Intrepid, running at 0.25 simulated-years-per-day and taking 25 million core-hours. This is the first simulation using both the CAM5 physics and the highly scalable spectral element dynamical core. The animation of Total Precipitable Water clearly shows hurricanes developing in the Atlantic and Pacific.

None

2012-01-01T23:59:59.000Z

176

Total Sustainability Humber College  

E-Print Network [OSTI]

1 Total Sustainability Management Humber College November, 2012 SUSTAINABILITY SYMPOSIUM Green An Impending Global Disaster #12;3 Sustainability is NOT Climate Remediation #12;Our Premises "We cannot, you cannot improve it" (Lord Kelvin) "First rule of sustainability is to align with natural forces

Thompson, Michael

177

Stocking of Offsite Waters for Hungry Horse Dam Mitigation; Creston National Fish Hatchery, 2002-2003 Annual Report.  

SciTech Connect (OSTI)

Mitigation Objective 1: Produce Native Westslope Cutthroat Trout at Creston NFH--Task: Acquire eggs and rear up to 100,000 Westslope Cutthroat trout annually for offsite mitigation stocking. Accomplishments: A total of 141,000 westslope cutthroat eggs (M012 strain) was acquired from the State of Montana Washoe Park State Fish Hatchery in May 2002 for this objective. We also received an additional 22,000 westslope cutthroat eggs, MO12 strain naturalized, from feral fish at Rogers Lake, Flathead County, Montana. The fish were reared using approved fish culture techniques as defined in the U.S. Fish and Wildlife Service, Fish Hatchery Management guidelines. Survival from the swim up fry stage to stocking was 95.6%. We achieved a 0.80 feed conversion this year on a new diet, Skretting ''Nutra Plus''. Post release survival and angler success is monitored annually by Montana Fish Wildlife and Parks (MFWP) and the Confederated Salish and Kootenai Tribe (CSKT). Stocking numbers and locations vary yearly based on results of biological monitoring and adaptive management. Mitigation Objective 2: Produce Rainbow Trout at Creston NFH--Task: Acquire and rear up to 100,000 Rainbow trout annually for offsite mitigation in closed basin waters. Accomplishments: A total of 54,000 rainbow trout eggs (Arlee strain) was acquired from the Ennis National Fish Hatchery in December 2002 for this objective. The fish were reared using approved fish culture techniques as defined in the U.S. Fish and Wildlife Service, Fish Hatchery Management guidelines. Survival from the swim up fry stage to stocking was 99.9%. We achieved a 0.79 feed conversion this year on a new diet, Skretting ''Nutra Plus''. Arlee rainbow trout are being used for this objective because the stocking locations are terminal basin reservoirs and habitat conditions and returns to the creel are unsuitable for native cutthroat. Post release survival and angler success is monitored annually by the Confederated Salish and Kootenai Tribe (CSKT). Stocking numbers and locations vary yearly based on results of biological monitoring and adaptive management.

US Fish and Wildlife Service Staff, (US Fish and Wildlife Service, Creston National Fish Hatchery, Kalispell, MT)

2004-02-01T23:59:59.000Z

178

Distillate Stocks are Low - Especially on the East Coast  

Gasoline and Diesel Fuel Update (EIA)

8 8 Notes: Distillate stocks are normally built during the summer for use during the winter as shown by the normal band. Currently, stocks are very low for this time of year. This graph shows East Coast inventories, which at the end of August, were well below the normal band (over 9 million barrels or 19% below the low end of the band). The East Coast is about 31% lower than its 10-year average level for this time of year. We focus on the East Coast (PADD 1 ) because this a region in which heating oil is a major winter fuel. Furthermore, the East Coast consumes almost 2/3 of the nation's heating oil (high sulfur distillate). December 1999 was the turning point. Stocks were well within the normal range through November 1999, but in December, they dropped below the

179

Has Oil Price Predicted Stock Returns for Over a Century?  

Science Journals Connector (OSTI)

Abstract This paper contributes to the debate on the role of oil prices in predicting stock returns. The novelty of the paper is that it considers monthly time-series historical data that span over 150 years (1859:10-2013:12) and applies a predictive regression model that accommodates three salient features of the data, namely, a persistent and endogenous oil price, and model heteroskedasticity. Three key findings are unraveled: First, oil price predicts US stock returns. Second, in-sample evidence is corroborated by out-sample evidence of predictability. Third, both positive and negative oil price changes are important predictors of US stock returns, with negative changes relatively more important. Our results are robust to the use of different estimators and choice of in-sample periods.

Paresh Kumar Narayan; Rangan Gupta

2014-01-01T23:59:59.000Z

180

Total isomerization gains flexibility  

SciTech Connect (OSTI)

Isomerization extends refinery flexibility to meet changing markets. TIP (Total Isomerization Process) allows conversion of paraffin fractions in the gasoline boiling region including straight run naptha, light reformate, aromatic unit raffinate, and hydrocrackate. The hysomer isomerization is compared to catalytic reforming. Isomerization routes are graphed. Cost estimates and suggestions on the use of other feedstocks are given. TIP can maximize gas production, reduce crude runs, and complement cat reforming. In four examples, TIP reduces reformer severity and increases reformer yield.

Symoniak, M.F.; Holcombe, T.C.

1983-05-01T23:59:59.000Z

Note: This page contains sample records for the topic "type total stocks" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


181

SolarTotal | Open Energy Information  

Open Energy Info (EERE)

SolarTotal SolarTotal Jump to: navigation, search Name SolarTotal Place Bemmel, Netherlands Zip 6681 LN Sector Solar Product The company sells and installs PV solar instalations Coordinates 51.894112°, 5.89881° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":51.894112,"lon":5.89881,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

182

Big meter data analysis of the energy efficiency potential in Stockholm's building stock  

Science Journals Connector (OSTI)

Abstract The City of Stockholm is making substantial efforts towards meeting its climate change commitments including a GHG emission target of 3 tonnes per capita by 2020 and making its new eco-district Stockholm Royal Seaport a candidate of Clinton Climate Initiative's Climate Positive Program. Towards achieving these policies, this study evaluated the energy efficiency potential in the city, in collaboration with the district heating and electricity utility Fortum. Drawing on their vast billing meter data on the housing stock in Stockholm, a new understanding of energy use in the city emerged. Analysis of the energy efficiency potential of different building vintages revealed that the retrofitting potential of the building stock to current building codes would reduce heating energy use by one third. In terms of market segmentation, the greatest reduction potential in total energy was found to be for buildings constructed between 1946 and 1975. This is due to the large number of buildings constructed during that era and their poor energy performance. However, the least energy-efficient buildings were those built between 1926 and 1945 in contradiction to commonly held beliefs. These findings indicate the need for a shift in public policy towards the buildings with highest retrofitting potential.

Hossein Shahrokni; Fabian Levihn; Nils Brandt

2014-01-01T23:59:59.000Z

183

E-Print Network 3.0 - analogous fish stocks Sample Search Results  

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

fish stocks Search Powered by Explorit Topic List Advanced Search Sample search results for: analogous fish stocks Page: << < 1 2 3 4 5 > >> 1 2008 Status of U.S. Fisheries...

184

Variation of mitochondrial control region sequences of Steller sea lions: the three-stock hypothesis  

E-Print Network [OSTI]

into regions and stocks to examine structure at different spatial scales. F- and ?-statistics were computed for all pairwise comparisons of rookeries, regions and stocks. Significant (PAlaska to California...

Baker, Alyson Renee

2004-09-30T23:59:59.000Z

185

Clustering of Japanese stock returns by recursive modularity optimization for efficient portfolio diversification  

Science Journals Connector (OSTI)

......Toyota. Some major automobile parts suppliers that...relations with specific automobile companies mentioned...comprises stocks of Electric Appliances: Canon...Chemical (Ch) and Electric Appliances (EA) stocks...components suppliers for automobile companies and other......

Takashi Isogai

2014-07-01T23:59:59.000Z

186

Total Sales of Kerosene  

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

End Use: Total Residential Commercial Industrial Farm All Other Period: 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 2007 2008 2009 2010 2011 2012 View History U.S. 492,702 218,736 269,010 305,508 187,656 81,102 1984-2012 East Coast (PADD 1) 353,765 159,323 198,762 237,397 142,189 63,075 1984-2012 New England (PADD 1A) 94,635 42,570 56,661 53,363 38,448 15,983 1984-2012 Connecticut 13,006 6,710 8,800 7,437 7,087 2,143 1984-2012 Maine 46,431 19,923 25,158 24,281 17,396 7,394 1984-2012 Massachusetts 7,913 3,510 5,332 6,300 2,866 1,291 1984-2012 New Hampshire 14,454 6,675 8,353 7,435 5,472 1,977 1984-2012

187

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

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

Total Solids in Biomass and Total Dissolved Solids in Liquid Process Samples Laboratory Analytical Procedure (LAP) Issue Date: 3312008 A. Sluiter, B. Hames, D. Hyman, C. Payne,...

188

SWAMP Project Trip report Quantification of Carbon Stocks and Emissions  

E-Print Network [OSTI]

1 SWAMP Project Trip report Quantification of Carbon Stocks and Emissions from the Mangrove Forests University Corvallis, Oregon, USA. #12;2 1. Introduction Funding for this project came from a grant, Washington DC. This intensive study is part of the Sustainable Wetlands Adaptation and Mitigation Program

Tullos, Desiree

189

ALASKAN WOOD FROGS STOCK UP ON SOLUTES TO SURVIVE  

E-Print Network [OSTI]

Inside JEB i ALASKAN WOOD FROGS STOCK UP ON SOLUTES TO SURVIVE Outwardly, the tiny wood frog, Rana these wood frogs, which are native to Alaska, Canada and the northern USA, to unravel their secrets. Costanzo tolerance in a northern population of the wood frog. J. Exp. Biol. 216, 3461-3473. Nicola Stead THE GENETICS

Besansky, Nora J.

190

Terrorism, country attributes, and the volatility of stock returns  

Science Journals Connector (OSTI)

Abstract This study investigates the interplay between terrorism and finance, focusing on the stock return volatility of American firms targeted by terrorist attacks. We find terrorism risk is an important factor in explaining the volatility of stock returns, which should be taken into account when modelling volatility. Using a volatility event-study approach and a new bootstrapping technique, we find volatility increases on the day of the attack and remain significant for at least fifteen days following the day of the attack. Cross-sectional analysis of the abnormal volatility indicates that the impact of terrorist attacks differs according to the country characteristics in which the incident occurred. We find that firms operating in wealthier, or more democratic countries, face greater volatility in stock returns relative to firms operating in developing countries. Firm exposure varies with the nature of country location, with country wealth and level of democracy playing an important role in explaining the likelihood of a terrorist attack. Our results show that despite significant terrorist events this past decade, stock markets in developed countries have not taken terrorist risk into sufficient consideration.

Naceur Essaddam; John M. Karagianis

2014-01-01T23:59:59.000Z

191

LACTATION VS. IMPROVED GROWTH IN STOCK ALBINO RATS  

Science Journals Connector (OSTI)

...MIui UNVnERSITY OF ILLINOIS DINOSAUR TENDONS WHn1n...attributable to lack of milk production by the mothers. It is...stock diet. Cod-liver oil given in addition to...attention to possible cumulative deficiencies in such...carry on for three months field exploration, shore collecting...

Arthur H. Smith; William E. Anderson

1929-07-26T23:59:59.000Z

192

Mining The Stock Market: Which Measure Is Best ? [Extended Abstract  

E-Print Network [OSTI]

in history), production capacities, population statistics, and sales amounts. Since the data sets occurring the price of the stock at the beginning of an operational day. Every time series is assigned to one out of 102 clusters (e.g. ``Computers (Hardware)'', ``Oil and Gas'', etc). Assuming this classification

193

I. Introduction The Stock Assessment Improvement Plan (SAIP) is the  

E-Print Network [OSTI]

of fish- eries management systems. The resulting review (Appen- dix 7) contained ten recommendations are addressed in detail in Section II, along with other factors that define NMFS' stock assess- ment mandate. Section III provides background informa- tion on requirements for conducting assessments

194

iSTOCK PHOTO Oklahoma State University's innovation  

E-Print Network [OSTI]

AND INDIVIDUALS TO OFFER INNOVATIVE WAYS TO REDUCE THE COST OF ENERGY. FOR MORE INFORMATION, VISIT IGSHPAiSTOCK PHOTO FALL 2013 52 Oklahoma State University's innovation in geothermal production technology is a green option that provides long-term cost savings and production efficiency. The ground

195

A discussion of stock market speculation by Pierre-Joseph Proudhon  

E-Print Network [OSTI]

thought that the publication of a compilation of stock market transactions2 did not merit his signatureA discussion of stock market speculation by Pierre-Joseph Proudhon Nice #12;2 A discussion of stock market speculation by Pierre-Joseph Proudhon Abstract The object

Boyer, Edmond

196

On the relationship between world oil prices and GCC stock markets  

E-Print Network [OSTI]

On the relationship between world oil prices and GCC stock markets Mohamed El Hedi Arouri Associate ABSTRACT We provide comprehensive evidence on the relationship between oil prices and stock mar- kets to be more sensitive to negative than to positive oil shocks. Keywords: oil prices, stock markets, GCC

Paris-Sud XI, Université de

197

Market impact and trading protocols of hidden orders in stock markets Esteban Moro,1, 2  

E-Print Network [OSTI]

Market impact and trading protocols of hidden orders in stock markets Esteban Moro,1, 2 Javier study the market impact of trading orders. We are specifically interested in large trading orders market member codes using data from the Spanish Stock Market and the London Stock Exchange. We find

198

Total Marketed Production ..............  

Gasoline and Diesel Fuel Update (EIA)

billion cubic feet per day) billion cubic feet per day) Total Marketed Production .............. 68.95 69.77 70.45 71.64 71.91 71.70 71.46 71.57 72.61 72.68 72.41 72.62 70.21 71.66 72.58 Alaska ......................................... 1.04 0.91 0.79 0.96 1.00 0.85 0.77 0.93 0.97 0.83 0.75 0.91 0.93 0.88 0.87 Federal GOM (a) ......................... 3.93 3.64 3.44 3.82 3.83 3.77 3.73 3.50 3.71 3.67 3.63 3.46 3.71 3.70 3.62 Lower 48 States (excl GOM) ...... 63.97 65.21 66.21 66.86 67.08 67.08 66.96 67.14 67.92 68.18 68.02 68.24 65.58 67.07 68.09 Total Dry Gas Production .............. 65.46 66.21 66.69 67.79 68.03 67.83 67.61 67.71 68.69 68.76 68.50 68.70 66.55 67.79 68.66 Gross Imports ................................ 8.48 7.60 7.80 7.95 8.27 7.59 7.96 7.91 7.89 7.17 7.61 7.73 7.96 7.93 7.60 Pipeline ........................................

199

Total Space Heat-  

Gasoline and Diesel Fuel Update (EIA)

Released: September, 2008 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* ........................... 3,037 115 397 384 52 1,143 22 354 64 148 357 Building Floorspace (Square Feet) 1,001 to 5,000 ........................... 386 19 43 18 11 93 7 137 8 12 38 5,001 to 10,000 .......................... 262 12 35 17 5 83 4 56 6 9 35 10,001 to 25,000 ........................ 407 20 46 44 8 151 3 53 9 19 54 25,001 to 50,000 ........................ 350 15 55 50 9 121 2 34 7 16 42 50,001 to 100,000 ...................... 405 16 57 65 7 158 2 29 6 18 45 100,001 to 200,000 .................... 483 16 62 80 5 195 1 24 Q 31 56 200,001 to 500,000 .................... 361 8 51 54 5 162 1 9 8 19 43 Over 500,000 ............................. 383 8 47 56 3 181 2 12 8 23 43 Principal Building Activity

200

U.S. Sales for Resale, Total Refiner Motor Gasoline Sales Volumes  

Gasoline and Diesel Fuel Update (EIA)

Type: Sales to End Users, Total Through Retail Outlets Sales for Resale, Total DTW Rack Bulk Download Series History Download Series History Definitions, Sources & Notes...

Note: This page contains sample records for the topic "type total stocks" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


201

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

SciTech Connect (OSTI)

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.

Ekechukwu, A.A.

2002-05-10T23:59:59.000Z

202

Total Space Heat-  

Gasoline and Diesel Fuel Update (EIA)

Revised: December, 2008 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 ............................. 91.0 33.0 7.2 6.1 7.0 18.7 2.7 5.3 1.0 2.2 7.9 Building Floorspace (Square Feet) 1,001 to 5,000 ........................... 99.0 30.7 6.7 2.7 7.1 13.9 7.1 19.9 1.1 1.7 8.2 5,001 to 10,000 .......................... 80.0 30.1 5.5 2.6 6.1 13.6 5.2 8.2 0.8 1.4 6.6 10,001 to 25,000 ........................ 71.0 28.2 4.5 4.1 4.1 14.5 2.3 4.5 0.8 1.6 6.5 25,001 to 50,000 ........................ 79.0 29.9 6.8 5.9 6.3 14.9 1.7 3.9 0.8 1.8 7.1 50,001 to 100,000 ...................... 88.7 31.6 7.6 7.6 6.5 19.6 1.7 3.4 0.7 2.0 8.1 100,001 to 200,000 .................... 104.2 39.1 8.2 8.9 7.9 22.9 1.1 2.9 Q 3.2 8.7 200,001 to 500,000 ....................

203

Total Space Heat-  

Gasoline and Diesel Fuel Update (EIA)

Revised: December, 2008 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 ............................. 91.0 33.0 7.2 6.1 7.0 18.7 2.7 5.3 1.0 2.2 7.9 Building Floorspace (Square Feet) 1,001 to 5,000 ........................... 99.0 30.7 6.7 2.7 7.1 13.9 7.1 19.9 1.1 1.7 8.2 5,001 to 10,000 .......................... 80.0 30.1 5.5 2.6 6.1 13.6 5.2 8.2 0.8 1.4 6.6 10,001 to 25,000 ........................ 71.0 28.2 4.5 4.1 4.1 14.5 2.3 4.5 0.8 1.6 6.5 25,001 to 50,000 ........................ 79.0 29.9 6.8 5.9 6.3 14.9 1.7 3.9 0.8 1.8 7.1 50,001 to 100,000 ...................... 88.7 31.6 7.6 7.6 6.5 19.6 1.7 3.4 0.7 2.0 8.1 100,001 to 200,000 .................... 104.2 39.1 8.2 8.9 7.9 22.9 1.1 2.9 Q 3.2 8.7 200,001 to 500,000 ....................

204

Hubei Shenzhou New Energy Power Generation Stock Co Ltd | Open Energy  

Open Energy Info (EERE)

Hubei Shenzhou New Energy Power Generation Stock Co Ltd Hubei Shenzhou New Energy Power Generation Stock Co Ltd Jump to: navigation, search Name Hubei Shenzhou New Energy Power Generation Stock Co Ltd Place Hubei Province, China Sector Biomass Product Hubei-based biomass power project developer. References Hubei Shenzhou New Energy Power Generation Stock Co Ltd[1] LinkedIn Connections CrunchBase Profile No CrunchBase profile. Create one now! This article is a stub. You can help OpenEI by expanding it. Hubei Shenzhou New Energy Power Generation Stock Co Ltd is a company located in Hubei Province, China . References ↑ "Hubei Shenzhou New Energy Power Generation Stock Co Ltd" Retrieved from "http://en.openei.org/w/index.php?title=Hubei_Shenzhou_New_Energy_Power_Generation_Stock_Co_Ltd&oldid=346655

205

U.S. Total Exports  

Gasoline and Diesel Fuel Update (EIA)

Babb, MT Havre, MT Port of Morgan, MT Pittsburg, NH 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 India Freeport, TX Sabine Pass, LA Total to Japan Cameron, LA Kenai, AK Sabine Pass, LA Total to Mexico Douglas, AZ Nogales, AZ Calexico, CA Ogilby Mesa, CA Otay Mesa, CA Alamo, TX Clint, TX Del Rio, TX Eagle Pass, TX El Paso, TX Hidalgo, TX McAllen, TX Penitas, TX Rio Bravo, TX Roma, TX Total to Portugal Sabine Pass, LA Total to Russia Total to South Korea Freeport, TX Sabine Pass, LA Total to Spain Cameron, LA Sabine Pass, LA Total to United Kingdom Sabine Pass, LA Period: Monthly Annual

206

Connecticut Prices, Sales Volumes & Stocks  

Gasoline and Diesel Fuel Update (EIA)

- - - - - - 1986-2013 - - - - - - 1986-2013 Kerosene-Type Jet Fuel (Refiner Sales) W W W W W W 1984-2013 Kerosene (Refiner Sales) - W W - - NA 1984-2013 No. 1 Distillate (Refiner Sales) - - - - - - 1984-2013 No. 2 Distillate - - - - - - 1983-2013 No. 2 Fuel Oil (Residential) - - - - - - 1983-2013 No. 2 Diesel Fuel (Retail Outlets) - - - - - - 1994-2013 No. 4 Fuel Oil (Refiner Sales) W W W W W NA 1993-2013 Prime Supplier Sales Volumes (Thousand Gallons per Day) Motor Gasoline 3,969.5 4,012.0 3,982.9 4,034.9 3,938.4 3,955.8 1983-2013 Regular 3,431.9 3,470.2 3,458.0 3,486.5 3,382.7 3,432.7 1983-2013 Midgrade 62.5 64.9 67.3 73.9 67.8 57.4 1988-2013 Premium 475.0 476.9 457.6 474.5 487.9 465.7 1983-2013 Aviation Gasoline 2.7 4.1 3.0 6.1 3.4 3.5 1983-2013

207

Relation between total quanta and total energy for aquatic ...  

Science Journals Connector (OSTI)

Jan 22, 1974 ... havior of the ratio of total quanta to total energy (Q : W) within the spectral region of photosynthetic ..... For blue-green waters, where hRmax lies.

2000-01-02T23:59:59.000Z

208

A Model of the Oil Prices' Return Rate Threshold for the Two Stock Market Returns: An Evidence Study of the U.S. and Canada's Stock Markets  

Science Journals Connector (OSTI)

The empirical results show that the dynamic conditional correlation (DCC) and the bivariate asymmetric-IGARCH (1, 1) model is appropriate in evaluating the relationship of the U.S. and the Canada’s stock markets. The empirical result also indicates ... Keywords: Stock market returns, oil price, asymmetric effect, GJR-GARCH model, bivariate asymmetric-GARCH model

Wann-Jyi Horng; Ju-Lan Tsai; Yung-Chin Chiu

2009-11-01T23:59:59.000Z

209

Property:TotalValue | Open Energy Information  

Open Energy Info (EERE)

TotalValue TotalValue Jump to: navigation, search This is a property of type Number. Pages using the property "TotalValue" Showing 25 pages using this property. (previous 25) (next 25) 4 44 Tech Inc. Smart Grid Demonstration Project + 10,000,000 + A ALLETE Inc., d/b/a Minnesota Power Smart Grid Project + 3,088,007 + Amber Kinetics, Inc. Smart Grid Demonstration Project + 10,000,000 + American Transmission Company LLC II Smart Grid Project + 22,888,360 + American Transmission Company LLC Smart Grid Project + 2,661,650 + Atlantic City Electric Company Smart Grid Project + 37,400,000 + Avista Utilities Smart Grid Project + 40,000,000 + B Baltimore Gas and Electric Company Smart Grid Project + 451,814,234 + Battelle Memorial Institute, Pacific Northwest Division Smart Grid Demonstration Project + 177,642,503 +

210

Mujeres Hombres Total Hombres Total 16 5 21 0 10  

E-Print Network [OSTI]

Julio de 2011 Tipo de Discapacidad Sexo CENTRO 5-DistribuciĂłn del estudiantado con discapacidad por centro, tipo de discapacidad, sexo y totales. #12;

Autonoma de Madrid, Universidad

211

Relation between total quanta and total energy for aquatic ...  

Science Journals Connector (OSTI)

Jan 22, 1974 ... ment of the total energy and vice versa. From a measurement of spectral irradi- ance ... unit energy (for the wavelength region specified).

2000-01-02T23:59:59.000Z

212

Longevity of Imidacloprid Soil Drench on Citrus Nursery Stock for Sale at Retail Stores in Florida  

E-Print Network [OSTI]

Nursery Stock for Sale at Retail Stores in Florida Halbert,of contamination is the retail venues themselves. If this ispsyllid infestation in retail stores. Florida has a

Halbert, Susan E.; Manjunath, Keremane L.; Ramadugu, Chandrika; Lee, Richard F.

2014-01-01T23:59:59.000Z

213

E-Print Network 3.0 - anadromous fish stocks Sample Search Results  

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

Powered by Explorit Topic List Advanced Search Sample search results for: anadromous fish stocks Page: << < 1 2 3 4 5 > >> 1 Environmental Biology of Fishes 64: 229242, 2002....

214

Agent-based modeling of commercial building stocks for energy policy and demand response analysis.  

E-Print Network [OSTI]

??Managing a sustainable built environment with a large number of buildings rests on the ability to assess and improve the performance of the building stock… (more)

Zhao, Fei

2012-01-01T23:59:59.000Z

215

Financial liberalisation and the capital structure of firms listed on the Johannesburg stock exchange.  

E-Print Network [OSTI]

??This thesis examines the impact of financial liberalisation on the capital structure of non-financial firms listed on the Johannesburg Stock Exchange (JSE). The research hypotheses… (more)

Chipeta, Chimwemwe

2012-01-01T23:59:59.000Z

216

Total.................................................................  

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

49.2 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 Pump................................ 53.5 3.5 12.9 12.7 8.6 5.5 4.2 6.2 With a Heat Pump..................................... 12.3 0.4 2.2 2.9 2.5 1.5 1.0 1.8 Window/Wall Units........................................ 28.9 27.5 0.5 Q 0.3 Q Q Q 1 Unit......................................................... 14.5 13.5 0.3 Q Q Q N Q 2 Units.......................................................

217

Total........................................................................  

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

7.1 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 For One Housing Unit................................... 42.9 1.5 Q 3.1 6.0 For Two Housing Units................................. 1.8 Q N Q Q Steam or Hot Water System............................. 8.2 1.9 Q Q 0.2 For One Housing Unit................................... 5.1 0.8 Q N Q For Two Housing Units.................................

218

Total........................................................................  

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

5.6 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 Unit................................... 42.9 15.5 11.0 4.5 For Two Housing Units................................. 1.8 0.7 0.6 Q Steam or Hot Water System............................. 8.2 1.6 1.2 0.4 For One Housing Unit................................... 5.1 1.1 0.9 Q For Two Housing Units.................................

219

Total...........................................................................  

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

4.2 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 Pump........................................... 53.5 8.7 3.2 5.5 With a Heat Pump............................................... 12.3 1.7 0.7 1.0 Window/Wall Units.................................................. 28.9 3.6 0.6 3.0 1 Unit................................................................... 14.5 2.9 0.5 2.4 2 Units.................................................................

220

Total..............................................................  

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

,171 ,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 1,269 999 775 510 West North Central................................. 7.9 2,281 1,930 1,566 940 796 646 South.......................................................... 40.7 2,161 1,551 1,295 856 615 513 South Atlantic......................................... 21.7 2,243 1,607 1,359 896 642 543 East South Central.................................

Note: This page contains sample records for the topic "type total stocks" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


221

Total.............................................................................  

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

Cooking Appliances 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 Week....................................... 4.1 0.7 0.3 0.4 No Hot Meals Cooked........................................... 0.9 0.2 Q Q Conventional Oven Use an Oven......................................................... 109.6 23.7 7.5 16.2 More Than Once a Day..................................... 8.9 1.7 0.4 1.3 Once a Day.......................................................

222

Total..............................................................................  

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

0.7 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 Heat Pump.............................................. 53.5 23.2 10.9 3.8 8.4 With a Heat Pump................................................... 12.3 9.0 6.7 1.4 0.9 Window/Wall Units..................................................... 28.9 8.0 3.4 1.7 2.9 1 Unit......................................................................

223

Total....................................................................  

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

14.7 14.7 7.4 12.5 12.5 18.9 18.6 17.3 9.2 Household Size 1 Person.......................................................... 30.0 4.6 2.5 3.7 3.2 5.4 5.5 3.7 1.6 2 Persons......................................................... 34.8 4.3 1.9 4.4 4.1 5.9 5.3 5.5 3.4 3 Persons......................................................... 18.4 2.5 1.3 1.7 1.9 2.9 3.5 2.8 1.6 4 Persons......................................................... 15.9 1.9 0.8 1.5 1.6 3.0 2.5 3.1 1.4 5 Persons......................................................... 7.9 0.8 0.4 1.0 1.1 1.2 1.1 1.5 0.9 6 or More Persons........................................... 4.1 0.5 0.3 0.3 0.6 0.5 0.7 0.8 0.4 2005 Annual Household Income Category Less than $9,999............................................. 9.9 1.9 1.1 1.3 0.9 1.7 1.3 1.1 0.5 $10,000 to $14,999..........................................

224

Total....................................................................................  

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

Cooking Appliances 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..................................................... 3.9 1.7 0.6 0.9 0.8 Less Than Once a Week.............................................. 4.1 2.2 0.6 0.8 0.5 No Hot Meals Cooked................................................... 0.9 0.4 Q Q Q Conventional Oven Use an Oven................................................................. 109.6 46.2 18.8

225

Total..............................................................................  

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

20.6 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 Without a Heat Pump.............................................. 53.5 5.5 16.2 23.2 8.7 With a Heat Pump................................................... 12.3 0.5 1.1 9.0 1.7 Window/Wall Units..................................................... 28.9 10.7 6.6 8.0 3.6 1 Unit......................................................................

226

Total...................................................................  

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

15.2 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 Unit.............................. 3.3 2.9 Q Q Q N For Two Housing Units............................. 1.4 Q Q 0.5 0.8 N Central Warm-Air Furnace........................... 2.8 2.4 Q Q Q 0.2 Other Equipment......................................... 0.3 0.2 Q N Q N Wood..............................................................

227

Total...............................................................  

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

Do Not Have Cooling Equipment................. Do Not Have Cooling Equipment................. 17.8 5.3 4.7 2.8 1.9 3.1 3.6 7.5 Have Cooling Equipment.............................. 93.3 21.5 24.1 17.8 11.2 18.8 13.0 31.1 Use Cooling Equipment............................... 91.4 21.0 23.5 17.4 11.0 18.6 12.6 30.3 Have Equipment But Do Not Use it............. 1.9 0.5 0.6 0.4 Q Q 0.5 0.8 Air-Conditioning Equipment 1, 2 Central System............................................ 65.9 11.0 16.5 13.5 8.7 16.1 6.4 17.2 Without a Heat Pump.............................. 53.5 9.4 13.6 10.7 7.1 12.7 5.4 14.5 With a Heat Pump................................... 12.3 1.7 2.8 2.8 1.6 3.4 1.0 2.7 Window/Wall Units...................................... 28.9 10.5 8.1 4.5 2.7 3.1 6.7 14.1 1 Unit....................................................... 14.5 5.8 4.3 2.0 1.1 1.3 3.4 7.4 2 Units.....................................................

228

Total.............................................................................  

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

Cooking Appliances 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 Week....................................... 4.1 1.1 0.7 0.4 No Hot Meals Cooked........................................... 0.9 Q Q N Conventional Oven Use an Oven......................................................... 109.6 25.3 17.6 7.7 More Than Once a Day..................................... 8.9 1.3 0.8 0.5 Once a Day.......................................................

229

Total................................................................  

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

111.1 26.7 28.8 20.6 13.1 22.0 16.6 38.6 Do Not Have Space Heating Equipment....... 1.2 0.5 0.3 0.2 Q 0.2 0.3 0.6 Have Main Space Heating Equipment.......... 109.8 26.2 28.5 20.4 13.0 21.8 16.3 37.9 Use Main Space Heating Equipment............ 109.1 25.9 28.1 20.3 12.9 21.8 16.0 37.3 Have Equipment But Do Not Use It.............. 0.8 0.3 0.3 Q Q N 0.4 0.6 Main Heating Fuel and Equipment Natural Gas.................................................. 58.2 12.2 14.4 11.3 7.1 13.2 7.6 18.3 Central Warm-Air Furnace........................ 44.7 7.5 10.8 9.3 5.6 11.4 4.6 12.0 For One Housing Unit........................... 42.9 6.9 10.3 9.1 5.4 11.3 4.1 11.0 For Two Housing Units......................... 1.8 0.6 0.6 Q Q Q 0.4 0.9 Steam or Hot Water System..................... 8.2 2.4 2.5 1.0 1.0 1.3 1.5 3.6 For One Housing Unit...........................

230

Total........................................................................  

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

25.6 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 16.2 11.0 11.4 For One Housing Unit................................... 42.9 5.6 15.5 10.7 11.1 For Two Housing Units................................. 1.8 0.5 0.7 Q 0.3 Steam or Hot Water System............................. 8.2 4.9 1.6 1.0 0.6 For One Housing Unit................................... 5.1 3.2 1.1 0.4

231

Total...........................................................................  

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

0.6 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 Pump........................................... 53.5 5.5 4.8 0.7 With a Heat Pump............................................... 12.3 0.5 0.4 Q Window/Wall Units.................................................. 28.9 10.7 7.6 3.1 1 Unit................................................................... 14.5 4.3 2.9 1.4 2 Units.................................................................

232

Total........................................................................  

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

7.1 7.1 19.0 22.7 22.3 Do Not Have Space Heating Equipment............... 1.2 0.7 Q 0.2 Q Have Main Space Heating Equipment.................. 109.8 46.3 18.9 22.5 22.1 Use Main Space Heating Equipment.................... 109.1 45.6 18.8 22.5 22.1 Have Equipment But Do Not Use It...................... 0.8 0.7 Q N N Main Heating Fuel and Equipment Natural Gas.......................................................... 58.2 27.0 11.9 14.9 4.3 Central Warm-Air Furnace................................ 44.7 19.8 8.6 12.8 3.6 For One Housing Unit................................... 42.9 18.8 8.3 12.3 3.5 For Two Housing Units................................. 1.8 1.0 0.3 0.4 Q Steam or Hot Water System............................. 8.2 4.4 2.1 1.4 0.3 For One Housing Unit................................... 5.1 2.1 1.6 1.0

233

Total........................................................................  

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

15.1 15.1 5.5 Do Not Have Space Heating Equipment............... 1.2 Q Q Q Have Main Space Heating Equipment.................. 109.8 20.5 15.1 5.4 Use Main Space Heating Equipment.................... 109.1 20.5 15.1 5.4 Have Equipment But Do Not Use It...................... 0.8 N N N Main Heating Fuel and Equipment Natural Gas.......................................................... 58.2 11.4 9.1 2.3 Central Warm-Air Furnace................................ 44.7 6.1 5.3 0.8 For One Housing Unit................................... 42.9 5.6 4.9 0.7 For Two Housing Units................................. 1.8 0.5 0.4 Q Steam or Hot Water System............................. 8.2 4.9 3.6 1.3 For One Housing Unit................................... 5.1 3.2 2.2 1.0 For Two Housing Units.................................

234

Total..........................................................  

Gasoline and Diesel Fuel Update (EIA)

... 2.8 0.7 0.5 0.2 Million U.S. Housing Units Home Electronics Usage Indicators Table HC12.12 Home Electronics Usage Indicators by Midwest Census Region,...

235

Total..........................................................  

Gasoline and Diesel Fuel Update (EIA)

... 13.2 1.8 1.2 0.5 Table HC11.10 Home Appliances Usage Indicators by Northeast Census Region, 2005 Million U.S. Housing Units Home Appliances...

236

Total..........................................................  

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

... 2.8 1.1 0.7 Q 0.4 Million U.S. Housing Units Home Electronics Usage Indicators Table HC13.12 Home Electronics Usage Indicators by South Census Region,...

237

Total..........................................................  

Gasoline and Diesel Fuel Update (EIA)

... 13.2 3.1 1.0 2.2 Table HC14.10 Home Appliances Usage Indicators by West Census Region, 2005 Million U.S. Housing Units Home Appliances...

238

Total..........................................................  

Gasoline and Diesel Fuel Update (EIA)

States New York Florida Texas California Million U.S. Housing Units Home Electronics Usage Indicators Table HC15.12 Home Electronics Usage Indicators by Four Most Populated...

239

Total..........................................................  

Gasoline and Diesel Fuel Update (EIA)

... 13.2 2.7 3.5 2.2 1.3 3.5 1.3 3.8 Table HC7.10 Home Appliances Usage Indicators by Household Income, 2005 Below Poverty Line Eligible for Federal...

240

Total..........................................................  

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

... 13.2 3.4 2.0 1.4 Table HC12.10 Home Appliances Usage Indicators by Midwest Census Region, 2005 Million U.S. Housing Units Home Appliances...

Note: This page contains sample records for the topic "type total stocks" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


241

Total..........................................................  

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

Census Region Northeast Midwest South West Million U.S. Housing Units Home Electronics Usage Indicators Table HC10.12 Home Electronics Usage Indicators by U.S. Census Region, 2005...

242

Total..........................................................  

Gasoline and Diesel Fuel Update (EIA)

(as Self-Reported) City Town Suburbs Rural Million U.S. Housing Units Home Electronics Usage Indicators Table HC8.12 Home Electronics Usage Indicators by UrbanRural Location,...

243

Total..........................................................  

Gasoline and Diesel Fuel Update (EIA)

... 13.2 4.4 2.5 3.0 3.4 Table HC8.10 Home Appliances Usage Indicators by UrbanRural Location, 2005 Million U.S. Housing Units UrbanRural...

244

Total..........................................................  

Gasoline and Diesel Fuel Update (EIA)

... 2.8 0.6 Q 0.5 Million U.S. Housing Units Home Electronics Usage Indicators Table HC14.12 Home Electronics Usage Indicators by West Census Region, 2005...

245

Total..........................................................  

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

... 13.2 4.9 2.3 1.1 1.5 Table HC13.10 Home Appliances Usage Indicators by South Census Region, 2005 Million U.S. Housing Units South Census Region...

246

Total..........................................................  

Gasoline and Diesel Fuel Update (EIA)

... 51.9 7.0 4.8 2.2 Not Asked (Mobile Homes or Apartment in Buildings with 5 or More Units)... 23.7...

247

Total..........................................................  

Gasoline and Diesel Fuel Update (EIA)

Housing Units Living Space Characteristics Attached 2 to 4 Units 5 or More Units Mobile Homes Apartments in Buildings With-- Housing Units (millions) Single-Family Units Detached...

248

Total..........................................................  

Gasoline and Diesel Fuel Update (EIA)

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...

249

Total  

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

Normal ButaneButylene Other Liquids Oxygenates Fuel Ethanol MTBE Other Oxygenates Biomass-based Diesel Other Renewable Diesel Fuel Other Renewable Fuels Gasoline Blending...

250

Total  

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

Normal ButaneButylene Other Liquids Oxygenates Fuel Ethanol MTBE Other Oxygenates Biomass-based Diesel Fuel Other Renewable Diesel Fuel Other Renewable Fuels Gasoline Blending...

251

Total.............................................................................  

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

Cooking Appliances 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 Week....................................... 4.1 0.6 0.4 Q No Hot Meals Cooked........................................... 0.9 0.3 Q Q Conventional Oven Use an Oven......................................................... 109.6 20.3 14.9 5.4 More Than Once a Day..................................... 8.9 1.4 1.2 0.3 Once a Day.......................................................

252

Total........................................................  

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

111.1 24.5 1,090 902 341 872 780 441 Census Region and Division Northeast............................................. 20.6 6.7 1,247 1,032 Q 811 788 147 New England.................................... 5.5 1.9 1,365 1,127 Q 814 748 107 Middle Atlantic.................................. 15.1 4.8 1,182 978 Q 810 800 159 Midwest................................................ 25.6 4.6 1,349 1,133 506 895 810 346 East North Central............................ 17.7 3.2 1,483 1,239 560 968 842 351 West North Central........................... 7.9 1.4 913 789 329 751 745 337 South................................................... 40.7 7.8 881 752 572 942 873 797 South Atlantic................................... 21.7 4.9 875 707 522 1,035 934 926 East South Central........................... 6.9 0.7 Q Q Q 852 826 432 West South Central..........................

253

Total.................................................................  

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

26.7 26.7 28.8 20.6 13.1 22.0 16.6 38.6 Cooking Appliances Frequency of Hot Meals Cooked 3 or More Times A Day.............................. 8.2 2.9 2.5 1.3 0.5 1.0 2.4 4.6 2 Times A Day........................................... 24.6 6.5 7.0 4.3 3.2 3.6 4.8 10.3 Once a Day................................................ 42.3 8.8 9.8 8.7 5.1 10.0 5.0 12.9 A Few Times Each Week........................... 27.2 5.6 7.2 4.7 3.3 6.3 3.2 7.5 About Once a Week................................... 3.9 1.1 1.1 0.6 0.5 0.6 0.4 1.4 Less Than Once a Week............................ 4.1 1.3 1.0 0.9 0.5 0.4 0.7 1.4 No Hot Meals Cooked................................ 0.9 0.5 Q Q Q Q 0.2 0.5 Conventional Oven Use an Oven.............................................. 109.6 26.1 28.5 20.2 12.9 21.8 16.3 37.8 More Than Once a Day..........................

254

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 Central.................. 17.7 14.5 2,864 2,217 1,490 2,514 1,715 1,408 907 839 553 West North Central................. 7.9 6.4 2,729 2,289 1,924 1,806 1,510 1,085 1,299 1,113 1,059 South.......................................... 40.7 33.0 2,707 1,849 1,563 1,605 1,350 954 1,064 970 685 South Atlantic......................... 21.7 16.8 2,945 1,996 1,695 1,573 1,359 909 1,044 955

255

Total........................................................................  

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

4.2 4.2 7.6 16.6 Do Not Have Space Heating Equipment............... 1.2 0.7 Q 0.7 Have Main Space Heating Equipment.................. 109.8 23.4 7.5 16.0 Use Main Space Heating Equipment.................... 109.1 22.9 7.4 15.4 Have Equipment But Do Not Use It...................... 0.8 0.6 Q 0.5 Main Heating Fuel and Equipment Natural Gas.......................................................... 58.2 14.7 4.6 10.1 Central Warm-Air Furnace................................ 44.7 11.4 4.0 7.4 For One Housing Unit................................... 42.9 11.1 3.8 7.3 For Two Housing Units................................. 1.8 0.3 Q Q Steam or Hot Water System............................. 8.2 0.6 0.3 0.3 For One Housing Unit................................... 5.1 0.4 0.2 0.1 For Two Housing Units.................................

256

Idle Operating Total Stream Day  

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

3 3 Idle Operating Total Stream Day Barrels per Idle Operating Total Calendar Day Barrels per Atmospheric Crude Oil Distillation Capacity Idle Operating Total Operable Refineries Number of State and PAD District a b b 11 10 1 1,293,200 1,265,200 28,000 1,361,700 1,329,700 32,000 ............................................................................................................................................... PAD District I 1 1 0 182,200 182,200 0 190,200 190,200 0 ................................................................................................................................................................................................................................................................................................ Delaware......................................

257

Total Energy Facilities Biomass Facility | Open Energy Information  

Open Energy Info (EERE)

Total Energy Facilities Biomass Facility Total Energy Facilities Biomass Facility Jump to: navigation, search Name Total Energy Facilities Biomass Facility Facility Total Energy Facilities Sector Biomass Facility Type Non-Fossil Waste Location Los Angeles County, California Coordinates 34.3871821°, -118.1122679° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":34.3871821,"lon":-118.1122679,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

258

Crude Oil Stocks at Tank Farms & Pipelines  

Gasoline and Diesel Fuel Update (EIA)

Stocks at Tank Farms & Pipelines Stocks at Tank Farms & Pipelines (Thousand Barrels) Period: Monthly Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Area Apr-13 May-13 Jun-13 Jul-13 Aug-13 Sep-13 View History U.S. 263,633 264,749 252,781 242,174 232,837 248,898 1981-2013 East Coast (PADD 1) 2,000 1,635 1,585 1,793 1,507 2,033 1981-2013 Midwest (PADD 2) 100,842 101,525 99,186 89,116 84,420 84,878 1981-2013 Cushing, OK 49,237 50,172 48,671 40,459 34,809 33,017 2004-2013 Gulf Coast (PADD 3) 121,316 121,816 113,846 112,745 112,059 122,497 1981-2013 Rocky Mountain (PADD 4) 12,813 12,512 12,003 12,181 12,858 12,956 1981-2013 West Coast (PADD 5) 26,662 27,261 26,161 26,339 21,993 26,534 1981-2013

259

Stocking of Offsite Waters for Hungry Horse Dam Mitigation Creston National Fish Hatchery, FY 2006 Annual Report.  

SciTech Connect (OSTI)

A total of 350,000, M012 strain, westslope cutthroat trout (WCT) eggs were received from Montana Fish Wildlife & Parks (MFWP), Washoe Park State Fish Hatchery in June of 2005 to accomplish this fishery management objective. These eggs were incubated, hatched and reared entirely inside the hatchery nursery building using a protected well water supply. Fish grew according to schedule and survival was excellent. The hatchery achieved a 0.78 feed fed to pounds gained conversion ratio for this group of WCT. Not all of the progenies from this fish lot were used for Hungry Horse Dam Fishery Mitigation Implementation. Some were used for other regional fishery management projects. Westslope cutthroat trout were reared using approved fish culture techniques as recommended in the USFWS Fish Hatchery Management Handbook and also utilizing a regimen adapted for hatchery specific site conditions. The fish health for these WCT was very good. Survival from first feeding fry stage to stocking was 79%. The hatchery had an annual fish health inspection performed by the USFWS Bozeman Fish Health Center in mid March of 2006. This inspection found all fish lots at Creston to be disease free. The Montana State Fish Health Board has placed the hatchery under a limited quarantine since May of 2005 due to an epizootic of Furunculosis. This classification has allowed the Creston NFH to stock disease free fish in locations approved by regional fish managers. The hatchery has been working with the State Fish Pathologist to remove the limited quarantine classification from the facility. Although fish health for all station fish lots remains disease free, MFWP has asserted it will not remove the limited quarantine until the new influent water treatment system, including the ultraviolet disinfection unit, is running full time, year round. The USFWS is working to secure the additional funding necessary to operate the treatment building year round. Distribution of the WCT took place from March through June. The stocking locations on the Flathead Reservation and State managed waters were identified by Confederated Salish and Kootenai Tribe (CSKT) and MFWP fishery biologists. Post release survival and angler success is monitored routinely by CSKT and MFWP fishery technicians. Stocking numbers and locations vary annually based on the results of biological monitoring, creel evaluations and adaptive management decisions. A total of 99,126 WCT were stocked during nine distribution trips in management approved waters (see Table 1). The average size of WCT at stocking was 3.91-inches. A total of 101,600, Arlee strain, rainbow trout (RBT) eggs were received from the Ennis National Fish Hatchery, Ennis, Montana, in December of 2005 and 35,000 Kamloops strain eggs were received from Murray Springs SFH, Eureka, Montana, in March of 2006 to accomplish this fishery management objective. The RBT were reared using approved fish culture techniques as recommended in the USFWS Fish Hatchery Management Handbook. There was no fish health related problems associated with this lot of fish. Survival from swim up fry stage to stocking was 93% for the Arlee's and 79% for the Kamloops. The hatchery achieved a 0.68 feed fed to pounds gained conversion ratio for the Arlee and 0.97 for the Kamloops RBT. The excellent feed conversion ratio can be attributed to refined feeding techniques and the use of an extruded high performance fry feed made with premium fish meal and marine fish oil. The Arlee strain of rainbow trout is requested for this fishery mitigation objective because the chosen stocking locations are terminal basin reservoirs or lakes, habitat conditions prevent natural spawning runs and returns to the creel are more favorable then for native westslope cutthroat trout. MFWP also requested a fall plant of Kamloops strain RBT and they will be evaluated for performance and future fall stockings in Echo Lake. Post release survival and angler success is monitored routinely by the Confederated Salish and Kootenai Tribe (CSKT) and Montana Fish Wildlife & Parks (MFWP) fishery techn

Hooley, Sharon

2009-03-20T23:59:59.000Z

260

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" 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 Characteristics(a)","Supplier(b)","Supplier(c)","Supplier(b)","Supplier(c)","Factors" ,"Total United States" "RSE Column Factors:",0.3,2,1.6,1.2

Note: This page contains sample records for the topic "type total stocks" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


261

Total Estimated Contract Cost: Performance Period Total Fee Paid  

Office of Environmental Management (EM)

Analytical Services & Testing Contract June 2014 Contractor: Contract Number: Contract Type: Advanced Technologies & Labs International Inc. DE-AC27-10RV15051 Cost Plus Award Fee...

262

Charles A. Stock Research Oceanographer, NOAA/Geophysical Fluid Dynamics Laboratory  

E-Print Network [OSTI]

Change Impacts on Living Marine Resources", 2012 Ocean Sciences Meeting, Salt Lake City 2012-13 MemberCharles A. Stock Research Oceanographer, NOAA/Geophysical Fluid Dynamics Laboratory Princeton-mail: Charles.Stock@noaa.gov Education 2005 Ph.D., Woods Hole Oceanographic Institution/MIT Joint Program Civil

263

Retail Short Selling and Stock Prices ERIC K. KELLEY and PAUL C. TETLOCK*  

E-Print Network [OSTI]

Retail Short Selling and Stock Prices ERIC K. KELLEY and PAUL C. TETLOCK* January 2014 ABSTRACT This study tests asset pricing theories that feature short selling using a large database of retail trading. We find that retail short selling negatively predicts firms' monthly stock returns and news tone

Haller, Gary L.

264

Stock Market Volatility Prediction: A Service-Oriented Multi-Kernel Learning Approach  

E-Print Network [OSTI]

historical price fluctuations with either trading volume or news. In this paper we present a service: historical prices, trading volumes and stock related news articles. Our experiments show that 1) multi have been developed using historical stock price data, such as k-nearest neighbor and neural network

Liu, Ling

265

Consumption asymmetry and the stock market: New evidence through a threshold adjustment model  

E-Print Network [OSTI]

Consumption asymmetry and the stock market: New evidence through a threshold adjustment model whether stock market wealth affects real consumption asymmetrically through a threshold adjustment model. The empirical findings for the US show that wealth produces an asymmetric effect on real consumption

Ahmad, Sajjad

266

IPA Derivatives for Make-to-Stock Production-Inventory Systems With Lost Sales  

E-Print Network [OSTI]

IPA Derivatives for Make-to-Stock Production-Inventory Systems With Lost Sales Yao Zhao Benjamin-stock policy and unsatisfied demand is lost. The paper derives formulas for IPA (Infinitesimal Perturbation nonparametric in the sense that no specific probability law need be postulated. It is further shown that all IPA

267

8. Discussion This thesis has quantified the ecosystem carbon stocks of the Nhambita  

E-Print Network [OSTI]

destructive to woody biomass: aboveground carbon stocks can only be330 maintained under high intensity fires200 8. Discussion This thesis has quantified the ecosystem carbon stocks of the Nhambita area findings of this thesis and discuss some of the implications for 1) modelling the carbon cycle of miombo

268

Effects of grazing intensity on soil carbon stocks following deforestation of a Hawaiian dry tropical forest  

E-Print Network [OSTI]

Effects of grazing intensity on soil carbon stocks following deforestation of a Hawaiian dry carbon (SOC) along gradients of grazing intensity and elevation in pastures converted from dry tropical of forest-to-pasture conversion on soil carbon (C) stocks depend on a combination of climatic and management

Elmore, Andrew J.

269

The Conditional Relationship between Risk and Return in Iran's Stock Market  

E-Print Network [OSTI]

The Conditional Relationship between Risk and Return in Iran's Stock Market Mahdieh Rezagholizadeh an important role in Iran's economic growth. This paper examines the factors that affect stock returns in Iran by estimating the relationship between various sources of risk -- market risk, oil price risk

Lin, C.-Y. Cynthia

270

Managing the quality of a resource with stock and flow controls  

E-Print Network [OSTI]

stock. Thus, we try to prevent the deterioration of environmental quality and to keep our roads wellManaging the quality of a resource with stock and flow controls Nathaniel Keohane a, , Benjamin Van Roy b , Richard Zeckhauser c a Yale University, United States b Stanford University, United States c

Van Roy, Ben

271

Extreme Day Returns on Stocks: Evidence from Sweden* Adri De Ridder  

E-Print Network [OSTI]

Extreme Day Returns on Stocks: Evidence from Sweden* Adri De Ridder Gotland University Visby and Amalia Wallenberg foundation is gratefully acknowledged. #12;Extreme Day Returns on Stocks: Evidence from Sweden Abstract In this study we document that the frequency of extreme trading days, defined

Djehiche, Boualem

272

Above-and Belowground Carbon Stocks in a Miombo Woodland Landscape of Mozambique  

E-Print Network [OSTI]

cultivation) is likely to decouple changes in woody carbon stocks from soil carbon stocks, mediated by tree lost and degraded to meet agricultural and energy needs (Brouwer & Falca~o 2004). Rural land use, by burning and felling, to grow staple crops such as maize and sorghum for a number of years before

273

High-resolution forest carbon stocks and emissions in Gregory P. Asnera,1  

E-Print Network [OSTI]

High-resolution forest carbon stocks and emissions in the Amazon Gregory P. Asnera,1 , George V. N detection and ranging, and field plots, we mapped aboveground carbon stocks and emissions at 0.1-ha re emissions for REDD. We discovered previously unknown variation in carbon storage at multiple scales based

Saleska, Scott

274

Blood Types  

E-Print Network [OSTI]

Broadcast Transcript: According to the Japanese, you can tell a lot about a person by their blood type: Type A is the farmer, calm and responsible; Type B is the hunter, independent and creative; Type AB is humanistic, ...

Hacker, Randi; Tsutsui, William

2007-03-14T23:59:59.000Z

275

Total Sky Imager (TSI) Handbook  

SciTech Connect (OSTI)

The total sky imager (TSI) provides time series of hemispheric sky images during daylight hours and retrievals of fractional sky cover for periods when the solar elevation is greater than 10 degrees.

Morris, VR

2005-06-01T23:59:59.000Z

276

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

E-Print Network [OSTI]

a Very Low Energy Building Stock: Modeling the US Commercialof questions. The building stock modeling work outlined indetailed modeling of individual buildings). Beyond meeting

Coffey, Brian

2010-01-01T23:59:59.000Z

277

On the shortterm influence of oil price changes on stock markets in GCC countries: linear and nonlinear analyses  

E-Print Network [OSTI]

1 On the shortterm influence of oil price changes on stock markets in GCC countries the short-run relationships between oil prices and GCC stock markets. Since GCC countries are major world energy market players, their stock markets may be susceptible to oil price shocks. To account

Paris-Sud XI, Université de

278

Volume 29, Issue 2 On the short-term influence of oil price changes on stock markets in gcc  

E-Print Network [OSTI]

Volume 29, Issue 2 On the short-term influence of oil price changes on stock markets Rouen & LEO Abstract This paper examines the short-run relationships between oil prices and GCC stock to oil price shocks. To account for the fact that stock markets may respond nonlinearly to oil price

Paris-Sud XI, Université de

279

Total China Investment Co Ltd | Open Energy Information  

Open Energy Info (EERE)

Total China Investment Co Ltd Total 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 years through its activities of Exploration & Production, Gas & Power, Refining & Marketing, and Chemicals. Coordinates 39.90601°, 116.387909° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":39.90601,"lon":116.387909,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

280

Total Estimated Contract Cost: Performance Period Total Fee Paid  

Energy Savers [EERE]

Wastren-EnergX Mission Support LLC Contract Number: DE-CI0000004 Contract Type: Cost Plus Award Fee 128,879,762 Contract Period: December 2009 - July 2015 Fee Information...

Note: This page contains sample records for the topic "type total stocks" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


281

Total Estimated Contract Cost: Performance Period Total Fee Paid  

Office of Environmental Management (EM)

Period: Fee Information Maximum Fee Contract Type: Minimum Fee 91,085,394 74,386,573 Target Fee September 2002 - March 2017 Cost Plus Fixed FeeIncentive Fee 1,192,114,896...

282

Total Estimated Contract Cost:) Performance Period Total Fee...  

Office of Environmental Management (EM)

Washington Closure LLC DE-AC06-05RL14655 Contractor: Contract Number: Contract Type: Cost Plus Incentive Fee 2,251,328,348 Fee Information 0 Maximum Fee 337,699,252...

283

Total Estimated Contract Cost: Performance Period Total Fee Paid  

Energy Savers [EERE]

Cumulative Fee Paid 22,200,285 Wackenhut Services, Inc. DE-AC30-10CC60025 Contractor: Cost Plus Award Fee 989,000,000 Contract Period: Contract Type: January 2010 - December...

284

Total Estimated Contract Cost: Performance Period Total Fee Paid  

Energy Savers [EERE]

& Wilcox Conversion Services, LLC Contract Number: DE-AC30-11CC40015 Contract Type: Cost Plus Award Fee EM Contractor Fee June, 2014 Site: Portsmouth Paducah Project Office...

285

Total Estimated Contract Cost: Performance Period Total Fee Paid  

Office of Environmental Management (EM)

Number: Contract Type: Contract Period: 0 Minimum Fee Maximum Fee Washington River Protection Solutions LLC DE-AC27-08RV14800 Cost Plus Award Fee 5,553,789,617 Fee Information...

286

Total Estimated Contract Cost: Performance Period Total Fee Paid  

Office of Environmental Management (EM)

2011 - September 2015 June 2014 Contractor: Contract Number: Contract Type: Idaho Treatment Group LLC DE-EM0001467 Cost Plus Award Fee Fee Information 419,202,975 Contract Period:...

287

Total Estimated Contract Cost: Performance Period Total Fee Paid  

Office of Environmental Management (EM)

0 Contractor: Bechtel National Inc. Contract Number: DE-AC27-01RV14136 Contract Type: Cost Plus Award Fee Maximum Fee* 595,123,540 Fee Available 102,622,325 10,714,819,974...

288

Total Estimated Contract Cost: Performance Period Total Fee Paid  

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

Type: Cost Plus Award Fee 4,104,318,749 28,500,000 31,597,837 0 39,171,018 32,871,600 EM Contractor Fee Site: Savannah River Site Office - Aiken, SC Contract Name:...

289

Centennial Evolution of Aluminum In-Use Stocks on Our Aluminized Planet  

Science Journals Connector (OSTI)

(ii) What are the historical patterns of aluminum in-use stocks as societies evolve and how can these inform us about potential implications for future material demand, energy use, and GHG emissions? ... Figure 5 shows that aluminum in-use stocks start to take off at per-capita GDPs of 8000–10?000 dollars (PPP, 1990 international $), when a country has already industrialized. ... Figure 5. Per-capita aluminum stocks in use relative to per-capita GDP PPP for selected countries. ...

Gang Liu; Daniel B. Müller

2013-03-12T23:59:59.000Z

290

Sell the news? A news-driven model of the stock market  

E-Print Network [OSTI]

We attempt to explain stock market dynamics in terms of the interaction among three variables: market price, investor opinion and information flow. We propose a framework for such interaction upon which are based two models of stock market dynamics: the model for empirical study and its extended version for theoretical study. We demonstrate that these models replicate observed stock market behavior on all relevant timescales (from days to years) reasonably well. Using the models, we obtain and discuss a number of results that pose implications for current market theory and offer potential practical applications.

Gusev, Maxim; Govorkov, Boris; Sharov, Sergey V; Ushanov, Dmitry; Zhilyaev, Maxim

2014-01-01T23:59:59.000Z

291

Total Estimated Contract Cost: Performance Period Total Fee Paid  

Office of Environmental Management (EM)

Fee Paid 127,390,991 Contract Number: Fee Available Contract Period: Contract Type: Cost Plus Award Fee 4,104,318,749 28,500,000 31,597,837 0 39,171,018 32,871,600 EM...

292

Total Estimated Contract Cost: Performance Period Total Fee Paid  

Office of Environmental Management (EM)

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

293

ARM - Measurement - Total cloud water  

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

cloud water 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 list of all available measurements, including those recorded for diagnostic or quality assurance purposes. External Instruments NCEPGFS : National Centers for Environment Prediction Global Forecast System Field Campaign Instruments CSI : Cloud Spectrometer and Impactor PDI : Phase Doppler Interferometer

294

Artificial Neural Network Model for Forecasting the Stock Price of Indian IT Company  

Science Journals Connector (OSTI)

The central issue of the study is to model the movement of stock price for Indian Information Technology (IT) companies. It has been observed that IT industry has some promising role in Indian economy. We apply t...

Joydeep Sen; Arup K. Das

2014-01-01T23:59:59.000Z

295

A root cause analysis of stock-outs in the pharmaceutical industry  

E-Print Network [OSTI]

PharCo (an assumed name) is a leading global healthcare company with well-recognized brands of both pharmaceutical and consumer healthcare products. As PharCo continues to expand its global presence, product stock-outs in ...

Sun, Xuewen, M. Eng. Massachusetts Institute of Technology

2014-01-01T23:59:59.000Z

296

Conditional correlations in the returns on oil companies stock prices and their determinants  

Science Journals Connector (OSTI)

The identification of the forces that drive stock returns and the dynamics of their associated volatilities is a major concern in empirical economics and finance. This analysis is extremely important for determin...

Massimo Giovannini; Margherita Grasso; Alessandro Lanza; Matteo Manera

2006-09-01T23:59:59.000Z

297

Estimation of biomass and carbon stocks: the case of the Atlantic Forest  

E-Print Network [OSTI]

S.E. 2008. Estimation of biomass and carbon stocks: the casein Amazonian forest biomass. Global Change Biol. 10:545-562R. 2004b. Increasing biomass in Amazonian forest plots.

2008-01-01T23:59:59.000Z

298

Forecasting the Standard & Poor's 500 stock index futures price: interest rates, dividend yields, and cointegration  

E-Print Network [OSTI]

Daily Standard & Poor's 500 stock index cash and futures prices are studies in a cointegration framework using Johansen's maximum likelihood procedure. To account for the time varying relationship(basis) between the two markets, a theoretical...

Fritsch, Roger Erwin

1997-01-01T23:59:59.000Z

299

Quantifying stock-price response to demand fluctuations Vasiliki Plerou,1  

E-Print Network [OSTI]

Quantifying stock-price response to demand fluctuations Vasiliki Plerou,1 Parameswaran Gopikrishnan, Boston University, Boston, Massachusetts 02215 2 Department of Economics, Massachusetts Institute of Technology, Cambridge, Massachusetts 02142 Received 2 July 2001; revised manuscript received 13 May 2002

Stanley, H. Eugene

300

Disaster debris management and recovery of housing stock in San Francisco, CA  

E-Print Network [OSTI]

This thesis investigates the potential effects of a 7.2 magnitude earthquake in San Francisco City, particularly the implications on San Francisco's residential housing stock and impacts on the construction and demolition ...

Saiyed, Zahraa Nazim

2012-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "type total stocks" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


301

An Empirical Examination of Stock Market Reactions to Introduction of Co-branded Products  

E-Print Network [OSTI]

AN EMPIRICAL EXAMINATION OF STOCK MARKET REACTIONS TO INTRODUCTION OF CO-BRANDED PRODUCTS A Dissertation by ZIXIA CAO Submitted to the Office of Graduate Studies of Texas A&M University in partial fulfillment... of the requirements for the degree of DOCTOR OF PHILOSOPHY August 2012 Major: Marketing An Empirical Examination of Stock Market Reactions to Introduction of Co-branded Products Copyright 2012 Zixia Cao...

Cao, Zixia

2012-10-19T23:59:59.000Z

302

Stocking rate and weight gain with three forages utilized in sequence  

E-Print Network [OSTI]

) (Member) August 1977 ABSTRACT STOCKING RATE AND WEIGHT GAIN WITH THREE FORAGES UTILIZED IN SEQUENCE (August 1977) Andres Garcia, Ing. Zoot. Univ. Aut. de Chihuahua (Mexico) Chairman of Advisory Committee g T. CD Cartwright Twenty seven steers were...) (Member) August 1977 ABSTRACT STOCKING RATE AND WEIGHT GAIN WITH THREE FORAGES UTILIZED IN SEQUENCE (August 1977) Andres Garcia, Ing. Zoot. Univ. Aut. de Chihuahua (Mexico) Chairman of Advisory Committee g T. CD Cartwright Twenty seven steers were...

Garcia Jurado, Andres

2012-06-07T23:59:59.000Z

303

Does Turkish Stock Market React to Public Announcements of Major Capital Expenditures?  

Science Journals Connector (OSTI)

Research in quantitative management decision behavior using financial measures is a rapidly growing field. The issue whether and how managerial characteristics and decisions affect corporate behavior and stock performance has investigated in previous research in literature. Recently, many researchers have been pointing out some criticisms to the application of strategic investment decisions and their effect on firm's financial situation. These decisions may include restructuring, new process technology, organization change, technical projects, joint ventures, diversification. The purpose of this study is to investigate the stock market reaction to public announcements of corporate strategic investment decisions by observing companies listed in the Istanbul Stock Exchange (ISE) 30 Index. The stock market reaction to announcements of strategic investment decisions can be thought of as having two components: The first one is price reaction which reflects general factors influencing managerial strategic decisions and firm valuation; and the second one is price reactions to information that announced to the public through firm management. In the literature there are several hypotheses that try to explain stock market reaction to public announcements of corporate strategic investment decisions. One of the most widely known hypotheses is “The Shareholder Value Maximization” hypothesis which is also tested in this study. Shareholder value maximization is usually accepted as the appropriate goal in many business circles. In this study, based on Shareholder Value Maximization hypothesis we assume that there is a positive stock market reaction to corporate investments because the stock markets reward managers for developing strategies that increase shareholder wealth. The implications of a positive reaction by the stock market to investment announcements are vital for corporate strategy research, management practice and effectiveness and investment decisions

Ay?egül Özbebek; Seda Canikli; Yusuf Aytürk

2011-01-01T23:59:59.000Z

304

Geology of the Source Physics Experiment Site, Climax Stock, Nevada National Security Site  

SciTech Connect (OSTI)

A test bed for a series of chemical explosives tests known as Source Physics Experiments (SPE) was constructed in granitic rock of the Climax stock, in northern Yucca Flat at the Nevada National Security Site in 2010-2011. These tests are sponsored by the U.S. Department of Energy, National Nuclear Security Administration's National Center for Nuclear Security. The test series is designed to study the generation and propagation of seismic waves, and will provide data that will improve the predictive capability of calculational models for detecting and characterizing underground explosions. Abundant geologic data are available for the area, primarily as a result of studies performed in conjunction with the three underground nuclear tests conducted in the Climax granite in the 1960s and a few later studies of various types. The SPE test bed was constructed at an elevation of approximately 1,524 meters (m), and consists of a 91.4-centimeter (cm) diameter source hole at its center, surrounded by two rings of three 20.3-cm diameter instrument holes. The inner ring of holes is positioned 10 m away from the source hole, and the outer ring of holes is positioned 20 m from the source hole. An initial 160-m deep core hole was drilled at the location of the source hole that provided information on the geology of the site and rock samples for later laboratory testing. A suite of geophysical logs was run in the core hole and all six instruments holes to obtain matrix and fracture properties. Detailed information on the character and density of fractures encountered was obtained from the borehole image logs run in the holes. A total of 2,488 fractures were identified in the seven boreholes, and these were ranked into six categories (0 through 5) on the basis of their degree of openness and continuity. The analysis presented here considered only the higher-ranked fractures (ranks 2 through 5), of which there were 1,215 (approximately 49 percent of all fractures identified from borehole image logs). The fractures were grouped into sets based on their orientation. The most ubiquitous fracture set (50 percent of all higher-ranked fractures) is a group of low-angle fractures (dips 0 to 30 degrees). Fractures with dips of 60 to 90 degrees account for 38 percent of high-ranked fractures, and the remaining 12 percent are fractures with moderate dips (30 to 60 degrees). The higher-angle fractures are further subdivided into three sets based on their dip direction: fractures of Set 1 dip to the north-northeast, fractures of Set 2 dip to the south-southwest, and Set 3 consists of high-angle fractures that dip to the southeast and strike northeast. The low-angle fractures (Set 4) dip eastward. Fracture frequency does not appear to change substantially with depth. True fracture spacing averages 0.9 to 1.2 m for high-angle Sets 1, 2, and 3, and 0.6 m for Set 4. Two significant faults were observed in the core, centered at the depths of 25.3 and 32.3 m. The upper of these two faults dips 80 degrees to the north-northeast and, thus, is related to the Set-1 fractures. The lower fault dips 79 degrees to the south-southwest and is related to SPE Set-2 fractures. Neither fault has an identifiable surface trace. Groundwater was encountered in all holes drilled on the SPE test bed, and the fluid level averaged about 15.2 to 18.3 m below ground surface. An informal study of variations in the fluid level in the holes conducted during various phases of construction of the test bed concluded that groundwater flow through the fractured granitic rocks is not uniform, and appears to be controlled by variations in the orientation and degree of interconnectedness of the fractures. It may also be possible that an aplite dike or quartz vein may be present in the test bed, which could act as a barrier to groundwater flow and, thus, could account for anisotropy seen in the groundwater recovery measurements.

Townsend, M., Prothro, L. B., Obi, C.

2012-03-15T23:59:59.000Z

305

Broad-basing 'green' stock market indices: a concept note  

Science Journals Connector (OSTI)

Sustainability ('green') stock market indices are intended to focus attention on environmental credentials, to reward superior performance and to help channel investments. Such indices often incorporate clean energy, waste, water and waste water treatment, recycling and other 'pure play enviro' companies. This paper contends that in keeping with the philosophy of Green Economics, which advocates an expansive view of humankind's interaction with the environment, true environmental performance ('greenness') is indexed by the eco-sensitivity of mainstream businesses, by the level of stakeholder involvement and by the extent of information readily made available to society. Effective enforcement of environmental regulation requires contributions from all stakeholders concerned. With voluntary participation from businesses not readily forthcoming, and given the price-sensitivity of consumers, investors, through the incentive structures they face, could contribute to better enforcement of regulatory standards. Broad-basing the green index could be interpreted as recognising and rewarding the superior environmental performance of mainstream businesses and/or ensuring adequate representation in emerging markets, where a large number of 'pure play enviro' related instruments are unlikely to be listed.

Srinivasan Sunderasan

2008-01-01T23:59:59.000Z

306

Table A10. Total Inputs of Energy for Heat, Power, and Electricity...  

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...

307

Property:Geothermal/TotalProjectCost | Open Energy Information  

Open Energy Info (EERE)

TotalProjectCost TotalProjectCost Jump to: navigation, search Property Name Geothermal/TotalProjectCost Property Type Number Description Total Project Cost Pages using the property "Geothermal/TotalProjectCost" Showing 25 pages using this property. (previous 25) (next 25) A A 3D-3C Reflection Seismic Survey and Data Integration to Identify the Seismic Response of Fractures and Permeable Zones Over a Known Geothermal Resource at Soda Lake, Churchill Co., NV Geothermal Project + 14,571,873 + A Demonstration System for Capturing Geothermal Energy from Mine Waters beneath Butte, MT Geothermal Project + 2,155,497 + A Geothermal District-Heating System and Alternative Energy Research Park on the NM Tech Campus Geothermal Project + 6,135,381 + A new analytic-adaptive model for EGS assessment, development and management support Geothermal Project + 1,629,670 +

308

Total Adjusted Sales of Kerosene  

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

End Use: Total Residential Commercial Industrial Farm All Other Period: 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 2007 2008 2009 2010 2011 2012 View History U.S. 492,702 218,736 269,010 305,508 187,656 81,102 1984-2012 East Coast (PADD 1) 353,765 159,323 198,762 237,397 142,189 63,075 1984-2012 New England (PADD 1A) 94,635 42,570 56,661 53,363 38,448 15,983 1984-2012 Connecticut 13,006 6,710 8,800 7,437 7,087 2,143 1984-2012 Maine 46,431 19,923 25,158 24,281 17,396 7,394 1984-2012 Massachusetts 7,913 3,510 5,332 6,300 2,866 1,291 1984-2012 New Hampshire 14,454 6,675 8,353 7,435 5,472 1,977 1984-2012

309

Solar total energy project Shenandoah  

SciTech Connect (OSTI)

This document presents the description of the final design for the Solar Total Energy System (STES) to be installed at the Shenandoah, Georgia, site for utilization by the Bleyle knitwear plant. The system is a fully cascaded total energy system design featuring high temperature paraboloidal dish solar collectors with a 235 concentration ratio, a steam Rankine cycle power conversion system capable of supplying 100 to 400 kW(e) output with an intermediate process steam take-off point, and a back pressure condenser for heating and cooling. The design also includes an integrated control system employing the supervisory control concept to allow maximum experimental flexibility. The system design criteria and requirements are presented including the performance criteria and operating requirements, environmental conditions of operation; interface requirements with the Bleyle plant and the Georgia Power Company lines; maintenance, reliability, and testing requirements; health and safety requirements; and other applicable ordinances and codes. The major subsystems of the STES are described including the Solar Collection Subysystem (SCS), the Power Conversion Subsystem (PCS), the Thermal Utilization Subsystem (TUS), the Control and Instrumentation Subsystem (CAIS), and the Electrical Subsystem (ES). Each of these sections include design criteria and operational requirements specific to the subsystem, including interface requirements with the other subsystems, maintenance and reliability requirements, and testing and acceptance criteria. (WHK)

None

1980-01-10T23:59:59.000Z

310

Grantee Total Number of Homes  

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

Grantee Grantee Total Number of Homes Weatherized through November 2011 [Recovery Act] Total Number of Homes Weatherized through November 2011 (Calendar Year 2009 - November 2011) [Recovery Act + Annual Program Funding] Alabama 6,704 7,867 1 Alaska 443 2,363 American Samoa 304 410 Arizona 6,354 7,518 Arkansas 5,231 6,949 California 41,649 50,002 Colorado 12,782 19,210 Connecticut 8,940 10,009 2 Delaware** 54 54 District of Columbia 962 1,399 Florida 18,953 20,075 Georgia 13,449 14,739 Guam 574 589 Hawaii 604 1,083 Idaho** 4,470 6,614 Illinois 35,530 44,493 Indiana** 18,768 21,689 Iowa 8,794 10,202 Kansas 6,339 7,638 Kentucky 7,639 10,902 Louisiana 4,698 6,946 Maine 5,130 6,664 Maryland 8,108 9,015 Massachusetts 17,687 21,645 Michigan 29,293 37,137 Minnesota 18,224 22,711 Mississippi 5,937 6,888 Missouri 17,334 20,319 Montana 3,310 6,860 Navajo Nation

311

Type Fusion  

Science Journals Connector (OSTI)

Fusion is an indispensable tool in the arsenal ... Less well-known, but equally valuable is type fusion, which states conditions for fusing an application ... algebra. We provide a novel proof of type fusion base...

Ralf Hinze

2011-01-01T23:59:59.000Z

312

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 Capacity (B/SD) Thermal Cracking Downstream Charge Capacity (B/SD) Thermal Cracking Total Coking Downstream Charge Capacity (B/SD) Thermal Cracking Delayed Coking Downstream Charge Capacity (B/SD Thermal Cracking Fluid Coking Downstream Charge Capacity (B/SD) Thermal Cracking Visbreaking Downstream Charge Capacity (B/SD) Thermal Cracking Other/Gas Oil Charge Capacity (B/SD) Catalytic Cracking Fresh Feed Charge Capacity (B/SD) Catalytic Cracking Recycle Charge Capacity (B/SD) Catalytic Hydro-Cracking Charge Capacity (B/SD) Catalytic Hydro-Cracking Distillate Charge Capacity (B/SD) Catalytic Hydro-Cracking Gas Oil Charge Capacity (B/SD) Catalytic Hydro-Cracking Residual Charge Capacity (B/SD) Catalytic Reforming Charge Capacity (B/SD) Catalytic Reforming Low Pressure Charge Capacity (B/SD) Catalytic Reforming High Pressure Charge Capacity (B/SD) Catalytic Hydrotreating/Desulfurization Charge Capacity (B/SD) Catalytic Hydrotreating Naphtha/Reformer Feed Charge Cap (B/SD) Catalytic Hydrotreating Gasoline Charge Capacity (B/SD) Catalytic Hydrotreating Heavy Gas Oil Charge Capacity (B/SD) Catalytic Hydrotreating Distillate Charge Capacity (B/SD) Catalytic Hydrotreating Kerosene/Jet Fuel Charge Capacity (B/SD) Catalytic Hydrotreating Diesel Fuel Charge Capacity (B/SD) Catalytic Hydrotreating Other Distillate Charge Capacity (B/SD) Catalytic Hydrotreating Residual/Other Charge Capacity (B/SD) Catalytic Hydrotreating Residual Charge Capacity (B/SD) Catalytic Hydrotreating Other Oils Charge Capacity (B/SD) Fuels Solvent Deasphalting Charge Capacity (B/SD) Catalytic Reforming Downstream Charge Capacity (B/CD) Total Coking Downstream Charge Capacity (B/CD) Catalytic Cracking Fresh Feed Downstream Charge Capacity (B/CD) Catalytic Hydro-Cracking Downstream Charge Capacity (B/CD) Period:

313

Total quality management implementation guidelines  

SciTech Connect (OSTI)

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.

Not Available

1993-12-01T23:59:59.000Z

314

Total Estimated Contract Cost: Performance Period Total Fee Paid  

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

$ 3,422,994.00 $ 3,422,994.00 FY2011 4,445,142.00 $ FY2012 $ 5,021,951.68 FY2013 $ 3,501,670.00 FY2014 $0 FY2015 $0 FY2016 $0 FY2017 $0 FY2018 $0 FY2019 $0 Cumulative Fee Paid $16,391,758 Wackenhut Services, Inc. DE-AC30-10CC60025 Contractor: Cost Plus Award Fee $989,000,000 Contract Period: Contract Type: January 2010 - December 2019 Contract Number: EM Contractor Fee Site: Savannah River Site Office - Aiken, SC Contract Name: Comprehensive Security Services September 2013 Fee Information Maximum Fee $55,541,496 $5,204,095 $3,667,493 $5,041,415 Minimum Fee 0 Fee Available $5,428,947 $6,326,114

315

Total Heart Transplant: A Modern Overview  

E-Print Network [OSTI]

use of the total artificial heart. New England Journal ofJ. (1997). Artificial heart transplants. British medicala total artificial heart as a bridge to transplantation. New

Lingampalli, Nithya

2014-01-01T23:59:59.000Z

316

Institutional versus retail traders : a comparison of their order flow and impact on trading on the Australian Stock Exchange.  

E-Print Network [OSTI]

??The objective of the thesis is to examine the trading behaviour and characteristics of retail and institutional traders on the Australian Stock Exchange. There are… (more)

Wee, Marvin

2005-01-01T23:59:59.000Z

317

Cooperative Extension Instruction Public Service Research USDA -Hatch Total  

E-Print Network [OSTI]

Cooperative Extension Instruction Public Service Research USDA - Hatch Total Sponsor Type Sponsor,021,707 DEPARTMENT OF HOMELAND SECURITY 1 $5,041 2 $608,619 3 $613,660 NATIONAL AERONAUTICS AND SPACE ADMINISTRATION,137,910 244 $50,856,728 278 $54,994,638 INSTITUTE OF MUSEUM AND LIBRARY SERVICES 1 $49,296 1 $49

Arnold, Jonathan

318

Total Imports of Residual Fuel  

Gasoline and Diesel Fuel Update (EIA)

May-13 Jun-13 Jul-13 Aug-13 Sep-13 Oct-13 View May-13 Jun-13 Jul-13 Aug-13 Sep-13 Oct-13 View History U.S. Total 5,752 5,180 7,707 9,056 6,880 6,008 1936-2013 PAD District 1 1,677 1,689 2,008 3,074 2,135 2,814 1981-2013 Connecticut 1995-2009 Delaware 1995-2012 Florida 359 410 439 392 704 824 1995-2013 Georgia 324 354 434 364 298 391 1995-2013 Maine 65 1995-2013 Maryland 1995-2013 Massachusetts 1995-2012 New Hampshire 1995-2010 New Jersey 903 756 948 1,148 1,008 1,206 1995-2013 New York 21 15 14 771 8 180 1995-2013 North Carolina 1995-2011 Pennsylvania 1995-2013 Rhode Island 1995-2013 South Carolina 150 137 194 209 1995-2013 Vermont 5 4 4 5 4 4 1995-2013 Virginia 32 200 113 1995-2013 PAD District 2 217 183 235 207 247 179 1981-2013 Illinois 1995-2013

319

U.S. Total Exports  

Gasoline and Diesel Fuel Update (EIA)

Noyes, MN Warroad, MN Babb, 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 U.S. Pipeline Total from Mexico Ogilby, CA Otay Mesa, CA Galvan Ranch, TX LNG Imports from Algeria LNG Imports from Australia LNG Imports from Brunei LNG Imports from Canada Highgate Springs, VT LNG Imports from Egypt Cameron, LA Elba Island, GA Freeport, TX Gulf LNG, MS LNG Imports from Equatorial Guinea LNG Imports from Indonesia LNG Imports from Malaysia LNG Imports from Nigeria Cove Point, MD LNG Imports from Norway Cove Point, MD Freeport, TX Sabine Pass, LA LNG Imports from Oman LNG Imports from Peru Cameron, LA Freeport, TX LNG Imports from Qatar Elba Island, GA Golden Pass, TX Sabine Pass, LA LNG Imports from Trinidad/Tobago Cameron, LA Cove Point, MD Elba Island, GA Everett, MA Freeport, TX Gulf LNG, MS Lake Charles, LA Sabine Pass, LA LNG Imports from United Arab Emirates LNG Imports from Yemen Everett, MA Freeport, TX Sabine Pass, LA LNG Imports from Other Countries Period: Monthly Annual

320

Natural Gas Total Liquids Extracted  

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

Thousand Barrels) Thousand Barrels) Data Series: Natural Gas Processed Total Liquids Extracted NGPL Production, Gaseous Equivalent Period: Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: Data Series Area 2007 2008 2009 2010 2011 2012 View History U.S. 658,291 673,677 720,612 749,095 792,481 873,563 1983-2012 Alabama 13,381 11,753 11,667 13,065 1983-2010 Alaska 22,419 20,779 19,542 17,798 18,314 18,339 1983-2012 Arkansas 126 103 125 160 212 336 1983-2012 California 11,388 11,179 11,042 10,400 9,831 9,923 1983-2012 Colorado 27,447 37,804 47,705 57,924 1983-2010 Florida 103 16 1983-2008 Illinois 38 33 24 231 705 0 1983-2012

Note: This page contains sample records for the topic "type total stocks" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


321

Snake River Fall Chinook Salmon Brood-Stock Program, 1981-1986 Final Report of Research.  

SciTech Connect (OSTI)

The objective of the Snake River Fall Chinook Salmon Brood-stock Program was to hatch eggs from upriver stocks, rear the fish to spawning maturity, and use the resulting eggs for stock restoration in the Snake River. Approximately 15,000 eyed Snake River fall chinook salmon eggs were obtained each winter in 1981, 1982, 1983, and 1984 from various Columbia River hatcheries. Fish from these eggs were reared in dechlorinated City of Seattle water at the Northwest and Alaska Fisheries Center or in constant 10.5/degree/C groundwater at the University of Washington's Big Beef Creek Research Station. Seawater tolerance trials of 0+ age (3--5 months) juveniles in all four brood stocks were strongly suggestive of the 1+ age smoltification pattern of spring chinook salmon. Attempts to transfer 0+ age fish to marine net-pens at the Manchester Marine Experimental Station were unsuccessful during the four brood years. The only Snake River fall chinook salmon that demonstrated acceptable survival after 4 months residence in seawater were fish that were transferred as 1+ age smolts. After smolts were successfully transferred to seawater, losses were minimal for several months. However, in all Snake River chinook salmon stocks, mortality due to bacterial kidney disease (BKD) and a previously undescribed ''rosette disease'' resulted in very few maturing fish at 4 or 5 years of age. 5 refs., 7 figs.

Harrell, Lee W.

1987-03-01T23:59:59.000Z

322

Locating and total dominating sets in trees  

Science Journals Connector (OSTI)

A set S of vertices in a graph G = ( V , E ) is a total dominating set of G if every vertex of V is adjacent to a vertex in S. We consider total dominating sets of minimum cardinality which have the additional property that distinct vertices of V are totally dominated by distinct subsets of the total dominating set.

Teresa W. Haynes; Michael A. Henning; Jamie Howard

2006-01-01T23:59:59.000Z

323

Locating-total domination in graphs  

Science Journals Connector (OSTI)

In this paper, we continue the study of locating-total domination in graphs. A set S of vertices in a graph G is a total dominating set in G if every vertex of G is adjacent to a vertex in S . We consider total dominating sets S which have the additional property that distinct vertices in V ( G ) ? S are totally dominated by distinct subsets of the total dominating set. Such a set S is called a locating-total dominating set in G , and the locating-total domination number of G is the minimum cardinality of a locating-total dominating set in G . We obtain new lower and upper bounds on the locating-total domination number of a graph. Interpolation results are established, and the locating-total domination number in special families of graphs, including cubic graphs and grid graphs, is investigated.

Michael A. Henning; Nader Jafari Rad

2012-01-01T23:59:59.000Z

324

EM Rockets Past Target for Donations to Stock Food Banks | Department of  

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

Rockets Past Target for Donations to Stock Food Banks Rockets Past Target for Donations to Stock Food Banks EM Rockets Past Target for Donations to Stock Food Banks November 13, 2012 - 12:00pm Addthis EMCBC Director Jack Craig, left to right, EM Executive Assistant Jillian Carter, who is EM's Feds Feed Families representative, and Senior Advisor for Environmental Management David Huizenga pause for a photo Nov. 8. Craig holds the "Teamwork Award" he and his staff received. EMCBC Director Jack Craig, left to right, EM Executive Assistant Jillian Carter, who is EM's Feds Feed Families representative, and Senior Advisor for Environmental Management David Huizenga pause for a photo Nov. 8. Craig holds the "Teamwork Award" he and his staff received. Savannah River Site Acquisition Operations Division Director David Hepner donated more than 1,000 pounds of food to the campaign.

325

DOE Accepts Bids for Northeast Home Heating Oil Stocks | Department of  

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

Accepts Bids for Northeast Home Heating Oil Stocks Accepts Bids for Northeast Home Heating Oil Stocks DOE Accepts Bids for Northeast Home Heating Oil Stocks February 3, 2011 - 12:00pm Addthis Washington, DC - The U.S. Department of Energy (DOE) today has awarded contracts to three companies who successfully bid for the purchase of 984,253 barrels of heating oil from the Northeast Home Heating Oil Reserve. Awardee Amount Morgan Stanley 500,000 barrels Shell Trading U.S. Company 250,000 barrels George E. Warren Corporation 234,253 barrels Today's sale was the first held as part of the Department's initiative to convert the current 1,984,253-barrel heating oil reserve to cleaner burning ultra low sulfur distillate. Contracts for the heating oil will be executed upon final payment to DOE; final payment is required no later than

326

Distillate Stocks on the East Coast Were Very Low Entering Last Winter  

Gasoline and Diesel Fuel Update (EIA)

4 4 Notes: So, what happened last winter? At last year's SHOPP conference, my renowned colleague, Joanne Shore, warned of the potential for high prices. At this time last year, distillate stocks were very low. This graph shows East Coast inventories, which at the end of July 2000, were well below the normal band. We focus on the East Coast (PADD 1) because this is a region in which heating oil is a major winter fuel. Furthermore, the East Coast consumes almost 2/3 of the nation's heating oil (high sulfur distillate). East Coast stocks were well below normal last year from July through December, but then actually increased in January, when they typically decline. In fact, the increase was only the 2nd time East Coast distillate stocks have increased in January since EIA has kept PADD level data (1981)!

327

Feds Feed Families Wraps Up Successful Campaign to Stock Area Food Banks |  

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

Feds Feed Families Wraps Up Successful Campaign to Stock Area Food Feds Feed Families Wraps Up Successful Campaign to Stock Area Food Banks Feds Feed Families Wraps Up Successful Campaign to Stock Area Food Banks August 1, 2012 - 12:00pm Addthis EM’s Nevada Site Office took first place in the site-submitted category of DOE’s CANstruction Sculpture Contest for its entry, shown here, inspired by London’s Tower Bridge during the 2012 Summer Olympics. EM's Nevada Site Office took first place in the site-submitted category of DOE's CANstruction Sculpture Contest for its entry, shown here, inspired by London's Tower Bridge during the 2012 Summer Olympics. EM Office of Strategic Planning and Analysis Director Barry Gaffney throws the ball that sends Senior Advisor for Environmental Management David Huizenga into the dunk tank during an event to collect nonperishable food items for the DOE Feeds Families campaign.

328

DOE Completes Sale of Northeast Home Heating Oil Stocks | Department of  

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

Completes Sale of Northeast Home Heating Oil Stocks Completes Sale of Northeast Home Heating Oil Stocks DOE Completes Sale of Northeast Home Heating Oil Stocks February 10, 2011 - 12:00pm Addthis Washington, DC - The U.S. Department of Energy (DOE) today has awarded contracts to four companies who successfully bid for the purchase of 1,000,000 barrels of heating oil from the Northeast Home Heating Oil Reserve storage sites in Groton and New Haven, CT. Hess Groton Terminal, Groton, CT Shell Trading U.S. Company 150,000 barrels Sprague Energy Corp. 100,000 barrels Magellan New Haven Terminal, New Haven, CT Hess Corporation 300,000 barrels Morgan Stanley 450,000 barrels Today's sale was the second held as part of the Department's initiative to convert the 1,984,253 barrel heating oil reserve to cleaner burning

329

Window-Related Energy Consumption in the US Residential and Commercial Building Stock  

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

Window-Related Energy Consumption in the US Window-Related Energy Consumption in the US Residential and Commercial Building Stock Joshua Apte and Dariush Arasteh, Lawrence Berkeley National Laboratory LBNL-60146 Abstract We present a simple spreadsheet-based tool for estimating window-related energy consumption in the United States. Using available data on the properties of the installed US window stock, we estimate that windows are responsible for 2.15 quadrillion Btu (Quads) of heating energy consumption and 1.48 Quads of cooling energy consumption annually. We develop estimates of average U-factor and SHGC for current window sales. We estimate that a complete replacement of the installed window stock with these products would result in energy savings of approximately 1.2 quads. We demonstrate

330

Annual Coded Wire Tag Program; Oregon Stock Assessment, 2000 Annual Report.  

SciTech Connect (OSTI)

This annual report is in fulfillment of contract obligations with Bonneville Power Administration which is the funding source for the Oregon Department of Fish and Wildlife's Annual Stock Assessment - Coded Wire Tag Program (ODFW) Project. Tule stock fall chinook were caught primarily in British Columbia and Washington ocean, and Columbia Basin fisheries. Up-river bright stock fall chinook contributed primarily to Alaska and British Columbia ocean commercial, Columbia Basin gillnet and freshwater sport fisheries. Contribution of Rogue stock fall chinook released in the lower Columbia River occurred primarily in Oregon ocean commercial, Columbia Basin gillnet and freshwater sport fisheries. Willamette stock spring chinook contributed primarily to Alaska and British Columbia ocean, and Columbia Basin sport fisheries. Willamette stock spring chinook released by CEDC contributed to similar ocean fisheries, but had much higher catch in Columbia Basin gillnet fisheries than the same stocks released in the Willamette Basin. Up-river stocks of spring chinook contributed almost exclusively to Columbia Basin fisheries. The up-river stocks of Columbia River summer steelhead contributed almost exclusively to the Columbia Basin gillnet and freshwater sport fisheries. Coho ocean fisheries from Washington to California were closed or very limited from 1994 through 1999 (1991 through 1996 broods). This has resulted in a lower percent of catch in Washington, Oregon and California ocean fisheries, and a higher percent of catch in Alaska and British Columbia ocean and Columbia Basin freshwater fisheries. Coho stocks released by ODFW below Bonneville Dam were caught mainly in Oregon, Washington, and British Columbia ocean, Columbia Gillnet and freshwater sport fisheries. Coho stocks released in the Klaskanine River and Youngs Bay area had similar ocean catch distributions, but a much higher percent catch in gillnet fisheries than the other coho releases. Ocean catch distribution of coho stocks released above Bonneville Dam was similar to the other coho groups. However, they had a higher percent catch in gillnet fisheries above Bonneville Dam than coho released below the dam. Survival rates of salmon and steelhead are influenced, not only by factors in the hatchery (disease, density, diet, size and time of release) but also by environmental factors in the river and ocean. These environmental factors are influenced by large scale oceanic and weather patterns such as El Nino. Changes in rearing conditions in the hatchery do impact survival, however, these can be offset by impacts caused by environmental factors. Coho salmon released in the Columbia River generally experience better survival rates when released later in the spring. However, for the 1990 brood year June releases of Columbia River coho had much lower survival than May releases, for all ODFW hatcheries. In general survival of ODFW Columbia River hatchery coho has declined to low levels in recent years. Preliminary results from the evaluation of Visual Implant Elastomer (VIE) tags showed tagging rate and pre-release tag retention improved from the first to second years of tagging. Tagging rate remained identical from 1999 to 2000 while pre-release tag retention dropped to 95%. Returning jack and adult salmon were sampled for CWT and VIE tags in the fall of 2000. Of 606 adults recovered at Sandy Fish Hatchery in 2000, only 1 or 0.2%, retained their VIE tag. Of 36 jacks recovered in 2000, 13 or 36.1% retained their VIE tag.

Lewis, Mark; Mallette, Christine; Murray, William

2002-03-01T23:59:59.000Z

331

Oil Price and Stock Returns of Consumers and Producers of Crude Oil  

Science Journals Connector (OSTI)

Abstract In this paper we investigate how differently stock returns of oil producers and oil consumers are affected from oil price changes. We find that stock returns of oil producers are affected positively by oil price changes regardless of whether oil price is increasing or decreasing. For oil consumers, oil price changes do not affect all consumer sub-sectors and where it does, this effect is heterogeneous. We find that oil price returns have an asymmetric effect on stock returns for most sub-sectors. We devise simple trading strategies and find that while both consumers and producers of oil can make statistically significant profits, investors in oil producer sectors make relatively more profits than investors in oil consumer sectors

Dinh Hoang Bach Phan; Susan Sunila Sharma; Paresh Kumar Narayan

2014-01-01T23:59:59.000Z

332

The impact of oil price shocks on the stock market return and volatility relationship  

Science Journals Connector (OSTI)

Abstract This paper examines the impact of structural oil price shocks on the covariance of U.S. stock market return and stock market volatility. We construct from daily data on return and volatility the covariance of return and volatility at monthly frequency. The measures of daily volatility are realized-volatility at high frequency (normalized squared return), conditional-volatility recovered from a stochastic volatility model, and implied-volatility deduced from options prices. Positive shocks to aggregate demand and to oil-market specific demand are associated with negative effects on the covariance of return and volatility. Oil supply disruptions are associated with positive effects on the covariance of return and volatility. The spillover index between the structural oil price shocks and covariance of stock return and volatility is large and highly statistically significant.

Wensheng Kang; Ronald A. Ratti; Kyung Hwan Yoon

2015-01-01T23:59:59.000Z

333

U.S. Total Exports  

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

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 LNG Imports into Cameron, LA LNG Imports into Cove Point, MD LNG Imports into Elba Island, GA LNG Imports into Everett, MA LNG Imports into Freeport, TX LNG Imports into Golden Pass, TX LNG Imports into Gulf Gateway, LA LNG Imports into Gulf LNG, MS LNG Imports into Lake Charles, LA LNG Imports into Neptune Deepwater Port LNG Imports into Northeast Gateway LNG Imports into Sabine Pass, LA 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 Charles, LA LNG Imports from Australia Everett, MA Lake Charles, LA LNG Imports from Brunei Lake Charles, LA LNG Imports from Canada Highgate Springs, VT LNG Imports from Egypt Cameron, LA Cove Point, MD Elba Island, GA Everett, MA Freeport, TX Gulf LNG, MS Lake Charles, LA Northeast Gateway Sabine Pass, LA LNG Imports from Equatorial Guinea Elba Island, GA Lake Charles, LA LNG Imports from Indonesia Lake Charles, LA LNG Imports from Malaysia Gulf Gateway, LA Lake Charles, LA LNG Imports from Nigeria Cove Point, MD Elba Island, GA Freeport, TX Gulf Gateway, LA Lake Charles, LA Sabine Pass, LA LNG Imports from Norway Cove Point, MD Sabine Pass, LA LNG Imports from Oman Lake Charles, LA LNG Imports from Peru Cameron, LA Freeport, TX Sabine Pass, LA LNG Imports from Qatar Cameron, LA Elba Island, GA Golden Pass, TX Gulf Gateway, LA Lake Charles, LA Northeast Gateway Sabine Pass, LA LNG Imports from Trinidad/Tobago Cameron, LA Cove Point, MD Elba Island, GA Everett, MA Freeport, TX Gulf Gateway, LA Gulf LNG, MS Lake Charles, LA Neptune Deepwater Port Northeast Gateway Sabine Pass, LA LNG Imports from United Arab Emirates Lake Charles, LA LNG Imports from Yemen Everett, MA Freeport, TX Neptune Deepwater Port Sabine Pass, LA LNG Imports from Other Countries Lake Charles, LA Period: Monthly Annual

334

Cow-Calf and Vegetation Response to Heavy Rates of Stocking at the Texas Experimental Ranch.  

E-Print Network [OSTI]

. 1978. Stocking rate theory and its applica tion to grazing on rangeland. In: Proc. First Int. Range. Congr. Soc. Range Manage. Denver, CO pp. 606-609. Hart, R. H. 1980. Determining a proper stocking rate for a grazing system. Proc. Grazing. Manage.... Denver, CO pp. 541-546. Lewis, J. K., G. M. Van Dyne, L. R. Albee, and F. W. Whetzal. 1956. Intensity of grazing: Its effect on livestock and forage production. S. Oak. Agr. Exp. Sta. Bull. 459. 44 p. Mcilvain, E. H. and M. C. Shoop. 1962. Calves...

Heitschmidt, R.K.; Johnson, A.B.; Frasure, J.R.; Price, D.L.

1983-01-01T23:59:59.000Z

335

Approach for the Improvement of Energy Performance of a Stock of Buildings  

E-Print Network [OSTI]

. - The tools must be accessible via the Intranet of the ministry in order to be easily and widely accessible. DEVELOPMENT OF TOOLS ADAPTED TO END-USER To analyze and improve the performance of the ministry of equipment stock of buildings we have.... - The tools must be accessible via the Intranet of the ministry in order to be easily and widely accessible. DEVELOPMENT OF TOOLS ADAPTED TO END-USER To analyze and improve the performance of the ministry of equipment stock of buildings we have...

Vaezi-Nejad, H.; Bouillon, J.; Crozier, L.; Guyot, G.

2003-01-01T23:59:59.000Z

336

Stock Assessment of Columbia River Anadromous Salmonids : Final Report, Volume I, Chinook, Coho, Chum and Sockeye Salmon Summaries.  

SciTech Connect (OSTI)

The purpose was to identify and characterize the wild and hatchery stocks of salmon and steelhead in the Columbia River Basin on the basis of currently available information. This report provides a comprehensive compilation of data on the status and life histories of Columbia Basin salmonid stocks.

Howell, Philip J.

1986-07-01T23:59:59.000Z

337

Optimal production and rationing policies of a make-to-stock production system with batch demand and backordering  

Science Journals Connector (OSTI)

In this paper, we consider the stock rationing problem of a single-item make-to-stock production/inventory system with multiple demand classes. Demand arrives as a Poisson process with a randomly distributed batch size. It is assumed that the batch demand ... Keywords: Batch demand, Inventory, Markov decision process, Production, Rationing

Jianjun Xu; Shaoxiang Chen; Bing Lin; Rohit Bhatnagar

2010-05-01T23:59:59.000Z

338

IPA Derivatives for Make-to-Stock Production-Inventory Systems With Backorders Under the (R,r) Policy  

E-Print Network [OSTI]

IPA Derivatives for Make-to-Stock Production-Inventory Systems With Backorders Under the (R Infinitesimal Perturbation Analysis (IPA) in the class of Make-to Stock (MTS) production-inventory systems regularity assumptions. The paper then analyzes the SFM counterpart and derives closed-form IPA derivative

339

Relationships between fish stock changes in the Baltic Sea and the M74 syndrome, a reproductive disorder of Atlantic  

E-Print Network [OSTI]

Relationships between fish stock changes in the Baltic Sea and the M74 syndrome, a reproductive. Relationships between fish stock changes in the Baltic Sea and the M74 syndrome, a reproductive disorder in the BPr, primarily sprat, induce M74. By reducing the fishing pressure on cod (Gadus morhua) and by more

340

Oil Prices, Stock Markets and Portfolio Investment: Evidence from Sector Analysis in Europe over the Last Decade  

E-Print Network [OSTI]

Oil Prices, Stock Markets and Portfolio Investment: Evidence from Sector Analysis in Europe over This article extends the understanding of oil­stock market relationships over the last turbulent decade. Unlike returns to oil price changes differ greatly depending on the activity sector. In the out

Paris-Sud XI, Université de

Note: This page contains sample records for the topic "type total stocks" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


341

Melanin Types  

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

Melanin Types Melanin Types Name: Irfan Location: N/A Country: N/A Date: N/A Question: What are different types of melanins? And what are the functions of these types? Replies: Hi Irfan! Melanin is a dark compound or better a photoprotective pigment. Its major role in the skin is to absorb the ultraviolet (UV) light that comes from the sun so the skin is not damaged. Sun exposure usually produces a tan at the skin that represents an increase of melanin pigment in the skin. Melanin is important also in other areas of the body, as the eye and the brain., but it is not completely understood what the melanin pigment does in these areas. Melanin forms a special cell called melanocyte. This cell is found in the skin, in the hair follicle, and in the iris and retina of the eye.

342

Performance Period Total Fee Paid FY2001  

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

01 01 $4,547,400 FY2002 $4,871,000 FY2003 $6,177,902 FY2004 $8,743,007 FY2005 $13,134,189 FY2006 $7,489,704 FY2007 $9,090,924 FY2008 $10,045,072 FY2009 $12,504,247 FY2010 $17,590,414 FY2011 $17,558,710 FY2012 $14,528,770 Cumulative Fee Paid $126,281,339 Cost Plus Award Fee DE-AC29-01AL66444 Washington TRU Solutions LLC Contractor: Contract Number: Contract Type: $8,743,007 Contract Period: $1,813,482,000 Fee Information Maximum Fee $131,691,744 Total Estimated Contract Cost: $4,547,400 $4,871,000 $6,177,902 October 2000 - September 2012 Minimum Fee $0 Fee Available EM Contractor Fee Site: Carlsbad Field Office - Carlsbad, NM Contract Name: Waste Isolation Pilot Plant Operations March 2013 $13,196,690 $9,262,042 $10,064,940 $14,828,770 $12,348,558 $12,204,247 $17,590,414 $17,856,774

343

Total Crude Oil and Petroleum Products Exports  

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

Exports Exports Product: Total Crude Oil and Petroleum Products Crude Oil Natural Gas Plant Liquids and Liquefied Refinery Gases Pentanes Plus Liquefied Petroleum Gases Ethane/Ethylene Propane/Propylene Normal Butane/Butylene Isobutane/Isobutylene Other Liquids Hydrogen/Oxygenates/Renewables/Other Hydrocarbons Oxygenates (excl. Fuel Ethanol) Methyl Tertiary Butyl Ether (MTBE) Other Oxygenates Renewable Fuels (incl. Fuel Ethanol) Fuel Ethanol Biomass-Based Diesel Motor Gasoline Blend. Comp. (MGBC) MGBC - Reformulated MGBC - Conventional Aviation Gasoline Blend. Comp. Finished Petroleum Products Finished Motor Gasoline Reformulated Gasoline Conventional Gasoline Finished Aviation Gasoline Kerosene-Type Jet Fuel Kerosene Distillate Fuel Oil Distillate F.O., 15 ppm and under Distillate F.O., Greater than 15 to 500 ppm Distillate F.O., Greater than 500 ppm Residual Fuel Oil Naphtha for Petro. Feed. Use Other Oils Petro. Feed. Use Special Naphthas Lubricants Waxes Petroleum Coke Asphalt and Road Oil Miscellaneous Products Period-Unit: Monthly-Thousand Barrels Monthly-Thousand Barrels per Day Annual-Thousand Barrels Annual-Thousand Barrels per Day

344

State Residential Commercial Industrial Transportation Total  

Gasoline and Diesel Fuel Update (EIA)

schedules 4A-D, EIA-861S and EIA-861U) State Residential Commercial Industrial Transportation Total 2012 Total Electric Industry- Average Retail Price (centskWh) (Data from...

345

Total cost model for making sourcing decisions  

E-Print Network [OSTI]

This thesis develops a total cost model based on the work done during a six month internship with ABB. In order to help ABB better focus on low cost country sourcing, a total cost model was developed for sourcing decisions. ...

Morita, Mark, M.B.A. Massachusetts Institute of Technology

2007-01-01T23:59:59.000Z

346

Team Total Points Beta Theta Pi 2271  

E-Print Network [OSTI]

Bubbles 40 Upset City 30 Team Success 30 #12;Team Total Points Sly Tye 16 Barringer 15 Fire Stinespring 15

Buehrer, R. Michael

347

Rapid Monitoring of Hydrocarbon Blending Stocks in Modified Aviation Turbine Fuels  

Science Journals Connector (OSTI)

......stocks in JP-4 aviation turbine fuel. Introduction High resolution capillary gas chromatography affords...principal Air Force aviation turbine fuel, and the incorporation...Model 3700 capillary gas chromatographic system...Products), to remove residual oxygen and/or water......

P.C. Hayes; Jr.; E.W. Pitzer

1984-10-01T23:59:59.000Z

348

A hybrid FLANN and adaptive differential evolution model for forecasting of stock market indices  

Science Journals Connector (OSTI)

This paper presents a computationally efficient functional link artificial neural network CEFLANN based adaptive model for financial time series prediction of leading Indian stock market indices. Financial time-series data are usually non-stationary ... Keywords: Adaptive Differential Evolution Ade, Artificial Neural Network, Functional Link Neural Network Flann, Least Mean Squares Lms, Technical Indicators

Ajit Kumar Rout; Birendra Biswal; Pradipta Kishore Dash

2014-01-01T23:59:59.000Z

349

Stock Portfolio Evaluation: An Application of Genetic-Programming-Based Technical Analysis  

E-Print Network [OSTI]

of investment risk from historical price patterns. The purpose of this paper is not to provide justification on the belief that historical stock statistics exhibit regularities. According to the Efficient Market Hypothesis (EMH) (Fama 1970; Malkiel 1992), since historical statistics data is already reflected

Fernandez, Thomas

350

Rapid Monitoring of Hydrocarbon Blending Stocks in Modified Aviation Turbine Fuels  

Science Journals Connector (OSTI)

......JP-4 jet fuel. For JP-4 turbine fuel, the analysis is relatively...blending stocks in JP-4 aviation turbine fuel. Introduction High resolution...principal Air Force aviation turbine fuel, and the incorporation...Scientific). The column's efficiency was measured and found to be......

P.C. Hayes; Jr.; E.W. Pitzer

1984-10-01T23:59:59.000Z

351

John Sevier Aquatic Biological Program: Paddlefish stocking and assessment report for 1986. [Polyodon spathula  

SciTech Connect (OSTI)

In January, 1986, approximately 10,700 yearling paddlefish were released in Cherokee Reservoir. Initial mortality was apparently low, with fewer than 100 stocked paddlefish found dead in the vicinity of the release site. Subsequent sampling has yielded little data on distribution and abundance of paddlefish in Cherokee Reservoir. Observations suggest young paddlefish dispersed widely and may not have experienced heavy mortality. (ACR)

Pasch, R.W.

1986-06-01T23:59:59.000Z

352

SEASONAL AND INSHORE-OFFSHORE VARIATIONS IN THE STANDING STOCKS OF MICRONEKTON AND  

E-Print Network [OSTI]

SEASONAL AND INSHORE-OFFSHORE VARIATIONS IN THE STANDING STOCKS OF MICRONEKTON AND MACROZOOPLANKTON OFF OREGON WILLIAM G. PEARCyl ABSTRACT Dry weights of pelagic animals captured along an inshore-offshore, shrimps, and squids) were largest inshore (28 and 46 km offshore) in the winter (November

353

Systematic analysis of group identification in stock markets Dong-Hee Kim* and Hawoong Jeong  

E-Print Network [OSTI]

Systematic analysis of group identification in stock markets Dong-Hee Kim* and Hawoong Jeong that the statistics of the bulk eigenvalues are in remarkable agreements with the universal properties of the random correlation matrix. For example, the bulk part of the eigenvalue spectrum of the empirical correlation matrix

Jeong, Hawoong

354

IPA Derivatives for Make-to-Stock Production-Inventory Systems With Lost Sales  

E-Print Network [OSTI]

IPA Derivatives for Make-to-Stock Production-Inventory Systems With Lost Sales Yao Zhao for IPA (Infinitesimal Perturbation Analysis) derivatives of the sample-path time averages law need be postulated. It is further shown that all IPA derivatives under study are unbiased and very

Lin, Xiaodong

355

Tridacnid Clam Stocks on Helen Reef, Palau, Western CaroUnels Sli~s WENDY HIRSCHBERGER  

E-Print Network [OSTI]

Tridacnid Clam Stocks on Helen Reef, Palau, Western CaroUnels Sli~s WENDY HIRSCHBERGER Introduction in the south Palau District, Western Caroline Is- lands, Trust Territory of the Pacific Is- lands.-Helen Island at Helen Reef atoll, in Palau's southwest islands. remote area is uninhabited and receives only

356

Clustering of Japanese stock returns by recursive modularity optimization for efficient portfolio diversification  

Science Journals Connector (OSTI)

......these two groups are linked by statistical tests. The standard sector classification is...stability of communities detected, and test the significance quantitatively. In Japan...appropriate lag parameters. The Ljung-Box test is conducted for every stock to ensure......

Takashi Isogai

2014-12-01T23:59:59.000Z

357

The Visualization of Large Database in Stock Market Li Lin, Longbing Cao, Chengqi Zhang  

E-Print Network [OSTI]

and global trend with fish- eye technology. Second, for the result graph, there are many parameters, so we; Fish-eye view; Local details; Global trends; Dimension reducing 1. Introduction In stock market another problem for a trading system. In the paper, we have resolved the two problems with fish- eye

Cao, Longbing

358

Fossil fuel prices, exchange rate, and stock market: A dynamic causality analysis on the European market  

Science Journals Connector (OSTI)

The article investigates causality between fossil fuel prices, exchange rates and the German Stock Index (DAX). The analysis is conducted dynamically with the use of rolling VAR methodology on the basis of weekly data from the period October 2001–June 2012. The results obtained show that the relationship between the variables changed over time depending on the level of volatility in financial markets.

S?awomir ?miech; Monika Papie?

2013-01-01T23:59:59.000Z

359

Carbon Stocks and Projections on Public Forestlands in the United States, 19522040  

E-Print Network [OSTI]

ARTICLES Carbon Stocks and Projections on Public Forestlands in the United States, 1952­2040 JAMES are publicly owned; they represent a substantial area of potential carbon sequestration in US for- ests inventoried than privately owned forests. Thus, less information is avail- able about their role as carbon

360

Market impact and trading profile of hidden orders in stock markets Esteban Moro,1,2  

E-Print Network [OSTI]

Market impact and trading profile of hidden orders in stock markets Esteban Moro,1,2 Javier Vicente, Italy Received 3 August 2009; published 1 December 2009 We empirically study the market impact, which we call hidden orders. These are statistically reconstructed based on information about market

Note: This page contains sample records for the topic "type total stocks" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


361

Million Cu. Feet Percent of National Total  

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

38 38 Nevada - Natural Gas 2012 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, 2008-2012 2008 2009 2010 2011 2012 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 4 4 4 3 4 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 4 4 4 3 4

362

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

4 4 Idaho - Natural Gas 2011 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, 2007-2011 2007 2008 2009 2010 2011 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 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

363

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

4 4 Washington - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S49. Summary statistics for natural gas - Washington, 2007-2011 2007 2008 2009 2010 2011 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 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

364

Million Cu. Feet Percent of National Total  

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

0 0 Maine - Natural Gas 2012 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, 2008-2012 2008 2009 2010 2011 2012 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 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0 0

365

Million Cu. Feet Percent of National Total  

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

8 8 Minnesota - Natural Gas 2012 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 S25. Summary statistics for natural gas - Minnesota, 2008-2012 2008 2009 2010 2011 2012 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 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0 0 0

366

Million Cu. Feet Percent of National Total  

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

2 2 South Carolina - Natural Gas 2012 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 S42. Summary statistics for natural gas - South Carolina, 2008-2012 2008 2009 2010 2011 2012 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 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

367

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

6 6 North Carolina - Natural Gas 2011 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 S35. Summary statistics for natural gas - North Carolina, 2007-2011 2007 2008 2009 2010 2011 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 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

368

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

0 0 Iowa - Natural Gas 2011 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, 2007-2011 2007 2008 2009 2010 2011 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 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0 0

369

Million Cu. Feet Percent of National Total  

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

4 4 Massachusetts - Natural Gas 2012 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, 2008-2012 2008 2009 2010 2011 2012 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 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

370

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

6 6 Minnesota - Natural Gas 2011 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 S25. Summary statistics for natural gas - Minnesota, 2007-2011 2007 2008 2009 2010 2011 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 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0 0 0

371

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

0 0 New Jersey - Natural Gas 2011 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 S32. Summary statistics for natural gas - New Jersey, 2007-2011 2007 2008 2009 2010 2011 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 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

372

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

0 0 Vermont - Natural Gas 2011 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 S47. Summary statistics for natural gas - Vermont, 2007-2011 2007 2008 2009 2010 2011 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 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0 0 0

373

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

8 8 Wisconsin - Natural Gas 2011 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 S51. Summary statistics for natural gas - Wisconsin, 2007-2011 2007 2008 2009 2010 2011 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 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0 0 0

374

Million Cu. Feet Percent of National Total  

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

8 8 North Carolina - Natural Gas 2012 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 S35. Summary statistics for natural gas - North Carolina, 2008-2012 2008 2009 2010 2011 2012 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 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

375

Million Cu. Feet Percent of National Total  

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

2 2 New Jersey - Natural Gas 2012 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 S32. Summary statistics for natural gas - New Jersey, 2008-2012 2008 2009 2010 2011 2012 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 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

376

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

0 0 Maryland - Natural Gas 2011 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 S22. Summary statistics for natural gas - Maryland, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 7 7 7 7 8 Production (million cubic feet) Gross Withdrawals From Gas Wells 35 28 43 43 34 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 35

377

Million Cu. Feet Percent of National Total  

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

0 0 New Hampshire - Natural Gas 2012 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 S31. Summary statistics for natural gas - New Hampshire, 2008-2012 2008 2009 2010 2011 2012 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 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

378

Million Cu. Feet Percent of National Total  

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

2 2 Maryland - Natural Gas 2012 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 S22. Summary statistics for natural gas - Maryland, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 7 7 7 8 9 Production (million cubic feet) Gross Withdrawals From Gas Wells 28 43 43 34 44 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 28

379

Million Cu. Feet Percent of National Total  

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

2 2 Missouri - Natural Gas 2012 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, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 0 0 0 53 100 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

380

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

2 2 Massachusetts - Natural Gas 2011 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, 2007-2011 2007 2008 2009 2010 2011 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 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

Note: This page contains sample records for the topic "type total stocks" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


381

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

0 0 South Carolina - Natural Gas 2011 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 S42. Summary statistics for natural gas - South Carolina, 2007-2011 2007 2008 2009 2010 2011 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 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

382

Million Cu. Feet Percent of National Total  

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

0 0 Rhode Island - Natural Gas 2012 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 S41. Summary statistics for natural gas - Rhode Island, 2008-2012 2008 2009 2010 2011 2012 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 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

383

TotalView Parallel Debugger at NERSC  

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

Totalview Totalview Totalview Description TotalView from Rogue Wave Software is a parallel debugging tool that can be run with up to 512 processors. It provides both X Windows-based Graphical User Interface (GUI) and command line interface (CLI) environments for debugging. 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 about some of the advanced TotalView features. Accessing Totalview at NERSC To use TotalView at NERSC, first load the TotalView modulefile to set the correct environment settings with the following command: % module load totalview Compiling Code to Run with TotalView In order to use TotalView, code must be compiled with the -g option. We

384

Property:Building/TotalFloorArea | Open Energy Information  

Open Energy Info (EERE)

Property Property Edit with form History Facebook icon Twitter icon » Property:Building/TotalFloorArea Jump to: navigation, search This is a property of type Number. Total floor area (BRA), m2 Pages using the property "Building/TotalFloorArea" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 19,657 + Sweden Building 05K0002 + 7,160 + Sweden Building 05K0003 + 4,855 + Sweden Building 05K0004 + 25,650 + Sweden Building 05K0005 + 2,260 + Sweden Building 05K0006 + 13,048 + Sweden Building 05K0007 + 24,155 + Sweden Building 05K0008 + 7,800 + Sweden Building 05K0009 + 34,755 + Sweden Building 05K0010 + 437 + Sweden Building 05K0011 + 15,310 + Sweden Building 05K0012 + 22,565 + Sweden Building 05K0013 + 19,551 +

385

Property:RenewableFuelStandard/Total | Open Energy Information  

Open Energy Info (EERE)

Total Total Jump to: navigation, search This is a property of type Number. Pages using the property "RenewableFuelStandard/Total" Showing 15 pages using this property. R Renewable Fuel Standard Schedule + 13.95 + Renewable Fuel Standard Schedule + 26 + Renewable Fuel Standard Schedule + 15.2 + Renewable Fuel Standard Schedule + 28 + Renewable Fuel Standard Schedule + 16.55 + Renewable Fuel Standard Schedule + 30 + Renewable Fuel Standard Schedule + 18.15 + Renewable Fuel Standard Schedule + 9 + Renewable Fuel Standard Schedule + 33 + Renewable Fuel Standard Schedule + 20.5 + Renewable Fuel Standard Schedule + 11.1 + Renewable Fuel Standard Schedule + 36 + Renewable Fuel Standard Schedule + 22.25 + Renewable Fuel Standard Schedule + 12.95 + Renewable Fuel Standard Schedule + 24 +

386

Empirically-driven hierarchical classification of stock keeping units  

Science Journals Connector (OSTI)

This paper proposes a hierarchical multi-criteria classification method developed for inventory management purposes and applied in a case study of the spare parts business of a household appliance manufacturer. The classification method is built on the basis of SIX dimensions, resulting in 12 different classes of spare parts, for which differentiated forecasting and inventory policies are proposed and tested. The results of our simulation study demonstrate the reduction of the total logistics costs by about 20% whilst still achieving the specified target service level for each class. Even more importantly, the proposed approach is simple enough to be understood and applied by company managers, thus increasing the probability of its adoption (in the same or similar fashion) in other real world settings.

A. Bacchetti; F. Plebani; N. Saccani; A.A. Syntetos

2013-01-01T23:59:59.000Z

387

Effect of Oil Price Volatility on Tunisian Stock Market at Sector-level and Effectiveness of Hedging Strategy  

Science Journals Connector (OSTI)

Abstract In this work, our objective is to study in a first step links and interaction between oil and stock markets in Tunisia in terms of volatility at the sector-level, and then in a second step to determine the best hedging strategy for oil-stock portfolio against the risk of negative variation in stock market prices. Our methodology consist to model the data by a bivariate GARCH model to capture the effect in terms of volatility in the variation of the oil price on the different sector index, and to use the conditional variances and conditional correlation to calculate the hedging ratio and determinate the best hedging strategy. The empirical results indicate that the majority of relationships are unidirectional from the oil market to Tunisian stock market, and the conditional variance of a stock sector returns is affected not only by the volatility surprises of the stock market, but also by those of oil market. The model GARCH-BEKK is more effective than the others versions to minimize the risk of oil-stock portfolio.

Wajdi Hamma; Anis Jarboui; Ahmed Ghorbel

2014-01-01T23:59:59.000Z

388

Window-Related Energy Consumption in the US Residential and Commercial Building Stock  

E-Print Network [OSTI]

the fraction of total energy consumption attributable toFraction of Total Energy Consumption Background Although thewindow fraction of total energy consumption. We believe that

Apte, Joshua; Arasteh, Dariush

2008-01-01T23:59:59.000Z

389

Million Cu. Feet Percent of National Total  

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

6 6 Tennessee - Natural Gas 2012 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, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 285 310 230 210 212 Production (million cubic feet) Gross Withdrawals From Gas Wells 4,700 5,478 5,144 4,851 5,825 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0

390

Million Cu. Feet Percent of National Total  

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

2 2 Connecticut - Natural Gas 2012 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 S7. Summary statistics for natural gas - Connecticut, 2008-2012 2008 2009 2010 2011 2012 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 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0

391

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

4 4 Oregon - Natural Gas 2011 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, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 18 21 24 26 24 Production (million cubic feet) Gross Withdrawals From Gas Wells 409 778 821 1,407 1,344 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0

392

Million Cu. Feet Percent of National Total  

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

6 6 District of Columbia - Natural Gas 2012 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, 2008-2012 2008 2009 2010 2011 2012 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 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0

393

Million Cu. Feet Percent of National Total  

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

6 6 Oregon - Natural Gas 2012 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, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 21 24 26 24 27 Production (million cubic feet) Gross Withdrawals From Gas Wells 778 821 1,407 1,344 770 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0

394

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

8 8 Georgia - Natural Gas 2011 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, 2007-2011 2007 2008 2009 2010 2011 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 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0

395

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

2 2 Delaware - Natural Gas 2011 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 S8. Summary statistics for natural gas - Delaware, 2007-2011 2007 2008 2009 2010 2011 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 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0

396

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

4 4 District of Columbia - Natural Gas 2011 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, 2007-2011 2007 2008 2009 2010 2011 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 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0

397

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

4 4 Tennessee - Natural Gas 2011 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, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 305 285 310 230 210 Production (million cubic feet) Gross Withdrawals From Gas Wells NA 4,700 5,478 5,144 4,851 From Oil Wells 3,942 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0

398

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

4 4 Nebraska - Natural Gas 2011 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, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 186 322 285 276 322 Production (million cubic feet) Gross Withdrawals From Gas Wells 1,331 2,862 2,734 2,092 1,854 From Oil Wells 228 221 182 163 126 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0

399

Million Cu. Feet Percent of National Total  

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

0 0 Georgia - Natural Gas 2012 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, 2008-2012 2008 2009 2010 2011 2012 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 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0

400

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

0 0 Connecticut - Natural Gas 2011 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 S7. Summary statistics for natural gas - Connecticut, 2007-2011 2007 2008 2009 2010 2011 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 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0

Note: This page contains sample records for the topic "type total stocks" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


401

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

6 6 Florida - Natural Gas 2011 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, 2007-2011 2007 2008 2009 2010 2011 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 2,000 2,742 290 13,938 17,129 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0

402

Million Cu. Feet Percent of National Total  

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

4 4 Delaware - Natural Gas 2012 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 S8. Summary statistics for natural gas - Delaware, 2008-2012 2008 2009 2010 2011 2012 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 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0

403

ARM - Measurement - Shortwave spectral total downwelling irradiance  

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

Shadowband Spectroradiometer SPEC-TOTDN : Shortwave Total Downwelling Spectrometer UAV-EGRETT : UAV-Egrett Value-Added Products VISST : Minnis Cloud Products Using Visst...

404

,"New York Natural Gas Total Consumption (MMcf)"  

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

Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","New York Natural Gas Total Consumption (MMcf)",1,"Annual",2013 ,"Release Date:","12312014"...

405

Total Supplemental Supply of Natural Gas  

Gasoline and Diesel Fuel Update (EIA)

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

406

Total Natural Gas Gross Withdrawals (Summary)  

Gasoline and Diesel Fuel Update (EIA)

Additions LNG Storage Withdrawals LNG Storage Net Withdrawals Total Consumption Lease and Plant Fuel Consumption Lease Fuel Plant Fuel Pipeline & Distribution Use Delivered to...

407

Million Cu. Feet Percent of National Total  

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

0 0 Indiana - Natural Gas 2012 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, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 525 563 620 914 819 Production (million cubic feet) Gross Withdrawals From Gas Wells 4,701 4,927 6,802 9,075 8,814 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0

408

The Behaviour of Base Metals in Arc-Type Magmatic-Hydrothermal Systems Insights from Merapi Volcano,  

E-Print Network [OSTI]

zone stratovolcanoes provide important windows on the magmatic-hydrothermal processes at playThe Behaviour of Base Metals in Arc-Type Magmatic- Hydrothermal Systems ­ Insights from Merapi systems include a shallow magmatic reservoir (the porphyry stock), an overlying hydrothermal cell, its

Barnes, Sarah-Jane

409

Stock type performance in addressing top-down and bottom-up factors for the restoration of indigenous trees  

E-Print Network [OSTI]

to the initial size and biomass of seedlings. Inversely, in plantations exposed to deer, the apparency hypothesis.07) that had been almost twice their biomass at the onset of plantation. The overall browsing occurrence Exclosure Competition Plantation White-tailed deer a b s t r a c t Using planted trees to restore

Laval, Université

410

Total Synthesis of Irciniastatin A (Psymberin)  

E-Print Network [OSTI]

Total Synthesis of Irciniastatin A (Psymberin) Michael T. Crimmins,* Jason M. Stevens, and Gregory, North Carolina 27599 crimmins@email.unc.edu Received July 21, 2009 ABSTRACT The total synthesis of a hemiaminal and acid chloride to complete the synthesis. In 2004, Pettit and Crews independently reported

411

TOTAL REFLUX OPERATION OF MULTIVESSEL BATCH DISTILLATION  

E-Print Network [OSTI]

TOTAL REFLUX OPERATION OF MULTIVESSEL BATCH DISTILLATION BERND WITTGENS, RAJAB LITTO, EVA S RENSEN a generalization of previously proposed batch distillation schemes. A simple feedback control strategy for total re verify the simulations. INTRODUCTION Although batch distillation generally is less energy e cient than

Skogestad, Sigurd

412

Type: Renewal  

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

1 INCITE Awards 1 INCITE Awards Type: Renewal Title: -Ab Initio Dynamical Simulations for the Prediction of Bulk Properties‖ Principal Investigator: Theresa Windus, Iowa State University Co-Investigators: Brett Bode, Iowa State University Graham Fletcher, Argonne National Laboratory Mark Gordon, Iowa State University Monica Lamm, Iowa State University Michael Schmidt, Iowa State University Scientific Discipline: Chemistry: Physical INCITE Allocation: 10,000,000 processor hours Site: Argonne National Laboratory Machine (Allocation): IBM Blue Gene/P (10,000,000 processor hours) Research Summary: This project uses high-quality electronic structure theory, statistical mechanical methods, and

413

U.S. Crude & Gasoline Stocks Low But Showing Signs of Recovering  

Gasoline and Diesel Fuel Update (EIA)

5 5 Notes: The current U.S. inventory levels for crude oil and gasoline stocks are low, but improved modestly in March. While crude oil inventories are still well below normal levels, they have increased about 10 million barrels since the end of January, despite the tight crude oil market. Gasoline stocks at the end of February had dropped about 5% below the low end of the normal range. But during March, they rose slightly, instead of dropping further as they normally would do. This allowed gasoline inventories to re-enter the low end of the normal band. While the inventory situation is improving, it remains low. With crude oil inventories still well below normal, and gasoline inventories on the low side of normal, we have little cushion to absorb unexpected events

414

SMA and MACD combinations for stock investment decisions in frontier markets: evidence from Dubai financial market  

Science Journals Connector (OSTI)

One of the most challenging financial decisions is when to buy and sell stocks. Frontier markets offer high profit opportunities but also have high risk. Consequently, technical analysis is used to assist in properly timing entry and exit points from stock trades. Previous research presented applications of technical analysis in developed and emerging markets since they, unlike frontier markets, exist in an environment of political stability, regulations, and liquidity. This paper shows how trade signals generated from Simple Moving Average (SMA) confirmed by Moving Average Convergence Divergence (MACD) can be used to minimise trading risk in frontier markets such as Dubai Financial Market (DFM). The results show that the standard time-periods for SMA and MACD do not apply well to frontier markets and that trade signals generated from SMA and confirmed by signals generated from medium to long-term MACD or vice versa result in excellent hit ratios.

Hazim El-Baz; Ibrahim Al Awadhi; Assia Lasfer

2013-01-01T23:59:59.000Z

415

Political geography and stock returns: The value and risk implications of proximity to political power  

Science Journals Connector (OSTI)

We show that political geography has a pervasive effect on the cross-section of stock returns. We collect election results over a 40-year period and use a political alignment index (PAI) of each state's leading politicians with the ruling (presidential) party to proxy for local firms’ proximity to political power. Firms whose headquarters are located in high PAI states outperform those located in low PAI states, both in terms of raw returns, and on a risk-adjusted basis. Overall, although we cannot rule out indirect political connectedness advantages as an explanation of the PAI effect, our results are consistent with the notion that proximity to political power has stock return implications because it reflects firms’ exposure to policy risk.

Chansog (Francis) Kim; Christos Pantzalis; Jung Chul Park

2012-01-01T23:59:59.000Z

416

How political risks and events have influenced Pakistan's stock markets from 1947 to the present  

Science Journals Connector (OSTI)

In this paper, we analyse Pakistan's political risks and events that have affected the country's stock markets since 1947. We collected data in the form of questionnaires from historians, economists, politicians, government officials, bankers and stock market analysts in Pakistan and make forecasts using Bayesian hierarchical modelling and Markov Chain Monte Carlo (MCMC) techniques. Findings show that the probability of an event in any year is relatively high with an average arrival rate of 1.5 events per year with no time trend. In addition, forecasts suggest that the level of political risk should be remaining unchanged for the foreseeable future. Finally, we find that Pakistan's political risk carries a risk premium of between 7.5% and 12%.

Omar Masood; Bruno S. Sergi

2008-01-01T23:59:59.000Z

417

Window-Related Energy Consumption in the US Residential andCommercial Building Stock  

SciTech Connect (OSTI)

We present a simple spreadsheet-based tool for estimating window-related energy consumption in the United States. Using available data on the properties of the installed US window stock, we estimate that windows are responsible for 2.15 quadrillion Btu (Quads) of heating energy consumption and 1.48 Quads of cooling energy consumption annually. We develop estimates of average U-factor and SHGC for current window sales. We estimate that a complete replacement of the installed window stock with these products would result in energy savings of approximately 1.2 quads. We demonstrate that future window technologies offer energy savings potentials of up to 3.9 Quads.

Apte, Joshua; Arasteh, Dariush

2006-06-16T23:59:59.000Z

418

Name Address Place Zip Sector Product Stock Symbol Year founded Number  

Open Energy Info (EERE)

Address Place Zip Sector Product Stock Symbol Year founded Number Address Place Zip Sector Product Stock Symbol Year founded Number of employees Number of employees Telephone number Website Coordinates Region ABS Alaskan Inc Van Horn Rd Fairbanks Alaska Gateway Solar Wind energy Marine and Hydrokinetic Solar PV Solar thermal Wind Hydro Small scale wind turbine up to kW and solar systems distributor http www absak com United States AER NY Kinetics LLC PO Box Entrance Avenue Ogdensburg Marine and Hydrokinetic United States AW Energy Lars Sonckin kaari Espoo FI Marine and Hydrokinetic http www aw energy com Finland AWS Ocean Energy formerly Oceanergia Redshank House Alness Point Business Park Alness Ross shire IV17 UP Marine and Hydrokinetic http www awsocean com United Kingdom Able Technologies Audubon Road Englewood Marine and Hydrokinetic http

419

Chapter 8 - An Econometric Analysis of the Impact of Oil Prices on Stock Markets in Gulf Cooperation Countries  

Science Journals Connector (OSTI)

Abstract This paper implements recent bootstrap panel cointegration techniques and Seemingly Unrelated Regression (SUR) methods to investigate the existence of a long-run relationship between oil prices and Gulf Cooperation Council (GCC) Countries stock markets. Since GCC countries are major world energy market players, their stock markets are likely to be susceptible to oil price shocks. Using two different (weekly and monthly) datasets covering, respectively, the periods from June 7, 2005 to October 21, 2008, and from January 1996 to December 2007, our investigation shows that there is evidence for cointegration of oil prices and stock markets in GCC countries, while the SUR results indicate that oil price increases have a positive impact on stock prices, except in Saudi Arabia.

Mohamed El Hedi Arouri; Christophe Rault

2014-01-01T23:59:59.000Z

420

Oil and stock market activity when prices go up and down: the case of the oil and gas industry  

Science Journals Connector (OSTI)

We examine the asymmetric effects of daily oil price changes on equity returns, market betas, oil betas, return variances, and trading volumes for the US oil and gas industry. The responses of stock returns assoc...

Sunil K. Mohanty; Aigbe Akhigbe…

2013-08-01T23:59:59.000Z

Note: This page contains sample records for the topic "type total stocks" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


421

Multi-Attribute Choice Model: An Application of the Generalized Nested Logit Model at the Stock-Keeping Unit Level  

Science Journals Connector (OSTI)

This paper proposes an application of the generalized nested logit (GNL) model which is used in transportation science for product choice problems at the stock-keeping unit level. I explain two alternative nestin...

Kei Takahashi

2011-01-01T23:59:59.000Z

422

Refinery Stocks of Crude Oil and Petroleum Products  

Gasoline and Diesel Fuel Update (EIA)

Product: Crude Oil and Petroleum Products Crude Oil Petroleum Products Pentanes Plus Liquefied Petroleum Gases Ethane/Ethylene Propane/Propylene Normal Butane/Butylene Isobutane/Isobutylene Oxygenates/Renewables/Other Hydrocarbons Oxygenates (excl. Fuel Ethanol) Methyl Tertiary Butyl Ether (MTBE) All Other Oxygenates Renewable Fuels (incl. Fuel Ethanol) Fuel Ethanol Renewable Diesel Fuel Other Renewable Fuels Other Hydrocarbons Unfinished Oils Naphthas and Lighter Kerosene and Light Gas Oils Heavy Gas Oils Residuum Motor Gasoline Blending Components MGBC - Reformulated MGBC - Reformulated - RBOB MGBC - RBOB for Blending with Alcohol* MGBC - RBOB for Blending with Ether* MGBC - Conventional MGBC - Conventional CBOB MGBC - Conventional GTAB MGBC - Conventional Other Aviation Gasoline Blending Components Finished Motor Gasoline Reformulated Reformulated Blended with Fuel Ethanol Reformulated, Other Conventional Gasoline Conventional Gasoline Blended with Fuel Ethanol Conventional Gasoline Blended with Fuel Ethanol, Ed55 and Lower Conventional Other Gasoline Finished Aviation Gasoline Kerosene-Type Jet Fuel Kerosene Distillate Fuel Oil Distillate Fuel Oil, 15 ppm and Under Distillate Fuel Oil, Greater than 15 ppm to 500 ppm Distillate Fuel Oil, Greater than 500 ppm Residual Fuel Oil Less than 0.31 Percent Sulfur 0.31 to 1.00 Percent Sulfur Greater than 1.00 Percent Sulfur Petrochemical Feedstocks Naphtha for Petrochemical Feedstock Use Other Oils for Petrochemical Feedstock Use Special Naphthas Lubricants Waxes Petroleum Coke Marketable Coke Asphalt and Road Oil Miscellaneous Products Period-Units: Monthly-Thousand Barrels Annual-Thousand Barrels

423

Bacteria Types  

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

Bacteria Types Bacteria Types Name: Evelyn Location: N/A Country: N/A Date: N/A Question: What is the significance of S. marcescens,M.luteus, S.epidermidis, and E. Coli? Which of these are gram-positive and gram-negative, and where can these be found? Also, what problems can they cause? When we culture these bacteria, we used four methods: plates, broth, slants, and pour plates. The media was made of TSB, TSA, NAP, and NAD. What is significant about these culturing methods? Replies: I could give you the answer to that question but it is more informative, and fun, to find out yourself. Start with the NCBI library online (http://www.ncbi.nlm.nih.gov/) and do a query with the species name, and 'virulence' if you want to know what they're doing to us. Have a look at the taxonomy devision to see how they are related. To find out if they're gram-pos or neg you should do a gram stain if you can. Otherwise you'll find that information in any bacteriology determination guide. Your question about the media is not specific enough so I can't answer it.

424

Evolution of stocks and massifs from burial of salt sheets, continental slope, northern Gulf of Mexico  

SciTech Connect (OSTI)

Salt structures in a 4000-km{sup 2} region of the continental slope, the northeast Green Canyon area, include stocks, massifs, remnant structures, and an allochthonous sheet. Salt-withdrawal basins include typical semicircular basins and an extensive linear trough that is largely salt-free. Counterregional growth faults truncate the landward margin of salt sheets that extend 30-50 km to the Sigsbee Escarpment. The withdrawal basins, stocks, and massifs occur within a large graben between an east-northeast-trending landward zone of shelf-margin growth faults and a parallel trend of counterregional growth faults located 48-64 km basinward. The graben formed by extension and subsidence as burial of the updip portion of a thick salt sheet produced massifs and stocks by downbuilding. Differential loading segmented the updip margin of the salt sheet into stocks and massifs separated by salt-withdrawal basins. Initially, low-relief structures evolved by trap-door growth as half-graben basins buried the salt sheet. Remnant-salt structures and a turtle-structure anticline overlay a salt-weld disconformity in sediments formerly separated by a salt sheet. Age of sediments below the weld is inferred to be be late Miocene to early Pliocene (4.6-5.3 Ma); age of sediments above the weld is late Pliocene (2.8-3.5 Ma). The missing interval of time (1-2.5 Ma) is the duration between emplacement of the salt sheet and burial of the sheet. Sheet extrusion began in the late Miocene to early Pliocene, and sheet burial began in the late Pliocene in the area of the submarine trough to early Pleistocene in the area of the massifs.

Seni, S.J. (Univ. of Texas, Austin (United States))

1991-03-01T23:59:59.000Z

425

The Language of the Stock Exchange – A Contrastive Analysis of the Lexis  

E-Print Network [OSTI]

Language of the Stock Exchange ... As to the structural aspect, a divergence had been expected of the following kind: SLO EN simple NP simple NP complex NP complex NP complex NP simple NP On the semantic level, an occasional discrepancy had been... anticipated between the meaning of a particular NP in isolation and that in a particular context (in differ- ent word combinations, most notably collocations), semantic tailoring being a feature of not only LGP (language for general purposes) but also LSP...

Božinovski, Biljana

2009-01-01T23:59:59.000Z

426

"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" 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 Industry","Supplier(b)","Supplier(c)","Supplier(b)","Supplier(c)","Factors" ,,"Total United States"

427

Decision-Making Aid Tool for the Evaluation and Improvement of the Energy Performance of Stock of Buildings  

E-Print Network [OSTI]

, the simulation of buildings stock is possible starting from the definition of some standard buildings. SIMBAD (SIMulator of Building And Devices) is the first HVAC toolbox developed under the MATLAB/SIMULINK environment. This toolbox provides a large..., the simulation of buildings stock is possible starting from the definition of some standard buildings. SIMBAD (SIMulator of Building And Devices) is the first HVAC toolbox developed under the MATLAB/SIMULINK environment. This toolbox provides a large...

Joutey, H. A.; Vaezi-Nejad, H.; Lahrech, R.

2005-01-01T23:59:59.000Z

428

Facility Type!  

Office of Legacy Management (LM)

ITY: ITY: --&L~ ----------- srct-r~ -----------~------~------- if yee, date contacted ------------- cl Facility Type! i I 0 Theoretical Studies Cl Sample 84 Analysis ] Production 1 Diepasal/Storage 'YPE OF CONTRACT .--------------- 1 Prime J Subcontract&- 1 Purchase Order rl i '1 ! Other information (i.e., ---------~---~--~-------- :ontrait/Pirchaee Order # , I C -qXlJ- --~-------~~-------~~~~~~ I I ~~~---~~~~~~~T~~~ FONTRACTING PERIODi IWNERSHIP: ,I 1 AECIMED AECMED GOVT GOUT &NTtiAC+OR GUN-I OWNED ----- LEEE!? M!s LE!Ps2 -LdJG?- ---L .ANDS ILJILDINGS X2UIPilENT IRE OR RAW HA-I-L :INAL PRODUCT IASTE Z. RESIDUE I I kility l pt I ,-- 7- ,+- &!d,, ' IN&"E~:EW AT SITE -' ---------------- , . Control 0 AEC/tlED managed operations

429

Property:Building/FloorAreaTotal | Open Energy Information  

Open Energy Info (EERE)

FloorAreaTotal FloorAreaTotal Jump to: navigation, search This is a property of type Number. Total Pages using the property "Building/FloorAreaTotal" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 19,657 + Sweden Building 05K0002 + 7,160 + Sweden Building 05K0003 + 4,454 + Sweden Building 05K0004 + 25,650 + Sweden Building 05K0005 + 2,260 + Sweden Building 05K0006 + 14,348 + Sweden Building 05K0007 + 24,155 + Sweden Building 05K0008 + 7,800 + Sweden Building 05K0009 + 34,755 + Sweden Building 05K0010 + 437 + Sweden Building 05K0011 + 15,300 + Sweden Building 05K0012 + 22,565 + Sweden Building 05K0013 + 19,551 + Sweden Building 05K0014 + 1,338.3 + Sweden Building 05K0015 + 1,550 + Sweden Building 05K0016 + 2,546 +

430

Property:Building/SPElectrtyUsePercTotal | Open Energy Information  

Open Energy Info (EERE)

SPElectrtyUsePercTotal SPElectrtyUsePercTotal Jump to: navigation, search This is a property of type String. Total Pages using the property "Building/SPElectrtyUsePercTotal" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 100.0 + Sweden Building 05K0002 + 100.0 + Sweden Building 05K0003 + 100.0 + Sweden Building 05K0004 + 100.0 + Sweden Building 05K0005 + 100.0 + Sweden Building 05K0006 + 100.0 + Sweden Building 05K0007 + 100.0 + Sweden Building 05K0008 + 100.0 + Sweden Building 05K0009 + 100.0 + Sweden Building 05K0010 + 100.0 + Sweden Building 05K0011 + 100.0 + Sweden Building 05K0012 + 100.0 + Sweden Building 05K0013 + 100.0 + Sweden Building 05K0014 + 100.0 + Sweden Building 05K0015 + 100.0 + Sweden Building 05K0016 + 100.0 +

431

Million Cu. Feet Percent of National Total  

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

8 8 Illinois - Natural Gas 2012 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, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 45 51 50 40 40 Production (million cubic feet) Gross Withdrawals From Gas Wells E 1,188 E 1,438 E 1,697 2,114 2,125 From Oil Wells E 5 E 5 E 5 7 0 From Coalbed Wells E 0 E 0 0 0 0 From Shale Gas Wells 0

432

Million Cu. Feet Percent of National Total  

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

50 50 North Dakota - Natural Gas 2012 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, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 194 196 188 239 211 Production (million cubic feet) Gross Withdrawals From Gas Wells 13,738 11,263 10,501 14,287 22,261 From Oil Wells 54,896 45,776 38,306 27,739 17,434 From Coalbed Wells 0

433

Million Cu. Feet Percent of National Total  

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

0 0 Mississippi - Natural Gas 2012 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, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 2,343 2,320 1,979 5,732 1,669 Production (million cubic feet) Gross Withdrawals From Gas Wells 331,673 337,168 387,026 429,829 404,457 From Oil Wells 7,542 8,934 8,714 8,159 43,421 From Coalbed Wells 7,250

434

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

2 2 Virginia - Natural Gas 2011 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, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 5,735 6,426 7,303 7,470 7,903 Production (million cubic feet) Gross Withdrawals From Gas Wells R 6,681 R 7,419 R 16,046 R 23,086 20,375 From Oil Wells 0 0 0 0 0 From Coalbed Wells R 86,275 R 101,567

435

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

4 4 Michigan - Natural Gas 2011 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, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 9,712 9,995 10,600 10,100 11,100 Production (million cubic feet) Gross Withdrawals From Gas Wells R 80,090 R 16,959 R 20,867 R 7,345 18,470 From Oil Wells 54,114 10,716 12,919 9,453 11,620 From Coalbed Wells 0

436

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

2 2 Montana - Natural Gas 2011 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, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 6,925 7,095 7,031 6,059 6,477 Production (million cubic feet) Gross Withdrawals From Gas Wells R 69,741 R 67,399 R 57,396 R 51,117 37,937 From Oil Wells 23,092 22,995 21,522 19,292 21,777 From Coalbed Wells

437

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

8 8 Mississippi - Natural Gas 2011 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, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 2,315 2,343 2,320 1,979 5,732 Production (million cubic feet) Gross Withdrawals From Gas Wells R 259,001 R 331,673 R 337,168 R 387,026 429,829 From Oil Wells 6,203 7,542 8,934 8,714 8,159 From Coalbed Wells

438

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

8 8 Indiana - Natural Gas 2011 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, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 2,350 525 563 620 914 Production (million cubic feet) Gross Withdrawals From Gas Wells 3,606 4,701 4,927 6,802 9,075 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0

439

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

4 4 New York - Natural Gas 2011 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, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 6,680 6,675 6,628 6,736 6,157 Production (million cubic feet) Gross Withdrawals From Gas Wells 54,232 49,607 44,273 35,163 30,495 From Oil Wells 710 714 576 650 629 From Coalbed Wells 0

440

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

6 6 Texas - Natural Gas 2011 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, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 76,436 87,556 93,507 95,014 100,966 Production (million cubic feet) Gross Withdrawals From Gas Wells R 4,992,042 R 5,285,458 R 4,860,377 R 4,441,188 3,794,952 From Oil Wells 704,092 745,587 774,821 849,560 1,073,301

Note: This page contains sample records for the topic "type total stocks" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


441

Million Cu. Feet Percent of National Total  

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

2 2 Ohio - Natural Gas 2012 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, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 34,416 34,963 34,931 46,717 35,104 Production (million cubic feet) Gross Withdrawals From Gas Wells 79,769 83,511 73,459 30,655 65,025 From Oil Wells 5,072 5,301 4,651 45,663 6,684 From Coalbed Wells 0

442

Million Cu. Feet Percent of National Total  

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

0 0 Colorado - Natural Gas 2012 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, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 25,716 27,021 28,813 30,101 32,000 Production (million cubic feet) Gross Withdrawals From Gas Wells 496,374 459,509 526,077 563,750 1,036,572 From Oil Wells 199,725 327,619 338,565

443

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

2 2 South Dakota - Natural Gas 2011 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 S43. Summary statistics for natural gas - South Dakota, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 71 71 89 102 100 Production (million cubic feet) Gross Withdrawals From Gas Wells 422 R 1,098 R 1,561 1,300 933 From Oil Wells 11,458 10,909 11,366 11,240 11,516 From Coalbed Wells 0 0

444

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

6 6 Illinois - Natural Gas 2011 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, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 43 45 51 50 40 Production (million cubic feet) Gross Withdrawals From Gas Wells RE 1,389 RE 1,188 RE 1,438 RE 1,697 2,114 From Oil Wells E 5 E 5 E 5 E 5 7 From Coalbed Wells RE 0 RE

445

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

8 8 Colorado - Natural Gas 2011 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, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 22,949 25,716 27,021 28,813 30,101 Production (million cubic feet) Gross Withdrawals From Gas Wells R 436,330 R 496,374 R 459,509 R 526,077 563,750 From Oil Wells 160,833 199,725 327,619

446

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

0 0 Alaska - Natural Gas 2011 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, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 239 261 261 269 277 Production (million cubic feet) Gross Withdrawals From Gas Wells 165,624 150,483 137,639 127,417 112,268 From Oil Wells 3,313,666 3,265,401 3,174,747 3,069,683 3,050,654

447

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

0 0 Ohio - Natural Gas 2011 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, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 34,416 34,416 34,963 34,931 46,717 Production (million cubic feet) Gross Withdrawals From Gas Wells R 82,812 R 79,769 R 83,511 R 73,459 30,655 From Oil Wells 5,268 5,072 5,301 4,651 45,663 From Coalbed Wells

448

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

4 4 Kentucky - Natural Gas 2011 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, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 16,563 16,290 17,152 17,670 14,632 Production (million cubic feet) Gross Withdrawals From Gas Wells 95,437 R 112,587 R 111,782 133,521 122,578 From Oil Wells 0 1,529 1,518 1,809 1,665 From Coalbed Wells 0

449

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

8 8 Utah - Natural Gas 2011 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, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 5,197 5,578 5,774 6,075 6,469 Production (million cubic feet) Gross Withdrawals From Gas Wells R 271,890 R 331,143 R 340,224 R 328,135 351,168 From Oil Wells 35,104 36,056 36,795 42,526 49,947 From Coalbed Wells

450

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

6 6 California - Natural Gas 2011 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, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 1,540 1,645 1,643 1,580 1,308 Production (million cubic feet) Gross Withdrawals From Gas Wells 93,249 91,460 82,288 73,017 63,902 From Oil Wells R 116,652 R 122,345 R 121,949 R 151,369 120,880

451

Million Cu. Feet Percent of National Total  

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

0 0 Utah - Natural Gas 2012 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, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 5,578 5,774 6,075 6,469 6,900 Production (million cubic feet) Gross Withdrawals From Gas Wells 331,143 340,224 328,135 351,168 402,899 From Oil Wells 36,056 36,795 42,526 49,947 31,440 From Coalbed Wells 74,399

452

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

6 6 Louisiana - Natural Gas 2011 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, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 18,145 19,213 18,860 19,137 21,235 Production (million cubic feet) Gross Withdrawals From Gas Wells R 1,261,539 R 1,288,559 R 1,100,007 R 911,967 883,712 From Oil Wells 106,303 61,663 58,037 63,638 68,505

453

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

2 2 Oklahoma - Natural Gas 2011 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, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 38,364 41,921 43,600 44,000 41,238 Production (million cubic feet) Gross Withdrawals From Gas Wells R 1,583,356 R 1,452,148 R 1,413,759 R 1,140,111 1,281,794 From Oil Wells 35,186 153,227 92,467 210,492 104,703

454

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

2 2 New Mexico - Natural Gas 2011 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, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 42,644 44,241 44,784 44,748 32,302 Production (million cubic feet) Gross Withdrawals From Gas Wells R 657,593 R 732,483 R 682,334 R 616,134 556,024 From Oil Wells 227,352 211,496 223,493 238,580 252,326

455

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

6 6 West Virginia - Natural Gas 2011 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, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 48,215 49,364 50,602 52,498 56,813 Production (million cubic feet) Gross Withdrawals From Gas Wells R 189,968 R 191,444 R 192,896 R 151,401 167,113 From Oil Wells 701 0 0 0 0 From Coalbed Wells

456

Million Cu. Feet Percent of National Total  

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

6 6 Michigan - Natural Gas 2012 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, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 9,995 10,600 10,100 11,100 10,900 Production (million cubic feet) Gross Withdrawals From Gas Wells 16,959 20,867 7,345 18,470 17,041 From Oil Wells 10,716 12,919 9,453 11,620 4,470 From Coalbed Wells 0

457

Million Cu. Feet Percent of National Total  

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

8 8 West Virginia - Natural Gas 2012 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, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 49,364 50,602 52,498 56,813 50,700 Production (million cubic feet) Gross Withdrawals From Gas Wells 191,444 192,896 151,401 167,113 397,313 From Oil Wells 0 0 0 0 1,477 From Coalbed Wells 0

458

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

80 80 Wyoming - Natural Gas 2011 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 S52. Summary statistics for natural gas - Wyoming, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 27,350 28,969 25,710 26,124 26,180 Production (million cubic feet) Gross Withdrawals From Gas Wells R 1,649,284 R 1,764,084 R 1,806,807 R 1,787,599 1,709,218 From Oil Wells 159,039 156,133 135,269 151,871 152,589

459

Million Cu. Feet Percent of National Total  

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

6 6 New York - Natural Gas 2012 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, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 6,675 6,628 6,736 6,157 7,176 Production (million cubic feet) Gross Withdrawals From Gas Wells 49,607 44,273 35,163 30,495 25,985 From Oil Wells 714 576 650 629 439 From Coalbed Wells 0

460

Million Cu. Feet Percent of National Total  

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

2 2 Wyoming - Natural Gas 2012 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 S52. Summary statistics for natural gas - Wyoming, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 28,969 25,710 26,124 26,180 22,171 Production (million cubic feet) Gross Withdrawals From Gas Wells 1,764,084 1,806,807 1,787,599 1,709,218 1,762,095 From Oil Wells 156,133 135,269 151,871 152,589 24,544

Note: This page contains sample records for the topic "type total stocks" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


461

Million Cu. Feet Percent of National Total  

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

4 4 Virginia - Natural Gas 2012 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, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 6,426 7,303 7,470 7,903 7,843 Production (million cubic feet) Gross Withdrawals From Gas Wells 7,419 16,046 23,086 20,375 21,802 From Oil Wells 0 0 0 0 9 From Coalbed Wells 101,567 106,408

462

Million Cu. Feet Percent of National Total  

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

6 6 Kentucky - Natural Gas 2012 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, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 16,290 17,152 17,670 14,632 17,936 Production (million cubic feet) Gross Withdrawals From Gas Wells 112,587 111,782 133,521 122,578 106,122 From Oil Wells 1,529 1,518 1,809 1,665 0 From Coalbed Wells 0

463

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

6 6 Pennsylvania - Natural Gas 2011 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, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 52,700 55,631 57,356 44,500 54,347 Production (million cubic feet) Gross Withdrawals From Gas Wells 182,277 R 188,538 R 184,795 R 173,450 242,305 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0

464

Total synthesis and study of myrmicarin alkaloids  

E-Print Network [OSTI]

I. Enantioselective Total Synthesis of Tricyclic Myrmicarin Alkaloids An enantioselective gram-scale synthesis of a key dihydroindolizine intermediate for the preparation of myrmicarin alkaloids is described. Key transformations ...

Ondrus, Alison Evelynn, 1981-

2009-01-01T23:59:59.000Z

465

Total synthesis of cyclotryptamine and diketopiperazine alkaloids  

E-Print Network [OSTI]

I. Total Synthesis of the (+)-12,12'-Dideoxyverticillin A The fungal metabolite (+)-12,12'-dideoxyverticillin A, a cytotoxic alkaloid isolated from a marine Penicillium sp., belongs to a fascinating family of densely ...

Kim, Justin, Ph. D. Massachusetts Institute of Technology

2013-01-01T23:59:59.000Z

466

Provides Total Tuition Charge to Source Contribution  

E-Print Network [OSTI]

,262 1,938 TGR 4-20 0-3 2,871 2,871 - % of time appointed Hours of Work/Week Units TAL Provides Total

Kay, Mark A.

467

Enantioselective Total Synthesis of (?)-Acylfulvene and (?)- Irofulven  

E-Print Network [OSTI]

We report our full account of the enantioselective total synthesis of (?)-acylfulvene (1) and (?)-irofulven (2), which features metathesis reactions for the rapid assembly of the molecular framework of these antitumor ...

Movassaghi, Mohammad

468

A GENUINELY HIGH ORDER TOTAL VARIATION DIMINISHING ...  

E-Print Network [OSTI]

(TVD) schemes solving one-dimensional scalar conservation laws degenerate to first order .... where the total variation is measured by the standard bounded variation ..... interval Ij and into the jump discontinuities at cell interfaces, see [12].

469

Million Cu. Feet Percent of National Total  

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

8 8 Texas - Natural Gas 2012 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, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 87,556 93,507 95,014 100,966 96,617 Production (million cubic feet) Gross Withdrawals From Gas Wells 5,285,458 4,860,377 4,441,188 3,794,952 3,619,901 From Oil Wells 745,587 774,821 849,560 1,073,301 860,675

470

Million Cu. Feet Percent of National Total  

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

0 0 Alabama - Natural Gas 2012 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, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 6,860 6,913 7,026 7,063 6,327 Production (million cubic feet) Gross Withdrawals From Gas Wells 158,964 142,509 131,448 116,872 114,407 From Oil Wells 6,368 5,758 6,195 5,975 10,978

471

Million Cu. Feet Percent of National Total  

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

8 8 Louisiana - Natural Gas 2012 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, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 19,213 18,860 19,137 21,235 19,792 Production (million cubic feet) Gross Withdrawals From Gas Wells 1,288,559 1,100,007 911,967 883,712 775,506 From Oil Wells 61,663 58,037 63,638 68,505 49,380

472

Million Cu. Feet Percent of National Total  

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

4 4 South Dakota - Natural Gas 2012 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 S43. Summary statistics for natural gas - South Dakota, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 71 89 102 100 95 Production (million cubic feet) Gross Withdrawals From Gas Wells 1,098 1,561 1,300 933 14,396 From Oil Wells 10,909 11,366 11,240 11,516 689 From Coalbed Wells 0 0 0 0 0

473

Million Cu. Feet Percent of National Total  

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

4 4 Kansas - Natural Gas 2012 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, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 17,862 21,243 22,145 25,758 24,697 Production (million cubic feet) Gross Withdrawals From Gas Wells 286,210 269,086 247,651 236,834 264,610 From Oil Wells 45,038 42,647 39,071 37,194 0 From Coalbed Wells 44,066

474

Million Cu. Feet Percent of National Total  

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

6 6 Arkansas - Natural Gas 2012 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, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 5,592 6,314 7,397 8,388 8,538 Production (million cubic feet) Gross Withdrawals From Gas Wells 173,975 164,316 152,108 132,230 121,684 From Oil Wells 7,378 5,743 5,691 9,291 3,000

475

Million Cu. Feet Percent of National Total  

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

8 8 California - Natural Gas 2012 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, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 1,645 1,643 1,580 1,308 1,423 Production (million cubic feet) Gross Withdrawals From Gas Wells 91,460 82,288 73,017 63,902 120,579 From Oil Wells 122,345 121,949 151,369 120,880 70,900

476

Million Cu. Feet Percent of National Total  

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

4 4 Oklahoma - Natural Gas 2012 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, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 41,921 43,600 44,000 41,238 40,000 Production (million cubic feet) Gross Withdrawals From Gas Wells 1,452,148 1,413,759 1,140,111 1,281,794 1,394,859 From Oil Wells 153,227 92,467 210,492 104,703 53,720

477

Million Cu. Feet Percent of National Total  

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

2 2 Alaska - Natural Gas 2012 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, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 261 261 269 277 185 Production (million cubic feet) Gross Withdrawals From Gas Wells 150,483 137,639 127,417 112,268 107,873 From Oil Wells 3,265,401 3,174,747 3,069,683 3,050,654 3,056,918

478

Residential Energy Consumption Survey Results: Total Energy Consumption,  

Open Energy Info (EERE)

Survey Results: Total Energy Consumption, Survey Results: Total Energy Consumption, Expenditures, and Intensities (2005) Dataset Summary Description The Residential Energy Consumption Survey (RECS) is a national survey that collects residential energy-related data. The 2005 survey collected data from 4,381 households in housing units statistically selected to represent the 111.1 million housing units in the U.S. Data were obtained from residential energy suppliers for each unit in the sample to produce the Consumption & Expenditures data. The Consumption & Expenditures and Intensities data is divided into two parts: Part 1 provides energy consumption and expenditures by census region, population density, climate zone, type of housing unit, year of construction and ownership status; Part 2 provides the same data according to household size, income category, race and age. The next update to the RECS survey (2009 data) will be available in 2011.

479

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" 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 Industry","Total","Northeast","Midwest","South","West","Factors" ,"RSE Column Factors:",0.7,1.2,1.1,0.9,1.2 "20-39","ALL INDUSTRY GROUPS" ,"Participation in One or More of the Following Types of Programs",12605,1209,3303,6386,1706,2.9

480

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" 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 Industry","Total","Northeast","Midwest","South","West","Factors" ,"RSE Column Factors:",0.7,1.3,1,0.9,1.2 "20-39","ALL INDUSTRY GROUPS" ,"Participation in One or More of the Following Types of Programs",10743,1150,2819,5309,1464,2.6,,,"/WIR{D}~"

Note: This page contains sample records for the topic "type total stocks" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


481

| Los Alamos National Laboratory | Total Scattering Developments forTotal Scattering Developments for  

E-Print Network [OSTI]

Laboratory | Total Scattering at the Lujan Center Neutron Powder Diffractometer (NPDF) High-Intensity Powder. Shoemaker, et al., Reverse Monte Carlo neutron scattering study of disordered crystalline materials neutron| Los Alamos National Laboratory | Total Scattering Developments forTotal Scattering Developments

Magee, Joseph W.

482

Energy Perspectives, Total Energy - Energy Information Administration  

Gasoline and Diesel Fuel Update (EIA)

Total Energy Total Energy Glossary › FAQS › Overview Data Monthly Annual Analysis & Projections this will be filled with a highchart PREVIOUSNEXT Energy Perspectives 1949-2011 September 2012 PDF | previous editions Release Date: September 27, 2012 Introduction Energy Perspectives is a graphical overview of energy history in the United States. The 42 graphs shown here reveal sweeping trends related to the Nation's production, consumption, and trade of energy from 1949 through 2011. Energy Flow, 2011 (Quadrillion Btu) Total Energy Flow diagram image For footnotes see here. Energy can be grouped into three broad categories. First, and by far the largest, is the fossil fuels-coal, petroleum, and natural gas. Fossil fuels have stored the sun's energy over millennia past, and it is primarily

483

ARM - Measurement - Net broadband total irradiance  

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

govMeasurementsNet broadband total irradiance 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 instrument for a list of all available measurements, including those recorded for diagnostic or quality assurance purposes. ARM Instruments EBBR : Energy Balance Bowen Ratio Station SEBS : Surface Energy Balance System External Instruments ECMWF : European Centre for Medium Range Weather Forecasts Model

484

Total Cross Sections for Neutron Scattering  

E-Print Network [OSTI]

Measurements of neutron total cross-sections are both extensive and extremely accurate. Although they place a strong constraint on theoretically constructed models, there are relatively few comparisons of predictions with experiment. The total cross-sections for neutron scattering from $^{16}$O and $^{40}$Ca are calculated as a function of energy from $50-700$~MeV laboratory energy with a microscopic first order optical potential derived within the framework of the Watson expansion. Although these results are already in qualitative agreement with the data, the inclusion of medium corrections to the propagator is essential to correctly predict the energy dependence given by the experiment.

C. R. Chinn; Ch. Elster; R. M. Thaler; S. P. Weppner

1994-10-19T23:59:59.000Z

485

National Fuel Cell and Hydrogen Energy Overview: Total Energy...  

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

and Hydrogen Energy Overview: Total Energy USA 2012 National Fuel Cell and Hydrogen Energy Overview: Total Energy USA 2012 Presentation by Sunita Satyapal at the Total Energy USA...

486

Maximizing net income for pork producers by determining the interaction between dietary energy concentration and stocking density on finishing pig performance, welfare, and carcass composition.  

E-Print Network [OSTI]

??Marketplace volatility in the pork industry demands that producers re-evaluate production practices in order to remain profitable. Stocking density and dietary energy concentration independently affect… (more)

Rozeboom, Garrett

2015-01-01T23:59:59.000Z

487

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

E-Print Network [OSTI]

the US EIA Commercial Buildings Energy Consumption Survey (2: US commercial building stock energy consumption and floorof time varying energy consumption in the US commercial

Coffey, Brian

2010-01-01T23:59:59.000Z

488

Duck Valley Reservoirs Fish Stocking and Operation and Maintenance, 2005-2006 Annual Progress Report.  

SciTech Connect (OSTI)

The Duck Valley Reservoirs Fish Stocking and Operations and Maintenance (DV Fisheries) project is an ongoing resident fish program designed to enhance both subsistence fishing, educational opportunities for Tribal members of the Shoshone-Paiute Tribes, and recreational fishing facilities for non-Tribal members. In addition to stocking rainbow trout (Oncorhynchus mykiss) in Mountain View, Lake Billy Shaw, and Sheep Creek Reservoirs, the program also intends to afford and maintain healthy aquatic conditions for fish growth and survival, to provide superior facilities with wilderness qualities to attract non-Tribal angler use, and to offer clear, consistent communication with the Tribal community about this project as well as outreach and education within the region and the local community. Tasks for this performance period are divided into operations and maintenance plus monitoring and evaluation. Operation and maintenance of the three reservoirs include fences, roads, dams and all reservoir structures, feeder canals, water troughs and stock ponds, educational signs, vehicles and equipment, and outhouses. Monitoring and evaluation activities included creel, gillnet, wildlife, and bird surveys, water quality and reservoir structures monitoring, native vegetation planting, photo point documentation, control of encroaching exotic vegetation, and community outreach and education. The three reservoirs are monitored in terms of water quality and fishery success. Sheep Creek Reservoir was the least productive as a result of high turbidity levels and constraining water quality parameters. Lake Billy Shaw trout were in poorer condition than in previous years potentially as a result of water quality or other factors. Mountain View Reservoir trout exhibit the best health of the three reservoirs and was the only reservoir to receive constant flows of water.

Sellman, Jake; Dykstra, Tim [Shoshone-Paiute Tribes

2009-05-11T23:59:59.000Z

489

Cooling slope casting to produce EN AW 6082 forging stock for manufacture of suspension components  

Science Journals Connector (OSTI)

Abstract The potential of cooling slope casting process to produce EN AW 6082 forging stock for the manufacture of EN AW 6082 suspension components was investigated. EN AW 6082 billets cast over a cooling plate offer a fine uniform structure that can be forged even without a separate homogenization treatment. This is made it possible by the limited superheat of the melt at the start of casting and the fractional solidification that occurs already on the cooling plate. Suspension parts forged from cast and homogenized billets with or without Cr all showed a uniform structure, and the hardness reached HV 110 after the standard artificial ageing treatment.

Yucel BIROL; Seracettin AKDI

2014-01-01T23:59:59.000Z

490

U.S. Department of Energy Commercial Reference Building Models of the National Building Stock  

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

Department of Energy Department of Energy Commercial Reference Building Models of the National Building Stock Michael Deru, Kristin Field, Daniel Studer, Kyle Benne, Brent Griffith, and Paul Torcellini National Renewable Energy Laboratory Bing Liu, Mark Halverson, Dave Winiarski, and Michael Rosenberg Pacific Northwest National Laboratory Mehry Yazdanian Lawrence Berkeley National Laboratory Joe Huang Formerly of Lawrence Berkeley National Laboratory Drury Crawley Formerly of the U.S. Department of Energy Technical Report NREL/TP-5500-46861 February 2011 NREL is a national laboratory of the U.S. Department of Energy, Office of Energy Efficiency & Renewable Energy, operated by the Alliance for Sustainable Energy, LLC. National Renewable Energy Laboratory

491

Million U.S. Housing Units Total............................................................................  

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

Attached Attached 2 to 4 Units Table HC2.12 Home Electronics Usage Indicators by Type of Housing Unit, 2005 5 or More Units Mobile Homes Type of Housing Unit Housing Units (millions) Single-Family Units Apartments in Buildings With-- Home Electronics Usage Indicators Detached Energy Information Administration: 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Million U.S. Housing Units Attached 2 to 4 Units Table HC2.12 Home Electronics Usage Indicators by Type of Housing Unit, 2005 5 or More Units Mobile Homes Type of Housing Unit Housing Units (millions) Single-Family Units Apartments in Buildings With-- Home Electronics Usage Indicators Detached Status of PC When Not in Use Left On..............................................................

492

Million U.S. Housing Units Total...............................  

Gasoline and Diesel Fuel Update (EIA)

... 13.2 10.2 0.6 0.3 1.1 1.1 Table HC2.10 Home Appliances Usage Indicators by Type of Housing Unit, 2005 Housing Units (millions) Single-Family Units...

493

The Leica TCRA1105 Reflectorless Total Station  

SciTech Connect (OSTI)

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.

Gaudreault, F.

2005-09-06T23:59:59.000Z

494

TOTAL REFLUX OPERATION OF MULTIVESSEL BATCH DISTILLATION  

E-Print Network [OSTI]

TOTAL REFLUX OPERATION OF MULTIVESSEL BATCH DISTILLATION BERND WITTGENS, RAJAB LITTO, EVA SĂ?RENSEN in this paper provides a generalization of previously proposed batch distillation schemes. A simple feedback been built and the experiments verify the simulations. INTRODUCTION Although batch distillation

Skogestad, Sigurd

495

Total Solar Irradiance Satellite Composites and their  

E-Print Network [OSTI]

Chapter 12 Total Solar Irradiance Satellite Composites and their Phenomenological Effect on Climate. Phenomenological solar signature on climate 310 9. Conclusion 312 1. INTRODUCTION A contiguoustotal solar from each other, in particular about whether the TSI minimum during solar Cycles 22e23 (1995

Scafetta, Nicola

496

U.S. Total No. 2 Distillate Prices by Sales Type  

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

Area: U.S. East Coast (PADD 1) New England (PADD 1A) Connecticut Maine Massachusetts New Hampshire Rhode Island Vermont Central Atlantic (PADD 1B) Delaware District of Columbia...

497

Table 40. U.S. Coal Stocks at Manufacturing Plants by North American Industry Classification System (NAICS) Code  

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

0. U.S. Coal Stocks at Manufacturing Plants by North American Industry Classification System (NAICS) Code 0. U.S. Coal Stocks at Manufacturing Plants by North American Industry Classification System (NAICS) Code (thousand short tons) U.S. Energy Information Administration | Quarterly Coal Report, April - June 2013 Table 40. U.S. Coal Stocks at Manufacturing Plants by North American Industry Classification System (NAICS) Code (thousand short tons) U.S. Energy Information Administration | Quarterly Coal Report, April - June 2013 NAICS Code June 30, 2013 March 31, 2013 June 30, 2012 Percent Change (June 30) 2013 versus 2012 311 Food Manufacturing 875 926 1,015 -13.9 312 Beverage and Tobacco Product Mfg. 26 17 19 35.8 313 Textile Mills 22 22 25 -13.9 315 Apparel Manufacturing w w w w 321 Wood Product Manufacturing w w w w 322 Paper Manufacturing 570 583

498

Conditional correlations and volatility spillovers between crude oil and stock index returns  

Science Journals Connector (OSTI)

This paper investigates the conditional correlations and volatility spillovers between the crude oil and financial markets, based on crude oil returns and stock index returns. Daily returns from 2 January 1998 to 4 November 2009 of the crude oil spot, forward and futures prices from the WTI and Brent markets, and the FTSE100, NYSE, Dow Jones and S&P500 stock index returns, are analysed using the CCC model of Bollerslev (1990), VARMA-GARCH model of Ling and McAleer (2003), VARMA-AGARCH model of McAleer, Hoti, and Chan (2008), and DCC model of Engle (2002). Based on the CCC model, the estimates of conditional correlations for returns across markets are very low, and some are not statistically significant, which means the conditional shocks are correlated only in the same market and not across markets. However, the DCC estimates of the conditional correlations are always significant. This result makes it clear that the assumption of constant conditional correlations is not supported empirically. Surprisingly, the empirical results from the VARMA-GARCH and VARMA-AGARCH models provide little evidence of volatility spillovers between the crude oil and financial markets. The evidence of asymmetric effects of negative and positive shocks of equal magnitude on the conditional variances suggests that VARMA-AGARCH is superior to VARMA-GARCH and CCC.

Chia-Lin Chang; Michael McAleer; Roengchai Tansuchat

2013-01-01T23:59:59.000Z

499

Microscopic determinants of the weak-form efficiency of an artificial order-driven stock market  

E-Print Network [OSTI]

Stock markets are efficient in the weak form in the sense that no significant autocorrelations can be identified in the returns. However, the microscopic mechanisms are unclear. We aim at understanding the impacts of order flows on the weak-form efficiency through computational experiments based on an empirical order-driven model. Three possible determinants embedded in the model are investigated, including the tail heaviness of relative prices of the placed orders characterized by the tail index $\\alpha_x$, the degree of long memory in relative prices quantified by its Hurst index $H_x$, and the strength of long memory in order direction depicted by $H_x$. It is found that the degree of autocorrelations in returns (quantified by its Hurst index $H_r$) is negatively correlated with $\\alpha_x$ and $H_x$ and positively correlated with $H_s$. In addition, the values of $\\alpha_x$ and $H_x$ have negligible impacts on $H_r$, whereas $H_s$ exhibits a dominating impact on $H_r$. Our results suggest that stock market...

Zhou, Jian; Jiang, Zhi-Qiang; Xiong, Xiong; Zhang, Wei; Zhou, Wei-Xing

2014-01-01T23:59:59.000Z

500

ARM - Measurement - Shortwave broadband total downwelling irradiance  

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

downwelling irradiance 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 instruments. Refer to the datastream (netcdf) file headers of each instrument for a list of all available measurements, including those recorded for diagnostic or quality assurance purposes. ARM Instruments AMC : Ameriflux Measurement Component BSRN : Baseline Solar Radiation Network