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  1. Electricity Subsector Cybersecurity Capability Maturity Model...

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

    Electricity Subsector Cybersecurity Capability Maturity Model (ES-C2M2) Electricity Subsector Cybersecurity Capability Maturity Model (ES-C2M2) Electricity Subsector Cybersecurity ...

  2. Integrating Electricity Subsector

    Energy Savers [EERE]

    Integrating Electricity Subsector Failure Scenarios into a Risk Assessment Methodology 3002001181 | DEC 2013 Program Leads Jason D. Christopher Technical Lead, Cyber Security Capabilities & Risk Management Department of Energy (DOE), Office of Electricity Delivery and Energy Reliability (OE) Annabelle Lee Senior Technical Executive, Cyber Security Electric Power Research Institute (EPRI) For more information on the DOE's cyber security risk management programs, please contact

  3. Notice of Publication of Electricity Subsector Cybersecurity...

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

    Publication of Electricity Subsector Cybersecurity Risk Management Process: Federal Register Notice Volume 77, No. 100 - May 23, 2012 Notice of Publication of Electricity Subsector...

  4. Electricity Subsector Cybersecurity Capability Maturity Model...

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

    Subsector Cybersecurity Capability Maturity Model v. 1.1. (February 2014) Electricity Subsector Cybersecurity Capability Maturity Model v. 1.1. (February 2014) The Electricity ...

  5. Electricity Subsector Cybersecurity Capability Maturity Model...

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

    The Electricity Subsector Cybersecurity Capability Maturity Model (ES-C2M2) Version 1.1, which allows electric utilities and grid operators to assess their cybersecurity...

  6. "Code(a)","Subsector and Industry","Source(b)","Electricity(c...

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

    Gas(e)","NGL(f)","Coal","Breeze","Other(g)","Produced Onsite(h)" ,,"Total United ... raw" "Natural Gas Liquids '(NGL).'" " (g) 'Other' includes net steam (the sum of ...

  7. Oil and Natural Gas Subsector Cybersecurity Capability Maturity...

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

    Oil and Natural Gas Subsector Cybersecurity Capability Maturity Model (February 2014) Oil and Natural Gas Subsector Cybersecurity Capability Maturity Model (February 2014) The Oil ...

  8. Oil and Natural Gas Subsector Cybersecurity Capability Maturity...

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

    Oil and Natural Gas Subsector Cybersecurity Capability Maturity Model (ONG-C2M2) Oil and Natural Gas Subsector Cybersecurity Capability Maturity Model (ONG-C2M2) Oil and Natural ...

  9. Oil and Natural Gas Subsector Cybersecurity Capability Maturity Model

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

    (ONG-C2M2) | Department of Energy Oil and Natural Gas Subsector Cybersecurity Capability Maturity Model (ONG-C2M2) Oil and Natural Gas Subsector Cybersecurity Capability Maturity Model (ONG-C2M2) Oil and Natural Gas Subsector Cybersecurity Capability Maturity Model (ONG-C2M2) The Oil and Natural Gas Subsector Cybersecurity Capability Maturity Model (ONG-C2M2) was established as a result of the Administration's efforts to improve electricity subsector cybersecurity capabilities, and to

  10. ELECTRICITY SUBSECTOR CYBERSECURITY RISK MANAGEMENT PROCESS

    Energy Savers [EERE]

    CYBERSECURITY RISK MANAGEMENT PROCESS U.S. Department of Energy May 2012 DOE/OE-0003 Acknowledgments This electricity subsector cybersecurity Risk Management Process (RMP) guideline was developed by the Department of Energy (DOE), in collaboration with the National Institute of Standards and Technology (NIST) and the North American Electric Reliability Corporation (NERC). Members of industry and utility-specific trade groups were included in authoring this guidance designed to be meaningful and

  11. DOE Releases Electricity Subsector Cybersecurity Risk Management Process

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

    (RMP) Guideline | Department of Energy Electricity Subsector Cybersecurity Risk Management Process (RMP) Guideline DOE Releases Electricity Subsector Cybersecurity Risk Management Process (RMP) Guideline May 23, 2012 - 9:30am Addthis News Media Contact: (202) 586-4940 For Immediate Release: May 23, 2012 Department of Energy Releases Electricity Subsector Cybersecurity Risk Management Process (RMP) Guideline Public-Private Sector Collaboration Produces Guidance to Help Electric Utilities

  12. Electricity Subsector Cybersecurity Capability Maturity Model v. 1.1.

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

    (February 2014) | Department of Energy Subsector Cybersecurity Capability Maturity Model v. 1.1. (February 2014) Electricity Subsector Cybersecurity Capability Maturity Model v. 1.1. (February 2014) The Electricity Subsector Cybersecurity Capability Maturity Model (ES-C2M2) Version 1.1, which allows electric utilities and grid operators to assess their cybersecurity capabilities and prioritize their actions and investments to improve cybersecurity, combines elements from existing

  13. Integrating Electricity Subsector Failure Scenarios into a Risk...

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

    Integrating Electricity Subsector Failure Scenarios into a Risk Assessment Methodology ... Cybersecurity is important because the bi-directional flow of two-way communication and ...

  14. Oil and Natural Gas Subsector Cybersecurity Capability Maturity Model

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

    (February 2014) | Department of Energy Oil and Natural Gas Subsector Cybersecurity Capability Maturity Model (February 2014) Oil and Natural Gas Subsector Cybersecurity Capability Maturity Model (February 2014) The Oil and Natural Gas Subsector Cybersecurity Capability Maturity Model (ONG-C2M2) is a derivative of the Electricity Subsector Cybersecurity Capability Maturity Model (ES-C2M2) Version 1.1. The ES-C2M2 was developed in support of a White House initiative led by the Department of

  15. Originally Released: July 2009

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

    Coke and Shipments Net Residual Distillate Natural Gas(e) LPG and Coal Breeze of Energy Sources NAICS Total(b) Electricity(c) Fuel Oil Fuel Oil(d) (billion NGL(f) (million (million Other(g) Produced Onsite(h) Code(a) Subsector and Industry (trillion Btu) (million kWh) (million bbl) (million bbl) cu ft) (million bbl) short tons) short tons) (trillion Btu) (trillion Btu) Total United States 311 Food 1,186 73,440 4 3 620 1 7 * 105 * 3112 Grain and Oilseed Milling 318 15,464 * * 117 * 5 0 29 *

  16. Originally Released: July 2009

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

    Coke and Shipments Net Residual Distillate Natural Gas(e) LPG and Coal Breeze of Energy Sources NAICS Total(b) Electricity(c) Fuel Oil Fuel Oil(d) (billion NGL(f) (million (million Other(g) Produced Onsite(h) Code(a) Subsector and Industry (trillion Btu) (million kWh) (million bbl) (million bbl) cu ft) (million bbl) short tons) short tons) (trillion Btu) (trillion Btu) Total United States 311 Food 1,186 73,440 4 3 620 1 7 * 105 * 3112 Grain and Oilseed Milling 318 15,464 * * 117 * 5 0 29 *

  17. Originally Released: July 2009

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

    1.2 First Use of Energy for All Purposes (Fuel and Nonfuel), 2006; Level: National and Regional Data; Row: NAICS Codes; Column: Energy Sources and Shipments; Unit: Trillion Btu. Shipments NAICS Net Residual Distillate LPG and Coke and of Energy Sources Code(a) Subsector and Industry Total(b) Electricity(c) Fuel Oil Fuel Oil(d) Natural Gas(e) NGL(f) Coal Breeze Other(g) Produced Onsite(h) Total United States 311 Food 1,186 251 26 16 638 3 147 1 105 * 3112 Grain and Oilseed Milling 318 53 2 1 120

  18. Table 1.1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2010;

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

    1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2010; Level: National and Regional Data; Row: NAICS Codes; Column: Energy Sources and Shipments; Unit: Physical Units or Btu. Coke and Shipments Net Residual Distillate Natural Gas(e) LPG and Coal Breeze of Energy Sources NAICS Total(b) Electricity(c) Fuel Oil Fuel Oil(d) (billion NGL(f) (million (million Other(g) Produced Onsite(h) Code(a) Subsector and Industry (trillion Btu) (million kWh) (million bbl) (million bbl) cu ft) (million

  19. Table 1.2 First Use of Energy for All Purposes (Fuel and Nonfuel), 2010

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

    2 First Use of Energy for All Purposes (Fuel and Nonfuel), 2010; Level: National and Regional Data; Row: NAICS Codes; Column: Energy Sources and Shipments; Unit: Trillion Btu. Shipments NAICS Net Residual Distillate LPG and Coke and of Energy Sources Code(a) Subsector and Industry Total(b) Electricity(c) Fuel Oil Fuel Oil(d) Natural Gas(e) NGL(f) Coal Breeze Other(g) Produced Onsite(h) Total United States 311 Food 1,162 257 12 23 583 8 182 2 96 * 3112 Grain and Oilseed Milling 355 56 * 1 123 Q

  20. Level: National Data; Row: NAICS Codes; Column: Energy Sources and Shipments

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

    1.4 Number of Establishments by First Use of Energy for All Purposes (Fuel and Nonfuel), 2006; Level: National Data; Row: NAICS Codes; Column: Energy Sources and Shipments Unit: Establishment Counts. Any Shipments NAICS Energy Net Residual Distillate LPG and Coke and of Energy Sources Code(a) Subsector and Industry Source(b) Electricity(c) Fuel Oil Fuel Oil(d) Natural Gas(e) NGL(f) Coal Breeze Other(g) Produced Onsite(h) Total United States 311 Food 14,128 14,113 326 1,475 11,399 2,947 67 15

  1. Level: National Data; Row: NAICS Codes; Column: Energy Sources and Shipments;

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

    .4 Number of Establishments by First Use of Energy for All Purposes (Fuel and Nonfuel), 2010; Level: National Data; Row: NAICS Codes; Column: Energy Sources and Shipments; Unit: Establishment Counts. Any Shipments NAICS Energy Net Residual Distillate LPG and Coke and of Energy Sources Code(a) Subsector and Industry Source(b) Electricity(c) Fuel Oil Fuel Oil(d) Natural Gas(e) NGL(f) Coal Breeze Other(g) Produced Onsite(h) Total United States 311 Food 13,269 13,265 151 2,494 10,376 4,061 64 7

  2. Table B-1: Analytical Results Statistical Mean Upper Confidence

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

    .1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2010; Level: National and Regional Data; Row: NAICS Codes; Column: Energy Sources and Shipments; Unit: Physical Units or Btu. Coke and Shipments Net Residual Distillate Natural Gas(e) LPG and Coal Breeze of Energy Sources NAICS Total(b) Electricity(c) Fuel Oil Fuel Oil(d) (billion NGL(f) (million (million Other(g) Produced Onsite(h) Code(a) Subsector and Industry (trillion Btu) (million kWh) (million bbl) (million bbl) cu ft) (million

  3. table1.4_02

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

    4 Number of Establishments by First Use of Energy for All Purposes (Fuel and Nonfuel), 2002 Level: National Data; Row: NAICS Codes; Column: Energy Sources and Shipments; Unit: Establishment Counts. Any Shipments NAICS Energy Net Residual Distillate Natural LPG and Coke and of Energy Sources Code(a) Subsector and Industry Source(b) Electricity(c) Fuel Oil Fuel Oil(d) Gas(e) NGL(f) Coal Breeze Other(g) Produced Onsite(h) Total United States RSE Column Factors: 0.7 0.7 1.4 1.2 0.9 1.3 1.1 1.2 1.3

  4. Integrating Electricity Subsector Failure Scenarios into a Risk Assessment

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

    Methodology (December 2013) | Department of Energy Integrating Electricity Subsector Failure Scenarios into a Risk Assessment Methodology (December 2013) Integrating Electricity Subsector Failure Scenarios into a Risk Assessment Methodology (December 2013) The nation's power system consists of both legacy and next generation technologies. New grid technologies are introducing millions of novel, intelligent components to the electric grid that communicate in much more advanced ways than in

  5. Electricity Subsector Cybersecurity Capability Maturity Model (ES-C2M2) |

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

    Department of Energy Electricity Subsector Cybersecurity Capability Maturity Model (ES-C2M2) Electricity Subsector Cybersecurity Capability Maturity Model (ES-C2M2) Electricity Subsector Cybersecurity Capability Maturity Model (ES-C2M2) The Electricity Subsector Cybersecurity Capability Maturity Model (ES-C2M2) was established as a result of the Administration's efforts to improve electricity subsector cybersecurity capabilities, and to understand the cybersecurity posture of the energy

  6. OIL AND NATURAL GAS SUBSECTOR CYBERSECURITY CAPABILITY MATURITY MODEL (ONG-C2M2)

    Energy Savers [EERE]

    OIL AND NATURAL GAS SUBSECTOR CYBERSECURITY CAPABILITY MATURITY MODEL (ONG-C2M2) Version 1.1 February 2014 Oil and Natural Gas Subsector Cybersecurity Capability Maturity Model Version 1.1 iii TABLE OF CONTENTS Acknowledgments ......................................................................................................................................... v 1. Introduction

  7. Level: National and Regional Data; Row: NAICS Codes; Column: Energy Sources and Shipments;

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

    Coke and Shipments Net Residual Distillate Natural LPG and Coal Breeze of Energy Sources NAICS Total(b) Electricity(c) Fuel Oil Fuel Oil(d) Gas(e) NGL(f) (million (million Other(g) Produced Onsite(h) Code(a) Subsector and Industry (trillion Btu) (million kWh) (million bbl) (million bbl) (billion cu ft) (million bbl) short tons) short tons) (trillion Btu) (trillion Btu) Total United States RSE Column Factors: 0.9 1 1.2 1.8 1 1.6 0.8 0.9 1.2 0.4 311 Food 1,123 67,521 2 3 567 1 8 * 89 0 311221 Wet

  8. table1.1_02

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

    Coke and Shipments Net Residual Distillate Natural LPG and Coal Breeze of Energy Sources RSE NAICS Total(b) Electricity(c) Fuel Oil Fuel Oil(d) Gas(e) NGL(f) (million (million Other(g) Produced Onsite(h) Row Code(a) Subsector and Industry (trillion Btu) (million kWh) (million bbl) (million bbl) (billion cu ft) (million bbl) short tons) short tons) (trillion Btu) (trillion Btu) Factors Total United States RSE Column Factors: 0.9 1 1.2 1.8 1 1.6 0.8 0.9 1.2 0.4 311 Food 1,123 67,521 2 3 567 1 8 *

  9. table1.2_02

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

    2 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National and Regional Data; Row: NAICS Codes; Column: Energy Sources and Shipments; Unit: Trillion Btu. Shipments RSE NAICS Net Residual Distillate Natural LPG and Coke and of Energy Sources Row Code(a) Subsector and Industry Total(b) Electricity(c) Fuel Oil Fuel Oil(d) Gas(e) NGL(f) Coal Breeze Other(g) Produced Onsite(h) Factors Total United States RSE Column Factors: 0.9 1 1.2 1.8 1 1.6 0.8 0.9 1.2 0.4 311 Food 1,123 230

  10. Notice of Publication of Electricity Subsector Cybersecurity Risk Management Process: Federal Register Notice Volume 77, No. 100- May 23, 2012

    Broader source: Energy.gov [DOE]

    This serves as public notification of the publication, by the Department of Energy (DOE) of the Electricity Subsector Cybersecurity Risk Management Process guideline. The guideline describes a risk...

  11. Current and future industrial energy service characterizations. Volume III. Energy data on 15 selected states' manufacturing subsector

    SciTech Connect (OSTI)

    Krawiec, F.; Thomas, T.; Jackson, F.; Limaye, D.R.; Isser, S.; Karnofsky, K.; Davis, T.D.

    1980-11-01

    An examination is made of the current and future energy demands, and uses, and cost to characterize typical applications and resulting services in the US and industrial sectors of 15 selected states. Volume III presents tables containing data on selected states' manufacturing subsector energy consumption, functional uses, and cost in 1974 and 1976. Alabama, California, Illinois, Indiana, Louisiana, Michigan, Missouri, New Jersey, New York, Ohio, Oregon, Pennsylvania, Texas, West Virginia, and Wisconsin were chosen as having the greatest potential for replacing conventional fuel with solar energy. Basic data on the quantities, cost, and types of fuel and electric energy purchased by industr for heat and power were obtained from the 1974 and 1976 Annual Survey of Manufacturers. The specific indutrial energy servic cracteristics developed for each selected state include. 1974 and 1976 manufacturing subsector fuels and electricity consumption by 2-, 3-, and 4-digit SIC and primary fuel (quantity and relative share); 1974 and 1976 manufacturing subsector fuel consumption by 2-, 3-, and 4-digit SIC and primary fuel (quantity and relative share); 1974 and 1976 manufacturing subsector average cost of purchsed fuels and electricity per million Btu by 2-, 3-, and 4-digit SIC and primary fuel (in 1976 dollars); 1974 and 1976 manufacturing subsector fuels and electric energy intensity by 2-, 3-, and 4-digit SIC and primary fuel (in 1976 dollars); manufacturing subsector average annual growth rates of (1) fuels and electricity consumption, (2) fuels and electric energy intensity, and (3) average cost of purchased fuels and electricity (1974 to 1976). Data are compiled on purchased fuels, distillate fuel oil, residual ful oil, coal, coal, and breeze, and natural gas. (MCW)

  12. Integrating Electricity Subsector

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

    ... The electric sector cyber security domain threat model incorporates the following elements: * Adversaries with intent, driven by money, politics, religion, activist causes, ...

  13. Electricity Subsector Cybersecurity Capability Maturity Model...

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

    Sector Cybersecurity Framework Implementation Guidance (January 2015) The Electricity Journal: Cybersecurity and the Smarter Grid CEDS Fact Sheets Cybersecurity Procurement...

  14. ELECTRICITY SUBSECTOR CYBERSECURITY CAPABILITY MATURITY MODEL...

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

    ... Retrieved from http:www.esisac.comPublic%20LibraryReports CRPA%202010%20Report.pdf * * ... that measure, collect, and analyze energy usage, from advanced devices such as "smart" ...

  15. ELECTRICITY SUBSECTOR CYBERSECURITY RISK MANAGEMENT PROCESS

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

    and Technology (NIST) and the North American Electric Reliability Corporation (NERC). ... of Electricity Delivery and Energy Reliability National Institute of Standards and ...

  16. DOE Releases Electricity Subsector Cybersecurity Risk Management...

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

    Delivery and Energy Reliability, in collaboration with the National Institute of Standards and Technology (NIST) and the North American Electric Reliability Corporation (NERC), ...

  17. Released: June 2010

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

    4 Percent of Establishments by Levels of Lowest Price Difference that Would Cause Fuel Switching from Electricity to a Less Expensive Substitute, 2006; Level: National Data; Row: NAICS Codes; Column: Levels of Lowest Price Difference; Unit: Establishment Counts. Would Switch Would Not Estimate to More NAICS Establishments Switch Due 1 to 10 11 to 25 26 to 50 Over 50 Cannot Expensive Code(a) Subsector and Industry Able to Switch(b) to Price Percent Percent Percent Percent Be Provided Substitute

  18. Released: June 2010

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

    5 Percent of Establishments by Levels of Lowest Price Difference that Would Cause Fuel Switching from Natural Gas to a Less Expensive Substitute, 2006; Level: National Data; Row: NAICS Codes; Column: Levels of Lowest Price Difference; Unit: Establishment Counts. Would Switch Would Not Estimate to More NAICS Establishments Switch Due 1 to 10 11 to 25 26 to 50 Over 50 Cannot Expensive Code(a) Subsector and Industry Able to Switch(b) to Price Percent Percent Percent Percent Be Provided Substitute

  19. Released: June 2010

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

    6 Percent of Establishments by Levels of Lowest Price Difference that Would Cause Fuel Switching from Coal to a Less Expensive Substitute, 2006; Level: National Data; Row: NAICS Codes; Column: Levels of Lowest Price Difference; Unit: Establishment Counts. Would Switch Would Not Estimate to More NAICS Establishments Switch Due 1 to 10 11 to 25 26 to 50 Over 50 Cannot Expensive Code(a) Subsector and Industry Able to Switch(b) to Price Percent Percent Percent Percent Be Provided Substitute Total

  20. Released: June 2010

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

    7 Percent of Establishments by Levels of Lowest Price Difference that Would Cause Fuel Switching from LPG to a Less Expensive Substitute, 2006; Level: National Data; Row: NAICS Codes; Column: Levels of Lowest Price Difference; Unit: Establishment Counts. Would Switch Would Not Estimate to More NAICS Establishments Switch Due 1 to 10 11 to 25 26 to 50 Over 50 Cannot Expensive Code(a) Subsector and Industry Able to Switch(b) to Price Percent Percent Percent Percent Be Provided Substitute Total

  1. Released: June 2010

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

    8 Percent of Establishments by Levels of Lowest Price Difference that Would Cause Fuel Switching from Distillate Fuel Oil to a Less Expensive Substitute, 2006; Level: National Data; Row: NAICS Codes; Column: Levels of Lowest Price Difference; Unit: Establishment Counts. Would Switch Would Not Estimate to More NAICS Establishments Switch Due 1 to 10 11 to 25 26 to 50 Over 50 Cannot Expensive Code(a) Subsector and Industry Able to Switch(b) to Price Percent Percent Percent Percent Be Provided

  2. Released: June 2010

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

    9 Percent of Establishments by Levels of Lowest Price Difference that Would Cause Fuel Switching from Residual Fuel Oil to a Less Expensive Substitute, 2006; Level: National Data; Row: NAICS Codes; Column: Levels of Lowest Price Difference; Unit: Establishment Counts. Would Switch Would Not Estimate to More NAICS Establishments Switch Due 1 to 10 11 to 25 26 to 50 Over 50 Cannot Expensive Code(a) Subsector and Industry Able to Switch(b) to Price Percent Percent Percent Percent Be Provided

  3. Table 10.24 Reasons that Made Distillate Fuel Oil Unswitchable, 2006;

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

    4 Reasons that Made Distillate Fuel Oil Unswitchable, 2006; Level: National Data; Row: NAICS Codes; Column: Reasons that Made Quantity Unswitchable; Unit: Million barrels. Total Amount of Total Amount of Equipment is Not Switching Unavailable Long-Term Unavailable Combinations of NAICS Distillate Fuel Oil Unswitchable Distillate Capable of Using Adversely Affects Alternative Environmenta Contract Storage for Another Columns F, G, Code(a) Subsector and Industry Consumed as a Fue Fuel Oil Fuel Use

  4. Table 10.25 Reasons that Made Residual Fuel Oil Unswitchable, 2006;

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

    5 Reasons that Made Residual Fuel Oil Unswitchable, 2006; Level: National Data; Row: NAICS Codes; Column: Reasons that Made Quantity Unswitchable; Unit: Million barrels. Total Amount of Total Amount of Equipment is Not Switching Unavailable Long-Term Unavailable Combinations of NAICS Residual Fuel Oil Unswitchable ResiduaCapable of Using Adversely Affects Alternative Environmental Contract Storage for Another Columns F, G, Code(a) Subsector and Industry Consumed as a Fue Fuel Oil Fuel Use

  5. Level: National Data; Row: NAICS Codes; Column: Energy Sources;

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

    0.5 Number of Establishments with Capability to Switch Residual Fuel Oil to Alternative Energy Sources, 2010; Level: National Data; Row: NAICS Codes; Column: Energy Sources; Unit: Establishment Counts. Residual Fuel Oil(b) Alternative Energy Sources(c) Coal Coke NAICS Total Establishments Not Electricity Natural Distillate and Code(a) Selected Subsectors and Industry Consuming Residual Fuel Oil(d Switchable Switchable Receipts(e) Gas Fuel Oil Coal LPG Breeze Other(f) Total United States 311 Food

  6. Level: National Data; Row: NAICS Codes; Column: Floorspace and Buildings;

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

    9.1 Enclosed Floorspace and Number of Establishment Buildings, 2010; Level: National Data; Row: NAICS Codes; Column: Floorspace and Buildings; Unit: Floorspace Square Footage and Building Counts. Approximate Approximate Average Enclosed Floorspace Average Number Number of All Buildings Enclosed Floorspace of All Buildings of Buildings Onsite NAICS Onsite Establishments(b) per Establishment Onsite per Establishment Code(a) Subsector and Industry (million sq ft) (counts) (sq ft) (counts) (counts)

  7. Level: National Data; Row: NAICS Codes; Column: Levels of Price Difference;

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

    6 Percent of Establishments by Levels of Price Difference that Would Cause Fuel Switching from Coal to a Less Expensive Substitute, 2010; Level: National Data; Row: NAICS Codes; Column: Levels of Price Difference; Unit: Establishment Counts. Would Switch Would Not Estimate to More NAICS Establishments Switch Due 1 to 10 11 to 25 26 to 50 Over 50 Cannot Expensive Code(a) Subsector and Industry Able to Switch(b) to Price Percent Percent Percent Percent Be Provided Substitute Total United States

  8. Level: National Data; Row: NAICS Codes; Column: Reasons that Made Quantity Unswitchable;

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

    0 Reasons that Made Electricity Unswitchable, 2006; Level: National Data; Row: NAICS Codes; Column: Reasons that Made Quantity Unswitchable; Unit: Million kWh. Total Amount of Total Amount of Equipment is Not Switching Unavailable Long-Term Unavailable Combinations of NAICS Electricity Consumed Unswitchable Capable of Using Adversely Affects Alternative Environmenta Contract Storage for Another Columns F, G, Code(a) Subsector and Industry as a Fuel Electricity Fuel Use Another Fuel the Products

  9. Level: National Data; Row: NAICS Codes; Column: Reasons that Made Quantity Unswitchable;

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

    1 Reasons that Made Natural Gas Unswitchable, 2006; Level: National Data; Row: NAICS Codes; Column: Reasons that Made Quantity Unswitchable; Unit: Billion cubic feet. Total Amount of Total Amount of Equipment is Not Switching Unavailable Long-Term Unavailable Combinations of NAICS Natural Gas Unswitchable Capable of Using Adversely Affects Alternative Environmenta Contract Storage for Another Columns F, G, Code(a) Subsector and Industry Consumed as a FueNatural Gas Fuel Use Another Fuel the

  10. Level: National Data; Row: NAICS Codes; Column: Reasons that Made Quantity Unswitchable;

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

    2 Reasons that Made Coal Unswitchable, 2006; Level: National Data; Row: NAICS Codes; Column: Reasons that Made Quantity Unswitchable; Unit: Million short tons. Total Amount of Total Amount of Equipment is Not Switching Unavailable Long-Term Unavailable Combinations of NAICS Coal Consumed Unswitchable Capable of Using Adversely Affects Alternative Environmenta Contract Storage for Another Columns F, G, Code(a) Subsector and Industry as a Fuel Coal Fuel Use Another Fuel the Products Fuel

  11. Level: National Data; Row: NAICS Codes; Column: Reasons that Made Quantity Unswitchable;

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

    3 Reasons that Made LPG Unswitchable, 2006; Level: National Data; Row: NAICS Codes; Column: Reasons that Made Quantity Unswitchable; Unit: Million barrels. Total Amount of Total Amount of Equipment is Not Switching Unavailable Long-Term Unavailable Combinations of NAICS LPG Consumed Unswitchable Capable of Using Adversely Affects Alternative Environmenta Contract Storage for Another Columns F, G, Code(a) Subsector and Industry as a Fuel LPG Fuel Use Another Fuel the Products Fuel

  12. table9.1_02.xls

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

    Enclosed Floorspace and Number of Establishment Buildings, 2002; Level: National Data; Row: NAICS Codes; Column: Floorspace and Buildings; Unit: Floorspace Square Footage and Building Counts. Approximate Approximate Average Enclosed Floorspace Average Number Number of All Buildings Enclosed Floorspace of All Buildings of Buildings Onsite RSE NAICS Onsite Establishments(b) per Establishment Onsite per Establishment Row Code(a) Subsector and Industry (million sq ft) (counts) (sq ft) (counts)

  13. Originally Released: July 2009

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

    2 Offsite-Produced Fuel Consumption, 2006 Level: National and Regional Data; Row: NAICS Codes; Column: Energy Sources Unit: Trillion Btu. NAICS Residual Distillate LPG and Coke Code(a) Subsector and Industry Total Electricity(b) Fuel Oil Fuel Oil(c) Natural Gas(d) NGL(e) Coal and Breeze Total United States 311 Food 1,124 251 26 16 635 3 147 1 3112 Grain and Oilseed Milling 316 53 2 1 118 * 114 0 311221 Wet Corn Milling 179 23 * * 52 * 95 0 31131 Sugar Manufacturing 67 3 9 1 18 * 31 1 3114 Fruit

  14. Level: National Data; Row: NAICS Codes (3-Digit Only); Column: Energy Sources

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

    4.4 Number of Establishments by Offsite-Produced Fuel Consumption, 2006; Level: National Data; Row: NAICS Codes (3-Digit Only); Column: Energy Sources Unit: Establishment Counts. Any NAICS Energy Residual Distillate LPG and Coke Code(a) Subsector and Industry Source(b) Electricity(c) Fuel Oil Fuel Oil(d) Natural Gas(e) NGL(f) Coal and Breeze Other(g) Total United States 311 Food 14,128 14,109 326 1,462 11,395 2,920 67 13 1,149 3112 Grain and Oilseed Milling 580 580 15 174 445 269 35 0 144 311221

  15. Level: National Data; Row: NAICS Codes; Column: Energy Sources

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

    2.4 Number of Establishments by Nonfuel (Feedstock) Use of Combustible Energy, 2006 Level: National Data; Row: NAICS Codes; Column: Energy Sources Unit: Establishment Counts. Any Combustible NAICS Energy Residual Distillate LPG and Coke Code(a) Subsector and Industry Source(b) Fuel Oil Fuel Oil(c) Natural Gas(d) NGL(e) Coal and Breeze Other(f) Total United States 311 Food 183 0 105 38 Q 0 W 8 3112 Grain and Oilseed Milling 36 0 Q 13 W 0 0 6 311221 Wet Corn Milling W 0 0 0 0 0 0 W 31131 Sugar

  16. Level: National Data; Row: NAICS Codes; Column: Energy Sources

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

    3.4 Number of Establishments by Fuel Consumption, 2006; Level: National Data; Row: NAICS Codes; Column: Energy Sources Unit: Establishment Counts. Any NAICS Energy Net Residual Distillate LPG and Coke Code(a) Subsector and Industry Source(b) Electricity(c) Fuel Oil Fuel Oil(d) Natural Gas(e) NGL(f) Coal and Breeze Other(g) Total United States 311 Food 14,128 14,113 326 1,462 11,395 2,920 67 13 1,240 3112 Grain and Oilseed Milling 580 580 15 174 445 269 35 0 148 311221 Wet Corn Milling 47 47 W 17

  17. Level: National Data; Row: NAICS Codes; Column: Energy Sources;

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

    2.4 Number of Establishments by Nonfuel (Feedstock) Use of Combustible Energy, 2010; Level: National Data; Row: NAICS Codes; Column: Energy Sources; Unit: Establishment Counts. Any Combustible NAICS Energy Residual Distillate LPG and Coke Code(a) Subsector and Industry Source(b) Fuel Oil Fuel Oil(c) Natural Gas(d) NGL(e) Coal and Breeze Other(f) Total United States 311 Food 592 W Q Q Q 0 0 345 3112 Grain and Oilseed Milling 85 0 W 15 Q 0 0 57 311221 Wet Corn Milling 8 0 0 0 0 0 0 8 31131 Sugar

  18. Level: National Data; Row: NAICS Codes; Column: Energy Sources;

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

    3.4 Number of Establishments by Fuel Consumption, 2010; Level: National Data; Row: NAICS Codes; Column: Energy Sources; Unit: Establishment Counts. Any NAICS Energy Net Residual Distillate LPG and Coke Code(a) Subsector and Industry Source(b) Electricity(c) Fuel Oil Fuel Oil(d) Natural Gas(e) NGL(f) Coal and Breeze Other(g) Total United States 311 Food 13,269 13,265 144 2,416 10,373 4,039 64 7 1,538 3112 Grain and Oilseed Milling 602 602 9 204 489 268 30 0 140 311221 Wet Corn Milling 59 59 W 28

  19. Level: National Data; Row: NAICS Codes; Column: Energy Sources;

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

    4.4 Number of Establishments by Offsite-Produced Fuel Consumption, 2010; Level: National Data; Row: NAICS Codes; Column: Energy Sources; Unit: Establishment Counts. Any NAICS Energy Residual Distillate LPG and Coke Code(a) Subsector and Industry Source(b) Electricity(c) Fuel Oil Fuel Oil(d) Natural Gas(e) NGL(f) Coal and Breeze Other(g) Total United States 311 Food 13,269 13,265 144 2,413 10,373 4,039 64 W 1,496 3112 Grain and Oilseed Milling 602 602 9 201 489 268 30 0 137 311221 Wet Corn

  20. Level: National Data; Row: NAICS Codes; Column: Energy Sources;

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

    1 Number of Establishments with Capability to Switch Coal to Alternative Energy Sources, 2006; Level: National Data; Row: NAICS Codes; Column: Energy Sources; Unit: Establishment Counts. NAICS Total Not Electricity Natural Distillate Residual Code(a) Subsector and Industry Consumed(d) Switchable Switchable Receipts(e) Gas Fuel Oil Fuel Oil LPG Other(f) Total United States 311 Food 67 21 49 W 19 10 W W W 3112 Grain and Oilseed Milling 35 7 29 W 7 3 0 W W 311221 Wet Corn Milling 18 4 17 0 4 W 0 W

  1. Level: National Data; Row: NAICS Codes; Column: Energy Sources;

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

    3 Number of Establishments with Capability to Switch LPG to Alternative Energy Sources, 2006; Level: National Data; Row: NAICS Codes; Column: Energy Sources; Unit: Establishment Counts. Coal Coke NAICS Total Not Electricity Natural Distillate Residual and Code(a) Subsector and Industry Consumed(d) Switchable Switchable Receipts(e) Gas Fuel Oil Fuel Oil Coal Breeze Other(f) Total United States 311 Food 2,920 325 1,945 171 174 25 W 0 0 15 3112 Grain and Oilseed Milling 269 36 152 Q Q W W 0 0 W

  2. Level: National Data; Row: NAICS Codes; Column: Energy Sources;

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

    3 Number of Establishments with Capability to Switch Natural Gas to Alternative Energy Sources, 2006; Level: National Data; Row: NAICS Codes; Column: Energy Sources; Unit: Establishment Counts. Natural Gas(b) Alternative Energy Sources(c) Coal Coke NAICS Total Not Electricity Distillate Residual and Code(a) Subsector and Industry Consumed(d) Switchable Switchable Receipts(e) Fuel Oil Fuel Oil Coal LPG Breeze Other(f) Total United States 311 Food 11,395 1,830 6,388 484 499 245 Q 555 0 203 3112

  3. Level: National Data; Row: NAICS Codes; Column: Energy Sources;

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

    5 Number of Establishments with Capability to Switch Residual Fuel Oil to Alternative Energy Sources, 2006; Level: National Data; Row: NAICS Codes; Column: Energy Sources; Unit: Establishment Counts. Residual Fuel Oil(b) Alternative Energy Sources(c) Coal Coke NAICS Total Not Electricity Natural Distillate and Code(a) Subsector and Industry Consumed(d) Switchable Switchable Receipts(e) Gas Fuel Oil Coal LPG Breeze Other(f) Total United States 311 Food 326 178 23 0 150 Q 0 Q 0 W 3112 Grain and

  4. Level: National Data; Row: NAICS Codes; Column: Energy Sources;

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

    7 Number of Establishments with Capability to Switch Electricity to Alternative Energy Sources, 2006; Level: National Data; Row: NAICS Codes; Column: Energy Sources; Unit: Establishment Counts. Coal Coke NAICS Total Not Natural Distillate Residual and Code(a) Subsector and Industry Receipts(d) Switchable Switchable Gas Fuel Oil Fuel Oil Coal LPG Breeze Other(e) Total United States 311 Food 14,109 708 8,259 384 162 0 Q 105 0 84 3112 Grain and Oilseed Milling 580 27 472 3 Q 0 W W 0 W 311221 Wet

  5. Level: National Data; Row: NAICS Codes; Column: Energy Sources;

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

    9 Number of Establishments with Capability to Switch Distillate Fuel Oil to Alternative Energy Sources, 2006; Level: National Data; Row: NAICS Codes; Column: Energy Sources; Unit: Establishment Counts. Coal Coke NAICS Total Not Electricity Natural Residual and Code(a) Subsector and Industry Consumed(d) Switchable Switchable Receipts(e) Gas Fuel Oil Coal LPG Breeze Other(f) Total United States 311 Food 1,462 276 900 Q 217 8 0 25 0 16 3112 Grain and Oilseed Milling 174 10 131 W 4 W 0 W 0 W 311221

  6. Level: National Data; Row: NAICS Codes; Column: Energy Sources;

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

    1 Number of Establishments with Capability to Switch Coal to Alternative Energy Sources, 2010; Level: National Data; Row: NAICS Codes; Column: Energy Sources; Unit: Establishment Counts. NAICS Total Establishments Not Electricity Natural Distillate Residual Code(a) Selected Subsectors and Industry Consuming Coal(d) Switchable Switchable Receipts(e) Gas Fuel Oil Fuel Oil LPG Other(f) Total United States 311 Food 64 19 54 0 17 6 W W W 3112 Grain and Oilseed Milling 30 13 24 0 12 W 0 W W 311221 Wet

  7. Level: National Data; Row: NAICS Codes; Column: Energy Sources;

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

    3 Number of Establishments with Capability to Switch LPG to Alternative Energy Sources, 2010; Level: National Data; Row: NAICS Codes; Column: Energy Sources; Unit: Establishment Counts. Coal Coke NAICS Total Establishments Not Electricity Natural Distillate Residual and Code(a) Selected Subsectors and Industry Consuming LPG(d) Switchable Switchable Receipts(e) Gas Fuel Oil Fuel Oil Coal Breeze Other(f) Total United States 311 Food 4,039 600 2,860 356 221 Q W 0 0 16 3112 Grain and Oilseed Milling

  8. Level: National Data; Row: NAICS Codes; Column: Energy Sources;

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

    3 Number of Establishments with Capability to Switch Natural Gas to Alternative Energy Sources, 2010; Level: National Data; Row: NAICS Codes; Column: Energy Sources; Unit: Establishment Counts. Natural Gas(b) Alternative Energy Sources(c) Coal Coke NAICS Total Establishments Not Electricity Distillate Residual and Code(a) Selected Subsectors and Industry Consuming Natural Gas(d Switchable Switchable Receipts(e) Fuel Oil Fuel Oil Coal LPG Breeze Other(f) Total United States 311 Food 10,373 1,667

  9. Level: National Data; Row: NAICS Codes; Column: Energy Sources;

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

    7 Number of Establishments with Capability to Switch Electricity to Alternative Energy Sources, 2010; Level: National Data; Row: NAICS Codes; Column: Energy Sources; Unit: Establishment Counts. Coal Coke NAICS Total Establishments Not Natural Distillate Residual and Code(a) Selected Subsectors and Industry with Electricity Receipts(d Switchable Switchable Gas Fuel Oil Fuel Oil Coal LPG Breeze Other(e) Total United States 311 Food 13,265 765 11,829 482 292 Q Q 51 Q Q 3112 Grain and Oilseed

  10. Level: National Data; Row: NAICS Codes; Column: Energy Sources;

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

    9 Number of Establishments with Capability to Switch Distillate Fuel Oil to Alternative Energy Sources, 2010; Level: National Data; Row: NAICS Codes; Column: Energy Sources; Unit: Establishment Counts. Coal Coke NAICS Total Establishments Not Electricity Natural Residual and Code(a) Selected Subsectors and Industry Consuming Distillate Fuel Oil(d Switchable Switchable Receipts(e) Gas Fuel Oil Coal LPG Breeze Other(f) Total United States 311 Food 2,416 221 2,115 82 160 Q 0 Q 0 30 3112 Grain and

  11. Level: National Data; Row: NAICS Codes; Column: Levels of Price Difference;

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

    Next MECS will be fielded in 2015 Table 10.17 Percent of Establishments by Levels of Price Difference that Would Cause Fuel Switching from LPG to a Less Expensive Substitute, 2010; Level: National Data; Row: NAICS Codes; Column: Levels of Price Difference; Unit: Establishment Counts. Would Switch Would Not Estimate to More NAICS Establishments Switch Due 1 to 10 11 to 25 26 to 50 Over 50 Cannot Expensive Code(a) Subsector and Industry Able to Switch(b) to Price Percent Percent Percent Percent

  12. Level: National Data; Row: NAICS Codes; Column: Usage within Cogeneration Technologies;

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

    3 Number of Establishments by Usage of Cogeneration Technologies, 2006; Level: National Data; Row: NAICS Codes; Column: Usage within Cogeneration Technologies; Unit: Establishment Counts. Establishments with Any Cogeneration NAICS Technology Code(a) Subsector and Industry Establishments(b) in Use(c) In Use(d) Not in Use Don't Know In Use(d) Not in Use Don't Know In Use(d) Not in Use Don't Know In Use(d) Not in Use Don't Know In Use(d) Not in Use Don't Know Total United States 311 Food 14,128 297

  13. Level: National Data; Row: NAICS Codes; Column: Usage within Cogeneration Technologies;

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

    3 Number of Establishments by Usage of Cogeneration Technologies, 2010; Level: National Data; Row: NAICS Codes; Column: Usage within Cogeneration Technologies; Unit: Establishment Counts. Establishments with Any Cogeneration NAICS Technology Code(a) Selected Subsectors and Industry Establishments(b) in Use(c) In Use(d) Not in Use(e) Don't Know In Use(d) Not in Use(e) Don't Know In Use(d) Not in Use(e) Don't Know In Use(d) Not in Use(e) Don't Know In Use(d) Not in Use(e) Don't Know Total United

  14. Level: National and Regional Data; Row: NAICS Codes; Column: Energy-Consumption Ratios

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

    Next MECS will be conducted in 2010 Table 6.1 Consumption Ratios of Fuel, 2006 Level: National and Regional Data; Row: NAICS Codes; Column: Energy-Consumption Ratios Unit: Varies. Consumption Consumption per Dollar Consumption per Dollar of Value NAICS per Employee of Value Added of Shipments Code(a) Subsector and Industry (million Btu) (thousand Btu) (thousand Btu) Total United States 311 Food 879.8 5.0 2.2 3112 Grain and Oilseed Milling 6,416.6 17.5 5.7 311221 Wet Corn Milling 21,552.1 43.6

  15. Level: National and Regional Data; Row: Selected NAICS Codes; Column: Energy Sources

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

    August 2009 Next MECS will be conducted in 2010 Table 3.6 Selected Wood and Wood-Related Products in Fuel Consumption, 2006 Level: National and Regional Data; Row: Selected NAICS Codes; Column: Energy Sources Unit: Trillion Btu. Wood Residues and Wood-Related Pulping Liquor Wood Byproducts and NAICS or Biomass Agricultural Harvested Directly from Mill Paper-Related Code(a) Subsector and Industry Black Liquor Total(b) Waste(c) from Trees(d) Processing(e) Refuse(f) Total United States 311 Food 0

  16. Levelized Cost of Electricity and Levelized Avoided Cost of Electricity Methodology Supplement

    Gasoline and Diesel Fuel Update (EIA)

    32,080 134,757 130,374 133,976 134,320 127,472 1980

    0 Capability to Switch Coal to Alternative Energy Sources, 2006; Level: National Data and Regional Totals; Row: NAICS Codes, Value of Shipments and Employment Sizes; Column: Energy Sources; Unit: Thousand Short Tons. NAICS Total Not Electricity Natural Distillate Residual Code(a) Subsector and Industry Consumed(c) Switchable Switchable Receipts(d) Gas Fuel Oil Fuel Oil LPG Other(e) Total United States 311 Food 6,603 1,013 5,373 27 981 303 93

  17. Other States Natural Gas Coalbed Methane, Reserves Based Production

    Gasoline and Diesel Fuel Update (EIA)

    August 2009 Revised: October 2009 Next MECS will be conducted in 2010 Table 3.5 Selected Byproducts in Fuel Consumption, 2006; Level: National and Regional Data; Row: NAICS Codes; Column: Energy Sources; Unit: Trillion Btu. Waste Blast Pulping Liquor Oils/Tars NAICS Furnace/Coke Petroleum or Wood Chips, and Waste Code(a) Subsector and Industry Total Oven Gases Waste Gas Coke Black Liquor Bark Materials Total United States 311 Food 10 0 3 0 0 7 Q 3112 Grain and Oilseed Milling 7 0 1 0 0 6 *

  18. Table 3.6 Selected Wood and Wood-Related Products in Fuel Consumption, 2010;

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

    Table 3.6 Selected Wood and Wood-Related Products in Fuel Consumption, 2010; Level: National and Regional Data; Row: Selected NAICS Codes; Column: Energy Sources; Unit: Trillion Btu. Wood Residues and Wood-Related Pulping Liquor Wood Byproducts and NAICS or Biomass Agricultural Harvested Directly from Mill Paper-Related Code(a) Subsector and Industry Black Liquor Total(b) Waste(c) from Trees(d) Processing(e) Refuse(f) Total United States 311 Food 0 44 43 * * 1 311221 Wet Corn Milling 0 1 1 0 0 0

  19. Table 7.1 Average Prices of Purchased Energy Sources, 2010

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

    Average Prices of Purchased Energy Sources, 2010; Level: National and Regional Data; Row: NAICS Codes; Column: All Energy Sources Collected; Unit: U.S. Dollars per Physical Units. Coal NAICS TOTAL Acetylene Breeze Total Anthracite Code(a) Subsector and Industry (million Btu) (cu ft) (short tons) (short tons) (short tons) Total United States 311 Food 9.12 0.26 0.00 53.43 90.85 3112 Grain and Oilseed Milling 6.30 0.29 0.00 51.34 50.47 311221 Wet Corn Milling 4.87 0.48 0.00 47.74 50.47 31131 Sugar

  20. table10.10_02.xls

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

    0 Capability to Switch Coal to Alternative Energy Sources, 2002; Level: National Data and Regional Totals; Row: NAICS Codes, Value of Shipments and Employment Sizes; Column: Energy Sources; Unit: Thousand Short Tons. RSE NAICS Total Not Electricity Natural Distillate Residual Row Code(a) Subsector and Industry Consumed(c) Switchable Switchable Receipts(d) Gas Fuel Oil Fuel Oil LPG Other(e) Factors Total United States RSE Column Factors: 1.4 1.1 1.5 0.7 1.1 0.8 1.2 1.5 0.5 311 Food 8,290 1,689

  1. table10.11_02.xls

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

    1 Number of Establishments with Capability to Switch Coal to Alternative Energy Sources, 2002; Level: National Data; Row: NAICS Codes; Column: Energy Sources; Unit: Establishment Counts. RSE NAICS Total Not Electricity Natural Distillate Residual Row Code(a) Subsector and Industry Consumed(d) Switchable Switchable Receipts(e) Gas Fuel Oil Fuel Oil LPG Other(f) Factors Total United States RSE Column Factors: 1.5 1.2 1.5 0.7 1.1 0.8 1.1 1 0.5 311 Food 91 50 92 0 26 Q Q W W 10.7 311221 Wet Corn

  2. table10.12_02.xls

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

    2 Capability to Switch LPG to Alternative Energy Sources, 2002; Level: National Data and Regional Totals; Row: NAICS Codes, Value of Shipments and Employment Sizes; Column: Energy Sources; Unit: Thousand Barrels. Coal Coke RSE NAICS Total Not Electricity Natural Distillate Residual and Row Code(a) Subsector and Industry Consumed(c) Switchable Switchable Receipts(d) Gas Fuel Oil Fuel Oil Coal Breeze Other(e) Factors Total United States RSE Column Factors: 1 1 1 1.1 0.8 0.9 0.5 4.3 0 0.5 311 Food

  3. table10.13_02.xls

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

    3 Number of Establishments with Capability to Switch LPG to Alternative Energy Sources, 2002; Level: National Data; Row: NAICS Codes; Column: Energy Sources; Unit: Establishment Counts. Coal Coke RSE NAICS Total Not Electricity Natural Distillate Residual and Row Code(a) Subsector and Industry Consumed(d) Switchable Switchable Receipts(e) Gas Fuel Oil Fuel Oil Coal Breeze Other(f) Factors Total United States RSE Column Factors: 0.6 0.8 0.6 0.9 0.7 0.8 1 2.8 2.7 0.7 311 Food 3,159 793 2,492 570

  4. table10.2_02.xls

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

    2 Capability to Switch Natural Gas to Alternative Energy Sources, 2002; Level: National Data and Regional Totals; Row: NAICS Codes, Value of Shipments and Employment Sizes; Column: Energy Sources; Unit: Billion Cubic Feet. Coal Coke RSE NAICS Total Not Electricity Distillate Residual and Row Code(a) Subsector and Industry Consumed(c) Switchable Switchable Receipts(d) Fuel Oil Fuel Oil Coal LPG Breeze Other(e) Factors Total United States RSE Column Factors: 0.8 1 0.9 1.6 1 1 1.1 1.1 0.5 1.3 311

  5. table10.3_02.xls

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

    3 Number of Establishments with Capability to Switch Natural Gas to Alternative Energy Sources, 2002; Level: National Data; Row: NAICS Codes; Column: Energy Sources; Unit: Establishment Counts. Coal Coke RSE NAICS Total Not Electricity Distillate Residual and Row Code(a) Subsector and Industry Consumed(d) Switchable Switchable Receipts(e) Fuel Oil Fuel Oil Coal LPG Breeze Other(f) Factors Total United States RSE Column Factors: 0.6 1.1 0.7 1.2 1.1 1.1 1.2 1.1 0.9 1.1 311 Food 12,018 2,210 10,674

  6. table10.4_02.xls

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

    4 Capability to Switch Residual Fuel Oil to Alternative Energy Sources, 2002; Level: National Data and Regional Totals; Row: NAICS Codes, Value of Shipments and Employment Sizes; Column: Energy Sources; Unit: Thousand Barrels. Coal Coke RSE NAICS Total Not Electricity Natural Distillate and Row Code(a) Subsector and Industry Consumed(c) Switchable Switchable Receipts(d) Gas Fuel Oil Coal LPG Breeze Other(e) Factors Total United States RSE Column Factors: 1.9 1.4 1.9 0.6 1.5 0.6 0.6 0.9 0 0.7 311

  7. table10.5_02.xls

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

    5 Number of Establishments with Capability to Switch Residual Fuel Oil to Alternative Energy Sources, 2002; Level: National Data; Row: NAICS Codes; Column: Energy Sources; Unit: Establishment Counts. Coal Coke RSE NAICS Total Not Electricity Natural Distillate and Row Code(a) Subsector and Industry Consumed(d) Switchable Switchable Receipts(e) Gas Fuel Oil Coal LPG Breeze Other(f) Factors Total United States RSE Column Factors: 1.3 1 1.5 0.7 1 0.8 0.6 1.2 1.4 0.8 311 Food 274 183 108 0 119 72 W

  8. table10.6_02.xls

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

    Capability to Switch Electricity to Alternative Energy Sources, 2002; Level: National Data and Regional Totals; Row: NAICS Codes, Value of Shipments and Employment Sizes; Column: Energy Sources; Unit: Million Kilowatthours. Coal Coke RSE NAICS Total Not Natural Distillate Residual and Row Code(a) Subsector and Industry Receipts(c) Switchable Switchable Gas Fuel Oil Fuel Oil Coal LPG Breeze Other(d) Factors Total United States RSE Column Factors: 0.9 1.4 0.9 1.6 1.7 0.6 0.8 1.7 0.5 0.9 311 Food

  9. table10.7_02.xls

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

    Number of Establishments with Capability to Switch Electricity to Alternative Energy Sources, 2002; Level: National Data; Row: NAICS Codes; Column: Energy Sources; Unit: Establishment Counts. Coal Coke RSE NAICS Total Not Natural Distillate Residual and Row Code(a) Subsector and Industry Receipts(d) Switchable Switchable Gas Fuel Oil Fuel Oil Coal LPG Breeze Other(e) Factors Total United States RSE Column Factors: 0.6 1.2 0.6 1.2 1.3 1 0.8 1.4 1.3 1.2 311 Food 15,045 582 14,905 185 437 30 W 170

  10. table10.8_02.xls

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

    Capability to Switch Distillate Fuel Oil to Alternative Energy Sources, 2002; Level: National Data and Regional Totals; Row: NAICS Codes, Value of Shipments and Employment Sizes; Column: Energy Sources; Unit: Thousand Barrels. Coal Coke RSE NAICS Total Not Electricity Natural Residual and Row Code(a) Subsector and Industry Consumed(c) Switchable Switchable Receipts(d) Gas Fuel Oil Coal LPG Breeze Other(e) Factors Total United States RSE Column Factors: 1.7 1.6 1.7 0.9 1.5 0.6 0.7 1.7 0.3 0.8

  11. table10.9_02.xls

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

    Number of Establishments with Capability to Switch Distillate Fuel Oil to Alternative Energy Sources, 2002; Level: National Data; Row: NAICS Codes; Column: Energy Sources; Unit: Establishment Counts. Coal Coke RSE NAICS Total Not Electricity Natural Residual and Row Code(a) Subsector and Industry Consumed(d) Switchable Switchable Receipts(e) Gas Fuel Oil Coal LPG Breeze Other(f) Factors Total United States RSE Column Factors: 1 1.3 1 0.9 1.2 1 0.8 1.3 0.8 0.9 311 Food 2,418 789 1,899 129 447

  12. table11.1_02.xls

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

    Electricity: Components of Net Demand, 2002; Level: National and Regional Data; Row: NAICS Codes; Column: Electricity Components; Unit: Million Kilowatthours. Total Sales and Net Demand RSE NAICS Transfers Onsite Transfers for Row Code(a) Subsector and Industry Purchases In(b) Generation(c) Offsite Electricity(d) Factors Total United States RSE Column Factors: 1.3 1.1 0.9 0.6 1.2 311 Food W W 5,622 708 73,143 5.1 311221 Wet Corn Milling W W 2,755 248 9,606 2.6 31131 Sugar 733 * 1,126 8 1,851 1

  13. table11.3_02.xls

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

    Electricity: Components of Onsite Generation, 2002; Level: National and Regional Data; Row: NAICS Codes; Column: Onsite-Generation Components; Unit: Million Kilowatthours. Renewable Energy (excluding Wood RSE NAICS Total Onsite and Row Code(a) Subsector and Industry Generation Cogeneration(b) Other Biomass)(c) Other(d) Factors Total United States RSE Column Factors: 0.9 0.8 1.1 1.3 311 Food 5,622 5,375 0 247 12.5 311221 Wet Corn Milling 2,755 2,717 0 38 2.6 31131 Sugar 1,126 1,077 0 48 1 311421

  14. table11.5_02.xls

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

    Electricity: Sales to Utility and Nonutility Purchasers, 2002; Level: National and Regional Data; Row: NAICS Codes; Column: Utility and Nonutility Purchasers; Unit: Million Kilowatthours. Total of RSE NAICS Sales and Utility Nonutility Row Code(a) Subsector and Industry Transfers Offsite Purchaser(b) Purchaser(c) Factors Total United States RSE Column Factors: 1 0.9 1 311 Food 708 380 328 31 311221 Wet Corn Milling 248 W W 20.1 31131 Sugar 8 8 0 1 311421 Fruit and Vegetable Canning 28 W W 1 312

  15. table2.1_02.xls

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

    1 Nonfuel (Feedstock) Use of Combustible Energy, 2002; Level: National and Regional Data; Row: NAICS Codes; Column: Energy Sources; Unit: Physical Units or Btu. Coke Residual Distillate Natural LPG and Coal and Breeze NAICS Total Fuel Oil Fuel Oil(b) Gas(c) NGL(d) (million (million Other(e) Code(a) Subsector and Industry (trillion Btu) (million bbl) (million bbl) (billion cu ft) (million bbl) short tons) short tons) (trillion Btu) Total United States RSE Column Factors: 1.4 0.4 1.6 1.2 1.2 1.1

  16. table2.4_02.xls

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

    Number of Establishments by Nonfuel (Feedstock) Use of Combustible Energy, 2002; Level: National Data; Row: NAICS Codes (3-Digit Only); Column: Energy Sources; Unit: Establishment Counts. Any Combustible RSE NAICS Energy Residual Distillate Natural LPG and Coke Row Code(a) Subsector and Industry Source(b) Fuel Oil Fuel Oil(c) Gas(d) NGL(e) Coal and Breeze Other(f) Factors Total United States RSE Column Factors: 1.5 0.6 1.1 1 1.1 0.7 1 1.4 311 Food 406 W 152 185 0 0 4 83 9.6 311221 Wet Corn

  17. table3.6_02

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

    Selected Wood and Wood-Related Products in Fuel Consumption, 2002; Level: National and Regional Data; Row: Selected NAICS Codes; Column: Energy Sources; Unit: Trillion Btu. S e l e c t e d W o o d a n d W o o d - R e l a t e d P r o d u c t s B i o m a s s Wood Residues and Wood-Related Pulping Liquor Wood Byproducts and RSE NAICS or Biomass Agricultural Harvested Directly from Mill Paper-Related Row Code(a) Subsector and Industry Black Liquor Total(b) Waste(c) from Trees(d) Processing(e)

  18. table4.1_02.xls

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

    Offsite-Produced Fuel Consumption, 2002; Level: National and Regional Data; Row: NAICS Codes; Column: Energy Sources; Unit: Physical Units or Btu. Coke Residual Distillate Natural LPG and Coal and Breeze RSE NAICS Total Electricity(b) Fuel Oil Fuel Oil(c) Gas(d) NGL(e) (million (million Other(f) Row Code(a) Subsector and Industry (trillion Btu) (million kWh) (million bbl) (million bbl) (billion cu ft) (million bbl) short tons) short tons) (trillion Btu) Factors Total United States RSE Column

  19. table6.1_02.xls

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

    1 Consumption Ratios of Fuel, 2002; Level: National and Regional Data; Row: NAICS Codes; Column: Energy-Consumption Ratios; Unit: Varies. Consumption Consumption per Dollar Consumption per Dollar of Value RSE NAICS per Employee of Value Added of Shipments Row Code(a) Subsector and Industry (million Btu) (thousand Btu) (thousand Btu) Factors Total United States RSE Column Factors: 1.1 0.9 1 311 Food 867.8 6.0 2.6 5.9 311221 Wet Corn Milling 24,113.7 65.7 26.2 1.8 31131 Sugar 8,414.5 54.2 17.9 1

  20. table7.1_02.xls

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

    Average Prices of Purchased Energy Sources, 2002; Level: National and Regional Data; Row: NAICS Codes; Column: All Energy Sources Collected; Unit: U.S. Dollars per Physical Units. Bituminous and Coal Subbituminous Coal Petroleum NAICS TOTAL Acetylene Breeze Total Anthracite Coal Lignite Coke Coke Code(a) Subsector and Industry (million Btu) (cu ft) (short tons) (short tons) (short tons) (short tons) (short tons) (short tons) (gallons) Total United States RSE Column Factors: 1.1 2.1 0.6 1 0.6

  1. table7.6_02.xls

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

    6 Quantity of Purchased Energy Sources, 2002; Level: National and Regional Data; Row: NAICS Codes; Column: Energy Sources; Unit: Physical Units or Btu. Coke Residual Distillate Natural LPG and Coal and Breeze RSE NAICS Total Electricity Fuel Oil Fuel Oil(b) Gas(c) NGL(d) (million (million Other(e) Row Code(a) Subsector and Industry (trillion Btu) (million kWh) (million bbl) (million bbl) (billion cu ft) (million bbl) short tons) short tons) (trillion Btu) Factors Total United States RSE Column

  2. table8.3_02.xls

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

    Number of Establishments by Usage of Cogeneration Technologies, 2002; Level: National Data; Row: NAICS Codes; Column: Usage within Cogeneration Technologies; Unit: Establishment Counts. NAICS Code(a) Subsector and Industry Establishments(b) Establishments with Any Cogeneration Technology in Use(c) In Use(d) Not in Use Don't Know In Use(d) Not in Use Don't Know Total United States RSE Column Factors: 0 1 0.7 0.8 1.7 0.6 0.8 1.7 311 Food 15,089 443 131 13,850 1,109 80 13,729 1,280 311221 Wet Corn

  3. "Code(a)","Subsector and Industry","Total","Electricity","Fuel...

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

    ...es",0,0,"X",0,0,0,0,"X",0 325193," Ethyl Alcohol ",0,0,"X",0,0,0,0,"X",0 325199," Other ...",0,0,"X",0,0,0,"X","X",0 325193," Ethyl Alcohol ",0,0,"X","X",0,0,"X","X","X" 325199," ...

  4. Level: National Data; Row: NAICS Codes; Column: Usage within General Energy-Saving Technologies;

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

    2 Number of Establishments by Usage of General Energy-Saving Technologies, 2006; Level: National Data; Row: NAICS Codes; Column: Usage within General Energy-Saving Technologies; Unit: Establishment Counts. NAICS Code(a) Subsector and Industry Establishments(b) In Use(e) Not in Use Don't Know In Use(e) Not in Use Don't Know In Use(e) Not in Use Don't Know In Use(e) Not in Use Don't Know In Use(e) Not in Use Don't Know Total United States 311 Food 14,128 1,632 9,940 2,556 3,509 8,048 2,571 1,590

  5. table2.2_02.xls

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

    Nonfuel (Feedstock) Use of Combustible Energy, 2002; Level: National and Regional Data; Row: NAICS Codes; Column: Energy Sources; Unit: Trillion Btu. RSE NAICS Residual Distillate Natural LPG and Coke Row Code(a) Subsector and Industry Total Fuel Oil Fuel Oil(b) Gas(c) NGL(d) Coal and Breeze Other(e) Factors Total United States RSE Column Factors: 1.4 0.4 1.6 1.2 1.2 1.1 0.7 1.2 311 Food 8 * Q 7 0 0 * * 10.2 311221 Wet Corn Milling * 0 * 0 0 0 0 * 0.7 31131 Sugar * 0 * * 0 0 * * 0.9 311421

  6. table3.4_02.xls

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

    Number of Establishments by Fuel Consumption, 2002; Level: National Data; Row: NAICS Codes; Column: Energy Sources; Unit: Establishment Counts. Any RSE NAICS Energy Net Residual Distillate Natural LPG and Coke Row Code(a) Subsector and Industry Source(b) Electricity(c) Fuel Oil Fuel Oil(d) Gas(e) NGL(f) Coal and Breeze Other(g) Factors Total United States RSE Column Factors: 0.7 0.7 1.3 1.1 0.9 1.2 1.2 1 1.2 311 Food 15,089 15,045 274 2,418 12,018 3,159 91 19 1,858 5.1 311221 Wet Corn Milling

  7. table4.2_02.xls

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

    Offsite-Produced Fuel Consumption, 2002; Level: National and Regional Data; Row: NAICS Codes; Column: Energy Sources; Unit: Trillion Btu. RSE NAICS Residual Distillate Natural LPG and Coke Row Code(a) Subsector and Industry Total Electricity(b) Fuel Oil Fuel Oil(c) Gas(d) NGL(e) Coal and Breeze Other(f) Factors Total United States RSE Column Factors: 0.8 0.8 1.1 1.6 0.9 1.8 0.7 0.7 1.2 311 Food 1,079 233 13 19 575 5 184 1 50 8 311221 Wet Corn Milling 217 24 * * 61 * 121 0 11 1.1 31131 Sugar 74

  8. table7.2_02.xls

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

    Average Prices of Purchased Energy Sources, 2002; Level: National and Regional Data; Row: NAICS Codes; Column: All Energy Sources Collected; Unit: U.S. Dollars per Million Btu. Bituminous and NAICS Coal Subbituminous Coal Petroleum Code(a) Subsector and Industry TOTAL Acetylene Breeze Total Anthracite Coal Lignite Coke Coke Total United States RSE Column Factors: 1.1 2.1 0.6 0.9 0.6 0.9 1.4 0.7 0.9 311 Food 6.42 113.78 0 1.46 W 1.46 0 5.18 0 311221 Wet Corn Milling 3.11 106.84 0 1.32 0 1.32 0 0

  9. table7.9_02.xls

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

    Expenditures for Purchased Energy Sources, 2002; Level: National and Regional Data; Row: NAICS Codes; Column: Energy Sources; Unit: Million U.S. Dollars. RSE NAICS Residual Distillate Natural LPG and Coke Row Code(a) Subsector and Industry Total Electricity Fuel Oil Fuel Oil(b) Gas(c) NGL(d) Coal and Breeze Other(e) Factors Total United States RSE Column Factors: 0.9 0.9 1.1 1.5 0.9 1.4 0.8 0.7 1.2 311 Food 6,943 3,707 58 135 2,546 38 276 8 175 8 311221 Wet Corn Milling 683 252 2 1 237 * 165 0

  10. table8.2_02.xls

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

    Number of Establishments by Usage of General Energy-Saving Technologies, 2002 Level: National Data; Row: NAICS Codes; Column: Usage within General Energy-Saving Technologies Unit: Establishment Counts. NAICS Code(a) Subsector and Industry Establishments(b) In Use(e) Not in Use Don't Know In Use(e) Not in Use Don't Know Total United States RSE Column Factors: 0 1.1 0.7 1.2 1 0.9 1.3 311 Food 15,089 1,546 12,347 1,196 4,360 9,442 1,287 311221 Wet Corn Milling 49 14 34 1 38 10 1 31131 Sugar 77 4

  11. " Row: NAICS Codes; Column: Energy Sources...

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

    Gas(e)","NGL(f)","Coal","Breeze","Other(g)","Produced Onsite(h)" ,,"Total United ... raw" "Natural Gas Liquids '(NGL).'" " (g) 'Other' includes net steam (the sum of ...

  12. "Characteristic(a)","Total(b)","Electricity(c)","Fuel Oil","Fuel...

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

    Gas(e)","NGL(f)","Coal","Breeze","Other(g)","Produced Onsite(h)" ,"Total United ... raw" "Natural Gas Liquids '(NGL).'" " (g) 'Other' includes net steam (the sum of ...

  13. " Row: NAICS Codes; Column: Energy Sources...

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

    ..."Coal","Breeze","Other(g)","Produced Onsite(h)" ,,"Total United States" ... See also" "Footnote 'i'." " (h) 'Shipments of Energy Sources Produced Onsite' are those ...

  14. "Code(a)","Subsector and Industry","Source(b)","Electricity(c...

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

    Gas(e)","NGL(f)","Coal","and Breeze","Other(g)" ,,"Total United States" , ... raw" "Natural Gas Liquids '(NGL).'" " (g) 'Other' includes net steam (the sum of ...

  15. "Code(a)","Subsector and Industry","Source(b)","Electricity(c...

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

    Gas(e)","NGL(f)","Coal","and Breeze","Other(g)" ,,"Total United States" , ... raw" "Natural Gas Liquids '(NGL).'" " (g) 'Other' includes all other energy that was ...

  16. "Code(a)","Subsector and Industry","Source(b)","Fuel Oil","Fuel...

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

    Breeze","Other(f)" ,,"Total United States" 311,"Food",27.5,"X",42,39.5,62,"X",0,9.8 3112," Grain and Oilseed Milling",29.9,"X",59.3,28,12.1,"X","X",13.7 ...

  17. Forest Products Sector (NAICS 321 and 322) Energy and GHG Combustion...

    Office of Environmental Management (EM)

    Table 2.3-1 presents the subsectors in forest products with data reported in the 2006 EIA Manufacturing Energy Consumption Survey (MECS). Table 2.3-1. Forest products subsectors ...

  18. Cybersecurity Risk Management Process (RMP) | Department of Energy

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

    ... Related Links Integrating Electricity Subsector Failure Scenarios into a Risk Assessment Methodology (December 2013) Energy Sector Cybersecurity Framework Implementation Guidance ...

  19. Okmulgee Extended Facility

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

    (ONG-C2M2) | Department of Energy Oil and Natural Gas Subsector Cybersecurity Capability Maturity Model (ONG-C2M2) Oil and Natural Gas Subsector Cybersecurity Capability Maturity Model (ONG-C2M2) Oil and Natural Gas Subsector Cybersecurity Capability Maturity Model (ONG-C2M2) The Oil and Natural Gas Subsector Cybersecurity Capability Maturity Model (ONG-C2M2) was established as a result of the Administration's efforts to improve electricity subsector cybersecurity capabilities, and to

  20. EIA Energy Efficiency-Table 1d. Nonfuel Consumption (Site Energy...

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

    d Page Last Modified: May 2010 Table 1d. Nonfuel Consumption (Site Energy) for Selected Industries, 1998, 2002, and 2006 (Trillion Btu) MECS Survey Years NAICS Subsector and...

  1. " Level: National Data and Regional...

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

    Totals;" " Row: NAICS Codes, Value of Shipments and ... "Code(a)","Subsector and Industry","Consumed(c)","Switchabl... because Relative Standard Error is greater than 50 ...

  2. " Level: National Data;" " ...

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

    Data;" " Row: NAICS Codes;" " Column: Energy ... "Code(a)","Subsector and Industry","Consumed(d)","Switchabl... because Relative Standard Error is greater than 50 ...

  3. " Row: NAICS Codes;"

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

    Data; " " Row: NAICS Codes;" " Column: Floorspace and ... "Code(a)","Subsector and Industry","(million sq ... because Relative Standard Error is greater than 50 ...

  4. " Level: National Data;" " ...

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

    Data;" " Row: NAICS Codes;" " Column: Energy ... "Code(a)","Subsector and Industry","Receipts(d)","Switchabl... because Relative Standard Error is greater than 50 ...

  5. " Level: National Data and Regional...

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

    Totals;" " Row: NAICS Codes, Value of Shipments and ... "Code(a)","Subsector and Industry","Receipts(c)","Switchabl... because Relative Standard Error is greater than 50 ...

  6. Private Sector Outreach and Partnerships | Department of Energy

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

    Specific mission areas, such as risk and system analysis, modeling and visualization across subsectors, and incident response would not be possible without the participation of the ...

  7. "RSE Table C10.2. Relative Standard Errors for Table C10.2;...

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

    ...-Temperature","Processes" "NAICS"," ",,"Technology" "Code(a)","Subsector and ... that reported this" "cogeneration technology in use anytime in 1998." " NFNo ...

  8. " Row: NAICS Codes;"

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

    " ,,,"Cogeneration" "NAICS",,,"Technology" "Code(a)","Selected Subsectors and ... that reported this" "cogeneration technology in use anytime in 2010." " (e) This ...

  9. file://C:\\Documents and Settings\\bh5\\My Documents\\Energy Effici

    Gasoline and Diesel Fuel Update (EIA)

    2009. MECS Survey Years NAICS Subsector and Industry 1998 2002 2006 311 Food Manufacturing 418 435 457 312 Beverage and Tobacco Product Manufacturing 134 116 125 313 Textile...

  10. file://C:\\Documents and Settings\\bh5\\My Documents\\Energy Effici

    Gasoline and Diesel Fuel Update (EIA)

    Dollars) MECS Survey Years NAICS Subsector and Industry 1998 2002 2006 311 Food Manufacturing 430 468 552 312 Beverage and Tobacco Product Manufacturing 98 120 131 313 Textile...

  11. file://C:\\Documents and Settings\\bh5\\My Documents\\Energy Effici

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

    2009. MECS Survey Years NAICS Subsector and Industry 1998 2002 2006 311 Food Manufacturing 417 444 526 312 Beverage and Tobacco Product Manufacturing 114 128 144 313 Textile...

  12. file://C:\\Documents and Settings\\bh5\\My Documents\\Energy Effici

    Gasoline and Diesel Fuel Update (EIA)

    Dollars ) MECS Survey Years NAICS Subsector and Industry 1998 2002 2006 311 Food Manufacturing 431 447 473 312 Beverage and Tobacco Product Manufacturing 122 96 109 313 Textile...

  13. Advanced Metering Infrastructure Security Considerations | Department...

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

    More Documents & Publications Integrating Electricity Subsector Failure Scenarios into a Risk Assessment Methodology (December 2013) SGIG and SGDP Highlights: Jumpstarting a Modern ...

  14. Table 1.3 First Use of Energy for All Purposes (Fuel and Nonfuel), 2010;

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

    1.3 First Use of Energy for All Purposes (Fuel and Nonfuel), 2010; Level: National and Regional Data; Row: Values of Shipments and Employment Sizes; Column: Energy Sources and Shipments; Unit: Trillion Btu. Shipments Economic Net Residual Distillate LPG and Coke and of Energy Sources Characteristic(a) Total(b) Electricity(c) Fuel Oil Fuel Oil(d) Natural Gas(e) NGL(f) Coal Breeze Other(g) Produced Onsite(h) Total United States Value of Shipments and Receipts (million dollars) Under 20 1,169 314 6

  15. Level: National and Regional Data; Row: Values of Shipments and Employment Sizes

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

    1.3 First Use of Energy for All Purposes (Fuel and Nonfuel), 2006; Level: National and Regional Data; Row: Values of Shipments and Employment Sizes Column: Energy Sources and Shipments; Unit: Trillion Btu. Shipments Economic Net Residual Distillate LPG and Coke and of Energy Sources Characteristic(a) Total(b) Electricity(c) Fuel Oil Fuel Oil(d) Natural Gas(e) NGL(f) Coal Breeze Other(g) Produced Onsite(h) Total United States Value of Shipments and Receipts (million dollars) Under 20 1,166 367 23

  16. table1.3_02.xls

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

    3 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National and Regional Data; Row: Values of Shipments and Employment Sizes; Column: Energy Sources and Shipments; Unit: Trillion Btu. Shipments RSE Economic Net Residual Distillate Natural LPG and Coke and of Energy Sources Row Characteristic(a) Total(b) Electricity(c) Fuel Oil Fuel Oil(d) Gas(e) NGL(f) Coal Breeze Other(g) Produced Onsite(h) Factors Total United States RSE Column Factors: 0.8 0.9 1.4 2.7 0.8 0.6 2 1.4 1.1

  17. Level: National Data; Row: General Energy-Management Activities within NAICS Codes;

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

    Next MECS will be fielded in 2015 Table 8.1 Number of Establishments by Participation in General Energy-Management Activities, 2010; Level: National Data; Row: General Energy-Management Activities within NAICS Codes; Column: Participation and Source of Assistance; Unit: Establishment Counts. NAICS Code(a) Energy-Management Activity No Participation Participation(b) In-house Utility/Energy Suppler Product/Service Provider Federal Program State/Local Program Don't Know Total United States 311 -

  18. table6.3_02.xls

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

    3 Consumption Ratios of Fuel, 2002; Level: National Data; Row: Values of Shipments within NAICS Codes; Column: Energy-Consumption Ratios; Unit: Varies. Consumption Consumption per Dollar Consumption per Dollar of Value RSE NAICS per Employee of Value Added of Shipments Row Code(a) Economic Characteristic(b) (million Btu) (thousand Btu) (thousand Btu) Factors Total United States RSE Column Factors: 1 1 1 311 - 339 ALL MANUFACTURING INDUSTRIES Value of Shipments and Receipts (million dollars)

  19. New Draft of Cybersecurity Risk Management Process (RMP) Guideline Now Available for Public Comment (March 2012)

    Broader source: Energy.gov [DOE]

    The Department of Energy, in collaboration with the National Institute of Standards and Technology and the North American Electric Reliability Corporation, has released the second draft of the Electricity Subsector Cybersecurity Risk Management Process (RMP) Guideline for public comment.

  20. Market Report for the Industrial Sector, 2009

    SciTech Connect (OSTI)

    Sastri, Bhima; Brueske, Sabine; de los Reyes, Pamela; Jamison, Keith; Justiniano, Mauricio; Margolis, Nancy; Monfort, Joe; Raghunathan, Anand; Sabouni, Ridah

    2009-07-01

    This report provides an overview of trends in industrial-sector energy use. It focuses on some of the largest and most energy-intensive industrial subsectors and several emerging technologies that could transform key segments of industry.

  1. Economic and Environmental Impacts of Increased US Exports of...

    Energy Savers [EERE]

    ... Finally, we examine the impacts on the use of CNG in the transport sector. The CES virtually eliminates the use of CNG or LNG in the heavy duty truck sub-sector as shown in Figure ...

  2. EIA Energy Efficiency-Table 4b. Value of Production by Selected...

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

    b Page Last Modified: May 2010 Table 4b. Value of Production 1 by Selected Industries, 1998, 2002, and 2006 (Billion 2000 Dollars ) MECS Survey Years NAICS Subsector and Industry...

  3. EIA Energy Efficiency-Table 4a. Value of Shipments by Selected...

    Gasoline and Diesel Fuel Update (EIA)

    Table 4a Page Last Modified: May 2010 Table 4a. Value of Shipments1 by Selected Industries, 1998, 2002, and 2006 (Billion 2000 Dollars ) MECS Survey Years NAICS Subsector and...

  4. EIA Energy Efficiency-Table 3d. Value Added by Selected Industries...

    Gasoline and Diesel Fuel Update (EIA)

    d Page Last Modified: May 2010 Table 3d. Value Added1 by Selected Industries, 1998, 2002, and 2006 (Current Brillion Dollars) MECS Survey Years NAICS Subsector and Industry 1998...

  5. EIA Energy Efficiency-Table 3a. Value of Shipments by Selected...

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

    a Page Last Modified: May 2010 Table 3a. Value of Shipments 1 by Selected Industries, 1998, 2002, and 2006 (Current Billion Dollars) MECS Survey Years NAICS Subsector and Industry...

  6. EIA Energy Efficiency-Table 4d. Value Added by Selected Industries...

    Gasoline and Diesel Fuel Update (EIA)

    d Page Last Modified: May 2010 Table 4d. Value Added1 by Selected Industries, 1998, 2002, and 2006 (Billion 2000 Dollars 2) MECS Survey Years NAICS Subsector and Industry 1998 2002...

  7. EIA Energy Efficiency-Table 1b. Fuel Consumption for Selected...

    Gasoline and Diesel Fuel Update (EIA)

    b Page Last Modified: May 2010 Table 1b. End Uses of Fuel Consumption (Site Energy) for Selected Industries, 1998, 2002, and 2006 (Trillion Btu) MECS Survey Years NAICS Subsector...

  8. EIA Energy Efficiency-Table 4f. Industrial Production Indexes...

    Gasoline and Diesel Fuel Update (EIA)

    f Page Last Modified: May 2010 Table 4f. Industrial Production Indexes by Selected Industries, 1998, 2002, and 2006 (2000 100) MECS Survey Years NAICS Subsector and Industry 1998...

  9. Table 1c. Off-Site Produced Energy (Site Energy)For Selected...

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

    c Page Last Modified: May 2010 Table 1c. Off-Site Produced Energy (Site Energy) for Selected Industries, 1998, 2002 and 2006 (Trillion Btu) MECS Survey Years NAICS Subsector and...

  10. EIA Energy Efficiency-Table 4e. Gross Output by Selected Industries...

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

    e Page Last Modified: May 2010 Table 4e. Gross Output1by Selected Industries, 1998, 2002, and 2006 (Billion 2000 Dollars 2) MECS Survey Years NAICS Subsector and Industry 1998 2002...

  11. EIA Energy Efficiency-Table 3e. Gross Output by Selected Industries...

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

    e Page Last Modified: May 2010 Table 3e. Gross Output1 by Selected Industries, 1998, 2002, and 2006 (Current Billion Dollars) MECS Survey Years NAICS Subsector and Industry 1998...

  12. PowerPoint Presentation

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

    Subsector Cybersecurity Capability Maturity Model (ES-C2M2) ES-C2M2 Background ES-C2M2 Facilitated Self-Evaluation v1.0 2 * Administration initiative: Led by DOE in collaboration...

  13. file://C:\\Documents and Settings\\bh5\\My Documents\\Energy Effici

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

    Table 6. MECS Survey Years NAICS Subsector and Industry 1998 2002 2006 311 Food Manufacturing 429 456 539 312 Beverage and Tobacco Product Manufacturing 103 104 125 313 Textile...

  14. DYNAMIC MANUFACTURING ENERGY FLOWS TOOL (2010, UNITS: TRILLION...

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

    this diagram to explore (zoom, pan, select) and compare energy flows across U.S. manufacturing and key subsectors. Line widths indicate the volume of energy flow in trillions of...

  15. file://C:\\Documents and Settings\\bh5\\My Documents\\Energy Effici

    Gasoline and Diesel Fuel Update (EIA)

    Sept 2009. MECS Survey Years NAICS Subsector and Industry 1998 2002 2006 311 Food Manufacturing 430 448 472 312 Beverage and Tobacco Product Manufacturing 121 96 109 313 Textile...

  16. file://C:\\Documents and Settings\\bh5\\My Documents\\Energy Effici

    Gasoline and Diesel Fuel Update (EIA)

    Table 2. MECS Survey Years NAICS Subsector and Industry 1998 2002 2006 311 Food Manufacturing 428 460 537 312 Beverage and Tobacco Product Manufacturing 102 106 124 313 Textile...

  17. file://C:\\Documents and Settings\\bh5\\My Documents\\Energy Effici

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

    2009. MECS Survey Years NAICS Subsector and Industry 1998 2002 2006 311 Food Manufacturing 97.3 102.6 107.9 312 Beverage and Tobacco Product Manufacturing 109.0 90.0 99.4...

  18. Research Highlight

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

    and for divided sub-sectors (DF1 and DF2) in dust-free sector. Also PR estimated rain rate profiles with standard errors in dusty and dust-free sectors for both case and...

  19. DYNAMIC MANUFACTURING ENERGY SANKEY TOOL (2010, UNITS: TRILLION BTU) |

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

    Department of Energy Information Resources » Energy Analysis » DYNAMIC MANUFACTURING ENERGY SANKEY TOOL (2010, UNITS: TRILLION BTU) DYNAMIC MANUFACTURING ENERGY SANKEY TOOL (2010, UNITS: TRILLION BTU) About the Energy Data Use this diagram to explore (zoom, pan, select) and compare energy flows across U.S. manufacturing and key subsectors. Line widths indicate the volume of energy flow in trillions of British thermal units (TBtu). The 15 manufacturing subsectors together consume 95% of all

  20. Level: National Data; Row: Employment Sizes within NAICS Codes;

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

    4 Consumption Ratios of Fuel, 2006; Level: National Data; Row: Employment Sizes within NAICS Codes; Column: Energy-Consumption Ratios; Unit: Varies. Consumption Consumption per Dollar Consumption per Dollar of Value NAICS per Employee of Value Added of Shipments Code(a) Economic Characteristic(b) (million Btu) (thousand Btu) (thousand Btu) Total United States 311 - 339 ALL MANUFACTURING INDUSTRIES Employment Size Under 50 562.6 4.7 2.4 50-99 673.1 5.1 2.4 100-249 1,072.8 6.5 3.0 250-499 1,564.3

  1. Level: National Data; Row: Employment Sizes within NAICS Codes;

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

    4 Consumption Ratios of Fuel, 2010; Level: National Data; Row: Employment Sizes within NAICS Codes; Column: Energy-Consumption Ratios; Unit: Varies. Consumption Consumption per Dollar Consumption per Dollar of Value NAICS per Employee of Value Added of Shipments Code(a) Economic Characteristic(b) (million Btu) (thousand Btu) (thousand Btu) Total United States 311 - 339 ALL MANUFACTURING INDUSTRIES Employment Size Under 50 625.5 3.3 1.7 50-99 882.3 5.8 2.5 100-249 1,114.9 5.8 2.5 250-499 2,250.4

  2. Level: National Data; Row: End Uses within NAICS Codes; Column: Energy Sources, including Net Demand for Electricity;

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

    Next MECS will be conducted in 2010 Table 5.3 End Uses of Fuel Consumption, 2006; Level: National Data; Row: End Uses within NAICS Codes; Column: Energy Sources, including Net Demand for Electricity; Unit: Physical Units or Btu. Distillate Coal Fuel Oil (excluding Coal Net Demand Residual and Natural Gas(d) LPG and Coke and Breeze) NAICS for Electricity(b) Fuel Oil Diesel Fuel(c) (billion NGL(e) (million Code(a) End Use (million kWh) (million bbl) (million bbl) cu ft) (million bbl) short tons)

  3. Level: National Data; Row: End Uses within NAICS Codes; Column: Energy Sources, including Net Demand for Electricity;

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

    4 End Uses of Fuel Consumption, 2006; Level: National Data; Row: End Uses within NAICS Codes; Column: Energy Sources, including Net Demand for Electricity; Unit: Trillion Btu. Distillate Fuel Oil Coal NAICS Net Demand Residual and LPG and (excluding Coal Code(a) End Use for Electricity(b) Fuel Oil Diesel Fuel(c) Natural Gas(d) NGL(e) Coke and Breeze) Total United States 311 - 339 ALL MANUFACTURING INDUSTRIES TOTAL FUEL CONSUMPTION 3,335 251 129 5,512 79 1,016 Indirect Uses-Boiler Fuel 84 133 23

  4. Level: National Data; Row: End Uses within NAICS Codes; Column: Energy Sources, including Net Electricity;

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

    1 End Uses of Fuel Consumption, 2006; Level: National Data; Row: End Uses within NAICS Codes; Column: Energy Sources, including Net Electricity; Unit: Physical Units or Btu. Distillate Coal Fuel Oil (excluding Coal Net Residual and Natural Gas(d) LPG and Coke and Breeze) NAICS Total Electricity(b) Fuel Oil Diesel Fuel(c) (billion NGL(e) (million Other(f) Code(a) End Use (trillion Btu) (million kWh) (million bbl) (million bbl) cu ft) (million bbl) short tons) (trillion Btu) Total United States

  5. Level: National Data; Row: End Uses within NAICS Codes; Column: Energy Sources, including Net Electricity;

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

    2 End Uses of Fuel Consumption, 2006; Level: National Data; Row: End Uses within NAICS Codes; Column: Energy Sources, including Net Electricity; Unit: Trillion Btu. Distillate Fuel Oil Coal NAICS Net Residual and LPG and (excluding Coal Code(a) End Use Total Electricity(b) Fuel Oil Diesel Fuel(c) Natural Gas(d) NGL(e) Coke and Breeze) Other(f) Total United States 311 - 339 ALL MANUFACTURING INDUSTRIES TOTAL FUEL CONSUMPTION 15,658 2,850 251 129 5,512 79 1,016 5,820 Indirect Uses-Boiler Fuel --

  6. Level: National Data; Row: Specific Energy-Management Activities within NAICS Codes;

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

    Next MECS will be conducted in 2010 Table 8.4 Number of Establishments by Participation in Specific Energy-Management Activities, 2006; Level: National Data; Row: Specific Energy-Management Activities within NAICS Codes; Column: Participation; Unit: Establishment Counts. NAICS Code(a) Energy-Management Activity No Participation Participation(b) Don't Know Not Applicable Total United States 311 - 339 ALL MANUFACTURING INDUSTRIES Full-Time Energy Manager (c) 159,258 9,922 25,553 -- Set Goals for

  7. Level: National Data; Row: Specific Energy-Management Activities within NAICS Codes;

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

    Next MECS will be fielded in 2015 Table 8.4 Number of Establishments by Participation in Specific Energy-Management Activities, 2010; Level: National Data; Row: Specific Energy-Management Activities within NAICS Codes; Column: Participation; Unit: Establishment Counts. NAICS Code(a) Energy-Management Activity No Participation Participation(b) Don't Know No Steam Used Total United States 311 - 339 ALL MANUFACTURING INDUSTRIES Full-Time Energy Manager (c) 142,267 12,536 15,365 -- Set Goals for

  8. Level: National Data; Row: Values of Shipments within NAICS Codes;

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

    3 Consumption Ratios of Fuel, 2006; Level: National Data; Row: Values of Shipments within NAICS Codes; Column: Energy-Consumption Ratios; Unit: Varies. Consumption Consumption per Dollar Consumption per Dollar of Value NAICS per Employee of Value Added of Shipments Code(a) Economic Characteristic(b) (million Btu) (thousand Btu) (thousand Btu) Total United States 311 - 339 ALL MANUFACTURING INDUSTRIES Value of Shipments and Receipts (million dollars) Under 20 330.6 3.6 2.0 20-49 550.0 4.5 2.2

  9. Level: National Data; Row: Values of Shipments within NAICS Codes;

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

    3 Consumption Ratios of Fuel, 2010; Level: National Data; Row: Values of Shipments within NAICS Codes; Column: Energy-Consumption Ratios; Unit: Varies. Consumption Consumption per Dollar Consumption per Dollar of Value NAICS per Employee of Value Added of Shipments Code(a) Economic Characteristic(b) (million Btu) (thousand Btu) (thousand Btu) Total United States 311 - 339 ALL MANUFACTURING INDUSTRIES Value of Shipments and Receipts (million dollars) Under 20 405.4 4.0 2.1 20-49 631.3 4.7 2.2

  10. table5.1_02

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

    1 End Uses of Fuel Consumption, 2002; Level: National Data; Row: End Uses within NAICS Codes; Column: Energy Sources, including Net Electricity; Unit: Physical Units or Btu. Distillate Fuel Oil Coal Net Residual and Natural LPG and (excluding Coal RSE NAICS Total Electricity(b) Fuel Oil Diesel Fuel(c) Gas(d) NGL(e) Coke and Breeze) Other(f) Row Code(a) End Use (trillion Btu) (million kWh) (million bbl) (million bbl) (billion cu ft) (million bbl) (million short tons) (trillion Btu) Factors Total

  11. table5.2_02

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

    End Uses of Fuel Consumption, 2002; Level: National Data; Row: End Uses within NAICS Codes; Column: Energy Sources, including Net Electricity; Unit: Trillion Btu. Distillate Fuel Oil Coal RSE NAICS Net Residual and Natural LPG and (excluding Coal Row Code(a) End Use Total Electricity(b) Fuel Oil Diesel Fuel(c) Gas(d) NGL(e) Coke and Breeze) Other(f) Factors Total United States 311 - 339 ALL MANUFACTURING INDUSTRIES RSE Column Factors: 0.3 1 1 2.4 1.1 1.3 1 NF TOTAL FUEL CONSUMPTION 16,273 2,840

  12. table5.3_02

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

    3 End Uses of Fuel Consumption, 2002; Level: National Data; Row: End Uses within NAICS Codes; Column: Energy Sources, including Net Demand for Electricity; Unit: Physical Units or Btu. Distillate Net Demand Fuel Oil Coal for Residual and Natural LPG and (excluding Coal RSE NAICS Electricity(b) Fuel Oil Diesel Fuel(c) Gas(d) NGL(e) Coke and Breeze) Row Code(a) End Use (million kWh) (million bbl) (million bbl) (billion cu ft) (million bbl) (million short tons) Factors Total United States 311 - 339

  13. table5.4_02

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

    4 End Uses of Fuel Consumption, 2002; Level: National Data; Row: End Uses within NAICS Codes; Column: Energy Sources, including Net Demand for Electricity; Unit: Trillion Btu. Distillate Net Demand Fuel Oil Coal RSE NAICS for Residual and Natural LPG and (excluding Coal Row Code(a) End Use Electricity(b) Fuel Oil Diesel Fuel(c) Gas(d) NGL(e) Coke and Breeze) Factors Total United States 311 - 339 ALL MANUFACTURING INDUSTRIES RSE Column Factors: NF 1 2.4 1.1 1.3 1 TOTAL FUEL CONSUMPTION 3,297 208

  14. table6.4_02.xls

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

    4 Consumption Ratios of Fuel, 2002; Level: National Data; Row: Employment Sizes within NAICS Codes; Column: Energy-Consumption Ratios; Unit: Varies. Consumption Consumption per Dollar Consumption per Dollar of Value RSE NAICS per Employee of Value Added of Shipments Row Code(a) Economic Characteristic(b) (million Btu) (thousand Btu) (thousand Btu) Factors Total United States RSE Column Factors: 1.1 1 1 311 - 339 ALL MANUFACTURING INDUSTRIES Employment Size Under 50 395.7 4.3 2.3 3.6 50-99 663.4

  15. table8.1_02.xls

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

    1 Number of Establishments by Participation in Energy-Management Activity, 2002 Level: National Data; Row: Energy-Management Activities within NAICS Codes; Column: Participation and Source of Financial Support for Activity; Unit: Establishment Counts. RSE NAICS Row Code(a) Energy-Management Activity No Participation Participation(b) In-house Other Don't Know Factors Total United States RSE Column Factors: 0.9 1.4 0.9 0.9 1 311 - 339 ALL MANUFACTURING INDUSTRIES Participation in One or More of

  16. Energy-Related Carbon Dioxide Emissions in U.S. Manufacturing

    Reports and Publications (EIA)

    2006-01-01

    Based on the Manufacturing Energy Consumption Survey (MECS) conducted by the U.S. Department of Energy, Energy Information Administration (EIA), this paper presents historical energy-related carbon dioxide emission estimates for energy-intensive sub-sectors and 23 industries. Estimates are based on surveys of more than 15,000 manufacturing plants in 1991, 1994, 1998, and 2002. EIA is currently developing its collection of manufacturing data for 2006.

  17. RSE Table 10.12 Relative Standard Errors for Table 10.12

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

    2 Relative Standard Errors for Table 10.12;" " Unit: Percents." ,,"LPG",,,"Alternative Energy Sources(b)" ,,,,,,,,,,"Coal Coke" "NAICS"," ","Total"," ","Not","Electricity","Natural","Distillate","Residual",,"and" "Code(a)","Subsector and

  18. RSE Table 10.13 Relative Standard Errors for Table 10.13

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

    3 Relative Standard Errors for Table 10.13;" " Unit: Percents." ,,"LPG(b)",,,"Alternative Energy Sources(c)" ,,,,,,,,,,"Coal Coke" "NAICS"," ","Total"," ","Not","Electricity","Natural","Distillate","Residual",,"and" "Code(a)","Subsector and

  19. Released: June 2010

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

    3 Relative Standard Errors for Table 10.13;" " Unit: Percents." ,,"LPG(b)",,,"Alternative Energy Sources(c)" ,,,,,,,,,,"Coal Coke" "NAICS"," ","Total"," ","Not","Electricity","Natural","Distillate","Residual",,"and" "Code(a)","Subsector and

  20. Cybersecurity Capability Maturity Model (C2M2) Program | Department of

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

    Energy Cybersecurity Capability Maturity Model (C2M2) Program Cybersecurity Capability Maturity Model (C2M2) Program Cybersecurity Capability Maturity Model (C2M2) Program The Cybersecurity Capability Maturity Model (C2M2) program is a public-private partnership effort that was established as a result of the Administration's efforts to improve electricity subsector cybersecurity capabilities, and to understand the cybersecurity posture of the grid. The C2M2 helps organizations-regardless of

  1. Cybersecurity Risk Management Process (RMP) Guideline - Final (May 2012) |

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

    Department of Energy Risk Management Process (RMP) Guideline - Final (May 2012) Cybersecurity Risk Management Process (RMP) Guideline - Final (May 2012) This electricity subsector cybersecurity Risk Management Process (RMP) guideline was developed by the Department of Energy, in collaboration with the National Institute of Standards and Technology (NIST) and the North American Electric Reliability Corporation (NERC). The RMP is written with the goal of enabling organizations- regardless of

  2. DOE Releases Maturity Model to Better Protect the Nation's Grid from

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

    Cybersecurity Threats | Department of Energy Maturity Model to Better Protect the Nation's Grid from Cybersecurity Threats DOE Releases Maturity Model to Better Protect the Nation's Grid from Cybersecurity Threats May 31, 2012 - 4:32pm Addthis The Electricity Subsector Cybersecurity Capability Maturity Model, which allows electric utilities and grid operators to assess their cybersecurity capabilities and prioritize their actions and investments to improve cybersecurity, combines elements

  3. Recommendations on U. S. Grid Security - EAC 2011 | Department of Energy

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

    on U. S. Grid Security - EAC 2011 Recommendations on U. S. Grid Security - EAC 2011 Recommendations from the Electricity Advisory Committee on actions to be taken by the Department of Energy to compliment the North American Electric Reliability Corporation's (NERC's) Critical Infrastructure Strategic Roadmap developed by the Electricity Sub-Sector Coordinating Council and approved by the NERC Board of Trustees in November 2010. PDF icon EAC Recommendations on U. S. Grid Security Oct 2011.pdf

  4. Roadmap to Achieve Energy Delivery Systems Cybersecurity

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

    Roadmap to Achieve Energy Delivery Systems Cybersecurity ii Acknowledgements The Energy Sector Control Systems Working Group (ESCSWG) developed this roadmap in support of the Electricity Sub-sector Coordinating Council, Oil and Natural Gas Sector Coordinating Council, and the Government Coordinating Council for Energy under the Critical Infrastructure Partnership Advisory Council (CIPAC) Framework; the roadmap has been approved for release by these councils. The ESCSWG members volunteered their

  5. "RSE Table C12.1. Relative Standard Errors for Table C12.1;"

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

    2.1. Relative Standard Errors for Table C12.1;" " Units: Percents." ,,"Approximate",,,"Approximate","Average" ,,"Enclosed Floorspace",,"Average","Number","Number" "NAICS"," ","of All Buildings",,"Enclosed Floorspace","of All Buildings","of Buildings Onsite" "Code(a)","Subsector and

  6. 2006 Update of Business Downtime Costs

    SciTech Connect (OSTI)

    Hinrichs, Mr. Doug; Goggin, Mr. Michael

    2007-01-01

    The objective of this paper is to assess the downtime cost of power outages to businesses in the commercial and industrial sectors, updating and improving upon studies that have already been published on this subject. The goal is to produce a study that, relative to existing studies, (1) applies to a wider set of business types (2) reflects more current downtime costs, (3) accounts for the time duration factor of power outages, and (4) includes data on the costs imposed by real outages in a well-defined market. This study examines power outage costs in 11 commercial subsectors and 5 industrial subsectors, using data on downtime costs that was collected in the 1990's. This study also assesses power outage costs for power outages of 20 minutes, 1 hour, and 4 hours duration. Finally, this study incorporates data on the costs of real power outages for two business subsectors. However, the current limited state of data availability on the topic of downtime costs means there is room to improve upon this study. Useful next steps would be to generate more recent data on downtime costs, data that covers outages shorter than 20 minutes duration and longer than 4 hours duration, and more data that is based on the costs caused by real-world outages. Nevertheless, with the limited data that is currently available, this study is able to generate a clear and detailed picture of the downtime costs that are faced by different types of businesses.

  7. RSE Table 10.10 Relative Standard Errors for Table 10.10

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

    0 Relative Standard Errors for Table 10.10;" " Unit: Percents." ,,"Coal",,,"Alternative Energy Sources(b)" "NAICS"," ","Total"," ","Not","Electricity","Natural","Distillate","Residual" "Code(a)","Subsector and Industry","Consumed(c)","Switchable","Switchable","Receipts(d)","Gas","Fuel

  8. RSE Table 10.11 Relative Standard Errors for Table 10.11

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

    1 Relative Standard Errors for Table 10.11;" " Unit: Percents." ,,"Coal(b)",,,"Alternative Energy Sources(c)" "NAICS"," ","Total"," ","Not","Electricity","Natural","Distillate","Residual" "Code(a)","Subsector and Industry","Consumed(d)","Switchable","Switchable","Receipts(e)","Gas","Fuel

  9. RSE Table 2.1 Relative Standard Errors for Table 2.1

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

    2.1 Relative Standard Errors for Table 2.1;" " Unit: Percents." " "," " " "," " "NAICS"," "," ","Residual","Distillate","Natural ","LPG and",,"Coke"," " "Code(a)","Subsector and Industry","Total","Fuel Oil","Fuel Oil(b)","Gas(c)","NGL(d)","Coal","and

  10. RSE Table N2.1 and N2.2. Relative Standard Errors for Tables N2.1 and N2.2

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

    N2.1 and N2.2. Relative Standard Errors for Tables N2.1 and N2.2;" " Unit: Percents." " "," " "NAICS"," "," ","Residual","Distillate",,"LPG and",,"Coke"," " "Code(a)","Subsector and Industry","Total","Fuel Oil","Fuel Oil(b)","Natural Gas(c)","NGL(d)","Coal","and Breeze","Other(e)"

  11. Released: July 2009

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

    1 Relative Standard Errors for Table 1.1, 2006;" " Unit: Percents." " "," " " "," "," ",," "," ",," ",,," ","Shipments" "NAICS"," ",,"Net","Residual","Distillate",,"LPG and"," ","Coke and"," ","of Energy Sources" "Code(a)","Subsector and

  12. Released: July 2009

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

    2 Relative Standard Errors for Table 2.2, 2006;" " Unit: Percents." " "," "," "," "," "," "," "," "," "," " " "," " "NAICS"," "," ","Residual","Distillate",,"LPG and",,"Coke"," " "Code(a)","Subsector and Industry","Total","Fuel Oil","Fuel

  13. Released: July 2009

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

    2 Relative Standard Errors for Table 3.2, 2006;" " Unit: Percents." " "," " "NAICS"," "," ","Net","Residual","Distillate",,"LPG and",,"Coke"," " "Code(a)","Subsector and Industry","Total","Electricity(b)","Fuel Oil","Fuel Oil(c)","Natural Gas(d)","NGL(e)","Coal","and

  14. Released: July 2009

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

    2 Relative Standard Errors for Table 4.2, 2006;" " Unit: Percents." " "," "," ",," "," "," "," "," "," "," "," " " "," " "NAICS"," "," ",,"Residual","Distillate",,"LPG and",,"Coke"," " "Code(a)","Subsector and

  15. Released: June 2010

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

    1 Relative Standard Errors for Table 10.11;" " Unit: Percents." ,,"Coal(b)",,,"Alternative Energy Sources(c)" "NAICS"," ","Total"," ","Not","Electricity","Natural","Distillate","Residual" "Code(a)","Subsector and Industry","Consumed(d)","Switchable","Switchable","Receipts(e)","Gas","Fuel

  16. Cybersecurity Capability Maturity Model (February 2014) | Department of

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

    Energy (February 2014) Cybersecurity Capability Maturity Model (February 2014) The Cybersecurity Capability Maturity Model (C2M2) was derived from the Electricity Subsector Cybersecurity Capability Maturity Model (ES-C2M2) Version 1.1 by removing sector-specific references and terminology. The ES-C2M2 was developed in support of a White House initiative led by the Department of Energy (DOE), in partnership with the Department of Homeland Security (DHS), and in collaboration with private- and

  17. Bandwidth Study on Energy Use and Potential Energy Saving Opportunities in U.S. Chemical Manufacturing

    SciTech Connect (OSTI)

    Sabine Brueske, Caroline Kramer, Aaron Fisher

    2015-06-01

    Energy bandwidth studies of U.S. manufacturing sectors can serve as foundational references in framing the range (or bandwidth) of potential energy savings opportunities. This bandwidth study examines energy consumption and potential energy savings opportunities in U.S. chemical manufacturing. The study relies on multiple sources to estimate the energy used in the production of 74 individual chemicals, representing 57% of sector-wide energy consumption. Energy savings opportunities for individual chemicals and for 15 subsectors of chemicals manufacturing are based on technologies currently in use or under development; these potential savings are then extrapolated to estimate sector-wide energy savings opportunity.

  18. Class of supersymmetric solitons with naked singularities

    SciTech Connect (OSTI)

    Cvetic, M.; Youm, D. )

    1995-02-15

    We study vacuum domain walls in a class of four-dimensional [ital N]=1 supergravity theories where along with the matter field, forming the wall, there is more than one dilaton,'' each respecting SU(1,1) symmetry in their subsector. We find [ital supersymmetric] (planar, static) walls, interpolating between a Minkowski vacuum and a new class of supersymmetric vacua which have a naked (planar) singularity. Although such walls correspond to idealized configurations, i.e., they correspond to planar configurations of infinite extent, they provide the first example of supersymmetric classical solitons with naked singularities.

  19. Energy Efficiency Services Sector: Workforce Education and Training Needs

    SciTech Connect (OSTI)

    Goldman, Charles A.; Peters, Jane S.; Albers, Nathaniel; Stuart, Elizabeth; Fuller, Merrian C.

    2010-03-19

    This report provides a baseline assessment of the current state of energy efficiency-related education and training programs and analyzes training and education needs to support expected growth in the energy efficiency services workforce. In the last year, there has been a significant increase in funding for 'green job' training and workforce development (including energy efficiency), through the American Recovery and Reinvestment Act (ARRA). Key segments of the energy efficiency services sector (EESS) have experienced significant growth during the past several years, and this growth is projected to continue and accelerate over the next decade. In a companion study (Goldman et al. 2009), our research team estimated that the EESS will increase two- to four-fold by 2020, to 220,000 person-years of employment (PYE) (low-growth scenario) or up to 380,000 PYE (high-growth scenario), which may represent as many as 1.3 million individuals. In assessing energy efficiency workforce education and training needs, we focus on energy-efficiency services-related jobs that are required to improve the efficiency of residential and nonresidential buildings. Figure ES-1 shows the market value chain for the EESS, sub-sectors included in this study, as well as the types of market players and specific occupations. Our assessment does not include the manufacturing, wholesale, and retail distribution subsectors, or energy efficiency-focused operations and maintenance performed by facility managers.

  20. 2008 Industrial Technologies Market Report, May 2009

    SciTech Connect (OSTI)

    Energetics; DOE

    2009-07-01

    The industrial sector is a critical component of the U.S. economy, providing an array of consumer, transportation, and national defense-related goods we rely on every day. Unlike many other economic sectors, however, the industrial sector must compete globally for raw materials, production, and sales. Though our homes, stores, hospitals, and vehicles are located within our borders, elements of our goods-producing industries could potentially be moved offshore. Keeping U.S. industry competitive is essential to maintaining and growing the U.S. economy. This report begins with an overview of trends in industrial sector energy use. The next section of the report focuses on some of the largest and most energy-intensive industrial subsectors. The report also highlights several emerging technologies that could transform key segments of industry. Finally, the report presents policies, incentives, and drivers that can influence the competitiveness of U.S. industrial firms.

  1. Constructing vulnerabilty and protective measures indices for the enhanced critical infrastructure protection program.

    SciTech Connect (OSTI)

    Fisher, R. E.; Buehring, W. A.; Whitfield, R. G.; Bassett, G. W.; Dickinson, D. C.; Haffenden, R. A.; Klett, M. S.; Lawlor, M. A.; Decision and Information Sciences; LANL

    2009-10-14

    The US Department of Homeland Security (DHS) has directed its Protective Security Advisors (PSAs) to form partnerships with the owners and operators of assets most essential to the Nation's well being - a subclass of critical infrastructure and key resources (CIKR) - and to conduct site visits for these and other high-risk assets as part of the Enhanced Critical Infrastructure Protection (ECIP) Program. During each such visit, the PSA documents information about the facility's current CIKR protection posture and overall security awareness. The primary goals for ECIP site visits (DHS 2009) are to: (1) inform facility owners and operators of the importance of their facilities as an identified high-priority CIKR and the need to be vigilant in light of the ever-present threat of terrorism; (2) identify protective measures currently in place at these facilities, provide comparisons of CIKR protection postures across like assets, and track the implementation of new protective measures; and (3) enhance existing relationships among facility owners and operators; DHS; and various Federal, State, local tribal, and territorial partners. PSAs conduct ECIP visits to assess overall site security; educate facility owners and operators about security; help owners and operators identify gaps and potential improvements; and promote communication and information sharing among facility owners and operators, DHS, State governments, and other security partners. Information collected during ECIP visits is used to develop metrics; conduct sector-by-sector and cross-sector vulnerability comparisons; identify security gaps and trends across CIKR sectors and subsectors; establish sector baseline security survey results; and track progress toward improving CIKR security through activities, programs, outreach, and training (Snyder 2009). The data being collected are used in a framework consistent with the National Infrastructure Protection Plan (NIPP) risk criteria (DHS 2009). The NIPP framework incorporates consequence, threat, and vulnerability components and addresses all hazards. The analysis of the vulnerability data needs to be reproducible, support risk analysis, and go beyond protection. It also needs to address important security/vulnerability topics, such as physical security, cyber security, systems analysis, and dependencies and interdependencies. This report provides an overview of the approach being developed to estimate vulnerability and provide vulnerability comparisons for sectors and subsectors. the information will be used to assist DHS in analyzing existing protective measures and vulnerability at facilities, to identify potential ways to reduce vulnerabilities, and to assist in preparing sector risk estimates. The owner/operator receives an analysis of the data collected for a specific asset, showing a comparison between the facility's protection posture/vulnerability index and those of DHS sector/subsector sites visited. This comparison gives the owner/operator an indication of the asset's security strengths and weaknesses that may be contributing factors to its vulnerability and protection posture. The information provided to the owner/operator shows how the asset compares to other similar assets within the asset's sector or subsector. A 'dashboard' display is used to illustrate the results in a convenient format. The dashboard allows the owner/operator to analyze the implementation of additional protective measures and to illustrate how such actions would impact the asset's Protective Measures Index (PMI) or Vulnerability Index (VI).

  2. Exploring the Potential Business Case for Synergies Between Natural Gas and Renewable Energy

    SciTech Connect (OSTI)

    Cochran, J.; Zinaman, O.; Logan, J.; Arent, D.

    2014-02-01

    Natural gas and renewable energy each contribute to economic growth, energy independence, and carbon mitigation, sometimes independently and sometimes collectively. Often, natural gas and renewables are considered competitors in markets, such as those for bulk electricity. This paper attempts to address the question, 'Given near- and long-term needs for abundant, cleaner energy sources and decarbonization, how can more compelling business models be created so that these two domestic forms of energy work in greater concert?' This paper explores revenue opportunities that emerge from systems-level perspectives in 'bulk energy' (large-scale electricity and natural gas production, transmission, and trade) and four 'distribution edge' subsectors: industrial, residential, commercial, and transportation end uses.

  3. Public Interest Energy Research (PIER) Program. Final Project Report. California Energy Balance Update and Decomposition Analysis for the Industry and Building Sectors

    SciTech Connect (OSTI)

    de la Rue du Can, Stephane; Hasanbeigi, Ali; Sathaye, Jayant

    2010-12-01

    This report on the California Energy Balance version 2 (CALEB v2) database documents the latest update and improvements to CALEB version 1 (CALEB v1) and provides a complete picture of how energy is supplied and consumed in the State of California. The CALEB research team at Lawrence Berkeley National Laboratory (LBNL) performed the research and analysis described in this report. CALEB manages highly disaggregated data on energy supply, transformation, and end-use consumption for about 40 different energy commodities, from 1990 to 2008. This report describes in detail California's energy use from supply through end-use consumption as well as the data sources used. The report also analyzes trends in energy demand for the "Manufacturing" and "Building" sectors. Decomposition analysis of energy consumption combined with measures of the activity driving that consumption quantifies the effects of factors that shape energy consumption trends. The study finds that a decrease in energy intensity has had a very significant impact on reducing energy demand over the past 20 years. The largest impact can be observed in the industry sector where energy demand would have had increased by 358 trillion British thermal units (TBtu) if subsectoral energy intensities had remained at 1997 levels. Instead, energy demand actually decreased by 70 TBtu. In the "Building" sector, combined results from the "Service" and "Residential" subsectors suggest that energy demand would have increased by 264 TBtu (121 TBtu in the "Services" sector and 143 TBtu in the "Residential" sector) during the same period, 1997 to 2008. However, energy demand increased at a lesser rate, by only 162 TBtu (92 TBtu in the "Services" sector and 70 TBtu in the "Residential" sector). These energy intensity reductions can be indicative of energyefficiency improvements during the past 10 years. The research presented in this report provides a basis for developing an energy-efficiency performance index to measure progress over time in the State of California.

  4. How Can China Lighten Up? Urbanization, Industrialization and Energy Demand Scenarios

    SciTech Connect (OSTI)

    Aden, Nathaniel T.; Zheng, Nina; Fridley, David G.

    2009-07-01

    Urbanization has re-shaped China's economy, society, and energy system. Between 1990 and 2007 China added 290 million new urban residents, bringing the total urbanization rate to 45%. This population adjustment spurred energy demand for construction of new buildings and infrastructure, as well as additional residential use as rural biomass was replaced with urban commercial energy services. Primary energy demand grew at an average annual rate of 10% between 2000 and 2007. Urbanization's effect on energy demand was compounded by the boom in domestic infrastructure investment, and in the export trade following World Trade Organization (WTO) accession in 2001. Industry energy consumption was most directly affected by this acceleration. Whereas industry comprised 32% of 2007 U.S. energy use, it accounted for 75% of China's 2007 energy consumption. Five sub-sectors accounted for 78% of China's industry energy use in 2007: iron and steel, energy extraction and processing, chemicals, cement, and non-ferrous metals. Ferrous metals alone accounted for 25% of industry and 18% of total primary energy use. The rapid growth of heavy industry has led China to become by far the world's largest producer of steel, cement, aluminum, and other energy-intensive commodities. However, the energy efficiency of heavy industrial production continues to lag world best practice levels. This study uses scenario analysis to quantify the impact of urbanization and trade on industrial and residential energy consumption from 2000 to 2025. The BAU scenario assumed 67% urbanization, frozen export amounts of heavy industrial products, and achievement of world best practices by 2025. The China Lightens Up (CLU) scenario assumed 55% urbanization, zero net exports of heavy industrial products, and more aggressive efficiency improvements by 2025. The five dominant industry sub-sectors were modeled in both scenarios using a LEAP energy end-use accounting model. The results of this study show that a CLU-style development path would avoid 430 million tonnes coal-equivalent energy use by 2025. More than 60% of these energy savings would come from reduced activity and production levels. In carbon terms, this would amount to more than a billion-tonne reduction of energy-related carbon emissions compared with the BAU scenario in 2025, though the absolute level of emissions rises in both scenarios. Aside from the energy and carbon savings related to CLU scenario development, this study showed impending saturation effects in commercial construction, urban appliance ownership, and fertilizer application. The implication of these findings is that urbanization will have a direct impact on future energy use and emissions - policies to guide urban growth can play a central role in China's efforts to mitigate emissions growth.

  5. New trends in industrial energy efficiency in the Mexico iron and steel industry

    SciTech Connect (OSTI)

    Ozawa, Leticia; Martin, Nathan; Worrell, Ernst; Price, Lynn; Sheinbaum, Claudia

    1999-07-31

    Energy use in the Mexican industrial sector experienced important changes in the last decade related to changes in the Mexican economy. In previous studies, we have shown that a real change in energy-intensity was the most important factor in the overall decline of energy use and CO2 emissions in the Mexican industrial sector. Real changes in energy intensity were explained by different factors, depending on the industrial sub-sector. In this paper, we analyze the factors that influenced energy use in the Mexican iron and steel industry, the largest energy consuming and energy-intensive industry in the country. To understand the trends in this industry we used a decomposition analysis based on physical indicators to decompose the changes in intra-sectoral structural changes and efficiency improvements. Also, we use a structure-efficiency analysis for international comparisons, considering industrial structure and the best available technology. In 1995, Mexican iron and steel industry consumed 17.7 percent of the industrial energy consumption. Between 1970 and 1995, the steel production has increased with an annual growth rate of 4.7 percent, while the specific energy consumption (SEC) has decreased from 28.4 to 23.8 GJ/tonne of crude steel. This reduction was due to energy efficiency improvements (disappearance of the open hearth production, increase of the share of the continuous casting) and to structural changes as well (increase of the share of scrap input in the steelmaking).

  6. Current and future industrial energy service characterizations

    SciTech Connect (OSTI)

    Krawiec, F.; Thomas, T.; Jackson, F.; Limaye, D.R.; Isser, S.; Karnofsky, K.; Davis, T.D.

    1980-10-01

    Current and future energy demands, end uses, and cost used to characterize typical applications and resultant services in the industrial sector of the United States and 15 selected states are examined. A review and evaluation of existing industrial energy data bases was undertaken to assess their potential for supporting SERI research on: (1) market suitability analysis, (2) market development, (3) end-use matching, (3) industrial applications case studies, and (4) identification of cost and performance goals for solar systems and typical information requirements for industrial energy end use. In reviewing existing industrial energy data bases, the level of detail, disaggregation, and primary sources of information were examined. The focus was on fuels and electric energy used for heat and power purchased by the manufacturing subsector and listed by 2-, 3-, and 4-digit SIC, primary fuel, and end use. Projections of state level energy prices to 1990 are developed using the energy intensity approach. The effects of federal and state industrial energy conservation programs on future industrial sector demands were assessed. Future end-use energy requirements were developed for each 4-digit SIC industry and were grouped as follows: (1) hot water, (2) steam (212 to 300/sup 0/F, each 100/sup 0/F interval from 300 to 1000/sup 0/F, and greater than 1000/sup 0/F), and (3) hot air (100/sup 0/F intervals). Volume I details the activities performed in this effort.

  7. Industrial sector energy conservation programs in the People`s Republic of China during the seventh five-year plan (1986--1990)

    SciTech Connect (OSTI)

    Liu Zhiping; Sinton, J.E.; Yang Fuqiang; Levine, M.D.; Ting, M.K.

    1994-09-01

    The impetus at the national level to invest in energy conservation is quite strong and has long been reflected not only in official pronouncements, but also in the investments and organizational activities of the Chinese government. In the early 1980s the central government began a program of direct investments in industrial energy conservation that continues to the present. In addition, concurrently established governmental and quasi-governmental agencies have pursued conservation through administrative and educational measures. In Section 2 of this paper the authors outline the policies and institutions that supported China`s program of energy conservation investments in the Sixth and Seventh Five-Year Plans (FYPs) (1981--1985 and 1986--1990). In Section 3 they describe examples of the types of conservation projects pursued in four industrial subsectors: ferrous metals manufacturing; non-ferrous metals mining and manufacturing; chemicals manufacturing; and building materials manufacturing. Section 4 presents a simple methodology for comparing the costs of energy conservation to those of energy supply. Further discussion points out the applicability and limitations of this methodology to State Planning Commission published statistical material on the overall results of energy conservation investments. Though problematic, such analysis indicates that energy conservation investments were probably substantially cheaper than investments in equivalent energy supply would have been. They end with a discussion of some of the difficulties encountered in carrying out the conservation investment programs.

  8. Energy use and CO2 emissions of China’s industrial sector from a global perspective

    SciTech Connect (OSTI)

    Zhou, Sheng; Kyle, G. Page; Yu, Sha; Clarke, Leon E.; Eom, Jiyong; Luckow, Patrick W.; Chaturvedi, Vaibhav; Zhang, Xiliang; Edmonds, James A.

    2013-07-10

    The industrial sector has accounted for more than 50% of China’s final energy consumption in the past 30 years. Understanding the future emissions and emissions mitigation opportunities depends on proper characterization of the present-day industrial energy use, as well as industrial demand drivers and technological opportunities in the future. Traditionally, however, integrated assessment research has handled the industrial sector of China in a highly aggregate form. In this study, we develop a technologically detailed, service-oriented representation of 11 industrial subsectors in China, and analyze a suite of scenarios of future industrial demand growth. We find that, due to anticipated saturation of China’s per-capita demands of basic industrial goods, industrial energy demand and CO2 emissions approach a plateau between 2030 and 2040, then decrease gradually. Still, without emissions mitigation policies, the industrial sector remains heavily reliant on coal, and therefore emissions-intensive. With carbon prices, we observe some degree of industrial sector electrification, deployment of CCS at large industrial point sources of CO2 emissions at low carbon prices, an increase in the share of CHP systems at industrial facilities. These technological responses amount to reductions of industrial emissions (including indirect emission from electricity) are of 24% in 2050 and 66% in 2095.

  9. Analysis of Long-range Clean Energy Investment Scenarios forEritrea, East Africa

    SciTech Connect (OSTI)

    Van Buskirk, Robert D.

    2004-05-07

    We discuss energy efficiency and renewable energy investments in Eritrea from the strategic long-term economic perspective of meeting Eritrea's sustainable development goals and reducing greenhouse gas emissions. Energy efficiency and renewable energy are potentially important contributors to national productive capital accumulation, enhancement of the environment, expansion of energy services, increases in household standard of living, and improvements in health. In this study we develop a spreadsheet model for calculating some of the national benefits and costs of different levels of investment in energy efficiency and renewable energy. We then present the results of the model in terms of investment demand and investment scenario curves. These curves express the contribution that efficiency and renewable energy projects can make in terms of reduced energy sector operating expenses, and reduced carbon emissions. We provide demand and supply curves that show the rate of return, the cost of carbon emissions reductions vs. supply, and the evolution of the marginal carbon emissions per dollar of GDP for different investment levels and different fuel-type subsectors.

  10. Profile of the chemicals industry in California: Californiaindustries of the future program

    SciTech Connect (OSTI)

    Galitsky, Christina; Worrell, Ernst

    2004-06-01

    The U.S. Department of Energy (DOE) Office of Industrial Technologies (OIT) established the Industries of the Future (IOF) program to increase energy efficiency, reduce waste production and to improve competitiveness, currently focusing on nine sectors. The IOF is a partnership strategy involving industry, the research community and the government, working together to identify technology needs, promote industrial partnerships and implement joint measures with all partners involved. The State Industries of the Future (SIOF) program delivers the accomplishments of the national Industries of the Future strategy to the local level, to expand the technology opportunities to a larger number of partners and reach smaller businesses and manufacturers that were not initially involved in the IOF effort. The state programs bring together industry, academia, and state agencies to address the important issues confronting industry in the state. These public-private coalitions facilitate industry solutions locally and enhance economic development. California has started a State Industries of the Future effort, in collaboration with the U.S. Department of Energy. The California Energy Commission (CEC) is leading the SIOF program in California, as part of many other programs to improve the energy efficiency and performance of industries in California. The California State IOF program aims to build a network of participants from industry, academia and government in four selected industrial sectors as a basis for the development of a strategic partnership for industrial energy efficient technology in the state. In California the IOF effort focuses petroleum refining, chemical processing, food processing and electronics. As part of this effort, the SIOF program will develop roadmaps for technology development for the selected sectors. On the basis of the roadmap, the program will develop successful projects with co-funding from state and federal government, and promote industry-specific energy-efficiency. An important element of the SIOF-program is the preparation of R&D roadmaps for each of the selected industries. The roadmap will help to identify priority needs for the participating industries to meet their energy challenges. The roadmap effort builds on the roadmaps developed by DOE, and on the conditions specific for the industry in California. Key to the successful preparation of a roadmap in the selected industries is the development of a profile of the industries. The profile provides a basis for the participants in the roadmap-effort, especially as the structure of the industries in California can be different than in the nation. The sector profiles describe the current economic and energy situation of these industries in California, the processes and energy uses, and the potential future developments in each industry. The profiles are an integral part of the roadmap, to help working group partners to evaluate the industry's R&D needs for their industry in California. In this report, we focus on the chemicals industry. The industry is an important economic factor in the state, providing over 82,300 jobs directly, and more in indirect employment. Value of shipments in 2001 was just under $25.7 Billion, or 6% of all manufacturing in California. There are over 1,500 chemical plants in California, of which 52% are pharmaceutical companies. Many companies operate chemical plants in California. The industry consumes 8% of the electricity and 5% of the natural gas in California. In this report, we start with a description of the chemical industry in the United States and California. This is followed by a discussion of the energy consumption and energy intensity of the Californian chemical industry. Chapter 3 focuses on the main sub-sectors. For each of the sub-sectors a general process description is provided in Chapter 4. Based on this analysis, in Chapter 5, we discuss potential technology developments that can contribute to further improving the energy efficiency in chemical plants, with a focus on the situation in California.

  11. Constructing a resilience index for the Enhanced Critical Infrastructure Protection Program

    SciTech Connect (OSTI)

    Fisher, R. E.; Bassett, G. W.; Buehring, W. A.; Collins, M. J.; Dickinson, D. C.; Eaton, L. K.; Haffenden, R. A.; Hussar, N. E.; Klett, M. S.; Lawlor, M. A.; Millier, D. J.; Petit, F. D.; Peyton, S. M.; Wallace, K. E.; Whitfield, R. G.; Peerenboom, J P

    2010-10-14

    Following recommendations made in Homeland Security Presidential Directive 7, which established a national policy for the identification and increased protection of critical infrastructure and key resources (CIKR) by Federal departments and agencies, the U.S. Department of Homeland Security (DHS) in 2006 developed the Enhanced Critical Infrastructure Protection (ECIP) program. The ECIP program aimed to provide a closer partnership with state, regional, territorial, local, and tribal authorities in fulfilling the national objective to improve CIKR protection. The program was specifically designed to identify protective measures currently in place in CIKR and to inform facility owners/operators of the benefits of new protective measures. The ECIP program also sought to enhance existing relationships between DHS and owners/operators of CIKR and to build relationships where none existed (DHS 2008; DHS 2009). In 2009, DHS and its protective security advisors (PSAs) began assessing CIKR assets using the ECIP program and ultimately produced individual protective measure and vulnerability values through the protective measure and vulnerability indices (PMI/VI). The PMI/VI assess the protective measures posture of individual facilities at their 'weakest link,' allowing for a detailed analysis of the most vulnerable aspects of the facilities (Schneier 2003), while maintaining the ability to produce an overall protective measures picture. The PMI has six main components (physical security, security management, security force, information sharing, protective measures assessments, and dependencies) and focuses on actions taken by a facility to prevent or deter the occurrence of an incident (Argonne National Laboratory 2009). As CIKR continue to be assessed using the PMI/VI and owners/operators better understand how they can prevent or deter incidents, academic research, practitioner emphasis, and public policy formation have increasingly focused on resilience as a necessary component of the risk management framework and infrastructure protection. This shift in focus toward resilience complements the analysis of protective measures by taking into account the three other phases of risk management: mitigation, response, and recovery (Figure 1). Thus, the addition of a robust resilience index (RI) to the established PMI/VI provides vital information to owners/operators throughout the risk management process. Combining a pre-incident focus with a better understanding of resilience, as well as potential consequences from damaged CIKR, allows owners/operators to better understand different ways to decrease risk by (1) increasing physical security measures to prevent an incident, (2) supplementing redundancy to mitigate the effects of an incident, and (3) enhancing emergency action and business continuity planning to increase the effectiveness of recovery procedures. Information provided by the RI methodology is also used by facility owners/operators to better understand how their facilities compare to similar sector/subsector sites and to help them make risk-based decisions. This report provides an overview of the RI methodology developed to estimate resilience and provide resilience comparisons for sectors and subsectors. The information will be used to (1) assist DHS in analyzing existing response and recovery methods and programs at facilities and (2) identify potential ways to increase resilience. The RI methodology is based on principles of Appreciative Inquiry, which is 'the coevolutionary search for the best in people, their organizations, and the relevant world around them' (Cooperrider et al. 2005). Appreciative Inquiry identifies the best of 'what is' and helps to envision 'what might be.' The ECIP program and the RI represent a new model (using Appreciative Inquiry principles) for information sharing between government and industry (Fisher and Petit 2010). A 'dashboard' display, which provides an interactive tool - rather than a static report, presents the results of the RI in a convenient format. Additional resilience measures c

  12. Analysis of energy use in building services of the industrial sector in California: A literature review and a preliminary characterization

    SciTech Connect (OSTI)

    Akbari, H.; Borgers, T.; Gadgil, A.; Sezgen, O.

    1991-04-01

    Energy use patterns in many of California's fastest-growing industries are not typical of those in the mix of industries elsewhere in the US. Many California firms operate small and medium-sized facilities, often in buildings used simultaneously or interchangeably for commercial (office, retail, warehouse) and industrial activities. In these industrial subsectors, the energy required for building services'' to provide occupant comfort and necessities (lighting, HVAC, office equipment, computers, etc.) may be at least as important as the more familiar process energy requirements -- especially for electricity and on-peak demand. In this report, published or unpublished information on energy use for building services in the industrial sector have been compiled and analyzed. Seven different sources of information and data relevant to California have been identified. Most of these are studies and/or projects sponsored by the Department of Energy, the California Energy Commission, and local utilities. The objectives of these studies were diverse: most focused on industrial energy use in general, and, in one case, the objective was to analyze energy use in commercial buildings. Only one of these studies focused directly on non-process energy use in industrial buildings. Our analysis of Northern California data for five selected industries shows that the contribution of total electricity consumption for lighting ranges from 9.5% in frozen fruits to 29.1% in instruments; for air-conditioning, it ranges from nonexistent in frozen fruits to 35% in instrument manufacturing. None of the five industries selected had significant electrical space heating. Gas space heating ranges from 5% in motor vehicles facilities to more than 58% in the instrument manufacturing industry. 15 refs., 15 figs., 9 tabs.

  13. Assessing the Control Systems Capacity for Demand Response in California Industries

    SciTech Connect (OSTI)

    Ghatikar, Girish; McKane, Aimee; Goli, Sasank; Therkelsen, Peter; Olsen, Daniel

    2012-01-18

    California's electricity markets are moving toward dynamic pricing models, such as real-time pricing, within the next few years, which could have a significant impact on an industrial facility's cost of energy use during the times of peak use. Adequate controls and automated systems that provide industrial facility managers real-time energy use and cost information are necessary for successful implementation of a comprehensive electricity strategy; however, little is known about the current control capacity of California industries. To address this gap, Lawrence Berkeley National Laboratory, in close collaboration with California industrial trade associations, conducted a survey to determine the current state of controls technologies in California industries. This,study identifies sectors that have the technical capability to implement Demand Response (DR) and Automated Demand Response (Auto-DR). In an effort to assist policy makers and industry in meeting the challenges of real-time pricing, facility operational and organizational factors were taken into consideration to generate recommendations on which sectors Demand Response efforts should be focused. Analysis of the survey responses showed that while the vast majority of industrial facilities have semi- or fully automated control systems, participation in Demand Response programs is still low due to perceived barriers. The results also showed that the facilities that use continuous processes are good Demand Response candidates. When comparing facilities participating in Demand Response to those not participating, several similarities and differences emerged. Demand Response-participating facilities and non-participating facilities had similar timings of peak energy use, production processes, and participation in energy audits. Though the survey sample was smaller than anticipated, the results seemed to support our preliminary assumptions. Demonstrations of Auto-Demand Response in industrial facilities with good control capabilities are needed to dispel perceived barriers to participation and to investigate industrial subsectors suggested of having inherent Demand Response potential.

  14. SCENARIOS FOR MEETING CALIFORNIA'S 2050 CLIMATE GOALS California's Carbon Challenge Phase II Volume I: Non-Electricity Sectors and Overall Scenario Results

    SciTech Connect (OSTI)

    Wei, Max; Greenblatt, Jeffrey; Donovan, Sally; Nelson, James; Mileva, Ana; Johnston, Josiah; Kammen, Daniel

    2014-06-01

    This study provides an updated analysis of long-term energy system scenarios for California consistent with the State meeting its 2050 climate goal, including detailed analysis and assessment of electricity system build-out, operation, and costs across the Western Electricity Coordinating Council (WECC) region. Four key elements are found to be critical for the State to achieve its 2050 goal of 80 percent greenhouse (GHG) reductions from the 1990 level: aggressive energy efficiency; clean electricity; widespread electrification of passenger vehicles, building heating, and industry heating; and large-scale production of low-carbon footprint biofuels to largely replace petroleum-based liquid fuels. The approach taken here is that technically achievable energy efficiency measures are assumed to be achieved by 2050 and aggregated with the other key elements mentioned above to estimate resultant emissions in 2050. The energy and non-energy sectors are each assumed to have the objective of meeting an 80 percent reduction from their respective 1990 GHG levels for the purposes of analysis. A different partitioning of energy and non-energy sector GHG greenhouse reductions is allowed if emission reductions in one sector are more economic or technically achievable than in the other. Similarly, within the energy or non-energy sectors, greater or less than 80 percent reduction from 1990 is allowed for sub-sectors within the energy or non-energy sectors as long as the overall target is achieved. Overall emissions for the key economy-wide scenarios are considered in this report. All scenarios are compliant or nearly compliant with the 2050 goal. This finding suggests that multiple technical pathways exist to achieve the target with aggressive policy support and continued technology development of largely existing technologies.

  15. Energy-Efficiency Improvement Opportunities for the Textile Industry

    SciTech Connect (OSTI)

    China Energy Group; Hasanbeigi, Ali

    2010-09-29

    The textile industry is one of the most complicated manufacturing industries because it is a fragmented and heterogeneous sector dominated by small and medium enterprises (SMEs). Energy is one of the main cost factors in the textile industry. Especially in times of high energy price volatility, improving energy efficiency should be a primary concern for textile plants. There are various energy-efficiency opportunities that exist in every textile plant, many of which are cost-effective. However, even cost-effective options often are not implemented in textile plants mostly because of limited information on how to implement energy-efficiency measures, especially given the fact that a majority of textile plants are categorized as SMEs and hence they have limited resources to acquire this information. Know-how on energy-efficiency technologies and practices should, therefore, be prepared and disseminated to textile plants. This guidebook provides information on energy-efficiency technologies and measures applicable to the textile industry. The guidebook includes case studies from textile plants around the world and includes energy savings and cost information when available. First, the guidebook gives a brief overview of the textile industry around the world, with an explanation of major textile processes. An analysis of the type and the share of energy used in different textile processes is also included in the guidebook. Subsequently, energy-efficiency improvement opportunities available within some of the major textile sub-sectors are given with a brief explanation of each measure. The conclusion includes a short section dedicated to highlighting a few emerging technologies in the textile industry as well as the potential for the use of renewable energy in the textile industry.

  16. Chapter 9, Land and Bioenergy in Scientific Committee on Problems of the Environment (SCOPE), Bioenergy & Sustainability: bridging the gaps.

    SciTech Connect (OSTI)

    Woods J, Lynd LR; Laser, M; Batistella M, De Castro D; Kline, Keith L; Faaij, Andre

    2015-01-01

    In this chapter we address the questions of whether and how enough biomass could be produced to make a material contribution to global energy supply on a scale and timeline that is consistent with prominent low carbon energy scenarios. We assess whether bioenergy provision necessarily conflicts with priority ecosystem services including food security for the world s poor and vulnerable populations. In order to evaluate the potential land demand for bioenergy, we developed a set of three illustrative scenarios using specified growth rates for each bioenergy sub-sector. In these illustrative scenarios, bioenergy (traditional and modern) increases from 62 EJ/yr in 2010 to 100, 150 and 200 EJ/yr in 2050. Traditional bioenergy grows slowly, increasing by between 0.75% and 1% per year, from 40 EJ/yr in 2010 to 50 or 60 EJ/ yr in 2050, continuing as the dominant form of bioenergy until at least 2020. Across the three scenarios, total land demand is estimated to increase by between 52 and 200 Mha which can be compared with a range of potential land availability estimates from the literature of between 240 million hectares to over 1 billion hectares. Biomass feedstocks arise from combinations of residues and wastes, energy cropping and increased efficiency in supply chains for energy, food and materials. In addition, biomass has the unique capability of providing solid, liquid and gaseous forms of modern energy carriers that can be transformed into analogues to existing fuels. Because photosynthesis fixes carbon dioxide from the atmosphere, biomass supply chains can be configured to store at least some of the fixed carbon in forms or ways that it will not be reemitted to the atmosphere for considerable periods of time, so-called negative emissions pathways. These attributes provide opportunities for bioenergy policies to promote longterm and sustainable options for the supply of energy for the foreseeable future.

  17. Inflation in maximal gauged supergravities

    SciTech Connect (OSTI)

    Kodama, Hideo; Nozawa, Masato

    2015-05-18

    We discuss the dynamics of multiple scalar fields and the possibility of realistic inflation in the maximal gauged supergravity. In this paper, we address this problem in the framework of recently discovered 1-parameter deformation of SO(4,4) and SO(5,3) dyonic gaugings, for which the base point of the scalar manifold corresponds to an unstable de Sitter critical point. In the gauge-field frame where the embedding tensor takes the value in the sum of the 36 and 36’ representations of SL(8), we present a scheme that allows us to derive an analytic expression for the scalar potential. With the help of this formalism, we derive the full potential and gauge coupling functions in analytic forms for the SO(3)×SO(3)-invariant subsectors of SO(4,4) and SO(5,3) gaugings, and argue that there exist no new critical points in addition to those discovered so far. For the SO(4,4) gauging, we also study the behavior of 6-dimensional scalar fields in this sector near the Dall’Agata-Inverso de Sitter critical point at which the negative eigenvalue of the scalar mass square with the largest modulus goes to zero as the deformation parameter s approaches a critical value s{sub c}. We find that when the deformation parameter s is taken sufficiently close to the critical value, inflation lasts more than 60 e-folds even if the initial point of the inflaton allows an O(0.1) deviation in Planck units from the Dall’Agata-Inverso critical point. It turns out that the spectral index n{sub s} of the curvature perturbation at the time of the 60 e-folding number is always about 0.96 and within the 1σ range n{sub s}=0.9639±0.0047 obtained by Planck, irrespective of the value of the η parameter at the critical saddle point. The tensor-scalar ratio predicted by this model is around 10{sup −3} and is close to the value in the Starobinsky model.

  18. Community Wind: Once Again Pushing the Envelope of Project Finance

    SciTech Connect (OSTI)

    bolinger, Mark A.

    2011-01-18

    In the United States, the 'community wind' sector - loosely defined here as consisting of relatively small utility-scale wind power projects that sell power on the wholesale market and that are developed and owned primarily by local investors - has historically served as a 'test bed' or 'proving grounds' for up-and-coming wind turbine manufacturers that are trying to break into the U.S. wind power market. For example, community wind projects - and primarily those located in the state of Minnesota - have deployed the first U.S. installations of wind turbines from Suzlon (in 2003), DeWind (2008), Americas Wind Energy (2008) and later Emergya Wind Technologies (2010), Goldwind (2009), AAER/Pioneer (2009), Nordic Windpower (2010), Unison (2010), and Alstom (2011). Thus far, one of these turbine manufacturers - Suzlon - has subsequently achieved some success in the broader U.S. wind market as well. Just as it has provided a proving grounds for new turbines, so too has the community wind sector served as a laboratory for experimentation with innovative new financing structures. For example, a variation of one of the most common financing arrangements in the U.S. wind market today - the special allocation partnership flip structure (see Figure 1 in Section 2.1) - was first developed by community wind projects in Minnesota more than a decade ago (and is therefore sometimes referred to as the 'Minnesota flip' model) before being adopted by the broader wind market. More recently, a handful of community wind projects built over the past year have been financed via new and creative structures that push the envelope of wind project finance in the U.S. - in many cases, moving beyond the now-standard partnership flip structures involving strategic tax equity investors. These include: (1) a 4.5 MW project in Maine that combines low-cost government debt with local tax equity, (2) a 25.3 MW project in Minnesota using a sale/leaseback structure, (3) a 10.5 MW project in South Dakota financed by an intrastate offering of both debt and equity, (4) a 6 MW project in Washington state that taps into New Markets Tax Credits using an 'inverted' or 'pass-through' lease structure, and (5) a 9 MW project in Oregon that combines a variety of state and federal incentives and loans with unconventional equity from high-net-worth individuals. In most cases, these are first-of-their-kind structures that could serve as useful examples for other projects - both community and commercial wind alike. This report describes each of these innovative new financing structures in some detail, using a case-study approach. The purpose is twofold: (1) to disseminate useful information on these new financial structures, most of which are widely replicable; and (2) to highlight the recent policy changes - many of them temporary unless extended - that have facilitated this innovation. Although the community wind market is currently only a small sub-sector of the U.S. wind market - as defined here, less than 2% of the overall market at the end of 2009 (Wiser and Bolinger 2010) - its small size belies its relevance to the broader market. As such, the information provided in this report has relevance beyond its direct application to the community wind sector. The next two sections of this report briefly summarize how most community wind projects in the U.S. have been financed historically (i.e., prior to this latest wave of innovation) and describe the recent federal policy changes that have enabled a new wave of financial innovation to occur, respectively. Section 4 contains brief case studies of how each of the five projects mentioned above were financed, noting the financial significance of each. Finally, Section 5 concludes by distilling a number of general observations or pertinent lessons learned from the experiences of these five projects.

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

    SciTech Connect (OSTI)

    Zhou, Nan; McNeil, Michael A.; Fridley, David; Lin, Jiang; Price,Lynn; de la Rue du Can, Stephane; Sathaye, Jayant; Levine, Mark

    2007-10-04

    This report provides a detailed, bottom-up analysis ofenergy consumption in China. It recalibrates official Chinese governmentstatistics by reallocating primary energy into categories more commonlyused in international comparisons. It also provides an analysis of trendsin sectoral energy consumption over the past decades. Finally, itassesses the future outlook for the critical period extending to 2020,based on assumptions of likely patterns of economic activity,availability of energy services, and energy intensities. The followingare some highlights of the study's findings: * A reallocation of sectorenergy consumption from the 2000 official Chinese government statisticsfinds that: * Buildings account for 25 percent of primary energy, insteadof 19 percent * Industry accounts for 61 percent of energy instead of 69percent * Industrial energy made a large and unexpected leap between2000-2005, growing by an astonishing 50 percent in the 3 years between2002 and 2005. * Energy consumption in the iron and steel industry was 40percent higher than predicted * Energy consumption in the cement industrywas 54 percent higher than predicted * Overall energy intensity in theindustrial sector grew between 2000 and 2003. This is largely due tointernal shifts towards the most energy-intensive sub-sectors, an effectwhich more than counterbalances the impact of efficiency increases. *Industry accounted for 63 percent of total primary energy consumption in2005 - it is expected to continue to dominate energy consumption through2020, dropping only to 60 percent by that year. * Even assuming thatgrowth rates in 2005-2020 will return to the levels of 2000-2003,industrial energy will grow from 42 EJ in 2005 to 72 EJ in 2020. * Thepercentage of transport energy used to carry passengers (instead offreight) will double from 37 percent to 52 percent between 2000 to 2020,.Much of this increase is due to private car ownership, which willincrease by a factor of 15 from 5.1 million in 2000 to 77 million in2020. * Residential appliance ownership will show signs of saturation inurban households. The increase in residential energy consumption will belargely driven by urbanization, since rural homes will continue to havelow consumption levels. In urban households, the size of appliances willincrease, but its effect will be moderated by efficiency improvements,partially driven by government standards. * Commercial energy increaseswill be driven both by increases in floor space and by increases inpenetration of major end uses such as heating and cooling. Theseincreases will be moderated somewhat, however, by technology changes,such as increased use of heat pumps. * China's Medium- and Long-TermDevelopment plan drafted by the central government and published in 2004calls for a quadrupling of GDP in the period from 2000-2020 with only adoubling in energy consumption during the same period. A bottom-upanalysis with likely efficiency improvements finds that energyconsumption will likely exceed the goal by 26.12 EJ, or 28 percent.Achievements of these goals will there fore require a more aggressivepolicy of encouraging energy efficiency.

  20. Business Case for Energy Efficiency in Support of Climate Change Mitigation, Economic and Societal Benefits in China

    SciTech Connect (OSTI)

    McNeil, Michael A.; Bojda, Nicholas; Ke, Jing; Qin, Yining; de la Rue du Can, Stephane; Fridley, David; Letschert, Virginie E.; McMahon, James E.

    2011-08-18

    This study seeks to provide policymakers and other stakeholders with actionable information towards a road map for reducing energy consumption cost-effectively. We focus on individual end use equipment types (hereafter referred to as appliance groups) that might be the subject of policies - such as labels, energy performance standards, and incentives - to affect market transformation in the short term, and on high-efficiency technology options that are available today. As the study title suggests, the high efficiency or Business Case scenario is constructed around a model of cost-effective efficiency improvement. Our analysis demonstrates that a significant reduction in energy consumption and emissions is achievable at net negative cost, that is, as a profitable investment for consumers. Net savings are calculated assuming no additional costs to energy consumption such as carbon taxes. Savings relative to the base case as calculated in this way is often referred to as 'economic savings potential'. Chinese energy demand has grown dramatically over the last few decades. While heavy industry still plays a dominant role in greenhouse gas emissions, demand from residential and commercial buildings has also seen rapid growth in percentage terms. In the residential sector this growth is driven by internal migration from the countryside to cities. Meanwhile, income in both urban and rural subsectors allows ownership of major appliances. While residences are still relatively small by U.S. or European standards, nearly all households own a refrigerator, a television and an air conditioner. In the future, ownership rates are not expected to grow as much as in other developing countries, because they are already close to saturation. However, the gradual turnover of equipment in the world's largest consumer market provides a huge opportunity for greenhouse gas mitigation. In addition to residences, commercial floor space has expanded rapidly in recent years, and construction continues at a rapid pace. Growth in this sector means that commercial lighting and HVAC will play an increasingly important role in energy demand in China. The outlook for efficiency improvement in China is encouraging, since the Chinese national and local governments have implemented significant policies to contain energy intensity and announced their intention to continue and accelerate these. In particular, the Chinese appliance standards program, first established in 1989, was significantly strengthened and modernized after the passage of the Energy Conservation Law of 1997. Since then, the program has expanded to encompass over 30 equipment types (including motor vehicles). The current study suggests that, in spite of these efforts, there is significant savings to be captured through wide adoption of technologies already available on the Chinese market. The approach of the study is to assess the impact of short-term actions on long-term impacts. 'Short-term' market transformation is assumed to occur by 2015, while 'long-term' energy demand reduction impacts are assessed in 2030. In the intervening years, most but not all of the equipment studied will turn over completely. Early in 2011, the Chinese government announced a plan to reduce carbon dioxide emissions intensity (per unit GDP) by 16% by 2015 as part of the 12th five year plan. These targets are consistent with longer term goals to reduce emissions intensity 40-45% relative to 2005 levels by 2020. The efforts of the 12th FYP focus on short-term gains to meet the four-year targets, and concentrate mainly in industry. Implementation of cost-effective technologies for all new equipment in the buildings sector thus is largely complementary to the 12th FYP goals, and would provide a mechanism to sustain intensity reductions in the medium and long term. The 15-year time frame is significant for many products, in the sense that delay of implementation postpones economic benefits and mitigation of emissions of carbon dioxide. Such delays would result in putting in place energy-wasting technologies, postponing improvement until the end of their service life, or potentially resulting in expensive investment either in additional energy supplies or in early replacement to achieve future energy or emissions reduction targets.

  1. Control Systems Security Center Comparison Study of Industrial Control System Standards against the Control Systems Protection Framework Cyber-Security Requirements

    SciTech Connect (OSTI)

    Robert P. Evans

    2005-09-01

    Cyber security standards, guidelines, and best practices for control systems are critical requirements that have been delineated and formally recognized by industry and government entities. Cyber security standards provide a common language within the industrial control system community, both national and international, to facilitate understanding of security awareness issues but, ultimately, they are intended to strengthen cyber security for control systems. This study and the preliminary findings outlined in this report are an initial attempt by the Control Systems Security Center (CSSC) Standard Awareness Team to better understand how existing and emerging industry standards, guidelines, and best practices address cyber security for industrial control systems. The Standard Awareness Team comprised subject matter experts in control systems and cyber security technologies and standards from several Department of Energy (DOE) National Laboratories, including Argonne National Laboratory, Idaho National Laboratory, Pacific Northwest National Laboratory, and Sandia National Laboratories. This study was conducted in two parts: a standard identification effort and a comparison analysis effort. During the standard identification effort, the Standard Awareness Team conducted a comprehensive open-source survey of existing control systems security standards, regulations, and guidelines in several of the critical infrastructure (CI) sectors, including the telecommunication, water, chemical, energy (electric power, petroleum and oil, natural gas), and transportation--rail sectors and sub-sectors. During the comparison analysis effort, the team compared the requirements contained in selected, identified, industry standards with the cyber security requirements in ''Cyber Security Protection Framework'', Version 0.9 (hereafter referred to as the ''Framework''). For each of the seven sector/sub-sectors listed above, one standard was selected from the list of standards identified in the identification effort. The requirements in these seven standards were then compared against the requirements given in the Framework. This comparison identified gaps (requirements not covered) in both the individual industry standards and in the Framework. In addition to the sector-specific standards reviewed, the team compared the requirements in the cross-sector Instrumentation, Systems, and Automation Society (ISA) Technical Reports (TR) 99 -1 and -2 to the Framework requirements. The Framework defines a set of security classes separated into families as functional requirements for control system security. Each standard reviewed was compared to this template of requirements to determine if the standard requirements closely or partially matched these Framework requirements. An analysis of each class of requirements pertaining to each standard reviewed can be found in the comparison results section of this report. Refer to Appendix A, ''Synopsis of Comparison Results'', for a complete graphical representation of the study's findings at a glance. Some of the requirements listed in the Framework are covered by many of the standards, while other requirements are addressed by only a few of the standards. In some cases, the scope of the requirements listed in the standard for a particular industry greatly exceeds the requirements given in the Framework. These additional families of requirements, identified by the various standards bodies, could potentially be added to the Framework. These findings are, in part, due to the maturity both of the security standards themselves and of the different industries current focus on security. In addition, there are differences in how communication and control is used in different industries and the consequences of disruptions via security breaches to each particular industry that could affect how security requirements are prioritized. The differences in the requirements listed in the Framework and in the various industry standards are due, in part, to differences in the level and purpose of the standards. While the requirements in the Framework are fairly specific, many of the industry standard requirements are more general in nature. Additionally, the Framework requirements, derived from the ''Common Criteria for Information Technology Security Evaluation'', are component-based, while most of the industry standards are system-based. The findings of this study will allow the CSSC Framework Team and the standards organizations responsible for the reviewed standards to quickly grasp the relationship between their requirements and the Framework, as well as the relationship between their standard and other industry sectors. This will help identify areas for future work in developing improved security standards.