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1

Electricity Subsector Cybersecurity Capability Maturity Model...  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Cybersecurity Electricity Subsector Cybersecurity Capability Maturity Model Electricity Subsector Cybersecurity Capability Maturity Model Electricity Advisory Committee...

2

Electricity Subsector Cybersecurity Capability Maturity Model...  

NLE Websites -- All DOE Office Websites (Extended Search)

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

3

DOE Releases Electricity Subsector Cybersecurity Risk Management...  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

that help them manage their cybersecurity risks more effectively." Feedback provided by industry, vendors, and other electricity subsector stakeholders during two comment periods...

4

Electricity Subsector Cybersecurity Capability Maturity Model...  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

with the Department of Homeland Security (DHS) and involved close collaboration with industry, other Federal agencies, and other stakeholders. Electricity Subsector...

5

ELECTRICITY SUBSECTOR CYBERSECURITY RISK MANAGEMENT PROCESS  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

SUBSECTOR CYBERSECURITY SUBSECTOR 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 tailored for the electricity sector. The primary goal of this guideline is to describe an RMP that is tuned to the specific needs of electricity subsector organizations. The NIST Special Publication (SP) 800-39, Managing Information Security Risk, provides the foundational methodology for this document. The NIST Interagency Report

6

Anti-correlation and subsector structure in financial systems  

E-Print Network (OSTI)

With the random matrix theory, we study the spatial structure of the Chinese stock market, American stock market and global market indices. After taking into account the signs of the components in the eigenvectors of the cross-correlation matrix, we detect the subsector structure of the financial systems. The positive and negative subsectors are anti-correlated each other in the corresponding eigenmode. The subsector structure is strong in the Chinese stock market, while somewhat weaker in the American stock market and global market indices. Characteristics of the subsector structures in different markets are revealed.

Jiang, X F

2012-01-01T23:59:59.000Z

7

DOE Releases Electricity Subsector Cybersecurity Risk Management Process  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Releases Electricity Subsector Cybersecurity Risk Management Releases 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 Better Understand and Assess Cybersecurity Risk WASHINGTON, DC - The Department of Energy's (DOE) Office of Electricity Delivery and Energy Reliability, in collaboration with the National Institute of Standards and Technology (NIST) and the North American Electric Reliability Corporation (NERC), today released guidance to help

8

Electricity Subsector Cybersecurity Capability Maturity Model (May 2012) |  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Subsector Cybersecurity Capability Maturity Model (May Subsector Cybersecurity Capability Maturity Model (May 2012) Electricity Subsector Cybersecurity Capability Maturity Model (May 2012) The Electricity Subsector Cybersecurity Capability Maturity Model (ES-C2M2), 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 cybersecurity efforts into a common tool that can be used consistently across the industry. The Maturity Model was developed as part of a White House initiative led by the Department of Energy in partnership with the Department of Homeland Security (DHS) and involved close collaboration with industry, other Federal agencies, and other stakeholders. Electricity Subsector Cybersecurity Capability Maturity Model (ES-C2M2) -

9

Notice of Publication of Electricity Subsector Cybersecurity Risk  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Publication of Electricity Subsector Cybersecurity Risk Publication of Electricity Subsector Cybersecurity Risk Management Process: Federal Register Notice Volume 77, No. 100 - May 23, 2012 Notice of Publication of Electricity Subsector Cybersecurity Risk Management Process: Federal Register Notice Volume 77, No. 100 - May 23, 2012 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 management process that is targeted to the specific needs of electricity sector organizations. The objective of the guideline is to build upon existing guidance and requirements to develop a flexible risk management process tuned to the diverse missions, equipment, and business needs of the electric power

10

Notice of Publication of Electricity Subsector Cybersecurity Risk  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Notice of Publication of Electricity Subsector Cybersecurity Risk Notice of Publication of Electricity Subsector Cybersecurity Risk Management Process: Federal Register Notice Volume 77, No. 100 - May 23, 2012 Notice of Publication of Electricity Subsector Cybersecurity Risk Management Process: Federal Register Notice Volume 77, No. 100 - May 23, 2012 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 management process that is targeted to the specific needs of electricity sector organizations. The objective of the guideline is to build upon existing guidance and requirements to develop a flexible risk management process tuned to the diverse missions, equipment, and business needs of the electric power

11

Electricity Subsector Cybersecurity Capability Maturity Model (ES-C2M2)  

NLE Websites -- All DOE Office Websites (Extended Search)

Electricity Subsector Cybersecurity Electricity Subsector Cybersecurity Capability Maturity Model (ES-C2M2) Program Electricity Subsector Cybersecurity Capability Maturity Model (ES-C2M2) Program Electricity Subsector Cybersecurity Capability Maturity Model (ES-C2M2) Program The Electricity Subsector Cybersecurity Capability Maturity Model (ES-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 ES-C2M2 program comprises a maturity model, an evaluation tool, and DOE facilitated self-evaluations. The ES-C2M2 maturity model provides a mechanism to evaluate, prioritize, and improve cybersecurity capabilities. The model is a common set of

12

Electricity Subsector Cybersecurity Capability Maturity Model (ES-C2M2) - May 2012.pdf  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

ElEctricity SubSEctor ElEctricity SubSEctor cybErSEcurity capability Maturity MoDEl (ES-c2M2) Version 1.0 31 May 2012 Electricity Subsector Cybersecurity Capability Maturity Model Version 1.0 © 2012 Carnegie Mellon University TABLE OF CONTENTS i Acknowledgments ..................................................................................................................................................iii CAUTIONARY NOTE Intended Scope and Use of This Publication .................................................................................vi 1 Introduction .....................................................................................................................................................1 2 Background .....................................................................................................................................................1

13

Table 3.1 Fuel Consumption, 2010;  

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

1 Fuel Consumption, 2010; 1 Fuel Consumption, 2010; Level: National and Regional Data; Row: NAICS Codes; Column: Energy Sources; Unit: Physical Units or Btu. Coke Net Residual Distillate Natural Gas(d) LPG and Coal and Breeze NAICS Total Electricity(b) Fuel Oil Fuel Oil(c) (billion NGL(e) (million (million Other(f) Code(a) Subsector and Industry (trillion Btu) (million kWh) (million bbl) (million bbl) cu ft) (million bbl) short tons) short tons) (trillion Btu) Total United States 311 Food 1,158 75,407 2 4 563 1 8 * 99 3112 Grain and Oilseed Milling 350 16,479 * * 118 * 6 0 45 311221 Wet Corn Milling 214 7,467 * * 51 * 5 0 25 31131 Sugar Manufacturing 107 1,218 * * 15 * 2 * 36 3114 Fruit and Vegetable Preserving and Specialty Foods 143 9,203

14

Originally Released: July 2009  

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

4.1 Offsite-Produced Fuel Consumption, 2006; 4.1 Offsite-Produced Fuel Consumption, 2006; Level: National and Regional Data; Row: NAICS Codes; Column: Energy Sources; Unit: Physical Units or Btu. Coke Residual Distillate Natural Gas(d) LPG and Coal and Breeze NAICS Total Electricity(b) Fuel Oil Fuel Oil(c) (billion NGL(e) (million (million Other(f) Code(a) Subsector and Industry (trillion Btu) (million kWh) (million bbl) (million bbl) cu ft) (million bbl) short tons) short tons) (trillion Btu) Total United States 311 Food 1,124 73,551 4 3 618 1 7 * 45 3112 Grain and Oilseed Milling 316 15,536 * * 115 * 5 0 28 311221 Wet Corn Milling 179 6,801 * * 51 * 4 0 8 31131 Sugar Manufacturing 67 974 1 * 17 * 1 * 4 3114 Fruit and Vegetable Preserving and Specialty Food 168 9,721

15

Table 4.1 Offsite-Produced Fuel Consumption, 2010;  

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

1 Offsite-Produced Fuel Consumption, 2010; 1 Offsite-Produced Fuel Consumption, 2010; Level: National and Regional Data; Row: NAICS Codes; Column: Energy Sources; Unit: Physical Units or Btu. Coke Residual Distillate Natural Gas(d) LPG and Coal and Breeze NAICS Total Electricity(b) Fuel Oil Fuel Oil(c) (billion NGL(e) (million (million Other(f) Code(a) Subsector and Industry (trillion Btu) (million kWh) (million bbl) (million bbl) cu ft) (million bbl) short tons) short tons) (trillion Btu) Total United States 311 Food 1,113 75,673 2 4 563 1 8 * 54 3112 Grain and Oilseed Milling 346 16,620 * * 118 * 6 0 41 311221 Wet Corn Milling 214 7,481 * * 51 * 5 0 25 31131 Sugar Manufacturing 72 1,264 * * 15 * 2 * * 3114 Fruit and Vegetable Preserving and Specialty Foods 142 9,258 * Q 97

16

Originally Released: July 2009  

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

1 Fuel Consumption, 2006; 1 Fuel Consumption, 2006; Level: National and Regional Data; Row: NAICS Codes; Column: Energy Sources Unit: Physical Units or Btu Coke Net Residual Distillate Natural Gas(d) LPG and Coal and Breeze NAICS Total Electricity(b) Fuel Oil Fuel Oil(c) (billion NGL(e) (million (million Other(f) Code(a) Subsector and Industry (trillion Btu) (million kWh) (million bbl) (million bbl) cu ft) (million bbl) short tons) short tons) (trillion Btu) Total United States 311 Food 1,186 73,440 4 3 618 1 7 * 107 3112 Grain and Oilseed Milling 317 15,464 * * 115 * 5 0 30 311221 Wet Corn Milling 179 6,746 * * 51 * 4 0 9 31131 Sugar Manufacturing 82 968 1 * 17 * 1 * 20 3114 Fruit and Vegetable Preserving and Specialty Food 169 9,708 * * 123 * * 0 4 3115 Dairy Product

17

Level: National and Regional Data; Row: Selected NAICS Codes...  

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

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...

18

Table 3.2 Fuel Consumption, 2010;  

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

2 Fuel Consumption, 2010; 2 Fuel Consumption, 2010; Level: National and Regional Data; Row: NAICS Codes; Column: Energy Sources; Unit: Trillion Btu. 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 Breeze Other(f) Total United States 311 Food 1,158 257 12 22 579 6 182 2 99 3112 Grain and Oilseed Milling 350 56 * 1 121 * 126 0 45 311221 Wet Corn Milling 214 25 * * 53 * 110 0 25 31131 Sugar Manufacturing 107 4 1 1 15 * 49 2 36 3114 Fruit and Vegetable Preserving and Specialty Foods 143 31 1 Q 100 1 2 0 4 3115 Dairy Products 105 33 2 2 66 1 * 0 2 3116 Animal Slaughtering and Processing 212 69 5 3 125 2 Q 0 8 312 Beverage and Tobacco Products 86 29 1 1 38 1 10 0 7 3121 Beverages

19

table2.4_02.xls  

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

4 Number of Establishments by Nonfuel (Feedstock) Use of Combustible Energy, 2002; 4 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 Milling W 0 W 0 0 0 0 W 0.8 31131 Sugar 6 0 W W 0 0 4 W 0.9 311421 Fruit and Vegetable Canning 14 W 6 0 0 0 0 9 5.6 312 Beverage and Tobacco Products 31 W 5 W 0 0 0 15 12.4 3121 Beverages Q W 5 0 0 0 0 12 31.9 3122 Tobacco W 0 0 W 0 0 0 W 0.8

20

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; 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 10,674 532 1,170 413 75 862 3 25 9.9 311221 Wet Corn Milling 47 16 39 4 6 W W 6 0 W 1 31131 Sugar 62 23 51 W 4 13 4 0 W 0 1 311421 Fruit and Vegetable Canning 416 113 337 4 67 49 W 32 W W 5.5 312 Beverage and Tobacco Products

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


21

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; 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 Q 0 15 15.2 311221 Wet Corn Milling 3 W W 0 0 W 0 0 0 0 0.9 31131 Sugar 18 9 9 0 9 0 W 0 0 0 1 311421 Fruit and Vegetable Canning 38 26 30 0 26 W 0 0 0 0 8.1 312 Beverage and Tobacco Products 35 17 Q 0 17 6 W 0 0 0 8

22

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; 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 2,492 570 533 147 225 22 20 21 21.9 311221 Wet Corn Milling 14 W W W W 0 0 0 0 W 1.4 31131 Sugar 31 W W W 0 0 0 W 0 W 1.1 311421 Fruit and Vegetable Canning 229 15 215 11 4 W W 0 0 0 5.3 312 Beverage and Tobacco Products

23

table10.9_02.xls  

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

9 Number of Establishments with Capability to Switch Distillate Fuel Oil to Alternative Energy Sources, 2002; 9 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 1,899 129 447 176 W 280 0 40 12.4 311221 Wet Corn Milling 20 7 15 W 4 0 W W 0 W 1 31131 Sugar 40 W W W W 0 0 0 0 0 0.9 311421 Fruit and Vegetable Canning 123 6 117 0 5 0 0 0 0 W 6.9 312 Beverage and Tobacco Products 251 30 227

24

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; 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 Milling 19 8 17 0 7 0 0 W W 0.9 31131 Sugar 24 13 22 0 11 0 4 0 W 0.9 311421 Fruit and Vegetable Canning 0 0 0 0 0 0 0 0 0 0 312 Beverage and Tobacco Products 17 8 12 0 7 W 5 0 0 5.3 3121 Beverages 9 5 5 0 W W W 0 0 8.5

25

table4.2_02.xls  

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

Offsite-Produced Fuel Consumption, 2002; 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 3 2 1 22 * 37 1 8 1 311421 Fruit and Vegetable Canning 47 7 1 1 36 Q 0 0 1 12.4 312 Beverage and Tobacco Products 104 27 2 2 46 1 17 0 9 4.3 3121 Beverages 84 22 1 2 42 1 8 0 9 5.9 3122 Tobacco 19 5 1 * 4 * 10 0 * 0.9 313 Textile Mills 206 87 4 2 74 2

26

table4.1_02.xls  

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

1 Offsite-Produced Fuel Consumption, 2002; 1 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 Factors: 0.8 0.8 1.1 1.6 0.9 1.8 0.7 0.7 1.2 311 Food 1,079 68,230 2 3 560 1 8 * 50 8 311221 Wet Corn Milling 217 7,098 * * 59 * 5 0 11 1.1 31131 Sugar 74 733 * * 22 * 2 * 8 1 311421 Fruit and Vegetable Canning 47 1,987 * * 35 * 0

27

table3.6_02  

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

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...

28

Comparison Study of Energy Intensity in the Textile Industry: A Case Study in Five Textile Sub-sectors  

E-Print Network (OSTI)

This paper contributes to the understanding of energy use in the textile industry by comparing the energy intensity of textile plants in five major sub-sectors, i.e. spinning, weaving, wet-processing, worsted fabric manufacturing, and carpet manufacturing in Iran. Results of the study showed that spinning plant electricity intensity varies between 3.6 MWh/tonne yarn and 6.6 MWh/tonne yarn, while fuel intensity ranges between 6.7 MBtu/tonne yarn and 11.7 MBtu/tonne yarn. In weaving plants, electricity intensity ranges from 1.2 MWh/tonne fabric to 2.2 MWh/tonne fabric, while fuel intensity was 10.1 MBtu/tonne fabric and 16.4 MBtu/tonne fabric for the two plants studied. In three wet-processing plants, the electricity intensity was found to be between 1.5 MWh/tonne finished fabric and 2.5 MWh/tonne finished fabric, while the fuel intensity was between 38.2 MBtu/tonne finished fabric and 106.3 MBtu/tonne finished fabric. In addition, some methodological issues to improve such energy intensity comparison analysis and benchmarking in the textile industry is discussed.

Hasanbeigi, A.

2011-01-01T23:59:59.000Z

29

"Code(a)","Subsector and Industry","Source(b)","Electricity(c)","Fuel Oil","Fuel Oil(d)","Natural Gas(e)","NGL(f)","Coal","and Breeze","Other(g)"  

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

3.4 Relative Standard Errors for Table 3.4;" 3.4 Relative Standard Errors for Table 3.4;" " Unit: Percents." " "," "," ",," "," "," "," "," "," "," ",," " " "," ","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"

30

"Code(a)","Subsector and Industry","Source(b)","Fuel Oil","Fuel Oil(c)","Natural Gas(d)","NGL(e)","Coal","and Breeze","Other(f)"  

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

2.4 Relative Standard Errors for Table 2.4;" 2.4 Relative Standard Errors for Table 2.4;" " Unit: Percents." " "," "," "," "," "," "," "," "," "," ",," " " "," ","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",27.5,"X",42,39.5,62,"X",0,9.8

31

"Code(a)","Subsector and Industry","Source(b)","Electricity(c)","Fuel Oil","Fuel Oil(d)","Natural Gas(e)","NGL(f)","Coal","and Breeze","Other(g)"  

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

4.4 Relative Standard Errors for Table 4.4;" 4.4 Relative Standard Errors for Table 4.4;" " Unit: Percents." " "," "," ",," "," "," "," "," "," "," ",," " " "," ","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",0.4,0.4,19.4,9,2,6.9,5.4,0,10.3

32

Electricity Subsector Cyb ersecurity Risk Management ...  

Science Conference Proceedings (OSTI)

... SCADA Network OT – Systems Power Operations - Energy Mgmt Partial 2 ... Monitor Concentrator Substations (all) Varies N/A PineOpsNetwork vary ...

2012-08-21T23:59:59.000Z

33

ELECTRICITY SUBSECTOR CYBERSECURITY RISK MANAGEMENT PROCESS  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

complementary to and should be used as part of a more comprehensive enterprise risk management program. i | contents 1. INTRODUCTION ......

34

Electricity Subsector Cybersecurity Capability Maturity Model...  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Mellon University Software Engineering Institute - CERT Program Dr. Les Cardwell Central Lincoln PUD Douglas M. DePeppe Information Security & Center for Information Age...

35

"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)"  

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

1.4 Relative Standard Errors for Table 1.4;" 1.4 Relative Standard Errors for Table 1.4;" " Unit: Percents." ,,"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",0.4,0.4,19.4,8.9,2,6.9,5.4,0,10.1,9.1 3112," Grain and Oilseed Milling",0,0,21.1,14.7,8.4,13.3,7.9,"X",17.9,9.1

36

Table 5.2 End Uses of Fuel Consumption, 2010;  

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

2 End Uses of Fuel Consumption, 2010; 2 End Uses of Fuel Consumption, 2010; 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 14,228 2,437 79 130 5,211 69 868 5,435 Indirect Uses-Boiler Fuel -- 27 46 19 2,134 10 572 -- Conventional Boiler Use -- 27 20 4 733 3 72 -- CHP and/or Cogeneration Process -- 0 26 15 1,401 7 500 -- Direct Uses-Total Process -- 1,912 26 54 2,623 29 289 -- Process Heating -- 297 25 14 2,362 24 280

37

Table 5.1 End Uses of Fuel Consumption, 2010;  

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

5.1 End Uses of Fuel Consumption, 2010; 5.1 End Uses of Fuel Consumption, 2010; 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 311 - 339 ALL MANUFACTURING INDUSTRIES TOTAL FUEL CONSUMPTION 14,228 714,166 13 22 5,064 18 39 5,435 Indirect Uses-Boiler Fuel -- 7,788 7 3 2,074 3 26 -- Conventional Boiler Use -- 7,788 3 1 712 1 3 -- CHP and/or Cogeneration Process

38

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; 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 -- 41 133 23 2,119 8 547 -- Conventional Boiler Use -- 41 71 17 1,281 8 129 -- CHP and/or Cogeneration Process -- -- 62 6 838 1 417 -- Direct Uses-Total Process -- 2,244 62 52 2,788 39 412 -- Process Heating -- 346 59 19 2,487

39

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; 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 311 - 339 ALL MANUFACTURING INDUSTRIES TOTAL FUEL CONSUMPTION 15,658 835,382 40 22 5,357 21 46 5,820 Indirect Uses-Boiler Fuel -- 12,109 21 4 2,059 2 25 -- Conventional Boiler Use -- 12,109 11 3 1,245 2 6 -- CHP and/or Cogeneration Process

40

table5.1_02  

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

End Uses of Fuel Consumption, 2002; 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 United States 311 - 339 ALL MANUFACTURING INDUSTRIES RSE Column Factors: 0.3 1 1 2.4 1.1 1.4 1 NF TOTAL FUEL CONSUMPTION 16,273 832,257 33 24 5,641 26 53 6,006 3.4 Indirect Uses-Boiler Fuel -- 3,540 20 6

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


41

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

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

me",0,0,0,0,0,0,0,0,0 327420," Gypsum",0.3,1.6,0,0,0.1,2.9,"X","X",0.1 327993," Mineral Wool",0.3,0.5,"X",2.7,0.2,2.2,"X",3,0.1 331,"Primary Metals",0.5,0.7,0.1,1.7,0.7,4,0,0.2,0.4...

42

Food and Beverage Manufacturing Subsectors in Lane County, Oregon  

E-Print Network (OSTI)

and employment multipliers that indicate that the brewing, flour milling, and a few other select food

Oregon, University of

43

table5.2_02  

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

2 End Uses of Fuel Consumption, 2002; 2 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 2,840 208 141 5,794 103 1,182 6,006 3.3 Indirect Uses-Boiler Fuel -- 12 127 25 2,162 8 776 -- 5.5 Conventional Boiler Use -- 9 76 25 1,306 8 255 -- 5.6 CHP and/or Cogeneration Process -- 4 51 10 857 * 521 -- 3.7 Direct Uses-Total Process

44

table7.8_02  

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

8 Number of Establishments by Quantity of Purchased Electricity, Natural Gas, and Steam, 2002; 8 Number of Establishments by Quantity of Purchased Electricity, Natural Gas, and Steam, 2002; Level: National Data; Row: NAICS Codes; Column: Supplier Sources of Purchased Electricity, Natural Gas, and Steam; Unit: Establishment Counts. Electricity Components Natural Gas Components Steam Components Electricity Electricity Natural Gas Natural Gas Steam Steam from Only from Both from Only from Both from Only from Both Electricity Sources Local Utility Any Natural Gas Sources Local Utility Steam Sources Local Utility RSE NAICS Any from Only Other than and Natural from Only Other than and Any from Only Other than and Row Code(a) Subsector and Industry Electricity(b) Local Utility(c) Local Utility(d)

45

Originally Released: July 2009  

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

1 Nonfuel (Feedstock) Use of Combustible Energy, 2006 1 Nonfuel (Feedstock) Use of Combustible Energy, 2006 Level: National and Regional Data; Row: NAICS Codes; Column: Energy Sources Unit: Physical Units or Btu. Coke Residual Distillate Natural Gas(c) LPG and Coal and Breeze NAICS Total Fuel Oil Fuel Oil(b) (billion NGL(d) (million (million Other(e) Code(a) Subsector and Industry (trillion Btu) (million bbl) (million bbl) cu ft) (million bbl) short tons) short tons) (trillion Btu) Total United States 311 Food 3 0 * 2 * 0 * * 3112 Grain and Oilseed Milling 3 0 * 2 * 0 0 * 311221 Wet Corn Milling * 0 0 0 0 0 0 * 31131 Sugar Manufacturing * 0 * 0 * 0 * 0 3114 Fruit and Vegetable Preserving and Specialty Food * 0 0 0 * 0 0 0 3115 Dairy Product * 0 * * 0 0 0 * 3116 Animal Slaughtering and Processing

46

Table 7.10 Expenditures for Purchased Electricity, Natural Gas, and Steam, 2010;  

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

0 Expenditures for Purchased Electricity, Natural Gas, and Steam, 2010; 0 Expenditures for Purchased Electricity, Natural Gas, and Steam, 2010; Level: National and Regional Data; Row: NAICS Codes; Column: Supplier Sources of Purchased Electricity, Natural Gas, and Steam; Unit: Million U.S. Dollars. Electricity Components Natural Gas Electricity Electricity from Sources Natural Gas NAICS Electricity from Local Other than Natural Gas from Local Code(a) Subsector and Industry Total Utility(b) Local Utility(c) Total Utility(b) Total United States 311 Food 5,328 4,635 692 3,391 1,675 3112 Grain and Oilseed Milling 932 850 82 673 261 311221 Wet Corn Milling 352 331 21 296 103 31131 Sugar Manufacturing 105 87 18 87 39 3114 Fruit and Vegetable Preserving and Specialty Foods 698

47

table11.5_02.xls  

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

5 Electricity: Sales to Utility and Nonutility Purchasers, 2002; 5 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 Beverage and Tobacco Products W W W 1 3121 Beverages W W W 1 3122 Tobacco W W 0 1 313 Textile Mills W W W 1.8 314 Textile Product Mills 0 0 0 0 315 Apparel 0 0 0 0 316 Leather and Allied Products

48

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; 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 bbl) short tons) short tons) (trillion Btu) (trillion Btu) Total United States 311 Food 1,162 75,407 2 4 567 2 8 * 96 * 3112 Grain and Oilseed Milling 355 16,479 * * 119 Q 6 0 47 * 311221 Wet Corn Milling 215 7,467 * * 51 * 5 0 26 0 31131 Sugar Manufacturing

49

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

Gasoline and Diesel Fuel Update (EIA)

Next MECS will be fielded in 2015 Table 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 50 36 15 0 29 31131 Sugar Manufacturing 73 73 3 36 67 12 W 7 14 3114 Fruit and Vegetable Preserving and Specialty Foods 987 987 17 207 839 503 W 0 210 3115 Dairy Products 998 998 12 217 908

50

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

Gasoline and Diesel Fuel Update (EIA)

9.1 Enclosed Floorspace and Number of Establishment Buildings, 2010; 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) Total United States 311 Food 1,115 13,271 107,293.7 32,953 3.1 3112 Grain and Oilseed Milling 126 602 443,178.6 5,207 24.8 311221 Wet Corn Milling 14 59 270,262.7 982 18.3 31131 Sugar Manufacturing

51

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

Gasoline and Diesel Fuel Update (EIA)

Next MECS will be fielded in 2015 Table 6.1 Consumption Ratios of Fuel, 2010; 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 871.7 4.3 1.8 3112 Grain and Oilseed Milling 6,239.5 10.5 3.6 311221 Wet Corn Milling 28,965.0 27.1 12.6 31131 Sugar Manufacturing 7,755.9 32.6 13.4 3114 Fruit and Vegetable Preserving and Specialty Foods 861.3 4.8 2.2 3115 Dairy Products 854.8 3.5 1.1 3116 Animal Slaughtering and Processing 442.9 3.5 1.2 312

52

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; 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 0 312 Beverage and Tobacco Products 0 1 0 0 1 0 321 Wood Products 0 218 * 13 199 6 321113 Sawmills 0 100 * 5 94 1 3212 Veneer, Plywood, and Engineered Woods 0 95 * 6 87 2 321219 Reconstituted Wood Products 0 52 0 6 46 1 3219 Other Wood Products

53

Table 7.3 Average Prices of Purchased Electricity, Natural Gas, and Steam, 2010;  

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

3 Average Prices of Purchased Electricity, Natural Gas, and Steam, 2010; 3 Average Prices of Purchased Electricity, Natural Gas, and Steam, 2010; Level: National and Regional Data; Row: NAICS Codes; Column: Supplier Sources of Purchased Electricity, Natural Gas, and Steam; Unit: U.S. Dollars per Physical Units. Electricity Components Natural Gas Components Steam Components Electricity Natural Gas Steam Electricity from Sources Natural Gas from Sources Steam from Sources Electricity from Local Other than Natural Gas from Local Other than Steam from Local Other than NAICS Total Utility(b) Local Utility(c) Total Utility(b) Local Utility(c) Total Utility(b) Local Utility(c) Code(a) Subsector and Industry (kWh) (kWh) (kWh) (1000 cu ft) (1000 cu ft) (1000 cu ft) (million Btu)

54

Originally Released: August 2009  

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

August 2009 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 * 311221 Wet Corn Milling 5 0 * 0 0 4 0 31131 Sugar Manufacturing 1 0 0 0 0 1 0 3114 Fruit and Vegetable Preserving and Specialty Food Q 0 * 0 0 0 Q 3115 Dairy Product * 0 * 0 0 0 0 3116 Animal Slaughtering and Processing 1 0 1 0 0 * * 312 Beverage and Tobacco Products

55

Originally Released: July 2009  

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

2 Nonfuel (Feedstock) Use of Combustible Energy, 2006 2 Nonfuel (Feedstock) Use of Combustible Energy, 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 Fuel Oil Fuel Oil(b) Natural Gas(c) NGL(d) Coal and Breeze Other(e) Total United States 311 Food 3 0 * 2 * 0 * * 3112 Grain and Oilseed Milling 3 0 * 2 * 0 0 * 311221 Wet Corn Milling * 0 0 0 0 0 0 * 31131 Sugar Manufacturing * 0 * 0 * 0 * 0 3114 Fruit and Vegetable Preserving and Specialty Food * 0 0 0 * 0 0 0 3115 Dairy Product * 0 * * 0 0 0 * 3116 Animal Slaughtering and Processing * 0 * * 0 0 0 * 312 Beverage and Tobacco Products * 0 * 0 * 0 0 0 3121 Beverages * 0 * 0 0 0 0 0 3122 Tobacco * 0 0 0 * 0 0 0 313 Textile Mills 0 0

56

table7.3_02.xls  

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

3 Average Prices of Purchased Electricity, Natural Gas, and Steam, 2002; 3 Average Prices of Purchased Electricity, Natural Gas, and Steam, 2002; Level: National and Regional Data; Row: NAICS Codes; Column: Supplier Sources of Purchased Electricity, Natural Gas, and Steam; Unit: U.S. Dollars per Physical Units. Electricity Components Natural Gas Components Steam Components Electricity Natural Gas Steam Electricity from Sources Natural Gas from Sources Steam from Sources Electricity from Local Other than Natural Gas from Local Other than Steam from Local Other than RSE NAICS Total Utility(b) Local Utility(c) Total Utility(b) Local Utility(c) Total Utility(b) Local Utility(c) Row Code(a) Subsector and Industry (kWh) (kWh) (kWh) (1000 cu ft) (1000 cu ft) (1000 cu ft)

57

Level: National and Regional Data; Row: NAICS Codes; Column: Utility and Nonutility Purchasers;  

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

Next MECS will be conducted in 2010 Next MECS will be conducted in 2010 Table 11.5 Electricity: Sales to Utility and Nonutility Purchasers, 2006; Level: National and Regional Data; Row: NAICS Codes; Column: Utility and Nonutility Purchasers; Unit: Million Kilowatthours. Total of NAICS Sales and Utility Nonutility Code(a) Subsector and Industry Transfers Offsite Purchaser(b) Purchaser(c) Total United States 311 Food 111 86 25 3112 Grain and Oilseed Milling 72 51 21 311221 Wet Corn Milling 55 42 13 31131 Sugar Manufacturing 7 3 4 3114 Fruit and Vegetable Preserving and Specialty Foods 13 13 0 3115 Dairy Products 0 0 0 3116 Animal Slaughtering and Processing 0 0 0 312 Beverage and Tobacco Products * * 0 3121 Beverages

58

table7.7_02.xls  

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

7 Quantity of Purchased Electricity, Natural Gas, and Steam, 2002; 7 Quantity of Purchased Electricity, Natural Gas, and Steam, 2002; Level: National and Regional Data; Row: NAICS Codes; Column: Supplier Sources of Purchased Electricity, Natural Gas, and Steam; Unit: Physical Units or Btu. Electricity Components Natural Gas Components Steam Components Electricity Natural Gas Steam Electricity from Sources Natural Gas from Sources Steam from Sources Electricity from Local Other than Natural Gas from Local Other than Steam from Local Other than RSE NAICS Total Utility(b) Local Utility(c) Total Utility(b) Local Utility(c) Total Utility(b) Local Utility(c) Row Code(a) Subsector and Industry (million kWh) (million kWh) (million kWh) (billion cu ft) (billion cu ft)

59

Table 3.5 Selected Byproducts in Fuel Consumption, 2010;  

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

5 Selected Byproducts in Fuel Consumption, 2010; 5 Selected Byproducts in Fuel Consumption, 2010; Level: National and Regional Data; Row: NAICS Codes; Column: Energy Sources; Unit: Trillion Btu. Blast Pulping Liquor NAICS Furnace/Coke Petroleum or Wood Chips, Code(a) Subsector and Industry Total Oven Gases Waste Gas Coke Black Liquor Bark Total United States 311 Food 11 0 7 0 0 1 3112 Grain and Oilseed Milling 5 0 2 0 0 * 311221 Wet Corn Milling * 0 * 0 0 0 31131 Sugar Manufacturing * 0 * 0 0 * 3114 Fruit and Vegetable Preserving and Specialty Foods 1 0 1 0 0 0 3115 Dairy Products 1 0 1 0 0 0 3116 Animal Slaughtering and Processing 4 0 4 0 0 * 312 Beverage and Tobacco Products 3 0 2 0 0 1 3121 Beverages 3 0 2 0 0 1 3122 Tobacco 0 0 0 0 0 0 313 Textile Mills 0 0 0 0 0 0 314 Textile Product Mills

60

Table 11.5 Electricity: Sales to Utility and Nonutility Purchasers, 2010;  

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

5 Electricity: Sales to Utility and Nonutility Purchasers, 2010; 5 Electricity: Sales to Utility and Nonutility Purchasers, 2010; Level: National and Regional Data; Row: NAICS Codes; Column: Utility and Nonutility Purchasers; Unit: Million Kilowatthours. Total of NAICS Sales and Utility Nonutility Code(a) Subsector and Industry Transfers Offsite Purchaser(b) Purchaser(c) Total United States 311 Food 347 168 179 3112 Grain and Oilseed Milling 142 6 136 311221 Wet Corn Milling 14 4 10 31131 Sugar Manufacturing 109 88 21 3114 Fruit and Vegetable Preserving and Specialty Foods 66 66 0 3115 Dairy Products 22 0 22 3116 Animal Slaughtering and Processing 0 0 0 312 Beverage and Tobacco Products 1 1 * 3121 Beverages 1 1 * 3122 Tobacco 0 0 0 313 Textile Mills

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


61

Table 11.3 Electricity: Components of Onsite Generation, 2010;  

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

3 Electricity: Components of Onsite Generation, 2010; 3 Electricity: Components of Onsite Generation, 2010; Level: National and Regional Data; Row: NAICS Codes; Column: Onsite-Generation Components; Unit: Million Kilowatthours. Renewable Energy (excluding Wood NAICS Total Onsite and Code(a) Subsector and Industry Generation Cogeneration(b) Other Biomass)(c) Other(d) Total United States 311 Food 5,666 5,414 81 171 3112 Grain and Oilseed Milling 3,494 3,491 Q 2 311221 Wet Corn Milling 3,213 3,211 0 2 31131 Sugar Manufacturing 1,382 1,319 64 0 3114 Fruit and Vegetable Preserving and Specialty Foods 336 325 Q * 3115 Dairy Products 38 36 1 1 3116 Animal Slaughtering and Processing 19 Q Q 14 312 Beverage and Tobacco Products 342 238 Q 7 3121 Beverages 308 204 Q 7 3122 Tobacco 34

62

table7.10_02.xls  

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

0 Expenditures for Purchased Electricity, Natural Gas, and Steam, 2002; 0 Expenditures for Purchased Electricity, Natural Gas, and Steam, 2002; Level: National and Regional Data; Row: NAICS Codes; Column: Supplier Sources of Purchased Electricity, Natural Gas, and Steam; Unit: Million U.S. Dollars. Electricity Components Natural Gas Components Steam Components Electricity Natural Gas Steam Electricity from Sources Natural Gas from Sources Steam from Sources RSE NAICS Electricity from Local Other than Natural Gas from Local Other than Steam from Local Other than Row Code(a) Subsector and Industry Total Utility(b) Local Utility(c) Total Utility(b) Local Utility(c) Total Utility(b) Local Utility(c) Factors Total United States RSE Column Factors: 0.9 1 1.3 1 1.4

63

Table 7.7 Quantity of Purchased Electricity, Natural Gas, and Steam, 2010;  

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

7 Quantity of Purchased Electricity, Natural Gas, and Steam, 2010; 7 Quantity of Purchased Electricity, Natural Gas, and Steam, 2010; Level: National and Regional Data; Row: NAICS Codes; Column: Supplier Sources of Purchased Electricity, Natural Gas, and Steam; Unit: Physical Units or Btu. Electricity Components Natural Gas Components Steam Components Electricity Natural Gas Steam Electricity from Sources Natural Gas from Sources Steam from Sources Electricity from Local Other than Natural Gas from Local Other than Steam from Local Other than NAICS Total Utility(b) Local Utility(c) Total Utility(b) Local Utility(c) Total Utility(b) Local Utility(c) Code(a) Subsector and Industry (million kWh) (million kWh) (million kWh) (billion cu ft) (billion cu ft)

64

Table 2.1 Nonfuel (Feedstock) Use of Combustible Energy, 2010;  

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

1 Nonfuel (Feedstock) Use of Combustible Energy, 2010; 1 Nonfuel (Feedstock) Use of Combustible Energy, 2010; Level: National and Regional Data; Row: NAICS Codes; Column: Energy Sources; Unit: Physical Units or Btu. Coke Residual Distillate Natural Gas(c) LPG and Coal and Breeze NAICS Total Fuel Oil Fuel Oil(b) (billion NGL(d) (million (million Other(e) Code(a) Subsector and Industry (trillion Btu) (million bbl) (million bbl) cu ft) (million bbl) short tons) short tons) (trillion Btu) Total United States 311 Food 10 * * 4 Q 0 0 2 3112 Grain and Oilseed Milling 6 0 * 1 Q 0 0 2 311221 Wet Corn Milling 2 0 0 0 0 0 0 2 31131 Sugar Manufacturing * 0 * 0 * 0 0 * 3114 Fruit and Vegetable Preserving and Specialty Foods 1 * * 1 * 0 0 * 3115 Dairy Products Q 0 * * * 0 0 * 3116 Animal Slaughtering and Processing

65

table2.1_02.xls  

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

1 Nonfuel (Feedstock) Use of Combustible Energy, 2002; 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 0.7 1.2 311 Food 8 * * 7 0 0 * * 311221 Wet Corn Milling * 0 * 0 0 0 0 * 31131 Sugar * 0 * * 0 0 * * 311421 Fruit and Vegetable Canning * * * 0 0 0 0 * 312 Beverage and Tobacco Products 1 * * * 0 0 0 1 3121 Beverages * * * 0 0 0 0 *

66

Level: National and Regional Data; Row: NAICS Codes; Column: Onsite-Generation Components;  

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

3 Electricity: Components of Onsite Generation, 2006; 3 Electricity: Components of Onsite Generation, 2006; Level: National and Regional Data; Row: NAICS Codes; Column: Onsite-Generation Components; Unit: Million Kilowatthours. Renewable Energy (excluding Wood NAICS Total Onsite and Code(a) Subsector and Industry Generation Cogeneration(b) Other Biomass)(c) Other(d) Total United States 311 Food 4,563 4,249 * 313 3112 Grain and Oilseed Milling 2,845 2,819 0 27 311221 Wet Corn Milling 2,396 2,370 0 27 31131 Sugar Manufacturing 951 951 0 * 3114 Fruit and Vegetable Preserving and Specialty Foods 268 268 0 * 3115 Dairy Products 44 31 * Q 3116 Animal Slaughtering and Processing 17 0 0 17 312 Beverage and Tobacco Products 659 623 Q * 3121 Beverages 587 551 Q * 3122 Tobacco 72

67

table9.1_02.xls  

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

1 Enclosed Floorspace and Number of Establishment Buildings, 2002; 1 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) (counts) Factors Total United States RSE Column Factors: 0 0 0 0 0 311 Food 751 15,089 102,589.2 26,438 3.0 0 311221 Wet Corn Milling 5 49 239,993.7 428 13.0 0 31131 Sugar 17 77 418,497.0 821 15.2 0

68

China's Industrial Carbon Dioxide Emissions in Manufacturing Subsectors and in Selected Provinces  

E-Print Network (OSTI)

Gas Other Petroleum Products Natural Gas Source: NBS, 2009.Gas Other Petroleum Products Natural Gas Source: IPCC, 1997a

Lu, Hongyou

2013-01-01T23:59:59.000Z

69

China's Industrial Carbon Dioxide Emissions in Manufacturing Subsectors and in Selected Provinces  

E-Print Network (OSTI)

emissions. In this paper, energy use and CO 2 emissions ofinformation, this paper estimates industrial energy-relatedenergy-intensive products. Emissions from manufacturing of textiles, and paper

Lu, Hongyou

2013-01-01T23:59:59.000Z

70

China's Industrial Carbon Dioxide Emissions in Manufacturing Subsectors and in Selected Provinces  

E-Print Network (OSTI)

for fuels, such as crude oil and raw coal, and these valuesOther Gas Other Coking Products Crude Oil Gasoline KeroseneDiesel Fuel Oil LPG Refinery Gas Other Petroleum Products

Lu, Hongyou

2013-01-01T23:59:59.000Z

71

China's Industrial Carbon Dioxide Emissions in Manufacturing Subsectors and in Selected Provinces  

E-Print Network (OSTI)

Oil LPG Refinery Gas Other Petroleum Products Natural GasOil LPG Refinery Gas Other Petroleum Products Natural GasEquipment Chemicals Food Petroleum & Coking Textiles Paper

Lu, Hongyou

2013-01-01T23:59:59.000Z

72

China's Industrial Carbon Dioxide Emissions in Manufacturing Subsectors and in Selected Provinces  

E-Print Network (OSTI)

key resources for national energy consumption data in ChinaNBS published 2008 national energy consumption by industrialnational level, carbon emission factors for electricity consumption are calculated based on the energy

Lu, Hongyou

2013-01-01T23:59:59.000Z

73

China's Industrial Carbon Dioxide Emissions in Manufacturing Subsectors and in Selected Provinces  

E-Print Network (OSTI)

U.S. Energy-Related Carbon Dioxide Emissions, 2010. ” AugustChina’s Industrial Carbon Dioxide Emissions in ManufacturingChina’s Industrial Carbon Dioxide Emissions in Manufacturing

Lu, Hongyou

2013-01-01T23:59:59.000Z

74

China's Industrial Carbon Dioxide Emissions in Manufacturing Subsectors and in Selected Provinces  

E-Print Network (OSTI)

have a large iron and steel industry, while another provinceand has a clustered steel industry; therefore, it is nothas many large industries, such as steel and cement, its CO

Lu, Hongyou

2013-01-01T23:59:59.000Z

75

China's Industrial Carbon Dioxide Emissions in Manufacturing Subsectors and in Selected Provinces  

E-Print Network (OSTI)

for some fuels, such as coke oven gas and other gas, NBSby Fuel Fuel Type Raw Coal Cleaned Coal Washed Coal CokeCoke Oven Gas Other Gas Other Coking Products Crude Oil

Lu, Hongyou

2013-01-01T23:59:59.000Z

76

The Hesitant Boom: Indonesia's Oil Palm Sub-Sector in an Era of Economic Crisis and Political Change  

E-Print Network (OSTI)

This report was prepared with assistance from the Center for International Forestry Research (CIFOR). I am grateful for the guidance and support I have received there. I would especially like to thank Dr William Sunderlin who has provided endless academic support and constructive advice. The following people from CIFOR have also offered a great deal of assistance: Grahame Applegate, Chris Barr, Brian Belcher, Emily Boyd, Unna Chokkalingam, Carol Colfer, Rona Dennis, David Edmunds, Carmen Garcia, Wil De Jong, David Kaimowitz, Ken MacDicken, Cynthia McDougall, Michael Spilsbury, and Rachel Wrangham. Outside of CIFOR I have also received a great deal of support and assistance from: Peter Dauvergne, Chip Fey, Peter Kanowski, Togu Manurang, Stephen Midgley, Lesley Potter, Ben Santoso, Martua Sirait and Eric Wakker. Timothy Brown deserves special credit for providing very detailed and constructive comments on a final draft. Finally, I would like to thank all of the people interviewed who have given their time to help me put this paper together. Despite all the assistance I have received from the above people, any errors are my own

Anne Casson; Emily Boyd; Unna Chokkalingam; Carol Colfer; Rona Dennis; David Edmunds; Carmen Garcia; Wil De Jong; David Kaimowitz; Ken Macdicken; Peter Kanowski; Togu Manurang; Stephen Midgley; Lesley Potter; Ben Santoso; Martua Sirait; Eric Wakker; Timothy Brown

1999-01-01T23:59:59.000Z

77

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 Corn Milling 217 6,851 * * 59 * 5 0 11 0 31131 Sugar 112 725 * * 22 * 2 * 46 0 311421 Fruit and Vegetable Canning 47 1,960 * * 35 * 0 0 1 0 312 Beverage and Tobacco Products 105 7,639 * * 45 * 1 0 11 0 3121 Beverages 85 6,426 * * 41 * * 0 10 0 3122 Tobacco 20 1,213 * * 4 * * 0 1 0 313 Textile Mills 207 25,271 1 * 73 * 1 0 15 0 314

78

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 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 18.2 31131 Sugar Manufacturing 6,629.2 31.3 12.2 3114 Fruit and Vegetable Preserving and Specialty Foods 1,075.3 5.5 2.8 3115 Dairy Products 956.3 4.3 1.3 3116 Animal Slaughtering and Processing 493.8 4.4 1.6 312

79

Level: National and Regional Data; Row: NAICS Codes; Column: Electricity Components;  

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

1.1 Electricity: Components of Net Demand, 2006; 1.1 Electricity: Components of Net Demand, 2006; Level: National and Regional Data; Row: NAICS Codes; Column: Electricity Components; Unit: Million Kilowatthours. Total Sales and Net Demand NAICS Transfers Onsite Transfers for Code(a) Subsector and Industry Purchases In(b) Generation(c) Offsite Electricity(d) Total United States 311 Food 73,242 309 4,563 111 78,003 3112 Grain and Oilseed Milling 15,283 253 2,845 72 18,310 311221 Wet Corn Milling 6,753 48 2,396 55 9,142 31131 Sugar Manufacturing 920 54 951 7 1,919 3114 Fruit and Vegetable Preserving and Specialty Foo 9,720 1 268 13 9,976 3115 Dairy Products 10,079 0 44 0 10,123 3116 Animal Slaughtering and Processing 17,545 0 17 0 17,562 312 Beverage and Tobacco Products

80

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; 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 Wet Corn Milling 47 47 W 17 44 19 18 0 17 31131 Sugar Manufacturing 78 78 11 43 61 35 26 13 35 3114 Fruit and Vegetable Preserving and Specialty Food 1,125 1,125 13 112 961 325 W 0 127 3115 Dairy Product 1,044 1,044 25 88 941 147 W 0 95

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


81

table10.10_02.xls  

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

0 Capability to Switch Coal to Alternative Energy Sources, 2002; 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 7,112 0 1,410 Q 212 313 7 8.5 311221 Wet Corn Milling 5,462 771 5,201 0 766 0 0 249 6 0.9 31131 Sugar 1,648 388 1,260 0 243 0 W 0 2 0.9 311421 Fruit and Vegetable Canning 0 0 0 0 0 0 0 0 0 0 312 Beverage and Tobacco Products

82

table10.4_02.xls  

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

4 Capability to Switch Residual Fuel Oil to Alternative Energy Sources, 2002; 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 Food 2,125 1,411 508 0 819 W W Q 0 Q 11.1 311221 Wet Corn Milling 61 W 45 0 0 W 0 0 0 0 0.8 31131 Sugar 346 193 98 0 169 0 W 0 0 0 0.7 311421 Fruit and Vegetable Canning 153 29 Q 0 29 * 0 0 0 0 24.6 312 Beverage and Tobacco Products

83

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; 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 44 19 18 0 18 31131 Sugar Manufacturing 78 78 11 43 61 35 26 13 45 3114 Fruit and Vegetable Preserving and Specialty Food 1,125 1,125 13 112 961 325 W 0 127 3115 Dairy Product 1,044 1,044 25 88 941 147 W 0 104 3116 Animal Slaughtering and Processing

84

table3.4_02.xls  

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

4 Number of Establishments by Fuel Consumption, 2002; 4 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 49 49 3 20 47 14 19 0 15 1 31131 Sugar 77 77 18 40 62 31 24 19 44 1 311421 Fruit and Vegetable Canning 468 468 38 123 416 229 0 0 146 7.8 312 Beverage and Tobacco Products 1,595 1,595 35 251 1,132 630 17 0 184 11 3121 Beverages 1,517 1,517

85

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

Gasoline and Diesel Fuel Update (EIA)

1.4 Number of Establishments by First Use of Energy for All Purposes (Fuel and Nonfuel), 2010; 1.4 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 1,668 W 3112 Grain and Oilseed Milling 602 602 9 201 490 286 30 0 165 W 311221 Wet Corn Milling 59 59 W 26 50 36 15 0 29 0 31131 Sugar Manufacturing 73 73 3 36 67 13 11 7 15 0 3114 Fruit and Vegetable Preserving and Specialty Foods 987 987

86

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; 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 126 0 47 * 311221 Wet Corn Milling 215 25 * * 53 * 110 0 26 0 31131 Sugar Manufacturing 107 4 1 1 15 * 49 2 36 0 3114 Fruit and Vegetable Preserving and Specialty Foods 143 31 1 Q 100 1 2 0 4 0 3115 Dairy Products 105 33 2 2 67

87

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; 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 Manufacturing 5.02 0.31 0.00 53.34 236.66 3114 Fruit and Vegetable Preserving and Specialty Foods 9.78 0.27 0.00 90.59 0.00 3115 Dairy Products 11.21 0.10 0.00 103.12 0.00 3116 Animal Slaughtering and Processing

88

table6.1_02.xls  

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

1 Consumption Ratios of Fuel, 2002; 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 311421 Fruit and Vegetable Canning 824.1 5.4 2.5 10.6 312 Beverage and Tobacco Products 670.4 1.6 1.0 2.7 3121 Beverages 658.6 2.8 1.3 3.9 3122 Tobacco 729.4 0.6 0.5 1 313 Textile Mills 798.7 11.2 4.3

89

Table 7.9 Expenditures for Purchased Energy Sources, 2010;  

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

9 Expenditures for Purchased Energy Sources, 2010; 9 Expenditures for Purchased Energy Sources, 2010; Level: National and Regional Data; Row: NAICS Codes; Column: Energy Sources; Unit: Million U.S. Dollars. NAICS Residual Distillate LPG and Coke Code(a) Subsector and Industry Total Electricity Fuel Oil Fuel Oil(b) Natural Gas(c) NGL(d) Coal and Breeze Other(e) Total United States 311 Food 10,111 5,328 130 431 3,391 150 442 29 210 3112 Grain and Oilseed Milling 2,130 932 2 12 673 Q 294 0 158 311221 Wet Corn Milling 1,002 352 1 5 296 1 239 0 107 31131 Sugar Manufacturing 367 105 7 18 87 1 118 29 2 3114 Fruit and Vegetable Preserving and Specialty Foods 1,408 698 17 Q 579 18 7 0 18 3115 Dairy Products 1,186 695 20 40 412 8 1 0 10 3116 Animal Slaughtering and Processing

90

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; 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 99 11,338 2,691 51 11,217 2,860 10 11,333 2,786 164 11,129 2,836 9 11,235 2,884 3112 Grain and Oilseed Milling 580 53 Q 499 38 5 532 42 W 533 W Q 533 44 5 530 45 311221 Wet Corn Milling 47 11 W 35 W W 43 W W 39 W 0 44 3 0 41 6 31131 Sugar Manufacturing

91

table10.8_02.xls  

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

8 Capability to Switch Distillate Fuel Oil to Alternative Energy Sources, 2002; 8 Capability to Switch Distillate Fuel Oil to Alternative Energy Sources, 2002; Level: National Data and Regional Totals; Row: NAICS Codes, Value of Shipments and Employment Sizes; Column: Energy Sources; Unit: Thousand Barrels. 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 0.8 311 Food 3,177 986 767 Q 297 Q 1 Q 0 Q 10.4 311221 Wet Corn Milling 14 4 10 * 3 0 1 2 0 * 0.8 31131 Sugar 169 W 143 W W 0 0 0 0 0 0.7 311421 Fruit and Vegetable Canning 242 Q 121 0 Q 0 0 0 0 * 27.1 312 Beverage and Tobacco Products

92

table1.2_02  

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

2 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; 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 13 19 582 5 184 1 89 0 6.8 311221 Wet Corn Milling 217 23 * * 61 * 121 0 11 0 1.1 31131 Sugar 112 2 2 1 22 * 37 1 46 0 0.9 311421 Fruit and Vegetable Canning 47 7 1 1 36 Q 0 0 1 0 11 312 Beverage and Tobacco Products 105 26 2 2 46 1 17 0 11

93

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; 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 9,609 2,929 6,260 5,014 2,854 422 9,945 3,762 3112 Grain and Oilseed Milling 580 59 475 46 300 236 Q 154 398 28 446 95 Q 45 442 92 311221 Wet Corn Milling 47 9 34 4 36 W W 27 15 6 38 3 6 8 24 16 31131 Sugar Manufacturing 77

94

Originally Released: July 2009  

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

2 Offsite-Produced Fuel Consumption, 2006 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 and Vegetable Preserving and Specialty Food 168 33 2 1 126 1 1 0 3115 Dairy Product 121 34 1 1 83 * * 0 3116 Animal Slaughtering and Processing 220 60 3 5 145 1 0 0 312 Beverage and Tobacco Products 101 30 3 1 41 1 20 0 3121 Beverages 89 26 2 1 38 1 16 0 3122 Tobacco 13

95

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; 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 1,210 W 3112 Grain and Oilseed Milling 580 580 15 183 449 269 35 0 148 W 311221 Wet Corn Milling 47 47 W 17 44 19 18 0 18 0 31131 Sugar Manufacturing 78 78 11 45 61 35 26 15 45 0 3114 Fruit and Vegetable Preserving and Specialty Food 1,125

96

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

Gasoline and Diesel Fuel Update (EIA)

4.4 Number of Establishments by Offsite-Produced Fuel Consumption, 2010; 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 Milling 59 59 W 26 50 36 15 0 28 31131 Sugar Manufacturing 73 73 3 36 67 12 11 W 11 3114 Fruit and Vegetable Preserving and Specialty Foods 987 987 17 207 839 503 W 0 207 3115 Dairy Products 998 998 12 217 908 161 W 0 79 3116 Animal Slaughtering and Processing

97

table7.6_02.xls  

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

6 Quantity of Purchased Energy Sources, 2002; 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 Factors: 0.9 0.9 1.2 1.5 0.9 1.5 0.8 0.6 1.1 311 Food 1,082 W 2 3 566 1 9 * 40 8.2 311221 Wet Corn Milling 220 W * * 59 * 6 0 9 1.1 31131 Sugar 71 733 * * 22 * 2 * 3 1 311421 Fruit and Vegetable Canning 47 1,987 * * 35 * 0 0 1 12.6

98

table8.2_02.xls  

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

2 Number of Establishments by Usage of General Energy-Saving Technologies, 2002 2 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 68 5 59 14 4 311421 Fruit and Vegetable Canning 468 64 352 52 142 275 51 312 Beverage and Tobacco Products 1,595 234 1,095 266 367 954 274 3121 Beverages 1,517 214 1,039 264 333 913 271 3122 Tobacco 78

99

table7.2_02.xls  

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

2 Average Prices of Purchased Energy Sources, 2002; 2 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 0 31131 Sugar 3.14 80.39 0 1.65 W 1.64 0 5.18 0 311421 Fruit and Vegetable Canning 7.09 103.28 0 0 0 0 0 0 0 312 Beverage and Tobacco Products 7.53 123.52 0 2.32 0 2.32 0 0 0 3121 Beverages 7.96 124.83

100

table11.3_02.xls  

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

3 Electricity: Components of Onsite Generation, 2002; 3 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 Fruit and Vegetable Canning 388 W 0 W 1 312 Beverage and Tobacco Products W W * 1 1.6 3121 Beverages W W * * 3.8 3122 Tobacco W W 0 1 1 313 Textile Mills W 138 W W 11.9 314 Textile Product Mills 55 49 Q * 2.1

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


101

table10.6_02.xls  

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

6 Capability to Switch Electricity to Alternative Energy Sources, 2002; 6 Capability to Switch Electricity to Alternative Energy Sources, 2002; Level: National Data and Regional Totals; Row: NAICS Codes, Value of Shipments and Employment Sizes; Column: Energy Sources; Unit: Million Kilowatthours. 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 68,230 2,270 49,890 239 2,125 17 9 72 0 Q 12.2 311221 Wet Corn Milling 7,098 77 6,062 77 0 0 0 0 0 0 0.9 31131 Sugar 733 21 602 * 11 9 9 0 0 * 1 311421 Fruit and Vegetable Canning 1,987 Q 1,764 Q Q 0 0 25

102

table10.2_02.xls  

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

2 Capability to Switch Natural Gas to Alternative Energy Sources, 2002; 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 Food 560 155 298 20 70 40 2 63 * Q 12 311221 Wet Corn Milling 59 11 41 3 3 3 * 4 0 * 2 31131 Sugar 22 7 10 * 2 5 * 0 * 0 1 311421 Fruit and Vegetable Canning 35 10 19 2 6 2 * 1 * * 5.5 312 Beverage and Tobacco Products

103

table8.3_02.xls  

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

3 Number of Establishments by Usage of Cogeneration Technologies, 2002; 3 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 Milling 49 11 8 40 1 3 45 1 31131 Sugar 77 45 44 27 5 8 61 8 311421 Fruit and Vegetable Canning 468 50 42 375 51 44 374 50 312 Beverage and Tobacco Products 1,595 22 12 1,398 185 3 1,444 147

104

table2.2_02.xls  

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

2 Nonfuel (Feedstock) Use of Combustible Energy, 2002; 2 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 Fruit and Vegetable Canning * * * 0 0 0 0 * 1.7 312 Beverage and Tobacco Products 1 * * * 0 0 0 1 2.3 3121 Beverages * * * 0 0 0 0 * 28.9 3122 Tobacco 1 0 0 * 0 0 0 1 0.8 313 Textile Mills 1 0 * 1 0 0 0 * 0.8 314 Textile Product Mills * 0 0 * 0 * 0 * 2 315 Apparel

105

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 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 0.5 311 Food 15,089 15,045 275 2,536 12,106 3,159 91 23 1,911 0 311221 Wet Corn Milling 49 49 3 20 47 14 19 0 15 0 31131 Sugar 77 77 18 41 63 31 24 23 45 0 311421 Fruit and Vegetable Canning 468 468 40 128 416 229 0 0 153 0 312

106

table7.9_02.xls  

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

9 Expenditures for Purchased Energy Sources, 2002; 9 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 26 1.1 31131 Sugar 224 39 11 8 84 * 63 8 10 1 311421 Fruit and Vegetable Canning 333 139 5 8 168 Q 0 0 4 13.5 312 Beverage and Tobacco Products 780 479 8 18 201 9 40 0 25 5.8 3121 Beverages 665 413 4 Q 182 8 16 0 25 5.6 3122 Tobacco 115

107

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 * 311221 Wet Corn Milling 179 6,746 * * 51 * 4 0 9 0 31131 Sugar Manufacturing 82 968 1 * 17 * 1 * 20 0 3114 Fruit and Vegetable Preserving and Specialty Food 169 9,708 * * 123 * * 0 4 0 3115 Dairy Product 121 10,079 * * 80 * * 0 1 0 3116 Animal Slaughtering and Processing 226 17,545 1 1 141 * 0 0 12 0 312 Beverage and Tobacco Products 107

108

Table 11.1 Electricity: Components of Net Demand, 2010;  

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

1.1 Electricity: Components of Net Demand, 2010; 1.1 Electricity: Components of Net Demand, 2010; Level: National and Regional Data; Row: NAICS Codes; Column: Electricity Components; Unit: Million Kilowatthours. Total Sales and Net Demand NAICS Transfers Onsite Transfers for Code(a) Subsector and Industry Purchases In(b) Generation(c) Offsite Electricity(d) Total United States 311 Food 75,652 21 5,666 347 80,993 3112 Grain and Oilseed Milling 16,620 0 3,494 142 19,972 311221 Wet Corn Milling 7,481 0 3,213 14 10,680 31131 Sugar Manufacturing 1,264 0 1,382 109 2,537 3114 Fruit and Vegetable Preserving and Specialty Foods 9,258 0 336 66 9,528 3115 Dairy Products 9,585 2 38 22 9,602 3116 Animal Slaughtering and Processing 20,121 15 19 0 20,155 312 Beverage and Tobacco Products

109

table10.7_02.xls  

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

7 Number of Establishments with Capability to Switch Electricity to Alternative Energy Sources, 2002; 7 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 0 55 11.4 311221 Wet Corn Milling 49 W W W 0 0 0 0 0 0 1.2 31131 Sugar 77 8 74 W 4 W W 0 0 W 1.1 311421 Fruit and Vegetable Canning 468 37 443 Q 34 0 0 13 0 0 10.4 312 Beverage and Tobacco Products 1,595 70 1,556

110

China's Industrial Carbon Dioxide Emissions in Manufacturing...  

NLE Websites -- All DOE Office Websites (Extended Search)

China's Industrial Carbon Dioxide Emissions in Manufacturing Subsectors and in Selected Provinces Title China's Industrial Carbon Dioxide Emissions in Manufacturing Subsectors and...

111

4th Cybersecurity Framework Workshop: Overview  

Science Conference Proceedings (OSTI)

... under a specific scenario – an electric utility. • The electricity subsector has created several guidelines, standards, and ...

2013-09-17T23:59:59.000Z

112

Documentation of Calculation Methodology, Input data, and Infrastructure for the Home Energy Saver Web Site  

E-Print Network (OSTI)

5-digit ZIP code to a specific utility service territory.data. Utility Listing Methods – Accept state or ZIP codea ZIP code, users are asked to select their utility from a

2005-01-01T23:59:59.000Z

113

Table 4.2 Offsite-Produced Fuel Consumption, 2010  

Annual Energy Outlook 2012 (EIA)

Fuel Oil Fuel Oil(c) Natural Gas(d) NGL(e) Coal and Breeze Other(f) 327993 Mineral Wool 39 12 0 * 24 * 0 3 * 331 Primary Metals 1,328 412 1 9 537 3 23 291 53 331111 Iron and...

114

NIST.gov - Computer Security Division - Computer Security ...  

Science Conference Proceedings (OSTI)

... PIV Implementation, Daniel Wood, Treasury; Electricity Subsector Cybersecurity ... Basic Input/Output System (BIOS) Security - Andrew Regenscheid ...

115

Private Sector Outreach and Partnerships | Department of Energy  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

associations representing energy subsectors, including the American Petroleum Institute (API), American Gas Association (AGA), and North American Electric Reliability Corporation...

116

RSE Table 10.12 Relative Standard Errors for Table 10.12  

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

Energy Sources(b)" ,,,"Coal Coke" "NAICS"," ","Total"," ","Not","Electricity","Natural","Distillate","Residual",,"and" "Code(a)","Subsector and...

117

Cybersecurity Framework Supporting Documents  

Science Conference Proceedings (OSTI)

... 28, 2013. Discussion Draft - Illustrative Example, ICS Profile for the Electricity Subsector, August 30, 2013. DRAFT Outline ...

2013-10-29T23:59:59.000Z

118

Manufacturing Energy Consumption Survey (MECS) - Analysis ...  

U.S. Energy Information Administration (EIA)

The gross output for the petroleum and coal products subsector grew by about 3 percent, ... Manufacturing Energy Consumption Survey, MECS Definition of Fuel Use, ...

119

RFI Comments - SafeGov  

Science Conference Proceedings (OSTI)

... CIGIE), and sector coordinating councils such as Electricity Sub-Sector Coordinating Council will be important entities to help orient stakeholders ...

2013-04-10T23:59:59.000Z

120

China's sustainable energy future: Scenarios of energy and carbon emissions (Summary)  

E-Print Network (OSTI)

Natural Gas.. 22 Power Generation .subsector. Power generation use of natural gas is subject toof natural gas-fired and non-fossil fuel power generation in

2004-01-01T23:59:59.000Z

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


121

Framework Working Example 1  

Science Conference Proceedings (OSTI)

... 2, KNOW, Asset Management, Hardware Device/Software Inventory, ISO/IEC 27001 ISO/IEC 27002 HITRUST NERC CIP Electricity Sub-sector ...

2013-07-05T23:59:59.000Z

122

RFI Comments - Tacoma Public Utilities  

Science Conference Proceedings (OSTI)

... devices insecure due to lack of necessary support for basic security 38 ... Because of the critical nature of the 40 electricity subsector's service delivery ...

2013-04-11T23:59:59.000Z

123

Released: October 2009  

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

"Code(a)","Subsector and Industry","Generation","Cogeneration(b)","Other Biomass)(c)","Other(d)" ,,"Total United States" 311,"Food",4563,4249,"*",313 3112," Grain and...

124

Electricity demand analysis in different sectors: a case study of Iran.  

E-Print Network (OSTI)

??The objective of this thesis is to estimate the main determinants of electricity demand in Iran for various subsectors (residential, industrial, agricultural and public) using… (more)

Pourazarm, Elham

2012-01-01T23:59:59.000Z

125

China's Energy and Carbon Emissions Outlook to 2050  

E-Print Network (OSTI)

Furnace) 1 in iron & steel industry will increase over timecase of iron and steel and cement industries in particular,intensive industry subsectors such as cement, steel and

Zhou, Nan

2011-01-01T23:59:59.000Z

126

Industrial Sector Energy Conservation Programs in the People's Republic of China during the Seventh Five-Year Plan (1986-1990)  

E-Print Network (OSTI)

Subsector The iron and steel industry accounted for roughlyn importance, as in the steel industries in other countries.furnaces China's iron and steel industry uses approximately

Zhiping, L.

2010-01-01T23:59:59.000Z

127

,,,"with Any"," Steam Turbines Supplied by Either Conventional...  

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

Turbines Supplied by Heat Recovered from High-Temperature Processes",,,," " ,,,"Cogeneration" "NAICS",,,"Technology" "Code(a)","Subsector and Industry","Establishments(b)","in...

128

Statistics Canada Energy Data: 2005 - 2009 Statistics Canada...  

Open Energy Info (EERE)

statistics are published on the Statistics Canada website. The data includes: annual energy fuel consumption in the manufacturing sector, by fuel type and by subsectors (2005...

129

Analysis of Long-range Clean Energy Investment Scenarios for Eritrea, East Africa  

E-Print Network (OSTI)

to utilizing excellent wind energy resources as a driver toSubsector Efficiency, (5) Wind Energy Development, and (6)assumed return rate. For wind energy development, we assume

Van Buskirk, Robert D.

2004-01-01T23:59:59.000Z

130

"RSE Table N11.1. Relative Standard Errors for Table N11.1;...  

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

1. Relative Standard Errors for Table N11.1;" " Unit: Percents." " "," " "NAICS"," "," ",,"Residual","Distillate",,"LPG and",,"Coke"," " "Code(a)","Subsector and...

131

3219," Other Wood Products",41,43,0,58  

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

"Code(a)","Subsector and Industry","Generation","Cogeneration(b)","Other Biomass)(c)","Other(d)" ,,"Total United States" 311,"Food",7,7,0,38 311221," Wet Corn...

132

" Row: NAICS Codes (3-Digit Only); Column...  

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

l","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)","Fact...

133

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

Annual Energy Outlook 2012 (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...

134

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

Gasoline and Diesel Fuel Update (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...

135

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

Gasoline and Diesel Fuel Update (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...

136

" Level: National Data and Regional Totals...  

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

"," ",,"Residual","Distillate",,"LPG and",,"Coke"," ","Row" "Code(a)","Subsector and Industry","Total","Electricity","Fuel Oil","Fuel Oil(b)","Natural Gas(c)","NGL(d)","Coal",...

137

" Row: NAICS Codes;" " ...  

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

Only","Other than","and","Any","from Only","Other than","and" "Code(a)","Subsector and Industry","Electricity(b)","Local Utility(c)","Local Utility(d)","Other Sources","Natural...

138

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

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

and",,"Coke and"," ","of Energy Sources","Row" "Code(a)","Subsector and Industry","Source(b)","Electricity(c)","Fuel Oil","Fuel Oil(d)","Gas(e)","NGL(f)","Coal","...

139

" Row: NAICS Codes;" " ...  

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

than","and","Any","from Only","Other than","and","Row" "Code(a)","Subsector and Industry","Electricity(b)","Local Utility(c)","Local Utility(d)","Other Sources","Natural...

140

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

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

sidual","Distillate",,"LPG and",,"Coke and",,"of Energy Sources" "Code(a)","Subsector and Industry","Source(b)","Electricity(c)","Fuel Oil","Fuel Oil(d)","Natural...

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


141

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

E-Print Network (OSTI)

of China‘s iron and steel industry. ? Int. J. Productionof China‘s iron and steel industry. ? Int. J. ProductionAfter the iron and steel sub-sector, the industries with the

Aden, Nathaniel T.

2010-01-01T23:59:59.000Z

142

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

E-Print Network (OSTI)

Total embodied energy was highest for the hotel subsector,School Hotel The total non-operational embodied energy ofEnergy, Reference Case) Million Tonnes CO2 Hospital Hotel

Fridley, David G.

2008-01-01T23:59:59.000Z

143

Table N8.3. Average Prices of Purchased Electricity, Natural...  

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

y(c)","Total","Utility(b)","Local Utility(c)","Row" "Code(a)","Subsector and Industry","(kWh)","(kWh)","(kWh)","(1000 cu ft)","(1000 cu ft)","(1000 cu ft)","(million...

144

" Level: National Data and Regional Totals...  

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

(million","Other(e)","Row" "Code(a)","Subsector and Industry","(trillion Btu)","(million kWh)","(million bbl)","(million bbl)","cu ft)","(million bbl)","short tons)","short...

145

Agency datasets monthly list | Data.gov  

NLE Websites -- All DOE Office Websites (Extended Search)

or filter the data set by state or county , industry sectors and sub-sectors, annual facility emission thresholds, and greenhouse gas type. For more information on the GHG...

146

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

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

","Row" "Code(a)","Subsector and Industry","Source(b)","Fuel Oil","Fuel Oil(c)","Natural Gas(d)","NGL(e)","Coal","and Breeze","Other(f)","Factors" ,,"Total United States" ,"RSE...

147

" Generation, by Program Sponsorship, Industry Group, Selected"  

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

Number of Establishments by Total Inputs of Energy for Heat, Power, and Electricity" Number of Establishments by Total Inputs of Energy for Heat, Power, and Electricity" " Generation, by Program Sponsorship, Industry Group, Selected" " Industries, and Type of Energy-Management Program, 1994: Part 2" ,,,," Type of Sponsorship of Management Programs" ,,,,,"(1992 through 1994)" ,," " ,,,,,,"Federal, State, or" ,,"No Energy",,"Electric Utility",,"Local Government","Third Party","RSE" "SIC",,"Management","Any Type of","Sponsored","Self-Sponsored","Sponsored","Sponsored","Row" "Code(a)"," Industry Group and Industry","Program(b)","Sponsorship","Involvement","Involvement","Involvement","Involvement","Factors"

148

Page not found | Department of Energy  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

81 - 8990 of 9,640 results. 81 - 8990 of 9,640 results. Download Policy Flash 2012-32 Attached is Policy Flash 2012-32 Acquisition Guide Chapter 17.1 - Interagency Acquisitions, Interagency Transactions and Interagency Agreements http://energy.gov/management/downloads/policy-flash-2012-32 Download Electricity Subsector Cybersecurity Capability Maturity Model (May 2012) The Electricity Subsector Cybersecurity Capability Maturity Model (ES-C2M2), which allows electric utilities and grid operators to assess their cybersecurity capabilities and prioritize their... http://energy.gov/oe/downloads/electricity-subsector-cybersecurity-capability-maturity-model-may-2012 Download Smart Grid Investment Grant Program- Progress Report (July 2012) The SGIG program is structured as a public-private partnership to

149

Cybersecurity Risk Management Process (RMP) | Department of Energy  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

(RMP) (RMP) Cybersecurity Risk Management Process (RMP) The 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 tailored for the electricity subsector. The NIST Special Publication (SP) 800-39, Managing Information Security Risk, provides the foundational methodology for this document. The NIST Interagency Report (NISTIR) 7628, Guidelines for Smart Grid Cyber Security, and NERC critical infrastructure cybersecurity standards further refine the

150

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

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

2. Fuel Consumption, 1998;" 2. Fuel Consumption, 1998;" " Level: National and Regional Data; " " Row: NAICS Codes; Column: Energy Sources;" " Unit: Trillion Btu." " "," "," ",," "," "," "," "," "," "," "," ",," " " "," ",,,,,,,,,,"RSE" "NAICS"," "," ","Net","Residual","Distillate",,"LPG and",,"Coke"," ","Row" "Code(a)","Subsector and Industry","Total","Electricity(b)","Fuel Oil","Fuel Oil(c)","Natural Gas(d)","NGL(e)","Coal","and Breeze","Other(f)","Factors"

151

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

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

2 Fuel Consumption, 2010;" 2 Fuel Consumption, 2010;" " Level: National and Regional Data; " " Row: NAICS Codes; Column: Energy Sources;" " Unit: Trillion Btu." " "," "," ",," "," "," "," "," "," "," " " "," " "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 Breeze","Other(f)"

152

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

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

2 Fuel Consumption, 2002;" 2 Fuel Consumption, 2002;" " Level: National and Regional Data; " " Row: NAICS Codes; Column: Energy Sources;" " Unit: Trillion Btu." " "," "," ",," "," "," "," "," "," "," "," ",," " " "," ",,,,,,,,,,"RSE" "NAICS"," "," ","Net","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"

153

RSE Table 3.5 Relative Standard Errors for Table 3.5  

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

5 Relative Standard Errors for Table 3.5;" 5 Relative Standard Errors for Table 3.5;" " Unit: Percents." " "," "," "," "," "," "," "," ","Waste",," " " "," "," ","Blast"," "," ","Pulping Liquor"," ","Oils/Tars" "NAICS"," "," ","Furnace/Coke","Waste","Petroleum","or","Wood Chips,","and Waste" "Code(a)","Subsector and Industry","Total","Oven Gases","Gas","Coke","Black Liquor","Bark","Materials"

154

" Row: NAICS Codes; Column: Electricity Components;"  

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

1 Electricity: Components of Net Demand, 2002;" 1 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"

155

Table N13.3. Electricity: Sales to Utility and Nonutility Purchasers, 1998  

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

3. Electricity: Sales to Utility and Nonutility Purchasers, 1998;" 3. Electricity: Sales to Utility and Nonutility Purchasers, 1998;" " 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"

156

Argonne National Laboratory 9700 S. Cass Avenue  

E-Print Network (OSTI)

and vehicle (battery or FCV) cost #12;Transition issues for biofuels focus on building the fuel supply chain applicability across all transport subsectors, but low-carbon biofuel supplies could be a major constraint for conventional liquid fuels => biofuel costs become competitive. · But constraints on biomass supply lead

Kemner, Ken

157

Energy Efficiency Indicators Methodology Booklet  

E-Print Network (OSTI)

hotel), and those that by their nature consume little energy (energy use per subsector or building type within the service sector, such as retail, office, hotel,Hotel Office TWh Air Conditioning Space Heating Cooking & Water Heating Lighting Appliances Other Appliances TVs Washing Machines Commercial EJ Residential Refrigerators Energy

Sathaye, Jayant

2010-01-01T23:59:59.000Z

158

" Row: NAICS Codes; Column: Electricity Components;"  

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

1. Electricity: Components of Net Demand, 1998;" 1. Electricity: Components of Net Demand, 1998;" " Level: National and Regional Data; " " Row: NAICS Codes; Column: Electricity Components;" " Unit: Million Kilowatthours." " "," ",,,,,," " " "," ",,,,"Sales and","Net Demand","RSE" "NAICS"," ",,,"Total Onsite","Transfers","for","Row" "Code(a)","Subsector and Industry","Purchases","Transfers In(b)","Generation(c)","Offsite","Electricity(d)","Factors" ,,"Total United States"

159

"RSE Table N5.1. Relative Standard Errors for Table N5.1;"  

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

1. Relative Standard Errors for Table N5.1;" 1. Relative Standard Errors for Table N5.1;" " Unit: Percents." " "," "," "," "," "," "," "," ","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"

160

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; 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 2,119 8 547 Conventional Boiler Use 84 71 17 1,281 8 129 CHP and/or Cogeneration Process 0 62 6 838 1 417 Direct Uses-Total Process 2,639 62 52 2,788 39 412 Process Heating 379 59 19 2,487 32 345 Process Cooling and Refrigeration

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


161

table8.1_02.xls  

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

1 Number of Establishments by Participation in Energy-Management Activity, 2002 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 the Following Types of Activities 120,362 80,348 -- -- -- 1 Energy Audits 165,216 35,494 14,845 15,890 4,760 2.3 Direct Electricity Load Control 171,940 28,770 13,652 9,986 5,132 2.5 Special Rate Schedule (c)

162

Table 5.4 End Uses of Fuel Consumption, 2010;  

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

4 End Uses of Fuel Consumption, 2010; 4 End Uses of Fuel Consumption, 2010; 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 2,886 79 130 5,211 69 868 Indirect Uses-Boiler Fuel 44 46 19 2,134 10 572 Conventional Boiler Use 44 20 4 733 3 72 CHP and/or Cogeneration Process -- 26 15 1,401 7 500 Direct Uses-Total Process 2,304 26 54 2,623 29 289 Process Heating 318 25 14 2,362 24 280 Process Cooling and Refrigeration

163

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 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) Total United States 311 - 339 ALL MANUFACTURING INDUSTRIES TOTAL FUEL CONSUMPTION 977,338 40 22 5,357 21 46 Indirect Uses-Boiler Fuel 24,584 21 4 2,059 2 25 Conventional Boiler Use 24,584 11 3

164

table5.3_02  

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

3 End Uses of Fuel Consumption, 2002; 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 ALL MANUFACTURING INDUSTRIES RSE Column Factors: NF 1 2.4 1.1 1.4 1 TOTAL FUEL CONSUMPTION 966,231 33 24 5,641 26 53 3.4 Indirect Uses-Boiler Fuel 6,714 20 6 2,105 2 35 5.3 Conventional Boiler Use

165

table4.3_02.xls  

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

Offsite-Produced Fuel Consumption, 2002; Offsite-Produced Fuel Consumption, 2002; Level: National and Regional Data; Row: Values of Shipments and Employment Sizes; Column: Energy Sources; Unit: Trillion Btu. RSE Economic Residual Distillate Natural LPG and Coke and Row Characteristic(a) Total Electricity(b) Fuel Oil Fuel Oil(c) Gas(d) NGL(e) Coal Breeze Other(f) Factors Total United States RSE Column Factors: 0.6 0.6 1.3 2.2 0.7 1.4 1.5 0.6 1 Value of Shipments and Receipts (million dollars) Under 20 1,276 437 15 50 598 W 47 W 97 14.5 20-49 1,258 417 28 22 590 W 112 W 72 6.1 50-99 1,463 401 17 W 731 7 185 W 97 4.9 100-249 2,041 571 43 17 968 8 253 7 175 4.6 250-499 1,962 475 54 W 826 W 326 W 255 5.6 500 and Over 3,971 618 38 W 2,077 37 259 W 607 1.5 Total 11,970

166

Table 3.3 Fuel Consumption, 2010;  

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

3 Fuel Consumption, 2010; 3 Fuel Consumption, 2010; Level: National and Regional Data; Row: Values of Shipments and Employment Sizes; Column: Energy Sources; Unit: Trillion Btu. Economic Net Residual Distillate LPG and Coke and Characteristic(a) Total Electricity(b) Fuel Oil Fuel Oil(c) Natural Gas(d) NGL(e) Coal Breeze Other(f) Total United States Value of Shipments and Receipts (million dollars) Under 20 1,148 314 6 53 446 14 25 Q 291 20-49 1,018 297 13 22 381 18 97 5 185 50-99 1,095 305 7 13 440 6 130 9 186 100-249 1,728 411 16 11 793 7 131 7 353 250-499 1,916 391 16 11 583 3 185 5 722 500 and Over 7,323 720 21 21 2,569 21 300 348 3,323 Total 14,228 2,437 79 130 5,211 69 868 376 5,059 Employment Size Under 50 1,149 305 12 45 565 21 31

167

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

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

3.3 Fuel Consumption, 2006; 3.3 Fuel Consumption, 2006; Level: National and Regional Data; Row: Values of Shipments and Employment Sizes; Column: Energy Sources; Unit: Trillion Btu. Economic Net Residual Distillate LPG and Coke and Characteristic(a) Total Electricity(b) Fuel Oil Fuel Oil(c) Natural Gas(d) NGL(e) Coal Breeze Other(f) Total United States Value of Shipments and Receipts (million dollars) Under 20 1,139 367 23 45 535 14 21 3 131 20-49 1,122 333 13 19 530 8 93 5 122 50-99 1,309 349 22 17 549 10 157 8 197 100-249 2,443 607 25 19 994 11 263 10 512 250-499 2,092 413 53 13 633 4 244 3 730 500 and Over 7,551 781 115 17 2,271 31 240 344 3,752 Total 15,657 2,851 251 129 5,512 79 1,016 374 5,445 Employment Size Under 50 1,103 334 10 45 550 10

168

table3.3_02.xls  

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

Fuel Consumption, 2002; Fuel Consumption, 2002; Level: National and Regional Data; Row: Values of Shipments and Employment Sizes; Column: Energy Sources; Unit: Trillion Btu. RSE Economic Net Residual Distillate Natural LPG and Coke and Row Characteristic(a) Total Electricity(b) Fuel Oil Fuel Oil(c) Gas(d) NGL(e) Coal Breeze Other(f) Factors Total United States RSE Column Factors: 0.6 0.7 1.3 2.1 0.7 1.4 1.5 0.7 0.9 Value of Shipments and Receipts (million dollars) Under 20 1,312 436 15 50 598 W 47 W 132 13.9 20-49 1,465 407 28 22 590 W 112 W 289 6.9 50-99 1,598 394 17 W 731 7 185 W 237 4.5 100-249 2,385 561 43 17 972 8 253 7 525 4.2 250-499 2,598 458 57 W 826 W 326 W 906 5.4 500 and Over 6,914 584 47 21 2,077 55 259 530 3,342 1.5 Total 16,273 2,840

169

List of Manufacturing Groups Displayed in the 1998 Manufacturing Energy  

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

21 manufacturing subsectors (3-digit NAICS codes); 21 manufacturing subsectors (3-digit NAICS codes); 311 Food 312 Beverage and Tobacco Products 313 Textile Mills 314 Textile Product Mills 315 Apparel 316 Leather and Allied Products 321 Wood Products 322 Paper 323 Printing and Related Support 324 Petroleum and Coal Products 325 Chemicals 326 Plastics and Rubber Products 327 Nonmetallic Mineral Products 331 Primary Metals 332 Fabricated Metal Products 333 Machinery 334 Computer and Electronic Products 335 Electrical Equip., Appliances, and Components 336 Transportation Equipment 337 Furniture and Related Products 339 Miscellaneous 6 industry groups (4-digit NAICS codes); 3212 Veneer, Plywood, and Engineered Woods 3219 Other Wood Products 3272 Glass and Glass Products 3312 Steel Products from Purchased Steel 3313 Alumina and Aluminum

170

EIA - The National Energy Modeling System: An Overview 2003-Industrial  

Gasoline and Diesel Fuel Update (EIA)

Industrial Demand Module Industrial Demand Module The National Energy Modeling System: An Overview 2003 Industrial Demand Module Figure 7. Industrial Demand Module Structure. Need help, contact the National Energy Information Center at 202-586-8800. Economic Subsectors Within the IDM Table. Need help, contact the National Energy Information Center at 202-586-8800. Industrial Demand Module Table. Need help, contact the National Energy Information Center at 202-586-8800. Fuel Consuming Activities for the Energy-Intensive Manufacturing Subsectors Table. Need help, contact the National Energy Information Center at 202-586-8800. The industrial demand module (IDM) forecasts energy consumption for fuels and feedstocks for nine manufacturing industries and six nonmanufactur- ing

171

Measuring Changes in Energy Efficiency for the Annual Energy Outlook 2002  

Gasoline and Diesel Fuel Update (EIA)

Changes in Energy Efficiency Changes in Energy Efficiency for the Annual Energy Outlook 2002 by Steven H. Wade This paper describes the construction of an aggregate energy efficiency index based on projections of sectoral and subsector energy consumption and subsector-specific energy service indicators. The results are compared with the ratio energy to real gross domestic product, which typically is pre- sented as a measure of energy intensity. Introduction Energy efficiency and conservation are currently impor- tant components of the debate about the direction of future energy policy. Measuring the actual energy effi- ciency of the U.S. economy is a daunting task because of the immense data requirements for a proper calculation. Appropriate data are difficult to obtain, and as a result historical descriptions of the economy usually are sum- marized in two energy intensity measures: (1) energy

172

Page not found | Department of Energy  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

51 - 1860 of 31,917 results. 51 - 1860 of 31,917 results. Article 16 Projects To Advance Hydropower Technology U.S. Department Energy Secretary Steven Chu and U.S. Department of the Interior Secretary Ken Salazar announced nearly $17 million in funding over the next three years for research and development projects to advance hydropower technology. The list of 16 projects in 11 different states can be found here. http://energy.gov/articles/16-projects-advance-hydropower-technology Download Notice of Publication of Electricity Subsector Cybersecurity Risk Management Process: Federal Register Notice Volume 77, No. 100- May 23, 2012 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...

173

Private Sector Outreach and Partnerships | Department of Energy  

NLE Websites -- All DOE Office Websites (Extended Search)

Private Sector Outreach and Partnerships Private Sector Outreach and Partnerships Private Sector Outreach and Partnerships ISER's partnerships with the private sector are a strength which has enabled the division to respond to the needs of the sector and the nation. The division's domestic capabilities have been greatly enhanced by the relationships that have been created over years of collaborations with companies from all parts the sector, including electricity, oil, and natural gas. 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 private sector. The relationships ISER maintains with energy sector owners and operators and public associations representing energy subsectors, including the American

174

Joint Egypt/United States report on Egypt/United States cooperative energy assessment. Volume 3 of 5 Vols. Annexes 2--5  

SciTech Connect

The principal objectives of the energy assessment project for Egypt are to develop understanding of the current status of the principal energy users in Egypt's industrial and agricultural sectors; to estimate the energy demand and efficiency for each selected subsector within these major sectors; to identify opportunities for fuel type changes, technology switches, or production pattern changes which might increase the efficiency with which Egypt's energy is used both now and in the future; and based on options identified, to forecast energy efficiencies for selected Egyptian subsectors for the years 1985 and 2000. The areas studied in the industrial sector are the iron and steel, aluminum, fertilizer, chemical, petrochemical, cement, textile, and automotive manufacturing industries. Those studied in the agricultural sector concern drainage and irrigation, mechanization, and food processing. Additional information in 4 annexes include industrial/agricultural sector options; residential/commercial, transportation, and fossil fuels supply options.

1979-04-01T23:59:59.000Z

175

Effect on air and water emissions of energy conservation in industry  

DOE Green Energy (OSTI)

Environmental emissions for five large energy-consuming industries plus others are estimated for four US energy system scenarios for 1985 and 2000. Emissions are estimated by specifying fuel mixes to steam boilers and direct heat, combustion efficiencies, shifts in the relative shares of alternative industrial processes use of industrial cogenerators, and penetration of pollution-control technologies. Analyses show that emissions do not vary significantly among scenarios principally because of increased coal use and the reduced penetration rate of advanced pollution-control technologies in the low-energy-demand scenarios. Within scenarios, emissions from the chemical and iron and steel subsectors dominate all aggregate estimates. Hydrocarbon and carbon monoxide process emission coefficients for the chemical subsector must be improved.

Raskin, P D; Rosen, R A

1977-07-01T23:59:59.000Z

176

" Row: NAICS Codes; Column: Energy-Consumption Ratios;"  

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

N7.1. Consumption Ratios of Fuel, 1998;" N7.1. Consumption Ratios of Fuel, 1998;" " 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"

177

"RSE Table C2.1. Relative Standard Errors for Table C2.1;"  

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

C2.1. Relative Standard Errors for Table C2.1;" C2.1. Relative Standard Errors for Table C2.1;" " Unit: Percents." " "," "," "," "," "," "," "," "," "," ",," " " "," ","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",4,0,3,0,1,0,2,6

178

Released: March 2013  

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

3 Electricity: Components of Onsite Generation, 2010;" 3 Electricity: Components of Onsite Generation, 2010;" " Level: National and Regional Data; " " Row: NAICS Codes; Column: Onsite-Generation Components;" " Unit: Million Kilowatthours." " "," ",,,"Renewable Energy" " "," ",,,"(excluding Wood" "NAICS"," ","Total Onsite",,"and" "Code(a)","Subsector and Industry","Generation","Cogeneration(b)","Other Biomass)(c)","Other(d)" ,,"Total United States" 311,"Food",5666,5414,81,171 3112," Grain and Oilseed Milling",3494,3491,"Q",2

179

" Row: NAICS Codes; Column: Energy-Consumption Ratios;"  

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

1 Consumption Ratios of Fuel, 2002;" 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"

180

RSE Table 3.2 Relative Standard Errors for Table 3.2  

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

2 Relative Standard Errors for Table 3.2;" 2 Relative Standard Errors for Table 3.2;" " Unit: Percents." " "," "," ",," "," "," "," "," "," "," ",," " " "," " "NAICS"," "," ","Net","Residual","Distillate","Natural","LPG and",,"Coke"," " "Code(a)","Subsector and Industry","Total","Electricity(b)","Fuel Oil","Fuel Oil(c)","Gas(d)","NGL(e)","Coal","and Breeze","Other(f)" ,,"Total United States" 311,"Food",4,5,25,20,5,27,6,0,10

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


181

Originally Released: July 2009  

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

2 Nonfuel (Feedstock) Use of Combustible Energy, 2006;" 2 Nonfuel (Feedstock) Use of Combustible Energy, 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",,"Fuel Oil","Fuel Oil(b)","Natural Gas(c)",,"NGL(d)",,"Coal","and Breeze","Other(e)"

182

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

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

3.4 Number of Establishments by Fuel Consumption, 2006;" 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)"

183

Table 11.3 Electricity: Components of Onsite Generation, 2002  

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

3 Electricity: Components of Onsite Generation, 2002;" 3 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

184

Table 2.2 Nonfuel (Feedstock) Use of Combustible Energy, 2002  

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

2 Nonfuel (Feedstock) Use of Combustible Energy, 2002;" 2 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"

185

Table N13.2. Electricity: Components of Onsite Generation, 1998  

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

2. Electricity: Components of Onsite Generation, 1998;" 2. Electricity: Components of Onsite Generation, 1998;" " 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:",1,0.8,1.5,0.9

186

" Row: NAICS Codes (3-Digit Only); Column: Energy Sources;"  

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

2. Nonfuel (Feedstock) Use of Combustible Energy, 1998;" 2. Nonfuel (Feedstock) Use of Combustible Energy, 1998;" " Level: National Data; " " Row: NAICS Codes (3-Digit Only); Column: Energy Sources;" " Unit: Trillion Btu." " "," "," "," "," "," "," "," "," "," "," ",," " " "," ",,,,,,,,,"RSE" "NAICS"," "," ","Residual","Distillate",,"LPG and",,"Coke"," ","Row" "Code(a)","Subsector and Industry","Total","Fuel Oil","Fuel Oil(b)","Natural Gas(c)","NGL(d)","Coal","and Breeze","Other(e)","Factors"

187

Originally Released: August 2009  

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

August 2009" 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"

188

"RSE Table C3.1. Relative Standard Errors for Table C3.1;"  

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

C3.1. Relative Standard Errors for Table C3.1;" C3.1. Relative Standard Errors for Table C3.1;" " Unit: Percents." " "," "," ",," "," "," "," "," "," "," ",," " " "," ","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"

189

" Row: NAICS Codes; Column: Electricity Components;"  

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

1.1 Electricity: Components of Net Demand, 2010;" 1.1 Electricity: Components of Net Demand, 2010;" " Level: National and Regional Data; " " Row: NAICS Codes; Column: Electricity Components;" " Unit: Million Kilowatthours." " "," " " "," ",,,"Total ","Sales and","Net Demand" "NAICS"," ",,"Transfers ","Onsite","Transfers","for" "Code(a)","Subsector and Industry","Purchases","In(b)","Generation(c)","Offsite","Electricity(d)" ,,"Total United States" 311,"Food",75652,21,5666,347,80993

190

" 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;" 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)"

191

Released: March 2013  

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

2 Nonfuel (Feedstock) Use of Combustible Energy, 2010;" 2 Nonfuel (Feedstock) Use of Combustible Energy, 2010;" " 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","Fuel Oil","Fuel Oil(b)","Natural Gas(c)","NGL(d)","Coal","and Breeze","Other(e)"

192

Table 7.9 Expenditures for Purchased Energy Sources, 2002  

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

9 Expenditures for Purchased Energy Sources, 2002;" 9 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"

193

Released: July 2009  

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

2 Relative Standard Errors for Table 2.2, 2006;" 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 Oil(b)","Natural Gas(c)","NGL(d)","Coal","and Breeze","Other(e)" ,,"Total United States" 311,"Food",18.4,"X",16.5,22.4,95.1,"X",0,0.1

194

" Level: National Data;" " Row: NAICS Codes;"  

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

11 Number of Establishments with Capability to Switch Coal to Alternative Energy Sources, 2006;" 11 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." ,,"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 Oil","Fuel Oil","LPG","Other(f)"

195

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

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

2 Offsite-Produced Fuel Consumption, 2002;" 2 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"

196

Released: March 2013  

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

5 Selected Byproducts in Fuel Consumption, 2010;" 5 Selected Byproducts in Fuel Consumption, 2010;" " 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"

197

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

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

4 Number of Establishments by Offsite-Produced Fuel Consumption, 2002;" 4 Number of Establishments by Offsite-Produced Fuel Consumption, 2002;" " Level: National Data; " " Row: NAICS Codes; Column: Energy Sources;" " Unit: Establishment Counts." " "," "," ",," "," "," "," "," "," "," "," ",," " " "," ","Any",,,,,,,,,"RSE" "NAICS"," ","Energy",,"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"

198

" Level: National Data;" " Row: NAICS Codes;"  

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

7 Number of Establishments with Capability to Switch Electricity to Alternative Energy Sources, 2006; " 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." ,,"Electricity Receipts(b)",,,"Alternative Energy Sources(c)" ,,,,,,,,,,"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)"," "

199

RSE Table 7.9 Relative Standard Errors for Table 7.9  

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

9 Relative Standard Errors for Table 7.9;" 9 Relative Standard Errors for Table 7.9;" " Unit: Percents." " "," "," ",," "," "," "," "," "," "," ",," " " "," " "NAICS"," "," ",,"Residual","Distillate","Natural ","LPG and",,"Coke"," " "Code(a)","Subsector and Industry","Total","Electricity","Fuel Oil","Fuel Oil(b)","Gas(c)","NGL(d)","Coal","and Breeze","Other(e)" ,,"Total United States" 311,"Food",4,4,24,21,5,23,7,0,20

200

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

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

4 Number of Establishments by Fuel Consumption, 2002;" 4 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"

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


201

Released: June 2010  

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

9 Expenditures for Purchased Energy Sources, 2006;" 9 Expenditures for Purchased Energy Sources, 2006;" " Level: National and Regional Data;" " Row: NAICS Codes; Column: Energy Sources;" " Unit: Million U.S. Dollars." " "," "," ",," "," "," "," "," "," "," "," " " "," " "NAICS"," "," ",,"Residual","Distillate",,"LPG and",,"Coke"," " "Code(a)","Subsector and Industry","Total","Electricity","Fuel Oil","Fuel Oil(b)","Natural Gas(c)","NGL(d)","Coal","and Breeze","Other(e)"

202

" 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;" 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)"

203

" Row: NAICS Codes; Column: Electricity Components;"  

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

1.1 Electricity: Components of Net Demand, 2006;" 1.1 Electricity: Components of Net Demand, 2006;" " Level: National and Regional Data; " " Row: NAICS Codes; Column: Electricity Components;" " Unit: Million Kilowatthours." " "," " " "," ",,,"Total ","Sales and","Net Demand" "NAICS"," ",,"Transfers ","Onsite","Transfers","for" "Code(a)","Subsector and Industry","Purchases","In(b)","Generation(c)","Offsite","Electricity(d)" ,,"Total United States" 311,"Food",73242,309,4563,111,78003

204

Released: May 2013  

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

9 Expenditures for Purchased Energy Sources, 2010;" 9 Expenditures for Purchased Energy Sources, 2010;" " Level: National and Regional Data;" " Row: NAICS Codes; Column: Energy Sources;" " Unit: Million U.S. Dollars." " "," "," ",," "," "," "," "," "," "," " " "," " "NAICS"," "," ",,"Residual","Distillate",,"LPG and",,"Coke"," " "Code(a)","Subsector and Industry","Total","Electricity","Fuel Oil","Fuel Oil(b)","Natural Gas(c)","NGL(d)","Coal","and Breeze","Other(e)"

205

Released: July 2009  

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

2 Relative Standard Errors for Table 4.2, 2006;" 2 Relative Standard Errors for Table 4.2, 2006;" " Unit: Percents." " "," "," ",," "," "," "," "," "," "," "," " " "," " "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","Other(f)" ,,"Total United States" 311,"Food",4.7,4.1,21.5,13.1,7.1,15.7,1.1,0,18

206

Released: July 2009  

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

1 Relative Standard Errors for Table 1.1, 2006;" 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 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"

207

Released: October 2009  

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

5 Electricity: Sales to Utility and Nonutility Purchasers, 2006;" 5 Electricity: Sales to Utility and Nonutility Purchasers, 2006;" " Level: National and Regional Data; " " Row: NAICS Codes;" " Column: Utility and Nonutility Purchasers;" " Unit: Million Kilowatthours." " "," " " "," ","Total of" "NAICS"," ","Sales and","Utility","Nonutility" "Code(a)","Subsector and Industry","Transfers Offsite","Purchaser(b)","Purchaser(c)" ,,"Total United States" 311,"Food",111,86,25 3112," Grain and Oilseed Milling",72,51,21

208

"RSE Table C4.1. Relative Standard Errors for Table C4.1;"  

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

C4.1. Relative Standard Errors for Table C4.1;" C4.1. Relative Standard Errors for Table C4.1;" " Unit: Percents." " "," "," ",," "," "," "," "," "," "," ",," " " "," ","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" ,

209

Released: July 2009  

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

2 Relative Standard Errors for Table 1.2, 2006;" 2 Relative Standard Errors for Table 1.2, 2006;" " Unit: Percents." " "," "," "," "," "," "," "," "," "," "," " " "," "," ",," "," ",," "," ",," ","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)"

210

Released: March 2013  

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

5 Electricity: Sales to Utility and Nonutility Purchasers, 2010;" 5 Electricity: Sales to Utility and Nonutility Purchasers, 2010;" " Level: National and Regional Data; " " Row: NAICS Codes;" " Column: Utility and Nonutility Purchasers;" " Unit: Million Kilowatthours." " "," " " "," ","Total of" "NAICS"," ","Sales and","Utility","Nonutility" "Code(a)","Subsector and Industry","Transfers Offsite","Purchaser(b)","Purchaser(c)" ,,"Total United States" 311,"Food",347,168,179 3112," Grain and Oilseed Milling",142,6,136

211

"RSE Table C1.1. Relative Standard Errors for Table C1.1;"  

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

.1. Relative Standard Errors for Table C1.1;" .1. Relative Standard Errors for Table C1.1;" " Unit: Percents." " "," "," "," "," "," "," "," "," "," "," " " "," ","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)"

212

RSE Table 1.2 Relative Standard Errors for Table 1.2  

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

2 Relative Standard Errors for Table 1.2;" 2 Relative Standard Errors for Table 1.2;" " Unit: Percents." " "," "," "," "," "," "," "," "," "," "," " " "," "," ",," "," ",," "," ",," ","Shipments" "NAICS"," ",,"Net","Residual","Distillate","Natural","LPG and",,"Coke and"," ","of Energy Sources" "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)"

213

Framework for Evaluating Cyber Security Posture for Power Delivery Systems  

Science Conference Proceedings (OSTI)

While many asset owners and operators are performing self-assessments of their control systems, the methods used vary widely across the electric sector. This lack of consistent criteria and metrics makes it difficult to benchmark and compare the cyber security posture of power delivery systems.The objective of this technical update is to develop an evaluation framework that uses both the Department of Energy (DOE) Electricity Subsector Cybersecurity Capability Maturity Model (ES-C2M2) ...

2013-11-28T23:59:59.000Z

214

Generalized integrability conditions and target space geometry  

E-Print Network (OSTI)

In some higher dimensional nonlinear field theories integrable subsectors with infinitely many conservation laws have been identified by imposing additional integrability conditions. Originally, the complex eikonal equation was chosen as integrability condition, but recently further generalizations have been proposed. Here we show how these new integrability conditions may be derived from the geometry of the target space and, more precisely, from the Noether currents related to a certain class of target space transformations.

C. Adam; J. Sanchez-Guillen

2005-08-01T23:59:59.000Z

215

Factor Decomposition of Sectoral Growth in South Africa, 1970-2007  

E-Print Network (OSTI)

  2000, which  is  negative).  There  is a particularly strong correlation  in this regard since 2000, for the whole economy  and  for  manufacturing,  which  is  interesting  as  it  follows  the  period  of  rapid  trade  liberalisation...  in the mid? to late?1990s. This might suggest either that subsectors that were  less  affected  by  import  penetration  (for  instance,  because  there was  less  dramatic  tariff  liberalisation  affecting  them) were  able  to  grow  relatively  fast, or  that  sectors...

Tregenna, Fiona

216

" Level: National Data;" " Row: NAICS Codes;"  

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

1 Number of Establishments with Capability to Switch Coal to Alternative Energy Sources, 2002;" 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." ,,"Coal(b)",,,"Alternative Energy Sources(c)" ,,,,,,,,,,,"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"

217

Emissions of CO/sub 2/ to the atmosphere due to U. S. A. fossil fuel consumption  

SciTech Connect

Analysis and projection of carbon dioxide emitted to the atmosphere are estimated based on the Brookhaven reference energy system. Some new results are given on carbon dioxide contribution to the atmosphere from US fossil fuel consumption by different sectors including residential, commercial, industrial and transportation. The total weight of carbon as carbon dioxide emitted to the atmosphere and the additional CO/sub 2/ concentration over background by different subsectors in the years 1977, 1980, 1985, 1990, 2000 and 2020 are presented.

Dang, V.D.; Steinberg, M.

1980-06-01T23:59:59.000Z

218

" Level: National Data and Regional Totals;"  

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

6 Capability to Switch Electricity to Alternative Energy Sources, 2006; " 6 Capability to Switch Electricity to Alternative Energy Sources, 2006; " " Level: National Data and Regional Totals;" " Row: NAICS Codes, Value of Shipments and Employment Sizes;" " Column: Energy Sources;" " Unit: Million Kilowatthours." ,,"Electricity Receipts",,,"Alternative Energy Sources(b)" ,,,,,,,,,,"Coal Coke" "NAICS"," ","Total"," ","Not","Natural","Distillate","Residual",,,"and" "Code(a)","Subsector and Industry","Receipts(c)","Switchable","Switchable","Gas","Fuel Oil","Fuel Oil","Coal","LPG","Breeze","Other(d)"," "

219

Conservation laws in Skyrme-type models  

E-Print Network (OSTI)

The zero curvature representation of Zakharov and Shabat has been generalized recently to higher dimensions and has been used to construct non-linear field theories which either are integrable or contain integrable submodels. The Skyrme model, for instance, contains an integrable subsector with infinitely many conserved currents, and the simplest Skyrmion with baryon number one belongs to this subsector. Here we use a related method, based on the geometry of target space, to construct a whole class of theories which are either integrable or contain integrable subsectors (where integrability means the existence of infinitely many conservation laws). These models have three-dimensional target space, like the Skyrme model, and their infinitely many conserved currents turn out to be Noether currents of the volume-preserving diffeomorphisms on target space. Specifically for the Skyrme model, we find both a weak and a strong integrability condition, where the conserved currents form a subset of the algebra of volume-preserving diffeomorphisms in both cases, but this subset is a subalgebra only for the weak integrable submodel.

C. Adam; J. Sanchez-Guillen; A. Wereszczynski

2006-10-20T23:59:59.000Z

220

Conservation laws in Skyrme-type models  

Science Conference Proceedings (OSTI)

The zero curvature representation of Zakharov and Shabat [V. E. Zakharov and A. B. Shabat, Soviet Phys. JETP 34, 62 (1972)] has been generalized recently to higher dimensions and has been used to construct nonlinear field theories which are integrable or contain integrable submodels. The Skyrme model, for instance, contains an integrable subsector with infinitely many conserved currents, and the simplest Skyrmion with baryon number 1 belongs to this subsector. Here we use a related method, based on the geometry of target space, to construct a whole class of theories which are integrable or contain integrable subsectors (where integrability means the existence of infinitely many conservation laws). These models have three-dimensional target space, like the Skyrme model, and their infinitely many conserved currents turn out to be Noether currents of the volume-preserving diffeomorphisms on target space. Specifically for the Skyrme model, we find both weak and strong integrability conditions, where the conserved currents form a subset of the algebra of volume-preserving diffeomorphisms in both cases, but this subset is a subalgebra only for the weak integrable submodel.

Adam, C.; Sanchez-Guillen, J.; Wereszczynski, A. [Departamento de Fisica de Particulas, Universidad de Santiago de Compostela, Santiago de Compostela, Galicia E-15782 (Spain) and Instituto Galego de Fisica de Altas Enerxias (IGFAE), Universidad de Santiago de Compostela, Santiago de Compostela, Galicia E-15782 (Spain); Institute of Physics, Jagiellonian University, Reymonta 4, 30-059 Cracow (Poland)

2007-03-15T23:59:59.000Z

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


221

2006 Update of Business Downtime Costs  

SciTech Connect

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.

Hinrichs, Mr. Doug [Sentech, Inc.; Goggin, Mr. Michael [Sentech, Inc.

2007-01-01T23:59:59.000Z

222

2006 Update of Business Downtime Costs  

SciTech Connect

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.

Hinrichs, Mr. Doug [Sentech, Inc.; Goggin, Mr. Michael [Sentech, Inc.

2007-01-01T23:59:59.000Z

223

Case studies of the potential effects of carbon taxation on the stone, clay, and glass industry  

SciTech Connect

This case study focuses on the potential for a carbon tax ($25 and $100 per metric ton of carbon) to reduce energy use and associated carbon dioxide (CO{sub 2}) emissions in three subsectors of the stone, clay, and glass industry: hydraulic cement, glass and glass products, and other products. A conservation supply curve analysis found that (1) opportunities for reducing fossil fuel use in the subsectors are limited (15% reduction under $100 tax) and (2) the relationship between the tax and reduced CO{sub 2} emissions is nonlinear and diminishing. Because cement manufacturing produces a significant amount of CO{sub 2}, this subsector was analyzed. A plant-level analysis found more opportunities to mitigate CO{sub 2} emissions; under a $100 tax, fossil fuel use would decrease 52%. (A conservative estimate lies between 15% and 52%). It also confirmed the nonlinear relationship, suggesting significant benefits could result from small taxes (32% reduction under $25 tax). A fuel share analysis found the cement industry could reduce carbon loading 11% under a $100 tax if gas were substituted for coal. Under a $100 tax, cement demand would decrease 17% and its price would increase 32%, a substantial increase for a material commodity. Overall, CO{sub 2} emissions from cement manufacturing would decrease 24--33% under a $100 tax and 10--18% under a $25 tax. Much of the decrease would result from the reduced demand for cement.

Bock, M.J.; Boyd, G.A. [Argonne National Lab., IL (United States). Environmental Assessment and Information Sciences Div.; Rosenbaum, D.I. [Nebraska Univ., Lincoln, NE (United States). Dept. of Economics; Ross, M.H. [Michigan Univ., Ann Arbor, MI (United States). Dept. of Physics

1992-12-01T23:59:59.000Z

224

Case studies of the potential effects of carbon taxation on the stone, clay, and glass industry  

SciTech Connect

This case study focuses on the potential for a carbon tax ($25 and $100 per metric ton of carbon) to reduce energy use and associated carbon dioxide (CO[sub 2]) emissions in three subsectors of the stone, clay, and glass industry: hydraulic cement, glass and glass products, and other products. A conservation supply curve analysis found that (1) opportunities for reducing fossil fuel use in the subsectors are limited (15% reduction under $100 tax) and (2) the relationship between the tax and reduced CO[sub 2] emissions is nonlinear and diminishing. Because cement manufacturing produces a significant amount of CO[sub 2], this subsector was analyzed. A plant-level analysis found more opportunities to mitigate CO[sub 2] emissions; under a $100 tax, fossil fuel use would decrease 52%. (A conservative estimate lies between 15% and 52%). It also confirmed the nonlinear relationship, suggesting significant benefits could result from small taxes (32% reduction under $25 tax). A fuel share analysis found the cement industry could reduce carbon loading 11% under a $100 tax if gas were substituted for coal. Under a $100 tax, cement demand would decrease 17% and its price would increase 32%, a substantial increase for a material commodity. Overall, CO[sub 2] emissions from cement manufacturing would decrease 24--33% under a $100 tax and 10--18% under a $25 tax. Much of the decrease would result from the reduced demand for cement.

Bock, M.J.; Boyd, G.A. (Argonne National Lab., IL (United States). Environmental Assessment and Information Sciences Div.); Rosenbaum, D.I. (Nebraska Univ., Lincoln, NE (United States). Dept. of Economics); Ross, M.H. (Michigan Univ., Ann Arbor, MI (United States). Dept. of Physics)

1992-12-01T23:59:59.000Z

225

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

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

3 Consumption Ratios of Fuel, 2006; 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 50-99 830.1 5.9 2.7 100-249 1,130.0 6.7 3.1 250-499 1,961.4 7.6 3.6 500 and Over 3,861.9 9.0 3.6 Total 1,278.4 6.9 3.1 311 FOOD Value of Shipments and Receipts (million dollars) Under 20 979.3 10.3

226

table6.4_02.xls  

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

4 Consumption Ratios of Fuel, 2002; 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 6.8 3.3 5 100-249 905.8 7.9 3.8 3.6 250-499 1,407.1 11.1 5.1 4.3 500-999 1,999.6 12.4 5.9 5.6 1000 and Over 1,597.7 8.5 3.9 2.5 Total 1,172.2 8.9 4.2 2 311 FOOD Employment Size Under 50 893.5 6.6 2.4

227

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

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

4 Consumption Ratios of Fuel, 2006; 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 7.7 3.6 500-999 2,328.9 10.6 4.5 1000 and Over 1,415.5 5.7 2.5 Total 1,278.4 6.9 3.1 311 FOOD Employment Size Under 50 1,266.8 8.3 3.2 50-99 1,587.4 9.3 3.6 100-249 931.9 3.6 1.5 250-499 1,313.1 6.3

228

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

Gasoline and Diesel Fuel Update (EIA)

3 Consumption Ratios of Fuel, 2010; 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 50-99 832.0 4.9 2.3 100-249 1,313.4 6.2 2.8 250-499 1,905.2 7.4 3.6 500 and Over 4,225.4 7.5 3.1 Total 1,449.6 6.4 2.8 311 FOOD Value of Shipments and Receipts (million dollars) Under 20 576.6 5.9

229

table5.4_02  

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

4 End Uses of Fuel Consumption, 2002; 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 3,297 208 141 5,794 103 1,182 3.3 Indirect Uses-Boiler Fuel 23 127 25 2,162 8 776 5.5 Conventional Boiler Use 11 76 25 1,306 8 255 5.6 CHP and/or Cogeneration Process 12 51 10 857 * 521 3.7 Direct Uses-Total Process 2,624

230

table6.3_02.xls  

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

3 Consumption Ratios of Fuel, 2002; 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) Under 20 281.0 3.9 2.2 3 20-49 583.7 6.1 3.0 4.6 50-99 889.2 8.1 3.8 4.9 100-249 1,268.8 8.7 4.1 4.6 250-499 2,146.6 11.2 5.3 7.6 500 and Over 3,807.1 12.5 5.4 2.3 Total 1,172.2 8.9 4.2 2 311 FOOD Value of Shipments and Receipts

231

"NAICS",,"per Employee","of Value Added","of Shipments"  

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

1 Relative Standard Errors for Table 6.1;" 1 Relative Standard Errors for Table 6.1;" " Unit: Percents." ,,,,"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",3.8,4.3,4.1 3112," Grain and Oilseed Milling",8.2,5.8,5.6 311221," Wet Corn Milling",0,0,0 31131," Sugar Manufacturing",0,0,0 3114," Fruit and Vegetable Preserving and Specialty Foods ",7.3,6.7,6.2

232

" Level: National Data and Regional Totals;"  

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

8 Capability to Switch Distillate Fuel Oil to Alternative Energy Sources, 2006; " 8 Capability to Switch Distillate Fuel Oil to Alternative Energy Sources, 2006; " " Level: National Data and Regional Totals;" " Row: NAICS Codes, Value of Shipments and Employment Sizes;" " Column: Energy Sources;" " Unit: Thousand Barrels." ,,"Distillate Fuel Oil",,,"Alternative Energy Sources(b)" ,,,,,,,,,,"Coal Coke" "NAICS"," ","Total"," ","Not","Electricity","Natural","Residual",,,"and" "Code(a)","Subsector and Industry","Consumed(c)","Switchable","Switchable","Receipts(d)","Gas","Fuel Oil","Coal","LPG","Breeze","Other(e)"

233

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;" 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 Breeze","Other(e)" ,,"Total United States" 311,"Food",31,0,91,35,0,0,0,47 311221," Wet Corn Milling",0,0,0,0,0,0,0,0 31131," Sugar ",0,0,0,0,0,0,0,0 311421," Fruit and Vegetable Canning",1,0,0,0,0,0,0,8

234

" Level: National Data;" " Row: NAICS Codes;"  

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

9 Number of Establishments with Capability to Switch Distillate Fuel Oil to Alternative Energy Sources, 2002;" 9 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." ,,"Distillate Fuel Oil(b)",,,"Alternative Energy Sources(c)" ,,,,,,,,,,"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"

235

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;" 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 Oil","Fuel Oil","LPG","Other(e)" ,,"Total United States" 311,"Food",6,18,5,0,20,85,29,20,0 311221," Wet Corn Milling",0,0,0,0,0,0,0,0,0 31131," Sugar ",0,0,0,0,0,0,0,0,0

236

" Level: National Data;" " Row: NAICS Codes;"  

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

3 Number of Establishments with Capability to Switch LPG to Alternative Energy Sources, 2006;" 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." ,,"LPG(b)",,,"Alternative Energy Sources(c)" ,,,,,,,,,,"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)"

237

" Level: National Data;" " Row: NAICS Codes;"  

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

3 Number of Establishments with Capability to Switch LPG to Alternative Energy Sources, 2002;" 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." ,,"LPG(b)",,,"Alternative Energy Sources(c)" ,,,,,,,,,,"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"

238

" Level: National Data and Regional Totals;"  

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

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

239

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

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

1 Fuel Consumption, 2006;" 1 Fuel Consumption, 2006;" " Level: National and Regional Data; " " Row: NAICS Codes; Column: Energy Sources;" " Unit: Physical Units or Btu." ,,,,,,,,,,,,"Coke" ,,,,"Net",,"Residual","Distillate","Natural Gas(d)",,"LPG and","Coal","and Breeze" "NAICS",,"Total",,"Electricity(b)",,"Fuel Oil","Fuel Oil(c)","(billion",,"NGL(e)","(million","(million","Other(f)" "Code(a)","Subsector and Industry","(trillion Btu)",,"(million kWh)",,"(million bbl)","(million bbl)","cu ft)",,"(million bbl)","short tons)","short tons)","(trillion Btu)"

240

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;" 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 Industry","Consumed(d)","Switchable","Switchable","Receipts(e)","Gas","Fuel Oil","Fuel Oil","Coal","Breeze","Other(f)" ,,"Total United States" 311,"Food",8,17,8,20,21,43,34,35,37,29 311221," Wet Corn Milling",0,0,0,0,0,0,0,0,0,0

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


241

Released: June 2010  

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

1 Relative Standard Errors for Table 10.11;" 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 Oil","Fuel Oil","LPG","Other(f)" ,,"Total United States" 311,"Food",5.4,0.9,4.9,9.1,1,2,0,0,3.3 3112," Grain and Oilseed Milling",7.9,2.9,8.4,9.1,2.9,5.9,"X",0,9.1

242

" Level: National Data and Regional Totals;"  

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

2 Capability to Switch LPG to Alternative Energy Sources, 2002; " 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." ,,"LPG",,,"Alternative Energy Sources(b)" ,,,,,,,,,,"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"

243

" Level: National Data and Regional Totals;"  

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

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

244

3219," Other Wood Products",0,0,0  

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

5 Relative Standard Errors for Table 11.5;" 5 Relative Standard Errors for Table 11.5;" " Unit: Percents." " "," " " "," ","Total of" "NAICS"," ","Sales and","Utility","Nonutility" "Code(a)","Subsector and Industry","Transfers Offsite","Purchaser(b)","Purchaser(c)" ,,"Total United States" 311,"Food",25,34,35 311221," Wet Corn Milling",29,40,7 31131," Sugar ",0,0,0 311421," Fruit and Vegetable Canning",0,0,0 312,"Beverage and Tobacco Products",0,0,0 3121," Beverages",0,0,0 3122," Tobacco ",0,0,0 313,"Textile Mills",3,0,52

245

" Level: National Data and Regional Totals;"  

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

2 Capability to Switch Natural Gas to Alternative Energy Sources, 2006;" 2 Capability to Switch Natural Gas to Alternative Energy Sources, 2006;" " Level: National Data and Regional Totals;" " Row: NAICS Codes, Value of Shipments and Employment Sizes;" " Column: Energy Sources;" " Unit: Billion Cubic Feet." ,,"Natural Gas",,,"Alternative Energy Sources(b)" ,,,,,,,,,,"Coal Coke" "NAICS"," ","Total"," ","Not","Electricity","Distillate","Residual",,,"and" "Code(a)","Subsector and Industry","Consumed(c)","Switchable","Switchable","Receipts(d)","Fuel Oil","Fuel Oil","Coal","LPG","Breeze","Other(e)"

246

,,,"Natural Gas(b)",,,," Alternative Energy Sources(c)"  

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

10.3 Relative Standard Errors for Table 10.3;" 10.3 Relative Standard Errors for Table 10.3;" " Unit: Percents." ,,,"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",2,8.6,4,21.7,13.8,22.3,59.7,15.9,"X",24.9

247

RSE Table N3.1 and N3.2. Relative Standard Errors for Tables N3.1 and N3.2  

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

N3.1 and N3.2. Relative Standard Errors for Tables N3.1 and N3.2;" N3.1 and N3.2. Relative Standard Errors for Tables N3.1 and N3.2;" " 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 Breeze","Other(f)" ,,"Total United States" , 311,"Food",1,1,2,3,1,1,0,0,1

248

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

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

2 Fuel Consumption, 2006;" 2 Fuel Consumption, 2006;" " Level: National and Regional Data; " " Row: NAICS Codes; Column: Energy Sources;" " Unit: Trillion Btu." "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 Breeze","Other(f)" ,,"Total United States" 311,"Food",1186,,251,,26,16,635,,3,,147,1,107 3112," Grain and Oilseed Milling",317,,53,,2,1,118,,"*",,114,0,30

249

NAICS Search | Department of Energy  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

NAICS Search NAICS Search NAICS Search The North American Industry Classification System (NAICS) is the standard used by Federal statistical agencies in classifying businesses. 10000 21000 22000 23000 31000 32000 33000 42000 44000 45000 48000 49000 51000 53000 54000 56000 61000 62000 81000 92000 NAICS uses six-digit codes at the most detailed level, with the first two digits representing the largest business sector, the third designating a subsector, the fourth designating the industry group, and the fifth showing the particular industry. Use the documents below, which are labeled by series, to see Department of Energy facilities that have historically procured goods/services in that

250

" Row: NAICS Codes; Column: Energy-Consumption Ratios;"  

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

1 Consumption Ratios of Fuel, 2006;" 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",879.8,5,2.2 3112," Grain and Oilseed Milling",6416.6,17.5,5.7

251

311221," Wet Corn Milling",0,0,"X",0  

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

3 Relative Standard Errors for Table 11.3;" 3 Relative Standard Errors for Table 11.3;" " Unit: Percents." " "," ",,,"Renewable Energy" " "," ",,,"(excluding Wood" "NAICS"," ","Total Onsite",,"and" "Code(a)","Subsector and Industry","Generation","Cogeneration(b)","Other Biomass)(c)","Other(d)" ,,"Total United States" 311,"Food",2.8,1.1,86.8,37.8 3112," Grain and Oilseed Milling",0.7,0.7,"X",0 311221," Wet Corn Milling",0,0,"X",0 31131," Sugar Manufacturing",0,0,"X",0 3114," Fruit and Vegetable Preserving and Specialty Foods ",1.2,1.2,"X",44.1

252

" Level: National Data and Regional Totals;"  

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

4 Capability to Switch Residual Fuel Oil to Alternative Energy Sources, 2006;" 4 Capability to Switch Residual Fuel Oil to Alternative Energy Sources, 2006;" " Level: National Data and Regional Totals;" " Row: NAICS Codes, Value of Shipments and Employment Sizes;" " Column: Energy Sources;" " Unit: Thousand Barrels." ,,"Residual Fuel Oil",,,"Alternative Energy Sources(b)" ,,,,,,,,,,"Coal Coke" "NAICS"," ","Total"," ","Not","Electricity","Natural","Distillate",,,"and" "Code(a)","Subsector and Industry","Consumed(c)","Switchable","Switchable","Receipts(d)","Gas","Fuel Oil","Coal","LPG","Breeze","Other(e)"

253

Released: July 2009  

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

1 Relative Standard Errors for Table 4.1, 2006;" 1 Relative Standard Errors for Table 4.1, 2006;" " Unit: Percents." " "," "," ",," "," "," "," "," "," "," "," " " "," ",,,,,,,,"Coke" " "," "," ",,"Residual","Distillate","Natural Gas(d)","LPG and","Coal","and Breeze"," " "NAICS"," ","Total","Electricity(b)","Fuel Oil","Fuel Oil(c)","(billion","NGL(e)","(million","(million","Other(f)" "Code(a)","Subsector and Industry","(trillion Btu)","(million kWh)","(million bbl)","(million bbl)","cu ft)","(million bbl)","short tons)","short tons)","(trillion Btu)"

254

" Level: National Data;" " Row: NAICS Codes;"  

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

5 Number of Establishments with Capability to Switch Residual Fuel Oil to Alternative Energy Sources, 2006;" 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)"

255

Industrial Distributed Energy: Combined Heat & Power  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

(DOE) (DOE) Industrial Technology Program (ITP) Industrial Distributed Energy: Combined Heat & Power (CHP) Richard Sweetser Senior Advisor DOE's Mid-Atlantic Clean Energy Application Center 32% Helping plants save energy today using efficient energy management practices and efficient new technologies Activities to spur widespread commercial use of CHP and other distributed generation solutions 10% Manufacturing Energy Systems 33% Industries of the Future R&D addressing top priorities in America's most energy-intensive industries and cross-cutting activities applicable to multiple industrial subsectors 25% Industrial Distributed Energy Industrial Technical Assistance DOE ITP FY'11 Budget: $100M Knowledge development and

256

RSE Table 4.1 Relative Standard Errors for Table 4.1  

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

1 Relative Standard Errors for Table 4.1;" 1 Relative Standard Errors for Table 4.1;" " Unit: Percents." " "," " " "," " "NAICS"," "," ",,"Residual","Distillate","Natural","LPG and",,"Coke"," " "Code(a)","Subsector and Industry","Total","Electricity(b)","Fuel Oil","Fuel Oil(c)","Gas(d)","NGL(e)","Coal","and Breeze","Other(f)" ,,"Total United States" 311,"Food",4,5,25,20,5,27,6,0,17 311221," Wet Corn Milling",1,0,0,1,3,0,0,0,0 31131," Sugar ",0,0,0,0,0,0,0,0,0 311421," Fruit and Vegetable Canning",8,11,46,45,8,57,0,0,3

257

" Level: National Data and Regional Totals;"  

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

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

258

Released: August 2009  

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

5 Relative Standard Errors for Table 3.5;" 5 Relative Standard Errors for Table 3.5;" " Unit: Percents." ,,,,,,,,"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",9.1,"X",25,"X","X",6,55.6 3112," Grain and Oilseed Milling",8.9,"X",47.4,"X","X",0,0 311221," Wet Corn Milling",0,"X",0,"X","X",0,"X"

259

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

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

1 Offsite-Produced Fuel Consumption, 2010;" 1 Offsite-Produced Fuel Consumption, 2010;" " Level: National and Regional Data; " " Row: NAICS Codes; Column: Energy Sources;" " Unit: Physical Units or Btu." ,,,,,,,,,"Coke" ,,,,"Residual","Distillate","Natural Gas(d)","LPG and","Coal","and Breeze" "NAICS",,"Total","Electricity(b)","Fuel Oil","Fuel Oil(c)","(billion","NGL(e)","(million","(million","Other(f)" "Code(a)","Subsector and Industry","(trillion Btu)","(million kWh)","(million bbl)","(million bbl)","cu ft)","(million bbl)","short tons)","short tons)","(trillion Btu)"

260

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

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

2 Offsite-Produced Fuel Consumption, 2010;" 2 Offsite-Produced Fuel Consumption, 2010;" " 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","Other(f)" ,,"Total United States" 311,"Food",1113,258,12,22,579,5,182,2,54 3112," Grain and Oilseed Milling",346,57,"*",1,121,"*",126,0,41

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


261

RSE Table 7.6 Relative Standard Errors for Table 7.6  

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

6 Relative Standard Errors for Table 7.6;" 6 Relative Standard Errors for Table 7.6;" " Unit: Percents." " "," " " "," ",,,,,,,,," " "NAICS"," "," ",,"Residual","Distillate","Natural ","LPG and",,"Coke" "Code(a)","Subsector and Industry","Total","Electricity","Fuel Oil","Fuel Oil(b)","Gas(c)","NGL(d)","Coal","and Breeze","Other(e)" ,,"Total United States" 311,"Food",4,5,25,20,5,27,6,0,20 311221," Wet Corn Milling",1,0,0,1,3,0,0,0,0 31131," Sugar ",0,0,0,0,0,0,0,0,0 311421," Fruit and Vegetable Canning",8,11,42,45,8,57,0,0,4

262

" Level: National Data;" " Row: NAICS Codes;"  

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

3 Number of Establishments with Capability to Switch Natural Gas to Alternative Energy Sources, 2006;" 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)"

263

,,"Distillate Fuel Oil(b)",,,"Alternative Energy Sources(c)"  

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

0.9 Relative Standard Errors for Table 10.9;" 0.9 Relative Standard Errors for Table 10.9;" " Unit: Percents." ,,"Distillate Fuel Oil(b)",,,"Alternative Energy Sources(c)" ,,,,,,,,,,"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",8,15,9,21,19,18,0,27,0,41 311221," Wet Corn Milling",0,0,0,0,0,0,0,0,0,0

264

" Level: National Data;" " Row: NAICS Codes;"  

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

9 Number of Establishments with Capability to Switch Distillate Fuel Oil to Alternative Energy Sources, 2006;" 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." ,,"Distillate Fuel Oil(b)",,,"Alternative Energy Sources(c)" ,,,,,,,,,,"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)"

265

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;" 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 Oil","Fuel Oil","LPG","Other(f)" ,,"Total United States" 311,"Food",20,32,21,0,16,68,65,73,0 311221," Wet Corn Milling",0,0,0,0,0,0,0,0,0 31131," Sugar ",0,0,0,0,0,0,0,0,0

266

"RSE Table N13.3. Relative Standard Errors for Table N13.3;"  

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

3. Relative Standard Errors for Table N13.3;" 3. Relative Standard Errors for Table N13.3;" " Unit: Percents." " "," ","Total of" "NAICS"," ","Sales and","Utility","Nonutility" "Code(a)","Subsector and Industry","Transfers Offsite","Purchaser(b)","Purchaser(c)" ,,"Total United States" , 311,"Food",8,9,0 311221," Wet Corn Milling",0,0,0 312,"Beverage and Tobacco Products",0,0,0 313,"Textile Mills",0,0,0 313210," Broadwoven Fabric Mills",0,0,0 314,"Textile Product Mills",90,90,0 315,"Apparel",0,0,0 316,"Leather and Allied Products",0,0,0

267

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

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

2 Offsite-Produced Fuel Consumption, 2006;" 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","Other(f)" ,,"Total United States" 311,"Food",1124,,251,,26,16,635,,3,,147,1,45 3112," Grain and Oilseed Milling",316,,53,,2,1,118,,"*",,114,0,28

268

Released: July 2009  

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

1 Relative Standard Errors for Table 3.1, 2006;" 1 Relative Standard Errors for Table 3.1, 2006;" " Unit: Percents." " "," "," ",," "," "," "," "," "," "," "," " " "," ",,,,,,,,"Coke" " "," "," ","Net","Residual","Distillate","Natural Gas(d)","LPG and","Coal","and Breeze"," " "NAICS"," ","Total","Electricity(b)","Fuel Oil","Fuel Oil(c)","(billion","NGL(e)","(million","(million","Other(f)" "Code(a)","Subsector and Industry","(trillion Btu)","(million kWh)","(million bbl)","(million bbl)","cu ft)","(million bbl)","short tons)","short tons)","(trillion Btu)"

269

Released: June 2010  

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

3 Relative Standard Errors for Table 10.13;" 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 Industry","Consumed(d)","Switchable","Switchable","Receipts(e)","Gas","Fuel Oil","Fuel Oil","Coal","Breeze","Other(f)" ,,"Total United States" 311,"Food",6.9,22.9,9,33.5,29.1,29.3,3.3,"X","X",48.2

270

Originally Released: July 2009  

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

1 Nonfuel (Feedstock) Use of Combustible Energy, 2006;" 1 Nonfuel (Feedstock) Use of Combustible Energy, 2006;" " Level: National and Regional Data; " " Row: NAICS Codes; Column: Energy Sources;" " Unit: Physical Units or Btu." ,,,,,,,,,,,"Coke" ,,,,"Residual","Distillate","Natural Gas(c)",,"LPG and",,"Coal","and Breeze" "NAICS",,"Total",,"Fuel Oil","Fuel Oil(b)","(billion",,"NGL(d)",,"(million","(million","Other(e)" "Code(a)","Subsector and Industry","(trillion Btu)",,"(million bbl)","(million bbl)","cu ft)",,"(million bbl)",,"short tons)","short tons)","(trillion Btu)"

271

" Level: National Data and Regional Totals;"  

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

2 Capability to Switch LPG to Alternative Energy Sources, 2006; " 2 Capability to Switch LPG to Alternative Energy Sources, 2006; " " Level: National Data and Regional Totals;" " Row: NAICS Codes, Value of Shipments and Employment Sizes;" " Column: Energy Sources;" " Unit: Thousand Barrels." ,,"LPG",,,"Alternative Energy Sources(b)" ,,,,,,,,,,"Coal Coke" "NAICS"," ","Total"," ","Not","Electricity","Natural","Distillate","Residual",,"and" "Code(a)","Subsector and Industry","Consumed(c)","Switchable","Switchable","Receipts(d)","Gas","Fuel Oil","Fuel Oil","Coal","Breeze","Other(e)"

272

"RSE Table C10.1. Relative Standard Errors for Table C10.1;"  

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

1. Relative Standard Errors for Table C10.1;" 1. Relative Standard Errors for Table C10.1;" " Unit: Percents." " "," "," ",,,"Computer","Control of","Processes"," "," "," ",,,,," " " "," ","Computer Control","of Building-Wide","Environment(b)","or Major","Energy-Using","Equipment(c)","Waste","Heat","Recovery","Adjustable -","Speed","Motors" "NAICS"," " "Code(a)","Subsector and Industry","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"

273

Released: June 2010  

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

3 Relative Standard Errors for Table 10.23;" 3 Relative Standard Errors for Table 10.23;" " Unit: Percents." ,,,,"Reasons that Made LPG Unswitchable" " "," ",,,,,,,,,,,,," " ,,"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","Environmental","Contract ","Storage for ","Another","Columns F, G, " "Code(a)","Subsector and Industry","as a Fuel","LPG Fuel Use","Another Fuel","the Products","Fuel Supply","Restrictions(b)","in Place(c)","Alternative Fuels(d)","Reason","H, I, J, and K","Don't Know"

274

Released: June 2010  

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

2 Relative Standard Errors for Table 10.22;" 2 Relative Standard Errors for Table 10.22;" " Unit: Percents." ,,,,"Reasons that Made Coal Unswitchable" " "," ",,,,,,,,,,,,," " ,,"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","Environmental","Contract ","Storage for ","Another","Columns F, G, " "Code(a)","Subsector and Industry","as a Fuel","Coal Fuel Use","Another Fuel","the Products","Fuel Supply","Restrictions(b)","in Place(c)","Alternative Fuels(d)","Reason","H, I, J, and K","Don't Know"

275

Assessment of the Energy Impacts of Outside Air in the Commercial Sector  

SciTech Connect

The enormous quantity of energy consumed by U.S. commercial buildings places a significant burden on the energy supply and is a potential source of economic strain. To address this, the DOE Building Technologies Program has established the goal of developing market-viable zero energy buildings by 2025. This study focuses on the effects of outside air, and considers various outside air sources, types of building construction, building subsectors, and climates. Based on the information about energy consumption attributed to outside air, it identifies topics for further research that have the greatest potential to achieve energy savings.

Benne, K.; Griffith, B.; Long, N.; Torcellini, P.; Crawley, D.; Logee, T.

2009-04-01T23:59:59.000Z

276

Electricity Sector Liberalisation and Innovation: An Analysis of the UK Patenting Activities  

E-Print Network (OSTI)

on the energy sector. They search energy technology patent titles in the US Patent and Trademark Office (PTO) bibliographic database (PTO, 1998) using keywords.3 Also, patent abstracts of two energy technology sub-sectors were searched using key words... 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 £ m il li on s (2 00 6 pr ic es ) Other Power and storage Renewables Fossil Fuels Energy Efficiency Figure 3: Government energy...

Jamasb, Tooraj; Pollitt, Michael G.

277

Industrial Energy Use and Energy Efficiency in Developing Countries  

E-Print Network (OSTI)

The industrial sector accounts for over 50% of energy used in developing countries. Growth in this sector has been over 4.5% per year since 1980. Energy intensity trends for four energy-intensive sub-sectors (iron and steel, chemicals, building materials, and pulp and paper) are reviewed. Scenarios of future industrial sector energy use in developing countries show that this region will dominate world industrial energy use in 2020. Growth is expected to be about 3.0% per year in a business-as-usual case, but can be reduced using state-of-the art or advanced technologies. Polices to encourage adoption of these technologies are briefly discussed.

Price, L.; Martin, N.; Levine, M. D.; Worrell, E.

1996-04-01T23:59:59.000Z

278

Predictivity of models with spontaneously broken non-Abelian discrete flavor symmetries  

E-Print Network (OSTI)

In a class of supersymmetric flavor models predictions are based on residual symmetries of some subsectors of the theory such as those of the charged leptons and neutrinos. However, the vacuum expectation values of the so-called flavon fields generally modify the K\\"ahler potential of the setting, thus changing the predictions. We derive simple analytic formulae that allow us to understand the impact of these corrections on the predictions for the masses and mixing parameters. Furthermore, we discuss the effects on the vacuum alignment and on flavor changing neutral currents. Our results can also be applied to non--supersymmetric flavor models.

Chen, Mu-Chun; Omura, Yuji; Ratz, Michael; Staudt, Christian

2013-01-01T23:59:59.000Z

279

" Level: National Data;" " Row: NAICS Codes;"  

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

5 Number of Establishments with Capability to Switch Residual Fuel Oil to Alternative Energy Sources, 2002;" 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." ,,"Residual Fuel Oil(b)",,,"Alternative Energy Sources(c)" ,,,,,,,,,,"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"

280

RSE Table N4.1 and N4.2. Relative Standard Errors for Tables N4.1 and N4.2  

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

N4.1 and N4.2. Relative Standard Errors for Tables N4.1 and N4.2;" N4.1 and N4.2. Relative Standard Errors for Tables N4.1 and N4.2;" " Unit: Percents." " "," "," ",," "," "," "," "," "," "," ",," " "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","Other(f)" ,,"Total United States" , 311,"Food",1,1,2,3,1,1,0,0,1

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


281

Released: June 2010  

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

6 Relative Standard Errors for Table 7.6;" 6 Relative Standard Errors for Table 7.6;" " Unit: Percents." " "," "," ",," "," "," "," "," "," "," " " "," ",,,,,,,,"Coke" " "," "," ",,"Residual","Distillate","Natural Gas(c)","LPG and","Coal","and Breeze"," " "NAICS"," ","Total","Electricity","Fuel Oil","Fuel Oil(b)","(billion","NGL(d)","(million","(million","Other(e)" "Code(a)","Subsector and Industry","(trillion Btu)","(million kWh)","(million bbl)","(million bbl)","cu ft)","(million bbl)","short tons)","short tons)","(trillion Btu)"

282

Released: August 2009  

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

RSE Table 3.6 Relative Standard Errors for Table 3.6;" RSE Table 3.6 Relative Standard Errors for Table 3.6;" " Unit: Percents." ,,"Selected Wood and Wood-Related Products" ,,,"Biomass" ,,,,,,"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)"

283

"RSE Table N13.1. Relative Standard Errors for Table N13.1;"  

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

1. Relative Standard Errors for Table N13.1;" 1. Relative Standard Errors for Table N13.1;" " Unit: Percents." " "," " " "," ",,,,"Sales and","Net Demand" "NAICS"," ",,,"Total Onsite","Transfers","for" "Code(a)","Subsector and Industry","Purchases","Transfers In(b)","Generation(c)","Offsite","Electricity(d)" ,,"Total United States" , 311,"Food",1,1,1,8,1 311221," Wet Corn Milling",0,0,0,0,0 312,"Beverage and Tobacco Products",4,0,1,0,4 313,"Textile Mills",2,8,7,0,2 313210," Broadwoven Fabric Mills",3,0,22,0,3 314,"Textile Product Mills",11,73,8,90,11

284

RSE Table N1.1 and N1.2. Relative Standard Errors for Tables N1.1 and N1.2  

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

1 and N1.2. Relative Standard Errors for Tables N1.1 and N1.2;" 1 and N1.2. Relative Standard Errors for Tables N1.1 and N1.2;" " Unit: Percents." " "," "," "," "," "," "," "," "," "," "," " " "," "," ",," "," ",," "," ",," ","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)"

285

"RSE Table N7.1. Relative Standard Errors for Table N7.1;"  

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

N7.1. Relative Standard Errors for Table N7.1;" N7.1. Relative Standard Errors for Table N7.1;" " Unit: Percents." " "," ",,,"Consumption" " "," ",,"Consumption","per Dollar" "NAICS"," ","Consumption","per Dollar","of Value" "Code(a)","Subsector and Industry","per Employee","of Value Added","of Shipments" ,,"Total United States" , 311,"Food",1,1,1 311221," Wet Corn Milling",0,0,0 312,"Beverage and Tobacco Products",8,4,5 313,"Textile Mills",3,2,3 313210," Broadwoven Fabric Mills",3,4,3 314,"Textile Product Mills",7,5,5

286

"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;" 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 Industry","Onsite","Establishments(b)","per Establishment","Onsite","per Establishment" ,,"Total United States" , 311,"Food",2,0,2,1,1 311221," Wet Corn Milling",0,0,0,0,0 312,"Beverage and Tobacco Products",11,0,15,14,14

287

SWERA borrador051110  

Open Energy Info (EERE)

informe nacional informe nacional GEF MEM DGE Preparado por: Ing. Norbert Bons Borrador 14-11-05 SWERA borrador 14-11-2005 1 2 MEM DGE - Fundación Solar Contenido Prefacio 5 Resumen ejecutivo 6 Introducción 7 Datos socioeconómicos 7 Geografía y clima de Guatemala 7 Las energías renovables en Guatemala 9 La situación energética del país 13 Balance de energía de Guatemala 13 Marco institucional del sub-sector eléctrico 14 Ministerio de Energía y Minas 14 Comisión Nacional de Energía 15 Administrador del Mercado Mayorista 15 Autoridad designada para los créditos de carbono 16 Marco regulatorio del sub-sector eléctrico 16 Ley general de electricidad 17 Ley de incentivos para el desarrollo de proyectos de energía renovable 17 Sistema eléctrico 17 Generación 17 Transporte 18 Distribución 19 Mercado eléctrico

288

Manufacturing sector carbon dioxide emissions in nine OECD countries 1973--87: A Divisia index decomposition to changes in fuel mix, emission coefficients, industry structure, energy intensities, and international structure  

DOE Green Energy (OSTI)

In this paper the reduction in energy-related manufacturing carbon dioxide emissions for nine OECD countries in the period 1973 to 1987 is analyzed. Carbon dioxide emissions are estimated from energy use data. The emphasis is on carbon dioxide intensities, defined as emissions divided by value added. The overall manufacturing carbon dioxide intensity for the nine OECD countries was reduced by 42% in the period 1973--1987. Five fuels are specified together with six subsectors of manufacturing. Carbon dioxide emissions are estimated from fossil fuel consumption, employing emissions coefficients for gas, oil and solids. In addition, electricity consumption is specified. For electricity use an emission coefficient index is calculated from the shares of fossil fuels, nuclear power and hydro power used to generate electricity, and the efficiency in electricity generation from these energy sources. A Divisia index approach is used to sort out the contribution to reduced carbon dioxide intensity from different components. The major finding is that the main contribution to reduced carbon dioxide intensity is from the general reduction in manufacturing energy intensity, most likely driven by economic growth and increased energy prices, giving incentives to invest in new technology and new industrial processes. There is also a significant contribution from reduced production in the most carbon dioxide intensive subsectors, and a contribution from higher efficiency in electricity generation together with a larger nuclear power share at the expense of oil. 19 refs., 5 figs., 11 tabs.

Torvanger, A. (Senter for Anvendt Forskning, Oslo (Norway) Lawrence Berkeley Lab., CA (USA))

1990-11-01T23:59:59.000Z

289

The effectiveness of jobs-housing balance as a strategy for reducing traffic congestion: a study of metropolitan Bangkok  

E-Print Network (OSTI)

Bangkok is widely known for its severe traffic congestion. The Thai government advocates the concept of jobs and housing balance (JHB) as a strategy for reducing traffic congestion in Metropolitan Bangkok. The basic idea is to decentralize the jobs to the neighboring provinces so that the commuters would live closer to their workplaces and thereby alleviate traffic congestion. The main purpose of this research is to examine empirically the effectiveness of JHB in reducing the severity of traffic congestion in the Bangkok Metropolitan Region. For this purpose, three data sets derived from the Bangkok Metropolitan Region Extended City Model (BMR-ECM) were obtained from the Office of the Commission for the Management of Land Traffic and the National Statistical Office of Thailand. Travel time index (TTI) was developed to measure congestion. In addition to JHB, a number of land use variables were included in the analysis. They are population density, school density, and job accessibility index. Multiple regression models of TTI as functions of JHB and other variables were estimated at two geographic scales: subsector and traffic analysis zone (TAZ). The study finds JHB is significant in influencing congestion levels in the Bangkok Metropolitan Region. Other influential factors include the population density, school density, and job accessibility. All of these factors are found to be statistically significant in explaining the variation of traffic congestion at the traffic analysis zone level, but not at the subsector level, however.

Lobyaem, Sonchai

2006-08-01T23:59:59.000Z

290

Energy Efficiency Services Sector: Workforce Education and Training Needs  

SciTech Connect

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.

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

2010-03-19T23:59:59.000Z

291

Revised Burnup Code System SWAT: Description and Validation Using Postirradiation Examination Data  

Science Conference Proceedings (OSTI)

The burnup code system Step-Wise Burnup Analysis Code System (SWAT) is revised for use in a burnup credit analysis. An important feature of the revised SWAT is that its functions are achieved by calling validated neutronics codes without any changes to the original codes. This feature is realized with a system function of the operating system, which allows the revised SWAT to be independent of the development status of each code.A package of the revised SWAT contains the latest libraries based on JENDL-3.2 and the second version of the JNDC FP library. These libraries allow us to analyze burnup problems, such as an analysis of postirradiation examination (PIE), using the latest evaluated data of not only cross sections but also fission yield and decay constants.Another function of the revised SWAT is a library generator for the ORIGEN2 code, which is one of the most reliable burnup codes. ORIGEN2 users can obtain almost the same results with the revised SWAT using the library prepared by this function.The validation of the revised SWAT is conducted by calculation of the Organization for Economic Cooperation and Development/Nuclear Energy Agency burnup credit criticality safety benchmark Phase I-B and analyses of PIE data for spent fuel from Takahama Unit 3. The analysis of PIE data shows that the revised SWAT can predict the isotopic composition of main uranium and plutonium with a deviation of 5% from experimental results taken from UO{sub 2} fuels of 17 x 17 fuel assemblies. Many results of fission products including samarium are within a deviation of 10%. This means that the revised SWAT has high reliability to predict the isotopic composition for pressurized water reactor spent fuel.

Suyama, Kenya [Japan Atomic Energy Research Institute (Japan); Mochizuki, Hiroki [Japan Atomic Energy Research Institute (Japan); Kiyosumi, Takehide [Japan Research Institute, Ltd. (Japan)

2002-05-15T23:59:59.000Z

292

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

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

Special Topic: Energy-Related Carbon Dioxide Emissions in U.S. Manufacturing 1 Special Topic: Energy-Related Carbon Dioxide Emissions in U.S. Manufacturing 1 Report #: DOE/EIA-0573(2005) Released Date: November 2006 Next Release Date: Not applicable Energy-Related Carbon Dioxide Emissions in U.S. Manufacturing Mark Schipper 1 , Energy Information Administration (EIA) Abstract 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.

293

Thailand-Status and Potential for the Development of Biofuels and Rural  

Open Energy Info (EERE)

Thailand-Status and Potential for the Development of Biofuels and Rural Renewable Energy Thailand-Status and Potential for the Development of Biofuels and Rural Renewable Energy Agency/Company /Organization Asian Development Bank Sector Energy, Land Focus Area Biomass, - Biofuels, Agriculture Topics Policies/deployment programs, Co-benefits assessment, - Energy Access, Resource assessment, Background analysis Website http://www.adb.org/Documents/R Country Thailand UN Region South-Eastern Asia References Thailand-Status and Potential for the Development of Biofuels and Rural Renewable Energy[1] Thailand-Status and Potential for the Development of Biofuels and Rural Renewable Energy Screenshot Summary "The objectives of this study are to: identify promising areas for investment in the development of the biofuel subsector in Thailand, with due consideration of the country's

294

Global Research Alliance on Agricultural Greenhouse Gases | Open Energy  

Open Energy Info (EERE)

Global Research Alliance on Agricultural Greenhouse Gases Global Research Alliance on Agricultural Greenhouse Gases Jump to: navigation, search Name Global Research Alliance on Agricultural Greenhouse Gases Agency/Company /Organization United States Department of Agriculture Sector Land Focus Area Agriculture Topics GHG inventory, Policies/deployment programs Resource Type Guide/manual, Lessons learned/best practices Website http://globalresearchalliance. References Global Research Alliance on Agricultural Greenhouse Gases [1] Background "The Alliance is a bottom-up network, founded on the voluntary, collaborative efforts of countries. It will coordinate research on agricultural greenhouse gas emission reductions by linking up existing and new research efforts across a range of sub-sectors and work areas. It will

295

"RSE Table N5.2. Relative Standard Errors for Table N5.2;"  

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

2. Relative Standard Errors for Table N5.2;" 2. Relative Standard Errors for Table N5.2;" " Unit: Percents." ,,"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",," " "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)"

296

New Electricity Advisory Committee Reports Delivered to the Department of  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

New Electricity Advisory Committee Reports Delivered to the New Electricity Advisory Committee Reports Delivered to the Department of Energy New Electricity Advisory Committee Reports Delivered to the Department of Energy November 1, 2011 - 9:50am Addthis The Electricity Advisory Committee approved three new reports at their meeting on October 20, 2011. These reports include recommendations on cyber security, storage, and the interdependence of electricity and natural gas. Recommendations on U. S. Grid Security The Electricity Advisory Committee recommends that the Department of Energy take a more active, complementary role in the efforts of the North American Electric Reliability Corporation with respect to the Critical Infrastructure Strategic Roadmap developed by the Electricity Sub-Sector Coordinating Council and approved by the NERC Board of Trustees in November

297

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

Gasoline and Diesel Fuel Update (EIA)

Table 4a Table 4a Page Last Modified: May 2010 Table 4a. Value of Shipments 1 by Selected Industries, 1998, 2002, and 2006 (Billion 2000 Dollars ) Notes: 1. Received or receivable net selling values (exclusive of freight and taxes) of all primary and secondary products shipped, as well as all miscellaneous receipts for contract work performed for others, installation and repair, sales of scrap, and sales of products bought and resold without further processing. Source: U.S. Department of Commerce, Bureau of Economic Analysis (BEA), "Value of Shipments and Price Indexes by Detailed Industry 1998- 2007," Sept 2009. MECS Survey Years NAICS Subsector and Industry 1998 2002 2006 311 Food Manufacturing 430 448 472 312 Beverage and Tobacco Product Manufacturing

298

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

Gasoline and Diesel Fuel Update (EIA)

a a Released Date: May 2006 Page Last Modified: April 2010 Table 3a. Value of Shipments 1 by Selected Industries, 1998, 2002, and 2006 (Current Billion Dollars) Notes: The value received for the complete systems at the company's net billing price, freight-on-board factory, including charges for cooperative advertising and warranties. This does not include excise taxes, freight or transportation charges, or installation charges. Source: U.S. Department of CoSources: U.S. Bureau of the Census, Annual Survey of Manufacturers, Statistics for Industry Groups and Industries, 2000 and 2006 (Sept 2009), 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

299

EIA Energy Efficiency-Table 3e. Gross Output by Selected Industries, 1998,  

Gasoline and Diesel Fuel Update (EIA)

e 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 2002 2006 311 Food Manufacturing 417 444 526 312 Beverage and Tobacco Product Manufacturing 114 128 144 313 Textile Mills 57 45 38 314 Textile Product Mills 31 30 32 315 Apparel Manufacturing 63 40 26 316 Leather and Allied Product Manufacturing 10 6 6 321 Wood Product Manufacturing 91 88 111 322 Paper Manufacturing 153 151 167 323 Printing and Related Support Activities 99 95 99 324 Petroleum and Coal Products Manufacturing 135 212 530 325 Chemical Manufacturing 407 444 639 326 Plastics and Rubber Products Manufacturing 162 169 208 327 Nonmetallic Mineral Product Manufacturing 91 94 126 331 Primary Metal Manufacturing 166 139 230 332 Fabricated Metal Product Manufacturing

300

Energy Information Administration (EIA)- Manufacturing Energy Consumption  

Gasoline and Diesel Fuel Update (EIA)

Chemical Industry Analysis Brief Change Topic: Steel | Chemical Chemical Industry Analysis Brief Change Topic: Steel | Chemical JUMP TO: Introduction | Energy Consumption | Energy Expenditures | Producer Prices and Production | Energy Intensity | Energy Management Activities | Fuel Switching Capacity Introduction The chemical industries are a cornerstone of the U.S. economy, converting raw materials such as oil, natural gas, air, water, metals, and minerals into thousands of various products. Chemicals are key materials for producing an extensive assortment of consumer goods. They are also crucial materials in creating many resources that are essential inputs to the numerous industries and sectors of the U.S. economy.1 The manufacturing sector is classified by the North American Industry Classification System (NAICS) of which the chemicals sub-sector is NAICS

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


301

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

Gasoline and Diesel Fuel Update (EIA)

a 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 1998 2002 2006 311 Food Manufacturing 428 457 538 312 Beverage and Tobacco Product Manufacturing 102 104 125 313 Textile Mills 57 45 39 314 Textile Product Mills 31 32 33 315 Apparel Manufacturing 65 45 30 316 Leather and Allied Product Manufacturing 10 7 6 321 Wood Product Manufacturing 91 88 112 322 Paper Manufacturing 155 153 170 323 Printing and Related Support Activities 100 96 100 324 Petroleum and Coal Products Manufacturing 138 216 549 325 Chemical Manufacturing 417 454 658 326 Plastics and Rubber Products Manufacturing 164 173 211

302

PowerPoint Presentation  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Electricity 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 with other public and private sector partners * Challenge: Develop capabilities to manage dynamic threats and understand cybersecurity posture of the grid * Approach: Develop a maturity model and self-evaluation survey to develop and measure cybersecurity capabilities * Results: A scalable, sector- specific model created in partnership with industry Future Objectives * Strengthen cybersecurity capabilities * Enable consistent evaluation and benchmarking of cybersecurity capabilities * Share knowledge and best practices ES-C2M2 Model Includes 10 Domains ES-C2M2 Facilitated Self-Evaluation v1.0

303

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

Gasoline and Diesel Fuel Update (EIA)

b b Page Last Modified: May 2010 Table 2b. End Uses of Fuel Consumption (Primary 1 Energy) for Selected Industries, 1998, 2002, and 2006 (Trillion Btu) Note: The Btu conversion factors used for primary electricity are 10,197 Btu/KWh, 10,173 Btu/KWh, and 9,919 Btu/KWh for 1998, 2002, and 2006, respectively. Sources: Energy Information Administration, Form EIA-846, Manufacturing Energy Consumption Surveys, 1998, 2002, and 2006. and Monthly Energy Review November 2005, and September 2009 DOE/EIA-0035(2005, 2009),Table A6. MECS Survey Years NAICS Subsector and Industry 1998 2002 2006 311 Food 1,468 1,572 1,665 312 Beverage and Tobacco Products 156 156 166 313 Textile Mills 457 375 304 314 Textile Product Mills 85 94 110 315 Apparel 84 54 27 316 Leather and Allied Products 14

304

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

Gasoline and Diesel Fuel Update (EIA)

d 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 Industry 1998 2002 2006 311 Food 1 8 3 312 Beverage and Tobacco Products * 1 * 313 Textile Mills 2 1 0 314 Textile Product Mills 1 * 0 315 Apparel * 0 0 316 Leather and Allied Products * * 0 321 Wood Products 6 4 0 322 Paper 2 1 1 323 Printing and Related Support * * * 324 Petroleum and Coal Products 3,748 3,689 3,572 325 Chemicals 2,772 3,750 2,812 326 Plastics and Rubber Products * Q Q 327 Nonmetallic Mineral Products 10 7 12 331 Primary Metals 758 646 529 332 Fabricated Metal Products 3 1 1 333 Machinery Q 2 * 334 Computer and Electronic Products * 1 1 335 Electrical Equip., Appliances, and Components 27 69 21 336 Transportation Equipment

305

EIA Energy Efficiency-Table 3b. Value of Production a by Selected  

Gasoline and Diesel Fuel Update (EIA)

and 2006 > Table 3b and 2006 > Table 3b Page Last Modified: May 2010 Table 3b. Value of Production 1 by Selected Industries, 1998, 2002, and 2006 (Current Billion Dollars) 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 Mills 57 45 39 314 Textile Product Mills 31 31 33 315 Apparel Manufacturing 65 43 30 316 Leather and Allied Product Manufacturing 10 6 6 321 Wood Product Manufacturing 91 88 112 322 Paper Manufacturing 155 152 171 323 Printing and Related Support Activities 100 95 100 324 Petroleum and Coal Products Manufacturing 136 218 551 325 Chemical Manufacturing 419 452 662 326 Plastics and Rubber Products Manufacturing 164 172 212

306

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

Gasoline and Diesel Fuel Update (EIA)

4b 4b 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 1998 2002 2006 311 Food Manufacturing 431 447 473 312 Beverage and Tobacco Product Manufacturing 122 96 109 313 Textile Mills 56 46 37 314 Textile Product Mills 31 30 30 315 Apparel Manufacturing 66 43 30 316 Leather and Allied Product Manufacturing 10 6 6 321 Wood Product Manufacturing 92 89 100 322 Paper Manufacturing 168 155 153 323 Printing and Related Support Activities 103 93 93 324 Petroleum and Coal Products Manufacturing 224 244 266 325 Chemical Manufacturing 442 450 513 326 Plastics and Rubber Products Manufacturing 168 170 176 327 Nonmetallic Mineral Product Manufacturing 97 93 103 331 Primary Metal Manufacturing 165 145 163 332

307

Complex Queries | Open Energy Information  

Open Energy Info (EERE)

Complex Queries Complex Queries < User:Jweers Jump to: navigation, search Contents 1 Using Nested Queries 1.1 Programs 2 Using Inverse Property Ask Query 3 Using Wildcards Plus Array Print with Count 3.1 States start with A (4) Using Nested Queries Complex Help:Inline queries are queries which involve multiple subjects, properties, or nested queries. The following is an example of a nested query which will return only Programs (Category:Programs) in the Energy Sector (Property:ProgramSector = Energy) within the subsector of Wind (Property:Sector = Wind) which have been developed by National Labs (Category:United States Department of Energy National Laboratories). The last piece mentioned is where the nested query comes into play. To find Programs which have been developed by National Labs, we must search the

308

Page not found | Department of Energy  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

31 - 23740 of 28,905 results. 31 - 23740 of 28,905 results. Article Students Compete to Design Energy-Efficient Appliances What is an efficient building without efficient appliances? That's the question students must face as part of the Energy Department's Max Tech and Beyond competition. http://energy.gov/articles/students-compete-design-energy-efficient-appliances Article DOE Releases Electricity Subsector Cybersecurity Risk Management Process (RMP) Guideline DOE's Office of Electricity Delivery and Energy Reliability, in collaboration with the National Institute of Standards and Technology (NIST) and the North American Electric Reliability Corporation (NERC), has released guidance to help utilities better understand their cybersecurity risks, assess severity, and allocate resources more efficiently to manage

309

,,,,"Reasons that Made Residual Fuel Oil Unswitchable"  

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

5 Relative Standard Errors for Table 10.25;" 5 Relative Standard Errors for Table 10.25;" " Unit: Percents." ,,,,"Reasons that Made Residual Fuel Oil Unswitchable" " "," ",,,,,,,,,,,,," " ,,"Total Amount of ","Total Amount of","Equipment is Not","Switching","Unavailable ",,"Long-Term","Unavailable",,"Combinations of " "NAICS"," ","Residual Fuel Oil ","Unswitchable Residual","Capable of Using","Adversely Affects ","Alternative","Environmental","Contract ","Storage for ","Another","Columns F, G, " "Code(a)","Subsector and Industry","Consumed as a Fuel","Fuel Oil Fuel Use","Another Fuel","the Products","Fuel Supply","Restrictions(b)","in Place(c)","Alternative Fuels(d)","Reason","H, I, J, and K","Don't Know"

310

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

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Cybersecurity Risk Management Process (RMP) Guideline - Final (May Cybersecurity 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 size or organizational or governance structure-to apply effective and efficient risk management processes and tailor them to meet their organizational requirements. This guideline may be used to implement a new cybersecurity program within an organization or to build upon an organization's existing internal

311

Roadmap to Achieve Energy Delivery Systems Cybersecurity  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Roadmap to Achieve Energy Delivery Systems Cybersecurity 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 time and expertise to this effort and would like to thank the other participants for their valuable perspectives and contributions to this important effort. Special thanks go to the U.S. Department of Energy, which provided the funds and support needed to convene participants

312

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

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Releases Maturity Model to Better Protect the Nation's Grid Releases 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 from existing cybersecurity efforts into a common tool that can be used consistently across the industry. The Maturity Model was developed as part of a White House initiative led by the Department of Energy in partnership with the Department of Homeland Security (DHS) and involved close collaboration with industry, other

313

EIA Energy Efficiency-Table 2a. First Use for All Purposes (Primary a  

Gasoline and Diesel Fuel Update (EIA)

a a Page Last Modified: May 2010 Table 2a. Consumption of Energy (Primary 1 Energy) for All Purposes (First Use) for Selected Industries, 1998, 2002, and 2006 (Trillion Btu) MECS Survey Years NAICS Subsector and Industry 1998 2002 2006 311 Food 1,468 1,579 1,665 312 Beverage and Tobacco Products 156 157 164 313 Textile Mills 459 377 304 314 Textile Product Mills 86 94 110 315 Apparel 84 54 27 316 Leather and Allied Products 14 11 5 321 Wood Products 652 520 625 322 Paper 3,224 2,805 2,825 323 Printing and Related Support 199 197 171 324 Petroleum and Coal Products 7,571 7,051 7,125 325 Chemicals 7,211 7,499 6,135 326 Plastics and Rubber Products 692 710 684 327 Nonmetallic Mineral Products 1,245 1,338 1,394

314

" 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;" 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." ,,,"Computer Control of Building Wide Evironment(c)",,,"Computer Control of Processes or Major Energy-Using Equipment(d)",,,"Waste Heat Recovery",,,"Adjustable - Speed Motors",,,"Oxy - Fuel Firing",,,," " "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"

315

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

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Cybersecurity Risk Management Process (RMP) Guideline - Final (May Cybersecurity 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 size or organizational or governance structure-to apply effective and efficient risk management processes and tailor them to meet their organizational requirements. This guideline may be used to implement a new cybersecurity program within an organization or to build upon an organization's existing internal

316

Electricity Advisory Committee Meeting Presentations June 2013 - Wednesday,  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Meeting Presentations June 2013 - Meeting Presentations June 2013 - Wednesday, June 5, 2013 Electricity Advisory Committee Meeting Presentations June 2013 - Wednesday, June 5, 2013 The Department of Energy's Electricity Advisory Committee held a meeting on Wednesday, June 5 and Thursday, June 6 at the National Rural Electric Cooperative Association (NRECA). Wednesday, June 5, 2013 EAC Race to the Top Initiative Working Group Discussion - Sonny Popowsky, Working Group Chair Panel: Key Federal Roles to Enhance Cybersecurity in the Power Sector - Chris Peters, moderator Marianne Swanson, NIST Jason Christopher, DOE Robert Coles, National Grid DOE's Race to the Top - Sonny Popowsky Cybersecurity Panel - NIST and Smart Grid Cybersecurity - Marianne Swanson, NIST Cybersecurity Panel - Electricity Subsector Cybersecurity Capability

317

EIA Energy Efficiency-Table 3d. Value Added by Selected Industries, 1998,  

Gasoline and Diesel Fuel Update (EIA)

d 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 2002 2006 311 Food Manufacturing 173 205 233 312 Beverage and Tobacco Product Manufacturing 62 67 79 313 Textile Mills 24 19 17 314 Textile Product Mills 13 13 15 315 Apparel Manufacturing 32 21 16 316 Leather and Allied Product Manufacturing 5 3 3 321 Wood Product Manufacturing 34 35 44 322 Paper Manufacturing 73 76 80 323 Printing and Related Support Activities 60 59 60 324 Petroleum and Coal Products Manufacturing 32 37 126 325 Chemical Manufacturing 230 254 340 326 Plastics and Rubber Products Manufacturing 86 92 99 327 Nonmetallic Mineral Product Manufacturing 53 55 72 331 Primary Metal Manufacturing 69 57 84 332 Fabricated Metal Product Manufacturing

318

EIA Energy Efficiency-Table 4c. Capacity Adjusted Value of Production a by  

Gasoline and Diesel Fuel Update (EIA)

c c Page Last Modified: May 2010 Table 4c. Capacity Adjusted Value of Production 1 by Selected Industries, 1998, 2002, and 2006 (Billion 2000 Dollars 2) MECS Survey Years NAICS Subsector and Industry 1998 2002 2006 311 Food Manufacturing 432 459 487 312 Beverage and Tobacco Product Manufacturing 116 110 115 313 Textile Mills 55 52 42 314 Textile Product Mills 32 34 32 315 Apparel Manufacturing 67 53 31 316 Leather and Allied Product Manufacturing 11 8 6 321 Wood Product Manufacturing 88 95 98 322 Paper Manufacturing 172 163 160 323 Printing and Related Support Activities 107 106 99 324 Petroleum and Coal Products Manufacturing 221 241 254 325 Chemical Manufacturing 437 468 510 326 Plastics and Rubber Products Manufacturing 162 181 175

319

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

Gasoline and Diesel Fuel Update (EIA)

e e Page Last Modified: May 2010 Table 3e. Gross Output 1 by Selected Industries, 1998, 2002, and 2006 (Current Billion Dollars) Note: 1. Gross output of an industry is the market value of the goods and services produced by an industry, including commodity taxes. The components of gross output include sales or receipts and other operating income, commodity taxes, plus inventory change. Gross output differs from value added, which measures the contribution of the industry's labor and capital to its gross output. Source: U.S. Department of Commerce, Bureau of Economic Analysis, "Gross Domestic Product by Industry 1998-2007," October 2009. MECS Survey Years NAICS Subsector and Industry 1998 2002 2006 311 Food Manufacturing 417 444 526 312 Beverage and Tobacco Product

320

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

Gasoline and Diesel Fuel Update (EIA)

and 2006 > Table 3b and 2006 > Table 3b Page Last Modified: May 2010 Table 3b. Value of Production 1 by Selected Industries, 1998, 2002, and 2006 (Current Billion Dollars) Notes: 1. Value of production is the name for inventory-adjusted value of shipment data. Source: U.S. Department of Commerce, Bureau of Economic Analysis, "Value of Shipments by Detailed Industry 1998- 2007," December 2005, September 2009 and U.S. Census Bureau, Annual Survey of Manufacturers, Industry Statistics 2001, 2004, and 2006, 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 Mills 57 45 39 314 Textile Product Mills 31 31 33 315 Apparel Manufacturing 65 43 30 316 Leather and Allied Product

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


321

EIA Energy Efficiency-Table 4d. Value Added by Selected Industries, 1998  

Gasoline and Diesel Fuel Update (EIA)

d 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 2006 311 Food Manufacturing 193 182 214 312 Beverage and Tobacco Product Manufacturing 70 59 73 313 Textile Mills 23 18 17 314 Textile Product Mills 13 13 15 315 Apparel Manufacturing 32 22 17 316 Leather and Allied Product Manufacturing 5 3 3 321 Wood Product Manufacturing 35 35 37 322 Paper Manufacturing 84 77 85 323 Printing and Related Support Activities 62 56 59 324 Petroleum and Coal Products Manufacturing 38 46 53 325 Chemical Manufacturing 225 248 291 326 Plastics and Rubber Products Manufacturing 84 88 99 327 Nonmetallic Mineral Product Manufacturing 55 54 66

322

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

Gasoline and Diesel Fuel Update (EIA)

c c Page Last Modified: May 2010 Table 3c. Capacity Adjusted Value of Production 1 by Selected Industries, 1998, 2002, and 2006 (Current Billion 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 Mills 57 50 44 314 Textile Product Mills 31 34 36 315 Apparel Manufacturing 66 53 31 316 Leather and Allied Product Manufacturing 11 8 7 321 Wood Product Manufacturing 87 94 110 322 Paper Manufacturing 159 160 177 323 Printing and Related Support Activities 104 109 107 324 Petroleum and Coal Products Manufacturing 134 215 523 325 Chemical Manufacturing 415 470 657 326 Plastics and Rubber Products Manufacturing 158 183 212 327 Nonmetallic Mineral Product Manufacturing 85 97 134 331 Primary Metal Manufacturing

323

Study on Prompting Mechanism of Energy EFficiency Technology  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

on Prompting Mechanism of on Prompting Mechanism of Energy Efficiency Technology The Second U.S.-China Energy Efficiency Forum 2011-5-7 San Francisco China Quality Certification Center Shaoshan Xu Contents  Background  Energy Efficiency Technology  Prompting Mechanism of Energy Efficiency Technology  Information Collection and Evaluation of Energy Efficiency Technologies  Grading and Sub-sector Classification of Energy Efficiency Technologies  Dynamic Tracking and Verification of Energy Efficiency Technologies  Methods/Tools of prompting Energy Efficiency Technologies  China-U.S. Technical Exchange of Energy Efficiency Technologies  Shaoshan(Kevin) Xu 0086-10-83886686(Office)0086-13911564619(MP) E-Mail:xushaoshan@cqc.com.cn Director, Office of Resource-Saving Product Certification

324

Institutional applications of solar total-energy systems. Draft final report. Volume 2. Appendixes  

DOE Green Energy (OSTI)

The appendices present the analytical basis for the analysis of solar total energy (STE) systems. A regional-climate model and a building-load requirements model are developed, along with fuel-price scenarios. Life-cycle costs are compared for conventional-utility, total energy, and STE systems. Thermal STE system design trade-offs are performed and thermal STE system performance is determined. The sensitivity of STE competitiveness to fuel prices is examined. The selection of the photovoltaic array is briefly discussed. The institutional-sector decision processes are analyzed. Hypothetical regional back-up rates and electrical-energy costs are calculated. The algorithms and equations used in operating the market model are given, and a general methodology is developed for projecting the size of the market for STE systems and applied to each of 8 institutional subsectors. (LEW)

None

1978-07-01T23:59:59.000Z

325

Energy intensities in OECD countries, 1970--1989: A sectoral analysis  

SciTech Connect

We discuss the evolution of energy intensities in key sectors or subsectors between the early 1970s and the late 1980s in nine OECD countries. The sectors covered are manufacturing, automobile and air travel, freight trucking, residential space heating, and the service sector. Intensity changes varied among the sectors and countries, but common trends are visible in many cases. In most cases, the intensity decline slowed or ceased in the mid-1980s. We discuss the causes for the changes observed in each area, showing how energy-price changes were but one of many factors that played a role. Weighting the changes in intensities by 1973 energy use patterns, we find that the aggregate energy intensity index fell by 14--19% between 1973 and 1988 in the US, Japan, and West Germany.

Schipper, L.; Meyers, S.; Howarth, R.

1992-11-01T23:59:59.000Z

326

2008 Industrial Technologies Market Report, May 2009  

SciTech Connect

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.

Energetics; DOE

2009-07-01T23:59:59.000Z

327

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

SciTech Connect

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).

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

2009-10-14T23:59:59.000Z

328

Static Heat Loads in the LHC Arc Cryostats: Final Assessment  

E-Print Network (OSTI)

This note presents the final assessment of the static heat loads in the LHC arc cryostats, using different experimental methods during the first commissioning period in 2007. This assessment further develops and completes previous estimates made during the commissioning of sector 7_8 [1]. The estimate of the helium inventory, a prerequisite for the heat load calculation, is also presented. Heat loads to the cold mass are evaluated from the internal energy balance during natural as well as powered warm-ups of the helium baths in different subsector. The helium inventory is calculated from the internal energy balance during powered warm-ups and matched with previous assessments. Furthermore, heat loads to the thermal shield are estimated from the non-isothermal cooling of the supercritical helium in line E. The comparison of measured heat loads with previous estimates and with budgeted values is then presented, while their correlation with some important parameters like insulation vacuum pressure and some heat ...

Parma, V

2010-01-01T23:59:59.000Z

329

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

Gasoline and Diesel Fuel Update (EIA)

Table 4a 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 Industry 1998 2002 2006 311 Food Manufacturing 430 448 472 312 Beverage and Tobacco Product Manufacturing 121 96 109 313 Textile Mills 56 47 37 314 Textile Product Mills 31 32 30 315 Apparel Manufacturing 65 45 30 316 Leather and Allied Product Manufacturing 10 6 6 321 Wood Product Manufacturing 92 89 100 322 Paper Manufacturing 168 156 153 323 Printing and Related Support Activities 103 93 92 324 Petroleum and Coal Products Manufacturing 227 242 265 325 Chemical Manufacturing 440 452 509 326 Plastics and Rubber Products Manufacturing 168 171 175

330

EIA Energy Efficiency-Table 3c. Capacity Adjusted Value of Production a by  

Gasoline and Diesel Fuel Update (EIA)

c c Page Last Modified: May 2010 Table 3c. Capacity Adjusted Value of Production 1 by Selected Industries, 1998, 2002, and 2006 (Current Billion 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 Mills 57 50 44 314 Textile Product Mills 31 34 36 315 Apparel Manufacturing 66 53 31 316 Leather and Allied Product Manufacturing 11 8 7 321 Wood Product Manufacturing 87 94 110 322 Paper Manufacturing 159 160 177 323 Printing and Related Support Activities 104 109 107 324 Petroleum and Coal Products Manufacturing 134 215 523 325 Chemical Manufacturing 415 470 657 326 Plastics and Rubber Products Manufacturing 158 183 212 327 Nonmetallic Mineral Product Manufacturing 85 97 134

331

Released: February 2010  

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

2 Relative Standard Errors for Table 8.2;" 2 Relative Standard Errors for Table 8.2;" " Unit: Percents." ,,,"Computer Control of Building Wide Evironment(c)",,,"Computer Control of Processes or Major Energy-Using Equipment(d)",,,"Waste Heat Recovery",,,"Adjustable - Speed Motors",,,"Oxy - Fuel Firing",,,," " "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"

332

" "," ",,," Steam Turbines Supplied by Either Conventional or Fluidized Bed Boilers",,,"Conventional Combusion Turbines with Heat Recovery",,,"Combined-Cycle Combusion Turbines",,,"Internal Combusion Engines with Heat Recovery",,," Steam Turbines Supplied by Heat Recovered from High-Temperature Processes",,,," "  

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

3 Relative Standard Errors for Table 8.3;" 3 Relative Standard Errors for Table 8.3;" " Unit: Percents." " "," ",,," Steam Turbines Supplied by Either Conventional or Fluidized Bed Boilers",,,"Conventional Combusion Turbines with Heat Recovery",,,"Combined-Cycle Combusion Turbines",,,"Internal Combusion Engines with Heat Recovery",,," Steam Turbines Supplied by Heat Recovered from High-Temperature Processes",,,," " " "," " ," " "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","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"

333

"RSE Table N11.2. Relative Standard Errors for Table N11.2;"  

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

2. Relative Standard Errors for Table N11.2;" 2. Relative Standard Errors for Table N11.2;" " Unit: Percents." " "," " "NAICS"," "," ",,"Residual","Distillate",,"LPG and",,"Coke"," " "Code(a)","Subsector and Industry","Total","Electricity","Fuel Oil","Fuel Oil(b)","Natural Gas(c)","NGL(d)","Coal","and Breeze","Other(e)" ,,"Total United States" , 311,"Food",1,1,3,3,1,1,0,0,1 311221," Wet Corn Milling",0,0,0,0,0,0,0,0,0 312,"Beverage and Tobacco Products",4,4,16,41,4,22,3,0,15 313,"Textile Mills",2,2,5,14,3,5,1,0,5

334

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;" 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)" ,,"Total United States" , 311,"Food",6,0,8,0,0,0,0,7 312,"Beverage and Tobacco Products",10,0,82,0,0,0,0,9 313,"Textile Mills",19,0,77,3,20,0,0,48 314,"Textile Product Mills",38,0,0,38,27,0,0,42

335

Released: July 2009  

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

2 Relative Standard Errors for Table 3.2, 2006;" 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 Breeze","Other(f)" ,,"Total United States" 311,"Food",5.5,4.1,21.5,13.1,7.1,15.7,1.1,0,35.7 3112," Grain and Oilseed Milling",3.3,4.7,19.1,2.1,3.9,65.9,1.3,"X",22.1 311221," Wet Corn Milling",0,0,0,0,0,0,0,"X",0

336

New Draft of Cybersecurity Risk Management Process (RMP) Guideline Now  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Draft of Cybersecurity Risk Management Process (RMP) Guideline Draft of Cybersecurity Risk Management Process (RMP) Guideline Now Available for Public Comment (March 2012) New Draft of Cybersecurity Risk Management Process (RMP) Guideline Now Available for Public Comment (March 2012) March 1, 2012 - 3:26pm Addthis The Department of Energy, in collaboration with the National Institute of Standards and Technology (NIST) and the North American Electric Reliability Corporation (NERC), has released a second draft of the Electricity Subsector Cybersecurity Risk Management Process (RMP) guideline for public comment. This new draft, which will be the last opportunity for public comment prior to final publication, incorporates input submitted by the electric sector during the first public comment period. Many of the submitted comments suggested that the guideline:

337

Analysis and Decomposition of the Energy Intensity of Industries in  

NLE Websites -- All DOE Office Websites (Extended Search)

and Decomposition of the Energy Intensity of Industries in and Decomposition of the Energy Intensity of Industries in California Title Analysis and Decomposition of the Energy Intensity of Industries in California Publication Type Journal Article Year of Publication 2012 Authors de la du Can, Stephane Rue, Ali Hasanbeigi, and Jayant A. Sathaye Journal Energy Policy Volume 46 Pagination 234-245 Keywords california, co2 emissions, energy intensity, energy use Abstract In 2008, the gross domestic product (GDP) of California industry was larger than GDP of industry in any other U.S. states. This study analyses the energy use of and output from seventeen industry subsectors in California and performs decomposition analysis to assess the influence of different factors on California industry energy use. The logarithmic mean Divisia index method is used for the decomposition analysis. The decomposition analysis results show that the observed reduction of energy use in California industry since 2000 is the result of two main factors: the intensity effect and the structural effect. The intensity effect has started pushing final energy use downward in 2000 and has since amplified. The second large effect is the structural effect. The significant decrease of the energy-intensive "Oil and Gas Extraction" subsector's share of total industry value added, from 15% in 1997 to 5% in 2008, and the increase of the non-energy intensive "Electric and electronic equipment manufacturing" sector's share of value added, from 7% in 1997 to 30% in 2008, both contributed to a decrease in the energy intensity in the industry sector

338

Analysis of energy use in building services of the industrial sector in California: Two case studies  

SciTech Connect

Energy-use patterns in many of California's fastest-growing industries are not typical of the existing mix of industries in the US. Many California firms operate small- and medium-sized facilities housed in buildings used simultaneously or interchangeably over time for commercial (office, retail, warehouse) and industrial activities. In these industrial subsectors, the energy required for building services (providing occupant comfort and necessities like 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. Electricity for building services is sometimes priced as if it were base loaded like process uses; in reality this load varies significantly according to occupancy schedules and cooling and heating loads, much as in any commercial building. Using informal field surveys, simulation studies, and detailed analyses of existing data (including utility commercial/industrial audit files), we studied the energy use of this industrial subsector through a multi-step procedure: (1) characterizing non-process building energy and power use in California industries, (2) identifying conservation and load-shaping opportunities in industrial building services, and (3) investigating industrial buildings and system design methodologies. In an earlier report, we addressed these issues by performing an extensive survey of the existing publicly available data, characterizing and comparing the building energy use in this sector. In this report, we address the above objectives by examining and analyzing energy use in two industrial case-study facilities in California. Based on the information for the case studies, we discuss the design consideration for these industrial buildings, characterize their energy use, and review their conservation and load-shaping potentials. In addition, we identify and discuss some research ideas for further investigation.

Akbari, H.; Sezgen, O.

1991-09-01T23:59:59.000Z

339

Analysis of energy use in building services of the industrial sector in California: Two case studies. Final report  

SciTech Connect

Energy-use patterns in many of California`s fastest-growing industries are not typical of the existing mix of industries in the US. Many California firms operate small- and medium-sized facilities housed in buildings used simultaneously or interchangeably over time for commercial (office, retail, warehouse) and industrial activities. In these industrial subsectors, the energy required for building services (providing occupant comfort and necessities like 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. Electricity for building services is sometimes priced as if it were base loaded like process uses; in reality this load varies significantly according to occupancy schedules and cooling and heating loads, much as in any commercial building. Using informal field surveys, simulation studies, and detailed analyses of existing data (including utility commercial/industrial audit files), we studied the energy use of this industrial subsector through a multi-step procedure: (1) characterizing non-process building energy and power use in California industries, (2) identifying conservation and load-shaping opportunities in industrial building services, and (3) investigating industrial buildings and system design methodologies. In an earlier report, we addressed these issues by performing an extensive survey of the existing publicly available data, characterizing and comparing the building energy use in this sector. In this report, we address the above objectives by examining and analyzing energy use in two industrial case-study facilities in California. Based on the information for the case studies, we discuss the design consideration for these industrial buildings, characterize their energy use, and review their conservation and load-shaping potentials. In addition, we identify and discuss some research ideas for further investigation.

Akbari, H.; Sezgen, O.

1991-09-01T23:59:59.000Z

340

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

Gasoline and Diesel Fuel Update (EIA)

c 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 Industry 1998 2002 2006 311 Food 992 1,079 1,124 312 Beverage and Tobacco Products 109 104 101 313 Textile Mills 255 206 178 314 Textile Product Mills 49 60 72 315 Apparel 48 30 14 316 Leather and Allied Products 8 7 3 321 Wood Products 285 198 296 322 Paper 1,648 1,413 1,350 323 Printing and Related Support 97 98 85 324 Petroleum and Coal Products 1,475 1,290 1,434 325 Chemicals 3,377 3,154 2,772 326 Plastics and Rubber Products 327 347 336 327 Nonmetallic Mineral Products 921 960 1,105 331 Primary Metals 2,010 1,614 1,353 332 Fabricated Metal Products 441 387 396

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


341

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

Gasoline and Diesel Fuel Update (EIA)

f f Page Last Modified: May 2010 Table 4f. Industrial Production Indexes by Selected Industries, 1998, 2002, and 2006 (2000 = 100) Source: The Federal Reserve System, http://www.federalreserve.gov/releases/g17/ipdisk/ip_sa.txt February 2006 and December 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 99.4 313 Textile Mills 108.1 88.5 71.9 314 Textile Product Mills 93.0 88.1 88.6 315 Apparel Manufacturing 109.7 71.9 50.8 316 Leather and Allied Product Manufacturing 108.0 62.2 62.7 321 Wood Product Manufacturing 97.4 96.5 106.1 322 Paper Manufacturing 101.4 95.3 92.7 323 Printing and Related Support Activities 98.4 88.5 88.2 324 Petroleum and Coal Products Manufacturing

342

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

Gasoline and Diesel Fuel Update (EIA)

b b Page Last Modified: May 2010 Table 1b. End Uses of Fuel Consumption (Site Energy) for Selected Industries, 1998, 2002, and 2006 (Trillion Btu) Sources: Energy Information Administration, Form EIA-846, Manufacturing Energy Consumption Surveys, 1998, 2002, and 2006. MECS Survey Years NAICS Subsector and Industry 1998 2002 2006 311 Food 1,044 1,116 1,186 312 Beverage and Tobacco Products 108 104 109 313 Textile Mills 254 205 178 314 Textile Product Mills 49 60 72 315 Apparel 48 30 14 316 Leather and Allied Products 8 7 3 321 Wood Products 504 375 445 322 Paper 2,744 2,361 2,354 323 Printing and Related Support 98 98 85 324 Petroleum and Coal Products 3,622 3,202 3,396 325 Chemicals 3,704 3,769 3,195 326 Plastics and Rubber Products 327 348 336 327 Nonmetallic Mineral Products 969 1,052 1,105 331 Primary Metals

343

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

Gasoline and Diesel Fuel Update (EIA)

b 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 and Industry 1998 2002 2006 311 Food 1,044 1,116 1,186 312 Beverage and Tobacco Products 108 104 109 313 Textile Mills 254 205 178 314 Textile Product Mills 49 60 72 315 Apparel 48 30 14 316 Leather and Allied Products 8 7 3 321 Wood Products 504 375 445 322 Paper 2,744 2,361 2,354 323 Printing and Related Support 98 98 85 324 Petroleum and Coal Products 3,622 3,202 3,396 325 Chemicals 3,704 3,769 3,195 326 Plastics and Rubber Products 327 348 336 327 Nonmetallic Mineral Products 969 1,052 1,105 331 Primary Metals 2,576 2,123 1,744 332 Fabricated Metal Products 441 387 397

344

Coordinated Low Emissions Assistance Network toolkit search  

Open Energy Info (EERE)

Low Emissions Assistance Network (CLEAN) Low Emissions Assistance Network (CLEAN) Inventory of Support for Low Emission Planning Are we missing something? Add a Tool software models, databases, training materials, publications Add a Program climate-related activites or strategies How to search the CLEAN Inventory: To find information on low emission development planning activities you can search a number of categories below including by whether it is a Program or Tool, the resource type, the Topic, the Sector, the Sub-Sector and/or Organization involved. On the right-hand side of the screen you can also search by Country or Region. This faceted search is meant to allow you to combine as many search options as you would like to narrow down your search and once you have done this the results will be displayed in the middle of the screen. If you would like to start over, press Reset all Filters at the top center of the screen. If you find that we are missing certain tools or programs you can also add to the site clicking on Add a Tool or Add a Program in the upper right-hand corner. ....[read more][show less]

345

EIA Energy Efficiency-Table 2b. Primary Fuel Consumption for Selected  

Gasoline and Diesel Fuel Update (EIA)

b b Page Last Modified: May 2010 Table 2b. End Uses of Fuel Consumption (Primary 1 Energy) for Selected Industries, 1998, 2002, and 2006 (Trillion Btu) MECS Survey Years NAICS Subsector and Industry 1998 2002 2006 311 Food 1,468 1,572 1,665 312 Beverage and Tobacco Products 156 156 166 313 Textile Mills 457 375 304 314 Textile Product Mills 85 94 110 315 Apparel 84 54 27 316 Leather and Allied Products 14 11 5 321 Wood Products 647 518 619 322 Paper 3,221 2,803 2,833 323 Printing and Related Support 199 197 171 324 Petroleum and Coal Products 3,873 3,454 3,657 325 Chemicals 4,851 4,803 4,181 326 Plastics and Rubber Products 691 707 683 327 Nonmetallic Mineral Products 1,235 1,331 1,385 331 Primary Metals 3,660 3,100 2,617 332 Fabricated Metal Products 791 706 670 333 Machinery 404 341 416 334 Computer and Electronic Products

346

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

Gasoline and Diesel Fuel Update (EIA)

1a 1a Page Last Modified: May 2010 Table 1a. Consumption of Energy (Site Energy) for All Purposes (First Use) for Selected Industries, 1998, 2002, and 2006 (Trillion Btu) Sources: Energy Information Administration, Form EIA-846, Manufacturing Energy Consumption Surveys, 1998, 2002, and 2006. MECS Survey Years NAICS Subsector and Industry 1998 2002 2006 311 Food 1,044 1,123 1,186 312 Beverage and Tobacco Products 108 105 107 313 Textile Mills 256 207 178 314 Textile Product Mills 50 60 72 315 Apparel 48 30 14 316 Leather and Allied Products 8 7 3 321 Wood Products 509 377 451 322 Paper 2,747 2,363 2,354 323 Printing and Related Support 98 98 85 324 Petroleum and Coal Products 7,320 6,799 6,864 325 Chemicals 6,064 6,465 5,149 326 Plastics and Rubber Products 328 351 337 327 Nonmetallic Mineral Products 979 1,059

347

EIA Energy Efficiency-Table 1a. Table 1a. Consumption of Site Energy For  

Gasoline and Diesel Fuel Update (EIA)

a a Page Last Modified: May 2010 Table 1a. Consumption of Energy (Site Energy) for All Purposes (First Use) for Selected Industries, 1998, 2002, and 2006 (Trillion Btu) MECS Survey Years NAICS Subsector and Industry 1998 2002 2006 311 Food 1,044 1,123 1,186 312 Beverage and Tobacco Products 108 105 107 313 Textile Mills 256 207 178 314 Textile Product Mills 50 60 72 315 Apparel 48 30 14 316 Leather and Allied Products 8 7 3 321 Wood Products 509 377 451 322 Paper 2,747 2,363 2,354 323 Printing and Related Support 98 98 85 324 Petroleum and Coal Products 7,320 6,799 6,864 325 Chemicals 6,064 6,465 5,149 326 Plastics and Rubber Products 328 351 337 327 Nonmetallic Mineral Products 979 1,059 1,114 331 Primary Metals 2,560 2,120 1,736

348

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

Gasoline and Diesel Fuel Update (EIA)

c c Page Last Modified: May 2010 Table 1c. Off-Site Produced Energy (Site Energy) for Selected Industries, 1998, 2002 and 2006 (Trillion Btu) Sources: Energy Information Administration, Form EIA-846, Manufacturing Energy Consumption Surveys, 1998, 2002, and 2006. MECS Survey Years NAICS Subsector and Industry 1998 2002 2006 311 Food 992 1,079 1,124 312 Beverage and Tobacco Products 109 104 101 313 Textile Mills 255 206 178 314 Textile Product Mills 49 60 72 315 Apparel 48 30 14 316 Leather and Allied Products 8 7 3 321 Wood Products 285 198 296 322 Paper 1,648 1,413 1,350 323 Printing and Related Support 97 98 85 324 Petroleum and Coal Products 1,475 1,290 1,434 325 Chemicals 3,377 3,154 2,772 326 Plastics and Rubber Products 327 347 336 327 Nonmetallic Mineral Products 921 960 1,105 331 Primary Metals 2,010 1,614

349

Solar-Based Rural Electrification and Micro-Enterprise Development in Latin America: A Gender Analysis  

DOE Green Energy (OSTI)

Worldwide, an estimated 1.5 to 2 billion people do not have access to electricity, including 100 million in the Latin America region. Depending on the country, 30 to 90% of this unelectrified Latin American population lives in rural areas where geographic remoteness and low energy consumption patterns may preclude the extension of the conventional electricity grid. Women are heavily impacted by the energy scarcity given their role as primary energy procurers and users for the household, agricultural and small industrial subsectors in developing countries. As a result, women spend disproportionately more time engaged in energy-related activities like carrying water and searching for cooking fuel. This paper describes the use of decentralized renewable energy systems as one approach to meet the energy needs of rural areas in Latin America. It outlines the advantages of a decentralized energy paradigm to achieve international development goals, especially as they relate to women. The paper studies Enersol Associates, Inc.'s Solar-Based Rural Electrification model as an example of a decentralized energy program which has merged energy and development needs through the local involvement of energy entrepreneurs, non-governmental organizations and community members.

Smith, J.

2000-11-16T23:59:59.000Z

350

A model for Long-term Industrial Energy Forecasting (LIEF)  

SciTech Connect

The purpose of this report is to establish the content and structural validity of the Long-term Industrial Energy Forecasting (LIEF) model, and to provide estimates for the model's parameters. The model is intended to provide decision makers with a relatively simple, yet credible tool to forecast the impacts of policies which affect long-term energy demand in the manufacturing sector. Particular strengths of this model are its relative simplicity which facilitates both ease of use and understanding of results, and the inclusion of relevant causal relationships which provide useful policy handles. The modeling approach of LIEF is intermediate between top-down econometric modeling and bottom-up technology models. It relies on the following simple concept, that trends in aggregate energy demand are dependent upon the factors: (1) trends in total production; (2) sectoral or structural shift, that is, changes in the mix of industrial output from energy-intensive to energy non-intensive sectors; and (3) changes in real energy intensity due to technical change and energy-price effects as measured by the amount of energy used per unit of manufacturing output (KBtu per constant $ of output). The manufacturing sector is first disaggregated according to their historic output growth rates, energy intensities and recycling opportunities. Exogenous, macroeconomic forecasts of individual subsector growth rates and energy prices can then be combined with endogenous forecasts of real energy intensity trends to yield forecasts of overall energy demand. 75 refs.

Ross, M. (Lawrence Berkeley Lab., CA (United States) Michigan Univ., Ann Arbor, MI (United States). Dept. of Physics Argonne National Lab., IL (United States). Environmental Assessment and Information Sciences Div.); Hwang, R. (Lawrence Berkeley Lab., CA (United States))

1992-02-01T23:59:59.000Z

351

A model for Long-term Industrial Energy Forecasting (LIEF)  

SciTech Connect

The purpose of this report is to establish the content and structural validity of the Long-term Industrial Energy Forecasting (LIEF) model, and to provide estimates for the model`s parameters. The model is intended to provide decision makers with a relatively simple, yet credible tool to forecast the impacts of policies which affect long-term energy demand in the manufacturing sector. Particular strengths of this model are its relative simplicity which facilitates both ease of use and understanding of results, and the inclusion of relevant causal relationships which provide useful policy handles. The modeling approach of LIEF is intermediate between top-down econometric modeling and bottom-up technology models. It relies on the following simple concept, that trends in aggregate energy demand are dependent upon the factors: (1) trends in total production; (2) sectoral or structural shift, that is, changes in the mix of industrial output from energy-intensive to energy non-intensive sectors; and (3) changes in real energy intensity due to technical change and energy-price effects as measured by the amount of energy used per unit of manufacturing output (KBtu per constant $ of output). The manufacturing sector is first disaggregated according to their historic output growth rates, energy intensities and recycling opportunities. Exogenous, macroeconomic forecasts of individual subsector growth rates and energy prices can then be combined with endogenous forecasts of real energy intensity trends to yield forecasts of overall energy demand. 75 refs.

Ross, M. [Lawrence Berkeley Lab., CA (United States)]|[Michigan Univ., Ann Arbor, MI (United States). Dept. of Physics]|[Argonne National Lab., IL (United States). Environmental Assessment and Information Sciences Div.; Hwang, R. [Lawrence Berkeley Lab., CA (United States)

1992-02-01T23:59:59.000Z

352

Session 1: Fatal Construction Injuries Guiding Construction Injury Research: Data Coupled with Industry  

E-Print Network (OSTI)

of examining current construction injury research, identifying research gaps, and developing a strategic research plan. Through existing injury surveillance data systems, much is known about the leading causes of fatal (falls, motor vehicles, machines, and electrocutions) and nonfatal injury (overexertion, falls, and struck by objects) in the construction industry; however, little research has focused on identifying injury problems for specific subsectors of the construction industry. Research that is focused on specific injury problems and specific types of construction work (e.g., falls during truss installation) may lead more directly to identification of effective interventions than research on general injury categories in the construction industry as a whole (e.g., falls in construction). Three high-risk construction industry sectors (highway and street construction, residential building construction, and roofing and truss installation) were selected based on a review of fatal and nonfatal injury data, the number of workers at risk, current trends in the construction industry, OSHA’s regulatory agenda, an external

Casini V; Furrow K; Hause M; Linn H; Washenitz F

1997-01-01T23:59:59.000Z

353

Energy conservation opportunities in commercial appliances. Final report  

SciTech Connect

This study establishes a data base of energy-consuming appliances in the commercial sector, and identifies and rates the most-promising development opportunities that would save significant amounts of energy on a national level. A detailed national inventory of 45 major appliances and their energy consumption was established for the year 1975. Thirty-four potential appliance improvements were identified, evaluated, and ranked. The opportunities are identified by means of a literature search and contact with industry representatives. The commercial sector is defined in terms of the divisions prescribed in the S.I.C. Manual (1972) of the OMB. These groups are recombined into the commercial subsectors of communications; utilities; wholesale; retail; finance, insurance, real estate, and services; hospital; schools; and public administration. The major energy-consuming appliances in the following six functional-use categories were identified: space heating and cooling; water heating; refrigeration; cooking; and lighting. The equipment in these categories was estimated to consume 87% of the total energy used in the commercial sector, with the remaining 13% consumed by equipment such as computers, business machines, laundry equipment, dishwashing, and other food-service equipment. (MCW)

Hurley, J.R.; Searight, E.F.; Wong, A.

1978-12-01T23:59:59.000Z

354

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

Science Conference Proceedings (OSTI)

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.

Liu Zhiping [State Planning Commission, Beijing (China). Energy Research Inst.; Sinton, J.E.; Yang Fuqiang; Levine, M.D.; Ting, M.K. [Lawrence Berkeley Lab., CA (United States)

1994-09-01T23:59:59.000Z

355

Vintage-level energy and environmental performance of manufacturing establishments  

SciTech Connect

This report examines the relationship between an industrial plant`s vintage and its energy and environmental performance. Basic questions related to defining vintage and measuring the effects of the manufacturing industry`s vintage distribution of plant-level capacity and energy intensity are explored in general for six energy-intensive sectors (paper, chlorine, nitrogenous fertilizer, aluminum, steel, and cement) at the four-digit standard industrial classification (SIC) level and in detail for two sectors (steel and cement). Results show that greenfield (i.e., newly opened) plants in the paper, steel, and cement industries exhibit low fossil fuel intensities. These results are consistent with expectations. New plants in the paper and steel industries, where processes are undergoing electrification, exhibit high electricity intensities. An analysis of a subsector of the steel industry -- minimills that use scrap-based, electric arc furnaces -- reveals a decline in electricity intensity of 6.2 kilowatt-hours per ton for each newer year of installed vintage. This estimate is consistent with those of engineering studies and raises confidence that analyses of vintage effects in other industries could be conducted. When a vintage measure is assigned on the basis of investment data rather than trade association data, the vintage/performance relationship results for the cement industry are reasonably robust; thus, the analysis of vintage and performance could be extended to sectors for which only US Bureau of the Census data are available.

Boyd, G.A.; Bock, M.J.; Neifer, M.J. [Argonne National Lab., IL (United States); Karlson, S.H. [Northern Illinois Univ., De Kalb, IL (United States). Dept. of Economics; Ross, M.H. [Michigan Univ., Ann Arbor, MI (United States). Dept. of Physics

1994-05-01T23:59:59.000Z

356

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

SciTech Connect

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.

Van Buskirk, Robert D.

2004-05-07T23:59:59.000Z

357

Current and future industrial energy service characterizations  

DOE Green Energy (OSTI)

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.

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

1980-10-01T23:59:59.000Z

358

Market potential for electrolytic hydrogen. Final report  

SciTech Connect

The economics of hydrogen production by the major users of hydrogen (petroleum refiners and manufacturers of ammonia and methanol) favor the continued use of fossil fuels for hydrogen generation. However, there are a large number of miscellaneous small users for whom hydrogen produced by advanced electrolyzers may become economically attractive. Many of these small users, with hydrogen demands of < 0.5 million SCF per day, purchase their hydrogen requirements from industrial gas suppliers. Forseeable improvements in current electrolyzer technology, which will reduce plant capital costs and improve plant performance and efficiency, may make electrolytic hydrogen competitive with purchased hydrogen for many specialty users. This study analyzed the small user hydrogen market. Telephone interviews were conducted with representative hydrogen users in the chemical, pharmaceutical, electronics, metals, fats and oils, and float glass industries to determine the decision factors governing the choice of their hydrogen supply. Cost projections to the year 2000 for production of hydrogen by advanced electrolyzers were made and compared with price projections for merchant hydrogen, and the estimates of the potential market for each of the industrial sub-sectors were determined. By the year 2000, the potential market for advanced technology electrolytic hydrogen among specialty users is projected to be about half of what the merchant hydrogen market would be in the absence of electrolytic hydrogen. This potential market, representing an annual demand of about 16 billion SCF of hydrogen, will develop from market penetrations of electrolyzers assumed to begin in the early 1980s.

Fein, E.; Mathey, C.J.; Arnstein, C.

1979-08-01T23:59:59.000Z

359

Constructing a resilience index for the enhanced critical in Frastructure Protection Program.  

Science Conference Proceedings (OSTI)

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

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.; Decision and Information Sciences

2010-10-14T23:59:59.000Z

360

Addressing an Uncertain Future Using Scenario Analysis  

Science Conference Proceedings (OSTI)

The Office of Energy Efficiency and Renewable Energy (EERE) has had a longstanding goal of introducing uncertainty into the analysis it routinely conducts in compliance with the Government Performance and Results Act (GPRA) and for strategic management purposes. The need to introduce some treatment of uncertainty arises both because it would be good general management practice, and because intuitively many of the technologies under development by EERE have a considerable advantage in an uncertain world. For example, an expected kWh output from a wind generator in a future year, which is not exposed to volatile and unpredictable fuel prices, should be truly worth more than an equivalent kWh from an alternative fossil fuel fired technology. Indeed, analysts have attempted to measure this value by comparing the prices observed in fixed-price natural gas contracts compared to ones in which buyers are exposed to market prices (see Bolinger, Wiser, and Golove and (2004)). In addition to the routine reasons for exploring uncertainty given above, the history of energy markets appears to have exhibited infrequent, but troubling, regime shifts, i.e., historic turning points at which the center of gravity or fundamental nature of the system appears to have abruptly shifted. Figure 1 below shows an estimate of how the history of natural gas fired generating costs has evolved over the last three decades. The costs shown incorporate both the well-head gas price and an estimate of how improving generation technology has gradually tended to lower costs. The purpose of this paper is to explore scenario analysis as a method for introducing uncertainty into EERE's forecasting in a manner consistent with the preceding observation. The two questions are how could it be done, and what is its academic basis, if any. Despite the interest in uncertainty methods, applying them poses some major hurdles because of the heavy reliance of EERE on forecasting tools that are deterministic in nature, such as the Energy Information Administration's (EIA's) National Energy Modeling System (NEMS). NEMS is the source of the influential Annual Energy Outlook whose business-as-usual (BAU) case, the Reference Case, forms the baseline for most of the U.S. energy policy discussion. NEMS is an optimizing model because: 1. it iterates to an equilibrium among modules representing the supply, demand, and energy conversion subsectors; and 2. several subsectoral models are individually solved using linear programs (LP). Consequently, it is deeply rooted in the recent past and any effort to simulate the consequences of a major regime shift as depicted in Figure 1 must come by applying an exogenously specified scenario. And, more generally, simulating futures that lie outside of our recent historic experience, even if they do not include regime switches suggest some form of scenario approach. At the same time, the statistical validity of scenarios that deviate significantly outside the ranges of historic inputs should be questioned.

Siddiqui, Afzal S.; Marnay, Chris

2006-12-15T23:59:59.000Z

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361

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

SciTech Connect

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 Califor

Galitsky, Christina; Worrell, Ernst

2004-06-01T23:59:59.000Z

362

Cooperative ExtensionTHE ECONOMIC IMPACTS OF AGRICULTURE IN WISCONSIN COUNTIES  

E-Print Network (OSTI)

In Wisconsin, policy makers are exploring ways to unleash the private sector to stimulate the economy with an emphasis on job creation. Historically agriculture has been an important part of the Wisconsin economy, but over the years the relative importance of agriculture in the economy has diminished as the service sector employment, such as recreation and tourism, became more predominant. With the loss of many manufacturing jobs and the recent recession, there is renewed interest in agriculture in terms of employment and as a potential source of new employment opportunities. But is this renewed interest justified? Is the agricultural sector one that can have a larger or stimulative role in the Wisconsin economy? How should local and state policy makers consider an “old ” industry that seems to again have relevance? In an original study by Deller (2004), the contributions of agriculture to the Wisconsin economy were documented and more recently re-examined by Deller and Williams in 2009. In both of these studies agriculture was defined to include on-farm production and food processing. Using 2007 data, Wisconsin agriculture was found to contribute $59.16 billion to total business sales (about 12.5 percent of the Wisconsin total); 353,991 jobs (10 percent of total employment) and $20.2 billion of total income (about nine percent of the Wisconsin total). For the first time, the 2009 study also used “clustering analysis ” to examine changes (2001 to 2007) in subsectors of on-farm and food processing to identify strengths, weaknesses, opportunities and threats of the

Steven Deller; David Williams; Steven C. Deller; David Williams

2011-01-01T23:59:59.000Z

363

Everything You Ever Wanted To Know About Food Processing  

E-Print Network (OSTI)

The food processing industry is the fourth largest consumer of energy in the US industrial sector. Food processors use nearly 1,200 trillion Btu of energy per year. The industry is comprised of more than 21,000 processing plants. Total production values make it $400 billion industry. While energy represents on average between one and two percent of total operating costs, in some industry sub-sectors energy comprises as much as 20%. Major energy end-uses include drying, refrigeration, process heating and cooling, and machine drives. Energy efficiency becomes more important in an industry of tight margins. Today, Americans spend the same percentage of disposable income on food as they did 20 years ago. The Food Marketing Institute notes that supermarket sales were only expected to rise about 2% in 2000. Rising energy costs, increasing restrictions on land application of waste, sanitation standards, and a high demand for product quality, and processed foods contribute to the industry's energy and power quality needs. In addition to documenting a variety of energy end uses in the industry in spring 2000, E SOURCE surveyed 148 plant managers by telephone and conducted in-depth interviews with 8 corporate energy managers. We asked the plant managers to respond to a variety of questions on topics such as decision-making, plant energy use, electricity and deregulation, natural gas use, energy services and outsourcing, energy efficiency, and plans for plant renovations and new construction. In our interviews with the corporate energy managers, we explored their current strategies for purchasing energy and energy services and asked them what they expect to do in the future. This paper provides some of the key findings from this report including an overview of industry challenges, key energy end-uses and innovations, and valuable insights from energy managers on the energy issues that food processors face.

Adams, N.; Milmoe, P. H.

2001-05-01T23:59:59.000Z

364

Plant Energy Benchmarking: A Ten Year Retrospective of the ENERGY STAR Energy Performace Indicators (ES-EPI)  

E-Print Network (OSTI)

Over the past several years, there has been growing interest among policy makers and others in the role that benchmarking industrial energy efficiency can play in climate, air, and other potential regulatory actives. For over ten years, the US EPA has supported the development of sector specific industrial energy efficiency benchmarks, known as ENERGY STAR Energy Performance Indicators (ES-EPI). To date there are ES-EPI that are either completed or under development for fourteen broad industries. Within these industries, ES-EPI account for over two dozen sub-sectors and many more detailed product types. Newer versions, or updates for three of the industries' ES-EPI have been developed in recent years. Through the process of updating this ES-EPI, the program has been able to observe changes in the energy performance of the sector as well as the range in performance found in the sector. This paper provides an overview of the approach that has been used in this research to develop this ES-EPI; summarizing the industry specific and general findings regarding the range of performance within and across industries. Observations about industrial plant benchmarking and lessons learned will be explored. In general, there are no sectors that are easily represented by a simple energy per widget benchmark; less energy intensive sectors tend to exhibit a wider range of performance than energy intensive ones; changes over time in the level and range of energy performance, i.e. industry curve shift, for ES-EPI that have been updated do not reveal any single pattern.

Boyd, G.; Tunnessen, W.

2013-01-01T23:59:59.000Z

365

Power Conservation Strategies for MEMS-based Storage Devices  

E-Print Network (OSTI)

Power dissipation in mobile computers is crucial and researchers have expended significant effort to improve power management for the hard drive, which accounts for a large percentage of the power consumed by the system. A new class of secondary storage devices based on microelectromechanical systems (MEMS) promises to consume an order of magnitude less power with 10--20 times shorter latency and 10 times greater storage densities. Though MEMS storage devices promise to provide a more energy-efficient storage solution for mobile computing applications, little research has been conducted on how to manage the power consumption of these devices. In this paper we examine the power model of a MEMSbased storage device and perform a quantitative analysis of the power distribution among different working modes. Based on our analysis, we present three strategies to reduce power consumption: aggressive spin-down, merging of sequential requests, and subsector accesses. We show that immediate spin-down can save 50% of the total energy consumed by the device at the cost of increased response time. Merging of sequential requests can save up to 18% of the servicing energy and reduce response time by about 20%. Transferring less data for small requests such as those for metadata can save 40% of the servicing energy. Finally, we show that by applying all three power management strategies simultaneously the total power consumption of MEMS-based storage devices can be reduced by about 54% with no impact on I/O performance. This research is supported by the National Science Foundation under grant number CCR-073509 and the Institute for Scientific Computation Research at Lawrence Livermore National Laboratory under grant number SC-20010378.

Ying Lin; Scott A. Brandt; Darrell D. E. Long; Ethan L. Miller

2002-01-01T23:59:59.000Z

366

Energy-economy interactions revisited within a comprehensive sectoral model  

Science Conference Proceedings (OSTI)

This paper describes a computable general equilibrium (CGE) model with considerable sector and technology detail, the ``All Modular Industry Growth Assessment'' Model (AMIGA). It is argued that a detailed model is important to capture and understand the several rolls that energy plays within the economy. Fundamental consumer and industrial demands are for the services from energy; hence, energy demand is a derived demand based on the need for heating, cooling mechanical, electrical, and transportation services. Technologies that provide energy-services more efficiently (on a life cycle basis), when adopted, result in increased future output of the economy and higher paths of household consumption. The AMIGA model can examine the effects on energy use and economic output of increases in energy prices (e.g., a carbon charge) and other incentive-based policies or energy-efficiency programs. Energy sectors and sub-sector activities included in the model involve energy extraction conversion and transportation. There are business opportunities to produce energy-efficient goods (i.e., appliances, control systems, buildings, automobiles, clean electricity). These activities are represented in the model by characterizing their likely production processes (e.g., lighter weight motor vehicles). Also, multiple industrial processes can produce the same output but with different technologies and inputs. Secondary recovery, i.e., recycling processes, are examples of these multiple processes. Combined heat and power (CHP) is also represented for energy-intensive industries. Other modules represent residential and commercial building technologies to supply energy services. All sectors of the economy command real resources (capital services and labor).

Hanson, D. A.; Laitner, J. A.

2000-07-24T23:59:59.000Z

367

Energy-Efficiency Improvement Opportunities for the Textile Industry  

SciTech Connect

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.

China Energy Group; Hasanbeigi, Ali

2010-09-29T23:59:59.000Z

368

Assessing the Control Systems Capacity for Demand Response in California Industries  

SciTech Connect

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.

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

2012-01-18T23:59:59.000Z

369

China's Industrial Energy Consumption Trends and Impacts of the Top-1000  

NLE Websites -- All DOE Office Websites (Extended Search)

China's Industrial Energy Consumption Trends and Impacts of the Top-1000 China's Industrial Energy Consumption Trends and Impacts of the Top-1000 Enterprises Energy-Saving Program and the Ten Key Energy-Saving Projects Title China's Industrial Energy Consumption Trends and Impacts of the Top-1000 Enterprises Energy-Saving Program and the Ten Key Energy-Saving Projects Publication Type Journal Year of Publication 2012 Authors Ke, Jing, Lynn K. Price, Stephanie Ohshita, David Fridley, Nina Zheng Khanna, Nan Zhou, and Mark D. Levine Keywords energy saving, energy trends, industrial energy efficiency, top-1000 Abstract This study analyzes China's industrial energy consumption trends from 1996 to 2010 with a focus on the impact of the Top-1000 Enterprises Energy-Saving Program and the Ten Key Energy-Saving Projects. From 1996 to 2010, China's industrial energy consumption increased by 134%, even as the industrial economic energy intensity decreased by 46%. Decomposition analysis shows that the production effect was the dominant cause of the rapid growth in industrial energy consumption, while the efficiency effect was the major factor slowing the growth of industrial energy consumption. The structural effect had a relatively small and fluctuating influence. Analysis shows the strong association of industrial energy consumption with the growth of China's economy and changing energy policies. An assessment of the Top-1000 Enterprises Energy-Saving Program and the Ten Key Energy-Saving Projects indicates that the economic energy intensity of major energy-intensive industrial sub-sectors, as well as the physical energy intensity of major energy-intensive industrial products, decreased significantly during China's 11th Five Year Plan (FYP) period (2006-2010). This study also shows the importance and challenge of realizing structural change toward less energy-intensive activities in China during the 12th FYP period (2011-2015).

370

Assessing the Control Systems Capacity for Demand Response in California  

NLE Websites -- All DOE Office Websites (Extended Search)

the Control Systems Capacity for Demand Response in California the Control Systems Capacity for Demand Response in California Industries Title Assessing the Control Systems Capacity for Demand Response in California Industries Publication Type Report LBNL Report Number LBNL-5319E Year of Publication 2012 Authors Ghatikar, Girish, Aimee T. McKane, Sasank Goli, Peter L. Therkelsen, and Daniel Olsen Date Published 01/2012 Publisher CEC/LBNL Keywords automated dr, controls and automation, demand response, dynamic pricing, industrial controls, market sectors, openadr Abstract 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.

371

Final Technical Report: "Representing Endogenous Technological Change in Climate Policy Models: General Equilibrium Approaches"  

SciTech Connect

The research supported by this award pursued three lines of inquiry: (1) The construction of dynamic general equilibrium models to simulate the accumulation and substitution of knowledge, which has resulted in the preparation and submission of several papers: (a) A submitted pedagogic paper which clarifies the structure and operation of computable general equilibrium (CGE) models (C.2), and a review article in press which develops a taxonomy for understanding the representation of technical change in economic and engineering models for climate policy analysis (B.3). (b) A paper which models knowledge directly as a homogeneous factor, and demonstrates that inter-sectoral reallocation of knowledge is the key margin of adjustment which enables induced technical change to lower the costs of climate policy (C.1). (c) An empirical paper which estimates the contribution of embodied knowledge to aggregate energy intensity in the U.S. (C.3), followed by a companion article which embeds these results within a CGE model to understand the degree to which autonomous energy efficiency improvement (AEEI) is attributable to technical change as opposed to sub-sectoral shifts in industrial composition (C.4) (d) Finally, ongoing theoretical work to characterize the precursors and implications of the response of innovation to emission limits (E.2). (2) Data development and simulation modeling to understand how the characteristics of discrete energy supply technologies determine their succession in response to emission limits when they are embedded within a general equilibrium framework. This work has produced two peer-reviewed articles which are currently in press (B.1 and B.2). (3) Empirical investigation of trade as an avenue for the transmission of technological change to developing countries, and its implications for leakage, which has resulted in an econometric study which is being revised for submission to a journal (E.1). As work commenced on this topic, the U.S. withdrawal from Kyoto and the administration's announcement of a voluntary target based on emission intensity made it apparent that the degree of emission leakage to developing countries would depend on (i) the form of the emission limit set by developed countries and (ii) the incentives faced by developing nations to accede to an international climate regime. This realization led to synergistic research on the properties of intensity targets under uncertainty, which resulted in two theoretical studies, one which has been published (A.1) and the other which is currently in review (C.5).

Ian Sue Wing

2006-04-18T23:59:59.000Z

372

Transportation and Greenhouse Gas Emissions Trading. Final Technical Report  

SciTech Connect

The authors conclude in this report that an upstream system would ensure complete regulatory coverage of transportation sector emissions in an efficient and feasible manner, and as such represents a key component of a national least-cost GHG emissions abatement strategy. The broad coverage provided by an upstream system recommends this approach over vehicle-maker based approaches, which would not cover emissions from heavy-duty vehicles and the aviation, marine and off-road sub-sectors. The on-road fleet approach unfairly and inefficiently burdens vehicle manufacturers with responsibility for emissions that they cannot control. A new vehicles approach would exclude emissions from vehicles on the road prior to program inception. The hybrid approach faces significant technical and political complications, and it is not clear that the approach would actually change behavior among vehicle makers and users, which is its main purpose. They also note that a trading system would fail to encourage many land use and infrastructure measures that affect VMT growth and GHG emissions. They recommend that this market failure be addressed by complementing the trading system with a program specifically targeting land use- and infrastructure-related activities. A key issue that must be addressed in designing a national GHG control strategy is whether or not it is necessary to guarantee GHG reductions from the transport sector. Neither an upstream system nor a downstream approach would do so, since both would direct capital to the least-cost abatement opportunities wherever they were found. They review two reasons why it may be desirable to force transportation sector reductions: first, that the long-term response to climate change will require reductions in all sectors; and second, the many ancillary benefits associated with transportation-related, and especially VMT-related, emissions reduction activities. If policy makers find it desirable to establish transportation-specific policies, they recommend (in addition to the land use policies mentioned above), that they combine an upstream trading system with a carbon efficiency standard similar to the current CAFE standard. Under this approach a fuel price signal would be complemented by incentives for manufacturers to produce more carbon efficient vehicles. To prevent vehicle manufacturers from being forced to pay more than other sectors for reducing GHG emissions, they recommend that the vehicle makers be allowed to pay a cash penalty equal to the market price of allowances in lieu of meeting carbon efficiency requirements.

Steve Winkelman; Tim Hargrave; Christine Vanderlan

1999-10-01T23:59:59.000Z

373

Community Wind: Once Again Pushing the Envelope of Project Finance  

SciTech Connect

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.

bolinger, Mark A.

2011-01-18T23:59:59.000Z

374

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

SciTech Connect

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, postponin

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

2011-08-18T23:59:59.000Z

375

Energy Use in China: Sectoral Trends and Future Outlook  

SciTech Connect

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.

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

2007-10-04T23:59:59.000Z

376

Energy Use in China: Sectoral Trends and Future Outlook  

SciTech Connect

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.

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

2007-10-04T23:59:59.000Z

377

Economically Optimum Agricultural Utilization of a Reclaimed Water Resource in the Texas Rolling Plains  

E-Print Network (OSTI)

The U.S. Army Corps of Engineers (COE) has proposed a project that would reduce the flow from saline springs and seeps within the groundwater alluvium of the Red River Basin. While the amount of salts moving through the alluvium would be controlled by the project, total water quantity would not be appreciably affected. Presently, salinity levels in the basin are quite high, making irrigated agriculture an infeasible alternative. In areas affected by salinity, salts accumulate in the active root zone, thereby restricting the availability of soil moisture to the crop and reducing yield. To counteract the deleterious presence of the salts, extra irrigation water is applied to "leach" the salts below the active root zone thus maintaining the yield at some specified level. Waters containing over 13,000 parts per million (ppm) salts have been sampled by the COE in the Pease River watershed (a subsector of the entire area to be impacted by the project). It is estimated that installation of the project would reduce this level to approximately 3000 ppm. Although 3000 ppm is not below the tolerance threshold of most plants, rainfall in the area is sufficient to act as a natural leaching agent. The purpose of this study was to estimate the response of the agricultural sector to the project. A recursive linear program was designed in such a manner that the time path of producer adjustments to the reclaimed water source could be estimated. The Pease River watershed was chosen due to the sizable reduction in the salinity due to the proposed project, relative to other areas within the basin. By considering only a single watershed, the adoption process could be more closely studied. Two scenarios were considered in the analysis in an attempt to better understand the effects of the initial assumptions on the measure of project benefits. The first scenario applied guidelines established by the Water Resources Council (WRC). WRC guidelines required the use of OBERS SERIES E' yield projections, normalized prices, and an interest rate of 7.125 percent to discount future costs and benefits. The second scenario applied in alternative criteria, which assumed no trend in yield, a three-year average of current prices, and a real interest rate of 2.5 percent. Since probabilistic estimates indicating the improvement in water quality through time were unavailable from the COE, it was assumed that all improvement in water quality occurred linearly over time, with full water quality improvement in the tenth year. The adjustment process was then evaluated over a twenty year horizon. Several irrigation strategies were considered for each crop, thereby allowing the model to select an optimal leaching policy given the level of water quality for any point in time. The linear programming model maximized expected net returns from representative crop enterprises on the basis of a three-year moving average of past actual yields. This means expected yield in the linear programming model was slightly less than actual yield for any particular year. When all improvements in water quality had taken place and the model achieved steady state, the economically optimal allocation of the water resource had been determined. Results from the study indicated that a policy of rapid adoption should be undertaken. In the initial year, a 40 percent leaching fraction was economically feasible on limited acreage. Dryland production then shifted quickly to irrigation as water quality improved. Water use also shifted, moving from a 40 percent to a 20 percent leaching fraction. By the ninth year of the analysis, all adjustment's had occurred and a 10 percent leaching fraction was economically optimal on all irrigated acreage. Due to its profitability and for relative salt tolerance, cotton was the only irrigated activity chosen by the model. An optimal cropping pattern of 55,121 acres of irrigated cotton, 14,437 acres of dryland cotton and 7,728 acres of native pasture was selected by the model under the first scenario. For the second, sc

Zacharias, T.; Taylor, C. R.; Lacewell, R. D.

1980-09-01T23:59:59.000Z