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Note: This page contains sample records for the topic "household characteristics census" 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.


1

char_household2001.pdf  

Annual Energy Outlook 2012 (EIA)

9a. Household Characteristics by Northeast Census Region, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total U.S. Northeast Census Region RSE Row...

2

Table HC1-11a. Housing Unit Characteristics by South Census Region,  

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

1a. Housing Unit Characteristics by South Census Region, 1a. Housing Unit Characteristics by South Census Region, Million U.S. Households, 2001 Housing Unit Characteristics RSE Column Factor: Total U.S. South Census Region RSE Row Factors Total Census Division South Atlantic East South Central West South Central 0.5 0.9 1.2 1.4 1.4 Total .............................................................. 107.0 38.9 20.3 6.8 11.8 NE Census Region and Division Northeast ..................................................... 20.3 -- -- -- -- NF New England ............................................. 5.4 -- -- -- -- NF Middle Atlantic ........................................... 14.8 -- -- -- -- NF Midwest ....................................................... 24.5 -- -- -- -- NF East North Central .....................................

3

Table HC1-12a. Housing Unit Characteristics by West Census Region,  

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

2a. Housing Unit Characteristics by West Census Region, 2a. Housing Unit Characteristics by West Census Region, Million U.S. Households, 2001 Housing Unit Characteristics RSE Column Factor: Total U.S. West Census Region RSE Row Factors Total Census Division Mountain Pacific 0.5 1.0 1.7 1.1 Total .............................................................. 107.0 23.3 6.7 16.6 NE Census Region and Division Northeast ..................................................... 20.3 -- -- -- NF New England ............................................. 5.4 -- -- -- NF Middle Atlantic ........................................... 14.8 -- -- -- NF Midwest ....................................................... 24.5 -- -- -- NF East North Central ..................................... 17.1 -- -- -- NF West North Central ....................................

4

PRELIMINARY DATA Housing Unit and Household Characteristics  

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

PRELIMINARY DATA Housing Unit and Household Characteristics RSE Column Factor: Total Households (million) Households With Fans (million) Percent of Households With Fans Number of...

5

Household energy and consumption and expenditures, 1990. [Contains Division, Census Region, and Climate Zone maps  

Science Conference Proceedings (OSTI)

The purpose of this supplement to the Household Energy Consumption and Expenditures 1990 report is to provide information on the use of energy in residential housing units, specifically at the four Census regions and nine Census division levels. This report includes household energy consumption, expenditures, and prices for natural gas, electricity, fuel oil, liquefied petroleum gas (LPG), and kerosene as well as household wood consumption. For national-level data, see the main report, Household Energy Consumption and Expenditures 1990.

Not Available

1993-03-02T23:59:59.000Z

6

Section J: HOUSEHOLD CHARACTERISTICS  

U.S. Energy Information Administration (EIA)

2001 Residential Energy Consumption Survey Form EIA-457A (2001)--Household Questionnaire OMB No.: 1905-0092, Expiring February 29, 2004 42 Section J: HOUSEHOLD ...

7

Table HC1-10a. Housing Unit Characteristics by Midwest Census Region,  

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

0a. Housing Unit Characteristics by Midwest Census Region, 0a. Housing Unit Characteristics by Midwest Census Region, Million U.S. Households, 2001 Housing Unit Characteristics RSE Column Factor: Total U.S. Midwest Census Region RSE Row Factors Total Census Division East North Central West North Central 0.5 1.0 1.2 1.8 Total .............................................................. 107.0 24.5 17.1 7.4 NE Census Region and Division Northeast ..................................................... 20.3 -- -- -- NF New England ............................................. 5.4 -- -- -- NF Middle Atlantic ........................................... 14.8 -- -- -- NF Midwest ....................................................... 24.5 24.5 17.1 7.4 NF East North Central ..................................... 17.1 17.1

8

Table HC1-9a. Housing Unit Characteristics by Northeast Census Region,  

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

9a. Housing Unit Characteristics by Northeast Census Region, 9a. Housing Unit Characteristics by Northeast Census Region, Million U.S. Households, 2001 Housing Unit Characteristics RSE Column Factor: Total U.S. Northeast Census Region RSE Row Factors Total Census Division Middle Atlantic New England 0.5 1.0 1.2 1.6 Total .............................................................. 107.0 20.3 14.8 5.4 NE Census Region and Division Northeast ..................................................... 20.3 20.3 14.8 5.4 NF New England ............................................. 5.4 5.4 Q 5.4 NF Middle Atlantic ........................................... 14.8 14.8 14.8 Q NF Midwest ....................................................... 24.5 -- -- -- NF East North Central ..................................... 17.1 -- -- -- NF

9

"Table HC11.8 Water Heating Characteristics by Northeast Census...  

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

8 Water Heating Characteristics by Northeast Census Region, 2005" " Million U.S. Housing Units" ,,"Northeast Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division"...

10

Housing Characteristics 1993 - Detailed Tables  

U.S. Energy Information Administration (EIA)

Household Characteristics by Census Region and Climate Zone, Million U.S. Households, 1993 Source: Energy Information Administration, ...

11

" of Supplier, Census Region, Census Division, and Economic Characteristics"  

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

Quantity of Purchased Electricity and Steam by Type" Quantity of Purchased Electricity and Steam by Type" " of Supplier, Census Region, Census Division, and Economic Characteristics" " of the Establishment, 1994" " (Estimates in Btu or Physical Units)" ," Electricity",," Steam" ," (million kWh)",," (billion Btu)" ,,,,,"RSE" " ","Utility","Nonutility","Utility","Nonutility","Row" "Economic Characteristics(a)","Supplier(b)","Supplier(c)","Supplier(b)","Supplier(c)","Factors"

12

Table HC14.8 Water Heating Characteristics by West Census Region ...  

U.S. Energy Information Administration (EIA)

Table HC14.8 Water Heating Characteristics by West Census Region, 2005 Million U.S. Housing Units Water Heating Characteristics Mountain Pacific West Census Region

13

Table HC11.8 Water Heating Characteristics by Northeast Census ...  

U.S. Energy Information Administration (EIA)

Water Heating Characteristics Middle Atlantic New England Northeast Census Region U.S. Housing Units (millions) Census Division Total Northeast Energy Information ...

14

Table HC12.8 Water Heating Characteristics by Midwest Census ...  

U.S. Energy Information Administration (EIA)

Water Heating Characteristics East North Central West North Central Midwest Census Region U.S. Housing Units (millions) Census Division Total Midwest

15

ac_household2001.pdf  

Annual Energy Outlook 2012 (EIA)

2a. Air Conditioning by West Census Region, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total U.S. West Census Region RSE Row Factors Total...

16

Estimating household fuel oil/kerosine, natural gas, and LPG prices by census region  

SciTech Connect

The purpose of this research is to estimate individual fuel prices within the residential sector. The data from four US Department of Energy, Energy Information Administration, residential energy consumption surveys were used to estimate the models. For a number of important fuel types - fuel oil, natural gas, and liquefied petroleum gas - the estimation presents a problem because these fuels are not used by all households. Estimates obtained by using only data in which observed fuel prices are present would be biased. A correction for this self-selection bias is needed for estimating prices of these fuels. A literature search identified no past studies on application of the selectivity model for estimating prices of residential fuel oil/kerosine, natural gas, and liquefied petroleum gas. This report describes selectivity models that utilize the Dubin/McFadden correction method for estimating prices of residential fuel oil/kerosine, natural gas, and liquefied petroleum gas in the Northeast, Midwest, South, and West census regions. Statistically significant explanatory variables are identified and discussed in each of the models. This new application of the selectivity model should be of interest to energy policy makers, researchers, and academicians.

Poyer, D.A.; Teotia, A.P.S.

1994-08-01T23:59:59.000Z

17

Census Snapshot: Alaska  

E-Print Network (OSTI)

out of all Geographic Area couples households Aleutians EastBorough Aleutians West Census Area Anchorage Municipality

Romero, Adam P; Baumle, Amanda K; Badgett, M.V. Lee; Gates, Gary J

2007-01-01T23:59:59.000Z

18

Table HC4-12a. Air Conditioning by West Census Region, Million U.S ...  

U.S. Energy Information Administration (EIA)

Table HC4-12a. Air Conditioning by West Census Region, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total U.S.

19

Table HC4-9a. Air Conditioning by Northeast Census Region, Million ...  

U.S. Energy Information Administration (EIA)

Table HC4-9a. Air Conditioning by Northeast Census Region, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total

20

char_household2001.pdf  

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

2a. Household Characteristics by West Census Region, 2a. Household Characteristics by West Census Region, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total U.S. West Census Region RSE Row Factors Total Census Division Mountain Pacific 0.5 1.0 1.8 1.1 Total .............................................................. 107.0 23.3 6.7 16.6 NE Household Size 1 Person ...................................................... 28.2 5.6 1.8 3.8 5.4 2 Persons .................................................... 35.1 7.3 1.9 5.5 4.9 3 Persons .................................................... 17.0 3.5 0.9 2.6 7.6 4 Persons .................................................... 15.6 3.5 1.1 2.4 6.4 5 Persons .................................................... 7.1 2.0 0.6 1.4 9.7 6 or More Persons

Note: This page contains sample records for the topic "household characteristics census" 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

char_household2001.pdf  

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

0a. Household Characteristics by Midwest Census Region, 0a. Household Characteristics by Midwest Census Region, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total U.S. Midwest Census Region RSE Row Factors Total Census Division East North Central West North Central 0.5 1.0 1.2 1.7 Total .............................................................. 107.0 24.5 17.1 7.4 NE Household Size 1 Person ...................................................... 28.2 6.7 4.7 2.0 6.2 2 Persons .................................................... 35.1 8.0 5.4 2.6 5.0 3 Persons .................................................... 17.0 3.8 2.7 1.1 7.9 4 Persons .................................................... 15.6 3.5 2.5 1.0 8.1 5 Persons .................................................... 7.1 1.7

22

Assumptions to the Annual Energy Outlook - Household Expenditures Module  

Gasoline and Diesel Fuel Update (EIA)

Household Expenditures Module Household Expenditures Module Assumption to the Annual Energy Outlook Household Expenditures Module Figure 5. United States Census Divisions. Having problems, call our National Energy Information Center at 202-586-8800 for help. The Household Expenditures Module (HEM) constructs household energy expenditure profiles using historical survey data on household income, population and demographic characteristics, and consumption and expenditures for fuels for various end-uses. These data are combined with NEMS forecasts of household disposable income, fuel consumption, and fuel expenditures by end-use and household type. The HEM disaggregation algorithm uses these combined results to forecast household fuel consumption and expenditures by income quintile and Census Division (see

23

Table HC13.8 Water Heating Characteristics by South Census Region ...  

U.S. Energy Information Administration (EIA)

No Separate Water Heater..... 3.4 0.9 0.6 Q Q Total South Table HC13.8 Water Heating Characteristics by South Census Region, 2005 Million U.S. Housing Units ...

24

"Table HC13.2 Living Space Characteristics by South Census Region, 2005"  

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

2 Living Space Characteristics by South Census Region, 2005" 2 Living Space Characteristics by South Census Region, 2005" " Million U.S. Housing Units" ,,"South Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total South" "Living Space Characteristics",,,"South Atlantic","East South Central","West South Central" "Total",111.1,40.7,21.7,6.9,12.1 "Floorspace (Square Feet)" "Total Floorspace1" "Fewer than 500",3.2,0.9,0.6,"Q","Q" "500 to 999",23.8,9,4.2,1.5,3.2 "1,000 to 1,499",20.8,8.6,4.7,1.5,2.5 "1,500 to 1,999",15.4,6,2.9,1.2,1.9 "2,000 to 2,499",12.2,4.1,2.1,0.7,1.3 "2,500 to 2,999",10.3,3,1.8,0.5,0.7

25

"Table HC12.1 Housing Unit Characteristics by Midwest Census Region, 2005"  

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

Housing Unit Characteristics by Midwest Census Region, 2005" Housing Unit Characteristics by Midwest Census Region, 2005" " Million U.S. Housing Units" ,,"Midwest Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total Midwest" "Housing Unit Characteristics",,,"East North Central","West North Central" "Total",111.1,25.6,17.7,7.9 "Urban/Rural Location (as Self-Reported)" "City",47.1,9.7,7.3,2.4 "Town",19,5,2.9,2.1 "Suburbs",22.7,5.7,4.3,1.4 "Rural",22.3,5.2,3.3,1.9 "Climate Zone1" "Less than 2,000 CDD and--" "Greater than 7,000 HDD",10.9,6.9,4.9,"Q" "5,500 to 7,000 HDD",26.1,12.3,9.9,"Q"

26

"Table HC13.9 Home Appliances Characteristics by South Census Region, 2005"  

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

3.9 Home Appliances Characteristics by South Census Region, 2005" 3.9 Home Appliances Characteristics by South Census Region, 2005" " Million U.S. Housing Units" ,,"South Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total South" "Home Appliances Characteristics",,,"South Atlantic","East South Central","West South Central" "Total U.S.",111.1,40.7,21.7,6.9,12.1 "Cooking Appliances" "Conventional Ovens" "Use an Oven",109.6,40.2,21.5,6.8,11.9 "1.",103.3,38.2,20.5,6.4,11.3 "2 or More",6.2,2.1,1,0.4,0.7 "Do Not Use an Oven",1.5,0.5,"Q","Q","Q" "Most-Used Oven Fuel" "Electric",67.9,30.1,17.3,5.6,7.1

27

"Table HC11.2 Living Space Characteristics by Northeast Census Region, 2005"  

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

2 Living Space Characteristics by Northeast Census Region, 2005" 2 Living Space Characteristics by Northeast Census Region, 2005" " Million U.S. Housing Units" ,,"Northeast Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total Northeast" "Living Space Characteristics",,,"Middle Atlantic","New England" "Total",111.1,20.6,15.1,5.5 "Floorspace (Square Feet)" "Total Floorspace1" "Fewer than 500",3.2,0.9,0.5,0.4 "500 to 999",23.8,4.6,3.6,1.1 "1,000 to 1,499",20.8,2.8,2.2,0.6 "1,500 to 1,999",15.4,1.9,1.4,0.5 "2,000 to 2,499",12.2,2.3,1.7,0.5 "2,500 to 2,999",10.3,2.2,1.7,0.6 "3,000 to 3,499",6.7,1.6,1,0.6

28

"Table HC11.6 Air Conditioning Characteristics by Northeast Census Region, 2005"  

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

6 Air Conditioning Characteristics by Northeast Census Region, 2005" 6 Air Conditioning Characteristics by Northeast Census Region, 2005" " Million U.S. Housing Units" ,,"Northeast Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total Northeast" "Air Conditioning Characteristics",,,"Middle Atlantic","New England" "Total",111.1,20.6,15.1,5.5 "Do Not Have Cooling Equipment",17.8,4,2.4,1.7 "Have Coolling Equipment",93.3,16.5,12.8,3.8 "Use Cooling Equipment",91.4,16.3,12.6,3.7 "Have Equipment But Do Not Use it",1.9,0.3,"Q","Q" "Air-Conditioning Equipment1, 2 " "Central System",65.9,6,5.2,0.8 "Without a Heat Pump",53.5,5.5,4.8,0.7

29

"Table HC12.8 Water Heating Characteristics by Midwest Census Region, 2005"  

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

8 Water Heating Characteristics by Midwest Census Region, 2005" 8 Water Heating Characteristics by Midwest Census Region, 2005" " Million U.S. Housing Units" ,,"Midwest Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total Midwest" "Water Heating Characteristics",,,"East North Central","West North Central" "Total",111.1,25.6,17.7,7.9 "Number of Water Heaters" "1.",106.3,24.5,17.1,7.4 "2 or More",3.7,0.9,0.5,0.4 "Do Not Use Hot Water",1.1,"Q","Q","Q" "Housing Units Served by Main Water Heater" "One Housing Unit",99.7,23.5,16.2,7.3 "Two or More Housing Units",10.3,1.9,1.4,0.5 "Do Not Use Hot Water",1.1,"Q","Q","Q"

30

"Table HC13.4 Space Heating Characteristics by South Census Region, 2005"  

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

4 Space Heating Characteristics by South Census Region, 2005" 4 Space Heating Characteristics by South Census Region, 2005" " Million U.S. Housing Units" ,,"South Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total South" "Space Heating Characteristics",,,"South Atlantic","East South Central","West South Central" "Total",111.1,40.7,21.7,6.9,12.1 "Do Not Have Space Heating Equipment",1.2,"Q","Q","N","Q" "Have Main Space Heating Equipment",109.8,40.3,21.4,6.9,12 "Use Main Space Heating Equipment",109.1,40.1,21.2,6.9,12 "Have Equipment But Do Not Use It",0.8,"Q","Q","N","N"

31

"Table HC12.9 Home Appliances Characteristics by Midwest Census Region, 2005"  

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

2.9 Home Appliances Characteristics by Midwest Census Region, 2005" 2.9 Home Appliances Characteristics by Midwest Census Region, 2005" " Million U.S. Housing Units" ,,"Midwest Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total Midwest" "Home Appliances Characteristics",,,"East North Central","West North Central" "Total U.S.",111.1,25.6,17.7,7.9 "Cooking Appliances" "Conventional Ovens" "Use an Oven",109.6,25.3,17.6,7.7 "1.",103.3,24,16.8,7.3 "2 or More",6.2,1.3,0.8,0.5 "Do Not Use an Oven",1.5,0.3,"Q","Q" "Most-Used Oven Fuel" "Electric",67.9,14.7,9.5,5.2 "Natural Gas",36.4,9.6,7.5,2.1

32

"Table HC14.4 Space Heating Characteristics by West Census Region, 2005"  

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

4 Space Heating Characteristics by West Census Region, 2005" 4 Space Heating Characteristics by West Census Region, 2005" " Million U.S. Housing Units" ,,"West Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total West" "Space Heating Characteristics",,,"Mountain","Pacific" "Total",111.1,24.2,7.6,16.6 "Do Not Have Space Heating Equipment",1.2,0.7,"Q",0.7 "Have Main Space Heating Equipment",109.8,23.4,7.5,16 "Use Main Space Heating Equipment",109.1,22.9,7.4,15.4 "Have Equipment But Do Not Use It",0.8,0.6,"Q",0.5 "Main Heating Fuel and Equipment" "Natural Gas",58.2,14.7,4.6,10.1 "Central Warm-Air Furnace",44.7,11.4,4,7.4

33

"Table HC13.11 Home Electronics Characteristics by South Census Region, 2005"  

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

1 Home Electronics Characteristics by South Census Region, 2005" 1 Home Electronics Characteristics by South Census Region, 2005" " Million U.S. Housing Units" ,,"South Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total South" "Home Electronics Characteristics",,,"South Atlantic","East South Central","West South Central" "Total",111.1,40.7,21.7,6.9,12.1 "Personal Computers" "Do Not Use a Personal Computer ",35.5,14.2,7.2,2.8,4.2 "Use a Personal Computer",75.6,26.6,14.5,4.1,7.9 "Number of Desktop PCs" "1.",50.3,18.2,10,2.9,5.3 "2.",16.2,5.5,3,0.7,1.8 "3 or More",9,2.9,1.5,0.5,0.8 "Number of Laptop PCs"

34

"Table HC13.1 Housing Unit Characteristics by South Census Region, 2005"  

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

Housing Unit Characteristics by South Census Region, 2005" Housing Unit Characteristics by South Census Region, 2005" " Million U.S. Housing Units" ,,"South Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total South" "Housing Unit Characteristics",,,"South Atlantic","East South Central","West South Central" "Total",111.1,40.7,21.7,6.9,12.1 "Urban/Rural Location (as Self-Reported)" "City",47.1,17.8,10.5,2.2,5.1 "Town",19,4.9,2.2,0.7,2 "Suburbs",22.7,7.6,4.1,1.1,2.4 "Rural",22.3,10.4,4.9,2.9,2.6 "Climate Zone1" "Less than 2,000 CDD and--" "Greater than 7,000 HDD",10.9,"N","N","N","N"

35

"Table HC13.8 Water Heating Characteristics by South Census Region, 2005"  

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

8 Water Heating Characteristics by South Census Region, 2005" 8 Water Heating Characteristics by South Census Region, 2005" " Million U.S. Housing Units" ,,"South Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total South" "Water Heating Characteristics",,,"South Atlantic","East South Central","West South Central" "Total",111.1,40.7,21.7,6.9,12.1 "Number of Water Heaters" "1.",106.3,39,21.1,6.6,11.3 "2 or More",3.7,1.5,0.5,0.3,0.7 "Do Not Use Hot Water",1.1,"Q","Q","N","Q" "Housing Units Served by Main Water Heater" "One Housing Unit",99.7,38.2,20.2,6.7,11.3 "Two or More Housing Units",10.3,2.4,1.5,0.2,0.7

36

"Table HC14.9 Home Appliances Characteristics by West Census Region, 2005"  

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

4.9 Home Appliances Characteristics by West Census Region, 2005" 4.9 Home Appliances Characteristics by West Census Region, 2005" " Million U.S. Housing Units" ,,"West Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total West" "Home Appliances Characteristics",,,"Mountain","Pacific" "Total U.S.",111.1,24.2,7.6,16.6 "Cooking Appliances" "Conventional Ovens" "Use an Oven",109.6,23.7,7.5,16.2 "1.",103.3,22.4,6.8,15.6 "2 or More",6.2,1.3,0.6,0.6 "Do Not Use an Oven",1.5,0.5,"Q",0.4 "Most-Used Oven Fuel" "Electric",67.9,13.4,4.5,8.9 "Natural Gas",36.4,9.2,2.2,7.1 "Propane/LPG",5.2,1,0.7,0.3

37

"Table HC11.9 Home Appliances Characteristics by Northeast Census Region, 2005"  

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

1.9 Home Appliances Characteristics by Northeast Census Region, 2005" 1.9 Home Appliances Characteristics by Northeast Census Region, 2005" " Million U.S. Housing Units" ,,"Northeast Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total Northeast" "Home Appliances Characteristics",,,"Middle Atlantic","New England" "Total U.S.",111.1,20.6,15.1,5.5 "Cooking Appliances" "Conventional Ovens" "Use an Oven",109.6,20.3,14.9,5.4 "1.",103.3,18.7,13.6,5.2 "2 or More",6.2,1.6,1.4,0.2 "Do Not Use an Oven",1.5,0.2,"Q","Q" "Most-Used Oven Fuel" "Electric",67.9,9.7,6.2,3.6 "Natural Gas",36.4,9.4,7.9,1.5

38

"Table HC12.2 Living Space Characteristics by Midwest Census Region, 2005"  

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

2 Living Space Characteristics by Midwest Census Region, 2005" 2 Living Space Characteristics by Midwest Census Region, 2005" " Million U.S. Housing Units" ,,"Midwest Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total Midwest" "Living Space Characteristics",,,"East North Central","West North Central" "Total",111.1,25.6,17.7,7.9 "Floorspace (Square Feet)" "Total Floorspace1" "Fewer than 500",3.2,0.5,0.3,"Q" "500 to 999",23.8,3.9,2.4,1.5 "1,000 to 1,499",20.8,4.4,3.2,1.2 "1,500 to 1,999",15.4,3.5,2.4,1.1 "2,000 to 2,499",12.2,3.2,2.1,1.1 "2,500 to 2,999",10.3,2.7,1.8,0.9 "3,000 to 3,499",6.7,2.1,1.6,0.5

39

"Table HC13.6 Air Conditioning Characteristics by South Census Region, 2005"  

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

6 Air Conditioning Characteristics by South Census Region, 2005" 6 Air Conditioning Characteristics by South Census Region, 2005" " Million U.S. Housing Units" ,,"South Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total South" "Air Conditioning Characteristics",,,"South Atlantic","East South Central","West South Central" "Total",111.1,40.7,21.7,6.9,12.1 "Do Not Have Cooling Equipment",17.8,1.4,0.8,0.2,0.3 "Have Cooling Equipment",93.3,39.3,20.9,6.7,11.8 "Use Cooling Equipment",91.4,38.9,20.7,6.6,11.7 "Have Equipment But Do Not Use it",1.9,0.5,"Q","Q","Q" "Air-Conditioning Equipment1, 2 "

40

"Table HC11.11 Home Electronics Characteristics by Northeast Census Region, 2005"  

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

1 Home Electronics Characteristics by Northeast Census Region, 2005" 1 Home Electronics Characteristics by Northeast Census Region, 2005" " Million U.S. Housing Units" ,,"Northeast Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total Northeast" "Home Electronics Characteristics",,,"Middle Atlantic","New England" "Total",111.1,20.6,15.1,5.5 "Personal Computers" "Do Not Use a Personal Computer ",35.5,6.9,5.3,1.6 "Use a Personal Computer",75.6,13.7,9.8,3.9 "Number of Desktop PCs" "1.",50.3,9.3,6.8,2.5 "2.",16.2,2.9,1.9,1 "3 or More",9,1.5,1.1,0.4 "Number of Laptop PCs" "1.",22.5,4.7,3.5,1.2 "2.",4,0.6,0.4,0.2

Note: This page contains sample records for the topic "household characteristics census" 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

"Table HC12.4 Space Heating Characteristics by Midwest Census Region, 2005"  

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

4 Space Heating Characteristics by Midwest Census Region, 2005" 4 Space Heating Characteristics by Midwest Census Region, 2005" " Million U.S. Housing Units" ,,"Midwest Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total Midwest" "Space Heating Characteristics",,,"East North Central","West North Central" "Total",111.1,25.6,17.7,7.9 "Do Not Have Space Heating Equipment",1.2,"Q","Q","N" "Have Main Space Heating Equipment",109.8,25.6,17.7,7.9 "Use Main Space Heating Equipment",109.1,25.6,17.7,7.9 "Have Equipment But Do Not Use It",0.8,"N","N","N" "Main Heating Fuel and Equipment"

42

"Table HC14.8 Water Heating Characteristics by West Census Region, 2005"  

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

8 Water Heating Characteristics by West Census Region, 2005" 8 Water Heating Characteristics by West Census Region, 2005" " Million U.S. Housing Units" ,,"West Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total West" "Water Heating Characteristics",,,"Mountain","Pacific" "Total",111.1,24.2,7.6,16.6 "Number of Water Heaters" "1.",106.3,23.2,7.1,16.1 "2 or More",3.7,1,0.4,0.6 "Do Not Use Hot Water",1.1,"Q","Q","N" "Housing Units Served by Main Water Heater" "One Housing Unit",99.7,21.9,7.1,14.8 "Two or More Housing Units",10.3,2.3,0.4,1.9 "Do Not Use Hot Water",1.1,"Q","Q","N"

43

"Table HC12.11 Home Electronics Characteristics by Midwest Census Region, 2005"  

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

1 Home Electronics Characteristics by Midwest Census Region, 2005" 1 Home Electronics Characteristics by Midwest Census Region, 2005" " Million U.S. Housing Units" ,,"Midwest Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total Midwest" "Home Electronics Characteristics",,,"East North Central","West North Central" "Total",111.1,25.6,17.7,7.9 "Personal Computers" "Do Not Use a Personal Computer ",35.5,8.1,5.6,2.5 "Use a Personal Computer",75.6,17.5,12.1,5.4 "Number of Desktop PCs" "1.",50.3,11.9,8.4,3.4 "2.",16.2,3.5,2.2,1.3 "3 or More",9,2.1,1.5,0.6 "Number of Laptop PCs" "1.",22.5,4.6,2.8,1.9 "2.",4,0.9,0.6,0.2

44

Table HC1-3a. Housing Unit Characteristics by Household Income,  

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

3a. Housing Unit Characteristics by Household Income, 3a. Housing Unit Characteristics by Household Income, Million U.S. Households, 2001 Housing Unit Characteristics RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral Assist- ance 1 RSE Row Factors Less than $14,999 $15,000 to $29,999 $30,000 to $49,999 $50,000 or More 0.6 1.3 1.1 1.0 0.9 1.4 1.0 Total ............................................... 107.0 18.7 22.9 27.1 38.3 15.0 33.8 3.3 Census Region and Division Northeast ...................................... 20.3 3.3 4.2 4.9 7.8 2.6 6.8 6.4 New England .............................. 5.4 0.8 1.1 1.3 2.3 0.6 1.6 9.9 Middle Atlantic ............................ 14.8 2.6 3.2 3.5 5.6 2.0 5.2 7.7 Midwest ......................................... 24.5 3.7 5.2 6.8 8.9 2.8 7.4 5.8 East North Central ......................

45

"Table HC14.2 Living Space Characteristics by West Census Region, 2005"  

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

2 Living Space Characteristics by West Census Region, 2005" 2 Living Space Characteristics by West Census Region, 2005" " Million U.S. Housing Units" ,,"West Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total West" "Living Space Characteristics",,,"Mountain","Pacific" "Total",111.1,24.2,7.6,16.6 "Floorspace (Square Feet)" "Total Floorspace1" "Fewer than 500",3.2,1,0.2,0.8 "500 to 999",23.8,6.3,1.4,4.9 "1,000 to 1,499",20.8,5,1.6,3.4 "1,500 to 1,999",15.4,4,1.4,2.6 "2,000 to 2,499",12.2,2.6,0.9,1.7 "2,500 to 2,999",10.3,2.4,0.9,1.4 "3,000 to 3,499",6.7,0.9,0.3,0.6 "3,500 to 3,999",5.2,0.9,0.4,0.5

46

Table HC11.1 Housing Unit Characteristics by Northeast Census Region, 2005  

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

1.1 Housing Unit Characteristics by Northeast Census Region, 2005 1.1 Housing Unit Characteristics by Northeast Census Region, 2005 Total......................................................................... 111.1 20.6 15.1 5.5 Urban/Rural Location (as Self-Reported) City....................................................................... 47.1 6.9 4.7 2.2 Town..................................................................... 19.0 6.0 4.2 1.9 Suburbs................................................................ 22.7 4.4 4.0 0.5 Rural..................................................................... 22.3 3.2 2.3 0.9 Climate Zone 1 Less than 2,000 CDD and-- Greater than 7,000 HDD.................................... 10.9 1.9 Q 1.3 5,500 to 7,000 HDD........................................... 26.1 9.8 5.7 4.1 4,000 to 5,499 HDD...........................................

47

char_household2001.pdf  

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

1a. Household Characteristics by South Census Region, 1a. Household Characteristics by South Census Region, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total U.S. South Census Region RSE Row Factors Total Census Division South Atlantic East South Central West South Central 0.5 0.8 1.1 1.5 1.6 Total .............................................................. 107.0 38.9 20.3 6.8 11.8 NE Household Size 1 Person ...................................................... 28.2 9.9 5.0 1.8 3.1 6.3 2 Persons .................................................... 35.1 13.0 6.7 2.5 3.8 4.2 3 Persons .................................................... 17.0 6.6 3.7 1.2 1.7 8.8 4 Persons .................................................... 15.6 6.0 3.3 0.8 1.9 10.7 5 Persons ....................................................

48

"Table HC10.4 Space Heating Characteristics by U.S. Census Region, 2005"  

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

4 Space Heating Characteristics by U.S. Census Region, 2005" 4 Space Heating Characteristics by U.S. Census Region, 2005" " Million U.S. Housing Units" ,"Housing Units (millions)","U.S. Census Region" "Space Heating Characteristics",,"Northeast","Midwest","South","West" "Total",111.1,20.6,25.6,40.7,24.2 "Do Not Have Space Heating Equipment",1.2,"Q","Q","Q",0.7 "Have Main Space Heating Equipment",109.8,20.5,25.6,40.3,23.4 "Use Main Space Heating Equipment",109.1,20.5,25.6,40.1,22.9 "Have Equipment But Do Not Use It",0.8,"N","N","Q",0.6 "Main Heating Fuel and Equipment" "Natural Gas",58.2,11.4,18.4,13.6,14.7

49

"Table HC10.8 Water Heating Characteristics by U.S. Census Region, 2005"  

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

8 Water Heating Characteristics by U.S. Census Region, 2005" 8 Water Heating Characteristics by U.S. Census Region, 2005" " Million U.S. Housing Units" ,"Housing Units (millions)","U.S. Census Region" "Water Heating Characteristics",,"Northeast","Midwest","South","West" "Total",111.1,20.6,25.6,40.7,24.2 "Number of Water Heaters" "1.",106.3,19.6,24.5,39,23.2 "2 or More",3.7,0.3,0.9,1.5,1 "Do Not Use Hot Water",1.1,0.7,"Q","Q","Q" "Housing Units Served by Main Water Heater" "One Housing Unit",99.7,16.1,23.5,38.2,21.9 "Two or More Housing Units",10.3,3.7,1.9,2.4,2.3 "Do Not Use Hot Water",1.1,0.7,"Q","Q","Q"

50

Household and environmental characteristics related to household energy-consumption change: A human ecological approach  

Science Conference Proceedings (OSTI)

This study focused on the family household as an organism and on its interaction with the three environments of the human ecosystem (natural, behavioral, and constructed) as these influence energy consumption and energy-consumption change. A secondary statistical analysis of data from the US Department of Energy Residential Energy Consumption Surveys (RECS) was completed. The 1980 and 1983 RECS were used as the data base. Longitudinal data, including household, environmental, and energy-consumption measures, were available for over 800 households. The households were selected from a national sample of owner-occupied housing units surveyed in both years. Results showed a significant( p = household, cooling degree days, heating degree days, year the housing unit was built, and number of stories in the housing unit.

Guerin, D.A.

1988-01-01T23:59:59.000Z

51

Table 1. Household Characteristics by Ceiling Fans, 2001  

U.S. Energy Information Administration (EIA)

A reporting of the number of housing units using ceiling fans in U.S. households as reported in the 2001 Residential Energy Consumption Survey

52

Ventilation Behavior and Household Characteristics in NewCalifornia Houses  

SciTech Connect

A survey was conducted to determine occupant use of windows and mechanical ventilation devices; barriers that inhibit their use; satisfaction with indoor air quality (IAQ); and the relationship between these factors. A questionnaire was mailed to a stratified random sample of 4,972 single-family detached homes built in 2003, and 1,448 responses were received. A convenience sample of 230 houses known to have mechanical ventilation systems resulted in another 67 completed interviews. Some results are: (1) Many houses are under-ventilated: depending on season, only 10-50% of houses meet the standard recommendation of 0.35 air changes per hour. (2) Local exhaust fans are under-utilized. For instance, about 30% of households rarely or never use their bathroom fan. (3) More than 95% of households report that indoor air quality is ''very'' or ''somewhat'' acceptable, although about 1/3 of households also report dustiness, dry air, or stagnant or humid air. (4) Except households where people cook several hours per week, there is no evidence that households with significant indoor pollutant sources get more ventilation. (5) Except households containing asthmatics, there is no evidence that health issues motivate ventilation behavior. (6) Security and energy saving are the two main reasons people close windows or keep them closed.

Price, Phillip N.; Sherman, Max H.

2006-02-01T23:59:59.000Z

53

appl_household2001.pdf  

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

9a. Appliances by Northeast Census Region, 9a. Appliances by Northeast Census Region, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total U.S. Northeast Census Region RSE Row Factors Total Census Division Middle Atlantic New England 0.5 1.0 1.3 1.6 Total .............................................................. 107.0 20.3 14.8 5.4 NE Kitchen Appliances Cooking Appliances Oven ......................................................... 101.7 19.6 14.5 5.2 1.1 1 .............................................................. 95.2 18.2 13.3 4.9 1.1 2 or More ................................................. 6.5 1.4 1.1 0.3 11.7 Most Used Oven ...................................... 101.7 19.6 14.5 5.2 1.1 Electric .....................................................

54

spaceheat_household2001.pdf  

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

1a. Space Heating by South Census Region, 1a. Space Heating by South Census Region, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total U.S. South Census Region RSE Row Factors Total Census Division South Atlantic East South Central West South Central 0.5 0.9 1.2 1.4 1.3 Total .............................................................. 107.0 38.9 20.3 6.8 11.8 NE Heat Home .................................................... 106.0 38.8 20.2 6.8 11.8 NE Do Not Heat Home ....................................... 1.0 Q Q Q Q 20.1 No Heating Equipment ................................ 0.5 Q Q Q Q 39.8 Have Equipment But Do Not Use It ............................................... 0.4 Q Q Q Q 39.0 Main Heating Fuel and Equipment (Have and Use Equipment) ........................... 106.0

55

spaceheat_household2001.pdf  

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

9a. Space Heating by Northeast Census Region, 9a. Space Heating by Northeast Census Region, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total U.S. Northeast Census Region RSE Row Factors Total Census Division Middle Atlantic New England 0.5 1.0 1.2 1.7 Total .............................................................. 107.0 20.3 14.8 5.4 NE Heat Home .................................................... 106.0 20.1 14.7 5.4 NE Do Not Heat Home ....................................... 1.0 Q Q Q 19.9 No Heating Equipment ................................ 0.5 Q Q Q 39.5 Have Equipment But Do Not Use It ............................................... 0.4 Q Q Q 38.7 Main Heating Fuel and Equipment (Have and Use Equipment) ........................... 106.0 20.1 14.7 5.4 NE Natural Gas .................................................

56

spaceheat_household2001.pdf  

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

0a. Space Heating by Midwest Census Region, 0a. Space Heating by Midwest Census Region, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total U.S. Midwest Census Region RSE Row Factors Total Census Division East North Central West North Central 0.5 1.0 1.2 1.6 Total .............................................................. 107.0 24.5 17.1 7.4 NE Heat Home .................................................... 106.0 24.5 17.1 7.4 NE Do Not Heat Home ....................................... 1.0 Q Q Q 19.8 No Heating Equipment ................................ 0.5 Q Q Q 39.2 Have Equipment But Do Not Use It ............................................... 0.4 Q Q Q 38.4 Main Heating Fuel and Equipment (Have and Use Equipment) ........................... 106.0 24.5 17.1 7.4 NE Natural Gas

57

spaceheat_household2001.pdf  

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

2a. Space Heating by West Census Region, 2a. Space Heating by West Census Region, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total U.S. West Census Region RSE Row Factors Total Census Division Mountain Pacific 0.6 1.0 1.6 1.2 Total .............................................................. 107.0 23.3 6.7 16.6 NE Heat Home .................................................... 106.0 22.6 6.7 15.9 NE Do Not Heat Home ....................................... 1.0 0.7 Q 0.7 10.6 No Heating Equipment ................................ 0.5 0.4 Q 0.4 18.1 Have Equipment But Do Not Use It ............................................... 0.4 0.2 Q 0.2 27.5 Main Heating Fuel and Equipment (Have and Use Equipment) ........................... 106.0 22.6 6.7 15.9 NE Natural Gas .................................................

58

appl_household2001.pdf  

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

2a. Appliances by West Census Region, 2a. Appliances by West Census Region, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total U.S. West Census Region RSE Row Factors Total Census Division Mountain Pacific 0.5 1.0 1.7 1.2 Total .............................................................. 107.0 23.3 6.7 16.6 NE Kitchen Appliances Cooking Appliances Oven ......................................................... 101.7 22.1 6.6 15.5 1.1 1 .............................................................. 95.2 20.9 6.4 14.5 1.1 2 or More ................................................. 6.5 1.2 0.2 1.0 14.6 Most Used Oven ...................................... 101.7 22.1 6.6 15.5 1.1 Electric .....................................................

59

Household solid waste characteristics and management in Chittagong, Bangladesh  

Science Conference Proceedings (OSTI)

Solid waste management (SWM) is a multidimensional challenge faced by urban authorities, especially in developing countries like Bangladesh. We investigated per capita waste generation by residents, its composition, and the households' attitudes towards waste management at Rahman Nagar Residential Area, Chittagong, Bangladesh. The study involved a structured questionnaire and encompassed 75 households from five different socioeconomic groups (SEGs): low (LSEG), lower middle (LMSEG), middle (MSEG), upper middle (UMSEG) and high (HSEG). Wastes, collected from all of the groups of households, were segregated and weighed. Waste generation was 1.3 kg/household/day and 0.25 kg/person/day. Household solid waste (HSW) was comprised of nine categories of wastes with vegetable/food waste being the largest component (62%). Vegetable/food waste generation increased from the HSEG (47%) to the LSEG (88%). By weight, 66% of the waste was compostable in nature. The generation of HSW was positively correlated with family size (r{sub xy} = 0.236, p management initiative. Of the respondents, an impressive 44% were willing to pay US$0.3 to US$0.4 per month to waste collectors and it is recommended that service charge be based on the volume of waste generated by households. Almost a quarter (22.7%) of the respondents preferred 12-1 pm as the time period for their waste to be collected. This study adequately shows that household solid waste can be converted from burden to resource through segregation at the source, since people are aware of their role in this direction provided a mechanism to assist them in this pursuit exists and the burden is distributed according to the amount of waste generated.

Sujauddin, Mohammad [Institute of Forestry and Environmental Sciences, Chittagong University, Chittagong-4331 (Bangladesh)], E-mail: mohammad.sujauddin@gmail.com; Huda, S.M.S. [Institute of Forestry and Environmental Sciences, Chittagong University, Chittagong-4331 (Bangladesh); Hoque, A.T.M. Rafiqul [Institute of Forestry and Environmental Sciences, Chittagong University, Chittagong-4331 (Bangladesh); Laboratory of Ecology and Systematics (Plant Ecophysiology Section), Faculty of Science, Biology Division, University of the Ryukyus, Okinawa 903-0213 (Japan)

2008-07-01T23:59:59.000Z

60

Table HC6.11 Home Electronics Characteristics by Number of Household...  

Gasoline and Diesel Fuel Update (EIA)

1 Home Electronics Characteristics by Number of Household Members, 2005 Total... 111.1 30.0 34.8 18.4 15.9 12.0...

Note: This page contains sample records for the topic "household characteristics census" 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 HC10.9 Home Appliances Characteristics by U.S. Census Regions, 2005"  

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

0.9 Home Appliances Characteristics by U.S. Census Regions, 2005" 0.9 Home Appliances Characteristics by U.S. Census Regions, 2005" " Million U.S. Housing Units" ,"Housing Units (millions)","U.S. Census Region" "Home Appliances Characteristics",,"Northeast","Midwest","South","West" "Total U.S.",111.1,20.6,25.6,40.7,24.2 "Cooking Appliances" "Conventional Ovens" "Use an Oven",109.6,20.3,25.3,40.2,23.7 "1.",103.3,18.7,24,38.2,22.4 "2 or More",6.2,1.6,1.3,2.1,1.3 "Do Not Use an Oven",1.5,0.2,0.3,0.5,0.5 "Most-Used Oven Fuel" "Electric",67.9,9.7,14.7,30.1,13.4 "Natural Gas",36.4,9.4,9.6,8.1,9.2 "Propane/LPG",5.2,1.2,1.1,2,1

62

"Table HC10.2 Living Space Characteristics by U.S. Census Region, 2005"  

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

2 Living Space Characteristics by U.S. Census Region, 2005" 2 Living Space Characteristics by U.S. Census Region, 2005" " Million U.S. Housing Units" ,"Housing Units (millions)","U.S. Census Region" "Living Space Characteristics",,"Northeast","Midwest","South","West" "Total",111.1,20.6,25.6,40.7,24.2 "Floorspace (Square Feet)" "Total Floorspace1" "Fewer than 500",3.2,0.9,0.5,0.9,1 "500 to 999",23.8,4.6,3.9,9,6.3 "1,000 to 1,499",20.8,2.8,4.4,8.6,5 "1,500 to 1,999",15.4,1.9,3.5,6,4 "2,000 to 2,499",12.2,2.3,3.2,4.1,2.6 "2,500 to 2,999",10.3,2.2,2.7,3,2.4 "3,000 to 3,499",6.7,1.6,2.1,2.1,0.9 "3,500 to 3,999",5.2,1.1,1.7,1.5,0.9

63

ac_household2001.pdf  

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

0a. Air Conditioning by Midwest Census Region, 0a. Air Conditioning by Midwest Census Region, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total U.S. Midwest Census Region RSE Row Factors Total Census Division East North Central West North Central 0.5 1.0 1.2 1.4 Households With Electric Air-Conditioning Equipment ...................... 82.9 20.5 13.6 6.8 2.2 Air Conditioners Not Used ........................... 2.1 0.3 Q Q 27.5 Households Using Electric Air-Conditioning 1 ........................................ 80.8 20.2 13.4 6.7 2.3 Type of Electric Air-Conditioning Used Central Air-Conditioning 2 ............................ 57.5 14.3 9.5 4.8 3.8 Without a Heat Pump ................................ 46.2 13.6 9.0 4.6 3.9 With a Heat Pump .....................................

64

ac_household2001.pdf  

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

1a. Air Conditioning by South Census Region, 1a. Air Conditioning by South Census Region, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total U.S. South Census Region RSE Row Factors Total Census Division South Atlantic East South Central West South Central 0.5 0.8 1.2 1.3 1.4 Households With Electric Air-Conditioning Equipment ...................... 82.9 37.2 19.3 6.4 11.5 1.5 Air Conditioners Not Used ........................... 2.1 0.4 Q Q Q 28.2 Households Using Electric Air-Conditioning 1 ........................................ 80.8 36.9 19.0 6.4 11.5 1.6 Type of Electric Air-Conditioning Used Central Air-Conditioning 2 ............................ 57.5 30.4 16.1 5.0 9.2 2.8 Without a Heat Pump ................................ 46.2 22.1 10.4 3.4 8.3 5.6 With a Heat Pump

65

ac_household2001.pdf  

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

9a. Air Conditioning by Northeast Census Region, 9a. Air Conditioning by Northeast Census Region, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total U.S. Northeast Census Region RSE Row Factors Total Census Division Middle Atlantic New England 0.5 1.0 1.2 1.8 Households With Electric Air-Conditioning Equipment ...................... 82.9 14.5 11.3 3.2 3.3 Air Conditioners Not Used ........................... 2.1 0.3 0.3 Q 28.3 Households Using Electric Air-Conditioning 1 ........................................ 80.8 14.2 11.1 3.2 3.4 Type of Electric Air-Conditioning Used Central Air-Conditioning 2 ............................ 57.5 5.7 4.9 0.8 8.9 Without a Heat Pump ................................ 46.2 5.2 4.5 0.7 9.2 With a Heat Pump .....................................

66

"Table HC14.1 Housing Unit Characteristics by West Census Region...  

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

areas, determined according to the 30-year average (1971-2000) of the annual heating and cooling degree-days. A household is assigned to a climate zone according to the 30-year...

67

"Table HC10.1 Housing Unit Characteristics by U.S. Census Region...  

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

areas, determined according to the 30-year average (1971-2000) of the annual heating and cooling degree-days. A household is assigned to a climate zone according to the 30-year...

68

"Table HC11.1 Housing Unit Characteristics by Northeast Census...  

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

areas, determined according to the 30-year average (1971-2000) of the annual heating and cooling degree-days.. A household is assigned to a climate zone according to the 30-year...

69

"Table HC15.3 Household Characteristics by Four Most Populated States, 2005"  

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

3 Household Characteristics by Four Most Populated States, 2005" 3 Household Characteristics by Four Most Populated States, 2005" " Million U.S. Housing Units" ,"Housing Units (millions)","Four Most Populated States" "Household Characteristics",,"New York","Florida","Texas","California" "Total",111.1,7.1,7,8,12.1 "Household Size" "1 Person",30,1.8,1.9,2,3.2 "2 Persons",34.8,2.2,2.3,2.4,3.2 "3 Persons",18.4,1.1,1.3,1.2,1.8 "4 Persons",15.9,1,0.9,1,2.3 "5 Persons",7.9,0.6,0.6,0.9,0.9 "6 or More Persons",4.1,0.4,"Q",0.5,0.7 "2005 Annual Household Income Category" "Less than $9,999",9.9,0.8,0.7,0.9,1 "$10,000 to $14,999",8.5,0.8,0.4,0.6,0.7

70

Improving Demographic Components of Integrated Assessment Models: The Effect of Changes in Population Composition by Household Characteristics  

SciTech Connect

This report describes results of the research project on "Improving Demographic Components of Integrated Assessment Models: The Effect of Changes in Population Composition by Household Characteristics". The overall objective of this project was to improve projections of energy demand and associated greenhouse gas emissions by taking into account demographic factors currently not incorporated in Integrated Assessment Models (IAMs) of global climate change. We proposed to examine the potential magnitude of effects on energy demand of changes in the composition of populations by household characteristics for three countries: the U.S., China, and Indonesia. For each country, we planned to analyze household energy use survey data to estimate relationships between household characteristics and energy use; develop a new set of detailed household projections for each country; and combine these analyses to produce new projections of energy demand illustrating the potential importance of consideration of households.

Brian C. O'Neill

2006-08-09T23:59:59.000Z

71

char_household2001.pdf  

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

Household Tables Household Tables (Million U.S. Households; 24 pages, 122 kb) Contents Pages HC2-1a. Household Characteristics by Climate Zone, Million U.S. Households, 2001 2 HC2-2a. Household Characteristics by Year of Construction, Million U.S. Households, 2001 2 HC2-3a. Household Characteristics by Household Income, Million U.S. Households, 2001 2 HC2-4a. Household Characteristics by Type of Housing Unit, Million U.S. Households, 2001 2 HC2-5a. Household Characteristics by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 2 HC2-6a. Household Characteristics by Type of Rented Housing Unit, Million U.S. Households, 2001 2 HC2-7a. Household Characteristics by Four Most Populated States, Million U.S. Households, 2001 2

72

"Table HC11.4 Space Heating Characteristics by Northeast Census...  

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

Consumption Survey. " " Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables" "Table HC11.4 Space Heating...

73

"Table HC14.6 Air Conditioning Characteristics by West Census...  

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

Characteristics",,,"Mountain","Pacific" "Total",111.1,24.2,7.6,16.6 "Do Not Have Cooling Equipment",17.8,10.3,3.1,7.3 "Have Cooling Equipment",93.3,13.9,4.5,9.4 "Use...

74

Table HC6.9 Home Appliances Characteristics by Number of Household Members, 2005  

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

HC6.9 Home Appliances Characteristics by Number of Household Members, 2005 HC6.9 Home Appliances Characteristics by Number of Household Members, 2005 Total U.S.............................................................. 111.1 30.0 34.8 18.4 15.9 12.0 Cooking Appliances Conventional Ovens Use an Oven.................................................. 109.6 29.5 34.4 18.2 15.7 11.8 1................................................................. 103.3 28.4 32.0 17.3 14.7 11.0 2 or More.................................................... 6.2 1.1 2.5 1.0 0.9 0.8 Do Not Use an Oven...................................... 1.5 0.6 0.4 Q Q Q Most-Used Oven Fuel Electric....................................................... 67.9 18.2 22.5 11.2 9.5 6.5 Natural Gas................................................ 36.4 9.9 10.0 6.1 5.6 4.7 Propane/LPG.............................................

75

Table HC6.4 Space Heating Characteristics by Number of Household Members, 2005  

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

4 Space Heating Characteristics by Number of Household Members, 2005 4 Space Heating Characteristics by Number of Household Members, 2005 Total..................................................................... 111.1 30.0 34.8 18.4 15.9 12.0 Do Not Have Space Heating Equipment............ 1.2 0.3 0.3 Q 0.2 0.2 Have Main Space Heating Equipment............... 109.8 29.7 34.5 18.2 15.6 11.8 Use Main Space Heating Equipment................. 109.1 29.5 34.4 18.1 15.5 11.6 Have Equipment But Do Not Use It................... 0.8 Q Q Q Q Q Main Heating Fuel and Equipment Natural Gas....................................................... 58.2 15.6 18.0 9.5 8.4 6.7 Central Warm-Air Furnace............................. 44.7 10.7 14.3 7.6 6.9 5.2 For One Housing Unit................................ 42.9 10.1 13.8 7.3 6.5 5.2 For Two Housing Units...............................

76

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

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

Components of Total Electricity Demand by Census Region, Census Division, and" Components of Total Electricity Demand by Census Region, Census Division, and" " Economic Characteristics of the Establishment, 1994" " (Estimates in Million Kilowatthours)" " "," "," "," ","Sales/"," ","RSE" " "," ","Transfers","Onsite","Transfers"," ","Row" "Economic Characteristics(a)","Purchases","In(b)","Generation(c)","Offsite","Net Demand(d)","Factors" ,"Total United States" "RSE Column Factors:",0.5,2.1,1.2,2,0.4 "Value of Shipments and Receipts"

77

Key Words: Power Plants, Hedonic Price Method, Restricted Census Microdata  

E-Print Network (OSTI)

This paper uses restricted census microdata to examine housing values and rents for neighborhoods in the United States where power plants were opened during the 1990s. Compared to neighborhoods with similar housing and demographic characteristics, neighborhoods within two miles of plants experienced 3-7 percent decreases in housing values and rents with some evidence of larger decreases within one mile and for large capacity plants. In addition, there is evidence of taste-based sorting with neighborhoods near plants associated with modest but statistically significant decreases in mean household income, educational attainment, and the proportion of homes that is owner occupied.

Lucas W. Davis; Jel D; Michael Greenstone; Matt Kahn; Ian Lange; Matt White; Seminar Participants

2010-01-01T23:59:59.000Z

78

Census Snapshot: Michigan  

E-Print Network (OSTI)

INSTITUTE CENSUS SNAPSHOT | MICHIGAN | SEPTEMBER 2007INSTITUTE CENSUS SNAPSHOT | MICHIGAN | SEPTEMBER 2007 AboutMICHIGAN Adam P. Romero, Public Policy Fellow Amanda Baumle,

Romero, Adam P; Baumle, Amanda; Badgett, M.V. Lee; Gates, Gary J

2007-01-01T23:59:59.000Z

79

Household energy and consumption and expenditures, 1990. Supplement, Regional  

Science Conference Proceedings (OSTI)

The purpose of this supplement to the Household Energy Consumption and Expenditures 1990 report is to provide information on the use of energy in residential housing units, specifically at the four Census regions and nine Census division levels. This report includes household energy consumption, expenditures, and prices for natural gas, electricity, fuel oil, liquefied petroleum gas (LPG), and kerosene as well as household wood consumption. For national-level data, see the main report, Household Energy Consumption and Expenditures 1990.

Not Available

1993-03-02T23:59:59.000Z

80

homeoffice_household2001.pdf  

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

9a. Home Office Equipment by Northeast Census Region, 9a. Home Office Equipment by Northeast Census Region, Million U.S. Households, 2001 Home Office Equipment RSE Column Factor: Total U.S. Northeast Census Region RSE Row Factors Total Census Division Middle Atlantic New England 0.5 1.1 1.4 1.2 Total .............................................................. 107.0 20.3 14.8 5.4 NE Households Using Office Equipment ......................................... 96.2 17.9 12.8 5.0 1.3 Personal Computers 1 ................................. 60.0 10.9 7.7 3.3 3.1 Number of Desktop PCs 1 ................................................................ 45.1 8.7 6.2 2.5 3.7 2 or more ................................................... 9.1 1.4 0.9 0.5 12.9 Number of Laptop PCs 1 ................................................................

Note: This page contains sample records for the topic "household characteristics census" 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

homeoffice_household2001.pdf  

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

0a. Home Office Equipment by Midwest Census Region, 0a. Home Office Equipment by Midwest Census Region, Million U.S. Households, 2001 Home Office Equipment RSE Column Factor: Total U.S. Midwest Census Region RSE Row Factors Total Census Division East North Central West North Central 0.5 1.0 1.2 1.6 Total .............................................................. 107.0 24.5 17.1 7.4 NE Households Using Office Equipment ......................................... 96.2 22.4 15.7 6.7 1.3 Personal Computers 1 ................................. 60.0 14.1 9.9 4.2 3.7 Number of Desktop PCs 1 ................................................................ 45.1 10.4 7.2 3.2 3.7 2 or more ................................................... 9.1 2.3 1.6 0.7 10.1 Number of Laptop PCs 1 ................................................................

82

Texas Census Snapshot: 2010  

E-Print Network (OSTI)

Abilene Missouri Conroe Texas Odessa San Angelo LongviewTexas Census Snapshot: 2010 Same-sex couples Same-sex

Gates, Gary J.; Cooke, Abigail M.

2011-01-01T23:59:59.000Z

83

Colorado Census Snapshot: 2010  

E-Print Network (OSTI)

Colorado Census Snapshot: 2010 Same-sex couples Same-sexThornton Longmont Northglenn Colorado Springs Fort Collins

Gates, Gary J.; Cooke, Abigail M.

2011-01-01T23:59:59.000Z

84

housingunit_household2001.pdf  

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

Housing Unit Tables Housing Unit Tables (Million U.S. Households; 49 pages, 210 kb) Contents Pages HC1-1a. Housing Unit Characteristics by Climate Zone, Million U.S. Households, 2001 5 HC1-2a. Housing Unit Characteristics by Year of Construction, Million U.S. Households, 2001 4 HC1-3a. Housing Unit Characteristics by Household Income, Million U.S. Households, 2001 4 HC1-4a. Housing Unit Characteristics by Type of Housing Unit, Million U.S. Households, 2001 4 HC1-5a. Housing Unit Characteristics by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 4 HC1-6a. Housing Unit Characteristics by Type of Rented Housing Unit, Million U.S. Households, 2001 4 HC1-7a. Housing Unit Characteristics by Four Most Populated States, Million U.S. Households, 2001 4

85

Table 2. Percent of Households with Vehicles, Selected Survey Years  

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

Percent of Households with Vehicles, Selected Survey Years " Percent of Households with Vehicles, Selected Survey Years " ,"Survey Years" ,1983,1985,1988,1991,1994,2001 "Total",85.5450237,89.00343643,88.75545852,89.42917548,87.25590956,92.08566108 "Household Characteristics" "Census Region and Division" " Northeast",77.22222222,"NA",79.16666667,82.9015544,75.38461538,85.09615385 " New England",88.37209302,"NA",81.81818182,82.9787234,82,88.52459016 " Middle Atlantic ",73.72262774,"NA",78.37837838,82.31292517,74.30555556,83.67346939 " Midwest ",85.51401869,"NA",90.66666667,90.17094017,92.30769231,91.47286822 " East North Central",82,"NA",88.81987578,89.88095238,91.51515152,90.55555556

86

Table CE1-10c. Total Energy Consumption in U.S. Households by ...  

U.S. Energy Information Administration (EIA)

Table CE1-10c. Total Energy Consumption in U.S. Households by Midwest Census Region, 2001 RSE Column Factor: Total U.S. Midwest Census Region RSE Row

87

Table 4. LPG Consumption and Expeditures in U.S. Households by End ...  

U.S. Energy Information Administration (EIA)

Table 4. LPG Consumption and Expeditures in U.S. Households by End Uses and Census Region, 2001 RSE Column Factor: Total U.S. Census Region RSE Row

88

Evidence from Restricted Census Microdata  

E-Print Network (OSTI)

Current trends in electricity consumption imply that hundreds of new fossil-fuel power plants will be built in the United States over the next several decades. Power plant siting has become increasingly contentious, in part because power plants are a source of numerous negative local externalities including elevated levels of air pollution, haze, noise and traffic. Policymakers attempt to take these local disamenities into account when siting facilities, but little reliable evidence is available about their quantitative importance. This paper examines neighborhoods in the United States where power plants were opened during the 1990s using household-level data from a restricted version of the U.S. decennial census. Compared to neighborhoods farther away, housing values and rents decreased by 3-5 % between 1990 and 2000 in neighborhoods near sites. Estimates of household marginal willingness-to-pay to avoid power plants are reported separately for natural gas and other types of plants, large plants and small plants, base load plants and peaker plants, and upwind and downwind households.

Lucas W. Davis; Lucas W. Davis; Jel D

2008-01-01T23:59:59.000Z

89

Census Snapshot: Vermont  

E-Print Network (OSTI)

THE WILLIAMS INSTITUTE CENSUS SNAPSHOT VERMONT DECEMBER 2007VERMONT Adam P. Romero, Public Policy Fellow Amanda K.couples raising children in Vermont. We compare same-sex “

Romero, Adam P; Baumle, Amanda K; Badgett, M.V. Lee; Gates, Gary J

2007-01-01T23:59:59.000Z

90

Residential Census Maps - Energy Information Administration  

U.S. Energy Information Administration (EIA)

Home >>Energy Users > Residential Home Page > Census Maps . U. S. Census Regions and Divisions: Contact: James ...

91

Census Snapshot: Texas  

E-Print Network (OSTI)

THE WILLIAMS INSTITUTE CENSUS SNAPSHOT TEXAS JANUARY 2008TEXAS Adam P. Romero, Public Policy Fellow Clifford J.sex couples raising children in Texas. We compare same-sex “

Romero, Adam P; Rosky, Clifford J; Badgett, M.V. Lee; Gates, Gary J

2008-01-01T23:59:59.000Z

92

Census Snapshot: Idaho  

E-Print Network (OSTI)

THE WILLIAMS INSTITUTE CENSUS SNAPSHOT IDAHO APRIL 2008IDAHO Adam P. Romero, Public Policy Fellow Clifford J.sex couples raising children in Idaho. We compare same-sex “

Romero, Adam P; Rosky, Clifford J; Badgett, M.V. Lee; Gates, Gary J

2008-01-01T23:59:59.000Z

93

Idaho Census Snapshot: 2010  

E-Print Network (OSTI)

Idaho Census Snapshot: 2010 Same-sex couples Husband/wifeFranklin Fremont Gem Gooding Idaho Jefferson Jerome LemhiTwin Falls Nampa Caldwell Idaho Falls Meridian About the

Gates, Gary J.; Cooke, Abigail M.

2011-01-01T23:59:59.000Z

94

Census Snapshot: Puerto Rico  

E-Print Network (OSTI)

WILLIAMS INSTITUTE CENSUS SNAPSHOT PUERTO RICO APRIL 2008PUERTO RICO Adam P. Romero, Public Policy Fellow Clifford J.in the Commonwealth of Puerto Rico. We compare same-sex “

Romero, Adam P; Rosky, Clifford J; Badgett, M.V. Lee; Gates, Gary J

2008-01-01T23:59:59.000Z

95

Census Snapshot: New Mexico  

E-Print Network (OSTI)

THE WILLIAMS INSTITUTE CENSUS SNAPSHOT NEW MEXICO APRIL 2008NEW MEXICO Adam P. Romero, Public Policy Fellow Clifford J.raising children in New Mexico. We compare same-sex “

Romero, Adam P.; Rosky, Clifford J; Badgett, M.V. Lee; Gates, Gary J

2008-01-01T23:59:59.000Z

96

Characteristics, Welfare Use and Material Hardship Among California AFDC Households with Disabled and Chronically Ill Family Members  

E-Print Network (OSTI)

completed telephone survey o f AFDC-recipient households tocare for disabled members. When AFDC and SSI are consideredfamilies in this sample of AFDC recipient families were very

Meyers, Marcia k.

1996-01-01T23:59:59.000Z

97

"Table A33. Total Quantity of Purchased Energy Sources by Census Region, Census Division,"  

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

Quantity of Purchased Energy Sources by Census Region, Census Division," Quantity of Purchased Energy Sources by Census Region, Census Division," " and Economic Characteristics of the Establishment, 1994" " (Estimates in Btu or Physical Units)" ,,,,,"Natural",,,"Coke" " ","Total","Electricity","Residual","Distillate","Gas(c)"," ","Coal","and Breeze","Other(d)","RSE" " ","(trillion","(million","Fuel Oil","Fuel Oil(b)","(billion","LPG","(1000 ","(1000","(trillion","Row" "Economic Characteristics(a)","Btu)","kWh)","(1000 bbl)","(1000 bbl)","cu ft)","(1000 bbl)","short tons)","short tons)","Btu)","Factors"

98

homeoffice_household2001.pdf  

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

1a. Home Office Equipment by South Census Region, 1a. Home Office Equipment by South Census Region, Million U.S. Households, 2001 Home Office Equipment RSE Column Factor: Total U.S. South Census Region RSE Row Factors Total Census Division South Atlantic East South Central West South Central 0.5 0.8 1.2 1.3 1.6 Total .............................................................. 107.0 38.9 20.3 6.8 11.8 NE Households Using Office Equipment ......................................... 96.2 34.6 18.4 6.0 10.1 1.2 Personal Computers 1 ................................. 60.0 20.7 11.7 3.2 5.8 4.0 Number of Desktop PCs 1 ................................................................ 45.1 15.5 8.6 2.6 4.3 4.9 2 or more ................................................... 9.1 3.1 2.0 0.4 0.7 9.6 Number of Laptop PCs

99

EIA - Census Division List  

Gasoline and Diesel Fuel Update (EIA)

Supplemental Tables > Census Division List Supplemental Tables > Census Division List Supplemental Tables to the Annual Energy Outlook 2010 Division 1 Division 2 Division 3 Division 4 Division 5 New England Middle Atlantic East North Central West North Central South Atlantic Connecticut New Jersey Illinois Iowa Delaware Maine New York Indiana Kansas District of Columbia Massachusetts Pennsylvania Michigan Minnesota Florida New Hampshire Ohio Missouri Georgia Rhode Island Wisconsin Nebraska Maryland Vermont North Dakota North Carolina South Dakota South Carolina Virginia West Virginia Division 6 Division 7 Division 8 Division 9 East South Central West South Central Mountain Pacific Alabama Arkansas Arizona Alaska Kentucky Louisiana Colorado California

100

Characteristics, Welfare Use and Material Hardship Among California AFDC Households with Disabled and Chronically Ill Family Members  

E-Print Network (OSTI)

Families with Severely Disabled Members, 262 cases weightedA F D C Households with Disabled and Chronically 111 Familylevels. 1'he treatment o f disabled individuals in these

Meyers, Marcia k.

1996-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "household characteristics census" 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

Household Vehicles Energy Consumption 1991  

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

. . Trends in Household Vehicle Stock The 1991 RTECS counted more than 150 million vehicles in use by U.S. households. This chapter examines recent trends in the vehicle stock, as measured by the RTECS and other reputable vehicle surveys. It also provides some details on the type and model year of the household vehicle stock, and identifies regional differences in vehicle stock. Because vehicles are continuously being bought and sold, this chapter also reports findings relating to turnover of the vehicle stock in 1991. Finally, it examines the average vehicle stock in 1991 (which takes into account the acquisition and disposal of household vehicles over the course of the year) and identifies variations in the average number of household vehicles based on differences in household characteristics. Number of Household Vehicles Over the past 8 years, the stock of household vehicles has

102

Census Snapshot: Rhode Island  

E-Print Network (OSTI)

The presence of a senior or disabled partner in a couple mayleast one partner who is disabled: 33% of same-sex couples,partner over 65 Percent disabled Average household income

Romero, Adam P; Baumle, Amanda; Badgett, M.V. Lee; Gates, Gary J

2007-01-01T23:59:59.000Z

103

Census Snapshot: Arizona  

E-Print Network (OSTI)

couples (0.68%), and Pinal County with 398 couples (0.65%).County sex couples of all households Apache Cochise Coconino Gila Graham Greenlee La Paz Maricopa Mohave Navajo Pima Pinal

Romero, Adam P; Rosky, Clifford J; Badgett, M.V. Lee; Gates, Gary J

2008-01-01T23:59:59.000Z

104

" Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1"  

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

Housing Unit Characteristics by Household Income, 2005" Housing Unit Characteristics by Household Income, 2005" " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ,"Housing Units (millions)" ,,"Less than $20,000","$20,000 to $39,999","$40,000 to $59,999","$60,000 to $79,999","$80,000 or More" "Housing Unit Characteristics" "Total",111.1,26.7,28.8,20.6,13.1,22,16.6,38.6 "Census Region and Division" "Northeast",20.6,4.9,5.4,3.5,2.4,4.3,3.2,8.1 "New England",5.5,1.3,1.3,1,0.6,1.2,0.7,2.3 "Middle Atlantic",15.1,3.7,4.1,2.5,1.8,3.1,2.5,5.8 "Midwest",25.6,6.5,6.6,4.7,3,4.8,3.5,9.4

105

Census Division List  

Gasoline and Diesel Fuel Update (EIA)

Supplement Tables to the Annual Energy Outlook 2003 Supplement Tables to the Annual Energy Outlook 2003 Census Division List Division 1 Division 2 Division 3 Division 4 Division 5 New England Middle Atlantic East North Central West North Central South Atlantic Connecticut New Jersey Illinois Iowa Delaware Maine New York Indiana Kansas District of Columbia Massachusetts Pennsylvania Michigan Minnesota Florida New Hampshire Ohio Missouri Georgia Rhode Island Wisconsin Nebraska Maryland Vermont North Dakota North Carolina South Dakota South Carolina Virginia West Virginia Division 6 Division 7 Division 8 Division 9 East South Central West South Central Mountain Pacific Alabama Arkansas Arizona Alaska Kentucky Louisiana Colorado California Mississippi Oklahoma Idaho Hawaii

106

Census Division List  

Gasoline and Diesel Fuel Update (EIA)

5 5 Census Division List Division 1 Division 2 Division 3 Division 4 Division 5 New England Middle Atlantic East North Central West North Central South Atlantic Connecticut New Jersey Illinois Iowa Delaware Maine New York Indiana Kansas District of Columbia Massachusetts Pennsylvania Michigan Minnesota Florida New Hampshire Ohio Missouri Georgia Rhode Island Wisconsin Nebraska Maryland Vermont North Dakota North Carolina South Dakota South Carolina Virginia West Virginia Division 6 Division 7 Division 8 Division 9 East South Central West South Central Mountain Pacific Alabama Arkansas Arizona Alaska Kentucky Louisiana Colorado California Mississippi Oklahoma Idaho Hawaii Tennessee Texas Montana Oregon

107

Table A26. Total Quantity of Purchased Energy Sources by Census...  

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

Total Quantity of Purchased Energy Sources by Census Region and" " Economic Characteristics of the Establishment, 1991" " (Estimates in Btu or Physical Units)"...

108

Household Vehicles Energy Consumption 1991  

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

3. 3. Vehicle Miles Traveled This chapter presents information on household vehicle usage, as measured by the number of vehicle miles traveled (VMT). VMT is one of the two most important components used in estimating household vehicle fuel consumption. (The other, fuel efficiency, is discussed in Chapter 4). In addition, this chapter examines differences in driving behavior based on the characteristics of the household and the type of vehicle driven. Trends in household driving patterns are also examined using additional information from the Department of Transportation's Nationwide Personal Transportation Survey (NPTS). Household VMT is a measure of the demand for personal transportation. Demand for transportation may be viewed from either an economic or a social perspective. From the economic point-of-view, the use of a household vehicle represents the consumption of one

109

Census Division List  

Gasoline and Diesel Fuel Update (EIA)

please contact the National Energy Information Center at (202) 586-8800. please contact the National Energy Information Center at (202) 586-8800. Supplement Tables to the Annual Energy Outlook 2002 Census Division List Division 1 Division 2 Division 3 Division 4 Division 5 New England Middle Atlantic East North Central West North Central South Atlantic Connecticut New Jersey Illinois Iowa Delaware Maine New York Indiana Kansas District of Columbia Massachusetts Pennsylvania Michigan Minnesota Florida New Hampshire Ohio Missouri Georgia Rhode Island Wisconsin Nebraska Maryland Vermont North Dakota North Carolina South Dakota South Carolina Virginia West Virginia Division 6 Division 7 Division 8 Division 9 East South Central West South Central Mountain Pacific Alabama Arkansas Arizona Alaska

110

char_household2001.pdf  

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

3a. Household Characteristics by Household Income, 3a. Household Characteristics by Household Income, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral Assist- ance 1 RSE Row Factors Less than $14,999 $15,000 to $29,999 $30,000 to $49,999 $50,000 or More 0.6 1.3 1.1 1.0 0.9 1.4 1.0 Total ............................................... 107.0 18.7 22.9 27.1 38.3 15.0 33.8 3.3 Household Size 1 Person ....................................... 28.2 9.7 -- -- -- 6.5 11.3 5.7 2 Persons ...................................... 35.1 4.3 -- -- -- 2.0 7.8 5.8 3 Persons ...................................... 17.0 -- 3.3 -- -- 2.2 5.2 7.3 4 Persons ...................................... 15.6 -- 2.2 -- -- -- 4.3 8.1 5 Persons ...................................... 7.1

111

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

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

7. Total Expenditures for Purchased Energy Sources by Census Region," 7. Total Expenditures for Purchased Energy Sources by Census Region," " Census Division, and Economic Characteristics of the Establishment, 1994" " (Estimates in Million Dollars)" " "," "," "," ",," "," "," "," "," ","RSE" " "," "," ","Residual","Distillate","Natural"," "," ","Coke"," ","Row" "Economic Characteristics(a)","Total","Electricity","Fuel Oil","Fuel Oil(b)","Gas(c)","LPG","Coal","and Breeze","Other(d)","Factors"

112

Space-Heating energy used by households in the residential sector.  

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

Detailed Tables Detailed Tables Energy End Uses Ranked by Energy Consumption, 1989 The following 28 tables present detailed data describing the consumption of and expenditures for energy used by households in the residential sector. The data are presented at the national level, Census region and division levels, for climate zones and for the most populous States, as well as for other selected characteristics of households. This section provides assistance in reading the tables by explaining some of the headings for the categories of data. It also explains the use of the row and column factors to compute the relative standard error of the estimates given in the tables. Organization of the Tables The tables cover consumption and expenditures for six topical areas: Major Energy Source

113

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

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

Total Expenditures for Purchased Energy Sources by Census Region" Total Expenditures for Purchased Energy Sources by Census Region" " and Economic Characteristics of the Establishment, 1991" " (Estimates in Million Dollars)" " "," "," "," ",," "," "," "," "," ","RSE" " "," "," ","Residual","Distillate","Natural"," "," ","Coke"," ","Row" "Economic Characteristics(a)","Total","Electricity","Fuel Oil","Fuel Oil(b)","Gas(c)","LPG","Coal","and Breeze","Other(d)","Factors"

114

EIA - Household Transportation report: Household Vehicles ...  

U.S. Energy Information Administration (EIA)

This report, Household Vehicles Energy Use: Latest Data & Trends, provides details on the nation's energy use for household passenger travel. A primary purpose of ...

115

Table A28. Components of Onsite Electricity Generation by Census Region, Cens  

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

Components of Onsite Electricity Generation by Census Region, Census Division, and" Components of Onsite Electricity Generation by Census Region, Census Division, and" " Economic Characteristics of the Establishment, 1994" " (Estimates in Million Kilowatthours)" ,,,"Renewables" ,,,"(excluding Wood",,"RSE" " "," "," ","and"," ","Row" "Economic Characteristics(a)","Total","Cogeneration(b)","Other Biomass)(c)","Other(d)","Factors" ,"Total United States" "RSE Column Factors:",0.6,0.6,1.8,1.4 "Value of Shipments and Receipts" "(million dollars)" " Under 20",1098,868," W "," W ",22.3

116

Household energy consumption and expenditures 1987  

SciTech Connect

This report is the third in the series of reports presenting data from the 1987 Residential Energy Consumption Survey (RECS). The 1987 RECS, seventh in a series of national surveys of households and their energy suppliers, provides baseline information on household energy use in the United States. Data from the seven RECS and its companion survey, the Residential Transportation Energy Consumption Survey (RTECS), are made available to the public in published reports such as this one, and on public use data files. This report presents data for the four Census regions and nine Census divisions on the consumption of and expenditures for electricity, natural gas, fuel oil and kerosene (as a single category), and liquefied petroleum gas (LPG). Data are also presented on consumption of wood at the Census region level. The emphasis in this report is on graphic depiction of the data. Data from previous RECS surveys are provided in the graphics, which indicate the regional trends in consumption, expenditures, and uses of energy. These graphs present data for the United States and each Census division. 12 figs., 71 tabs.

Not Available

1990-01-22T23:59:59.000Z

117

Household Vehicles Energy Consumption 1991  

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

. . Vehicle Fuel Efficiency and Consumption Fuel consumption is estimated from RTECS data on the vehicle stock (Chapter 2) and miles traveled (Chapter 3), in combination with vehicle fuel efficiency ratings, adjusted to account for individual driving circumstances. The first two sections of this chapter present estimates of household vehicle fuel efficiency and household fuel consumption calculated from these fuel efficiency estimates. These sections also discuss variations in fuel efficiency and consumption based on differences in household and vehicle characteristics. The third section presents EIA estimates of the potential savings from replacing the oldest (and least fuel-efficient) household vehicles with new (and more fuel-efficient) vehicles. The final section of this chapter focuses on households receiving (or eligible to receive) supplemental income under

118

Commercial Buildings Characteristics 1992  

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

Buildings Characteristics 1992 Buildings Characteristics Overview Full Report Tables National and Census region estimates of the number of commercial buildings in the U.S. and...

119

Housing Diversity and Consolidation in Low-Income Colonias: Patterns of House Form and Household Arrangements in Colonias of the US-Mexico Border  

E-Print Network (OSTI)

Colonias are low-income settlements on the US-Mexico border characterized by poor infrastructure, minimum services, and an active housing construction with a high self-help and self-management component. Housing in colonias is very diverse showing house forms that include temporary and permanent structures, campers, trailers or manufactured houses and conventional homes. Most of this housing does not meet construction standards and codes and is considered substandard. Colonias households are also of diverse nature and composition including single households, nuclear and extended families, as well as multiple households sharing lots. This wide variety of house forms and households in colonias fits poorly within the nuclear household, single family detached housing idealized by conventional low-income housing projects, programs and policies. As a result, colonias marginally benefit from the resources available to them and continue to depend mostly on the individual efforts of their inhabitants. This research identifies the housing diversity and the process of housing consolidation in colonias of the US-Mexico border by looking at the patterns of house form and household arrangements in colonias of South Texas. Ten colonias located to the east of the city of Laredo along Highway 359 in Webb County, Texas were selected based on their characteristics, data availability and accessibility. Data collected included periodic aerial images of the colonias spanning a period of 28 years, household information from the 2000 census disaggregated at the block level for these colonias, and information from a field survey and a semi structured interview made to a random sample of 123 households between February and June 2007. The survey collected information about house form and household characteristics. The survey also incorporated descriptive accounts on how households completed their house from the initial structure built or set on the lot until the current house form. Data was compiled and analyzed using simple statistical methods looking for identifiable patterns on house form and household characteristics and changes over time. Findings showed that housing in colonias is built and consolidated following identifiable patterns of successive changes to the house form. Findings also showed that households in colonias share characteristics that change over time in similar ways. These results suggest similarities of colonias with extra-legal settlements in other developing areas. Based on these findings, the study reflects on possible considerations that could improve the impact of projects, programs and policies directed to support colonias and improve colonias housing.

Reimers-Arias, Carlos Alberto

2009-08-01T23:59:59.000Z

120

Household vehicles energy consumption 1994  

SciTech Connect

Household Vehicles Energy Consumption 1994 reports on the results of the 1994 Residential Transportation Energy Consumption Survey (RTECS). The RTECS is a national sample survey that has been conducted every 3 years since 1985. For the 1994 survey, more than 3,000 households that own or use some 6,000 vehicles provided information to describe vehicle stock, vehicle-miles traveled, energy end-use consumption, and energy expenditures for personal vehicles. The survey results represent the characteristics of the 84.9 million households that used or had access to vehicles in 1994 nationwide. (An additional 12 million households neither owned or had access to vehicles during the survey year.) To be included in then RTECS survey, vehicles must be either owned or used by household members on a regular basis for personal transportation, or owned by a company rather than a household, but kept at home, regularly available for the use of household members. Most vehicles included in the RTECS are classified as {open_quotes}light-duty vehicles{close_quotes} (weighing less than 8,500 pounds). However, the RTECS also includes a very small number of {open_quotes}other{close_quotes} vehicles, such as motor homes and larger trucks that are available for personal use.

NONE

1997-08-01T23:59:59.000Z

Note: This page contains sample records for the topic "household characteristics census" 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

1999 Commercial Buildings Characteristics--Census Region  

Annual Energy Outlook 2012 (EIA)

and population were found in the South region, while the Northeast had the smallest percentage of each (less than 20 percent). Detailed tables Figure 1. Percentage of Buildings,...

122

Transferring 2001 National Household Travel Survey  

Science Conference Proceedings (OSTI)

Policy makers rely on transportation statistics, including data on personal travel behavior, to formulate strategic transportation policies, and to improve the safety and efficiency of the U.S. transportation system. Data on personal travel trends are needed to examine the reliability, efficiency, capacity, and flexibility of the Nation's transportation system to meet current demands and to accommodate future demand. These data are also needed to assess the feasibility and efficiency of alternative congestion-mitigating technologies (e.g., high-speed rail, magnetically levitated trains, and intelligent vehicle and highway systems); to evaluate the merits of alternative transportation investment programs; and to assess the energy-use and air-quality impacts of various policies. To address these data needs, the U.S. Department of Transportation (USDOT) initiated an effort in 1969 to collect detailed data on personal travel. The 1969 survey was the first Nationwide Personal Transportation Survey (NPTS). The survey was conducted again in 1977, 1983, 1990, 1995, and 2001. Data on daily travel were collected in 1969, 1977, 1983, 1990 and 1995. In 2001, the survey was renamed the National Household Travel Survey (NHTS) and it collected both daily and long-distance trips. The 2001 survey was sponsored by three USDOT agencies: Federal Highway Administration (FHWA), Bureau of Transportation Statistics (BTS), and National Highway Traffic Safety Administration (NHTSA). The primary objective of the survey was to collect trip-based data on the nature and characteristics of personal travel so that the relationships between the characteristics of personal travel and the demographics of the traveler can be established. Commercial and institutional travel were not part of the survey. Due to the survey's design, data in the NHTS survey series were not recommended for estimating travel statistics for categories smaller than the combination of Census division (e.g., New England, Middle Atlantic, and Pacific), MSA size, and the availability of rail. Extrapolating NHTS data within small geographic areas could risk developing and subsequently using unreliable estimates. For example, if a planning agency in City X of State Y estimates travel rates and other travel characteristics based on survey data collected from NHTS sample households that were located in City X of State Y, then the agency could risk developing and using unreliable estimates for their planning process. Typically, this limitation significantly increases as the size of an area decreases. That said, the NHTS contains a wealth of information that could allow statistical inferences about small geographic areas, with a pre-determined level of statistical certainty. The question then becomes whether a method can be developed that integrates the NHTS data and other data to estimate key travel characteristics for small geographic areas such as Census tract and transportation analysis zone, and whether this method can outperform other, competing methods.

Hu, Patricia S [ORNL; Reuscher, Tim [ORNL; Schmoyer, Richard L [ORNL; Chin, Shih-Miao [ORNL

2007-05-01T23:59:59.000Z

123

Household vehicles energy consumption 1991  

Science Conference Proceedings (OSTI)

The purpose of this report is to provide information on the use of energy in residential vehicles in the 50 States and the District of Columbia. Included are data about: the number and type of vehicles in the residential sector, the characteristics of those vehicles, the total annual Vehicle Miles Traveled (VMT), the per household and per vehicle VMT, the vehicle fuel consumption and expenditures, and vehicle fuel efficiencies. The data for this report are based on the household telephone interviews from the 1991 RTECS, conducted during 1991 and early 1992. The 1991 RTECS represents 94.6 million households, of which 84.6 million own or have access to 151.2 million household motor vehicles in the 50 States and the District of Columbia.

Not Available

1993-12-09T23:59:59.000Z

124

char_household2001.pdf  

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

a. Household Characteristics by Climate Zone, a. Household Characteristics by Climate Zone, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total Climate Zone 1 RSE Row Factors Fewer than 2,000 CDD and -- 2,000 CDD or More and Fewer than 4,000 HDD More than 7,000 HDD 5,500 to 7,000 HDD 4,000 to 5,499 HDD Fewer than 4,000 HDD 0.4 1.9 1.1 1.1 1.2 1.0 Total ............................................... 107.0 9.2 28.6 24.0 21.0 24.1 7.8 Household Size 1 Person ....................................... 28.2 2.5 8.1 6.5 4.8 6.2 9.9 2 Persons ...................................... 35.1 3.1 9.4 8.2 6.5 7.9 8.7 3 Persons ...................................... 17.0 1.3 4.3 4.0 3.3 4.1 10.7 4 Persons ...................................... 15.6 1.4 3.9 3.4 3.4 3.5 10.5 5 Persons ......................................

125

char_household2001.pdf  

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

6a. Household Characteristics by Type of Rented Housing Unit, 6a. Household Characteristics by Type of Rented Housing Unit, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total Rented Units Type of Rented Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.5 0.8 1.1 0.9 2.5 Total Rented Units ........................ 34.3 10.5 7.4 15.2 1.1 6.9 Household Size 1 Person ....................................... 12.3 2.5 2.6 7.0 0.3 10.0 2 Persons ...................................... 9.2 2.5 2.5 4.1 Q 11.8 3 Persons ...................................... 5.4 2.0 1.1 2.0 0.4 13.9 4 Persons ...................................... 3.8 1.6 0.7 1.4 Q 17.7 5 Persons ...................................... 2.0 0.9 0.4 0.6 Q 24.1 6 or More Persons ........................

126

char_household2001.pdf  

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

5a. Household Characteristics by Type of Owner-Occupied Housing Unit, 5a. Household Characteristics by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total Owner- Occupied Units Type of Owner-Occupied Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Homes Two to Four Units Five or More Units 0.3 0.4 2.0 2.9 1.3 Total Owner-Occupied Units ....... 72.7 63.2 2.1 1.8 5.7 6.7 Household Size 1 Person ....................................... 15.8 12.5 0.8 0.9 1.6 10.3 2 Persons ...................................... 25.9 23.4 0.5 0.5 1.5 10.1 3 Persons ...................................... 11.6 9.6 0.5 Q 1.3 12.1 4 Persons ...................................... 11.8 10.9 Q Q 0.7 15.7 5 Persons ...................................... 5.1 4.5 Q Q 0.4 24.2 6 or More Persons

127

char_household2001.pdf  

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

8a. Household Characteristics by Urban/Rural Location, 8a. Household Characteristics by Urban/Rural Location, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total Urban/Rural Location 1 RSE Row Factors City Town Suburbs Rural 0.5 0.8 1.4 1.3 1.4 Total .............................................................. 107.0 49.9 18.0 21.2 17.9 4.1 Household Size 1 Person ...................................................... 28.2 14.6 5.3 4.8 3.6 6.4 2 Persons .................................................... 35.1 15.7 5.7 6.9 6.8 5.4 3 Persons .................................................... 17.0 7.6 2.8 3.5 3.1 7.2 4 Persons .................................................... 15.6 6.8 2.3 4.1 2.4 8.1 5 Persons .................................................... 7.1 3.1 1.3 1.3 1.4 12.3 6 or More Persons

128

char_household2001.pdf  

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

2a. Household Characteristics by Year of Construction, 2a. Household Characteristics by Year of Construction, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total Year of Construction RSE Row Factors 1990 to 2001 1 1980 to 1989 1970 to 1979 1960 to 1969 1950 to 1959 1949 or Before 0.4 1.6 1.2 1.0 1.2 1.2 0.9 Total ............................................... 107.0 15.5 18.2 18.8 13.8 14.2 26.6 4.2 Household Size 1 Person ....................................... 28.2 2.5 4.5 5.1 4.0 3.7 8.3 7.5 2 Persons ...................................... 35.1 4.8 6.2 6.6 4.5 5.3 7.8 5.8 3 Persons ...................................... 17.0 2.5 3.3 2.9 2.3 1.9 4.1 8.4 4 Persons ...................................... 15.6 3.4 2.8 2.3 1.9 1.8 3.4 9.6 5 Persons ...................................... 7.1 1.6 1.2 1.3 0.6 0.7 1.6 14.3 6 or More Persons

129

ac_household2001.pdf  

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

3a. Air Conditioning by Household Income, 3a. Air Conditioning by Household Income, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral Assist- ance 1 RSE Row Factors Less than $14,999 $15,000 to $29,999 $30,000 to $49,999 $50,000 or More 0.5 1.4 1.1 1.0 0.9 1.5 0.9 Households With Electric Air-Conditioning Equipment ........ 82.9 12.3 17.4 21.5 31.7 9.6 23.4 3.9 Air Conditioners Not Used ............ 2.1 0.4 0.7 0.5 0.5 0.4 0.9 20.8 Households Using Electric Air-Conditioning 2 .......................... 80.8 11.9 16.7 21.0 31.2 9.1 22.6 3.9 Type of Electric Air-Conditioning Used Central Air-Conditioning 3 .............. 57.5 6.2 10.7 15.2 25.3 4.5 12.4 5.3 Without a Heat Pump .................. 46.2 4.9 9.1 12.1 20.1 3.6 10.4 6.1 With a Heat Pump

130

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

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

Components of Total Electricity Demand by Census Region and" Components of Total Electricity Demand by Census Region and" " Economic Characteristics of the Establishment, 1991" " (Estimates in Million Kilowatthours)" " "," "," "," ","Sales/"," ","RSE" " "," ","Transfers","Onsite","Transfers"," ","Row" "Economic Characteristics(a)","Purchases","In(b)","Generation(c)","Offsite","Net Demand(d)","Factors" ,"Total United States" "RSE Column Factors:",0.5,1.4,1.3,1.9,0.5 "Value of Shipments and Receipts" "(million dollars)"

131

Residential energy consumption and expenditure patterns of black and nonblack households in the United States  

Science Conference Proceedings (OSTI)

Residential energy consumption and expenditures by black and nonblack households are presented by Census region and for the nation based on the Energy Information Administration's 1982-83 Residential Energy Consumption Survey (RECS). Black households were found to have significantly lower levels of electricity consumption at both the national and regional level. Natural gas is the dominant space heating fuel used by black households. Natural gas consumption was typically higher for black households. However, when considering natural gas consumption conditional on natural gas space heating no significant differences were found. 10 refs., 1 fig., 8 tabs.

Vyas, A.D.; Poyer, D.A.

1987-01-01T23:59:59.000Z

132

Why sequence census of fungal biology?  

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

sequence census of fungal biology? Despite the large number of sequenced fungal genomes, the current taxonomic sampling is limited to well-characterized lineages of the Kingdom and...

133

Census and viewing of organisms  

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

Census and viewing of organisms Census and viewing of organisms Name: m hariaczyi Status: N/A Age: N/A Location: N/A Country: N/A Date: Around 1993 Question: How many organisms exist in the world today? What is the most powerful microscope that could be used for viewing organism? Replies: The most powerful microscope is called an electron microscope, which can be used for viewing entire organisms, although few organisms are small enough to see all of them at high magnifications allowed by this microscope. So most often its used to look at fixed sections of organisms. Since the electron microscope only works in a vacuum, with no air, you cannot look at live organisms. To do that, probably the most powerful microscope is called a Nomarski, or in technical terms, a "differential interference contrast" microscope. This is a modification of a normal light microscope that allows better contrast in living tissue. It is not any more powerful than a light microscope, and is much less powerful than an electron microscope, but it allows you to see living things much better.

134

Model documentation: household model of energy  

Science Conference Proceedings (OSTI)

The Household Model of Energy is an econometric model, meaning that energy use is determined quantitatively with the use of economic variables such as fuel prices and income. HOME is also primarily a structural model, meaning that energy use is determined as the result of interactions of intermediate components such as the number of households, the end use fuel shares and the energy use per household. HOME forecasts energy consumption in all occupied residential structures (households) in the United States on an annual basis through 1990. The forecasts are made based upon a number of initial conditions in 1980, various estimated elasticities, various parameters and assumptions, and a set of forecasted fuel prices and income. In addition to the structural detail, HOME operates on a more disaggregated level. This includes four end-use services (space heating, water heating, air conditioning, and others), up to seven fuel/technology types (dependent upon the end use service), two housing types, four structure vintages, and four Census regions. When the model is run as a module in IFFS, a sharing scheme further disaggregates the model to 10 Federal regions.

Holte, J.A.

1984-02-01T23:59:59.000Z

135

Essays on the effects of demographics on household consumption.  

E-Print Network (OSTI)

??My dissertation analyses the relationship between households' consumption behavior and changes in family demographic characteristics. The first paper studies consumption over the period of the… (more)

Stepanova, Ekaterina, 1977-

2006-01-01T23:59:59.000Z

136

Census of Tribal Justice Agencies in Indian  

E-Print Network (OSTI)

Census of Tribal Justice Agencies in Indian Country, 2002 · Law enforcement · Courts Criminal Justice Reference Service 1-800-851-3420 #12;Census of Tribal Justice Agencies in Indian Country Figure 1 -- Map of States, by Public Law 83-280 Status Table 2 -- Number of tribes, by State, Public law

Hemmers, Oliver

137

Characterization of household waste in Greenland  

Science Conference Proceedings (OSTI)

The composition of household waste in Greenland was investigated for the first time. About 2 tonnes of household waste was sampled as every 7th bag collected during 1 week along the scheduled collection routes in Sisimiut, the second largest town in Greenland with about 5400 inhabitants. The collection bags were sorted manually into 10 material fractions. The household waste composition consisted primarily of biowaste (43%) and the combustible fraction (30%), including anything combustible that did not belong to other clean fractions as paper, cardboard and plastic. Paper (8%) (dominated by magazine type paper) and glass (7%) were other important material fractions of the household waste. The remaining approximately 10% constituted of steel (1.5%), aluminum (0.5%), plastic (2.4%), wood (1.0%), non-combustible waste (1.8%) and household hazardous waste (1.2%). The high content of biowaste and the low content of paper make Greenlandic waste much different from Danish household waste. The moisture content, calorific value and chemical composition (55 elements, of which 22 were below detection limits) were determined for each material fraction. These characteristics were similar to what has been found for material fractions in Danish household waste. The chemical composition and the calorific value of the plastic fraction revealed that this fraction was not clean but contained a lot of biowaste. The established waste composition is useful in assessing alternative waste management schemes for household waste in Greenland.

Eisted, Rasmus, E-mail: raei@env.dtu.dk [Department of Environmental Engineering, Technical University of Denmark, Kongens Lyngby (Denmark); Christensen, Thomas H. [Department of Environmental Engineering, Technical University of Denmark, Kongens Lyngby (Denmark)

2011-07-15T23:59:59.000Z

138

Factors influencing county level household fuelwood use  

Science Conference Proceedings (OSTI)

This study explains household fuelwood consumption behavior at the county level by linking it to economic and demographic conditions in counties. Using this link, counties are identified where potential fuelwood use problems and benefits are greatest. A probit equation estimates household probability of wood use (percent woodburners in a county heating degree days, household income, nonwood fuel price, fuelwood price, percent forest land, population density, and fraction of households using various types of heating equipment. A linear-in-parameters equation estimates average wood consumed by a woodburner based on county heating degree days, household income, percent forest land, and price of nonwood fuel divided by fuelwood price. Parameters are estimated using fuelwood use data for individual households from a 1908-81 nationwide survey. The probit equation predicts percentage of wood burns well over a wide range of county conditions. The wood consumption equation overpredicts for counties with high income and high population density (over 6000 persons per square mile). The model shows average woodburning per household over all households decreases with increasing population density, and the influence of county economic characteristics varies with density.

Skog, K.E.

1986-01-01T23:59:59.000Z

139

Table 5A. Residential Average Monthly Bill by Census Division ...  

U.S. Energy Information Administration (EIA)

Table 5A. Residential Average Monthly Bill by Census Division, and State, 2009: Census Division State Number of Consumers Average Monthly Consumption ...

140

spaceheat_household2001.pdf  

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

3a. Space Heating by Household Income, 3a. Space Heating by Household Income, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral Assist- ance 1 RSE Row Factors Less than $14,999 $15,000 to $29,999 $30,000 to $49,999 $50,000 or More 0.6 1.3 1.1 1.0 0.9 1.4 1.0 Total ............................................... 107.0 18.7 22.9 27.1 38.3 15.0 33.8 3.3 Heat Home ..................................... 106.0 18.4 22.7 26.8 38.1 14.6 33.4 3.3 Do Not Heat Home ........................ 1.0 0.3 Q 0.3 0.3 0.3 0.4 23.4 No Heating Equipment .................. 0.5 Q Q Q 0.2 Q Q 35.0 Have Equipment But Do Not Use It ................................ 0.4 Q Q Q Q 0.2 0.3 22.8 Main Heating Fuel and Equipment (Have and Use Equipment) ............ 106.0 18.4 22.7

Note: This page contains sample records for the topic "household characteristics census" 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

appl_household2001.pdf  

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

3a. Appliances by Household Income, 3a. Appliances by Household Income, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral Assist- ance 1 RSE Row Factors Less than $14,999 $15,000 to $29,999 $30,000 to $49,999 $50,000 or More 0.5 1.4 1.1 1.0 0.8 1.6 1.0 Total ............................................... 107.0 18.7 22.9 27.1 38.3 15.0 33.8 3.2 Kitchen Appliances Cooking Appliances Oven ........................................... 101.7 18.0 22.0 26.1 35.6 14.4 32.6 3.2 1 ................................................ 95.2 17.3 21.1 24.8 32.0 13.8 31.1 3.4 2 or More .................................. 6.5 0.8 0.9 1.3 3.6 0.6 1.5 13.1 Most Used Oven ........................ 101.7 18.0 22.0 26.1 35.6 14.4 32.6 3.2

142

,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member"  

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

6 Average Square Footage of Mobile Homes, by Housing Characteristics, 2009" 6 Average Square Footage of Mobile Homes, by Housing Characteristics, 2009" " Final" ,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member" "Housing Characteristics","Millions","Total2","Heated","Cooled","Total2","Heated","Cooled" "Total Mobile Homes",6.9,1087,985,746,413,375,283 "Census Region" "Northeast",0.5,1030,968,711,524,492,362 "Midwest",1.1,1090,1069,595,400,392,218 "South",3.9,1128,1008,894,423,378,335 "West",1.4,995,867,466,369,322,173 "Urban and Rural3" "Urban",3.5,1002,919,684,396,364,271

143

,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member"  

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

4 Average Square Footage of Single-Family Homes, by Housing Characteristics, 2009" 4 Average Square Footage of Single-Family Homes, by Housing Characteristics, 2009" " Final" ,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member" "Housing Characteristics","Millions","Total2","Heated","Cooled","Total2","Heated","Cooled" "Total Single-Family",78.6,2422,2002,1522,880,727,553 "Census Region" "Northeast",12.7,2843,2150,1237,1009,763,439 "Midwest",19.2,2721,2249,1664,1019,842,624 "South",29.7,2232,1945,1843,828,722,684 "West",16.9,2100,1712,1009,725,591,348 "Urban and Rural3"

144

,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member"  

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

5 Average Square Footage of Multi-Family Homes, by Housing Characteristics, 2009" 5 Average Square Footage of Multi-Family Homes, by Housing Characteristics, 2009" " Final" ,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member" "Housing Characteristics","Millions","Total2","Heated","Cooled","Total2","Heated","Cooled" "Total Multi-Family",28.1,930,807,535,453,393,261 "Census Region" "Northeast",7.6,991,897,408,471,426,194 "Midwest",5.6,957,857,518,521,466,282 "South",8.4,924,846,819,462,423,410 "West",6.5,843,606,329,374,269,146 "Urban and Rural3" "Urban",26.9,927,803,531,450,390,258

145

,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member"  

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

9 Average Square Footage of U.S. Homes, by Housing Characteristics, 2009" 9 Average Square Footage of U.S. Homes, by Housing Characteristics, 2009" " Final" ,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member" "Housing Characteristics","Millions","Total2","Heated","Cooled","Total2","Heated","Cooled" "Total",113.6,1971,1644,1230,766,639,478 "Census Region" "Northeast",20.8,2121,1663,921,836,656,363 "Midwest",25.9,2272,1898,1372,912,762,551 "South",42.1,1867,1637,1549,732,642,607 "West",24.8,1708,1374,800,628,506,294 "Urban and Rural3" "Urban",88.1,1857,1546,1148,728,607,450

146

book review: Census of marine life  

E-Print Network (OSTI)

and update  ISSN 1948?6596  book review  Census of marine blackwell   This  is  a  book  about  which  superlatives oceans of the world.   The  book  itself  is  beautifully 

Sheppard, Charles

2011-01-01T23:59:59.000Z

147

EIA - Household Transportation report: Household Vehicles Energy  

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

4 4 Transportation logo printer-friendly version logo for Portable Document Format file Household Vehicles Energy Consumption 1994 August 1997 Release Next Update: EIA has discontinued this series. Based on the 1994 Residential Transportation Energy Consumption Survey conducted by the Energy Information Administration (EIA) - survey series has been discontinued Only light-duty vehicles and recreational vehicles are included in this report. EIA has excluded motorcycles, mopeds, large trucks, and buses. Household Vehicles Energy Consumption 1994 reports on the results of the 1994 Residential Transportation Energy Consumption Survey (RTECS). The RTECS is a national sample survey that has been conducted every 3 years since 1985. For the 1994 survey, more than 3,000 households that own or use

148

" by Census Region, Census Division, Industry Group, Selected Industries, and"  

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

Total Inputs of Energy for Heat, Power, and Electricity Generation" Total Inputs of Energy for Heat, Power, and Electricity Generation" " by Census Region, Census Division, Industry Group, Selected Industries, and" " Presence of Industry-Specific Technologies for Selected Industries, 1994: Part 1" " (Estimates in Trillion Btu)" ,,,," Census Region",,,,,,,"Census Division",,,,,"RSE" "SIC"," ",,,,,,,"Middle","East North","West North","South","East South","West South",,,"Row" "Code(a)","Industry Group and Industry","Total","Northeast","Midwest","South","West","New England","Atlantic","Central","Central","Atlantic","Central","Central","Mountain","Pacific","Factors"

149

Car Sharing within Households  

E-Print Network (OSTI)

The objective of this paper was to analyse two activities: who rents a car and why? Which households share the driving of their cars? In order to do that, the Parc-Auto (Car-Fleet) database, built from annual postal surveys conducted with a panel of 10,000 French households, has been processed. Among approximately one hundred questions in the survey, two key questions have been crossed against many social, economic, demographic, geographic or time variables. KQ1: “During the last 12 months, did you — or another person from your home — rent a car in France for personal purposes? ” KQ2: “Is this car occasionally used by other persons?” Here are the main findings. Renting households are mainly working, high income households, living in the core of big cities, and in particular in Paris. Most of them have two wage-sheets and two cars, one of which is generally a recent, high power, high quality car. Car rental is mainly an occasional practice. Yet for a minority of renters, it is a sustained habit. Households with more licence holders than cars share the most: about three quarters of them share their cars. On the contrary, single driver-single car households have less opportunity to share: only 15 % share. Household car sharing shed light on the gender role within households: while 58 % of the main users of the shared cars are male, 55 % of secondary users are female. Household car sharing is mainly a regular practice. Finally, without diminishing the merits of innovative transport solutions proposed here and there, it is not a waste of time to give some insight on self established behaviour within households. This reveals that complex patterns have been built over time by the people themselves, to cope with diverse situations that cannot be easily handled by straightforward classifications. The car cannot be reduced to a personal object. Household car sharing also carries strong links with the issue of car dependency. Sifting car availability and choice

Francis Papon; Laurent Hivert

2008-01-01T23:59:59.000Z

150

Census Bureau. Field Experiences 2 Field Representative Experiences with the Current Population Survey  

E-Print Network (OSTI)

In September 2007, U.S. Census Bureau researchers completed a third pilot study on factors that contribute to gaining cooperation and successfully completing survey interviews. This pilot study was part of a larger effort to systematically study interview dynamics and how they affect respondent cooperation with Census Bureau surveys. The results of this study will add to extant data on two previous pilot studies on gaining cooperation behavior (Beck, Wright, & Petkunas, 2007). In 2006, we collected data from Program Coordinators, Program Supervisors, and Senior Field Representatives (SFRs) working on (Beck, Wright, & Petkunas, 2007). The current pilot study involved collecting information from a sample of Census Bureau survey interviewers, called Field Representatives (FRs), throughout the United States. Like these other “field ” employees, FRs work from one of the twelve Census Bureau Regional Offices, which are responsible for the management of field data collection. The FRs filled out a brief questionnaire asking them to list practices, techniques, and recommendations they felt were either successful or unsuccessful at gaining respondent cooperation with Current Population Survey (CPS) interviews. The CPS is a panel survey involving eight monthly interviews with each sampled household. Respondents complete four consecutive monthly interviews, rotate out

Jennifer Beck; Jennifer Beck

2008-01-01T23:59:59.000Z

151

Household Vehicles Energy Consumption 1991  

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

1. 1. Introduction The purpose of this report is to provide information on the use of energy in residential vehicles in the 50 States and the District of Columbia. Included are data about: the number and type of vehicles in the residential sector, the characteristics of those vehicles, the total annual Vehicle Miles Traveled (VMT), the per household and per vehicle VMT, the vehicle fuel consumption and expenditures, and vehicle fuel efficiencies. The Energy Information Administration (EIA) is mandated by Congress to collect, analyze, and disseminate impartial, comprehensive data about energy--how much is produced, who uses it, and the purposes for which it is used. To comply with this mandate, EIA collects energy data from a variety of sources covering a range of topics 1 . Background The data for this report are based on the household telephone interviews from the 1991 RTECS, conducted

152

Household Vehicles Energy Consumption 1991  

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

Detailed Detailed Tables The following tables present detailed characteristics of vehicles in the residential sector. Data are from the 1991 Residential Transportation Energy Consumption Survey. The "Glossary" contains the definitions of terms used in the tables. Table Organization The "Detailed Tables" section consists of three types of tables: (1) Tables of totals such as number of vehicle miles traveled (VMT) or gallons consumed; (2) Tables of per household statistics such as VMT per household; and (3) Tables of per vehicle statistics such as vehicle fuel consumption per vehicle. The tables have been grouped together by specific topics such as model year data, or family income data to facilitate finding related information. The Quick-Reference Guide to the detailed tables indicates major topics of each table. Row and Column Factors These tables present estimates

153

Urban household energy use in Thailand  

SciTech Connect

Changes in household fuel and electricity use that accompany urbanization in Third World countries bear large economic and environmental costs. The processes driving the fuel transition, and the policy mechanisms by which it can be influenced, need to be better understood for the sake of forecasting and planning, especially in the case of electricity demand. This study examines patterns of household fuel use and electrical appliance utilization in Bangkok, Chieng Mai and Ayutthaya, Thailand, based on the results of a household energy survey. Survey data are statistically analyzed using a variety of multiple regression techniques to evaluate the relative influence of various household and fuel characteristics on fuel and appliance choice. Results suggest that changes to the value of women's time in urban households, as women become increasingly active in the labor force, have a major influence on patterns of household energy use. The use of the home for small-scale commercial activities, particularly food preparation, also has a significant influence on fuel choice. In general, household income does not prove to be an important factor in fuel and appliance selection in these cities, although income is closely related to total electricity use. The electricity use of individual household appliances is also analyzed using statistical techniques as well as limited direct metering. The technology of appliance production in Thailand is evaluated through interviews with manufacturers and comparisons of product performance. These data are used to develop policy recommendations for improving the efficiency of electrical appliances in Thailand by relying principally on the dynamism of the consumer goods market, rather than direct regulation. The annual electricity savings from the recommended program for fostering rapid adoption of efficient technologies are estimated to reach 1800 GWh by the year 2005 for urban households alone.

Tyler, S.R.

1992-01-01T23:59:59.000Z

154

" Electricity Generation by Census Region, Census Division, Industry Group, and"  

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

A6. Total Inputs of Selected Byproduct Energy for Heat, Power, and" A6. Total Inputs of Selected Byproduct Energy for Heat, Power, and" " Electricity Generation by Census Region, Census Division, Industry Group, and" " Selected Industries, 1994" " (Estimates in Trillion Btu)" " "," "," "," "," "," "," "," ","Waste"," " " "," "," ","Blast"," "," "," "," ","Oils/Tars","RSE" "SIC"," "," ","Furnace/Coke"," ","Petroleum","Pulping","Wood Chips,","And Waste","Row"

155

A Framework for Corporate Householding  

E-Print Network (OSTI)

Previous research on corporate household and corporate householding has presented examples, literature review, and working definitions. In this paper, we first improve our ...

Madnick, Stuart

2003-03-21T23:59:59.000Z

156

Table A20. Components of Onsite Electricity Generation by Census Region and  

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

Components of Onsite Electricity Generation by Census Region and" Components of Onsite Electricity Generation by Census Region and" " Economic Characteristics of the Establishment, 1991" " (Estimates in Million Kilowatthours)" ,,,,,"RSE" " "," "," "," "," ","Row" "Economic Characteristics(a)","Total","Cogeneration","Renewables","Other(b)","Factors" ,"Total United States" "RSE Column Factors:",0.8,0.8,1.2,1.3 "Value of Shipments and Receipts" "(million dollars)" " Under 20",562,349,"W","W",23 " 20-49",4127,3917,79,131,20.1 " 50-99",8581,7255,955,371,10

157

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

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

A9. Total Primary Consumption of Energy for All Purposes by Census" A9. Total Primary Consumption of Energy for All Purposes by Census" " Region and Economic Characteristics of the Establishment, 1991" " (Estimates in Btu or Physical Units)" ,,,,,,,,"Coke" " "," ","Net","Residual","Distillate","Natural Gas(d)"," ","Coal","and Breeze"," ","RSE" " ","Total","Electricity(b)","Fuel Oil","Fuel Oil(c)","(billion","LPG","(1000","(1000","Other(e)","Row" "Economic Characteristics(a)","(trillion Btu)","(million kWh)","(1000 bbls)","(1000 bbls)","(cu ft)","(1000 bbls)","short tons)","short tons)","(trillion Btu)","Factors"

158

char_household2001.pdf  

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

2001 2001 Household Characteristics RSE Column Factor: Total U.S. Four Most Populated States RSE Row Factors New York California Texas Florida 0.4 1.1 1.0 1.5 1.5 Total .............................................................. 107.0 7.1 12.3 7.7 6.3 NE Household Size 1 Person ...................................................... 28.2 2.2 2.4 1.8 1.7 7.3 2 Persons .................................................... 35.1 2.2 4.0 2.4 2.0 6.9 3 Persons .................................................... 17.0 1.1 2.0 1.2 1.2 9.5 4 Persons .................................................... 15.6 0.8 1.9 1.3 0.9 11.2 5 Persons .................................................... 7.1 0.4 1.1 0.4 0.5 19.8 6 or More Persons ....................................... 4.0 0.4 0.9 0.4 0.1 16.4 2001 Household Income Category

159

ac_household2001.pdf  

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

8a. Air Conditioning by Urban/Rural Location, 8a. Air Conditioning by Urban/Rural Location, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total Urban/Rural Location 1 RSE Row Factors City Town Suburbs Rural 0.5 0.8 1.4 1.3 1.4 Households With Electric Air-Conditioning Equipment ...................... 82.9 36.8 13.6 18.9 13.6 4.3 Air Conditioners Not Used ........................... 2.1 1.2 0.2 0.4 0.3 21.4 Households Using Electric Air-Conditioning 2 ........................................ 80.8 35.6 13.4 18.6 13.3 4.3 Type of Electric Air-Conditioning Used Central Air-Conditioning 3 ............................ 57.5 23.6 8.6 15.8 9.4 5.1 Without a Heat Pump ................................ 46.2 19.3 7.4 13.1 6.4 6.3 With a Heat Pump ..................................... 11.3 4.4

160

ac_household2001.pdf  

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

5a. Air Conditioning by Type of Owner-Occupied Housing Unit, 5a. Air Conditioning by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total Owner- Occupied Units Type of Owner-Occupied Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.5 0.5 1.5 1.4 1.8 Households With Electric Air-Conditioning Equipment ........ 59.5 58.7 6.5 12.4 5.3 5.2 Air Conditioners Not Used ............ 1.2 1.1 Q 0.6 Q 23.3 Households Using Electric Air-Conditioning 1 .......................... 58.2 57.6 6.3 11.8 5.1 5.3 Type of Electric Air-Conditioning Used Central Air-Conditioning 2 .............. 44.7 43.6 3.2 7.1 3.5 7.0 Without a Heat Pump .................. 35.6 35.0 2.4 6.1 2.7 7.7 With a Heat Pump .......................

Note: This page contains sample records for the topic "household characteristics census" 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

ac_household2001.pdf  

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

6a. Air Conditioning by Type of Rented Housing Unit, 6a. Air Conditioning by Type of Rented Housing Unit, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total Rented Units Type of Rented Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.8 0.5 1.4 1.2 1.6 Households With Electric Air-Conditioning Equipment ........ 23.4 58.7 6.5 12.4 5.3 6.1 Air Conditioners Not Used ............ 0.9 1.1 Q 0.6 Q 23.0 Households Using Electric Air-Conditioning 1 .......................... 22.5 57.6 6.3 11.8 5.1 6.2 Type of Electric Air-Conditioning Used Central Air-Conditioning 2 .............. 12.7 43.6 3.2 7.1 3.5 8.5 Without a Heat Pump .................. 10.6 35.0 2.4 6.1 2.7 9.3 With a Heat Pump ....................... 2.2 8.6 0.8 1.0

162

ac_household2001.pdf  

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

2a. Air Conditioning by Year of Construction, 2a. Air Conditioning by Year of Construction, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total Year of Construction RSE Row Factors 1990 to 2001 1 1980 to 1989 1970 to 1979 1960 to 1969 1950 to 1959 1949 or Before 0.4 1.6 1.2 1.1 1.2 1.1 0.9 Households With Electric Air-Conditioning Equipment ........ 82.9 13.6 16.0 14.7 10.4 10.5 17.6 4.7 Air Conditioners Not Used ............ 2.1 Q 0.3 0.5 0.3 0.4 0.5 27.2 Households Using Electric Air-Conditioning 2 .......................... 80.8 13.4 15.8 14.2 10.1 10.2 17.1 4.7 Type of Electric Air-Conditioning Used Central Air-Conditioning 3 .............. 57.5 12.6 13.7 11.0 7.1 6.6 6.4 5.9 Without a Heat Pump .................. 46.2 10.1 10.4 8.0 6.1 5.9 5.7 7.0 With a Heat Pump ....................... 11.3 2.5 3.3

163

ac_household2001.pdf  

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

4a. Air Conditioning by Type of Housing Unit, 4a. Air Conditioning by Type of Housing Unit, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total Type of Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.4 0.6 1.5 1.4 1.8 Households With Electric Air-Conditioning Equipment ........ 82.9 58.7 6.5 12.4 5.3 4.9 Air Conditioners Not Used ............ 2.1 1.1 Q 0.6 Q 21.8 Households Using Electric Air-Conditioning 1 .......................... 80.8 57.6 6.3 11.8 5.1 4.9 Type of Electric Air-Conditioning Used Central Air-Conditioning 2 .............. 57.5 43.6 3.2 7.1 3.5 6.7 Without a Heat Pump .................. 46.2 35.0 2.4 6.1 2.7 7.7 With a Heat Pump ....................... 11.3 8.6 0.8 1.0 0.8 19.7 Room Air-Conditioning

164

34th annual reed rotary rig census  

SciTech Connect

This article reports that the number of rigs active according to the 1986 census is 1052, which represents a decline of 1573 rigs from 1985 figures. This 60 percent decrease is the largest decline of active rigs in the 34-year history of the census. The 1986 census takers found 3993 rigs are available with the capacity to drill deeper than 3000 ft. The count has thus declined by 416 rigs (9 percent) from the 1985 total of 4409. Rig availability declined for the fourth consecutive year following nine straight years of fleet expansion (1974-1982). During the past four years, 1651 rigs have been removed from the drilling fleet representing a 29 percent decline from the record high number of rigs available in 1982. The 1986 decline in the available U.S. fleet is considerably less than what many industry observers had been anticipating. A larger decrease in the rig fleet has not been realized for a number of reasons.

Hutchinson, D.L.; Pastusek, P.E.

1986-10-01T23:59:59.000Z

165

Hanford Site Regional Population - 2010 Census  

Science Conference Proceedings (OSTI)

The U.S. Department of Energy conducts radiological operations in south-central Washington State. Population dose estimates must be performed to provide a measure of the impact from site radiological releases. Results of the U.S. 2010 Census were used to determine counts and distributions for the residential population located within 50-miles of several operating areas of the Hanford Site. Year 2010 was the first census year that a 50-mile population of a Hanford Site operational area exceeded the half-million mark.

Hamilton, Erin L.; Snyder, Sandra F.

2011-08-12T23:59:59.000Z

166

"Table HC13.13 Lighting Usage Indicators by South Census Region...  

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

3 Lighting Usage Indicators by South Census Region, 2005" " Million U.S. Housing Units" ,,"South Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total...

167

"Table HC11.13 Lighting Usage Indicators by Northeast Census...  

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

3 Lighting Usage Indicators by Northeast Census Region, 2005" " Million U.S. Housing Units" ,,"Northeast Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division"...

168

"Table HC12.13 Lighting Usage Indicators by Midwest Census Region...  

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

3 Lighting Usage Indicators by Midwest Census Region, 2005" " Million U.S. Housing Units" ,,"Midwest Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total...

169

"Table HC14.13 Lighting Usage Indicators by West Census Region...  

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

3 Lighting Usage Indicators by West Census Region, 2005" " Million U.S. Housing Units" ,,"West Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total West"...

170

Geographic Trends Among Same-Sex Couples in the US Census and the American Community Survey  

E-Print Network (OSTI)

WILLIAMS INSTITUTE GEOGRAPHIC TRENDS IN THE CENSUS AND ACSWILLIAMS INSTITUTE GEOGRAPHIC TRENDS IN THE CENSUS AND ACSWILLIAMS INSTITUTE GEOGRAPHIC TRENDS IN THE CENSUS AND ACS

Gates, Gary J

2007-01-01T23:59:59.000Z

171

1997 Housing Characteristics Tables Housing Unit Tables  

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

Million U.S. Households; 45 pages, 128 kb) Million U.S. Households; 45 pages, 128 kb) Contents Pages HC1-1a. Housing Unit Characteristics by Climate Zone, Million U.S. Households, 1997 4 HC1-2a. Housing Unit Characteristics by Year of Construction, Million U.S. Households, 1997 4 HC1-3a. Housing Unit Characteristics by Household Income, Million U.S. Households, 1997 4 HC1-4a. Housing Unit Characteristics by Type of Housing Unit, Million U.S. Households, 1997 3 HC1-5a. Housing Unit Characteristics by Type of Owner-Occupied Housing Unit, Million U.S. Households, 1997 3 HC1-6a. Housing Unit Characteristics by Type of Rented Housing Unit, Million U.S. Households, 1997 3 HC1-7a. Housing Unit Characteristics by Four Most Populated States, Million U.S. Households, 1997 4

172

Form EIA-457E (2001) -- Household Bottled Gas Usage  

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

F (2001) -- Household Natural Gas Usage Form F (2001) -- Household Natural Gas Usage Form OMB No. 1905-0092, Expiring February 29, 2004 2001 Residential Energy Consumption Survey Answers to Frequently Asked Questions About the Household Natural Gas Usage Form What is the purpose of the Residential Energy Consumption Survey? The Residential Energy Consumption Survey (RECS) collects data on energy consumption and expenditures in U.S. housing units. Over 5,000 statistically selected households across the U.S. have already provided information about their household, the physical characteristics of their housing unit, their energy-using equipment, and their energy suppliers. Now we are requesting the energy billing records for these households from each of their energy suppliers. After all this information has been collected, the information will be used to

173

Form EIA-457E (2001) -- Household Bottled Gas Usage  

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

E (2001) - Household Electricity Usage Form E (2001) - Household Electricity Usage Form OMB No. 1905-0092, Expiring February 29, 2004 2001 Residential Energy Consumption Survey Answers to Frequently Asked Questions About the Household Electricity Usage Form What is the purpose of the Residential Energy Consumption Survey? The Residential Energy Consumption Survey (RECS) collects data on energy consumption and expenditures in U.S. housing units. Over 5,000 statistically selected households across the U.S. have already provided information about their household, the physical characteristics of their housing unit, their energy-using equipment, and their energy suppliers. Now we are requesting the energy billing records for these households from each of their energy suppliers. After all this information has been collected, the information will be used to

174

Table 5C. Industrial Average Monthly Bill by Census Division ...  

U.S. Energy Information Administration (EIA)

Home > Electricity > Electric Sales, Revenue, and Price > Industrial Average Monthly Bill by Census Division, and State: Table 5C. Industrial ...

175

" by Type of Supplier, Census Region, Census Division, Industry Group,"  

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

3. Average Prices of Purchased Electricity and Steam" 3. Average Prices of Purchased Electricity and Steam" " by Type of Supplier, Census Region, Census Division, Industry Group," " and Selected Industries, 1994" " (Estimates in Dollars per Physical Units)" ,," Electricity",," Steam" ,," (kWh)",," (million Btu)" ,,,,,,"RSE" "SIC",,"Utility","Nonutility","Utility","Nonutility","Row" "Code(a)","Industry Group and Industry","Supplier(b)","Supplier(c)","Supplier(b)","Supplier(c)","Factors"

176

" by Census Region, Census Division, Industry Group, Selected Industries, and"  

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

Total Inputs of Energy for Heat, Power, and Electricity Generation" Total Inputs of Energy for Heat, Power, and Electricity Generation" " by Census Region, Census Division, Industry Group, Selected Industries, and" " Presence of Cogeneration Technologies, 1994: Part 1" " (Estimates in Trillion Btu)",," ",,,,,,," "," "," " ,,,"Steam Turbines",,,,"Steam Turbines" ,," ","Supplied by Either","Conventional",,,"Supplied by","One or More",," " " "," ",,"Conventional","Combustion ","Combined-Cycle","Internal Combustion","Heat Recovered from","Cogeneration",,"RSE"

177

" Census Region, Census Division, Industry Group, and Selected Industries, 1994"  

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

Quantity of Purchased Electricity and Steam by Type of Supplier," Quantity of Purchased Electricity and Steam by Type of Supplier," " Census Region, Census Division, Industry Group, and Selected Industries, 1994" " (Estimates in Btu or Physical Units)" ,," Electricity",," Steam" ,," (million kWh)",," (billion Btu)" ,,,,,,"RSE" "SIC",,"Utility","Nonutility","Utility","Nonutility","Row" "Code(a)","Industry Group and Industry","Supplier(b)","Supplier(c)","Supplier(b)","Supplier(c)","Factors"

178

" and Electricity Generation by Census Region, Census Division, Industry Group,"  

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

3. Total Inputs of Selected Wood and Wood-Related Products for Heat, Power," 3. Total Inputs of Selected Wood and Wood-Related Products for Heat, Power," " and Electricity Generation by Census Region, Census Division, Industry Group," " and Selected Industries, 1994" " (Estimates in Billion Btu)" ,,,,"Selected Wood and Wood-Related Products" ,,,,,"Biomass" " "," ",," "," "," ","Wood Residues","Wood-Related"," " " "," ","Pulping Liquor",," ","Wood Harvested","and Byproducts","and","RSE" "SIC"," ","or","Biomass","Agricultural","Directly","from","Paper-Related","Row"

179

" by Census Region, Census Division, Industry Group, Selected Industries, and"  

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

Total Inputs of Energy for Heat, Power, and Electricity Generation" Total Inputs of Energy for Heat, Power, and Electricity Generation" " by Census Region, Census Division, Industry Group, Selected Industries, and" " Presence of General Technologies, 1994: Part 1" " (Estimates in Trillion Btu)" ,,,,"Computer Control" ,," "," ","of Processes"," "," ",," "," "," "," " ,," ","Computer Control","or Major",,,"One or More"," ","RSE",," " "SIC"," ",,"of Building","Energy-Using","Waste Heat"," Adjustable-Speed","General Technologies","None","Row"

180

usage_household2001.pdf  

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

Usage Indicators Tables Usage Indicators Tables (Million U.S. Households; 60 pages, 247 kb) Contents Pages HC6-1a. Usage Indicators by Climate Zone, Million U.S. Households, 2001 5 HC6-2a. Usage Indicators by Year of Construction, Million U.S. Households, 2001 5 HC6-3a. Usage Indicators by Household Income, Million U.S. Households, 2001 5 HC6-4a. Usage Indicators by Type of Housing Unit, Million U.S. Households, 2001 5 HC6-5a. Usage Indicators by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 5 HC6-6a. Usage Indicators by Type of Rented Housing Unit, Million U.S. Households, 2001 5 HC6-7a. Usage Indicators by Four Most Populated States, Million U.S. Households, 2001 5

Note: This page contains sample records for the topic "household characteristics census" 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

homeoffice_household2001.pdf  

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

Home Office Equipment Tables Home Office Equipment Tables (Million U.S. Households; 12 pages, 123 kb) Contents Pages HC7-1a. Home Office Equipment by Climate Zone, Million U.S. Households, 2001 1 HC7-2a. Home Office Equipment by Year of Construction, Million U.S. Households, 2001 1 HC7-3a. Home Office Equipment by Household Income, Million U.S. Households, 2001 1 HC7-4a. Home Office Equipment by Type of Housing Unit, Million U.S. Households, 2001 1 HC7-5a. Home Office Equipment by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 1 HC7-6a. Home Office Equipment by Type of Rented Housing Unit, Million U.S. Households, 2001 1 HC7-7a. Home Office Equipment by Four Most Populated States, Million U.S. Households, 2001 1

182

Commercial Buildings Characteristics 1995 - Index Page  

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

>Commercial Buildings Home > 1995 Characteristics Data 1995 Data Executive Summary Table of Contents Overview to Detailed Tables Detailed Tables 1995 national and Census region...

183

"Table A25. Components of Total Electricity Demand by Census Region, Census Division, Industry"  

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

Components of Total Electricity Demand by Census Region, Census Division, Industry" Components of Total Electricity Demand by Census Region, Census Division, Industry" " Group, and Selected Industries, 1994" " (Estimates in Million Kilowatthours)" " "," "," "," "," "," "," "," " " "," "," "," "," ","Sales and/or"," ","RSE" "SIC"," "," ","Transfers","Total Onsite","Transfers","Net Demand for","Row" "Code(a)","Industry Group and Industry","Purchases","In(b)","Generation(c)","Offsite","Electricity(d)","Factors"

184

Household Vehicles Energy Use Cover Page  

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

Household Vehicles Energy Use Cover Page Glossary Home > Households, Buildings & Industry >Transportation Surveys > Household Vehicles Energy Use Cover Page Contact Us * Feedback *...

185

Household Vehicles Energy Consumption 1991  

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

Aggregate Aggregate Ratio: See Mean and Ratio Estimate. AMPD: Average miles driven per day. See Appendix B, "Estimation Methodologies." Annual Vehicle Miles Traveled: See Vehicle Miles Traveled. Automobile: Includes standard passenger car, 2-seater car and station wagons; excludes passenger vans, cargo vans, motor homes, pickup trucks, and jeeps or similar vehicles. See Vehicle. Average Household Energy Expenditures: A ratio estimate defined as the total household energy expenditures for all RTECS households divided by the total number of households. See Ratio Estimate, and Combined Household Energy Expenditures. Average Number of Vehicles per Household: The average number of vehicles used by a household for personal transportation during 1991. For this report, the average number of vehicles per household is computed as the ratio of the total number of vehicles to the

186

ac_household2001.pdf  

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

2001 2001 Air Conditioning Characteristics RSE Column Factor: Total U.S. Four Most Populated States RSE Row Factors New York California Texas Florida 0.4 1.1 1.7 1.2 1.2 Households With Electric Air-Conditioning Equipment ...................... 82.9 4.9 6.0 7.4 6.2 2.4 Air Conditioners Not Used ........................... 2.1 0.1 0.8 Q 0.1 23.2 Households Using Electric Air-Conditioning 1 ........................................ 80.8 4.7 5.2 7.4 6.1 2.6 Type of Electric Air-Conditioning Used Central Air-Conditioning 2 ............................ 57.5 1.3 3.9 6.2 5.7 6.7 Without a Heat Pump ................................ 46.2 1.2 3.2 5.5 3.8 8.1 With a Heat Pump ..................................... 11.3 Q 0.8 0.6 1.9 14.7 Room Air-Conditioning ................................ 23.3 3.4 1.2 1.2 0.3 13.6 1 Unit

187

Racial and demographic differences in household travel and fuel purchase behavior  

Science Conference Proceedings (OSTI)

Monthly fuel purchase logs from the Residential Energy Consumption Survey's Household Transportation Panel (TP) were analyzed to determine the relationship between various household characteristics and purchase frequency, tank inventories, vehicle-miles traveled, and fuel expenditures. Multiple classification analysis (MCA) was used to relate observed differences in dependent variables to such index-type household characteristics as income and residence location, and sex, race and age of household head. Because it isolates the net effect of each parameter, after accounting for the effects of all other parameters, MCA is particularly appropriate for this type of analysis. Results reveal clear differences in travel and fuel purchase behavior for four distinct groups of vehicle-owning households. Black households tend to own far fewer vehicles with lower fuel economy, to use them more intensively, to purchase fuel more frequently, and to maintain lower fuel inventories than white households. Similarly, poor households own fewer vehicles with lower fuel economy, but they drive them less intensively, purchase fuel more frequently, and maintain lower fuel inventories than nonpoor households. Elderly households also own fewer vehicles with lower fuel economy. But since they drive them much less intensively, their fuel purchases are much less frequent and their fuel inventories are higher than nonelderly households. Female-headed households also own fewer vehicles but with somewhat higher fuel economy. They drive them less intensively, maintain higher fuel inventories, and purchase fuel less frequently than male-headed households. 13 refs., 8 tabs.

Gur, Y.; Millar, M.

1987-01-01T23:59:59.000Z

188

Table 2.4 Household Energy Consumption by Census Region, Selected ...  

U.S. Energy Information Administration (EIA)

Short-Term Energy Outlook › Annual Energy Outlook ... no data available. - Data for 1978-1984 are for April of year shown through March of following year; data

189

Household Vehicles Energy Use: Latest Data and Trends - Table A01  

U.S. Energy Information Administration (EIA)

Table A1. U.S. Number of Vehicles, Vehicles-Miles, Motor Fuel Consumption and Expenditures, 2001: 2001 Household and Vehicle Characteristics

190

Residential demand for natural gas by black and nonblack households in the Midwest  

SciTech Connect

This paper presents a comparative analysis of natural gas demand by black and nonblack households in the Midwest census region. Historically, such comparative analyses have been grounded in comparisons of the share of income spent for energy (see Newman and Day, 1975; Grier, 1979; and Brazzel and Hunter, 1979). Because of theoretical flaws associated with this approach, our analysis is couched within a complete demand system (see Morrissey, 1984) in which certain restrictions required by consumer demand theory are imposed on our energy demand system. This approach should provide more precise measurement of the relative nature of natural gas demand. Philips (1983), Deaton and Muellbauer (1980), and Theil (1980), along with Morrissev, provide fine discussions of the complete demand system. Our working hypothesis is that the structural demand relationship for natural gas is different for black and nonblack households and that this difference reflects the greater vulnerability of blacks to rising prices of natural gas. Because of deficient economic resources and a long legacy of institutional constraints such as financial red-lining and housing discrimination, as well as lingering behavioral characteristics, it remains difficult for blacks to move out of energy-inefficient housing. This, in turn, corresponds directly to a larger energy demand burden for blacks in the Midwest. This paper is organized into four sections. The first section provides the historical background upon which our analysis is based. The second section is a discussion of our demand model. Our empirical results are described in the third section. In the fourth and final section, our conclusions and suggestions for future research are presented. 18 refs., 7 tabs.

Poyer, D.A.; Johnson, G.

1985-10-01T23:59:59.000Z

191

Household Hazardous Waste Household hazardous waste is the discarded, unused, or leftover portion of household products  

E-Print Network (OSTI)

Household Hazardous Waste Household hazardous waste is the discarded, unused, or leftover portion of household products containing toxic chemicals. These wastes CANNOT be disposed of in regular garbage. Any should be considered hazardous. You cannot treat hazardous wastes like other kinds of garbage

de Lijser, Peter

192

" Million U.S. Housing Units"  

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

"Table HC10.3 Household Characteristics by U.S. Census Region, 2005" " Million U.S. Housing Units" ,"Housing Units (millions)","U.S. Census Region" "Household Characteristics",,"No...

193

ac_household2001.pdf  

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

Air Conditioning Tables Air Conditioning Tables (Million U.S. Households; 24 pages, 138 kb) Contents Pages HC4-1a. Air Conditioning by Climate Zone, Million U.S. Households, 2001 2 HC4-2a. Air Conditioning by Year of Construction, Million U.S. Households, 2001 2 HC4-3a. Air Conditioning by Household Income, Million U.S. Households, 2001 2 HC4-4a. Air Conditioning by Type of Housing Unit, Million U.S. Households, 2001 2 HC4-5a. Air Conditioning by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 2 HC4-6a. Air Conditioning by Type of Rented Housing Unit, Million U.S. Households, 2001 2 HC4-7a. Air Conditioning by Four Most Populated States, Million U.S. Households, 2001 2 HC4-8a. Air Conditioning by Urban/Rural Location, Million U.S. Households, 2001 2

194

Table 5B. Commercial Average Monthly Bill by Census Division ...  

U.S. Energy Information Administration (EIA)

Home > Electricity > Electric Sales, Revenue, and Price > Commercial Average Monthly Bill by Census Division, and State: Table 5B. Commercial Average Monthly Bill by ...

195

Table 5B. Commercial average monthly bill by census division...  

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

" Census Division " " State ","Number of Consumers "," Average Monthly Consumption (kWh)","Price (Cents per Kilowatthour)","Average Monthly Bill (Dollar and cents)" "New...

196

Housing characteristics 1993  

Science Conference Proceedings (OSTI)

This report, Housing Characteristics 1993, presents statistics about the energy-related characteristics of US households. These data were collected in the 1993 Residential Energy Consumption Survey (RECS) -- the ninth in a series of nationwide energy consumption surveys conducted since 1978 by the Energy Information Administration of the US Department of Energy. Over 7 thousand households were surveyed, representing 97 million households nationwide. A second report, to be released in late 1995, will present statistics on residential energy consumption and expenditures.

NONE

1995-06-01T23:59:59.000Z

197

Householder’s Perceptions of Insulation Adequacy and Drafts in the Home in 2001  

E-Print Network (OSTI)

In order to improve the estimation of end-use heating consumption, the Energy Information Administration's (EIA), 2001 Residential Energy Consumption Survey (RECS), for the first time, asked respondents to judge how drafty they perceived their homes to be as a measure of insulation quality. The analysis of the 2001 RECS data shows that householders in newlyconstructed homes perceived their homes to be better insulated and less drafty than do householders in older homes. Single-family homes are perceived to be better insulated and less drafty than are apartments in buildings with two to four units. Cross-variable comparisons also provide the associations between the level of insulation and winter drafts in the homes with household characteristics and location of the home.

Behjat Hojjati

2004-01-01T23:59:59.000Z

198

Energy Spending and Vulnerable Households  

E-Print Network (OSTI)

 off than before. In particular large households with low  incomes seem to have been adversely affected by the new tariff structures since  they have comparably large energy expenditure (Bennet et al., 2002).    5. Vulnerable Households and Energy Spending  The...  tariffs can play an important part in the public debate  on  eradicating  fuel  poverty  and  helping  the  vulnerable  households.  Smart  metering  can  provide  consumers  with  information  on  the  actual  energy  consumption and might  lead  to...

Jamasb, Tooraj; Meier, Helena

2011-01-26T23:59:59.000Z

199

Household Vehicles Energy Consumption 1991  

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

DOEEIA-0464(91) Distribution Category UC-950 Household Vehicles Energy Consumption 1991 December 1993 Energy Information Administration Office of Energy Markets and End Use U.S....

200

Household Energy Consumption and Expenditures  

Reports and Publications (EIA)

Presents information about household end use consumption of energy and expenditures for that energy. These data were collected in the 2005 Residential Energy Consumption Survey (RECS)

Information Center

2008-09-01T23:59:59.000Z

Note: This page contains sample records for the topic "household characteristics census" 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

Household Vehicles Energy Consumption 1991  

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

a regular basis at the time of the 1990 RECS personal interviews. Electricity: See Main Heating Fuel. Energy Information AdministrationHousehold Vehicles Energy Consumption 1991...

202

Household Vehicles Energy Consumption 1994  

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

AdministrationHousehold Vehicles Energy Consumption 1994 110 Electricity: See Main Heating Fuel. Energy Used in the Home: For electricity or natural gas, the quantity is the...

203

U.S. Census Regions and Divisions Map for Commercial Buildings  

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

Background Information on CBECS > Census Regions and Divisions Map U. S. Census Regions and Divisions: Map of the U.S. Census Regions and Divisions Return to CBECS Home Page...

204

Aleutians West Census Area, Alaska ASHRAE 169-2006 Climate Zone...  

Open Energy Info (EERE)

Aleutians West Census Area, Alaska ASHRAE 169-2006 Climate Zone Jump to: navigation, search County Climate Zone Place Aleutians West Census Area, Alaska ASHRAE Standard ASHRAE...

205

appl_household2001.pdf  

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

a. Appliances by Climate Zone, a. Appliances by Climate Zone, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total Climate Zone 1 RSE Row Factors Fewer than 2,000 CDD and -- 2,000 CDD or More and Fewer than 4,000 HDD More than 7,000 HDD 5,500 to 7,000 HDD 4,000 to 5,499 HDD Fewer than 4,000 HDD 0.4 1.9 1.1 1.1 1.2 1.1 Total .................................................. 107.0 9.2 28.6 24.0 21.0 24.1 7.8 Kitchen Appliances Cooking Appliances Oven .............................................. 101.7 9.1 27.9 23.1 19.4 22.2 7.8 1 ................................................... 95.2 8.7 26.0 21.6 17.7 21.2 7.9 2 or More ..................................... 6.5 0.4 1.9 1.5 1.7 1.0 14.7 Most Used Oven ........................... 101.7 9.1 27.9 23.1 19.4 22.2

206

appl_household2001.pdf  

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

4a. Appliances by Type of Housing Unit, 4a. Appliances by Type of Housing Unit, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total Type of Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.4 0.5 1.7 1.6 1.9 Total ............................................... 107.0 73.7 9.5 17.0 6.8 4.2 Kitchen Appliances Cooking Appliances Oven ........................................... 101.7 69.1 9.4 16.7 6.6 4.3 1 ................................................ 95.2 63.7 8.9 16.2 6.3 4.3 2 or More .................................. 6.5 5.4 0.4 0.4 0.2 15.9 Most Used Oven ........................ 101.7 69.1 9.4 16.7 6.6 4.3 Electric ...................................... 63.0 43.3 5.2 10.9 3.6

207

spaceheat_household2001.pdf  

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

8a. Space Heating by Urban/Rural Location, 8a. Space Heating by Urban/Rural Location, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total Urban/Rural Location 1 RSE Row Factors City Town Suburbs Rural 0.6 0.9 1.3 1.3 1.2 Total .............................................................. 107.0 49.9 18.0 21.2 17.9 4.3 Heat Home .................................................... 106.0 49.1 18.0 21.2 17.8 4.3 Do Not Heat Home ....................................... 1.0 0.7 0.1 0.1 0.1 25.8 No Heating Equipment ................................ 0.5 0.4 0.1 Q 0.1 33.2 Have Equipment But Do Not Use It ............................................... 0.4 0.3 Q Q Q 30.2 Main Heating Fuel and Equipment (Have and Use Equipment) ........................... 106.0 49.1 18.0 21.2 17.8 4.3 Natural Gas

208

spaceheat_household2001.pdf  

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

5a. Space Heating by Type of Owner-Occupied Housing Unit, 5a. Space Heating by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total Owner- Occupied Units Type of Owner-Occupied Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.4 0.4 1.9 3.0 1.3 Total ............................................... 72.7 63.2 2.1 1.8 5.7 6.7 Heat Home ..................................... 72.4 63.0 2.0 1.7 5.7 6.7 Do Not Heat Home ........................ 0.4 0.2 Q Q Q 46.2 No Heating Equipment .................. 0.3 0.2 Q Q Q 39.0 Have Equipment But Do Not Use It ................................ Q Q Q Q Q NF Main Heating Fuel and Equipment (Have and Use Equipment) ............ 72.4 63.0 2.0 1.7 5.7 6.7 Natural Gas

209

spaceheat_household2001.pdf  

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

2a. Space Heating by Year of Construction, 2a. Space Heating by Year of Construction, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total Year of Construction RSE Row Factors 1990 to 2001 1 1980 to 1989 1970 to 1979 1960 to 1969 1950 to 1959 1949 or Before 0.5 1.5 1.1 1.1 1.1 1.1 0.9 Total ............................................... 107.0 15.5 18.2 18.8 13.8 14.2 26.6 4.3 Heat Home ..................................... 106.0 15.4 18.2 18.6 13.6 13.9 26.4 4.3 Do Not Heat Home ........................ 1.0 Q Q Q 0.2 0.3 Q 23.2 No Heating Equipment .................. 0.5 Q Q Q 0.2 Q Q 30.3 Have Equipment But Do Not Use It ................................ 0.4 Q Q Q Q Q Q 37.8 Main Heating Fuel and Equipment (Have and Use Equipment) ............ 106.0 15.4 18.2 18.6 13.6 13.9 26.4 4.3 Natural Gas ...................................

210

appl_household2001.pdf  

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

5a. Appliances by Type of Owner-Occupied Housing Unit, 5a. Appliances by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total Owner- Occupied Units Type of Owner-Occupied Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.3 0.4 2.1 3.1 1.3 Total ............................................... 72.7 63.2 2.1 1.8 5.7 6.7 Kitchen Appliances Cooking Appliances Oven ........................................... 68.3 59.1 2.0 1.7 5.4 7.0 1 ................................................ 62.9 54.1 2.0 1.6 5.2 7.1 2 or More .................................. 5.4 5.0 Q Q 0.2 22.1 Most Used Oven ........................ 68.3 59.1 2.0 1.7 5.4 7.0 Electric ......................................

211

spaceheat_household2001.pdf  

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

4a. Space Heating by Type of Housing Unit, 4a. Space Heating by Type of Housing Unit, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total Type of Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.5 0.5 1.5 1.4 1.7 Total ............................................... 107.0 73.7 9.5 17.0 6.8 4.4 Heat Home ..................................... 106.0 73.4 9.4 16.4 6.8 4.5 Do Not Heat Home ........................ 1.0 0.3 Q 0.6 Q 19.0 No Heating Equipment .................. 0.5 0.2 Q 0.3 Q 24.2 Have Equipment But Do Not Use It ................................ 0.4 Q Q 0.3 Q 28.1 Main Heating Fuel and Equipment (Have and Use Equipment) ............ 106.0 73.4 9.4 16.4 6.8 4.5 Natural Gas ...................................

212

appl_household2001.pdf  

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

2a. Appliances by Year of Construction, 2a. Appliances by Year of Construction, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total Year of Construction RSE Row Factors 1990 to 2001 1 1980 to 1989 1970 to 1979 1960 to 1969 1950 to 1959 1949 or Before 0.4 1.5 1.2 1.1 1.2 1.1 0.9 Total ............................................... 107.0 15.5 18.2 18.8 13.8 14.2 26.6 4.2 Kitchen Appliances Cooking Appliances Oven ........................................... 101.7 14.3 17.2 17.8 12.9 13.7 25.9 4.2 1 ................................................ 95.2 13.1 16.3 16.6 12.1 12.7 24.3 4.4 2 or More .................................. 6.5 1.2 0.9 1.1 0.7 1.0 1.6 14.8 Most Used Oven ........................ 101.7 14.3 17.2 17.8 12.9 13.7 25.9 4.2 Electric ......................................

213

spaceheat_household2001.pdf  

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

6a. Space Heating by Type of Rented Housing Unit, 6a. Space Heating by Type of Rented Housing Unit, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total Rented Units Type of Rented Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.5 0.8 1.1 0.9 2.5 Total ............................................... 34.3 10.5 7.4 15.2 1.1 6.9 Heat Home ..................................... 33.7 10.4 7.4 14.8 1.1 6.9 Do Not Heat Home ........................ 0.6 Q Q 0.5 Q 21.4 No Heating Equipment .................. 0.2 Q Q Q Q 84.5 Have Equipment But Do Not Use It ................................ 0.4 Q Q 0.3 Q 36.4 Main Heating Fuel and Equipment (Have and Use Equipment) ............ 33.7 10.4 7.4 14.8 1.1 6.9 Natural Gas ...................................

214

Extending Efficiency Services to Underserved Households: NYSERDA...  

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

Extending Efficiency Services to Underserved Households: NYSERDA's Assisted Home Performance with ENERGY STAR Program Title Extending Efficiency Services to Underserved Households:...

215

" Million U.S. Housing Units"  

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

"Table HC14.3 Household Characteristics by West Census Region, 2005" " Million U.S. Housing Units" ,,"West Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division"...

216

EIA - Household Transportation report: Household Vehicles Energy Use:  

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

Transportation logo printer-friendly version logo for Portable Document Format file Household Vehicles Energy Use: Latest Data & Trends November 2005 Release (Next Update: Discontinued) Based on the 2001 National Household Travel Survey conducted by the U.S. Department of Transportation and augmented by EIA Only light-duty vehicles and recreational vehicles are included in this report. EIA has excluded motorcycles, mopeds, large trucks, and buses in an effort to maintain consistency with its past residential transportation series, which was discontinued after 1994. This report, Household Vehicles Energy Use: Latest Data & Trends, provides details on the nation's energy use for household passenger travel. A primary purpose of this report is to release the latest consumer-based data

217

Cover Page of Household Vehicles Energy Use: Latest Data & Trends  

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

Household Vehicles Energy Use Cover Page Cover Page of Household Vehicles Energy Use: Latest Data & Trends...

218

Household Vehicles Energy Consumption 1994  

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

W as hi ng to n, DC DOEEIA-0464(94) Distribution Category UC-950 Household Vehicles Energy Consumption 1994 August 1997 Energy Information Administration Office of Energy Markets...

219

Household savings and portfolio choice  

E-Print Network (OSTI)

This thesis consists of three essays that examine household savings and portfolio choice behavior. Chapter One analyses the effects of employer matching contributions and tax incentives on participation and contribution ...

Klein, Sean Patrick

2010-01-01T23:59:59.000Z

220

An economic assessment of the impact of two crude oil price scenarios on households  

SciTech Connect

The impact of two possible future crude oil price scenarios -- high and low price cases -- is assessed for three population groups: majority (non-Hispanic and nonblack), black, and Hispanic. The two price scenarios were taken from the energy security'' report published by the US Department of Energy in 1987. Effects of the two crude oil price scenarios for the 1986--95 period are measured for energy demand and composition and for share of income spent on energy by the three population groups at both the national and census-region levels. The effects on blacks are marginally more adverse than on majority householders, while effects on Hispanics are about the same as those on the majority. Little change is seen in percentage of income spent on energy over the forecast period. Both Hispanic and black households would spend a larger share of their incomes on energy than would majority households. The relatively adverse effects in the higher price scenario shift from the South and West Census regions to the Northeast and Midwest. 24 refs., 7 figs., 22 tabs.

Poyer, D.A.; Teotia, A.P.S.; Hemphill, R.C.; Hill, L.G.; Marinelli, J.L.; Rose, K.J.; Santini, D.J.

1990-02-01T23:59:59.000Z

Note: This page contains sample records for the topic "household characteristics census" 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

Table 38. Coal Stocks at Coke Plants by Census Division  

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

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

222

homeoffice_household2001.pdf  

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

3a. Home Office Equipment by Household Income, 3a. Home Office Equipment by Household Income, Million U.S. Households, 2001 Home Office Equipment RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral Assist- ance 1 RSE Row Factors Less than $14,999 $15,000 to $29,999 $30,000 to $49,999 $50,000 or More 0.4 1.9 1.2 1.0 0.6 1.9 0.9 Total ............................................... 107.0 18.7 22.9 27.1 38.3 15.0 47.6 3.0 Households Using Office Equipment .......................... 96.2 13.2 19.8 25.5 37.7 10.7 38.8 3.2 Personal Computers 2 ................... 60.0 3.7 8.7 16.0 31.6 3.7 17.4 4.6 Number of Desktop PCs 1 .................................................. 45.1 2.8 7.1 12.8 22.4 2.8 13.6 5.1 2 or more .................................... 9.1 0.6 0.7 1.7 6.2 0.6 2.2 13.0 Number of Laptop PCs

223

The Household Market for Electric Vehicles: Testing the Hybrid Household Hypothesis--A Reflively Designed Survey of New-car-buying, Multi-vehicle California Households  

E-Print Network (OSTI)

HOW MANY HYBRID HOUSEHOLDS IN THE CALIFORNIA NEW CAR MARKET?average 2.43 cars per household, then the hybrid householdnumber of multi-car households that fit our hybrid household

Turrentine, Thomas; Kurani, Kenneth

1995-01-01T23:59:59.000Z

224

Assessing urban and rural neighborhood characteristics using audit and GIS data: derivation and reliability of constructs  

E-Print Network (OSTI)

Bureau: Census 2000 urban and rural classifications. 2009 [Assessing urban and rural neighborhood characteristics usingreliability in both urban and rural segments (r = 0.96).

Evenson, Kelly R; Sotres-Alvarez, Daniela; Herring, Amy H; Messer, Lynne; Laraia, Barbara A; Rodríguez, Daniel A

2009-01-01T23:59:59.000Z

225

Household energy in South Asia  

Science Conference Proceedings (OSTI)

This research study on the use of energy in South Asis (India, Pakistan, Sri Lanka and Bangladesh) was sponsored by the Food and Agriculture Organization of the UN, the International Bank for Reconstruction and Development (the World Bank), and the Directorate-General for Development of the Commission of the European Communities. The aim of this book is to improve the understanding of household energy and its linkages, by reviewing the data resources on household energy use, supply, prices and other relevant factors that exist in South Asia.

Leach, G.

1987-01-01T23:59:59.000Z

226

Delivering Energy Efficiency to Middle Income Single Family Households  

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

Delivering Energy Efficiency to Middle Income Single Family Households Delivering Energy Efficiency to Middle Income Single Family Households Title Delivering Energy Efficiency to Middle Income Single Family Households Publication Type Report Year of Publication 2011 Authors Zimring, Mark, Merrian Borgeson, Ian M. Hoffman, Charles A. Goldman, Elizabeth Stuart, Annika Todd, and Megan A. Billingsley Pagination 102 Date Published 12/2011 Publisher LBNL City Berkeley Keywords electricity markets and policy group, energy analysis and environmental impacts department Abstract The question posed in this report is: How can programs motivate these middle income single family households to seek out more comprehensive energy upgrades, and empower them to do so? Research methods included interviews with more than 35 program administrators, policy makers, researchers, and other experts; case studies of programs, based on interviews with staff and a review of program materials and data; and analysis of relevant data sources and existing research on demographics, the financial status of Americans, and the characteristics of middle income American households. While there is no 'silver bullet' to help these households overcome the range of barriers they face, this report describes outreach strategies, innovative program designs, and financing tools that show promise in increasing the attractiveness and accessibility of energy efficiency for this group. These strategies and tools should be seen as models that are currently being honed to build our knowledge and capacity to deliver energy improvements to middle income households. However, the strategies described in this report are probably not sufficient, in the absence of robust policy frameworks, to deliver these improvements at scale. Instead, these strategies must be paired with enabling and complementary policies to reach their full potential.

227

Energy Information Administration/Household Vehicles Energy Consumption 1994  

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

, , Energy Information Administration/Household Vehicles Energy Consumption 1994 ix Household Vehicles Energy Consumption 1994 presents statistics about energy-related characteristics of highway vehicles available for personal use by members of U.S. households. The data were collected in the 1994 Residential Transportation Energy Consumption Survey, the final cycle in a series of nationwide energy consumption surveys conducted during the 1980's and 1990's by the Energy Information Administrations. Engines Became More Powerful . . . Percent Distribution of Total Residential Vehicle Fleet by Number of Cylinders, 1988 and 1994 Percent Distribution of Vehicle Fleet by Engine Size, 1988 and 1994 Percent Percent 4 cyl Less than 2.50 liters 6 cyl 2.50- 4.49 liters 8 cyl 4.50 liters or greater 20 20 40 40 Vehicle

228

Assumptions to the Annual Energy Outlook 2002 - Household Expenditures...  

Annual Energy Outlook 2012 (EIA)

Expenditures Module The Household Expenditures Module (HEM) constructs household energy expenditure profiles using historical survey data on household income, population and...

229

Table WH1. Total Households Using Water Heating Equipment, 2005 ...  

U.S. Energy Information Administration (EIA)

Table WH1. Total Households Using Water Heating Equipment, 2005 Million U.S. Households Fuels Used (million U.S. households) Number of Water Heaters Used

230

Residential energy consumption survey. Consumption patterns of household vehicles, supplement: January 1981-September 1981  

Science Conference Proceedings (OSTI)

Information on the fuel consumption characteristics on household vehicles in the 48 contiguous States and the District of Columbia is presented by monthly statistics of fuel consumption, expenditures, miles per gallon, and miles driven.

Not Available

1983-02-01T23:59:59.000Z

231

Household Energy Consumption and Expenditures 1993 -- Executive ...  

U.S. Energy Information Administration (EIA)

national level data on energy-related issues on households and energy expenditures in the residential sector.

232

1997 Housing Characteristics Tables Housing Unit Tables  

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

Percent of U.S. Households; 45 pages, 121 kb) Percent of U.S. Households; 45 pages, 121 kb) Contents Pages HC1-1b. Housing Unit Characteristics by Climate Zone, Percent of U.S. Households, 1997 4 HC1-2b. Housing Unit Characteristics by Year of Construction, Percent of U.S. Households, 1997 4 HC1-3b. Housing Unit Characteristics by Household Income, Percent of U.S. Households, 1997 4 HC1-4b. Housing Unit Characteristics by Type of Housing Unit, Percent of U.S. Households, 1997 3 HC1-5b. Housing Unit Characteristics by Type of Owner-Occupied Housing Unit, Percent of U.S. Households, 1997 3 HC1-6b. Housing Unit Characteristics by Type of Rented Housing Unit, Percent of U.S. Households, 1997 3 HC1-7b. Housing Unit Characteristics by Four Most Populated States, Percent of U.S. Households, 1997 4

233

Comparative analysis of energy data bases for household residential and transportation energy use  

SciTech Connect

Survey data bases covering household residential and transportation energy use were reviewed from the perspective of energy policy analysts and data base users. Twenty-three surveys, taken from 1972 to 1985, collected information on household energy consumption and expenditures, energy-using capital stock, and conservation activities. Ten of the surveys covered residential energy use only, including that for space heating and cooling, cooking, water heating, and appliances. Six surveys covered energy use only for household travel in personal vehicles. Seven surveys included data on both of these household energy sectors. Complete energy use data for a household in one year can be estimated only for 1983, using two surveys (one residential and one transportation) taken in the same households. The last nine surveys of the 23 were recent (1983--1985). Review of those nine was based on published materials only. The large-scale surveys generally had less-comprehensive data, while the comprehensive surveys were based on small samples. The surveys were timely and useful for analyzing four types of energy policies: economic regulation, environmental regulation, federal energy production, and direct regulation of energy consumption or production. Future surveys of energy use, such as those of residential energy consumption, should try to link their energy-use questions to large surveys, such as the American Housing Survey, to allow more accurate analysis of comparative impacts of energy policies among population categories of interest (e.g., minority/majority, metropolitan/nonmetropolitan area, census regions, and income class). 78 refs., 9 figs., 29 tabs.

Teotia, A.; Klein, Y.; LaBelle, S.

1988-11-01T23:59:59.000Z

234

" Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1"  

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

3 Household Characteristics by Household Income, 2005" 3 Household Characteristics by Household Income, 2005" " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ,"Housing Units (millions)" ,,"Less than $20,000","$20,000 to $39,999","$40,000 to $59,999","$60,000 to $79,999","$80,000 or More" "Household Characteristics" "Total",111.1,26.7,28.8,20.6,13.1,22,16.6,38.6 "Household Size" "1 Person",30,13.5,8.5,4.3,2,1.8,5.9,13.1 "2 Persons",34.8,6,8.8,7.3,4.4,8.4,3.5,8.4 "3 Persons",18.4,3.1,4.7,3.4,2.5,4.6,2,5.8 "4 Persons",15.9,2.2,3.5,3.3,2.7,4.3,2.2,5.1

235

DRAFT-- DO NOT CITE Subsidized Housing, Emergency Shelters, and Homelessness: An Empirical Investigation Using Data from the 1990 Census  

E-Print Network (OSTI)

This paper uses the S-Night counts of persons in homeless shelters and living on the streets from the 1990 Decennial census to study the causes of variation in rates of homelessness across metropolitan areas. The effects of several policies are explored. Specifically, we estimate the importance of emergency homeless shelters and federally subsidized housing as solutions to the problem of homelessness. The results suggest that the expansion of homeless shelters has led to an increase in the total number of homeless persons. Additional shelters induce some households to leave the worst traditional housing situations. We find no evidence in support of the notion that increasing the number of federally subsidized units would decrease the number of homeless. However, our estimates suggest that a city can lower the rate of homelessness by targeting subsidized housing toward the very poor. Considerable debate exists over which policies are the most successful at reducing the number of homeless. This study uses data from the 1990 decennial census to estimate the effectiveness of, among other things, the expansion of homeless shelters and the availability and targeting of subsidized housing. The results suggest that the introduction of emergency shelters for the homeless has led to an increase in the number of homeless in the U.S. No evidence is found to support the notion that a general increase in the number of subsidized units will decrease the total number of homeless. However, estimates suggest that federally subsidized housing targeted toward the poor reduces the rate of homelessness.

Dirk W. Early; Edgar O. Olsen

2000-01-01T23:59:59.000Z

236

Table 33. Coal Carbonized at Coke Plants by Census Division  

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

Coal Carbonized at Coke Plants by Census Division Coal Carbonized at Coke Plants by Census Division (thousand short tons) U.S. Energy Information Administration | Quarterly Coal Report, April - June 2013 Table 33. Coal Carbonized at Coke Plants by Census Division (thousand short tons) U.S. Energy Information Administration | Quarterly Coal Report, April - June 2013 Year to Date Census Division April - June 2013 January - March 2013 April - June 2012 2013 2012 Percent Change Middle Atlantic w w w w w w East North Central 3,051 2,997 3,092 6,048 6,156 -1.8 South Atlantic w w w w w w East South Central w w w w w w U.S. Total 5,471 5,280 5,296 10,751 10,579 1.6 w = Data withheld to avoid disclosure. Note: Total may not equal sum of components because of independent rounding. Source: U.S. Energy Information Administration (EIA), Form EIA-5, 'Quarterly Coal Consumption and Quality Report - Coke Plants

237

Table 23. Coal Receipts at Coke Plants by Census Division  

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

Receipts at Coke Plants by Census Division Receipts at Coke Plants by Census Division (thousand short tons) U.S. Energy Information Administration | Quarterly Coal Report, April - June 2013 Table 23. Coal Receipts at Coke Plants by Census Division (thousand short tons) U.S. Energy Information Administration | Quarterly Coal Report, April - June 2013 Year to Date Census Division April - June 2013 January - March 2013 April - June 2012 2013 2012 Percent Change Middle Atlantic w w w w w w East North Central 3,189 2,679 3,225 5,867 5,993 -2.1 South Atlantic w w w w w w East South Central w w w w w w U.S. Total 5,770 4,962 5,370 10,732 10,440 2.8 w = Data withheld to avoid disclosure. Note: Total may not equal sum of components because of independent rounding. Source: U.S. Energy Information Administration (EIA), Form EIA-5, 'Quarterly Coal Consumption and Quality Report - Coke Plants

238

"Table HC10.13 Lighting Usage Indicators by U.S. Census Region...  

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

3 Lighting Usage Indicators by U.S. Census Region, 2005" " Million U.S. Housing Units" ,"Housing Units (millions)","U.S. Census Region" "Lighting Usage Indicators",,"Northeast","Mi...

239

Image Gallery from the Census of Marine Life  

DOE Data Explorer (OSTI)

The Census has evolved a strategy of 14 field projects to touch the major habitats and groups of species in the global ocean. Eleven field projects address habitats, such as seamounts or the Arctic Ocean. Three field projects look globally at animals that either traverse the seas or appear globally distributed: the top predators such as tuna and the plankton and the microbes. The projects employ a mix of technologies. These include acoustics or sound, optics or cameras, tags placed on individual animals that store or report data, and genetics, as well as some actual capture of animals. The Census of Marine Life provides a much clearer picture of what lives below the surface around the globe. Several reasons make such a report timely, indeed urgent. Better information is needed to fashion the management that will sustain fisheries, conserve diversity, reverse losses of habitat, reduce impacts of pollution, and respond to global climate change. Hence, there are biological, economic, philosophical and political reasons to push for greater exploration and understanding of the ocean and its inhabitants. Indeed, the United Nations Convention on Biological Diversity requires signatories to collect information on living resources, but, as yet, no nation has a complete baseline of such information. The Census of Marine Life's global network of researchers will help to fill this knowledge gap, providing critical information to help guide decisions on how to manage global marine resources for the future. [This information was copied from http://www.coml.org/about, then edited and shortened.] The Image Gallery from the Census provides close-up photography of species, many never before seen. In addition, the maps and visualizations produced at Duke University's Marine Geospatial Ecology Lab provide striking visual overviews of the Census projects and activities as a whole.

None

240

Energy and household expenditure patterns  

Science Conference Proceedings (OSTI)

Since households account, either directly or indirectly, for two-thirds of the energy consumed in the US, changes in household activities will affect energy use. Expected changes in prices, personal income, and family spending over the next 20 years are looked at as well as the implications for energy consumption. The analysis shows that direct energy purchases will break with past trends, dropping from 2.6% to 0.2% annual growth for the rest of the century. Growth in spending on energy-using goods is also likely to slow down. The year 2000 will see a marked decrease in the growth of national energy consumption. 58 references, 3 figures, 35 tables.

Lareau, T.J.; Darmstadter, J.

1983-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "household characteristics census" 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

Inconsistent pathways of household waste  

Science Conference Proceedings (OSTI)

The aim of this study was to provide policy-makers and waste management planners with information about how recycling programs affect the quantities of specific materials recycled and disposed of. Two questions were addressed: which factors influence household waste generation and pathways? and how reliable are official waste data? Household waste flows were studied in 35 Swedish municipalities, and a wide variation in the amount of waste per capita was observed. When evaluating the effect of different waste collection policies, it was found to be important to identify site-specific factors influencing waste generation. Eleven municipal variables were investigated in an attempt to explain the variation. The amount of household waste per resident was higher in populous municipalities and when net commuting was positive. Property-close collection of dry recyclables led to increased delivery of sorted metal, plastic and paper packaging. No difference was seen in the amount of separated recyclables per capita when weight-based billing for the collection of residual waste was applied, but the amount of residual waste was lower. Sixteen sources of error in official waste statistics were identified and the results of the study emphasize the importance of reliable waste generation and composition data to underpin waste management policies.

Dahlen, Lisa [Division of Waste Science and Technology, Lulea University of Technology, SE, 971 87 Lulea (Sweden)], E-mail: lisa.dahlen@ltu.se; Aberg, Helena [Department of Food, Health and Environment, University of Gothenburg, P.O. Box 12204, SE, 402 42 Gothenburg (Sweden); Lagerkvist, Anders [Division of Waste Science and Technology, Lulea University of Technology, SE, 971 87 Lulea (Sweden); Berg, Per E.O. [HB Anttilator, Stagnellsgatan 3, SE, 652 23, Karlstad (Sweden)

2009-06-15T23:59:59.000Z

242

Residential energy use and conservation actions: analysis of disaggregate household data  

Science Conference Proceedings (OSTI)

The Energy Information Administration recently published data they collected from the National Interim Energy Consumption Survey (NIECS). NIECS includes detailed information on 4081 individual households: demographic characteristics, energy-related features of the structure, heating equipment and appliances therein, recent conservation actions taken by the household, and fuel consumption and cost for the April 1978 to March 1979 one-year period. This data set provides a new and valuable resource for analysis. The NIECS data on household energy consumption - total energy use, electricity use, and use of the primary space heating fuel, are summarized and analyzed. The regression equations constructed explain roughly half the variation in energy use among households. These equations contain ten or fewer independent variables, the most important of which are fuel price, year house was built, floor area, and heating degree days. Regression equations were developed that estimate the energy saving achieved by each household based on their recent retrofit actions. These equations predict 20 to 40% of the variation among households. Total annual energy use is the most important determinant of retrofit energy saving; other significant variables include age of household head, household income, year house was built, housing tenure, and proxies for the cost of heating and air conditioning the house.

Hirst, E.; Goeltz, R.; Carney, J.

1981-03-01T23:59:59.000Z

243

Bethel Census Area, Alaska: Energy Resources | Open Energy Information  

Open Energy Info (EERE)

Census Area, Alaska: Energy Resources Census Area, Alaska: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 61.093446°, -160.8640774° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":61.093446,"lon":-160.8640774,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

244

Yukon-Koyukuk Census Area, Alaska: Energy Resources | Open Energy  

Open Energy Info (EERE)

Yukon-Koyukuk Census Area, Alaska: Energy Resources Yukon-Koyukuk Census Area, Alaska: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 65.8443667°, -153.4302993° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":65.8443667,"lon":-153.4302993,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

245

Wade Hampton Census Area, Alaska: Energy Resources | Open Energy  

Open Energy Info (EERE)

Wade Hampton Census Area, Alaska: Energy Resources Wade Hampton Census Area, Alaska: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 62.1458336°, -162.8919191° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":62.1458336,"lon":-162.8919191,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

246

Video Gallery from the Census of Marine Life  

DOE Data Explorer (OSTI)

Two video galleries provide different views of the Census effort. One contains videos of activities from the various individual projects and informational, overview videos. The other presents interviews with researchers, speeches and presentations, and clips from artistic films. The Census of Marine Life is a global network of researchers in more than 80 nations engaged in a 10-year scientific initiative to assess and explain the diversity, distribution, and abundance of life in the oceans. The Census has evolved a strategy of field projects to touch the major habitats and groups of species in the global ocean. Some address habitats, such as seamounts or the Arctic Ocean. Others look globally at animals that either traverse the seas or appear globally distributed: the top predators such as tuna and the plankton and the microbes. The projects employ a mix of technologies. These include acoustics or sound, optics or cameras, tags placed on individual animals that store or report data, and genetics, as well as some actual capture of animals. [This information was copied from http://www.coml.org/about, then edited and shortened.

247

Home > Households, Buildings & Industry > Energy Efficiency Page ...  

U.S. Energy Information Administration (EIA)

Home > Households, Buildings & Industry > Energy Efficiency Page > Energy Intensities >Table 7a Glossary U.S. Residential Housing Primary Page Last Revised: July 2009

248

Nationwide Survey on Household Energy Use  

U.S. Energy Information Administration (EIA)

4 ~ Apartment in house or building divided into 2, 3, or 4 apartments ... of your family (living in your household). Include income from all sources--before taxes

249

Alston S. Householder Fellowship | Careers | ORNL  

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

in Scientific Computing honors Dr. Alston S. Householder, founding Director of the Mathematics Division (now Computer Science and Mathematics Division) at the Oak Ridge National...

250

Household Vehicles Energy Consumption 1994 - PDF Tables  

U.S. Energy Information Administration (EIA)

Table 1 U.S. Number of Vehicles, Vehicle Miles, Motor Fuel Consumption and Expenditures, 1994 Table 2 U.S. per Household Vehicle Miles Traveled, Vehicle Fuel ...

251

Home > Households, Buildings & Industry > Energy Efficiency ...  

U.S. Energy Information Administration (EIA)

Glossary Home > Households, Buildings & Industry > Energy Efficiency > Residential Buildings Energy Intensities > Table 4 Total Square Feet of U.S. Housing Units

252

Home > Households, Buildings & Industry > Energy Efficiency Page ...  

U.S. Energy Information Administration (EIA)

Home > Households, Buildings & Industry > Energy Efficiency Page > Energy Intensities > Table 5c Glossary U.S. Residential Housing Site Page Last Revised: July 2009

253

Residential Energy Usage by Origin of Householder  

U.S. Energy Information Administration (EIA)

Home > Energy Users > Residential Home Page > Energy Usage by Origin of Householder. Consumption and Expenditures. NOTE: To View and/or Print PDF's ...

254

Home > Households, Buildings & Industry > Energy Efficiency Page ...  

U.S. Energy Information Administration (EIA)

Home > Households, Buildings & Industry > Energy Efficiency Page > Energy Intensities >Table 7b Glossary U.S. Residential Housing Primary Energy Intensity

255

Home > Households, Buildings & Industry > Energy Efficiency Page ...  

U.S. Energy Information Administration (EIA)

Home > Households, Buildings & Industry > Energy Efficiency Page > Energy Intensities > Table 8b Glossary U.S. Residential Buildings Primary Energy Intensity

256

Black Same-Sex Couples in California: Data from Census 2000  

E-Print Network (OSTI)

Households included in black households had a householderwho identified as an black. Seventy-eight percentsame-sex couples that include an black had an black as the

Gates, Gary; Sears, Brad

2005-01-01T23:59:59.000Z

257

Electricity Prices for Households - EIA  

Gasoline and Diesel Fuel Update (EIA)

Households for Selected Countries1 Households for Selected Countries1 (U.S. Dollars per Kilowatthour) Country 2001 2002 2003 2004 2005 2006 2007 2008 2009 Argentina NA NA NA NA NA NA 0.023 NA NA Australia 0.091 0.092 0.094 0.098 NA NA NA NA NA Austria 0.144 0.154 0.152 0.163 0.158 0.158 0.178 0.201 NA Barbados NA NA NA NA NA NA NA NA NA Belgium NA NA NA NA NA NA NA NA NA Bolivia NA NA NA NA NA NA NA NA NA Brazil NA NA NA NA NA NA 0.145 0.171 NA Canada 0.067 0.069 0.070 0.071 0.076 0.078 NA NA NA Chile NA NA NA NA NA NA 0.140 0.195 NA China NA NA NA NA NA NA NA NA NA Chinese Taipei (Taiwan) 0.075 0.071 0.074 0.076 0.079 0.079 0.080 0.086 NA Colombia NA NA NA NA NA NA 0.111 0.135 NA

258

homeoffice_household2001.pdf  

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

2a. Home Office Equipment by Year of Construction, 2a. Home Office Equipment by Year of Construction, Million U.S. Households, 2001 Home Office Equipment RSE Column Factor: Total Year of Construction RSE Row Factors 1990 to 2001 1 1980 to 1989 1970 to 1979 1960 to 1969 1950 to 1959 1949 or Before 0.4 1.4 1.1 1.1 1.2 1.2 1.0 Total ............................................... 107.0 15.5 18.2 18.8 13.8 14.2 26.6 4.2 Households Using Office Equipment .......................... 96.2 14.9 16.7 17.0 12.2 13.0 22.4 4.4 Personal Computers 2 ................... 60.0 11.0 11.6 10.3 7.2 7.8 12.0 5.3 Number of Desktop PCs 1 .................................................. 45.1 8.0 9.0 7.7 5.3 6.1 9.1 5.8 2 or more .................................... 9.1 1.8 1.6 2.0 1.1 1.0 1.6 11.8 Number of Laptop PCs 1 ..................................................

259

homeoffice_household2001.pdf  

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

a. Home Office Equipment by Climate Zone, a. Home Office Equipment by Climate Zone, Million U.S. Households, 2001 Home Office Equipment RSE Column Factor: Total Climate Zone 1 RSE Row Factors Fewer than 2,000 CDD and -- 2,000 CDD or More and Fewer than 4,000 HDD More than 7,000 HDD 5,500 to 7,000 HDD 4,000 to 5,499 HDD Fewer than 4,000 HDD 0.4 1.9 1.1 1.2 1.1 1.0 Total ............................................... 107.0 9.2 28.6 24.0 21.0 24.1 7.9 Households Using Office Equipment .......................... 96.2 8.4 26.2 21.1 19.0 21.5 7.8 Personal Computers 2 ................... 60.0 5.7 16.7 13.1 12.1 12.6 7.4 Number of Desktop PCs 1 .................................................. 45.1 4.2 12.8 9.6 8.8 9.6 7.8 2 or more .................................... 9.1 0.8 2.4 2.3 2.0 1.7 12.1 Number of Laptop PCs 1 ..................................................

260

Household Vehicles Energy Use: Latest Data & Trends  

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

This page left blank. This page left blank. E N E R G Y O V E RV I E W ENERGY INFORMATION ADMINISTRATION/HOUSEHOLD VEHICLES ENERGY USE: LATEST DATA & TRENDS ENERGY OVERVIEW E N E R G Y O V E RV I E W INTRODUCTION Author's Note Estimates of gallons of fuel consumed, type of fuel used, price paid for fuel, and fuel economy are based on data imputed by EIA, using vehicle characteristics and vehicle-miles traveled data collected during the interview process for the 2001 National Household Travel Survey (NHTS). Rather than obtaining that information directly from fuel purchase diaries, EIA exploited its experience and expertise with modeling techniques for transportation studies, filling missing and uncollected data with information reported to other federal agencies, as described in Appendices

Note: This page contains sample records for the topic "household characteristics census" 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

RECS data show decreased energy consumption per household  

Reports and Publications (EIA)

Total United States energy consumption in homes has remained relatively stable for many years as increased energy efficiency has offset the increase in the number and average size of housing units, according to the newly released data from the Residential Energy Consumption Survey (RECS). The average household consumed 90 million British thermal units (Btu) in 2009 based on RECS. This continues the downward trend in average residential energy consumption of the last 30 years. Despite increases in the number and the average size of homes plus increased use of electronics, improvements in efficiency for space heating, air conditioning, and major appliances have all led to decreased consumption per household. Newer homes also tend to feature better insulation and other characteristics, such as double-pane windows, that improve the building envelope.

2012-06-06T23:59:59.000Z

262

Household Vehicles Energy Use: Latest Data & Trends  

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

E E N E R G Y O V E RV I E W ENERGY INFORMATION ADMINISTRATION/HOUSEHOLD VEHICLES ENERGY USE: LATEST DATA & TRENDS ENERGY OVERVIEW E N E R G Y O V E RV I E W INTRODUCTION Author's Note Estimates of gallons of fuel consumed, type of fuel used, price paid for fuel, and fuel economy are based on data imputed by EIA, using vehicle characteristics and vehicle-miles traveled data collected during the interview process for the 2001 National Household Travel Survey (NHTS). Rather than obtaining that information directly from fuel purchase diaries, EIA exploited its experience and expertise with modeling techniques for transportation studies, filling missing and uncollected data with information reported to other federal agencies, as described in Appendices B and C of this report.

263

Table HC1-8a. Housing Unit Characteristics by Urban/Rural Location ...  

U.S. Energy Information Administration (EIA)

Table HC1-8a. Housing Unit Characteristics by Urban/Rural Location, Million U.S. Households, 2001 Housing Unit Characteristics RSE Column Factor:

264

Table HC1-1a. Housing Unit Characteristics by Climate Zone ...  

U.S. Energy Information Administration (EIA)

Table HC1-1a. Housing Unit Characteristics by Climate Zone, Million U.S. Households, 2001 Housing Unit Characteristics RSE Column Factor: Total Climate Zone1

265

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

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

6. Total Expenditures for Purchased Energy Sources by Census Region," 6. Total Expenditures for Purchased Energy Sources by Census Region," " Census Division, Industry Group, and Selected Industries, 1994" " (Estimates in Million Dollars)" ,,,,,,,,,,,"RSE" "SIC"," "," "," ","Residual","Distillate ","Natural"," "," ","Coke"," ","Row" "Code(a)","Industry Group and Industry","Total","Electricity","Fuel Oil","Fuel Oil(b)","Gas(c)","LPG","Coal","and Breeze","Other(d)","Factors" ,,"Total United States"

266

"Table A27. Components of Onsite Electricity Generation by Census Region,"  

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

Components of Onsite Electricity Generation by Census Region," Components of Onsite Electricity Generation by Census Region," " Census Division, Industry Group, and Selected Industries, 1994" " (Estimates in Million Kilowatthours)" ," "," "," "," " " "," "," "," ",," ","RSE" "SIC"," "," "," ",," ","Row" "Code(a)","Industry Group and Industry","Total","Cogeneration","Renewables","Other(b)","Factors" ,,"Total United States" ,"RSE Column Factors:",0.8,0.8,1.6,1 , 20,"Food and Kindred Products",6962,6754,90,118,11.2

267

Probit Model Estimation Revisited: Trinomial Models of Household Car Ownership  

E-Print Network (OSTI)

Household Ownership of Car Davidon, W. C. (1959) VariableStudy Report 9: Models of Car Ownership and License Holding.Trinomial Models of Household Car Ownership. Transportation

Bunch, David S.; Kitamura, Ryuichi

1991-01-01T23:59:59.000Z

268

Modeling patterns of hot water use in households  

E-Print Network (OSTI)

7 No Dishwashers . . . . . . . .to households without dishwashers. no_cw is only applied towasher; the absence of a dishwasher; a household consisting

Lutz, James D.; Liu, Xiaomin; McMahon, James E.; Dunham, Camilla; Shown, Leslie J.; McCure, Quandra T.

1996-01-01T23:59:59.000Z

269

ASSESSMENT OF HOUSEHOLD CARBON FOOTPRINT REDUCTION POTENTIALS  

SciTech Connect

The term ?household carbon footprint? refers to the total annual carbon emissions associated with household consumption of energy, goods, and services. In this project, Lawrence Berkeley National Laboratory developed a carbon footprint modeling framework that characterizes the key underlying technologies and processes that contribute to household carbon footprints in California and the United States. The approach breaks down the carbon footprint by 35 different household fuel end uses and 32 different supply chain fuel end uses. This level of end use detail allows energy and policy analysts to better understand the underlying technologies and processes contributing to the carbon footprint of California households. The modeling framework was applied to estimate the annual home energy and supply chain carbon footprints of a prototypical California household. A preliminary assessment of parameter uncertainty associated with key model input data was also conducted. To illustrate the policy-relevance of this modeling framework, a case study was conducted that analyzed the achievable carbon footprint reductions associated with the adoption of energy efficient household and supply chain technologies.

Kramer, Klaas Jan; Homan, Greg; Brown, Rich; Worrell, Ernst; Masanet, Eric

2009-04-15T23:59:59.000Z

270

Characterizing Walk Trips in communities by Using Data from 2009 National Household Travel Survey, American Community Survey, and Other Sources  

SciTech Connect

Non-motorized travel (i.e. walking and bicycling) are of increasing interest to the transportation profession, especially in context with energy consumption, reducing vehicular congestion, urban development patterns, and promotion of healthier life styles. This research project aimed to identify factors impacting the amount of travel for both walk and bike trips at the Census block group or tract level, using several public and private data sources. The key survey of travel behavior is the 2009 National Household Travel Survey (NHTS) which had over 87,000 walk trips for persons 16 and over, and over 6000 bike trips for persons 16 and over. The NHTS, in conjunction with the Census Bureau s American Community Survey, street density measures using Census Bureau TIGER, WalkScore , Nielsen Claritas employment estimates, and several other sources were used for this study. Stepwise Logistic Regression modeling techniques as well as Discriminant Analysis were applied using the integrated data set. While the models performed reasonably well for walk trips, travel by bike was abandoned due to sparseness of data. This paper discusses data sources utilized and modeling processes conducted under this study. It also presents a summary of findings and addresses data challenges and lesson-learned from this research effort.

Hwang, Ho-Ling [ORNL; Reuscher, Tim [Macrosys; Wilson, Daniel W [ORNL; Murakami, Elaine [FHWA USDOT

2013-01-01T23:59:59.000Z

271

Did Household Consumption Become More Volatile?  

E-Print Network (OSTI)

I show that after accounting for predictable variation arising from movements in real interest rates, preferences, income shocks, liquidity constraints and measurement errors, volatility of household consumption in the US increased between 1970 and 2004. For households headed by nonwhite and/or poorly educated individuals, this rise was significantly larger. This stands in sharp contrast with the dramatic fall in instability of the aggregate U.S. economy over the same period. Thus, while aggregate shocks affecting households fell over time, idiosyncratic shocks increased. This finding may lead to significant welfare implications.

Olga Gorbachev

2009-01-01T23:59:59.000Z

272

Table HC1-1a. Housing Unit Characteristics by Climate Zone,  

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

a. Housing Unit Characteristics by Climate Zone, a. Housing Unit Characteristics by Climate Zone, Million U.S. Households, 2001 Housing Unit Characteristics RSE Column Factor: Total Climate Zone 1 RSE Row Factors Fewer than 2,000 CDD and -- 2,000 CDD or More and Fewer than 4,000 HDD More than 7,000 HDD 5,500 to 7,000 HDD 4,000 to 5,499 HDD Fewer than 4,000 HDD 0.4 1.8 1.0 1.1 1.2 1.1 Total ............................................... 107.0 9.2 28.6 24.0 21.0 24.1 8.0 Census Region and Division Northeast ...................................... 20.3 1.9 10.0 8.4 Q Q 6.8 New England .............................. 5.4 1.4 4.0 Q Q Q 18.4 Middle Atlantic ............................ 14.8 0.5 6.0 8.4 Q Q 4.6 Midwest ......................................... 24.5 5.4 14.8 4.3 Q Q 19.0 East North Central ...................... 17.1

273

Table HC1-2a. Housing Unit Characteristics by Year of Construction,  

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

2a. Housing Unit Characteristics by Year of Construction, 2a. Housing Unit Characteristics by Year of Construction, Million U.S. Households, 2001 Housing Unit Characteristics RSE Column Factor: Total Year of Construction RSE Row Factors 1990 to 2001 1 1980 to 1989 1970 to 1979 1960 to 1969 1950 to 1959 1949 or Before 0.5 1.6 1.2 1.0 1.1 1.1 0.8 Total ............................................... 107.0 15.5 18.2 18.8 13.8 14.2 26.6 4.3 Census Region and Division Northeast ...................................... 20.3 1.5 2.4 2.1 2.8 3.0 8.5 8.8 New England .............................. 5.4 0.4 0.7 0.4 0.8 0.9 2.3 11.3 Middle Atlantic ............................ 14.8 1.1 1.7 1.7 2.0 2.2 6.2 11.2 Midwest ......................................... 24.5 2.8 3.7 3.6 2.9 3.5 8.1 10.2 East North Central ...................... 17.1 2.0 2.5 2.5 2.0 2.6 5.5 11.9

274

Table HC1-8a. Housing Unit Characteristics by Urban/Rural Location,  

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

8a. Housing Unit Characteristics by Urban/Rural Location, 8a. Housing Unit Characteristics by Urban/Rural Location, Million U.S. Households, 2001 Housing Unit Characteristics RSE Column Factor: Total Urban/Rural Location 1 RSE Row Factors City Town Suburbs Rural 0.5 0.8 1.3 1.3 1.4 Total .............................................................. 107.0 49.9 18.0 21.2 17.9 4.2 Census Region and Division Northeast ..................................................... 20.3 7.7 4.5 4.7 3.4 7.4 New England ............................................. 5.4 2.1 1.6 0.7 1.1 13.4 Middle Atlantic ........................................... 14.8 5.6 2.9 4.0 2.3 8.5 Midwest ....................................................... 24.5 11.1 4.9 4.8 3.7 10.1 East North Central ..................................... 17.1 8.3 3.0 3.4 2.5

275

Microsoft Word - Household Energy Use CA  

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

0 20 40 60 80 100 US PAC CA Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US PAC CA Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 2,000 4,000 6,000 8,000 10,000 12,000 US PAC CA Site Consumption kilowatthours $0 $250 $500 $750 $1,000 $1,250 $1,500 US PAC CA Expenditures dollars ELECTRICITY ONLY average per household ď‚· California households use 62 million Btu of energy per home, 31% less than the U.S. average. The lower than average site consumption results in households spending 30% less for energy than the U.S. average. ď‚· Average site electricity consumption in California homes is among the lowest in the nation, as the mild climate in much of the state leads to less reliance on

276

Microsoft Word - Household Energy Use CA  

Gasoline and Diesel Fuel Update (EIA)

0 20 40 60 80 100 US PAC CA Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US PAC CA Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 2,000 4,000 6,000 8,000 10,000 12,000 US PAC CA Site Consumption kilowatthours $0 $250 $500 $750 $1,000 $1,250 $1,500 US PAC CA Expenditures dollars ELECTRICITY ONLY average per household ď‚· California households use 62 million Btu of energy per home, 31% less than the U.S. average. The lower than average site consumption results in households spending 30% less for energy than the U.S. average. ď‚· Average site electricity consumption in California homes is among the lowest in the nation, as the mild climate in much of the state leads to less reliance on

277

U.S. Household Electricity Report  

Reports and Publications (EIA)

Brief analysis reports on the amount of electricity consumed annually by U.S. households for each of several end uses, including space heating and cooling, water heating, lighting, and the operation of more than two dozen appliances.

Barbara Fichman

2005-07-14T23:59:59.000Z

278

Household energy consumption and expenditures 1993  

Science Conference Proceedings (OSTI)

This presents information about household end-use consumption of energy and expenditures for that energy. These data were collected in the 1993 Residential Energy Consumption Survey; more than 7,000 households were surveyed for information on their housing units, energy consumption and expenditures, stock of energy-consuming appliances, and energy-related behavior. The information represents all households nationwide (97 million). Key findings: National residential energy consumption was 10.0 quadrillion Btu in 1993, a 9% increase over 1990. Weather has a significant effect on energy consumption. Consumption of electricity for appliances is increasing. Houses that use electricity for space heating have lower overall energy expenditures than households that heat with other fuels. RECS collected data for the 4 most populous states: CA, FL, NY, TX.

NONE

1995-10-05T23:59:59.000Z

279

Do Disaster Expectations Explain Household Portfolios?  

E-Print Network (OSTI)

use the American Consumer Expenditure Survey (CEX) for consumption ex- penditure information. The data covers the period between 1983 and 2004. The expenditure information is recorded quarterly with approximately 5000 households in each wave. Every...

Alan, Sule

280

Household gasoline demand in the United States  

E-Print Network (OSTI)

Continuing rapid growth in U.S. gasoline consumption threatens to exacerbate environmental and congestion problems. We use flexible semiparametric and nonparametric methods to guide analysis of household gasoline consumption, ...

Schmalensee, Richard

1995-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "household characteristics census" 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

"Table A17. Components of Onsite Electricity Generation by Census Region,"  

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

7. Components of Onsite Electricity Generation by Census Region," 7. Components of Onsite Electricity Generation by Census Region," " Industry Group, and Selected Industries, 1991" " (Estimates in Million Kilowatthours)" " "," "," "," "," "," "," "," " " "," "," "," "," "," ","RSE" "SIC"," "," "," "," "," ","Row" "Code(a)","Industry Groups and Industry","Total","Cogeneration","Renewables","Other(b)","Factors" ,,"Total United States" ,"RSE Column Factors:",0.8,0.8,1.4,1.2

282

IPUMS-international statistical disclosure controls: 159 census microdata samples in dissemination, 100+ in preparation  

Science Conference Proceedings (OSTI)

In the last decade, a revolution has occurred in access to census microdata for social and behavioral research. More than 325 million person records (55 countries, 159 samples) representing two-thirds of the world's population are now readily available ... Keywords: IPUMS-international, census microdata samples, data dissemination, data privacy

Robert McCaa; Steven Ruggles; Matt Sobek

2010-09-01T23:59:59.000Z

283

Ventilation Behavior and Household Characteristics in New California Houses  

E-Print Network (OSTI)

region were fr om climate zones 6, 7, and 9. Figure 7 showssample. (The other climate zones ha d to o few samples totion hour s. F our climate zones with very few houses (le ss

Price, Phillip N.; Sherman, Max H.

2006-01-01T23:59:59.000Z

284

Ventilation Behavior and Household Characteristics in New California Houses  

E-Print Network (OSTI)

outdoor noise, home security, privacy, convenience, localand security concerns were very strong , as people did not w ant to leave windows open when they were not home and

Price, Phillip N.; Sherman, Max H.

2006-01-01T23:59:59.000Z

285

Ventilation Behavior and Household Characteristics in New California Houses  

E-Print Network (OSTI)

wood fireplace with tight doors, Fireplace without tight-fitting do ors, Freestanding combustioncombustion appliances, cooking, heating, sources of organic chemicals (VOCs) such as pressed woodwood fireplace with tight-fitting doors o Other Fireplace without tight- fitting doors o Freestanding combustion

Price, Phillip N.; Sherman, Max H.

2006-01-01T23:59:59.000Z

286

Ventilation Behavior and Household Characteristics in New California Houses  

E-Print Network (OSTI)

Pump Heating Gas Wall Heater Electric Wall Heater Wood stovepump Heating, Gas Wall Heater, Electric Wall He ater, Woodheating, sources of organic chemicals (VOCs) such as pressed wood

Price, Phillip N.; Sherman, Max H.

2006-01-01T23:59:59.000Z

287

Residential energy consumption and expenditure patterns of low-income households in the United States  

SciTech Connect

The principal objective of this study is to compare poor and non-poor households with respect to energy consumption and expenditures, housing characteristics, and energy-related behavior. We based our study on an analysis of a national data base created by the US Department of Energy, the 1982-1983 Residential Energy Consumption Survey (RECS). RECS includes detailed information on individual households: demographic characteristics, energy-related features of the structure, heating equipment and appliances, recent conservation actions taken by the household, and fuel consumption and costs for April 1982-March 1983. We found a number of statistically significant (at the 0.05 level) differences between the two income groups in terms of demographics, heating/cooling/water heating systems, appliance saturation, the thermal integrity of their home, energy conservation behavior, energy consumption, energy expenditures, and the percentage of income spent on energy costs. For example, the non-poor used 22% more energy and paid 25% more money on utilities than the poor; however, the poor spent 20% more energy per square foot than the non-poor and spent about 25% of their income on energy expenditures, compared to 7% for the non-poor. These differences suggest different approaches that might be taken for targeting energy conservation programs to low-income households. Since the poor's ''energy burden'' is large, informational, technical, and financial assistance to low-income households remains an urgent, national priority. 13 refs., 26 tabs.

Vine, E.L.; Reyes, I.

1987-09-01T23:59:59.000Z

288

Table 2. Number of U.S. Housing Units by Census Region and ...  

U.S. Energy Information Administration (EIA)

Home > Households, Buildings & Industry > Energy Efficiency > Residential Buildings Energy Intensities > Table 2. Number of U.S. ...

289

Vehicle Technologies Office: Fact #451: January 8, 2007 Household Vehicle  

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

1: January 8, 1: January 8, 2007 Household Vehicle Trips to someone by E-mail Share Vehicle Technologies Office: Fact #451: January 8, 2007 Household Vehicle Trips on Facebook Tweet about Vehicle Technologies Office: Fact #451: January 8, 2007 Household Vehicle Trips on Twitter Bookmark Vehicle Technologies Office: Fact #451: January 8, 2007 Household Vehicle Trips on Google Bookmark Vehicle Technologies Office: Fact #451: January 8, 2007 Household Vehicle Trips on Delicious Rank Vehicle Technologies Office: Fact #451: January 8, 2007 Household Vehicle Trips on Digg Find More places to share Vehicle Technologies Office: Fact #451: January 8, 2007 Household Vehicle Trips on AddThis.com... Fact #451: January 8, 2007 Household Vehicle Trips In a day, the average household traveled 32.7 miles in 2001 (the latest

290

Vehicle Technologies Office: Fact #392: October 3, 2005 Household Vehicle  

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

2: October 3, 2: October 3, 2005 Household Vehicle Ownership to someone by E-mail Share Vehicle Technologies Office: Fact #392: October 3, 2005 Household Vehicle Ownership on Facebook Tweet about Vehicle Technologies Office: Fact #392: October 3, 2005 Household Vehicle Ownership on Twitter Bookmark Vehicle Technologies Office: Fact #392: October 3, 2005 Household Vehicle Ownership on Google Bookmark Vehicle Technologies Office: Fact #392: October 3, 2005 Household Vehicle Ownership on Delicious Rank Vehicle Technologies Office: Fact #392: October 3, 2005 Household Vehicle Ownership on Digg Find More places to share Vehicle Technologies Office: Fact #392: October 3, 2005 Household Vehicle Ownership on AddThis.com... Fact #392: October 3, 2005 Household Vehicle Ownership Household vehicle ownership has changed significantly over the last 40

291

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

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

Quantity of Purchased Energy Sources by Census Region," Quantity of Purchased Energy Sources by Census Region," " Census Division, Industry Group, and Selected Industries, 1994" " (Estimates in Btu or Physical Units)" ,,,,,,"Natural",,,"Coke" " "," ","Total","Electricity","Residual","Distillate","Gas(c)"," ","Coal","and Breeze"," ","RSE" "SIC"," ","(trillion","(million","Fuel Oil","Fuel Oil(b)","(billion","LPG","(1000","(1000","Other(d)","Row" "Code(a)","Industry Group and Industry","Btu)","kWh)","(1000 bbl)","(1000 bbl)","cu ft)","(1000 bbl)","short tons)","short tons)","(trillion Btu)","Factors"

292

Table HC1-5a. Housing Unit Characteristics by Type of Owner-Occupied Housing Unit,  

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

5a. Housing Unit Characteristics by Type of Owner-Occupied Housing Unit, 5a. Housing Unit Characteristics by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 Housing Unit Characteristics RSE Column Factor: Total Owner- Occupied Units Type of Owner-Occupied Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Homes Two to Four Units Five or More Units 0.4 0.4 1.8 2.1 1.4 Total ............................................... 72.7 63.2 2.1 1.8 5.7 6.7 Census Region and Division Northeast ...................................... 13.0 10.8 1.1 0.5 0.6 11.4 New England .............................. 3.5 3.1 0.2 Q 0.1 16.9 Middle Atlantic ............................ 9.5 7.7 0.9 0.4 0.4 13.4 Midwest ......................................... 17.5 16.0 0.3 Q 1.0 10.3 East North Central ......................

293

"Table HC11.13 Lighting Usage Indicators by Northeast Census Region, 2005"  

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

3 Lighting Usage Indicators by Northeast Census Region, 2005" 3 Lighting Usage Indicators by Northeast Census Region, 2005" " Million U.S. Housing Units" ,,"Northeast Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total Northeast" "Lighting Usage Indicators",,,"Middle Atlantic","New England" "Total U.S. Housing Units",111.1,20.6,15.1,5.5 "Indoor Lights Turned On During Summer" "Number of Lights Turned On" "Between 1 and 4 Hours per Day",91.8,16.8,12.2,4.6 "1.",28.6,5,3.5,1.5 "2.",29.5,6.2,4.8,1.4 "3.",14.7,2.5,1.7,0.8 "4.",9.3,1.5,1.1,0.4 "5 or More",9.7,1.6,1.1,0.5 "Energy-Efficient Bulbs Used",31.1,5.2,3.6,1.6

294

"Table HC13.13 Lighting Usage Indicators by South Census Region, 2005"  

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

3 Lighting Usage Indicators by South Census Region, 2005" 3 Lighting Usage Indicators by South Census Region, 2005" " Million U.S. Housing Units" ,,"South Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total South" "Lighting Usage Indicators",,,"South Atlantic","East South Central","West South Central" "Total U.S. Housing Units",111.1,40.7,21.7,6.9,12.1 "Indoor Lights Turned On During Summer" "Number of Lights Turned On" "Between 1 and 4 Hours per Day",91.8,33.8,17.5,6.1,10.3 "1.",28.6,11.2,6.5,1.5,3.2 "2.",29.5,10.5,5.4,2,3.1 "3.",14.7,5,2.1,1.2,1.7 "4.",9.3,3.4,1.5,0.8,1.2 "5 or More",9.7,3.7,1.9,0.6,1.2

295
296

Table 1.10 Cooling Degree-Days by Census Division, 1949-2011  

U.S. Energy Information Administration (EIA)

Table 1.10 Cooling Degree-Days by Census Division, 1949-2011: Year: New England: Middle Atlantic: East North Central: West North Central: South Atlantic: East South

297
298

"Table HC14.13 Lighting Usage Indicators by West Census Region, 2005"  

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

3 Lighting Usage Indicators by West Census Region, 2005" 3 Lighting Usage Indicators by West Census Region, 2005" " Million U.S. Housing Units" ,,"West Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total West" "Lighting Usage Indicators",,,"Mountain","Pacific" "Total U.S. Housing Units",111.1,24.2,7.6,16.6 "Indoor Lights Turned On During Summer" "Number of Lights Turned On" "Between 1 and 4 Hours per Day",91.8,19.5,6.1,13.4 "1.",28.6,6.1,1.7,4.4 "2.",29.5,6.3,1.8,4.5 "3.",14.7,3.1,1.1,2 "4.",9.3,1.9,0.6,1.3 "5 or More",9.7,2,0.8,1.2 "Energy-Efficient Bulbs Used",31.1,8.6,2.3,6.3 "1.",14.6,3.6,1,2.6

299

"Table A25. Average Prices of Selected Purchased Energy Sources by Census"  

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

. Average Prices of Selected Purchased Energy Sources by Census" . Average Prices of Selected Purchased Energy Sources by Census" " Region, Industry Group, and Selected Industries, 1991: Part 1" " (Estimates in Dollars per Physical Unit)" ,,,,," " " "," "," ","Residual","Distillate","Natural Gas(c)"," "," ","RSE" "SIC"," ","Electricity","Fuel Oil","Fuel Oil(b)","(1000","LPG","Coal","Row" "Code(a)","Industry Groups and Industry","(kWh)","(gallon)","(gallon)","cu ft)","(gallon)","(short ton)","Factors"

300

" Generation by Census Region, Industry Group, Selected Industries, Presence of"  

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

4. Total Inputs of Energy for Heat, Power, and Electricity" 4. Total Inputs of Energy for Heat, Power, and Electricity" " Generation by Census Region, Industry Group, Selected Industries, Presence of" " General Technologies, and Industry-Specific Technologies for Selected" " Industries, 1991" " (Estimates in Trillion Btu)" ,,," Census Region",,,,"RSE" "SIC","Industry Groups",," -------------------------------------------",,,,"Row" "Code(a)","and Industry","Total","Northeast","Midwest","South","West","Factors" ,"RSE Column Factors:",0.7,1.3,1,0.9,1.3

Note: This page contains sample records for the topic "household characteristics census" 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

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

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

6. Components of Total Electricity Demand by Census Region, Industry" 6. Components of Total Electricity Demand by Census Region, Industry" " Group, and Selected Industries, 1991" " (Estimates in Million Kilowatthours)" " "," "," "," "," "," "," "," " " "," "," "," "," ","Sales and/or"," ","RSE" "SIC"," "," ","Transfers","Total Onsite","Transfers","Net Demand for","Row" "Code(a)","Industry Groups and Industry","Purchases","In(b)","Generation(c)","Offsite","Electricity(d)","Factors"

302

Vehicle Technologies Office: Fact #455: February 5, 2007 Household Vehicle  

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

5: February 5, 5: February 5, 2007 Household Vehicle Miles to someone by E-mail Share Vehicle Technologies Office: Fact #455: February 5, 2007 Household Vehicle Miles on Facebook Tweet about Vehicle Technologies Office: Fact #455: February 5, 2007 Household Vehicle Miles on Twitter Bookmark Vehicle Technologies Office: Fact #455: February 5, 2007 Household Vehicle Miles on Google Bookmark Vehicle Technologies Office: Fact #455: February 5, 2007 Household Vehicle Miles on Delicious Rank Vehicle Technologies Office: Fact #455: February 5, 2007 Household Vehicle Miles on Digg Find More places to share Vehicle Technologies Office: Fact #455: February 5, 2007 Household Vehicle Miles on AddThis.com... Fact #455: February 5, 2007 Household Vehicle Miles The graphs below show the average vehicle miles of travel (VMT) - daily

303

Competition Helps Kids Learn About Energy and Save Their Households...  

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

Competition Helps Kids Learn About Energy and Save Their Households Some Money Competition Helps Kids Learn About Energy and Save Their Households Some Money May 21, 2013 - 2:40pm...

304

Vehicle Technologies Office: Fact #453: January 22, 2007 Household Vehicle  

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

3: January 22, 3: January 22, 2007 Household Vehicle Ownership to someone by E-mail Share Vehicle Technologies Office: Fact #453: January 22, 2007 Household Vehicle Ownership on Facebook Tweet about Vehicle Technologies Office: Fact #453: January 22, 2007 Household Vehicle Ownership on Twitter Bookmark Vehicle Technologies Office: Fact #453: January 22, 2007 Household Vehicle Ownership on Google Bookmark Vehicle Technologies Office: Fact #453: January 22, 2007 Household Vehicle Ownership on Delicious Rank Vehicle Technologies Office: Fact #453: January 22, 2007 Household Vehicle Ownership on Digg Find More places to share Vehicle Technologies Office: Fact #453: January 22, 2007 Household Vehicle Ownership on AddThis.com... Fact #453: January 22, 2007 Household Vehicle Ownership

305

Vehicle Technologies Office: Fact #259: March 17, 2003 Household...  

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

9: March 17, 2003 Household Travel by Gender to someone by E-mail Share Vehicle Technologies Office: Fact 259: March 17, 2003 Household Travel by Gender on Facebook Tweet about...

306

Essays on household decision making in developing countries  

E-Print Network (OSTI)

This dissertation contains three essays on household decision making in the areas of education and health in developing countries. The first chapter explores intra-household decision making in the context of conditional ...

Berry, James W. (James Wesley)

2009-01-01T23:59:59.000Z

307

Development of the Household Sample for Furnace and Boiler Life...  

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

households in the country. The data sample provides the household energy consumption and energy price inputs to the life-cycle cost analysis segment of the furnace and boiler...

308

ANALYSIS OF CEE HOUSEHOLD SURVEY NATIONAL AWARENESS OF ENERGY STAR  

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

ANALYSIS OF CEE HOUSEHOLD SURVEY ANALYSIS OF CEE HOUSEHOLD SURVEY NATIONAL AWARENESS OF ENERGY STAR ® FOR 2012 TABLE OF CONTENTS Acknowledgements .................................................................................. ii Executive Summary ............................................................................ ES-1 Introduction ............................................................................................... 1 Methodology Overview ............................................................................. 2 Key Findings ............................................................................................. 5 Recognition .................................................................................................................. 5 Understanding ........................................................................................................... 12

309

"Table HC12.6 Air Conditioning Characteristics by Midwest Census...  

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

North Central","West North Central" "Total",111.1,25.6,17.7,7.9 "Do Not Have Cooling Equipment",17.8,2.1,1.8,0.3 "Have Cooling Equipment",93.3,23.5,16,7.5 "Use Cooling...

310

"Table HC10.6 Air Conditioning Characteristics by U.S. Census...  

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

ics",,"Northeast","Midwest","South","West" "Total",111.1,20.6,25.6,40.7,24.2 "Do Not Have Cooling Equipment",17.8,4,2.1,1.4,10.3 "Have Cooling Equipment",93.3,16.5,23.5,39.3,13.9...

311

"Table HC10.11 Home Electronics Characteristics by U.S. Census...  

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

",13.6,2.4,2.7,5.1,3.5 "Laptop (Flat-panel LCD)",16.9,3.3,3.4,6.1,4.1 "Have Access to Internet" "Yes",66.9,12.3,15.3,23.3,16 "Dial-up (phone)",26.8,4.3,6.9,10.2,5.4...

312

"Table HC14.11 Home Electronics Characteristics by West Census...  

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

LCD",13.6,3.5,1,2.5 "Laptop (Flat-panel LCD)",16.9,4.1,1.1,3 "Have Access to Internet" "Yes",66.9,16,4.7,11.3 "Dial-up (phone)",26.8,5.4,1.8,3.6 "DSL",19.1,5.4,1.3,4.1...

313

Table HC10.8 Water Heating Characteristics by U.S. Census Region ...  

U.S. Energy Information Administration (EIA)

No Separate Water Heater..... 3.4 1.1 0.5 0.9 1.0 Housing Units (millions) Table HC10.8 Water Heating ...

314

Household carbon dioxide production in relation to the greenhouse effect  

SciTech Connect

A survey of 655 households from eastern suburbs of Melbourne was undertaken to determine householders[prime] attitudes to, and understanding of, the greenhouse effect. Carbon dioxide emissions resulting from car, electricity and gas use were computed and household actions which could reduce CO[sub 2] emissions were addressed. Preliminary analysis of the results indicates that householders in this area are aware of, and concerned about, the greenhouse effect, although their understanding of its causes is often poor. Many appreciate the contribution of cars, but are unclear about the relative importance of other household activities. Carbon dioxide emissions from the three sources examined averaged 21[center dot]2 tonnes/year per household and 7[center dot]4 tonnes/year per person. Electricity was the largest contributor (8[center dot]6 tonnes/year), cars the next largest (7[center dot]7 tonnes/year) and gas third (5[center dot] tonnes/year) per household. Emissions varied considerably from household to household. There was a strong positive correlation between availability of economic resources and household CO[sub 2] output from all sources. Carbon dioxide production, particularly from car use, was greater from households which were most distant from a railway station, and from larger households, and numbers of children in the household had little effect on emissions. There were also some economics of scale for households containing more adults. Understanding the causes of the greenhouse bore little relation to change in CO[sub 2] emissions; being concerned about it was associated with a small reduction; but actual actions to reduce car use and household heating, however motivated, produced significant reductions. 12 refs., 9 figs., 6 tabs.

Stokes, D.; Lindsay, A.; Marinopoulos, J.; Treloar, A.; Wescott, G. (Deakin Univ., Clayton (Australia))

1994-03-01T23:59:59.000Z

315

Mitigating Carbon Emissions: the Potential of Improving Efficiency of Household Appliances in China  

E-Print Network (OSTI)

Efficiency of Household Appliances in China Jiang Lin8 Appliance Market inEfficiency of Household Appliances in China Executive

Lin, Jiang

2006-01-01T23:59:59.000Z

316

Use of electricity billing data to determine household energy use fingerprints  

Science Conference Proceedings (OSTI)

Ways to analyze billing data are discussed. The starting point for these analyses is a method developed at Princeton University. Their Scorekeeping model permits decomposition of total household energy use into its weather- and nonweather-sensitive elements; the weather-sensitive portion is assumed proportional to heating degree days. The Scorekeeping model also allows one to compute weather-adjusted energy consumption for each household based on its billing data and model parameters; this is the model's estimate of annual consumption under long-run weather conditions. The methods discussed here extend the Scorekeeping results to identify additional characteristics of household energy use. In particular, the methods classify households in terms of the intensity with which the particular fuel is used for space heating (primary heating fuel vs supplemental heating fuel vs no heating at all with the fuel). In addition, households that use the particular fuel for air conditioning are identified. In essence, the billing data and model results are used to determine household energy use fingerprints. The billing data and model results can also be used to identify and correct anomalous bills. The automated method discussed here identifies anomalously high or low utility bills, which are then dropped before re-estimation of the Scorekeeping model parameters. Alternatively, a pair of bills may be combined if one is very high and a temporally adjacent bill is very low. The Scorekeeping model is then re-estimated after the two bills are combined into one. The methods permit careful examination and analysis of changes in energy use from one year to another.

Hirst, E.; Goeltz, R.; White, D.

1984-08-01T23:59:59.000Z

317

The Household Market for Electric Vehicles: Testing the Hybrid Household Hypothesis--A Reflively Designed Survey of New-car-buying, Multi-vehicle California Households  

E-Print Network (OSTI)

by electric and hybrid vehicles", SAE Technical Papers No.household response to hybrid vehicles. Finally, we suggestas electric or hybrid vehicles. Transitions in choices of

Turrentine, Thomas; Kurani, Kenneth

1995-01-01T23:59:59.000Z

318

Forecasting the Population of Census Tracts by Age and Sex: An Example of the Hamilton–Perry Method in Action  

E-Print Network (OSTI)

approach to economic forecasting and policy analysis.for K-12 enrollment forecasting. Educational Research65 and 69 85 and over Forecasting the Population of Census

Swanson, David A.; Schlottmann, Alan; Schmidt, Bob

2010-01-01T23:59:59.000Z

319

AEO2011: Natural Gas Consumption by End-Use Sector and Census Division |  

Open Energy Info (EERE)

Consumption by End-Use Sector and Census Division Consumption by End-Use Sector and Census Division Dataset Summary Description This dataset comes from the Energy Information Administration (EIA), and is part of the 2011 Annual Energy Outlook Report (AEO2011). This dataset is table 136, and contains only the reference case. This dataset is in trillion cubic feet. The data is broken down into residential, commercial, industrial, electric power and transportation. Source EIA Date Released April 26th, 2011 (3 years ago) Date Updated Unknown Keywords 2011 AEO EIA Natural gas consumption Data application/vnd.ms-excel icon AEO2011: Natural Gas Consumption by End-Use Sector and Census Division- Reference Case (xls, 138.4 KiB) Quality Metrics Level of Review Peer Reviewed Comment Temporal and Spatial Coverage

320

AEO2011: Natural Gas Delivered Prices by End-Use Sector and Census Division  

Open Energy Info (EERE)

Delivered Prices by End-Use Sector and Census Division Delivered Prices by End-Use Sector and Census Division Dataset Summary Description This dataset comes from the Energy Information Administration (EIA), and is part of the 2011 Annual Energy Outlook Report (AEO2011). This dataset is table 137, and contains only the reference case. This dataset is in trillion cubic feet. The data is broken down into residential, commercial, industrial, electric power and transportation. Source EIA Date Released April 26th, 2011 (3 years ago) Date Updated Unknown Keywords 2011 AEO EIA Natural Gas Data application/vnd.ms-excel icon AEO2011: Natural Gas Delivered Prices by End-Use Sector and Census Division- Reference Case (xls, 140.7 KiB) Quality Metrics Level of Review Peer Reviewed Comment Temporal and Spatial Coverage Frequency Annually

Note: This page contains sample records for the topic "household characteristics census" 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

202-328-5000 www.rff.orgA New Look at Residential Electricity Demand Using Household Expenditure Data  

E-Print Network (OSTI)

We estimate residential electricity demand for different regions of the country, assuming that consumers respond to average electricity prices. We circumvent the need for individual billing information by developing a novel generalized method of moments approach that allows us to estimate demand based on household electricity expenditure data from the Consumer Expenditure Survey, which does not have quantity and price information. We find that price elasticity estimates vary across the four census regions—the South at –1.02 is the most price-elastic region and the Northeast at –0.82 is the least—and are essentially equivalent across income quartiles. In general, these price elasticity estimates are considerably larger in magnitude than those found in other studies using household-level data that assume that consumers respond to marginal prices. We also apply our elasticity estimates in a U.S. climate policy simulation to determine how these elasticity estimates alter consumption and price outcomes compared to the more conservative elasticity estimates commonly used in policy analysis.

Harrison Fell; Shanjun Li; Anthony Paul; Harrison Fell; Shanjun Li; Anthony Paul; Monte Carlo Analysis

2010-01-01T23:59:59.000Z

322

"Table A7. Shell Storage Capacity of Selected Petroleum Products by Census"  

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

Shell Storage Capacity of Selected Petroleum Products by Census" Shell Storage Capacity of Selected Petroleum Products by Census" " Region, Industry Group, and Selected Industries, 1991" " (Estimates in Thousand Barrels)" " "," "," "," "," ","Other","RSE" "SIC"," ","Motor","Residual"," ","Distillate","Row" "Code(a)","Industry Groups and Industry","Gasoline","Fuel Oil","Diesel","Fuel Oil","Factors" ,,"Total United States" ,"RSE Column Factors:",1,0.9,1,1.1 , 20,"Food and Kindred Products",38,1448,306,531,12.1 2011," Meat Packing Plants",1,229,40,13,13.2

323

"Table A25 Average Prices of Selected Purchased Energy Sources by Census"  

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

Average Prices of Selected Purchased Energy Sources by Census" Average Prices of Selected Purchased Energy Sources by Census" " Region, Industry Group, and Selected Industries, 1991: Part 2" " (Estimates in Dollars per Million Btu)" ,,,,,,,,"RSE" "SIC"," "," ","Residual","Distillate"," "," "," ","Row" "Code(a)","Industry Groups and Industry","Electricity","Fuel Oil","Fuel Oil(b)","Natural Gas(c)","LPG","Coal","Factors" ,,"Total United States" ,"RSE Column Factors:",0.7,0.8,1,2.8,1,0.7 20,"Food and Kindred Products",15.789,2.854,6.064,2.697,7.596,1.433,4.5

324

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

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

4. Total Expenditures for Purchased Energy Sources by Census Region," 4. Total Expenditures for Purchased Energy Sources by Census Region," " Industry Group, and Selected Industries, 1991" " (Estimates in Million Dollars)" ,,,,,,,,,,,"RSE" "SIC"," "," "," ","Residual","Distillate ","Natural"," "," ","Coke"," ","Row" "Code(a)","Industry Groupsc and Industry","Total","Electricity","Fuel Oil","Fuel Oil(b)","Gas(c)","LPG","Coal","and Breeze","Other(d)","Factors" ,,"Total United States" ,"RSE Column Factors:","0.6 ",0.6,1.3,1.3,0.7,1.2,1.2,1.5,1.1

325

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

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

2. Total Quantity of Purchased Energy Sources by Census Region," 2. Total Quantity of Purchased Energy Sources by Census Region," " Industry Group, and Selected Industries, 1991" " (Estimates in Btu or Physical Units)" ,,,,,,"Natural",,,"Coke" " "," ","Total","Electricity","Residual","Distillate","Gas(c)"," ","Coal","and Breeze"," ","RSE" "SIC"," ","(trillion","(million","Fuel Oil","Fuel Oil(b)","(billion","LPG","(1000","(1000","Other(d)","Row" "Code(a)","Industry Groups and Industry","Btu)","kWh)","(1000 bbls)","(1000 bbls)","cu ft)","(1000 bbls)","short tons)","short tons)","(trillion Btu)","Factors"

326

Public census data on CD-ROM at Lawrence Berkeley Laboratory  

Science Conference Proceedings (OSTI)

In connection with the comprehensive Epidemiologic Data Resource (CEDR) and Populations at risk to Environmental Pollution (PAREP) projects in the Information and Computing Sciences Division (ICSD) at Lawrence Berkeley Laboratory (LBL), public data files containing socio-economic and geographic data are available to CEDR and PAREP collaborators in the LBL computing network. At this time 60 CD-ROM diskettes (approximately 30 gigabytes) are on line in the Unix file server cedrcd.lbl.gov. Most of the files are from the US Bureau of the Census, and most of those pertain to the 1990 Census of Population and Housing. This paper contains a list of the CD-ROMS available.

Merrill, D.W.

1992-04-01T23:59:59.000Z

327

Public census data on CD-ROM at Lawrence Berkeley Laboratory  

SciTech Connect

In connection with the Comprehensive Epidemiologic Data Resource (CEDR) and Populations at Risk to Environmental Pollution (PAREP) projects, of the Information and Computing Sciences Division (ICSD) at Lawrence Berkeley Laboratory (LBL), are using public socioeconomic and geographic data files which are available to CEDR and PAREP collaborators via LBL's computing network. At this time 67 CD-ROM diskettes (approximately 35 gigabytes) are on line via the Unix file server cedrcd.lbl.gov. Most of the files are from the US Bureau of the Census, and most pertain to the 1990 Census of Population and Housing. This paper contains a list of the CD-ROMs available.

Merrill, D.W.

1992-07-02T23:59:59.000Z

328

Public census data on CD-ROM at Lawrence Berkeley Laboratory. Revision 1  

SciTech Connect

In connection with the Comprehensive Epidemiologic Data Resource (CEDR) and Populations at Risk to Environmental Pollution (PAREP) projects, of the Information and Computing Sciences Division (ICSD) at Lawrence Berkeley Laboratory (LBL), are using public socioeconomic and geographic data files which are available to CEDR and PAREP collaborators via LBL`s computing network. At this time 67 CD-ROM diskettes (approximately 35 gigabytes) are on line via the Unix file server cedrcd.lbl.gov. Most of the files are from the US Bureau of the Census, and most pertain to the 1990 Census of Population and Housing. This paper contains a list of the CD-ROMs available.

Merrill, D.W.

1992-07-02T23:59:59.000Z

329

"Table A40. Average Prices of Selected Purchased Energy Sources by Census"  

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

Region, Census Division, Industry Group, and Selected Industries, 1994: Part 1" Region, Census Division, Industry Group, and Selected Industries, 1994: Part 1" " (Estimates in Dollars per Physical Units)" ,,,,," " " "," "," ","Residual","Distillate","Natural Gas(c)"," "," ","RSE" "SIC"," ","Electricity","Fuel Oil","Fuel Oil(b)","(1000","LPG","Coal","Row" "Code(a)","Industry Group and Industry","(kWh)","(gallons)","(gallons)","cu ft)","(gallons)","(short tons)","Factors" ,,"Total United States" ,"RSE Column Factors:",0.8,1,1.3,0.8,1.6,0.8

330

file://C:\Documents%20and%20Settings\VM3\My%20Documents\hc6-12a  

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

2a. Usage Indicators by West Census Region, 2a. Usage Indicators by West Census Region, Million U.S. Households, 2001 ____________________________________________________________________________________________ | | | | | West Census Region | | |___________________________________| | | | | | | | Census Division | | | |_______________________|

331

file://C:\Documents%20and%20Settings\VM3\My%20Documents\hc6-10a  

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

0a. Usage Indicators by Midwest Census Region, 0a. Usage Indicators by Midwest Census Region, Million U.S. Households, 2001 ____________________________________________________________________________________________ | | | | | Midwest Census Region | | |___________________________________| | | | | | | | Census Division | | | |_______________________|

332

Towards sustainable household energy use in the Netherlands, Int  

E-Print Network (OSTI)

Abstract: Households consume direct energy, using natural gas, heating oil, gasoline and electricity, and consume indirect energy, the energy related to the production of goods and the delivery of services for the households. Past trends and present-day household energy use (direct and indirect) are analysed and described. A comparison of these findings with objectives concerning ecological sustainability demonstrates that present-day household energy use is not sustainable. A scenario towards sustainable household energy use is designed containing far-reaching measures with regard to direct energy use. Scenario evaluation shows a substantial reduction of direct energy use; however, this is not enough to meet the sustainability objectiv es. Based on these results, the possibilities and the limitations are discussed to enable households to make their direct and indirect energy use sustainable on the long run.

Jack Van Der Wal; Henri C. Moll

2001-01-01T23:59:59.000Z

333

Commercial Buildings Characteristics 1992 - Publication and Tables  

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

Buildings Characteristics Data > Publication and Tables Buildings Characteristics Data > Publication and Tables Publication and Tables Percent of Buildings and Floorspace by Census Region, 1992 figure on percent of building and floorspace by census region, 1992 separater bar To View and/or Print Reports (requires Adobe Acrobat Reader) - Download Adobe Acrobat Reader If you experience any difficulties, visit our Technical Frequently Asked Questions. You have the option of downloading the entire report or selected sections of the report. Full Report - Commercial Buildings Characteristics, 1992 with only selected tables (file size 1.34 MB) pages: 157 Selected Sections: Main Text (file size 883,980 bytes) pages: 28, includes the following: Contacts Contents Executive Summary Introduction Background Organization of the report

334

A Model of Household Demand for Activity Participation and Mobility  

E-Print Network (OSTI)

household car ownership, car usage, and travel by differentownership demand, and car usage demand. Modal travel demand,mode), car ownership, and car usage for spatial aggregations

Golob, Thomas F.

1996-01-01T23:59:59.000Z

335

Crime and the Nation’s Households, 2000 By  

E-Print Network (OSTI)

experienced 1 or more violent or property crimes in 2000, according to data from the National Crime Victimization Survey (NCVS). About 4.3 million households had members who experienced 1 or more nonfatal violent crimes, including rape, sexual assault, robbery, and aggravated or simple assault. About 14.8 million households experienced 1 or more property crimes — household burglary, motor vehicle theft, or theft. Vandalism, presented for the first time in a Bureau of Justice Statistics (BJS) report, victimized about 6.1 million households. The households that sustained vandalism were counted separately from those experiencing other crimes. Because vandalism is included for the first time, findings are presented in a box on page 4. Beginning in 2001, NCVS victimizations will be measured both with and without vandalism. Measuring the extent to which households are victimized by crime One measure of the impact of crime throughout the Nation is gained through estimating the number and percentage of households victimized Highlights During 2000, 16 % of U.S. households had a member who experienced a crime, with 4 % having a member victimized by violent crime. During 1994, 25 % of households experienced at least one crime; 7 % a violent crime.

Patsy A. Klaus

2002-01-01T23:59:59.000Z

336

Barriers to household investment in residential energy conservation: preliminary assessment  

Science Conference Proceedings (OSTI)

A general assessment of the range of barriers which impede household investments in weatherization and other energy efficiency improvements for their homes is provided. The relationship of similar factors to households' interest in receiving a free energy audits examined. Rates of return that underly household investments in major conservation improvements are assessed. A special analysis of household knowledge of economically attractive investments is provided that compares high payback improvements specified by the energy audit with the list of needed or desirable conservation improvements identified by respondents. (LEW)

Hoffman, W.L.

1982-12-01T23:59:59.000Z

337

Household Responses to the Financial Crisis in Indonesia  

E-Print Network (OSTI)

on farm households in Indonesia and Thailand,” World Bank20. Cameron, Lisa. (1999). “Indonesia: a quarterly review,”The Real Costs of Indonesia's Economic Crisis: Preliminary

Thomas, Duncan; Frankenberg, Elizabeth

2005-01-01T23:59:59.000Z

338

Answers to Frequently Asked Questions About the Household Bottled ...  

U.S. Energy Information Administration (EIA)

Form EIA-457D (2001) -- Household Bottled Gas (LPG or Propane) Usage Form OMB No. 1905-0092, Expiring February 29, 2004 2001 Residential Energy Consumption Survey

339

SUPPLEMENTAL ENERGY-RELATED DATA FOR THE 2001 NATIONAL HOUSEHOLD ...  

U.S. Energy Information Administration (EIA)

... vehicle manufacturer, vehicle model, vehicle model year, and vehicle type – several ENERGY INFORMATION ADMINISTRATION/2001 NATIONAL HOUSEHOLD TRAVEL SURVEY K-23 ...

340

U.S. households are incorporating energy–efficient features ...  

U.S. Energy Information Administration (EIA)

... area of increased efficiency: about 60% of households use at least some energy-efficient compact fluorescent (CFL) or light-emitting diode (LED) ...

Note: This page contains sample records for the topic "household characteristics census" 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

Analysis of the energy requirement for household consumption.  

E-Print Network (OSTI)

??Humans in households use energy for their activities. This use is both direct, for example electricity and natural gas, but also indirect, for the production,… (more)

Vringer, Kees

2005-01-01T23:59:59.000Z

342

Householder's Perceptions of Insulation Adequacy and Drafts in the ...  

U.S. Energy Information Administration (EIA)

The 2001 RECS was the first RECS to request household perceptions regarding the presence of winter drafts in the home. The data presented in this report ...

343

1997 Residential Energy Consumption and Expenditures per Household ...  

U.S. Energy Information Administration (EIA)

Return to: Residential Home Page . Changes in the 1997 RECS: Housing Unit Type Per Household Member Per Building Increase. Residential Energy Consumption ...

344

Answers to Frequently Asked Questions About the Household ...  

U.S. Energy Information Administration (EIA)

Form EIA-457E (2001) – Household Electricity Usage Form OMB No. 1905-0092, Expiring February 29, 2004 2001 Residential Energy Consumption Survey

345

Appliance Commitment for Household Load Scheduling  

Science Conference Proceedings (OSTI)

This paper presents a novel appliance commitment algorithm that schedules thermostatically-controlled household loads based on price and consumption forecasts considering users comfort settings to meet an optimization objective such as minimum payment or maximum comfort. The formulation of an appliance commitment problem was described in the paper using an electrical water heater load as an example. The thermal dynamics of heating and coasting of the water heater load was modeled by physical models; random hot water consumption was modeled with statistical methods. The models were used to predict the appliance operation over the scheduling time horizon. User comfort was transformed to a set of linear constraints. Then, a novel linear, sequential, optimization process was used to solve the appliance commitment problem. The simulation results demonstrate that the algorithm is fast, robust, and flexible. The algorithm can be used in home/building energy-management systems to help household owners or building managers to automatically create optimal load operation schedules based on different cost and comfort settings and compare cost/benefits among schedules.

Du, Pengwei; Lu, Ning

2011-06-30T23:59:59.000Z

346

In-vessel composting of household wastes  

Science Conference Proceedings (OSTI)

The process of composting has been studied using five different types of reactors, each simulating a different condition for the formation of compost; one of which was designed as a dynamic complete-mix type household compost reactor. A lab-scale study was conducted first using the compost accelerators culture (Trichoderma viridae, Trichoderma harzianum, Trichorus spirallis, Aspergillus sp., Paecilomyces fusisporus, Chaetomium globosum) grown on jowar (Sorghum vulgare) grains as the inoculum mixed with cow-dung slurry, and then by using the mulch/compost formed in the respective reactors as the inoculum. The reactors were loaded with raw as well as cooked vegetable waste for a period of 4 weeks and then the mulch formed was allowed to maturate. The mulch was analysed at various stages for the compost and other environmental parameters. The compost from the designed aerobic reactor provides good humus to build up a poor physical soil and some basic plant nutrients. This proves to be an efficient, eco-friendly, cost-effective, and nuisance-free solution for the management of household solid wastes.

Iyengar, Srinath R. [Civil and Environmental Engineering Department, V.J. Technological Institute, H.R. Mahajani Road, Matunga, Mumbai 400 019 (India)]. E-mail: srinathrangamani@yahoo.com; Bhave, Prashant P. [Civil and Environmental Engineering Department, V.J. Technological Institute, H.R. Mahajani Road, Matunga, Mumbai 400 019 (India)]. E-mail: drppbhave@vsnl.net

2006-07-01T23:59:59.000Z

347

REACTION OF DOLPHINS TO A SURVEY VESSEL: EFFECTS ON CENSUS DATA  

E-Print Network (OSTI)

REACTION OF DOLPHINS TO A SURVEY VESSEL: EFFECTS ON CENSUS DATA RoGER P. HEWITI'l ABSTRACf A field of a survey vessel prior to their detection by shipboard observers and that the use of a monotonically decreasing detection function is adequate to minimize bias. Aerial and shipboard estimates of school size

348

Model of home heating and calculation of rates of return to household energy conservation investment  

Science Conference Proceedings (OSTI)

This study attempts to find out if households' investments on energy conservation yield expected returns. It first builds a home-heating regression model, then uses the results of the model to calculate the rates of return for households' investments on the energy conservation. The home heating model includes housing characteristics, economic and demographic variables, appliance related variables, and regional dummy variables. Housing characteristic variables are modeled according to the specific physical relationship between the house and its heating requirement. Data from the Residential Energy Consumption Survey (RECS) of 1980-1981 is used for the empirical testing of the model. The model is estimated for single-detached family houses separately for three major home-heating fuel types: electricity, natural gas and fuel oil. Four scenarios are used to calculate rates of return for each household. The results show in the Northern areas the rates of return in most of the cases are a lot higher than market interest rates. In the Western and Southern areas, with few exceptions, the rates of return are lower than market interest rates. The variation of heating degree days and energy prices can affect the rates of return up to 20 percentage points.

Hsueh, L.M.

1984-01-01T23:59:59.000Z

349

A REVIEW OF ASSUMPTIONS AND ANALYSIS IN EPRI EA-3409, "HOUSEHOLD APPLIANCE CHOICE: REVISION OF REEPS BEHAVIORAL MODELS"  

E-Print Network (OSTI)

EPRI EA-3409, "Household Appliance Choice: Revision of REEPSEA",3409: "HOUSEHOLD APPLIANCE CHOICE: REVISION OF REEPSreport EA-3409, "Household Appliance Choice: Revi- sion of

Wood, D.J.

2010-01-01T23:59:59.000Z

350

Simulating household activities to lower consumption peaks: demonstration  

Science Conference Proceedings (OSTI)

Energy experts need fine-grained dynamics oriented tools to investigate household activities in order to improve power management in the residential sector. This paper presents the SMACH framework for modelling, simulating and analy- sis of household ... Keywords: agent-based modelling, energy, social simulation

Edouard Amouroux, Francois Sempé, Thomas Huraux, Nicolas Sabouret, Yvon Haradji

2013-05-01T23:59:59.000Z

351

Elements of consumption: an abstract visualization of household consumption  

Science Conference Proceedings (OSTI)

To promote sustainability consumers must be informed about their consumption behaviours. Ambient displays can be used as an eco-feedback technology to convey household consumption information. Elements of Consumption (EoC) demonstrates this by visualizing ... Keywords: a-life, eco-feedback, household consumption, sustainability

Stephen Makonin; Philippe Pasquier; Lyn Bartram

2011-07-01T23:59:59.000Z

352

Table CE2-3e. Space-Heating Energy Expenditures in U.S. Households ...  

U.S. Energy Information Administration (EIA)

Table CE2-3e. Space-Heating Energy Expenditures in U.S. Households by Household Income, 2001 RSE Column Factor: Total 2001 Household Income Below Poverty

353

CBECS 1992 - Building Characteristics, Detailed Tables  

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

Detailed Tables Detailed Tables Detailed Tables Percent of Buildings and Floorspace by Census Region, 1992 Percent of Buildings and Floorspace by Census Region, 1992 The following 70 tables present extensive cross-tabulations of commercial buildings characteristics. These data are from the Buildings Characteristics Survey portion of the 1992 CBECS. The "Quick-Reference Guide," indicates the major topics of each table. Directions for calculating an approximate relative standard error (RSE) for each estimate in the tables are presented in Figure A1, "Use of RSE Row and Column Factor." The Glossary contains the definitions of the terms used in the tables. See the preceding "At A Glance" section for highlights of the detailed tables. Table Organization

354

" Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1"  

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

2 Living Space Characteristics by Household Income, 2005" 2 Living Space Characteristics by Household Income, 2005" " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ,"Housing Units (millions)" ,,"Less than $20,000","$20,000 to $39,999","$40,000 to $59,999","$60,000 to $79,999","$80,000 or More" "Living Space Characteristics" "Total",111.1,26.7,28.8,20.6,13.1,22,16.6,38.6 "Floorspace (Square Feet)" "Total Floorspace1" "Fewer than 500",3.2,1.9,0.9,"Q","Q","Q",1.3,2.3 "500 to 999",23.8,10.5,7.3,3.3,1.4,1.2,6.6,12.9 "1,000 to 1,499",20.8,5.8,7,3.8,2.2,2,3.9,8.9

355

" Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1"  

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

8 Water Heating Characteristics by Household Income, 2005" 8 Water Heating Characteristics by Household Income, 2005" " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ,"Housing Units (millions)" ,,"Less than $20,000","$20,000 to $39,999","$40,000 to $59,999","$60,000 to $79,999","$80,000 or More" "Water Heating Characteristics" "Total",111.1,26.7,28.8,20.6,13.1,22,16.6,38.6 "Number of Water Heaters" "1.",106.3,25.8,28,19.6,12.7,20.2,16,37.3 "2 or More",3.7,0.3,0.5,0.9,0.4,1.7,"Q",0.5 "Do Not Use Hot Water",1.1,0.6,0.3,"Q","N","Q",0.5,0.8

356

" Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1"  

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

4 Space Heating Characteristics by Household Income, 2005" 4 Space Heating Characteristics by Household Income, 2005" " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ,"Housing Units (millions)" ,,"Less than $20,000","$20,000 to $39,999","$40,000 to $59,999","$60,000 to $79,999","$80,000 or More" "Space Heating Characteristics" "Total",111.1,26.7,28.8,20.6,13.1,22,16.6,38.6 "Do Not Have Space Heating Equipment",1.2,0.5,0.3,0.2,"Q",0.2,0.3,0.6 "Have Main Space Heating Equipment",109.8,26.2,28.5,20.4,13,21.8,16.3,37.9 "Use Main Space Heating Equipment",109.1,25.9,28.1,20.3,12.9,21.8,16,37.3

357

" Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1"  

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

HC7.9 Home Appliances Characteristics by Household Income, 2005" HC7.9 Home Appliances Characteristics by Household Income, 2005" " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ,"Housing Units (millions)" ,,"Less than $20,000","$20,000 to $39,999","$40,000 to $59,999","$60,000 to $79,999","$80,000 or More" "Home Appliances Characteristics" "Total U.S.",111.1,26.7,28.8,20.6,13.1,22,16.6,38.6 "Cooking Appliances" "Conventional Ovens" "Use an Oven",109.6,26.1,28.5,20.2,12.9,21.8,16.3,37.8 "1.",103.3,25.1,27.1,19.2,12.3,19.6,15.8,36.3 "2 or More",6.2,0.9,1.4,1,0.6,2.2,0.5,1.5

358

" Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1"  

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

1 Home Electronics Characteristics by Household Income, 2005" 1 Home Electronics Characteristics by Household Income, 2005" " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ,"Housing Units (millions)" ,,"Less than $20,000","$20,000 to $39,999","$40,000 to $59,999","$60,000 to $79,999","$80,000 or More" "Home Electronics Characteristics" "Total",111.1,26.7,28.8,20.6,13.1,22,16.6,38.6 "Personal Computers" "Do Not Use a Personal Computer ",35.5,17.1,10.8,4.2,1.8,1.6,10.3,20.6 "Use a Personal Computer",75.6,9.6,18,16.4,11.3,20.3,6.4,17.9 "Number of Desktop PCs" "1.",50.3,8.3,14.2,11.4,7.2,9.2,5.3,14.2

359

Residential energy consumption survey: housing characteristics 1984  

SciTech Connect

Data collected in the 1984 Residential Energy Consumption Survey (RECS), the sixth national survey of households and their fuel suppliers, provides baseline information on how households use energy. Households living in all types of housing units - single-family homes (including townhouses), apartments, and mobile homes - were chosen to participate. Data from the surveys are available to the public. The housing characteristics this report describes include fuels and the uses they are put to in the home; appliances; square footage of floorspace; heating (and cooling) equipment; thermal characteristics of housing structures; conservation features and measures taken; the consumption of wood; temperatures indoors; and regional weather. These data are tabulated in sets, first showing counts of households and then showing percentages. Results showed: Fewer households are changing their main heating fuel. More households are air conditioned than before. Some 50% of air-conditioned homes now use central systems. The three appliances considered essential are the refrigerator, the range, and the television set. At least 98% of US homes have at least one television set; but automatic dishwashers are still not prevalent. Few households use the budget plans tht are available from their utility companies to ease the payment burden of seasonal surges in fuel bills. The most common type of heating equipment in the United States is the natural-gas forced-air furnace. About 40% ofthose furnaces are at least 15 years old. The oldest water heaters are those that use fuel oil. The most common conservation feature in 1984 is ceiling or attic insulation - 80% of homes report having this item. Relatively few households claimed tax credits in 1984 for energy-conservation improvements.

Not Available

1986-10-08T23:59:59.000Z

360

Table AC1. Total Households Using Air-Conditioning Equipment, 2005 ...  

U.S. Energy Information Administration (EIA)

Table AC1. Total Households Using Air-Conditioning Equipment, 2005 Million U.S. Households Type of Air-Conditioning Equipment (millions) Central System

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


361

Table SH1. Total Households Using a Space Heating Fuel, 2005 ...  

U.S. Energy Information Administration (EIA)

Total Households Using a Space Heating Fuel, 2005 Million U.S. Households Using a Non-Major Fuel 5 ... Space Heating (millions) Energy Information Administration

362

Testing Electric Vehicle Demand in `Hybrid Households' Using a Reflexive Survey  

E-Print Network (OSTI)

1994) Demand for Electric Vehicles in Hybrid Households: A nand the Household Electric Vehicle Market: A Constraintsthe mar- ket for electric vehicles in California. Presented

Kurani, Kenneth; Turrentine, Thomas; Sperling, Daniel

1996-01-01T23:59:59.000Z

363

Table CE2-3c. Space-Heating Energy Consumption in U.S. Households ...  

U.S. Energy Information Administration (EIA)

Physical Units (PU) per Household4,a Physical Units of Space-Heating Consumption per Household,3 Where the Main Space-Heating Fuel Is:

364

Table CE2-7c. Space-Heating Energy Consumption in U.S. Households ...  

U.S. Energy Information Administration (EIA)

Physical Units (PU) per Household3,a Physical Units of Space-Heating Consumption per Household,2 Where the Main Space-Heating Fuel Is:

365

Table CE2-12c. Space-Heating Energy Consumption in U.S. Households ...  

U.S. Energy Information Administration (EIA)

Physical Units (PU) per Household3,a Physical Units of Space-Heating Consumption per Household,2 Where the Main Space-Heating Fuel Is:

366

Table CE2-4c. Space-Heating Energy Consumption in U.S. Households ...  

U.S. Energy Information Administration (EIA)

Physical Units (PU) per Household3,a Physical Units of Space-Heating Consumption per Household,2 Where the Main Space-Heating Fuel Is:

367

Table CE2-7c. Space-Heating Energy Consumption in U.S. Households ...  

U.S. Energy Information Administration (EIA)

Physical Units (PU) per Household3 Physical Units of Space-Heating Consumption per Household,2 Where the Main Space-Heating Fuel Is:

368

Material World: Forecasting Household Appliance Ownership in a Growing Global Economy  

E-Print Network (OSTI)

of Household Income and Appliance Ownership. ECEEE Summerof decreasing prices of appliances, if price data becomesForecasting Household Appliance Ownership in a Growing

Letschert, Virginie

2010-01-01T23:59:59.000Z

369

Projecting household energy consumption within a conditional demand framework  

SciTech Connect

Few models attempt to assess and project household energy consumption and expenditure by taking into account differential household choices correlated with such variables as race, ethnicity, income, and geographic location. The Minority Energy Assessment Model (MEAM), developed by Argonne National Laboratory (ANL) for the US Department of Energy (DOE), provides a framework to forecast the energy consumption and expenditure of majority, black, Hispanic, poor, and nonpoor households. Among other variables, household energy demand for each of these population groups in MEAM is affected by housing factors (such as home age, home ownership, home type, type of heating fuel, and installed central air conditioning unit), demographic factors (such as household members and urban/rural location), and climate factors (such as heating degree days and cooling degree days). The welfare implications of the revealed consumption patterns by households are also forecast. The paper provides an overview of the model methodology and its application in projecting household energy consumption under alternative energy scenarios developed by Data Resources, Inc., (DRI).

Teotia, A.; Poyer, D.

1991-01-01T23:59:59.000Z

370

Projecting household energy consumption within a conditional demand framework  

Science Conference Proceedings (OSTI)

Few models attempt to assess and project household energy consumption and expenditure by taking into account differential household choices correlated with such variables as race, ethnicity, income, and geographic location. The Minority Energy Assessment Model (MEAM), developed by Argonne National Laboratory (ANL) for the US Department of Energy (DOE), provides a framework to forecast the energy consumption and expenditure of majority, black, Hispanic, poor, and nonpoor households. Among other variables, household energy demand for each of these population groups in MEAM is affected by housing factors (such as home age, home ownership, home type, type of heating fuel, and installed central air conditioning unit), demographic factors (such as household members and urban/rural location), and climate factors (such as heating degree days and cooling degree days). The welfare implications of the revealed consumption patterns by households are also forecast. The paper provides an overview of the model methodology and its application in projecting household energy consumption under alternative energy scenarios developed by Data Resources, Inc., (DRI).

Teotia, A.; Poyer, D.

1991-12-31T23:59:59.000Z

371

Table B3. Census Region, Number of Buildings and Floorspace, 1999  

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

. Census Region, Number of Buildings and Floorspace, 1999" . Census Region, Number of Buildings and Floorspace, 1999" ,"Number of Buildings (thousand)",,,,,"Total Floorspace (million square feet)" ,"All Buildings","North- east","Midwest ","South","West","All Buildings","North- east","Midwest","South","West" "All Buildings ................",4657,686,1188,1762,1021,67338,12360,16761,23485,14731 "Building Floorspace" "(Square Feet)" "1,001 to 5,000 ...............",2348,305,620,916,506,6774,901,1835,2536,1503 "5,001 to 10,000 ..............",1110,169,273,413,255,8238,1302,2045,3058,1834 "10,001 to 25,000 .............",708,130,188,260,130,11153,1954,2881,4194,2124

372

Residential Energy Consumption Survey (RECS) - Data - U.S. Energy  

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

2001 RECS Survey Data 2009 | 2005 | 2001 | 1997 | 1993 | Previous 2001 RECS Survey Data 2009 | 2005 | 2001 | 1997 | 1993 | Previous Housing Characteristics Consumption & Expenditures Microdata Methodology Housing Characteristics Tables + EXPAND ALL Tables HC1: Housing Unit Characteristics, Million U.S. Households PDF (all tables) Climate Zone PDF Year of Construction PDF Household Income PDF Type of Owner-Occupied Housing Unit PDF Four Most Populated States PDF Urban/Rural Location PDF Northeast Census Region PDF Midwest Census Region PDF South Census Region PDF West Census Region PDF Tables HC2: Household Characteristics, Million U.S. Households PDF (all tables) Climate Zone PDF Year of Construction PDF Household Income PDF Type of Housing Unit PDF Type of Owner-Occupied Housing Unit PDF Type of Rented Housing Unit PDF

373

Residential Energy Consumption Survey: housing characteristics, 1982  

Science Conference Proceedings (OSTI)

Data in this report cover fuels and their use in the home, appliances, square footage of floor space, heating equipment, thermal characteristics of the housing unit, conservation activities, wood consumption, indoor temperatures, and weather. The 1982 survey included a number of questions on the reasons households make energy conservation improvements to their homes. Results of these questions are presented. Discussion also highlights data pertaining to: trends in home heating fuels, trends in conservation improvements, and characteristics of households whose energy costs are included in their rent.

Thompson, W.

1984-08-01T23:59:59.000Z

374

Cooling Degree Days, by State (Weighted by Population, per 2000 Census) |  

Open Energy Info (EERE)

Cooling Degree Days, by State (Weighted by Population, per 2000 Census) Cooling Degree Days, by State (Weighted by Population, per 2000 Census) Dataset Summary Description The National Oceanic and Atmospheric Administration's (NOAA) National Environmental Satellite, Data, and Information Services (NESDIS), in conjunction with the National Climatic Data Center (NCDC) publish monthly and annual climate data by state for the U.S., including, cooling degree days (total number of days per month and per year). The average values for each state are weighted by population, using 2000 Census data. The base temperature for this dataset is 65 degrees F. Included here are monthly and annual values averaged over several periods of time: 1931-2000, 1931-60, 1941-70, 1951-80, 1961-90, 1971-2000 (standard deviation is also provided). Detailed monthly climatic information (including cooling degree days) is available for the time period between 1895 and 2011, from NOAA (http://www7.ncdc.noaa.gov/CDO/CDODivisionalSelect.jsp#).

375

Public census data on CD-ROM at Lawrence Berkeley Laboratory  

Science Conference Proceedings (OSTI)

The Comprehensive Epidemiologic Data Resource (CEDR) and Populations at Risk to Environmental Pollution (PAREP) projects, of the Information and Computing Sciences Division (ICSD) at Lawrence Berkeley Laboratory (LBL), are using public socio-economic and geographic data files which are available to CEDR and PAREP collaborators via LBL's computing network. At this time 70 CD-ROM diskettes (approximately 36 gigabytes) are on line via the Unix file server cedrcd. lbl. gov. Most of the files are from the US Bureau of the Census, and most pertain to the 1990 Census of Population and Housing. All the CD-ROM diskettes contain documentation in the form of ASCII text files. Printed documentation for most files is available for inspection at University of California Data and Technical Assistance (UC DATA), or the UC Documents Library. Many of the CD-ROM diskettes distributed by the Census Bureau contain software for PC compatible computers, for easily accessing the data. Shared access to the data is maintained through a collaboration among the CEDR and PAREP projects at LBL, and UC DATA, and the UC Documents Library. Via the Sun Network File System (NFS), these data can be exported to Internet computers for direct access by the user's application program(s).

Merrill, D.W.

1992-10-01T23:59:59.000Z

376

Public census data on CD-ROM at Lawrence Berkeley Laboratory  

SciTech Connect

The Comprehensive Epidemiologic Data Resource (CEDR) and Populations at Risk to Environmental Pollution (PAREP) projects, of the Information and Computing Sciences Division (ICSD) at Lawrence Berkeley Laboratory (LBL), are using public socio-economic and geographic data files which are available to CEDR and PAREP collaborators via LBL`s computing network. At this time 70 CD-ROM diskettes (approximately 36 gigabytes) are on line via the Unix file server cedrcd. lbl. gov. Most of the files are from the US Bureau of the Census, and most pertain to the 1990 Census of Population and Housing. All the CD-ROM diskettes contain documentation in the form of ASCII text files. Printed documentation for most files is available for inspection at University of California Data and Technical Assistance (UC DATA), or the UC Documents Library. Many of the CD-ROM diskettes distributed by the Census Bureau contain software for PC compatible computers, for easily accessing the data. Shared access to the data is maintained through a collaboration among the CEDR and PAREP projects at LBL, and UC DATA, and the UC Documents Library. Via the Sun Network File System (NFS), these data can be exported to Internet computers for direct access by the user`s application program(s).

Merrill, D.W.

1992-10-01T23:59:59.000Z

377

"Table HC11.12 Home Electronics Usage Indicators by Northeast Census Region, 2005"  

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

2 Home Electronics Usage Indicators by Northeast Census Region, 2005" 2 Home Electronics Usage Indicators by Northeast Census Region, 2005" " Million U.S. Housing Units" ,,"Northeast Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total Northeast" "Home Electronics Usage Indicators",,,"Middle Atlantic","New England" "Total",111.1,20.6,15.1,5.5 "Personal Computers" "Do Not Use a Personal Computer",35.5,6.9,5.3,1.6 "Use a Personal Computer",75.6,13.7,9.8,3.9 "Most-Used Personal Computer" "Type of PC" "Desk-top Model",58.6,10.4,7.3,3.1 "Laptop Model",16.9,3.3,2.6,0.7 "Hours Turned on Per Week" "Less than 2 Hours",13.6,2.4,1.8,0.6

378

"Table HC11.7 Air-Conditioning Usage Indicators by Northeast Census Region, 2005"  

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

7 Air-Conditioning Usage Indicators by Northeast Census Region, 2005" 7 Air-Conditioning Usage Indicators by Northeast Census Region, 2005" " Million U.S. Housing Units" ,,"Northeast Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total Northeast" "Air Conditioning Usage Indicators",,,"Middle Atlantic","New England" "Total",111.1,20.6,15.1,5.5 "Do Not Have Cooling Equipment",17.8,4,2.4,1.7 "Have Cooling Equipment",93.3,16.5,12.8,3.8 "Use Cooling Equipment",91.4,16.3,12.6,3.7 "Have Equipment But Do Not Use it",1.9,0.3,"Q","Q" "Type of Air-Conditioning Equipment1, 2" "Central System",65.9,6,5.2,0.8 "Without a Heat Pump",53.5,5.5,4.8,0.7

379

"Table HC12.12 Home Electronics Usage Indicators by Midwest Census Region, 2005"  

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

2 Home Electronics Usage Indicators by Midwest Census Region, 2005" 2 Home Electronics Usage Indicators by Midwest Census Region, 2005" " Million U.S. Housing Units" ,,"Midwest Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total Midwest" "Home Electronics Usage Indicators",,,"East North Central","West North Central" "Total",111.1,25.6,17.7,7.9 "Personal Computers" "Do Not Use a Personal Computer",35.5,8.1,5.6,2.5 "Use a Personal Computer",75.6,17.5,12.1,5.4 "Most-Used Personal Computer" "Type of PC" "Desk-top Model",58.6,14.1,10,4 "Laptop Model",16.9,3.4,2.1,1.3 "Hours Turned on Per Week" "Less than 2 Hours",13.6,3.4,2.5,0.9

380

"Table HC12.5 Space Heating Usage Indicators by Midwest Census Region, 2005"  

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

5 Space Heating Usage Indicators by Midwest Census Region, 2005" 5 Space Heating Usage Indicators by Midwest Census Region, 2005" " Million U.S. Housing Units" ,,"Midwest Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total Midwest" "Space Heating Usage Indicators",,,"East North Central","West North Central" "Total U.S. Housing Units",111.1,25.6,17.7,7.9 "Do Not Have Heating Equipment",1.2,"Q","Q","N" "Have Space Heating Equipment",109.8,25.6,17.7,7.9 "Use Space Heating Equipment",109.1,25.6,17.7,7.9 "Have But Do Not Use Equipment",0.8,"N","N","N" "Space Heating Usage During 2005"

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


381

"Table HC13.10 Home Appliances Usage Indicators by South Census Region, 2005"  

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

0 Home Appliances Usage Indicators by South Census Region, 2005" 0 Home Appliances Usage Indicators by South Census Region, 2005" " Million U.S. Housing Units" ,,"South Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total South" "Home Appliances Usage Indicators",,,"South Atlantic","East South Central","West South Central" "Total",111.1,40.7,21.7,6.9,12.1 "Cooking Appliances" "Frequency of Hot Meals Cooked" "3 or More Times A Day",8.2,3,1.6,0.3,1.1 "2 Times A Day",24.6,8.3,4.2,1.3,2.7 "Once a Day",42.3,15,8.1,2.7,4.2 "A Few Times Each Week",27.2,10.9,6,1.8,3.1 "About Once a Week",3.9,1.6,0.7,0.4,0.5

382

"Table HC14.12 Home Electronics Usage Indicators by West Census Region, 2005"  

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

2 Home Electronics Usage Indicators by West Census Region, 2005" 2 Home Electronics Usage Indicators by West Census Region, 2005" " Million U.S. Housing Units" ,,"West Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total West" "Home Electronics Usage Indicators",,,"Mountain","Pacific" "Total",111.1,24.2,7.6,16.6 "Personal Computers" "Do Not Use a Personal Computer",35.5,6.4,2.2,4.2 "Use a Personal Computer",75.6,17.8,5.3,12.5 "Most-Used Personal Computer" "Type of PC" "Desk-top Model",58.6,13.7,4.2,9.5 "Laptop Model",16.9,4.1,1.1,3 "Hours Turned on Per Week" "Less than 2 Hours",13.6,2.9,0.9,2 "2 to 15 Hours",29.1,6.6,2,4.6

383

"Table HC14.10 Home Appliances Usage Indicators by West Census Region, 2005"  

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

0 Home Appliances Usage Indicators by West Census Region, 2005" 0 Home Appliances Usage Indicators by West Census Region, 2005" " Million U.S. Housing Units" ,,"West Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total West" "Home Appliances Usage Indicators",,,"Mountain","Pacific" "Total",111.1,24.2,7.6,16.6 "Cooking Appliances" "Frequency of Hot Meals Cooked" "3 or More Times A Day",8.2,2.6,0.7,1.9 "2 Times A Day",24.6,6.6,2,4.6 "Once a Day",42.3,8.8,2.9,5.8 "A Few Times Each Week",27.2,4.7,1.5,3.1 "About Once a Week",3.9,0.7,"Q",0.6 "Less Than Once a Week",4.1,0.7,0.3,0.4 "No Hot Meals Cooked",0.9,0.2,"Q","Q"

384

"Table HC13.7 Air-Conditioning Usage Indicators by South Census Region, 2005"  

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

7 Air-Conditioning Usage Indicators by South Census Region, 2005" 7 Air-Conditioning Usage Indicators by South Census Region, 2005" " Million U.S. Housing Units" ,,"South Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total South" "Air Conditioning Usage Indicators",,,"South Atlantic","East South Central","West South Central" "Total",111.1,40.7,21.7,6.9,12.1 "Do Not Have Cooling Equipment",17.8,1.4,0.8,0.2,0.3 "Have Cooling Equipment",93.3,39.3,20.9,6.7,11.8 "Use Cooling Equipment",91.4,38.9,20.7,6.6,11.7 "Have Equipment But Do Not Use it",1.9,0.5,"Q","Q","Q" "Type of Air-Conditioning Equipment1, 2"

385

"Table HC11.5 Space Heating Usage Indicators by Northeast Census Region, 2005"  

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

5 Space Heating Usage Indicators by Northeast Census Region, 2005" 5 Space Heating Usage Indicators by Northeast Census Region, 2005" " Million U.S. Housing Units" ,,"Northeast Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total Northeast" "Space Heating Usage Indicators",,,"Middle Atlantic","New England" "Total U.S. Housing Units",111.1,20.6,15.1,5.5 "Do Not Have Heating Equipment",1.2,"Q","Q","Q" "Have Space Heating Equipment",109.8,20.5,15.1,5.4 "Use Space Heating Equipment",109.1,20.5,15.1,5.4 "Have But Do Not Use Equipment",0.8,"N","N","N" "Space Heating Usage During 2005"

386

"Table HC11.10 Home Appliances Usage Indicators by Northeast Census Region, 2005"  

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

0 Home Appliances Usage Indicators by Northeast Census Region, 2005" 0 Home Appliances Usage Indicators by Northeast Census Region, 2005" " Million U.S. Housing Units" ,,"Northeast Census Region" ," U.S. Housing Units (millions) " ,,,"Census Division" ,,"Total Northeast" "Home Appliances Usage Indicators",,,"Middle Atlantic","New England" "Total",111.1,20.6,15.1,5.5 "Cooking Appliances" "Frequency of Hot Meals Cooked" "3 or More Times A Day",8.2,1.2,1,0.2 "2 Times A Day",24.6,4,2.7,1.2 "Once a Day",42.3,7.9,5.4,2.5 "A Few Times Each Week",27.2,6,4.8,1.2 "About Once a Week",3.9,0.6,0.5,"Q" "Less Than Once a Week",4.1,0.6,0.4,"Q"

387

Measurement of nicotine in household dust  

Science Conference Proceedings (OSTI)

An analytical method of measuring nicotine in house dust was optimized and associations among three secondhand smoking exposure markers were evaluated, i.e., nicotine concentrations of both house dust and indoor air, and the self-reported number of cigarettes smoked daily in a household. We obtained seven house dust samples from self-reported nonsmoking homes and 30 samples from smoking homes along with the information on indoor air nicotine concentrations and the number of cigarettes smoked daily from an asthma cohort study conducted by the Johns Hopkins Center for Childhood Asthma in the Urban Environment. House dust nicotine was analyzed by isotope dilution gas chromatography-mass spectrometry (GC/MS). Using our optimized method, the median concentration of nicotine in the dust of self-reported nonsmoking homes was 11.7 ng/mg while that of smoking homes was 43.4 ng/mg. We found a substantially positive association (r=0.67, P<0.0001) between house dust nicotine concentrations and the numbers of cigarettes smoked daily. Optimized analytical methods showed a feasibility to detect nicotine in house dust. Our results indicated that the measurement of nicotine in house dust can be used potentially as a marker of longer term SHS exposure.

Kim, Sungroul [Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Institute for Global Tobacco Control, 627 N. Washington Street, 2nd Floor Baltimore, MD 21205 (United States); Department of Environmental Health Sciences, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205 (United States)], E-mail: srkim@jhsph.edu; Aung, Ther; Berkeley, Emily [Department of Environmental Health Sciences, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205 (United States); Diette, Gregory B. [Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205 (United States); Department of Medicine, Johns Hopkins University School of Medicine (United States); Breysse, Patrick N. [Department of Environmental Health Sciences, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205 (United States)

2008-11-15T23:59:59.000Z

388

Appliance Standby Power and Energy Consumption in South African Households  

Open Energy Info (EERE)

Appliance Standby Power and Energy Consumption in South African Households Appliance Standby Power and Energy Consumption in South African Households Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Appliance Standby Power and Energy Consumption in South African Households Focus Area: Appliances & Equipment Topics: Policy Impacts Website: active.cput.ac.za/energy/web/DUE/DOCS/422/Paper%20-%20Shuma-Iwisi%20M. Equivalent URI: cleanenergysolutions.org/content/appliance-standby-power-and-energy-co Language: English Policies: Deployment Programs DeploymentPrograms: Technical Assistance A modified engineering model is proposed to estimate standby power and energy losses in households. The modified model accounts for the randomness of standby power and energy losses due to unpredicted user appliance operational behavior.

389

Assumptions to the Annual Energy Outlook 2000 - Household Expenditures  

Gasoline and Diesel Fuel Update (EIA)

Key Assumptions Key Assumptions The historical input data used to develop the HEM version for the AEO2000 consists of recent household survey responses, aggregated to the desired level of detail. Two surveys performed by the Energy Information Administration are included in the AEO2000 HEM database, and together these input data are used to develop a set of baseline household consumption profiles for the direct fuel expenditure analysis. These surveys are the 1997 Residential Energy Consumption Survey (RECS) and the 1991 Residential Transportation Energy Consumption Survey (RTECS). HEM uses the consumption forecast by NEMS for the residential and transportation sectors as inputs to the disaggregation algorithm that results in the direct fuel expenditure analysis. Household end-use and personal transportation service consumption are obtained by HEM from the NEMS Residential and Transportation Demand Modules. Household disposable income is adjusted with forecasts of total disposable income from the NEMS Macroeconomic Activity Module.

390

Profiling energy use in households and office spaces  

Science Conference Proceedings (OSTI)

Energy consumption is largely studied in the context of different environments, such as domestic, corporate, industrial, and public sectors. In this paper, we discuss two environments, households and office spaces, where people have an especially ...

Salman Taherian; Marcelo Pias; George Coulouris; Jon Crowcroft

2010-04-01T23:59:59.000Z

391

Household Preferences for Supporting Renewable Energy, and Barriers...  

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

Household Preferences for Supporting Renewable Energy, and Barriers to Green Power Demand Speaker(s): Ryan Wiser Date: May 9, 2002 - 12:00pm Location: Bldg. 90 Nearly 40% of the...

392

Energy Consumption of Refrigerators in Ghana - Outcomes of Household...  

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

Energy Consumption of Refrigerators in Ghana - Outcomes of Household Surveys Speaker(s): Essel Ben Hagan Date: July 12, 2007 - 12:00pm Location: 90-3122 Seminar HostPoint of...

393

Smoothing consumption across households and time : essays in development economics  

E-Print Network (OSTI)

This thesis studies two strategies that households may use to keep their consumption smooth in the face of fluctuations in income and expenses: credit (borrowing and savings) and insurance (state contingent transfers between ...

Kinnan, Cynthia Georgia

2010-01-01T23:59:59.000Z

394

A Theoretical Basis for Household Energy Conservation UsingProduct...  

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

A Theoretical Basis for Household Energy Conservation Using Product-Integrated Feedback Speaker(s): Teddy McCalley Date: October 11, 2002 - 12:00pm Location: Bldg. 90 Seminar Host...

395

Characterizing Household Plug Loads through Self-Administered Load Research  

Science Conference Proceedings (OSTI)

Household miscellaneous loads, which include consumer electronics, are the fastest growing segment of household energy use in the United States. Although the relative energy intensity of applications such as heating and cooling is declining, the DOEAnnual Energy Outlook forecasts that the intensity of residential miscellaneous end uses will increase substantially by 2030. Studies by TIAX and Ecos Consulting reveal that miscellaneous devices8212smaller devices in terms of energy draw but growing in usage8...

2009-12-09T23:59:59.000Z

396

Chapter 2. Vehicle Characteristics  

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

2. Vehicle Characteristics 2. Vehicle Characteristics Chapter 2. Vehicle Characteristics U.S. households used a fleet of nearly 157 million vehicles in 1994. Despite remarkable growth in the number of minivans and sport-utility vehicles, passenger cars continued to predominate in the residential vehicle fleet. This chapter looks at changes in the composition of the residential fleet in 1994 compared with earlier years and reviews the effect of technological changes on fuel efficiency (how efficiently a vehicle engine processes motor fuel) and fuel economy (how far a vehicle travels on a given amount of fuel). Using data unique to the Residential Transportation Energy Consumption Survey, it also explores the relationship between residential vehicle use and family income.

397

Household waste disposal in Mekelle city, Northern Ethiopia  

SciTech Connect

In many cities of developing countries, such as Mekelle (Ethiopia), waste management is poor and solid wastes are dumped along roadsides and into open areas, endangering health and attracting vermin. The effects of demographic factors, economic and social status, waste and environmental attributes on household solid waste disposal are investigated using data from household survey. Household level data are then analyzed using multinomial logit estimation to determine the factors that affect household waste disposal decision making. Results show that demographic features such as age, education and household size have an insignificant impact over the choice of alternative waste disposal means, whereas the supply of waste facilities significantly affects waste disposal choice. Inadequate supply of waste containers and longer distance to these containers increase the probability of waste dumping in open areas and roadsides relative to the use of communal containers. Higher household income decreases the probability of using open areas and roadsides as waste destinations relative to communal containers. Measures to make the process of waste disposal less costly and ensuring well functioning institutional waste management would improve proper waste disposal.

Tadesse, Tewodros [Agricultural Economics and Rural Policy Group, Wageningen University, Hollandseweg 1 6706 KN Wageningen (Netherlands)], E-mail: tewodroslog@yahoo.com; Ruijs, Arjan [Environmental Economics and Natural Resources Group, Wageningen University, P.O. Box 8130, 6700 EW Wageningen (Netherlands); Hagos, Fitsum [International Water Management Institute (IWMI), Subregional Office for the Nile Basin and East Africa, P.O. Box 5689, Addis Ababa (Ethiopia)

2008-07-01T23:59:59.000Z

398

Source separation of household waste: A case study in China  

SciTech Connect

A pilot program concerning source separation of household waste was launched in Hangzhou, capital city of Zhejiang province, China. Detailed investigations on the composition and properties of household waste in the experimental communities revealed that high water content and high percentage of food waste are the main limiting factors in the recovery of recyclables, especially paper from household waste, and the main contributors to the high cost and low efficiency of waste disposal. On the basis of the investigation, a novel source separation method, according to which household waste was classified as food waste, dry waste and harmful waste, was proposed and performed in four selected communities. In addition, a corresponding household waste management system that involves all stakeholders, a recovery system and a mechanical dehydration system for food waste were constituted to promote source separation activity. Performances and the questionnaire survey results showed that the active support and investment of a real estate company and a community residential committee play important roles in enhancing public participation and awareness of the importance of waste source separation. In comparison with the conventional mixed collection and transportation system of household waste, the established source separation and management system is cost-effective. It could be extended to the entire city and used by other cities in China as a source of reference.

Zhuang Ying; Wu Songwei; Wang Yunlong [Department of Environmental Engineering, Zhejiang University, Hangzhou 310029 (China); Wu Weixiang [Department of Environmental Engineering, Zhejiang University, Hangzhou 310029 (China)], E-mail: weixiang@zju.edu.cn; Chen Yingxu [Department of Environmental Engineering, Zhejiang University, Hangzhou 310029 (China)

2008-07-01T23:59:59.000Z

399

" Million U.S. Housing Units"  

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

3 Household Characteristics by South Census Region, 2005" 3 Household Characteristics by South Census Region, 2005" " Million U.S. Housing Units" ,,"South Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total South" "Household Characteristics",,,"South Atlantic","East South Central","West South Central" "Total",111.1,40.7,21.7,6.9,12.1 "Household Size" "1 Person",30,11.5,6.2,2.1,3.2 "2 Persons",34.8,12.5,6.5,2.1,3.9 "3 Persons",18.4,7,4,1.1,1.8 "4 Persons",15.9,5.6,2.9,1.2,1.5 "5 Persons",7.9,2.9,1.5,0.3,1.1 "6 or More Persons",4.1,1.2,0.5,"Q",0.6 "2005 Annual Household Income Category"

400

" Million U.S. Housing Units"  

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

3 Household Characteristics by Northeast Census Region, 2005" 3 Household Characteristics by Northeast Census Region, 2005" " Million U.S. Housing Units" ,,"Northeast Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total Northeast" "Household Characteristics",,,"Middle Atlantic","New England" "Total",111.1,20.6,15.1,5.5 "Household Size" "1 Person",30,5.5,3.8,1.7 "2 Persons",34.8,6.5,4.8,1.7 "3 Persons",18.4,3.4,2.4,1.1 "4 Persons",15.9,3,2.4,0.7 "5 Persons",7.9,1.4,1.2,0.2 "6 or More Persons",4.1,0.7,0.6,0.1 "2005 Annual Household Income Category" "Less than $9,999",9.9,1.9,1.4,0.5 "$10,000 to $14,999",8.5,1.8,1.4,0.4

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


401

" Million U.S. Housing Units"  

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

3 Household Characteristics by Midwest Census Region, 2005" 3 Household Characteristics by Midwest Census Region, 2005" " Million U.S. Housing Units" ,,"Midwest Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total Midwest" "Household Characteristics",,,"East North Central","West North Central" "Total",111.1,25.6,17.7,7.9 "Household Size" "1 Person",30,7.3,5,2.3 "2 Persons",34.8,8.4,5.7,2.7 "3 Persons",18.4,4.1,3,1.1 "4 Persons",15.9,3.2,2.2,1 "5 Persons",7.9,1.8,1.4,0.4 "6 or More Persons",4.1,0.7,0.4,0.3 "2005 Annual Household Income Category" "Less than $9,999",9.9,2.3,1.8,0.5 "$10,000 to $14,999",8.5,2,1.4,0.6

402

Public census data on CD-ROM at Lawrence Berkeley Laboratory  

SciTech Connect

The Comprehensive Epidemiologic Data Resource (CEDR) and Populations at Risk to Environmental Pollution (PAREP) projects, of the Information and Computing Sciences Division (ICSD) at Lawrence Berkeley Laboratory (LBL), are using public socioeconomic and geographic data files which are available to CEDR and PAREP collaborators via LBL's computing network. At this time 72 CD-ROM diskettes (approximately 37 gigabytes) are on line via the Unix file server cedrcd.lbl.gov''. Most of the files are from the US Bureau of the Census, and many of these pertain to the 1990 Census of Population and Housing. All the CD-ROM diskettes contain documentation in the form of ASCII text files. In addition, printed documentation for most files is available for inspection at University of California Data and Technical Assistance (UC DATA), tel. (510) 642-6571, or the UC Documents Library, tel. (510) 642-2569, both located on the UC Berkeley Campus. Many of the CD-ROM diskettes distributed by the Census Bureau contain software for PC compatible computers, for easily accessing the data. Shared access to the data is maintained through a collaboration among the CEDR and PAREP projects at LBL, and UC DATA, and the UC Documents Library. LBL is grateful to UC DATA and the UC Documents Library for the use of their CD-ROM diskettes. Shared access to LBL facilities may be restricted in the future if costs become prohibitive. Via the Sun Network File System (NFS), these data can be exported to Internet computers for direct access by the user's application program(s). Due to the size of the files, this access method is preferred over File Transfer Protocol (FTP) access. Please contact Deane Merrill (dwmerrill lbl.gov) if you wish to make use of the data.

Merrill, D.W.

1993-01-16T23:59:59.000Z

403

Public census data on CD-ROM at Lawrence Berkeley Laboratory. Revision 4  

SciTech Connect

The Comprehensive Epidemiologic Data Resource (CEDR) and Populations at Risk to Environmental Pollution (PAREP) projects, of the Information and Computing sciences Division (ICSD) at Lawrence Berkeley Laboratory (LBL), are using public socioeconomic and geographic data files which are available to CEDR and PAREP collaborators via LBL`s computing network. At this time 89 CD-ROM diskettes (approximately 45 gigabytes) are on line via the Unix file server cedrcd.lbl.gov. Most of the files are from the US Bureau of the Census, and many of these pertain to the 1990 Census of Population and Housing. All the CD-ROM diskettes contain documentation in the form of ASCII text files. In addition, printed documentation for most files is available for inspection at University of California Data and Technical Assistance (UC DATA), tel. (510) 642-6571, or the UC Documents Library, tel. (510) 642-2569, both located on the UC Berkeley Campus. Many of the CD-ROM diskettes distributed by the Census Bureau contain software for PC compatible computers, for easily accessing the data. Shared access to the data is maintained through a collaboration among the CEDR and PAREP projects at LBL, and UC DATA, and the UC Documents Library. LBL is grateful to UC DATA and the UC Documents Library for the use of their CD-ROM diskettes. Shared access to LBL facilities may be restricted in the future if costs become prohibitive. Via the Sun Network File System (NFS), these data can be exported to Internet computers for direct access by the user`s application program(s). Due to the size of the files, this access method is preferred over File Transfer Protocol (FTP) access.

Merrill, D.W.

1993-03-12T23:59:59.000Z

404

Public census data on CD-ROM at Lawrence Berkeley Laboratory. Revision 3  

Science Conference Proceedings (OSTI)

The Comprehensive Epidemiologic Data Resource (CEDR) and Populations at Risk to Environmental Pollution (PAREP) projects, of the Information and Computing Sciences Division (ICSD) at Lawrence Berkeley Laboratory (LBL), are using public socioeconomic and geographic data files which are available to CEDR and PAREP collaborators via LBL`s computing network. At this time 72 CD-ROM diskettes (approximately 37 gigabytes) are on line via the Unix file server ``cedrcd.lbl.gov``. Most of the files are from the US Bureau of the Census, and many of these pertain to the 1990 Census of Population and Housing. All the CD-ROM diskettes contain documentation in the form of ASCII text files. In addition, printed documentation for most files is available for inspection at University of California Data and Technical Assistance (UC DATA), tel. (510) 642-6571, or the UC Documents Library, tel. (510) 642-2569, both located on the UC Berkeley Campus. Many of the CD-ROM diskettes distributed by the Census Bureau contain software for PC compatible computers, for easily accessing the data. Shared access to the data is maintained through a collaboration among the CEDR and PAREP projects at LBL, and UC DATA, and the UC Documents Library. LBL is grateful to UC DATA and the UC Documents Library for the use of their CD-ROM diskettes. Shared access to LBL facilities may be restricted in the future if costs become prohibitive. Via the Sun Network File System (NFS), these data can be exported to Internet computers for direct access by the user`s application program(s). Due to the size of the files, this access method is preferred over File Transfer Protocol (FTP) access. Please contact Deane Merrill (dwmerrill@lbl.gov) if you wish to make use of the data.

Merrill, D.W.

1993-01-16T23:59:59.000Z

405

1992 Commercial Buildings Characteristics -- Overview/Executive Summary  

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

Overview Overview Overview Percent of Buildings and Floorspace by Census Region, 1992 Percent of Buildings and Floorspace By Census Region divider line Executive Summary Commercial Buildings Characteristics 1992 presents statistics about the number, type, and size of commercial buildings in the United States as well as their energy-related characteristics. These data are collected in the Commercial Buildings Energy Consumption Survey (CBECS), a national survey of buildings in the commercial sector. The 1992 CBECS is the fifth in a series conducted since 1979 by the Energy Information Administration. Approximately 6,600 commercial buildings were surveyed, representing the characteristics and energy consumption of 4.8 million commercial buildings and 67.9 billion square feet of commercial floorspace nationwide. Overall, the amount of commercial floorspace in the United States increased an average of 2.4 percent annually between 1989 and 1992, while the number of commercial buildings increased an average of 2.0 percent annually.

406

Residential energy consumption of low-income and elderly households: how non-discretionary is it  

SciTech Connect

The energy literature is replete with opinions that the poor and elderly have cut their residential energy consumption to a minimum. This paper challenges such conclusions through an analysis of data on a sample of 319 Decatur, Illinois homeowners. The data include utility bill histories and survey information on housing characteristics, energy-related behaviors, attitudes, and socio-economic and demographic characteristics. It shows that residential energy consumption per square foot of living space is significantly higher for the elderly and poor than for other groups of Decatur homeowners. By breaking energy use into seasonal components, the paper estimates consumption for various household uses. This information, combined with the survey data, suggests that both subgroups heat and cool their homes inefficiently, due in part to the conditions of their homes, but also due to energy-related behaviors. The public policy implications of the findings are discussed.

Brown, M.A.; Rollinson, P.A.

1984-01-01T23:59:59.000Z

407

Water Related Energy Use in Households and Cities - an Australian  

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

Water Related Energy Use in Households and Cities - an Australian Water Related Energy Use in Households and Cities - an Australian Perspective Speaker(s): Steven Kenway Date: May 12, 2011 - 12:00pm Location: 90-3122 Seminar Host/Point of Contact: Anita Estner James McMahon This presentation covers the content of recent journal papers and reports focused on the water-energy nexus and the related theory of urban metabolism. This includes (i) a review of the water-energy nexus focused on cities (ii) quantifying water-related energy in cities (iii) modeling household water-related energy use including key factors, sensitivity and uncertainty analysis, and (iv) relevance and implications of the urban metabolism theoretical framework. Steven's work focuses on understanding the indirect connections between urban water management, energy use and

408

EIA - Gasoline and Diesel Fuel report: Household Vehicles Energy  

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

1 1 Transportation logo printer-friendly version logo for Portable Document Format file Household Vehicles Energy Consumption 1991 December 1993 Release Next Update: August 1997. Based on the 1991 Residential Transportation Energy Consumption Survey conducted by the Energy Information Administration (EIA) - survey series has been discontinued after EIA's 1994 survey. Only light-duty vehicles and recreational vehicles are included in this report. EIA has excluded motorcycles, mopeds, large trucks, and buses. This report, Household Vehicles Energy Consumption 1991, is based on data from the 1991 Residential Transportation Energy Consumption Survey (RTECS). Focusing on vehicle miles traveled (VMT) and energy enduse consumption and expenditures by households for personal transportation, the 1991 RTECS is

409

Energy Consumption of Refrigerators in Ghana - Outcomes of Household  

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

Energy Consumption of Refrigerators in Ghana - Outcomes of Household Energy Consumption of Refrigerators in Ghana - Outcomes of Household Surveys Speaker(s): Essel Ben Hagan Date: July 12, 2007 - 12:00pm Location: 90-3122 Seminar Host/Point of Contact: Robert Van Buskirk Galen Barbose As part of activities to develop refrigerator efficiency standards regulations in Ghana, a national survey on the energy consumption of refrigerators and refrigerator-freezers has been conducted. The survey covered 1000 households in urban, peri-urban and rural communities in various parts of the country. The survey found that, on average, refrigerators and refrigerator-freezers in Ghana use almost three times what is allowed by minimum efficiency standards in the U.S., and a few refrigerators had energy use at levels almost ten times the U.S.

410

Assumptions to the Annual Energy Outlook 2001 - Household Expenditures  

Gasoline and Diesel Fuel Update (EIA)

Completed Copy in PDF Format Completed Copy in PDF Format Related Links Annual Energy Outlook2001 Supplemental Data to the AEO2001 NEMS Conference To Forecasting Home Page EIA Homepage Household Expenditures Module Key Assumptions The historical input data used to develop the HEM version for the AEO2001 consists of recent household survey responses, aggregated to the desired level of detail. Two surveys performed by the Energy Information Administration are included in the AEO2001 HEM database, and together these input data are used to develop a set of baseline household consumption profiles for the direct fuel expenditure analysis. These surveys are the 1997 Residential Energy Consumption Survey (RECS) and the 1991 Residential Transportation Energy Consumption Survey (RTECS). HEM uses the consumption forecast by NEMS for the residential and

411

Econometric analysis of energy use in urban households  

SciTech Connect

This article analyzes the pattern of energy carrier consumption in the residential sector of Bangalore, a major city in south India. A 1,000-household survey was used to study the type of energy carrier used by households in different income groups for different end-uses, such as cooking, water heating, and lighting. The dependence of income on the carrier utilized is established using a carrier dependence index. Using regression analysis, the index analyses the impact of different explanatory variables such as family income, family size, and price of energy carrier on consumption. The results show that income plays an important role not only in the selection of an energy carrier but also on the quantity of consumption per household. Also, a source-service matrix is prepared for Bangalore`s residential sector, which shows the disaggregation of energy consumption by the type of energy carrier and end-use.

Reddy, B.S. [Indira Gandhi Inst. of Development Research, Bombay (India)

1995-05-01T23:59:59.000Z

412

The welfare effects of raising household energy prices in Poland  

Science Conference Proceedings (OSTI)

We examine the welfare effects from increasing household energy prices in Poland. Subsidizing household energy prices, common in the transition economies, is shown to be highly regressive. The wealthy spend a larger portion of their income on energy and consume more energy in absolute terms. We therefore rule out the oft-used social welfare argument for delaying household energy price increases. Raising prices, while targeting relief to the poor through a social assistance program is the first-best response. However, if governments want to ease the adjustment, several options are open, including: in-kind transfers to the poor, vouchers, in-cash transfers, and lifeline pricing for electricity. Our simulations show that if raising prices to efficient levels is not politically feasible at present and social assistance targeting is sufficiently weak, it may be socially better to use lifeline pricing and a large price increase than an overall, but smaller, price increase.

Freund, C.L. [Columbia Univ., New York, NY (United States); Wallich, C.I. [World Bank, Washington, DC (United States)

1996-06-01T23:59:59.000Z

413

Modeling patterns of hot water use in households  

Science Conference Proceedings (OSTI)

This report presents a detailed model of hot water use patterns in individual household. The model improves upon an existing model by including the effects of four conditions that were previously unaccounted for: the absence of a clothes washer; the absence of a dishwasher; a household consisting of seniors only; and a household that does not pay for its own hot water use. Although these four conditions can significantly affect residential hot water use, and have been noted in other studies, this is the first time that they have been incorporated into a detailed model. This model allows detailed evaluation of the impact of potential efficiency standards for water heaters and other market transformation policies. 21 refs., 3 figs., 10 tabs.

Lutz, J.D.; Liu, Xiaomin; McMahon, J.E. [and others

1996-11-01T23:59:59.000Z

414

Modeling patterns of hot water use in households  

SciTech Connect

This report presents a detailed model of hot water use patterns in individual households. The model improves upon an existing model by including the effects of four conditions that were previously unaccounted for: the absence of a clothes washer; the absence of a dishwasher; a household consisting of seniors only; and a household that does not pay for its own hot water use. Although these four conditions can significantly affect residential hot water use, and have been noted in other studies, this is the first time that they have been incorporated into a detailed model. This model allows detailed evaluation of the impact of potential efficiency standards for water heaters and other market transformation policies.

Lutz, James D.; Liu, Xiaomin; McMahon, James E.; Dunham, Camilla; Shown, Leslie J.; McCure, Quandra T.

1996-01-01T23:59:59.000Z

415

Heating Degree Days, by State (Weighted by Population, per 2000 Census) |  

Open Energy Info (EERE)

66 66 Varnish cache server Browse Upload data GDR 429 Throttled (bot load) Error 429 Throttled (bot load) Throttled (bot load) Guru Meditation: XID: 2142278566 Varnish cache server Heating Degree Days, by State (Weighted by Population, per 2000 Census) Dataset Summary Description The National Oceanic and Atmospheric Administration's (NOAA) National Environmental Satellite, Data, and Information Services (NESDIS), in conjunction with the National Climatic Data Center (NCDC) publish monthly and annual climate data by state for the U.S., including, heating degree days (total number of days per month and per year). The average values for each state are weighted by population, using 2000 Census data. The base temperature for this dataset is 65 degrees F. Included here are monthly and annual values averaged over several periods of time: 1931-2000, 1931-60, 1941-70, 1951-80, 1961-90, 1971-2000 (standard deviation is also provided). Detailed monthly climatic information (including heating degree days) is available for the time period between 1895 and 2011, from NOAA (http://www7.ncdc.noaa.gov/CDO/CDODivisionalSelect.jsp#).

416

"Table HC10.7 Air-Conditioning Usage Indicators by U.S. Census Region, 2005"  

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

7 Air-Conditioning Usage Indicators by U.S. Census Region, 2005" 7 Air-Conditioning Usage Indicators by U.S. Census Region, 2005" " Million U.S. Housing Units" ,"Housing Units (millions)","U.S. Census Region" "Air Conditioning Usage Indicators",,"Northeast","Midwest","South","West" "Total",111.1,20.6,25.6,40.7,24.2 "Do Not Have Cooling Equipment",17.8,4,2.1,1.4,10.3 "Have Cooling Equipment",93.3,16.5,23.5,39.3,13.9 "Use Cooling Equipment",91.4,16.3,23.4,38.9,12.9 "Have Equipment But Do Not Use it",1.9,0.3,"Q",0.5,1 "Type of Air-Conditioning Equipment1, 2" "Central System",65.9,6,17.3,32.1,10.5 "Without a Heat Pump",53.5,5.5,16.2,23.2,8.7

417

"Table HC10.5 Space Heating Usage Indicators by U.S. Census Region, 2005"  

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

5 Space Heating Usage Indicators by U.S. Census Region, 2005" 5 Space Heating Usage Indicators by U.S. Census Region, 2005" " Million U.S. Housing Units" ,"Housing Units (millions)","U.S. Census Region" "Space Heating Usage Indicators",,"Northeast","Midwest","South","West" "Total U.S. Housing Units",111.1,20.6,25.6,40.7,24.2 "Do Not Have Heating Equipment",1.2,"Q","Q","Q",0.7 "Have Space Heating Equipment",109.8,20.5,25.6,40.3,23.4 "Use Space Heating Equipment",109.1,20.5,25.6,40.1,22.9 "Have But Do Not Use Equipment",0.8,"N","N","Q",0.6 "Space Heating Usage During 2005" "Heated Floorspace (Square Feet)"

418

Household Energy Expenditure and Income Groups: Evidence from Great Britain  

E-Print Network (OSTI)

  and  0.024  for  district heating However, as income is not observed its effect cannot be analysed.  Wu et al. (2004) examine the demand for space heating in Armenia, Moldova, and  Kyrgyz  Republic  using  household  survey  data.  In  these  countries...  and in some regions incomes are not sufficient to  afford space heating from district heating systems making these systems unviable.  We  analyse  electricity,  gas  and  overall  energy  spending  for  a  large  sample  of  households  in  Great  Britain.  We  discern  inflection  points  and  discuss...

Jamasb, Tooraj; Meier, H

419

New York Household Travel Patterns: A Comparison Analysis  

SciTech Connect

In 1969, the U. S. Department of Transportation began collecting detailed data on personal travel to address various transportation planning issues. These issues range from assessing transportation investment programs to developing new technologies to alleviate congestion. This 1969 survey was the birth of the Nationwide Personal Transportation Survey (NPTS). The survey was conducted again in 1977, 1983, 1990 and 1995. Longer-distance travel was collected in 1977 and 1995. In 2001, the survey was renamed to the National Household Travel Survey (NHTS) and collected both daily and longer-distance trips in one survey. In addition to the number of sample households that the national NPTS/NHTS survey allotted to New York State (NYS), the state procured an additional sample of households in both the 1995 and 2001 surveys. In the 1995 survey, NYS procured an addition sample of more than 9,000 households, increasing the final NY NPTS sample size to a total of 11,004 households. Again in 2001, NYS procured 12,000 additional sample households, increasing the final New York NHTS sample size to a total of 13,423 households with usable data. These additional sample households allowed NYS to address transportation planning issues pertinent to geographic areas significantly smaller than for what the national NPTS and NHTS data are intended. Specifically, these larger sample sizes enable detailed analysis of twelve individual Metropolitan Planning Organizations (MPOs). Furthermore, they allowed NYS to address trends in travel behavior over time. In this report, travel data for the entire NYS were compared to those of the rest of the country with respect to personal travel behavior and key travel determinants. The influence of New York City (NYC) data on the comparisons of the state of New York to the rest of the country was also examined. Moreover, the analysis examined the relationship between population density and travel patterns, and the similarities and differences among New York MPOs. The 1995 and 2001 survey data make it possible to examine and identify travel trends over time. This report does not address, however, the causes of the differences and/or trends.

Hu, Patricia S [ORNL; Reuscher, Tim [ORNL

2007-05-01T23:59:59.000Z

420

A Glance at China’s Household Consumption  

SciTech Connect

Known for its scale, China is the most populous country with the world’s third largest economy. In the context of rising living standards, a relatively lower share of household consumption in its GDP, a strong domestic market and globalization, China is witnessing an unavoidable increase in household consumption, related energy consumption and carbon emissions. Chinese policy decision makers and researchers are well aware of these challenges and keen to promote green lifestyles. China has developed a series of energy policies and programs, and launched a wide?range social marketing activities to promote energy conservation.

Shui, Bin

2009-10-22T23:59:59.000Z

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


421

EvoNILM: evolutionary appliance detection for miscellaneous household appliances  

Science Conference Proceedings (OSTI)

To improve the energy awareness of consumers, it is necessary to provide them with information about their energy demand, not just on the household level. Non-intrusive load monitoring (NILM) gives the consumer the opportunity to disaggregate their consumed ... Keywords: evolutionary algorithm, load disaggregation, non-intrusive load monitoring

Dominik Egarter; Wilfried Elmenreich

2013-07-01T23:59:59.000Z

422

Modelling the Energy Demand of Households in a Combined  

E-Print Network (OSTI)

. Emissions from passenger transport, households'electricity and heat consumption are growing rapidly despite demand analysis for electricity (e.g. Larsen and Nesbakken, 2004; Holtedahl and Joutz, 2004; Hondroyiannis, 2004) and passenger cars (Meyer et al., 2007). Some recent studies cover the whole residential

Steininger, Karl W.

423

Fuelwood Use by Rural Households in the Brazilian Atlantic Forest  

E-Print Network (OSTI)

Fuelwood is an important source of domestic energy in rural regions of Brazil. In the Zona da Mata of Minas Gerais, native species from the Atlantic Forest are an important source of fuelwood, supplemented by wood from eucalyptus and coffee plantations. The use of native species is complicated by their increasing scarcity and the recent enforcement of forest policies that prohibit the felling of even dead natives trees without a permit. In this study, the factors contributing to the use of fuelwood in this region, despite the simultaneous use of liquid petroleum gas in most households, are explored by examining fuelwood use patterns in four small rural communities in the Zona da Mata Mineira using household surveys and semi-structured interviews. Two hypotheses were tested using a Jacknife regression. The first hypothesis, based on the energy ladder model, tested the predictive power of socioeconomic status in relation to fuelwood use. Two dependent variables were used to represent the importance of fuelwood to a household: the amount of time a household spent collecting fuelwood (Effort) and the number of purposes a household used fuelwood for (Class of Fuelwood Use). Socioeconomic status did explain a statistically significant percentage of the variance in Effort, but not in Class of Fuelwood Use. The second hypothesis tested for a moderating effect of the availability of fuelwood on the relationship between the socioeconomic status of a household and the dependent variables. The interaction between access to fuelwood and socioeconomic status was shown to explain a significant percentage of the variance in Effort, thereby indicating that the effect of socioeconomic status on time spent collecting fuelwood depends on access to fuelwood. However, there was no statistically significant interaction found between Class of Fuelwood Use and fuelwood availability. The Atlantic Forest Policy was found to have little influence on domestic energy decisions made by surveyed households. Few research subjects had a good understanding of the basic tenets of this policy and the Forest Police do not have adequate resources to enforce the policy at this level.

Wilcox-Moore, Kellie J.

2010-05-01T23:59:59.000Z

424

When excessive perturbation goes wrong and why IPUMS-International relies instead on sampling, suppression, swapping, and other minimally harmful methods to protect privacy of census microdata  

Science Conference Proceedings (OSTI)

IPUMS-International disseminates population census microdata at no cost for 69 countries. Currently, a series of 212 samples totaling almost a half billion person records are available to researchers. Registration is required for researchers to gain ... Keywords: IPUMS-international, data dissemination, data privacy, microdata samples, population census, statistical disclosure controls

Lara Cleveland; Robert McCaa; Steven Ruggles; Matthew Sobek

2012-09-01T23:59:59.000Z

425

Using unlabeled Wi-Fi scan data to discover occupancy patterns of private households  

Science Conference Proceedings (OSTI)

This poster presents the homeset algorithm, a lightweight approach to estimate occupancy schedules of private households. The algorithm relies on the mobile phones of households' occupants to collect Wi-Fi scans. The scans are then used to determine ...

Wilhelm Kleiminger, Christian Beckel, Anind Dey, Silvia Santini

2013-11-01T23:59:59.000Z

426

California’s Immigrant Households and Public-Assistance Participation in the 1990s - Policy Brief  

E-Print Network (OSTI)

with Dependent Children (AFDC)/California Work Opportunitystate households participating in AFDC/ CalWORKs pro- grams.of noncitizen households received AFDC, compared to 4.5% of

2002-01-01T23:59:59.000Z

427

Table 1. Total Energy Consumption in U.S. Households by Origin ...  

U.S. Energy Information Administration (EIA)

Wood (million cords) ..... 21.4 19.8 0.8 0.6 0.3 19.3 Million Btu per Household3 Total Btu Consumption per Household, Fuels Used: Electricity Primary ...

428

An Analysis of the Price Elasticity of Demand for Household Appliances  

E-Print Network (OSTI)

Customers’ Choice of Appliance Efficiency Level: CombiningThe Effect of Income on Appliances in U.S. Households. U.S.Household’s Choice of Appliance Efficiency Level. Review of

Dale, Larry

2008-01-01T23:59:59.000Z

429

Measuring the energy efficiency of households: an application of frontier production function analysis  

SciTech Connect

A new method to estimate the energy efficiency of households is presented. Households are viewed as productive units organized to provide the occupants with numerous services requiring fuel as an input: house heating to achieve a desired interior temperature, lighting for recreation, etc. The focus is on the efficiency of energy use, not the demand for energy. The approach to measuring efficiency compares a group of productive units along several dimensions of input resources and service outputs. The comparison identifies a subset of units that are considered efficient because they require the least resources per unit of service provided. The efficient units form a production possibility frontier of best practice in service provision. A regression of the two sets of efficiency scores on other variables reflecting locational, dwelling unit, and occupational characteristics is performed to identify factors accounting for differences in efficiency. The results indicate that the more efficient units used electric heat, had higher ratios of non-electric to electric fuel inputs, were owner-occupied, and were built after 1974. The findings also suggest that both family life cycle and income effects account for efficiency differences.

Baxter, L.W.

1984-01-01T23:59:59.000Z

430

Housing Characteristics, 1990  

DOE Green Energy (OSTI)

This report on energy consumption in the residential sector covers the following topics: housing trends 1980--1990, new housing trends, availability and usage of natural gas by households, changes in appliance usage (refrigerators, entertainment appliances, cooking appliances, convenience appliances), age of major household appliances and equipment, household energy conservation activities, demand-side management programs, and a portrait of households using solar or wood as a source of energy.

Not Available

1992-05-14T23:59:59.000Z

431

Household Vehicles Energy Use: Latest Data and Trends - Table A04  

U.S. Energy Information Administration (EIA)

... Buildings & Industry > Transportation Surveys > Household Vehicles Energy ... U.S. Vehicles by Model ... Office of Coal, Nuclear, Electric, and Alternate ...

432

Integrating GIS and data warehousing in a Web environment: A case study of the US 1880 Census  

Science Conference Proceedings (OSTI)

While the business intelligence sector, involving data warehouses and online analytical processing (OLAP) technologies, is experiencing strong growth in the IT marketplace, relatively little attention has been devoted to the problem of utilizing such ... Keywords: Data warehousing, Historical census analysis, OLAP, Web-based GIS

R. G. Healey; J. Delve

2007-01-01T23:59:59.000Z

433

Household Vehicles Energy Use: Latest Data & Trends  

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

B B : E S T I M AT I O N M E T H O D O L O G I E S APPENDIX B A P P E N D I X B ESTIMATION METHODOLOGIES INTRODUCTION The National Household Travel Survey (NHTS) is the nation's inventory of local and long distance travel, according to the U.S. Department of Transportation. Between April 2001 and May 2002, roughly 26 thousand households 41 were interviewed about their travel, based on the use of over 53 thousand vehicles. Using confidential data collected during those interviews, coupled with EIA's retail fuel prices, external data sources of test 42 fuel economy, and internal procedures for modifying test fuel economy to on-road, in-use fuel economy, EIA has extended this inventory to include the energy used for travel, thereby continuing a data series that was discontinued by EIA in 1994. This appendix presents the methods used for each eligible sampled

434

Modeling household adoption of earthquake hazard adjustments: a longitudinal panel study of Southern California and Western Washington residents  

E-Print Network (OSTI)

This research, aimed at advancing the theory of environmental hazard adjustment processes by contrasting households from three cities in a high seismic hazard area with households from three other cities in a moderate seismic hazard area. It identified seven types of stakeholders namely, the risk area residents and their families (primary group), the news media, employers, and friends (secondary group), and federal, state, and local governments (tertiary group), and explained why they are relevant to the adoption of seismic hazard adjustments. It also addressed three key attributes� knowledge, trustworthiness, and responsibility for protection�ascribed to these multiple stakeholders and the relationships of these stakeholder attributes with risk perception, hazard intrusiveness, hazard experience, gender, resource adequacy, fatalism and hazard adjustment adoption. It was specifically concerned with the effects of nested interactions due to trust and power differentials among the seven stakeholders, with the self reported adoption of 16 earthquake protective measures at two points in time (1997 and 1999). Some of the key findings indicate that risk perception, gender, fatalism, city activity in earthquake management and demographic characteristics did not significantly predict hazard adjustment adoption. However, all stakeholder characteristics had significant positive correlations with risk perception and hazard adjustment, implying a peripheral route for social influence. Hazard intrusiveness, hazard experience, and stakeholder knowledge, trustworthiness, and responsibility affected the increased adoption of hazard adjustments by households. Particularly important are the peer groups� (employers, friends and family) knowledge, trustworthiness and responsibility. These findings suggest, hazard managers cannot count only on the federal, state, and local government advisories put out through the news media to affect community decisions and thereby households� decisions to take protective actions. Instead, hazard managers need to shift focus and work through peer group networks such as service organizations, industry groups, trade unions, neighborhood organizations, community emergency response teams, faith-based organizations, and educational institutions to increase the knowledge, trustworthiness and responsibility of all in the peer group. This will assure higher household hazard adjustment adoption levels, thus facilitating a reduction in post disaster losses and recovery time.

Arlikatti, Sudha S

2006-08-01T23:59:59.000Z

435

Energy conservation for household refrigerators and water heaters  

Science Conference Proceedings (OSTI)

An energy conservation arrangement for household refrigerators and water heaters, in which the source of cold water to the hot water heater is divided and part is caused to flow through and be warmed in the condenser of the refrigerator. The warmed water is then further heated in the oil cooling loop of the refrigerator compressor, and proceeds then to the top of the hot water tank.

Speicher, T. L.

1984-12-11T23:59:59.000Z

436

Elasticities of Electricity Demand in Urban Indian Households  

E-Print Network (OSTI)

Energy demand, and in particular electricity demand in India has been growing at a very rapid rate over the last decade. Given, current trends in population growth, industrialisation, urbanisation, modernisation and income growth, electricity consumption is expected to increase substantially in the coming decades as well. Tariff reforms could play a potentially important role as a demand side management tool in India. However, the effects of any price revisions on consumption will depend on the price elasticity of demand for electricity. In the past, electricity demand studies for India published in international journals have been based on aggregate macro data at the country or sub-national / state level. In this paper, price and income elasticities of electricity demand in the residential sector of all urban areas of India are estimated for the first time using disaggregate level survey data for over thirty thousand households. Three electricity demand functions have been estimated using monthly data for the following seasons: winter, monsoon and summer. The results show electricity demand is income and price inelastic in all three seasons, and that household, demographic and geographical variables are important in determining electricity demand, something that is not possible to determine using aggregate macro models alone. Key Words Residential electricity demand, price elasticity, income elasticity Short Title Electricity demand in Indian households Acknowledgements: The authors would like to gratefully acknowledge the National Sample Survey Organisation, Department of Statistics of the Government of India, for making available to us the unit level, household survey data. We would also like to thank Prof. Daniel Spreng for his support of our research. 2 1.

Shonali Pachauri

2002-01-01T23:59:59.000Z

437

Sizing Wind/Photovoltaic Hybrids for Households in Inner Mongolia  

DOE Green Energy (OSTI)

Approximately 140,000 wind turbines currently provide electricity to about one-third of the non-grid-connected households in Inner Mongolia. However, these households often suffer from a lack of power during the low-wind summer months. This report describes an analysis of hybrid wind/photovoltaic (PV) systems for such households. The sizing of the major components is based on a subjective trade-off between the cost of the system and the percent unmet load, as determined by the Hybrid 2 software in conjunction with a simplified time-series model. Actual resource data (wind speed and solar radiation) from the region are processed so as to best represent the scenarios of interest. Small wind turbines of both Chinese and U.S. manufacture are considered in the designs. The results indicate that combinations of wind and PV are more cost-effective than either one alone, and that the relative amount of PV in the design increases as the acceptable unmet load decreases and as the average wind sp eed decreases.

Barley, C. D.; Lew, D. J.; Flowers, L. T.

1997-06-01T23:59:59.000Z

438

,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member"  

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

1 Average Square Footage of Midwest Homes, by Housing Characteristics, 2009" 1 Average Square Footage of Midwest Homes, by Housing Characteristics, 2009" " Final" ,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member" "Housing Characteristics","Millions","Total2","Heated","Cooled","Total2","Heated","Cooled" "Total Midwest",25.9,2272,1898,1372,912,762,551 "Midwest Divisions and States" "East North Central",17.9,2251,1869,1281,892,741,508 "Illinois",4.8,2186,1911,1451,860,752,571 "Michigan",3.8,1954,1559,962,729,582,359 "Wisconsin",2.3,2605,2091,1258,1105,887,534

439

,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member"  

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

3 Average Square Footage of West Homes, by Housing Characteristics, 2009" 3 Average Square Footage of West Homes, by Housing Characteristics, 2009" " Final" ,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member" "Housing Characteristics","Millions","Total2","Heated","Cooled","Total2","Heated","Cooled" "Total West",24.8,1708,1374,800,628,506,294 "West Divisions and States" "Mountain",7.9,1928,1695,1105,723,635,415 "Mountain North",3.9,2107,1858,912,776,684,336 "Colorado",1.9,2082,1832,722,896,788,311 "Idaho, Montana, Utah, Wyoming",2,2130,1883,1093,691,610,354

440

Interracial Marriage in Brazil: a discussion about local marriage market, parents' characteristics, and household chores  

E-Print Network (OSTI)

Identity: Comparing the United States and Brazil. ” Pp.Politics in Contemporary Brazil, edited by M Hanchard and NUnmixing for Race Making in Brazil. ” American Journal of

Tomas, Maria Carolina

2012-01-01T23:59:59.000Z

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


441

"Table HC10.13 Lighting Usage Indicators by U.S. Census Region, 2005"  

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

3 Lighting Usage Indicators by U.S. Census Region, 2005" 3 Lighting Usage Indicators by U.S. Census Region, 2005" " Million U.S. Housing Units" ,"Housing Units (millions)","U.S. Census Region" "Lighting Usage Indicators",,"Northeast","Midwest","South","West" "Total U.S. Housing Units",111.1,20.6,25.6,40.7,24.2 "Indoor Lights Turned On During Summer" "Number of Lights Turned On" "Between 1 and 4 Hours per Day",91.8,16.8,21.7,33.8,19.5 "1.",28.6,5,6.3,11.2,6.1 "2.",29.5,6.2,6.5,10.5,6.3 "3.",14.7,2.5,4,5,3.1 "4.",9.3,1.5,2.5,3.4,1.9 "5 or More",9.7,1.6,2.4,3.7,2 "Energy-Efficient Bulbs Used",31.1,5.2,6.7,10.6,8.6

442

"Table HC10.10 Home Appliances Usage Indicators by U.S. Census Regions, 2005"  

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

0 Home Appliances Usage Indicators by U.S. Census Regions, 2005" 0 Home Appliances Usage Indicators by U.S. Census Regions, 2005" " Million U.S. Housing Units" ,"Housing Units (millions)","U.S. Census Region" "Home Appliances Usage Indicators",,"Northeast","Midwest","South","West" "Total",111.1,20.6,25.6,40.7,24.2 "Cooking Appliances" "Frequency of Hot Meals Cooked" "3 or More Times A Day",8.2,1.2,1.4,3,2.6 "2 Times A Day",24.6,4,5.8,8.3,6.6 "Once a Day",42.3,7.9,10.7,15,8.8 "A Few Times Each Week",27.2,6,5.6,10.9,4.7 "About Once a Week",3.9,0.6,0.9,1.6,0.7 "Less Than Once a Week",4.1,0.6,1.1,1.7,0.7 "No Hot Meals Cooked",0.9,0.3,"Q","Q",0.2

443

" Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1"  

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

6 Air Conditioning Characteristics by Household Income, 2005" 6 Air Conditioning Characteristics by Household Income, 2005" " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ,"Housing Units (millions)" ,,"Less than $20,000","$20,000 to $39,999","$40,000 to $59,999","$60,000 to $79,999","$80,000 or More" "Air Conditioning Characteristics" "Total",111.1,26.7,28.8,20.6,13.1,22,16.6,38.6 "Do Not Have Cooling Equipment",17.8,5.3,4.7,2.8,1.9,3.1,3.6,7.5 "Have Cooling Equipment",93.3,21.5,24.1,17.8,11.2,18.8,13,31.1 "Use Cooling Equipment",91.4,21,23.5,17.4,11,18.6,12.6,30.3 "Have Equipment But Do Not Use it",1.9,0.5,0.6,0.4,"Q","Q",0.5,0.8

444

Microsoft Word - 20050821_Appendix_A.doc  

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

9. U.S. Average Vehicle-Miles Traveled by EIA Household Composition 9. U.S. Average Vehicle-Miles Traveled by EIA Household Composition 1 , 2001 (Thousand Miles per Household) ENERGY INFORMATION ADMINISTRATION / HOUSEHOLD VEHICLES ENERGY USE: LATEST A N D TRENDS 118 Households With Children Households Without Children Age of Oldest Child One Adult--Age of Householder Two or More Adults--Age of Householder 2001 Household Characteristics Total Under 7 Years 7 to 15 Years 16 or 17 Years Total Under 35 Years 35 to 59 Years 60 Years or Over Under 35 Years 35 to 59 Years 60 Years or Over Household Characteristics Total.............................. 29.0 27.0 28.3 34.1 19.6 14.5 13.8 8.1 28.1 27.9 18.6 Census Region and Division

445

Indoor Secondary Pollutants from Household Product Emissions in the  

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

Indoor Secondary Pollutants from Household Product Emissions in the Indoor Secondary Pollutants from Household Product Emissions in the Presence of Ozone: A Bench-Scale Chamber Study Title Indoor Secondary Pollutants from Household Product Emissions in the Presence of Ozone: A Bench-Scale Chamber Study Publication Type Journal Article LBNL Report Number LBNL-58785 Year of Publication 2006 Authors Destaillats, Hugo, Melissa M. Lunden, Brett C. Singer, Beverly K. Coleman, Alfred T. Hodgson, Charles J. Weschler, and William W. Nazaroff Journal Environmental Science and Technology Volume 40 Start Page Chapter Pagination 4421-4428 Abstract Ozone-driven chemistry is a major source of indoor secondary pollutants of health concern. This study investigates secondary air pollutants formed from reactions between constituents of household products and ozone. Gas-phase product emissions were introduced along with ozone at constant rates into a 198-L Teflon-lined reaction chamber. Gas-phase concentrations of reactive terpenoids and oxidation products were measured. Formaldehyde was a predominant oxidation byproduct for the three studied products, with yields under most conditions of 20-30% with respect to ozone consumed. Acetaldehyde, acetone, glycolaldehyde, formic acid and acetic acid were each also detected for two or three of the products. Immediately upon mixing of reactants, a scanning mobility particle sizer detected particle nucleation events that were followed by a significant degree of ultrafine particle growth. The production of secondary gaseous pollutants and particles depended primarily on the ozone level and was influenced by other parameters such as the air-exchange rate. Hydroxyl radical concentrations in the range 0.04-200 Ă— 105 molecules cm-3 were measured. OH concentrations were observed to vary strongly with residual ozone level in the chamber, which was in the range 1 - 25 ppb, as is consistent with expectations from a simplified kinetic model. In a separate test, we exposed the dry residue of two products to ozone in the chamber and observed the formation of gas-phase and particle-phase secondary oxidation products

446

Vehicle Technologies Office: Fact #301: January 5, 2004 Number of Household  

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

1: January 5, 1: January 5, 2004 Number of Household Vehicles has Grown Significantly to someone by E-mail Share Vehicle Technologies Office: Fact #301: January 5, 2004 Number of Household Vehicles has Grown Significantly on Facebook Tweet about Vehicle Technologies Office: Fact #301: January 5, 2004 Number of Household Vehicles has Grown Significantly on Twitter Bookmark Vehicle Technologies Office: Fact #301: January 5, 2004 Number of Household Vehicles has Grown Significantly on Google Bookmark Vehicle Technologies Office: Fact #301: January 5, 2004 Number of Household Vehicles has Grown Significantly on Delicious Rank Vehicle Technologies Office: Fact #301: January 5, 2004 Number of Household Vehicles has Grown Significantly on Digg Find More places to share Vehicle Technologies Office: Fact #301:

447

Exemplifying Business Opportunities for Improving Data Quality From Corporate Household Research  

E-Print Network (OSTI)

Corporate household (CHH) refers to the organizational information about the structure within the corporation and a variety of inter-organizational relationships. Knowledge derived from this data is ...

Madnick, Stuart

2004-12-10T23:59:59.000Z

448

U.S. households forecast to use more heating fuels this ...  

U.S. Energy Information Administration (EIA)

What is the role of coal in the United States? ... 2012 U.S. households ... many located in rural areas. Propane inventories totaled almost 76 million ...

449

Methodology and Estimation of the Welfare Impact of Energy Reforms on Households in Azerbaijan.  

E-Print Network (OSTI)

??ABSTRACT Title of Dissertation: METHODOLOGY AND ESTIMATION OF THE WELFARE IMPACT OF ENERGY REFORMS ON HOUSEHOLDS IN AZERBAIJAN Irina Klytchnikova, Doctor of Philosophy, 2006 Dissertation… (more)

Klytchnikova, Irina

2006-01-01T23:59:59.000Z

450

Table CE1-4c. Total Energy Consumption in U.S. Households by Type ...  

U.S. Energy Information Administration (EIA)

Total Energy Consumption in U.S. Households by Type of Housing Unit, 2001 RSE Column Factor: Total ... where the end use is electric air-conditioning, ...

451

The Other Energy Crisis: Managing Urban Household Energy Use in Senegal  

E-Print Network (OSTI)

for 62 percent of national energy consumption, or over 1 .1energy consumption, and (2) residential, because of the dominant role that households play in national

Leitmann, Josef

1989-01-01T23:59:59.000Z

452

Table HC6.7 Air-Conditioning Usage Indicators by Number of Household...  

Gasoline and Diesel Fuel Update (EIA)

7 Air-Conditioning Usage Indicators by Number of Household Members, 2005 Total... 111.1 30.0 34.8 18.4 15.9...

453

Table 1. Consumption and Expenditures in U.S. Households, 1997  

U.S. Energy Information Administration (EIA)

A household is assigned to a climate zone according to the 30-year average annual degree-days for an appropriate nearby weather station. (5) ...

454

In the UNITED STATES there are 96.6 million households  

U.S. Energy Information Administration (EIA)

In the UNITED STATES there are 96.6 million households 69% are single-family homes; 25% are apartments; and 6% are mobile homes. Housing stock is ...

455

Table 1. Total Energy Consumption in U.S. Households by ...  

U.S. Energy Information Administration (EIA)

This write-up presents 1997 Residential Energy Consumption and Expenditures by Origin of Householder. In 1997, there were 101.5 million residential ho ...

456

Table WH2. Total Households by Water Heating Fuels Used, 2005 ...  

U.S. Energy Information Administration (EIA)

Total Households by Water Heating Fuels Used, 2005 ... 2005 Residential Energy Consumption Survey: Energy Consumption and Expenditures Tables. Table WH2.

457

Table CE1-7c. Total Energy Consumption in U.S. Households by Four ...  

U.S. Energy Information Administration (EIA)

Other Appliances and Lighting ... It does include the small number of households where the fuel for central air-conditioning equipment was something other than ...

458

Household Vehicles Energy Use: Latest Data and Trends - Table A01  

U.S. Energy Information Administration (EIA)

U.S. Per Household Vehicle-Miles Traveled ... and Alternate Fuels, Form EIA-826, "Monthly Electric Utility Sales and Revenue Report with State Distributions."

459

Testing Electric Vehicle Demand in "Hybrid Households" Using a Reflexive Survey  

E-Print Network (OSTI)

In contrast to a hybrid vehicle whichcombines multiple1994) "Demand Electric Vehicles in Hybrid for Households:or 180 mile hybrid electric vehicle. Natural gas vehicles (

Kurani, Kenneth S.; Turrentine, Thomas; Sperling, Daniel

2001-01-01T23:59:59.000Z

460

The impact of physical planning policy on household energy use and greenhouse emissions .  

E-Print Network (OSTI)

??This thesis investigates the impact of physical planning policy on combined transport and dwelling-related energy use by households. Separate analyses and reviews are conducted into… (more)

Rickwood, Peter

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


461

Table AP1. Total Households Using Home Appliances and Lighting by ...  

U.S. Energy Information Administration (EIA)

Total Consumption for Home Appliances and Lighting by Fuels Used, 2005 Quadrillion British Thermal Units (Btu) U.S. Households (millions) Electricity

462

Table SH2. Total Households by Space Heating Fuels Used, 2005 ...  

U.S. Energy Information Administration (EIA)

Total Households by Space Heating Fuels Used, 2005 ... 2005 Residential Energy Consumption Survey: ... Electricity Natural Gas Fuel Oil Kerosene LPG Other

463

Table 2. Fuel Oil Consumption and Expeditures in U.S. Households ...  

U.S. Energy Information Administration (EIA)

Fuel Oil Consumption and Expeditures in U.S. Households ... Space Heating - Main or Secondary ... Forms EIA-457 A-G of the 2001 Residential Energy Consumption

464

Effect of Income on Appliances in U.S. Households, The  

Reports and Publications (EIA)

This web page page entails how people live, the factors that cause the most differences in home lifestyle, including energy use in Geographic Location, Socioeconomics and Household Income.

Michael Laurence

2004-01-01T23:59:59.000Z

465

U.S. household expenditures for gasoline account for nearly 4% of ...  

U.S. Energy Information Administration (EIA)

Electricity. Sales, revenue and prices, power plants, fuel use, ... a rise in average gasoline prices has led to higher overall household gasoline expenditures.

466

Assessing the Environmental Costs and Benefits of Households Electricity Consumption Management.  

E-Print Network (OSTI)

?? In this study the environmental costs and benefits of smart metering technology systems installed in households in Norway have been assessed. Smart metering technology… (more)

Segtnan, Ida Lund

2011-01-01T23:59:59.000Z

467

Material World: Forecasting Household Appliance Ownership in a Growing Global Economy  

E-Print Network (OSTI)

and V. Letschert (2005). Forecasting Electricity Demand in8364 Material World: Forecasting Household ApplianceMcNeil, 2008). Forecasting Diffusion Forecasting Variables

Letschert, Virginie

2010-01-01T23:59:59.000Z

468

An Analysis of the Price Elasticity of Demand for Household Appliances  

E-Print Network (OSTI)

Refrigerators Clothes Washers Dishwashers Economic VariablesWASHERS, AND DISHWASHERS……………………………3 Physical Household andclothes washers and dishwashers. In the context of

Dale, Larry

2008-01-01T23:59:59.000Z

469

Table 3. Total Energy Consumption in U.S. Households by ...  

U.S. Energy Information Administration (EIA)

This write-up presents 1997 Residential Energy Consumption and Expenditures by Origin of Householder. In 1997, there were 101.5 million residential ...

470

U.S. household expenditures for gasoline account for nearly 4% ...  

U.S. Energy Information Administration (EIA)

Gasoline expenditures in 2012 for the average U.S. household reached $2,912, or just under 4% of income before taxes, according to EIA estimates.

471

An analysis of residential energy consumption and expenditures by minority households by home type and housing vintage  

SciTech Connect

In this paper a descriptive analysis of the relationship between energy consumption, patterns of energy use, and housing stock variables is presented. The purpose of the analysis is to uncover evidence of variations in energy consumption and expenditures, and patterns of energy use between majority households (defines as households with neither a black nor Hispanic head of household), black households (defined as households with a black head of household), and Hispanic households (defined as households with a Hispanic head of household) between 1980 (time of the first DOE/EIA Residential Energy Consumption Survey, 1982a) and 1987 (time of the last DOE/EIA Residential Energy Consumption Survey, 1989a). The analysis is three-dimensional: energy consumption and expenditures are presented by time (1980 to 1987), housing vintage, and housing type. A comparative analysis of changes in energy variables for the three population groups -- majority, black, and Hispanic -- within and between specific housing stock categories is presented.

Poyer, D.A.

1992-01-01T23:59:59.000Z

472

An analysis of residential energy consumption and expenditures by minority households by home type and housing vintage  

SciTech Connect

In this paper a descriptive analysis of the relationship between energy consumption, patterns of energy use, and housing stock variables is presented. The purpose of the analysis is to uncover evidence of variations in energy consumption and expenditures, and patterns of energy use between majority households (defines as households with neither a black nor Hispanic head of household), black households (defined as households with a black head of household), and Hispanic households (defined as households with a Hispanic head of household) between 1980 (time of the first DOE/EIA Residential Energy Consumption Survey, 1982a) and 1987 (time of the last DOE/EIA Residential Energy Consumption Survey, 1989a). The analysis is three-dimensional: energy consumption and expenditures are presented by time (1980 to 1987), housing vintage, and housing type. A comparative analysis of changes in energy variables for the three population groups -- majority, black, and Hispanic -- within and between specific housing stock categories is presented.

Poyer, D.A.

1992-06-01T23:59:59.000Z

473

THE BARYON CENSUS IN A MULTIPHASE INTERGALACTIC MEDIUM: 30% OF THE BARYONS MAY STILL BE MISSING  

Science Conference Proceedings (OSTI)

Although galaxies, groups, and clusters contain {approx}10% of the baryons, many more reside in the photoionized and shocked-heated intergalactic medium (IGM) and in the circumgalactic medium (CGM). We update the baryon census in the (H I) Ly{alpha} forest and warm-hot IGM (WHIM) at 10{sup 5-6} K traced by O VI {lambda}1032, 1038 absorption. From Enzo cosmological simulations of heating, cooling, and metal transport, we improve the H I and O VI baryon surveys using spatially averaged corrections for metallicity (Z/Z {sub Sun }) and ionization fractions (f {sub HI}, f {sub OVI}). Statistically, the O VI correction product correlates with column density, (Z/Z {sub Sun })f {sub OVI} Almost-Equal-To (0.015)(N {sub OVI}/10{sup 14} cm{sup -2}){sup 0.70}, with an N {sub OVI}-weighted mean of 0.01, which doubles previous estimates of WHIM baryon content. We also update the Ly{alpha} forest contribution to baryon density out to z = 0.4, correcting for the (1 + z){sup 3} increase in absorber density, the (1 + z){sup 4.4} rise in photoionizing background, and cosmological proper length dl/dz. We find substantial baryon fractions in the photoionized Ly{alpha} forest (28% {+-} 11%) and WHIM traced by O VI and broad-Ly{alpha} absorbers (25% {+-} 8%). The collapsed phase (galaxies, groups, clusters, CGM) contains 18% {+-} 4%, leaving an apparent baryon shortfall of 29% {+-} 13%. Our simulations suggest that {approx}15% reside in hotter WHIM (T {>=} 10{sup 6} K). Additional baryons could be detected in weaker Ly{alpha} and O VI absorbers. Further progress requires higher-precision baryon surveys of weak absorbers, down to minimum column densities N {sub HI} {>=} 10{sup 12.0} cm{sup -2}, N {sub OVI} {>=} 10{sup 12.5} cm{sup -2}, N {sub OVII} {>=} 10{sup 14.5} cm{sup -2}, using high signal-to-noise data from high-resolution UV and X-ray spectrographs.

Shull, J. Michael; Danforth, Charles W.; Smith, Britton D., E-mail: michael.shull@colorado.edu, E-mail: smit1685@msu.edu, E-mail: charles.danforth@colorado.edu [CASA, Department of Astrophysical and Planetary Sciences, University of Colorado, Boulder, CO 80309 (United States)

2012-11-01T23:59:59.000Z

474

Users and households appliances: design suggestions for a better, sustainable interaction  

Science Conference Proceedings (OSTI)

The Human Machine Interaction has a big role in the user approach with households appliances. During the main phase (the use one), users are called to manage energy choices, often without available efficient information regarding the best behavior they ... Keywords: energy saving, households appliances, interaction design, interfaces, sustainability

Anna Zandanel

2011-09-01T23:59:59.000Z

475

A Comprehensive Model for Evaluation of Carbon Footprint and Greenhouse Gages Emission in Household Biogas Plants  

Science Conference Proceedings (OSTI)

Based on Life Cycle Assessment and other related methods, this paper introduced a comprehensive model for the evaluation of the carbon footprint and greenhouse gases emission in household biogas plants including nearly all the processes of the household ... Keywords: Biogas Plant, Carbon Footprint, Life Cycle, Greenhouse Gas

Jie Zhou; Shubiao Wu; Wanqin Zhang; Changle Pang; Baozhi Wang; Renjie Dong; Li Chen

2012-07-01T23:59:59.000Z

476

An examination of how households share and coordinate the completion of errands  

Science Conference Proceedings (OSTI)

People often complete tasks and to-dos not only for themselves but also for others in their household. In this work, we examine how household members share and accomplish errands both individually and together. We conducted a three-week diary study with ... Keywords: cooperative errands, coordination, families, roommates

Timothy Sohn; Lorikeet Lee; Stephanie Zhang; David Dearman; Khai Truong

2012-02-01T23:59:59.000Z

477

A spotlight on security and privacy risks with future household robots: attacks and lessons  

Science Conference Proceedings (OSTI)

Future homes will be populated with large numbers of robots with diverse functionalities, ranging from chore robots to elder care robots to entertainment robots. While household robots will offer numerous benefits, they also have the potential to introduce ... Keywords: cyber-physical systems, domestic robots, household robots, multi-robot attack, privacy, robots, security, single-robot attack, ubiquitous robots

Tamara Denning; Cynthia Matuszek; Karl Koscher; Joshua R. Smith; Tadayoshi Kohno

2009-09-01T23:59:59.000Z

478

A Census of Mid-Infrared Selected Active Galactic Nuclei in Massive Galaxy Clusters at 0 < z < 1.3  

E-Print Network (OSTI)

We conduct a deep mid-infrared census of nine massive galaxy clusters at (0 = 3 sigma level, we identify 12 that host mid-infrared selected active galactic nuclei (IR-AGN). To compare the IR-AGN across our redshift range, we define two complete samples of cluster galaxies: (1) optically-selected members with rest-frame VAB magnitude 0.5 Mpc) and are hosted by highly morphologically disturbed members. Although our sample is limited, our results suggest that f_IR-AGN in massive galaxy clusters is not strongly correlated with star formation at z 1.

Tomczak, Adam 1987-

2012-12-01T23:59:59.000Z

479

Household Vehicles Energy Use: Latest Data & Trends  

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

C C : Q U A L I T Y O F T H E D ATA APPENDIX C A P P E N D I X C QUALITY OF THE DATA INTRODUCTION This section discusses several issues relating to the quality of the National Household Travel Survey (NHTS) data and to the interpretation of conclusions based on these data. In particular, the focus of our discussion is on the quality of specific data items, such as the fuel economy and fuel type, that were imputed to the NHTS via a cold-decking imputation procedure. This imputation procedure used vehicle-level information from the NHTSA Corporate Average Fuel Economy files for model year's 1978 through 2001. It is nearly impossible to quantify directly the quality of this imputation procedure because NHTS does not collect the necessary fuel economy information for comparison. At best, we have indirect evidence on the quality of our

480

Load Component Database of Household Appliances and Small Office Equipment  

Science Conference Proceedings (OSTI)

This paper discusses the development of a load component database for household appliances and office equipment. To develop more accurate load models at both transmission and distribution level, a better understanding on the individual behaviors of home appliances and office equipment under power system voltage and frequency variations becomes more and more critical. Bonneville Power Administration (BPA) has begun a series of voltage and frequency tests against home appliances and office equipments since 2005. Since 2006, Researchers at Pacific Northwest National Laboratory has collaborated with BPA personnel and developed a load component database based on these appliance testing results to facilitate the load model validation work for the Western Electricity Coordinating Council (WECC). In this paper, the testing procedure and testing results are first presented. The load model parameters are then derived and grouped. Recommendations are given for aggregating the individual appliance models to feeder level, the models of which are used for distribution and transmission level studies.

Lu, Ning; Xie, YuLong; Huang, Zhenyu; Puyleart, Francis; Yang, Steve

2008-07-24T23:59:59.000Z

Note: This page contains sample records for the topic "household characteristics census" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
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481

How Do You Encourage Everyone in Your Household to Save Energy? |  

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

Do You Encourage Everyone in Your Household to Save Energy? Do You Encourage Everyone in Your Household to Save Energy? How Do You Encourage Everyone in Your Household to Save Energy? June 18, 2009 - 5:25pm Addthis Anyone who has decided to save energy at home knows that the entire household needs to be involved if you really want to see savings. Some people-be they roommates, spouses, children, or maybe even yourself-just seem to need some extra reminders to take simple energy-saving steps. How do you encourage everyone in your household to save energy? Each Thursday, you have the chance to share your thoughts on a topic related to energy efficiency or renewable energy for consumers. Please comment with your answers, and also feel free to respond to other comments. Addthis Related Articles How Have You Helped Someone Else Save Energy?

482

How Do You Encourage Everyone in Your Household to Save Energy? |  

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

Everyone in Your Household to Save Energy? Everyone in Your Household to Save Energy? How Do You Encourage Everyone in Your Household to Save Energy? June 18, 2009 - 5:25pm Addthis Anyone who has decided to save energy at home knows that the entire household needs to be involved if you really want to see savings. Some people-be they roommates, spouses, children, or maybe even yourself-just seem to need some extra reminders to take simple energy-saving steps. How do you encourage everyone in your household to save energy? Each Thursday, you have the chance to share your thoughts on a topic related to energy efficiency or renewable energy for consumers. Please comment with your answers, and also feel free to respond to other comments. Addthis Related Articles How Have You Helped Someone Else Save Energy?

483

Household energy handbook: an interim guide and reference manual. World Bank technical paper  

SciTech Connect

A standard framework for measuring and assessing technical information on the household energy sector in developing countries is needed. The handbook is intended as a first step toward creating such a framework. Chapter I discusses energy terms and principles underlying the energy units, definitions, and calculations presented in the following chapters. Chapter II describes household consumption patterns and their relationship to income, location, and household-size variables. Chapter III evaluates energy end uses and the technologies that provide cooking, lighting, refrigeration, and space-heating services. Chapter IV examines household energy resources and supplies, focusing on traditional biomass fuels. Finally, Chapter V demonstrates simple assessment methods and presents case studies to illustrate how household energy data can be used in different types of assessments.

Leach, G.; Gowen, M.

1987-01-01T23:59:59.000Z

484

Microsoft Word - 20050821_Appendix_A.doc  

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

8. U.S. Vehicles by EIA Household Composition 8. U.S. Vehicles by EIA Household Composition 1 , 2001 (Million Vehicles) ENERGY INFORMATION ADMINISTRATION / HOUSEHOLD VEHICLES ENERGY USE: LATEST A N D TRENDS 114 Households With Children Households Without Children Age of Oldest Child One Adult--Age of Householder Two or More Adults--Age of Householder 2001 Household and Vehicle Characteristics Total Under 7 Years 7 to 15 Years 16 or 17 Years Total Under 35 Years 35 to 59 Years 60 Years or Over Under 35 Years 35 to 59 Years 60 Years or Over Household Characteristics Total.............................. 79.8 20.0 41.5 18.2 111.2 3.7 11.5 11.4 13.4 41.0 30.3 Census Region and Division Northeast......................... 13.4 3.4 7.0

485

"Table HC11.5 Space Heating Usage Indicators by Northeast Census...  

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

"No",54.7,9.8,6.7,3 "Housing Unit Characteristics Affecting Usage" "Adequacy of Insulation" "Well Insulated",42.8,8.2,5.9,2.3 "Adequately Insulated",46.3,8.1,6.1,2 "Poorly...

486

Housing Characteristics, 1990. [Contains glossary  

DOE Green Energy (OSTI)

This report on energy consumption in the residential sector covers the following topics: housing trends 1980--1990, new housing trends, availability and usage of natural gas by households, changes in appliance usage (refrigerators, entertainment appliances, cooking appliances, convenience appliances), age of major household appliances and equipment, household energy conservation activities, demand-side management programs, and a portrait of households using solar or wood as a source of energy.

Not Available

1992-05-14T23:59:59.000Z

487

Household Projection and Its Application to Health/Long-Term Care Expenditures in Japan Using INAHSIM-II  

Science Conference Proceedings (OSTI)

Using a microsimulation model named Integrated Analytical Model for Household Simulation (INAHSIM), the author conducted a household projection in Japan for the period of 2010â??2050. INAHSIM-II specifically means that the initial population is ... Keywords: dynamic micro simulation, health expenditure, household projection, initial population, long-term care expenditure, transition probabilities

Tetsuo Fukawa

2011-02-01T23:59:59.000Z

488

Commercial viability of hybrid vehicles : best household use and cross national considerations.  

DOE Green Energy (OSTI)

Japanese automakers have introduced hybrid passenger cars in Japan and will soon do so in the US. In this paper, we report how we used early computer simulation model results to compare the commercial viability of a hypothetical near-term (next decade) hybrid mid-size passenger car configuration under varying fuel price and driving patterns. The fuel prices and driving patterns evaluated are designed to span likely values for major OECD nations. Two types of models are used. One allows the ''design'' of a hybrid to a specified set of performance requirements and the prediction of fuel economy under a number of possible driving patterns (called driving cycles). Another provides an estimate of the incremental cost of the hybrid in comparison to a comparably performing conventional vehicle. In this paper, the models are applied to predict the NPV cost of conventional gasoline-fueled vehicles vs. parallel hybrid vehicles. The parallel hybrids are assumed to (1) be produced at high volume, (2) use nickel metal hydride battery packs, and (3) have high-strength steel bodies. The conventional vehicle also is assumed to have a high-strength steel body. The simulated vehicles are held constant in many respects, including 0-60 time, engine type, aerodynamic drag coefficient, tire rolling resistance, and frontal area. The hybrids analyzed use the minimum size battery pack and motor to meet specified 0-60 times. A key characteristic affecting commercial viability is noted and quantified: that hybrids achieve the most pronounced fuel economy increase (best use) in slow, average-speed, stop-and-go driving, but when households consistently drive these vehicles under these conditions, they tend to travel fewer miles than average vehicles. We find that hours driven is a more valuable measure than miles. Estimates are developed concerning hours of use of household vehicles versus driving cycle, and the pattern of minimum NPV incremental cost (or benefit) of selecting the hybrid over the conventional vehicle at various fuel prices is illustrated. These results are based on data from various OECD motions on fuel price, annual miles of travel per vehicle, and driving cycles assumed to be applicable in those nations. Scatter in results plotted as a function of average speed, related to details of driving cycles and the vehicles selected for analysis, is discussed.

Santini, D. J.; Vyas, A. D.

1999-07-16T23:59:59.000Z

489

The Determinants of Homeonwership in Presence of Shocks Experienced by Mexican Households  

E-Print Network (OSTI)

Homeownership is both an individual and society objective, because of the positive neighborhood effects associated with areas of higher homeownership. To help realize these positive effects, the Mexican government has several programs directed to increasing homeownership. Many factors, however, may influence homeownership including shocks experienced by households. Shocks such as death in family, illness or accidents, unemployment, and business, crop, or livestock loss affect homeownership if households are unable to cushion the impact of the shock. Government income support programs, however, may help cushion the effect of a shock. The main objective is to determine how shocks that households’ experience and government income support programs influence homeownership in Mexico. A secondary objective is to determine how socio-demographic variables influence homeownership in Mexico. Based on the Random Utility Model, logit models of homeownership are estimated using data are from the 2002 Mexican National Survey on Living Levels of Households. Two models are estimated; with and without income. Income is excluded because of a large number of households that did not report income. Generally, inferences from the two models are similar. Homeownership appears to not be affected by shocks experienced by households. It appears households are able to cushion the impact of shocks. The two income support programs, the Program of Direct Rural Support of Mexico (PROGRESA) and the Program of Direct Rural Support of Mexico (PROCAMPO), appear to be increasing homeownership. These social welfare programs provide cash transfers to households. For whatever reason, PROGRESA has a larger effect on homeownership than PROCAMPO. Households with older heads have a larger probability of being a homeowner than households with younger heads. No statistically significance relationship exists between education and homeownership. Regional differences are seen in homeownership, with households located in the northwest region having a higher probability of homeownership than other regions. Differences in the significance of variable representing the household head’s gender, marital status, and occupation on homeownership exist between logit models that include and do not include current income. The most likely reason for these differences is interactions between the variables and a wealth effect.

Lopez Cabrera, Jesus 1977-

2012-12-01T23:59:59.000Z

490

Special Topics on Energy Use in Household Transportation  

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

Home Page Welcome to the Energy Information Administration's Residential Transportation Energy Consumption Home Page. If you need assistance in viewing this page, please call (202) 586-8800 Home Page Welcome to the Energy Information Administration's Residential Transportation Energy Consumption Home Page. If you need assistance in viewing this page, please call (202) 586-8800 Home > Transportation Home Page > Special Topics Special Topics Change in Method for Estimating Fuel Economy for the 1988 and subsequent RTECS (Released 09/12/2000) Can Household Members Accurately Report How Many Miles Their Vehicles Are Driven? (Released 08/03/2000) Calculate your Regional Gasoline Costs of Driving using the “Transportation Calculator” updated for new model years! Choose your car or SUV and see the gasoline part of the cost of driving in various parts of the country using EIA's current weekly prices. This application uses DOE/EPA's Fuel Economy Guide to set the MPG, but you can change it to compare your estimate of your car's mpg to the average of everyone else who takes the test. (Released 04/11/2000; Updated Yearly for Fuel Economies and Weekly for Fuel Prices)

491

Household appliance choice: revision of REEPS behavioral models. Final report  

Science Conference Proceedings (OSTI)

This report describes the analysis of household decisions to install space heating, central cooling, and water heating in new housing as well as decisions to own freezers and second refrigerators. This analysis was conducted as part of the enhancements to the Residential End-Use Energy Planning System (REEPS) under EPRI project RP1918-1. The empirical models used in this analysis were the multinomial logit and its generalization the nested logit. The choice model parameters were estimated statistically on national and regional survey data. The results show that capital and operating costs are significant determinants of appliance market penetrations, and the relative magnitudes of the cost coefficients imply discount rates ranging from 3.4 to twenty-one percent. Several tests were conducted to examine the temporal and geographical stability of the key parameters. The estimated parameters have been incorporated into the REEPS computer code. The revised version of REEPS is now available on a limited release basis to EPRI member utilities for testing on their system.

Goett, A.A.

1984-02-01T23:59:59.000Z

492

A Reliable Natural Language Interface to Household Appliances  

E-Print Network (OSTI)

“I have always wished that my computer would be as easy to use as my telephone. My wish has come true. I no longer know how to use my telephone.” – Bjarne Stroustrop (originator of C++) As household appliances grow in complexity and sophistication, they become harder and harder to use, particularly because of their tiny display screens and limited keyboards. This paper describes a strategy for building natural language interfaces to appliances that circumvents these problems. Our approach leverages decades of research on planning and natural language interfaces to databases by reducing the appliance problem to the database problem; the reduction provably maintains desirable properties of the database interface. The paper goes on to describe the implementation and evaluation of the EXACT interface to appliances, which is based on this reduction. EXACT maps each English user request to an SQL query, which is transformed to create a PDDL goal, and uses the Blackbox planner [13] to map the planning problem to a sequence of appliance commands that satisfy the original request. Both theoretical arguments and experimental evaluation show that EXACT is highly reliable.

Alexander Yates

2003-01-01T23:59:59.000Z

493

Laboratory Testing of Demand-Response Enabled Household Appliances  

SciTech Connect

With the advent of the Advanced Metering Infrastructure (AMI) systems capable of two-way communications between the utility's grid and the building, there has been significant effort in the Automated Home Energy Management (AHEM) industry to develop capabilities that allow residential building systems to respond to utility demand events by temporarily reducing their electricity usage. Major appliance manufacturers are following suit by developing Home Area Network (HAN)-tied appliance suites that can take signals from the home's 'smart meter,' a.k.a. AMI meter, and adjust their run cycles accordingly. There are numerous strategies that can be employed by household appliances to respond to demand-side management opportunities, and they could result in substantial reductions in electricity bills for the residents depending on the pricing structures used by the utilities to incent these types of responses.The first step to quantifying these end effects is to test these systems and their responses in simulated demand-response (DR) conditions while monitoring energy use and overall system performance.

Sparn, B.; Jin, X.; Earle, L.

2013-10-01T23:59:59.000Z

494

"Table HC13.5 Space Heating Usage Indicators by South Census...  

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

No",54.7,20.9,11.3,3.6,6 "Housing Unit Characteristics Affecting Usage" "Adequacy of Insulation" "Well Insulated",42.8,16.1,9.1,2.5,4.5 "Adequately Insulated",46.3,17,9.1,3.2,4.7...

495

"Table HC10.5 Space Heating Usage Indicators by U.S. Census...  

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

,54.7,9.8,12.9,20.9,11.2 "Housing Unit Characteristics Affecting Usage" "Adequacy of Insulation" "Well Insulated",42.8,8.2,10.6,16.1,7.9 "Adequately Insulated",46.3,8.1,10.6,17,10....

496

"Table HC12.5 Space Heating Usage Indicators by Midwest Census...  

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

"No",54.7,12.9,9.1,3.7 "Housing Unit Characteristics Affecting Usage" "Adequacy of Insulation" "Well Insulated",42.8,10.6,7.2,3.4 "Adequately Insulated",46.3,10.6,7.5,3.1 "Poorly...

497

"Table HC14.5 Space Heating Usage Indicators by West Census...  

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

"No",54.7,11.2,3.4,7.8 "Housing Unit Characteristics Affecting Usage" "Adequacy of Insulation" "Well Insulated",42.8,7.9,2.8,5.1 "Adequately Insulated",46.3,10.6,3.3,7.3 "Poorly...

498