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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

Using census aggregates to proxy for household characteristics: an application to vehicle ownership  

E-Print Network [OSTI]

Instead, Asian and Hispanic households were undersampled byhousehold Age of the householder/Average age of residents Hispanichousehold Age of the householder/Average age of residents Hispanic

Adjemian, Michael; Williams, Jeffrey

2009-01-01T23:59:59.000Z

2

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 ....................................

3

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 .....................................

4

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

5

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

6

" 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"

7

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

SciTech Connect (OSTI)

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

8

Characteristics RSE Column Factor: Households with Children Households...  

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

... 6.1 0.8 2.7 2.6 Q Q Q Q Q Q Q 23.2 Race of Householder White ... 54.8 14.4 27.6 12.8 83.7 3.2 6.7 7.2...

9

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

10

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

11

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

12

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 ......................

13

"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

14

"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"

15

"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"

16

"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

17

"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

18

"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"

19

"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"

20

"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

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

"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

22

"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

23

"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

24

"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 "

25

"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

26

"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"

27

"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

28

"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

29

"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

30

"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"

31

"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"

32

"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

33

"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

34

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...........................................

35

Oklahoma Census Snapshot: 2010  

E-Print Network [OSTI]

Oklahoma Census Snapshot: 2010 Same-sex couples per 1,000same-sex couples County Oklahoma Same-sex couples (adjusted)households (adjusted) Tulsa Oklahoma City Norman Shawnee

Gates, Gary J.; Cooke, Abigail M.

2011-01-01T23:59:59.000Z

36

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 ....................................................

37

"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

38

"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"

39

Ventilation Behavior and Household Characteristics in NewCalifornia Houses  

SciTech Connect (OSTI)

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

40

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 .....................................................

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

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

42

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 .................................................

43

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

44

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 .................................................

45

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 .....................................................

46

Household solid waste characteristics and management in Chittagong, Bangladesh  

SciTech Connect (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 < 0.05), education level (r{sub xy} = 0.244, p < 0.05) and monthly income (r{sub xy} = 0.671, p < 0.01) of the households. Municipal authorities are usually the responsible agencies for solid waste collection and disposal, but the magnitude of the problem is well beyond the ability of any municipal government to tackle. Hence dwellers were found to take the service from the local waste 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

47

"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

48

"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

49

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 .....................................

50

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

51

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 .....................................

52

"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

53

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

54

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.............................................

55

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...............................

56

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"

57

A theoretical and simulation-based examination of household vehicle choice through an adoption perspective  

E-Print Network [OSTI]

=2 Senior h =3 Table 17: Japan household income distributionto 2005 Japan Census (millions of households)). CHAPTER 5.same shifts of household dynamics as Japan (i.e. lower birth

Liu, Jenny Hsing-I

2010-01-01T23:59:59.000Z

58

The effect of household characteristics on saving behaviour and the theory of savings in Japan  

Science Journals Connector (OSTI)

The purpose of this paper is to estimate the household saving functions based on cross-section data which contain fruitful informations of individual observations. The paper also attempts to test various theor...

T. Suruga; T. Tachibanaki

1991-01-01T23:59:59.000Z

59

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 ................................................................

60

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 ................................................................

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

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

62

Census 2000 Demographic Profiles City of Pittsburgh Neighborhoods  

E-Print Network [OSTI]

1 data. Summary File 1 (SF 1) contains 286 detailed tables focusing on age, sex, households, families, and housing units. These tables provide in-depth figures by race and Hispanic origin; some tables they considered themselves and other members of their households to be. For the 2000 census, more than one racial

Sibille, Etienne

63

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

64

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

65

A gap in formal long-term care use related to characteristics of caregivers and households, under the public universal system in Japan: 2001–2010  

Science Journals Connector (OSTI)

Abstract We investigated whether the universal provision of long-term care (LTC) under Japan's public system has equalized its use across households with different socio-economic characteristics, with a special focus on the gender and marital status of primary caregivers, and income. We used repeated cross-sectional data from national household surveys (2001, 2004, 2007, 2010) and conducted multiple logistic regression analyses to obtain odds ratios of caregiver and household characteristics for service use, adjusting for recipients’ characteristics. The results showed that the patterns of service use have been consistently determined by caregivers’ gender and marital status over the period despite demographic changes among caregivers. The gap in service use first narrowed, then widened again across income levels after the global economic recession. The results indicate that the traditional gender-bound norms and capacity constraints on households’ informal care provision remained influential on decisions over service use, even after the universal provision of formal care. To improve equality of service utilization, the universal LTC system needs to meet diversifying needs of caregivers/recipients and their households, by overcoming barriers related to gender norms and economic disparity.

Mutsumi Tokunaga; Hideki Hashimoto; Nanako Tamiya

2014-01-01T23:59:59.000Z

66

Census Snapshot: Oklahoma  

E-Print Network [OSTI]

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

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

2008-01-01T23:59:59.000Z

67

"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"

68

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

69

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

70

Table 5.17. U.S. Number of Households by Vehicle Fuel Expenditures...  

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

5.17. U.S. Number of Households by Vehicle Fuel Expenditures, 1994 (Continued) (Million Households) 1993 Household and 1994 Vehicle Characteristics RSE Column Factor: All...

71

Louisiana Census Snapshot: 2010  

E-Print Network [OSTI]

City New Orleans Same-sex couples (adjusted) Same-sex couples per 1,000 households (adjusted) Lafayette Baton Rouge Lake Charles

Gates, Gary J.; Cooke, Abigail M.

2011-01-01T23:59:59.000Z

72

Census Snapshot: Washington  

E-Print Network [OSTI]

households in the state. King County reported the most same-of same-sex couples are King County (1.09% of all county

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

2008-01-01T23:59:59.000Z

73

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

74

" 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

75

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

76

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

77

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

78

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

79

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

80

"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"

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

Harvesting Machine Census 1999 & 2001  

E-Print Network [OSTI]

1 Harvesting Machine Census 1999 & 2001 231 Corstorphine Road Edinburgh EH12 7AT www.forestry.gov.uk FCTN001 SUMMARY This Technical Note contains information on the 1999 and 2001 harvesting machine machines, converted forwarders, etc., account for the remaining machines. In the 2001 census, 65

82

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

83

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

84

"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"

85

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...

86

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

87

http://www.census.gov/  

National Nuclear Security Administration (NNSA)

FAQs Subjects A to Z New on the Site Data Tools American FactFinder Jobs@Census Catalog Publications Are You in a Survey? About the Bureau Regional Offices Doing Business with Us...

88

Modeling households’ decisions on reconstruction of houses damaged by earthquakes––Japanese case study  

Science Journals Connector (OSTI)

In this study, households’ decisions on reconstruction of damaged houses were modeled, using questionnaire data in Japan. Characteristics of households’ decisions were investigated using parameter estimation resu...

H. Sakakibara; H. Murakami; S. Esaki; D. Mori; H. Nakata

2008-02-01T23:59:59.000Z

89

Household vehicles energy consumption 1994  

SciTech Connect (OSTI)

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

90

Transferring 2001 National Household Travel Survey  

SciTech Connect (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

91

Household vehicles energy consumption 1991  

SciTech Connect (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

92

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

93

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

94

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 ......................................

95

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 ........................

96

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

97

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

98

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)"

99

44. Annual Reed rig census  

SciTech Connect (OSTI)

Reed Tool Company`s 44th annual rotary rig census found a spirit of increased optimism in the US oil and gas drilling industry. Rig utilization rose to 77% this year, the highest since the boom times of 15 years ago. A combination of a higher number of active rigs and another decline in available units to a historical low, led to this higher-than-average utilization rate. The paper discusses results from the survey.

Stokes, T.A.; Rodriguez, M.R. [Reed Tool Co., Houston, TX (United States)

1996-10-01T23:59:59.000Z

100

http://factfinder.census.gov/servlet/MetadataBrowserServlet?typ  

National Nuclear Security Administration (NNSA)

I MEDIAN HOUSEHOLD INCOME IN 1999 (DOLLARS) (WHITE ALONE, NOT HISPANIC OR LATINO HOUSEHOLDER) 1 Universe: Households with a householder who is White alone, not Hispanic or Latino...

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

,"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"

102

,"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

103

,"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

104

,"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

105

Census and viewing of organisms  

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

106

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

107

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

108

YELLOWSTONE LAKE TROUT CREEL CENSUSES, 1950-51  

E-Print Network [OSTI]

7^ YELLOWSTONE LAKE TROUT CREEL CENSUSES, 1950-51 SPECIAL SCIENTIFIC REPORT: FISHERIES No. 81 -, h Census method .......... ,o ..... |j Fishing Bridge Dock ........... 5 West Thumb Dock Bridge ,.....,.....,,.,.,.. 18 Lake shore census .......... . ip Private boat fishery

109

Households and Pension  

Science Journals Connector (OSTI)

This chapter deals with two economic issues. First, we examine Japan’s household structure. In the previous chapter ( Chapter 10 ...), we recognized the importance of the ...

Mitsuhiko Iyoda

2010-01-01T23:59:59.000Z

110

HOUSEHOLD SOLAR POWER SYSTEM.  

E-Print Network [OSTI]

?? Photovoltaic power has become one of the most popular research area in new energy field. In this report, the case of household solar power… (more)

Jiang, He

2014-01-01T23:59:59.000Z

111

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

112

Rural Studies Brief No. 2 November 2010 n winter 2010, the U.S. Census Bureau will release  

E-Print Network [OSTI]

characteristics Age Sex Hispanic origin Race Relationship to householder (e.g., spouse) Marital status and marital and households. The data will cover the past 5 years (2005­ 2009) and come from a sample of roughly one in eight U.S. households. Every year after 2010 these data will be updated, granting decision makers

Tullos, Desiree

113

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

114

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

115

36th annual Reed rig census  

SciTech Connect (OSTI)

For the sixth straight year, the number of rigs available in the U.S. declined. Five hundred and seventy-nine rotary rigs dropped out of drilling industry competition during the past 12 months as attrition forced rig supply closer toward balance with demand. Significant highlights of this year's census are: The U.S. rig fleet now stands at 2,752 drilling rigs, a 17.4% reduction from the census count in 1987. This is the largest percentage decline and the third largest absolute decline in available rigs in census history; The 1988 census active count was 1,532 rigs, up 10% over 1987; The 1988 census utilization rate was 55.7%, up from the 41.7% reported last year and a 110% improvement over the all-time low of 26.3% in 1986; Every region in the country reported a reduction in total available rigs. Each region also reported an increase in the active ring count with the exception of Ark-La-Tex; California had the highest utilization rate in the census (63.9%), and all regions reported a utilization rate greater than 50% with the exception of Ark-La-Tex, which reported a 45.5% rate; The number of rig owners declined 12% from 691 to 608. The decline in available rigs would have been greater, but owners brought back 226 rigs that had been dropped from previous census tabulations.

Fitts, R.L.; Crowhurst, M.E. (Reed Tool Co., Houston, TX (US))

1988-10-01T23:59:59.000Z

116

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

117

Household Vehicles Energy Consumption 1991  

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

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...

118

" 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"

119

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

120

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.


121

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

122

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

123

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

124

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

125

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

126

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"

127

The Household “Pie”  

Science Journals Connector (OSTI)

The discussion of theoretical, conceptual, and methodological concerns in the last three chapters has set the stage for an examination of the total effort that households devote to domestic and market activiti...

Sarah Fenstermaker Berk

1985-01-01T23:59:59.000Z

128

" 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"

129

http://2010.census.gov/2010census/data/apportionment-dens-text...  

National Nuclear Security Administration (NNSA)

- 2010 Census 5252011 http:2010.census.gov2010censusdataapportionment-dens-text.php Population 331,069 437,571 486,869 663,091 802,178 763,956 756,510 638,333 606,900...

130

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

131

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

132

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...

133

34th annual reed rotary rig census  

SciTech Connect (OSTI)

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

134

"Table HC12.10 Home Appliances Usage Indicators by Midwest Census...  

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

0 Home Appliances Usage Indicators by Midwest Census Region, 2005" " Million U.S. Housing Units" ,,"Midwest Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division"...

135

"Table HC13.10 Home Appliances Usage Indicators by South Census...  

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

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"...

136

"Table HC14.10 Home Appliances Usage Indicators by West Census...  

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

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...

137

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

138

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

139

Hanford Site Regional Population - 2010 Census  

SciTech Connect (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

140

Household portfolios in Japan  

Science Journals Connector (OSTI)

I provide a detailed description and in-depth analysis of household portfolios in Japan. (1) It is shown that the share of equities in financial wealth and the stock market participation of Japanese households decreased throughout the 1990s. (2) Using survey data, age-related variations in the share of stocks in financial wealth are analyzed. The equity share and stock market participation increase with age among young households, peaking when people reach their 50s, and then stabilizing. However, the share of equities conditional on ownership exhibits no significant age-related pattern, implying that age-related patterns are primarily explained by the decision to hold stocks. A similar mechanism operates to that found in previous studies of Western countries. (3) Owner-occupied housing has a significantly positive effect on stock market participation and on the share of stocks in financial wealth.

Tokuo Iwaisako

2009-01-01T23:59:59.000Z

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.


141

Household Vehicles Energy Use Cover Page  

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

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142

"Keeping Up" or "Keeping Afloat"? : how American households accumulate wealth  

E-Print Network [OSTI]

having a Black or Hispanic household head, and experiencingBlack households, Hispanic households, poor households, etc.that Black- and Hispanic- headed households appear to be at

Lundy, Jeffrey Dalton

2012-01-01T23:59:59.000Z

143

42nd Annual Reed rig census  

SciTech Connect (OSTI)

The eleven-year trend of attrition in the US rig fleet slowed significantly this year as only 12 rigs, or less than 1%, left the available fleet. The number of rotary rigs available for drilling in the US now stands at 1,841. but for the 42-year history of the Reed Tool Co. Rotary Rig Census, the 1973 available rig count of 1,767 remains the record low for yet another year. The count of rigs active during the 45-day census period also declined since last year's census. The active count was down 4.5% to 1,221 from 1,279 in 1993. As a consequence, rig utilization fell to 66.3% in 1994, from 69.0% last year. Notably, a strong shift to gas from oil drilling has occurred. Of the 1,221 rigs active in the census period, 540 were drilling for gas on the last well vs. 356 drilling for oil. Compared to last year, this is an increase in gas drilling of 29% and a decrease in oil drilling 22%. (Rigs targeting both oil and gas totaled 325 in 1994.)

Stokes, T.A.; Rodriquez, M.R. (Reed Tool Co., Houston, TX (United States))

1994-10-01T23:59:59.000Z

144

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

145

Wealth: Determinants of Savings Net Worth and Housing Net Worth of Pre-Retired Households  

Science Journals Connector (OSTI)

The objectives of this study are to determine effects of household members' characteristics, financial resources, and attitude ... Subsamples of White respondents, Black respondents, and Hispanic respondents were...

Satomi Wakita; Vicki Schram Fitzsimmons…

2000-12-01T23:59:59.000Z

146

39th annual Reed rig census  

SciTech Connect (OSTI)

This paper reports on cutbacks in U.S. exploration and development drilling during the first half of 1991 which squeezed most of the optimism out of the drilling industry. Just how rough the year has been is underscored by the results of this year's rig census. The number of rotary rigs available for U.S. drilling declined by only 69 units (3%) during the past 12 months. But despite those withdrawals from competition, only 66% of the remaining rigs were working at the time the census was taken. Results of the 1991 census contrasted sharply with the stability and optimism that seemed apparent a year ago when 72% of the available rig fleet met the census definition of active. At that time, the mini-boom in horizontal drilling coupled with tax-credit- driven gas drilling led to a relatively high rig utilization rate and suggested that rig supply and demand might be close to an economically acceptable balance. However, it quickly became apparent in early 1991 that industry optimism was unjustified. Horizontal drilling began to drop and the lowest natural gas prices in 12 years triggered rapid declines in gas drilling. Although oil prices have been relatively stable and above $18 per bbl since January 1989, most major operators have concluded that a better return on investment can be had outside the U.S. and have drastically cut their domestic drilling budgets. These factors, combined with softened energy demand from the worldwide recession, further slowed U.S. drilling. The long awaited balance between rig supply and demand has seemingly slipped away. The 1991 Reed rig census describes an industry facing several more rough years. Details of this year's census include: The available U.S. fleet now stands at 2,251 rigs, down by 69 from the 2,320-unit total in 1990, and the lowest since 1976. Rigs meeting the census definition of active numbered 1,485, down 192 (11.4%) from the 1,677 active rigs counted a year earlier.

Crowhurst, M.E.; Fitts, R.L. (Reed Tool Co., Houston, TX (US))

1991-10-01T23:59:59.000Z

147

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

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 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"

149

" 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"

150

" 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"

151

" 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"

152

" 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"

153

"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"

154

Housing characteristics 1993  

SciTech Connect (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

155

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

E-Print Network [OSTI]

be damaged when corrosive chemicals are put down the drain. Burning hazardous wastes simply distributes themHousehold 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

de Lijser, Peter

156

http://factfinder.census.gov/servlet/MetadataBrowserServlet?typ  

National Nuclear Security Administration (NNSA)

a householder who is Hispanic or Latino P155I MEDIAN FAMILY INCOME IN 1999 (DOLLARS) (WHITE ALONE, NOT HISPANIC OR LATINO HOUSEHOLDER) 1 Universe: Families with a householder...

157

45th annual Reed rig census  

SciTech Connect (OSTI)

Since 1983, Reed Tool Co.`s annual rotary rig census has reported 14 consecutive annual reductions in the U.S. rig fleet. This year, the downward trend has reversed and more rigs have been added to the available fleet than have left. Robust drilling activity has also spurred higher rig utilization in 1997. Utilization climbed to 86.9% this year, more than ten percentage points higher than a year ago and the highest since 1981. Data and trends are discussed.

Stokes, T.A.; Rodriguez, M.R. [Reed Tool Co., Houston, TX (United States)

1997-10-01T23:59:59.000Z

158

40th annual Reed rig census  

SciTech Connect (OSTI)

This paper reports that declines characterize the 1992 rig census-in the number of available drilling rigs, in the number of active rigs, in rig utilization rate, in the number of rig owners and in industry optimism. The number of rotary rigs available for U.S. drilling fell by 255 units (11.3%) during the past 12 months, an attrition rate almost four times greater than in 1991. But despite the high attrition, only 59.7% of remaining rigs were working during the time the census was taken. Results of the 1992 census bring emphasis to an industry trend that became apparent in early 1991. The major oil companies, and many independents, continued their exodus form the U.S., and the remaining independents, which were hurt by low natural gas prices and unfavorable tax treatment of intangible drilling costs, were not able to pick u the drilling slack. Consequently, the past year has been disastrous for many U.S. drilling contractors, and the outlook for this industry segment remains bleak.

Fitts, R.L.; Stokes, T.A. (Reed Tool Co., Houston, TX (United States))

1992-10-01T23:59:59.000Z

159

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

160

Household Vehicles Energy Consumption 1991  

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

vehicle aging have an additional but unknown effect on the MPG of individual vehicles. Energy Information AdministrationHousehold Vehicles Energy Consumption 1991 27 Of the...

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

Asset Pricing with Countercyclical Household Consumption Risk  

E-Print Network [OSTI]

1 Asset Pricing with Countercyclical Household Consumption Risk George M. Constantinides that shocks to household consumption growth are negatively skewed, persistent, and countercyclical and play that drives the conditional cross-sectional moments of household consumption growth. The estimated model

Sadeh, Norman M.

162

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

163

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

164

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

165

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

166

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 ...................................

167

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 ......................................

168

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 ...................................

169

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 ......................................

170

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 ...................................

171

CREEL CENSUS AND EXPENDITURE STUDY, NORTH FORK SUN RIVER,  

E-Print Network [OSTI]

CREEL CENSUS AND EXPENDITURE STUDY, NORTH FORK SUN RIVER, MONTANA, 1951 Marine Biological STUDY, NORTH FORK SUN RIVER, MONTANA, 1951 Marine Biological Laboratory JUN16 1954 WOODS HOLE, MASS MAP CREEL CENSUS SUN RIVER MONTANA DRAWN i*^ ^ TRACED- _2£jLt:l SUBMITTED . 1 V N 01 1 VN ei

172

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...

173

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

174

CensusPlus: A sampling and prediction approach for the 2000 census of the United States  

SciTech Connect (OSTI)

For a general audience, this paper offers details of a simple proposal for estimation of the population and housing in the year 2000 for the United States. Under CensusPlus, two surveys (mass enumeration and plus sample enumeration) are made of a universe with M blocks. The mass enumeration results in an initial preliminary count for each and every block in the country. The plus sample blocks undergo a second extra high quality count which when compared with the initial count leads to observed resolved counts for the sample blocks. Under a simple model, resolved counts are predicted for the nonsample blocks. Hence an optimal estimator of N, the universe size. is obtained by adding these observed (in sample) and predicted (not in sample) resolved block counts. In fact, this sum turns out to be the classical ratio estimator. This one number census collection is additive and consistent for all levels of geography. In addition, this paper presents sample sizes for the number of blocks required by the plus sample enumeration to support reliable state level estimates of population produced by CensusPlus. In particular and using data from the 1990 Census Files and the 1990 PES Block Data File, it is shown that a nationwide deeply stratified probability sample of 22,120 blocks is needed to ensure that the housing unit population of a given state is estimated with a standard error of 40,000 persons. The 1990 PES Block Data File also provides some early empirical evidence that the model is very likely to hold.

Wright, T.

1995-07-01T23:59:59.000Z

175

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

Gasoline and Diesel Fuel Update (EIA)

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

176

Using Geocoded Census Data for Nonresponse Bias Correction: An Assessment  

Science Journals Connector (OSTI)

......sex, race, ethnicity, and household composition. Dichotomizing...Asian, other), Hispanicity (Hispanic/non-Hispanic), age (18-24, 25-34...50-59, 60 and older), household size (1 person/1+ persons......

Paul Biemer; Andy Peytchev

2013-05-01T23:59:59.000Z

177

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

SciTech Connect (OSTI)

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

178

Communications on energy Household energy conservation  

Science Journals Connector (OSTI)

This study assesses the influence of attitudinal and socio-economic factors on household energy conservation actions. A household interview survey in Regina, Saskatchewan found that respondents perceive an energy problem, although no association with energy conservation actions was determined. Two attitudinal and five socio-economic variables influence household energy conservation. Energy and monetary savings are available to households through energy conservation. Public awareness of household energy conservation through the media can reinforce existing energy conservation actions and encourage new actions.

Fred A. Curtis; P. Simpson-Housley; S. Drever

1984-01-01T23:59:59.000Z

179

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.'

180

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

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

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

182

Delivering Energy Efficiency to Middle Income Single Family Households  

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

183

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

184

Physical activity of adults in households with and without children  

E-Print Network [OSTI]

whites, fewer Hispanics, and higher household incomes thanWhites, fewer Hispanics, and higher household incomes thanWhites, fewer Hispanics, and higher household incomes than

Candelaria, Jeanette Irene

2010-01-01T23:59:59.000Z

185

Minority and poor households: patterns of travel and transportation fuel use  

SciTech Connect (OSTI)

This report documents the travel behavior and transportation fuel use of minority and poor households in the US, using information from numerous national-level sources. The resulting data base reveals distinctive patterns of household vehicle availability and use, travel, and fuel use and enables us to relate observed differences between population groups to differences in their demographic characteristics and in the attributes of their household vehicles. When income and residence location are controlled, black (and to a lesser extent, Hispanic and poor) households have fewer vehicles regularly available than do comparable white or nonpoor households; moreover, these vehicles are older and larger and thus have significantly lower fuel economy. The net result is that average black, Hispanic, and poor households travel fewer miles per year but use more fuel than do average white and nonpoor households. Certain other findings - notably, that of significant racial differences in vehicle availability and use by low-income households - challenge the conventional wisdom that such racial variations arise solely because of differences in income and residence location. Results of the study suggest important differences - primarily in the yearly fluctuation of income - between black and white low-income households even when residence location is controlled. These variables are not captured by cross-sectional data sets (either the national surveys used in our analysis or the local data sets that are widely used for urban transportation planning).

Millar, M.; Morrison, R.; Vyas, A.

1986-05-01T23:59:59.000Z

186

Immigrant characteristics and Hispanic-Anglo housing inequality  

Science Journals Connector (OSTI)

This paper seeks to explain why Hispanic households in the United States live in housing ... Anglos’. I argue that immigrant characteristics of Hispanic households and...the metropolitan areas in which Hispanics ...

Lauren J. Krivo

1995-11-01T23:59:59.000Z

187

" 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

188

Household Vehicles Energy Consumption 1991  

Gasoline and Diesel Fuel Update (EIA)

or More...... 23.1 15.2 197 12.3 10.7 13.0 1.3 12.8 13.0| 6.7 | Race of Householder | White... 135.3 89.5 1,429 89.2 73.9 89.2 9.1 87.5 89.1| 2.0...

189

The World Distribution of Household Wealth  

E-Print Network [OSTI]

Japan is not a remote prospect. In summary, it is clear that householdJapan Korea, South New Zealand Norway Spain Sweden Switzerland United Kingdom United States Year Unit share of top 2002 household

DAVIES, JAMES B; Shorrocks, Anthony; Sandstrom, Susanna; WOLFF, EDWARD N

2007-01-01T23:59:59.000Z

190

Trip rate comparison of workplace and household surveys  

E-Print Network [OSTI]

Available vs. Trip Rate) 14 El Paso Household Survey (Household Income vs. Trip Rate) . 15 El Paso Workplace Survey (Household Income vs. Trip Rate) . 52 52 53 53 54 54 16 BPA Household Survey (Household Size vs. Trip Rate) . . 17 BPA Workplace... Survey (Household Size vs. Trip Rate) . . 56 56 18 BPA Household Survey (No. of Employees vs. Trip Rate) . . 19 BPA Workplace Survey (No. of Employees vs. Trip Rate) . . 20 BPA Household Survey (Vehicles Available vs. Trip Rate) . . 21 BPA Workplace...

Endres, Stephen Michael

2012-06-07T23:59:59.000Z

191

"Table HC10.10 Home Appliances Usage Indicators by U.S. Census...  

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

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...

192

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

193

Mining Spatial Association Rules in Census Data: A Relational Approach  

E-Print Network [OSTI]

Mining Spatial Association Rules in Census Data: A Relational Approach Donato Malerba, Francesca A involving spatial relations among (spatial) objects. The method is based on a multi-relational data mining by traditional statistical techniques in spatial data analysis. The proposed method has been implemented

Malerba, Donato

194

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

195

Who counts? how the state (re)creates households  

E-Print Network [OSTI]

Prior research focused upon the intersection of race, ethnicity, citizenship and identity produced as a result of the Census Schedule. In this dissertation, I focus on the Census, as an instrument of the state, to capture the process of inclusion...

Walther, Carol Sue

2009-05-15T23:59:59.000Z

196

A comparative evaluation of household preferences for solar photovoltaic standalone and mini-grid system: An empirical study in a costal village of Indian Sundarban  

Science Journals Connector (OSTI)

Solar PhotoVoltaic (SPV) based systems have been widely accepted technology for rural electrification in developing countries. The standalone SPV home lighting system has increasingly been popular among rural households, while SPV mini-grid supply system is being promoted for rural electrification schemes. This study uses data from household survey to explore the impact of household characteristics on the preference for electrical energy from SPV systems. Econometric evidence shows heterogeneity in behavioural pattern for these two SPV systems. The flexibility in use and cost of systems might explain this difference. Household characteristics such as monthly household income, household size, occupational status of household head, number of room and type of house significantly influence household’s decision for SPV standalone home lighting systems. For SPV mini-grid supply household’s income and monthly expenditure on kerosene are significant predictors. The result reported in this paper might be a valuable input for policy makers to frame right policy mix with regard to provide subsidy on rural electrification programmes.

Amit K. Bhandari; Chinmoy Jana

2010-01-01T23:59:59.000Z

197

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 ..................................................

198

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

199

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 ..................................................

200

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.


201

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.

2012-01-01T23:59:59.000Z

202

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.

203

Household transmission of pandemic 2009 influenza A (H1N1) virus in Osaka, Japan in May 2009  

Science Journals Connector (OSTI)

SummaryObjective To assess household transmission of pandemic influenza A (H1N1) and effectiveness of postexposure prophylaxis (PEP) of antiviral drugs among household contacts of patients during the first pandemic influenza A (H1N1) outbreak in Osaka, Japan in May 2009. Methods Active surveillance of patients and their families was conducted. Public Health Center staff visited each home with an infected patient and advised every household member with regard to precautionary measures, and PEP was provided to household contacts to prevent secondary infection. We analyzed the effectiveness of PEP and characteristics of secondary infection. Results The secondary attack rate (SAR) among household contacts was 3.7%. The SAR among household contacts without PEP was 26.1%. However, the SAR among those with PEP was 0.6%. Only two of 331 household contacts with PEP became infected. One of the two was infected with an oseltamivir-resistant strain. Analysis of SAR by age group showed that those under 20 years of age were at higher risk than those over 20 (relative risk [RR] = 7.9; 95% confidence interval [CI] = 2.24–27.8). Significant differences with respect to sex, number of household contacts, and use of antiviral medications in the index cases were not observed. Conclusions Our present results indicate that PEP is effective for preventing secondary H1N1 infection among household contacts.

N. Komiya; Y. Gu; H. Kamiya; Y. Yahata; Y. Yasui; K. Taniguchi; N. Okabe

2010-01-01T23:59:59.000Z

204

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":""}]}

205

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":""}]}

206

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":""}]}

207

Household Response To Dynamic Pricing Of Electricity: A Survey...  

Open Energy Info (EERE)

Household Response To Dynamic Pricing Of Electricity: A Survey Of The Experimental Evidence Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Household Response To Dynamic...

208

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

209

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

210

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

211

Household Vehicles Energy Consumption 1991  

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

Protection Agency (EPA) certification files (CERT files) containing laboratory test results of MPG. When the vehicle characteristic was missing from the questionnaire, but...

212

More efficient household electricity use  

SciTech Connect (OSTI)

The energy efficiency of electric appliances has increased markedly in OECD countries, according to data provided by utilities, appliance associations, appliance manufacturers, and independent analyses of each country we reviewed (US, Sweden, Norway, Holland, Japan, Germany, UK). These improvements have, in part, offset increases in electricity demand due to increasing saturation of appliances. However, we see evidence that the efficiency of new devices has hit a temporary plateau: Appliances sold in 1988, while far more efficient than similar ones sold in the early 1970s, may not be significantly more efficient than those sold in 1987. The reason for this plateau, according to manufacturers we interviewed, is that the simple energy-saving features have been incorporated; more sophisticated efficiency improvements are economically justified by five to ten year paybacks, but unattractive to consumers in most countries who appear to demand paybacks of less than three years. Manufacturers see features other than efficiency --- such as number of storage compartments and automatic ice-makers --- as more likely to boost sales, market share, or profits. If this efficiency plateau'' proves lasting, then electricity use for appliance could begin to grow again as larger and more fancy models appear in households. 38 refs., 10 figs., 1 tab.

Schipper, L.; Hawk, D.V.

1989-12-01T23:59:59.000Z

213

"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"

214

"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

215

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  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.  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

216

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  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.  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

217

ASSESSMENT OF HOUSEHOLD CARBON FOOTPRINT REDUCTION POTENTIALS  

E-Print Network [OSTI]

Energy Efficiency Potential Study.  Technical Report Energy Efficiency  Potential Study.  Technical Report Energy Efficiency   Renewable Energy Technologies   Transportation   Assessment of Household Carbon Footprint Reduction Potentials is the final report 

Masanet, Eric

2010-01-01T23:59:59.000Z

218

Household energy consumption and expenditures 1993  

SciTech Connect (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

219

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

220

Nevada: Kingston Creek Hydro Project Powers 100 Households  

Broader source: Energy.gov [DOE]

Hydropower project produces enough electricity to annually power nearly 100 typical American households.

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 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 ......................

222

The Atlas3D project --III. A census of the stellar angular momentum within the  

E-Print Network [OSTI]

The Atlas3D project -- III. A census of the stellar angular momentum within the effective radius style file v2.2) The ATLAS3D project ­ III. A census of the stellar angular momentum within¨ur extraterrestrische Physik, PO Box 1312, D-85478 Garching, Germany 8Space Telescope European Coordinating Facility

Bureau, Martin

223

"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

224

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

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

225

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

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

226

Survey of Household Energy Use (SHEU)  

E-Print Network [OSTI]

Survey of Household Energy Use (SHEU) 2003 Detailed Statistical Report #12;To obtain additional copies of this or other free publications on energy efficiency, please contact: Energy Publications Office of Energy Efficiency Natural Resources Canada c/o St. Joseph Communications Order Processing Unit

227

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

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

228

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

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

229

Opportunities to reduce greenhouse gas emissions from households in Nigeria  

Science Journals Connector (OSTI)

Efforts to mitigate climate threats should not exclude the household as the household is a major driver of greenhouse gas (GHG) emissions through its consumption...2) emissions from kerosene combustion for lighting

O. Adeoti; S. O. Osho

2012-02-01T23:59:59.000Z

230

Household Wealth in a Cross-Country Perspective  

Science Journals Connector (OSTI)

This paper provides a comparative analysis of household wealth in the United States, the United Kingdom, Japan, France, Germany, Spain, and Italy. ... wealth, looking at the instruments in which households invest...

Laura Bartiloro; Massimo Coletta…

2012-01-01T23:59:59.000Z

231

ANALYSIS OF CEE HOUSEHOLD SURVEY NATIONAL AWARENESS OF ENERGY STAR  

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

232

"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"

233

Home Prices and Household Callan Windsor, Jarkko Jskel and  

E-Print Network [OSTI]

Research Discussion Paper Home Prices and Household Spending Callan Windsor, Jarkko Jääskelä. ISSN 1320-7729 (Print) ISSN 1448-5109 (Online) #12;Home Prices and Household Spending Callan Windsor Abstract This paper explores the positive relationship between home prices and household spending

234

Handling Frame Problems When Address-Based Sampling Is Used for In-Person Household Surveys  

Science Journals Connector (OSTI)

......use as the sampling frame for household surveys. This subset includes...However, around 90 percent of households with PO box addresses also have...recent growth, new construction, Hispanic households, non-English-speaking households......

Graham Kalton; Jennifer Kali; Richard Sigman

2014-09-01T23:59:59.000Z

235

E-Print Network 3.0 - assessing household solid Sample Search...  

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

of Groundwater Contamination from Household Wastewater... 12;Glossary Household Wastewater Treatment These terms may help you make more accurate assessments......

236

"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

237

"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

238

The Census of Marine Life—evolution of worldwide marine biodiversity research  

Science Journals Connector (OSTI)

This paper discusses the origin and development of the 10-year Census of Marine Life, describing the way in which a ... was ripe to engage in a large-scale marine biodiversity program incorporating the newest tec...

Vera Alexander; Patricia Miloslavich; Kristen Yarincik

2011-12-01T23:59:59.000Z

239

The Census of Antarctic Marine Life: The First Available Baseline for Antarctic Marine Biodiversity  

Science Journals Connector (OSTI)

CAML was also one of the fourteen projects of the international Census of Marine Life (CoML, www.coml.org ) (Gutt et al. 2010...), each focusing on specific g...

Stefano Schiaparelli; Bruno Danis…

2013-01-01T23:59:59.000Z

240

Solar Census - Perfecting the Art of Automated, Remote Solar Shading Assessments (Fact Sheet)  

SciTech Connect (OSTI)

To validate the work completed by Solar Census as part of the Department of Energy SunShot Incubator 8 award, NREL validated the performanec of the Solar Census Surveyor tool against the industry standard Solmetric SunEye measurements for 4 residential sites in California who experienced light to heavy shading. Using the a two one-sided test (TOST) of statistical equivalence, NREL found that the mean differences between the Solar Census and SunEye mean solar access values for Annual, Summer, and Winter readings fall within the 95% confidence intervals and the confidence intervals themselves fall within the tolerances of +/- 5 SAVs, the Solar Census calculations are statistically equivalent to the SunEye measurements.

Not Available

2014-04-01T23:59:59.000Z

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

"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

242

"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"

243

" 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

244

"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"

245

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

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

Shingle)",1.9,0.7,0.3,0.7,"Q" "Stone",1,0.4,"Q",0.5,"Q" "Other",1.5,"Q",0.7,0.5,"Q" "FoundationBasement of Single-" "Family Units and Apartments in" "2 to 4 Unit Buildings" "(more...

246

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

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

(Shingle)",1.9,0.7,0.6,0.2 "Stone",1,0.4,0.4,"N" "Other",1.5,"Q","Q","Q" "FoundationBasement of Single-" "Family Units and Apartments in" "2 to 4 Unit Buildings" "(more...

247

Towards sustainable consumption: do green households have smaller ecological footprints?  

Science Journals Connector (OSTI)

The need for households in rich countries to develop more sustainable consumption patterns is high on the political agenda. An increased awareness of environmental issues among the general public is often presented as an important prerequisite for this change. This article describes how the study team compared the ecological footprints of ''green'' and ''ordinary'' households. These footprint calculations are based on a number of consumption categories that have severe environmental consequences, such as energy and material use in the home, and transport. The comparison is based on a survey of 404 households in the city of Stavanger, where 66 respondents were members of the Environmental Home Guard in Norway. The analysis suggests that, even if the green households have a smaller ecological footprint per household member, this is not caused by their participation in the Home Guard. It merely reflects the fact that green households are larger than ordinary households.

Erling Holden

2004-01-01T23:59:59.000Z

248

Household transitions to energy efficient lighting  

Science Journals Connector (OSTI)

Abstract New energy efficient lighting technologies can significantly reduce household electricity consumption, but adoption has been slow. A unique dataset of German households is used in this paper to examine the factors associated with the replacement of old incandescent lamps (ILs) with new energy efficient compact fluorescent lamps (CFLs) and light emitting diodes (LEDs). The ‘rebound’ effect of increased lamp luminosity in the transition to energy efficient bulbs is analyzed jointly with the replacement decision to account for household self-selection in bulb-type choice. Results indicate that the EU ban on \\{ILs\\} accelerated the pace of transition to \\{CFLs\\} and LEDs, while storage of bulbs significantly dampened the speed of the transition. Higher lighting needs and bulb attributes like energy efficiency, environmental friendliness, and durability spur IL replacement with \\{CFLs\\} or LEDs. Electricity gains from new energy efficient lighting are mitigated by 23% and 47% increases in luminosity for CFL and LED replacements, respectively. Model results suggest that taking the replacement bulb from storage and higher levels of education dampen the magnitude of these luminosity rebounds in IL to CFL transitions.

Bradford Mills; Joachim Schleich

2014-01-01T23:59:59.000Z

249

UNCOVERING BASIC WANTS USING THE ROTTERDAM AND AIDS MODELS: THE US HOUSEHOLD ENERGY CONSUMPTION CASE  

E-Print Network [OSTI]

refers to these latent goods as transformed goods or T-goods. Leading researchers have explored this technique of incorporating characteristics. In this study, we revisit this technique by trying to uncover the basic wants behind the demand for gas..., distillate fuel oil, and the liquefied petroleum gases (LPG) by US households. To give some examples, electricity may be used for many basic wants such as lighting, cooking, and cooling. Similarly, without being exhaustive, gas may be used for heating...

Diallo, Ibrahima

2013-05-31T23:59:59.000Z

250

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

251

Can ambient persuasive technology persuade unconsciously?: using subliminal feedback to influence energy consumption ratings of household appliances  

Science Journals Connector (OSTI)

In this paper we explore a fundamental characteristic of Ambient Persuasive Technology: Can it persuade the user without receiving the user's conscious attention? In a task consisting of 90 trials, participants had to indicate which of three household ... Keywords: ambient persuasive technology, energy conservation behavior, human-technology interaction, persuasion, social feedback, subliminal feedback

Jaap Ham; Cees Midden; Femke Beute

2009-04-01T23:59:59.000Z

252

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 | | | |_______________________|

253

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 | | | |_______________________|

254

Delivering Energy Efficiency to Middle Income Single Family Households  

E-Print Network [OSTI]

Neighborhood Program GETS – Green Energy Training ServicesGJGEI – Green Jobs, Green Energy Initiative CEWO – Cleanincome households. The Green Energy Training Services (GETS)

Zimring, Mark

2012-01-01T23:59:59.000Z

255

Barriers to household investment in residential energy conservation: preliminary assessment  

SciTech Connect (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

256

Economic theory and women's household status: The case of Japan  

Science Journals Connector (OSTI)

Economic development disadvantages wives. Conventional microeconomic theory predicts this. As household incomes rise, wives have incentives to specialize in intangible household production. This may raise total household production according to the theory of comparative advantage, but disproportionately favors husbands in distribution of the gains according to the marginal productivity theory of distribution. Wives may become better off in absolute terms but more dependent financially on their husbands and lose power within the household. Historically, Japanese gender roles became highly specialized and wives’ legal status declined, although other Meiji-era features protected wives. Policies to improve women's status should address the precise economic problem involved.

Barbara J. Redman

2008-01-01T23:59:59.000Z

257

Confronting earthquake risk in Japan—are private households underinsured?  

Science Journals Connector (OSTI)

Despite the fact that Japan is an earthquake-prone country and Japanese ... risk averse, less than half of Japanese households are insured against earthquake risk. Based on...

Franz Waldenberger

2013-03-01T23:59:59.000Z

258

Salmon consumption at the household level in Japan.  

E-Print Network [OSTI]

??The primary purpose of this study is to investigate the salmon demand of Japanese households. The specific goals are to illuminate the substitutional relationship between… (more)

Kikuchi, Akihiro

1987-01-01T23:59:59.000Z

259

Consumer perspectives on household hazardous waste management in Japan  

Science Journals Connector (OSTI)

We give an overview of the management systems of household hazardous waste (HHW) in Japan and discuss the management systems and their...

Misuzu Asari; Shin-ichi Sakai

2011-02-01T23:59:59.000Z

260

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.


261

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

262

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

263

A comparative multivariate analysis of household energy requirements in Australia, Brazil, Denmark, India and Japan  

Science Journals Connector (OSTI)

In this paper, we appraise sustainable household consumption from a global perspective. Using per capita energy requirements as an indicator of environmental pressure, we focus on the importance of income growth in a cross-country analysis. Our analysis is supported by a detailed within-country analysis encompassing five countries, in which we assess the importance of various socioeconomic-demographic characteristics of household energy requirements. We bring together family expenditure survey data, input–output tables, and energy statistics in a multivariate analysis. Instead of a uniform Kuznet's curve, we find that the effect of increasing income varies considerably across countries, even when controlling for socioeconomic and demographic variations. The latter variables show similar influences, but differing importance across countries.

Manfred Lenzen; Mette Wier; Claude Cohen; Hitoshi Hayami; Shonali Pachauri; Roberto Schaeffer

2006-01-01T23:59:59.000Z

264

"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

265

"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

266

"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

267

"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"

268

Public census data on CD-ROM at Lawrence Berkeley Laboratory  

SciTech Connect (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

269

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

SciTech Connect (OSTI)

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

270

Public census data on CD-ROM at Lawrence Berkeley Laboratory  

SciTech Connect (OSTI)

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

271

"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

272

Intra-Household Inequality in Transitional Russia Ekaterina Kalugina  

E-Print Network [OSTI]

1 Intra-Household Inequality in Transitional Russia Ekaterina Kalugina Natalia Radtchenko Catherine and satisfaction. Using two different subjective questions of the Russian data RLMS (Russia Longitudinal Monitoring and social changes in Russia, we investigate the dynamics of household behavior. Keywords: subjective data

Paris-Sud XI, Université de

273

Controlling Households' Drilling Fever in France: an economic modeling approach  

E-Print Network [OSTI]

to generate environmental benefits through reducing water use, has produced economic incentives for households; France; households; domestic boreholes; tube well; water pricing. Author-produced version Fourth World negative environmental impact of water price increase in the drinking water sector. Using primary data

Boyer, Edmond

274

Page 1 TXCRDC Notes on Datasets Available in CRDCs Texas A&M University Census Research Data Center  

E-Print Network [OSTI]

Page 1 ­ TXCRDC ­ Notes on Datasets Available in CRDCs Texas A&M University Census Research Data Center Datasets Available in Census Research Data Centers Overview This document brings together short. They include: 1. Links to Detailed Information about Available Datasets 2. Quick Summary Listings of Available

Bermúdez, José Luis

275

" 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

276

" 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

277

" 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

278

" 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

279

" 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

280

Assimilation and differences between the settlement patterns of individual immigrants and immigrant households  

Science Journals Connector (OSTI)

...delineate directions for future household-scale investigations of...Categorization: Individuals or Households? The concentration on the...individual bodies. Of course, household structure and geographic context...children compared with non-Hispanic white children hinge on such...

Mark Ellis; Richard Wright

2005-01-01T23:59:59.000Z

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

Efficient Use of Commercial Lists in U.S. Household Sampling  

Science Journals Connector (OSTI)

......educational attainment, Hispanic ethnicity, household income, and home tenure...on the two persons in the household as well as the Hispanic ethnicity status of the head of household (assuming that the Hispanic ethnicity status of persons......

Richard Valliant; Frost Hubbard; Sunghee Lee; Chiungwen Chang

2014-06-01T23:59:59.000Z

282

Household actions can provide a behavioral wedge to rapidly reduce US carbon emissions  

Science Journals Connector (OSTI)

...ineffective in reducing household energy consumption. Mass media...10 years. The changes in household behavior outlined above result...European Union countries and Japan, where the household sector is less energy intensive. Analyses similar...

Thomas Dietz; Gerald T. Gardner; Jonathan Gilligan; Paul C. Stern; Michael P. Vandenbergh

2009-01-01T23:59:59.000Z

283

COALITION FOR A SUSTAINABLE AGRICULTURAL WORKFORCE 2013 AGRICULTURAL SCIENCE WORKFORCE CENSUS  

E-Print Network [OSTI]

workforce planning and development data to create a broad inventory of the future need for scientistsCOALITION FOR A SUSTAINABLE AGRICULTURAL WORKFORCE 2013 AGRICULTURAL SCIENCE WORKFORCE CENSUS #12;Summary SUMMARY In January 2013, CSAW (Coalition for a Sustainable Agricultural Workforce) conducted

Wang, Xiaorui "Ray"

284

Patterns of Protein-Fold Usage in Eight Microbial Genomes: A Comprehensive Structural Census  

E-Print Network [OSTI]

Patterns of Protein-Fold Usage in Eight Microbial Genomes: A Comprehensive Structural Census Mark in terms of patterns of fold usage--whether a given fold occurs in a particular organism. Of the 340 be analyzed through trans- membrane-helix (TM) prediction. All the genomes appear to have similar usage

Gerstein, Mark

285

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.

286

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

287

"Table HC7.10 Home Appliances Usage Indicators by Household...  

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

0 Home Appliances Usage Indicators by Household Income, 2005" " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1"...

288

E-Print Network 3.0 - acute household accidental Sample Search...  

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

Evaluating the health benefits of transitions in household energy Summary: ; Household energy; Indoor air pollution; Intervention assessment; Kenya 1. Introduction Acute...

289

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

E-Print Network [OSTI]

of household refrigerators and freezers 2 . Therefore, thesales of the refrigerators and freezers are about 20.6for household refrigerators and freezers has been updated

Lin, Jiang

2006-01-01T23:59:59.000Z

290

2012 Census of Agriculture Underway Respond Now For many farmers across the nation, this is the time of year to finish paperwork after a busy  

E-Print Network [OSTI]

2012 Census of Agriculture Underway ­ Respond Now For many farmers across the nation. This makes it a perfect time to also fill out and return your 2012 Census of Agriculture form. The Census of Agriculture is sent to all farmers and ranchers only once every five years by USDA's National Agricultural

Watson, Craig A.

291

P o P u l a t i o n April 1, 2010 Census...............................................................12,702,379  

E-Print Network [OSTI]

or more races...................................................237,835...............1.9 Hispanic m i c Median Household Income * ...................................................$49,288 Median

Yener, Aylin

292

Household Vehicles Energy Consumption 1994 - Appendix C  

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

Protection Agency (EPA) certification files (CERT files) containing laboratory test results of MPG. When the vehicle characteristic was missing from the questionnaire, but...

293

Projecting household energy consumption within a conditional demand framework  

SciTech Connect (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

294

Projecting household energy consumption within a conditional demand framework  

SciTech Connect (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.

1991-01-01T23:59:59.000Z

295

" 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"

296

" 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

297

" 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

298

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.

299

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.

300

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

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

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

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

in gallons, of this household's storage tank(s)? Enter the capacity for the two largest tanks (if there is more than one) in the boxes below. If the capacity is not known, write...

302

Fact #614: March 15, 2010 Average Age of Household Vehicles  

Broader source: Energy.gov [DOE]

The average age of household vehicles has increased from 6.6 years in 1977 to 9.2 years in 2009. Pickup trucks have the oldest average age in every year listed. Sport utility vehicles (SUVs), first...

303

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

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

or More","NA","NA",93.75,96.42857143,91.27516779,97.46835443 "Race of Householder1" " White",88.61111111,"NA",91.54929577,91.68704156,90.27093596,92.77845777 " Black...

304

Fact #748: October 8, 2012 Components of Household Expenditures...  

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

but then declined until about 2004 when gasoline and motor oil expenditures began to rise again. The share of household expenditures on gasoline and oil was exactly the same...

305

Householder Symposium on Numerical Linear Algebra June 1721, 2002  

E-Print Network [OSTI]

for discussions. This year's symposium is held at Peebles Hotel Hydro in the small town of Peebles (populationHouseholder Symposium on Numerical Linear Algebra June 17­21, 2002 Peebles Hotel Hydro, Scotland

Higham, Nicholas J.

306

The impact of retirement on household consumption in Japan  

Science Journals Connector (OSTI)

Using monthly data from the Japanese Family Income and Expenditure Survey, we examine the impact of retirement on household consumption. We find little evidence of an immediate change in consumption at retirement, on average, in Japan. However, we find a decrease in consumption at retirement for low income households that is concentrated in food and work-related consumption. The availability of substantial retirement bonuses to a large share of Japanese retirees may help smooth consumption at retirement. We find that those households that are more likely to receive such bonuses experience a short-run consumption increase at retirement. However, among households that are less likely to receive a retirement bonus, we find that consumption decreases at retirement.

Melvin Stephens Jr.; Takashi Unayama

2012-01-01T23:59:59.000Z

307

Household energy consumption and its demand elasticity in Thailand  

Science Journals Connector (OSTI)

This study concentrates on the analysis of energy consumption, expenditure on oil and LPG use in cars and aims to examine the elasticity effect of various types of oil consumption. By using the Deaton's analysis framework, the cross-sectional data of Thai households economic survey 2009 were used. By defining energy goods in the scope of automobile fuel, the results reflect the low importance of high-quality automobile fuel on all income level households. Thai households tend to vary the quality rather than the quantity of thermal energy. All income groups have a tendency to switch to lower quality fuel. Middle and high-middle households (Q3 and Q4) are the income groups with the greatest tendency to switch to lower-quality fuel when a surge in the price of oil price occurs. The poorest households (Q1) are normally insensitive to a change of energy expenditure in terms of quality and quantity. This finding illustrates the LPG price subsidy policy favours middle and high-middle income households. The price elasticity of energy quantity demand is negative in all income levels. High to middle income families are the most sensitive to changes in the price of energy.

Montchai Pinitjitsamut

2012-01-01T23:59:59.000Z

308

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

309

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.

310

"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"

311

"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"

312

"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

313

"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

314

"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

315

"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"

316

"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

317

"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

318

"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"

319

"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"

320

University of Saskatchewan Student Entrance Census, 2013 Published July, 2014 Contact: University Learning Centre ulc_surveys@usask.ca  

E-Print Network [OSTI]

University of Saskatchewan Student Entrance Census, 2013 Published July, 2014 their first-year of studies at the University of Saskatchewan to complete a series Percentage Count Saskatoon 28% 826 In a Saskatchewan city with population

Peak, Derek

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

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#).

322

Public census data on CD-ROM at Lawrence Berkeley Laboratory  

SciTech Connect (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

323

Public census data on CD-ROM at Lawrence Berkeley Laboratory  

SciTech Connect (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

324

The Household Market for Electric Vehicles: Testing the Hybrid Household Hypothesis -- A Reflexively Designed Survey of New-Car-Buying Multi-Vehicle California Households  

E-Print Network [OSTI]

EV,then we expect 13.3 to 15.2% of all light-duty vehicle sales,EV marketpotential for smaller and shorter range velucles represented by our sampleis about 7%of annual, newhght duty vehicle sales.EV body styles" EVs ICEVs Total PAGE 66 THE HOUSEHOLD MA RKET FOR ELECTRIC VEHICLES percent mandatein the year 2003will dependon sales

Turrentine, Thomas; Kurani, Kenneth S.

2001-01-01T23:59:59.000Z

325

Population and households dynamics: A mountainous district in northern Japan in the Shûmon Aratame Chô of Aizu, 1750–1850  

Science Journals Connector (OSTI)

The authors examine population trends, demographic characteristics, and the family reproduction system in a highland area of Japan. Aizu district is located in northeastern Japan and has both a mountainous area and a narrow plain. The study is based on Shûmon Aratame Chô (SAC), population registers of four villages between 1750 and 1850 and focuses on the mountainous sector. Demographically, this area stagnated because of its isolation and remoteness. There were few migrations in or out. The peasants married early but bore few children. The authors show how demographic patterns are interrelated with family and household patterns. The most frequent family type was the stem family household, traditionally considered as characteristic of Japan, where the ie (house) was usually transmitted to a single heir. Family transmissions of the rural estate are observed in detail. A household cycle took about 30–35 years to complete. Major differences were seen among social classes, but, overall, Aizu families possessed ideals of ie and were incorporated into ie systems, particularly in the upper classes.

Akira Hayami; Aoi Okada

2005-01-01T23:59:59.000Z

326

Energy Consumption of Refrigerators in Ghana - Outcomes of Household  

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

327

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

328

Water Related Energy Use in Households and Cities - an Australian  

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

329

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

330

An exploratory study of Spanish households' WEEE disposal behaviour  

Science Journals Connector (OSTI)

This paper presents the findings of an exploratory study based on a survey of 1,537 households in Spain. The questionnaire included 23 key questions regarding the number of appliances in use, previous appliances lifetimes, reasons for buying each new appliance and end-of-life handling of discarded appliances. The distribution of the households along a number of relevant factors was analysed and a prototypical household was identified. A non-parametric analysis of the duration of each type of appliance has also been carried out and it was found that television sets are the most durable of the appliances considered. Survival rates for irons fall more rapidly than for microwaves. Moreover, television sets are the most durable of the appliances considered. Replacement rates of personal computers rapidly increase after approximately six to eight years. Finally, a statistical analysis of the respondents motivations for recycling the appliances considered in this study was carried out.

Ester Gutiérrez; Belarmino Adenso-Díaz; Sebastián Lozano; Plácido Moreno

2011-01-01T23:59:59.000Z

331

Energy demand of German households and saving potential  

Science Journals Connector (OSTI)

The implementation of the principles of sustainable development requires both using potentialities in saving resources and cutting down emissions (efficiency strategies) as well as more conscious patterns of behaviour of the actors involved (sufficiency strategies). Starting from the current situation of annual CO2 emissions of about 10 t and a sustainability goal of 1â??2 t CO2 emissions per inhabitant and year, the question arises in how far households can contribute to achieve this goal. Therefore, in this paper, the environmental impacts of the energy demand of German households will be evaluated by means of describing its status quo and there from deriving saving potentials.

Anke Eber; Dominik Most; Otto Rentz; Thomas Lutzkendorf

2008-01-01T23:59:59.000Z

332

Public census data on CD-ROM at Lawrence Berkeley Laboratory  

SciTech Connect (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

333

Public census data on CD-ROM at Lawrence Berkeley Laboratory. Revision 3  

SciTech Connect (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

334

Public census data on CD-ROM at Lawrence Berkeley Laboratory. Revision 4  

SciTech Connect (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 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

335

The Travel Behavior of Immigrants and Race/Ethnicity Groups: An Analysis of the 2001 National Household Transportation Survey  

E-Print Network [OSTI]

the average household size for Hispanic respondents isper year, while households of black and Hispanic respondentsHispanic” versus “settled” and native born residents. Vehicle ownership is highly correlated with mode choice as households

Handy, Susan L; Tal, Gil

2005-01-01T23:59:59.000Z

336

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

Gasoline and Diesel Fuel Update (EIA)

... 32.8 17.2 307 13.4 16.1 14.2 2.0 21.3 14.1 Race of Householder White... 149.5 78.3 1,774 77.6...

337

THE DESIRE TO ACQUIRE: FORECASTING THE EVOLUTION OF HOUSEHOLD  

E-Print Network [OSTI]

energy-using devices in the average U.S. household that used over 4,700 kWh of electricity, natural gas.46]. The cost of these devices was also statistically significant. Keywords: electricity use; energy efficiency the Canadian Industrial Energy End Use Data and Analysis (CIEEDAC) for their financial support made possible

338

Household Segmentation in Food Insecurity and Soil Improving Practices in Ghana  

E-Print Network [OSTI]

secure household, and households farming medium quality soil increase the probability of adopting soil improving practices. Application of chemical fertilizers, commercial seeds, and pesticides, along with operating under a seasonal lease tenure...

Nata, Jifar T

2013-08-09T23:59:59.000Z

339

Logistic regression models for predicting trip reporting accuracy in GPS-enhanced household travel surveys  

E-Print Network [OSTI]

This thesis presents a methodology for conducting logistic regression modeling of trip and household information obtained from household travel surveys and vehicle trip information obtained from global positioning systems (GPS) to better understand...

Forrest, Timothy Lee

2007-04-25T23:59:59.000Z

340

Fact #747: October 1, 2012 Behind Housing, Transportation is the Top Household Expenditure  

Broader source: Energy.gov [DOE]

Except for housing, transportation was the largest single expenditure for the average American household in 2010. The average household spends more on transportation in a year than on food. Vehicle...

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

Fact #727: May 14, 2012 Nearly Twenty Percent of Households Own Three or More Vehicles  

Broader source: Energy.gov [DOE]

Household vehicle ownership has changed over the last six decades. In 1960, over twenty percent of households did not own a vehicle, but by 2010, that number fell to less than 10%. The number of...

342

Fact #729: May 28, 2012 Secondary Household Vehicles Travel Fewer Miles  

Broader source: Energy.gov [DOE]

When a household has more than one vehicle, the secondary vehicles travel fewer miles than the primary vehicle. In a two-vehicle household, the second vehicle travels less than half of the miles...

343

A Comparison of Household Budget Allocation Patterns Between Hispanic Americans and Non-Hispanic White Americans  

Science Journals Connector (OSTI)

The budget allocation patterns of Hispanic versus non-Hispanic White households are examined. Annual household expenditure data from 1980 to 1992 are ... Index (1990). The sample includes 588 Hispanic and 8,444 n...

Jessie X. Fan; Virginia Solis Zuiker

1998-06-01T23:59:59.000Z

344

The household production function approach to valuing climate: the case of Japan  

Science Journals Connector (OSTI)

In fact ours is not the first attempt to use the household production function technique empirically to estimate the ... climate and the impact of climate change on households. But our analysis uses repeated cros...

David Maddison; Katrin Rehdanz; Daiju Narita

2013-01-01T23:59:59.000Z

345

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#).

346

"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

347

"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)"

348

Standby electricity consumption and saving potentials of Turkish households  

Science Journals Connector (OSTI)

Abstract The share of the residential sector currently accounts for about 25% of the national electricity consumption in Turkey. Due to increase in household income levels and decrease in the costs of appliances; significant increases in appliance ownerships and residential electricity consumption levels have been observed in recent years. Most domestic appliances continue consuming electricity when they are not performing their primary functions, i.e. at standby mode, which can constitute up 15% of the total household electricity consumption in some countries. Although the demand in Turkish residential electricity consumption is increasing, there are limited studies on the components of the residential electricity consumption and no studies specifically examining the extent and effects of standby electricity consumption using a surveying/measurement methodology. Thus, determining the share of standby electricity consumption in total home electricity use and the ways of reducing it are important issues in residential energy conservation strategies. In this study, surveys and standby power measurements are conducted at 260 households in Ankara, Turkey, to determine the amount, share, and saving potentials of the standby electricity consumption of Turkish homes. The survey is designed to gather information on the appliance properties, lights, electricity consumption behavior, economic and demographics of the occupants, and electricity bills. A total of 1746 appliances with standby power are measured in the surveyed homes. Using the survey and standby power measurements data, the standby, active, and lighting end-use electricity consumptions of the surveyed homes are determined. The average Turkish household standby power and standby electricity consumption are estimated as 22 W and 95 kW h/yr, respectively. It was also found that the standby electricity consumption constitutes 4% of the total electricity consumption in Turkish homes. Two scenarios are then applied to the surveyed homes to determine the potentials in reducing standby electricity consumption of the households.

Mustafa Cagri Sahin; Merih Aydinalp Koksal

2014-01-01T23:59:59.000Z

349

Frequency and longitudinal trends of household care product use Rebecca E. Moran a  

E-Print Network [OSTI]

SUPERB Indoor environment d-limonene a b s t r a c t The use of household cleaning products and air, frequencies of use of eight types of household cleaning products and air fresheners and the performance. Introduction Household care products, such as cleaning products and air fresheners, are frequently used

Leistikow, Bruce N.

350

,"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

351

,"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

352

Income inequality and carbon dioxide emissions: The case of Chinese urban households  

Science Journals Connector (OSTI)

This paper draws on Chinese survey data to investigate variations in carbon dioxide emissions across households with different income levels. Rich households generate more emissions per capita than poor households via both their direct energy consumption and their higher expenditure on goods and services that use energy as an intermediate input. An econometric analysis confirms a positive relationship between emissions and income and establishes a slightly increasing marginal propensity to emit (MPE) over the relevant income range. The redistribution of income from rich to poor households is therefore shown to reduce aggregate household emissions, suggesting that the twin pursuits of reducing inequality and emissions can be achieved in tandem.

Jane Golley; Xin Meng

2012-01-01T23:59:59.000Z

353

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

354

Chandra Orion Ultradeep Project census of X-ray stars in the BN-KL and OMC-1S regions  

E-Print Network [OSTI]

Chandra Orion Ultradeep Project census of X-ray stars in the BN-KL and OMC-1S regions N. Grosso1 Molecular Cloud 1 (OMC-1) behind the Orion Nebula Cluster (ONC), as seen in the exceptionally deep ( 10 days) exposure of the Chandra Orion Ultradeep Project (COUP). We focus on a 40 Ã? 50 region around the Becklin

Boyer, Edmond

355

Long-term behaviour of baled household waste  

Science Journals Connector (OSTI)

This study was carried out at the laboratory scale (approximately 15 l) and using real baled waste of industrial dimensions (about 1 m3), in order to assess the long-term behaviour of baled household waste. The laboratory assays were carried out with real household waste which was fractioned on site, reconstituted in the laboratory and then compacted into 15 l airtight containers (unless stated otherwise). These containers were incubated under different experimental conditions at a constant temperature (28°C). Three assays were conducted over 34 months and two others over 27 months. For the assays incubated in conditions simulating those of real baled waste (confined medium, with no aeration or water flow), a very low microbial activity was observed. The assay incubated in the same conditions but with slight aeration during the first three months in order to simulate imperfectly airtight wrapping, revealed biodegradation which started in a significant manner after 800 days of incubation. The evolution of two real wrapped bales each containing 900 kg of household waste was monitored over 8 months. These bales were produced industrially, one in July 97 and the other in July 98 at the incinerator plant at Agde (France). The bales were then stored outside at the laboratory location and their evolution was monitored mainly by biogas analysis and temperature measurement. No methane formation was observed, revealing the absence of anaerobic biodegradation, thus confirming the laboratory assays.

Fabian Robles-Mart??nez; Rémy Gourdon

2000-01-01T23:59:59.000Z

356

Developing Livestock Facility Type Information from USDA Agricultural Census Data for Use in Epidemiological and Economic Models  

SciTech Connect (OSTI)

The epidemiological and economic modeling of livestock diseases requires knowing the size, location, and operational type of each livestock facility within the US. At the present time, the only national database of livestock facilities that is available to the general public is the USDA's 2002 Agricultural Census data, published by the National Agricultural Statistics Service, herein referred to as the 'NASS data.' The NASS data provides facility data at the county level for various livestock types (i.e., beef cows, milk cows, cattle on feed, other cattle, total hogs and pigs, sheep and lambs, milk goats, and angora goats). However, the number and sizes of facilities for the various livestock types are not independent since some facilities have more than one type of livestock, and some livestock are of more than one type (e.g., 'other cattle' that are being fed for slaughter are also 'cattle on feed'). In addition, any data tabulated by NASS that could identify numbers of animals or other data reported by an individual respondent is suppressed by NASS and coded with a 'D.'. To be useful for epidemiological and economic modeling, the NASS data must be converted into a unique set of facility types (farms having similar operational characteristics). The unique set must not double count facilities or animals. At the same time, it must account for all the animals, including those for which the data has been suppressed. Therefore, several data processing steps are required to work back from the published NASS data to obtain a consistent database for individual livestock operations. This technical report documents data processing steps that were used to convert the NASS data into a national livestock facility database with twenty-eight facility types. The process involves two major steps. The first step defines the rules used to estimate the data that is suppressed within the NASS database. The second step converts the NASS livestock types into the operational facility types used by the epidemiological and economic model. Comparison of the resulting database with an independent survey of farms in central California shows excellent agreement between the numbers of farms for the various facility types. This suggests that the NASS data are well suited for providing a consistent set of county-level information on facility numbers and sizes that can be used in epidemiological and economic models.

Melius, C; Robertson, A; Hullinger, P

2006-10-24T23:59:59.000Z

357

" 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

358

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

359

Energy use of US residential refrigerators and freezers: function derivation based on household and climate characteristics  

E-Print Network [OSTI]

all units in our da- taset. (AHAM) (see Appendix 7-B in DOEownership provided by AHAM (2010, personal communication).in ownership provided by AHAM to weight the RECS ownership

Greenblatt, Jeffery

2013-01-01T23:59:59.000Z

360

Energy use of US residential refrigerators and freezers: function derivation based on household and climate characteristics  

E-Print Network [OSTI]

residential refrigerators and freezers: function derivationsecond most-used) refrigerators, and freezers, and residualfor more efficient refrigerators and freezers, as well as

Greenblatt, Jeffery

2013-01-01T23:59:59.000Z

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.


361

Energy use of US residential refrigerators and freezers: function derivation based on household and climate characteristics  

E-Print Network [OSTI]

Residential Energy Consumption Survey (RECS), U.S. Energyod for estimating field energy consumption of US residentialconsumption survey—detailed tables. Residential Energy Con- sumption Survey (RECS), U.S.

Greenblatt, Jeffery

2013-01-01T23:59:59.000Z

362

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

363

Vehicle Technologies Office: Fact #301: January 5, 2004 Number of Household  

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

364

Indoor Secondary Pollutants from Household Product Emissions in the  

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

365

Greenhouse Gas Implications of Household Energy Technology in Kenya  

Science Journals Connector (OSTI)

Energy and Resources Group, University of California, Berkeley, California 94720-3050, Risk, Resource, and Environmental Management Division, Resources for the Future, 1616 P Street NW, Washington, D.C. 20036, and Goldman School of Public Policy, University of California, Berkeley, California 94720-7320 ... Household energy policy is further complicated because charcoal markets in many sub-Saharan African countries operate within a complex political economy that can be hard to characterize and still more difficult to regulate. ... While charcoal consumption carries a larger burden of GHG emissions than firewood use, it also has more potential to attract investment in GHG mitigation activities. ...

Rob Bailis; Majid Ezzati; Daniel M. Kammen

2003-04-01T23:59:59.000Z

366

Enhanced naphthenic refrigeration oils for household refrigerator systems  

SciTech Connect (OSTI)

Due to industry concerns about the successful employment of hydrofluorocarbon-immiscible hydrocarbon oils in refrigeration systems, enhanced naphthenic refrigeration oils have been developed. These products have been designed to be more dispersible with hydrofluorocarbon (HFC) refrigerants, such as R-134a, in order to facilitate lubricant return to the compressor and to ensure proper energy efficiency of the system. Bench tests and system performance evaluations indicate the feasibility of these oils for use in household refrigeration applications. Results of these evaluations are compared with those obtained with polyol esters and typical naphthenic mineral oils employed in chlorofluorocarbon (CFC) and hydrochlorofluorocarbon (HCFC) refrigeration applications.

Reyes-Gavilan, J.L.; Flak, G.T.; Tritcak, T.R. [Witco Corp., Oakland, NJ (United States); Barbour, C.B. [Americold, Cullman, AL (United States)

1997-12-31T23:59:59.000Z

367

Table HC6.10 Home Appliances Usage Indicators by Number of Household...  

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

0 Home Appliances Usage Indicators by Number of Household Members, 2005 Total... 111.1 30.0 34.8 18.4...

368

Socioeconomic Differences in Household Automobile Ownership Rates: Implications for Evacuation Policy  

E-Print Network [OSTI]

Differences in 10 Household Automobile Ownership Rates:hauseltoldr lacking automobiles were mmit like! ) to be leftWithout 3 Access to an Automobile. Top Ten Metropolitan

Raphael, S; Berube, A; Deakin, Elizabeth

2006-01-01T23:59:59.000Z

369

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

370

Household environmental monitoring a strategy to help homeowners reduce their environmental impact  

Science Journals Connector (OSTI)

A group of 20 households was established to study whether we can motivate environmentally sustainable behaviour by providing homeowners with a clear picture of their impact, tangible reasons for improvement, and tailored solutions to follow. Reports for each household compared heating fuel, electricity, water, vehicle fuel/waste generation within the group and recommended cost-effective measures to reduce consumption. On average, 26% of the recommended measures were implemented, resulting in an estimated greenhouse gas reduction of about 2 tonnes per household. Wide variations were found between households, demonstrating the potential to reduce environmental impact through lifestyle, conservation, and energy conscious retrofits.

Jane Thompson; Magda Goemans; Peter C. Goemans; Andrzej Wisniowski

2008-01-01T23:59:59.000Z

371

An analysis of residential energy consumption and expenditures by minority households by home type and housing vintage  

SciTech Connect (OSTI)

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

372

An analysis of residential energy consumption and expenditures by minority households by home type and housing vintage  

SciTech Connect (OSTI)

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

373

Control of household refrigerators. Part 1: Modeling temperature control performance  

SciTech Connect (OSTI)

Commercial household refrigerators use simple, cost-effective, temperature controllers to obtain acceptable control. A manually adjusted airflow damper regulates the freezer compartment temperature while a thermostat controls operation of the compressor and evaporator fan to regulate refrigerator compartment temperature. Dual compartment temperature control can be achieved with automatic airflow dampers that function independently of the compressor and evaporator fan thermostat, resulting in improved temperature control quality and energy consumption. Under dual control, freezer temperature is controlled by the thermostat while the damper controls refrigerator temperature by regulating airflow circulation. A simulation model is presented that analyzes a household refrigerator configured with a conventional thermostat and both manual and automatic dampers. The model provides a new paradigm for investigating refrigerator systems and temperature control performance relative to the extensive verification testing that is typically done by manufacturers. The effects of each type of control and damper configuration are compared with respect to energy usage, control quality, and ambient temperature shift criteria. The results indicate that the appropriate control configuration can have significant effects and can improve plant performance.

Graviss, K.J.; Collins, R.L.

1999-07-01T23:59:59.000Z

374

Environmental attitudes and household consumption: an ambiguous relationship  

Science Journals Connector (OSTI)

This article analyses the relationship between environmental attitudes and energy use in the home and for transport by Norwegian households. Quantitative surveys were used to find statistical correlations, and qualitative analyses to reveal mechanisms that influence the ability to behave in an environmentally friendly way. Three theses about attitudes, mechanisms and household consumption are presented. Firstly, a desire to project an environmentally friendly image has little influence on energy use in the home and for transport. Secondly, a sense of powerlessness prevents people from translating positive environmental attitudes into low energy use in the home and for everyday transport. Thirdly, a desire to self-indulge prevents people from translating positive environmental attitudes into low energy use for long distance leisure travel. These results have important implications for environmental policy. Public information and awareness campaigns can give consumers information on how to behave in an environmentally responsible way, but tend only to influence categories of consumption with little environmental impact. Structural change can be used to mitigate the effect of the sense of powerlessness and encourage environmentally friendly behaviour, but the desire to self-indulge is much more difficult to deal with.

Erling Holden; Kristin Linnerud

2010-01-01T23:59:59.000Z

375

Household demand and willingness to pay for hybrid vehicles  

Science Journals Connector (OSTI)

Abstract This paper quantitatively evaluates consumers' willingness to pay for hybrid vehicles by estimating the demand of hybrid vehicles in the U.S. market. Using micro-level data on consumer purchases of hybrid and non-hybrid vehicles from National Household Travel Survey 2009, this paper formulates a mixed logit model of consumers' vehicle choices. Parameter estimates are then used to evaluate consumers' willingness to pay for hybrids. Results suggest that households' willingness to pay for hybrids ranges from $963 to $1718 for different income groups, which is significantly lower than the average price premium (over $5000) of hybrid vehicles, even when taking the fuel costs savings of hybrid vehicles into consideration. The differences reveal that although the market has shown increasing interest in hybrid vehicles, consumers' valuation of the hybrid feature is still not high enough to compensate for the price premium when they make new purchases. Policy simulations are conducted to examine the effects of raising federal tax incentives on the purchase of hybrid vehicles.

Yizao Liu

2014-01-01T23:59:59.000Z

376

"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

377

"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

378

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

379

Using Multiple Household Food Inventories to Measure Food Availability in the Home  

E-Print Network [OSTI]

-home assessment included an audio recorded interview on food habits and beliefs. Complete data were collected from all 9 women (32.8 y +/- 6.0; 3 married; 4 +/- 1.6 adults/children in household; 4 SNAP; 6 food insecure) and their households. Weekly grocery...

Sisk, Cheree L.

2010-10-12T23:59:59.000Z

380

Dimethyl ether (DME) from coal as a household cooking fuel in China  

E-Print Network [OSTI]

technologies. Given China's rich coal resources, the production and use of coal-derived DME as a cooking fuelDimethyl ether (DME) from coal as a household cooking fuel in China Eric D. Larson Princeton gas (LPG) as a household cooking fuel. As such, DME is an attractive fuel for clean cooking. DME can

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

Socioeconomic Differences in Household Automobile Ownership Rates: Implications for Evacuation Policy  

E-Print Network [OSTI]

Socioeconomic Differences in Household Automobile Ownership Rates: Implications for Evacuation's aftermath concerned the size and composition of the area's populations that lacked access to an automobile for all U.S. metropolitan areas that reside in a household without access to an automobile. Finally, we

Sekhon, Jasjeet S.

382

The Driving Internal Beliefs of Household Internet Adoption among Jordanians and the Role of Cultural Values  

Science Journals Connector (OSTI)

The purpose of this study is to develop and validate a comprehensive model for the determinants of household Internet adoption through identifying the driving internal beliefs of individuals and the effect of cultural values on behavioral intention to ... Keywords: Hofstede's Cultural Dimensions, Household Internet Adoption, Internal Beliefs, Micro Cultural Level, Perceived Risks, Technology Acceptance Model

Amin A. Shaqrah; Khaled Saleh Al Omoush; Raed Musbah Alqirem

2011-01-01T23:59:59.000Z

383

Particle and Gas Emissions from a Simulated Coal-Burning Household Fire Pit  

Science Journals Connector (OSTI)

Particle and Gas Emissions from a Simulated Coal-Burning Household Fire Pit ... Chinese anthracite and bituminous coals produce different amounts of emissions when burned in a fire pit that simulates common rural household use of these fuels. ... Here we present emissions from burning 15 different fuels in a laboratory system designed to mimic the fire pits used in Xuan Wei County, China. ...

Linwei Tian; Donald Lucas; Susan L. Fischer; S. C. Lee; S. Katharine Hammond; Catherine P. Koshland

2008-02-21T23:59:59.000Z

384

Journal: Ecological Applications1 Carbon, nitrogen, and phosphorus fluxes in household ecosystems in the3  

E-Print Network [OSTI]

#12;1 Journal: Ecological Applications1 2 Carbon, nitrogen, and phosphorus fluxes in household Resources Center, Saint Paul, MN 551089 3 University of Minnesota, Department of Ecology, Evolution with several29 components of household activities including air and motor vehicle travel, food consumption,30

Minnesota, University of

385

Flame Retardant Transfers from U.S. Households (Dust and Laundry Wastewater) to the Aquatic Environment  

Science Journals Connector (OSTI)

Analytes were ionized by APPI; dopant (acetone) was introduced (150 ?L/min) by a liquid chromatography pump (LC-20AD, Shimadzu Corporation, Kyoto, Japan). ... We collected repeat dust samples from 292 households in the Northern California Childhood Leukemia Study during two sampling rounds (from 2001 to 2007 and during 2010) using household vacuum cleaners and measured 22 PBDEs using high resoln. ...

Erika D. Schreder; Mark J. La Guardia

2014-09-17T23:59:59.000Z

386

Passive sampling methods to determine household and personal care product use  

E-Print Network [OSTI]

Passive sampling methods to determine household and personal care product use DEBORAH H. BENNETTa, cleaning products, passive sampling, SUPERB, longitudinal. Introduction Personal care and household care products, such as cleaning products and pesticides, are frequently used in most house- holds although

Leistikow, Bruce N.

387

A HERSCHEL AND APEX CENSUS OF THE REDDEST SOURCES IN ORION: SEARCHING FOR THE YOUNGEST PROTOSTARS  

SciTech Connect (OSTI)

We perform a census of the reddest, and potentially youngest, protostars in the Orion molecular clouds using data obtained with the PACS instrument on board the Herschel Space Observatory and the LABOCA and SABOCA instruments on APEX as part of the Herschel Orion Protostar Survey (HOPS). A total of 55 new protostar candidates are detected at 70 {mu}m and 160 {mu}m that are either too faint (m{sub 24} > 7 mag) to be reliably classified as protostars or undetected in the Spitzer/MIPS 24 {mu}m band. We find that the 11 reddest protostar candidates with log {lambda}F{sub {lambda}}70/{lambda}F{sub {lambda}}24 > 1.65 are free of contamination and can thus be reliably explained as protostars. The remaining 44 sources have less extreme 70/24 colors, fainter 70 {mu}m fluxes, and higher levels of contamination. Taking the previously known sample of Spitzer protostars and the new sample together, we find 18 sources that have log {lambda}F{sub {lambda}}70/{lambda}F{sub {lambda}}24 > 1.65; we name these sources 'PACS Bright Red sources', or PBRs. Our analysis reveals that the PBR sample is composed of Class 0 like sources characterized by very red spectral energy distributions (SEDs; T{sub bol} < 45 K) and large values of sub-millimeter fluxes (L{sub smm}/L{sub bol} > 0.6%). Modified blackbody fits to the SEDs provide lower limits to the envelope masses of 0.2-2 M{sub Sun} and luminosities of 0.7-10 L{sub Sun }. Based on these properties, and a comparison of the SEDs with radiative transfer models of protostars, we conclude that the PBRs are most likely extreme Class 0 objects distinguished by higher than typical envelope densities and hence, high mass infall rates.

Stutz, Amelia M.; Robitaille, Thomas; Henning, Thomas; Krause, Oliver [Max Planck Institute for Astronomy, Koenigstuhl 17, D-69117 Heidelberg (Germany)] [Max Planck Institute for Astronomy, Koenigstuhl 17, D-69117 Heidelberg (Germany); Tobin, John J. [National Radio Astronomy Observatory, Charlottesville, VA 22903 (United States)] [National Radio Astronomy Observatory, Charlottesville, VA 22903 (United States); Stanke, Thomas [ESO, Karl-Schwarzschild-Strasse 2, D-85748 Garching bei Muenchen (Germany)] [ESO, Karl-Schwarzschild-Strasse 2, D-85748 Garching bei Muenchen (Germany); Megeath, S. Thomas; Fischer, William J. [Department of Physics and Astronomy, University of Toledo, 2801 W. Bancroft Street, Toledo, OH 43606 (United States)] [Department of Physics and Astronomy, University of Toledo, 2801 W. Bancroft Street, Toledo, OH 43606 (United States); Ali, Babar; Furlan, Elise [NHSC/IPAC/Caltech, 770 S. Wilson Avenue, Pasadena, CA 91125 (United States)] [NHSC/IPAC/Caltech, 770 S. Wilson Avenue, Pasadena, CA 91125 (United States); Di Francesco, James [National Research Council of Canada, Herzberg Institute of Astrophysics, 5071 West Saanich Road, Victoria, BC V9E 2E7 (Canada)] [National Research Council of Canada, Herzberg Institute of Astrophysics, 5071 West Saanich Road, Victoria, BC V9E 2E7 (Canada); Hartmann, Lee [Department of Astronomy, University of Michigan, 830 Dennison Building, 500 Church Street, Ann Arbor, MI 48109 (United States)] [Department of Astronomy, University of Michigan, 830 Dennison Building, 500 Church Street, Ann Arbor, MI 48109 (United States); Osorio, Mayra [Instituto de Astrofisica de Andalucia, CSIC, Camino Bajo de Huetor 50, E-18008 Granada (Spain)] [Instituto de Astrofisica de Andalucia, CSIC, Camino Bajo de Huetor 50, E-18008 Granada (Spain); Wilson, Thomas L. [Naval Research Laboratory, 4555 Overlook Avenue SW, Washington, DC 20375 (United States)] [Naval Research Laboratory, 4555 Overlook Avenue SW, Washington, DC 20375 (United States); Allen, Lori [National Optical Astronomy Observatory, 950 North Cherry Avenue, Tucson, AZ 85719 (United States)] [National Optical Astronomy Observatory, 950 North Cherry Avenue, Tucson, AZ 85719 (United States); Manoj, P., E-mail: stutz@mpia.de [Department of Physics and Astronomy, 500 Wilson Boulevard, University of Rochester, Rochester, NY 14627 (United States)

2013-04-10T23:59:59.000Z

388

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

389

How Do You Encourage Everyone in Your Household to Save Energy? |  

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

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?

390

How Do You Encourage Everyone in Your Household to Save Energy? |  

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

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?

391

Lifestyle change and energy use in Japan: Household equipment and energy consumption  

Science Journals Connector (OSTI)

Energy use in the Japanese residential sector has more than doubled (on a per-household basis) during the post-war period. Important factors contributing to the increase include changes in the types of housing built, heating, cooling, water-heating equipment, and other appliances. In this paper, the developments of household equipment and living conditions in Japan are described, from their 1950s state to the present. Trends in energy consumption by fuel types and end uses are reviewed over the same period. The past trends are combined with expectations for future developments in household equipment and quality, as well as with international comparisons of household-energy use, to predict further increases in household-energy consumption. The results indicate the importance of a renewed emphasis on energy efficiency in the residential sector.

Hidetoshi Nakagami

1996-01-01T23:59:59.000Z

392

Interaction between building design, management, household and individual factors in relation to energy use for space heating in apartment buildings  

Science Journals Connector (OSTI)

Abstract In Stockholm, 472 multi-family buildings with 7554 dwellings has been selected by stratified random sampling. Information about building characteristics and property management was gathered from each property owners. Energy use for space heating was collected from the utility company. Perceived thermal comfort, household and personal factors were assessed by a standardized self-administered questionnaire, answered by one adult person in each dwelling, and a proportion of each factor was calculated for each building. Statistical analysis was performed by multiple linear regression models with control for relevant factors all at the same time in the model. Energy use for heating was significantly related to the building age, type of building and ventilation, length of time since the last heating adjustment, ownership form, proportion of females, and proportion of occupants expressing thermal discomfort. How beneficial energy efficiency measures will be may depend on the relationship between energy use and factors related to the building and the property maintenance together with household and personal factors, as all these factors interact with each other. The results show that greater focus should be on real estate management and maintenance and also a need for research with a gender perspective on energy use for space heating.

Karin Engvall; Erik Lampa; Per Levin; Per Wickman; Egil Öfverholm

2014-01-01T23:59:59.000Z

393

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...

Arlikatti, Sudha S

2006-10-30T23:59:59.000Z

394

2014 Virginia Polytechnic Institute and State University BSE-158NP Household Water Quality in Loudoun County, Virginia  

E-Print Network [OSTI]

2014 Virginia Polytechnic Institute and State University BSE-158NP Household Water Quality in Loudoun County, Virginia OCTOBER 2013 VIRGINIA HOUSEHOLD WATER QUALITY PROGRAM Erin Ling, Water Quality Extension Associate, and Brian Benham, Extension Specialist and Professor

Liskiewicz, Maciej

395

2014 Virginia Polytechnic Institute and State University BSE-151NP Household Water Quality in Albemarle County, Virginia  

E-Print Network [OSTI]

2014 Virginia Polytechnic Institute and State University BSE-151NP Household Water Quality in Albemarle County, Virginia APRIL 2013 VIRGINIA HOUSEHOLD WATER QUALITY PROGRAM Erin Ling, Water Quality Extension Associate, and Brian Benham, Extension Specialist and Professor

Liskiewicz, Maciej

396

2014 Virginia Polytechnic Institute and State University BSE-162NP Household Water Quality in Pittsylvania County, Virginia  

E-Print Network [OSTI]

2014 Virginia Polytechnic Institute and State University BSE-162NP Household Water Quality in Pittsylvania County, Virginia OCTOBER 2013 VIRGINIA HOUSEHOLD WATER QUALITY PROGRAM Erin Ling, Water Quality Extension Associate, and Brian Benham, Extension Specialist and Professor

Liskiewicz, Maciej

397

Community Rating, Cross Subsidies and Underinsurance: Why so many Households in Japan do not Purchase Earthquake Insurance  

Science Journals Connector (OSTI)

Japan is famous for its earthquakes. According to ... survey, however, only 20% of Japanese households purchased an earthquake insurance policy in 2005. Why do so many households in Japan not purchase earthquake ...

Michio Naoi; Miki Seko; Kazuto Sumita

2010-05-01T23:59:59.000Z

398

Commercial viability of hybrid vehicles : best household use and cross national considerations.  

SciTech Connect (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

399

A CENSUS OF STAR-FORMING GALAXIES AT z = 1-3 IN THE SUBARU DEEP FIELD  

SciTech Connect (OSTI)

Several UV and near-infrared color selection methods have identified galaxies at z = 1-3. Since each method suffers from selection biases, we have simultaneously applied three leading techniques (Lyman break, BX/BM, and BzK selection) in the Subaru Deep Field. This field has reliable ({Delta}z/(1 + z) = 0.02-0.09) photometric redshifts for {approx}53,000 galaxies from 20 bands (1500 A-2.2 {mu}m). The BzK, LBG, and BX/BM samples suffer contamination from z < 1 interlopers of 6%, 8%, and 20%, respectively. Around the redshifts where it is most sensitive (z {approx} 1.9 for star-forming BzK, z {approx} 1.8 for z {approx} 2 LBGs, z {approx} 1.6 for BM, and z {approx} 2.3 for BX), each technique finds 60%-80% of the census of the three methods. In addition, each of the color techniques shares 75%-96% of its galaxies with another method, which is consistent with previous studies that adopt identical criteria on magnitudes and colors. Combining the three samples gives a comprehensive census that includes {approx}90% of z{sub phot} = 1-3 galaxies, using standard magnitude limits similar to previous studies. In fact, we find that among z = 1-2.5 galaxies in the color selection census, 81%-90% of them can be selected by just combining the BzK selection with one of the UV techniques (z {approx} 2 LBG or BX and BM). The average galaxy stellar mass, reddening, and star formation rates (SFRs) all decrease systematically from the sBzK population to the LBGs, and to the BX/BMs. The combined color selections yield a total cosmic SFR density of 0.18 {+-} 0.03 M{sub sun} yr{sup -1} Mpc{sup -3} for K{sub AB} {approx}< 24. We find that 65% of the star formation is in galaxies with E(B - V) > 0.25 mag, even though they are only one-fourth of the census by number.

Ly, Chun; Malkan, Matthew A. [Department of Physics and Astronomy, UCLA, Box 951547, Los Angeles, CA (United States); Hayashi, Masao; Shimasaku, Kazuhiro [Department of Astronomy, School of Science, University of Tokyo, Bunkyo, Tokyo (Japan); Motohara, Kentaro [Institute of Astronomy, University of Tokyo, Mitaka, Tokyo (Japan); Kashikawa, Nobunari [Optical and Infrared Astronomy Division, National Astronomical Observatory, Mitaka, Tokyo (Japan); Nagao, Tohru [The Hakubi Project, Kyoto University, Kyoto (Japan); Grady, Celestine, E-mail: chunly@stsci.edu [Department of Applied Science, UC Davis, Davis, CA (United States)

2011-07-10T23:59:59.000Z

400

Household equipment of Canadians -- features of the 1993 stock and the 1994 and 1995 purchases: Analysis report  

SciTech Connect (OSTI)

This report reviews the results of three surveys that collected information on household equipment: The 1994 and 1995 Household Equipment Surveys and the 1993 Survey of Household Energy Use. The goal of the report is to highlight the features of energy-consuming equipment bought by Canadian households in 1994 and 1995 in comparison to those owned by households in 1993. Results are presented by type of equipment: Refrigerators, stoves, dishwashers, freezers, automatic washers, automatic dryers, air conditioning systems, heating systems, and water heaters. Appendices include information on survey methodology and a copy of the survey questionnaire.

Not Available

1997-01-01T23:59:59.000Z

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.


401

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)

402

Analysis of household refrigerators for different testing standards  

SciTech Connect (OSTI)

This study highlights the salient differences among various testing standards for household refrigerator-freezers and proposes a methodology for predicting the performance of a single evaporator-based vapor-compression refrigeration system (either refrigerator or freezer) from one test standard (where the test data are available-the reference case) to another (the alternative case). The standards studied during this investigation include the Australian-New Zealand Standard (ANZS), the International Standard (ISO), the American National Standard (ANSI), the Japanese Industrial Standard (JIS), and the Chinese National Standard (CNS). A simple analysis in conjunction with the BICYCLE model (Bansal and Rice 1993) is used to calculate the energy consumption of two refrigerator cabinets from the reference case to the alternative cases. The proposed analysis includes the effect of door openings (as required by the JIS) as well as defrost heaters. The analytical results are found to agree reasonably well with the experimental observations for translating energy consumption information from one standard to another.

Bansal, P.K. [Univ. of Auckland (New Zealand). Dept. of Mechanical Engineering; McGill, I. [Fischer and Paykel Ltd., Auckland (New Zealand)

1995-08-01T23:59:59.000Z

403

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

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

2 Average Square Footage of South Homes, by Housing Characteristics, 2009" 2 Average Square Footage of South 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 South",42.1,1867,1637,1549,732,642,607 "South Divisions and States" "South Atlantic",22.2,1944,1687,1596,771,668,633 "Virginia",3,2227,1977,1802,855,759,692 "Georgia",3.5,2304,1983,1906,855,736,707 "Florida",7,1668,1432,1509,690,593,625 "DC, DE, MD, WV",3.4,2218,1831,1440,864,713,561

404

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

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

0 Average Square Footage of Northeast Homes, by Housing Characteristics, 2009" 0 Average Square Footage of Northeast 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 Northeast",20.8,2121,1663,921,836,656,363 "Northeast Divisions and States" "New England",5.5,2232,1680,625,903,680,253 "Massachusetts",2.5,2076,1556,676,850,637,277 "CT, ME, NH, RI, VT",3,2360,1781,583,946,714,234 "Mid-Atlantic",15.3,2080,1657,1028,813,647,402

405

Solar disinfection: an approach for low-cost household water treatment technology in Southwestern Ethiopia  

Science Journals Connector (OSTI)

Disinfection of contaminated water using solar radiation (SODIS) is known to inactivate ... study was aiming to test the efficiency of solar disinfection using different water parameters as low-cost household wat...

Awrajaw Dessie; Esayas Alemayehu…

2014-01-01T23:59:59.000Z

406

Metering Campaign on All Cooking End-Uses in 100 Households  

Science Journals Connector (OSTI)

This paper presents the findings of an experimental study performed in 100 French households on the end-use power demand and energy consumption of domestic appliances focusing on cooking appliances [1].

Olivier Sidler

2001-01-01T23:59:59.000Z

407

Monitoring effective use of household water treatment and safe storage technologies in Ethiopia and Ghana  

E-Print Network [OSTI]

Household water treatment and storage (HWTS) technologies dissemination is beginning to scale-up to reach the almost 900 million people without access to an improved water supply (WHO/UNICEF/JMP, 2008). Without well-informed ...

Stevenson, Matthew M

2009-01-01T23:59:59.000Z

408

9 - Chinese healthcare system reforms and household saving patterns: some stylised facts  

Science Journals Connector (OSTI)

Abstract: This chapter aims to evaluate the relationship between one of the recent healthcare reforms in the People’s Republic of China and household decisions both in terms of out-of-pocket expenditure and saving. Evidence on the results achieved by reforms of the health insurance sector in terms of reducing out-of-pocket medical expenditure is still uncertain and contradictory, and very little is known about the effect of these measures on the consumption and saving behaviour of the Chinese population. To shed light on this issue we use data collected by Chinese Household Income Project surveys (CHIPs), through a series of questionnaire-based interviews conducted in urban areas in 1995 and 2002. Our descriptive analysis suggests that there is a positive relationship between public health insurance coverage and household saving. This empirical evidence suggests that public insurance coverage is ineffective as a source of protection against income losses and might induce households to save more.

Vincenzo Atella; Agar Brugiavini; Hao Chen; Noemi Pace

2014-01-01T23:59:59.000Z

409

Household technology adoption in a global marketplace: Incorporating the role of espoused cultural values  

Science Journals Connector (OSTI)

While MATH and the extended MATH have done an excellent job in explaining household technology adoption, there is still room for advancing our understanding of this phenomenon in light of the complexities embo...

Xiaojun Zhang; Likoebe M. Maruping

2008-09-01T23:59:59.000Z

410

Distributional Impacts of Carbon Pricing: A General Equilibrium Approach with Micro-Data for Households  

E-Print Network [OSTI]

Many policies to limit greenhouse gas emissions have at their core efforts to put a price on carbon emissions. Carbon pricing impacts households both by raising the cost of carbon intensive products and by changing factor ...

Rausch, Sebastian

411

Fact #748: October 8, 2012 Components of Household Expenditures on Transportation, 1984-2010  

Broader source: Energy.gov [DOE]

The overall share of annual household expenditures for transportation was lower in 2010 than it was in 1984, reaching its lowest point in 2009 at 15.5%. In the early to mid-1980s when oil prices...

412

Essays on Price Dynamics, Welfare Analysis, Household Food Insecurity in Mexico  

E-Print Network [OSTI]

prices, and determinants of household food insecurity are discussed and presented in three separate essays. In the first essay, the dynamic information flows among prices of important agricultural commodities in the United States (U.S.) and Mexico...

Magana Lemus, David

2013-09-20T23:59:59.000Z

413

Race, median household income, and primary Grade IV glioma treatment patterns  

Science Journals Connector (OSTI)

...behaviors among a population of Hispanic origin. Daisy Gonzalez 1...population subgroups, including Hispanics. Objective: This study assessed...population-based sample of Hispanic women in PR. Methods: This...complex sampling design of households in the San Juan Metropolitan...

Jill S. Barnholtz-Sloan; Vonetta L. Williams; Marc Chamberlain; and Andrew E. Sloan

2006-04-15T23:59:59.000Z

414

Household structure and labor force participation of black, hispanic, and white mothers  

Science Journals Connector (OSTI)

This paper investigates whether the inclusion of nonnuclear adults in a household facilitates the labor force participation of single and married mothers. Results based on a sample of extended and nuclear hous...

Marta Tienda; Jennifer Glass

1985-08-01T23:59:59.000Z

415

Drivers of U.S. Household Energy Consumption, 1980-2009  

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

Drivers of U.S. Household Energy Consumption, 1980-2009 February 2015 Independent Statistics & Analysis www.eia.gov U.S. Department of Energy Washington, DC 20585 U.S. Energy...

416

A Dynamic household Alternative-fuel Vehicle Demand Model Using Stated and Revealed Transaction Information  

E-Print Network [OSTI]

market share for alternative-fuel vehicles drop from thePreferences for Alternative-Fuel Vehicles”, Brownstone DavidA Dynamic Household Alternative-fuel Vehicle Demand Model

Sheng, Hongyan

1999-01-01T23:59:59.000Z

417

The Relationship Between Life Satisfaction Among Wives and Financial Preparedness of Households in Japan  

Science Journals Connector (OSTI)

The wealth gap between the rich and poor is widening and contributing to Japan’s shrinking middle class. This study examined ... future and life satisfaction and their association with household financial prepare...

Yoko Mimura

2014-02-01T23:59:59.000Z

418

Modelling useful energy demand system as derived from basic needs in the household sector  

Science Journals Connector (OSTI)

Inter-fuel substitution in the household sector depends on whether their target energy use is similar or not. To account ... for the effect of end-use application on energy demand, the concept of useful energy is...

Zahra A. Barkhordar; Yadollah Saboohi

2014-10-01T23:59:59.000Z

419

Development of the Household Sample for Furnace and Boiler Life-Cycle Cost  

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

Development of the Household Sample for Furnace and Boiler Life-Cycle Cost Development of the Household Sample for Furnace and Boiler Life-Cycle Cost Analysis Title Development of the Household Sample for Furnace and Boiler Life-Cycle Cost Analysis Publication Type Report LBNL Report Number LBNL-55088 Year of Publication 2005 Authors Whitehead, Camilla Dunham, Victor H. Franco, Alexander B. Lekov, and James D. Lutz Document Number LBNL-55088 Pagination 22 Date Published May 31 Publisher Lawrence Berkeley National Laboratory City Berkeley Abstract Residential household space heating energy use comprises close to half of all residential energy consumption. Currently, average space heating use by household is 43.9 Mbtu for a year. An average, however, does not reflect regional variation in heating practices, energy costs, or fuel type. Indeed, a national average does not capture regional or consumer group cost impacts from changing efficiency levels of heating equipment. The US Department of Energy sets energy standards for residential appliances in, what is called, a rulemaking process. The residential furnace and boiler efficiency rulemaking process investigates the costs and benefits of possible updates to the current minimum efficiency regulations. Lawrence Berkeley National Laboratory (LBNL) selected the sample used in the residential furnace and boiler efficiency rulemaking from publically available data representing United States residences. The sample represents 107 million 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 rulemaking. This paper describes the choice of criteria to select the sample of houses used in the rulemaking process. The process of data extraction is detailed in the appendices and is easily duplicated.The life-cycle cost is calculated in two ways with a household marginal energy price and a national average energy price. The LCC results show that using an national average energy price produces higher LCC savings but does not reflect regional differences in energy price.

420

A Mixed Nordic Experience: Implementing Competitive Retail Electricity Markets for Household Customers  

SciTech Connect (OSTI)

Although the Nordic countries were among the first to develop competition in the electricity industry, it took a long time to make retail competition work. In Norway and Sweden a considerable number of households are actively using the market but very few households are active in Finland and Denmark. One problem has been institutional barriers involving metering, limited unbundling of distribution and supply, and limited access to reliable information on contracts and prices. (author)

Olsen, Ole Jess; Johnsen, Tor Arnt; Lewis, Philip

2006-11-15T23:59:59.000Z

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

The Determinants of Homeonwership in Presence of Shocks Experienced by Mexican Households  

E-Print Network [OSTI]

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 Direct Rural Support of Mexico (PROGRESA) and the Program of Direct Rural Support of Mexico (PROCAMPO), appear to be increasing iii homeownership. These social welfare programs provide cash transfers to households. For whatever reason, PROGRESA...

Lopez Cabrera, Jesus Antonio 1977-

2012-11-05T23:59:59.000Z

422

Applications of demand analysis for the dairy industry using household scanner data  

E-Print Network [OSTI]

Education 7 10 Martial Status 5 11 Male Head Occupation 12 12 Female Head Occupation 12 13 Household Composition 8 14 Race 4 15 Hispanic Origin 2 16 Region 4 17 Scantrack Market Identifier 53 18 Projection Factor 1... classified as either Hispanic or not Hispanic, with 18% being Hispanic and 82% not Hispanic. Since female household heads are considered primary to making food purchase decisions some key statistics about this demographic variable are included. Of all...

Stockton, Matthew C.

2005-02-17T23:59:59.000Z

423

Household Light Makes Global Heat: High Black Carbon Emissions From Kerosene Wick Lamps  

Science Journals Connector (OSTI)

(3) Lighting is another component of this household energy challenge, with millions of households still relying on simple liquid-fueled lamps, but little is known of the associated environmental and health impacts. ... For laboratory tests, CO2 and CO concentrations were measured in real-time with a Li-COR 6252 (Li-COR Biosciences, Lincoln, NE) and Horiba AIA-220 (Horiba, Kyoto, Japan) nondispersive infrared (NDIR) analyzer, respectively. ...

Nicholas L. Lam; Yanju Chen; Cheryl Weyant; Chandra Venkataraman; Pankaj Sadavarte; Michael A. Johnson; Kirk R. Smith; Benjamin T. Brem; Joseph Arineitwe; Justin E. Ellis; Tami C. Bond

2012-11-19T23:59:59.000Z

424

Arsenic Removal from Groundwater by Household Sand Filters:? Comparative Field Study, Model Calculations, and Health Benefits  

Science Journals Connector (OSTI)

Arsenic Removal from Groundwater by Household Sand Filters:? Comparative Field Study, Model Calculations, and Health Benefits ... Simultaneously, raw groundwater from the same households and additional 31 tubewells was sampled to investigate arsenic coprecipitation with hydrous ferric iron from solution, i.e., without contact to sand surfaces. ... Concentra tions of total Fe, Mn, Na, K, Mg, and Ca were quantified by atomic absorption spectroscopy (Shimadzu AA-6800, Kyoto, Japan). ...

Michael Berg; Samuel Luzi; Pham Thi Kim Trang; Pham Hung Viet; Walter Giger; Doris Stüben

2006-07-19T23:59:59.000Z

425

"Table HC15.1 Housing Unit Characteristics by Four Most Populated States, 2005"  

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

Housing Unit Characteristics by Four Most Populated States, 2005" Housing Unit Characteristics by Four Most Populated States, 2005" " Million Housing Units" ,"U.S. Housing Units (millions)","Four Most Populated States" "Housing Unit Characteristics",,"New York","Florida","Texas","California" "Total",111.1,7.1,7,8,12.1 "Census Region and Division" "Northeast",20.6,7.1,"N","N","N" "New England",5.5,"N","N","N","N" "Middle Atlantic",15.1,7.1,"N","N","N" "Midwest",25.6,"N","N","N","N" "East North Central",17.7,"N","N","N","N"

426

" Million Housing Units, Final...  

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

0 Household Demographics of Homes in South Region, Divisions, and States, 2009" " Million Housing Units, Final" ,,"South Census Region" ,,,"South Atlantic Census...

427

" Million Housing Units, Final...  

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

1 Household Demographics of Homes in West Region, Divisions, and States, 2009" " Million Housing Units, Final" ,,"West Census Region" ,,,"Mountain Census Division",,,"Pacific...

428

" Million Housing Units, Final...  

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

9 Household Demographics of Homes in Midwest Region, Divisions, and States, 2009" " Million Housing Units, Final" ,,"Midwest Census Region" ,,,"East North Central Census...

429

The impact of the Persian Gulf crisis on household energy consumption and expenditure patterns  

SciTech Connect (OSTI)

The Iraqi invasion of the Kingdom of Kuwait on August 2, 1990, and the subsequent war between Iraq and an international alliance led by the United States triggered first immediate and then fluctuating world petroleum prices. Increases in petroleum prices and in U.S. petroleum imports resulted in increases in the petroleum prices paid by U.S. residential, commercial, and industrial consumers. The result was an immediate price shock that reverberated throughout the U.S. economy. The differential impact of these price increases and fluctuations on poor and minority households raised immediate, significant, and potentially long-term research, policy, and management issues for a variety of federal, state, and local government agencies, including the U.S. Department of Energy (DOE). Among these issues are (1) the measurement of variations in the impact of petroleum price changes on poor, nonpoor, minority, and majority households; (2) how to use the existing policy resources and policy innovation to mitigate regressive impacts of petroleum price increases on lower-income households; and (3) how to pursue such policy mitigation through government agencies severely circumscribed by tax and expenditure limitations. Few models attempt to assess household energy consumption and energy expenditure under various alternative price scenarios and with respect to the inclusion of differential household choices correlated with such variables as race, ethnicity, income, and geographic location. This paper provides a preliminary analysis of the nature and extent of potential impacts of petroleum price changes attributable to the Persian Gulf War and its aftermath on majority, black, and Hispanic households and on overlapping poor and nonpoor households. At the time this was written, the Persian Gulf War had concluded with Iraq`s total surrender to all of the resolutions and demands of the United Nations and United States.

Henderson, L. [Univ. of Baltimore, MD (United States); Poyer, D.; Teotia, A. [Argonne National Lab., IL (United States)

1994-09-01T23:59:59.000Z

430

Evaluation of the soft measures' effects on ambient water quality improvement and household and industry economies  

Science Journals Connector (OSTI)

Abstract Various ecological footprint calculators, carbon footprint calculators and water footprint calculators have been developed in recent years. The basic concepts of ecological behaviour record notebooks and of carbon dioxide emission calculators have been developed since the late 20th century. The first carbon dioxide emission calculator was developed in 1991. Likewise, water pollutant discharge calculators have been developed to estimate the effects of soft measures introduced into households to reduce pollutant discharge since 2004. The soft measures which have been developed in Japan may consist of a wider framework, household sustainable consumption, which has been developed in Europe, and can be referred to cleaner consumption. In this research, summarisation of the short history of ecological behaviour record notebooks and ecological footprint calculators in Japan since the 1980s was conducted, and the soft measures in households to reduce pollutant discharge were evaluated for their effects on ambient water quality improvement as well as household and industry economies. Effects of the soft measures on related industry economies were investigated using an Input–Output Table analysis and the effects of the imported goods were evaluated with an import effect matrix, which was developed in this research. The effects of the soft measures on household expenditures were estimated to be a decrease by 2.5% or USD 285 person?1 year?1 in 2003–2006. The results show that the soft measures positively affect the chemical fibre industry and significantly affect the detergent industry. Analysis of the import effect matrix proved that the six industries were tightly related through extensive amounts of imported goods. The soft measures in households may lead to household sustainable consumption and thus reduce disadvantageous human impacts on water environments. The effects of the measures introduced to improve the environment should be qualitatively and quantitatively evaluated to avoid redundant concerns and discord between the environment and the economy, which may be worried when the relationship is not well understood.

Yoshiaki Tsuzuki

2014-01-01T23:59:59.000Z

431

CHANDRA ORION ULTRADEEP PROJECT CENSUS OF X-RAY STARS IN THE BN-KL AND OMC-1S REGIONS N. Grosso,1  

E-Print Network [OSTI]

CHANDRA ORION ULTRADEEP PROJECT CENSUS OF X-RAY STARS IN THE BN-KL AND OMC-1S REGIONS N. Grosso,1 E), as seen in the exceptionally deep ($10 days) exposure of the Chandra Orion Ultradeep Project (COUP). We (collectively BN-KL) and a 6000 ; 7500 region around OMC-1S, a secondary star- forming peak some 9000 south

Micela, Giusi

432

Greenhouse gas emissions from home composting of organic household waste  

SciTech Connect (OSTI)

The emission of greenhouse gases (GHGs) is a potential environmental disadvantage of home composting. Because of a lack of reliable GHG emission data, a comprehensive experimental home composting system was set up. The system consisted of six composting units, and a static flux chamber method was used to measure and quantify the GHG emissions for one year composting of organic household waste (OHW). The average OHW input in the six composting units was 2.6-3.5 kg week{sup -1} and the temperature inside the composting units was in all cases only a few degrees (2-10 {sup o}C) higher than the ambient temperature. The emissions of methane (CH{sub 4}) and nitrous oxide (N{sub 2}O) were quantified as 0.4-4.2 kg CH{sub 4} Mg{sup -1} input wet waste (ww) and 0.30-0.55 kg N{sub 2}O Mg{sup -1} ww, depending on the mixing frequency. This corresponds to emission factors (EFs) (including only CH{sub 4} and N{sub 2}O emissions) of 100-239 kg CO{sub 2}-eq. Mg{sup -1} ww. Composting units exposed to weekly mixing had the highest EFs, whereas the units with no mixing during the entire year had the lowest emissions. In addition to the higher emission from the frequently mixed units, there was also an instant release of CH{sub 4} during mixing which was estimated to 8-12% of the total CH{sub 4} emissions. Experiments with higher loads of OHW (up to 20 kg every fortnight) entailed a higher emission and significantly increased overall EFs (in kg substance per Mg{sup -1} ww). However, the temperature development did not change significantly. The GHG emissions (in kg CO{sub 2}-eq. Mg{sup -1} ww) from home composting of OHW were found to be in the same order of magnitude as for centralised composting plants.

Andersen, J.K., E-mail: jka@env.dtu.d [Department of Environmental Engineering, Technical University of Denmark, DK-2800, Kongens Lyngby (Denmark); Boldrin, A.; Christensen, T.H.; Scheutz, C. [Department of Environmental Engineering, Technical University of Denmark, DK-2800, Kongens Lyngby (Denmark)

2010-12-15T23:59:59.000Z

433

Chemical Characterization and Source Apportionment of Household Fine Particulate Matter in Rural, Peri-urban, and Urban West Africa  

Science Journals Connector (OSTI)

In addition to household’s own fuel, HAP in urban households is affected by the extent of biomass use in the neighborhood, and by traffic-related sources. ... The elemental concentrations of the samples were quantified by energy dispersive X-ray fluorescence (ED-XRF) using a Shimadzu EDX-700HS spectrometer (Shimadzu Corp., Japan) at the Institute of Astronomy, Geophysics and Atmospheric Science, University of Sao Paulo, Brazil. ...

Zheng Zhou; Kathie L. Dionisio; Thiago G. Verissimo; Americo S. Kerr; Brent Coull; Stephen Howie; Raphael E. Arku; Petros Koutrakis; John D. Spengler; Kimberly Fornace; Allison F. Hughes; Jose Vallarino; Samuel Agyei-Mensah; Majid Ezzati

2013-12-18T23:59:59.000Z

434

"Table A29. Average Prices of Selected Purchased Energy Sources by Census"  

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

1" 1" " (Estimates in Dollars per Physical Unit)" " "," ","Residual","Distillate ","Natural"," "," ","RSE" " ","Electricity","Fuel Oil","Fuel Oil(b)","Gas(c)","LPG","Coal","Row" "Economic Characteristics(a)","(kWh)","(gallon)","(gallon)","(1000 cu ft)","(gallon)","(short ton)","Factors" ,"Total United States" "RSE Column Factors:",0.7,1.2,1.1,0.8,1.2,1 "Value of Shipments and Receipts " "(million dollars)" " Under 20",0.066,0.404,0.813,3.422,0.705,37.024,3.4

435

Development of the household sample for furnace and boilerlife-cycle cost analysis  

SciTech Connect (OSTI)

Residential household space heating energy use comprises close to half of all residential energy consumption. Currently, average space heating use by household is 43.9 Mbtu for a year. An average, however, does not reflect regional variation in heating practices, energy costs, or fuel type. Indeed, a national average does not capture regional or consumer group cost impacts from changing efficiency levels of heating equipment. The US Department of Energy sets energy standards for residential appliances in, what is called, a rulemaking process. The residential furnace and boiler efficiency rulemaking process investigates the costs and benefits of possible updates to the current minimum efficiency regulations. Lawrence Berkeley National Laboratory (LBNL) selected the sample used in the residential furnace and boiler efficiency rulemaking from publically available data representing United States residences. The sample represents 107 million 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 rulemaking. This paper describes the choice of criteria to select the sample of houses used in the rulemaking process. The process of data extraction is detailed in the appendices and is easily duplicated. The life-cycle cost is calculated in two ways with a household marginal energy price and a national average energy price. The LCC results show that using an national average energy price produces higher LCC savings but does not reflect regional differences in energy price.

Whitehead, Camilla Dunham; Franco, Victor; Lekov, Alex; Lutz, Jim

2005-05-31T23:59:59.000Z

436

Feed the Future Bangladesh: Baseline Integrated Household Survey | Data.gov  

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

Feed the Future Bangladesh: Baseline Integrated Household Survey Feed the Future Bangladesh: Baseline Integrated Household Survey Agriculture Community Menu DATA APPS EVENTS DEVELOPER STATISTICS COLLABORATE ABOUT Agriculture You are here Data.gov » Communities » Agriculture » Data Feed the Future Bangladesh: Baseline Integrated Household Survey Dataset Summary Description The Bangladesh Integrated Household Survey dataset is a thorough assessment of current standard of food security in Bangladesh taken from 2011-2012. The dataset includes all baseline household surveys made under the USAID-led Feed the Future initiative, a collaborative effort that supports country-owned processes and plans for improving food security and promoting transparency, and within the Zones of Influence as outlined by the Feed the Future Bangladesh plan .The BIHS sample is statistically representative at the following levels: (a) nationally representative of rural Bangladesh; (b) representative of rural areas of each of the seven administrative divisions of the country; and, (c) representative of the Feed the Future (FTF) zone of influence.

437

CBECS Buildings Characteristics --Revised Tables  

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

Geographic Location Tables Geographic Location Tables (24 pages, 136kb) CONTENTS PAGES Table 3. Census Region, Number of Buildings and Floorspace, 1995 Table 4. Census Region and Division, Number of Buildings, 1995 Table 5. Census Region and Division, Floorspace, 1995 Table 6. Climate Zone, Number of Buildings and Floorspace, 1995 Table 7. Metropolitan Status, Number of Buildings and Floorspace, 1995 These data are from the 1995 Commercial Buildings Energy Consumption Survey (CBECS), a national probability sample survey of commercial buildings sponsored by the Energy Information Administration, that provides information on the use of energy in commercial buildings in the United States. The 1995 CBECS was the sixth survey in a series begun in 1979. The data were collected from a sample of 6,639 buildings representing 4.6 million commercial buildings

438

"Table HC7.5 Space Heating Usage Indicators by Household Income, 2005"  

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

5 Space Heating Usage Indicators by Household Income, 2005" 5 Space Heating Usage Indicators 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 Usage Indicators" "Total U.S. Housing Units",111.1,26.7,28.8,20.6,13.1,22,16.6,38.6 "Do Not Have Heating Equipment",1.2,0.5,0.3,0.2,"Q",0.2,0.3,0.6 "Have Space Heating Equipment",109.8,26.2,28.5,20.4,13,21.8,16.3,37.9 "Use Space Heating Equipment",109.1,25.9,28.1,20.3,12.9,21.8,16,37.3

439

Could a Common Household Fungus Reduce Oil Imports? | Department of Energy  

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

Could a Common Household Fungus Reduce Oil Imports? Could a Common Household Fungus Reduce Oil Imports? Could a Common Household Fungus Reduce Oil Imports? June 21, 2011 - 11:37am Addthis A view of Aspergillus niger with the fungus’ DNA highlighted in green | Photo Courtesy of: PNNL. A view of Aspergillus niger with the fungus' DNA highlighted in green | Photo Courtesy of: PNNL. Ben Squires Analyst, Office of Energy Efficiency & Renewable Energy What does this mean for me? The Department's Pacific Northwest National Laboratory (PNNL) are working to harness the natural process that spoils fruits and vegetables as a way to make fuel and other petroleum substitutes from the parts of plants that we can't eat. The genetic bases of the behaviors and abilities of these two industrially relevant fungal strains will allow researchers to exploit

440

Competition Helps Kids Learn About Energy and Save Their Households Some  

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

Competition Helps Kids Learn About Energy and Save Their Households 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 Addthis Students can register now to save energy and win prizes with the Home Energy Challenge. Students can register now to save energy and win prizes with the Home Energy Challenge. Eric Barendsen Energy Technology Program Specialist, Office of Energy Efficiency and Renewable Energy How can I participate? Visit HomeEnergyChallenge.org to register for the competition. Third through eighth grade students and teachers will be excited to hear about a competition starting up for next school year that challenges students to learn about energy, develop techniques for saving energy, and

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 HC7.10 Home Appliances Usage Indicators by Household Income, 2005"  

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

0 Home Appliances Usage Indicators by Household Income, 2005" 0 Home Appliances Usage Indicators 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 Usage Indicators" "Total",111.1,26.7,28.8,20.6,13.1,22,16.6,38.6 "Cooking Appliances" "Frequency of Hot Meals Cooked" "3 or More Times A Day",8.2,2.9,2.5,1.3,0.5,1,2.4,4.6 "2 Times A Day",24.6,6.5,7,4.3,3.2,3.6,4.8,10.3 "Once a Day",42.3,8.8,9.8,8.7,5.1,10,5,12.9

442

Could a Common Household Fungus Reduce Oil Imports? | Department of Energy  

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

a Common Household Fungus Reduce Oil Imports? a Common Household Fungus Reduce Oil Imports? Could a Common Household Fungus Reduce Oil Imports? June 21, 2011 - 11:37am Addthis A view of Aspergillus niger with the fungus’ DNA highlighted in green | Photo Courtesy of: PNNL. A view of Aspergillus niger with the fungus' DNA highlighted in green | Photo Courtesy of: PNNL. Ben Squires Analyst, Office of Energy Efficiency & Renewable Energy What does this mean for me? The Department's Pacific Northwest National Laboratory (PNNL) are working to harness the natural process that spoils fruits and vegetables as a way to make fuel and other petroleum substitutes from the parts of plants that we can't eat. The genetic bases of the behaviors and abilities of these two industrially relevant fungal strains will allow researchers to exploit

443

The causes of Japan's ‘lost decade’: The role of household consumption  

Science Journals Connector (OSTI)

In this paper, I analyze the causes of the prolonged slowdown of the Japanese economy in the 1990s and find that the stagnation of investment, especially private fixed investment, was the primary culprit. I then investigate the causes of the stagnation of household consumption during the 1990s and find that the stagnation of household disposable income, the decline in household wealth, and increased uncertainty about the future are among the contributing factors. Finally, I consider whether demand side factors or supply side factors were more important as causes of the prolonged slowdown of the Japanese economy in the 1990s and conclude that the former (especially misguided government policies) were probably more important.

Charles Yuji Horioka

2006-01-01T23:59:59.000Z

444

Examining the Variation of Household Vehicles Holding Behavior in the Chukyo Region in Japan  

Science Journals Connector (OSTI)

Abstract Japan began initial stage of motorization in 1960s. The motorization made life of human highly dependent on private cars. As a result, vehicle holding behavior in the household might have a change during this process. This study examines the variation of the household vehicles owning behavior in the Chukyo region in Japan. The vehicle type is classified into the light motor car and the ordinary motor one. Meanwhile, the impact of the ownership of trucks is not taken into consideration. The person trip survey data in 1971 and 2001 are used as the sample. A bivariate ordered probit model is proposed for analyzing the ownership of two types of private cars. Since the maximal likelihood estimation method was found to be low efficient, the Gibbs sampler algorithm is implemented in this study. The conclusions of this study are listed as follows. Firstly, age of the householder, numbers of workers and number of members (>= 25 years old) were significant factors with same effects both in 1971 and 2001. Secondly, gender of the householder, district, population density and density of railway stations changed their effects from 1971 to 2001. The households with female householder were unwilling to own the light motor car only in 1971.The residents living in Nagoya would not like to own the ordinary motor car in 2001. Population density and density of railway stations affected ownership of the light motor car only in 2001. Lastly, there was a substitution effect on ownership between the light motor car and the ordinary motor one only in 2001.

Jia Yang; Mimi Tian; Tomio Miwa; Takayuki Morikawa

2014-01-01T23:59:59.000Z

445

Table HC1.2.2 Living Space Characteristics by Average Floorspace  

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

2 Living Space Characteristics by Average Floorspace, " 2 Living Space Characteristics by Average Floorspace, " " Per Housing Unit and Per Household Member, 2005" ,,"Average Square Feet" ," Housing Units (millions)" ,,"Per Housing Unit",,,"Per Household Member" "Living Space Characteristics",,"Total1","Heated","Cooled","Total1","Heated","Cooled" "Total",111.1,2033,1618,1031,791,630,401 "Total Floorspace (Square Feet)" "Fewer than 500",3.2,357,336,113,188,177,59 "500 to 999",23.8,733,667,308,343,312,144 "1,000 to 1,499",20.8,1157,1086,625,435,409,235 "1,500 to 1,999",15.4,1592,1441,906,595,539,339 "2,000 to 2,499",12.2,2052,1733,1072,765,646,400

446

Long Term Dynamics of Inequalities between French Households concerning Automobile COLLET, Roger; BOUCQ, Elise; MADRE, Jean-Loup; HIVERT, Laurent.  

E-Print Network [OSTI]

Long Term Dynamics of Inequalities between French Households concerning Automobile COLLET, Roger TERM DYNAMICS OF INEQUALITIES BETWEEN FRENCH HOUSEHOLDS CONCERNING AUTOMOBILE Roger Collet, INRETS of automobile. As the curves representing car ownership (number of cars per adult) and car use (annual mileage

Paris-Sud XI, Université de

447

Abstract--Numerous studies have shown that households' consumption is an important part of the total energy consumed  

E-Print Network [OSTI]

appropriate strategies of giving households' effective feedback on their energy consumption. This study, Energy efficiency. I. INTRODUCTION HE energy consumption of households in buildings attracts a lot in the housing sector. Energy consumption in buildings accounts for 39% of Sweden's total final energy

Beigl, Michael

448

Patterns of stove usage after introduction of an advanced cookstove: the long-term application of household sensors  

Science Journals Connector (OSTI)

Household air pollution generated from solid fuel use for cooking is one of the leading risk factors for ill-health globally. ... However, household usage of these stoves and resulting changes in usage of traditional polluting stoves is not well characterized. ...

Ajay Pillarisetti; Mayur Vaswani; Darby Jack; Kalpana Balakrishnan; Michael N. Bates; Narendra K. Arora; Kirk R. Smith

2014-11-12T23:59:59.000Z

449

Effects on minority and low-income households of the EPA proposal to reduce leaded gasoline use  

SciTech Connect (OSTI)

To reduce the potentially harmful environmental effects of lead in the environment, the US Environmental Protection Agency (EPA) has proposed a reduction in the amount of lead used in leaded gasoline. This report examines the potential impacts of such action on minority and low-income households in the US. The benefits of the EPA's proposal would presumably accrue primarily to households that contain small children and that are located in the central cities of metropolitan areas. This is because small children (under age seven) are particularly susceptible to the effects of lead and also because the automobile traffic density in central cities is higher than in any other area. Potential costs are examined in terms of households that own vehicles requiring leaded gasoline. Costs could accrue either because of higher gasoline prices due to reduced lead content or because of higher vehicle repair costs for engines that must use leaded gasoline to prevent excessive wear. Because of their location and number, minority and low-income households with small children would benefit more than the average US household. No costs would be incurred by the relatively large segment of minority and low-income households that own no vehicles. However, the Hispanic and other minority (except black) and low-income households that do own vehicles have a greater than average share of vehicles that require leaded gasoline; costs to these households because of the EPA's proposed action would be comparatively high.

Rose, K.; LaBelle, S.; Winter, R.; Klein, Y.

1985-04-01T23:59:59.000Z

450

The federal energy policy: An example of its potential impact on energy consumption and expenditures in minority and poor households  

SciTech Connect (OSTI)

This report presents an analysis of the relative impacts of the National Energy Strategy on majority and minority households and on nonpoor and poor households. (Minority households are defined as those headed by black or Hispanic persons; poor households are defined as those having combined household income less than or equal to 125% of the Office of Management and Budget`s poverty-income threshold.) Energy consumption and expenditures, and projected energy expenditures as a share of income, for the period 1987 to 2009 are reported. Projected consumptions of electricity and nonelectric energy over this period are also reported for each group. An analysis of how these projected values are affected under different housing growth scenarios is performed. The analysis in this report presents a preliminary set of projections generated under a set of simplifying assumptions. Future analysis will rigorously assess the sensitivity of the projected values to various changes in a number of these assumptions.

Poyer, D.A.

1991-09-01T23:59:59.000Z

451

Exploring nonresponse bias in a health survey using neighborhood characteristics.  

E-Print Network [OSTI]

of non-Hispanic Whites, urban populations, and householdsof non-Hispanic Asians, sin- gles, 1-person households,Non-Hispanic Asian Never married, % 1-person household, %

Lee, Sunghee; Brown, E Richard; Grant, David; Belin, Thomas R; Brick, J Michael

2009-01-01T23:59:59.000Z

452

Household Response To Dynamic Pricing Of Electricity: A Survey Of The  

Open Energy Info (EERE)

Household Response To Dynamic Pricing Of Electricity: A Survey Of The Household Response To Dynamic Pricing Of Electricity: A Survey Of The Experimental Evidence Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Household Response To Dynamic Pricing Of Electricity: A Survey Of The Experimental Evidence Focus Area: Crosscutting Topics: Market Analysis Website: www.hks.harvard.edu/hepg/Papers/2009/The%20Power%20of%20Experimentatio Equivalent URI: cleanenergysolutions.org/content/household-response-dynamic-pricing-el Language: English Policies: "Deployment Programs,Regulations,Financial Incentives" is not in the list of possible values (Deployment Programs, Financial Incentives, Regulations) for this property. DeploymentPrograms: Demonstration & Implementation Regulations: "Mandates/Targets,Cost Recovery/Allocation,Enabling Legislation" is not in the list of possible values (Agriculture Efficiency Requirements, Appliance & Equipment Standards and Required Labeling, Audit Requirements, Building Certification, Building Codes, Cost Recovery/Allocation, Emissions Mitigation Scheme, Emissions Standards, Enabling Legislation, Energy Standards, Feebates, Feed-in Tariffs, Fuel Efficiency Standards, Incandescent Phase-Out, Mandates/Targets, Net Metering & Interconnection, Resource Integration Planning, Safety Standards, Upgrade Requirements, Utility/Electricity Service Costs) for this property.

453

Environmental and Resource Economics Household Energy Demand in Urban China: Accounting for regional prices and rapid  

E-Print Network [OSTI]

growth, China's energy consumption is rising at one of the fastest rates in the world, almost 8% per year over the period 2000-2010. Residential energy consumption has grown even faster than the national total . Although household energy consumption per capita is still low compared to the developed countries

454

Characterizing probability density distributions for household electricity load profiles from high-resolution electricity use data  

Science Journals Connector (OSTI)

Abstract This paper presents a high-resolution bottom-up model of electricity use in an average household based on fit to probability distributions of a comprehensive high-resolution household electricity use data set for detached houses in Sweden. The distributions used in this paper are the Weibull distribution and the Log-Normal distribution. These fitted distributions are analyzed in terms of relative variation estimates of electricity use and standard deviation. It is concluded that the distributions have a reasonable overall goodness of fit both in terms of electricity use and standard deviation. A Kolmogorov–Smirnov test of goodness of fit is also provided. In addition to this, the model is extended to multiple households via convolution of individual electricity use profiles. With the use of the central limit theorem this is analytically extended to the general case of a large number of households. Finally a brief comparison with other models of probability distributions is made along with a discussion regarding the model and its applicability.

Joakim Munkhammar; Jesper Rydén; Joakim Widén

2014-01-01T23:59:59.000Z

455

Reforming Household Energy Markets: Some Welfare Effects in the United Catherine Waddams Price  

E-Print Network [OSTI]

Reforming Household Energy Markets: Some Welfare Effects in the United Kingdom by Catherine Waddams remain vulnerable. The implications of these findings for the future of energy markets both in the UK This paper summarises some early effects of deregulating the UK energy sector, focusing on the effects

Feigon, Brooke

456

Increased Levels of Markers of Microbial Exposure in Homes with Indoor Storage of Organic Household Waste  

Science Journals Connector (OSTI)

...Levels of Markers of Microbial Exposure in Homes with Indoor Storage of Organic Household...might increase microbial exposure in the home environment. In this study we evaluated...House dust samples were collected in 99 homes in The Netherlands selected on the basis...

Inge M. Wouters; Jeroen Douwes; Gert Doekes; Peter S. Thorne; Bert Brunekreef; Dick J. J. Heederik

2000-02-01T23:59:59.000Z

457

Table 5.2. U.S. per Household Vehicle-Miles Traveled, Vehicle...  

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

Years or More ... 13.6 1.8 17.1 907 1,044 4.6 Race of Householder White ... 73.3 1.9 21.7 1,099 1,267 1.8 Black...

458

Table 5.12. U.S. Average Vehicle-Miles Traveled by Household...  

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

... 30.7 Q 26.3 37.2 Q Q Q Q Q Q Q 20.7 Race of Householder White ... 26.0 23.2 25.2 32.6 19.3 16.4 13.3...

459

Home ownership as wealth over the life cycle European Household Motivation for Residential Assets  

E-Print Network [OSTI]

Home ownership as wealth over the life cycle European Household Motivation for Residential Assets Current situation and future prospects INTRODUCTION Encouraging Home Ownership Most countries encourage a country's wealth and the proportion of home owners. 44 Homeownership rates in Western Europe (Source: EMF

Birmingham, University of

460

Greenhouse Gas Emissions from the Consumption of Electric and Electronic Equipment by Norwegian Households  

Science Journals Connector (OSTI)

Greenhouse Gas Emissions from the Consumption of Electric and Electronic Equipment by Norwegian Households ... Conventional wisdom holds that large appliances, in particular washers, dryers, refrigerators and freezers, dominate residential energy consumption apart from heat, hot water and light. ... (16) It excludes lighting, all professional equipment, space heating, hot water, garden or car equipment, fire alarms, and air conditioning. ...

Edgar G. Hertwich; Charlotte Roux

2011-08-30T23:59:59.000Z

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.


461

Using Circuit-Level Power Measurements in Household Energy Management Systems  

E-Print Network [OSTI]

Using Circuit-Level Power Measurements in Household Energy Management Systems Alan Marchiori and Qi to accurately measure en- ergy usage in the home. Measuring energy usage is not dif- ficult, however we must decide what to measure. Whole- home energy measurement is cheap and easy to setup be- cause only one

Han, Qi "Chee"

462

Energy Policy 30 (2002) 815826 Evaluating the health benefits of transitions in household energy  

E-Print Network [OSTI]

as the primary source of domestic energy, has put preventive measures to reduce exposure to indoor air pollutionEnergy Policy 30 (2002) 815­826 Evaluating the health benefits of transitions in household energy for the Future, 1616 P Street NW, Washington, DC 20036, USA b Epidemiology and Burden of Disease Unit, Global

Kammen, Daniel M.

463

Finding the creatures of habit; Clustering households based on their flexibility in using electricity  

E-Print Network [OSTI]

electricity Ian Dent, Uwe Aickelin and Tom Rodden School of Computer Science University of Nottingham, UK, AB15 8QH tony.craig@hutton.ac.uk ABSTRACT Changes in the UK electricity market, particularly to change households' electricity usage patterns for the benefit of the overall sys- tem. Users show

Aickelin, Uwe

464

Stranded Vehicles: How Gasoline Taxes Change the Value of Households' Vehicle Assets  

E-Print Network [OSTI]

Stranded Vehicles: How Gasoline Taxes Change the Value of Households' Vehicle Assets Meghan Busse pollution caused by the burning of fossil fuels. Argu- ments against energy taxes, and gasoline taxes more incidence of the tax. We study the effect of a gasoline tax using changes in vehicle values. We construct

Rothman, Daniel

465

Fact #616: March 29, 2010 Household Vehicle-Miles of Travel by Trip Purpose  

Broader source: Energy.gov [DOE]

In 2009, getting to and from work accounted for about 27% of household vehicle-miles of travel (VMT). Work-related business was 8.4% of VMT in 2001, but declined to 6.7% in 2009, possibly due to...

466

Household use of paint and petroleum solvents and the risk of childhood leukemia  

Science Journals Connector (OSTI)

...African American, or non-Hispanic White according to their physician...Screening identified 1,253 Hispanic cases of whom 1,119 (89...random telephone numbers. A household enumeration was obtained for...controls, identified 1,668 Hispanics of whom 1,462 (88) completed...

Ghislaine Scelo; Catherine Metayer; Steve Selvin; Martyn Smith; Melinda Aldrich; Joseph Wiemels; Luoping Zhang; and Patricia Buffler

2008-05-01T23:59:59.000Z

467

Table HC1.1.4 Housing Unit Characteristics by Average Floorspace--Apartments, 2  

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

4 Housing Unit Characteristics by Average Floorspace--Apartments, 2005" 4 Housing Unit Characteristics by Average Floorspace--Apartments, 2005" ,,,"Average Square Feet per Apartment in a --" ," Housing Units (millions)" ,,,"2 to 4 Unit Building",,,"5 or More Unit Building" ,,"Apartments (millions)" "Housing Unit Characteristics",,,"Total","Heated","Cooled","Total","Heated","Cooled" "Total",111.1,24.5,1090,902,341,872,780,441 "Census Region and Division" "Northeast",20.6,6.7,1247,1032,"Q",811,788,147 "New England",5.5,1.9,1365,1127,"Q",814,748,107 "Middle Atlantic",15.1,4.8,1182,978,"Q",810,800,159 "Midwest",25.6,4.6,1349,1133,506,895,810,346

468

Household electricity consumption and CO2 emissions in the Netherlands: A model-based analysis  

Science Journals Connector (OSTI)

Abstract Twenty percent of the total energy consumption in the Netherlands comes from household electricity consumption. This comes from household electric appliances whose number has grown in recent years. The paper explores the effect of smart meter introduction, appliance efficiency and consumer behaviour on reducing electricity consumption in the Netherlands. It does so by combining two perspectives: a sociotechnical approach and a bottom up simulation approach. The range of scenarios explored through simulation in the paper provides an understanding of the interplay between efficiency, smart meter diffusion and consumer behaviour. The results show their effect on electricity consumption and suggest that further effort is required to control and reduce it. Insights from the paper suggest that future studies should disaggregate with respect to a number of factors.

George Papachristos

2015-01-01T23:59:59.000Z

469

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

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

N April 4, 2012 Extending Efficiency Services to Underserved Households: NYSERDA's Assisted Home Performance with ENERGY STAR Program Since 2001, New York residents have completed over 39,000 energy upgrades through NYSERDA's Home Performance with ENERGY STAR (HPwES) initiative. Approximately one third of these projects have been completed through the Assisted HPwES track, which offers large incentives to middle income

470

TEX-A-SYST: Reducing the Risk of Ground Water Contamination by Improving Household Wastewater Treatment  

E-Print Network [OSTI]

. This publication covers the following topics: 1. Septic tanks/soil absorption systems 2. Quantity of wastewater 3. Quality of wastewater 4. Collection of wastewater 5. Treatment systems 6. Disposal system 7. Assistance with failing systems or new designs 8.... Evaluation table Septic Tanks/Soil Absorption Systems The most common form of on-site waste- water treatment is a septic tank/soil absorption system. In this system, wastewater flows from the household sewage lines into an under- ground septic tank...

Harris, Bill L.; Hoffman, D.; Mazac Jr., F. J.

1997-08-29T23:59:59.000Z

471

Household energy use: Applying behavioural economics to understand consumer decision-making and behaviour  

Science Journals Connector (OSTI)

Abstract Household energy conservation has emerged as a major challenge and opportunity for researchers, practitioners and policymakers. Consumers also seem to be gaining greater awareness of the value and need for sustainable energy practices, particularly amid growing public concerns over greenhouse gas emissions and climate change. Yet even with adequate knowledge of how to save energy and a professed desire to do so, many consumers still fail to take noticeable steps towards energy efficiency and conservation. There is often a sizeable discrepancy between peoples’ self-reported knowledge, values, attitudes and intentions, and their observable behaviour—examples include the well-known ‘knowledge-action gap’ and ‘value-action gap’. But neither is household energy consumption driven primarily by financial incentives and the rational pursuit of material interests. In fact, people sometimes respond in unexpected and undesirable ways to rewards and sanctions intended to shift consumers’ cost–benefit calculus in favour of sustainable behaviours. Why is this so? Why is household energy consumption and conservation difficult to predict from either core values or material interests? By drawing on critical insights from behavioural economics and psychology, we illuminate the key cognitive biases and motivational factors that may explain why energy-related behaviour so often fails to align with either the personal values or material interests of consumers. Understanding these psychological phenomena can make household and community responses to public policy interventions less surprising, and in parallel, can help us design more cost-effective and mass-scalable behavioural solutions to encourage renewable and sustainable energy use among consumers.

Elisha R. Frederiks; Karen Stenner; Elizabeth V. Hobman

2015-01-01T23:59:59.000Z

472

Space Heating Scenarios for Ontario: a Demonstration of the Statistics Canada Household Model  

Science Journals Connector (OSTI)

ABSTRACT This paper describes the analytical and simulation capabilities of the currently implemented version of the “household model” developed by the Structural Analysis Division, Statistics Canada. The household model, as described in A Design Framework for Long Term Energy – Economic Analysis of Dwelling Related Demand [1], is a simulation framework and related data base of the Canadian housing stocks, residential construction, and end-use energy consumption in the residential sector. The purpose of the model is to provide an analytical tool for evaluating a variety of residential energy conservation strategies including insulation retrofitting and the introduction of new building standards, the possibilities for fuel substitution afforded by equipment retrofitting, and the impact of new technologies for space conditioning with respect to impacts on residential energy requirements and construction materials over time. The simulation results for Ontario that are presented in the paper are for demonstration purposes only and do not constitute a forecast. The choice of Ontario was arbitrary; similar calculations can be performed for other provinces, for Canada as a whole, and for selected subprovincial regions. At the time of preparation of this paper, the population and household formation block at the national level, the housing stock block, and the space heating part of the space conditioning block are implemented. Therefore simulation results are limited to these areas.

R.H.H. Moll; K.H. Dickinson

1982-01-01T23:59:59.000Z

473

Inefficient subsidy in Nigerian oil sector; implications for revenue generation and household welfare in Nigeria  

Science Journals Connector (OSTI)

Subsidy exists when consumers are assisted by the government to pay less than the prevailing market price of a given commodity. In respect of fuel subsidy, it means that consumers would pay below the market price per litre of petroleum product. This paper is aim at analysing the effects of the increase in energy prices on the social welfare of Nigerian households and comparing the consequences with the condition in which in concurrence with increase in energy prices, the government undertakes transfer payments to Nigerian households in order to protect their social welfare status. An analytical reasoning model was adopted and within the framework of this model the effects of increase in energy price on social welfare is discussed. Decrease in energy subsidies and a shift towards market prices will result in a lower budget deficit for the government and powerfully harness one of the main causes of inflation. However, if the elimination of subsidies be accompanied by transfer payments to households, the result is increase in the government budget deficit which in its turn will enhance inflation thus very negatively affecting social welfare.

Benjamin Anabori Mmadu; David Chuks Akan

2013-01-01T23:59:59.000Z

474

Voluntary electricity conservation of households after the Great East Japan Earthquake: A stated preference analysis  

Science Journals Connector (OSTI)

Abstract This paper examines the voluntary electricity-saving awareness of households after the Great East Japan Earthquake and the subsequent accident at the Fukushima nuclear power station. We conduct a conjoint analysis of consumer stated preferences for the settings of air conditioners, refrigerators, and the standby power of electrical appliances, based on a web questionnaire survey administered in the areas supplied by the Tokyo Electric Power Company (TEPCO) and Kansai Electric Power Company (KEPCO). The main findings of this paper are as follows. First, we observe awareness of voluntary electricity conservation among the households in both the TEPCO and KEPCO areas after the disasters. Second, awareness of voluntary power saving is higher in the TEPCO area, which has been directly affected by the electric power shortages, in comparison with the KEPCO area, where there was no such direct impact. Third, if power prices are to be further raised, the consumer responses to the price changes would be small in both areas. Furthermore, we show that the potential voluntary reduction in electric power consumption of a household in the TEPCO area is 26% more than that in the KEPCO area during the summer peak periods.

Makoto Tanaka; Takanori Ida

2013-01-01T23:59:59.000Z

475

An evaluation on the environmental consequences of residual CFCs from obsolete household refrigerators in China  

SciTech Connect (OSTI)

Chlorofluorocarbons (CFCs) contained in household refrigerators consist mainly of CFC-11 and CFC-12, which will be eventually released into the environment. Consequentially, environmental releases of these refrigerants will lead to ozone depletion and contribute significantly to the greenhouse effect, if waste refrigerators are not disposed of properly. In the present paper, the potential release of residual CFCs and their substitutes from obsolete household refrigerators in China is examined, and their contributions to ozone depletion and greenhouse effect are compared with those of other recognized ozone-depleting substances (ODS) and greenhouse gases (GHGs). The results imply that annual potential amounts of released residual CFC-11 and CFC-12 will reach their maximums at 4600 and 2300 tons, respectively in 2011, and then decrease gradually to zero until 2020. Meanwhile, the amounts of their most widely used substitutes HCFC-141b and HFC-134a will keep increasing. Subsequently, the contribution ratio of these CFCs and their substitutes to ozone depletion will remain at 25% through 2011, and reach its peak value of 34% by 2018. The contribution to greenhouse effect will reach its peak value of 0.57% by 2010. Moreover, the contribution ratio of these CFCs to the total global release of CFCs will steadily increase, reaching its peak of 15% by 2018. Thus, this period from 2010 to 2018 is a crucial time during which residual CFCs and their substitutes from obsolete household refrigerators in China will contribute significantly to ozone depletion.

Zhao Xiangyang; Duan Huabo [Department of Environmental Science and Engineering, Tsinghua University, Beijing (China); Li Jinhui, E-mail: jinhui@tsinghua.edu.cn [Department of Environmental Science and Engineering, Tsinghua University, Beijing (China)

2011-03-15T23:59:59.000Z

476

An Analysis of the Price Elasticity of Demand for Household Appliances  

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

the Price Elasticity of Demand for Household Appliances the Price Elasticity of Demand for Household Appliances Title An Analysis of the Price Elasticity of Demand for Household Appliances Publication Type Report LBNL Report Number LBNL-326E Year of Publication 2008 Authors Dale, Larry L., and Sydny K. Fujita Document Number LBNL-326E Pagination 19 Date Published 02/2008 Publisher Lawrence Berkeley National Laboratory City Berkeley Abstract This article summarizes our study of the price elasticity of demand1 for home appliances, including refrigerators, clothes washers and dishwashers. In the context of increasingly stringent appliance standards, we are interested in what kind of impact the increased manufacturing costs caused by higher efficiency requirements will have on appliance sales. We chose to study this particular set of appliances because data for the elasticity calculation was more readily available for refrigerators, clothes washers, and dishwashers than for other appliances. We begin with a review of the existing economics literature describing the impact of economic variables on the sale of durable goods. We then describe the market for home appliances and changes in it over the past 20 years. We conclude with summary and interpretation of the results of our regression analysis and present estimates of the price elasticity of demand for the three appliances.

477

The Impact of the Earned Income Tax Credit on Economic Well-Being: A Comparison Across Household Types  

Science Journals Connector (OSTI)

Using survey data from Earned Income Tax Credit (EITC) recipients in Madison County, New ... of the EITC across household types. For tax years 2002 through 2004, we find that ... of EITC amounts, poverty rates, u...

Nicole B. Simpson; Jill Tiefenthaler; Jameson Hyde

2010-12-01T23:59:59.000Z

478

Development of program implementation, evaluation, and selection tools for household water treatment and safe storage systems in developing countries  

E-Print Network [OSTI]

Over the past six years, the MIT Department of Civil and Environmental Engineering's Master of Engineering program has undertaken various projects involved with the design and implementation of a wide range of household ...

Baffrey, Robert Michael Nuval, 1977-

2005-01-01T23:59:59.000Z

479

Risk factors of functional disability among community-dwelling elderly people by household in Japan: a prospective cohort study  

Science Journals Connector (OSTI)

Although the number of elderly people needing care is increasing rapidly in the home setting in Japan, family size and ability to provide such ... identify the risk factors of functional disability by household c...

Emiko Saito; Shouzoh Ueki; Nobufumi Yasuda; Sachiko Yamazaki…

2014-08-01T23:59:59.000Z

480

Water Flows in the Spanish Economy: Agri-Food Sectors, Trade and Households Diets in an Input-Output Framework  

Science Journals Connector (OSTI)

Water Flows in the Spanish Economy: Agri-Food Sectors, Trade and Households Diets in an Input-Output Framework ... So although we use the information from a SAM, since we leave as exogenous accounts the household consumption and foreign trade; it is not a traditional SAM analysis, but more an extended input-output analysis. ... The countries concerned are France, Germany, Portugal, Italy, UK, Netherlands, U.S., Belgium, China, and Japan. ...

Ignacio Cazcarro; Rosa Duarte; Julio Sánchez-Chóliz

2012-05-21T23:59:59.000Z

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.


481

Census Snapshot: Colorado  

E-Print Network [OSTI]

COLORADO Adam P. Romero, Public Policy Fellow Clifford J.couples raising children in Colorado. We compare same-sex “sex married couples in Colorado. 1 APRIL 2008 In many ways,

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

2008-01-01T23:59:59.000Z

482

Census Snapshot: Virginia  

E-Print Network [OSTI]

City Isle of Wight County James City County King andQueen County KingGeorge County King William County Lancaster County Lee

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

2008-01-01T23:59:59.000Z

483

THE CENSUS OF 1930  

Science Journals Connector (OSTI)

...of California, to a site not yet selected, to...at-mnosphere. THE ELECTROLYTIC PRODUCTION OF FLUORINE FLUORINE...that do not react to electricity. Fluorine, however...cities such as Chicago, Kansas City, Syracuse, Denver...prehistoric animals at the same site, also announces a discovery...

1929-06-07T23:59:59.000Z

484

Census Snapshot: Connecticut  

E-Print Network [OSTI]

CONNECTICUT Adam P. Romero, Public Policy Fellow Clifford J.raising children in Connecticut. We compare same-sex “sex married couples in Connecticut. 1 APRIL 2008 In many

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

2008-01-01T23:59:59.000Z

485

EIA - Census Division List  

Gasoline and Diesel Fuel Update (EIA)

9 9 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

486

Report for Development of a Census Array and Evaluation of the Array to Detect Biothreat Agents and Environmental Samples for DHS  

SciTech Connect (OSTI)

The objective of this project is to provide DHS a comprehensive evaluation of the current genomic technologies including genotyping, Taqman PCR, multiple locus variable tandem repeat analysis (MLVA), microarray and high-throughput DNA sequencing in the analysis of biothreat agents from complex environmental samples. This report focuses on the design, testing and results of samples on the Census Array. We designed a Census/Detection Array to detect all sequenced viruses (including phage), bacteria (eubacteria), and plasmids. Family-specific probes were selected for all sequenced viral and bacterial complete genomes, segments, and plasmids. Probes were designed to tolerate some sequence variation to enable detection of divergent species with homology to sequenced organisms, and to be unique relative to the human genome. A combination of 'detection' probes with high levels of conservation within a family plus 'census' probes targeting strain/isolate specific regions enabled detection and taxonomic classification from the level of family down to the strain. The array has wider coverage of bacterial and viral targets based on more recent sequence data and more probes per target than other microbial detection/discovery arrays in the literature. We tested the array with purified bacterial and viral DNA/RNA samples, artificial mixes of known bacterial/viral samples, spiked DNA against complex background including BW aerosol samples and soil samples, and environmental samples to evaluate the array's sensitivity and forensic capability. The data were analyzed using our novel maximum likelihood software. For most of the organisms tested, we have achieved at least species level discrimination.

Jaing, C; Jackson, P

2011-04-14T23:59:59.000Z

487

Characteristics of Cleanroom  

Science Journals Connector (OSTI)

Cleanroom shows different characteristics when it is in ... , the curve will reveal the law of cleanroom.

Zhonglin Xu

2014-01-01T23:59:59.000Z

488

Residential Buildings Historical Publications reports, data and housing  

Gasoline and Diesel Fuel Update (EIA)

7 7 Average Natural Gas Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per Household Households Number (billion (million (thousand Household Member Building Foot Household Member Characteristics (million) (million) sq. ft.) Btu) Btu) (million Btu) (million Btu) (dollars) (dollars) (dollars) (dollars) Total U.S. Households 57.3 42.5 99.4 114 49 84.3 33 615 0.26 456 176 Census Region and Division Northeast 11.7 7.4 21.2 139 49 88.5 34 898 0.31 571 221 New England 1.7 1.0 3.0 155 49 86.8 33 1,044 0.33 586 223 Middle Atlantic 10.0 6.5 18.2 137 49 88.8 35 877 0.31 568 221

489

Residential Buildings Historical Publications reports, data and housing  

Gasoline and Diesel Fuel Update (EIA)

3 3 Average Natural Gas Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per Household Households Number (billion (million (thousand Household Member Building Foot Household Member Characteristics (million) (million) sq. ft.) Btu) Btu) (million Btu) (million Btu) (dollars) (dollars) (dollars) (dollars) Total U.S. Households 58.7 46.0 111.9 115 47 89.9 34 696 0.29 546 206 Census Region and Division Northeast 12.2 7.7 23.3 145 48 90.9 35 1,122 0.37 703 272 New England 2.2 1.2 4.2 154 45 85.7 34 1,298 0.38 722 290 Middle Atlantic 10.0 6.4 19.1 143 48 92.0 35 1,089 0.37 699 269

490

Residential Buildings Historical Publications reports, data and housing  

Gasoline and Diesel Fuel Update (EIA)

Fuel Oil/Kerosene, 2001 Fuel Oil/Kerosene, 2001 Average Fuel Oil/Kerosene Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per Household Households Number (billion (million (thousand Household Member Building Foot Household Member Characteristics (million) (million) sq. ft.) Btu) Btu) (million Btu) (million Btu) (dollars) (dollars) (dollars) (dollars) Total U.S. Households 11.2 9.4 26.0 80 29 67.1 26 723 0.26 607 236 Census Region and Division Northeast 7.1 5.4 16.8 111 36 84.7 33 992 0.32 757 297 New England 2.9 2.5 8.0 110 35 96.3 39 1,001 0.32 875 350 Middle Atlantic 4.2 2.8 8.8 112 36 76.6 30 984 0.32 675 260

491

Residential Buildings Historical Publications reports, data and housing  

Gasoline and Diesel Fuel Update (EIA)

0 0 Average Natural Gas Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per Household Households Number (billion (million (thousand Household Member Building Foot Household Member Characteristics (million) (million) sq. ft.) Btu) Btu) (million Btu) (million Btu) (dollars) (dollars) (dollars) (dollars) Total U.S. Households 57.7 44.8 106.3 109 46 84.2 32 609 0.26 472 181 Census Region and Division Northeast 11.9 7.7 23.6 134 44 86.8 33 952 0.31 615 232 New England 2.0 1.1 3.5 146 45 76.0 29 1,135 0.35 592 227 Middle Atlantic 9.9 6.6 20.1 133 44 89.1 34 923 0.30 620 234

492

Residential Buildings Historical Publications reports, data and housing  

Gasoline and Diesel Fuel Update (EIA)

4 4 Average Natural Gas Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per Household Households Number (billion (million (thousand Household Member Building Foot Household Member Characteristics (million) (million) sq. ft.) Btu) Btu) (million Btu) (million Btu) (dollars) (dollars) (dollars) (dollars) Total U.S. Households 55.4 41.3 93.2 121 53 89.9 33 722 0.32 537 198 Census Region and Division Northeast 11.7 7.5 21.1 125 44 79.2 30 925 0.33 588 221 New England 2.0 1.3 4.2 122 39 80.3 29 955 0.30 626 224 Middle Atlantic 9.7 6.1 16.9 125 45 78.9 30 919 0.33 580 220

493

Residential Buildings Historical Publications reports, data and housing  

Gasoline and Diesel Fuel Update (EIA)

1 1 Average LPG Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per Household Households Number (billion (million (thousand Household Member Building Foot Household Member Characteristics (million) (million) sq. ft.) Btu) Btu) (million Btu) (million Btu) (dollars) (dollars) (dollars) (dollars) Total U.S. Households 7.3 7.2 12.2 44 26 42.8 15 389 0.23 382 133 Census Region and Division Northeast 1.2 1.1 2.7 29 11 26.2 9 318 0.13 288 94 New England 0.5 0.4 1.0 25 11 22.5 8 282 0.12 250 91 Middle Atlantic 0.7 0.7 1.7 31 12 28.6 9 341 0.13 312 96

494

Residential Buildings Historical Publications reports, data and housing  

Gasoline and Diesel Fuel Update (EIA)

7 7 Average Fuel Oil/Kerosene Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per Household Households Number (billion (million (thousand Household Member Building Foot Household Member Characteristics (million) (million) sq. ft.) Btu) Btu) (million Btu) (million Btu) (dollars) (dollars) (dollars) (dollars) Total U.S. Households 17.4 14.0 33.3 87 37 70.3 27 513 0.22 414 156 Census Region and Division Northeast 9.1 6.3 17.8 140 49 96.0 37 808 0.28 556 212 New England 2.6 2.0 5.8 130 46 102.1 39 770 0.27 604 233 Middle Atlantic 6.5 4.2 12.1 144 51 93.6 36 826 0.29 537 204

495

Residential Buildings Historical Publications reports, data and housing  

Gasoline and Diesel Fuel Update (EIA)

4 4 Average LPG Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per Household Households Number (billion (million (thousand Household Member Building Foot Household Member Characteristics (million) (million) sq. ft.) Btu) Btu) (million Btu) (million Btu) (dollars) (dollars) (dollars) (dollars) Total U.S. Households 7.8 7.7 12.0 41 26 40.1 15 406 0.26 398 146 Census Region and Division Northeast 1.4 1.2 2.7 23 10 20.1 7 295 0.13 264 91 New England 0.5 0.4 1.0 31 14 27.6 9 370 0.17 330 114 Middle Atlantic 0.9 0.8 1.8 18 8 15.9 6 253 0.11 226 79

496

Residential Buildings Historical Publications reports, data and housing  

Gasoline and Diesel Fuel Update (EIA)

90 90 Average Fuel Oil/Kerosene Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per Household Households Number (billion (million (thousand Household Member Building Foot Household Member Characteristics (million) (million) sq. ft.) Btu) Btu) (million Btu) (million Btu) (dollars) (dollars) (dollars) (dollars) Total U.S. Households 16.3 13.5 33.2 77 31 63.9 23 609 0.25 506 181 Census Region and Division Northeast 8.9 6.4 19.3 121 40 87.7 32 950 0.32 690 253 New England 2.5 2.1 5.9 121 43 99.0 39 956 0.34 784 307 Middle Atlantic 6.3 4.4 13.4 121 39 83.2 30 947 0.31 652 234

497

Residential Buildings Historical Publications reports, data and housing  

Gasoline and Diesel Fuel Update (EIA)

1 1 Average Fuel Oil/Kerosene Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per Household Households Number (billion (million (thousand Household Member Building Foot Household Member Characteristics (million) (million) sq. ft.) Btu) Btu) (million Btu) (million Btu) (dollars) (dollars) (dollars) (dollars) Total U.S. Households 14.6 11.0 28.9 116 44 87.9 32 1,032 0.39 781 283 Census Region and Division Northeast 8.9 5.9 18.0 158 51 103.5 36 1,405 0.46 923 323 New England 2.4 1.7 5.1 148 50 105.3 36 1,332 0.45 946 327 Middle Atlantic 6.5 4.1 12.8 161 52 102.9 36 1,435 0.46 915 322

498

Residential Buildings Historical Publications reports, data and housing  

Gasoline and Diesel Fuel Update (EIA)

0 0 Average Fuel Oil/Kerosene Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per Household Households Number (billion (million (thousand Household Member Building Foot Household Member Characteristics (million) (million) sq. ft.) Btu) Btu) (million Btu) (million Btu) (dollars) (dollars) (dollars) (dollars) Total U.S. Households 15.4 11.6 29.7 131 51 99.0 36 1,053 0.41 795 287 Census Region and Division Northeast 9.2 6.0 18.2 176 59 116.2 42 1,419 0.47 934 335 New England 2.7 2.0 6.0 161 53 118.3 42 1,297 0.43 954 336 Middle Atlantic 6.5 4.1 12.2 184 61 115.3 42 1,478 0.49 926 335

499

Residential Buildings Historical Publications reports, data and housing  

Gasoline and Diesel Fuel Update (EIA)

Natural Gas, 1997 Natural Gas, 1997 Average Natural Gas Residential Buildings Consumption Expenditures Total per Floor- per Square per per per Total Total space (1) Building Foot per Household per Square per Household Households Number (billion (million (thousand Household Member Building Foot Household Member Characteristics (million) (million) sq. ft.) Btu) Btu) (million Btu) (million Btu) (dollars) (dollars) (dollars) (dollars) Total U.S. Households 61.9 51.3 106.1 103 50 85.3 32 698 0.34 579 218 Census Region and Division Northeast 11.8 8.3 19.9 123 52 86.9 35 1,097 0.46 772 310 New England 1.9 1.4 3.3 123 50 87.0 32 1,158 0.48 819 301 Middle Atlantic 9.9 6.9 16.6 124 52 86.9 36 1,085 0.45 763 312

500

Residential Buildings Historical Publications reports, data and housing  

Gasoline and Diesel Fuel Update (EIA)

3 3 Average Electricity Residential Buildings Consumption Expenditures per Total per Square per per per Total Total Floorspace Building Foot per Household per Square per Household Households Number (billion (million (thousand Household Member Building Foot Household Member Characteristics (million) (million) sq. ft.) Btu) Btu) (million Btu) (million Btu) (dollars) (dollars) (dollars) (dollars) Total U.S. Households 96.6 76.4 181.2 43 18 34.0 13 1,061 0.45 840 321 Census Region and Division Northeast 19.5 13.8 40.1 34 12 24.1 9 1,144 0.39 809 309 New England 5.1 3.7 10.6 33 11 24.1 9 1,089 0.38 797 311 Middle Atlantic 14.4 10.1 29.4 35 12 24.2 9 1,165 0.40 814 309