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Note: This page contains sample records for the topic "household income million" from the National Library of EnergyBeta (NLEBeta).
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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

" 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

2

" 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

3

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

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

3 Lighting Usage Indicators by Household Income, 2005" 3 Lighting 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" "Lighting Usage Indicators" "Total U.S. Housing Units",111.1,26.7,28.8,20.6,13.1,22,16.6,38.6 "Indoor Lights Turned On During Summer" "Number of Lights Turned On" "Between 1 and 4 Hours per Day",91.8,20.8,23.6,17,11.3,19.1,13,30.7 "1.",28.6,9.4,9.1,4.5,2.4,3.2,5.7,12.6 "2.",29.5,6.8,8,5.8,3.7,5.2,4.2,10.2

4

" 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

5

" 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

6

" 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

7

" 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

8

" 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

9

" 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

10

"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

11

"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

12

" Million Housing Units, Final...  

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

5 Appliances in U.S. Homes, by Household Income, 2009" " Million Housing Units, Final" ,,"Household Income" ,"Total U.S.1 (millions)",,,"Below Poverty Line2" ,,"Less than...

13

Delivering Energy Efficiency to Middle Income Single Family Households  

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

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

14

Household Energy Expenditure and Income Groups: Evidence from Great Britain  

E-Print Network (OSTI)

  and  0.024  for  district heating However, as income is not observed its effect cannot be analysed.  Wu et al. (2004) examine the demand for space heating in Armenia, Moldova, and  Kyrgyz  Republic  using  household  survey  data.  In  these  countries...  and in some regions incomes are not sufficient to  afford space heating from district heating systems making these systems unviable.  We  analyse  electricity,  gas  and  overall  energy  spending  for  a  large  sample  of  households  in  Great  Britain.  We  discern  inflection  points  and  discuss...

Jamasb, Tooraj; Meier, H

15

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

16

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

17

In the UNITED STATES there are 96.6 million households  

U.S. Energy Information Administration (EIA)

In the UNITED STATES there are 96.6 million households 69% are single-family homes; 25% are apartments; and 6% are mobile homes. Housing stock is ...

18

Department of Energy Provides Nearly $88 Million to Low-Income...  

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

spend 5 percent of their income on paying energy bills, but for lower-income households the costs average 16 percent. These costs can include anything from heating and...

19

Department of Energy Provides Nearly $112 Million to Low-Income...  

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

spend five percent of their income on paying energy bills, but for lower-income households the costs average 16 percent. These costs can include anything from heating and...

20

Energy Department Provides $140.3 Million to Low-Income Families...  

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

spend 3.5 percent of their income on paying energy bills, but for lower-income households the costs average 14 percent. These costs can include anything from heating and...

Note: This page contains sample records for the topic "household income million" 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

Effect of Income on Appliances in U.S. Households, The  

Reports and Publications (EIA)

This web page page entails how people live, the factors that cause the most differences in home lifestyle, including energy use in Geographic Location, Socioeconomics and Household Income.

Michael Laurence

2004-01-01T23:59:59.000Z

22

" Million U.S. Housing Units" ,,"2005...  

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

7 Air-Conditioning Usage Indicators by Household Income, 2005" " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1"...

23

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

24

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

25

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

26

DOE Provides $96.4 Million to Low-Income Families for Home Weatherization |  

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

96.4 Million to Low-Income Families for Home 96.4 Million to Low-Income Families for Home Weatherization DOE Provides $96.4 Million to Low-Income Families for Home Weatherization July 6, 2006 - 2:50pm Addthis Funding is Second Installment of $243 Million in Total Weatherization Grants for FY 2006 WASHINGTON, D.C. - U.S. Department of Energy (DOE) Secretary Samuel W. Bodman today announced $96.4 million in weatherization program grants to 19 states to make energy efficiency improvements in homes of low-income families. Weatherization can reduce an average home's energy costs by $358 annually. Total Fiscal Year 2006 funding is $243 million and will provide weatherization to approximately 96,560 homes. "Weatherizing your home is a valuable way to save energy and money," Secretary Bodman said. "The Department of Energy's weatherization program

27

Department of Energy Provides Nearly $112 Million to Low-Income Families  

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

112 Million to Low-Income 112 Million to Low-Income Families for Home Weatherization Department of Energy Provides Nearly $112 Million to Low-Income Families for Home Weatherization March 29, 2007 - 12:17pm Addthis Funding is First Installment of $204.5 Million in Total Weatherization Grants for FY 2007 WASHINGTON, DC - U.S. Department of Energy (DOE) today announced $111.6 million in weatherization grants to 30 states and the Navajo Nation to make energy efficiency improvements in homes of low-income families. Weatherization can reduce an average home's energy costs by $358 annually. Total Fiscal Year 2007 funding is $204.5 million and will provide weatherization to approximately 70,000 homes. "Weatherization is a valuable way to help save money and energy," DOE Assistant Secretary for Energy Efficiency and Renewable Energy Alexander

28

Energy Department Provides $140.3 Million to Low-Income Families for Home  

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

140.3 Million to Low-Income Families 140.3 Million to Low-Income Families for Home Weatherization Energy Department Provides $140.3 Million to Low-Income Families for Home Weatherization April 3, 2006 - 9:55am Addthis Funding is first installment of $243 million in total weatherization grants for FY 2006 WASHINGTON, D.C. - U.S. Department of Energy (DOE) Secretary Samuel W. Bodman today announced $140.3 million in weatherization program grants to 31 states and the Navajo Nation to make energy efficiency improvements in homes of low-income families; weatherization can reduce an average home's energy costs by $358 annually. Total Fiscal Year 2006 funding is $243 million and will provide weatherization to approximately 96,560 homes. "Weatherizing your home is a valuable way to save energy and money,"

29

Delivering Energy Efficiency to Middle Income Single Family Households  

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

AHPwES - Assisted Home Performance with ENERGY STAR AMI - Area Median Income APS - Arizona Public Service ARRA - American Reinvestment and Recovery Act ASEC - Annual Social and...

30

Department of Energy Provides Nearly $88 Million to Low-Income Families for  

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

88 Million to Low-Income 88 Million to Low-Income Families for Home Weatherization Department of Energy Provides Nearly $88 Million to Low-Income Families for Home Weatherization June 29, 2007 - 2:36pm Addthis Funding is Second Installment of $200 Million in Total Weatherization Grants for FY 2007 WASHINGTON, DC - U.S. Department of Energy (DOE) today announced $88 million in weatherization grants to 20 states to make energy efficiency improvements in homes of low-income families. Weatherization can reduce an average home's energy costs by $358 annually, and this year, DOE expects funding to weatherize approximately 70,000 homes nationwide. For every dollar spent, weatherization returns $1.53 in energy savings over the life of the measures. DOE's weatherization program performs energy

31

Department of Energy Provides Nearly $88 Million to Low-Income Families for  

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

Provides Nearly $88 Million to Low-Income Provides Nearly $88 Million to Low-Income Families for Home Weatherization Department of Energy Provides Nearly $88 Million to Low-Income Families for Home Weatherization June 29, 2007 - 2:36pm Addthis Funding is Second Installment of $200 Million in Total Weatherization Grants for FY 2007 WASHINGTON, DC - U.S. Department of Energy (DOE) today announced $88 million in weatherization grants to 20 states to make energy efficiency improvements in homes of low-income families. Weatherization can reduce an average home's energy costs by $358 annually, and this year, DOE expects funding to weatherize approximately 70,000 homes nationwide. For every dollar spent, weatherization returns $1.53 in energy savings over the life of the measures. DOE's weatherization program performs energy

32

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

SciTech Connect

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

Vine, E.L.; Reyes, I.

1987-09-01T23:59:59.000Z

33

Own-price and income elasticities for household electricity demand : a survey of literature using meta-regression analysis.  

E-Print Network (OSTI)

??Maria Wist Langmoen Own-price and income elasticities for household electricity demand -A Literature survey using meta-regression analysis Economists have been modelling the electricity demand for… (more)

Langmoen, Maria Wist

2004-01-01T23:59:59.000Z

34

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

DOE Green Energy (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

35

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

36

The Impact of Carbon Control on Low-Income Household Electricity and Gasoline Expenditures  

SciTech Connect

In July of 2007 The Department of Energy's (DOE's) Energy Information Administration (EIA) released its impact analysis of 'The Climate Stewardship And Innovation Act of 2007,' known as S.280. This legislation, cosponsored by Senators Joseph Lieberman and John McCain, was designed to significantly cut U.S. greenhouse gas emissions over time through a 'cap-and-trade' system, briefly described below, that would gradually but extensively reduce such emissions over many decades. S.280 is one of several proposals that have emerged in recent years to come to grips with the nation's role in causing human-induced global climate change. EIA produced an analysis of this proposal using the National Energy Modeling System (NEMS) to generate price projections for electricity and gasoline under the proposed cap-and-trade system. Oak Ridge National Laboratory integrated those price projections into a data base derived from the EIA Residential Energy Consumption Survey (RECS) for 2001 and the EIA public use files from the National Household Transportation Survey (NHTS) for 2001 to develop a preliminary assessment of impact of these types of policies on low-income consumers. ORNL will analyze the impacts of other specific proposals as EIA makes its projections for them available. The EIA price projections for electricity and gasoline under the S.280 climate change proposal, integrated with RECS and NHTS for 2001, help identify the potential effects on household electric bills and gasoline expenditures, which represent S.280's two largest direct impacts on low-income household budgets in the proposed legislation. The analysis may prove useful in understanding the needs and remedies for the distributive impacts of such policies and how these may vary based on patterns of location, housing and vehicle stock, and energy usage.

Eisenberg, Joel Fred [ORNL

2008-06-01T23:59:59.000Z

37

The Impact of Carbon Control on Low-Income Household Electricity and Gasoline Expenditures  

SciTech Connect

In July of 2007 The Department of Energy's (DOE's) Energy Information Administration (EIA) released its impact analysis of 'The Climate Stewardship And Innovation Act of 2007,' known as S.280. This legislation, cosponsored by Senators Joseph Lieberman and John McCain, was designed to significantly cut U.S. greenhouse gas emissions over time through a 'cap-and-trade' system, briefly described below, that would gradually but extensively reduce such emissions over many decades. S.280 is one of several proposals that have emerged in recent years to come to grips with the nation's role in causing human-induced global climate change. EIA produced an analysis of this proposal using the National Energy Modeling System (NEMS) to generate price projections for electricity and gasoline under the proposed cap-and-trade system. Oak Ridge National Laboratory integrated those price projections into a data base derived from the EIA Residential Energy Consumption Survey (RECS) for 2001 and the EIA public use files from the National Household Transportation Survey (NHTS) for 2001 to develop a preliminary assessment of impact of these types of policies on low-income consumers. ORNL will analyze the impacts of other specific proposals as EIA makes its projections for them available. The EIA price projections for electricity and gasoline under the S.280 climate change proposal, integrated with RECS and NHTS for 2001, help identify the potential effects on household electric bills and gasoline expenditures, which represent S.280's two largest direct impacts on low-income household budgets in the proposed legislation. The analysis may prove useful in understanding the needs and remedies for the distributive impacts of such policies and how these may vary based on patterns of location, housing and vehicle stock, and energy usage.

Eisenberg, Joel Fred [ORNL

2008-06-01T23:59:59.000Z

38

PRELIMINARY DATA Housing Unit and Household Characteristics  

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

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

39

Patterns of residential energy demand by type of household: white, black, Hispanic, and low- and nonlow-income  

SciTech Connect

This report compares patterns of residential energy use by white, black, Hispanic, low-income, and nonlow-income households. The observed downward trend in residential energy demand over the period of this study can be attributed primarily to changes in space-heating energy demand. Demand for space-heating energy has experienced a greater decline than energy demand for other end uses for two reasons: (1) it is the largest end use of residential energy, causing public attention to focus on it and on strategies for conserving it; and (2) space-heating expenditures are large relative to other residential energy expenditures. The price elasticity of demand is thus greater, due to the income effect. The relative demand for space-heating energy, when controlled for the effect of climate, declined significantly over the 1978-1982 period for all fuels studied. Income classes do not differ significantly. In contrast, black households were found to use more energy for space heating than white households were found to use, although those observed differences are statistically significant only for houses heated with natural gas. As expected, the average expenditure for space-heating energy increased significantly for dwellings heated by natural gas and fuel oil. No statistically significant increases were found in electricity expenditures for space heating. Electric space heat is, in general, confined to milder regions of the country, where space heating is relatively less essential. As a consequence, we would expect the electricity demand for space heating to be more price-elastic than the demand for other fuels.

Klein, Y.; Anderson, J.; Kaganove, J.; Throgmorton, J.

1984-10-01T23:59:59.000Z

40

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

Note: This page contains sample records for the topic "household income million" 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

char_household2001.pdf  

Annual Energy Outlook 2012 (EIA)

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

42

Residential energy consumption of low-income and elderly households: how non-discretionary is it  

SciTech Connect

The energy literature is replete with opinions that the poor and elderly have cut their residential energy consumption to a minimum. This paper challenges such conclusions through an analysis of data on a sample of 319 Decatur, Illinois homeowners. The data include utility bill histories and survey information on housing characteristics, energy-related behaviors, attitudes, and socio-economic and demographic characteristics. It shows that residential energy consumption per square foot of living space is significantly higher for the elderly and poor than for other groups of Decatur homeowners. By breaking energy use into seasonal components, the paper estimates consumption for various household uses. This information, combined with the survey data, suggests that both subgroups heat and cool their homes inefficiently, due in part to the conditions of their homes, but also due to energy-related behaviors. The public policy implications of the findings are discussed.

Brown, M.A.; Rollinson, P.A.

1984-01-01T23:59:59.000Z

43

" Million Housing Units, Final"  

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

5 Air Conditioning in U.S. Homes, by Household Income, 2009" 5 Air Conditioning in U.S. Homes, by Household Income, 2009" " Million Housing Units, Final" ,,"Household Income" ,"Total U.S.1 (millions)",,,,,,,,"Below Poverty Line2" ,,"Less than $20,000","$20,000 to $39,999","$40,000 to $59,999","$60,000 to $79,999","$80,000 to $99,999","$100,000 to $119,999","$120,000 or More" "Air Conditioning" "Total Homes",113.6,23.7,27.5,21.2,14.2,9.3,5.7,12,16.9 "Air Conditioning Equipment" "Use Air Conditioning Equipment",94,18.3,22.3,17.9,11.9,8.1,5.1,10.4,12.8 "Have Air Conditioning Equipment But" "Do Not Use It",4.9,1.5,1.3,0.9,0.5,0.2,0.1,0.3,1

44

" Million Housing Units, Final"  

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

5 Space Heating in U.S. Homes, by Household Income, 2009" 5 Space Heating in U.S. Homes, by Household Income, 2009" " Million Housing Units, Final" ,,"Household Income" ,"Total U.S.1 (millions)",,,,,,,,"Below Poverty Line2" ,,"Less than $20,000","$20,000 to $39,999","$40,000 to $59,999","$60,000 to $79,999","$80,000 to $99,999","$100,000 to $119,999","$120,000 or More" "Space Heating" "Total Homes",113.6,23.7,27.5,21.2,14.2,9.3,5.7,12,16.9 "Space Heating Equipment" "Use Space Heating Equipment",110.1,22.8,26.5,20.5,13.8,9.1,5.6,11.8,16.1 "Have Space Heating Equipment But Do " "Not Use It",2.4,0.6,0.7,0.5,0.2,0.2,0.1,0.1,0.5

45

" Million Housing Units, Final"  

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

5 Appliances in U.S. Homes, by Household Income, 2009" 5 Appliances in U.S. Homes, by Household Income, 2009" " Million Housing Units, Final" ,,"Household Income" ,"Total U.S.1 (millions)",,,,,,,,"Below Poverty Line2" ,,"Less than $20,000","$20,000 to $39,999","$40,000 to $59,999","$60,000 to $79,999","$80,000 to $99,999","$100,000 to $119,999","$120,000 or More" "Appliances" "Total Homes",113.6,23.7,27.5,21.2,14.2,9.3,5.7,12,16.9 "Cooking Appliances" "Stoves (Units With Both" "an Oven and a Cooktop)" "Use a Stove",102.3,22.2,25.8,19.4,13,8.1,4.9,8.8,15.9 "1.",100.8,22,25.6,19.2,12.8,8,4.7,8.5,15.8

46

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

E-Print Network (OSTI)

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

Reimers-Arias, Carlos Alberto

2009-08-01T23:59:59.000Z

47

" Million Housing Units, Final"  

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

5 Household Demographics of U.S. Homes, by Household Income, 2009" 5 Household Demographics of U.S. Homes, by Household Income, 2009" " Million Housing Units, Final" ,,"Household Income" ,"Total U.S.1 (millions)",,,,,,,,"Below Poverty Line2" ,,"Less than $20,000","$20,000 to $39,999","$40,000 to $59,999","$60,000 to $79,999","$80,000 to $99,999","$100,000 to $119,999","$120,000 or More" "Household Demographics" "Total Homes",113.6,23.7,27.5,21.2,14.2,9.3,5.7,12,16.9 "Number of Household Members" "1 Person",31.3,11.3,9.4,5,2.8,1.2,0.5,1,5 "2 Persons",35.8,5.7,8.3,7,5.3,3.1,2,4.3,3.9 "3 Persons",18.1,2.9,3.9,3.5,2.3,1.9,1.1,2.4,2.9

48

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

49

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

U.S. Energy Information Administration (EIA)

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

50

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

51

" Million U.S. Housing Units"  

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

3 Lighting Usage Indicators by Number of Household Members, 2005" " Million U.S. Housing Units" ,,"Number of Households With --" ,"Housing Units (millions)" ,,"1 Member","2...

52

" Million U.S. Housing Units"  

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

7 Air-Conditioning Usage Indicators by Number of Household Members, 2005" " Million U.S. Housing Units" ,,"Number of Households With --" ,"Housing Units (millions)" ,,"1 Member","2...

53

This Policy Brief is an excerpt from the report: "Delivering Energy Efficiency to Middle Income Single Family Households." For the full report and other resources visit: http://middleincome.lbl.gov  

E-Print Network (OSTI)

This Policy Brief is an excerpt from the report: "Delivering Energy Efficiency to Middle Income://middleincome.lbl.gov March 6, 2012 Scaling Energy Efficiency in the Heart of the Residential Market: Increasing Middle America's Access to Capital for Energy Improvements Middle income American households ­ broadly defined

54

" Million U.S. Housing Units, Final"  

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

5 Structural and Geographic Characteristics of U.S. Homes, by Household Income, 2009" 5 Structural and Geographic Characteristics of U.S. Homes, by Household Income, 2009" " Million U.S. Housing Units, Final" ,,"Household Income" ,"Total U.S.1 (millions)",,,,,,,,"Below Poverty Line2" "Structural and Geographic Characteristics",,"Less than $20,000","$20,000 to $39,999","$40,000 to $59,999","$60,000 to $79,999","$80,000 to $99,999","$100,000 to $119,999","$120,000 or More" "Total Homes",113.6,23.7,27.5,21.2,14.2,9.3,5.7,12,16.9 "Census Region and Division" "Northeast",20.8,4,4.3,3.5,2.8,1.9,1.5,2.8,2.9 "New England",5.5,1.1,1,1,0.8,0.5,0.4,0.8,0.8

55

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

56

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

57

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

Annual Energy Outlook 2012 (EIA)

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

58

" 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"

59

" 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

60

" 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

Note: This page contains sample records for the topic "household income million" 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

" Million Housing Units, Final"  

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

4 Household Demographics of U.S. Homes, by Number of Household Members, 2009" 4 Household Demographics of U.S. Homes, by Number of Household Members, 2009" " Million Housing Units, Final" ,,"Number of Household Members" ,"Total U.S.1 (millions)" ,,,,,,"5 or More Members" "Number of Household Members",,"1 Member","2 Members","3 Members","4 Members" "Total Homes",113.6,31.3,35.8,18.1,15.7,12.7 "2009 Annual Household Income" "Less than $20,000",23.7,11.3,5.7,2.9,2,1.9 "$20,000 to $39,999",27.5,9.4,8.3,3.9,3,2.9 "$40,000 to $59,000",21.2,5,7,3.5,3,2.6 "$60,000 to $79,999",14.2,2.8,5.3,2.3,2.2,1.6 "$80,000 to $99,999",9.3,1.2,3.1,1.9,1.7,1.3 "$100,000 to $119,999",5.7,0.5,2,1.1,1.4,0.7

62

Correlation between Median Household Income and LEED Sustainable Site Criteria for Public Transportation Access and a Regression Model Predicting Appraised Unit Value of Unimproved Parcels in Houston, Texas  

E-Print Network (OSTI)

The Leadership in Energy and Environmental Design (LEED) Green Building Rating System provides third-party verification for environmentally sustainable construction. LEED certified buildings often provide healthier work and living environments, however, it does not provide any direct economic incentives to the owners and developers. An early research suggested that there was a significant correlation between appraised unit value of a parcel and LEED sustainable site criteria for public transportation access. Moreover, the regression model for predicting appraised unit value of a parcel suggested that the coefficient of Number of Light Rail Stations was positive, while the coefficient of Number of Bus Stops was negative. This result contradicted our original expectation that both number of bus stops and light rail stations could have a positive effect on the appraised unit value. Hence it becomes important to conduct further research to explain this phenomenon. In this research, Pearson correlation was examined to determine whether there is a significant correlation between median household income and the number of bus stops and light rail stations for a given parcel that meet LEED sustainable site criteria for public transportation access. After confirming no significant correlation exists, multiple regression analysis was applied to establish a regression model for predicting unit value of a given parcel using number of bus stops and light rail stations for a given parcel that meet LEED sustainable site criteria for public transportation access, median household income and parcel area as the independent variables. Result of Pearson correlation indicated that there was no significant correlation exists between median household income and the number of bus stops and light rail stations for a given parcel which met LEED sustainable site criteria for public transportation access. Findings of multiple regression analysis suggested that all independent variables were significant predictors for unit value of a parcel. Besides, this regression model had a higher adjusted R- square value than that of the model which was established by Bhagyashri Joshi. It means that this regression model could better predict appraised unit value of an unimproved parcel.

Ji, Qundi

2010-05-01T23:59:59.000Z

63

This Policy Brief is an excerpt from the report: "Delivering Energy Efficiency to Middle Income Single Family Households." For the full report and other resources visit: http://middleincome.lbl.gov  

E-Print Network (OSTI)

This Policy Brief is an excerpt from the report: "Delivering Energy Efficiency to Middle Income households. This paper is part of the LBNL Clean Energy Financing Policy Brief series. To join the email list in this Policy Brief was funded by the Department of Energy Office of Energy Efficiency and Renewable Energy

64

" Million Housing Units, Final"  

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

5 Televisions in U.S. Homes, by Household Income, 2009" 5 Televisions in U.S. Homes, by Household Income, 2009" " Million Housing Units, Final" ,,"Household Income" ,"Total U.S.1 (millions)",,,,,,,,"Below Poverty Line2" ,,"Less than $20,000","$20,000 to $39,999","$40,000 to $59,999","$60,000 to $79,999","$80,000 to $99,999","$100,000 to $119,999","$120,000 or More" "Televisions" "Total Homes",113.6,23.7,27.5,21.2,14.2,9.3,5.7,12,16.9 "Televisions" "Number of Televisions" 0,1.5,0.5,0.4,0.2,0.2,"Q","Q",0.1,0.3 1,24.2,8,6.4,4.2,2.5,1.1,0.7,1.2,4.8 2,37.5,8.7,10.3,6.7,4.6,2.7,1.4,3.1,5.9 3,26.6,4.2,6.3,5.4,3.6,2.6,1.6,2.9,3.5

65

" Million Housing Units, Final"  

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

5 Computers and Other Electronics in U.S. Homes, by Household Income, 2009" 5 Computers and Other Electronics in U.S. Homes, by Household Income, 2009" " Million Housing Units, Final" ,,"Household Income" ,"Total U.S.1 (millions)",,,,,,,,"Below Poverty Line2" ,,"Less than $20,000","$20,000 to $39,999","$40,000 to $59,999","$60,000 to $79,999","$80,000 to $99,999","$100,000 to $119,999","$120,000 or More" "Computers and Other Electronics" "Total Homes",113.6,23.7,27.5,21.2,14.2,9.3,5.7,12,16.9 "Computers" "Number of Computers" 0,27.4,12.4,9,3.6,1.5,0.4,0.1,0.3,8.4 1,46.9,8.2,13,10.6,6.7,3.7,1.8,2.8,5.8 2,24.3,2.2,4.1,4.6,3.7,2.9,2.2,4.6,1.8 3,9.5,0.6,1,1.6,1.5,1.6,1,2.3,0.5

66

" Million Housing Units, Final"  

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

5 Water Heating in U.S. Homes, by Household Income, 2009" 5 Water Heating in U.S. Homes, by Household Income, 2009" " Million Housing Units, Final" ,,"Household Income" ,"Total U.S.1 (millions)",,,,,,,,"Below Poverty Line2" ,,"Less than $20,000","$20,000 to $39,999","$40,000 to $59,999","$60,000 to $79,999","$80,000 to $99,999","$100,000 to $119,999","$120,000 or More" "Water Heating" "Total Homes",113.6,23.7,27.5,21.2,14.2,9.3,5.7,12,16.9 "Number of Storage Tank Water Heaters" 0,2.9,0.7,0.5,0.3,0.4,0.3,0.2,0.5,0.5 1,108.1,22.9,26.7,20.4,13.4,8.7,5.3,10.6,16.3 "2 or More",2.7,0.1,0.3,0.4,0.4,0.3,0.2,0.9,0.1 "Number of Tankless Water Heaters3"

67

" Million Housing Units, Final"  

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

7 Household Demographics of U.S. Homes, by Census Region, 2009" 7 Household Demographics of U.S. Homes, by Census Region, 2009" " Million Housing Units, Final" ,,"Census Region" ,"Total U.S.1 (millions)" ,,"Northeast","Midwest","South","West" "Number of Household Members" "Total Homes",113.6,20.8,25.9,42.1,24.8 "Number of Household Members" "1 Person",31.3,6,7.4,11.5,6.3 "2 Persons",35.8,6.3,8.5,13.4,7.6 "3 Persons",18.1,3.3,3.9,6.8,4.1 "4 Persons",15.7,3.1,3.5,5.8,3.3 "5 Persons",7.7,1.3,1.7,2.8,2 "6 or More Persons",5,0.8,0.9,1.8,1.5 "2009 Annual Household Income" "Less than $20,000",23.7,4,5.5,10,4.3 "$20,000 to $39,999",27.5,4.3,6.5,10.7,6

68

" Million U.S. Housing Units"  

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

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

69

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

70

Buildings Energy Data Book: 2.9 Low-Income Housing  

Buildings Energy Data Book (EERE)

Level and Weatherization Eligibility (Millions) Single-Family Multi-Family Unit Mobile Home 2005 Household Income Own Rent Own Rent Own Rent Less than 15,000 6.1 2.4 0.3 7.1 1.6...

71

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

U.S. Energy Information Administration (EIA)

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

72

Table US14. Average Consumption by Energy End Uses, 2005 Million ...  

U.S. Energy Information Administration (EIA)

Million British Thermal Units (Btu) per Household U.S. Households (millions) Other Appliances and Lighting Space Heating 4 Air-Conditioning 5 Water Heating 6 ...

73

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

U.S. Energy Information Administration (EIA)

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

74

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

U.S. Energy Information Administration (EIA)

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

75

Nationwide Survey on Household Energy Use  

U.S. Energy Information Administration (EIA)

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

76

" Million U.S. Housing Units"  

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

3 Household Characteristics by Urban/Rural Location, 2005" 3 Household Characteristics by Urban/Rural Location, 2005" " Million U.S. Housing Units" ,,"Urban/Rural Location (as Self-Reported)" ,"Housing Units (millions)" "Household Characteristics",,"City","Town","Surburbs","Rural" "Total",111.1,47.1,19,22.7,22.3 "Household Size" "1 Person",30,14.7,5.1,5.1,5.1 "2 Persons",34.8,12.8,6.1,7.5,8.5 "3 Persons",18.4,7.6,3,3.8,3.9 "4 Persons",15.9,6.8,2.6,3.3,3.1 "5 Persons",7.9,3.3,1.5,2.1,1 "6 or More Persons",4.1,1.9,0.7,0.8,0.7 "2005 Annual Household Income Category" "Less than $9,999",9.9,5.2,1.6,1.2,1.9 "$10,000 to $14,999",8.5,4.5,1.6,0.8,1.6

77

Buildings Energy Data Book: 2.9 Low-Income Housing  

Buildings Energy Data Book (EERE)

4 4 Weatherization Population Facts - Roughly 25% of Federally eligible households move in and out of poverty "classification" each year. - The average income of Federally eligible households in FY 2005 was $16,264, based on RECS and Bureau of the Census' Current Population Survey (CPS) data. - States target the neediest, especially the elderly, persons with disabilities, and families with children. - Since the inception of the Weatherization Assistance Program in 1976, over 6.3 million households have received weatherization services with DOE and leveraged funding. - In FY 2009, the energy burden on Federally eligible households was about four times the burden on Federally ineligible households (14% versus 4%). Source(s): ORNL, Weatherization Works: Final Report on the National Weatherization Evaluation, Sept. 1994, p. 1 for migrating poor; ORNL, 1996 for targeting; HHS,

78

Energy Spending and Vulnerable Households  

E-Print Network (OSTI)

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

Jamasb, Tooraj; Meier, Helena

2011-01-26T23:59:59.000Z

79

Material World: Forecasting Household Appliance Ownership in a Growing Global Economy  

E-Print Network (OSTI)

of Household Income and Appliance Ownership. ECEEE Summerof decreasing prices of appliances, if price data becomesForecasting Household Appliance Ownership in a Growing

Letschert, Virginie

2010-01-01T23:59:59.000Z

80

Car Sharing within Households –  

E-Print Network (OSTI)

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

Francis Papon; Laurent Hivert

2008-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "household income million" 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

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

82

" Million U.S. Housing Units"  

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

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

83

" Million U.S. Housing Units"  

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

3 Household Characteristics by Owner-Occupied Housing Unit, 2005" " Million U.S. Housing Units" ,," Owner-Occupied Housing Units (millions)","Type of Owner-Occupied Housing Unit"...

84

ac_household2001.pdf  

Annual Energy Outlook 2012 (EIA)

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

85

Buildings Energy Data Book: 2.9 Low-Income Housing  

Buildings Energy Data Book (EERE)

Program Definitions DOE Weatherization: Department of Energy's Weatherization Assistance Program DOE Weatherization Eligible Households: Households with incomes at or below 125% of the Federal poverty level, which varies by family size; however, a State may instead elect to use the LIHEAP income standard if its State LIHEAP income standard is at least 125% of the Federal poverty level. Data listed in this chapter include previously weatherized units. DOE Weatherization Eligible Households are a subset of Federally Eligible Households. DOE Weatherization Recipient Households: Households that have received weatherization under DOE Weatherization funding. Federally Eligible Households: Households with incomes below the Federal maximum standard of 150% to 200% of the poverty

86

Utility investments in low-income-energy-efficiency programs  

SciTech Connect

The objective of this study is to describe the energy-efficiency programs being operated by utilities for low-income customers. The study focuses, in particular, on programs that install major residential weatherization measures free-of-charge to low-income households. A survey was mailed to a targeted list of 600 utility program managers. Follow-up telephone calls were made to key non- respondents, and a random sample of other non-respondents also was contacted. Completed surveys were received from 180 utilities, 95 of which provided information on one or more of their 1992 low-income energy-efficiency programs for a total of 132 individual programs. These 132 utility programs spent a total of $140.6 million in 1992. This represents 27% of the total program resources available to weatherize the dwellings of low-income households in that year. Both the total funding and the number of programs has grown by 29% since 1989. A majority of the 132 programs are concentrated in a few regions of the country (California, the Pacific Northwest, the Upper Midwest, and the Northeast). Although a majority of the programs are funded by electric utilities, gas utilities have a significantly greater average expenditure per participant ($864 vs. $307 per participant). The most common primary goal of low-income energy-efficiency programs operating in 1992 was {open_quotes}to make energy services more affordable to low-income customers{close_quotes}. Only 44% of the programs were operated primarily to provide a cost-effective energy resource. Based on a review of household and measure selection criteria, equity and not the efficiency of resource acquisition appears to dominate the design of these programs.

Brown, M.A. [Oak Ridge National Lab., TN (United States); Beyer, M.A. [Aspen Systems Corp., Oak Ridge, TN (United States); Eisenberg, J.; Power, M. [Economic Opportunity Research Institute, Washington, DC (United States); Lapsa, E.J. [Manhattan Data Systems, Knoxville, TN (United States)

1994-09-01T23:59:59.000Z

87

Household vehicles energy consumption 1991  

Science Conference Proceedings (OSTI)

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

Not Available

1993-12-09T23:59:59.000Z

88

" Million U.S. Housing Units"  

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

3 Household Characteristics by Number of Household Members, 2005" 3 Household Characteristics by Number of Household Members, 2005" " Million U.S. Housing Units" ,,"Number of Households With --" ,"Housing Units (millions)" ,,"1 Member","2 Members","3 Members","4 Members","5 or More Members" "Household Characteristics" "Total",111.1,30,34.8,18.4,15.9,12 "Household Size" "1 Person",30,30,"N","N","N","N" "2 Persons",34.8,"N",34.8,"N","N","N" "3 Persons",18.4,"N","N",18.4,"N","N" "4 Persons",15.9,"N","N","N",15.9,"N"

89

file://C:\Documents%20and%20Settings\VM3\My%20Documents\hc6-3a_  

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

3a. Usage Indicators by Household Income, 3a. Usage Indicators by Household Income, Million U.S. Households, 2001 ___________________________________________________________________________________________________________ | | | | | | | 2001 Household Income | | Eli- | | | | | gible | | |___________________________________| | for | | | | | | | | Fed- |

90

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

91

"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

92

" Million Housing Units, Final"  

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

2 Household Demographics of U.S. Homes, by Owner/Renter Status, 2009" 2 Household Demographics of U.S. Homes, by Owner/Renter Status, 2009" " Million Housing Units, Final" ,,,,"Housing Unit Type" ,,,,"Single-Family Units",,,,"Apartments in Buildings With" ,"Total U.S.1 (millions)",,,"Detached",,"Attached",,"2 to 4 Units",,"5 or More Units",,"Mobile Homes" "Household Demographics",,"Own","Rent","Own","Rent","Own","Rent","Own","Rent","Own","Rent","Own","Rent" "Total Homes",113.6,76.5,37.1,63.2,8.6,3.9,2.8,1.5,7.6,2.3,16.8,5.5,1.4 "Number of Household Members"

93

Low-income energy assistance: State responses to funding reductions  

SciTech Connect

Appropriations for the Low Income Home Energy Assistance Program have declined each year since FY 1986, from a level of about $2.0 billion to about $1.5 billion in FY 1988. The President's budget for FY 1989 has proposed a further reduction to about $1.2 billion. The reduction was proposed in recognition of the hundreds of millions of dollars in oil overcharge settlements available to states for this and certain other activities. GAO reviewed 13 states for information on the availability and use of oil overcharge funds; federal allotments to LIHEAP, total LIHEAP funding, and a projection of possible FY 1989 funding; the number of LIHEAP households provided heating assistance; heating benefit levels per household; LIHEAP transfers to and from other block grants; and perceptions of interest groups of past and proposed LIHEAP budget cuts.

Not Available

1988-01-01T23:59:59.000Z

94

Table 1. Total Energy Consumption in U.S. Households by Origin ...  

U.S. Energy Information Administration (EIA)

Wood (million cords) ..... 21.4 19.8 0.8 0.6 0.3 19.3 Million Btu per Household3 Total Btu Consumption per Household, Fuels Used: Electricity Primary ...

95

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

96

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

97

Household vehicles energy consumption 1994  

SciTech Connect

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

NONE

1997-08-01T23:59:59.000Z

98

Factors influencing county level household fuelwood use  

Science Conference Proceedings (OSTI)

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

Skog, K.E.

1986-01-01T23:59:59.000Z

99

An Analysis of the Price Elasticity of Demand for Household Appliances  

E-Print Network (OSTI)

Customers’ Choice of Appliance Efficiency Level: CombiningThe Effect of Income on Appliances in U.S. Households. U.S.Household’s Choice of Appliance Efficiency Level. Review of

Dale, Larry

2008-01-01T23:59:59.000Z

100

Low income home energy assistance  

Science Conference Proceedings (OSTI)

The Low Income Home Energy Assistance Program provides eligible households with assistance for home energy costs. Assistance is available to (1) help families pay heating and cooling costs, (2) prevent energy cutoff in crisis situations, and (3) help families make their homes more energy efficient. This report provides background information on the program in preparation for the program's reauthorization in 1990.

Not Available

1990-10-01T23:59:59.000Z

Note: This page contains sample records for the topic "household income million" 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

EIA - Household Transportation report: Household Vehicles ...  

U.S. Energy Information Administration (EIA)

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

102

U.S. household expenditures for gasoline account for nearly 4% ...  

U.S. Energy Information Administration (EIA)

Gasoline expenditures in 2012 for the average U.S. household reached $2,912, or just under 4% of income before taxes, according to EIA estimates.

103

Top Incomes in Indonesia, 1920-2004 *  

E-Print Network (OSTI)

Using taxation and household survey data, this paper estimates top income shares for Indonesia during 1920-2004. Our results suggest that top income shares grew during the 1920s and 1930s, but fell in the post-war era. In more recent decades, we observe a sharp rise in top income shares during the late-1990s, coincident with the economic downturn, and some evidence that top income shares fell in the early-2000s. For prewar Indonesia, we decompose top income shares by income source, and find that for groups below the top 0.5 percent, a majority of income was derived from wages. Throughout the twentieth century, top income shares in Indonesia have been higher than in India, broadly comparable to Japan, and somewhat lower than levels prevailing in the

Andrew Leigh; Pierre Van Der Eng

2006-01-01T23:59:59.000Z

104

Did Household Consumption Become More Volatile?  

E-Print Network (OSTI)

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

Olga Gorbachev

2009-01-01T23:59:59.000Z

105

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

106

" Million Housing Units, Final"  

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

Household Demographics of U.S. Homes, by Housing Unit Type, 2009" Household Demographics of U.S. Homes, by Housing Unit Type, 2009" " Million Housing Units, Final" ,,"Housing Unit Type" ,,"Single-Family Units",,"Apartments in Buildings With" ,"Total U.S.1 (millions)" ,," Detached"," Attached"," 2 to 4 Units","5 or More Units","Mobile Homes" "Household Demographics" "Total Homes",113.6,71.8,6.7,9,19.1,6.9 "Number of Household Members" "1 Person",31.3,14.4,2.1,3.4,9.6,1.9 "2 Persons",35.8,24.2,1.9,2.5,5,2.1 "3 Persons",18.1,12.1,1.2,1.3,2.2,1.2 "4 Persons",15.7,11.5,1,1,1.5,0.8 "5 Persons",7.7,5.8,0.3,0.5,0.6,0.5

107

" Million Housing Units, Final"  

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

6 Household Demographics of U.S. Homes, by Climate Region, 2009" 6 Household Demographics of U.S. Homes, by Climate Region, 2009" " Million Housing Units, Final" ,,"Climate Region2" ,"Total U.S.1 (millions)" ,,"Very Cold/","Mixed- Humid","Mixed-Dry/" "Household Demographics",,"Cold",,"Hot-Dry","Hot-Humid","Marine" "Total Homes",113.6,38.8,35.4,14.1,19.1,6.3 "Number of Household Members" "1 Person",31.3,11,9.7,3.3,5.4,1.9 "2 Persons",35.8,12.4,11.2,4.4,5.9,1.8 "3 Persons",18.1,6,5.7,2.2,3.1,1.1 "4 Persons",15.7,5.3,4.9,2,2.6,0.9 "5 Persons",7.7,2.6,2.4,1.1,1.2,0.4 "6 or More Persons",5,1.5,1.5,1,0.8,0.2

108

" Million Housing Units, Final"  

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

8 Household Demographics of Homes in Northeast Region, Divisions, and States, 2009" 8 Household Demographics of Homes in Northeast Region, Divisions, and States, 2009" " Million Housing Units, Final" ,,"Northeast Census Region" ,,,"New England Census Division",,,"Middle Atlantic Census Division" ,"Total U.S.1 (millions)",,"Total New England",,,"Total Middle Atlantic" ,,"Total Northeast",,,"CT, ME, NH, RI, VT" "Household Demographics",,,,"MA",,,"NY","PA","NJ" "Total Homes",113.6,20.8,5.5,2.5,3,15.3,7.2,4.9,3.2 "Number of Household Members" "1 Person",31.3,6,1.5,0.7,0.8,4.5,2.1,1.6,0.8 "2 Persons",35.8,6.3,1.8,0.8,1,4.5,2,1.5,0.9

109

" Million Housing Units, Final"  

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

9 Household Demographics of Homes in Midwest Region, Divisions, and States, 2009" 9 Household Demographics of Homes in Midwest Region, Divisions, and States, 2009" " Million Housing Units, Final" ,,"Midwest Census Region" ,,,"East North Central Census Division",,,,,"West North Central Census Division" ,,,"Total East North Central",,,,,"Total West North Central" ,"Total U.S.1 (millions)" ,,"Total Midwest",,,,," IN, OH",,,"IA, MN, ND, SD" "Household Demographics",,,,"IL","MI","WI",,,"MO",,"KS, NE" "Total Homes",113.6,25.9,17.9,4.8,3.8,2.3,7,8.1,2.3,3.9,1.8 "Number of Household Members" "1 Person",31.3,7.4,5.1,1.4,1,0.6,2.1,2.3,0.6,1.1,0.6

110

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

111

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

112

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

113

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

114

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

115

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

116

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

117

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

118

This Policy Brief is an excerpt from the report: "Delivering Energy Efficiency to Middle Income Single Family Households." For the full report and other resources visit: http://middleincome.lbl.gov  

E-Print Network (OSTI)

This Policy Brief is an excerpt from the report: "Delivering Energy Efficiency to Middle Income Purcell, Deputy Director at Home This paper is part of the LBNL Clean Energy Financing Policy Brief series://eetd.lbl.gov/EAP/EMP/. The work described in this Policy Brief was funded by the Department of Energy Office of Energy Efficiency

119

This Policy Brief is an excerpt from the report: "Delivering Energy Efficiency to Middle Income Single Family Households." For the full report and other resources visit: http://middleincome.lbl.gov  

E-Print Network (OSTI)

This Policy Brief is an excerpt from the report: "Delivering Energy Efficiency to Middle Income of the LBNL Clean Energy Program Policy Brief series. These working papers highlight emerging program models and industry). Energy conservation in new and existing buildings plays a key role in the plan's ambitious goals

120

This Policy Brief is an excerpt from the report: "Delivering Energy Efficiency to Middle Income Single Family Households." For the full report and other resources visit: http://middleincome.lbl.gov  

E-Print Network (OSTI)

This Policy Brief is an excerpt from the report: "Delivering Energy Efficiency to Middle Income Clean Energy Financing Policy Brief series. To join the email list to receive these policy briefs for Credit: Case Study on Clean Energy Works Oregon Launched as a Portland-based pilot in April 2010, Clean

Note: This page contains sample records for the topic "household income million" 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

Section J: HOUSEHOLD CHARACTERISTICS  

U.S. Energy Information Administration (EIA)

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

122

Urban household energy use in Thailand  

SciTech Connect

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

Tyler, S.R.

1992-01-01T23:59:59.000Z

123

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

124

Energy and household expenditure patterns  

Science Conference Proceedings (OSTI)

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

Lareau, T.J.; Darmstadter, J.

1983-01-01T23:59:59.000Z

125

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

U.S. Energy Information Administration (EIA)

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

126

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

U.S. Energy Information Administration (EIA)

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

127

Table HC3-1a. Space Heating by Climate Zone, Million U.S ...  

U.S. Energy Information Administration (EIA)

Table HC3-1a. Space Heating by Climate Zone, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total Climate Zone1 RSE

128

Table HC5-7a. Appliances by Four Most Populated States, Million U ...  

U.S. Energy Information Administration (EIA)

Table HC5-7a. Appliances by Four Most Populated States, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total

129

U.S. households forecast to use more heating fuels this ...  

U.S. Energy Information Administration (EIA)

What is the role of coal in the United States? ... 2012 U.S. households ... many located in rural areas. Propane inventories totaled almost 76 million ...

130

Table 1. Total Energy Consumption in U.S. Households by ...  

U.S. Energy Information Administration (EIA)

This write-up presents 1997 Residential Energy Consumption and Expenditures by Origin of Householder. In 1997, there were 101.5 million residential ho ...

131

Table AP1. Total Households Using Home Appliances and Lighting by ...  

U.S. Energy Information Administration (EIA)

Total Consumption for Home Appliances and Lighting by Fuels Used, 2005 Quadrillion British Thermal Units (Btu) U.S. Households (millions) Electricity

132

Table 3. Total Energy Consumption in U.S. Households by ...  

U.S. Energy Information Administration (EIA)

This write-up presents 1997 Residential Energy Consumption and Expenditures by Origin of Householder. In 1997, there were 101.5 million residential ...

133

Econometric analysis of energy use in urban households  

SciTech Connect

This article analyzes the pattern of energy carrier consumption in the residential sector of Bangalore, a major city in south India. A 1,000-household survey was used to study the type of energy carrier used by households in different income groups for different end-uses, such as cooking, water heating, and lighting. The dependence of income on the carrier utilized is established using a carrier dependence index. Using regression analysis, the index analyses the impact of different explanatory variables such as family income, family size, and price of energy carrier on consumption. The results show that income plays an important role not only in the selection of an energy carrier but also on the quantity of consumption per household. Also, a source-service matrix is prepared for Bangalore`s residential sector, which shows the disaggregation of energy consumption by the type of energy carrier and end-use.

Reddy, B.S. [Indira Gandhi Inst. of Development Research, Bombay (India)

1995-05-01T23:59:59.000Z

134

" Million Housing Units, Final"  

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

4 Air Conditioning in U.S. Homes, by Number of Household Members, 2009" 4 Air Conditioning in U.S. Homes, by Number of Household Members, 2009" " Million Housing Units, Final" ,,"Number of Household Members" ,"Total U.S.1 (millions)" ,,,,,,"5 or More Members" "Air Conditioning",,"1 Member","2 Members","3 Members","4 Members" "Total Homes",113.6,31.3,35.8,18.1,15.7,12.7 "Air Conditioning Equipment" "Use Air Conditioning Equipment",94,24.6,30.2,15.1,13.5,10.6 "Have Air Conditioning Equipment But" "Do Not Use It",4.9,1.7,1.5,0.7,0.6,0.5 "Do Not Have Air Conditioning Equipment",14.7,5,4.1,2.3,1.7,1.7 "Type of Air Conditioning Equipment "

135

" Million Housing Units, Final"  

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

4 Space Heating in U.S. Homes, by Number of Household Members, 2009" 4 Space Heating in U.S. Homes, by Number of Household Members, 2009" " Million Housing Units, Final" ,,"Number of Household Members" ,"Total U.S.1 (millions)" ,,,,,,"5 or More Members" "Space Heating",,"1 Member","2 Members","3 Members","4 Members" "Total Homes",113.6,31.3,35.8,18.1,15.7,12.7 "Space Heating Equipment" "Use Space Heating Equipment",110.1,30.3,35,17.6,15.2,12 "Have Space Heating Equipment But Do " "Not Use It",2.4,0.6,0.6,0.3,0.4,0.4 "Do Not Have Space Heating Equipment",1.2,0.3,0.3,0.2,0.1,0.3 "Main Heating Fuel and Equipment2" "Natural Gas",55.6,14.1,17.9,9.4,7.9,6.3

136

" Million Housing Units, Final"  

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

4 Appliances in U.S. Homes, by Number of Household Members, 2009" 4 Appliances in U.S. Homes, by Number of Household Members, 2009" " Million Housing Units, Final" ,,"Number of Household Members" ,"Total U.S.1 (millions)" ,,,,,,"5 or More Members" "Appliances",,"1 Member","2 Members","3 Members","4 Members" "Total Homes",113.6,31.3,35.8,18.1,15.7,12.7 "Cooking Appliances" "Stoves (Units With Both" "an Oven and a Cooktop)" "Use a Stove",102.3,28.8,31.7,16.3,14,11.5 "1.",100.8,28.5,31.2,16,13.9,11.2 "2 or More",1.5,0.3,0.5,0.2,0.2,0.3 "Do Not Use a Stove",11.3,2.5,4.1,1.8,1.7,1.2 "Most-Used Stove Fuel" "Electric",61.9,18.3,19.7,9.7,8.2,6.1

137

" Million Housing Units, Final"  

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

0 Household Demographics of Homes in South Region, Divisions, and States, 2009" 0 Household Demographics of Homes in South Region, Divisions, and States, 2009" " Million Housing Units, Final" ,,"South Census Region" ,,,"South Atlantic Census Division",,,,,,"East South Central Census Division",,,"West South Central Census Division" ,,,,,,,,,"Total East South Central",,,"Total West South Central" ,"Total U.S.1 (millions)",,"Total South Atlantic" ,,"Total South",,,,,"DC, DE, MD, WV",,,,"AL, KY, MS",,,"AR, LA, OK" "Household Demographics",,,,"VA","GA","FL",,"NC, SC",,"TN",,,"TX" "Total Homes",113.6,42.1,22.2,3,3.5,7,3.4,5.4,7.1,2.4,4.6,12.8,8.5,4.2

138

" Million Housing Units, Final"  

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

1 Household Demographics of Homes in West Region, Divisions, and States, 2009" 1 Household Demographics of Homes in West Region, Divisions, and States, 2009" " Million Housing Units, Final" ,,"West Census Region" ,,,"Mountain Census Division",,,,,,,"Pacific Census Division" ,,,,"Mountain North Sub-Division",,,"Mountain South Sub-Division" ,"Total U.S.1 (millions)",,,"Total Mountain North",,,"Total Mountain South" ,,"Total West","Total Mountain",,,"ID, MT, UT, WY",,,,"Total Pacific",,"AK, HI, OR, WA" "Household Demographics",,,,,"CO",,,"AZ","NM, NV",,"CA" "Total Homes",113.6,24.8,7.9,3.9,1.9,2,4,2.3,1.7,16.9,12.2,4.7

139

" Million Housing Units, Final"  

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

4 Structural and Geographic Characteristics of U.S. Homes, by Number of Household Members, 2009" 4 Structural and Geographic Characteristics of U.S. Homes, by Number of Household Members, 2009" " Million Housing Units, Final" ,,"Number of Household Members" ,"Total U.S.1 (millions)" "Structural and Geographic Characteristics",,,,,,"5 or More Members" ,,"1 Member","2 Members","3 Members","4 Members" "Total Homes",113.6,31.3,35.8,18.1,15.7,12.7 "Census Region and Division" "Northeast",20.8,6,6.3,3.3,3.1,2.1 "New England",5.5,1.5,1.8,1,0.7,0.5 "Middle Atlantic",15.3,4.5,4.5,2.3,2.4,1.6 "Midwest",25.9,7.4,8.5,3.9,3.5,2.6 "East North Central",17.9,5.1,5.6,2.7,2.5,1.9

140

Crime and the Nation’s Households, 2000 By  

E-Print Network (OSTI)

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

Patsy A. Klaus

2002-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "household income million" 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

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

142

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

143

Household energy consumption and expenditures 1993  

Science Conference Proceedings (OSTI)

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

NONE

1995-10-05T23:59:59.000Z

144

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

145

" Million U.S. Housing Units"  

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

3 Household Characteristics by Renter-Occupied Housing Unit, 2005" 3 Household Characteristics by Renter-Occupied Housing Unit, 2005" " Million U.S. Housing Units" ,," Renter-Occupied Housing Units (millions)","Type of Renter-Occupied Housing Unit" ,"U.S. Housing Units (millions" ,,,"Single-Family Units",,"Apartments in Buildings With--" "Household Characteristics",,,"Detached","Attached","2 to 4 Units","5 or More Units","Mobile Homes" "Total",111.1,33,8,3.4,5.9,14.4,1.2 "Household Size" "1 Person",30,11.4,1.6,1,1.9,6.6,0.3 "2 Persons",34.8,8,1.9,0.8,1.5,3.5,0.3 "3 Persons",18.4,5.6,1.5,0.7,1.2,1.9,0.2 "4 Persons",15.9,4.3,1.3,0.6,0.7,1.6,"Q"

146

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

147

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

148

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

149

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

150

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

151

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

152

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

153

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

154

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.

155

Model documentation: household model of energy  

Science Conference Proceedings (OSTI)

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

Holte, J.A.

1984-02-01T23:59:59.000Z

156

New Industry Commitments to Give 15 Million Households ...  

Science Conference Proceedings (OSTI)

... a sufficiently large market to support the creation of innovative applications that can help consumers make the most of their energy information. ...

2012-03-26T23:59:59.000Z

157

" Million Housing Units, Final"  

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

Energy Consumption Survey: Final Housing Characteristics Tables" "Preliminary Release: August 19, 2011" "Final Release: April 2013" "Table HC9.5 Household Demographics of U.S....

158

" Million Housing Units, Final...  

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

Energy Consumption Survey: Final Housing Characteristics Tables" "Preliminary Release: August 19, 2011" "Final Release: April 2013" "Table HC9.8 Household Demographics of Homes...

159

" Million Housing Units, Final...  

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

Energy Consumption Survey: Final Housing Characteristics Tables" "Preliminary Release: August 19, 2011" "Final Release: April 2013" "Table HC9.1 Household Demographics of U.S....

160

" Million Housing Units, Final...  

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

Energy Consumption Survey: Final Housing Characteristics Tables" "Preliminary Release: August 19, 2011" "Final Release: April 2013" "Table HC9.7 Household Demographics of U.S....

Note: This page contains sample records for the topic "household income million" 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

" Million Housing Units, Final...  

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

Energy Consumption Survey: Final Housing Characteristics Tables" "Preliminary Release: August 19, 2011" "Final Release: April 2013" "Table HC9.6 Household Demographics of U.S....

162

" Million Housing Units, Final...  

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

Energy Consumption Survey: Final Housing Characteristics Tables" "Preliminary Release: August 19, 2011" "Final Release: April 2013" "Table HC9.3 Household Demographics of U.S....

163

" Million Housing Units, Final"  

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

Energy Consumption Survey: Final Housing Characteristics Tables" "Preliminary Release: August 19, 2011" "Final Release: April 2013" "Table HC9.4 Household Demographics of U.S....

164

" Million Housing Units, Final...  

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

Energy Consumption Survey: Final Housing Characteristics Tables" "Preliminary Release: August 19, 2011" "Final Release: April 2013" "Table HC9.11 Household Demographics of Homes...

165

" Million Housing Units, Final...  

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

Energy Consumption Survey: Final Housing Characteristics Tables" "Preliminary Release: August 19, 2011" "Final Release: April 2013" "Table HC9.10 Household Demographics of Homes...

166

" Million Housing Units, Final...  

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

Energy Consumption Survey: Final Housing Characteristics Tables" "Preliminary Release: August 19, 2011" "Final Release: April 2013" "Table HC9.9 Household Demographics of Homes...

167

" Million Housing Units, Final...  

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

Energy Consumption Survey: Final Housing Characteristics Tables" "Preliminary Release: August 19, 2011" "Final Release: April 2013" "Table HC9.2 Household Demographics of U.S....

168

" Million Housing Units, Final"  

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

3 Household Demographics of U.S. Homes, by Year of Construction, 2009" 3 Household Demographics of U.S. Homes, by Year of Construction, 2009" " Million Housing Units, Final" ,,"Year of Construction" ,"Total U.S.1 (millions)" ,,"Before 1940","1940 to 1949","1950 to 1959","1960 to 1969","1970 to 1979","1980 to 1989","1990 to 1999","2000 to 2009" "Household Demographics" "Total Homes",113.6,14.4,5.2,13.5,13.3,18.3,17,16.4,15.6 "Number of Household Members" "1 Person",31.3,4.8,1.5,3.9,3.9,5,5,3.9,3.3 "2 Persons",35.8,4.5,1.6,4.1,4.3,6.2,5.2,5.2,4.6 "3 Persons",18.1,2,0.9,2.3,2.1,2.8,2.9,2.7,2.4 "4 Persons",15.7,1.8,0.6,1.8,1.6,2.2,2.1,2.6,3.1

169

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

170

" Million U.S. Housing Units"  

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

3 Household Characteristics by Type of Housing Unit, 2005" 3 Household Characteristics by Type of Housing Unit, 2005" " Million U.S. Housing Units" ,,"Type of Housing Unit" ,"Housing Units (millions)","Single-Family Units",,"Apartments in Buildings With--" "Household Characteristics",,"Detached","Attached","2 to 4 Units","5 or More Units","Mobile Homes" "Total",111.1,72.1,7.6,7.8,16.7,6.9 "Household Size" "1 Person",30,14.8,2.4,2.6,7.9,2.4 "2 Persons",34.8,24.8,2.1,2,4.2,1.7 "3 Persons",18.4,12.3,1.2,1.6,2.2,1.2 "4 Persons",15.9,11.1,1.2,0.9,1.6,1 "5 Persons",7.9,6.2,0.5,0.4,0.4,0.4 "6 or More Persons",4.1,2.9,0.2,0.3,0.4,0.3

171

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

172

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

173

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

174

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

175

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

176

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

177

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

178

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

179

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

180

A Framework for Corporate Householding  

E-Print Network (OSTI)

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

Madnick, Stuart

2003-03-21T23:59:59.000Z

Note: This page contains sample records for the topic "household income million" 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

" Million Housing Units, Final...  

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

3 Appliances in U.S. Homes, by Year of Construction, 2009" " Million Housing Units, Final" ,,"Year of Construction" ,"Total U.S.1 (millions)" ,,"Before 1940","1940 to 1949","1950...

182

" Million Housing Units, Final...  

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

6 Appliances in U.S. Homes, by Climate Region, 2009" " Million Housing Units, Final" ,,"Climate Region2" ,"Total U.S.1 (millions)" ,,"Very Cold","Mixed- Humid","Mixed-Dry"...

183

Racial and demographic differences in household travel and fuel purchase behavior  

Science Conference Proceedings (OSTI)

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

Gur, Y.; Millar, M.

1987-01-01T23:59:59.000Z

184

Delivering Energy Efficiency to Middle Income Single Family Households  

E-Print Network (OSTI)

Home Energy Management DIY – Do-It-Yourself HERS – Homeare completed. Do-It-Yourself (DIY) Improvements. About oneand financial incentives for DIY improvements.    Flexible

Zimring, Mark

2012-01-01T23:59:59.000Z

185

Delivering Energy Efficiency to Middle Income Single Family Households  

E-Print Network (OSTI)

HVAC replacement, air sealing, duct sealing, additionaltoday – for example, air sealing and climate-appropriatesome combination of air sealing, insulation, lighting

Zimring, Mark

2012-01-01T23:59:59.000Z

186

Delivering Energy Efficiency to Middle Income Single Family Households  

E-Print Network (OSTI)

rentalhousing/Energy_Efficiency_Project/COB_rebates_8.2.11.PDS/rentalhousing/Energy_Efficiency_Project/SmartRegs_Final_s residential energy efficiency loan program November 2010-

Zimring, Mark

2012-01-01T23:59:59.000Z

187

Delivering Energy Efficiency to Middle Income Single Family Households  

E-Print Network (OSTI)

and Renewable Energy (DOE EERE), Weatherization andand Roya Stanley (DOE EERE) for their support of thisfor Humanity International DOE EERE – Department of Energy

Zimring, Mark

2012-01-01T23:59:59.000Z

188

Equitable economic energy efficiency : creating good jobs in low-income efficiency programming  

E-Print Network (OSTI)

Energy efficiency is an important consideration in energy policy-making. So, a federal program aimed at funding "energy efficiency retrofits" for low-income households could be an important step in increasing the overall ...

Sarin, Amit

2009-01-01T23:59:59.000Z

189

The forgotten class : reconceptualizing contemporary middle-income housing in New York City  

E-Print Network (OSTI)

New York City's costly real estate poses housing affordability challenges for not only low- or even moderate-income households, but also for the so-called "middle class." Because New York is predominantly a renter's market, ...

Milchman, Karina (Karina Faye)

2013-01-01T23:59:59.000Z

190

" Million Housing Units, Final"  

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

4 Fuels Used and End Uses in U.S. Homes, by Number of Household Members, 2009" 4 Fuels Used and End Uses in U.S. Homes, by Number of Household Members, 2009" " Million Housing Units, Final" ,,"Number of Household Members" ,"Total U.S.1 (millions)" ,,,,,,"5 or More Members" "Fuels Used and End Uses",,"1 Member","2 Members","3 Members","4 Members" "Total Homes",113.6,31.3,35.8,18.1,15.7,12.7 "Fuels Used for Any Use" "Electricity",113.6,31.3,35.8,18.1,15.7,12.7 "Natural Gas",69.2,18,21.6,11.5,9.8,8.2 "Propane/LPG",48.9,8.3,17.6,8.4,8.3,6.3 "Wood",13.1,2.3,4.8,2.3,2,1.7 "Fuel Oil",7.7,2.2,2.4,1.1,1.1,0.9 "Kerosene",1.7,0.4,0.5,0.3,0.2,0.3

191

" Million Housing Units, Preliminary"  

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

Computers and Other Electronics in U.S. Homes, By Number of Household Members, 2009" Computers and Other Electronics in U.S. Homes, By Number of Household Members, 2009" " Million Housing Units, Preliminary" ,,"Number of Household Members" ,"Total U.S.1 (millions)" ,,,,,,"5 or More Members" "Computers and Other Electronics",,"1 Member","2 Members","3 Members","4 Members" "Total Homes",113.6,31.3,35.8,18.1,15.7,12.7 "Computers" "Number of Computers" 0,27.4,12.9,7.6,3,1.8,2.1 1,46.9,14.5,15.5,6.7,5.7,4.5 2,24.3,3.1,9.3,4.6,4.2,3.1 3,9.5,0.5,2.6,2.5,2.3,1.7 4,3.6,0.2,0.6,0.9,1.2,0.7 "5 or More",2,0.1,0.3,0.4,0.5,0.7 "Most-Used Computer" "Computer Type" "Desktop",48.3,10.5,16.2,7.9,7.4,6.3

192

" Million Housing Units, Final"  

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

4 Water Heating in U.S. Homes, by Number of Household Members, 2009" 4 Water Heating in U.S. Homes, by Number of Household Members, 2009" " Million Housing Units, Final" ,,"Number of Household Members" ,"Total U.S.1 (millions)" ,,,,,,"5 or More Members" "Water Heating",,"1 Member","2 Members","3 Members","4 Members" "Total Homes",113.6,31.3,35.8,18.1,15.7,12.7 "Number of Storage Tank Water Heaters" 0,2.9,0.9,0.8,0.4,0.4,0.3 1,108.1,30.2,33.9,17.3,14.9,11.9 "2 or More",2.7,0.2,1.1,0.4,0.4,0.5 "Number of Tankless Water Heaters2" 0,110.4,30.6,34.8,17.5,15.2,12.3 1,3.1,0.7,1,0.5,0.5,0.4 "2 or More",0.1,"Q","Q","Q","Q","Q"

193

" Million Housing Units, Final"  

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

4 Televisions in U.S. Homes, by Number of Household Members, 2009" 4 Televisions in U.S. Homes, by Number of Household Members, 2009" " Million Housing Units, Final" ,,"Number of Household Members" ,"Total U.S.1 (millions)" ,,,,,,"5 or More Members" "Televisions",,"1 Member","2 Members","3 Members","4 Members" "Total Homes",113.6,31.3,35.8,18.1,15.7,12.7 "Televisions" "Number of Televisions" 0,1.5,1,0.3,"Q","Q",0.1 1,24.2,12.9,6.7,2.2,1.3,1.1 2,37.5,11.6,13.6,5.4,4,2.8 3,26.6,4,9.1,5.7,4.5,3.3 4,14.2,1.2,3.9,2.9,3.3,2.8 "5 or More",9.7,0.6,2.1,1.7,2.6,2.7 "Most-Used Television" "Display Size" "Less than 21 Inches",12.5,4.9,3.9,1.4,1.1,1.2

194

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

E-Print Network (OSTI)

Homeownership is both an individual and society objective, because of the positive neighborhood effects associated with areas of higher homeownership. To help realize these positive effects, the Mexican government has several programs directed to increasing homeownership. Many factors, however, may influence homeownership including shocks experienced by households. Shocks such as death in family, illness or accidents, unemployment, and business, crop, or livestock loss affect homeownership if households are unable to cushion the impact of the shock. Government income support programs, however, may help cushion the effect of a shock. The main objective is to determine how shocks that households’ experience and government income support programs influence homeownership in Mexico. A secondary objective is to determine how socio-demographic variables influence homeownership in Mexico. Based on the Random Utility Model, logit models of homeownership are estimated using data are from the 2002 Mexican National Survey on Living Levels of Households. Two models are estimated; with and without income. Income is excluded because of a large number of households that did not report income. Generally, inferences from the two models are similar. Homeownership appears to not be affected by shocks experienced by households. It appears households are able to cushion the impact of shocks. The two income support programs, the Program of Direct Rural Support of Mexico (PROGRESA) and the Program of Direct Rural Support of Mexico (PROCAMPO), appear to be increasing homeownership. These social welfare programs provide cash transfers to households. For whatever reason, PROGRESA has a larger effect on homeownership than PROCAMPO. Households with older heads have a larger probability of being a homeowner than households with younger heads. No statistically significance relationship exists between education and homeownership. Regional differences are seen in homeownership, with households located in the northwest region having a higher probability of homeownership than other regions. Differences in the significance of variable representing the household head’s gender, marital status, and occupation on homeownership exist between logit models that include and do not include current income. The most likely reason for these differences is interactions between the variables and a wealth effect.

Lopez Cabrera, Jesus 1977-

2012-12-01T23:59:59.000Z

195

Projecting household energy consumption within a conditional demand framework  

SciTech Connect

Few models attempt to assess and project household energy consumption and expenditure by taking into account differential household choices correlated with such variables as race, ethnicity, income, and geographic location. The Minority Energy Assessment Model (MEAM), developed by Argonne National Laboratory (ANL) for the US Department of Energy (DOE), provides a framework to forecast the energy consumption and expenditure of majority, black, Hispanic, poor, and nonpoor households. Among other variables, household energy demand for each of these population groups in MEAM is affected by housing factors (such as home age, home ownership, home type, type of heating fuel, and installed central air conditioning unit), demographic factors (such as household members and urban/rural location), and climate factors (such as heating degree days and cooling degree days). The welfare implications of the revealed consumption patterns by households are also forecast. The paper provides an overview of the model methodology and its application in projecting household energy consumption under alternative energy scenarios developed by Data Resources, Inc., (DRI).

Teotia, A.; Poyer, D.

1991-01-01T23:59:59.000Z

196

Projecting household energy consumption within a conditional demand framework  

Science Conference Proceedings (OSTI)

Few models attempt to assess and project household energy consumption and expenditure by taking into account differential household choices correlated with such variables as race, ethnicity, income, and geographic location. The Minority Energy Assessment Model (MEAM), developed by Argonne National Laboratory (ANL) for the US Department of Energy (DOE), provides a framework to forecast the energy consumption and expenditure of majority, black, Hispanic, poor, and nonpoor households. Among other variables, household energy demand for each of these population groups in MEAM is affected by housing factors (such as home age, home ownership, home type, type of heating fuel, and installed central air conditioning unit), demographic factors (such as household members and urban/rural location), and climate factors (such as heating degree days and cooling degree days). The welfare implications of the revealed consumption patterns by households are also forecast. The paper provides an overview of the model methodology and its application in projecting household energy consumption under alternative energy scenarios developed by Data Resources, Inc., (DRI).

Teotia, A.; Poyer, D.

1991-12-31T23:59:59.000Z

197

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

198

" Million Housing Units, Final...  

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

0 Appliances in Homes in South Region, Divisions, and States, 2009" " Million Housing Units, Final" ,,"South Census Region" ,,,"South Atlantic Census Division",,,,,,"East South...

199

" Million Housing Units, Final...  

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

8 Home Appliances in Homes in Northeast Region, Divisions, and States, 2009" " Million Housing Units, Final" ,,"Northeast Census Region" ,,,"New England Census Division",,,"Middle...

200

" Million U.S. Housing Units"  

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

5 Space Heating Usage Indicators by Number of Household Members, 2005" 5 Space Heating Usage Indicators by Number of Household Members, 2005" " Million U.S. Housing Units" ,,"Number of Households With --" ,"Housing Units (millions)" ,,"1 Member","2 Members","3 Members","4 Members","5 or More Members" "Space Heating Usage Indicators" "Total U.S. Housing Units",111.1,30,34.8,18.4,15.9,12 "Do Not Have Heating Equipment",1.2,0.3,0.3,"Q",0.2,0.2 "Have Space Heating Equipment",109.8,29.7,34.5,18.2,15.6,11.8 "Use Space Heating Equipment",109.1,29.5,34.4,18.1,15.5,11.6 "Have But Do Not Use Equipment",0.8,"Q","Q","Q","Q","Q"

Note: This page contains sample records for the topic "household income million" 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

" Million U.S. Housing Units"  

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

7 Air-Conditioning Usage Indicators by Number of Household Members, 2005" 7 Air-Conditioning Usage Indicators by Number of Household Members, 2005" " Million U.S. Housing Units" ,,"Number of Households With --" ,"Housing Units (millions)" ,,"1 Member","2 Members","3 Members","4 Members","5 or More Members" "Air-Conditioning Usage Indicators" "Total",111.1,30,34.8,18.4,15.9,12 "Do Not Have Cooling Equipment",17.8,5.4,5.3,2.7,2.5,2 "Have Cooling Equipment",93.3,24.6,29.6,15.7,13.4,10 "Use Cooling Equipment",91.4,24,29.1,15.5,13.2,9.7 "Have Equipment But Do Not Use it",1.9,0.6,0.5,"Q",0.2,0.4 "Type of Air-Conditioning Equipment1, 2" "Central System",65.9,15.3,22.6,10.7,9.9,7.3

202

" Million U.S. Housing Units"  

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

2 Home Electronics Usage Indicators by Number of Household Members, 2005" 2 Home Electronics Usage Indicators by Number of Household Members, 2005" " Million U.S. Housing Units" ,,"Number of Households With --" ,"Housing Units (millions)" ,,"1 Member","2 Members","3 Members","4 Members","5 or More Members" "Home Electronics Usage Indicators" "Total",111.1,30,34.8,18.4,15.9,12 "Personal Computers" "Do Not Use a Personal Computer",35.5,16.3,9.4,4,2.7,3.2 "Use a Personal Computer",75.6,13.8,25.4,14.4,13.2,8.8 "Most-Used Personal Computer" "Type of PC" "Desk-top Model",58.6,10,20,11.2,10.1,7.3 "Laptop Model",16.9,3.7,5.4,3.2,3.1,1.5 "Hours Turned on Per Week"

203

" Million U.S. Housing Units"  

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

0 Home Appliances Usage Indicators by Number of Household Members, 2005" 0 Home Appliances Usage Indicators by Number of Household Members, 2005" " Million U.S. Housing Units" ,,"Number of Households With --" ,"Housing Units (millions)" ,,"1 Member","2 Members","3 Members","4 Members","5 or More Members" "Home Appliances Usage Indicators" "Total",111.1,30,34.8,18.4,15.9,12 "Cooking Appliances" "Frequency of Hot Meals Cooked" "3 or More Times A Day",8.2,1.4,1.9,1.4,1,2.4 "2 Times A Day",24.6,4.3,7.6,4.3,4.8,3.7 "Once a Day",42.3,9.9,14.4,7.4,6.7,4 "A Few Times Each Week",27.2,8.9,9.1,4.6,3.1,1.5 "About Once a Week",3.9,2.2,1,0.5,"Q","Q"

204

" Million U.S. Housing Units"  

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

1 Home Electronics Characteristics by Number of Household Members, 2005" 1 Home Electronics Characteristics by Number of Household Members, 2005" " Million U.S. Housing Units" ,,"Number of Households With --" ,"Housing Units (millions)" ,,"1 Member","2 Members","3 Members","4 Members","5 or More Members" "Home Electronics Characteristics" "Total",111.1,30,34.8,18.4,15.9,12 "Personal Computers" "Do Not Use a Personal Computer ",35.5,16.3,9.4,4,2.7,3.2 "Use a Personal Computer",75.6,13.8,25.4,14.4,13.2,8.8 "Number of Desktop PCs" "1.",50.3,11.9,17.4,8.5,7.3,5.2 "2.",16.2,1.5,5.8,3.8,3.3,1.9 "3 or More",9,0.4,2.2,2.1,2.7,1.7 "Number of Laptop PCs"

205

" Million U.S. Housing Units"  

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" " Million U.S. Housing Units" ,,"Number of Households With --" ,"Housing Units (millions)" ,,"1 Member","2 Members","3 Members","4 Members","5 or More Members" "Home Appliances Characteristics" "Total U.S.",111.1,30,34.8,18.4,15.9,12 "Cooking Appliances" "Conventional Ovens" "Use an Oven",109.6,29.5,34.4,18.2,15.7,11.8 "1.",103.3,28.4,32,17.3,14.7,11 "2 or More",6.2,1.1,2.5,1,0.9,0.8 "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

206

" Million U.S. Housing Units"  

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

6 Air Conditioning Characteristics by Number of Household Members, 2005" 6 Air Conditioning Characteristics by Number of Household Members, 2005" " Million U.S. Housing Units" ,,"Number of Households With --" ,"Housing Units (millions)" ,,"1 Member","2 Members","3 Members","4 Members","5 or More Members" "Air Conditioning Characteristics" "Total",111.1,30,34.8,18.4,15.9,12 "Do Not Have Cooling Equipment",17.8,5.4,5.3,2.7,2.5,2 "Have Coolling Equipment",93.3,24.6,29.6,15.7,13.4,10 "Use Cooling Equipment",91.4,24,29.1,15.5,13.2,9.7 "Have Equipment But Do Not Use it",1.9,0.6,0.5,"Q",0.2,0.4 "Air-Conditioning Equipment1, 2 " "Central System",65.9,15.3,22.6,10.7,9.9,7.3

207

" Million U.S. Housing Units"  

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" " Million U.S. Housing Units" ,,"Number of Households With --" ,"Housing Units (millions)" ,,"1 Member","2 Members","3 Members","4 Members","5 or More Members" "Space Heating Characteristics" "Total",111.1,30,34.8,18.4,15.9,12 "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"

208

" Million U.S. Housing Units"  

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

8 Water Heating Characteristics by Number of Household Members, 2005" 8 Water Heating Characteristics by Number of Household Members, 2005" " Million U.S. Housing Units" ,,"Number of Households With --" ,"Housing Units (millions)" ,,"1 Member","2 Members","3 Members","4 Members","5 or More Members" "Water Heating Characteristics" "Total",111.1,30,34.8,18.4,15.9,12 "Number of Water Heaters" "1.",106.3,28.8,33.4,17.4,15.3,11.4 "2 or More",3.7,0.6,1.1,0.8,0.5,0.6 "Do Not Use Hot Water",1.1,0.6,0.3,"Q","Q","Q" "Housing Units Served by Main Water Heater" "One Housing Unit",99.7,25.3,31.8,16.6,14.6,11.3 "Two or More Housing Units",10.3,4.2,2.7,1.6,1.2,0.6

209

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

SciTech Connect

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

210

Household Vehicles Energy Use Cover Page  

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

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

211

Million Cu. Feet  

Gasoline and Diesel Fuel Update (EIA)

0 0 Alaska - Natural Gas 2010 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table 29. Summary Statistics for Natural Gas - Alaska, 2006-2010 Number of Producing Gas Wells at End of Year................................................... 231 239 261 261 269 Production (million cubic feet) Gross Withdrawals From Gas Wells .............................................. 193,654 165,624 150,483 137,639 127,417 From Oil Wells ................................................ 3,012,097 3,313,666 3,265,401

212

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

213

Household waste disposal in Mekelle city, Northern Ethiopia  

SciTech Connect

In many cities of developing countries, such as Mekelle (Ethiopia), waste management is poor and solid wastes are dumped along roadsides and into open areas, endangering health and attracting vermin. The effects of demographic factors, economic and social status, waste and environmental attributes on household solid waste disposal are investigated using data from household survey. Household level data are then analyzed using multinomial logit estimation to determine the factors that affect household waste disposal decision making. Results show that demographic features such as age, education and household size have an insignificant impact over the choice of alternative waste disposal means, whereas the supply of waste facilities significantly affects waste disposal choice. Inadequate supply of waste containers and longer distance to these containers increase the probability of waste dumping in open areas and roadsides relative to the use of communal containers. Higher household income decreases the probability of using open areas and roadsides as waste destinations relative to communal containers. Measures to make the process of waste disposal less costly and ensuring well functioning institutional waste management would improve proper waste disposal.

Tadesse, Tewodros [Agricultural Economics and Rural Policy Group, Wageningen University, Hollandseweg 1 6706 KN Wageningen (Netherlands)], E-mail: tewodroslog@yahoo.com; Ruijs, Arjan [Environmental Economics and Natural Resources Group, Wageningen University, P.O. Box 8130, 6700 EW Wageningen (Netherlands); Hagos, Fitsum [International Water Management Institute (IWMI), Subregional Office for the Nile Basin and East Africa, P.O. Box 5689, Addis Ababa (Ethiopia)

2008-07-01T23:59:59.000Z

214

Do homeowners increase consumption after the last mortgage payment? An alternative test of the permanent income hypothesis  

E-Print Network (OSTI)

The maturity date of a mortgage loan marks the end of monthly mortgage payments for homeowners. In the period after the last payment, homeowners experience an increase in their monthly disposable income that is equal to the average monthly mortgage payment. Our study interprets this event as an anticipated increase in income, and analyzes consumption behavior over the transition period. In particular, we test whether households smooth consumption as predicted by the rational expectation Life-Cycle/Permanent Income Hypothesis (Re-LC/PIH). We find that they do. Households do not alter nondurable goods consumption in the period following the last mortgage payment despite the increase in disposable income.

Brahima Coulibaly; Geng Li

2006-01-01T23:59:59.000Z

215

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

216

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

217

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

218

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

219

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

220

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

Note: This page contains sample records for the topic "household income million" 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

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

222

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

223

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

224

Portfolio Substitution and the Revenue Cost of the Federal Income Tax Exemption for State and Local Government Bonds  

E-Print Network (OSTI)

This paper illustrates how different assumptions about household portfolio behavior influence estimates of the amount of individual income tax revenue that would be collected if the interest tax exemption for state and ...

Poterba, James M.

225

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

E-Print Network (OSTI)

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

de Lijser, Peter

226

Elasticities of Electricity Demand in Urban Indian Households  

E-Print Network (OSTI)

Energy demand, and in particular electricity demand in India has been growing at a very rapid rate over the last decade. Given, current trends in population growth, industrialisation, urbanisation, modernisation and income growth, electricity consumption is expected to increase substantially in the coming decades as well. Tariff reforms could play a potentially important role as a demand side management tool in India. However, the effects of any price revisions on consumption will depend on the price elasticity of demand for electricity. In the past, electricity demand studies for India published in international journals have been based on aggregate macro data at the country or sub-national / state level. In this paper, price and income elasticities of electricity demand in the residential sector of all urban areas of India are estimated for the first time using disaggregate level survey data for over thirty thousand households. Three electricity demand functions have been estimated using monthly data for the following seasons: winter, monsoon and summer. The results show electricity demand is income and price inelastic in all three seasons, and that household, demographic and geographical variables are important in determining electricity demand, something that is not possible to determine using aggregate macro models alone. Key Words Residential electricity demand, price elasticity, income elasticity Short Title Electricity demand in Indian households Acknowledgements: The authors would like to gratefully acknowledge the National Sample Survey Organisation, Department of Statistics of the Government of India, for making available to us the unit level, household survey data. We would also like to thank Prof. Daniel Spreng for his support of our research. 2 1.

Shonali Pachauri

2002-01-01T23:59:59.000Z

227

The welfare effects of raising household energy prices in Poland  

Science Conference Proceedings (OSTI)

We examine the welfare effects from increasing household energy prices in Poland. Subsidizing household energy prices, common in the transition economies, is shown to be highly regressive. The wealthy spend a larger portion of their income on energy and consume more energy in absolute terms. We therefore rule out the oft-used social welfare argument for delaying household energy price increases. Raising prices, while targeting relief to the poor through a social assistance program is the first-best response. However, if governments want to ease the adjustment, several options are open, including: in-kind transfers to the poor, vouchers, in-cash transfers, and lifeline pricing for electricity. Our simulations show that if raising prices to efficient levels is not politically feasible at present and social assistance targeting is sufficiently weak, it may be socially better to use lifeline pricing and a large price increase than an overall, but smaller, price increase.

Freund, C.L. [Columbia Univ., New York, NY (United States); Wallich, C.I. [World Bank, Washington, DC (United States)

1996-06-01T23:59:59.000Z

228

2 The Financial and Economic Crises: Implications for Consumer Finance and for Households in Michigan  

E-Print Network (OSTI)

IPPSR and MSUE at Michigan State University for financial support. This paper was partially written while a Visiting Scholar at the National Poverty Center at the University of Michigan, and its Michigan is an epicenter of the recent economic and financial crises. Median personal income was 8 percent above the national average at the beginning of the decade and was 8 percent below the national average by the end of it. Between 2008 and 2009, personal income fell for the first time since 1958. Rates of unemployment and foreclosure activity remain high and above the national average. Indeed, the Michigan economy is changing in dramatic and important ways, but there is little information on household responses to this changing environment. How are Michigan households responding to economic and financial shocks? Are they smoothing income, consumption, or both? What mechanisms are they using to achieve these outcomes? On which factors does the degree of adjustment depend? Using data collected from recent household surveys,

Lisa D. Cook; Lisa D. Cook; Ann Marie Schneider; Lauren Meunier; Lisa D. Cook

2010-01-01T23:59:59.000Z

229

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

230

Household energy handbook: an interim guide and reference manual. World Bank technical paper  

SciTech Connect

A standard framework for measuring and assessing technical information on the household energy sector in developing countries is needed. The handbook is intended as a first step toward creating such a framework. Chapter I discusses energy terms and principles underlying the energy units, definitions, and calculations presented in the following chapters. Chapter II describes household consumption patterns and their relationship to income, location, and household-size variables. Chapter III evaluates energy end uses and the technologies that provide cooking, lighting, refrigeration, and space-heating services. Chapter IV examines household energy resources and supplies, focusing on traditional biomass fuels. Finally, Chapter V demonstrates simple assessment methods and presents case studies to illustrate how household energy data can be used in different types of assessments.

Leach, G.; Gowen, M.

1987-01-01T23:59:59.000Z

231

Household Vehicles Energy Consumption 1991  

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

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

232

Household Energy Consumption and Expenditures  

Reports and Publications (EIA)

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

Information Center

2008-09-01T23:59:59.000Z

233

Household Vehicles Energy Consumption 1991  

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

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

234

Household Vehicles Energy Consumption 1994  

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

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

235

" Million U.S. Housing Units"  

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

3 Household Characteristics by Year of Construction Unit, 2005" 3 Household Characteristics by Year of Construction Unit, 2005" " Million U.S. Housing Units" ,,"Year of Construction" ,"Housing Units (millions)" ,,"Before 1940","1940 to 1949","1950 to 1959","1960 to 1969","1970 to 1979","1980 to 1989","1990 to 1999","2000 to 2005" "Household Characteristics" "Total",111.1,14.7,7.4,12.5,12.5,18.9,18.6,17.3,9.2 "Household Size" "1 Person",30,4.6,2.5,3.7,3.2,5.4,5.5,3.7,1.6 "2 Persons",34.8,4.3,1.9,4.4,4.1,5.9,5.3,5.5,3.4 "3 Persons",18.4,2.5,1.3,1.7,1.9,2.9,3.5,2.8,1.6 "4 Persons",15.9,1.9,0.8,1.5,1.6,3,2.5,3.1,1.4

236

" Million U.S. Housing Units"  

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

3 Household Characteristics by Climate Zone, 2005" 3 Household Characteristics by Climate Zone, 2005" " Million U.S. Housing Units" ,,"Climate Zone1" ,,"Less than 2,000 CDD and --",,,,"2,000 CDD or More and Less than 4,000 HDD" ,"Housing Units (millions)" ,,"Greater than 7,000 HDD","5,500 to 7,000 HDD","4,000 to 5,499 HDD","Less than 4,000 HDD" "Household Characteristics" "Total",111.1,10.9,26.1,27.3,24,22.8 "Household Size" "1 Person",30,2.6,7.9,7.3,6.5,5.8 "2 Persons",34.8,4.3,7.7,8.2,7.1,7.5 "3 Persons",18.4,1.8,4.2,4.8,3.9,3.7 "4 Persons",15.9,1.2,3.7,4,3.9,2.9 "5 Persons",7.9,0.7,1.8,2,1.4,2 "6 or More Persons",4.1,0.3,0.8,1,1.1,0.8

237

Buildings Energy Data Book: 2.9 Low-Income Housing  

Buildings Energy Data Book (EERE)

2 2 Energy Burden Definitions Energy burden is an important statistic for policy makers who are considering the need for energy assistance. Energy burden can be defined broadly as the burden placed on household incomes by the cost of energy, or more simply, the ratio of energy expenditures to household income. However, there are different ways to compute energy burden, and different interpretations and uses of the energy burden statistics. DOE Weatherization primarily uses mean individual burden and mean group burden since these statistics provide data on how an "average" individual household fares against an "average" group of households (that is, how burdens are distributed for the population). DOE Weatherization (and HHS) also uses the median individual burden which shows

238

Smoking, Drinking, and Income  

E-Print Network (OSTI)

A growing literature identifies a beneficial effect of moderate and even heavy drinking on wages and a negative effect of smoking on wages. An outstanding issue is whether these results obtain because of a causal effect of substance use on wages or whether the observed correlations reflect the effects of income on consumption or other endogeneity problems. This paper presents full information estimates of the structural parameters of a simultaneous model of drinking and smoking status and income using repeated cross--section data. With all else in the system held constant, both smoking and drinking behaviour still have large effects on income, and the income elasticities of smoking and drinking are shown to be larger in magnitude when controlling for endogeneity. JEL Classification: I12 Keywords: alcohol, tobacco, simultaneous equations, maximum simulated likelihood, multinomial probit, limited dependent variables 1 I thank Cam Donaldson, Herb Emery, David Feeny, Chris Ferrall, Jon ...

Mingshan Lu; James Mackinnon; Ken Mckenzie; Harry Paarsche; Seminar Participants; M. Christopher Auld; M. Christopher Auld

1999-01-01T23:59:59.000Z

239

Weatherizing the Homes of Low-Income Home Energy Assistance Program Clients: A Programmatic Assessment  

SciTech Connect

The purpose of this project was to assess the relationships between two federal programs that support low income households, the Weatherization Assistance Program (WAP) and the Low Income Home Energy Assistance Program (LIHEAP). The specific question addressed by this research is: what impact does weatherizing homes of LIHEAP recipients have on the level of need for LIHEAP assistance? The a priori expectation is that the level of need will decrease. If this is the case, then it can be argued that a non-energy benefit of WAP is the reduction in the level of need for LIHEAP assistance for households receiving weatherization assistance. The study area for this project was Boston, Massachusetts, which is representative of large northern urban areas. Additionally, Boston was chosen because one of its social service agencies, Action for Boston Community Development (ABCD), administers both WAP and LIHEAP programs. ABCD has a substantial client base of low-income households and was willing to cooperate in this study. In the State of Massachusetts, an income test is used to determine whether low-income households qualify for standard LIHEAP benefits. Benefits provided to eligible households are determined by a schedule that gauges benefit levels based on household income and number of members in the household. Additionally, households that consume large amounts of primary heating fuel can also qualify an additional high energy subsidy. It was expected that weatherization's biggest influence on the LIHEAP program would be in reducing the number of households qualifying for high energy subsidies. Data were collected for three groups of households that received both weatherization and LIHEAP assistance and for one control group that only received LIHEAP assistance. Table ES-1 indicates the sample sizes, weatherization dates, and winter time periods when changes in energy consumption and receipt of LIHEAP benefits could be expected to be observed. The reason why there is a lag of one year when weatherization impacts upon LIHEAP benefits might be observed is that LIHEAP benefits--specifically high energy benefits--are based on the previous year's primary heat fuel bills.

Tonn, B.

2002-09-16T23:59:59.000Z

240

Extending Efficiency Services to Underserved Households: NYSERDA...  

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

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

Note: This page contains sample records for the topic "household income million" 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

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

Science Conference Proceedings (OSTI)

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

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

1981-03-01T23:59:59.000Z

242

Obama Administration Delivers More than $101 Million for Weatherization  

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

Delivers More than $101 Million for Delivers More than $101 Million for Weatherization Programs in Guam and Pennsylvania Obama Administration Delivers More than $101 Million for Weatherization Programs in Guam and Pennsylvania August 25, 2009 - 12:00am Addthis WASHINGTON, DC - U.S. Department of Energy Secretary Steven Chu today announced that the Department of Energy is providing more than $101 million in funding from the American Recovery and Reinvestment Act to expand weatherization assistance programs in Guam and Pennsylvania. The funding, along with additional funds to be disbursed after the grantees meet certain Recovery Act milestones, will help them weatherize approximately 29,200 homes, lowering energy costs for low-income families that need it, reducing pollution, and creating green jobs across the country.

243

Obama Administration Delivers More Than $66 Million for Weatherization  

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

Than $66 Million for Than $66 Million for Weatherization Programs in Alaska, Colorado, Connecticut and Hawaii Obama Administration Delivers More Than $66 Million for Weatherization Programs in Alaska, Colorado, Connecticut and Hawaii August 13, 2009 - 12:00am Addthis WASHINGTON, DC - U.S. Department of Energy Secretary Steven Chu today announced that the Department of Energy is providing more than $66 million in funding from the American Recovery and Reinvestment Act to expand weatherization assistance programs in Alaska, Colorado, Connecticut and Hawaii. The funding, along with additional funds to be disbursed after the states meet certain Recovery Act milestones, will help these states weatherize approximately 26,300 homes, lowering energy costs for low-income families that need it, reducing pollution, and creating green jobs across

244

Obama Administration Delivers More than $63 Million for Weatherization  

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

Delivers More than $63 Million for Delivers More than $63 Million for Weatherization Programs in Indiana and New Mexico Obama Administration Delivers More than $63 Million for Weatherization Programs in Indiana and New Mexico July 21, 2009 - 12:00am Addthis WASHINGTON, DC - U.S. Department of Energy Secretary Steven Chu today announced that the Department of Energy is providing more than $63 million in funding from the American Recovery and Reinvestment Act to expand weatherization assistance programs in Indiana and New Mexico. The funding, along with additional funds to be disbursed after the states meet certain Recovery Act milestones, will help these states achieve their goal of weatherizing more than 22,400 homes, lowering energy costs for low-income families that need it, reducing greenhouse gas emissions, and creating

245

Obama Administration Delivers More than $60 Million for Weatherization  

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

Obama Administration Delivers More than $60 Million for Obama Administration Delivers More than $60 Million for Weatherization Programs in Six States and Territories Obama Administration Delivers More than $60 Million for Weatherization Programs in Six States and Territories September 14, 2009 - 12:00am Addthis WASHINGTON, DC - U.S. Department of Energy Secretary Steven Chu today announced that the Department of Energy is providing more than $60 million in funding from the American Recovery and Reinvestment Act to expand weatherization assistance programs in American Samoa, Northern Arapaho Tribe, Northern Mariana Islands, Puerto Rico, Tennessee, and the U.S. Virgin Islands. The funding, along with additional funds to be disbursed after the grantees meet certain Recovery Act milestones, will help to weatherize nearly 17,000 homes, lowering energy costs for low-income

246

Obama Administration Delivers More than $448 Million for Weatherization  

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

48 Million for 48 Million for Weatherization Programs in Thirteen States Obama Administration Delivers More than $448 Million for Weatherization Programs in Thirteen States July 10, 2009 - 12:00am Addthis WASHINGTON, DC - U.S. Department of Energy Secretary Steven Chu today announced that the Department of Energy is providing more than $448 million in Recovery Act funding to expand weatherization assistance programs in Alabama, Idaho, Maine, Missouri, New Jersey, Oklahoma, Rhode Island, Texas, Vermont, Virginia, Washington, Wisconsin, and Wyoming. These funds, along with additional funds to be disbursed after the states meet certain Recovery Act milestones, will help to weatherize more than 125,000 homes, cutting energy costs for low-income families that need it, reducing

247

Obama Administration Delivers More than $101 Million for Weatherization  

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

Obama Administration Delivers More than $101 Million for Obama Administration Delivers More than $101 Million for Weatherization Programs in Guam and Pennsylvania Obama Administration Delivers More than $101 Million for Weatherization Programs in Guam and Pennsylvania August 25, 2009 - 12:00am Addthis WASHINGTON, DC - U.S. Department of Energy Secretary Steven Chu today announced that the Department of Energy is providing more than $101 million in funding from the American Recovery and Reinvestment Act to expand weatherization assistance programs in Guam and Pennsylvania. The funding, along with additional funds to be disbursed after the grantees meet certain Recovery Act milestones, will help them weatherize approximately 29,200 homes, lowering energy costs for low-income families that need it, reducing pollution, and creating green jobs across the country.

248

Obama Administration Delivers More than $288 Million for Weatherization  

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

Delivers More than $288 Million for Delivers More than $288 Million for Weatherization Programs in Seven States Obama Administration Delivers More than $288 Million for Weatherization Programs in Seven States July 6, 2009 - 12:00am Addthis WASHINGTON, DC - U.S. Department of Energy Secretary Steven Chu today announced that the Department of Energy is providing more than $288 million in Recovery Act funding to expand weatherization assistance programs in Arkansas, Iowa, Kentucky, Massachusetts, Michigan, Minnesota, and New Hampshire. These funds, along with additional funds to be disbursed after the states meet certain Recovery Act milestones, will help these states achieve their goal of weatherizing more than 91,000 homes, lowering energy costs for low-income families that need it, reducing greenhouse gas

249

Obama Administration Delivers More than $60 Million for Weatherization  

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

Obama Administration Delivers More than $60 Million for Obama Administration Delivers More than $60 Million for Weatherization Programs in Six States and Territories Obama Administration Delivers More than $60 Million for Weatherization Programs in Six States and Territories September 14, 2009 - 12:00am Addthis WASHINGTON, DC - U.S. Department of Energy Secretary Steven Chu today announced that the Department of Energy is providing more than $60 million in funding from the American Recovery and Reinvestment Act to expand weatherization assistance programs in American Samoa, Northern Arapaho Tribe, Northern Mariana Islands, Puerto Rico, Tennessee, and the U.S. Virgin Islands. The funding, along with additional funds to be disbursed after the grantees meet certain Recovery Act milestones, will help to weatherize nearly 17,000 homes, lowering energy costs for low-income

250

Obama Administration Delivers More than $288 Million for Weatherization  

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

288 Million for 288 Million for Weatherization Programs in Seven States Obama Administration Delivers More than $288 Million for Weatherization Programs in Seven States July 6, 2009 - 12:00am Addthis WASHINGTON, DC - U.S. Department of Energy Secretary Steven Chu today announced that the Department of Energy is providing more than $288 million in Recovery Act funding to expand weatherization assistance programs in Arkansas, Iowa, Kentucky, Massachusetts, Michigan, Minnesota, and New Hampshire. These funds, along with additional funds to be disbursed after the states meet certain Recovery Act milestones, will help these states achieve their goal of weatherizing more than 91,000 homes, lowering energy costs for low-income families that need it, reducing greenhouse gas emissions, and creating green jobs across the country.

251

Obama Administration Delivers More than $63 Million for Weatherization  

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

Delivers More than $63 Million for Delivers More than $63 Million for Weatherization Programs in Indiana and New Mexico Obama Administration Delivers More than $63 Million for Weatherization Programs in Indiana and New Mexico July 21, 2009 - 12:00am Addthis WASHINGTON, DC - U.S. Department of Energy Secretary Steven Chu today announced that the Department of Energy is providing more than $63 million in funding from the American Recovery and Reinvestment Act to expand weatherization assistance programs in Indiana and New Mexico. The funding, along with additional funds to be disbursed after the states meet certain Recovery Act milestones, will help these states achieve their goal of weatherizing more than 22,400 homes, lowering energy costs for low-income families that need it, reducing greenhouse gas emissions, and creating

252

Obama Administration Delivers More than $304 Million for Weatherization  

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

304 Million for 304 Million for Weatherization Programs in Georgia, Illinois and New York Obama Administration Delivers More than $304 Million for Weatherization Programs in Georgia, Illinois and New York June 26, 2009 - 12:00am Addthis WASHINGTON, DC -- U.S. Department of Energy Secretary Steven Chu today announced that the Department of Energy is providing more than $304 million in Recovery Act funding to expand weatherization assistance programs in Georgia, Illinois and New York. These funds, along with additional funds to be disbursed after the states meet certain Recovery Act milestones, will help these states achieve their goal of weatherizing more than 85,000 homes, lowering energy costs for low-income families that need it, reducing greenhouse gas emissions, and creating green jobs across the country.

253

Obama Administration Delivers More than $453 Million for Weatherization  

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

53 Million for 53 Million for Weatherization Programs in 15 States Obama Administration Delivers More than $453 Million for Weatherization Programs in 15 States June 18, 2009 - 12:00am Addthis COLUMBUS, OHIO - U.S. Department of Energy Secretary Steven Chu today announced that the Department of Energy is providing more than $453 million in Recovery Act funding to expand weatherization assistance programs in 15 additional states. These funds, along with additional funds to be disbursed after the states meet certain Recovery Act milestones, will help these states achieve their goal of weatherizing more than 165,000 homes, lowering energy costs for low-income families that need it, reducing greenhouse gas emissions, and creating green jobs across the country. Secretary Chu made today's announcement while helping to weatherize a local

254

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

255

Energy Department Awards $92.5 Million to 19 States to Weatherize Homes of  

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

92.5 Million to 19 States to Weatherize 92.5 Million to 19 States to Weatherize Homes of Low-Income Families Energy Department Awards $92.5 Million to 19 States to Weatherize Homes of Low-Income Families July 18, 2005 - 2:22pm Addthis WASHINGTON, DC - Secretary of Energy Samuel W. Bodman announced that $92.5 million has been awarded to 19 states to improve the energy efficiency of low-income family homes. The Department of Energy's (DOE) Weatherization Assistance Program makes improvements such as plugging air leaks, improving insulation and tuning air conditioning and heating systems, which reduces energy waste and lowers energy bills. Through DOE's weatherization program, approximately 92,300 homes will be upgraded this year. "The Department of Energy's Weatherization Assistance Program helps

256

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

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

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

257

Private Sector Saw Solyndra as a Sound Investment, Put $961 Million Behind  

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

Saw Solyndra as a Sound Investment, Put $961 Million Behind Saw Solyndra as a Sound Investment, Put $961 Million Behind the Promising Company Solyndra's great promise and innovative technologies were widely recognized and highly valued by a wide range of very sophisticated private investors. In its S-1 Form filed with the Securities and Exchange Commission in December 2009, Solyndra detailed more than $961 million of private capital that investors had put on the line after conducting their own independent assessments of the company. The list is below: Affiliates of Artis Capital Management, L.P.: $44 million Affiliates of Kohlberg Kravis Roberts & Co. (Fixed Income) LLC: $2.07 million Argonaut Ventures I, L.L.C.: $270.658 million CMEA Ventures VI, L.P.: $17.666 million CMEA Ventures VII, L.P.: $10 million

258

Household Vehicles Energy Consumption 1994  

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

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

259

Household savings and portfolio choice  

E-Print Network (OSTI)

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

Klein, Sean Patrick

2010-01-01T23:59:59.000Z

260

" Million U.S. Housing Units"  

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

2 Living Space Characteristics by Number of Household Members, 2005" 2 Living Space Characteristics by Number of Household Members, 2005" " Million U.S. Housing Units" ,,"Number of Households With --" ,"Housing Units (millions)" ,,"1 Member","2 Members","3 Members","4 Members","5 or More Members" "Living Space Characteristics" "Total",111.1,30,34.8,18.4,15.9,12 "Floorspace (Square Feet)" "Total Floorspace1" "Fewer than 500",3.2,1.7,0.8,0.4,0.3,"Q" "500 to 999",23.8,10.2,6.4,3.4,2.3,1.5 "1,000 to 1,499",20.8,5.5,6.3,3,3.3,2.6 "1,500 to 1,999",15.4,3.8,4.7,2.9,2.2,1.9 "2,000 to 2,499",12.2,2.6,4,2.5,2,1.3 "2,500 to 2,999",10.3,1.9,4.1,1.7,1.3,1.3

Note: This page contains sample records for the topic "household income million" 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

Million Solar Roofs: Become One In A Million  

SciTech Connect

Since its announcement in June 1997, the Million Solar Roofs Initiative has generated a major buzz in communities, states, and throughout the nation. With more than 300,000 installations, the buzz is getting louder. This brochure describes Million Solar Roofs activities and partnerships.

2003-11-01T23:59:59.000Z

262

projects are valued at approximately $67 million (including $15 million  

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

projects are valued at approximately $67 million (including $15 million projects are valued at approximately $67 million (including $15 million in non-Federal cost sharing) over four years. The overall goal of the research is to develop carbon dioxide (CO 2 ) capture and separation technologies that can achieve at least 90 percent CO 2 removal at no more than a 35 percent increase in the cost of electricity. The projects, managed by FE's National Energy Technology Laboratory (NETL), include: (1) Linde, LLC, which will use a post-combustion capture technology incorporating BASF's novel amine-based process at a 1-megawatt electric (MWe) equivalent slipstream pilot plant at the National Carbon Capture Center (NCCC) (DOE contribution: $15 million); (2) Neumann Systems Group, Inc., which will design, construct, and test a patented NeuStreamTM absorber at the Colorado

263

Household energy use in urban Venezuela: Implications from surveys in Maracaibo, Valencia, Merida, and Barcelona-Puerto La Cruz  

Science Conference Proceedings (OSTI)

This report identifies the most important results of a comparative analysis of household commercial energy use in Venezuelan urban cities. The use of modern fuels is widespread among all cities. Cooking consumes the largest share of urban household energy use. The survey documents no use of biomass and a negligible use of kerosene for cooking. LPG, natural gas, and kerosene are the main fuels available. LPG is the fuel choice of low-income households in all cities except Maracaibo, where 40% of all households use natural gas. Electricity consumption in Venezuela`s urban households is remarkably high compared with the levels used in households in comparable Latin American countries and in households of industrialized nations which confront harsher climatic conditions and, therefore, use electricity for water and space heating. The penetration of appliances in Venezuela`s urban households is very high. The appliances available on the market are inefficient, and there are inefficient patterns of energy use among the population. Climate conditions and the urban built form all play important roles in determining the high level of energy consumption in Venezuelan urban households. It is important to acknowledge the opportunities for introducing energy efficiency and conservation in Venezuela`s residential sector, particularly given current economic and financial constraints, which may hamper the future provision of energy services.

Figueroa, M.J.; Sathaye, J.

1993-08-01T23:59:59.000Z

264

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

E-Print Network (OSTI)

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

Turrentine, Thomas; Kurani, Kenneth

1995-01-01T23:59:59.000Z

265

RECS data show decreased energy consumption per household  

Reports and Publications (EIA)

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

2012-06-06T23:59:59.000Z

266

EERE Celebrates Completion of 1 Million Weatherized American Homes |  

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

EERE Celebrates Completion of 1 Million Weatherized American Homes EERE Celebrates Completion of 1 Million Weatherized American Homes EERE Celebrates Completion of 1 Million Weatherized American Homes September 27, 2012 - 10:07am Addthis 1 of 6 David Poindexter with Veterans Green Jobs, puts moisture barrier and insulation into the crawl space of this Lakewood, Colorado, home. This home is part of the Energy Department's Weatherization Assistance Program that supports energy efficiency upgrades to low-income homes in Denver. In addition, the Department's Weatherization and Intergovernmental Program supports development of National Residential Retrofit Guidelines that will improve worker training and workforce development for weatherization and home improvement workers and enable these industries to increase the value of their services to homeowners. | Photo courtesy of Dennis Schroeder,

267

Celebrating the Completion of 1 Million Weatherized American Homes |  

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

Celebrating the Completion of 1 Million Weatherized American Homes Celebrating the Completion of 1 Million Weatherized American Homes Celebrating the Completion of 1 Million Weatherized American Homes Addthis 1 of 6 David Poindexter with Veterans Green Jobs, puts moisture barrier and insulation into the crawl space of this Lakewood, Colorado, home. This home is part of the Energy Department's Weatherization Assistance Program that supports energy efficiency upgrades to low-income homes in Denver. In addition, the Department's Weatherization and Intergovernmental Program supports development of National Residential Retrofit Guidelines that will improve worker training and workforce development for weatherization and home improvement workers and enable these industries to increase the value of their services to homeowners. | Photo courtesy of Dennis Schroeder,

268

LOW CARBON & 570 million GVA  

E-Print Network (OSTI)

,240 PEOPLE, CONTRIBUTING £570 MILLION IN GVA. Across Sheffield City Region, the low carbon and renewable sec nuclear, wind, solar, geo-thermal and tidal power. The total market value of the low carbon environmental goods and services sector for Sheffield City Region is estimated at £1,620 million. Independent research

Wrigley, Stuart

269

Household energy in South Asia  

Science Conference Proceedings (OSTI)

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

Leach, G.

1987-01-01T23:59:59.000Z

270

Energy for 500 Million Homes: Drivers and Outlook for Residential Energy Consumption in China  

SciTech Connect

China's rapid economic expansion has propelled it to the rank of the largest energy consuming nation in the world, with energy demand growth continuing at a pace commensurate with its economic growth. The urban population is expected to grow by 20 million every year, accompanied by construction of 2 billion square meters of buildings every year through 2020. Thus residential energy use is very likely to continue its very rapid growth. Understanding the underlying drivers of this growth helps to identify the key areas to analyze energy efficiency potential, appropriate policies to reduce energy use, as well as to understand future energy in the building sector. This paper provides a detailed, bottom-up analysis of residential building energy consumption in China using data from a wide variety of sources and a modelling effort that relies on a very detailed characterization of China's energy demand. It assesses the current energy situation with consideration of end use, intensity, and efficiency etc, and forecast the future outlook for the critical period extending to 2020, based on assumptions of likely patterns of economic activity, availability of energy services, technology improvement and energy intensities. From this analysis, we can conclude that Chinese residential energy consumption will more than double by 2020, from 6.6 EJ in 2000 to 15.9 EJ in 2020. This increase will be driven primarily by urbanization, in combination with increases in living standards. In the urban and higher income Chinese households of the future, most major appliances will be common, and heated and cooled areas will grow on average. These shifts will offset the relatively modest efficiency gains expected according to current government plans and policies already in place. Therefore, levelling and reduction of growth in residential energy demand in China will require a new set of more aggressive efficiency policies.

Zhou, Nan; McNeil, Michael A.; Levine, Mark

2009-06-01T23:59:59.000Z

271

Energy for 500 Million Homes: Drivers and Outlook for Residential Energy Consumption in China  

SciTech Connect

China's rapid economic expansion has propelled it to the rank of the largest energy consuming nation in the world, with energy demand growth continuing at a pace commensurate with its economic growth. The urban population is expected to grow by 20 million every year, accompanied by construction of 2 billion square meters of buildings every year through 2020. Thus residential energy use is very likely to continue its very rapid growth. Understanding the underlying drivers of this growth helps to identify the key areas to analyze energy efficiency potential, appropriate policies to reduce energy use, as well as to understand future energy in the building sector. This paper provides a detailed, bottom-up analysis of residential building energy consumption in China using data from a wide variety of sources and a modelling effort that relies on a very detailed characterization of China's energy demand. It assesses the current energy situation with consideration of end use, intensity, and efficiency etc, and forecast the future outlook for the critical period extending to 2020, based on assumptions of likely patterns of economic activity, availability of energy services, technology improvement and energy intensities. From this analysis, we can conclude that Chinese residential energy consumption will more than double by 2020, from 6.6 EJ in 2000 to 15.9 EJ in 2020. This increase will be driven primarily by urbanization, in combination with increases in living standards. In the urban and higher income Chinese households of the future, most major appliances will be common, and heated and cooled areas will grow on average. These shifts will offset the relatively modest efficiency gains expected according to current government plans and policies already in place. Therefore, levelling and reduction of growth in residential energy demand in China will require a new set of more aggressive efficiency policies.

Zhou, Nan; McNeil, Michael A.; Levine, Mark

2009-06-01T23:59:59.000Z

272

Sustainable Energy Sources and Nanomaterials (+$5 million ...  

Science Conference Proceedings (OSTI)

Sustainable Energy Sources and Nanomaterials (+$5 million for Advanced Solar Technologies; +$4 million for Nanomaterial Environmental Health ...

2010-10-05T23:59:59.000Z

273

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

Science Conference Proceedings (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

274

Patterns of rural household energy use: a study in the White Nile province - the Sudan  

Science Conference Proceedings (OSTI)

The study investigates rural household domestic energy consumption patterns in a semiarid area of the Sudan. It describes the socioeconomic and evironmental context of energy use, provides an estimation of local woody biomass production and evaluates ecological impacts of increased energy demand on the local resource base. It is based on findings derived from field surveys, a systematic questionnaire and participant observations. Findings indicate that households procure traditional fuels by self-collection and purchases. Household members spent on average 20% of their working time gathering fuels. Generally per caput and total annual expenditure and consumption of domestic fuels are determined by household size, physical availability, storage, prices, income, conservation, substitution and competition among fuel resource uses. Households spend on average 16% of their annual income on traditional fuels. Aggregation of fuels on heat equivalent basis and calculation of their contribution shows that on average firewood provides 63%, charcoal 20.7%, dung 10.4%, crop residues 3.4% and kerosene/diesel 2.5% of the total demand for domestic purposes. Estimated total household woodfuel demand exceeds woody biomass available from the local forests. This demand is presently satisfied by a net depletion of the local forests and purchases from other areas. Degradation of the resource base is further exacerbated by development of irrigation along the White Nile River, increasing livestock numbers (overgrazing) and forest clearance for rainfed cultivation. The most promising relevant and appropriate strategies to alleviate rural household domestic energy problems include: conservation of the existing forest, augmentation through village woodlots and community forestry programmes and improvements in end-use (stoves) and conversion (wood to charcoal) technologies.

Abdu, A.S.E.

1985-01-01T23:59:59.000Z

275

Arizona - Natural Gas 2012 Million  

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

4 4 Arizona - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S3. Summary statistics for natural gas - Arizona, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 6 6 5 5 5 Production (million cubic feet) Gross Withdrawals From Gas Wells 523 711 183 168 117 From Oil Wells * * 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0

276

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

U.S. Energy Information Administration (EIA)

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

277

Earned Income Credit  

E-Print Network (OSTI)

This management advisory report presents the results of our review of the effectiveness of the Internal Revenue Service’s (IRS) administration of the Earned Income Credit (EIC). 1 The objective of this review was to evaluate the history of the EIC, difficulties the IRS has faced involving the EIC in the past, and the problems the IRS faces in the future. This is the first in a series of audits on the EIC. Currently, the Treasury Inspector General for Tax Administration has the following five audits in process involving the EIC: • The EIC Recertification Process. • Duplicate Dependent Claims. • Revenue Protection Strategy on Improving Taxpayer Compliance. • Educating and Assisting Taxpayers on the EIC.

Review Process; Pamela J. Gardiner

2000-01-01T23:59:59.000Z

278

Million Solar Roofs Flyer (Revision)  

SciTech Connect

The Million Solar Roofs Initiative, announced in June 1997, assists businesses and communities in installing solar energy systems on one million buildings across the United States by 2010. The US Department of Energy leads this trailblazing initiative by partnering with the building industry, local governments, state agencies, the solar industry, electric service providers, and non-governmental organizations to remove barriers and strengthen the demand for solar technologies.

Not Available

2000-11-01T23:59:59.000Z

279

DOE to Fund up to $454 Million for Retrofit Ramp-Ups in Energy Efficiency |  

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

to Fund up to $454 Million for Retrofit Ramp-Ups in Energy to Fund up to $454 Million for Retrofit Ramp-Ups in Energy Efficiency DOE to Fund up to $454 Million for Retrofit Ramp-Ups in Energy Efficiency September 14, 2009 - 12:00am Addthis WASHINGTON, DC - U.S. Secretary of Energy Steven Chu today announced a new $450 million program designed to catalyze a nationwide energy upgrade that experts estimate could save $100 million annually in utility bills for households and businesses. The Recovery Act's "Retrofit Ramp-Up" program will pioneer innovative models for rolling out energy efficiency to hundreds of thousands of homes and businesses in a variety of communities. Much like past roll-outs for cable TV or the Internet, DOE intends to create models that, when undertaken nationally, will save consumers billions of dollars on their utility bills and make the huge

280

WORKINGPAPER SERIES Number 150CAP AND DIVIDEND: HOW TO CURB GLOBAL WARMING WHILE PROTECTING THE INCOMES OF AMERICAN FAMILIES  

E-Print Network (OSTI)

This essay examines the distributional effects of a “cap-and-dividend ” policy for reducing carbon emission in the United States: a policy that auctions carbon permits and rebates the revenue to the public on an equal per capita basis. The aim of the policy is to reduce U.S. emissions of carbon dioxide, the main pollutant causing global warming, while at the same time protecting the real incomes of middle-income and lower-income American families. The number of permits is set by a statutory cap on carbon emissions that gradually diminishes over time. The sale of carbon permits will generate very large revenues, posing the critical question of who will get the money. The introduction of carbon permits – or, for that matter, any policy to curb emissions – will raise prices of fossil fuels, Key words: Global warming; fossil fuels; climate change; carbon permits; cap-and-dividend; cap-and-auction; cap-and-trade. and have a regressive impact on income distribution, since fuel expenditures represent a larger fraction of income for lower-income households than for upper-income households. The net effect of carbon emission-reduction policies depends on who gets the money that households pay in higher prices. We find that a cap-and-dividend policy would have a strongly progressive net effect. Moreover, the majority of U.S. households would be net winners in purely monetary terms: that is, their real incomes, after paying higher fuel prices and receiving their dividends, would rise. From the standpoints of both distributional equity and political feasibility, a cap-and-dividend policy is therefore an attractive way to curb carbon emissions. s s

James K. Boyce; Matthew Riddle; James K. Boyce; Matthew Riddle

2007-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "household income million" 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

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

NLE Websites -- All DOE Office Websites (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

282

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

283

Inconsistent pathways of household waste  

Science Conference Proceedings (OSTI)

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

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

2009-06-15T23:59:59.000Z

284

Buildings Energy Data Book: 2.9 Low-Income Housing  

Buildings Energy Data Book (EERE)

7 7 Residential Energy Burdens, by Weatherization Eligibility and Year (1) 1987 Mean Mean Mean Mean Mdn Mean Mean Mdn Mean Group Indvdl Group Indvdl Indvdl Group Indvdl Indvdl Group Total U.S. Households 4.0% 6.8% 3.2% 6.1% 3.5% 2.4% 7.2% 4.4% 3.2% Federally Eligible 13.0% 14.4% 10.1% 12.1% 7.9% 7.7% 13.8% 9.6% 10.0% Federally Ineligible 4.0% 3.5% N.A. 3.0% 2.6% 2.0% 3.6% 3.1% 2.6% Below 125% Poverty Line 13.0% N.A. N.A. N.A. N.A. N.A. N.A. N.A. N.A. Note(s): Source(s): 1990 FY 2000 (2) FY 2009 (3) 1) Energy burden can be defined broadly as the burden placed on household incomes by the cost of energy, or the ratio of energy expenditures to income for a household. DOE Weatherization primarily uses mean individual burden and mean group burden since these statistics provide data on how an "average" individual household fares against an "average" group of households (that is, how burdens are

285

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

SciTech Connect

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

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

1990-02-01T23:59:59.000Z

286

Low income energy assistance  

Science Conference Proceedings (OSTI)

States are limited in their ability to manage their heating assistance programs because they normally receive funds from the Low Income Home Energy Assistance Program after the heating season has begun and after they have decided on the benefits to be provided to eligible participants. In addition, the Department of Health and Human Services does not have enough flexibility to respond to unanticipated energy cost increases that can occur as a result of unusually severe weather or fuel price increases. HHS and the states could better manage the program if (1) it were forward funded so the states would know exactly how much federal assistance they would receive before they begin handling applications for heating assistance and (2) HHS had some discretion in how funds are allocated to the states to enable it to react to unanticipated energy-related circumstances.

Not Available

1990-10-01T23:59:59.000Z

287

Project #: UM08-Q3Saving among Low-Income Women: Motivation and Obstacles  

E-Print Network (OSTI)

How do low-income households think about saving? What motivations do they identify for saving, and what obstacles to meeting their goals? We use data from qualitative interviews with 51 households in Detroit to shed light on these questions. We find that they wish they could save- primarily for protection against the unexpected or to put children through college- but that most of them cannot. Friends and family surface as a major obstacle to saving, since those who have liquid assets are asked for help. When savings is feasible in this population, it occurs

Helen Levy; Kristin Seefeldt; Helen Levy; Kristin Seefeldt; Ann Arbor; Andrea Fischer Newman; Ann Arbor; Andrew C. Richner; Grosse Pointe; Park S. Martin; Helen Levy; Kristin Seefeldt

2008-01-01T23:59:59.000Z

288

Texas Natural Gas Repressuring (Million Cubic Feet)  

Gasoline and Diesel Fuel Update (EIA)

View History: Monthly Annual Download Data (XLS File) Texas Natural Gas Repressuring (Million Cubic Feet) Texas Natural Gas Repressuring (Million Cubic Feet) Year Jan Feb Mar Apr...

289

Texas Natural Gas Repressuring (Million Cubic Feet)  

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

View History: Monthly Annual Download Data (XLS File) Texas Natural Gas Repressuring (Million Cubic Feet) Texas Natural Gas Repressuring (Million Cubic Feet) Decade Year-0 Year-1...

290

Illinois Natural Gas Underground Storage Withdrawals (Million...  

Gasoline and Diesel Fuel Update (EIA)

Gas Underground Storage Withdrawals (Million Cubic Feet) Illinois Natural Gas Underground Storage Withdrawals (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov...

291

Pharmacy Research $1 Million Graduate  

E-Print Network (OSTI)

Pharmacy Research $1 Million Graduate Endowment Gift University of Florida College of Pharmacy Fall able to serve the faculty, staff, students and alumni of the University of Florida College of Pharmacy, Minnesota, Kentucky, Iowa and Michigan. During the early part of the 21st Century, the college also occupied

Roy, Subrata

292

Low-income energy assistance programs: a profile of need and policy options  

Science Conference Proceedings (OSTI)

This second report of the Fuel Oil Marketing Advisory Committee (FOMAC) of DOE is twofold: to update information on the energy needs of low-income persons and governmental response to such needs; and to emphasize the need for energy-conservation programs that may alleviate the enormous financial burden placed on low-income people by rising energy prices. FOMAC has continued to develop further and refine its initial energy-conservation recommendations. Mainly, the updated assessment document finds that the poor will expend at least 35% of their income directly on energy and will spend at least 21% of their income on household energy. Other economic impacts of rising energy costs on low-income groups are summarized. Appropriations and stipulations by Congress to aid the lo-income people are reviewed. After careful review of various program designs, FOMAC continues to support the income indexing/vendor line of credit approach. This design provides assistance to elgible households based on: energy needed, cost of fuel, and percentage of income. The cost of implementing the FOMAC design nationally would, according to estimates, range from $3.5 to $4.6 billion for the 1980-1981 winter heating season. A figure of $1.6 to $2.2 billion is being discussed in the Congress. Meeting the ongoing energy needs of the poor will require a coherent national policy which consists of aid in paying energy bills and aid in the poor's effort to conserve energy. The report seeks to promote such policies. Needs assessment, government response, FOMAC model, comments on the programs, projected cost of 1980-1981 Energy Assistance Program, need for conservation programs, and program financing are discussed.

Not Available

1980-07-01T23:59:59.000Z

293

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

NLE Websites -- All DOE Office Websites (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.

294

Household energy handbook: an interim guide and reference manual. World Bank technical paper. Manuel d'energie domestique: memento et guide interimaire  

Science Conference Proceedings (OSTI)

A standard framework for measuring and assessing technical information on the household energy sources in developing countries is needed. This handbook is intended as a first step toward creating such a framework. Chapter 1 discusses energy terms and principals underlying the energy units, definitions, and calculations presented in the following chapters. Chapter 2 describes household consumption patterns and their relationship to income, location and household use variables. Chapter 3 evaluates energy end-uses and the technologies that provide cooking, lighting, refrigeration, and space heating services. Chapter 4 examines household energy resources and supplies, focusing on traditional biomass fuels. Finally, Chapter 5 demonstrates simple assessment methods and presents case studies to illustrate how household energy data can be used in different types of assessments.

Leach, G.; Gowen, M.

1989-01-01T23:59:59.000Z

295

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

U.S. Energy Information Administration (EIA)

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

296

Alston S. Householder Fellowship | Careers | ORNL  

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

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

297

Household Vehicles Energy Consumption 1994 - PDF Tables  

U.S. Energy Information Administration (EIA)

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

298

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

U.S. Energy Information Administration (EIA)

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

299

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

U.S. Energy Information Administration (EIA)

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

300

Residential Energy Usage by Origin of Householder  

U.S. Energy Information Administration (EIA)

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

Note: This page contains sample records for the topic "household income million" 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

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

U.S. Energy Information Administration (EIA)

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

302

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

U.S. Energy Information Administration (EIA)

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

303

Secretary Chu Announces Closing of $117 Million Loan Guarantee for Kahuku  

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

17 Million Loan Guarantee for 17 Million Loan Guarantee for Kahuku Wind Power Project Secretary Chu Announces Closing of $117 Million Loan Guarantee for Kahuku Wind Power Project July 27, 2010 - 12:00am Addthis Washington D.C. --- Energy Secretary Steven Chu today announced that the Department of Energy has finalized a $117 million loan guarantee for Kahuku Wind Power, LLC, the owner and operator of the Kahuku Wind Power project. The project includes the development of an innovative 30 megawatt (MW) wind power plant that will supply electricity to approximately 7,700 households per year. According to company estimates, the project, located in Kahuku, Hawaii, will create over 200 jobs on the island of Oahu. "This project is another example of America's leadership in the global clean energy economy," said Secretary Chu. "Through the Recovery Act, we

304

DOE Awards $235 Million to Southern Company to Build Clean Coal Plant |  

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

235 Million to Southern Company to Build Clean Coal 235 Million to Southern Company to Build Clean Coal Plant DOE Awards $235 Million to Southern Company to Build Clean Coal Plant February 22, 2006 - 12:13pm Addthis WASHINGTON , DC - The U.S. Department of Energy awarded $235 million to Southern Company, in partnership with the Orlando Utilities Commission and Kellogg, Brown and Root, to develop one of the cleanest coal-fired power plants in the world. Representatives of the Energy Department and Southern Company signed a cooperative agreement that launches the design, construction, and demonstration of an integrated gasification combined cycle (IGCC) power generation system at the Orlando Utilities Commission's Stanton Energy Center. The system will produce 285 megawatts of electricity for the Orlando area - which will power approximately 285,000 households - and is

305

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

306

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

307

Characterization of household waste in Greenland  

Science Conference Proceedings (OSTI)

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

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

2011-07-15T23:59:59.000Z

308

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

Science Conference Proceedings (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

309

Income Statement -- A Financial Management Tool  

E-Print Network (OSTI)

An income statement measures the success of a business in terms of net income or loss for a period of time. An income statement of a farm business includes items in seven major categories. This publication describes each of these categories and gives a sample income statement.

Klinefelter, Danny A.

2008-09-16T23:59:59.000Z

310

Probit Model Estimation Revisited: Trinomial Models of Household Car Ownership  

E-Print Network (OSTI)

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

Bunch, David S.; Kitamura, Ryuichi

1991-01-01T23:59:59.000Z

311

Modeling patterns of hot water use in households  

E-Print Network (OSTI)

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

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

1996-01-01T23:59:59.000Z

312

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

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

5,11.2,6.7,13.2,5.8,14.5 "Housing Unit Characteristics Affecting Usage" "Adequacy of Insulation" "Well Insulated",42.8,9,11,8.2,5.1,9.5,4.8,13.1 "Adequately Insulated",46.3,10.4,11...

313

ASSESSMENT OF HOUSEHOLD CARBON FOOTPRINT REDUCTION POTENTIALS  

SciTech Connect

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

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

2009-04-15T23:59:59.000Z

314

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

SciTech Connect

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

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

1988-11-01T23:59:59.000Z

315

" Million U.S. Housing Units"  

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

3 Lighting Usage Indicators by Type of Housing Unit, 2005" " Million U.S. Housing Units" ,,"Type of Housing Unit" ,"Housing Units (millions)","Single-Family Units",,"Apartments in...

316

Ohio Natural Gas Repressuring (Million Cubic Feet)  

Gasoline and Diesel Fuel Update (EIA)

Repressuring (Million Cubic Feet) Ohio Natural Gas Repressuring (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0 0 0...

317

California Natural Gas International Deliveries (Million Cubic...  

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

Deliveries (Million Cubic Feet) California Natural Gas International Deliveries (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9...

318

California Natural Gas International Receipts (Million Cubic...  

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

Receipts (Million Cubic Feet) California Natural Gas International Receipts (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's...

319

Massachusetts Natural Gas Underground Storage Withdrawals (Million...  

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

Withdrawals (Million Cubic Feet) Massachusetts Natural Gas Underground Storage Withdrawals (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7...

320

Georgia Natural Gas Underground Storage Withdrawals (Million...  

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

Withdrawals (Million Cubic Feet) Georgia Natural Gas Underground Storage Withdrawals (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8...

Note: This page contains sample records for the topic "household income million" 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

Connecticut Natural Gas Underground Storage Withdrawals (Million...  

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

Withdrawals (Million Cubic Feet) Connecticut Natural Gas Underground Storage Withdrawals (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8...

322

Delaware Natural Gas Underground Storage Withdrawals (Million...  

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

Withdrawals (Million Cubic Feet) Delaware Natural Gas Underground Storage Withdrawals (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8...

323

Wisconsin Natural Gas Underground Storage Withdrawals (Million...  

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

Withdrawals (Million Cubic Feet) Wisconsin Natural Gas Underground Storage Withdrawals (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8...

324

Million U.S. Housing Units Total...............................  

Gasoline and Diesel Fuel Update (EIA)

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

325

Become One In A Million: Partnership Updates -- Million Solar Roofs and Interstate Renewable Energy Council  

DOE Green Energy (OSTI)

The Million Solar Roofs Partnership Update is an annual report from all the Partnership and Partners who participate in the Million Solar Roofs Initiative.

Not Available

2004-06-01T23:59:59.000Z

326

Material World: Forecasting Household Appliance Ownership in a Growing Global Economy  

SciTech Connect

Over the past years the Lawrence Berkeley National Laboratory (LBNL) has developed an econometric model that predicts appliance ownership at the household level based on macroeconomic variables such as household income (corrected for purchase power parity), electrification, urbanization and climate variables. Hundreds of data points from around the world were collected in order to understand trends in acquisition of new appliances by households, especially in developing countries. The appliances covered by this model are refrigerators, lighting fixtures, air conditioners, washing machines and televisions. The approach followed allows the modeler to construct a bottom-up analysis based at the end use and the household level. It captures the appliance uptake and the saturation effect which will affect the energy demand growth in the residential sector. With this approach, the modeler can also account for stock changes in technology and efficiency as a function of time. This serves two important functions with regard to evaluation of the impact of energy efficiency policies. First, it provides insight into which end uses will be responsible for the largest share of demand growth, and therefore should be policy priorities. Second, it provides a characterization of the rate at which policies affecting new equipment penetrate the appliance stock. Over the past 3 years, this method has been used to support the development of energy demand forecasts at the country, region or global level.

Letschert, Virginie; McNeil, Michael A.

2009-03-23T23:59:59.000Z

327

A Multi Agent-Based Framework for Simulating Household PHEV Distribution and Electric Distribution Network Impact  

DOE Green Energy (OSTI)

The variation of household attributes such as income, travel distance, age, household member, and education for different residential areas may generate different market penetration rates for plug-in hybrid electric vehicle (PHEV). Residential areas with higher PHEV ownership could increase peak electric demand locally and require utilities to upgrade the electric distribution infrastructure even though the capacity of the regional power grid is under-utilized. Estimating the future PHEV ownership distribution at the residential household level can help us understand the impact of PHEV fleet on power line congestion, transformer overload and other unforeseen problems at the local residential distribution network level. It can also help utilities manage the timing of recharging demand to maximize load factors and utilization of existing distribution resources. This paper presents a multi agent-based simulation framework for 1) modeling spatial distribution of PHEV ownership at local residential household level, 2) discovering PHEV hot zones where PHEV ownership may quickly increase in the near future, and 3) estimating the impacts of the increasing PHEV ownership on the local electric distribution network with different charging strategies. In this paper, we use Knox County, TN as a case study to show the simulation results of the agent-based model (ABM) framework. However, the framework can be easily applied to other local areas in the US.

Cui, Xiaohui [ORNL; Liu, Cheng [ORNL; Kim, Hoe Kyoung [ORNL; Kao, Shih-Chieh [ORNL; Tuttle, Mark A [ORNL; Bhaduri, Budhendra L [ORNL

2011-01-01T23:59:59.000Z

328

U.S. Household Electricity Report  

Reports and Publications (EIA)

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

Barbara Fichman

2005-07-14T23:59:59.000Z

329

Do Disaster Expectations Explain Household Portfolios?  

E-Print Network (OSTI)

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

Alan, Sule

330

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

331

China's Income Distribution, 1985-2001  

E-Print Network (OSTI)

China’s Income Distribution, 1985-2001 Ximing Wu* andBureau of Statistics of China, for explaining many featuresa new method to estimate China’s income distributions using

Wu, Ximing; Perloff, Jeffrey M.

2005-01-01T23:59:59.000Z

332

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

SciTech Connect

China is already the second's largest energy consumer in the world after the United States, and its demand for energy is expected to continue to grow rapidly in the foreseeable future, due to its fast economic growth and its low level of energy use per capita. From 2001 to 2005, the growth rate of energy consumption in China has exceeded the growth rate of its economy (NBS, 2006), raising serious concerns about the consequences of such energy use on local environment and global climate. It is widely expected that China is likely to overtake the US in energy consumption and greenhouse gas (GHG) emissions during the first half of the 21st century. Therefore, there is considerable interest in the international community in searching for options that may help China slow down its growth in energy consumption and GHG emissions through improving energy efficiency and adopting more environmentally friendly fuel supplies such as renewable energy. This study examines the energy saving potential of three major residential energy end uses: household refrigeration, air-conditioning, and water heating. China is already the largest consumer market in the world for household appliances, and increasingly the global production base for consumer appliances. Sales of household refrigerators, room air-conditioners, and water heaters are growing rapidly due to rising incomes and booming housing market. At the same time, the energy use of Chinese appliances is relatively inefficient compared to similar products in the developed economies. Therefore, the potential for energy savings through improving appliance efficiency is substantial. This study focuses particularly on the impact of more stringent energy efficiency standards for household appliances, given that such policies are found to be very effective in improving the efficiency of household appliances, and are well established both in China and around world (CLASP, 2006).

Lin, Jiang

2006-07-10T23:59:59.000Z

333

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

Science Conference Proceedings (OSTI)

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

Guerin, D.A.

1988-01-01T23:59:59.000Z

334

1 million gallons of grout.doc  

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

Historic Milestone Achieved as 1 Million Gallons of Grout Historic Milestone Achieved as 1 Million Gallons of Grout Is Poured into SRS Waste Tanks 18 and 19 AIKEN, S.C. (May 9, 2012) - Operational closure of the next two radioactive waste tanks at the Savannah River Site (SRS) has achieved a historic milestone with the placement of over 1 million gallons of grout inside the massive underground tanks. Filling Tanks 18 and 19 began on April 2, 2012. As of today, over 1 million gallons of

335

Million U.S. Housing Units Total...............................  

Gasoline and Diesel Fuel Update (EIA)

Units (millions) Single-Family Units Apartments in Buildings With-- Home Electronics Usage Indicators Detached Energy Information Administration: 2005 Residential Energy...

336

Energy Department Announces $66 Million for Transformational...  

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

- 34 Million REMOTE will develop transformational biological technologies to convert gas to liquids (GTL) for transportation fuels. Current synthetic gas-to-liquids conversion...

337

Microsoft Word - 1 Million Electric Vehicle Report Final | Department...  

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

1 Million Electric Vehicle Report Final Microsoft Word - 1 Million Electric Vehicle Report Final Microsoft Word - 1 Million Electric Vehicle Report Final More Documents &...

338

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

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

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

339

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

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

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

340

S:\VM3\RX97\TBL_LIST.WPD [PFP#201331587]  

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

Million U.S. Households; 12 pages, 47 kb) Million U.S. Households; 12 pages, 47 kb) Contents Pages HC7-1a. Home Office Equipment by Climate Zone, Million U.S. Households, 1997 1 HC7-2a. Home Office Equipment by Year of Construction, Million U.S. Households, 1997 1 HC7-3a. Home Office Equipment by Household Income, Million U.S. Households, 1997 1 HC7-4a. Home Office Equipment by Type of Housing Unit, Million U.S. Households, 1997 1 HC7-5a. Home Office Equipment by Type of Owner-Occupied Housing Unit, Million U.S. Households, 1997 1 HC7-6a. Home Office Equipment by Type of Rented Housing Unit, Million U.S. Households, 1997 1 HC7-7a. Home Office Equipment by Four Most Populated States, Million U.S. Households, 1997 1

Note: This page contains sample records for the topic "household income million" 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

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

342

Estimating the Impacts of Low-Income Weatherization Assistance...  

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

to estimate the impact of WAP. These approaches compare the consumption of households participating in WAP to the consumption of non-participating households. An...

343

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

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

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

344

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

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

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

345

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

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

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

346

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

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

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

347

Essays on household decision making in developing countries  

E-Print Network (OSTI)

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

Berry, James W. (James Wesley)

2009-01-01T23:59:59.000Z

348

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

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

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

349

ANALYSIS OF CEE HOUSEHOLD SURVEY NATIONAL AWARENESS OF ENERGY STAR  

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

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

350

Million Cu. Feet Percent of National Total  

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

8 8 North Carolina - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S35. Summary statistics for natural gas - North Carolina, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

351

Million Cu. Feet Percent of National Total  

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

2 2 New Jersey - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S32. Summary statistics for natural gas - New Jersey, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

352

Million Cu. Feet Percent of National Total  

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

0 0 Georgia - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S11. Summary statistics for natural gas - Georgia, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0

353

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

0 0 Connecticut - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S7. Summary statistics for natural gas - Connecticut, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0

354

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

0 0 Maryland - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S22. Summary statistics for natural gas - Maryland, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 7 7 7 7 8 Production (million cubic feet) Gross Withdrawals From Gas Wells 35 28 43 43 34 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 35

355

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

6 6 Florida - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S10. Summary statistics for natural gas - Florida, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 2,000 2,742 290 13,938 17,129 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0

356

Million Cu. Feet Percent of National Total  

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

0 0 New Hampshire - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S31. Summary statistics for natural gas - New Hampshire, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

357

Million Cu. Feet Percent of National Total  

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

2 2 Maryland - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S22. Summary statistics for natural gas - Maryland, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 7 7 7 8 9 Production (million cubic feet) Gross Withdrawals From Gas Wells 28 43 43 34 44 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 28

358

Million Cu. Feet Percent of National Total  

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

2 2 Missouri - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S27. Summary statistics for natural gas - Missouri, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 0 0 0 53 100 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

359

Million Cu. Feet Percent of National Total  

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

4 4 Delaware - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S8. Summary statistics for natural gas - Delaware, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0

360

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

2 2 Massachusetts - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S23. Summary statistics for natural gas - Massachusetts, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

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


361

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

0 0 South Carolina - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S42. Summary statistics for natural gas - South Carolina, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

362

Million Cu. Feet Percent of National Total  

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

6 6 Tennessee - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S44. Summary statistics for natural gas - Tennessee, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 285 310 230 210 212 Production (million cubic feet) Gross Withdrawals From Gas Wells 4,700 5,478 5,144 4,851 5,825 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0

363

Million Cu. Feet Percent of National Total  

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

38 38 Nevada - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S30. Summary statistics for natural gas - Nevada, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 4 4 4 3 4 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 4 4 4 3 4

364

Million Cu. Feet Percent of National Total  

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

2 2 Connecticut - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S7. Summary statistics for natural gas - Connecticut, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0

365

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

4 4 Oregon - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S39. Summary statistics for natural gas - Oregon, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 18 21 24 26 24 Production (million cubic feet) Gross Withdrawals From Gas Wells 409 778 821 1,407 1,344 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0

366

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

4 4 Idaho - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S14. Summary statistics for natural gas - Idaho, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

367

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

4 4 Washington - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S49. Summary statistics for natural gas - Washington, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

368

Million Cu. Feet Percent of National Total  

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

0 0 Maine - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S21. Summary statistics for natural gas - Maine, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0 0

369

Million Cu. Feet Percent of National Total  

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

8 8 Minnesota - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S25. Summary statistics for natural gas - Minnesota, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0 0 0

370

Million Cu. Feet Percent of National Total  

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

2 2 South Carolina - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S42. Summary statistics for natural gas - South Carolina, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

371

Million Cu. Feet Percent of National Total  

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

6 6 District of Columbia - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S9. Summary statistics for natural gas - District of Columbia, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0

372

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

6 6 North Carolina - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S35. Summary statistics for natural gas - North Carolina, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

373

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

0 0 Iowa - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S17. Summary statistics for natural gas - Iowa, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0 0

374

Million Cu. Feet Percent of National Total  

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

4 4 Massachusetts - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S23. Summary statistics for natural gas - Massachusetts, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

375

Million Cu. Feet Percent of National Total  

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

6 6 Oregon - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S39. Summary statistics for natural gas - Oregon, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 21 24 26 24 27 Production (million cubic feet) Gross Withdrawals From Gas Wells 778 821 1,407 1,344 770 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0

376

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

8 8 Georgia - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S11. Summary statistics for natural gas - Georgia, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0

377

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

6 6 Minnesota - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S25. Summary statistics for natural gas - Minnesota, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0 0 0

378

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

2 2 Delaware - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S8. Summary statistics for natural gas - Delaware, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0

379

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

4 4 District of Columbia - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S9. Summary statistics for natural gas - District of Columbia, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0

380

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

0 0 New Jersey - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S32. Summary statistics for natural gas - New Jersey, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

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


381

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

4 4 Tennessee - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S44. Summary statistics for natural gas - Tennessee, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 305 285 310 230 210 Production (million cubic feet) Gross Withdrawals From Gas Wells NA 4,700 5,478 5,144 4,851 From Oil Wells 3,942 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0

382

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

4 4 Nebraska - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S29. Summary statistics for natural gas - Nebraska, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 186 322 285 276 322 Production (million cubic feet) Gross Withdrawals From Gas Wells 1,331 2,862 2,734 2,092 1,854 From Oil Wells 228 221 182 163 126 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0

383

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

0 0 Vermont - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S47. Summary statistics for natural gas - Vermont, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0 0 0

384

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

8 8 Wisconsin - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S51. Summary statistics for natural gas - Wisconsin, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0 0 0

385

Million Cu. Feet Percent of National Total  

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

0 0 Rhode Island - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S41. Summary statistics for natural gas - Rhode Island, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

386

Million Cu. Feet Percent of National Total  

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

0 0 Indiana - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S16. Summary statistics for natural gas - Indiana, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 525 563 620 914 819 Production (million cubic feet) Gross Withdrawals From Gas Wells 4,701 4,927 6,802 9,075 8,814 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0

387

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

Science Conference Proceedings (OSTI)

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

Not Available

1993-03-02T23:59:59.000Z

388

A Million Meter Milestone | Department of Energy  

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

A Million Meter Milestone A Million Meter Milestone A Million Meter Milestone March 4, 2011 - 2:36pm Addthis To see what installing the 1 millionth meter looked like, check out this video. Don Macdonald Program Manager, Smart Grid Investment Grant Program What does this mean for me? Smart meters allow consumers to take personal control and ownership of her energy usage in a way not possible before. As program manager for the Department of Energy's Recovery Act funded Smart Grid Investment Grant (SGIG) program, I've had the pleasure of seeing SGIG reach several important milestones recently. Among the most notable has been the recent achievement of three million smart meters installed by SGIG recipients as of December 31, 2010. On February 23, 2011, along with my colleague Chris Irwin, I was in Houston, Texas where SGIG

389

Million Solar Roofs: Partners Make Markets  

DOE Green Energy (OSTI)

Million Solar Roofs (MSR) Partners Make Markets Executive Summary is a summary of the MSR Annual Partnership Update, a report from all the partners and partnerships who participate in the MSR Initiative.

Not Available

2004-06-01T23:59:59.000Z

390

President Obama Announces $400 Million Conditional Commitment...  

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

400 million to Abound Solar Manufacturing, LLC to manufacture state-of-the-art thin-film solar panels. This will be the first time this new manufacturing technology for...

391

California Natural Gas Residential Consumption (Million Cubic ...  

U.S. Energy Information Administration (EIA)

California Natural Gas Residential Consumption (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9; 1960's: 522,122 ...

392

Million U.S. Housing Units Total...............................  

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

Attached 2 to 4 Units Table HC2.12 Home Electronics Usage Indicators by Type of Housing Unit, 2005 5 or More Units Mobile Homes Type of Housing Unit Housing Units (millions)...

393

storage of several million tonnes of carbon  

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

of several million tonnes of carbon dioxide (CO of several million tonnes of carbon dioxide (CO 2 ). The three recipients of the award are: the In Salah CO 2 Storage Project in Algeria; the Sleipner CO 2 Project in the North Sea; and the Weyburn-Midale CO 2 Project in Canada. In addition to providing scientific research opportunities, the projects are also being recognized as exemplary global models for their willingness to share their experiences in

394

Upgrade energy building standards and develop rating system for existing low-income housing  

SciTech Connect

The city of Memphis Division of Housing and Community Development (HCD) receives grant funding each year from the U.S. Department of Housing and Urban Development (HUD) to provide local housing assistance to low-income residents. Through the years, HCD has found that many of the program recipients have had difficulty in managing their households, particularly in meeting monthly financial obligations. One of the major operating costs to low-income households is the utility bill. Furthermore, HCD`s experience has revealed that many low-income residents are simply unaware of ways to reduce their utility bill. Most of the HCD funds are distributed to low-income persons as grants or no/low interest loans for the construction or rehabilitation of single-family dwellings. With these funds, HCD builds 80 to 100 new houses and renovates about 500 homes each year. Houses constructed or renovated by HCD must meet HUD`s minimum energy efficiency standards. While these minimum standards are more than adequate to meet local building codes, they are not as aggressive as the energy efficiency standards being promoted by the national utility organizations and the home building industry. Memphis Light, Gas and Water (MLGW), a city-owned utility, has developed an award-winning program named Comfort Plus which promotes energy efficiency{open_quote} in new residential construction. Under Comfort Plus, MLGW models house plans on computer for a fee and recommends cost-effective alterations which improve the energy efficiency of the house. If the builder agrees to include these recommendations, MLGW will certify the house and guarantee a maximum annual heating/cooling bill for two years. While the Comfort Plus program has received recognition in the new construction market, it does not address the existing housing stock.

Muller, D.; Norville, C. [Memphis and Shelby County Div. of Planning and Development, TN (United States)

1993-07-01T23:59:59.000Z

395

Household carbon dioxide production in relation to the greenhouse effect  

SciTech Connect

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

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

1994-03-01T23:59:59.000Z

396

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

E-Print Network (OSTI)

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

Lin, Jiang

2006-01-01T23:59:59.000Z

397

The Myth of Post-Reform Income Stagnation: Evidence from Brazil and Mexico  

E-Print Network (OSTI)

This Working Paper should not be reported as representing the views of the IMF. The views expressed in this Working Paper are those of the author(s) and do not necessarily represent those of the IMF or IMF policy. Working Papers describe research in progress by the author(s) and are published to elicit comments and to further debate. Economic policies are often judged by a handful of statistics, some of which may be biased during periods of change. We estimate the income growth implied by the evolution of food demand and durable good ownership in post-reform Brazil and Mexico, and find that changes in consumption patterns are inconsistent with official estimates of near stagnant incomes. That is attributed to biases in the price deflator. The estimated unmeasured income gains are higher for poorer households, implying marked reductions in “real ” inequality. These findings challenge the conventional wisdom that post-reform income growth was low and did not benefit the poor. 25BJEL Classification

Irineu De Carvalho Filho; Prepared Irineu; Carvalho Filho; Marcos Chamon

2008-01-01T23:59:59.000Z

398

S:\VM3\RX97\TBL_LIST.WPD  

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

Million U.S. Households; 13 pages, 52 kb) Million U.S. Households; 13 pages, 52 kb) Contents Pages HC2-1a. Household Characteristics by Climate Zone, Million U.S. Households, 1997 2 HC2-2a. Household Characteristics by Year of Construction, Million U.S. Households, 1997 1 HC2-3a. Household Characteristics by Household Income, Million U.S. Households, 1997 1 HC2-4a. Household Characteristics by Type of Housing Unit, Million U.S. Households, 1997 1 HC2-5a. Household Characteristics by Type of Owner-Occupied Housing Unit, Million U.S. Households, 1997 1 HC2-6a. Household Characteristics by Type of Rented Housing Unit, Million U.S. Households, 1997 1 HC2-7a. Household Characteristics by Four Most Populated States, Million U.S. Households, 1997 1 HC2-8a. Household Characteristics by Urban/Rural Location, Million U.S. Households, 1997 1

399

Agricultural Biomass Income Tax Credit (Personal) | Department of Energy  

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

Personal) Personal) Agricultural Biomass Income Tax Credit (Personal) < Back Eligibility Agricultural Savings Category Bioenergy Maximum Rebate Statewide annual limit of 5 million in total credits Program Info Start Date 1/1/2011 State New Mexico Program Type Personal Tax Credit Rebate Amount 5 per wet ton Provider New Mexico Energy, Minerals and Natural Resources Department [http://www.nmlegis.gov/Sessions/10%20Regular/final/HB0171.pdf House Bill 171] of 2010 created a tax credit for agricultural biomass from a dairy or feedlot transported to a facility that uses agricultural biomass to generate electricity or make biocrude or other liquid or gaseous fuel for commercial use. For the purposes of this tax credit, agricultural biomass means wet manure. The Energy, Minerals and Natural Resources Department may

400

Agricultural Biomass Income Tax Credit (Corporate) | Department of Energy  

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

Corporate) Corporate) Agricultural Biomass Income Tax Credit (Corporate) < Back Eligibility Agricultural Savings Category Bioenergy Maximum Rebate Statewide annual limit of 5 million in total credits Program Info Start Date 1/1/2011 State New Mexico Program Type Corporate Tax Credit Rebate Amount 5 per wet ton Provider New Mexico Energy, Minerals and Natural Resources Department [http://www.nmlegis.gov/Sessions/10%20Regular/final/HB0171.pdf House Bill 171] of 2010 created a tax credit for agricultural biomass from a dairy or feedlot transported to a facility that uses agricultural biomass to generate electricity or make biocrude or other liquid or gaseous fuel for commercial use. For the purposes of this tax credit, agricultural biomass means wet manure. The Energy, Minerals and Natural Resources Department may

Note: This page contains sample records for the topic "household income million" 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

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

E-Print Network (OSTI)

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

Turrentine, Thomas; Kurani, Kenneth

1995-01-01T23:59:59.000Z

402

Million Cu. Feet Percent of National Total  

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

6 6 Michigan - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S24. Summary statistics for natural gas - Michigan, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 9,995 10,600 10,100 11,100 10,900 Production (million cubic feet) Gross Withdrawals From Gas Wells 16,959 20,867 7,345 18,470 17,041 From Oil Wells 10,716 12,919 9,453 11,620 4,470 From Coalbed Wells 0

403

Million U.S. Housing Units Total............................................................................  

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

Attached Attached 2 to 4 Units Table HC2.12 Home Electronics Usage Indicators by Type of Housing Unit, 2005 5 or More Units Mobile Homes Type of Housing Unit Housing Units (millions) Single-Family Units Apartments in Buildings With-- Home Electronics Usage Indicators Detached Energy Information Administration: 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Million U.S. Housing Units Attached 2 to 4 Units Table HC2.12 Home Electronics Usage Indicators by Type of Housing Unit, 2005 5 or More Units Mobile Homes Type of Housing Unit Housing Units (millions) Single-Family Units Apartments in Buildings With-- Home Electronics Usage Indicators Detached Status of PC When Not in Use Left On..............................................................

404

Million Cu. Feet Percent of National Total  

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

8 8 West Virginia - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S50. Summary statistics for natural gas - West Virginia, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 49,364 50,602 52,498 56,813 50,700 Production (million cubic feet) Gross Withdrawals From Gas Wells 191,444 192,896 151,401 167,113 397,313 From Oil Wells 0 0 0 0 1,477 From Coalbed Wells 0

405

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

80 80 Wyoming - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S52. Summary statistics for natural gas - Wyoming, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 27,350 28,969 25,710 26,124 26,180 Production (million cubic feet) Gross Withdrawals From Gas Wells R 1,649,284 R 1,764,084 R 1,806,807 R 1,787,599 1,709,218 From Oil Wells 159,039 156,133 135,269 151,871 152,589

406

Million Cu. Feet Percent of National Total  

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

6 6 New York - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S34. Summary statistics for natural gas - New York, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 6,675 6,628 6,736 6,157 7,176 Production (million cubic feet) Gross Withdrawals From Gas Wells 49,607 44,273 35,163 30,495 25,985 From Oil Wells 714 576 650 629 439 From Coalbed Wells 0

407

Million Cu. Feet Percent of National Total  

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

2 2 Wyoming - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S52. Summary statistics for natural gas - Wyoming, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 28,969 25,710 26,124 26,180 22,171 Production (million cubic feet) Gross Withdrawals From Gas Wells 1,764,084 1,806,807 1,787,599 1,709,218 1,762,095 From Oil Wells 156,133 135,269 151,871 152,589 24,544

408

Million Cu. Feet Percent of National Total  

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

4 4 Virginia - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S48. Summary statistics for natural gas - Virginia, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 6,426 7,303 7,470 7,903 7,843 Production (million cubic feet) Gross Withdrawals From Gas Wells 7,419 16,046 23,086 20,375 21,802 From Oil Wells 0 0 0 0 9 From Coalbed Wells 101,567 106,408

409

Million Cu. Feet Percent of National Total  

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

6 6 Kentucky - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S19. Summary statistics for natural gas - Kentucky, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 16,290 17,152 17,670 14,632 17,936 Production (million cubic feet) Gross Withdrawals From Gas Wells 112,587 111,782 133,521 122,578 106,122 From Oil Wells 1,529 1,518 1,809 1,665 0 From Coalbed Wells 0

410

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

6 6 Pennsylvania - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S40. Summary statistics for natural gas - Pennsylvania, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 52,700 55,631 57,356 44,500 54,347 Production (million cubic feet) Gross Withdrawals From Gas Wells 182,277 R 188,538 R 184,795 R 173,450 242,305 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0

411

Million Cu. Feet Percent of National Total  

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

8 8 Illinois - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S15. Summary statistics for natural gas - Illinois, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 45 51 50 40 40 Production (million cubic feet) Gross Withdrawals From Gas Wells E 1,188 E 1,438 E 1,697 2,114 2,125 From Oil Wells E 5 E 5 E 5 7 0 From Coalbed Wells E 0 E 0 0 0 0 From Shale Gas Wells 0

412

Million Cu. Feet Percent of National Total  

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

50 50 North Dakota - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S36. Summary statistics for natural gas - North Dakota, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 194 196 188 239 211 Production (million cubic feet) Gross Withdrawals From Gas Wells 13,738 11,263 10,501 14,287 22,261 From Oil Wells 54,896 45,776 38,306 27,739 17,434 From Coalbed Wells 0

413

Million Cu. Feet Percent of National Total  

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

0 0 Mississippi - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S26. Summary statistics for natural gas - Mississippi, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 2,343 2,320 1,979 5,732 1,669 Production (million cubic feet) Gross Withdrawals From Gas Wells 331,673 337,168 387,026 429,829 404,457 From Oil Wells 7,542 8,934 8,714 8,159 43,421 From Coalbed Wells 7,250

414

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

2 2 Virginia - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S48. Summary statistics for natural gas - Virginia, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 5,735 6,426 7,303 7,470 7,903 Production (million cubic feet) Gross Withdrawals From Gas Wells R 6,681 R 7,419 R 16,046 R 23,086 20,375 From Oil Wells 0 0 0 0 0 From Coalbed Wells R 86,275 R 101,567

415

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

4 4 Michigan - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S24. Summary statistics for natural gas - Michigan, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 9,712 9,995 10,600 10,100 11,100 Production (million cubic feet) Gross Withdrawals From Gas Wells R 80,090 R 16,959 R 20,867 R 7,345 18,470 From Oil Wells 54,114 10,716 12,919 9,453 11,620 From Coalbed Wells 0

416

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

2 2 Montana - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S28. Summary statistics for natural gas - Montana, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 6,925 7,095 7,031 6,059 6,477 Production (million cubic feet) Gross Withdrawals From Gas Wells R 69,741 R 67,399 R 57,396 R 51,117 37,937 From Oil Wells 23,092 22,995 21,522 19,292 21,777 From Coalbed Wells

417

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

8 8 Mississippi - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S26. Summary statistics for natural gas - Mississippi, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 2,315 2,343 2,320 1,979 5,732 Production (million cubic feet) Gross Withdrawals From Gas Wells R 259,001 R 331,673 R 337,168 R 387,026 429,829 From Oil Wells 6,203 7,542 8,934 8,714 8,159 From Coalbed Wells

418

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

8 8 Indiana - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S16. Summary statistics for natural gas - Indiana, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 2,350 525 563 620 914 Production (million cubic feet) Gross Withdrawals From Gas Wells 3,606 4,701 4,927 6,802 9,075 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0

419

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

4 4 New York - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S34. Summary statistics for natural gas - New York, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 6,680 6,675 6,628 6,736 6,157 Production (million cubic feet) Gross Withdrawals From Gas Wells 54,232 49,607 44,273 35,163 30,495 From Oil Wells 710 714 576 650 629 From Coalbed Wells 0

420

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

6 6 Texas - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S45. Summary statistics for natural gas - Texas, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 76,436 87,556 93,507 95,014 100,966 Production (million cubic feet) Gross Withdrawals From Gas Wells R 4,992,042 R 5,285,458 R 4,860,377 R 4,441,188 3,794,952 From Oil Wells 704,092 745,587 774,821 849,560 1,073,301

Note: This page contains sample records for the topic "household income million" 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

Million Cu. Feet Percent of National Total  

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

2 2 Ohio - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S37. Summary statistics for natural gas - Ohio, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 34,416 34,963 34,931 46,717 35,104 Production (million cubic feet) Gross Withdrawals From Gas Wells 79,769 83,511 73,459 30,655 65,025 From Oil Wells 5,072 5,301 4,651 45,663 6,684 From Coalbed Wells 0

422

Million Cu. Feet Percent of National Total  

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

0 0 Colorado - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S6. Summary statistics for natural gas - Colorado, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 25,716 27,021 28,813 30,101 32,000 Production (million cubic feet) Gross Withdrawals From Gas Wells 496,374 459,509 526,077 563,750 1,036,572 From Oil Wells 199,725 327,619 338,565

423

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

2 2 South Dakota - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S43. Summary statistics for natural gas - South Dakota, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 71 71 89 102 100 Production (million cubic feet) Gross Withdrawals From Gas Wells 422 R 1,098 R 1,561 1,300 933 From Oil Wells 11,458 10,909 11,366 11,240 11,516 From Coalbed Wells 0 0

424

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

6 6 Illinois - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S15. Summary statistics for natural gas - Illinois, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 43 45 51 50 40 Production (million cubic feet) Gross Withdrawals From Gas Wells RE 1,389 RE 1,188 RE 1,438 RE 1,697 2,114 From Oil Wells E 5 E 5 E 5 E 5 7 From Coalbed Wells RE 0 RE

425

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

8 8 Colorado - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S6. Summary statistics for natural gas - Colorado, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 22,949 25,716 27,021 28,813 30,101 Production (million cubic feet) Gross Withdrawals From Gas Wells R 436,330 R 496,374 R 459,509 R 526,077 563,750 From Oil Wells 160,833 199,725 327,619

426

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

0 0 Alaska - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S2. Summary statistics for natural gas - Alaska, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 239 261 261 269 277 Production (million cubic feet) Gross Withdrawals From Gas Wells 165,624 150,483 137,639 127,417 112,268 From Oil Wells 3,313,666 3,265,401 3,174,747 3,069,683 3,050,654

427

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

0 0 Ohio - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S37. Summary statistics for natural gas - Ohio, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 34,416 34,416 34,963 34,931 46,717 Production (million cubic feet) Gross Withdrawals From Gas Wells R 82,812 R 79,769 R 83,511 R 73,459 30,655 From Oil Wells 5,268 5,072 5,301 4,651 45,663 From Coalbed Wells

428

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

4 4 Kentucky - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S19. Summary statistics for natural gas - Kentucky, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 16,563 16,290 17,152 17,670 14,632 Production (million cubic feet) Gross Withdrawals From Gas Wells 95,437 R 112,587 R 111,782 133,521 122,578 From Oil Wells 0 1,529 1,518 1,809 1,665 From Coalbed Wells 0

429

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

8 8 Utah - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S46. Summary statistics for natural gas - Utah, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 5,197 5,578 5,774 6,075 6,469 Production (million cubic feet) Gross Withdrawals From Gas Wells R 271,890 R 331,143 R 340,224 R 328,135 351,168 From Oil Wells 35,104 36,056 36,795 42,526 49,947 From Coalbed Wells

430

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

6 6 California - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S5. Summary statistics for natural gas - California, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 1,540 1,645 1,643 1,580 1,308 Production (million cubic feet) Gross Withdrawals From Gas Wells 93,249 91,460 82,288 73,017 63,902 From Oil Wells R 116,652 R 122,345 R 121,949 R 151,369 120,880

431

Million Cu. Feet Percent of National Total  

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

0 0 Utah - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S46. Summary statistics for natural gas - Utah, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 5,578 5,774 6,075 6,469 6,900 Production (million cubic feet) Gross Withdrawals From Gas Wells 331,143 340,224 328,135 351,168 402,899 From Oil Wells 36,056 36,795 42,526 49,947 31,440 From Coalbed Wells 74,399

432

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

6 6 Louisiana - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S20. Summary statistics for natural gas - Louisiana, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 18,145 19,213 18,860 19,137 21,235 Production (million cubic feet) Gross Withdrawals From Gas Wells R 1,261,539 R 1,288,559 R 1,100,007 R 911,967 883,712 From Oil Wells 106,303 61,663 58,037 63,638 68,505

433

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

2 2 Oklahoma - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S38. Summary statistics for natural gas - Oklahoma, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 38,364 41,921 43,600 44,000 41,238 Production (million cubic feet) Gross Withdrawals From Gas Wells R 1,583,356 R 1,452,148 R 1,413,759 R 1,140,111 1,281,794 From Oil Wells 35,186 153,227 92,467 210,492 104,703

434

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

2 2 New Mexico - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S33. Summary statistics for natural gas - New Mexico, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 42,644 44,241 44,784 44,748 32,302 Production (million cubic feet) Gross Withdrawals From Gas Wells R 657,593 R 732,483 R 682,334 R 616,134 556,024 From Oil Wells 227,352 211,496 223,493 238,580 252,326

435

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

6 6 West Virginia - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S50. Summary statistics for natural gas - West Virginia, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 48,215 49,364 50,602 52,498 56,813 Production (million cubic feet) Gross Withdrawals From Gas Wells R 189,968 R 191,444 R 192,896 R 151,401 167,113 From Oil Wells 701 0 0 0 0 From Coalbed Wells

436

Million Cu. Feet Percent of National Total  

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

8 8 Texas - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S45. Summary statistics for natural gas - Texas, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 87,556 93,507 95,014 100,966 96,617 Production (million cubic feet) Gross Withdrawals From Gas Wells 5,285,458 4,860,377 4,441,188 3,794,952 3,619,901 From Oil Wells 745,587 774,821 849,560 1,073,301 860,675

437

Million Cu. Feet Percent of National Total  

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

0 0 Alabama - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S1. Summary statistics for natural gas - Alabama, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 6,860 6,913 7,026 7,063 6,327 Production (million cubic feet) Gross Withdrawals From Gas Wells 158,964 142,509 131,448 116,872 114,407 From Oil Wells 6,368 5,758 6,195 5,975 10,978

438

Million Cu. Feet Percent of National Total  

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

8 8 Louisiana - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S20. Summary statistics for natural gas - Louisiana, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 19,213 18,860 19,137 21,235 19,792 Production (million cubic feet) Gross Withdrawals From Gas Wells 1,288,559 1,100,007 911,967 883,712 775,506 From Oil Wells 61,663 58,037 63,638 68,505 49,380

439

Million Cu. Feet Percent of National Total  

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

4 4 South Dakota - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S43. Summary statistics for natural gas - South Dakota, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 71 89 102 100 95 Production (million cubic feet) Gross Withdrawals From Gas Wells 1,098 1,561 1,300 933 14,396 From Oil Wells 10,909 11,366 11,240 11,516 689 From Coalbed Wells 0 0 0 0 0

440

Million Cu. Feet Percent of National Total  

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

4 4 Kansas - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S18. Summary statistics for natural gas - Kansas, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 17,862 21,243 22,145 25,758 24,697 Production (million cubic feet) Gross Withdrawals From Gas Wells 286,210 269,086 247,651 236,834 264,610 From Oil Wells 45,038 42,647 39,071 37,194 0 From Coalbed Wells 44,066

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


441

Million Cu. Feet Percent of National Total  

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

6 6 Arkansas - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S4. Summary statistics for natural gas - Arkansas, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 5,592 6,314 7,397 8,388 8,538 Production (million cubic feet) Gross Withdrawals From Gas Wells 173,975 164,316 152,108 132,230 121,684 From Oil Wells 7,378 5,743 5,691 9,291 3,000

442

Million Cu. Feet Percent of National Total  

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

8 8 California - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S5. Summary statistics for natural gas - California, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 1,645 1,643 1,580 1,308 1,423 Production (million cubic feet) Gross Withdrawals From Gas Wells 91,460 82,288 73,017 63,902 120,579 From Oil Wells 122,345 121,949 151,369 120,880 70,900

443

Million Cu. Feet Percent of National Total  

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

4 4 Oklahoma - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S38. Summary statistics for natural gas - Oklahoma, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 41,921 43,600 44,000 41,238 40,000 Production (million cubic feet) Gross Withdrawals From Gas Wells 1,452,148 1,413,759 1,140,111 1,281,794 1,394,859 From Oil Wells 153,227 92,467 210,492 104,703 53,720

444

Million Cu. Feet Percent of National Total  

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

2 2 Alaska - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S2. Summary statistics for natural gas - Alaska, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 261 261 269 277 185 Production (million cubic feet) Gross Withdrawals From Gas Wells 150,483 137,639 127,417 112,268 107,873 From Oil Wells 3,265,401 3,174,747 3,069,683 3,050,654 3,056,918

445

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

E-Print Network (OSTI)

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

Behjat Hojjati

2004-01-01T23:59:59.000Z

446

Short and Long-Term Perspectives: The Impact on Low-Income Consumers of Forecasted Energy Price Increases in 2008 and A Cap & Trade Carbon Policy in 2030  

SciTech Connect

The Department of Energy's Energy Information Administration (EIA) recently released its short-term forecast for residential energy prices for the winter of 2007-2008. The forecast indicates increases in costs for low-income consumers in the year ahead, particularly for those using fuel oil to heat their homes. In the following analysis, the Oak Ridge National Laboratory has integrated the EIA price projections with the Residential Energy Consumption Survey (RECS) for 2001 in order to project the impact of these price increases on the nation's low-income households by primary heating fuel type, nationally and by Census Region. The report provides an update of bill estimates provided in a previous study, "The Impact Of Forecasted Energy Price Increases On Low-Income Consumers" (Eisenberg, 2005). The statistics are intended for use by policymakers in the Department of Energy's Weatherization Assistance Program and elsewhere who are trying to gauge the nature and severity of the problems that will be faced by eligible low-income households during the 2008 fiscal year. In addition to providing expenditure forecasts for the year immediately ahead, this analysis uses a similar methodology to give policy makers some insight into one of the major policy debates that will impact low-income energy expenditures well into the middle decades of this century and beyond. There is now considerable discussion of employing a cap-and-trade mechanism to first limit and then reduce U.S. emissions of carbon into the atmosphere in order to combat the long-range threat of human-induced climate change. The Energy Information Administration has provided an analysis of projected energy prices in the years 2020 and 2030 for one such cap-and-trade carbon reduction proposal that, when integrated with the RECS 2001 database, provides estimates of how low-income households will be impacted over the long term by such a carbon reduction policy.

Eisenberg, Joel Fred [ORNL

2008-01-01T23:59:59.000Z

447

" Million Housing Units, Final"  

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

2 Appliances in U.S. Homes, by Owner/Renter Status, 2009" 2 Appliances in U.S. Homes, by Owner/Renter Status, 2009" " Million Housing Units, Final" ,,,,"Housing Unit Type" ,,,,"Single-Family Units",,,,"Apartments in Buildings With" ,"Total U.S.1 (millions)",,,"Detached",,"Attached",,"2 to 4 Units",,"5 or More Units",,"Mobile Homes" "Appliances",,"Own","Rent","Own","Rent","Own","Rent","Own","Rent","Own","Rent","Own","Rent" "Total Homes",113.6,76.5,37.1,63.2,8.6,3.9,2.8,1.5,7.6,2.3,16.8,5.5,1.4 "Cooking Appliances" "Stoves (Units With Both"

448

" Million Housing Units, Final"  

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

0 Structural and Geographic Characteristics of Homes in South Region, Divisions, and States, 2009" 0 Structural and Geographic Characteristics of Homes in South Region, Divisions, and States, 2009" " Million Housing Units, Final" ,,"South Census Region" ,,,"South Atlantic Census Division",,,,,,"East South Central Census Division",,,"West South Central Census Division" ,,,,,,,,,"Total East South Central",,,"Total West South Central" ,"Total U.S.1 (millions)",,"Total South Atlantic" "Structural and Geographic Characteristics",,"Total South",,,,,"DC, DE, MD, WV",,,,"AL, KY, MS",,,"AR, LA, OK" ,,,,"VA","GA","FL",,"NC, SC",,"TN",,,"TX"

449

" Million Housing Units, Final"  

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

2 Televisions in U.S. Homes, by Owner/Renter Status, 2009" 2 Televisions in U.S. Homes, by Owner/Renter Status, 2009" " Million Housing Units, Final" ,,,,"Housing Unit Type" ,,,,"Single-Family Units",,,,"Apartments in Buildings With" ,,,,"Detached",,"Attached",,"2 to 4 Units",,"5 or More Units",,"Mobile Homes" ,"Total U.S.1 (millions)" ,,"Own","Rent","Own","Rent","Own","Rent","Own","Rent","Own","Rent","Own","Rent" "Televisions" "Total Homes",113.6,76.5,37.1,63.2,8.6,3.9,2.8,1.5,7.6,2.3,16.8,5.5,1.4 "Televisions" "Number of Televisions"

450

" Million Housing Units, Final"  

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

2 Air Conditioning in U.S. Homes, by Owner/Renter Status, 2009" 2 Air Conditioning in U.S. Homes, by Owner/Renter Status, 2009" " Million Housing Units, Final" ,,,,"Housing Unit Type" ,,,,"Single-Family Units",,,,"Apartments in Buildings With" ,,,,"Detached",,"Attached",,"2 to 4 Units",,"5 or More Units",,"Mobile Homes" ,"Total U.S.1 (millions)" "Air Conditioning",,"Own","Rent","Own","Rent","Own","Rent","Own","Rent","Own","Rent","Own","Rent" "Total Homes",113.6,76.5,37.1,63.2,8.6,3.9,2.8,1.5,7.6,2.3,16.8,5.5,1.4 "Air Conditioning Equipment"

451

" Million Housing Units, Final"  

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

0 Computers and Other Electronics in Homes in South Region, Divisions, and States, 2009" 0 Computers and Other Electronics in Homes in South Region, Divisions, and States, 2009" " Million Housing Units, Final" ,,"South Census Region" ,,,"South Atlantic Census Division",,,,,,"East South Central Census Division",,,"West South Central Census Division" ,,,,,,,,,"Total East South Central",,,"Total West South Central" ,"Total U.S.1 (millions)",,"Total South Atlantic" ,,"Total South",,,,,"DC, DE, MD, WV",,,,"AL, KY, MS",,,"AR, LA, OK" "Computers and Other Electronics",,,,"VA","GA","FL",,"NC, SC",,"TN",,,"TX"

452

" Million Housing Units, Final"  

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

2 Space Heating in U.S. Homes, by Owner/Renter Status, 2009" 2 Space Heating in U.S. Homes, by Owner/Renter Status, 2009" " Million Housing Units, Final" ,,,,"Housing Unit Type" ,,,,"Single-Family Units",,,,"Apartments in Buildings With" ,,,,"Detached",,"Attached",,"2 to 4 Units",,"5 or More Units",,"Mobile Homes" ,"Total U.S.1 (millions)" ,,"Own","Rent","Own","Rent","Own","Rent","Own","Rent","Own","Rent","Own","Rent" "Space Heating" "Total Homes",113.6,76.5,37.1,63.2,8.6,3.9,2.8,1.5,7.6,2.3,16.8,5.5,1.4 "Space Heating Equipment"

453

" Million Housing Units, Final"  

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

1 Televisions in Homes in West Region, Divisions, and States, 2009" 1 Televisions in Homes in West Region, Divisions, and States, 2009" " Million Housing Units, Final" ,,"West Census Region" ,,,"Mountain Census Division",,,,,,,"Pacific Census Division" ,,,,"Mountain North Sub-Division",,,"Mountain South Sub-Division" ,"Total U.S.1 (millions)",,,"Total Mountain North",,,"Total Mountain South" ,,"Total West","Total Mountain",,,"ID, MT, UT, WY",,,,"Total Pacific",,"AK, HI, OR, WA" "Televisions",,,,,"CO",,,"AZ","NM, NV",,"CA" "Total Homes",113.6,24.8,7.9,3.9,1.9,2,4,2.3,1.7,16.9,12.2,4.7

454

" Million Housing Units, Final"  

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

9 Appliances in Homes in Midwest Region, Divisions, and States, 2009" 9 Appliances in Homes in Midwest Region, Divisions, and States, 2009" " Million Housing Units, Final" ,,"Midwest Census Region" ,,,"East North Central Census Division",,,,,"West North Central Census Division" ,,,"Total East North Central",,,,,"Total West North Central" ,"Total U.S.1 (millions)" ,,"Total Midwest",,,,," IN, OH",,,"IA, MN, ND, SD" "Appliances",,,,"IL","MI","WI",,,"MO",,"KS, NE" "Total Homes",113.6,25.9,17.9,4.8,3.8,2.3,7,8.1,2.3,3.9,1.8 "Cooking Appliances" "Stoves (Units With Both" "an Oven and a Cooktop)"

455

Energy Secretary Chu Announces $108 Million in Recovery Act Funding...  

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

08 Million in Recovery Act Funding for Environmental Cleanup in Utah Energy Secretary Chu Announces 108 Million in Recovery Act Funding for Environmental Cleanup in Utah March 31,...

456

Energy Department Invests $60 Million to Train Next Generation...  

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

60 Million to Train Next Generation Nuclear Energy Leaders, Pioneer Advanced Nuclear Technology Energy Department Invests 60 Million to Train Next Generation Nuclear Energy...

457

Idaho Natural Gas Vehicle Fuel Consumption (Million Cubic Feet...  

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

View History: Monthly Annual Download Data (XLS File) Idaho Natural Gas Vehicle Fuel Consumption (Million Cubic Feet) Idaho Natural Gas Vehicle Fuel Consumption (Million Cubic...

458

Energy Department Invests Over $7 Million to Commercialize Cost...  

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

Over 7 Million to Commercialize Cost-Effective Hydrogen and Fuel Cell Technologies Energy Department Invests Over 7 Million to Commercialize Cost-Effective Hydrogen and Fuel...

459

Michigan Company Eaton Awarded $2 Million by Energy Department...  

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

Michigan Company Eaton Awarded 2 Million by Energy Department to Reduce Cost of Advanced Fuel Cells Michigan Company Eaton Awarded 2 Million by Energy Department to Reduce Cost...

460

Department of Energy Awards $6 Million Grant to Paducah Area...  

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

6 Million Grant to Paducah Area Community Reuse Organization Department of Energy Awards 6 Million Grant to Paducah Area Community Reuse Organization Department of Energy Awards...

Note: This page contains sample records for the topic "household income million" 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

Department of Energy Awards More Than $11 Million to Advance...  

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

Department of Energy Awards More Than 11 Million to Advance Innovative Geothermal Energy Technologies Department of Energy Awards More Than 11 Million to Advance Innovative...

462

California Natural Gas Exports (No Intransit Deliveries) (Million...  

Annual Energy Outlook 2012 (EIA)

Exports (No Intransit Deliveries) (Million Cubic Feet) California Natural Gas Exports (No Intransit Deliveries) (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4...

463

Indiana Crude Oil + Lease Condensate Proved Reserves (Million...  

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

Crude Oil + Lease Condensate Proved Reserves (Million Barrels) Indiana Crude Oil + Lease Condensate Proved Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4...

464

Alaska Crude Oil + Lease Condensate Proved Reserves (Million...  

Gasoline and Diesel Fuel Update (EIA)

Crude Oil + Lease Condensate Proved Reserves (Million Barrels) Alaska Crude Oil + Lease Condensate Proved Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4...

465

Mississippi Crude Oil + Lease Condensate Proved Reserves (Million...  

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

Crude Oil + Lease Condensate Proved Reserves (Million Barrels) Mississippi Crude Oil + Lease Condensate Proved Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4...

466

California Crude Oil + Lease Condensate Proved Reserves (Million...  

Gasoline and Diesel Fuel Update (EIA)

Crude Oil + Lease Condensate Proved Reserves (Million Barrels) California Crude Oil + Lease Condensate Proved Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4...

467

Nebraska Crude Oil + Lease Condensate Proved Reserves (Million...  

Gasoline and Diesel Fuel Update (EIA)

Crude Oil + Lease Condensate Proved Reserves (Million Barrels) Nebraska Crude Oil + Lease Condensate Proved Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4...

468

Pennsylvania Crude Oil + Lease Condensate Proved Reserves (Million...  

Annual Energy Outlook 2012 (EIA)

+ Lease Condensate Proved Reserves (Million Barrels) Pennsylvania Crude Oil + Lease Condensate Proved Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5...

469

Louisiana Crude Oil + Lease Condensate Proved Reserves (Million...  

Annual Energy Outlook 2012 (EIA)

Crude Oil + Lease Condensate Proved Reserves (Million Barrels) Louisiana Crude Oil + Lease Condensate Proved Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4...

470

Alabama Crude Oil + Lease Condensate Proved Reserves (Million...  

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

Crude Oil + Lease Condensate Proved Reserves (Million Barrels) Alabama Crude Oil + Lease Condensate Proved Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4...

471

DOE Moab Site Cost-Effectively Eliminates 200 Million Gallons...  

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

Moab Site Cost-Effectively Eliminates 200 Million Gallons of Contaminated Ground Water DOE Moab Site Cost-Effectively Eliminates 200 Million Gallons of Contaminated Ground Water...

472

Secretary of Energy Announces Nearly $24 Million in Grants for...  

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

Secretary of Energy Announces Nearly 24 Million in Grants for Carbon Sequestration Research Secretary of Energy Announces Nearly 24 Million in Grants for Carbon Sequestration...

473

President Obama Announces Over $467 Million in Recovery Act Funding...  

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

here Home President Obama Announces Over 467 Million in Recovery Act Funding for Geothermal and Solar Energy Projects President Obama Announces Over 467 Million in Recovery...

474

Department of Energy Offers $102 Million Conditional Commitment...  

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

of Energy Offers 102 Million Conditional Commitment for Loan Guarantee to U.S. Geothermal, Inc. Department of Energy Offers 102 Million Conditional Commitment for Loan...

475

Department of Energy Awards $338 Million to Accelerate Domestic...  

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

You are here Home Department of Energy Awards 338 Million to Accelerate Domestic Geothermal Energy Department of Energy Awards 338 Million to Accelerate Domestic Geothermal...

476

Secretary Chu Announces Nearly $50 Million of Recovery Act Funding...  

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

Chu Announces Nearly 50 Million of Recovery Act Funding to Accelerate Deployment of Geothermal Heat Pumps Secretary Chu Announces Nearly 50 Million of Recovery Act Funding to...

477

Department of Energy Awards More Than $11 Million to Advance...  

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

here Home Department of Energy Awards More Than 11 Million to Advance Innovative Geothermal Energy Technologies Department of Energy Awards More Than 11 Million to Advance...

478

Ohio Natural Gas Liquids Lease Condensate, Proved Reserves (Million...  

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

Liquids Lease Condensate, Proved Reserves (Million Barrels) Ohio Natural Gas Liquids Lease Condensate, Proved Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4...

479

ARPA-E Announces $43 Million for Transformational Energy Storage...  

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

43 Million for Transformational Energy Storage Projects to Advance Electric Vehicle and Grid Technologies ARPA-E Announces 43 Million for Transformational Energy Storage Projects...

480

Department of Energy and Beacon Power Finalize $43 Million Loan...  

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

Beacon Power Finalize 43 Million Loan Guarantee for Innovative Energy Storage Project in New York State Department of Energy and Beacon Power Finalize 43 Million Loan Guarantee...

Note: This page contains sample records for the topic "household income million" 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

Secretary Chu Announces $620 Million for Smart Grid Demonstration...  

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

620 Million for Smart Grid Demonstration and Energy Storage Projects Secretary Chu Announces 620 Million for Smart Grid Demonstration and Energy Storage Projects November 24,...

482

Energy Department, Treasury Announce Availability of $150 Million...  

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

Department, Treasury Announce Availability of 150 Million in Tax Credits for Clean Energy Manufacturers Energy Department, Treasury Announce Availability of 150 Million in Tax...

483

Departments of Energy and Interior Award Nearly $17 Million for...  

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

Departments of Energy and Interior Award Nearly 17 Million for Advanced Hydropower Technologies Departments of Energy and Interior Award Nearly 17 Million for Advanced Hydropower...

484

Energy Department Finalizes $337 Million Loan Guarantee to Mesquite...  

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

337 Million Loan Guarantee to Mesquite Solar 1 for Innovative Solar Power Plant Energy Department Finalizes 337 Million Loan Guarantee to Mesquite Solar 1 for Innovative Solar...

485

Energy Department Finalizes $646 Million Loan Guarantee to Support...  

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

646 Million Loan Guarantee to Support Innovative Solar Power Plant Energy Department Finalizes 646 Million Loan Guarantee to Support Innovative Solar Power Plant September 30,...

486

Department of Energy Finalizes Partial Guarantee for $852 Million...  

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

Partial Guarantee for 852 Million Loan to Support California Concentrating Solar Power Plant Department of Energy Finalizes Partial Guarantee for 852 Million Loan to Support...

487

Idaho Natural Gas Pipeline and Distribution Use (Million Cubic...  

Annual Energy Outlook 2012 (EIA)

View History: Annual Download Data (XLS File) Idaho Natural Gas Pipeline and Distribution Use (Million Cubic Feet) Idaho Natural Gas Pipeline and Distribution Use (Million Cubic...

488

Nevada Natural Gas Pipeline and Distribution Use (Million Cubic...  

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

View History: Annual Download Data (XLS File) Nevada Natural Gas Pipeline and Distribution Use (Million Cubic Feet) Nevada Natural Gas Pipeline and Distribution Use (Million Cubic...

489

Delaware Natural Gas Pipeline and Distribution Use (Million Cubic...  

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

View History: Annual Download Data (XLS File) Delaware Natural Gas Pipeline and Distribution Use (Million Cubic Feet) Delaware Natural Gas Pipeline and Distribution Use (Million...

490

Alaska Natural Gas Pipeline and Distribution Use (Million Cubic...  

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

View History: Annual Download Data (XLS File) Alaska Natural Gas Pipeline and Distribution Use (Million Cubic Feet) Alaska Natural Gas Pipeline and Distribution Use (Million Cubic...

491

Minnesota Natural Gas Pipeline and Distribution Use (Million...  

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

View History: Annual Download Data (XLS File) Minnesota Natural Gas Pipeline and Distribution Use (Million Cubic Feet) Minnesota Natural Gas Pipeline and Distribution Use (Million...

492

Oregon Natural Gas Pipeline and Distribution Use (Million Cubic...  

Annual Energy Outlook 2012 (EIA)

View History: Annual Download Data (XLS File) Oregon Natural Gas Pipeline and Distribution Use (Million Cubic Feet) Oregon Natural Gas Pipeline and Distribution Use (Million Cubic...

493

Kansas Natural Gas Pipeline and Distribution Use (Million Cubic...  

Gasoline and Diesel Fuel Update (EIA)

View History: Annual Download Data (XLS File) Kansas Natural Gas Pipeline and Distribution Use (Million Cubic Feet) Kansas Natural Gas Pipeline and Distribution Use (Million Cubic...

494

Utah Natural Gas Pipeline and Distribution Use (Million Cubic...  

Annual Energy Outlook 2012 (EIA)

View History: Annual Download Data (XLS File) Utah Natural Gas Pipeline and Distribution Use (Million Cubic Feet) Utah Natural Gas Pipeline and Distribution Use (Million Cubic...

495

Alabama Natural Gas Pipeline and Distribution Use (Million Cubic...  

Annual Energy Outlook 2012 (EIA)

View History: Annual Download Data (XLS File) Alabama Natural Gas Pipeline and Distribution Use (Million Cubic Feet) Alabama Natural Gas Pipeline and Distribution Use (Million...

496

Kentucky Natural Gas Pipeline and Distribution Use (Million Cubic...  

Annual Energy Outlook 2012 (EIA)

View History: Annual Download Data (XLS File) Kentucky Natural Gas Pipeline and Distribution Use (Million Cubic Feet) Kentucky Natural Gas Pipeline and Distribution Use (Million...

497

Indiana Natural Gas Pipeline and Distribution Use (Million Cubic...  

Annual Energy Outlook 2012 (EIA)

View History: Annual Download Data (XLS File) Indiana Natural Gas Pipeline and Distribution Use (Million Cubic Feet) Indiana Natural Gas Pipeline and Distribution Use (Million...

498

Virginia Natural Gas Pipeline and Distribution Use (Million Cubic...  

Gasoline and Diesel Fuel Update (EIA)

View History: Annual Download Data (XLS File) Virginia Natural Gas Pipeline and Distribution Use (Million Cubic Feet) Virginia Natural Gas Pipeline and Distribution Use (Million...

499

Alamo, TX Natural Gas Pipeline Imports From Mexico (Million Cubic...  

Gasoline and Diesel Fuel Update (EIA)

View History: Annual Download Data (XLS File) Alamo, TX Natural Gas Pipeline Imports From Mexico (Million Cubic Feet) Alamo, TX Natural Gas Pipeline Imports From Mexico (Million...

500

Ohio Natural Gas Pipeline and Distribution Use (Million Cubic...  

Annual Energy Outlook 2012 (EIA)

View History: Annual Download Data (XLS File) Ohio Natural Gas Pipeline and Distribution Use (Million Cubic Feet) Ohio Natural Gas Pipeline and Distribution Use (Million Cubic...