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Note: This page contains sample records for the topic "median household income" from the National Library of EnergyBeta (NLEBeta).
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We encourage you to perform a real-time search of NLEBeta
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1

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

2

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...

3

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.

4

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

5

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

6

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

7

"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

8

"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

9

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

10

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

11

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

12

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

13

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

14

" 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

15

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

16

" 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

17

" 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

18

" 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

19

" 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

20

" 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

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

" 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

22

" 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

23

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

24

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

25

" 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

26

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

27

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

28

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...

29

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

30

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

31

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

32

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

33

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

34

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

35

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

36

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

37

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

38

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

39

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

40

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 "median household income" 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  

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

42

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

43

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

44

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

45

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

46

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

47

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

48

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

49

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

50

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

51

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

52

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 ...

53

Median statistics cosmological parameter values  

E-Print Network (OSTI)

We present median statistics central values and ranges for 12 cosmological parameters, using 582 measurements (published during 1990-2010) collected by Croft & Dailey (2011). On comparing to the recent Planck collaboration Ade et al. 2013 estimates of 11 of these parameters, we find good consistency in nine cases.

Crandall, Sara

2013-01-01T23:59:59.000Z

54

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.

55

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

56

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

57

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

58

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...

59

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...

60

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 "median household income" 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

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

62

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

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 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

64

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 ...

65

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

66

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

67

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

68

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

69

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...

70

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

71

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.

72

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

73

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

74

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...

75

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

76

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

77

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

78

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

79

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

80

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

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

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

82

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

83

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

84

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

85

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

86

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

87

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 *...

88

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

89

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

90

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

91

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

92

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.

93

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

94

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

95

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

96

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

97

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

98

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

99

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....

100

Household Energy Consumption and Expenditures  

Reports and Publications (EIA)

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

Information Center

2008-09-01T23:59:59.000Z

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


101

Household Vehicles Energy Consumption 1991  

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

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

102

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...

103

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

104

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

105

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

106

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

107

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:...

108

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

109

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

110

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

111

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,

112

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...

113

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...

114

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...

115

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

116

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

117

On the Median Volume Diameter Approximation for Droplet Collision Efficiency  

Science Conference Proceedings (OSTI)

In this note, we examine a shortcut for calculating the overall collision efficiency of a droplet spectrum, known as the “median volume diameter” (mvd) approximation. By calculating the overall collision efficiency of a circular cylinder for a ...

Karen J. Finstad; Edward P. Lozowski; Lasse Makkonen

1988-12-01T23:59:59.000Z

118

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...

119

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

120

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

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

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

122

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

123

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

124

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

125

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

126

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

127

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

128

Property:EstimatedCostMedianUSD | Open Energy Information  

Open Energy Info (EERE)

EstimatedCostMedianUSD EstimatedCostMedianUSD Jump to: navigation, search Property Name EstimatedCostMedianUSD Property Type Quantity Description the median estimate of cost in USD Use this type to express a monetary value in US Dollars. The default unit is one US Dollar. http://en.wikipedia.org/wiki/Area Acceptable units (and their conversions) are: 100 cent USD,cents USD,Cent USD,Cents USD .001 k USD,thousand USD,Thousand USD .000001 M USD,million USD,Million USD .000000001 T USD,trillion USD,Trillion USD Pages using the property "EstimatedCostMedianUSD" Showing 25 pages using this property. (previous 25) (next 25) 2 2-M Probe Survey + 30030,000 centUSD 0.3 kUSD 3.0e-4 MUSD 3.0e-7 TUSD + A Acoustic Logs + 4.62462 centUSD 0.00462 kUSD 4.62e-6 MUSD 4.62e-9 TUSD + Aerial Photography + 240.5424,054 centUSD

129

Property:EstimatedTimeMedian | Open Energy Information  

Open Energy Info (EERE)

EstimatedTimeMedian EstimatedTimeMedian Jump to: navigation, search Property Name EstimatedTimeMedian Property Type Quantity Description the median estimate of time required Use this type to enumerate a length of time. The default unit is the year. Acceptable units (and their conversions) are: 8766 hours,hour,h,H,Hour,Hours,HOUR,HOURS 365.25 days,day,d,Day,Days,D,DAY,DAYS 52.17857 weeks,week,w,Week,Weeks,W,WEEK,WEEKS 12 months,month,m,Month,Months,M,MONTH,MONTHS 1 years,year,y,Year,Years,Y,YEAR,YEARS Pages using the property "EstimatedTimeMedian" Showing 25 pages using this property. (previous 25) (next 25) 2 2-M Probe Survey + 2.281542e-4 years2 hours 0.0833 days 0.0119 weeks 0.00274 months + A Acoustic Logs + 0.044 years385.92 hours 16.08 days 2.297 weeks 0.528 months +

130

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

131

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

132

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

133

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

134

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

135

Measurement of nicotine in household dust  

Science Conference Proceedings (OSTI)

An analytical method of measuring nicotine in house dust was optimized and associations among three secondhand smoking exposure markers were evaluated, i.e., nicotine concentrations of both house dust and indoor air, and the self-reported number of cigarettes smoked daily in a household. We obtained seven house dust samples from self-reported nonsmoking homes and 30 samples from smoking homes along with the information on indoor air nicotine concentrations and the number of cigarettes smoked daily from an asthma cohort study conducted by the Johns Hopkins Center for Childhood Asthma in the Urban Environment. House dust nicotine was analyzed by isotope dilution gas chromatography-mass spectrometry (GC/MS). Using our optimized method, the median concentration of nicotine in the dust of self-reported nonsmoking homes was 11.7 ng/mg while that of smoking homes was 43.4 ng/mg. We found a substantially positive association (r=0.67, P<0.0001) between house dust nicotine concentrations and the numbers of cigarettes smoked daily. Optimized analytical methods showed a feasibility to detect nicotine in house dust. Our results indicated that the measurement of nicotine in house dust can be used potentially as a marker of longer term SHS exposure.

Kim, Sungroul [Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Institute for Global Tobacco Control, 627 N. Washington Street, 2nd Floor Baltimore, MD 21205 (United States); Department of Environmental Health Sciences, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205 (United States)], E-mail: srkim@jhsph.edu; Aung, Ther; Berkeley, Emily [Department of Environmental Health Sciences, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205 (United States); Diette, Gregory B. [Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205 (United States); Department of Medicine, Johns Hopkins University School of Medicine (United States); Breysse, Patrick N. [Department of Environmental Health Sciences, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205 (United States)

2008-11-15T23:59:59.000Z

136

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.

137

Weighted median filters with sigma-delta modulation encoding  

Science Conference Proceedings (OSTI)

Digital decimation filters play a fundamental role in oversampled sigma-delta A/D decoders. In this paper, we first show that weighted median (WM) filtering of a demodulated sequence (at the Nyquist rate) can be implemented concurrently in the A/D decoder. ...

G.R. Arce; N.A. Grabowski; N.C. Gallagher

2000-02-01T23:59:59.000Z

138

Placement of Traffic Barriers on Roadside and Median Slopes  

E-Print Network (OSTI)

Cross median crashes have become a serious problem in recent years. Most of the median cross sections used for divided highways have terrains with steep slopes. Traffic barriers, frequently used on slopes, are generally designed based on the findings obtained from crash tests performed on flat terrain. For barriers placed on roadside and median slopes, vehicle impact height varies depending on the trajectory of the vehicle along the ditch section and lateral offset of the barrier. Thus depending on the placement location on a relatively steep slope, a barrier can be impacted by an errant vehicle at height and orientation more critical compared to those considered during its design. Hence, detailed study of performance of barriers on roadside and median slopes is needed to achieve acceptable safety performance. In this study, performances of modified G4(1S) W-beam, Midwest Guardrail System (MGS), modified Thrie-beam, modified weak post W-beam, and box-beam guardrail systems on sloped terrains are investigated using numerical simulations. A procedure is developed that provide guidance for their placement on roadside and median slopes. The research approach consists of nonlinear finite element analyses and multi-rigid-body dynamic analyses approach. Detailed finite element representation for each of the barriers is developed using LS-DYNA. Model fidelity is assessed through comparison of simulated and measured responses reported in full scale crash test studies conducted on flat terrain. LS-DYNA simulations of vehicle impacts on barriers placed on flat terrain at different impact heights are performed to identify performance limits of the barriers in terms of acceptable vehicle impact heights. The performances of the barriers are evaluated following the guidelines provided in NCHRP Report 350. Multi-rigid-body dynamic analysis code, CARSIM, is used to identify trajectories of the vehicles traversing various roadside and median cross-slopes. After analyzing vehicle trajectories and barrier performance limits, a guideline has been prepared with recommendations for the placement of barriers along roadside and median slopes. This guideline is then verified and refined using the responses obtained from full-scale LS-DYNA simulations. These simulations capture the full encroachment event from departure of the vehicle off the traveled way through impact with the barrier.

Ferdous, Md Rubiat

2011-05-01T23:59:59.000Z

139

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

140

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

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


141

Household Vehicles Energy 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

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

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

144

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

145

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

146

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

147

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

148

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

149

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

150

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

151

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

152

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

153

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

154

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

155

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

156

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

157

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

158

"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

159

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

160

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

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

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...

162

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 ...

163

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

164

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

165

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 ...

166

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

167

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

168

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

169

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

170

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

171

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

172

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

173

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

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

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

178

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

179

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

180

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

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

"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...

182

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

183

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

184

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

185

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

186

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

187

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

188

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

189

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

190

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

191

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

192

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

193

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

194

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

195

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

196

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

197

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

198

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

199

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

200

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

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

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

202

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

203

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

204

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

205

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

206

Vehicle Technologies Office: Fact #597: November 16, 2009 Median Age of  

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

7: November 16, 7: November 16, 2009 Median Age of Cars and Trucks Rising in 2008 to someone by E-mail Share Vehicle Technologies Office: Fact #597: November 16, 2009 Median Age of Cars and Trucks Rising in 2008 on Facebook Tweet about Vehicle Technologies Office: Fact #597: November 16, 2009 Median Age of Cars and Trucks Rising in 2008 on Twitter Bookmark Vehicle Technologies Office: Fact #597: November 16, 2009 Median Age of Cars and Trucks Rising in 2008 on Google Bookmark Vehicle Technologies Office: Fact #597: November 16, 2009 Median Age of Cars and Trucks Rising in 2008 on Delicious Rank Vehicle Technologies Office: Fact #597: November 16, 2009 Median Age of Cars and Trucks Rising in 2008 on Digg Find More places to share Vehicle Technologies Office: Fact #597: November 16, 2009 Median Age of Cars and Trucks Rising in 2008 on

207

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

208

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

209

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...

210

Table B2. Summary Table: Totals and Medians of Floorspace, Number of Workers,  

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

. Summary Table: Totals and Medians of Floorspace, Number of Workers, Hours of Operation, and Age of Building, 1999" . Summary Table: Totals and Medians of Floorspace, Number of Workers, Hours of Operation, and Age of Building, 1999" ,"All Buildings (thousand)","Total Floorspace (million square feet)","Total Workers in All Buildings (thousand)","Median Square Feet per Building (thousand)","Median Square Feet per Worker","Median Hours per Week","Median Age of Buildings (years)" "All Buildings ................",4657,67338,81852,5,909,50,30.5 "Building Floorspace" "(Square Feet)" "1,001 to 5,000 ...............",2348,6774,11125,2.5,667,50,30.5 "5,001 to 10,000 ..............",1110,8238,10968,7,1000,50,34.5 "10,001 to 25,000 .............",708,11153,11378,15,1354,55,28.5

211

A GRASP with path-relinking for the p-median problem ?  

E-Print Network (OSTI)

Sep 18, 2002 ... Given n customers and a set F of m potential facilities, the p-median ..... The pool must support two essential operations: addition of new ...

212

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

213

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...

214

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

215

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

216

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...

217

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

218

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...

219

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

220

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

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

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

222

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

223

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

224

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

225

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

226

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

227

Indoor environment quality and energy retrofits in low-income...  

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

Indoor environment quality and energy retrofits in low-income apartments: retrofit selection protocol Title Indoor environment quality and energy retrofits in low-income...

228

Revisiting the Income Effect: Gasoline Prices and Grocery Purchases  

E-Print Network (OSTI)

or Rent Gasoline and Motor Oil Income after taxes Number ofor Rent Gasoline and Motor Oil Income after taxes Number of

Gicheva, Dora; Hastings, Justine; Villas-Boas, Sofia B

2008-01-01T23:59:59.000Z

229

Integrating Photovoltaic Systems into Low-Income Housing Developments...  

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

Residential Financing Model and Low-Income Resident Job Training Program SEPTEMBER 2011 SOLAR ENERGY TECHNOLOGIES PROGRAM II Integrating PV Systems into Low-Income Housing...

230

An Analysis of the Price Elasticity of Demand for Household Appliances  

SciTech Connect

This report summarizes our study of the price elasticity of demand for home appliances, including refrigerators, clothes washers, and dishwashers. In the context of increasingly stringent appliance standards, we are interested in what kind of impact the increased manufacturing costs caused by higher efficiency requirements will have on appliance sales. We begin with a review of existing economics literature describing the impact of economic variables on the sale of durable goods.We then describe the market for home appliances and changes in this market over the past 20 years, performing regression analysis on the shipments of home appliances and relevant economic variables including changes to operating cost and household income. Based on our analysis, we conclude that the demand for home appliances is price inelastic.

Fujita, Kimberly; Dale, Larry; Fujita, K. Sydny

2008-01-25T23:59:59.000Z

231

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

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

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

232

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

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

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

233

Towards sustainable household energy use in the Netherlands, Int  

E-Print Network (OSTI)

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

Jack Van Der Wal; Henri C. Moll

2001-01-01T23:59:59.000Z

234

Solar upgrading of low income housing  

SciTech Connect

The design, installation, training and operation experience of retrofitting solar devices (active and passive water heaters, Trombe walls, convective loop window units, etc.) on hundreds of low-income houses along the Southwest Border Region are summarized. The project demonstrates a wide variety of appropriate low-cost solar applications and provides prototypical models for the region's low-income inhabitants. Space heating and cooling systems and water heating systems have been combined with weatherization and conservation techniques. CETA employees, members of various community groups and youth groups, and employees of local non-profit organizations have been trained as installers, and low-income people have been educated in the operation and use of these solar devices. It is anticipated that this transfer of appropriate technology into the region will result in continued retrofitting of solar installations and in the stimulation of local industries, which will create employment opportunities for members of the low-income population.

Lumsdaine, E.; Farrer, R.; Callahan, D.

1980-01-01T23:59:59.000Z

235

A Model of Household Demand for Activity Participation and Mobility  

E-Print Network (OSTI)

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

Golob, Thomas F.

1996-01-01T23:59:59.000Z

236

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

237

Barriers to household investment in residential energy conservation: preliminary assessment  

Science Conference Proceedings (OSTI)

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

Hoffman, W.L.

1982-12-01T23:59:59.000Z

238

Household Responses to the Financial Crisis in Indonesia  

E-Print Network (OSTI)

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

Thomas, Duncan; Frankenberg, Elizabeth

2005-01-01T23:59:59.000Z

239

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

U.S. Energy Information Administration (EIA)

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

240

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

U.S. Energy Information Administration (EIA)

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

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

Essays on the effects of demographics on household consumption.  

E-Print Network (OSTI)

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

Stepanova, Ekaterina, 1977-

2006-01-01T23:59:59.000Z

242

Table 1. Household Characteristics by Ceiling Fans, 2001  

U.S. Energy Information Administration (EIA)

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

243

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

U.S. Energy Information Administration (EIA)

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

244

Analysis of the energy requirement for household consumption.  

E-Print Network (OSTI)

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

Vringer, Kees

2005-01-01T23:59:59.000Z

245

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

U.S. Energy Information Administration (EIA)

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

246

1997 Residential Energy Consumption and Expenditures per Household ...  

U.S. Energy Information Administration (EIA)

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

247

Answers to Frequently Asked Questions About the Household ...  

U.S. Energy Information Administration (EIA)

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

248

Appliance Commitment for Household Load Scheduling  

Science Conference Proceedings (OSTI)

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

Du, Pengwei; Lu, Ning

2011-06-30T23:59:59.000Z

249

Household energy consumption and expenditures 1987  

SciTech Connect

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

Not Available

1990-01-22T23:59:59.000Z

250

In-vessel composting of household wastes  

Science Conference Proceedings (OSTI)

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

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

2006-07-01T23:59:59.000Z

251

Measuring the energy efficiency of households: an application of frontier production function analysis  

SciTech Connect

A new method to estimate the energy efficiency of households is presented. Households are viewed as productive units organized to provide the occupants with numerous services requiring fuel as an input: house heating to achieve a desired interior temperature, lighting for recreation, etc. The focus is on the efficiency of energy use, not the demand for energy. The approach to measuring efficiency compares a group of productive units along several dimensions of input resources and service outputs. The comparison identifies a subset of units that are considered efficient because they require the least resources per unit of service provided. The efficient units form a production possibility frontier of best practice in service provision. A regression of the two sets of efficiency scores on other variables reflecting locational, dwelling unit, and occupational characteristics is performed to identify factors accounting for differences in efficiency. The results indicate that the more efficient units used electric heat, had higher ratios of non-electric to electric fuel inputs, were owner-occupied, and were built after 1974. The findings also suggest that both family life cycle and income effects account for efficiency differences.

Baxter, L.W.

1984-01-01T23:59:59.000Z

252

Vickers microindentation toughness of a sintered SiC in the median-crack regime  

SciTech Connect

The Vickers microindentation method for the determination of the fracture toughness of ceramics was investigated in the median crack regime for a sintered alpha SiC. The results are compared with fracture toughness measurements by conventional fracture mechanics technique and also with the reported indentation toughness for the low-load Palmqvist crack regime. Indentation toughnesses in the median crack regime vary widely depending on the choice of the specific equation which is applied. The indentation toughnesses are also load (crack length) dependent. A decreasing R-curve trend results, in contradiction to the flat R-curve that has been observed with conventional fracture mechanics techniques. It is concluded that the Vickers microindentation method is not a reliable technique for the determination of the fracture toughness of ceramics in the median crack regime.

Ghosh, Asish; Kobayashi, A.S. (Washington Univ., Seattle, WA (United States). Coll. of Engineering); Li, Zhuang (Argonne National Lab., IL (United States)); Henager, C.H. Jr. (Pacific Northwest Lab., Richland, WA (United States)); Bradt, R.C. (Nevada Univ., Reno, NV (United States). Mackay School of Mines)

1991-01-01T23:59:59.000Z

253

2003 CBECS National Median Source Energy Use and Performance Comparisons by  

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

2003 CBECS National Median Source Energy Use and Performance 2003 CBECS National Median Source Energy Use and Performance Comparisons by Building Type Secondary menu About us Press room Contact Us Portfolio Manager Login Facility owners and managers Existing buildings Commercial new construction Industrial energy management Small business Service providers Service and product providers Verify applications for ENERGY STAR certification Design commercial buildings Energy efficiency program administrators Commercial and industrial program sponsors Associations State and local governments Federal agencies Tools and resources Training In This Section Campaigns Commercial building design Communications resources Energy management guidance Financial resources Portfolio Manager Products and purchasing Recognition Research and reports Service and product provider (SPP) resources

254

Consumption patterns and household hazardous solid waste generation in an urban settlement in Mexico  

SciTech Connect

Mexico is currently facing a crisis in the waste management field. Some efforts have just commenced in urban and in rural settlements, e.g., conversion of open dumps into landfills, a relatively small composting culture, and implementation of source separation and plastic recycling strategies. Nonetheless, the high heterogeneity of components in the waste, many of these with hazardous properties, present the municipal collection services with serious problems, due to the risks to the health of the workers and to the impacts to the environment as a result of the inadequate disposition of these wastes. A generation study in the domestic sector was undertaken with the aim of finding out the composition and the generation rate of household hazardous waste (HHW) produced at residences. Simultaneously to the generation study, a socioeconomic survey was applied to determine the influence of income level on the production of HHW. Results from the solid waste generation analysis indicated that approximately 1.6% of the waste stream consists of HHW. Correspondingly, it was estimated that in Morelia, a total amount of 442 ton/day of domestic waste are produced, including 7.1 ton of HHW per day. Furthermore, the overall amount of HHW is not directly related to income level, although particular byproducts do correlate. However, an important difference was observed, as the brands and the presentation sizes of goods and products used in each socioeconomic stratum varied.

Delgado Otoniel, Buenrostro [Instituto De Investigaciones Agricolas y Forestales, Universidad Michoacana De San Nicolas De Hidalgo, Av. San Juanito Itzicuaro S/N, Col. San Juanito Itzicuaro, C.P. 58330, Morelia-Aeropuerto, Michoacan (Mexico)], E-mail: otonielb@zeus.umich.mx; Liliana, Marquez-Benavides; Gaona Francelia, Pinette [Instituto De Investigaciones Agricolas y Forestales, Universidad Michoacana De San Nicolas De Hidalgo, Av. San Juanito Itzicuaro S/N, Col. San Juanito Itzicuaro, C.P. 58330, Morelia-Aeropuerto, Michoacan (Mexico)

2008-07-01T23:59:59.000Z

255

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

E-Print Network (OSTI)

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

Wood, D.J.

2010-01-01T23:59:59.000Z

256

Simulating household activities to lower consumption peaks: demonstration  

Science Conference Proceedings (OSTI)

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

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

2013-05-01T23:59:59.000Z

257

Elements of consumption: an abstract visualization of household consumption  

Science Conference Proceedings (OSTI)

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

Stephen Makonin; Philippe Pasquier; Lyn Bartram

2011-07-01T23:59:59.000Z

258

Performance Analysis of DS Signal Code Acquisition Using the Matched Filter and the Median Filter  

Science Conference Proceedings (OSTI)

The theoretical analysis and simulation of the performance of a matched filter code acquisition structure with a median filter as the aiding device to cancel CW jamming in the AWGN channel is described. Both coherent and noncoherent structures are ... Keywords: interference cancellation, synchronization

J. Iinatti; P. Leppänen

1998-09-01T23:59:59.000Z

259

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

260

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

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

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

E-Print Network (OSTI)

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

Kurani, Kenneth; Turrentine, Thomas; Sperling, Daniel

1996-01-01T23:59:59.000Z

262

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

U.S. Energy Information Administration (EIA)

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

263

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

U.S. Energy Information Administration (EIA)

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

264

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

U.S. Energy Information Administration (EIA)

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

265

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

U.S. Energy Information Administration (EIA)

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

266

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

U.S. Energy Information Administration (EIA)

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

267

Alternative Fuels Data Center: Biodiesel Income Tax Credit  

Alternative Fuels and Advanced Vehicles Data Center (EERE)

Income Tax Income Tax Credit to someone by E-mail Share Alternative Fuels Data Center: Biodiesel Income Tax Credit on Facebook Tweet about Alternative Fuels Data Center: Biodiesel Income Tax Credit on Twitter Bookmark Alternative Fuels Data Center: Biodiesel Income Tax Credit on Google Bookmark Alternative Fuels Data Center: Biodiesel Income Tax Credit on Delicious Rank Alternative Fuels Data Center: Biodiesel Income Tax Credit on Digg Find More places to share Alternative Fuels Data Center: Biodiesel Income Tax Credit on AddThis.com... More in this section... Federal State Advanced Search All Laws & Incentives Sorted by Type Biodiesel Income Tax Credit A taxpayer that delivers pure, unblended biodiesel (B100) into the tank of a vehicle or uses B100 as an on-road fuel in their trade or business may be

268

Entrepreneurship and income inequality in southern Ethiopia  

Science Conference Proceedings (OSTI)

Apr 7, 2009 ... source of cash income for the local population. In ... followed over the years, enforced by tradition, by the socialist administration that was in power until .... index following a uniform percentage change in yk is .... hand, require access to markets and changes in the ..... tion of earnings in the United States.

269

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- |

270

Financial Incentives for Increasing Work and Income Among Low-Income Families  

E-Print Network (OSTI)

v j-i_ruCM Earnings + AFDC Earnings + Supplement 1 [ t 1—(—6a: Annual Income Under AFDC and CAP Single Parent With Two+ Food Stamps I Earnings + AFDC + Food Stamps $o I I I i I I

Blank, Rebecca M.; Card, David; Robins, Philip K.

1999-01-01T23:59:59.000Z

271

Appliance Standby Power and Energy Consumption in South African Households  

Open Energy Info (EERE)

Appliance Standby Power and Energy Consumption in South African Households Appliance Standby Power and Energy Consumption in South African Households Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Appliance Standby Power and Energy Consumption in South African Households Focus Area: Appliances & Equipment Topics: Policy Impacts Website: active.cput.ac.za/energy/web/DUE/DOCS/422/Paper%20-%20Shuma-Iwisi%20M. Equivalent URI: cleanenergysolutions.org/content/appliance-standby-power-and-energy-co Language: English Policies: Deployment Programs DeploymentPrograms: Technical Assistance A modified engineering model is proposed to estimate standby power and energy losses in households. The modified model accounts for the randomness of standby power and energy losses due to unpredicted user appliance operational behavior.

272

Profiling energy use in households and office spaces  

Science Conference Proceedings (OSTI)

Energy consumption is largely studied in the context of different environments, such as domestic, corporate, industrial, and public sectors. In this paper, we discuss two environments, households and office spaces, where people have an especially ...

Salman Taherian; Marcelo Pias; George Coulouris; Jon Crowcroft

2010-04-01T23:59:59.000Z

273

Household Preferences for Supporting Renewable Energy, and Barriers...  

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

Household Preferences for Supporting Renewable Energy, and Barriers to Green Power Demand Speaker(s): Ryan Wiser Date: May 9, 2002 - 12:00pm Location: Bldg. 90 Nearly 40% of the...

274

Energy Consumption of Refrigerators in Ghana - Outcomes of Household...  

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

Energy Consumption of Refrigerators in Ghana - Outcomes of Household Surveys Speaker(s): Essel Ben Hagan Date: July 12, 2007 - 12:00pm Location: 90-3122 Seminar HostPoint of...

275

A Theoretical Basis for Household Energy Conservation UsingProduct...  

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

A Theoretical Basis for Household Energy Conservation Using Product-Integrated Feedback Speaker(s): Teddy McCalley Date: October 11, 2002 - 12:00pm Location: Bldg. 90 Seminar Host...

276

Characterizing Household Plug Loads through Self-Administered Load Research  

Science Conference Proceedings (OSTI)

Household miscellaneous loads, which include consumer electronics, are the fastest growing segment of household energy use in the United States. Although the relative energy intensity of applications such as heating and cooling is declining, the DOEAnnual Energy Outlook forecasts that the intensity of residential miscellaneous end uses will increase substantially by 2030. Studies by TIAX and Ecos Consulting reveal that miscellaneous devices8212smaller devices in terms of energy draw but growing in usage8...

2009-12-09T23:59:59.000Z

277

Three essays on the impacts of income taxes  

E-Print Network (OSTI)

This dissertation consists of three essays studying the impacts of income and wage taxes. Chapter One examines how income tax changes differentially affect the pre-tax wages of different industries based on the injury and ...

Powell, David Matthew, Ph. D. Massachusetts Institute of Technology

2009-01-01T23:59:59.000Z

278

Transferring 2001 National Household Travel Survey  

Science Conference Proceedings (OSTI)

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

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

2007-05-01T23:59:59.000Z

279

Ventilation Behavior and Household Characteristics in NewCalifornia Houses  

SciTech Connect

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

Price, Phillip N.; Sherman, Max H.

2006-02-01T23:59:59.000Z

280

Source separation of household waste: A case study in China  

SciTech Connect

A pilot program concerning source separation of household waste was launched in Hangzhou, capital city of Zhejiang province, China. Detailed investigations on the composition and properties of household waste in the experimental communities revealed that high water content and high percentage of food waste are the main limiting factors in the recovery of recyclables, especially paper from household waste, and the main contributors to the high cost and low efficiency of waste disposal. On the basis of the investigation, a novel source separation method, according to which household waste was classified as food waste, dry waste and harmful waste, was proposed and performed in four selected communities. In addition, a corresponding household waste management system that involves all stakeholders, a recovery system and a mechanical dehydration system for food waste were constituted to promote source separation activity. Performances and the questionnaire survey results showed that the active support and investment of a real estate company and a community residential committee play important roles in enhancing public participation and awareness of the importance of waste source separation. In comparison with the conventional mixed collection and transportation system of household waste, the established source separation and management system is cost-effective. It could be extended to the entire city and used by other cities in China as a source of reference.

Zhuang Ying; Wu Songwei; Wang Yunlong [Department of Environmental Engineering, Zhejiang University, Hangzhou 310029 (China); Wu Weixiang [Department of Environmental Engineering, Zhejiang University, Hangzhou 310029 (China)], E-mail: weixiang@zju.edu.cn; Chen Yingxu [Department of Environmental Engineering, Zhejiang University, Hangzhou 310029 (China)

2008-07-01T23:59:59.000Z

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

Survey of Income and Program Participation (SIPP) | Data.gov  

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

Tags Employment, labor force, Demographics, Income, Program Participation, AFDC, Food Stamps, SSI, Energy Assistance, Welfare, General Assistance, School Meals, Health...

282

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

SciTech Connect

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

Poyer, D.A.; Johnson, G.

1985-10-01T23:59:59.000Z

283

Digital pipelined hardware median filter design for real-time image processing  

Science Conference Proceedings (OSTI)

A hardware median filter is described which is designed to filter imagery at a rate of 10*10/sup 6/ pixels/second. The data is windowed with line buffers, and propagated through n pipelined stages where n is the number of bits in a pixel. The algorithm described is a form of the Radix method of Ataman modified to reduce the decisionmaking at each stage. The filter can be implemented with available logic components and would be useful as a preprocessor in a pattern recognition system. 6 references.

Delman, D.J.

1981-01-01T23:59:59.000Z

284

Empire District Electric - Low Income New Homes Program | Department of  

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

Empire District Electric - Low Income New Homes Program Empire District Electric - Low Income New Homes Program Empire District Electric - Low Income New Homes Program < Back Eligibility Construction Low-Income Residential Savings Category Home Weatherization Commercial Weatherization Heating & Cooling Commercial Heating & Cooling Cooling Heat Pumps Appliances & Electronics Commercial Lighting Lighting Maximum Rebate Total: $1,100 Program Info State Missouri Program Type Utility Rebate Program Rebate Amount Insulation: full incremental cost above the appropriate baseline Heat Pumps: $400 Central AC: $400 Refrigerator: $200 Lighting: $100 Provider Empire District Electric Empire District Electric offers rebates for the utilization of energy efficient measures and appliances in new, low-income homes. Rebates are

285

Household solid waste characteristics and management in Chittagong, Bangladesh  

Science Conference Proceedings (OSTI)

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

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

2008-07-01T23:59:59.000Z

286

Income Tax Capital Credit (Alabama) | Department of Energy  

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

Income Tax Capital Credit (Alabama) Income Tax Capital Credit (Alabama) Income Tax Capital Credit (Alabama) < Back Eligibility Commercial Construction Industrial Savings Category Alternative Fuel Vehicles Hydrogen & Fuel Cells Buying & Making Electricity Water Home Weatherization Solar Wind Program Info State Alabama Program Type Corporate Tax Incentive The purpose of this law is to create jobs and to stimulate business and economic growth in the state by providing an income tax capital credit for approved projects. The Income Tax Capital Credit is a credit of five percent (5%) of the capital costs of a qualifying project offered by the Alabama Department of Revenue. The credits is applied to the Alabama income tax liability or financial institution excise tax generated by the project income, each year for 20 years. This credit cannot be carried forward or

287

Cost-effectiveness of freeway median high occupancy vehicle (HOV) facility conversion to rail guideway transit  

E-Print Network (OSTI)

Many freeways in the United States contain median high occupancy vehicle (HOV) facilities. These facilities have been envisioned by some as reserved space for future rail guideway transit. This thesis examines the cost-effectiveness of converting a freeway median HOV lane into a guideway transit line. A full-cost model was developed to determine the cost effectiveness of converting an HOV lane into a rail transit line. The measure of cost-effectiveness used was the benefit-to-cost ratio. The full-cost model contained two cost categories (capital and operating costs) and two benefit categories (travel time and externality benefits). This fullcost model was adopted to conditions on the Katy Freeway in Houston Texas which served as a case study for this thesis. It was found that 29 percent of the person-miles of travel on the Katy Freeway under given conditions must utilize guideway transit for conversion to be cost-effective. It was also found that the model is sensitive to assumptions of the value of time, project soft costs (administrative, planning, and design costs) and the operating cost of the rail transit system. The model is also sensitive to assumptions regarding latent demand. It was concluded that conversion to rail guideway transit in the case study example is not cost-effective. It was reconunended that further investigation be taken into full-cost model components to allow more certain estimates of cost components. Also recommended was further consideration of the effects of latent demand on HOV to rail guideway transit conversions.

Best, Matthew Evans

1996-01-01T23:59:59.000Z

288

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

E-Print Network (OSTI)

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

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

2010-01-01T23:59:59.000Z

289

Water Related Energy Use in Households and Cities - an Australian  

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

Water Related Energy Use in Households and Cities - an Australian Water Related Energy Use in Households and Cities - an Australian Perspective Speaker(s): Steven Kenway Date: May 12, 2011 - 12:00pm Location: 90-3122 Seminar Host/Point of Contact: Anita Estner James McMahon This presentation covers the content of recent journal papers and reports focused on the water-energy nexus and the related theory of urban metabolism. This includes (i) a review of the water-energy nexus focused on cities (ii) quantifying water-related energy in cities (iii) modeling household water-related energy use including key factors, sensitivity and uncertainty analysis, and (iv) relevance and implications of the urban metabolism theoretical framework. Steven's work focuses on understanding the indirect connections between urban water management, energy use and

290

EIA - Gasoline and Diesel Fuel report: Household Vehicles Energy  

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

1 1 Transportation logo printer-friendly version logo for Portable Document Format file Household Vehicles Energy Consumption 1991 December 1993 Release Next Update: August 1997. Based on the 1991 Residential Transportation Energy Consumption Survey conducted by the Energy Information Administration (EIA) - survey series has been discontinued after EIA's 1994 survey. Only light-duty vehicles and recreational vehicles are included in this report. EIA has excluded motorcycles, mopeds, large trucks, and buses. This report, Household Vehicles Energy Consumption 1991, is based on data from the 1991 Residential Transportation Energy Consumption Survey (RTECS). Focusing on vehicle miles traveled (VMT) and energy enduse consumption and expenditures by households for personal transportation, the 1991 RTECS is

291

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

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

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

292

Energy Information Administration/Household Vehicles Energy Consumption 1994  

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

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

293

Energy Consumption of Refrigerators in Ghana - Outcomes of Household  

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

Energy Consumption of Refrigerators in Ghana - Outcomes of Household Energy Consumption of Refrigerators in Ghana - Outcomes of Household Surveys Speaker(s): Essel Ben Hagan Date: July 12, 2007 - 12:00pm Location: 90-3122 Seminar Host/Point of Contact: Robert Van Buskirk Galen Barbose As part of activities to develop refrigerator efficiency standards regulations in Ghana, a national survey on the energy consumption of refrigerators and refrigerator-freezers has been conducted. The survey covered 1000 households in urban, peri-urban and rural communities in various parts of the country. The survey found that, on average, refrigerators and refrigerator-freezers in Ghana use almost three times what is allowed by minimum efficiency standards in the U.S., and a few refrigerators had energy use at levels almost ten times the U.S.

294

Assumptions to the Annual Energy Outlook 2001 - Household Expenditures  

Gasoline and Diesel Fuel Update (EIA)

Completed Copy in PDF Format Completed Copy in PDF Format Related Links Annual Energy Outlook2001 Supplemental Data to the AEO2001 NEMS Conference To Forecasting Home Page EIA Homepage Household Expenditures Module Key Assumptions The historical input data used to develop the HEM version for the AEO2001 consists of recent household survey responses, aggregated to the desired level of detail. Two surveys performed by the Energy Information Administration are included in the AEO2001 HEM database, and together these input data are used to develop a set of baseline household consumption profiles for the direct fuel expenditure analysis. These surveys are the 1997 Residential Energy Consumption Survey (RECS) and the 1991 Residential Transportation Energy Consumption Survey (RTECS). HEM uses the consumption forecast by NEMS for the residential and

295

Modeling patterns of hot water use in households  

Science Conference Proceedings (OSTI)

This report presents a detailed model of hot water use patterns in individual household. The model improves upon an existing model by including the effects of four conditions that were previously unaccounted for: the absence of a clothes washer; the absence of a dishwasher; a household consisting of seniors only; and a household that does not pay for its own hot water use. Although these four conditions can significantly affect residential hot water use, and have been noted in other studies, this is the first time that they have been incorporated into a detailed model. This model allows detailed evaluation of the impact of potential efficiency standards for water heaters and other market transformation policies. 21 refs., 3 figs., 10 tabs.

Lutz, J.D.; Liu, Xiaomin; McMahon, J.E. [and others

1996-11-01T23:59:59.000Z

296

Modeling patterns of hot water use in households  

SciTech Connect

This report presents a detailed model of hot water use patterns in individual households. The model improves upon an existing model by including the effects of four conditions that were previously unaccounted for: the absence of a clothes washer; the absence of a dishwasher; a household consisting of seniors only; and a household that does not pay for its own hot water use. Although these four conditions can significantly affect residential hot water use, and have been noted in other studies, this is the first time that they have been incorporated into a detailed model. This model allows detailed evaluation of the impact of potential efficiency standards for water heaters and other market transformation policies.

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

1996-01-01T23:59:59.000Z

297

New York Household Travel Patterns: A Comparison Analysis  

SciTech Connect

In 1969, the U. S. Department of Transportation began collecting detailed data on personal travel to address various transportation planning issues. These issues range from assessing transportation investment programs to developing new technologies to alleviate congestion. This 1969 survey was the birth of the Nationwide Personal Transportation Survey (NPTS). The survey was conducted again in 1977, 1983, 1990 and 1995. Longer-distance travel was collected in 1977 and 1995. In 2001, the survey was renamed to the National Household Travel Survey (NHTS) and collected both daily and longer-distance trips in one survey. In addition to the number of sample households that the national NPTS/NHTS survey allotted to New York State (NYS), the state procured an additional sample of households in both the 1995 and 2001 surveys. In the 1995 survey, NYS procured an addition sample of more than 9,000 households, increasing the final NY NPTS sample size to a total of 11,004 households. Again in 2001, NYS procured 12,000 additional sample households, increasing the final New York NHTS sample size to a total of 13,423 households with usable data. These additional sample households allowed NYS to address transportation planning issues pertinent to geographic areas significantly smaller than for what the national NPTS and NHTS data are intended. Specifically, these larger sample sizes enable detailed analysis of twelve individual Metropolitan Planning Organizations (MPOs). Furthermore, they allowed NYS to address trends in travel behavior over time. In this report, travel data for the entire NYS were compared to those of the rest of the country with respect to personal travel behavior and key travel determinants. The influence of New York City (NYC) data on the comparisons of the state of New York to the rest of the country was also examined. Moreover, the analysis examined the relationship between population density and travel patterns, and the similarities and differences among New York MPOs. The 1995 and 2001 survey data make it possible to examine and identify travel trends over time. This report does not address, however, the causes of the differences and/or trends.

Hu, Patricia S [ORNL; Reuscher, Tim [ORNL

2007-05-01T23:59:59.000Z

298

A Glance at China’s Household Consumption  

SciTech Connect

Known for its scale, China is the most populous country with the world’s third largest economy. In the context of rising living standards, a relatively lower share of household consumption in its GDP, a strong domestic market and globalization, China is witnessing an unavoidable increase in household consumption, related energy consumption and carbon emissions. Chinese policy decision makers and researchers are well aware of these challenges and keen to promote green lifestyles. China has developed a series of energy policies and programs, and launched a wide?range social marketing activities to promote energy conservation.

Shui, Bin

2009-10-22T23:59:59.000Z

299

Minnesota Energy Resources (Gas) - Low-Income New Construction Rebates |  

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

Minnesota Energy Resources (Gas) - Low-Income New Construction Minnesota Energy Resources (Gas) - Low-Income New Construction Rebates Minnesota Energy Resources (Gas) - Low-Income New Construction Rebates < Back Eligibility Low-Income Residential Nonprofit Savings Category Heating & Cooling Commercial Heating & Cooling Heating Heat Pumps Appliances & Electronics Water Heating Program Info State Minnesota Program Type Utility Rebate Program Rebate Amount Gas Furnace: 500 Integrated Space and Water Heating System: 900 Electronic Programmable Set-Back Thermostat: 100 Water Heater: 100 Drain Water Heat Recovery Device: 300 Provider Minnesota Energy Resources Minnesota Energy Resources is now offering rebates for non-profits servicing low-income communities. New construction organizations can take advantage of rebates for efficient technologies if the low-income homes are

300

Approaches to Electric Utility Energy Efficiency for Low Income...  

Open Energy Info (EERE)

to Electric Utility Energy Efficiency for Low Income Customers in a Changing Regulatory Environment Jump to: navigation, search Name Approaches to Electric Utility Energy...

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

Income Tax Deduction for Energy Efficiency Upgrades (Idaho) ...  

Open Energy Info (EERE)

Facebook icon Twitter icon Income Tax Deduction for Energy Efficiency Upgrades (Idaho) This is the approved revision of this page, as well as being the most recent. Jump...

302

Low-Income Loan Program for Energy Conservation Improvements...  

Open Energy Info (EERE)

energy sources by offering low-interest loans to low- and moderate-income homeowners for repairs to existing homes. All renewable energy technologies are eligible. The...

303

Understanding the world wool market : trade, productivity and grower incomes.  

E-Print Network (OSTI)

??[Truncated abstract] The core objective of this thesis is summarised by its title: “Understanding the World Wool Market: Trade, Productivity and Grower Incomes”. Thus, we… (more)

Verikios, George

2007-01-01T23:59:59.000Z

304

California Solar Initiative - Low-Income Solar Water Heating...  

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

Public Utilities Commission (CPUC) voted in October 2011 to create the California Solar Initiative (CSI) Thermal Low-Income program for single and multifamily residential...

305

Measurement and Verification of Low Income Energy Efficiency...  

Open Energy Info (EERE)

and Verification of Low Income Energy Efficiency Programs in Brazil: Methodological Challenges Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Measurement and...

306

Income Tax Deduction for Energy Efficiency Upgrades | Department...  

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

1, 2002, qualify for an income tax deduction for 100% of the cost of installing new insulation or other approved energy efficiency improvements in an existing residence. Any...

307

EvoNILM: evolutionary appliance detection for miscellaneous household appliances  

Science Conference Proceedings (OSTI)

To improve the energy awareness of consumers, it is necessary to provide them with information about their energy demand, not just on the household level. Non-intrusive load monitoring (NILM) gives the consumer the opportunity to disaggregate their consumed ... Keywords: evolutionary algorithm, load disaggregation, non-intrusive load monitoring

Dominik Egarter; Wilfried Elmenreich

2013-07-01T23:59:59.000Z

308

Modelling the Energy Demand of Households in a Combined  

E-Print Network (OSTI)

. Emissions from passenger transport, households'electricity and heat consumption are growing rapidly despite demand analysis for electricity (e.g. Larsen and Nesbakken, 2004; Holtedahl and Joutz, 2004; Hondroyiannis, 2004) and passenger cars (Meyer et al., 2007). Some recent studies cover the whole residential

Steininger, Karl W.

309

Fuelwood Use by Rural Households in the Brazilian Atlantic Forest  

E-Print Network (OSTI)

Fuelwood is an important source of domestic energy in rural regions of Brazil. In the Zona da Mata of Minas Gerais, native species from the Atlantic Forest are an important source of fuelwood, supplemented by wood from eucalyptus and coffee plantations. The use of native species is complicated by their increasing scarcity and the recent enforcement of forest policies that prohibit the felling of even dead natives trees without a permit. In this study, the factors contributing to the use of fuelwood in this region, despite the simultaneous use of liquid petroleum gas in most households, are explored by examining fuelwood use patterns in four small rural communities in the Zona da Mata Mineira using household surveys and semi-structured interviews. Two hypotheses were tested using a Jacknife regression. The first hypothesis, based on the energy ladder model, tested the predictive power of socioeconomic status in relation to fuelwood use. Two dependent variables were used to represent the importance of fuelwood to a household: the amount of time a household spent collecting fuelwood (Effort) and the number of purposes a household used fuelwood for (Class of Fuelwood Use). Socioeconomic status did explain a statistically significant percentage of the variance in Effort, but not in Class of Fuelwood Use. The second hypothesis tested for a moderating effect of the availability of fuelwood on the relationship between the socioeconomic status of a household and the dependent variables. The interaction between access to fuelwood and socioeconomic status was shown to explain a significant percentage of the variance in Effort, thereby indicating that the effect of socioeconomic status on time spent collecting fuelwood depends on access to fuelwood. However, there was no statistically significant interaction found between Class of Fuelwood Use and fuelwood availability. The Atlantic Forest Policy was found to have little influence on domestic energy decisions made by surveyed households. Few research subjects had a good understanding of the basic tenets of this policy and the Forest Police do not have adequate resources to enforce the policy at this level.

Wilcox-Moore, Kellie J.

2010-05-01T23:59:59.000Z

310

INCOMING DOCUMENT CONTROL FORM DOCUMENT DESCRIPTION ORGANIZATIO  

Office of Legacy Management (LM)

INCOMING DOCUMENT CONTROL FORM DOCUMENT DESCRIPTION ORGANIZATIO )ATE COMPLETED: ACTION NUMBER: I ! I I DOCUMENT CONTROL DATE INITIALS DATA BASE: ACTION LOG: FILED: To : Doug Tonkay, OTS Decen From: MIchele Landis, dRW Subject: Draft report ~ Result= of the Radiologic; Former Ore Storage Site, Palmerton, Pennsylvania Attached is one copy of the draft report. PIE provide your comments to me by January 16, 1990. tlichele Landis ,9, 1989 "ey at the review and Results of the Radiological SJrvey at the Former Ore S&age Site, Palmerton, PennsylvLnia (PPOOI) J. L Quikd J. W. Cdchdr W. D. &rei ! I : HEALTH AND t5UEI-Y RESEARCH DMSi Waste Management Research and Development Prc (Activity No. AH 10 05 00 0; NEAHOOl) RESULTS OF 'I-HE RADIOLOGICAL SURV

311

Using unlabeled Wi-Fi scan data to discover occupancy patterns of private households  

Science Conference Proceedings (OSTI)

This poster presents the homeset algorithm, a lightweight approach to estimate occupancy schedules of private households. The algorithm relies on the mobile phones of households' occupants to collect Wi-Fi scans. The scans are then used to determine ...

Wilhelm Kleiminger, Christian Beckel, Anind Dey, Silvia Santini

2013-11-01T23:59:59.000Z

312

California’s Immigrant Households and Public-Assistance Participation in the 1990s - Policy Brief  

E-Print Network (OSTI)

with Dependent Children (AFDC)/California Work Opportunitystate households participating in AFDC/ CalWORKs pro- grams.of noncitizen households received AFDC, compared to 4.5% of

2002-01-01T23:59:59.000Z

313

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 ...

314

Household Vehicles Energy Use: Latest Data and Trends - Table A04  

U.S. Energy Information Administration (EIA)

... Buildings & Industry > Transportation Surveys > Household Vehicles Energy ... U.S. Vehicles by Model ... Office of Coal, Nuclear, Electric, and Alternate ...

315

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

Science Conference Proceedings (OSTI)

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

Not Available

1993-03-02T23:59:59.000Z

316

Income Growth, Energy Consumption and Carbon Emissions in China  

Science Conference Proceedings (OSTI)

The paper examines the long-run relationship between per capita income growth, energy consumption, and pollutant emissions in China during the period 1953–2004. We find that energy consumption, pollutant emissions and income are cointegrated in ... Keywords: Energy consumption, Pollutant emissions, Causality, Multivariate cointegration, China

Zhi Zhao; Jiahai Yuan

2008-11-01T23:59:59.000Z

317

Residential Renewable Energy Income Tax Credit | Department of Energy  

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

Renewable Energy Income Tax Credit Renewable Energy Income Tax Credit Residential Renewable Energy Income Tax Credit < Back Eligibility Residential Savings Category Solar Buying & Making Electricity Heating & Cooling Commercial Heating & Cooling Heating Water Heating Wind Maximum Rebate 1,000 Program Info Start Date 1979 State Massachusetts Program Type Personal Tax Credit Rebate Amount 15% Provider Massachusetts Department of Revenue Massachusetts allows a 15% credit -- up to $1,000 -- against the state income tax for the net expenditure* of a renewable-energy system (including installation costs) installed on an individual's primary residence. If the credit amount is greater than a resident's income tax liability, the excess credit amount may be carried forward to the next succeeding year for

318

Household Vehicles Energy Use: Latest Data & Trends  

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

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

319

Household Vehicles Energy Use: Latest Data & Trends  

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

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

320

Household Vehicles Energy Use: Latest Data & Trends  

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

B B : E S T I M AT I O N M E T H O D O L O G I E S APPENDIX B A P P E N D I X B ESTIMATION METHODOLOGIES INTRODUCTION The National Household Travel Survey (NHTS) is the nation's inventory of local and long distance travel, according to the U.S. Department of Transportation. Between April 2001 and May 2002, roughly 26 thousand households 41 were interviewed about their travel, based on the use of over 53 thousand vehicles. Using confidential data collected during those interviews, coupled with EIA's retail fuel prices, external data sources of test 42 fuel economy, and internal procedures for modifying test fuel economy to on-road, in-use fuel economy, EIA has extended this inventory to include the energy used for travel, thereby continuing a data series that was discontinued by EIA in 1994. This appendix presents the methods used for each eligible sampled

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

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

322

Energy conservation for household refrigerators and water heaters  

Science Conference Proceedings (OSTI)

An energy conservation arrangement for household refrigerators and water heaters, in which the source of cold water to the hot water heater is divided and part is caused to flow through and be warmed in the condenser of the refrigerator. The warmed water is then further heated in the oil cooling loop of the refrigerator compressor, and proceeds then to the top of the hot water tank.

Speicher, T. L.

1984-12-11T23:59:59.000Z

323

Sizing Wind/Photovoltaic Hybrids for Households in Inner Mongolia  

DOE Green Energy (OSTI)

Approximately 140,000 wind turbines currently provide electricity to about one-third of the non-grid-connected households in Inner Mongolia. However, these households often suffer from a lack of power during the low-wind summer months. This report describes an analysis of hybrid wind/photovoltaic (PV) systems for such households. The sizing of the major components is based on a subjective trade-off between the cost of the system and the percent unmet load, as determined by the Hybrid 2 software in conjunction with a simplified time-series model. Actual resource data (wind speed and solar radiation) from the region are processed so as to best represent the scenarios of interest. Small wind turbines of both Chinese and U.S. manufacture are considered in the designs. The results indicate that combinations of wind and PV are more cost-effective than either one alone, and that the relative amount of PV in the design increases as the acceptable unmet load decreases and as the average wind sp eed decreases.

Barley, C. D.; Lew, D. J.; Flowers, L. T.

1997-06-01T23:59:59.000Z

324

States fund an expanded range of activities under low-income home energy assistance block grant  

SciTech Connect

The low-income home energy assistance (LIHEA) block grant expanded states' flexibility and authority and permitted funds to be used for a broader range of activities not previously permitted. Unlike other block grants created under the Omnibus Budget Reconciliation Act of 1981, LIHEA received increased appropriations over the level established for the prior program to assist eligible households in meeting the costs of home energy. While heating assistance continued to account for the bulk of expenditures in most states, the majority of the 13 states GAO visited used their new authority to provide weatherization, transfer energy assistance funds to other block grants, and carry over funds to the following year. In addition, states gave increased emphasis to energy crisis assistance. Few changes were made to program management procedures. Overall, state executive and legislative branch officials found the block grant less burdensome and more desirable than the prior program. However, about half the interest groups viewed the block grant as a less desirable method of funding energy assistance programs.

Not Available

1984-06-27T23:59:59.000Z

325

Measurement and Verification of Low Income Energy Efficiency Programs in  

Open Energy Info (EERE)

Measurement and Verification of Low Income Energy Efficiency Programs in Measurement and Verification of Low Income Energy Efficiency Programs in Brazil: Methodological Challenges Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Measurement and Verification of Low Income Energy Efficiency Programs in Brazil: Methodological Challenges Focus Area: Energy Efficiency Topics: Socio-Economic Website: www.eceee.org/conference_proceedings/eceee/2009/Panel_3/3.049/ Equivalent URI: cleanenergysolutions.org/content/measurement-and-verification-low-inco Language: English Policies: "Regulations,Financial Incentives" is not in the list of possible values (Deployment Programs, Financial Incentives, Regulations) for this property. Regulations: Feebates This report presents results from Brazilian electric utilities evaluation

326

Income Tax Credits Program (Arkansas) | Department of Energy  

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

Income Tax Credits Program (Arkansas) Income Tax Credits Program (Arkansas) Income Tax Credits Program (Arkansas) < Back Eligibility Agricultural Commercial Construction Developer Fuel Distributor Industrial Installer/Contractor Institutional Investor-Owned Utility Rural Electric Cooperative Systems Integrator Utility Savings Category Alternative Fuel Vehicles Hydrogen & Fuel Cells Buying & Making Electricity Water Home Weatherization Solar Wind Program Info State Arkansas Program Type Personal Tax Incentives Corporate Tax Incentive Rebate Program Provider Department of Economic Develoment There are multiple tax credit programs for businesses new to Arkansas. Additionally, there are investment tax credit programs, job creation incentives, discretionary incentives, and targeted business incentives,

327

Domestic Hot Water Consumption in Four Low-Income Apartment Buildings  

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

Domestic Hot Water Consumption in Four Low-Income Apartment Buildings Title Domestic Hot Water Consumption in Four Low-Income Apartment Buildings Publication Type Conference...

328

The Farmer's Conundrum: Income from Biofuels or Protect the Soil? |  

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

The Farmer's Conundrum: Income from Biofuels or Protect the Soil? The Farmer's Conundrum: Income from Biofuels or Protect the Soil? The Farmer's Conundrum: Income from Biofuels or Protect the Soil? July 1, 2010 - 11:39am Addthis Lindsay Gsell After a harvest is over, crops can be sold, shipped, canned or consumed. But what happens to the parts of the crops that are inedible-the corn stover, stalks or cobs? Selling crop residues for bioenergy could provide farmers with an extra source of income. Yet, leaving some residue on the fields helps reduce soil erosion and maintain healthy levels of soil carbon and other nutrients. So how can land managers find this balance? Idaho National Laboratory (INL) is developing the Residue Removal Tool -- new software designed to simulate sustainability criteria -- to help find this balance of what to remove and what to leave behind. The software will

329

Income and Health Spending: Evidence from Oil Price Shocks  

E-Print Network (OSTI)

Health expenditures as a share of GDP in the United States have more than tripled over the past half-century. A common conjecture is that this is a consequence of rising income. We investigate this hypothesis by instrumenting ...

Acemoglu, Daron

330

EmPOWER Maryland Low Income Energy Efficiency Program (Maryland) |  

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

EmPOWER Maryland Low Income Energy Efficiency Program (Maryland) EmPOWER Maryland Low Income Energy Efficiency Program (Maryland) EmPOWER Maryland Low Income Energy Efficiency Program (Maryland) < Back Eligibility Low-Income Residential Savings Category Home Weatherization Commercial Weatherization Other Heating & Cooling Commercial Heating & Cooling Heating Appliances & Electronics Commercial Lighting Lighting Water Heating Program Info Funding Source EmPOWER Maryland State Maryland Program Type State Rebate Program Rebate Amount Direct installation, no cost to the recipient Provider Maryland Department of Housing and Community Development Note: The eligible technologies listed above are only examples of some improvements that might be supported under this program as detailed on the program web site. Not all potentially eligible improvements will be

331

Weatherization Assistance for Low-Income Persons: Maintaining the Privacy  

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

Weatherization Assistance for Low-Income Persons: Maintaining the Weatherization Assistance for Low-Income Persons: Maintaining the Privacy of Applicants for and Recipients of Services Weatherization Assistance for Low-Income Persons: Maintaining the Privacy of Applicants for and Recipients of Services Amending regulations to require all States and other service providers that participate in the Weatherization Assistance Program (WAP) to treat all requests for information concerning applicants and recipients of WAP funds in a manner consistent with the Federal government's treatment of information requested under the Freedom of Information Act (FOIA), 5 U.S.C. 552, including the privacy protections contained in Exemption (b)(6) of the FOIA, 5 U.S.C. 552(b)(6). Weatherization Assistance for Low-Income Persons: Maintaining the Privacy

332

Xcel Energy - Residential and Low Income Home Energy Service | Department  

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

Xcel Energy - Residential and Low Income Home Energy Service Xcel Energy - Residential and Low Income Home Energy Service Xcel Energy - Residential and Low Income Home Energy Service < Back Eligibility Installer/Contractor Low-Income Residential Multi-Family Residential Residential Savings Category Home Weatherization Commercial Weatherization Heating & Cooling Commercial Heating & Cooling Cooling Other Sealing Your Home Ventilation Heat Pumps Appliances & Electronics Commercial Lighting Lighting Water Heating Windows, Doors, & Skylights Program Info Start Date 1/1/2011 Expiration Date 12/31/2012 State New Mexico Program Type Utility Rebate Program Rebate Amount Evaporative Cooling: $200-$1000/unit Saver's Switch A/C Cycling: $20/ton of enrolled air conditioning Refrigerator Recycling: $75 CFLs: $1/bulb LED's: $10/bulb

333

Figure ES2. Annual Indices of Real Disposable Income, Vehicle...  

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

ES2 Figure ES2. Annual Indices of Real Disposable Income, Vehicle-Miles Traveled, Consumer Price Index (CPI-U), and Real Average Retail Gasoline Price, 1978-2004, 1985100...

334

Buildings Energy Data Book: 2.9 Low-Income Housing  

Buildings Energy Data Book (EERE)

0 2005 Average Energy Expenditures per Household Member and per Square Foot, by Weatherization Eligibility (2010) Members Hhold Hhold Total U.S. Households 780 2.6 0.86 Federally...

335

Indoor Secondary Pollutants from Household Product Emissions in the  

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

Indoor Secondary Pollutants from Household Product Emissions in the Indoor Secondary Pollutants from Household Product Emissions in the Presence of Ozone: A Bench-Scale Chamber Study Title Indoor Secondary Pollutants from Household Product Emissions in the Presence of Ozone: A Bench-Scale Chamber Study Publication Type Journal Article LBNL Report Number LBNL-58785 Year of Publication 2006 Authors Destaillats, Hugo, Melissa M. Lunden, Brett C. Singer, Beverly K. Coleman, Alfred T. Hodgson, Charles J. Weschler, and William W. Nazaroff Journal Environmental Science and Technology Volume 40 Start Page Chapter Pagination 4421-4428 Abstract Ozone-driven chemistry is a major source of indoor secondary pollutants of health concern. This study investigates secondary air pollutants formed from reactions between constituents of household products and ozone. Gas-phase product emissions were introduced along with ozone at constant rates into a 198-L Teflon-lined reaction chamber. Gas-phase concentrations of reactive terpenoids and oxidation products were measured. Formaldehyde was a predominant oxidation byproduct for the three studied products, with yields under most conditions of 20-30% with respect to ozone consumed. Acetaldehyde, acetone, glycolaldehyde, formic acid and acetic acid were each also detected for two or three of the products. Immediately upon mixing of reactants, a scanning mobility particle sizer detected particle nucleation events that were followed by a significant degree of ultrafine particle growth. The production of secondary gaseous pollutants and particles depended primarily on the ozone level and was influenced by other parameters such as the air-exchange rate. Hydroxyl radical concentrations in the range 0.04-200 × 105 molecules cm-3 were measured. OH concentrations were observed to vary strongly with residual ozone level in the chamber, which was in the range 1 - 25 ppb, as is consistent with expectations from a simplified kinetic model. In a separate test, we exposed the dry residue of two products to ozone in the chamber and observed the formation of gas-phase and particle-phase secondary oxidation products

336

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

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

1: January 5, 1: January 5, 2004 Number of Household Vehicles has Grown Significantly to someone by E-mail Share Vehicle Technologies Office: Fact #301: January 5, 2004 Number of Household Vehicles has Grown Significantly on Facebook Tweet about Vehicle Technologies Office: Fact #301: January 5, 2004 Number of Household Vehicles has Grown Significantly on Twitter Bookmark Vehicle Technologies Office: Fact #301: January 5, 2004 Number of Household Vehicles has Grown Significantly on Google Bookmark Vehicle Technologies Office: Fact #301: January 5, 2004 Number of Household Vehicles has Grown Significantly on Delicious Rank Vehicle Technologies Office: Fact #301: January 5, 2004 Number of Household Vehicles has Grown Significantly on Digg Find More places to share Vehicle Technologies Office: Fact #301:

337

Exemplifying Business Opportunities for Improving Data Quality From Corporate Household Research  

E-Print Network (OSTI)

Corporate household (CHH) refers to the organizational information about the structure within the corporation and a variety of inter-organizational relationships. Knowledge derived from this data is ...

Madnick, Stuart

2004-12-10T23:59:59.000Z

338

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 ...

339

Methodology and Estimation of the Welfare Impact of Energy Reforms on Households in Azerbaijan.  

E-Print Network (OSTI)

??ABSTRACT Title of Dissertation: METHODOLOGY AND ESTIMATION OF THE WELFARE IMPACT OF ENERGY REFORMS ON HOUSEHOLDS IN AZERBAIJAN Irina Klytchnikova, Doctor of Philosophy, 2006 Dissertation… (more)

Klytchnikova, Irina

2006-01-01T23:59:59.000Z

340

Table CE1-4c. Total Energy Consumption in U.S. Households by Type ...  

U.S. Energy Information Administration (EIA)

Total Energy Consumption in U.S. Households by Type of Housing Unit, 2001 RSE Column Factor: Total ... where the end use is electric air-conditioning, ...

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

The Other Energy Crisis: Managing Urban Household Energy Use in Senegal  

E-Print Network (OSTI)

for 62 percent of national energy consumption, or over 1 .1energy consumption, and (2) residential, because of the dominant role that households play in national

Leitmann, Josef

1989-01-01T23:59:59.000Z

342

Table HC6.7 Air-Conditioning Usage Indicators by Number of Household...  

Gasoline and Diesel Fuel Update (EIA)

7 Air-Conditioning Usage Indicators by Number of Household Members, 2005 Total... 111.1 30.0 34.8 18.4 15.9...

343

Table 1. Consumption and Expenditures in U.S. Households, 1997  

U.S. Energy Information Administration (EIA)

A household is assigned to a climate zone according to the 30-year average annual degree-days for an appropriate nearby weather station. (5) ...

344

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 ...

345

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 ...

346

Table WH2. Total Households by Water Heating Fuels Used, 2005 ...  

U.S. Energy Information Administration (EIA)

Total Households by Water Heating Fuels Used, 2005 ... 2005 Residential Energy Consumption Survey: Energy Consumption and Expenditures Tables. Table WH2.

347

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

Science Conference Proceedings (OSTI)

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

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

1987-01-01T23:59:59.000Z

348

Table CE1-7c. Total Energy Consumption in U.S. Households by Four ...  

U.S. Energy Information Administration (EIA)

Other Appliances and Lighting ... It does include the small number of households where the fuel for central air-conditioning equipment was something other than ...

349

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

U.S. Energy Information Administration (EIA)

U.S. Per Household Vehicle-Miles Traveled ... and Alternate Fuels, Form EIA-826, "Monthly Electric Utility Sales and Revenue Report with State Distributions."

350

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

U.S. Energy Information Administration (EIA)

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

351

Testing Electric Vehicle Demand in "Hybrid Households" Using a Reflexive Survey  

E-Print Network (OSTI)

In contrast to a hybrid vehicle whichcombines multiple1994) "Demand Electric Vehicles in Hybrid for Households:or 180 mile hybrid electric vehicle. Natural gas vehicles (

Kurani, Kenneth S.; Turrentine, Thomas; Sperling, Daniel

2001-01-01T23:59:59.000Z

352

The impact of physical planning policy on household energy use and greenhouse emissions .  

E-Print Network (OSTI)

??This thesis investigates the impact of physical planning policy on combined transport and dwelling-related energy use by households. Separate analyses and reviews are conducted into… (more)

Rickwood, Peter

353

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

354

Table SH2. Total Households by Space Heating Fuels Used, 2005 ...  

U.S. Energy Information Administration (EIA)

Total Households by Space Heating Fuels Used, 2005 ... 2005 Residential Energy Consumption Survey: ... Electricity Natural Gas Fuel Oil Kerosene LPG Other

355

Table 2. Fuel Oil Consumption and Expeditures in U.S. Households ...  

U.S. Energy Information Administration (EIA)

Fuel Oil Consumption and Expeditures in U.S. Households ... Space Heating - Main or Secondary ... Forms EIA-457 A-G of the 2001 Residential Energy Consumption

356

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

U.S. Energy Information Administration (EIA)

Electricity. Sales, revenue and prices, power plants, fuel use, ... a rise in average gasoline prices has led to higher overall household gasoline expenditures.

357

Assessing the Environmental Costs and Benefits of Households Electricity Consumption Management.  

E-Print Network (OSTI)

?? In this study the environmental costs and benefits of smart metering technology systems installed in households in Norway have been assessed. Smart metering technology… (more)

Segtnan, Ida Lund

2011-01-01T23:59:59.000Z

358

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

E-Print Network (OSTI)

and V. Letschert (2005). Forecasting Electricity Demand in8364 Material World: Forecasting Household ApplianceMcNeil, 2008). Forecasting Diffusion Forecasting Variables

Letschert, Virginie

2010-01-01T23:59:59.000Z

359

An Analysis of the Price Elasticity of Demand for Household Appliances  

E-Print Network (OSTI)

Refrigerators Clothes Washers Dishwashers Economic VariablesWASHERS, AND DISHWASHERS……………………………3 Physical Household andclothes washers and dishwashers. In the context of

Dale, Larry

2008-01-01T23:59:59.000Z

360

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 ...

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

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

SciTech Connect

In this paper a descriptive analysis of the relationship between energy consumption, patterns of energy use, and housing stock variables is presented. The purpose of the analysis is to uncover evidence of variations in energy consumption and expenditures, and patterns of energy use between majority households (defines as households with neither a black nor Hispanic head of household), black households (defined as households with a black head of household), and Hispanic households (defined as households with a Hispanic head of household) between 1980 (time of the first DOE/EIA Residential Energy Consumption Survey, 1982a) and 1987 (time of the last DOE/EIA Residential Energy Consumption Survey, 1989a). The analysis is three-dimensional: energy consumption and expenditures are presented by time (1980 to 1987), housing vintage, and housing type. A comparative analysis of changes in energy variables for the three population groups -- majority, black, and Hispanic -- within and between specific housing stock categories is presented.

Poyer, D.A.

1992-01-01T23:59:59.000Z

362

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

SciTech Connect

In this paper a descriptive analysis of the relationship between energy consumption, patterns of energy use, and housing stock variables is presented. The purpose of the analysis is to uncover evidence of variations in energy consumption and expenditures, and patterns of energy use between majority households (defines as households with neither a black nor Hispanic head of household), black households (defined as households with a black head of household), and Hispanic households (defined as households with a Hispanic head of household) between 1980 (time of the first DOE/EIA Residential Energy Consumption Survey, 1982a) and 1987 (time of the last DOE/EIA Residential Energy Consumption Survey, 1989a). The analysis is three-dimensional: energy consumption and expenditures are presented by time (1980 to 1987), housing vintage, and housing type. A comparative analysis of changes in energy variables for the three population groups -- majority, black, and Hispanic -- within and between specific housing stock categories is presented.

Poyer, D.A.

1992-06-01T23:59:59.000Z

363

Approaches to Electric Utility Energy Efficiency for Low Income Customers  

Open Energy Info (EERE)

Approaches to Electric Utility Energy Efficiency for Low Income Customers Approaches to Electric Utility Energy Efficiency for Low Income Customers in a Changing Regulatory Environment Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Approaches to Electric Utility Energy Efficiency for Low Income Customers in a Changing Regulatory Environment Focus Area: Energy Efficiency Topics: Best Practices Website: www.ornl.gov/~webworks/cppr/y2001/misc/99601.pdf Equivalent URI: cleanenergysolutions.org/content/approaches-electric-utility-energy-ef Language: English Policies: "Regulations,Financial Incentives" is not in the list of possible values (Deployment Programs, Financial Incentives, Regulations) for this property. Regulations: Feebates This report, written for members of the Weatherization Assistance Program

364

Users and households appliances: design suggestions for a better, sustainable interaction  

Science Conference Proceedings (OSTI)

The Human Machine Interaction has a big role in the user approach with households appliances. During the main phase (the use one), users are called to manage energy choices, often without available efficient information regarding the best behavior they ... Keywords: energy saving, households appliances, interaction design, interfaces, sustainability

Anna Zandanel

2011-09-01T23:59:59.000Z

365

A Comprehensive Model for Evaluation of Carbon Footprint and Greenhouse Gages Emission in Household Biogas Plants  

Science Conference Proceedings (OSTI)

Based on Life Cycle Assessment and other related methods, this paper introduced a comprehensive model for the evaluation of the carbon footprint and greenhouse gases emission in household biogas plants including nearly all the processes of the household ... Keywords: Biogas Plant, Carbon Footprint, Life Cycle, Greenhouse Gas

Jie Zhou; Shubiao Wu; Wanqin Zhang; Changle Pang; Baozhi Wang; Renjie Dong; Li Chen

2012-07-01T23:59:59.000Z

366

An examination of how households share and coordinate the completion of errands  

Science Conference Proceedings (OSTI)

People often complete tasks and to-dos not only for themselves but also for others in their household. In this work, we examine how household members share and accomplish errands both individually and together. We conducted a three-week diary study with ... Keywords: cooperative errands, coordination, families, roommates

Timothy Sohn; Lorikeet Lee; Stephanie Zhang; David Dearman; Khai Truong

2012-02-01T23:59:59.000Z

367

A spotlight on security and privacy risks with future household robots: attacks and lessons  

Science Conference Proceedings (OSTI)

Future homes will be populated with large numbers of robots with diverse functionalities, ranging from chore robots to elder care robots to entertainment robots. While household robots will offer numerous benefits, they also have the potential to introduce ... Keywords: cyber-physical systems, domestic robots, household robots, multi-robot attack, privacy, robots, security, single-robot attack, ubiquitous robots

Tamara Denning; Cynthia Matuszek; Karl Koscher; Joshua R. Smith; Tadayoshi Kohno

2009-09-01T23:59:59.000Z

368

Household Vehicles Energy Use: Latest Data & Trends  

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

C C : Q U A L I T Y O F T H E D ATA APPENDIX C A P P E N D I X C QUALITY OF THE DATA INTRODUCTION This section discusses several issues relating to the quality of the National Household Travel Survey (NHTS) data and to the interpretation of conclusions based on these data. In particular, the focus of our discussion is on the quality of specific data items, such as the fuel economy and fuel type, that were imputed to the NHTS via a cold-decking imputation procedure. This imputation procedure used vehicle-level information from the NHTSA Corporate Average Fuel Economy files for model year's 1978 through 2001. It is nearly impossible to quantify directly the quality of this imputation procedure because NHTS does not collect the necessary fuel economy information for comparison. At best, we have indirect evidence on the quality of our

369

Load Component Database of Household Appliances and Small Office Equipment  

Science Conference Proceedings (OSTI)

This paper discusses the development of a load component database for household appliances and office equipment. To develop more accurate load models at both transmission and distribution level, a better understanding on the individual behaviors of home appliances and office equipment under power system voltage and frequency variations becomes more and more critical. Bonneville Power Administration (BPA) has begun a series of voltage and frequency tests against home appliances and office equipments since 2005. Since 2006, Researchers at Pacific Northwest National Laboratory has collaborated with BPA personnel and developed a load component database based on these appliance testing results to facilitate the load model validation work for the Western Electricity Coordinating Council (WECC). In this paper, the testing procedure and testing results are first presented. The load model parameters are then derived and grouped. Recommendations are given for aggregating the individual appliance models to feeder level, the models of which are used for distribution and transmission level studies.

Lu, Ning; Xie, YuLong; Huang, Zhenyu; Puyleart, Francis; Yang, Steve

2008-07-24T23:59:59.000Z

370

Investigating the impacts of time-of-use electricity rates on lower-income and senior-headed households: A case study of Milton, Ontario (Canada).  

E-Print Network (OSTI)

??Through the Smart Metering Initiative in the Canadian province of Ontario, all residential electricity customers will be converted from a tiered rate regime to a… (more)

Simmons, Sarah Ivy

2010-01-01T23:59:59.000Z

371

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

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

Do You Encourage Everyone in Your Household to Save Energy? Do You Encourage Everyone in Your Household to Save Energy? How Do You Encourage Everyone in Your Household to Save Energy? June 18, 2009 - 5:25pm Addthis Anyone who has decided to save energy at home knows that the entire household needs to be involved if you really want to see savings. Some people-be they roommates, spouses, children, or maybe even yourself-just seem to need some extra reminders to take simple energy-saving steps. How do you encourage everyone in your household to save energy? Each Thursday, you have the chance to share your thoughts on a topic related to energy efficiency or renewable energy for consumers. Please comment with your answers, and also feel free to respond to other comments. Addthis Related Articles How Have You Helped Someone Else Save Energy?

372

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

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

Everyone in Your Household to Save Energy? Everyone in Your Household to Save Energy? How Do You Encourage Everyone in Your Household to Save Energy? June 18, 2009 - 5:25pm Addthis Anyone who has decided to save energy at home knows that the entire household needs to be involved if you really want to see savings. Some people-be they roommates, spouses, children, or maybe even yourself-just seem to need some extra reminders to take simple energy-saving steps. How do you encourage everyone in your household to save energy? Each Thursday, you have the chance to share your thoughts on a topic related to energy efficiency or renewable energy for consumers. Please comment with your answers, and also feel free to respond to other comments. Addthis Related Articles How Have You Helped Someone Else Save Energy?

373

Oil Prices, External Income, and Growth: Lessons from Jordan  

E-Print Network (OSTI)

This paper extends the long-run growth model of Esfahani et al. (2012a) to a labour exporting country that receives large in‡ows of external income – the sum of remittances, FDI and general government transfers – from major oil exporting economies. The theoretical model predicts real oil prices to be one of the main long-run drivers of real output. Using quarterly data between 1979 and 2009 on core macroeconomic variables for Jordan and a number of key foreign variables, we identify two long-run relationships: an output equation as predicted by theory and an equation linking foreign and domestic in‡ation rates. It is shown that real output in the long run is shaped by (i) oil prices through their impact on external income and in turn on capital accumulation, and (ii) technological transfers through foreign output. The empirical analysis of the paper con…rms the hypothesis that a large share of Jordan’s output volatility can be associated with ‡uctuations in net income received from abroad (arising from oil price shocks). External factors, however, cannot be relied upon to provide similar growth stimuli in the future, and therefore it will be important to diversify the sources of growth in order to achieve a high and sustained level of income.

Kamiar Mohaddes A; Mehdi Raissi B

2013-01-01T23:59:59.000Z

374

Controlling incoming connections using certificates and distributed hash tables  

Science Conference Proceedings (OSTI)

The current architecture of the Internet where anyone can send anything to anybody presents many problems. The recipient of the connection might be using a mobile access network and thus unwanted incoming connections could produce a high cost to the ... Keywords: DoS countermeasures, certificates, rights delegation, rights management, session management

Dmitrij Lagutin; Hannu H. Kari

2007-09-01T23:59:59.000Z

375

Household Projection and Its Application to Health/Long-Term Care Expenditures in Japan Using INAHSIM-II  

Science Conference Proceedings (OSTI)

Using a microsimulation model named Integrated Analytical Model for Household Simulation (INAHSIM), the author conducted a household projection in Japan for the period of 2010â??2050. INAHSIM-II specifically means that the initial population is ... Keywords: dynamic micro simulation, health expenditure, household projection, initial population, long-term care expenditure, transition probabilities

Tetsuo Fukawa

2011-02-01T23:59:59.000Z

376

Juanita's Money Order: Income Effects on Human Capital Investment in Mexico  

E-Print Network (OSTI)

Desarrollo Social Juanita’s Money Order: Income Effects onAvellaneda, 2005. Juanita’s Money Order: Income E?ects on13 Vice expenditures include money spent on alcohol and

Suarez, Juan Carlos; Avellaneda, Zenide

2007-01-01T23:59:59.000Z

377

"Shelter within my reach" : medium rise apartment housing for the middle income group in Karachi, Pakistan  

E-Print Network (OSTI)

This thesis identifies the project development processes of medium rise (five storied or less) apartment housing built by the private formal sector, catering to the middle income groups in Karachi, Pakistan. Middle income ...

Mahmood, Saman, 1972-

1999-01-01T23:59:59.000Z

378

55,"Aberdeen City of",5,1,482619,"Taxes Other Than Income Taxes...  

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

Services to Municipality or Other Government Units (line 14, less line 19)" 13523,"Newberry City of",5,1,0,"Taxes Other Than Income Taxes, Operating Income (408.1)"...

379

55,"Aberdeen City of",5,1,479437,"Taxes Other Than Income Taxes...  

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

Services to Municipality or Other Government Units (line 14, less line 19)" 13523,"Newberry City of",5,1,0,"Taxes Other Than Income Taxes, Operating Income (408.1)"...

380

Special Topics on Energy Use in Household Transportation  

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

Home Page Welcome to the Energy Information Administration's Residential Transportation Energy Consumption Home Page. If you need assistance in viewing this page, please call (202) 586-8800 Home Page Welcome to the Energy Information Administration's Residential Transportation Energy Consumption Home Page. If you need assistance in viewing this page, please call (202) 586-8800 Home > Transportation Home Page > Special Topics Special Topics Change in Method for Estimating Fuel Economy for the 1988 and subsequent RTECS (Released 09/12/2000) Can Household Members Accurately Report How Many Miles Their Vehicles Are Driven? (Released 08/03/2000) Calculate your Regional Gasoline Costs of Driving using the “Transportation Calculator” updated for new model years! Choose your car or SUV and see the gasoline part of the cost of driving in various parts of the country using EIA's current weekly prices. This application uses DOE/EPA's Fuel Economy Guide to set the MPG, but you can change it to compare your estimate of your car's mpg to the average of everyone else who takes the test. (Released 04/11/2000; Updated Yearly for Fuel Economies and Weekly for Fuel Prices)

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

Household appliance choice: revision of REEPS behavioral models. Final report  

Science Conference Proceedings (OSTI)

This report describes the analysis of household decisions to install space heating, central cooling, and water heating in new housing as well as decisions to own freezers and second refrigerators. This analysis was conducted as part of the enhancements to the Residential End-Use Energy Planning System (REEPS) under EPRI project RP1918-1. The empirical models used in this analysis were the multinomial logit and its generalization the nested logit. The choice model parameters were estimated statistically on national and regional survey data. The results show that capital and operating costs are significant determinants of appliance market penetrations, and the relative magnitudes of the cost coefficients imply discount rates ranging from 3.4 to twenty-one percent. Several tests were conducted to examine the temporal and geographical stability of the key parameters. The estimated parameters have been incorporated into the REEPS computer code. The revised version of REEPS is now available on a limited release basis to EPRI member utilities for testing on their system.

Goett, A.A.

1984-02-01T23:59:59.000Z

382

A Reliable Natural Language Interface to Household Appliances  

E-Print Network (OSTI)

“I have always wished that my computer would be as easy to use as my telephone. My wish has come true. I no longer know how to use my telephone.” – Bjarne Stroustrop (originator of C++) As household appliances grow in complexity and sophistication, they become harder and harder to use, particularly because of their tiny display screens and limited keyboards. This paper describes a strategy for building natural language interfaces to appliances that circumvents these problems. Our approach leverages decades of research on planning and natural language interfaces to databases by reducing the appliance problem to the database problem; the reduction provably maintains desirable properties of the database interface. The paper goes on to describe the implementation and evaluation of the EXACT interface to appliances, which is based on this reduction. EXACT maps each English user request to an SQL query, which is transformed to create a PDDL goal, and uses the Blackbox planner [13] to map the planning problem to a sequence of appliance commands that satisfy the original request. Both theoretical arguments and experimental evaluation show that EXACT is highly reliable.

Alexander Yates

2003-01-01T23:59:59.000Z

383

Laboratory Testing of Demand-Response Enabled Household Appliances  

SciTech Connect

With the advent of the Advanced Metering Infrastructure (AMI) systems capable of two-way communications between the utility's grid and the building, there has been significant effort in the Automated Home Energy Management (AHEM) industry to develop capabilities that allow residential building systems to respond to utility demand events by temporarily reducing their electricity usage. Major appliance manufacturers are following suit by developing Home Area Network (HAN)-tied appliance suites that can take signals from the home's 'smart meter,' a.k.a. AMI meter, and adjust their run cycles accordingly. There are numerous strategies that can be employed by household appliances to respond to demand-side management opportunities, and they could result in substantial reductions in electricity bills for the residents depending on the pricing structures used by the utilities to incent these types of responses.The first step to quantifying these end effects is to test these systems and their responses in simulated demand-response (DR) conditions while monitoring energy use and overall system performance.

Sparn, B.; Jin, X.; Earle, L.

2013-10-01T23:59:59.000Z

384

Table CE3-3e. Electric Air-Conditioning Energy Expenditures in U.S ...  

U.S. Energy Information Administration (EIA)

Electric Air-Conditioning Energy Expenditures in U.S. Households by Household Income, 2001 RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli-

385

Monetary Policy and Household Mobility: The Effects of Mortgage Interest Rats.  

E-Print Network (OSTI)

Homeowner Mobility and Mortgage Interest Rates: New Evidencenew mortgages. Table 2 Basic Hazard Models of Household Mobility (mobility decisions are related to increases in family size, the existence of a new

Quigley, John M.

2005-01-01T23:59:59.000Z

386

Seasonality, precautionary savings and health uncertainty: Evidence from farm households in Central Kenya  

E-Print Network (OSTI)

on rural households in Kenya." World Development 32(1):91-Second report on poverty in Kenya. Incidence and depth ofPlanning. Government of Kenya. —. 2004. "Kenya Demographic

Ndirangu, Lydia; Burger, Kees; Moll, Hank A.J.; Kuyvenhoven, Arie

2009-01-01T23:59:59.000Z

387

Trends in the Use of Natural Gas in U.S. Households, 1987 to 2001  

U.S. Energy Information Administration (EIA)

used, the RECS is ideal as a data source so as to reveal the underlying factors behind the trends in energy demand--and in this paper, household natural gas demand.

388

The Design and Implementation of a Corporate Householding Knowledge Processor to Improve Data Quality  

E-Print Network (OSTI)

Advances in Corporate Householding are needed to address certain categories of data quality problems caused by data misinterpretation. In this paper, we first summarize some of these data quality problems and our more ...

Madnick, Stuart

2004-02-06T23:59:59.000Z

389

Table CE1-4c. Total Energy Consumption in U.S. Households by Type ...  

U.S. Energy Information Administration (EIA)

Table CE1-4c. Total Energy Consumption in U.S. Households by Type of Housing Unit, 1997 ... where the end use is electric air-conditioning, ...

390

Table CE1-1c. Total Energy Consumption in U.S. Households by ...  

U.S. Energy Information Administration (EIA)

Table CE1-1c. Total Energy Consumption in U.S. Households by Climate Zone, 2001 RSE Column Factor: Total Climate Zone1 RSE Row Factors Fewer than 2,000 CDD and --

391

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

U.S. Energy Information Administration (EIA)

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

392

10Tips to Spend Less on Household Goods Spend about $20 on a battery  

E-Print Network (OSTI)

10Tips to Spend Less on Household Goods Spend about $20 on a battery recharger. Over time, replace your used batteries with the kind you can use over and over again. 6 You can reuse plastic bags you get

Tullos, Desiree

393

Household water treatment and safe storage options for Northern Region Ghana : consumer preference and relative cost  

E-Print Network (OSTI)

A range of household water treatment and safe storage (HWTS) products are available in Northern Region Ghana which have the potential to significantly improve local drinking water quality. However, to date, the region has ...

Green, Vanessa (Vanessa Layton)

2008-01-01T23:59:59.000Z

394

Facts about FEMA Household Disaster Aid: Examining the 2008 Floods and Tornadoes in Missouri  

Science Conference Proceedings (OSTI)

Very little empirical work has been done on disaster aid in the United States. This paper examines postdisaster grants to households from the Federal Emergency Management Agency in the state of Missouri in 2008, when the state experienced flooding,...

Carolyn Kousky

2013-10-01T23:59:59.000Z

395

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

E-Print Network (OSTI)

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

Rausch, Sebastian

396

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

U.S. Energy Information Administration (EIA)

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

397

Table CE4-7c. Water-Heating Energy Consumption in U.S. Households ...  

U.S. Energy Information Administration (EIA)

Table CE4-7c. Water-Heating Energy Consumption in U.S. Households by Four Most Populated States, 1997 RSE Column Factor: Total U.S. Four Most Populated States

398

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

Science Conference Proceedings (OSTI)

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

Not Available

1983-02-01T23:59:59.000Z

399

Table CE2-7e. Space-Heating Energy Expenditures in U.S. Households ...  

U.S. Energy Information Administration (EIA)

Table CE2-7e. Space-Heating Energy Expenditures in U.S. Households by Four Most Populated States, 2001 RSE Column Factor: Total U.S. Four Most Populated States

400

Households to pay more than expected to stay warm this winter  

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

stay warm this winter Following a colder-than-expected November, U.S. households are forecast to consume more heating fuels than previously expected....resulting in higher heating...

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

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

402

Calculating economic indexes per household and censal section from official Spanish databases  

Science Conference Proceedings (OSTI)

In the competitive environments, in which all sorts of organisations move it is of utmost importance to have information about clients. Public databases offer information about households and families. However, the non-crossed and non-georeferenced format ...

Sonia Frutos; Ernestina Menasalvas; Cesar Montes; Javier Segovia

2003-12-01T23:59:59.000Z

403

California Immigrant Households and Public Assistance Participation in the 1990s - Detailed Research Findings  

E-Print Network (OSTI)

Seon Lee. 1999. “Transitions from AFDC to Child Welfare inHouseholds Receiving AFDC/TANF by Recency of Entry, 1993?Earnings for Those Receiving AFDC/TANF, Table 7. Proportion

2002-01-01T23:59:59.000Z

404

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

E-Print Network (OSTI)

or 180 mile hybrid electric vehicle. Natural gas vehicles (1994) Demand for Electric Vehicles in Hybrid Households: A nof Electric, Hybrid and Other Alternative Vehicles. A r t h

Kurani, Kenneth; Turrentine, Thomas; Sperling, Daniel

1996-01-01T23:59:59.000Z

405

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

Gasoline and Diesel Fuel Update (EIA)

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

406

Table CE5-2c. Appliances Energy Consumption in U.S. Households by ...  

U.S. Energy Information Administration (EIA)

Table CE5-2c. Appliances1 Energy Consumption in U.S. Households by Year of Construction, 2001 RSE Column Factor: Total Year of Construction RSE Row

407

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.

408

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

Science Conference Proceedings (OSTI)

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

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

2006-11-15T23:59:59.000Z

409

Overview of CFC replacement issues for household refrigeration  

Science Conference Proceedings (OSTI)

In 1974, the famous ozone depletion theory of Rowland and Molina claimed that chlorofluorocarbons (CFCs) diffuse into the stratosphere where they are broken down by photolysis to release chlorine atoms that catalytically destroy ozone. Although the understanding of the science is still imperfect, there is little doubt that CFCs play a major role in the Antarctic ozone hole phenomenon and the decline in ozone observed in the rest of the world. Another issue that has become increasingly important is the potential of CFCs to change the earth's temperature and to modify the climate. While the main impact in global warming is made by increased concentrations of carbon dioxide, CFCs and other trace gases also contribute to this effect. In an effort to respond to the global environmental threat, a CFC protocol was adopted during a diplomatic conference in Montreal. This document, known as the Montreal Protocol, was ratified in 1988 and put into effect on January 1, 1989. In accordance with Article 6 of the Montreal Protocol, the countries that signed the agreement shall periodically assess the control measures provided for in the Protocol. As part of that assessment process, household refrigeration was investigated to determine the status of CFC-12 replacements. The conclusion was that much progress has been made towards finding a suitable replacement. Compressors designed for HFC-134a have efficiencies comparable to those for CFC-12 and acceptable reliability tests have been obtained with ester lubricants. In addition, other replacements such as R-152a and refrigerant mixtures exist, but will require more study. Cycle options, such as the Stirling cycle, may be viable, but are further out in the future. The impact of new refrigerants is expected to result in elimination of CFC-12 consumption in developed countries by 1997 and in developing countries by 2005.

Vineyard, E.A. (Oak Ridge National Lab., TN (United States)); Roke, L. (Fisher and Paykel, Auckland (New Zealand)); Hallett, F. (Frigidaire, Washington, DC (United States))

1991-01-01T23:59:59.000Z

410

Overview of CFC replacement issues for household refrigeration  

Science Conference Proceedings (OSTI)

In 1974, the famous ozone depletion theory of Rowland and Molina claimed that chlorofluorocarbons (CFCs) diffuse into the stratosphere where they are broken down by photolysis to release chlorine atoms that catalytically destroy ozone. Although the understanding of the science is still imperfect, there is little doubt that CFCs play a major role in the Antarctic ozone hole phenomenon and the decline in ozone observed in the rest of the world. Another issue that has become increasingly important is the potential of CFCs to change the earth`s temperature and to modify the climate. While the main impact in global warming is made by increased concentrations of carbon dioxide, CFCs and other trace gases also contribute to this effect. In an effort to respond to the global environmental threat, a CFC protocol was adopted during a diplomatic conference in Montreal. This document, known as the Montreal Protocol, was ratified in 1988 and put into effect on January 1, 1989. In accordance with Article 6 of the Montreal Protocol, the countries that signed the agreement shall periodically assess the control measures provided for in the Protocol. As part of that assessment process, household refrigeration was investigated to determine the status of CFC-12 replacements. The conclusion was that much progress has been made towards finding a suitable replacement. Compressors designed for HFC-134a have efficiencies comparable to those for CFC-12 and acceptable reliability tests have been obtained with ester lubricants. In addition, other replacements such as R-152a and refrigerant mixtures exist, but will require more study. Cycle options, such as the Stirling cycle, may be viable, but are further out in the future. The impact of new refrigerants is expected to result in elimination of CFC-12 consumption in developed countries by 1997 and in developing countries by 2005.

Vineyard, E.A. [Oak Ridge National Lab., TN (United States); Roke, L. [Fisher and Paykel, Auckland (New Zealand); Hallett, F. [Frigidaire, Washington, DC (United States)

1991-12-31T23:59:59.000Z

411

California Solar Initiative - Low-Income Solar Water Heating Rebate Program  

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

You are here You are here Home » California Solar Initiative - Low-Income Solar Water Heating Rebate Program California Solar Initiative - Low-Income Solar Water Heating Rebate Program < Back Eligibility Low-Income Residential Multi-Family Residential Savings Category Heating & Cooling Solar Water Heating Maximum Rebate Single-Family Low-Income: $3,750 Multi-Family Low-Income: $500,000 Program Info Funding Source Ratepayer Funds Start Date 3/29/2012 State California Program Type State Rebate Program Rebate Amount Step 1 Incentive Rates (contact utility to determine current incentive levels): Single-Family Low-Income: $25.64 per therm displaced Multi-Family Low-Income: $19.23 per therm displaced The California Public Utilities Commission (CPUC) voted in October 2011 to

412

Income distribution impacts of climate change mitigation policy in the Susquehanna River Basin Economy  

SciTech Connect

We examine the cost-side income distribution impacts of a carbon tax in the Susquehanna River Basin (SRB) Region of the United States utilizing a computable general equilibrium model. We find the aggregate impacts of a $25/ton carbon tax on the SRB economy are likely to be negative but modest-an approximately one-third of 1% reduction in Gross Regional Product (GRP) in the short-run and double that amount in the long-run. However, unlike many previous studies, we find that the carbon tax is mildly progressive as measured by income bracket changes, per capita equivalent variation, and Gini coefficient changes based on expenditure patterns. The dominant factors affecting the distributional impacts are the pattern of output, income and consumption impacts that affect lower income groups relatively less than higher income ones, an increase in transfer payments favoring lower income groups, and decreased corporate profits absorbed primarily by higher income groups.

Oladosu, Gbadebo A [ORNL

2007-01-01T23:59:59.000Z

413

Decomposition of the price and income elasticities of the consumer demand for gasoline  

Science Conference Proceedings (OSTI)

The authors specify and estimate a model of the short-run demand for gasoline which allows them to decompose a consumer's gasoline demand elasticities into miles-driven and driving-efficiency components. Their model is estimated using detailed household survey data which allows direct focus on the short run, holding both the household's automobile stock and demographic profile fixed. Among the most interesting results are: (1) The data allow interesting insights to be drawn into the interrelationship between these important variables and household behavior with respect to gasoline consumption, miles driven, and driving efficiency. (2) The gasoline demand behavior of one-car and multi-car households differ significantly from each other. Evaluated at overall sample means, one-car households have higher (in absolute value) price elasticites for gasoline, miles driven and fuel-efficiency demand. Conversely, multi-car households have higher (in absolute value) total expenditure elasticities for each category. (3) For both one-car and multi-car households, roughly 75% of the estimated price elasticity and roughly 80% of the estimated total-expenditure elasticity of gasoline demand stem from the miles-driven component. The estimated fuel-efficiency elasticities, though smaller than their standard errors, indicate that households respond to changes in prices and total-expenditure levels not only by changing the number of miles they drive, but also by changing the efficiency with which they drive them. 23 references, 3 tables.

Archibald, R. (College of William and Mary, Williamsburg, VA); Gillingham, R.

1981-04-01T23:59:59.000Z

414

Greenhouse gas emissions from home composting of organic household waste  

Science Conference Proceedings (OSTI)

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

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

2010-12-15T23:59:59.000Z

415

Evaluating the income and employment impacts of gas cooling technologies  

SciTech Connect

The purpose of this study is to estimate the potential employment and income benefits of the emerging market for gas cooling products. The emphasis here is on exports because that is the major opportunity for the U.S. heating, ventilating, and air-conditioning (HVAC) industry. But domestic markets are also important and considered here because without a significant domestic market, it is unlikely that the plant investments, jobs, and income associated with gas cooling exports would be retained within the United States. The prospects for significant gas cooling exports appear promising for a variety of reasons. There is an expanding need for cooling in the developing world, natural gas is widely available, electric infrastructures are over-stressed in many areas, and the cost of building new gas infrastructure is modest compared to the cost of new electric infrastructure. Global gas cooling competition is currently limited, with Japanese and U.S. companies, and their foreign business partners, the only product sources. U.S. manufacturers of HVAC products are well positioned to compete globally, and are already one of the faster growing goods-exporting sectors of the U.S. economy. Net HVAC exports grew by over 800 percent from 1987 to 1992 and currently exceed $2.6 billion annually (ARI 1994). Net gas cooling job and income creation are estimated using an economic input-output model to compare a reference case to a gas cooling scenario. The reference case reflects current policies, practices, and trends with respect to conventional electric cooling technologies. The gas cooling scenario examines the impact of accelerated use of natural gas cooling technologies here and abroad.

Hughes, P.J. [Oak Ridge National Lab., TN (United States); Laitner, S.

1995-03-01T23:59:59.000Z

416

Assumptions to the Annual Energy Outlook 1999 - Commercial Demand...  

Annual Energy Outlook 2012 (EIA)

household.gif (5637 bytes) The Household Expenditures Module (HEM) constructs household energy expenditure profiles using historical survey data on household income, population and...

417

Low Impact, Affordable, Low Income Houses for Mexico  

E-Print Network (OSTI)

This paper discusses an effort to develop low impact, affordable, low income houses for Mexico. Low impact houses are defined as houses with energy and water needs that are substantially reduced below levels corresponding to code compliance. This paper includes an analysis of the population and energy consumption of the different climate regions in Mexico (Hot-Dry Deserts, Great Plains, Mediterranean, Semi-Arid, Temperate, Hot-Dry Jungles and Hot-Humid Jungles) versus the USA and concludes with advice on an approach for low impact housing.

Alcocer, J. L. B.; Haberl, J. S.

2010-08-01T23:59:59.000Z

418

T.: Numerical sequence extraction in handwritten incoming mail documents  

E-Print Network (OSTI)

In this communication, we propose a method for the automatic extraction of numerical fields in handwritten documents. The approach exploits the known syntactic structure of the numerical field to extract, combined with a set of contextual morphological features to find the best label to each connected component. Applying an HMM based syntactic analyzer on the overall document allows to localize/extract fields of interest. Reported results on the extraction of zip codes, phone numbers and customer codes from handwritten incoming mail documents demonstrate the interest of the proposed approach. 1.

G. Koch; L. Heutte; T. Paquet

2003-01-01T23:59:59.000Z

419

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

SciTech Connect

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

Brian C. O'Neill

2006-08-09T23:59:59.000Z

420

A structural analysis of natural gas consumption by income class from 1987 to 1993  

SciTech Connect

This study had two major objectives: (1) assess and compare changes in natural gas consumption between 1987 and 1993 by income group and (2) assess the potential influence of energy policy on observed changes in natural gas consumption over time and across income groups. This analysis used U.S. Department of Energy (DOE) data files and involved both the generation of simple descriptive statistics and the use of multivariate regression analysis. The consumption of natural gas by the groups was studied over a six-year period. The results showed that: (1) natural gas use was substantially higher for the highest income group than for the two lower income groups and (2) natural gas consumption declined for the lowest and middle income quintiles and increased for the highest income quintile between 1987 and 1990; between 1990 and 1993, consumption increased for the lowest and middle income quintile, but remained relatively constant for the highest income quintile. The relative importance of the structural and variable factors in explaining consumption changes between survey periods varies by income group. The analysis provides two major energy policy implications: (1) natural gas intensity has been the highest for the lowest income group, indicating that this group is more vulnerable to sudden changes in demand-indicator variables, in particular weather-related variables, than increase natural gas consumption, and (2) the fall in natural gas intensity between 1987 and 1993 may indicate that energy policy has had some impact on reducing natural gas consumption. 11 refs., 4 figs., 16 tabs.

Poyer, D.A.

1996-12-01T23:59:59.000Z

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

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

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

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

422

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

423

A dynamic model system of household car ownership, trip generation, and modal split: model development and simulation experiment  

E-Print Network (OSTI)

household car ownership, mode usage, and sociodemographictrip making and mode usage upon car ownership appears to beto predict car ownership and mode usage by the panel

Kitamura, Ryuichi

2009-01-01T23:59:59.000Z

424

Essays on the Consumption and Investment Decisions of Households in the Presence of Housing and Human Capital  

E-Print Network (OSTI)

2 Housing and the Consumption Allocation of Households:of Indivisibility on Housing Consumption Volatility . 2.5and consumption allocation . . . . . . . . . . . . . . .

Betermier, Sebastien

2010-01-01T23:59:59.000Z

425

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

E-Print Network (OSTI)

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

Meyers, Marcia k.

1996-01-01T23:59:59.000Z

426

Load-shifting in a new perspective: Smart scheduling of smart household appliances using an Agent-Bsaed Modelling Approach.  

E-Print Network (OSTI)

??The electricity demand of households in the Netherlands has been growing rapidly for the last decades and will continue to grow in the near future.… (more)

De Blécourt, M.J.

2012-01-01T23:59:59.000Z

427

City of Tallahassee Utilities - Low-Income Energy Efficiency Grant Programs  

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

Tallahassee Utilities - Low-Income Energy Efficiency Grant Tallahassee Utilities - Low-Income Energy Efficiency Grant Programs City of Tallahassee Utilities - Low-Income Energy Efficiency Grant Programs < Back Eligibility Low-Income Residential Savings Category Home Weatherization Commercial Weatherization Sealing Your Home Ventilation Program Info State Florida Program Type Utility Grant Program Rebate Amount Ceiling Insulation Grant: $500 HVAC Repair: $500 Provider City of Tallahassee Utilities City of Tallahassee Utilities offers two different grants that encourage low-income residents to improve the energy efficiency of homes. Both programs require a free home energy audit to be conducted in order to determine the eligibility of the applicant. Applicants must also fit within the qualifying income levels detailed on the web site.

428

Competition Helps Kids Learn About Energy and Save Their Households Some  

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

Competition Helps Kids Learn About Energy and Save Their Households Competition Helps Kids Learn About Energy and Save Their Households Some Money Competition Helps Kids Learn About Energy and Save Their Households Some Money May 21, 2013 - 2:40pm Addthis Students can register now to save energy and win prizes with the Home Energy Challenge. Students can register now to save energy and win prizes with the Home Energy Challenge. Eric Barendsen Energy Technology Program Specialist, Office of Energy Efficiency and Renewable Energy How can I participate? Visit HomeEnergyChallenge.org to register for the competition. Third through eighth grade students and teachers will be excited to hear about a competition starting up for next school year that challenges students to learn about energy, develop techniques for saving energy, and

429

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

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

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

430

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

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

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

431

NYSERDA's Green Jobs-Green New York Program: Extending Energy Efficiency Financing To Underserved Households  

Science Conference Proceedings (OSTI)

The New York legislature passed the Green Jobs-Green New York (GJGNY) Act in 2009. Administered by the New York State Energy Research and Development Authority (NYSERDA), GJGNY programs provide New Yorkers with access to free or low-cost energy assessments,1 energy upgrade services,2 low-cost financing, and training for various 'green-collar' careers. Launched in November 2010, GJGNY's residential initiative is notable for its use of novel underwriting criteria to expand access to energy efficiency financing for households seeking to participate in New York's Home Performance with Energy Star (HPwES) program.3 The GJGNY financing program is a valuable test of whether alternatives to credit scores can be used to responsibly expand credit opportunities for households that do not qualify for traditional lending products and, in doing so, enable more households to make energy efficiency upgrades.

Zimring, Mark; Fuller, Merrian

2011-01-24T23:59:59.000Z

432

Use of electricity billing data to determine household energy use fingerprints  

Science Conference Proceedings (OSTI)

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

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

1984-08-01T23:59:59.000Z

433

The Impact of Wind Development on County-Level Income and Employment...  

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

Ruth Baranowski, NRELPIX 16410 The Impact of Wind Development on County-Level Income and Employment: A Review of Methods and an Empirical Analysis Introduction The economic...

434

The association between income smoothing and job security concerns in New Zealand.  

E-Print Network (OSTI)

??This study tests for a relationship between income smoothing, proxied by discretionary accruals, and job security concerns, proxied by product durability, capital intensity, and leverage,… (more)

Tauch, Sothyda

435

Tax Man Cometh: Income Taxation as a Measure of State Capacity  

E-Print Network (OSTI)

Dilemma: Building State Capacity in Latin America. Berkeley:2005. Challenges to state policy capacity: Global trends andfor our construct of state capacity because income taxes

Weller, Nick; Ziegler, Melissa

2008-01-01T23:59:59.000Z

436

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

437

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

438

Low-income communities : technological strategies for nurturing community, empowerment and self-sufficiency at a low-income housing development  

E-Print Network (OSTI)

There are a number of historically familiar and unfamiliar forces at work in low-income communities in the United States. Recurrent forces include rapidly changing economic and demographic trends, Welfare Reform, and the ...

O'Bryant, Richard Louis, 1964-

2004-01-01T23:59:59.000Z

439

Form 1: Basic Household Information A B C D E F G H I J K L  

E-Print Network (OSTI)

household? (year) 44 Do your household have a micro-hydro generator? (1 yes; 2 no >>next form) 45 When microhydro; 3 powergrid; 4 other Code 35 1 too expensive; 2 not available; 3 other (specify) #12;ain water; 5 water; 5 river Code 33 1 generator; 2 microhydro; 3 powergrid; 4 other Code 35 1 too expensive; 2

Tullos, Desiree

440

A functional analysis of electrical load curve modelling for some households specific electricity end-uses  

E-Print Network (OSTI)

A functional analysis of electrical load curve modelling for some households specific electricity and the way electrical devices are used will evolve significantly. The energy consumption is likely of electrical devices; · integration of decentralized energy production and stocking (PV modules with battery

Paris-Sud XI, Université de

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

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

Open Energy Info (EERE)

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

442

The household energy transition in India and China Shonali Pachauri a,, Leiwen Jiang b  

E-Print Network (OSTI)

household surveys. The two countries differ sharply in several respects. Residential energy consumption of national primary energy consumption statistics shows clearly that both India and China are countries energy consumption remains low in both countries, particularly in India. Average energy use is low

443

Recommending energy tariffs and load shifting based on smart household usage profiling  

Science Conference Proceedings (OSTI)

We present a system and study of personalized energy-related recommendation. AgentSwitch utilizes electricity usage data collected from users' households over a period of time to realize a range of smart energy-related recommendations on energy tariffs, ... Keywords: demand response, energy tariffs, load shifting, personalization, recommender systems, smart grid

Joel E. Fischer; Sarvapali D. Ramchurn; Michael Osborne; Oliver Parson; Trung Dong Huynh; Muddasser Alam; Nadia Pantidi; Stuart Moran; Khaled Bachour; Steve Reece; Enrico Costanza; Tom Rodden; Nicholas R. Jennings

2013-03-01T23:59:59.000Z

444

Food practices as situated action: exploring and designing for everyday food practices with households  

Science Conference Proceedings (OSTI)

Household food practices are complex. Many people are unable to effectively respond to challenges in their food environment to maintain diets considered to be in line with national and international standards for healthy eating. We argue that recognizing ... Keywords: everyday practice, food, health, situated action

Rob Comber; Jettie Hoonhout; Aart van Halteren; Paula Moynihan; Patrick Olivier

2013-04-01T23:59:59.000Z

445

Leaking electricity: Standby and off-mode power consumption in consumer electronics and household appliances  

Science Conference Proceedings (OSTI)

This report assesses ``leaking`` electricity from consumer electronics and small household appliances when they are in standby mode or turned off, and examines the impacts of these losses. The report identifies trends in relevant product industries and gives technical and policy options for reducing standby and off-mode power loss.

Thorne, J.; Suozzo, M.

1998-12-31T23:59:59.000Z

446

PHEV Utility Factors (UFs) Derived from Households' Vehicle Usage Patterns Jamie Davies, Ken Kurani  

E-Print Network (OSTI)

to calculate electrical consumption, emissions, fuel costs, and battery lifetime and degradation. Of particular of Battery Electric Vehicles (BEVs) while allowing consumers to make use of the familiar gasoline refueling, each household starts the day with a fully charged battery and does not recharge throughout the day

California at Davis, University of

447

Muffled Price Signals: Household Water Demand Under Increasing-Block Prices  

E-Print Network (OSTI)

The distinction has been quite important in the electricity demand literature, in which long-run price elasticity and electricity pricing, and volume discounts in general. Under increasing blocks, the budget constraintMuffled Price Signals: Household Water Demand Under Increasing-Block Prices Sheila M. Cavanagh, W

Kammen, Daniel M.

448

HOUSEHOLD RESPONSE TO DYNAMIC PRICING OF ELECTRICITY A SURVEY OF SEVENTEEN PRICING EXPERIMENTS  

E-Print Network (OSTI)

(DOE) defines demand response as "changes in electric usage by end-use customers from their normalHOUSEHOLD RESPONSE TO DYNAMIC PRICING OF ELECTRICITY A SURVEY OF SEVENTEEN PRICING EXPERIMENTS response in electricity markets. One of the best ways to let that happen is to let customers see

449

Facts about FEMA Household Disaster Aid: Examining the 2008 Floods and Tornadoes in Missouri  

Science Conference Proceedings (OSTI)

Very little empirical work has been done on disaster aid in the United States. This paper examines post-disaster grants to households from the Federal Emergency Management Agency in the state of Missouri in 2008. That year, the state experienced ...

Carolyn Kousky

450

Enabling energy efficiency for low-income housing in Developing countries using MIT Design Advisor  

E-Print Network (OSTI)

There is a great need to improve energy efficiency of low-income housing, since people who can afford it least have to pay a significant portion of their income to make their homes more habitable or else live with greater ...

Ali, Zehra (Zehra Hyder)

2009-01-01T23:59:59.000Z

451

China's Income Distribution, 1985-2001 Ximing Wu* and Jeffrey M. Perloff**  

E-Print Network (OSTI)

China's Income Distribution, 1985-2001 Ximing Wu* and Jeffrey M. Perloff** February, 2005 We Bureau of Statistics of China, for explaining many features of the Chinese urban survey. Ximing Wu@are.berkeley.edu. #12;Abstract We employ a new method to estimate China's income distributions using publicly available

Perloff, Jeffrey M.

452

Nepal-Program for Scaling Up Renewable Energy in Low Income Countries  

Open Energy Info (EERE)

Nepal-Program for Scaling Up Renewable Energy in Low Income Countries Nepal-Program for Scaling Up Renewable Energy in Low Income Countries (SREP) Jump to: navigation, search Name Nepal-Program for Scaling Up Renewable Energy in Low Income Countries (SREP) Agency/Company /Organization World Bank Sector Energy, Land Topics Background analysis, Finance, Implementation, Low emission development planning, Market analysis Website http://www.climatefundsupdate. Program Start 2009 Country Nepal UN Region Southern Asia References Program for Scaling Up Renewable Energy in Low Income Countries (SREP)[1] Ethiopia Specific Documents[2] Honduras Specific Documents[3] Kenya Specific Documents[4] Maldives Specific Documents[5] Mali Specific Documents[6] Nepal Specific Documents[7] Overview "The Scaling-Up Renewable Energy Program for Low Income Countries (SREP) is

453

Honduras-Program for Scaling Up Renewable Energy in Low Income Countries  

Open Energy Info (EERE)

Honduras-Program for Scaling Up Renewable Energy in Low Income Countries Honduras-Program for Scaling Up Renewable Energy in Low Income Countries (SREP) Jump to: navigation, search Name Honduras-Program for Scaling Up Renewable Energy in Low Income Countries (SREP) Agency/Company /Organization World Bank Sector Energy, Land Topics Background analysis, Finance, Implementation, Low emission development planning, Market analysis Website http://www.climatefundsupdate. Program Start 2009 Country Honduras UN Region Southern Asia References Program for Scaling Up Renewable Energy in Low Income Countries (SREP)[1] Ethiopia Specific Documents[2] Honduras Specific Documents[3] Kenya Specific Documents[4] Maldives Specific Documents[5] Mali Specific Documents[6] Nepal Specific Documents[7] Overview "The Scaling-Up Renewable Energy Program for Low Income Countries (SREP) is

454

Mali-Program for Scaling Up Renewable Energy in Low Income Countries (SREP)  

Open Energy Info (EERE)

Mali-Program for Scaling Up Renewable Energy in Low Income Countries (SREP) Mali-Program for Scaling Up Renewable Energy in Low Income Countries (SREP) Jump to: navigation, search Name Mali-Program for Scaling Up Renewable Energy in Low Income Countries (SREP) Agency/Company /Organization World Bank Sector Energy, Land Topics Background analysis, Finance, Implementation, Low emission development planning, Market analysis Website http://www.climatefundsupdate. Program Start 2009 Country Mali UN Region Southern Asia References Program for Scaling Up Renewable Energy in Low Income Countries (SREP)[1] Ethiopia Specific Documents[2] Honduras Specific Documents[3] Kenya Specific Documents[4] Maldives Specific Documents[5] Mali Specific Documents[6] Nepal Specific Documents[7] Overview "The Scaling-Up Renewable Energy Program for Low Income Countries (SREP) is

455

Kenya-Program for Scaling Up Renewable Energy in Low Income Countries  

Open Energy Info (EERE)

Kenya-Program for Scaling Up Renewable Energy in Low Income Countries Kenya-Program for Scaling Up Renewable Energy in Low Income Countries (SREP) Jump to: navigation, search Name Kenya-Program for Scaling Up Renewable Energy in Low Income Countries (SREP) Agency/Company /Organization World Bank Sector Energy, Land Topics Background analysis, Finance, Implementation, Low emission development planning, Market analysis Website http://www.climatefundsupdate. Program Start 2009 Country Kenya UN Region Southern Asia References Program for Scaling Up Renewable Energy in Low Income Countries (SREP)[1] Ethiopia Specific Documents[2] Honduras Specific Documents[3] Kenya Specific Documents[4] Maldives Specific Documents[5] Mali Specific Documents[6] Nepal Specific Documents[7] Overview "The Scaling-Up Renewable Energy Program for Low Income Countries (SREP) is

456

Ethiopia-Program for Scaling Up Renewable Energy in Low Income Countries  

Open Energy Info (EERE)

Ethiopia-Program for Scaling Up Renewable Energy in Low Income Countries Ethiopia-Program for Scaling Up Renewable Energy in Low Income Countries (SREP) Jump to: navigation, search Name Ethiopia-Program for Scaling Up Renewable Energy in Low Income Countries (SREP) Agency/Company /Organization World Bank Sector Energy, Land Topics Background analysis, Finance, Implementation, Low emission development planning, Market analysis Website http://www.climatefundsupdate. Program Start 2009 Country Ethiopia UN Region Southern Asia References Program for Scaling Up Renewable Energy in Low Income Countries (SREP)[1] Ethiopia Specific Documents[2] Honduras Specific Documents[3] Kenya Specific Documents[4] Maldives Specific Documents[5] Mali Specific Documents[6] Nepal Specific Documents[7] Overview "The Scaling-Up Renewable Energy Program for Low Income Countries (SREP) is

457

Maldives-Program for Scaling Up Renewable Energy in Low Income Countries  

Open Energy Info (EERE)

Maldives-Program for Scaling Up Renewable Energy in Low Income Countries Maldives-Program for Scaling Up Renewable Energy in Low Income Countries (SREP) Jump to: navigation, search Name Maldives-Program for Scaling Up Renewable Energy in Low Income Countries (SREP) Agency/Company /Organization World Bank Sector Energy, Land Topics Background analysis, Finance, Implementation, Low emission development planning, Market analysis Website http://www.climatefundsupdate. Program Start 2009 Country Maldives UN Region Southern Asia References Program for Scaling Up Renewable Energy in Low Income Countries (SREP)[1] Ethiopia Specific Documents[2] Honduras Specific Documents[3] Kenya Specific Documents[4] Maldives Specific Documents[5] Mali Specific Documents[6] Nepal Specific Documents[7] Overview "The Scaling-Up Renewable Energy Program for Low Income Countries (SREP) is

458

Program for Scaling Up Renewable Energy in Low Income Countries (SREP) |  

Open Energy Info (EERE)

Scaling Up Renewable Energy in Low Income Countries (SREP) Scaling Up Renewable Energy in Low Income Countries (SREP) Jump to: navigation, search Name Program for Scaling Up Renewable Energy in Low Income Countries (SREP) Agency/Company /Organization World Bank Sector Energy, Land Topics Background analysis, Finance, Implementation, Low emission development planning, Market analysis Website http://www.climatefundsupdate. Program Start 2009 Country Ethiopia, Honduras, Kenya, Maldives, Mali, Nepal UN Region Southern Asia References Program for Scaling Up Renewable Energy in Low Income Countries (SREP)[1] Ethiopia Specific Documents[2] Honduras Specific Documents[3] Kenya Specific Documents[4] Maldives Specific Documents[5] Mali Specific Documents[6] Nepal Specific Documents[7] Overview "The Scaling-Up Renewable Energy Program for Low Income Countries (SREP) is

459

EO 12898: Environmental Justice in Minority Populations and Low-Income  

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

2898: Environmental Justice in Minority Populations and 2898: Environmental Justice in Minority Populations and Low-Income Populations EO 12898: Environmental Justice in Minority Populations and Low-Income Populations To focus Federal attention on the environmental and human health conditions in minority communities and low-income communities with the goal of achieving environmental justice. That order is also intended to promote nondiscrimination in Federal programs substantially affecting human health and the environment, and to provide minority communities and low-income communities access to public information on, and an opportunity for public participation in, matters relating to human health or the environment. EO 12898: Environmental Justice in Minority Populations and Low-Income Populations More Documents & Publications

460

Commercializing Light-Duty Plug-In/Plug-Out Hydrogen-Fuel-Cell Vehicles: "Mobile Electricity" Technologies, Early California Household Markets, and Innovation Management  

E-Print Network (OSTI)

and vehicular-distributed-generation model to estimate zero-power, Vehicular distributed generation, Household marketdistributed generation .25

Williams, Brett D

2010-01-01T23:59:59.000Z

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

Commercializing Light-Duty Plug-In/Plug-Out Hydrogen-Fuel-Cell Vehicles:“Mobile Electricity” Technologies, Early California Household Markets, and Innovation Management  

E-Print Network (OSTI)

and vehicular-distributed-generation model to estimate zero-power, Vehicular distributed generation, Household marketdistributed generation .25

Williams, Brett D

2007-01-01T23:59:59.000Z

462

Investigating the book-tax income gap : factors which affect the gap and details regarding its most significant component  

E-Print Network (OSTI)

(cont.) In total, my thesis suggests that recent changes in the book-tax income gap may be exogenous and transitory, due to changes to the calculation of book income, general business conditions or other factors which ...

Seidman, Jeri

2008-01-01T23:59:59.000Z

463

The effect of household consumption patterns on energy use and greenhouse gas emissions: Comparison between Spain and Sweden.  

E-Print Network (OSTI)

??The purpose of this study is to provide a better understanding of the effect of increasing income on energy use and greenhouse gas (GHG) emissions… (more)

Cintas Sánchez, Olivia

2011-01-01T23:59:59.000Z

464

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

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

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

465

Household attitudes toward energy conservation in the Pacific Northwest: overview and comparisons  

SciTech Connect

This report presents an overview of a baseline residential energy conservation study for the Pacific Northwest conducted in November 1983 by RMH Research, Inc. It also compares the study results with available data from other surveys. The primary focus of the RMH study is conservation marketing. As such it assesses the attitudes, perceptions, and past conservation actions of the region's residents and provides market segmentation based upon past conservation actions and the propensity to invest in conservation in the future. Excluding renters, who account for about 24% of the region's households, three prospect groups for marketing conservation investments are identified: First Tier Prospects who are very likely to invest in additional conservation measures requiring larger sums of money (estimated at about 547,000 households, or 18 percent of the region's households); Second Tier Prospects who are somewhat likely to invest in full weatherization (estimated at about 22% of the region's households or 695,700); and Non-Prospects who are unlikely to invest in energy conservation in the near future (estimated to be 1,113,400 or 36% of the regional total). A summary comparison of the most important distinguishing attributes of the three prospect groups is presented. Considering the current surplus status of the region's electricity supply situation and the overall strategy in capability building, implications include (1) using public information programs through utilities and the news media to maintain the conservation interests of the first-tier prospects and (2) exploring ways to move the second-tier prospects into the first tier and to reach the so-called non-prospect and rental housing groups.

Fang, J.M.

1985-06-01T23:59:59.000Z

466

Gender Roles and Activities Among the Rural Poor Households: Case Studies from Hill Villages  

E-Print Network (OSTI)

. Therefore, social stratification is imperative and valuable to any social system (parsons, Davis More quoted by Pathy, 1987). Dahrendorf and Bottomore severely criticized the functionalist approach for over emphasizing consensus and considering... of the households. REFERENCES Archarya, Meena and Lynn, Bennett. 1981 The Status of Women in Nepal, Kathmandn CEDA. Ember, C and Melvin Ember J990 Anthropology, Prentice-Hall, Delhi. 82 Occasional Papers Haralumbus, M, 1997 Sociology Theme and Perspectives, Oxford...

Pokharel, Binod

2001-01-01T23:59:59.000Z

467

An Analysis of the Price Elasticity of Demand for Household Appliances  

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

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

468

Understanding and Improving Household Energy Consumption and Carbon Emissions Policies - A System Dynamics Approach  

E-Print Network (OSTI)

The purpose of this paper is to propose and demonstrate the application of system dynamics modeling approach to analyze and study the behavior the complex interrelationships among the different policies/interventions aimed at reducing household energy consumption and CO2 emissions (HECCE) based on the Climate Change Act of 2008 of the UK government. The paper uses the system dynamics as both the methodology and tool to model the policies/interventions regarding HECCE. The model so developed shows the complex interrelationships among the different policies/interventions variables and presents the basis for simulating the different scenarios of household energy consumption reduction strategies. The paper concludes that the model is capable of adding to the understanding of the complex system under which HECCE operate and improve it accordingly by studying the behavior of each policy/intervention over time. The outcomes of the research will help decision makers draw more realistic policies/interventions for household energy consumption which is critical to the CO2 emissions reductions agenda of the government.

Oladokun, M.; Motawa, I.; Banfill, P.

2012-01-01T23:59:59.000Z

469

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

Science Conference Proceedings (OSTI)

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

Hsueh, L.M.

1984-01-01T23:59:59.000Z

470

A statistical analysis of structural differences in minority household electricity demand  

SciTech Connect

In this paper, the structures for electricity demand in non-Latino Black and White households are compared. Electricity demand will be analyzed within the context of a complete demand system, and statistical tests for structural differences will be systematically conducted in the hope of pinpointing the location of differences within the context of this model. Structural differences in demand are defined as statistically significant differences in a parameter or group of parameters that identify the quantitative relationship between explanatory variables and electricity consumption. Along with population taste differences, which might emanate from historical and cultural population differences, structural differences might also occur because of differences in housing and geographic patterns and as a result of differences in access to markets and information. As a consequence, energy consumption decisions will differ, and the level and composition of energy consumption are likely to vary. In practice, it is nearly impossible to untangle the causes contributing to structural differences, but it is reasonably easy to test for statistical differences. The superficial evidence indicates there is a strong likelihood that structural differences do exist in electricity demand between White and Black households. The null hypothesis, which states that there exist no differences in the structures for electricity demand for Black and White households, is tested.

Poyer, D.A.; Earl, E.

1994-09-01T23:59:59.000Z

471

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

Science Conference Proceedings (OSTI)

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

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

2011-03-15T23:59:59.000Z

472

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

E-Print Network (OSTI)

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

Meyers, Marcia k.

1996-01-01T23:59:59.000Z

473

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

E-Print Network (OSTI)

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

Baffrey, Robert Michael Nuval, 1977-

2005-01-01T23:59:59.000Z

474

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

475

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

476

Urban settlement design, Seoul, Korea : a comparative study for low-income housing  

E-Print Network (OSTI)

The study proposes an alternative design approach for urban dwelling environments of the low-income sectors in Seoul, Korea, based upon a comparative evaluation of the physical and socio-economic performance of the existing ...

Je, Hae-Seong

1982-01-01T23:59:59.000Z

477

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

478

EO 12898: Environmental Justice in Minority Populations and Low-Income Populations  

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

WASHINGTON WASHINGTON February 11, 1994 MEMORANDUM FOR THE HEADS OF ALL DEPARTMENTS AND AGENCIES SUBJECT: Executive Order on Federal Actions to Address Environmental Justice in Minority Populations and Low- Income Populations Today I have issued an Executive Order on Federal Actions to Address Environmental Justice in Minority Populations and Low-Income Populations. That order is designed to focus Federal attention on the environmental and human health conditions in minority communities and low-income communities with the goal of achieving environmental justice. That order is also intended to promote nondiscrimination in Federal programs substantially affecting human health and the environment, and to provide minority communities and low-income communities access to public

479

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,"

480

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

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

The Impact of Wind Development on County-Level Income and Employment...  

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

The Impact of Wind Development on County-Level Income and Employment: A Review of Methods and an Empirical Analysis (Fact Sheet) Title The Impact of Wind Development on...

482

The Low-Income Housing Tax Credit : HERA, ARRA and beyond  

E-Print Network (OSTI)

The Low-Income Housing Tax Credit (LIHTC) has arguably been the most successful government subsidy to finance affordable housing. Since its creation in the Tax Reform Act of 1986 as Internal Revenue Code (IRC) Section 42, ...

Korb, Jason (Jason Bryan Patricof)

2009-01-01T23:59:59.000Z

483

Incoming Shortwave Fluxes at the Surface—A Comparison of GCM Results with Observations  

Science Conference Proceedings (OSTI)

Evidence is presented that the excess surface net radiation calculated in general circulation models at continental surfaces is mostly due to excess incoming shortwave fluxes. Based on long-term observations from 22 worldwide inland stations and ...

J. R. Garratt

1994-01-01T23:59:59.000Z

484

Relating Rainfall Patterns to Agricultural Income: Implications for Rural Development in Mozambique  

Science Conference Proceedings (OSTI)

Rural farmers in Mozambique rely on rainfed agriculture for food and income. Yet they experience high rainfall variability ranging from extreme drought to flooding rainfall from tropical cyclone systems. To explore linkages between rainfall and ...

Julie A. Silva; Corene J. Matyas

485

A Study of the Incoming Longwave Atmospheric Radiation from a Clear Sky  

Science Conference Proceedings (OSTI)

A band model for atmospheric absorption is used to calculate the incoming longwave atmospheric radiative flux for some typical clear sky conditions. The sky radiation is also measured using a specially-designed calorimetric apparatus over a wide ...

J. W. Ramsey; H. D. Chiang; R. J. Goldstein

1982-04-01T23:59:59.000Z

486

Causes, effects, and implications of subletting : experiences from low-income neighborhoods in Third World cities  

E-Print Network (OSTI)

In recent years increasing numbers of low-income families in Third World cities have found it necessary to share housing accommodation. Those with access to land may be unable to afford to build their house or to pay the ...

Bailey, Susan Ruth

1987-01-01T23:59:59.000Z

487

Low income housing tax credit properties : non-profit disposition strategies in the Commonwealth  

E-Print Network (OSTI)

This thesis examines how non-profit owners in Massachusetts have maintained affordability and ownership of Low-Income Housing Tax Credit (LIHTC) properties after the initial fifteen-year compliance period, at the lowest ...

Lew-Hailer, Lillian

2007-01-01T23:59:59.000Z

488

Community transportation : alternative transportation provision in a low-income neighborhoods in southeast Atlanta  

E-Print Network (OSTI)

Regional transit agencies are ineffective at meeting many of the basic transportation needs of a clustered "Study Area" of low-income Atlanta neighborhoods. For transit dependant residents in the Study Area, getting to the ...

Alexander, James W., 1977-

2004-01-01T23:59:59.000Z

489

New Hampshire Electric Co-Op - Low-Income Energy Assistance Grant...  

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

help NHEC's income-qualified members manage energy use with the goal of lowering total energy costs. Qualified members living in an apartment or house, either rented or owned, can...

490

Low-income communities in World Heritage Cities : revitalizing neighborhoods in Tunis and Quito  

E-Print Network (OSTI)

Since the 1970s, international preservation and funding agencies have promoted revitalization projects in developing countries aiming to, among other things, benefit low-income communities. For the most part, these projects ...

Young, T. Luke, 1972-

2000-01-01T23:59:59.000Z