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1

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

2

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

Open Energy Info (EERE)

property. This report surveys evidence from 15 recent experiments with dynamic pricing of electricity in the United States and Canada. The report suggests conclusive evidence that...

3

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.

4

1 HOUSEHOLD RESPONSE TO DYNAMIC PRICING OF ELECTRICITY—A SURVEY OF THE EXPERIMENTAL EVIDENCE  

E-Print Network (OSTI)

Since the energy crisis of 2000-2001 in the western United States, much attention has been given to boosting demand response in electricity markets. One of the best ways to let that happen is to pass through wholesale energy costs to retail customers. This can be accomplished by letting retail prices vary dynamically, either entirely or partly. For the overwhelming majority of customers, that requires a changeout of the metering infrastructure, which may cost as much as $40 billion for the US as a whole. While a good portion of this investment can be covered by savings in distribution system costs, about 40 percent may remain uncovered. This investment gap could be covered by reductions in power generation costs that could be brought about through demand response. Thus, state regulators in many states are investigating whether customers will respond to the higher prices by lowering demand and if so, by how much. To help inform this assessment, we survey the evidence from the 15 most recent experiments with dynamic pricing of electricity. We find conclusive evidence that households (residential customers) respond to higher prices by lowering usage. The magnitude of price response depends on several factors, such as the magnitude of the price increase, the presence of central air conditioning and the availability of enabling technologies such as two-way

Ahmad Faruqui; Sanem Sergici

2009-01-01T23:59:59.000Z

5

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

6

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

7

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

8

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

9

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

10

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

11

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.

12

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

13

ANALYSIS OF CEE HOUSEHOLD SURVEY NATIONAL AWARENESS OF ENERGY...  

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

2011 to four percent in 2012 and the proportion informed by their lender increased from zero percent in 2011 to one percent in 2012. All other responses were statistically...

14

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

15

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

16

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

17

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 ...

18

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

19

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

SciTech Connect

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

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

2013-01-01T23:59:59.000Z

20

United States Geological Survey Geospatial Information Response  

E-Print Network (OSTI)

requirements, capabilities, and operations in response to a natural or man-made disaster1 United States Geological Survey Geospatial Information Response Information Response Team (GIRT) Standard Operating Procedures (SOP) contains the GIRT

Fleskes, Joe

Note: This page contains sample records for the topic "household survey responses" 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

Residential energy use and conservation in Venezuela: Results and implications of a household survey in Caracas  

SciTech Connect

This document presents the final report of a study of residential energy use in Caracas, the capital of Venezuela. It contains the findings of a household energy-use survey held in Caracas in 1988 and examines options for introducing energy conservation measures in the Venezuelan residential sector. Oil exports form the backbone of the Venezuelan economy. Improving energy efficiency in Venezuela will help free domestic oil resources that can be sold to the rest of the world. Energy conservation will also contribute to a faster recovery of the economy by reducing the need for major investments in new energy facilities, allowing the Venezuelan government to direct its financial investments towards other areas of development. Local environmental benefits will constitute an important additional by-product of implementing energy-efficiency policies in Venezuela. Caracas`s residential sector shows great potential for energy conservation. The sector is characterized by high saturation levels of major appliances, inefficiency of appliances available in the market, and by careless patterns of energy use. Household energy use per capita average 6.5 GJ/per year which is higher than most cities in developing countries; most of this energy is used for cooking. Electricity accounts for 41% of all energy use, while LPG and natural gas constitute the remainder. Specific options for inducing energy conservation and energy efficiency in Caracas`s residential sector include energy-pricing policies, fuel switching, particularly from electricity to gas, improving the energy performance of new appliances and customer information. To ensure the accomplishment of an energy-efficiency strategy, a concerted effort by energy users, manufacturers, utility companies, government agencies, and research institutions will be needed.

Figueroa, M.J.; Ketoff, A.; Masera, O.

1992-10-01T23:59:59.000Z

22

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 *...

23

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

24

Electricity displacement by wood used for space heating in PNWRES (Pacific Northwest Residential Energy Survey) (1983) households  

DOE Green Energy (OSTI)

This report evaluates the amount of electricity for residential space heating displaced by the use of wood in a sample of single-family households that completed the 1983 Pacific Northwest Residential Energy Survey. Using electricity bills and daily weather data from the period of July 1981 to July 1982, it was determined that the average household used 21,800 kWh per year, normalized with respect to weather. If no households had used any wood, electricity use would have increased 9%, to 23,700 kWh; space heating electricity use would also have increased, by 21%, to 47% of total electricity use. In the unlikely event that all households had used a great deal of wood for space heating, electricity use could have dropped by 23.5% from the average use, to 16,700 kWh; space heating electricity use would have dropped by 56%, to 24% of total electricity use. Indications concerning future trends regarding the displacement of electricity by wood use are mixed. On one hand, continuing to weatherize homes in the Pacific Northwest may result in less wood use as households find using electricity more economical. On the other hand, historical trends in replacement decisions regarding old space heating systems show a decided preference for wood. 11 refs., 6 figs., 8 tabs.

White, D.L.; Tonn, B.E.

1988-12-01T23:59:59.000Z

25

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

E-Print Network (OSTI)

by electric and hybrid vehicles", SAETechmcal Papers No.may response to hybrid vehicles Finally, we suggest thatsamebetweenvehicle tyoes. Hybrid Vehicles for examplecost a

Turrentine, Thomas; Kurani, Kenneth S.

2001-01-01T23:59:59.000Z

26

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

27

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

28

Identification Strategies in Survey Response Using Vignettes  

E-Print Network (OSTI)

satisfaction over products and services (see Rossi, Gilula, and Allenby (2001)), surveys of job satisfaction (Kristensen and Johansson (2006)), health (Bago D’Uva, Lindeboom, O’Donnell, and Van Doorslaer (2009); Peracchi and Rossetti (2009); Salomon, Tandon... , and Murray (2004)), political efficacy (King, Murray, Salomon, and Tandon (2004)), work disability (Kapteyn, Smith, and Van Soest (2007)), and corruption (Olken (2007)). A fundamental barrier to inference using survey response is that respondents exhibit...

Corrado, Luisa; Weeks, Melvyn

29

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...

30

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.

31

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

32

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

33

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

34

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

35

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

36

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

37

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

38

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

39

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 ...

40

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

Note: This page contains sample records for the topic "household survey responses" 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

Survey of spectral response measurements for photovoltaic devices  

DOE Green Energy (OSTI)

A survey of the photovoltaic community was conducted to ascertain the present state-of-the-art for PV spectral response measurements. Specific topics explored included measurement system designs, good and bad features of the systems, and problems encountered in the evaluation of specific cell structures and materials. The survey showed that most spectral response data are used in diagnostic analysis for the optimization of developmental solar cells. Measurement systems commonly utilize a chopped narrowband source in conjunction with a constant bias illumination which simulates the ambient end use environment. Researchers emphasized the importance of bias illumination for all types of cells in order to minimize the effects of nonlinearities in cell response. Not surprisingly single crystal silicon cells present the fewest measurement problems to the researcher and have been studied more thoroughly than any other type of solar cell. But, the accurate characterization of silicon cells is still difficult and laboratory intercomparison studies have yielded data scatter ranging from +-5% to +-15%. The measurement experience with other types of cells is less extensive. The development of reliable data bases for some solar cells is complicated by problems of cell nonuniformity, environmental instability, nonlinearity, etc. Cascade cells present new problems associated with their structue (multiple cells in series) which are just beginning to be understood. In addition, the importance of many measurement parameters (spectral content of bias light, bias light intensity, bias voltage, chopping frequency, etc.) are not fully understood for most types of solar cells.

Hartman, J.S.; Lind, M.A.

1981-11-01T23:59:59.000Z

42

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

43

The Wikipedia Gender Gap Revisited: Characterizing Survey Response Bias with Propensity Score Estimation  

E-Print Network (OSTI)

Opt-in surveys are the most widespread method used to study participation in online communities, but produce biased results in the absence of adjustments for non-response. A 2008 survey conducted by the Wikimedia Foundation ...

Hill, Benjamin Mako

44

Figure 2. Energy Consumption of Vehicles, Selected Survey Years  

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

Home > Households, Buildings & Industry >Transportation Surveys > Household Vehicles Energy Use > Figure 2 Figure 2. Energy Consumption of Vehicles, Selected Survey Years...

45

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

46

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

47

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

48

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

49

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 ...

50

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 ...

51

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

52

Building Technologies Residential Survey  

SciTech Connect

Introduction A telephone survey of 1,025 residential occupants was administered in late October for the Building Technologies Program (BT) to gather information on residential occupant attitudes, behaviors, knowledge, and perceptions. The next section, Survey Results, provides an overview of the responses, with major implications and caveats. Additional information is provided in three appendices as follows: - Appendix A -- Summary Response: Provides summary tabular data for the 13 questions that, with subparts, comprise a total of 25 questions. - Appendix B -- Benchmark Data: Provides a benchmark by six categories to the 2001 Residential Energy Consumption Survey administered by EIA. These were ownership, heating fuel, geographic location, race, household size and income. - Appendix C -- Background on Survey Method: Provides the reader with an understanding of the survey process and interpretation of the results.

Secrest, Thomas J.

2005-11-07T23:59:59.000Z

53

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...

54

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

55

The 1997 Residential Energy Consumption Survey -- Two Decades  

U.S. Energy Information Administration (EIA)

1997 Residential Energy Consumption Survey presents two decades of changes in energy consumption related Household Characteristics

56

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

57

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

58

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

59

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

60

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

Note: This page contains sample records for the topic "household survey responses" 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

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

62

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

63

Being surveyed can change later behavior and related parameter estimates  

E-Print Network (OSTI)

Does completing a household survey change the later behavior of those surveyed? In three field studies of health and two of microlending, we randomly assigned subjects to be surveyed about health and/or household finances ...

Zwane, Alix Peterson

64

Residential Energy Consumption Survey Data Tables  

U.S. Energy Information Administration (EIA)

Below are historical data tables from the Residential Energy Consumption Survey (RECS). These tables cover the total number of households ...

65

Survey Expectations  

E-Print Network (OSTI)

of Michigan and is known as the Michigan survey, with many other similar surveys conducted across OECD countries so as to provide up to date information on consumer expectations. Questions on expectations are also sometimes included in panel surveys... be formed, do of course make it possible to assess whether, or how far, such expectations are well-founded by comparing the experiences of individual households with their prior expectations. A key aspect of the Michigan survey, and of many other more recent...

Pesaran, M Hashem; Weale, Martin

2006-03-14T23:59:59.000Z

66

Large Emergency-Response Exercises: Qualitative Characteristics - A Survey  

Science Conference Proceedings (OSTI)

Exercises, drills, or simulations are widely used, by governments, agencies and commercial organizations, to simulate serious incidents and train staff how to respond to them. International cooperation has led to increasingly large-scale exercises, often ... Keywords: 'large' exercises, 'play space', agency, bomb threats, crisis, disaster, drill, emergency, emergency response, emotions, exercise, experiential, feelings, fire service, government, group psychotherapy, health agencies, incident, industrial accidents, large group, large-scale exercises, learning, military, multidisciplinarity, personal trust, play, police, psychology, ritual, role-play, simulation, situational trust, situationism, social implications, staff training, trust

Yang-Im Lee; Peter Trim; Julia Upton; David Upton

2009-12-01T23:59:59.000Z

67

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

68

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...

69

Heterogeneous demand responses to discrete price changes: an application to the purchase of lottery tickets  

Science Conference Proceedings (OSTI)

During the survey period of any household expenditure survey price variations may occur. Such variation can be used to identify heterogeneous demand responses to price changes. This is feasible because expenditure surveys usually contain a large number ... Keywords: Expectation/maximisation algorithm, Lottery, Poisson distribution, Unobserved heterogeneity

Roger Hartley; Gauthier Lanot

2006-02-01T23:59:59.000Z

70

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...

71

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

72

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

73

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.

74

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

75

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

76

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

77

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

78

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

79

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

80

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.

Note: This page contains sample records for the topic "household survey responses" 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

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

82

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

83

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

84

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

85

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

86

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

87

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

88

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

89

University Loaned Normal Uranium Slug Disposition Study: University survey responses. Predecisional draft  

SciTech Connect

During the 1950`s and 1960`s, the Atomic Energy Commission loaned rejected natural uranium slugs from the Savannah River Site to United States universities for use in subcritical assemblies. Currently, there are sixty-two universities holding 91,798 slugs, containing about 167 metric tons of natural uranium. It was originally planned that the universities would return the material to Fernald when they no longer required it. Fernald has not received slugs since it was shut down in 1988. The Department of Energy`s Office of Weapons and Materials Planning requested that the Planning Support Group develop information to assist them in facilitating the return of the unwanted slugs to one or more of their facilities and develop alternatives for the ultimate disposition of this material. This supplemental report to the University Loaned Normal Uranium Slug Disposition Study documents responses to and summarizes the results of a survey of fifty-eight universities. University contacts and survey responses covering loaned slug descriptions, historical information, radiological data, current status, and plans and schedules are documented.

Becker, G.W. Jr.

1992-09-01T23:59:59.000Z

90

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

91

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

92

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....

93

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...

94

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...

95

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

96

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

97

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

98

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

99

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

100

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

Note: This page contains sample records for the topic "household survey responses" 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

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

102

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

103

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:...

104

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

105

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

106

Effect of questionnaire length, personalisation and reminder type on response rate to a complex postal survey: a randomised controlled trial  

E-Print Network (OSTI)

survey response behavior. Public Opin Q 1991, 55:613-639. 7. Mond JM, Rodgers B, Hay PJ, Owen C, Beumont PJV: Mode of delivery, but not questionnaire length, affected response in an epidemiological study of eating-disordered behavior. J Clin Epidemiol... 2004, 57:1167-1171. 8. Nakash R, Hutton J, Jørstad-Stein E, Gates S, Lamb S: Maximising response to postal questionnaires - A systematic review of randomised trials in health research. BMC Med Res Methodol 2006, 6:5. 9. Nicolaas G: Putting voters...

Sahlqvist, Shannon; Song, Yena; Bull, Fiona; Adams, Emma; Preston, John; Ogilvie, David

2011-05-06T23:59:59.000Z

107

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...

108

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...

109

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

110

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

111

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...

112

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

113

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

114

Residential Energy Consumption Survey: Quality Profile  

SciTech Connect

The Residential Energy Consumption Survey (RECS) is a periodic national survey that provides timely information about energy consumption and expenditures of U.S. households and about energy-related characteristics of housing units. The survey was first conducted in 1978 as the National Interim Energy Consumption Survey (NIECS), and the 1979 survey was called the Household Screener Survey. From 1980 through 1982 RECS was conducted annually. The next RECS was fielded in 1984, and since then, the survey has been undertaken at 3-year intervals. The most recent RECS was conducted in 1993.

NONE

1996-03-01T23:59:59.000Z

115

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

116

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

117

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

118

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

119

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

120

homeoffice_household2001.pdf  

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

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

Note: This page contains sample records for the topic "household survey responses" 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

Pacific Northwest residential energy survey. Volume 8. Montana cross-tabulations  

Science Conference Proceedings (OSTI)

Responses for the state of Montana to fifty questions asked during the survey (plus four variables computed from responses to several other questions) cross-tabulated against responses to nine questions which represent key explanatory characteristics of residential energy use are presented. The nine key questions are: means of payment for housing; type of dwelling; year dwelling built; total square-footage of living space; type of fuel for main heating system; combined 1978 income; unit cost of electricity; annual electricity consumption; and annual natural gas consumption. The fifty questions and four computed variables which are cross-tabulated against the above, fall into six categories: dwelling characteristics; heating and air-conditioning systems; water heating; appliances; demographic and dwelling characteristics; and insulation. The survey was conducted throughout the states of Washington, Oregon, Idaho, and Montana with a total of 4030 households sampled; 570 households were sampled in Montana.

Not Available

1980-07-01T23:59:59.000Z

123

Pacific Northwest residential energy survey. Volume 5. Washington cross-tabulations  

SciTech Connect

Responses for the state of Washington to fifty questions asked during the survey (plus four variables computed from responses to several other questions) cross-tabulated against responses to nine questions which represent key explanatory characteristics of residential energy use are presented. The nine key questions are: means of payment for housing; type of dwelling; year dwelling built; total square-footage of living space; type of fuel for main heating system; combined 1978 income; unit cost of electricity; annual electricity consumption; and annual natural gas consumption. The fifty questions and four computed variables which were cross-tabulated against the above, fall into six categories: dwelling characteristics; heating and air-conditioning systems; water heating; appliances; demographic and dwelling characteristics; and insulation. The survey was conducted throughout the states of Washington, Oregon, Idaho, and Montana with a total of 4030 households sampled; 1468 households were sampled in Washington. An explanation of the data in the 54 tables is given. (MCW)

Not Available

1980-07-01T23:59:59.000Z

124

Pacific Northwest residential energy survey. Volume 6. Oregon cross-tabulations  

SciTech Connect

Responses for the state of Oregon to fifty questions asked during the survey (plus four variables computed from responses to several other questions) cross-tabulated against responses to nine quesions which represent key explanatory characteristics of residential energy use are presented. The nine key questions are: means of payment for housing; type of dwelling; year dwelling built; total square-footage of living space; type of fuel for main heating system; combined 1978 income; unit cost of electricity; annual electricity consumption; and annual natural gas consumption. The fifty questions and four computed variables which were cross-tabulated against the above, fall into six categories: dwelling characteristics; heating and air-conditioning system; water heating; appliances; demographic and dwelling characteristics; and insulation. The survey was conducted throughout the states of Washington, Oregon, Idaho, and Montana with a total of 4030 households samples; 1165 households were sampled in Oregon. (MCW)

Not Available

1980-07-01T23:59:59.000Z

125

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

126

Household Vehicles Energy Consumption 1991  

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

Appendix A How the Survey Was Conducted Introduction The Residential Transportation Energy Consumption Survey (RTECS) was designed by the Energy Information Administration (EIA)...

127

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

128

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

129

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

130

A peak-capture algorithm used on an autonomous underwater vehicle in the 2010 Gulf of Mexico oil spill response scientific survey  

Science Conference Proceedings (OSTI)

During the Gulf of Mexico Oil Spill Response Scientific Survey on the National Oceanic and Atmospheric Administration Ship Gordon Gunter Cruise GU-10-02 (27 May–4 June 2010), a Monterey Bay Aquarium Research Institute autonomous underwater vehicle ...

Yanwu Zhang; Robert S. McEwen; John P. Ryan; James G. Bellingham; Hans Thomas; Charles H. Thompson; Erich Rienecker

2011-07-01T23:59:59.000Z

131

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.

132

Survey Statisticians  

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

Survey Statisticians Survey Statisticians The U.S.Energy Information Administration (EIA) within the Department of Energy has forged a world-class information program that stresses quality, teamwork, and employee growth. In support of our program, we offer a variety of profes- sional positions, including the Survey Statistician, who measures the amounts of energy produced and consumed in the United States. Responsibilities: Survey Statisticians perform or participate in one or more of the following important functions: * Design energy surveys by writing questions, creating layouts and testing questions for clarity and accuracy. * Conduct energy surveys to include sending out and tracking survey responses, editing and analyzing data submis- sions and communicating with respondents to verify data.

133

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

134

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

135

Evaluation program effectiveness of household hazardous waste collection: The Seattle-King County experience  

SciTech Connect

The Seattle-King County Hazardous Waste Management Plan provides the framework for an intensive effort to keep Household Hazardous and Small Quantity Generator (SQG) wastes from entering the normal'' municipal waste streams. The Plan sets ambitious goals for diverting thousands of tons of hazardous wastes from being thrown, poured or dumped in the municipal waste stream. During the first five years, over $30 millon will be spent for a variety of HHW and SQG programs. The Plan incorporates a wide range of elements, including education, collection, and compliance components. Many of the hazardous waste education and collection programs have been developed in response to the Plan, so their effectiveness is still undetermined. A key component of the Plan is program evaluation. This report provides descriptions of two evaluation methods used to establish baselines for assessing the effectiveness of the Hazardous Waste Management Plan's programs. Focusing on the Plan's household hazardous waste programs, the findings of the baseline evaluations are discussed and conclusions are made. A general population survey, conducted through telephone interviews, was designed to assess changes in knowledge, attitudes, and behaviors of area residents. Characterization of the solid waste stream was used to identify the hazardous constituents contributed to municipal solid waste by households. Monitoring changes in the amount of hazardous materials present in the waste stream was used to indicate whether or not Program strategies are influencing disposal behaviors. Comparing the data gathered by these two evaluation methods provided a unique opportunity to cross-check the findings and validate that change, if any, has occurred. From the comparisons, the report draws a number of conclusions.

1991-10-01T23:59:59.000Z

136

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

137

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

138

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

139

Demand Response-Ready Technology Capabilities: A Summary of Multi-Stakeholder Workshop and Survey Perspectives  

Science Conference Proceedings (OSTI)

This technical update describes technology capabilities that support more automated and ubiquitous demand response. It begins by describing the Demand Response-Ready (DR-Ready) concept and related industry activities that support realization of the concept. In the DR-Ready vision, consumers receive DR-Ready end-use products at the point of purchase, thus eliminating the need for utility truck service visits to retrofit equipment and significantly reducing the cost of deploying DR-enabling technologies. ...

2012-04-06T23:59:59.000Z

140

Demand Response-Ready Capabilities Roadmap: A Summary of Multi-Stakeholder Workshop and Survey Perspectives  

Science Conference Proceedings (OSTI)

The report describes a high-level roadmap for premise-level migration towards more automated and ubiquitous demand response. It begins by describing the Demand Response Ready (DR-Ready) concept and related industry activities supporting realization of the concept. In the DR-Ready vision, consumers receive DR-Ready end-use products at the point of purchase, thus eliminating the need for utility truck rolls to retrofit equipment, and thereby significantly reducing costs of deploying DR enabling ...

2012-12-31T23:59:59.000Z

Note: This page contains sample records for the topic "household survey responses" 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

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

144

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

145

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

146

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

147

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

148

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

149

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

150

ac_household2001.pdf  

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

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

151

ac_household2001.pdf  

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

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

152

ac_household2001.pdf  

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

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

153

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

154

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

155

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

156

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

157

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.

158

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

159

2001 Residential Energy Consumption Survey Answers to Frequently Asked Questions  

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

D (2001) -- Household Bottled Gas (LPG or Propane) Usage Form D (2001) -- Household Bottled Gas (LPG or Propane) Usage Form OMB No. 1905-0092, Expiring February 29, 2004 2001 Residential Energy Consumption Survey Answers to Frequently Asked Questions About the Household Bottled Gas (LPG or Propane) 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

160

Household Vehicles Energy Consumption 1991  

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

methodology used to estimate these statistics relied on data from the 1990 Residential Energy Consumption Survey (RECS), the 1991 Residential Transportation Energy Consumption...

Note: This page contains sample records for the topic "household survey responses" 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

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

162

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

163

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

164

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 ...

165

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

166

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

167

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...

168

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 ...

169

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

170

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

171

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

172

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

173

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

174

2005 Residential Energy Consumption Survey  

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

D (2005) - Household Propane (Bottled Gas or LPG) Usage Form D (2005) - Household Propane (Bottled Gas or LPG) Usage Form OMB No. 1905-0092, Expiring May 31, 2008 Household Propane (Bottled Gas or LPG) Usage Form Service Address: If the customer account number is not shown on the label, please enter it here. STEP 1 Customer Account: __/__/__/__/__/__/__/__/__/__/__/__/__/__/__/ STEP 2 Now, please turn the page and answer the seven questions for the household identified above. Completed forms are due by March 4, 2006. If you have any questions, please call (toll-free) 1-NNN-NNN-NNNN. Ask for the Supplier Survey Specialist. This report is mandatory under Public Law 93-275, as amended. See the enclosed Answers to Frequently Asked Questions for more details concerning confidentiality

175

2005 Residential Energy Consumption Survey  

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

F (2005) - Household Natural Gas Usage Form F (2005) - Household Natural Gas Usage Form OMB No. 1905-0092, Expiring May 31, 2008 Household Natural Gas Usage Form Service Address: If the customer account number is not shown above, please enter it here. STEP 1 Customer Account: __/__/__/__/__/__/__/__/__/__/__/__/__/__/__/ STEP 2 Now, please turn the page and provide the requested information for the household identified above. Completed forms are due by March 4, 2006. If you have any questions, please call (toll-free) 1-NNN-NNN-NNNN. Ask for the Supplier Survey Specialist. This report is mandatory under Public Law 93-275, as amended. See the enclosed Answers to Frequently Asked Questions for more details concerning confidentiality and sanctions. Use the enclosed self-addressed envelope and return the completed form to:

176

2005 Residential Energy Consumption Survey  

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

G (2005) - Household Fuel Oil or Kerosene Usage Form G (2005) - Household Fuel Oil or Kerosene Usage Form OMB No. 1905-0092, Expiring May 31, 2008 Household Fuel Oil or Kerosene Usage Form Service Address: If the customer account number is not shown on the label, please enter it here. STEP 1 Customer Account: __/__/__/__/__/__/__/__/__/__/__/__/__/__/__/ STEP 2 Now, please turn the page and answer the seven questions for the household identified above. Completed forms are due by March 4, 2006. If you have any questions, please call (toll-free) 1-NNN-NNN-NNNN. Ask for the Supplier Survey Specialist. This report is mandatory under Public Law 93-275, as amended. See the enclosed Answers to Frequently Asked Questions for more details concerning confidentiality and sanctions.

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

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

Note: This page contains sample records for the topic "household survey responses" 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

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

182

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

183

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

184

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

185

National Household Travel Survey (2009)

The 2009 National...  

Open Energy Info (EERE)

level, etc.); and

  • vehicle attributes (make, model, model year, amount of miles driven in a year).
      • These data are collected for:

        ...

  • 186

    National Household Travel Survey (2009) | OpenEI  

    Open Energy Info (EERE)

    education level, etc.); and vehicle attributes (make, model, model year, amount of miles driven in a year). These data are collected for: all trips, all modes, all purposes,...

    187

    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

    188

    ASSESSMENT OF HOUSEHOLD CARBON FOOTPRINT REDUCTION POTENTIALS  

    E-Print Network (OSTI)

    Residential Appliance Saturation Survey  Database.  Residential Appliance Saturation  Survey (RASS) database (

    Masanet, Eric

    2010-01-01T23:59:59.000Z

    189

    Department of Energy: 2011 Federal Employee Viewpoint Survey...  

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

    Department of Energy 2011 Federal Employee Viewpoint Survey: Trend Report Response Summary Surveys...

    190

    Residential Energy Consumption Survey (RECS) - Data - U.S. Energy  

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

    1997 RECS Survey Data 2009 | 2005 | 2001 | 1997 | 1993 | Previous 1997 RECS Survey Data 2009 | 2005 | 2001 | 1997 | 1993 | Previous Housing Characteristics Consumption & Expenditures Microdata Methodology Housing Characteristics Tables Table Titles (Released: February 2004) Entire Section Percents Tables: HC1 Housing Unit Characteristics, Million U.S. Households PDF PDF NOTE: As of 10/31/01, numbers in the "Housing Units" TABLES section for stub item: "Number of Floors in Apartment Buildings" were REVISED. These numbers will differ from the numbers in the published report. Tables: HC2 Household Characteristics, Million U.S. Households PDF PDF Tables: HC3 Space Heating, Million U.S. Households PDF PDF Tables: HC4 Air-Conditioning, Million U.S. Households PDF PDF Tables: HC5 Appliances, Million U.S. Households PDF PDF

    191

    Residential Energy Consumption Survey (RECS) - Data - U.S. Energy  

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

    3 RECS Survey Data 2009 | 2005 | 2001 | 1997 | 1993 | Previous 3 RECS Survey Data 2009 | 2005 | 2001 | 1997 | 1993 | Previous Housing Characteristics Consumption & Expenditures Microdata Methodology Housing Characteristics Tables Topical Sections Entire Section All Detailed Tables PDF Tables: HC1 Household Characteristics, Million U.S. Households Presents data relating to location, type, ownership, age, size, construction, and householder demographic and income characteristics. PDF Tables: HC2 Space Heating, Million U.S. Households Presents data describing the types of heating fuel and equipment used for main and secondary heating purposes. PDF Tables: HC3 Air-Conditioning, Million U.S. Households Presents data describing selected household characteristics including location, number of rooms and area cooled and air-conditioning usage. PDF

    192

    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

    193

    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

    194

    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

    195

    Household Vehicles Energy Consumption 1991  

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

    C C Quality of the Data Appendix C Quality of the Data Introduction This appendix discusses several issues relating to the quality of the Residential Transportation Energy Consumption Survey (RTECS) data and to the interpretation of conclusions based on these data. The first section discusses under- coverage of the vehicle stock in the residential sector. The second section discusses the effects of using July 1991 as a time reference for the survey. The remainder of this appendix discusses the treatment of sampling and nonsampling errors in the RTECS, the quality of specific data items such as the Vehicle Identification Number (VIN) and fuel prices, and poststratification procedures used in the 1991 RTECS. The quality of the data collection and the processing of the data affects the accuracy of estimates based on survey data. All the statistics published in this report such as total

    196

    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

    197

    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

    198

    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

    199

    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

    200

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

    Note: This page contains sample records for the topic "household survey responses" 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

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

    202

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

    203

    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

    204

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

    205

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

    206

    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 ï‚· 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. ï‚· 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

    207

    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 ï‚· 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. ï‚· 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

    208

    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

    209

    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

    210

    Public comments and Task Force responses regarding the environmental survey of the reprocessing and waste management portions of the LWR fuel cycle  

    SciTech Connect

    This document contains responses by the NRC Task Force to comments received on the report ''Environmental Survey of the Reprocessing and Waste Management Portions of the LWR Fuel Cycle'' (NUREG-0116). These responses are directed at all comments, inclding those received after the close of the comment period. Additional information on the environmental impacts of reprocessing and waste management which has either become available since the publication of NUREG-0116 or which adds requested clarification to the information in that document.

    1977-03-01T23:59:59.000Z

    211

    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

    212

    Pacific Northwest Residential Energy Survey 1983 : Basic Findings.  

    SciTech Connect

    The survey was designed to support BPA's conservation assessment, program evaluation, and power forecasting responsibilities. The resulting data base contains information on the socio-economic status, family size, and energy-related attitudes of residential consumers, as well as on the heating systems, electric appliances, weatherization, and other conservation practices followed in their dwellings. Personal interviews were conducted at a probability sample of 4703 households in 57 utility service areas. In addition to interviewing customers, the Louis Harris staff measured the temperature of hot water at the tap and recorded the outside dimensions of the dwellings. The survey was begun in late May 1983 and was completed in September 1983. About 70% of the interviews were done in June and July 1983. Surveyors also obtained waivers allowing access to utility data covering the period between September 1981 and January 1983. After the interviews, utility billing data were requested.

    United States. Bonneville Power Administration.

    1986-04-01T23:59:59.000Z

    213

    DOETEIAO32l/2 Residential Energy Consumption Survey; Consumption  

    Gasoline and Diesel Fuel Update (EIA)

    sample custom-designed to meet the analytic objectives for surveys of residential energy use; sample as many as 5,500 households; provide 2-day personal training sessions...

    214

    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

    215

    Residential Energy Consumption Survey (RECS) - Data - U.S. Energy  

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

    2001 RECS Survey Data 2009 | 2005 | 2001 | 1997 | 1993 | Previous 2001 RECS Survey Data 2009 | 2005 | 2001 | 1997 | 1993 | Previous Housing Characteristics Consumption & Expenditures Microdata Methodology Housing Characteristics Tables + EXPAND ALL Tables HC1: Housing Unit Characteristics, Million U.S. Households PDF (all tables) Climate Zone PDF Year of Construction PDF Household Income PDF Type of Owner-Occupied Housing Unit PDF Four Most Populated States PDF Urban/Rural Location PDF Northeast Census Region PDF Midwest Census Region PDF South Census Region PDF West Census Region PDF Tables HC2: Household Characteristics, Million U.S. Households PDF (all tables) Climate Zone PDF Year of Construction PDF Household Income PDF Type of Housing Unit PDF Type of Owner-Occupied Housing Unit PDF Type of Rented Housing Unit PDF

    216

    Residential energy consumption survey: housing characteristics 1984  

    SciTech Connect

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

    Not Available

    1986-10-08T23:59:59.000Z

    217

    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

    218

    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

    219

    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

    220

    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

    Note: This page contains sample records for the topic "household survey responses" 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

    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

    222

    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

    223

    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

    224

    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...

    225

    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...

    226

    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

    227

    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...

    228

    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

    229

    Survey Evidence on the Willingness of U.S. Consumers to Pay for Automotive Fuel Economy  

    Science Conference Proceedings (OSTI)

    Prospect theory, which was awarded the Nobel Prize in Economics in 2002, holds that human beings faced with a risky bet will tend to value potential losses about twice as much as potential gains. Previous research has demonstrated that prospect theory could be sufficient to explain an energy paradox in the market for automotive fuel economy. This paper analyzes data from four random sample surveys of 1,000 U.S. households each in 2004, 2011, 2012 and 2013. Households were asked about willingness to pay for future fuel savings as well as the annual fuel savings necessary to justify a given upfront payment. Payback periods inferred from household responses are consistent over time and across different formulations of questions. Mean calculated payback periods are short, about 3 years, but there is substantial dispersion among individual responses. Calculated payback periods do not appear to be correlated with the attributes of respondents. Respondents were able to quantitatively describe their uncertainty about both vehicle fuel economy and future fuel prices. Simulation of loss averse behavior based on this stated uncertainty illustrate how loss aversion could lead consumers to substantially undervalue future fuel savings relative to their expected value.

    Greene, David L [ORNL; Evans, David H [Sewanee, The University of the South; Hiestand, John [Indiana University

    2013-01-01T23:59:59.000Z

    230

    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

    231

    User-needs study for the 1993 residential energy consumption survey  

    Science Conference Proceedings (OSTI)

    During 1992, the Energy Information Administration (EIA) conducted a user-needs study for the 1993 Residential Energy Consumption Survey (RECS). Every 3 years, the RECS collects information on energy consumption and expenditures for various classes of households and residential buildings. The RECS is the only source of such information within EIA, and one of only a few sources of such information anywhere. EIA sent letters to more than 750 persons, received responses from 56, and held 15 meetings with users. Written responses were also solicited by notices published in the April 14, 1992 Federal Register and in several energy-related publications. To ensure that the 1993 RECS meets current information needs, EIA made a specific effort to get input from policy makers and persons needing data for forecasting efforts. These particular needs relate mainly to development of the National Energy Modeling System and new energy legislation being considered at the time of the user needs survey.

    Not Available

    1993-09-24T23:59:59.000Z

    232

    Pacific Northwest residential energy survey. Volume 11. Climate Zone 3 cross-tabulations  

    Science Conference Proceedings (OSTI)

    Responses for Climate Zone 3 to fifty questions asked during the survey (plus four variables computed from responses to several other questions) are presented. Climate Zone 3 is defined according to the sum of heating and cooling degree days, and amounts to 7000 to 7999. A map outlines these four zones. The fifty questions were cross-tabulated against responses to nine questions which represent key explanatory characteristics of residential energy use. The nine key questions are: means of payment for housing; type of dwelling; year dwelling built; total square-footage of living space; type of fuel for main heating system; combined 1978 income; unit cost of electricity; annual electricity consumption; and annual natural gas consumption. The fifty questions and four computed variables which were cross-tabulated against the above fall into six categories: dwelling characteristics; heating and air-conditioning systems; water heating; appliances; demographic and dwelling characteristics; and insulation. The survey was conducted throughout the states of Washington, Oregon, Idaho, and Montana, with a total of 4030 households sampled. 480 households were sampled in Climate Zone 3. Information on 54 tables is explained. (MCW)

    Not Available

    1980-07-01T23:59:59.000Z

    233

    Pacific Northwest residential energy survey. Volume 9. Climate Zone 1 cross-tabulations  

    Science Conference Proceedings (OSTI)

    Responses for Climate Zone 1 to fifty questions asked during the survey (plus four variables computed from responses to several other questions) are presented. Climate Zone 1, defined according to the sum of heating and cooling degree days, amounts to less than 6000. The fifty questions were cross-tabulated against responses to nine questions which represent key explanatory characteristics of residential energy use. The nine key questions are: means of payment for housing; type of dwelling; year dwelling built; total square-footage of living space; type of fuel for main heating system; combined 1978 income; unit cost of electricity; annual electricity consumption; and annual natural gas consumption. The fifty questions and four computed variables which were cross-tabulated against the above fall into six categories; dwelling characteristics; heating and air-conditioning systems; water heating; appliances; demographic and dwelling characteristics; and insulation. The survey was conducted throughout the states of Washington, Oregon, Idaho, and Montana, with a total of 4030 households sampled; 1873 households were sampled in Climate Zone 1. Information in 54 tables is explained. (MCW)

    Not Available

    1980-07-01T23:59:59.000Z

    234

    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

    235

    Energy, the Environment and Behaviour Change: A survey of insights from behavioural economics  

    E-Print Network (OSTI)

    frameworks are imperfect, participation can establish credibility and good will (Gowdy 2008). Given that the North got rich by burning fossil fuels is it fair to tell the developing world to stop using them? Stiglitz (2006) argues that a fair solution could... upfront/sunk costs may constrain for households, particularly those facing fuel poverty. Brutscher (2011a) analyses liquidity constraints on households in Northern Ireland Continuous Household Survey (NICHS) and finds that, whilst there is a positive...

    Baddeley, Michelle

    236

    2010 Federal Employee Viewpoint Survey  

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

    Federal Employee Viewpoint Survey Federal Employee Viewpoint Survey Page 1 of 20 ________________________________________________________________________________________________________________________________________________________________________________________________________________ Department of Energy 2010 Federal Employee Viewpoint Survey: Trend Report (2006 and 2008 results have been recalculated to exclude Do Not Know/No Basis to Judge responses) Response Summary Surveys Completed 2010 Governmentwide 263,475 2010 Department of Energy 6,648 2008 Department of Energy 6,093 2006 Department of Energy 7,742 This 2010 Federal Employee Viewpoint Survey Report provides summary results for your department or agency. The results include Positive, Neutral, and Negative response percentages for each survey item. For each of the

    237

    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

    238

    Pacific Northwest Residential Energy Consumption Survey : Sample Selection Activities.  

    Science Conference Proceedings (OSTI)

    The primary purpose of the 1983 Pacific Northwest Residential Energy Consumption Survey is to obtain a comprehensive data base regarding household energy usage patterns incorporating not only general behavioral indicators of usage (e.g., temperature at which the dwelling is maintained at different times of day during the months of the year in which heating systems are activated or conservation measures effected) but also those characteristics lying further beyond the realm of immediate influence of the household dwellers which directly effect energy consumption (e.g., housing and household characteristics including square footage, number of floors or levels, the number and characteristics of the appliances in the household and household demographics/composition). The data base to be assembled as part of this research effort is also to include households' actual level of energy use for two major fuels (i.e., electricity and natural gas) obtained, with the consent of respondents, from their servicing utility(ies). Two samples have been incorporated in the study. The primary sample - the Regional Sample - will generate a large and comprehensive data base from a representative cross-section of individual households in the Pacific Northwest. A second, Supplementary Sample was incorporated in the survey design to ensure that a sufficient number of households not participating in qualified loan or grant programs, but comparable to participant households on a number of key descriptive characteristics, were included in the assessment. Inclusion of such households in the assessment will permit a formal evaluation of the loan/grant programs to be accomplished. Sampling procedures are described thoroughly.

    Louis Harris and Associates

    1983-08-03T23:59:59.000Z

    239

    Residential Energy Consumption Survey (RECS) - Analysis & Projections -  

    Gasoline and Diesel Fuel Update (EIA)

    What's new in our home energy use? What's new in our home energy use? RECS 2009 - Release date: March 28, 2011 First results from EIA's 2009 Residential Energy Consumption Survey (RECS) The 2009 RECS collected home energy characteristics data from over 12,000 U.S. households. This report highlights findings from the survey, with details presented in the Household Energy Characteristics tables. How we use energy in our homes has changed substantially over the past three decades. Over this period U.S. homes on average have become larger, have fewer occupants, and are more energy-efficient. In 2005, energy use per household was 95 million British thermal units (Btu) of energy compared with 138 million Btu per household in 1978, a drop of 31 percent. Did You Know? Over 50 million U.S. homes have three or more televisions.

    240

    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

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


    241

    Residential Energy Consumption Survey: housing characteristics, 1982  

    Science Conference Proceedings (OSTI)

    Data in this report cover fuels and their use in the home, appliances, square footage of floor space, heating equipment, thermal characteristics of the housing unit, conservation activities, wood consumption, indoor temperatures, and weather. The 1982 survey included a number of questions on the reasons households make energy conservation improvements to their homes. Results of these questions are presented. Discussion also highlights data pertaining to: trends in home heating fuels, trends in conservation improvements, and characteristics of households whose energy costs are included in their rent.

    Thompson, W.

    1984-08-01T23:59:59.000Z

    242

    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

    243

    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

    244

    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

    245

    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

    246

    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) ...

    247

    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 ...

    248

    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 ...

    249

    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

    250

    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

    251

    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

    252

    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

    253

    Residential Energy Consumption Survey Results: Total Energy Consumption,  

    Open Energy Info (EERE)

    Survey Results: Total Energy Consumption, Survey Results: Total Energy Consumption, Expenditures, and Intensities (2005) Dataset Summary Description The Residential Energy Consumption Survey (RECS) is a national survey that collects residential energy-related data. The 2005 survey collected data from 4,381 households in housing units statistically selected to represent the 111.1 million housing units in the U.S. Data were obtained from residential energy suppliers for each unit in the sample to produce the Consumption & Expenditures data. The Consumption & Expenditures and Intensities data is divided into two parts: Part 1 provides energy consumption and expenditures by census region, population density, climate zone, type of housing unit, year of construction and ownership status; Part 2 provides the same data according to household size, income category, race and age. The next update to the RECS survey (2009 data) will be available in 2011.

    254

    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)

    even after purchase incentives for natural gas and electricnatural gas, and gasoline vehicles. The use of purchase incentives

    Turrentine, Thomas; Kurani, Kenneth

    1995-01-01T23:59:59.000Z

    255

    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)

    of electric vehicles the safety of compressed gas vehicleselectric vehicles the practicality of home recharging or the safety

    Turrentine, Thomas; Kurani, Kenneth

    1995-01-01T23:59:59.000Z

    256

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

    E-Print Network (OSTI)

    Gromer, C Newage of the electric car. Popular Mechanics.VEHICLES strongly favor electric cars, but on the other,electric vehicles, if an electric car wasavailable to buy

    Turrentine, Thomas; Kurani, Kenneth S.

    2001-01-01T23:59:59.000Z

    257

    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)

    Gromer, C. New age of the electric car. Popular Mechanics.VEHICLES strongly favor electric cars, but on the other,electric vehicles, if an electric car was available to buy

    Turrentine, Thomas; Kurani, Kenneth

    1995-01-01T23:59:59.000Z

    258

    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)

    size styles) 5. Compressed natural gas, ranges 80 or 120,Hybrid electric: Compressed natural gas: Reformulatedof electric, compressed natural gas and methanol fueled

    Turrentine, Thomas; Kurani, Kenneth

    1995-01-01T23:59:59.000Z

    259

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

    E-Print Network (OSTI)

    B. C. D. E. F. Compressed natural gas Reformulated gasolineelectric ~]1 compressed natural gas [~1 reformulatedgasolinefull size styles) Compressed natural gas, ranges 80 or 120,

    Turrentine, Thomas; Kurani, Kenneth S.

    2001-01-01T23:59:59.000Z

    260

    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)

    gas vehicles and hybrid electric vehicles, in addition toof range, and hybrid electric vehicles with 140 and 180possible designs of hybrid electric vehicles pose complex

    Turrentine, Thomas; Kurani, Kenneth

    1995-01-01T23:59:59.000Z

    Note: This page contains sample records for the topic "household survey responses" 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

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

    E-Print Network (OSTI)

    gas vebacles and hybrid electric vehicles, maddition tocontrast to a hybrid electric vehicle that combines electrichousehold.In contrast to a hybrid electric vehicle that of

    Turrentine, Thomas; Kurani, Kenneth S.

    2001-01-01T23:59:59.000Z

    262

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

    E-Print Network (OSTI)

    and the demand electric vehicles", Transportation ResearchA,Critical Review Electric Vehicle MarketStudies", ReleasableR. (1993) Report of the Electric Vehicle at-HomeRefi~ehng

    Turrentine, Thomas; Kurani, Kenneth S.

    2001-01-01T23:59:59.000Z

    263

    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)

    a sidebar to a longer article on electric vehicles. ) Cogan,R. Electric vehicles: Powerplay on the auto circuit. MotorA Critical Review of Electric Vehicle Market Studies",

    Turrentine, Thomas; Kurani, Kenneth

    1995-01-01T23:59:59.000Z

    264

    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

    265

    Residential energy conservation and price response  

    SciTech Connect

    This paper examines the factors affecting the quantity of home heating fuel used and compares the willingness of consumers of natural gas (NG) and liquified petroleum gas (LPG) to adjust to very different changes in their heating costs over similar periods of time. LPG households made more and bigger temporary changes than did NG households and were more persistent in maintaining their behavior. LPG households also made structural improvements to the heat resistance of their homes while few NG households did so. Although people can adjust their fuel-use habits, a substantial economic incentive is required to create a significant and sustained response.

    Ogus, M.R.

    1982-03-01T23:59:59.000Z

    266

    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

    267

    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

    268

    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

    269

    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

    270

    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

    271

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

    E-Print Network (OSTI)

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

    Jennifer Beck; Jennifer Beck

    2008-01-01T23:59:59.000Z

    272

    Technical Appendix PUBLIC RESPONSE TO COMMUNITY MITIGATION MEASURES FOR PANDEMIC INFLUENZA  

    E-Print Network (OSTI)

    The survey was conducted in English and Spanish with a representative national sample of 1,697 adults age 18 and over, including an over-sample of adults who had children under age 18 in their households. Altogether 821 such adults with children were interviewed. In the overall results, this group was weighted to its actual proportion of the total adult population. The cooperation rate was 75%, and the response rate was 36%. The survey whose results are reported here did not include interviews with cellphoneonly adults, which might be a possible source of non-coverage bias. Estimates from the 2006 National Health Interview Survey suggest that about one in eight American homes have only wireless (mainly cellphone) telephone service. The incidence of cellphone-only households is higher for low-income and young adults. 1 A recent study has shown that when data are weighted demographically, including a cell-only sample with a landline RDD sample produces population estimates that are nearly identical to those from the landline sample alone. 2 However, another 1 study has shown that even after weighting, landline telephone surveys will underestimate the prevalence of certain health behaviors. 3 The study used in this paper shows that low-income people are likely to encounter more

    unknown authors

    2006-01-01T23:59:59.000Z

    273

    A Framework for Assessing the Net Benefits of Home Area Networks to Enable Demand Response  

    Science Conference Proceedings (OSTI)

    EPRI conducted an analysis to provide insight into the value of a Home Area Network (HAN) to a household. A HAN accommodates the flow of information to and from network nodes each associated with a device or element of the households electric system and devices. This collectivization of household devices facilitates managing the whole house load under demand response program protocols, and provides opportunities for additional payments to the household. EPRI conducted an analysis to see if the added stre...

    2010-12-31T23:59:59.000Z

    274

    2006 NERSC User Survey Results  

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

    6 User Survey Results 6 User Survey Results Show All | 1 2 3 4 5 ... 15 | Next » 2006 User Survey Results Table of Contents Survey Results Users are invited to provide overall comments about NERSC: Here are the survey results: Respondent Demographics Overall Satisfaction and Importance All Satisfaction, Importance and Usefulness Ratings All Usefulness Topics Hardware Resources Software Visualization and Data Analysis HPC Consulting Services and Communications Web Interfaces Training Comments about NERSC Survey Results Many thanks to the 256 users who responded to this year's User Survey. This represents a response rate of about 13 percent of the active NERSC users. The respondents represent all six DOE Science Offices and a variety of home institutions: see Respondent Demographics. The survey responses provide feedback about every aspect of NERSC's

    275

    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

    276

    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:

    277

    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:

    278

    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:

    279

    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:

    280

    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:

    Note: This page contains sample records for the topic "household survey responses" 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

    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

    282

    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

    283

    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

    284

    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

    285

    Assessing responses of humpback whales to North Pacific Acoustic Laboratory (NPAL) transmissions: Results of 2001–2003 aerial surveys north of Kauai  

    Science Conference Proceedings (OSTI)

    Eight aerial surveys were flown north of the Hawaiian island of Kauai during 2001 when the North Pacific Acoustic Laboratory (NPAL) source was not transmitting

    Joseph R. Mobley Jr.

    2005-01-01T23:59:59.000Z

    286

    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

    287

    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

    288

    Household energy conservation attitudes and behaviors in the Northwest: Tracking changes between 1983 and 1985  

    SciTech Connect

    Pacific Northwest Laboratory (PNL) has analyzed the changes in consumer energy conservation attitudes and behaviors in the Pacific Northwest between 1983 and 1985. The information was collected through stratified random telephone surveys on 2000 and 1058 households, respectively, for 1983 and 1985 in the Bonneville Power Administration (BPA) service area in Idaho, Oregon, Washington and Western Montana. This report covers four topic areas and tests two hypotheses. The topics are as follows: consumer perceptions and attitudes of energy use and conservation in the home; consumer perceptions of energy institutions and other entities; past and intended conservation actions and investments; and segmentation of homeowners into market prospect groups. The hypotheses tested are as follows: (1) There has been no change in the size and psychographic make-up of the original three market segments found in the 1983 survey analysis; and (2) image profiles of institutions with respect to familiarity, overall impression, and believability as sources of energy conservation information remain unchanged since 1983.

    Fang, J.M.; Hattrup, M.P.; Nordi, R.T.; Shankle, S.A.; Ivey, D.L.

    1987-05-01T23:59:59.000Z

    289

    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

    290

    Household Vehicles Energy Consumption 1994 - Appendix C  

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

    Introduction This appendix discusses several issues relating to the quality of the Residential Transportation Energy Consumption Survey (RTECS) data and to the interpretation of conclusions based on these data. The first section discusses undercoverage of the vehicle stock in the residential sector. The second section discusses the effects of using July 1994 as a time reference for the survey. The remainder of this appendix discusses the treatment of sampling and nonsampling errors in the RTECS, the quality of specific data items such as the Vehicle Identification Number (VIN) and fuel prices, and poststratification procedures used in the 1994 RTECS. The quality of the data collection and the processing of the data affects the accuracy of estimates based on survey data. All the statistics

    291

    COOKING APPLIANCE USE IN CALIFORNIA HOMES DATA COLLECTED FROM A WEB-BASED SURVEY  

    SciTech Connect

    Cooking of food and use of natural gas cooking burners generate pollutants that can have substantial impacts on residential indoor air quality. The extent of these impacts depends on cooking frequency, duration and specific food preparation activities in addition to the extent to which exhaust fans or other ventilation measures (e.g. windows) are used during cooking. With the intent of improving our understanding of indoor air quality impacts of cooking-related pollutants, we created, posted and advertised a web-based survey about cooking activities in residences. The survey included questions similar to those in California's Residential Appliance Saturation Survey (RASS), relating to home, household and cooking appliance characteristics and weekly patterns of meals cooked. Other questions targeted the following information not captured in the RASS: (1) oven vs. cooktop use, the number of cooktop burners used and the duration of burner use when cooking occurs, (2) specific cooking activities, (3) the use of range hood or window to increase ventilation during cooking, and (4) occupancy during cooking. Specific cooking activity questions were asked about the prior 24 hours with the assumption that most people are able to recollect activities over this time period. We examined inter-relationships among cooking activities and patterns and relationships of cooking activities to household demographics. We did not seek to obtain a sample of respondents that is demographically representative of the California population but rather to inexpensively gather information from homes spanning ranges of relevant characteristics including the number of residents and presence or absence of children. This report presents the survey, the responses obtained, and limited analysis of the results.

    Klug, Victoria; Lobscheid, Agnes; Singer, Brett

    2011-08-01T23:59:59.000Z

    292

    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

    293

    PowerChoice Residential Customer Response to TOU Rates  

    Science Conference Proceedings (OSTI)

    Research Into Action, Inc. and the Sacramento Municipal Utility District (SMUD) worked together to conduct research on the behaviors and energy use patterns of SMUD residential customers who voluntarily signed on to a Time-of-Use rate pilot launched under the PowerChoice label. The project was designed to consider the how and why of residential customers ability and willingness to engage in demand reduction behaviors, and to link social and behavioral factors to observed changes in demand. The research drew on a combination of load interval data and three successive surveys of participating households. Two experimental treatments were applied to test the effects of increased information on households ability to respond to the Time-of-Use rates. Survey results indicated that participants understood the purpose of the Time-of-Use rate and undertook substantial appropriate actions to shift load and conserve. Statistical tests revealed minor initial price effects and more marked, but still modest, adjustments to seasonal rate changes. Tests of the two information interventions indicated that neither made much difference to consumption patterns. Despite the lackluster statistical evidence for load shifting, the analysis points to key issues for critical analysis and development of residential Time-of-Use rates, especially pertinent as California sets the stage for demand response in more California residences.

    Peters, Jane S.; Moezzi, Mithra; Lutzenhiser, Susan; Woods, James; Dethman, Linda; Kunkle, Rick

    2009-10-01T23:59:59.000Z

    294

    Residential Energy Consumption Survey (RECS) - Analysis & Projections -  

    Gasoline and Diesel Fuel Update (EIA)

    EIA household energy use data now includes detail on 16 States EIA household energy use data now includes detail on 16 States RECS 2009 - Release date: March 28, 2011 EIA is releasing new benchmark estimates for home energy use for the year 2009 that include detailed data for 16 States, 12 more than in past EIA residential energy surveys. EIA has conducted the Residential Energy Consumption Survey (RECS) since 1978 to provide data on home energy characteristics, end uses of energy, and expenses for the four Census Regions and nine Divisions. In 1997, EIA produced additional tabulations for the four most populous States (California, New York, Texas, and Florida). A threefold increase in the number of households included in the 2009 RECS offers more accuracy and coverage for understanding energy usage for all estimated States, Regions and Divisions.

    295

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

    E-Print Network (OSTI)

    The purpose of this study was to determine the feasibility of conducting multiple household food inventories over the course of 30 days to examine weekly food variability. Household food availability influences the foods individuals choose to consume; therefore, by assessing the home food environment a better understanding of what people are eating can be obtained. Methods of measuring home food availability have been developed and tested in recent years; however most of these methods assess food availability on one occasion only. This study aimed to capture "usual" availability by using multiple assessments. After the development and pre-testing of the 171-item home observation guide to determine the presence and amount of food items in the home (refrigerator, freezer, pantry, elsewhere), two trained researchers recruited a convenience sample of 9 households (44.4% minority), administered a baseline questionnaire (personal info, shopping habits, food resources, and food security), and conducted 5 in-home assessments (5-7 day interval) over a 30-day period. Each in-home assessment included shopping and fast food activities since the last assessment and an observational survey of types and amounts of foods present. The final in-home assessment included an audio recorded interview on food habits and beliefs. Complete data were collected from all 9 women (32.8 y +/- 6.0; 3 married; 4 +/- 1.6 adults/children in household; 4 SNAP; 6 food insecure) and their households. Weekly grocery purchases (place, amount, and purpose) use (frequency) varied from once (n=1) to every week (n=5); 4 used fast food 2-3 times/wk for 4 weeks. Quantity and types of fresh and processed fruits and vegetables varied by week and by family. The feasibility of conducting multiple in-home assessments was confirmed with 100% retention from all participants. This methodology is important in that it provided detailed information on intra-monthly variation in food availability. The findings suggest the inadequacy of a single measure to assess food availability in the home.

    Sisk, Cheree L.

    2009-08-01T23:59:59.000Z

    296

    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.

    297

    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...

    298

    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...

    299

    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

    300

    Smoothing consumption across households and time : essays in development economics  

    E-Print Network (OSTI)

    This thesis studies two strategies that households may use to keep their consumption smooth in the face of fluctuations in income and expenses: credit (borrowing and savings) and insurance (state contingent transfers between ...

    Kinnan, Cynthia Georgia

    2010-01-01T23:59:59.000Z

    Note: This page contains sample records for the topic "household survey responses" 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

    1997 Survey Methods -- Residential Energy Consumption Survey ...  

    U.S. Energy Information Administration (EIA)

    ... of local sources of information, such as building-permit-issuing agencies, ... The FSA is interested in households living below the poverty level. ...

    302

    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

    303

    Solar energy industry survey  

    SciTech Connect

    This report describes the results of a survey of companies in the solar energy industry. The general objective of the survey was to provide information to help evaluate the effectiveness of technology transfer mechanisms for the development of the solar industry. The specific objectives of the survey included: (1) determination of the needs of the solar industry; (2) identification of special concerns of the solar industry; and (3) determination of the types of technology transfer mechanisms that would be most helpful to the solar industry in addressing these needs and concerns. The major focus was on technical problems and developments, but institutional and marketing considerations were also treated. The majority of the sample was devoted to the solar heating and cooling (SHAC) component of the industry. However, a small number of photovoltaic (PV), wind, and power generation system manufacturers were also surveyed. Part I discusses the methodology used in the selection, performance, and data reduction stages of the survey, comments on the nature of the responses, and describes the conclusions drawn from the survey. The latter include both general conclusions concerning the entire solar industry, and specific conclusions concerning component groups, such as manufacturers, architects, installers, or dealers. Part II consists of tabulated responses and non-attributed verbatim comments that summarize and illustrate the survey results.

    1979-08-06T23:59:59.000Z

    304

    2005 NERSC User Survey Results  

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

    5 User Survey Results 5 User Survey Results Show All | 1 2 3 4 5 ... 10 | Next » 2005 User Survey Results Table of Contents Response Summary Respondent Demographics All Satisfaction, Importance and Usefulness Ratings Hardware Resources Software Visualization and Data Analysis Services and Communications Web Interfaces Training Comments about NERSC Response Summary Many thanks to the 201 users who responded to this year's User Survey. The respondents represent all six DOE Science Offices and a variety of home institutions: see Respondent Demographics. The survey responses provide feedback about every aspect of NERSC's operation, help us judge the quality of our services, give DOE information on how well NERSC is doing, and point us to areas we can improve. The survey results are listed below.

    305

    2000 NERSC User Survey Results  

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

    0 User Survey Results 0 User Survey Results Show All | 1 2 3 4 5 ... 10 | Next » 2000 User Survey Results Table of Contents Response Summary User Information Overall Satisfaction and Importance All Satisfaction Questions and FY 1999 to FY 2000 Changes Consulting and Account Support Web and Communications Hardware Resources Software Resources Training User Comments Response Summary NERSC extends its thanks to all the users who participated in this year's survey. Your responses provide feedback about every aspect of NERSC's operation, help us judge the quality of our services, give DOE information on how well NERSC is doing, and point us to areas we can improve. Every year we institute changes based on the survey; the FY 1999 survey resulted in the following changes: We created a long-running queue (12 hours maximum) for jobs using up

    306

    2002 NERSC User Survey Results  

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

    2 User Survey Results 2 User Survey Results Show All | 1 2 3 4 5 ... 11 | Next » 2002 User Survey Results Table of Contents Response Summary User Information Overall Satisfaction and Importance All Satisfaction Questions and Changes from Previous Years Visualization and Grid Computing Web, NIM, and Communications Hardware Resources Software Training User Services Comments about NERSC Response Summary Many thanks to the 300 users who responded to this year's User Survey -- this represents the highest response level in the five years we have conducted the survey. The respondents represent all five DOE Science Offices and a variety of home institutions: see User Information. You can see the FY 2002 User Survey text, in which users rated us on a 7-point satisfaction scale. Some areas were also rated on a 3-point

    307

    California DREAMing: the design of residential demand responsive technology with people in mind  

    E-Print Network (OSTI)

    to inform people of their energy usage. We tested the systemcertain quality and energy usage standards of variousprice and household energy usage to enable demand response

    Peffer, Therese E.

    2009-01-01T23:59:59.000Z

    308

    DOE/EIA-0193/P PRELIMINARY CONSERVATION TABLES FROM THE NATIONAL INTERIM ENERGY CONSUMPTION SURVEY  

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

    193/P 193/P PRELIMINARY CONSERVATION TABLES FROM THE NATIONAL INTERIM ENERGY CONSUMPTION SURVEY OFFICE OF THE CONSUMPTION DATA SYSTEM OFFICE OF PROGRAM DEVELOPMENT ENERGY INFORMATION ADMINISTRATION AUGUST 1, 1979 PRELIMINARY CONSERVATION TABLES FROM THE NATIONAL INTERIM ENERGY CONSUMPTION SURVEY Attached is the first report of the Office of the Consumption Data System, Office of Program Development, Energy Information Administration, presenting preliminary data from the National Interim Energy Consumption Survey (NIECS). The focus of this report is the conservation activities performed by households since January 1977, and the status of households with respect to insulation, storm windows, and other energy conserving characteristics. These tables are from preliminary data files.

    309

    NATURAL GAS PROCESSING PLANT SURVEY FORM EIA-757 INSTRUCTIONS  

    U.S. Energy Information Administration (EIA)

    emergency response planning and actual emergencies. data published from this survey’s information. Thus, there may be some statistics that are based ...

    310

    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.

    311

    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

    312

    Digital Surveying Directional Surveying Specialists | Open Energy  

    Open Energy Info (EERE)

    Digital Surveying Directional Surveying Specialists Digital Surveying Directional Surveying Specialists Jump to: navigation, search OpenEI Reference LibraryAdd to library Web Site: Digital Surveying Directional Surveying Specialists Author Directional Surveying Specialists Published Publisher Not Provided, 2012 DOI Not Provided Check for DOI availability: http://crossref.org Online Internet link for Digital Surveying Directional Surveying Specialists Citation Directional Surveying Specialists. Digital Surveying Directional Surveying Specialists [Internet]. 2012. [cited 2013/10/08]. Available from: http://www.digitalsurveying.co.za/services/geophysical-borehole-surveying/overview/optical-televiewer/ Retrieved from "http://en.openei.org/w/index.php?title=Digital_Surveying_Directional_Surveying_Specialists&oldid=690244"

    313

    SCO Survey  

    Science Conference Proceedings (OSTI)

    Survey on Future of NIST's Standards Information Services. June 5, 2013. *. Bookmark and Share. Contact: Clare Allocca 301-975-4359. ...

    2013-06-05T23:59:59.000Z

    314

    2008/2009 NERSC User Survey Results  

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

    8/2009 User Survey Results 8/2009 User Survey Results Show All | 1 2 3 4 5 ... 9 | Next » 2008/2009 User Survey Results Table of Contents Response Survey Respondent Demographics Overall Satisfaction and Importance All Satisfaction and Importance Ratings Hardware Resources Software HPC Consulting Services and Communications Comments Response Survey Many thanks to the 421 users who responded to this year's User Survey. The response rate is comparable to last year's and both are significantly increased from previous years: 77.4 percent of users who had used more than 250,000 XT4-based hours when the survey opened responded 36.6 percent of users who had used between 10,000 and 250,000 XT4-based hours responded The overall response rate for the 3,134 authorized users during the survey period was 13.4%.

    315

    Residential Energy Consumption Survey: Consumption and expenditures, April 1984 through March 1985: Part 1, National data  

    Science Conference Proceedings (OSTI)

    This report presents data collected in the 1984 Residential Energy Consumption Survey (RECS) conducted by the Energy Information Administration (EIA). The 1984 RECS was the sixth national survey of US households and their energy suppliers. The purpose of these surveys is to provide baseline information on how households use energy. Households in all types of housing units - single family homes (including townhouses), apartments, and mobile homes - were chosen to participate. Data from the surveys are available to the public in published reports such as this one and on public-use data tapes. The report presents data on the US consumption and expenditures for residential use of these ''major fuels'' - natural gas, electricity, fuel oil, kerosene, and liquefied petroleum gas (LPG) - from April 1984 through March 1985. These data are presented in tables in the Detailed Statistics section of this report. Except for kerosene and wood fuel, the consumption and expenditures data are based on actual household bills obtained, with the permission of the household, from the companies supplying energy to the household. Purchases of kerosene are based on respondent reports because records of ''cash and carry'' purchases of kerosene for individual households are usually unavailable. Data on the consumption of wood fuel (Table 27) covers the 12-month period ending November 1984 and are based on respondent recall of the amount of wood burned during the 12-month period. Both the kerosene and wood consumption data are subject to memory errors and other reporting errors. This report does not cover household use of motor fuel, which is reported separately.

    Not Available

    1987-03-04T23:59:59.000Z

    316

    2002 Manufacturing Energy Consumption Survey - User Needs Survey  

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

    2002 Manufacturing Energy Consumption Survey: User-Needs Survey 2002 Manufacturing Energy Consumption Survey: User-Needs Survey View current results. We need your help in designing the next “ Energy Consumption Survey” (MECS)! As our valued customer, you are in an important position to tell us what kinds of data are most useful in helping you understand energy consumption in the U.S. manufacturing sector. Below is a short electronic survey with just a few questions. We will stop collecting responses for user feedback on May 17, 2002. This deadline serves to meet our intended release date of April/May 2003 for fielding MECS2002. The MECS is designed to produce estimates of energy consumption and other energy-related activities in manufacturing. The survey also collects information on energy expenditures, average prices, onsite generation of

    317

    2004 NERSC User Survey Results  

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

    4 User Survey Results 4 User Survey Results Show All | 1 2 3 4 5 ... 13 | Next » 2004 User Survey Results Table of Contents Response Summary Respondent Demographics Overall Satisfaction and Importance All Satisfaction, Importance and Usefulness Ratings Hardware Resources Software Security and One Time Passwords Visualization and Data Analysis HPC Consulting Services and Communications Web Interfaces Training Comments about NERSC Response Summary Many thanks to the 209 users who responded to this year's User Survey. The respondents represent all six DOE Science Offices and a variety of home institutions: see Respondent Demographics. The survey responses provide feedback about every aspect of NERSC's operation, help us judge the quality of our services, give DOE information on how well NERSC is doing, and point us to areas we can improve. The

    318

    Survey Consumption  

    Gasoline and Diesel Fuel Update (EIA)

    fsidentoi fsidentoi Survey Consumption and 'Expenditures, April 1981 March 1982 Energy Information Administration Wasningtoa D '" N """"*"""*"Nlwr. . *'.;***** -. Mik>. I This publication is available from ihe your COr : 20585 Residential Energy Consumption Survey: Consum ption and Expendi tures, April 1981 Through March 1982 Part 2: Regional Data Prepared by: Bruce Egan This report was prepared by the Energy Information Administra tion, the independent statistical

    319

    Pacific Northwest residential energy survey. Volume 12. Climate Zone 4 cross-tabulations  

    Science Conference Proceedings (OSTI)

    Responses for Climate Zone 4 to fifty questions asked during the survey (plus four variables computed from responses to several other questions) are presented. Climate Zone 4 is defined according to the sum of heating and cooling degree days, and amounts to over 8000. A map outlines the four zones. The fifty questions were cross-tabulated against responses to nine questions which represent key explanatory characteristics of residential energy use. The nine key questions are: means of payment for housing; type of dwelling; year dwelling built; total square-footage of living space; type of fuel for main heating system; combined 1978 income; unit cost of electricity; annual electricity consumption; and annual natural gas consumption. The fifty questions and four computed variables which were cross-tabulated against the above fall into six categories: dwelling characteristics; heating and air-conditioning systems; water heating; appliances; demographic and dwelling characteristics; and insulation. The survey was conducted throughout the states of Washington, Oregon, Idaho, and Montana, with a total of 4030 households sampled; 992 househould were sampled in Climate Zone 4. Information on 54 tables is explained. (MCW)

    Not Available

    1980-07-01T23:59:59.000Z

    320

    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

    Note: This page contains sample records for the topic "household survey responses" 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

    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

    322

    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

    323

    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

    324

    Climate Survey  

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

    Operations Employee Operations Employee Climate Survey March 2009 Acknowledgements The Berkeley Lab Survey Team consisted of the following: Jim Krupnick, Sponsor Vera Potapenko, Project Lead Karen Ramorino, Project Manager Chris Paquette, MOR Associates Alexis Bywater, MOR Associates MOR Associates, an external consulting firm, acted as project manager for this effort, analyzing the data and preparing this report. MOR Associates specializes in continuous improve- ment, strategic thinking and leadership development. MOR Associates has conducted a number of large-scale surveys for organizations in higher education, including MIT, Stanford, the University of Chicago, and others. MOR Associates, Inc. 462 Main Street, Suite 300 Watertown, MA 02472 tel: 617.924.4501

    325

    Residential Housing Survey  

    U.S. Energy Information Administration (EIA)

    PCs, Modems and Laser Printers: Main Heating Fuels: Household PC Usage : Use of Central Heating Systems: Stoves, Ovens and Microwaves: Main Central ...

    326

    VLBI surveys  

    E-Print Network (OSTI)

    Systematic surveys of astronomical objects often lead to discoveries, but always provide invaluable information for statistical studies of well-defined samples. They also promote follow-up investigations of individual objects or classes. Surveys using a yet unexplored observing wavelength, a novel technique or a new instrument are of special importance. Significantly improved observing parameters (e.g. sensitivity, angular resolution, monitoring capability) provide new insight into the morphological and physical properties of the objects studied. I give a brief overview of the important Very Long Baseline Interferometry (VLBI) imaging surveys conducted in the past. A list of surveys guides us through the developments up until the present days. I also attempt to show directions for the near future.

    S. Frey

    2006-11-08T23:59:59.000Z

    327

    Review: A survey of models and algorithms for emergency response logistics in electric distribution systems. Part I: Reliability planning with fault considerations  

    Science Conference Proceedings (OSTI)

    Emergency response operations in electric distribution systems involve a host of decision-making problems at the reliability and contingency planning levels. Those operations include fault diagnosis, fault location, fault isolation, restoration, and ... Keywords: Depot location, District design, Electric power distribution, Emergency response, Operations research, System configuration

    Nathalie Perrier; Bruno Agard; Pierre Baptiste; Jean-Marc Frayret; André Langevin; Robert Pellerin; Diane Riopel; Martin TréPanier

    2013-07-01T23:59:59.000Z

    328

    Balancing Authority Related Proposals for EIA Surveys  

    U.S. Energy Information Administration (EIA)

    for EIA Surveys EIA Stakeholder Presentation June 5, 2012 . ... smart grid technologies and demand response. Require balancing authorities to post the next day

    329

    2009/2010 NERSC User Survey Results  

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

    Demographics Overall Satisfaction All Satisfaction and Importance Ratings HPC Resources NERSC Software Services Comments Survey Text Response Summary Many thanks to the 395 users...

    330

    Model development for household waste prevention behaviour  

    Science Conference Proceedings (OSTI)

    Highlights: Black-Right-Pointing-Pointer We model waste prevention behaviour using structure equation modelling. Black-Right-Pointing-Pointer We merge attitude-behaviour theories with wider models from environmental psychology. Black-Right-Pointing-Pointer Personal norms and perceived behaviour control are the main behaviour predictors. Black-Right-Pointing-Pointer Environmental concern, moral obligation and inconvenience are the main influence on the behaviour. Black-Right-Pointing-Pointer Waste prevention and recycling are different dimensions of waste management behaviour. - Abstract: Understanding waste prevention behaviour (WPB) could enable local governments and decision makers to design more-effective policies for reducing the amount of waste that is generated. By merging well-known attitude-behaviour theories with elements from wider models from environmental psychology, an extensive cognitive framework that provides new and valuable insights is developed for understanding the involvement of individuals in waste prevention. The results confirm the usefulness of the theory of planned behaviour and of Schwartz's altruistic behaviour model as bases for modelling participation in waste prevention. A more elaborate integrated model of prevention was shown to be necessary for the complete analysis of attitudinal aspects associated with waste prevention. A postal survey of 158 respondents provided empirical support for eight of 12 hypotheses. The proposed structural equation indicates that personal norms and perceived behaviour control are the main predictors and that, unlike the case of recycling, subjective norms have a weak influence on WPB. It also suggests that, since social norms have not presented a direct influence, WPB is likely to be influenced by a concern for the environment and the community as well by perceptions of moral obligation and inconvenience. Results also proved that recycling and waste prevention represent different dimensions of waste management behaviour requiring particular approaches to increase individuals' engagement in future policies.

    Bortoleto, Ana Paula, E-mail: a.bortoleto@sheffield.ac.uk [Department of Urban Engineering, University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo 113-8656 (Japan); Kurisu, Kiyo H.; Hanaki, Keisuke [Department of Urban Engineering, University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo 113-8656 (Japan)

    2012-12-15T23:59:59.000Z

    331

    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

    332

    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.

    333

    Modeling household adoption of earthquake hazard adjustments: a longitudinal panel study of Southern California and Western Washington residents  

    E-Print Network (OSTI)

    This research, aimed at advancing the theory of environmental hazard adjustment processes by contrasting households from three cities in a high seismic hazard area with households from three other cities in a moderate seismic hazard area. It identified seven types of stakeholders namely, the risk area residents and their families (primary group), the news media, employers, and friends (secondary group), and federal, state, and local governments (tertiary group), and explained why they are relevant to the adoption of seismic hazard adjustments. It also addressed three key attributes� knowledge, trustworthiness, and responsibility for protection�ascribed to these multiple stakeholders and the relationships of these stakeholder attributes with risk perception, hazard intrusiveness, hazard experience, gender, resource adequacy, fatalism and hazard adjustment adoption. It was specifically concerned with the effects of nested interactions due to trust and power differentials among the seven stakeholders, with the self reported adoption of 16 earthquake protective measures at two points in time (1997 and 1999). Some of the key findings indicate that risk perception, gender, fatalism, city activity in earthquake management and demographic characteristics did not significantly predict hazard adjustment adoption. However, all stakeholder characteristics had significant positive correlations with risk perception and hazard adjustment, implying a peripheral route for social influence. Hazard intrusiveness, hazard experience, and stakeholder knowledge, trustworthiness, and responsibility affected the increased adoption of hazard adjustments by households. Particularly important are the peer groups� (employers, friends and family) knowledge, trustworthiness and responsibility. These findings suggest, hazard managers cannot count only on the federal, state, and local government advisories put out through the news media to affect community decisions and thereby households� decisions to take protective actions. Instead, hazard managers need to shift focus and work through peer group networks such as service organizations, industry groups, trade unions, neighborhood organizations, community emergency response teams, faith-based organizations, and educational institutions to increase the knowledge, trustworthiness and responsibility of all in the peer group. This will assure higher household hazard adjustment adoption levels, thus facilitating a reduction in post disaster losses and recovery time.

    Arlikatti, Sudha S

    2006-08-01T23:59:59.000Z

    334

    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

    335

    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

    336

    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 ...

    337

    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

    338

    U.S. Climate Zones-Households - - Energy Information Administration  

    U.S. Energy Information Administration (EIA)

    Residential Sector energy Intensities for 1978-1997 using data from EIA Residential Energy Consumption Survey.

    339

    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

    340

    AERIAL RADIOLOGICAL SURVEYS  

    SciTech Connect

    Measuring terrestrial gamma radiation from airborne platforms has proved to be a useful method for characterizing radiation levels over large areas. Over 300 aerial radiological surveys have been carried out over the past 25 years including U.S. Department of Energy (DOE) sites, commercial nuclear power plants, Formerly Utilized Sites Remedial Action Program/Uranium Mine Tailing Remedial Action Program (FUSRAP/UMTRAP) sites, nuclear weapons test sites, contaminated industrial areas, and nuclear accident sites. This paper describes the aerial measurement technology currently in use by the Remote Sensing Laboratory (RSL) for routine environmental surveys and emergency response activities. Equipment, data-collection and -analysis methods, and examples of survey results are described.

    Proctor, A.E.

    1997-06-09T23:59:59.000Z

    Note: This page contains sample records for the topic "household survey responses" 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

    National Household Travel Survey (NHTS): Travel Trends, Analysis and Data Tools  

    E-Print Network (OSTI)

    of the nation's transportation system to meet current demands and accommodate future demands; to assess of alternative transportation investment programs; and to assess the energy-use and air-quality impacts Analysis Data, Statistical Analysis Geo-Spatial Information Tools Defense Transportation Energy Policy

    342

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

    E-Print Network (OSTI)

    of activity space to be associated with propulsion systemactivity spaces are related to choices of propulsion systems

    Kurani, Kenneth; Turrentine, Thomas; Sperling, Daniel

    1996-01-01T23:59:59.000Z

    343

    Household activities through various lenses: crossing surveys, diaries and electric consumption  

    E-Print Network (OSTI)

    comparison between electricity consumption and behavioralK. 2013. “Domestic energy consumption-What role do comfort,residential electricity consumption” Energy Policy, 42(2012)

    Durand-Daubin, Mathieu

    2013-01-01T23:59:59.000Z

    344

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

    E-Print Network (OSTI)

    travel by electric and hybrid vehicles. SAE Technical PapersIn contrast to a hybrid vehicle which combines multipleElectric, Hybrid and Other Alternative Vehicles. A r t h u r

    Kurani, Kenneth; Turrentine, Thomas; Sperling, Daniel

    1996-01-01T23:59:59.000Z

    345

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

    E-Print Network (OSTI)

    new feanlres of compressed natural gas. battery poweredgasoline, compressed natural gas, hybrid dectdc, two typesNatural gas vehicles (NGVs) were available with one two compressed

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

    2001-01-01T23:59:59.000Z

    346

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

    E-Print Network (OSTI)

    new features of compressed natural gas, battery poweredgasoline, compressed natural gas, hybrid electric, two typesNatural gas vehicles (NGVs) were available with one or two compressed

    Kurani, Kenneth; Turrentine, Thomas; Sperling, Daniel

    1996-01-01T23:59:59.000Z

    347

    Household activities through various lenses: crossing surveys, diaries and electric consumption  

    E-Print Network (OSTI)

    changes differ from one appliance to another. Referencespeople activities, appliances use, and electric consumption.of use of the three appliances studied. However, variations

    Durand-Daubin, Mathieu

    2013-01-01T23:59:59.000Z

    348

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

    E-Print Network (OSTI)

    the demand electric vehicles’, TransportationResearchA,1994) ~tive NewsCalifornia Electric Vehicle ConsumerStudy.1995) Forecasting Electric Vehicle Ownership Use in the

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

    2001-01-01T23:59:59.000Z

    349

    2001 NERSC User Survey Results  

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

    1 User Survey Results 1 User Survey Results Show All | 1 2 3 4 5 ... 11 | Next » 2001 User Survey Results Table of Contents Response Summary User Information Overall Satisfaction and Importance All Satisfaction Questions and Changes from Previous Years NERSC Information Management (NIM) System Web and Communications Hardware Resources Software Training User Services Comments about NERSC Response Summary NERSC extends its thanks to the 237 users who participated in this year's survey; this compares with 134 respondents last year. The respondents represent all five DOE Science Offices and a variety of home institutions: see User Information. Your responses provide feedback about every aspect of NERSC's operation, help us judge the quality of our services, give DOE information on how well

    350

    Magma Source Location Survey  

    DOE Green Energy (OSTI)

    A survey of Industry/University geophysicists was conducted to obtain their opinions on the existence of shallow (less than 10 km from surface) magma bodies in the western conterminous United States and methods for locating and defining them. Inputs from 35 individuals were received and are included. Responses were that shallow magma bodies exist and that existing geophysical sensing systems are adequate to locate them.

    Hardee, H.C.; Dunn, J.C.; Colp, J.L.

    1982-03-01T23:59:59.000Z

    351

    Analysis of Consumer Response to Automobile Regulation and Technological Change in Support of California Climate Change Rulemaking  

    E-Print Network (OSTI)

    percent of market) and the hybrid car segment (0.1 percentmost new cars (with the exceptions of hybrids) have aboutHybrid Household Hypothesis—A Reflexively Designed Survey of New-car-

    Kurani, Kenneth S; Turrentine, Tom

    2004-01-01T23:59:59.000Z

    352

    2007/2008 NERSC User Survey Results  

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

    7/2008 User Survey Results 7/2008 User Survey Results Show All | 1 2 3 4 5 ... 10 | Next » 2007/2008 User Survey Results Table of Contents Response Summary Overall Satisfaction and Importance All Satisfaction, Importance and Usefulness Ratings Hardware Resources Software Visualization and Data Analysis HPC Consulting Services and Communications Web Interfaces Comments about NERSC Response Summary Many thanks to the 467 users who responded to this year's User Survey. The response rate has significantly increased from previous years: 70 percent of users who had used more than 1 million MPP hours when the survey opened responded 43 percent of users who had used between 10,000 and 1 million MPP hours responded The overall response rate for the 2,804 authorized users during the survey period was 16.3%.

    353

    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

    354

    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

    355

    An Analysis of the Price Elasticity of Demand for Household Appliances  

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

    Analysis of the Price Elasticity of Demand for Analysis of the Price Elasticity of Demand for Household Appliances Larry Dale and K. Sydny Fujita February 2008 Energy Analysis Department Environmental Energy Technologies Division Lawrence Berkeley National Laboratory University of California Berkeley, CA 94720 DISCLAIMER This document was prepared as an account of work sponsored by the United States Government. While this document is believed to contain correct information, neither the United States Government nor any agency thereof, nor The Regents of the University of California, nor any of their employees, makes any warranty, express or implied, or assumes any legal responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not

    356

    1999 NERSC User Survey Results  

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

    9 User Survey Results 9 User Survey Results Show All | 1 2 3 4 5 ... 11 | Next » 1999 User Survey Results Table of Contents Respondent Summary Overall Satisfaction User Information Visualization Consulting and Account Support Information Technology and Communication Hardware Resources Software Training Comments about NERSC All Satisfaction Questions and FY 1998 to FY 1999 Changes Respondent Summary NERSC would like to thank all the users who participated in this year's survey. Your responses provide feedback about every aspect of NERSC's operation, help us judge the quality of our services, give DOE information on how well NERSC is doing, point us to areas we can improve, and show how we compare to similar facilities. This year 177 users responded to our survey, compared with 138 last year.

    357

    Cost comparison between private and public collection of residual household waste: Multiple case studies in the Flemish region of Belgium  

    SciTech Connect

    Highlights: Black-Right-Pointing-Pointer The goal is to compare collection costs for residual household waste. Black-Right-Pointing-Pointer We have clustered all municipalities in order to find mutual comparable pairs. Black-Right-Pointing-Pointer Each pair consists of one private and one public operating waste collection program. Black-Right-Pointing-Pointer All cases show that private service has lower costs than public service. Black-Right-Pointing-Pointer Municipalities were contacted to identify the deeper causes for the waste management program. - Abstract: The rising pressure in terms of cost efficiency on public services pushes governments to transfer part of those services to the private sector. A trend towards more privatizing can be noticed in the collection of municipal household waste. This paper reports the findings of a research project aiming to compare the cost between the service of private and public collection of residual household waste. Multiple case studies of municipalities about the Flemish region of Belgium were conducted. Data concerning the year 2009 were gathered through in-depth interviews in 2010. In total 12 municipalities were investigated, divided into three mutual comparable pairs with a weekly and three mutual comparable pairs with a fortnightly residual waste collection. The results give a rough indication that in all cases the cost of private service is lower than public service in the collection of household waste. Albeit that there is an interest in establishing whether there are differences in the costs and service levels between public and private waste collection services, there are clear difficulties in establishing comparisons that can be made without having to rely on a large number of assumptions and corrections. However, given the cost difference, it remains the responsibility of the municipalities to decide upon the service they offer their citizens, regardless the cost efficiency: public or private.

    Jacobsen, R., E-mail: ray.jacobsen@ugent.be [Department of Agricultural Economics, Ghent University, Coupure Links 653, B-9000 Ghent (Belgium); Buysse, J., E-mail: j.buysse@ugent.be [Department of Agricultural Economics, Ghent University, Coupure Links 653, B-9000 Ghent (Belgium); Gellynck, X., E-mail: xavier.gellynck@ugent.be [Department of Agricultural Economics, Ghent University, Coupure Links 653, B-9000 Ghent (Belgium)

    2013-01-15T23:59:59.000Z

    358

    JOM Salary Survey - TMS  

    Science Conference Proceedings (OSTI)

    JOM Salary Survey. This survey is currently closed. Please contact the author of this survey for further assistance. Javascript is required for this site to function, ...

    359

    DOE/EIA-0207/3 Residential Energy Consumption Survey: Conservation  

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

    3 3 Residential Energy Consumption Survey: Conservation February 1980 U.S. Department of Energy Energy Information Adminstration Assistant Administrater for Program Development Other NEICS Reports Preliminary Conservation Tables from the National Interim Energy Consumption Survey, August 1979, DOE/EIA-0193/P Characteristics of the Housing Stocks and Households: Preliminary Findings from the National Interim Energy Consumption Survey, October 1979, DOETllA-0199/P The above reports are available from the following address; U.S. Department of Energy Technical Information Center Attn:; EIA Coordinator P.O. Box 62 Oak Ridge, TN 37830 Residential Energy Consumption Survey; Characteristics of the Housing Stock and Households, DOE/EIA-0207/2, GPO Stock No,, 061-003-00093-2; $4.25

    360

    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

    Note: This page contains sample records for the topic "household survey responses" 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

    2012 NERSC User Survey  

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

    Results 2012 User Survey Text 2012 NERSC User Survey Text The 2012 NERSC User Survey is closed. The following is the text of the survey. Section 1: Overall Satisfaction with...

    362

    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:

    363

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

    Annual Energy Outlook 2012 (EIA)

    Fuel Oil or Kerosene Usage Form OMB No. 1905-0092, Expiring February 29, 2004 2001 Residential Energy Consumption Survey Answers to Frequently Asked Questions About the...

    364

    Household Electricity Usage Form - U.S. Energy Information ...  

    U.S. Energy Information Administration (EIA)

    2005 Residential Energy Consumption Survey. Sponsored by the Energy Information Administration . U.S. Department of Energy . Washington, DC 20585 . Form EIA-457E ...

    365

    Household Markets for Neighborhood Electric Vehicles in California  

    E-Print Network (OSTI)

    A Statewide ELECTRIC ELECTRIC and VEHICLES: Survey Sandrafor Neighborhood Electric Vehicles. Report prepared for theD. (1994). Future Drive: Electric Vehicles and Sustainable

    Kurani, Kenneth S.; Sperling, Daniel; Lipman, Timothy; Stanger, Deborah; Turrentine, Thomas; Stein, Aram

    2001-01-01T23:59:59.000Z

    366

    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

    367

    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

    368

    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 ...

    369

    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

    370

    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

    371

    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

    372

    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, ...

    373

    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

    374

    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...

    375

    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) ...

    376

    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.

    377

    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

    378

    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

    379

    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

    380

    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 ...

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


    381

    Table 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 ...

    382

    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

    383

    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

    384

    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 ...

    385

    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.

    386

    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 ...

    387

    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."

    388

    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

    389

    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

    390

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

    SciTech Connect

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

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

    1994-08-01T23:59:59.000Z

    391

    Nuclear Engineering Academic Programs Survey, 2002 Data  

    SciTech Connect

    The survey includes degrees granted between July 1, 2001 and June 30, 2002. Enrollment information refers to the fall term 2002. Thirty-five academic programs were in the survey universe and all responded (100% response rate). One of the 35 programs reported that it was discontinued after the 2001-2002 academic year. Also, two programs were discontinued after the previous academic year (2000-2001) and were not included in 2002 survey.

    Oak Ridge Institute for Science and Education

    2003-10-01T23:59:59.000Z

    392

    Nuclear Engineering Academic Programs Survey, 2003  

    SciTech Connect

    The survey includes degrees granted between September 1, 2002 and August 31, 2003. Thirty-three academic programs reported having nuclear engineering programs during the survey time period and all responded (100% response rate). Three of the programs included in last year's report were discontinued or out-of-scope in 2003. One new program has been added to the list. This year the survey data include U.S. citizenship, gender, and race/ethnicity by degree level.

    Science and Engineering Education, Oak Ridge Institute for Science and Education

    2004-03-01T23:59:59.000Z

    393

    Helicopter magnetic survey conducted to locate wells  

    Science Conference Proceedings (OSTI)

    A helicopter magnetic survey was conducted in August 2007 over 15.6 sq mi at the Naval Petroleum Reserve No. 3’s (NPR-3) Teapot Dome Field near Casper, Wyoming. The survey’s purpose was to accurately locate wells drilled there during more than 90 years of continuous oilfield operation. The survey was conducted at low altitude and with closely spaced flight lines to improve the detection of wells with weak magnetic response and to increase the resolution of closely spaced wells. The survey was in preparation for a planned CO2 flood for EOR, which requires a complete well inventory with accurate locations for all existing wells. The magnetic survey was intended to locate wells missing from the well database and to provide accurate locations for all wells. The ability of the helicopter magnetic survey to accurately locate wells was accomplished by comparing airborne well picks with well locations from an intense ground search of a small test area.

    Veloski, G.A.; Hammack, R.W.; Stamp, V. (Rocky Mountain Oilfield Testing Center); Hall, R. (Rocky Mountain Oilfield Testing Center); Colina, K. (Rocky Mountain Oilfield Testing Center)

    2008-07-01T23:59:59.000Z

    394

    AMS MEMBERSHIP SURVEY RESULTS: An Overview and Longitudinal Analysis of the Demographics of the AMS  

    Science Conference Proceedings (OSTI)

    The 2005 membership survey is the fifth in a series of surveys that has monitored the composition of the AMS since 1975. The responses of the 2005 survey reveal several interesting changes in the educational level, employment characteristics, and ...

    Shirley T. Murillo; Rajul E. Pandya; Raymond Y. Chu; Roman Czujko; Julie A. Winkler; Elen M. C. Cutrim

    2008-05-01T23:59:59.000Z

    395

    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

    396

    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

    397

    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

    398

    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

    399

    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

    400

    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?

    Note: This page contains sample records for the topic "household survey responses" 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

    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?

    402

    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

    403

    Residential Energy Consumption Survey (RECS) - U.S. Energy Information  

    Gasoline and Diesel Fuel Update (EIA)

    About the RECS About the RECS RECS Survey Forms RECS Maps RECS Terminology Archived Reports State fact sheets Arizona household graph See state fact sheets › 2009 RECS Features Heating and cooling no longer majority of U.S. home energy use March 7, 2013 Newer U.S. homes are 30% larger but consume about as much energy as older homes February 12, 2013 Where does RECS square footage data come from? July 11, 2012 RECS data show decreased energy consumption per household June 6, 2012 The impact of increasing home size on energy demand April 19, 2012 Did you know that air conditioning is in nearly 100 million U.S. homes? August 19, 2011 See more > graph of U.S. electricity end use, as explained in the article text U.S. electricity sales have decreased in four of the past five years

    404

    Residential Energy Consumption Survey (RECS) - Analysis & Projections -  

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

    About the RECS About the RECS RECS Survey Forms RECS Maps RECS Terminology Archived Reports State fact sheets Arizona household graph See state fact sheets › 2009 RECS Features Heating and cooling no longer majority of U.S. home energy use March 7, 2013 Newer U.S. homes are 30% larger but consume about as much energy as older homes February 12, 2013 Where does RECS square footage data come from? July 11, 2012 RECS data show decreased energy consumption per household June 6, 2012 The impact of increasing home size on energy demand April 19, 2012 Did you know that air conditioning is in nearly 100 million U.S. homes? August 19, 2011 See more > graph of U.S. electricity end use, as explained in the article text U.S. electricity sales have decreased in four of the past five years

    405

    Residential Energy Consumption Survey (RECS) - Analysis & Projections -  

    Gasoline and Diesel Fuel Update (EIA)

    About the RECS About the RECS RECS Survey Forms RECS Maps RECS Terminology Archived Reports State fact sheets Arizona household graph See state fact sheets › 2009 RECS Features Heating and cooling no longer majority of U.S. home energy use March 7, 2013 Newer U.S. homes are 30% larger but consume about as much energy as older homes February 12, 2013 Where does RECS square footage data come from? July 11, 2012 RECS data show decreased energy consumption per household June 6, 2012 The impact of increasing home size on energy demand April 19, 2012 Did you know that air conditioning is in nearly 100 million U.S. homes? August 19, 2011 See more > graph of U.S. electricity end use, as explained in the article text U.S. electricity sales have decreased in four of the past five years

    406

    Robotic Surveying  

    SciTech Connect

    ZAPATA ENGINEERING challenged our engineers and scientists, which included robotics expertise from Carnegie Mellon University, to design a solution to meet our client's requirements for rapid digital geophysical and radiological data collection of a munitions test range with no down-range personnel. A prime concern of the project was to minimize exposure of personnel to unexploded ordnance and radiation. The field season was limited by extreme heat, cold and snow. Geographical Information System (GIS) tools were used throughout this project to accurately define the limits of mapped areas, build a common mapping platform from various client products, track production progress, allocate resources and relate subsurface geophysical information to geographical features for use in rapidly reacquiring targets for investigation. We were hopeful that our platform could meet the proposed 35 acres per day, towing both a geophysical package and a radiological monitoring trailer. We held our breath and crossed our fingers as the autonomous Speedrower began to crawl across the playa lakebed. We met our proposed production rate, and we averaged just less than 50 acres per 12-hour day using the autonomous platform with a path tracking error of less than +/- 4 inches. Our project team mapped over 1,800 acres in an 8-week (4 days per week) timeframe. The expertise of our partner, Carnegie Mellon University, was recently demonstrated when their two autonomous vehicle entries finished second and third at the 2005 Defense Advanced Research Projects Agency (DARPA) Grand Challenge. 'The Grand Challenge program was established to help foster the development of autonomous vehicle technology that will some day help save the lives of Americans who are protecting our country on the battlefield', said DARPA Grand Challenge Program Manager, Ron Kurjanowicz. Our autonomous remote-controlled vehicle (ARCV) was a modified New Holland 2550 Speedrower retrofitted to allow the machine-actuated functions to be controlled by an onboard computer. The computer-controlled Speedrower was developed at Carnegie Mellon University to automate agricultural harvesting. Harvesting tasks require the vehicle to cover a field using minimally overlapping rows at slow speeds in a similar manner to geophysical data acquisition. The Speedrower had demonstrated its ability to perform as it had already logged hundreds of acres of autonomous harvesting. This project is the first use of autonomous robotic technology on a large-scale for geophysical surveying.

    Suzy Cantor-McKinney; Michael Kruzic

    2007-03-01T23:59:59.000Z

    407

    RTO and Balancing AuthoritProposals for EIA Surveys  

    U.S. Energy Information Administration (EIA)

    ... Integration of renewable generation Implementation of demand response Integration of new ... RTO and Balancing AuthoritProposals for EIA Surveys Author: USCX ...

    408

    EIA survey shows Gulf Coast plants recovering from hurricane ...  

    U.S. Energy Information Administration (EIA)

    In response to Hurricane Isaac, EIA invoked its emergency-activation survey Form EIA-757B to collect daily data on the status of natural gas ...

    409

    1998 NERSC User Survey Results  

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

    8 User Survey Results 1998 User Survey Results Respondent Summary NERSC has completed its first user survey since its move to Lawrence Berkeley National Laboratory. The survey is...

    410

    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

    411

    A model to assess the relative impact of policy in transportation energy expenditures  

    Science Conference Proceedings (OSTI)

    The research reported in this paper uses the 1977 and 1983 Nationwide Personal Transportation Study surveys (NPTS's) to estimate the cross-section and time responses of minority and majority households in terms of variations in vehicles held by the household, VMT per household vehicle, 1983 dollar income of the household, education and age of the household head, transit availability to the household, workers and nonworkers per household, and urban vs rural location.

    Santini, D.J.; Vyas, A.D.

    1987-01-01T23:59:59.000Z

    412

    Residential Energy Consumption Survey (RECS) - U.S. Energy Information  

    Gasoline and Diesel Fuel Update (EIA)

    About the RECS About the RECS RECS Survey Forms RECS Maps RECS Terminology Archived Reports State fact sheets Arizona household graph See state fact sheets › graph of U.S. electricity end use, as explained in the article text U.S. electricity sales have decreased in four of the past five years December 20, 2013 Gas furnace efficiency has large implications for residential natural gas use December 5, 2013 EIA publishes state fact sheets on residential energy consumption and characteristics August 19, 2013 All 48 related articles › Other End Use Surveys Commercial Buildings - CBECS Manufacturing - MECS Transportation About the RECS EIA administers the Residential Energy Consumption Survey (RECS) to a nationally representative sample of housing units. Specially trained interviewers collect energy characteristics on the housing unit, usage

    413

    EIA - Appendix B: Estimation Methodologies of Household Vehicles Energy  

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

    If you have trouble viewing this page, contact the National Energy Informaiton Center at (202) 586-8800. Return to Energy Information Administration Home Page If you have trouble viewing this page, contact the National Energy Informaiton Center at (202) 586-8800. Return to Energy Information Administration Home Page EIA Home > Transportation Home Page > Appendix B Estimation MethodologiesIntroduction Appendix B Estimation Methodologies Introduction Statistics concerning vehicle miles traveled (VMT), vehicle fuel efficiency (given in terms of miles per gallon (MPG)), vehicle fuel consumption, and vehicle fuel expenditures are presented in this report. The methodology used to estimate these statistics relied on data from the 1993 Residential Energy Consumption Survey (RECS), the 1994 Residential Transportation Energy Consumption Survey (RTECS), the U.S. Environmental Protection Agency (EPA) fuel efficiency test results, the U.S. Bureau of Labor Statistics (BLS) retail pump price series, and the Lundberg Survey, Inc., price series for 1994.

    414

    Design Code Survey Form | Department of Energy  

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

    Design Code Survey Form Design Code Survey Form Design Code Survey Form Survey of Safety Software Used in Design of Structures, Systems, and Components 1. Introduction The Department's Implementation Plan for Software Quality Assurance (SQA) that was developed in response to Defense Nuclear Facilities Safety Board Recommendation 2002-01, Quality Assurance for Safety-Related Software, includes a commitment (4.2.1.5) to conduct a survey of design codes currently in use to determine if any should be included as part of the toolbox codes. Design Code Survey Form September 11, 2003 More Documents & Publications Technical Standards, Safety Analysis Toolbox Codes - November 2003 DOE G 414.1-4, Safety Software Guide for Use with 10 CFR 830 Subpart A, Quality Assurance Requirements, and DOE O 414.1C, Quality Assurance

    415

    SURVEY OF FALLOUT OPERATIONS  

    SciTech Connect

    A survey was made of fall-out operations in the various countries of the world, These operations are outlined by country. The source of information has largely been the reports submitted to UNSCEAR forwarding data for their consideration. In addition, some material has been received directly in exchange for HASL Quarterlies and other publications of the Laboratory. In many cases, responsible scientists from the country concerned have reviewed the sheets and have made corrections. All of the programs that are shown have been and are subject to modification as time goes on, thus, the data indicate the status of the program as of 1961. No attempt has been made to list re search projects or special fall-out measurements and only programs of a continuing nature have been covered. (auth)

    1962-07-01T23:59:59.000Z

    416

    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)

    417

    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

    418

    Variable-response model of electricity demand by time of day: Results of a Wisconsin pricing experiment: Final report  

    Science Conference Proceedings (OSTI)

    Observationally alike households may differ in demand parameters and thus in economic quantities that are functions of those parameters. We have proposed a methodology for dealing with this variation. Estimation of both translog and CES versions of the model with data from the Wisconsin Electricity Pricing Experiment revealed considerable variation among households in time-of-day electricity consumption demand parameters for both summer and winter seasons and for several different definitions of the peak period. Observed household characteristics explained only a small share of total household differences, but permanent household differences dominated month-to-month variation in either expenditure shares or log consumption ratios in most cases. Permanent differences among households are important relative to total variation, including transitory month-to-month variation. We calculated various economic variables from the demand parameters, including the partial elasticity of substitution, compensated and uncompensated elasticities, and a measure of electricity expenditure under peak load pricing required to maintain the utility level under flat rate pricing relative to the flat rate expenditure. Because these are nonlinear functions of the household demand parameters, the mean parameter value over households with different demand parameters may be substantially different from the value of the function at mean values, under the representative household paradigm. For time-of-day electricity demand, variation among households is significant but small relative to mean parameter values. Therefore, controlling for the effect of household variation makes little difference in these mean calculations, but it does imply substantial variation among households in the welfare implications (and elasticities of response) of the introduction of time-of-day pricing. 25 refs., 12 tabs.

    Lillard, L.

    1987-06-01T23:59:59.000Z

    419

    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

    420

    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.

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


    421

    The 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

    422

    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

    423

    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

    424

    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

    425

    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

    426

    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

    427

    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, ...

    428

    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 --

    429

    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

    430

    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

    431

    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

    432

    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...

    433

    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

    434

    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...

    435

    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

    436

    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

    437

    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

    438

    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

    439

    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

    440

    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.

    Note: This page contains sample records for the topic "household survey responses" 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

    User_LaunchSurvey  

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

    and Completing Assigned Survey and Completing Assigned Survey © 2011 SuccessFactors, Inc. - 1 - SuccessFactors Learning Confidential. All rights reserved. Job Aid: Launching and Completing Assigned Survey Purpose The purpose of this job aid is to guide users through the step-by-step process of launching and completing assigned surveys. Task A. Launch and Complete Assigned Survey From the Home page, filter the To-Do List to show only Surveys. Hover over the course evaluation title. Click Open. 1 2 3 3 2 1 Launch and Complete Assigned Survey 6 Steps Task A SuccessFactors Learning v 6.4 User Job Aid Launching and Completing Assigned Survey © 2011 SuccessFactors, Inc. - 2 - SuccessFactors Learning Complete the survey by selecting the radio button for the appropriate rating

    442

    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

    443

    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

    444

    ORISE: Characterization surveys  

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

    Characterization surveys Characterization surveys An ORISE technicians performs a characterization survey The Oak Ridge Institute for Science and Education (ORISE) performs independent, objective characterization surveys to define the extent of radiological contamination at sites scheduled for decontamination and decommissioning (D&D). A fundamental aspect of all D&D projects, characterization surveys provide guidance to determine the best remediation procedures and are a cost-effective method of ensuring a site meets preliminary regulatory standards. ORISE designs characterization surveys using the data quality objectives process. This approach focuses on the particular objective of characterization, and ensures that only the data needed to address the characterization decisions are collected. Data collection efforts are

    445

    INFRASTRUCTURE SURVEY 2011  

    E-Print Network (OSTI)

    10 Appendices Appendix 1. Glossary of Terminology and Definitions 11 Appendix 2. Survey Definitions. There is a Glossary of Terminology and Definitions (Appendix 1). The survey form is Appendix 3 of this Report

    446

    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

    447

    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

    448

    Section_701_Surveys_Reviews_and_Self-Assessments  

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

    701 701 Surveys and Reviews Description This section describes the programs and procedures in effect at Headquarters (HQ) to conduct Safeguards and Security (S&S) surveys and reviews. These activities are conducted to assure the Secretary of Energy, Departmental elements, and other government agencies that safeguards and security interests are being protected at the required level. The Office of Information Security (HS-92) is responsible for the conduct of all surveys and reviews of HQ facilities. It is also responsible for conducting an annual survey of overall HQ security operations. The HQ Survey Team has been established within HS-92 to carry out these surveys and review activities. Types and Frequencies of Surveys and Reviews:

    449

    Residential energy survey provides greater detail on many more ...  

    U.S. Energy Information Administration (EIA)

    About 70% of households in California use energy-efficient light bulbs, compared to 47% of households in Pennsylvania. Almost half (48%) ...

    450

    DOE/EIA-0207/2 Residential Energy Consumption Survey:  

    Gasoline and Diesel Fuel Update (EIA)

    appliances used by the household, heating equip ment, and fuels used for space heating, water heating, cooking, and demographic information about the households. These tables are...

    451

    Environmental Survey preliminary report  

    SciTech Connect

    This report presents the preliminary findings from the first phase of the Environmental Survey of the United States Department of Energy (DOE) Sandia National Laboratories conducted August 17 through September 4, 1987. The objective of the Survey is to identify environmental problems and areas of environmental risk associated with Sandia National Laboratories-Albuquerque (SNLA). The Survey covers all environmental media and all areas of environmental regulation. It is being performed in accordance with the DOE Environmental Survey Manual. This phase of the Survey involves the review of existing site environmental data, observations of the operations carried on at SNLA, and interviews with site personnel. 85 refs., 49 figs., 48 tabs.

    Not Available

    1988-04-01T23:59:59.000Z

    452

    Impact of Poverty and Household Food Security on the Use of Preventive Medical Services in the California Health Interview Survey  

    E-Print Network (OSTI)

    a “medical home” regardless of food security status. ThereSecurity Status Food Insecure w/o hunger Have a medical home

    Harrison, Gail G.

    2004-01-01T23:59:59.000Z

    453

    CARSHARING’S IMPACT ON HOUSEHOLD VEHICLE HOLDINGS: RESULTS FROM A NORTH AMERICAN SHARED-USE VEHICLE SURVEY  

    E-Print Network (OSTI)

    Past, Present, and Future, Transportation Quarterly, Summer,in the future. ACKNOWLEDGMENTS The Mineta Transportation

    Martin, Elliot; Shaheen, Susan Alison; Lidicker, Jeffrey

    2010-01-01T23:59:59.000Z

    454

    The use of mobile phones as a data collection tool: A report from a household survey in South Africa  

    E-Print Network (OSTI)

    Systems Research Unit, Medical Research Council, Francie vanSystems Research Unit, Medical Research Council, Francie vanSystems Research Unit, Medical Research Council, 491 Ridge

    2009-01-01T23:59:59.000Z

    455

    Infrared Surveys for AGN  

    E-Print Network (OSTI)

    From the earliest extragalactic infrared studies AGN have shown themselves to be strong infrared sources and IR surveys have revealed new populations of AGN. I briefly review current motivations for AGN surveys in the infrared and results from previous IR surveys. The Luminous Infrared Galaxies, which in some cases house dust-enshrouded AGN, submillimeter surveys, and recent studies of the cosmic x-ray and infrared backgrounds suggest that there is a population of highly-obscured AGN at high redshift. ISO Surveys have begun to resolve the infrared background and may have detected this obscured AGN population. New infrared surveys, particularly the SIRTF Wide-area Infrared Extragalactic Legacy Survey (SWIRE), will detect this population and provide a platform for understanding the evolution of AGN, Starbursts and passively evolving galaxies in the context of large-scale structure and environment.

    Smith, H E

    2002-01-01T23:59:59.000Z

    456

    Infrared Surveys for AGN  

    E-Print Network (OSTI)

    From the earliest extragalactic infrared studies AGN have shown themselves to be strong infrared sources and IR surveys have revealed new populations of AGN. I briefly review current motivations for AGN surveys in the infrared and results from previous IR surveys. The Luminous Infrared Galaxies, which in some cases house dust-enshrouded AGN, submillimeter surveys, and recent studies of the cosmic x-ray and infrared backgrounds suggest that there is a population of highly-obscured AGN at high redshift. ISO Surveys have begun to resolve the infrared background and may have detected this obscured AGN population. New infrared surveys, particularly the SIRTF Wide-area Infrared Extragalactic Legacy Survey (SWIRE), will detect this population and provide a platform for understanding the evolution of AGN, Starbursts and passively evolving galaxies in the context of large-scale structure and environment.

    Harding E. Smith

    2002-03-06T23:59:59.000Z

    457

    National Interim Energy-Consumption Survey. Part VI. Energy assessment  

    Science Conference Proceedings (OSTI)

    The goal of energy assessment of the housing unit is to obtain physical information which can be combined with other survey results to give a more complete picture of the residential environment. A limited pretest of an energy assessment procedure was carried out in April-June 1979 with a subsample of 44 households that had been originally interviewed in the National Interim Energy Consumption Survey. In order to gain experience under a variety of environmental conditions, the pretest sites included locations in the Northeast, North Central, and South regions. As developed for the pretest, the energy assessment was a 90-minute inspection of the housing unit by a trained technician. Data collected during the inspection included square footage of the unit; age, make, and characteristics of appliances; insulation characteristics, characteristics of siting and apertures; and detailed information on the heating and cooling systems in the unit. The report describes the data collection procedures for the pretest.

    Not Available

    1981-01-01T23:59:59.000Z

    458

    "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

    459

    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

    460

    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

    Note: This page contains sample records for the topic "household survey responses" 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

    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

    462

    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

    463

    WOPR Seminar Series Responsiveness of Residential Electricity Demand to Changes in Price and Policy  

    E-Print Network (OSTI)

    Energy policy makers and scholars have sought to understand behavioral patterns of the residential energy consumers so as to design effective policies. Along the guideline of the literature, this study probes how consumers respond to changes in energy price in the short run with individual household survey data and analyzes how the consumers ’ behavioral attributes and

    Youngsun Baek

    2010-01-01T23:59:59.000Z

    464

    Assumptions to the Annual Energy Outlook 2000 - Household Expenditures  

    Gasoline and Diesel Fuel Update (EIA)

    Commercial Sector Demand Module generates forecasts of commercial sector energy demand through 2020. The definition of the commercial sector is consistent with EIAÂ’s State Energy Data System (SEDS). That is, the commercial sector includes business establishments that are not engaged in transportation or in manufacturing or other types of industrial activity (e.g., agriculture, mining or construction). The bulk of commercial sector energy is consumed within buildings; however, street lights, pumps, bridges, and public services are also included if the establishment operating them is considered commercial. Since most of commercial energy consumption occurs in buildings, the commercial module relies on the data from the EIA Commercial Buildings Energy Consumption Survey (CBECS) for characterizing the commercial sector activity mix as well as the equipment stock and fuels consumed to provide end use services.12

    465

    "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

    466

    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

    467

    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

    468

    "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

    469

    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

    470

    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

    471

    2009 Canadian Radiation Oncology Resident Survey  

    SciTech Connect

    Purpose: Statistics from the Canadian post-MD education registry show that numbers of Canadian radiation oncology (RO) trainees have risen from 62 in 1999 to approximately 150 per year between 2003 and 2009, contributing to the current perceived downturn in employment opportunities for radiation oncologists in Canada. When last surveyed in 2003, Canadian RO residents identified job availability as their main concern. Our objective was to survey current Canadian RO residents on their training and career plans. Methods and Materials: Trainees from the 13 Canadian residency programs using the national matching service were sought. Potential respondents were identified through individual program directors or chief resident and were e-mailed a secure link to an online survey. Descriptive statistics were used to report responses. Results: The eligible response rate was 53% (83/156). Similar to the 2003 survey, respondents generally expressed high satisfaction with their programs and specialty. The most frequently expressed perceived weakness in their training differed from 2003, with 46.5% of current respondents feeling unprepared to enter the job market. 72% plan on pursuing a postresidency fellowship. Most respondents intend to practice in Canada. Fewer than 20% of respondents believe that there is a strong demand for radiation oncologists in Canada. Conclusions: Respondents to the current survey expressed significant satisfaction with their career choice and training program. However, differences exist compared with the 2003 survey, including the current perceived lack of demand for radiation oncologists in Canada.

    Debenham, Brock, E-mail: debenham@ualberta.net [Department of Radiation Oncology, Cross Cancer Institute, University of Alberta, Edmonton, Alberta (Canada); Banerjee, Robyn [Department of Radiation Oncology, Tom Baker Cancer Centre, University of Calgary, Calgary, Alberta (Canada); Fairchild, Alysa; Dundas, George [Department of Radiation Oncology, Cross Cancer Institute, University of Alberta, Edmonton, Alberta (Canada); Trotter, Theresa [Department of Radiation Oncology, Tom Baker Cancer Centre, University of Calgary, Calgary, Alberta (Canada); Yee, Don [Department of Radiation Oncology, Cross Cancer Institute, University of Alberta, Edmonton, Alberta (Canada)

    2012-03-15T23:59:59.000Z

    472

    Berkeley Lab Postdoc Survey  

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

    Founded in 1983, MOR Associates has led dozens of major survey efforts on behalf of higher education, such as UC Berkeley, MIT, Stanford University, University of Washington,...

    473

    ORISE: Characterization surveys  

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

    extent of radiological contamination at sites scheduled for decontamination and decommissioning (D&D). A fundamental aspect of all D&D projects, characterization surveys provide...

    474

    The Dark Energy Survey  

    Science Conference Proceedings (OSTI)

    A new proposed optical?near infrared survey of 5000 square degrees of the South Galactic Cap is presented. To perform it

    E. Sánchez; Dark Energy Survey Collaboration

    2006-01-01T23:59:59.000Z

    475

    2011 NERSC User Survey (Read Only)  

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

    Results » Survey Text Results » Survey Text 2011 NERSC User Survey (Read Only) The survey is closed. Section 1: Overall Satisfaction with NERSC When you are finished with this page click "Save & Go to Next Section" or your responses will be lost. Please do not answer a specific question or rate a specific item if you have no opinion on it. For each item you use, please indicate both your satisfaction and its importance to you. Please rate: How satisfied are you? How important is this to you? Overall satisfaction with NERSC Not Answered Very Satisfied Mostly Satisfied Somewhat Sat. Neutral Somewhat Dissat. Mostly Dissat. Very Dissatisfied I Do Not Use This Not Answered Very Important Somewhat Important Not Important NERSC services Not Answered Very Satisfied Mostly Satisfied Somewhat Sat. Neutral Somewhat Dissat. Mostly Dissat. Very Dissatisfied I Do Not Use This Not Answered Very Important Somewhat Important Not Important

    476

    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

    477

    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

    478

    PRODUCT SURVEY April 2008 GIM International  

    E-Print Network (OSTI)

    PRODUCT SURVEY April 2008 GIM International [i] Insert here the spectral bands which can Aerial Cameras The first digital aerial cameras were presented to the photogrammetric community the two companies responsible for this innovation. Nine companies now manufacture digital aerial cameras

    Giger, Christine

    479

    REMOTE SENSING GEOLOGICAL SURVEY  

    E-Print Network (OSTI)

    REMOTE SENSING IN GEOLOGICAL SURVEY OF BRAZIL August/2010 Mônica Mazzini Perrotta Remote Sensing Division Head #12;SUMMARY The Geological Survey of Brazil mission The Remote Sensing Division Main remote, Paleontology, Remote Sensing Director of Hydrology and Land Management But Remote Sensing Division gives

    480

    Utility Baghouse Survey 2009  

    Science Conference Proceedings (OSTI)

    EPRI conducted comprehensive surveys of utility baghouse installations in 1981, 1991, and 2005 to summarize the state of the technology. The current survey focuses on nine selected pulse-jet baghouses to provide a better understanding of the design, performance, and operation of recent installations.

    2009-12-14T23:59:59.000Z

    Note: This page contains sample records for the topic "household survey responses" 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

    U.S. National Opinion Survey on Stacking Environmental Credits  

    Science Conference Proceedings (OSTI)

    This report summarizes and analyzes the responses of a national survey entitled "Evaluation of Credit Stacking" that was developed jointly by EPRI, the World Resources Institute, Stetson University College of Law and the University of Kentucky. The purpose of the survey was to collect opinions about credit