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We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


1

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

E-Print Network (OSTI)

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

Ji, Qundi

2010-05-01T23:59:59.000Z

2

Preamble: CEQ NEPA regulations (1986): Incomplete or Unavailable...  

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

Part 1502 National Environmental Pollcy Act Regulations; Incomplete or Unavailable Information AGENCY: Council on Environmental Quality, Executive Office of the President....

3

Preamble: CEQ NEPA regulations (1986): Incomplete or Unavailable Information  

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

618 618 Federal Register / Vol. 51, No. 80 / Friday, April 25, 1986 / Rules a n d Regulations - -- COUNCIL ON ENVIRONMENTAL QUALITY 40 CFR Part 1502 National Environmental Pollcy Act Regulations; Incomplete or Unavailable Information AGENCY: Council on Environmental Quality, Executive Office of the President. ACTION: Final rule. SUMMARY: The Council on Environmental Quality (CEQ) promulgates regulations, binding on all federal agencies, to implement the procedural provisions of the National Environmental Policy Act (NEPA). The regulations address the administration of the NEPA process, including preparation of environmental impact statements for major federal actions which significantly affect the quality of the human environment. On August 9 . 1985, CEQ published a proposed

4

Heber geothermal binary demonstration project: Unavailability distributions for principal pumps  

DOE Green Energy (OSTI)

The purpose of this study has been to review data sources relevant to the failure rate and mean time to repair for the principal pumps of the Heber geothermal project. Based upon that review the distributions of failure rates, repair times and pump unavailability were established. A total of 16 pumps are represented in this study. The method used to develop data distributions has been to first review as many sources of pump data as are currently available. This review was followed by a study of the features of the pumps specified for the Heber installation and the effects of operation and the environment on those features as they relate to anticipated failure rates and repair times. From this, determinations were made for mean failure rate and repair time values appropriate to specific Heber pumps. Range factors are then selected and used to establish the expected variability of the data. Failure rates and repair times were then combined to obtain the unavailability distribution of each type of pump.

Mulvihill, Robert J.; Cleveland, Edward B.

1982-04-01T23:59:59.000Z

5

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 ...

6

80 Fed Reg 15618:CEQ NEPA regulations (1986): Incomplete or Unavailable  

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

80 Fed Reg 15618:CEQ NEPA regulations (1986): Incomplete or 80 Fed Reg 15618:CEQ NEPA regulations (1986): Incomplete or Unavailable Information, Final Rule 80 Fed Reg 15618:CEQ NEPA regulations (1986): Incomplete or Unavailable Information, Final Rule The final amendment requires all federal agencies to disclose the fact of incomplete or unavailable information when evaluating reasonably foreseeable significant adverse impacts on the human environment in an EIS, and to obtain that information if the overall costs of doing so are not exorbitant. If the agency is unable to obtain the information because overall costs are exorbitant or because the means to obtain it are not known, the agency must (1) affirmatively discIose the fact that such information is unavailable; (2) explain the relevance of the unavailable information; (3) summarize the existing credible scientific evidence which

7

Median statistics cosmological parameter values  

E-Print Network (OSTI)

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

Crandall, Sara

2013-01-01T23:59:59.000Z

8

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 ...

9

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

10

Time-independent and time-dependent contributions to the unavailability of standby safety system components  

Science Conference Proceedings (OSTI)

The unavailability of standby safety system components due to failures in nuclear power plants is considered to involve a time independent and a time dependent part. The former relates to the component`s unavailability from demand stresses due to usage, and the latter represents the component`s unavailability due to standby time stresses related to the environment. In this paper, data from the nuclear plant reliability data system (NPRDS) were used to partition the component`s unavailability into the contributions from standby time stress (i.e., due to environmental factors) and demand stress (i.e., due to usage). Analyses are presented of motor operated valves (MOVs), motor driven pumps (MDPs), and turbine driven pumps (FDPs). MOVs fail predominantly (approx. 78%) from environmental factors (standby time stress failures). MDPs fail slightly more frequently from demand stresses (approx. 63%) than standby time stresses, while TDPs fail predominantly from standby time stresses (approx. 78%). Such partitions of component unavailability have many uses in risk informed and performance based regulation relating to modifications to Technical Specification, in-service testing, precise determination of dominant accident sequences, and implementation of maintenance rules.

Lofgren, E.V. [Science Applications International Corp., Fairfax Station, VA (United States); Uryasev, S.; Samanta, P. [Brookhaven National Lab., Upton, NY (United States)

1997-03-01T23:59:59.000Z

11

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...

12

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

13

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

14

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...

15

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

16

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

17

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

18

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

19

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 *...

20

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

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

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

22

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

23

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

24

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

25

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

26

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....

27

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

28

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...

29

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...

30

Methods for dependency estimation and system unavailability evaluation based on failure data statistics. Volume 1, Summary report  

SciTech Connect

This report introduces a new perspective on the basic concept of dependent failures where the definition of dependency is based on clustering in failure times of similar components. This perspective has two significant implications: first, it relaxes the conventional assumption that dependent failures must be simultaneous and result from a severe shock; second, it allows the analyst to use all the failures in a time continuum to estimate the potential for multiple failures in a window of time (e.g., a test interval), therefore arriving at a more accurate value for system unavailability. In addition, the models developed here provide a method for plant-specific analysis of dependency, reflecting the plant-specific maintenance practices that reduce or increase the contribution of dependent failures to system unavailability. The proposed methodology can be used for screening analysis of failure data to estimate the fraction of dependent failures among the failures. In addition, the proposed method can evaluate the impact of the observed dependency on system unavailability and plant risk. The formulations derived in this report have undergone various levels of validations through computer simulation studies and pilot applications. The pilot applications of these methodologies showed that the contribution of dependent failures of diesel generators in one plant was negligible, while in another plant was quite significant. It also showed that in the plant with significant contribution of dependency to Emergency Power System (EPS) unavailability, the contribution changed with time. Similar findings were reported for the Containment Fan Cooler breakers. Drawing such conclusions about system performance would not have been possible with any other reported dependency methodologies.

Azarm, M.A.; Hsu, F.; Martinez-Guridi, G. [Brookhaven National Lab., Upton, NY (US); Vesely, W.E. [Science Applications International Corp., Dublin, OH (US)

1993-07-01T23:59:59.000Z

31

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

32

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

33

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

34

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

35

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:...

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

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

38

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...

39

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...

40

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...

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

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

42

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

43

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

44

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

45

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

46

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

47

char_household2001.pdf  

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

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

48

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

49

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

50

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

51

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

52

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

53

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...

54

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

55

On the Median Volume Diameter Approximation for Droplet Collision Efficiency  

Science Conference Proceedings (OSTI)

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

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

1988-12-01T23:59:59.000Z

56

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

57

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

58

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

59

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.

60

Property:EstimatedCostMedianUSD | Open Energy Information  

Open Energy Info (EERE)

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

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

Property:EstimatedTimeMedian | Open Energy Information  

Open Energy Info (EERE)

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

62

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

63

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

64

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

65

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

66

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

67

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

68

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

69

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

70

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

71

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

72

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

73

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

74

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

75

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

76

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

77

Weighted median filters with sigma-delta modulation encoding  

Science Conference Proceedings (OSTI)

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

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

2000-02-01T23:59:59.000Z

78

Placement of Traffic Barriers on Roadside and Median Slopes  

E-Print Network (OSTI)

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

Ferdous, Md Rubiat

2011-05-01T23:59:59.000Z

79

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

80

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

U.S. Energy Information Administration (EIA)

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

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

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

82

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...

83

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 ...

84

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

85

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

86

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 ...

87

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

88

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

89

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

90

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

91

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

92

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

93

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

94

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

95

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

96

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

97

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

98

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

99

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

100

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 "unavailable median household" 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

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

102

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

103

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

104

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

105

Concentrated solar thermal (cst) system for fuelwood replacement and for household water sanitation in developing countries.  

DOE Green Energy (OSTI)

Concentrated Solar Thermal (CST) is a proven renewable energy technology that harnesses solar irradiation in its most primitive form. This technology with roots in ancient history is growing at a fast pace in recent times. Developing countries could use CST to solve fundamental human-needs challenges, such as for the substitution of fuelwood and the treatment of water for household use. This paper proposes a conceptual design for a standardized modular CST for these applications in developing countries. A modular-designed parabolic CST with an aperture area of 7.5 m2 is adequate to provide enough solar thermal energy to replace the fuelwood need (5 tons/yr) or to pasteurize the minimum daily water requirement (2500 liters) for a household. Critical parameters of the CST are discussed and an affordable solid thermal storage is recommended to be used as a backup when sunlight is unavailable. A funding program that includes in-country resources and external funding will be needed to sustain the development and wide spread adaptation of this technology.

Akinjiola, O. P.; Balachandran, U. (Energy Systems); (Rsage Research, LLC)

2012-01-01T23:59:59.000Z

106

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

107

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

108

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

109

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

110

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

111

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

112

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

113

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

114

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

115

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

116

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

117

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

118

Microsoft Word - Household Energy Use CA  

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

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

119

Microsoft Word - Household Energy Use CA  

Gasoline and Diesel Fuel Update (EIA)

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

120

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

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

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

122

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

123

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

124

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

125

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

126

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

127

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

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

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

128

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

129

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

130

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...

131

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

132

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...

133

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

134

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...

135

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

136

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

137

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

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

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

138

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

139

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

140

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

E-Print Network (OSTI)

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

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

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

142

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

143

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

144

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

145

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

146

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

147

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

148

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

149

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

150

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

151

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 ...

152

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

153

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

154

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) ...

155

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

156

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 ...

157

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 ...

158

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

159

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

160

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

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

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

162

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

163

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

164

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

165

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

166

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

SciTech Connect

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

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

1991-01-01T23:59:59.000Z

167

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

168

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

169

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

170

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:

171

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:

172

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:

173

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:

174

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:

175

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

176

2003 CBECS National Median Source Energy Use and Performance Comparisons by  

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

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

177

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

178

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

179

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

Science Conference Proceedings (OSTI)

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

J. Iinatti; P. Leppänen

1998-09-01T23:59:59.000Z

180

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.

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

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.

182

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

183

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...

184

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...

185

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

186

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...

187

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

188

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

189

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

190

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

191

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

192

Delivering Energy Efficiency to Middle Income Single Family Households  

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

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

193

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.

194

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

195

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

Science Conference Proceedings (OSTI)

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

Delman, D.J.

1981-01-01T23:59:59.000Z

196

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

197

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

198

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.

199

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

200

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

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

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

202

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

203

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

204

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

205

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

206

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

207

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

208

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

209

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

210

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

211

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.

212

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

213

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

214

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

215

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 ...

216

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

217

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

E-Print Network (OSTI)

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

Best, Matthew Evans

1996-01-01T23:59:59.000Z

218

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 ...

219

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

220

Household Vehicles Energy Use: Latest Data & Trends  

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

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

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

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

222

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

223

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.

224

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

225

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

226

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

227

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

228

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:

229

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

230

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 ...

231

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

232

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, ...

233

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

234

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...

235

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) ...

236

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 ...

237

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 ...

238

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.

239

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

240

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 ...

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

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."

242

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

243

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

244

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

245

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

246

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

247

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

248

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

249

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.

250

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

251

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

252

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

253

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 ...

254

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.

255

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

256

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

257

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

258

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

259

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

260

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

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

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

262

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

263

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

264

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?

265

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?

266

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

267

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

268

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

269

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)

270

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

271

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

272

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

273

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

274

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

275

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.

276

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

277

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, ...

278

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 --

279

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

280

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

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

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

282

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

283

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

284

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

285

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

286

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

287

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

288

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...

289

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

290

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

291

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

292

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

293

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...

294

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

295

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.

296

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

297

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

298

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

299

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

300

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

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

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

302

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

303

"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

304

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

305

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

306

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.

307

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

308

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

309

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

310

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

311

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

312

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

313

"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

314

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

315

"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

316

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

317

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

318

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

319

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

320

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

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

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

322

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

SciTech Connect

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

Poyer, D.A.

1991-09-01T23:59:59.000Z

323

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

E-Print Network (OSTI)

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

Paris-Sud XI, Université de

324

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.

325

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

326

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

327

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

Science Conference Proceedings (OSTI)

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

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

2013-04-01T23:59:59.000Z

328

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

Science Conference Proceedings (OSTI)

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

Thorne, J.; Suozzo, M.

1998-12-31T23:59:59.000Z

329

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

E-Print Network (OSTI)

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

California at Davis, University of

330

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

E-Print Network (OSTI)

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

Kammen, Daniel M.

331

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

332

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

333

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

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

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

334

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

Science Conference Proceedings (OSTI)

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

Carolyn Kousky

335

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

DOE Green Energy (OSTI)

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

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

2011-01-01T23:59:59.000Z

336

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

SciTech Connect

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

Lin, Jiang

2006-07-10T23:59:59.000Z

337

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

E-Print Network (OSTI)

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

Williams, Brett D

2010-01-01T23:59:59.000Z

338

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

E-Print Network (OSTI)

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

Williams, Brett D

2007-01-01T23:59:59.000Z

339

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

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

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

340

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

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

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

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

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

342

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

E-Print Network (OSTI)

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

Pokharel, Binod

2001-01-01T23:59:59.000Z

343

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

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

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

344

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

E-Print Network (OSTI)

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

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

2012-01-01T23:59:59.000Z

345

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

346

A statistical analysis of structural differences in minority household electricity demand  

SciTech Connect

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

Poyer, D.A.; Earl, E.

1994-09-01T23:59:59.000Z

347

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

Science Conference Proceedings (OSTI)

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

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

2011-03-15T23:59:59.000Z

348

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

SciTech Connect

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

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

1990-02-01T23:59:59.000Z

349

An Analysis of the Price Elasticity of Demand for Household Appliances  

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

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

350

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

E-Print Network (OSTI)

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

Meyers, Marcia k.

1996-01-01T23:59:59.000Z

351

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

E-Print Network (OSTI)

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

Baffrey, Robert Michael Nuval, 1977-

2005-01-01T23:59:59.000Z

352

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

353

Household disposables as breeding habitats of dengue vectors: Linking wastes and public health  

SciTech Connect

Highlights: Black-Right-Pointing-Pointer An assessment of different household wastes as larval habitats of dengue vectors Aedes aegypti and Aedes albopictus was made using Kolkata, India as a model geographical area. Black-Right-Pointing-Pointer Household wastes of four major categories namely earthen, porcelain, plastic and coconut shells varied significantly for Aedes immature depending on species, month and location. Black-Right-Pointing-Pointer Based on the relative density of Aedes immature, cluster analyses allowed segregation and classification of the waste containers and relative importance as mosquito larval habitats. Black-Right-Pointing-Pointer Conversion of disposed wastes into larval habitats cautions for continuance of Aedes population in Kolkata and similar cities of tropics lacking suitable waste management practices. - Abstract: An assessment of the household wastes as larval habitats of the dengue vectors was made considering Kolkata, India, as geographical area. Wastes of four major categories, namely, earthen, porcelain, plastic and coconut shells were monitored for positive with immature of either Aedes aegypti or Aedes albopictus. Twenty six types of wastes with varying size and shape, resembling containers, were identified that hosted mosquito immature. The number of waste containers positive for Aedes immature varied significantly (P < 0.05) with respect to location, type and month. The relative density of Aedes immature in the waste containers varied significantly (P < 0.05) with the types and months. The significant interaction between the month, waste container types and density of Aedes immature suggest that the household wastes are important contributors to the maintenance of the population of Aedes mosquito in the city. Based on the relative density of mosquito immature in the wastes, cluster analysis allowed segregation and classification of the wastes and their importance as mosquito larval habitats. Apparently, the containers that are most frequently disposed off contributed largely to the sustenance of Aedes mosquito population in the city. This calls for a strict legislation towards disposal as well as enhanced management of the household wastes. A link between the wastes disposed and subsequent conversion to the mosquito larval habitats cautions for continuance of Aedes population and possibility of dengue epidemics if the existing management practices are not improved.

Banerjee, Soumyajit, E-mail: soumyajitb@gmail.com [Department of Zoology, University of Calcutta, 35 Ballygunge Circular Road, Kolkata 700 019 (India); Aditya, Gautam, E-mail: gautamaditya2001@gmail.com [Department of Zoology, University of Calcutta, 35 Ballygunge Circular Road, Kolkata 700 019 (India); Department of Zoology, The University of Burdwan, Golapbag, Burdwan 713 104 (India); Saha, Goutam K, E-mail: gkszoo@rediffmail.com [Department of Zoology, University of Calcutta, 35 Ballygunge Circular Road, Kolkata 700 019 (India)

2013-01-15T23:59:59.000Z

354

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

355

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

356

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

357

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

358

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

359

Investigation of the use of biogas in a gas hob$$hand the feasibility of upgrading it on a household scale.  

E-Print Network (OSTI)

??Incldes abstract. The production and use of biogas on a household scale is becoming more common. The biogas is mainly used for lighting and cooking.… (more)

Trautmann, Christina.

2012-01-01T23:59:59.000Z

360

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

E-Print Network (OSTI)

assessment for fuel cell electric vehicles." Argonne, Ill. :of Plug-In Hybrid Electric Vehicles on Wind Energy Markets,"Recharging and Household Electric Vehicle Market: A Near-

Williams, Brett D

2010-01-01T23:59:59.000Z

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

On the energy sources of Mozambican households and the demand-supply curves for domestic electricity in the northern electrical grid in Mozambique.  

E-Print Network (OSTI)

??The development of electrical infrastructure to supply rural households is considered economically unfeasible because of the high cost of capital investment required to expand the… (more)

Arthur, Maria de Fatima Serra Ribeiro

2009-01-01T23:59:59.000Z

362

Table HC6.12 Home Electronics Usage Indicators by Number of Household Members, 2005  

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

2 Home Electronics Usage Indicators by Number of Household Members, 2005 2 Home Electronics Usage Indicators by Number of Household Members, 2005 Total................................................................................ 111.1 30.0 34.8 18.4 15.9 12.0 Personal Computers Do Not Use a Personal Computer............................. 35.5 16.3 9.4 4.0 2.7 3.2 Use a Personal Computer.......................................... 75.6 13.8 25.4 14.4 13.2 8.8 Most-Used Personal Computer Type of PC Desk-top Model..................................................... 58.6 10.0 20.0 11.2 10.1 7.3 Laptop Model........................................................ 16.9 3.7 5.4 3.2 3.1 1.5 Hours Turned on Per Week Less than 2 Hours................................................. 13.6 4.0 4.7 1.7 1.8 1.4 2 to 15 Hours........................................................

363

Experience with improved charcoal and wood stoves for households and institutions in Kenya  

SciTech Connect

Efforts at promoting more fuel-efficient charcoal stoves to replace traditional charcoal stoves in Kenya offer some lessons for the dissemination of appropriate technologies. This paper looks at the market-based approach which has made the Kenyan charcoal stoves project a success. Trends in woodfuels (wood and charcoal) consumption in Kenya are identified; the traditional technology for charcoal combustion and the upgraded traditional technologies are described; production achievement and the dissemination and promotion strategy used are examined; and a financial and economic analysis is performed with social, health and environmental effects assessed. Other ways to achieve a more favourable balance between woodfuels consumption and supply are then discussed looking at more efficient charcoal kilns and household woodstoves, improved institutional stoves and increased wood production. The replication potential of the Kenya experiment in other countries is also explored. The lessons learnt from the the Kenya experience concern the relationship between technology, choice and delivery systems as they interact with, economic, institutional, and policy factors. In this case, the design work accepted the traditional technology as a starting point which helped ensure widespread acceptance by households. The potential desirability of relying on local artisans to manufacture consumer durables using existing private sector channels to market these goods is also shown. It also highlights the importance of going beyond a laissez-faire approach and supporting training, demonstration, and publicity to faciliate the workings of the private sector. In the Kenyan case, technology choice was relatively unsubsidized and left ot the preferences of consumers.

Hyman, E.L.

1985-01-01T23:59:59.000Z

364

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

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

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

365

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

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

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

366

Table HC6.7 Air-Conditioning Usage Indicators by Number of Household Members, 2005  

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

7 Air-Conditioning Usage Indicators by Number of Household Members, 2005 7 Air-Conditioning Usage Indicators by Number of Household Members, 2005 Total........................................................................ 111.1 30.0 34.8 18.4 15.9 12.0 Do Not Have Cooling Equipment.......................... 17.8 5.4 5.3 2.7 2.5 2.0 Have Cooling Equipment...................................... 93.3 24.6 29.6 15.7 13.4 10.0 Use Cooling Equipment....................................... 91.4 24.0 29.1 15.5 13.2 9.7 Have Equipment But Do Not Use it...................... 1.9 0.6 0.5 Q 0.2 0.4 Type of Air-Conditioning Equipment 1, 2 Central System................................................... 65.9 15.3 22.6 10.7 9.9 7.3 Without a Heat Pump....................................... 53.5 12.5 17.9 8.7 8.2 6.3 With a Heat Pump............................................ 12.3

367

Table HC6.5 Space Heating Usage Indicators by Number of Household Members, 2005  

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

5 Space Heating Usage Indicators by Number of Household Members, 2005 5 Space Heating Usage Indicators by Number of Household Members, 2005 Total U.S. Housing Units.................................. 111.1 30.0 34.8 18.4 15.9 12.0 Do Not Have Heating Equipment..................... 1.2 0.3 0.3 Q 0.2 0.2 Have Space Heating Equipment....................... 109.8 29.7 34.5 18.2 15.6 11.8 Use Space Heating Equipment........................ 109.1 29.5 34.4 18.1 15.5 11.6 Have But Do Not Use Equipment.................... 0.8 Q Q Q Q Q Space Heating Usage During 2005 Heated Floorspace (Square Feet) None............................................................ 3.6 1.0 0.8 0.5 0.5 0.7 1 to 499........................................................ 6.1 3.0 1.6 0.6 0.6 0.3 500 to 999.................................................... 27.7 11.6 8.3 3.6 2.7 1.6 1,000 to 1,499..............................................

368

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

SciTech Connect

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

Baxter, L.W.

1984-01-01T23:59:59.000Z

369

Recovery and separation of high-value plastics from discarded household appliances  

DOE Green Energy (OSTI)

Argonne National Laboratory is conducting research to develop a cost- effective and environmentally acceptable process for the separation of high-value plastics from discarded household appliances. The process under development has separated individual high purity (greater than 99.5%) acrylonitrile-butadiene-styrene (ABS) and high- impact polystyrene (HIPS) from commingled plastics generated by appliance-shredding and metal-recovery operations. The process consists of size-reduction steps for the commingled plastics, followed by a series of gravity-separation techniques to separate plastic materials of different densities. Individual plastics of similar densities, such as ABS and HIPS, are further separated by using a chemical solution. By controlling the surface tension, the density, and the temperature of the chemical solution we are able to selectively float/separate plastics that have different surface energies. This separation technique has proven to be highly effective in recovering high-purity plastics materials from discarded household appliances. A conceptual design of a continuous process to recover high-value plastics from discarded appliances is also discussed. In addition to plastics separation research, Argonne National Laboratory is conducting research to develop cost-effective techniques for improving the mechanical properties of plastics recovered from appliances.

Karvelas, D.E.; Jody, B.J.; Poykala, J.A. Jr.; Daniels, E.J. [Argonne National Lab., IL (United States). Energy Systems Div.; Arman, B. [Argonne National Lab., IL (United States). Energy Systems Div.]|[Praxair, Inc., Tarrytown, NY (United States)

1996-03-01T23:59:59.000Z

370

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

371

EREV and BEV Economic Viability vs. Household Retail Electric Pricing Strategies: Two Charges a Day?  

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

EREV and BEV Economic Viability vs. EREV and BEV Economic Viability vs. Household Retail Electric Pricing Strategies: Two Charges a Day? By Dan Santini Argonne National Laboratory dsantini@anl.gov Remarks are attributable only to the author; not to Argonne or U.S. Department of Energy NAATBatt Conference: The Impact of PEVs on T&D Systems: Challenges and Solutions Dec. 7, 2010 The submitted manuscript has been created by Argonne National Laboratory, a U.S. Department of Energy laboratory managed by UChicago Argonne, LLC, under Contract No. DE-AC02-06CH11357. The U.S. Government retains for itself, and others acting on its behalf, a paid-up, nonexclusive, irrevocable worldwide license in said article to reproduce, prepare derivative works, distribute copies to the public, and perform publicly and display publicly,

372

An Analysis of the Price Elasticity of Demand for Household Appliances  

SciTech Connect

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

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

2008-01-25T23:59:59.000Z

373

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

374

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

375

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

SciTech Connect

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

Poyer, D.A.; Johnson, G.

1985-10-01T23:59:59.000Z

376

On the periphery of the periphery: household archaeology at Hacienda Tabi, Yucatan, Mexico  

E-Print Network (OSTI)

The archaeological remains at Hacienda Tabi provide an opportunity to study the effects of large-scale societal changes on the lives of the Maya who worked on the hacienda. The households, represented by the ruins of the worker�s village surrounding the main hacienda grounds, were at the core of late colonial/independence era Maya life. These households were subject to the forces of acculturation that accompanied the rise and supremacy of the hacienda system during the late eighteenth century. Archaeological excavations at Hacienda Tabi have revealed a re-orientation of social organization during this period. Prior to the formation of the hacienda system, domestic and social organization focused on kinship and extended family subsistence organization. Social status, wealth, and power in pre-hacienda communities were predicated on issues of age, sex, and familial rank within both the extended family and community. The hacienda system brought about fundamental changes in the organization and relations of production. These changes, e.g. the separation of producer from the means of production and commodity based production versus subsistence based production, changed the basis and therefore the form of Yucatecan social organization. Under the new system, the nuclear family rather than the extended family or community became the prime unit of social organization. In the hacienda community status was based on occupation and one�s place within the newly established labor hierarchy. The changing realities of social organization found under the hacienda system are reflected in the settlement patterns and material remains of the workers� village at Hacienda Tabi. The material culture and types of housing excavated and recorded at Tabi underscore the inequalities engendered within the hacienda system of production. The research conducted at Hacienda Tabi has illuminated the changes associated with Yucatan�s articulation into the greater world system.

Sweitz, Samuel Randles

2005-08-01T23:59:59.000Z

377

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

378

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

Science Conference Proceedings (OSTI)

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

Leach, G.; Gowen, M.

1989-01-01T23:59:59.000Z

379

Changing Trends: A Brief History of the US Household Consumption of Energy, Water, Food, Beverages and Tobacco  

E-Print Network (OSTI)

in household and per capita consumption of energy and water, and also at food, beverages, and tobacco, products invites several questions: Did per capita energy use increase from 1949 to 1973 due to bigger houses US primary energy consumption from 1949 to 2001 (Figure 1). In 1949, U.S. energy use per person stood

Diamond, Richard

380

Techno-economics analysis of a wind/PV hybrid system to provide electricity for a household in Malaysia  

Science Conference Proceedings (OSTI)

This paper is study on techno-economics analysis of a wind/PV hybrid system for a household in Malaysia. One year recorded wind speed and solar radiation are used for the design of a hybrid energy system. In 2004 average annual wind speed in Kuala Terengganu ... Keywords: electrical load, techno-economics analysis, wind/PV hybrid system

Ahmad Fudholi; Mohd Zamri Ibrahim; Mohd Hafidz Ruslan; Lim Chin Haw; Sohif Mat; Mohd Yusof Othman; Azami Zaharim; Kamaruzzaman Sopian

2012-01-01T23:59:59.000Z

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

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

DOE Green Energy (OSTI)

Japanese automakers have introduced hybrid passenger cars in Japan and will soon do so in the US. In this paper, we report how we used early computer simulation model results to compare the commercial viability of a hypothetical near-term (next decade) hybrid mid-size passenger car configuration under varying fuel price and driving patterns. The fuel prices and driving patterns evaluated are designed to span likely values for major OECD nations. Two types of models are used. One allows the ''design'' of a hybrid to a specified set of performance requirements and the prediction of fuel economy under a number of possible driving patterns (called driving cycles). Another provides an estimate of the incremental cost of the hybrid in comparison to a comparably performing conventional vehicle. In this paper, the models are applied to predict the NPV cost of conventional gasoline-fueled vehicles vs. parallel hybrid vehicles. The parallel hybrids are assumed to (1) be produced at high volume, (2) use nickel metal hydride battery packs, and (3) have high-strength steel bodies. The conventional vehicle also is assumed to have a high-strength steel body. The simulated vehicles are held constant in many respects, including 0-60 time, engine type, aerodynamic drag coefficient, tire rolling resistance, and frontal area. The hybrids analyzed use the minimum size battery pack and motor to meet specified 0-60 times. A key characteristic affecting commercial viability is noted and quantified: that hybrids achieve the most pronounced fuel economy increase (best use) in slow, average-speed, stop-and-go driving, but when households consistently drive these vehicles under these conditions, they tend to travel fewer miles than average vehicles. We find that hours driven is a more valuable measure than miles. Estimates are developed concerning hours of use of household vehicles versus driving cycle, and the pattern of minimum NPV incremental cost (or benefit) of selecting the hybrid over the conventional vehicle at various fuel prices is illustrated. These results are based on data from various OECD motions on fuel price, annual miles of travel per vehicle, and driving cycles assumed to be applicable in those nations. Scatter in results plotted as a function of average speed, related to details of driving cycles and the vehicles selected for analysis, is discussed.

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

1999-07-16T23:59:59.000Z

382

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

383

The comparative impact of the market penetration of energy-efficient measures: A sensitivity analysis of its impact on minority households  

SciTech Connect

A sensitivity study was made of the potential market penetration of residential energy efficiency as energy service ratio (ESR) improvements occurred in minority households, by age of house. The study followed a Minority Energy Assessment Model analysis of the National Energy Strategy projections of household energy consumption and prices, with majority, black, and Hispanic subgroup divisions. Electricity and total energy consumption and expenditure patterns were evaluated when the households` ESR improvement followed a logistic negative growth (i.e., market penetration) path. Earlier occurrence of ESR improvements meant greater discounted savings over the 22-year period.

Bozinovich, L.V.; Poyer, D.A.; Anderson, J.L.

1993-12-01T23:59:59.000Z

384

Municipal solid waste generation in municipalities: Quantifying impacts of household structure, commercial waste and domestic fuel  

Science Conference Proceedings (OSTI)

Waste management planning requires reliable data concerning waste generation, influencing factors on waste generation and forecasts of waste quantities based on facts. This paper aims at identifying and quantifying differences between different municipalities' municipal solid waste (MSW) collection quantities based on data from waste management and on socio-economic indicators. A large set of 116 indicators from 542 municipalities in the Province of Styria was investigated. The resulting regression model included municipal tax revenue per capita, household size and the percentage of buildings with solid fuel heating systems. The model explains 74.3% of the MSW variation and the model assumptions are met. Other factors such as tourism, home composting or age distribution of the population did not significantly improve the model. According to the model, 21% of MSW collected in Styria was commercial waste and 18% of the generated MSW was burned in domestic heating systems. While the percentage of commercial waste is consistent with literature data, practically no literature data are available for the quantity of MSW burned, which seems to be overestimated by the model. The resulting regression model was used as basis for a waste prognosis model (Beigl and Lebersorger, in preparation).

Lebersorger, S. [Institute of Waste Management, Department of Water, Atmosphere and Environment, University of Natural Resources and Life Sciences, Vienna, Muthgasse 107, A-1190 Wien (Austria); Beigl, P., E-mail: peter.beigl@boku.ac.at [Institute of Waste Management, Department of Water, Atmosphere and Environment, University of Natural Resources and Life Sciences, Vienna, Muthgasse 107, A-1190 Wien (Austria)

2011-09-15T23:59:59.000Z

385

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

386

Influence of assumptions about household waste composition in waste management LCAs  

SciTech Connect

Highlights: Black-Right-Pointing-Pointer Uncertainty in waste composition of household waste. Black-Right-Pointing-Pointer Systematically changed waste composition in a constructed waste management system. Black-Right-Pointing-Pointer Waste composition important for the results of accounting LCA. Black-Right-Pointing-Pointer Robust results for comparative LCA. - Abstract: This article takes a detailed look at an uncertainty factor in waste management LCA that has not been widely discussed previously, namely the uncertainty in waste composition. Waste composition is influenced by many factors; it can vary from year to year, seasonally, and with location, for example. The data publicly available at a municipal level can be highly aggregated and sometimes incomplete, and performing composition analysis is technically challenging. Uncertainty is therefore always present in waste composition. This article performs uncertainty analysis on a systematically modified waste composition using a constructed waste management system. In addition the environmental impacts of several waste management strategies are compared when applied to five different cities. We thus discuss the effect of uncertainty in both accounting LCA and comparative LCA. We found the waste composition to be important for the total environmental impact of the system, especially for the global warming, nutrient enrichment and human toxicity via water impact categories.

Slagstad, Helene, E-mail: helene.slagstad@ntnu.no [Department of Hydraulic and Environmental Engineering, Norwegian University of Science and Technology, N-7491 Trondheim (Norway); Brattebo, Helge [Department of Hydraulic and Environmental Engineering, Norwegian University of Science and Technology, N-7491 Trondheim (Norway)

2013-01-15T23:59:59.000Z

387

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

388

Secondary organic aerosol from ozone-initiated reactions with terpene-rich household products  

SciTech Connect

We analyzed secondary organic aerosol (SOA) data from a series of small-chamber experiments in which terpene-rich vapors from household products were combined with ozone under conditions analogous to product use indoors. Reagents were introduced into a continuously ventilated 198 L chamber at steady rates. Consistently, at the time of ozone introduction, nucleation occurred exhibiting behavior similar to atmospheric events. The initial nucleation burst and growth was followed by a period in which approximately stable particle levels were established reflecting a balance between new particle formation, condensational growth, and removal by ventilation. Airborne particles were measured with a scanning mobility particle sizer (SMPS, 10 to 400 nm) in every experiment and with an optical particle counter (OPC, 0.1 to 2.0 ?m) in a subset. Parameters for a three-mode lognormal fit to the size distribution at steady state were determined for each experiment. Increasing the supply ozone level increased the steady-state mass concentration and yield of SOA from each product tested. Decreasing the air-exchange rate increased the yield. The steady-state fine-particle mass concentration (PM1.1) ranged from 10 to> 300 mu g m-3 and yields ranged from 5percent to 37percent. Steady-state nucleation rates and SOA mass formation rates were on the order of 10 cm-3 s-1 and 10 mu g m-3 min-1, respectively.

Coleman, Beverly; Coleman, Beverly K.; Lunden, Melissa M.; Destaillats, Hugo; Nazaroff, William W.

2008-01-01T23:59:59.000Z

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

LCA for household waste management when planning a new urban settlement  

Science Conference Proceedings (OSTI)

Highlights: Black-Right-Pointing-Pointer Household waste management of a new carbon neutral settlement. Black-Right-Pointing-Pointer EASEWASTE as a LCA tool to compare different centralised and decentralised solutions. Black-Right-Pointing-Pointer Environmental benefit or close to zero impact in most of the categories. Black-Right-Pointing-Pointer Paper and metal recycling important for the outcome. Black-Right-Pointing-Pointer Discusses the challenges of waste prevention planning. - Abstract: When planning for a new urban settlement, industrial ecology tools like scenario building and life cycle assessment can be used to assess the environmental quality of different infrastructure solutions. In Trondheim, a new greenfield settlement with carbon-neutral ambitions is being planned and five different scenarios for the waste management system of the new settlement have been compared. The results show small differences among the scenarios, however, some benefits from increased source separation of paper and metal could be found. The settlement should connect to the existing waste management system of the city, and not resort to decentralised waste treatment or recovery methods. However, as this is an urban development project with ambitious goals for lifestyle changes, effort should be put into research and initiatives for proactive waste prevention and reuse issues.

Slagstad, Helene, E-mail: helene.slagstad@ntnu.no [Department of Hydraulic and Environmental Engineering, Norwegian University of Science and Technology, N-7491 Trondheim (Norway); Brattebo, Helge [Department of Hydraulic and Environmental Engineering, Norwegian University of Science and Technology, N-7491 Trondheim (Norway)

2012-07-15T23:59:59.000Z

391

Engineering of arbitrary U(N) transformations by quantum Householder reflections  

E-Print Network (OSTI)

We propose a simple physical implementation of the quantum Householder reflection (QHR) M(v)=I-2|v>N degenerate states (forming a qunit) coupled simultaneously to an ancillary (excited) state by N resonant or nearly resonant pulsed external fields. We also introduce the generalized QHR M(v;k)=I+(exp{ik}-1)|v>N-pod system when the fields are appropriately detuned from resonance with the excited state. We use these two operators as building blocks in constructing arbitrary preselected unitary transformations. We show that the most general U(N) transformation can be factorized (and thereby produced) by either N-1 standard QHRs and an N-dimensional phase gate, or N-1 generalized QHRs and a one-dimensional phase gate. Viewed mathematically, these QHR factorizations provide parametrizations of the U(N) group. As an example, we propose a recipe for constructing the quantum Fourier transform (QFT) by at most N interaction steps. For example, QFT requires a single QHR for N=2, and only two QHRs for N=3 and 4.

P. A. Ivanov; E. S. Kyoseva; N. V. Vitanov

2007-08-21T23:59:59.000Z

392

Status of not-in-kind refrigeration technologies for household space conditioning, water heating and food refrigeration  

Science Conference Proceedings (OSTI)

This paper presents a review of the next generation not-in-kind technologies to replace conventional vapor compression refrigeration technology for household applications. Such technologies are sought to provide energy savings or other environmental benefits for space conditioning, water heating and refrigeration for domestic use. These alternative technologies include: thermoacoustic refrigeration, thermoelectric refrigeration, thermotunneling, magnetic refrigeration, Stirling cycle refrigeration, pulse tube refrigeration, Malone cycle refrigeration, absorption refrigeration, adsorption refrigeration, and compressor driven metal hydride heat pumps. Furthermore, heat pump water heating and integrated heat pump systems are also discussed due to their significant energy saving potential for water heating and space conditioning in households. The paper provides a snapshot of the future R&D needs for each of the technologies along with the associated barriers. Both thermoelectric and magnetic technologies look relatively attractive due to recent developments in the materials and prototypes being manufactured.

Bansal, Pradeep [ORNL; Vineyard, Edward Allan [ORNL; Abdelaziz, Omar [ORNL

2012-01-01T23:59:59.000Z

393

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

394

The economics of US greenhouse gas emissions reduction policy : assessing distributional effects across households and the 50 United States using a recursive dynamic computable general equilibrium (CGE) model  

E-Print Network (OSTI)

The political economy of US climate policy has revolved around state- and district- level distributional economics, and to a lesser extent household-level distribution questions. Many politicians and analysts have suggested ...

Look, Wesley Allen

2013-01-01T23:59:59.000Z

395

Collection and representation of GIS data to aid household water treatment and safe storage technology implementation in the northern region of Ghana  

E-Print Network (OSTI)

In 2005, a start-up social business called Pure Home Water (PHW) was begun in Ghana to promote and sell household water treatment and safe storage (HWTS) technologies. The original aim of the company was to offer a variety ...

VanCalcar, Jenny E. (Jenny Elizabeth)

2006-01-01T23:59:59.000Z

396

A life cycle approach to the management of household food waste - A Swedish full-scale case study  

Science Conference Proceedings (OSTI)

Research Highlights: > The comparison of three different methods for management of household food waste show that anaerobic digestion provides greater environmental benefits in relation to global warming potential, acidification and ozone depilation compared to incineration and composting of food waste. Use of produced biogas as car fuel provides larger environmental benefits compared to a use of biogas for heat and power production. > The use of produced digestate from the anaerobic digestion as substitution for chemical fertilizer on farmland provides avoidance of environmental burdens in the same ratio as the substitution of fossil fuels with produced biogas. > Sensitivity analyses show that results are highly sensitive to assumptions regarding the environmental burdens connected to heat and energy supposedly substituted by the waste treatment. - Abstract: Environmental impacts from incineration, decentralised composting and centralised anaerobic digestion of solid organic household waste are compared using the EASEWASTE LCA-tool. The comparison is based on a full scale case study in southern Sweden and used input-data related to aspects such as source-separation behaviour, transport distances, etc. are site-specific. Results show that biological treatment methods - both anaerobic and aerobic, result in net avoidance of GHG-emissions, but give a larger contribution both to nutrient enrichment and acidification when compared to incineration. Results are to a high degree dependent on energy substitution and emissions during biological processes. It was seen that if it is assumed that produced biogas substitute electricity based on Danish coal power, this is preferable before use of biogas as car fuel. Use of biogas for Danish electricity substitution was also determined to be more beneficial compared to incineration of organic household waste. This is a result mainly of the use of plastic bags in the incineration alternative (compared to paper bags in the anaerobic) and the use of biofertiliser (digestate) from anaerobic treatment as substitution of chemical fertilisers used in an incineration alternative. Net impact related to GWP from the management chain varies from a contribution of 2.6 kg CO{sub 2}-eq/household and year if incineration is utilised, to an avoidance of 5.6 kg CO{sub 2}-eq/household and year if choosing anaerobic digestion and using produced biogas as car fuel. Impacts are often dependent on processes allocated far from the control of local decision-makers, indicating the importance of a holistic approach and extended collaboration between agents in the waste management chain.

Bernstad, A., E-mail: anna.bernstad@chemeng.lth.se [Department of Chemical Engineering, Box 124, Faculty of Engineering (LTH), Lund University, S-221 00 Lund (Sweden); Cour Jansen, J. la [Department of Chemical Engineering, Box 124, Faculty of Engineering (LTH), Lund University, S-221 00 Lund (Sweden)

2011-08-15T23:59:59.000Z

397

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

398

Residential energy consumption across different population groups: Comparative analysis for Latino and non-Latino households in U.S.A.  

SciTech Connect

Residential energy cost, an important part of the household budget, varies significantly across different population groups. In the United States, researchers have conducted many studies of household fuel consumption by fuel type -- electricity, natural gas, fuel oil, and liquefied petroleum gas (LPG) -- and by geographic areas. The results of past research have also demonstrated significant variation in residential energy use across various population groups, including white, black, and Latino. However, research shows that residential energy demand by fuel type for Latinos, the fastest-growing population group in the United States, has not been explained by economic and noneconomic factors in any available statistical model. This paper presents a discussion of energy demand and expenditure patterns for Latino and non-Latino households in the United States. The statistical model developed to explain fuel consumption and expenditures for Latino households is based on Stone and Geary`s linear expenditure system model. For comparison, the authors also developed models for energy consumption in non-Latino, black, and nonblack households. These models estimate consumption of and expenditures for electricity, natural gas, fuel oil, and LPG by various households at the national level. The study revealed significant variations in the patterns of fuel consumption for Latinos and non-Latinos. The model methodology and results of this research should be useful to energy policymakers in government and industry, researchers, and academicians who are concerned with economic and energy issues related to various population groups.

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

1998-05-01T23:59:59.000Z

399

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

SciTech Connect

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

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

1984-10-01T23:59:59.000Z

400

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

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401

Personal vehicles preferred by urban Americans: household automobile holdings and new car purchases projected to the year 2000  

DOE Green Energy (OSTI)

A procedure is described for modeling the choices made in urban American households among personal vehicles on the bases of cost, passenger capacity, and engine technology, and it projects those preferences to the year 1990 and 2000. The results of this disaggregate technique are used by the other predictive research tasks undertaken by Argonne National Laboratory in a project entitled Technology Assessment of Productive Conservation in Urban Transportation (TAPCUT). The vehicle preferences reported here furnish data for the overall TAPCUT objective of forecasting the probable effects of energy conservation policies in transportation. In our projections, vehicles with standard spark-ignition (Otto-cycle) engines continue to dominate automobile holdings and new car purchases in either of two socioeconomic scenarios under any of three settings (an existing policy set and two alternative conservation strategies). From 1990, small cars (seating four or fewer passengers) dominate urban holdings and sales in two of the three TAPCUT energy strategies - the exception being the strategy that emphasizes individual travel - and this holds true with only a minor variation for both socioeconomic scenarios (an optimistic one and a slightly pessimistic one). Advanced-technology vehicles are most successful under the Individual Travel Strategy. It appears that vehicle charateristics are far more significant than demographic descriptors in estimating household vehicle choice using this modeling approach.

Saricks, C.L.; Vyas, A.D.; Bunch, J.A.

1982-01-01T23:59:59.000Z

402

Emissions from small-scale energy production using co-combustion of biofuel and the dry fraction of household waste  

SciTech Connect

In sparsely populated rural areas, recycling of household waste might not always be the most environmentally advantageous solution due to the total amount of transport involved. In this study, an alternative approach to recycling has been tested using efficient small-scale biofuel boilers for co-combustion of biofuel and high-energy waste. The dry combustible fraction of source-sorted household waste was mixed with the energy crop reed canary-grass (Phalaris Arundinacea L.), and combusted in both a 5-kW pilot scale reactor and a biofuel boiler with 140-180 kW output capacity, in the form of pellets and briquettes, respectively. The chlorine content of the waste fraction was 0.2%, most of which originated from plastics. The HCl emissions exceeded levels stipulated in new EU-directives, but levels of equal magnitude were also generated from combustion of the pure biofuel. Addition of waste to the biofuel did not give any apparent increase in emissions of organic compounds. Dioxin levels were close to stipulated limits. With further refinement of combustion equipment, small-scale co-combustion systems have the potential to comply with emission regulations.

Hedman, Bjoern [Chemistry Department, Environmental Chemistry, Umeaa University, SE-901 87 Umeaa (Sweden)]. E-mail: bjorn.hedman@chem.umu.se; Burvall, Jan [Unit for Biomass Technology and Chemistry, Swedish University of Agricultural Sciences, Box 4097, SE-904 03 Umeaa (Sweden); Nilsson, Calle [NBC Defence, NBC Analysis, The Swedish Defence Research Agency, SE-901 82 Umeaa (Sweden); Marklund, Stellan [Chemistry Department, Environmental Chemistry, Umeaa University, SE-901 87 Umeaa (Sweden)

2005-07-01T23:59:59.000Z

403

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

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

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

404

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

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

3 Lighting Usage Indicators by Household Income, 2005" 3 Lighting Usage Indicators by Household Income, 2005" " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ,"Housing Units (millions)" ,,"Less than $20,000","$20,000 to $39,999","$40,000 to $59,999","$60,000 to $79,999","$80,000 or More" "Lighting Usage Indicators" "Total U.S. Housing Units",111.1,26.7,28.8,20.6,13.1,22,16.6,38.6 "Indoor Lights Turned On During Summer" "Number of Lights Turned On" "Between 1 and 4 Hours per Day",91.8,20.8,23.6,17,11.3,19.1,13,30.7 "1.",28.6,9.4,9.1,4.5,2.4,3.2,5.7,12.6 "2.",29.5,6.8,8,5.8,3.7,5.2,4.2,10.2

405

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

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

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

406

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

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

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

407

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

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

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

408

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

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

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

409

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

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

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

410

Separate collection of household food waste for anaerobic degradation - Comparison of different techniques from a systems perspective  

SciTech Connect

Highlight: Black-Right-Pointing-Pointer Four modern and innovative systems for household food waste collection are compared. Black-Right-Pointing-Pointer Direct emissions and resource use were based on full-scale data. Black-Right-Pointing-Pointer Conservation of nutrients/energy content over the system was considered. Black-Right-Pointing-Pointer Systems with high energy/nutrient recovery are most environmentally beneficial. - Abstract: Four systems for household food waste collection are compared in relation the environmental impact categories eutrophication potential, acidification potential, global warming potential as well as energy use. Also, a hotspot analysis is performed in order to suggest improvements in each of the compared collection systems. Separate collection of household food waste in paper bags (with and without drying prior to collection) with use of kitchen grinders and with use of vacuum system in kitchen sinks were compared. In all cases, food waste was used for anaerobic digestion with energy and nutrient recovery in all cases. Compared systems all resulted in net avoidance of assessed environmental impact categories; eutrophication potential (-0.1 to -2.4 kg NO{sub 3}{sup -}eq/ton food waste), acidification potential (-0.4 to -1.0 kg SO{sub 2}{sup -}eq/ton food waste), global warming potential (-790 to -960 kg CO{sub 2}{sup -}eq/ton food waste) and primary energy use (-1.7 to -3.6 GJ/ton food waste). Collection with vacuum system results in the largest net avoidance of primary energy use, while disposal of food waste in paper bags for decentralized drying before collection result in a larger net avoidance of global warming, eutrophication and acidification. However, both these systems not have been taken into use in large scale systems yet and further investigations are needed in order to confirm the outcomes from the comparison. Ranking of scenarios differ largely if considering only emissions in the foreground system, indicating the importance of taking also downstream emissions into consideration when comparing different collection systems. The hot spot identification shows that losses of organic matter in mechanical pretreatment as well as tank connected food waste disposal systems and energy in drying and vacuum systems reply to the largest impact on the results in each system respectively.

Bernstad, A., E-mail: Anna.bernstad@chemeng.lth.se [Water and Environmental Engineering, Department of Chemical Engineering, Lund University (Sweden); Cour Jansen, J. la [Water and Environmental Engineering, Department of Chemical Engineering, Lund University (Sweden)

2012-05-15T23:59:59.000Z

411

"Housing Unit and Household","Households","With Fans","Households...  

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

LPG",5,3.8,75.6,10,2.7,2 "Wood",2,1.5,73.5,3.7,2.5,1.8 "Kerosene",0.7,0.3,47,0.8,2.3,1.1 "Solar","Q","Q","Q","Q","Q","Q" "OtherNone",0.6,0.1,21.6,0.3,2.1,0.5 "Natural Gas...

412

Final report on the use of wood as a heat source and the quality of insulation in Vermont households  

SciTech Connect

The State of Vermont Energy Office conducted a study to provide the quantitative attitudinal and behavioral information essential to assessing the use of wood as a heat source in the state. General results show that 54% of all home owners in Vermont burn wood to some degree, 47% use wood as a supplementary heat source, 9% use wood as a primary source, and the extent to which wood is used does not differ by geographic area. Results on household uses (cooking and heating) are summarized. A summary of queries on insulation attitudes, awareness, and practices shows that a majority of homeowners believe they have adequate insulation, but are unaware of R factor. In Vermont, about one-fourth of homeowners improved their insulation in the last three years. (MCW)

1976-01-01T23:59:59.000Z

413

The impact of rising energy prices on household energy consumption and expenditure patterns: The Persian Gulf crisis as a case example  

SciTech Connect

The Iraqi invasion of Kuwait and the subsequent war between Iraq and an international alliance led by the United States triggered immediate increases in world oil prices. Increases in world petroleum prices and in US petroleum imports resulted in higher petroleum prices for US customers. In this report, the effects of the Persian Gulf War and its aftermath are used to demonstrate the potential impacts of petroleum price changes on majority, black, and Hispanic households, as well as on poor and nonpoor households. The analysis is done by using the Minority Energy Assessment Model developed by Argonne National Laboratory for the US Department of Energy (DOE). The differential impacts of these price increases and fluctuations on poor and minority households raise significant issues for a variety of government agencies, including DOE. Although the Persian Gulf crisis is now over and world oil prices have returned to their prewar levels, the differential impacts of rising energy prices on poor and minority households as a result of any future crisis in the world oil market remains a significant long-term issue.

Henderson, L.J. (Baltimore Univ., MD (United States)); Poyer, D.A.; Teotia, A.P.S. (Argonne National Lab., IL (United States). Energy Systems Div.)

1992-09-01T23:59:59.000Z

414

A comparative analysis of energy demand and expenditures by minority and majority households within the context of a conditional demand system  

SciTech Connect

Analysis and evaluation of the impact that programs and policies have on energy consumption and expenditures are confounded by many intervening variables. A clear understanding of how these variables influence energy consumption patterns should be grounded in a rigorously developed framework. In this regard much is documented in the literature. However, an analysis of the comparative relationship between energy demand and variables which influence it among different socioeconomic groups has not been thoroughly explored with any theoretical rigor. It is proposed that differences in patterns of energy use between black, Hispanic, and majority households (where the household head is neither black nor Hispanic) are due to both structural and distribution differences. It is felt that the structural dissimilarities are primarily due to the dynamic nature in which energy consumption patterns evolve, with differences in changing housing patterns playing a significant role. For minorities, this implies a potential difference in the effect of policy and programs on economic welfare when compared to majority households.To test this hypothesis, separate conditional demand systems are estimated for majority, black, and Hispanic households. With the use of separate variance/covariance matrices, various parameter groups are tested for statistically significant differences.

Poyer, D.A.

1992-08-01T23:59:59.000Z

415

A comparative analysis of energy demand and expenditures by minority and majority households within the context of a conditional demand system  

SciTech Connect

Analysis and evaluation of the impact that programs and policies have on energy consumption and expenditures are confounded by many intervening variables. A clear understanding of how these variables influence energy consumption patterns should be grounded in a rigorously developed framework. In this regard much is documented in the literature. However, an analysis of the comparative relationship between energy demand and variables which influence it among different socioeconomic groups has not been thoroughly explored with any theoretical rigor. It is proposed that differences in patterns of energy use between black, Hispanic, and majority households (where the household head is neither black nor Hispanic) are due to both structural and distribution differences. It is felt that the structural dissimilarities are primarily due to the dynamic nature in which energy consumption patterns evolve, with differences in changing housing patterns playing a significant role. For minorities, this implies a potential difference in the effect of policy and programs on economic welfare when compared to majority households.To test this hypothesis, separate conditional demand systems are estimated for majority, black, and Hispanic households. With the use of separate variance/covariance matrices, various parameter groups are tested for statistically significant differences.

Poyer, D.A.

1992-01-01T23:59:59.000Z

416

Location Games and Bounds for Median Problems  

E-Print Network (OSTI)

We consider a two-person zero-sum game in which the maximizer selects a point in a given bounded planar region, the minimizer selects K points in that region,.and the payoff is the distance from the maximizer's location ...

Haimovich, Mordecai

417

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

418

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

SciTech Connect

This paper revises and extends EPRI report EA-3409, ''Household Appliance Choice: Revision of REEPS Behavioral Models.'' That paper reported the results of an econometric study of major appliance choice in new residential construction. Errors appeared in two tables of that report. We offer revised versions of those tables, and a brief analysis of the consequences and significance of the errors. The present paper also proposes several possible extensions and re-specifications of the models examined by EPRI. Some of these are judged to be highly successful; they both satisfy economic intuition more completely than the original specification and produce a better quality fit to the dependent variable. We feel that inclusion of these modifications produces a more useful set of coefficients for economic modeling than the original specification. This paper focuses on EPRI's models of residential space heating technology choice. That choice was modeled as a nested logit structure, with consumers choosing whether to have central air conditioning or not, and, given that choice, what kind of space heating system to have. The model included five space heating alternatives with central cooling (gas, oil, and electric forced-air; heat pumps; and electric baseboard) and eight alternatives without it (gas, oil, and electric forced-air; gas and oil boilers and non-central systems; and electric baseboard heat). The structure of the nested logit model is shown in Figure 1.

Wood, D.J.; Ruderman, H.; McMahon, J. E.

1989-05-01T23:59:59.000Z

419

An econometric analysis of regional differences in household waste collection: The case of plastic packaging waste in Sweden  

Science Conference Proceedings (OSTI)

The Swedish producer responsibility ordinance mandates producers to collect and recycle packaging materials. This paper investigates the main determinants of collection rates of household plastic packaging waste in Swedish municipalities. This is done by the use of a regression analysis based on cross-sectional data for 252 Swedish municipalities. The results suggest that local policies, geographic/demographic variables, socio-economic factors and environmental preferences all help explain inter-municipality collection rates. For instance, the collection rate appears to be positively affected by increases in the unemployment rate, the share of private houses, and the presence of immigrants (unless newly arrived) in the municipality. The impacts of distance to recycling industry, urbanization rate and population density on collection outcomes turn out, though, to be both statistically and economically insignificant. A reasonable explanation for this is that the monetary compensation from the material companies to the collection entrepreneurs vary depending on region and is typically higher in high-cost regions. This implies that the plastic packaging collection in Sweden may be cost ineffective. Finally, the analysis also shows that municipalities that employ weight-based waste management fees generally experience higher collection rates than those municipalities in which flat and/or volume-based fees are used.

Hage, Olle [Economics Unit, Lulea University of Technology, SE 971 87, Lulea (Sweden)], E-mail: olle.hage@ltu.se; Soederholm, Patrik [Economics Unit, Lulea University of Technology, SE 971 87, Lulea (Sweden)

2008-07-01T23:59:59.000Z

420

The unavailable candidate model: a decision-theoretic view of social choice  

Science Conference Proceedings (OSTI)

One of the fundamental problems in the theory of social choice is aggregating the rankings of a set of agents (or voters) into a consensus ranking. Rank aggregation has found application in a variety of computational contexts. However, the goal ... Keywords: preferences, rank aggregation, social choice, voting

Tyler Lu; Craig E. Boutilier

2010-06-01T23:59:59.000Z

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


421

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

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

6 Air Conditioning Characteristics by Household Income, 2005" 6 Air Conditioning Characteristics by Household Income, 2005" " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ,"Housing Units (millions)" ,,"Less than $20,000","$20,000 to $39,999","$40,000 to $59,999","$60,000 to $79,999","$80,000 or More" "Air Conditioning Characteristics" "Total",111.1,26.7,28.8,20.6,13.1,22,16.6,38.6 "Do Not Have Cooling Equipment",17.8,5.3,4.7,2.8,1.9,3.1,3.6,7.5 "Have Cooling Equipment",93.3,21.5,24.1,17.8,11.2,18.8,13,31.1 "Use Cooling Equipment",91.4,21,23.5,17.4,11,18.6,12.6,30.3 "Have Equipment But Do Not Use it",1.9,0.5,0.6,0.4,"Q","Q",0.5,0.8

422

Household Vehicles Energy Consumption  

Reports and Publications (EIA)

This report provides newly available national and regional data and analyzes the nation's energy use by light-duty vehicles. This release represents the analytical component of the report, with a data component having been released in early 2005.

Mark Schipper

2005-11-30T23:59:59.000Z

423

Modelling household electricity consumption.  

E-Print Network (OSTI)

??A number of conclusions are drawn, however given the limited and non-representative na- ture of the data on which the model is calibrated, these can… (more)

de la Rue, Philip Martin

2010-01-01T23:59:59.000Z

424

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

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

1 Average Square Footage of Midwest Homes, by Housing Characteristics, 2009" 1 Average Square Footage of Midwest Homes, by Housing Characteristics, 2009" " Final" ,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member" "Housing Characteristics","Millions","Total2","Heated","Cooled","Total2","Heated","Cooled" "Total Midwest",25.9,2272,1898,1372,912,762,551 "Midwest Divisions and States" "East North Central",17.9,2251,1869,1281,892,741,508 "Illinois",4.8,2186,1911,1451,860,752,571 "Michigan",3.8,1954,1559,962,729,582,359 "Wisconsin",2.3,2605,2091,1258,1105,887,534

425

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

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

3 Average Square Footage of West Homes, by Housing Characteristics, 2009" 3 Average Square Footage of West Homes, by Housing Characteristics, 2009" " Final" ,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member" "Housing Characteristics","Millions","Total2","Heated","Cooled","Total2","Heated","Cooled" "Total West",24.8,1708,1374,800,628,506,294 "West Divisions and States" "Mountain",7.9,1928,1695,1105,723,635,415 "Mountain North",3.9,2107,1858,912,776,684,336 "Colorado",1.9,2082,1832,722,896,788,311 "Idaho, Montana, Utah, Wyoming",2,2130,1883,1093,691,610,354

426

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

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

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

427

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

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

2 Average Square Footage of South Homes, by Housing Characteristics, 2009" 2 Average Square Footage of South Homes, by Housing Characteristics, 2009" " Final" ,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member" "Housing Characteristics","Millions","Total2","Heated","Cooled","Total2","Heated","Cooled" "Total South",42.1,1867,1637,1549,732,642,607 "South Divisions and States" "South Atlantic",22.2,1944,1687,1596,771,668,633 "Virginia",3,2227,1977,1802,855,759,692 "Georgia",3.5,2304,1983,1906,855,736,707 "Florida",7,1668,1432,1509,690,593,625 "DC, DE, MD, WV",3.4,2218,1831,1440,864,713,561

428

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

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

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

429

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

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

0 Average Square Footage of Northeast Homes, by Housing Characteristics, 2009" 0 Average Square Footage of Northeast Homes, by Housing Characteristics, 2009" " Final" ,"Housing Units1","Average Square Footage Per Housing Unit",,,"Average Square Footage Per Household Member" "Housing Characteristics","Millions","Total2","Heated","Cooled","Total2","Heated","Cooled" "Total Northeast",20.8,2121,1663,921,836,656,363 "Northeast Divisions and States" "New England",5.5,2232,1680,625,903,680,253 "Massachusetts",2.5,2076,1556,676,850,637,277 "CT, ME, NH, RI, VT",3,2360,1781,583,946,714,234 "Mid-Atlantic",15.3,2080,1657,1028,813,647,402

430

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

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

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

431

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

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

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

432

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

E-Print Network (OSTI)

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

433

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

E-Print Network (OSTI)

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

434

Home composting as an alternative treatment option for organic household waste in Denmark: An environmental assessment using life cycle assessment-modelling  

SciTech Connect

An environmental assessment of the management of organic household waste (OHW) was performed from a life cycle perspective by means of the waste-life cycle assessment (LCA) model EASEWASTE. The focus was on home composting of OHW in Denmark and six different home composting units (with different input and different mixing frequencies) were modelled. In addition, incineration and landfilling was modelled as alternatives to home composting. The most important processes contributing to the environmental impact of home composting were identified as greenhouse gas (GHG) emissions (load) and the avoided emissions in relation to the substitution of fertiliser and peat when compost was used in hobby gardening (saving). The replacement of fertiliser and peat was also identified as one of the most sensible parameters, which could potentially have a significant environmental benefit. Many of the impact categories (especially human toxicity via water (HTw) and soil (HTs)) were affected by the heavy metal contents of the incoming OHW. The concentrations of heavy metals in the compost were below the threshold values for compost used on land and were thus not considered to constitute a problem. The GHG emissions were, on the other hand, dependent on the management of the composting units. The frequently mixed composting units had the highest GHG emissions. The environmental profiles of the home composting scenarios were in the order of -2 to 16 milli person equivalents (mPE) Mg{sup -1} wet waste (ww) for the non-toxic categories and -0.9 to 28 mPE Mg{sup -1} ww for the toxic categories. Home composting performed better than or as good as incineration and landfilling in several of the potential impact categories. One exception was the global warming (GW) category, in which incineration performed better due to the substitution of heat and electricity based on fossil fuels.

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

2012-01-15T23:59:59.000Z

435

Recall-Precision Curve Difference from Median in Precision at ...  

Science Conference Proceedings (OSTI)

... 7C3%& A50VAbADQbA('qA2 p(A3121C5 Q0f9C32 drig@f Q0ed9 C32 dri@ds Q0ef9 C32 drea@i Q0id9 C32 dret@g Q0@d9 C32 dresea ...

2003-03-07T23:59:59.000Z

436

Optimization Online - Reliable p-median facility location problem ...  

E-Print Network (OSTI)

Dec 18, 2012 ... A customized column-and- constraint generation approach is implemented and shown to be more effective ... Entry Last Modified: 12/18/2012.

437

VECTOR MEDIAN-RATIONALHYBRID FILTERS FOR MULTICHANNELIMAGE Lazhar Khriji  

E-Print Network (OSTI)

thevectorrationaloperator(VRF)(Theoutputisthe result of vector rational operation taking into account three sub/outputrelation, and hence the name "vectorrational filters" (VRF's)[3]. There are several advantage to the use

Gabbouj, Moncef

438

2003 CBECS National Median Source Energy Use and Performance...  

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

Building Type Secondary menu About us Press room Contact Us Portfolio Manager Login Facility owners and managers Existing buildings Commercial new construction Industrial energy...

439

Median Light Rail Crossing: Accident Causation And Countermeasures  

E-Print Network (OSTI)

Integration of Light Rail Transit Into City Streets. TCRPInfluencing Safety at Highway-Rail Grade Crossings. InK. , W. Hucke and W. Berg. Rail Highway Crossing Accident

Coifman, Benjamin; Bertini, Robert L.

1997-01-01T23:59:59.000Z

440

Median Light Rail Crossing: Accident Causation And Countermeasures  

E-Print Network (OSTI)

Cooperative Research Program. Integration of Light RailRail Grade Crossings. In National Cooperative Highway ResearchLight Rail Safety Issues. In Transportation Research Record

Coifman, Benjamin; Bertini, Robert L.

1997-01-01T23:59:59.000Z

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


441

Household 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

442

ac_household2001.pdf  

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

of the annual heating and cooling degree-days. For this report, the heating or cooling degree-days are a measure of how cold or how hot a location is over a period of...

443

homeoffice_household2001.pdf  

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

more ... 2.2 0.9 0.5 Q Q Q 0.4 23.9 Have Access to Internet ... 50.7 9.3 10.1 8.8 6.1 6.7 9.7 5.7 Hours PCs Turned On Each Week Less...

444

homeoffice_household2001.pdf  

Gasoline and Diesel Fuel Update (EIA)

... 2.2 Q 0.2 Q Q 32.7 Have Access to Internet ... 50.7 3.1 6.8 3.4 3.1 5.2 Hours PCs Turned On Each Week...

445

homeoffice_household2001.pdf  

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

... 2.2 0.5 Q 0.3 23.2 Have Access to Internet ... 50.7 12.2 3.3 9.0 4.3 Hours PCs Turned On Each Week Less...

446

appl_household2001.pdf  

Annual Energy Outlook 2012 (EIA)

Units ... 11.9 8.7 1.5 1.5 0.2 14.9 Heaters (other) Hot Tub or Spa (heaters) ... 4.4 1.6 0.6 1.2 1.0 14.8 Electric...

447

appl_household2001.pdf  

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

or More Units ... 11.9 2.3 2.0 0.4 19.8 Heaters (other) Hot Tub or Spa (heaters) ... 4.4 0.6 0.4 0.2 19.5 Electric...

448

appl_household2001.pdf  

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

More Units ... 11.9 1.9 0.9 Q 0.8 24.6 Heaters (other) Hot Tub or Spa (heaters) ... 4.4 1.5 0.6 0.2 0.8 12.2 Electric...

449

appl_household2001.pdf  

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

Units ... 11.9 2.6 1.9 0.8 0.2 15.2 Heaters (other) Hot Tub or Spa (heaters) ... 4.4 0.2 0.9 0.6 Q 14.6 Electric...

450

appl_household2001.pdf  

Gasoline and Diesel Fuel Update (EIA)

Very Large (23 or More cf) ... 5.3 0.3 1.1 1.1 1.1 1.6 18.3 Through-the-Door IceWater Service Yes ... 22.1 1.2 5.1 4.4 5.4 5.9 9.6...

451

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...

452

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)...

453

appl_household2001.pdf  

Annual Energy Outlook 2012 (EIA)

... Q Q Q Q Q NF Other Appliances Automobile BlockEngine Battery Heater ... 0.5 0.3 Q 0.1 Q 37.2 Ceiling Fans...

454

Household Vehicles Energy Consumption 1991  

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

all comparisons reported in the text are statistically significant, based on a standard test made at the 0.05 significance level. No adjustments were made for simultaneous...

455

ASSESSMENT OF HOUSEHOLD CARBON FOOTPRINT REDUCTION POTENTIALS  

E-Print Network (OSTI)

affordable, and reliable energy services and products to consumption of energy, goods, and services by  California consumption of energy, goods, and services by  California 

Masanet, Eric

2010-01-01T23:59:59.000Z

456

ASSESSMENT OF HOUSEHOLD CARBON FOOTPRINT REDUCTION POTENTIALS  

E-Print Network (OSTI)

Energy,  Industrial Technologies Program, Washington, D.C.    GlossaryEnergy Efficient Technology Potentials. 31 Conclusions and Recommendations 42 References. 45 Glossary .

Masanet, Eric

2010-01-01T23:59:59.000Z

457

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

458

Household Fuel Oil or Kerosene Usage Form  

U.S. Energy Information Administration (EIA)

Contractor’s Street Address . Contractor’s City, State, and ZIP Code . ... is a light distillate fuel oil intended for use in vaporizing pot-type burners.

459

ASSESSMENT OF HOUSEHOLD CARBON FOOTPRINT REDUCTION POTENTIALS  

E-Print Network (OSTI)

help California energy and policy analysts better assess end use detail  allows energy and policy analysts to better which would allow energy and policy analysts to better 

Masanet, Eric

2010-01-01T23:59:59.000Z

460

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

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

Household Vehicles Energy Use: Latest Data & Trends  

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

Jan-98 Jan-02 Constant 2005 per barrel Official Price of Saudi Light Refiner Acquisition Cost of Imported Crude Oil (RAC) Source: Energy Information Administration. Iran-Iraq War...

462

ASSESSMENT OF HOUSEHOLD CARBON FOOTPRINT REDUCTION POTENTIALS  

E-Print Network (OSTI)

heating Elec: Industrial refrigeration Petr: Agricultural estimates for industrial HVAC, refrigeration, and  lighting Commercial Refrigeration NG: Industrial process heating

Masanet, Eric

2010-01-01T23:59:59.000Z

463

ASSESSMENT OF HOUSEHOLD CARBON FOOTPRINT REDUCTION POTENTIALS  

E-Print Network (OSTI)

Renewable Energy Technologies   Transportation   Assessment Department of Energy, Industrial Technologies Program, Department of Energy, Industrial Technologies Program, 

Masanet, Eric

2010-01-01T23:59:59.000Z

464

ASSESSMENT OF HOUSEHOLD CARBON FOOTPRINT REDUCTION POTENTIALS  

E-Print Network (OSTI)

7: Estimated annual supply chain natural gas related GHG7: Estimated annual supply chain natural gas related GHGTotal Indirect ? supply chain Direct ? natural gas Direct ?

Masanet, Eric

2010-01-01T23:59:59.000Z

465

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

466

Advances in Household Appliances- A Review  

Science Conference Proceedings (OSTI)

An overview of options and potential barriers and risks for reducing the energy consumption, peak demand, and emissions for seven key energy consuming residential products (refrigerator-freezers, dishwashers, clothes washers, clothes dryers, electric ovens, gas ovens and microwave ovens) is presented. The paper primarily concentrates on the potential energy savings from the use of advanced technologies in appliances for the U.S. market. The significance and usefulness of each technology was evaluated in order to prioritize the R&D needs to improve energy efficiency of appliances in view of energy savings, cost, and complexity. The paper provides a snapshot of the future R&D needs for each of the technologies along with the associated barriers. Although significant energy savings may be achieved, one of the major barriers in most cases is high first cost. One way of addressing this issue and promoting the introduction of new technologies is to level the playing field for all manufacturers by establishing Minimum Energy Performance Standards (MEPS) which are not cost prohibitive and promoting energy efficient products through incentives to both manufacturers and consumers.

Bansal, Pradeep [ORNL; Vineyard, Edward Allan [ORNL; Abdelaziz, Omar [ORNL

2011-01-01T23:59:59.000Z

467

ASSESSMENT OF HOUSEHOLD CARBON FOOTPRINT REDUCTION POTENTIALS  

E-Print Network (OSTI)

which will help California energy and policy analysts and KEMA (2008).  California Energy Efficiency Potential Final Report.  California Energy Commission, Sacramento, 

Masanet, Eric

2010-01-01T23:59:59.000Z

468

Household Vehicles Energy Use: Latest Data & Trends  

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

These mpg values are associated with various combinations of engine and drive-train technologies (e.g., number of cylinders, engine size, gasoline or diesel fuel, and...

469

Household Vehicles Energy Use: Latest Data & Trends  

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

O V E M E U R T E C S N H T S S U R V E Y 2 0 0 1 I N D E X . H T M L The Energy Information Administration, the independent statistical and analytical administration...

470

ASSESSMENT OF HOUSEHOLD CARBON FOOTPRINT REDUCTION POTENTIALS  

E-Print Network (OSTI)

heating Dryer Range/oven Pool heating Spa heating TotalWater heating Space heating Range/oven Dryer Pool/spa Water heating Outdoor lighting Microwave Range/oven Clothes 

Masanet, Eric

2010-01-01T23:59:59.000Z

471

Household type load's effects on photovoltaic systems  

Science Conference Proceedings (OSTI)

The solar energy is one of the most important energy sources available because, besides the fact that it is not polluting the environment and it helps to the reduction of green house effect, it is free of charge and it can be easily converted to other ... Keywords: A.C. loads, D.C. loads, compact fluorescent lamp, photovoltaic system, power LED

Nazmi Ekren; Nevzat Onat; Safak Saglam

2008-12-01T23:59:59.000Z

472

ASSESSMENT OF HOUSEHOLD CARBON FOOTPRINT REDUCTION POTENTIALS  

E-Print Network (OSTI)

e.g. , reductions in landfill gas flaring),  or changes to landfills is +/?30%, the range for methane emissions from  natural gas 

Masanet, Eric

2010-01-01T23:59:59.000Z

473

ASSESSMENT OF HOUSEHOLD CARBON FOOTPRINT REDUCTION POTENTIALS  

E-Print Network (OSTI)

A/C Clothes washer Dishwasher First refrigerator Freezerenabled ENERGY STAR dishwashers, fryers, hot food holding

Masanet, Eric

2010-01-01T23:59:59.000Z

474

ASSESSMENT OF HOUSEHOLD CARBON FOOTPRINT REDUCTION POTENTIALS  

E-Print Network (OSTI)

Flour milling and malt  manufacturing   Fats and oils refining and  blending   Breakfast cereal  manufacturing   Sugar cane mills 

Masanet, Eric

2010-01-01T23:59:59.000Z

475

ASSESSMENT OF HOUSEHOLD CARBON FOOTPRINT REDUCTION POTENTIALS  

E-Print Network (OSTI)

Use Facility HVAC CHP and/or Cogeneration Process FacilityBoiler Use CHP and/or Cogeneration Process Facility HVAC Endby process heating, cogeneration, and steam systems  in the 

Masanet, Eric

2010-01-01T23:59:59.000Z

476

Reliable p-median facility location problem: two-stage robust models ...  

E-Print Network (OSTI)

Results show the significant influence of the demand loss factor on the network ...... Robust Unit Commitment Problem with Demand Response and Wind.

477

Difference from Median in T11U per Topic Difference from ...  

Science Conference Proceedings (OSTI)

... &'(( )01&2)2342354 6'7 89@ )ABCCD E&p &'E2)4F E)25G 6H4I'05H4'4HP@ I2GH0Q 6RS TA23(3U HP VI0 QCCp QIA3521AH@ W44H44I0 ...

2003-03-06T23:59:59.000Z

478

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

479

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

480

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

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


481

The 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