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


1

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

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

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

2

"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

3

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

4

Characteristics RSE Column Factor: Total  

Gasoline and Diesel Fuel Update (EIA)

Per- cent 125 Per- cent 0.4 2.4 1.8 1.2 0.9 0.8 0.8 0.7 1.4 1.1 0.9 Race of Householder White ... 1,592 27 60 105 272 255 358 514 97 155...

5

Ventilation Behavior and Household Characteristics in NewCalifornia Houses  

SciTech Connect (OSTI)

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

Price, Phillip N.; Sherman, Max H.

2006-02-01T23:59:59.000Z

6

Household solid waste characteristics and management in Chittagong, Bangladesh  

SciTech Connect (OSTI)

Solid waste management (SWM) is a multidimensional challenge faced by urban authorities, especially in developing countries like Bangladesh. We investigated per capita waste generation by residents, its composition, and the households' attitudes towards waste management at Rahman Nagar Residential Area, Chittagong, Bangladesh. The study involved a structured questionnaire and encompassed 75 households from five different socioeconomic groups (SEGs): low (LSEG), lower middle (LMSEG), middle (MSEG), upper middle (UMSEG) and high (HSEG). Wastes, collected from all of the groups of households, were segregated and weighed. Waste generation was 1.3 kg/household/day and 0.25 kg/person/day. Household solid waste (HSW) was comprised of nine categories of wastes with vegetable/food waste being the largest component (62%). Vegetable/food waste generation increased from the HSEG (47%) to the LSEG (88%). By weight, 66% of the waste was compostable in nature. The generation of HSW was positively correlated with family size (r{sub xy} = 0.236, p < 0.05), education level (r{sub xy} = 0.244, p < 0.05) and monthly income (r{sub xy} = 0.671, p < 0.01) of the households. Municipal authorities are usually the responsible agencies for solid waste collection and disposal, but the magnitude of the problem is well beyond the ability of any municipal government to tackle. Hence dwellers were found to take the service from the local waste management initiative. Of the respondents, an impressive 44% were willing to pay US$0.3 to US$0.4 per month to waste collectors and it is recommended that service charge be based on the volume of waste generated by households. Almost a quarter (22.7%) of the respondents preferred 12-1 pm as the time period for their waste to be collected. This study adequately shows that household solid waste can be converted from burden to resource through segregation at the source, since people are aware of their role in this direction provided a mechanism to assist them in this pursuit exists and the burden is distributed according to the amount of waste generated.

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

2008-07-01T23:59:59.000Z

7

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

8

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

9

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

E-Print Network [OSTI]

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

Beigl, Michael

10

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

E-Print Network [OSTI]

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

Adjemian, Michael; Williams, Jeffrey

2009-01-01T23:59:59.000Z

11

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

12

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

13

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

14

Total lightning characteristics of ordinary convection.  

E-Print Network [OSTI]

??Twenty-two isolated, non-severe, warm season thunderstorms (ordinary thunderstorms) were examined to test possible correlations between three-dimensional lightning flash characteristics and the complex evolution of the… (more)

Motley, Shane Michael

2009-01-01T23:59:59.000Z

15

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

16

Household Vehicles Energy Consumption 1991  

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

homes, pickup trucks, and jeeps or similar vehicles. See Vehicle. Average Household Energy Expenditures: A ratio estimate defined as the total household energy expenditures for...

17

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

Science Journals Connector (OSTI)

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

T. Suruga; T. Tachibanaki

1991-01-01T23:59:59.000Z

18

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

19

Household vehicles energy consumption 1991  

SciTech Connect (OSTI)

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

Not Available

1993-12-09T23:59:59.000Z

20

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

Note: This page contains sample records for the topic "household characteristics total" 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

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

22

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

23

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

24

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

25

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

26

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

27

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

Science Journals Connector (OSTI)

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

Mutsumi Tokunaga; Hideki Hashimoto; Nanako Tamiya

2014-01-01T23:59:59.000Z

28

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

29

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

30

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

31

The Household “Pie”  

Science Journals Connector (OSTI)

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

Sarah Fenstermaker Berk

1985-01-01T23:59:59.000Z

32

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

33

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

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

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

34

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

35

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

36

"Characteristic(a)","Total","Fuel Oil","Fuel Oil(b)","Natural...  

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

ual","Distillate",,"LPG and",,"Coke and"," " "Characteristic(a)","Total","Fuel Oil","Fuel Oil(b)","Natural Gas(c)","NGL(d)","Coal","Breeze","Other(e)" ,"Total United States" "Value...

37

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

38

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

39

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

40

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

Note: This page contains sample records for the topic "household characteristics total" 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

Total..........................................................  

Gasoline and Diesel Fuel Update (EIA)

... 13.2 2.7 3.5 2.2 1.3 3.5 1.3 3.8 Table HC7.10 Home Appliances Usage Indicators by Household Income, 2005 Below Poverty Line Eligible for Federal...

42

" 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

43

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

44

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

45

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

46

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

47

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

48

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

49

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

50

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

51

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

52

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

53

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

54

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

55

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

56

Total....................................................................  

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

14.7 14.7 7.4 12.5 12.5 18.9 18.6 17.3 9.2 Household Size 1 Person.......................................................... 30.0 4.6 2.5 3.7 3.2 5.4 5.5 3.7 1.6 2 Persons......................................................... 34.8 4.3 1.9 4.4 4.1 5.9 5.3 5.5 3.4 3 Persons......................................................... 18.4 2.5 1.3 1.7 1.9 2.9 3.5 2.8 1.6 4 Persons......................................................... 15.9 1.9 0.8 1.5 1.6 3.0 2.5 3.1 1.4 5 Persons......................................................... 7.9 0.8 0.4 1.0 1.1 1.2 1.1 1.5 0.9 6 or More Persons........................................... 4.1 0.5 0.3 0.3 0.6 0.5 0.7 0.8 0.4 2005 Annual Household Income Category Less than $9,999............................................. 9.9 1.9 1.1 1.3 0.9 1.7 1.3 1.1 0.5 $10,000 to $14,999..........................................

57

Total..........................................................  

Gasoline and Diesel Fuel Update (EIA)

Housing Units Living Space Characteristics Attached 2 to 4 Units 5 or More Units Mobile Homes Apartments in Buildings With-- Housing Units (millions) Single-Family Units Detached...

58

Total...........................................................  

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

Q Q Million U.S. Housing Units Renter- Occupied Housing Units (millions) Type of Renter-Occupied Housing Unit U.S. Housing Units (millions Single-Family Units Apartments in Buildings With-- Living Space Characteristics Detached Attached Table HC4.2 Living Space Characteristics by Renter-Occupied Housing Units, 2005 2 to 4 Units 5 or More Units Mobile Homes Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Million U.S. Housing Units Renter- Occupied Housing Units (millions) Type of Renter-Occupied Housing Unit U.S. Housing Units (millions Single-Family Units Apartments in Buildings With-- Living Space Characteristics Detached Attached Table HC4.2 Living Space Characteristics by Renter-Occupied Housing Units, 2005

59

Total  

Gasoline and Diesel Fuel Update (EIA)

Total Total .............. 16,164,874 5,967,376 22,132,249 2,972,552 280,370 167,519 18,711,808 1993 Total .............. 16,691,139 6,034,504 22,725,642 3,103,014 413,971 226,743 18,981,915 1994 Total .............. 17,351,060 6,229,645 23,580,706 3,230,667 412,178 228,336 19,709,525 1995 Total .............. 17,282,032 6,461,596 23,743,628 3,565,023 388,392 283,739 19,506,474 1996 Total .............. 17,680,777 6,370,888 24,051,665 3,510,330 518,425 272,117 19,750,793 Alabama Total......... 570,907 11,394 582,301 22,601 27,006 1,853 530,841 Onshore ................ 209,839 11,394 221,233 22,601 16,762 1,593 180,277 State Offshore....... 209,013 0 209,013 0 10,244 260 198,509 Federal Offshore... 152,055 0 152,055 0 0 0 152,055 Alaska Total ............ 183,747 3,189,837 3,373,584 2,885,686 0 7,070 480,828 Onshore ................ 64,751 3,182,782

60

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

Note: This page contains sample records for the topic "household characteristics total" 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

Total...........................................................  

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

Q Q Table HC3.2 Living Space Characteristics by Owner-Occupied Housing Units, 2005 2 to 4 Units 5 or More Units Mobile Homes Million U.S. Housing Units Owner- Occupied Housing Units (millions) Type of Owner-Occupied Housing Unit Housing Units (millions) Single-Family Units Apartments in Buildings With-- Living Space Characteristics Detached Attached Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Table HC3.2 Living Space Characteristics by Owner-Occupied Housing Units, 2005 2 to 4 Units 5 or More Units Mobile Homes Million U.S. Housing Units Owner- Occupied Housing Units (millions) Type of Owner-Occupied Housing Unit Housing Units (millions)

62

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

63

Total............................................................  

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

Total................................................................... Total................................................................... 111.1 2,033 1,618 1,031 791 630 401 Total Floorspace (Square Feet) Fewer than 500............................................... 3.2 357 336 113 188 177 59 500 to 999....................................................... 23.8 733 667 308 343 312 144 1,000 to 1,499................................................. 20.8 1,157 1,086 625 435 409 235 1,500 to 1,999................................................. 15.4 1,592 1,441 906 595 539 339 2,000 to 2,499................................................. 12.2 2,052 1,733 1,072 765 646 400 2,500 to 2,999................................................. 10.3 2,523 2,010 1,346 939 748 501 3,000 to 3,499................................................. 6.7 3,020 2,185 1,401 1,177 851 546

64

Total...................  

Gasoline and Diesel Fuel Update (EIA)

4,690,065 52,331,397 2,802,751 4,409,699 7,526,898 209,616 1993 Total................... 4,956,445 52,535,411 2,861,569 4,464,906 7,981,433 209,666 1994 Total................... 4,847,702 53,392,557 2,895,013 4,533,905 8,167,033 202,940 1995 Total................... 4,850,318 54,322,179 3,031,077 4,636,500 8,579,585 209,398 1996 Total................... 5,241,414 55,263,673 3,158,244 4,720,227 8,870,422 206,049 Alabama ...................... 56,522 766,322 29,000 62,064 201,414 2,512 Alaska.......................... 16,179 81,348 27,315 12,732 75,616 202 Arizona ........................ 27,709 689,597 28,987 49,693 26,979 534 Arkansas ..................... 46,289 539,952 31,006 67,293 141,300 1,488 California ..................... 473,310 8,969,308 235,068 408,294 693,539 36,613 Colorado...................... 110,924 1,147,743

65

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

Science Journals Connector (OSTI)

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

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

2008-02-01T23:59:59.000Z

66

Total...................................................................  

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

Single-Family Units Single-Family Units Detached Type of Housing Unit Table HC2.7 Air Conditioning Usage Indicators by Type of Housing Unit, 2005 Million U.S. Housing Units Air Conditioning Usage Indicators Attached 2 to 4 Units 5 or More Units Mobile Homes Apartments in Buildings With-- Housing Units (millions) Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Single-Family Units Detached Type of Housing Unit Table HC2.7 Air Conditioning Usage Indicators by Type of Housing Unit, 2005 Million U.S. Housing Units Air Conditioning Usage Indicators Attached 2 to 4 Units 5 or More Units Mobile Homes Apartments in Buildings With-- Housing Units (millions) At Home Behavior Home Used for Business

67

Household vehicles energy consumption 1994  

SciTech Connect (OSTI)

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

NONE

1997-08-01T23:59:59.000Z

68

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

69

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

70

Total..........................................................................  

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

7.1 7.1 19.0 22.7 22.3 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 2.1 0.6 Q 0.4 500 to 999........................................................... 23.8 13.6 3.7 3.2 3.2 1,000 to 1,499..................................................... 20.8 9.5 3.7 3.4 4.2 1,500 to 1,999..................................................... 15.4 6.6 2.7 2.5 3.6 2,000 to 2,499..................................................... 12.2 5.0 2.1 2.8 2.4 2,500 to 2,999..................................................... 10.3 3.7 1.8 2.8 2.1 3,000 to 3,499..................................................... 6.7 2.0 1.4 1.7 1.6 3,500 to 3,999..................................................... 5.2 1.6 0.8 1.5 1.4 4,000 or More.....................................................

71

Total..........................................................................  

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

0.7 0.7 21.7 6.9 12.1 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 0.9 0.6 Q Q 500 to 999........................................................... 23.8 9.0 4.2 1.5 3.2 1,000 to 1,499..................................................... 20.8 8.6 4.7 1.5 2.5 1,500 to 1,999..................................................... 15.4 6.0 2.9 1.2 1.9 2,000 to 2,499..................................................... 12.2 4.1 2.1 0.7 1.3 2,500 to 2,999..................................................... 10.3 3.0 1.8 0.5 0.7 3,000 to 3,499..................................................... 6.7 2.1 1.2 0.5 0.4 3,500 to 3,999..................................................... 5.2 1.5 0.8 0.3 0.4 4,000 or More.....................................................

72

Total..........................................................................  

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

25.6 25.6 40.7 24.2 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 0.9 0.5 0.9 1.0 500 to 999........................................................... 23.8 4.6 3.9 9.0 6.3 1,000 to 1,499..................................................... 20.8 2.8 4.4 8.6 5.0 1,500 to 1,999..................................................... 15.4 1.9 3.5 6.0 4.0 2,000 to 2,499..................................................... 12.2 2.3 3.2 4.1 2.6 2,500 to 2,999..................................................... 10.3 2.2 2.7 3.0 2.4 3,000 to 3,499..................................................... 6.7 1.6 2.1 2.1 0.9 3,500 to 3,999..................................................... 5.2 1.1 1.7 1.5 0.9 4,000 or More.....................................................

73

Total..........................................................................  

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

4.2 4.2 7.6 16.6 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 1.0 0.2 0.8 500 to 999........................................................... 23.8 6.3 1.4 4.9 1,000 to 1,499..................................................... 20.8 5.0 1.6 3.4 1,500 to 1,999..................................................... 15.4 4.0 1.4 2.6 2,000 to 2,499..................................................... 12.2 2.6 0.9 1.7 2,500 to 2,999..................................................... 10.3 2.4 0.9 1.4 3,000 to 3,499..................................................... 6.7 0.9 0.3 0.6 3,500 to 3,999..................................................... 5.2 0.9 0.4 0.5 4,000 or More.....................................................

74

Total.........................................................................  

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

Floorspace (Square Feet) Floorspace (Square Feet) Total Floorspace 2 Fewer than 500.................................................. 3.2 Q 0.8 0.9 0.8 0.5 500 to 999.......................................................... 23.8 1.5 5.4 5.5 6.1 5.3 1,000 to 1,499.................................................... 20.8 1.4 4.0 5.2 5.0 5.2 1,500 to 1,999.................................................... 15.4 1.4 3.1 3.5 3.6 3.8 2,000 to 2,499.................................................... 12.2 1.4 3.2 3.0 2.3 2.3 2,500 to 2,999.................................................... 10.3 1.5 2.3 2.7 2.1 1.7 3,000 to 3,499.................................................... 6.7 1.0 2.0 1.7 1.0 1.0 3,500 to 3,999.................................................... 5.2 0.8 1.5 1.5 0.7 0.7 4,000 or More.....................................................

75

Total..........................................................................  

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

. . 111.1 20.6 15.1 5.5 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 0.9 0.5 0.4 500 to 999........................................................... 23.8 4.6 3.6 1.1 1,000 to 1,499..................................................... 20.8 2.8 2.2 0.6 1,500 to 1,999..................................................... 15.4 1.9 1.4 0.5 2,000 to 2,499..................................................... 12.2 2.3 1.7 0.5 2,500 to 2,999..................................................... 10.3 2.2 1.7 0.6 3,000 to 3,499..................................................... 6.7 1.6 1.0 0.6 3,500 to 3,999..................................................... 5.2 1.1 0.9 0.3 4,000 or More.....................................................

76

Total..........................................................................  

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

7.1 7.1 7.0 8.0 12.1 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 0.4 Q Q 0.5 500 to 999........................................................... 23.8 2.5 1.5 2.1 3.7 1,000 to 1,499..................................................... 20.8 1.1 2.0 1.5 2.5 1,500 to 1,999..................................................... 15.4 0.5 1.2 1.2 1.9 2,000 to 2,499..................................................... 12.2 0.7 0.5 0.8 1.4 2,500 to 2,999..................................................... 10.3 0.5 0.5 0.4 1.1 3,000 to 3,499..................................................... 6.7 0.3 Q 0.4 0.3 3,500 to 3,999..................................................... 5.2 Q Q Q Q 4,000 or More.....................................................

77

Total..........................................................  

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

.. .. 111.1 24.5 1,090 902 341 872 780 441 Total Floorspace (Square Feet) Fewer than 500...................................... 3.1 2.3 403 360 165 366 348 93 500 to 999.............................................. 22.2 14.4 763 660 277 730 646 303 1,000 to 1,499........................................ 19.1 5.8 1,223 1,130 496 1,187 1,086 696 1,500 to 1,999........................................ 14.4 1.0 1,700 1,422 412 1,698 1,544 1,348 2,000 to 2,499........................................ 12.7 0.4 2,139 1,598 Q Q Q Q 2,500 to 2,999........................................ 10.1 Q Q Q Q Q Q Q 3,000 or More......................................... 29.6 0.3 Q Q Q Q Q Q Heated Floorspace (Square Feet) None...................................................... 3.6 1.8 1,048 0 Q 827 0 407 Fewer than 500......................................

78

Total...................................................................  

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

2,033 2,033 1,618 1,031 791 630 401 Total Floorspace (Square Feet) Fewer than 500............................................... 3.2 357 336 113 188 177 59 500 to 999....................................................... 23.8 733 667 308 343 312 144 1,000 to 1,499................................................. 20.8 1,157 1,086 625 435 409 235 1,500 to 1,999................................................. 15.4 1,592 1,441 906 595 539 339 2,000 to 2,499................................................. 12.2 2,052 1,733 1,072 765 646 400 2,500 to 2,999................................................. 10.3 2,523 2,010 1,346 939 748 501 3,000 to 3,499................................................. 6.7 3,020 2,185 1,401 1,177 851 546 3,500 to 3,999................................................. 5.2 3,549 2,509 1,508

79

Total...........................................................  

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

26.7 26.7 28.8 20.6 13.1 22.0 16.6 38.6 Floorspace (Square Feet) Total Floorspace 1 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 7.0 3.8 2.2 2.0 3.9 8.9 1,500 to 1,999..................................... 15.4 3.1 4.2 3.4 2.0 2.7 1.9 5.0 2,000 to 2,499..................................... 12.2 1.7 2.7 2.9 1.8 3.2 1.1 2.8 2,500 to 2,999..................................... 10.3 1.2 2.2 2.3 1.7 2.9 0.6 2.0 3,000 to 3,499..................................... 6.7 0.9 1.4 1.5 1.0 1.9 0.4 1.4 3,500 to 3,999..................................... 5.2 0.8 1.2 1.0 0.8 1.5 0.4 1.3 4,000 or More...................................... 13.3 0.9 1.9 2.2 2.0 6.4 0.6 1.9 Heated Floorspace

80

Total...........................................................  

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

14.7 14.7 7.4 12.5 12.5 18.9 18.6 17.3 9.2 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500.................................... 3.2 0.7 Q 0.3 0.3 0.7 0.6 0.3 Q 500 to 999........................................... 23.8 2.7 1.4 2.2 2.8 5.5 5.1 3.0 1.1 1,000 to 1,499..................................... 20.8 2.3 1.4 2.4 2.5 3.5 3.5 3.6 1.6 1,500 to 1,999..................................... 15.4 1.8 1.4 2.2 2.0 2.4 2.4 2.1 1.2 2,000 to 2,499..................................... 12.2 1.4 0.9 1.8 1.4 2.2 2.1 1.6 0.8 2,500 to 2,999..................................... 10.3 1.6 0.9 1.1 1.1 1.5 1.5 1.7 0.8 3,000 to 3,499..................................... 6.7 1.0 0.5 0.8 0.8 1.2 0.8 0.9 0.8 3,500 to 3,999..................................... 5.2 1.1 0.3 0.7 0.7 0.4 0.5 1.0 0.5 4,000 or More...................................... 13.3

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to obtain the most current and comprehensive results.


81

Total................................................  

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

.. .. 111.1 86.6 2,522 1,970 1,310 1,812 1,475 821 1,055 944 554 Total Floorspace (Square Feet) Fewer than 500............................. 3.2 0.9 261 336 162 Q Q Q 334 260 Q 500 to 999.................................... 23.8 9.4 670 683 320 705 666 274 811 721 363 1,000 to 1,499.............................. 20.8 15.0 1,121 1,083 622 1,129 1,052 535 1,228 1,090 676 1,500 to 1,999.............................. 15.4 14.4 1,574 1,450 945 1,628 1,327 629 1,712 1,489 808 2,000 to 2,499.............................. 12.2 11.9 2,039 1,731 1,055 2,143 1,813 1,152 Q Q Q 2,500 to 2,999.............................. 10.3 10.1 2,519 2,004 1,357 2,492 2,103 1,096 Q Q Q 3,000 or 3,499.............................. 6.7 6.6 3,014 2,175 1,438 3,047 2,079 1,108 N N N 3,500 to 3,999.............................. 5.2 5.1 3,549 2,505 1,518 Q Q Q N N N 4,000 or More...............................

82

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

83

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

84

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

85

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

86

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

87

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

88

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

89

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

90

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

91

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

92

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

93

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

94

RECS Data Show Decreased Energy Consumption per Household  

Reports and Publications (EIA)

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

2012-01-01T23:59:59.000Z

95

Households and Pension  

Science Journals Connector (OSTI)

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

Mitsuhiko Iyoda

2010-01-01T23:59:59.000Z

96

HOUSEHOLD SOLAR POWER SYSTEM.  

E-Print Network [OSTI]

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

Jiang, He

2014-01-01T23:59:59.000Z

97

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

98

" 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

99

1997 Housing Characteristics Tables Housing Unit Tables  

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

Million U.S. Households; 45 pages, 128 kb) Million U.S. Households; 45 pages, 128 kb) Contents Pages HC1-1a. Housing Unit Characteristics by Climate Zone, Million U.S. Households, 1997 4 HC1-2a. Housing Unit Characteristics by Year of Construction, Million U.S. Households, 1997 4 HC1-3a. Housing Unit Characteristics by Household Income, Million U.S. Households, 1997 4 HC1-4a. Housing Unit Characteristics by Type of Housing Unit, Million U.S. Households, 1997 3 HC1-5a. Housing Unit Characteristics by Type of Owner-Occupied Housing Unit, Million U.S. Households, 1997 3 HC1-6a. Housing Unit Characteristics by Type of Rented Housing Unit, Million U.S. Households, 1997 3 HC1-7a. Housing Unit Characteristics by Four Most Populated States, Million U.S. Households, 1997 4

100

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

Note: This page contains sample records for the topic "household characteristics total" 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

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

102

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

103

" 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

104

" 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

105

" 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

106

" 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

107

" 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

108

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

Science Journals Connector (OSTI)

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

Barbara J. Redman

2008-01-01T23:59:59.000Z

109

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

110

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

111

,"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

112

,"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

113

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

114

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

115

Household portfolios in Japan  

Science Journals Connector (OSTI)

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

Tokuo Iwaisako

2009-01-01T23:59:59.000Z

116

Household Vehicles Energy Use Cover Page  

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

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

117

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

E-Print Network [OSTI]

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

Lundy, Jeffrey Dalton

2012-01-01T23:59:59.000Z

118

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

Science Journals Connector (OSTI)

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

Satomi Wakita; Vicki Schram Fitzsimmons…

2000-12-01T23:59:59.000Z

119

Housing characteristics 1993  

SciTech Connect (OSTI)

This report, Housing Characteristics 1993, presents statistics about the energy-related characteristics of US households. These data were collected in the 1993 Residential Energy Consumption Survey (RECS) -- the ninth in a series of nationwide energy consumption surveys conducted since 1978 by the Energy Information Administration of the US Department of Energy. Over 7 thousand households were surveyed, representing 97 million households nationwide. A second report, to be released in late 1995, will present statistics on residential energy consumption and expenditures.

NONE

1995-06-01T23:59:59.000Z

120

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

E-Print Network [OSTI]

be damaged when corrosive chemicals are put down the drain. Burning hazardous wastes simply distributes themHousehold Hazardous Waste Household hazardous waste is the discarded, unused, or leftover portion of household products containing toxic chemicals. These wastes CANNOT be disposed of in regular garbage. Any

de Lijser, Peter

Note: This page contains sample records for the topic "household characteristics total" 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

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

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

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

122

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

123

Household Vehicles Energy Consumption 1991  

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

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

124

Asset Pricing with Countercyclical Household Consumption Risk  

E-Print Network [OSTI]

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

Sadeh, Norman M.

125

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.

126

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

127

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

Gasoline and Diesel Fuel Update (EIA)

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

128

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

E-Print Network [OSTI]

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

Turrentine, Thomas; Kurani, Kenneth S.

2001-01-01T23:59:59.000Z

129

Table HC1.2.2 Living Space Characteristics by Average Floorspace  

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

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

130

Communications on energy Household energy conservation  

Science Journals Connector (OSTI)

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

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

1984-01-01T23:59:59.000Z

131

Table HC1-12a. Housing Unit Characteristics by West Census Region,  

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

2a. Housing Unit Characteristics by West Census Region, 2a. Housing Unit Characteristics by West Census Region, Million U.S. Households, 2001 Housing Unit Characteristics RSE Column Factor: Total U.S. West Census Region RSE Row Factors Total Census Division Mountain Pacific 0.5 1.0 1.7 1.1 Total .............................................................. 107.0 23.3 6.7 16.6 NE Census Region and Division Northeast ..................................................... 20.3 -- -- -- NF New England ............................................. 5.4 -- -- -- NF Middle Atlantic ........................................... 14.8 -- -- -- NF Midwest ....................................................... 24.5 -- -- -- NF East North Central ..................................... 17.1 -- -- -- NF West North Central ....................................

132

Table HC1-11a. Housing Unit Characteristics by South Census Region,  

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

1a. Housing Unit Characteristics by South Census Region, 1a. Housing Unit Characteristics by South Census Region, Million U.S. Households, 2001 Housing Unit Characteristics RSE Column Factor: Total U.S. South Census Region RSE Row Factors Total Census Division South Atlantic East South Central West South Central 0.5 0.9 1.2 1.4 1.4 Total .............................................................. 107.0 38.9 20.3 6.8 11.8 NE Census Region and Division Northeast ..................................................... 20.3 -- -- -- -- NF New England ............................................. 5.4 -- -- -- -- NF Middle Atlantic ........................................... 14.8 -- -- -- -- NF Midwest ....................................................... 24.5 -- -- -- -- NF East North Central .....................................

133

1997 Housing Characteristics Tables Housing Unit Tables  

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

Percent of U.S. Households; 45 pages, 121 kb) Percent of U.S. Households; 45 pages, 121 kb) Contents Pages HC1-1b. Housing Unit Characteristics by Climate Zone, Percent of U.S. Households, 1997 4 HC1-2b. Housing Unit Characteristics by Year of Construction, Percent of U.S. Households, 1997 4 HC1-3b. Housing Unit Characteristics by Household Income, Percent of U.S. Households, 1997 4 HC1-4b. Housing Unit Characteristics by Type of Housing Unit, Percent of U.S. Households, 1997 3 HC1-5b. Housing Unit Characteristics by Type of Owner-Occupied Housing Unit, Percent of U.S. Households, 1997 3 HC1-6b. Housing Unit Characteristics by Type of Rented Housing Unit, Percent of U.S. Households, 1997 3 HC1-7b. Housing Unit Characteristics by Four Most Populated States, Percent of U.S. Households, 1997 4

134

Total ionizing dose effect of ?-ray radiation on the switching characteristics and filament stability of HfOx resistive random access memory  

SciTech Connect (OSTI)

The total ionizing dose (TID) effect of gamma-ray (?-ray) irradiation on HfOx based resistive random access memory was investigated by electrical and material characterizations. The memory states can sustain TID level ?5.2 Mrad (HfO{sub 2}) without significant change in the functionality or the switching characteristics under pulse cycling. However, the stability of the filament is weakened after irradiation as memory states are more vulnerable to flipping under the electrical stress. X-ray photoelectron spectroscopy was performed to ascertain the physical mechanism of the stability degradation, which is attributed to the Hf-O bond breaking by the high-energy ?-ray exposure.

Fang, Runchen; Yu, Shimeng, E-mail: shimengy@asu.edu [School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, Arizona 85281 (United States); School of Electrical, Computer, and Energy Engineering, Arizona State University, Tempe, Arizona 85287 (United States); Gonzalez Velo, Yago; Chen, Wenhao; Holbert, Keith E.; Kozicki, Michael N.; Barnaby, Hugh [School of Electrical, Computer, and Energy Engineering, Arizona State University, Tempe, Arizona 85287 (United States)

2014-05-05T23:59:59.000Z

135

Delivering Energy Efficiency to Middle Income Single Family Households  

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

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

136

Physical activity of adults in households with and without children  

E-Print Network [OSTI]

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

Candelaria, Jeanette Irene

2010-01-01T23:59:59.000Z

137

,"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

138

,"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"

139

,"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

140

,"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

Note: This page contains sample records for the topic "household characteristics total" 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

,"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

142

,"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

143

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

SciTech Connect (OSTI)

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

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

1986-05-01T23:59:59.000Z

144

Immigrant characteristics and Hispanic-Anglo housing inequality  

Science Journals Connector (OSTI)

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

Lauren J. Krivo

1995-11-01T23:59:59.000Z

145

Household Vehicles Energy Consumption 1991  

Gasoline and Diesel Fuel Update (EIA)

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

146

The World Distribution of Household Wealth  

E-Print Network [OSTI]

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

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

2007-01-01T23:59:59.000Z

147

Standby electricity consumption and saving potentials of Turkish households  

Science Journals Connector (OSTI)

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

Mustafa Cagri Sahin; Merih Aydinalp Koksal

2014-01-01T23:59:59.000Z

148

" 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

149

Trip rate comparison of workplace and household surveys  

E-Print Network [OSTI]

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

Endres, Stephen Michael

2012-06-07T23:59:59.000Z

150

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

Science Journals Connector (OSTI)

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

Amit K. Bhandari; Chinmoy Jana

2010-01-01T23:59:59.000Z

151

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

Science Journals Connector (OSTI)

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

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

2006-07-19T23:59:59.000Z

152

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

153

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

154

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.

155

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

Science Journals Connector (OSTI)

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

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

2010-01-01T23:59:59.000Z

156

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

Open Energy Info (EERE)

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

157

Transferring 2001 National Household Travel Survey  

SciTech Connect (OSTI)

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

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

2007-05-01T23:59:59.000Z

158

Household Vehicles Energy Consumption 1991  

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

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

159

More efficient household electricity use  

SciTech Connect (OSTI)

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

Schipper, L.; Hawk, D.V.

1989-12-01T23:59:59.000Z

160

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

Note: This page contains sample records for the topic "household characteristics total" 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

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

162

ASSESSMENT OF HOUSEHOLD CARBON FOOTPRINT REDUCTION POTENTIALS  

E-Print Network [OSTI]

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

Masanet, Eric

2010-01-01T23:59:59.000Z

163

Household energy consumption and expenditures 1993  

SciTech Connect (OSTI)

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

NONE

1995-10-05T23:59:59.000Z

164

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

165

Nevada: Kingston Creek Hydro Project Powers 100 Households  

Broader source: Energy.gov [DOE]

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

166

S:\\VM3\\RX97\\TBL_LIST.WPD  

Gasoline and Diesel Fuel Update (EIA)

b. Household Characteristics by Four Most Populated States, Percent of U.S. Households, 1997 Household Characteristics RSE Column Factor: Total Four Most Populated States RSE Row...

167

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

E-Print Network [OSTI]

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

168

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

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

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

169

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

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

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

170

Table HC1-9a. Housing Unit Characteristics by Northeast Census Region,  

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

9a. Housing Unit Characteristics by Northeast Census Region, 9a. Housing Unit Characteristics by Northeast Census Region, Million U.S. Households, 2001 Housing Unit Characteristics RSE Column Factor: Total U.S. Northeast Census Region RSE Row Factors Total Census Division Middle Atlantic New England 0.5 1.0 1.2 1.6 Total .............................................................. 107.0 20.3 14.8 5.4 NE Census Region and Division Northeast ..................................................... 20.3 20.3 14.8 5.4 NF New England ............................................. 5.4 5.4 Q 5.4 NF Middle Atlantic ........................................... 14.8 14.8 14.8 Q NF Midwest ....................................................... 24.5 -- -- -- NF East North Central ..................................... 17.1 -- -- -- NF

171

Table HC1-10a. Housing Unit Characteristics by Midwest Census Region,  

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

0a. Housing Unit Characteristics by Midwest Census Region, 0a. Housing Unit Characteristics by Midwest Census Region, Million U.S. Households, 2001 Housing Unit Characteristics RSE Column Factor: Total U.S. Midwest Census Region RSE Row Factors Total Census Division East North Central West North Central 0.5 1.0 1.2 1.8 Total .............................................................. 107.0 24.5 17.1 7.4 NE Census Region and Division Northeast ..................................................... 20.3 -- -- -- NF New England ............................................. 5.4 -- -- -- NF Middle Atlantic ........................................... 14.8 -- -- -- NF Midwest ....................................................... 24.5 24.5 17.1 7.4 NF East North Central ..................................... 17.1 17.1

172

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

SciTech Connect (OSTI)

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

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

1994-09-01T23:59:59.000Z

173

"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

174

"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

175

Survey of Household Energy Use (SHEU)  

E-Print Network [OSTI]

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

176

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

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

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

177

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

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

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

178

Opportunities to reduce greenhouse gas emissions from households in Nigeria  

Science Journals Connector (OSTI)

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

O. Adeoti; S. O. Osho

2012-02-01T23:59:59.000Z

179

Household Wealth in a Cross-Country Perspective  

Science Journals Connector (OSTI)

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

Laura Bartiloro; Massimo Coletta…

2012-01-01T23:59:59.000Z

180

ANALYSIS OF CEE HOUSEHOLD SURVEY NATIONAL AWARENESS OF ENERGY STAR  

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

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

Note: This page contains sample records for the topic "household characteristics total" 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

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

182

Home Prices and Household Callan Windsor, Jarkko Jskel and  

E-Print Network [OSTI]

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

183

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

Science Journals Connector (OSTI)

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

Graham Kalton; Jennifer Kali; Richard Sigman

2014-09-01T23:59:59.000Z

184

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

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

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

185

TOTAL Full-TOTAL Full-  

E-Print Network [OSTI]

Conducting - Orchestral 6 . . 6 5 1 . 6 5 . . 5 Conducting - Wind Ensemble 3 . . 3 2 . . 2 . 1 . 1 Early- X TOTAL Full- Part- X TOTAL Alternative Energy 6 . . 6 11 . . 11 13 2 . 15 Biomedical Engineering 52 English 71 . 4 75 70 . 4 74 72 . 3 75 Geosciences 9 . 1 10 15 . . 15 19 . . 19 History 37 1 2 40 28 3 3 34

Portman, Douglas

186

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

Science Journals Connector (OSTI)

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

Erling Holden

2004-01-01T23:59:59.000Z

187

Household transitions to energy efficient lighting  

Science Journals Connector (OSTI)

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

Bradford Mills; Joachim Schleich

2014-01-01T23:59:59.000Z

188

Total Imports  

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

Data Series: Imports - Total Imports - Crude Oil Imports - Crude Oil, Commercial Imports - by SPR Imports - into SPR by Others Imports - Total Products Imports - Total Motor Gasoline Imports - Finished Motor Gasoline Imports - Reformulated Gasoline Imports - Reformulated Gasoline Blended w/ Fuel Ethanol Imports - Other Reformulated Gasoline Imports - Conventional Gasoline Imports - Conv. Gasoline Blended w/ Fuel Ethanol Imports - Conv. Gasoline Blended w/ Fuel Ethanol, Ed55 & Ed55 Imports - Other Conventional Gasoline Imports - Motor Gasoline Blend. Components Imports - Motor Gasoline Blend. Components, RBOB Imports - Motor Gasoline Blend. Components, RBOB w/ Ether Imports - Motor Gasoline Blend. Components, RBOB w/ Alcohol Imports - Motor Gasoline Blend. Components, CBOB Imports - Motor Gasoline Blend. Components, GTAB Imports - Motor Gasoline Blend. Components, Other Imports - Fuel Ethanol Imports - Kerosene-Type Jet Fuel Imports - Distillate Fuel Oil Imports - Distillate F.O., 15 ppm Sulfur and Under Imports - Distillate F.O., > 15 ppm to 500 ppm Sulfur Imports - Distillate F.O., > 500 ppm to 2000 ppm Sulfur Imports - Distillate F.O., > 2000 ppm Sulfur Imports - Residual Fuel Oil Imports - Propane/Propylene Imports - Other Other Oils Imports - Kerosene Imports - NGPLs/LRGs (Excluding Propane/Propylene) Exports - Total Crude Oil and Products Exports - Crude Oil Exports - Products Exports - Finished Motor Gasoline Exports - Kerosene-Type Jet Fuel Exports - Distillate Fuel Oil Exports - Residual Fuel Oil Exports - Propane/Propylene Exports - Other Oils Net Imports - Total Crude Oil and Products Net Imports - Crude Oil Net Imports - Petroleum Products Period: Weekly 4-Week Avg.

189

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

E-Print Network [OSTI]

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

Diallo, Ibrahima

2013-05-31T23:59:59.000Z

190

Total lightning characteristics of ordinary convection  

E-Print Network [OSTI]

processes involved in the electrical development of thunderstorms. Nine of the thunderstorm cases examined occurred within range of Vaisala Inc.'s Dallas-Fort Worth (DFW) Lightning Detection and Ranging (LDAR) network and the other thirteen cases occurred...

Motley, Shane Michael

2009-06-02T23:59:59.000Z

191

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

Science Journals Connector (OSTI)

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

Jaap Ham; Cees Midden; Femke Beute

2009-04-01T23:59:59.000Z

192

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

SciTech Connect (OSTI)

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

193

Delivering Energy Efficiency to Middle Income Single Family Households  

E-Print Network [OSTI]

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

Zimring, Mark

2012-01-01T23:59:59.000Z

194

Barriers to household investment in residential energy conservation: preliminary assessment  

SciTech Connect (OSTI)

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

Hoffman, W.L.

1982-12-01T23:59:59.000Z

195

Confronting earthquake risk in Japan—are private households underinsured?  

Science Journals Connector (OSTI)

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

Franz Waldenberger

2013-03-01T23:59:59.000Z

196

Salmon consumption at the household level in Japan.  

E-Print Network [OSTI]

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

Kikuchi, Akihiro

1987-01-01T23:59:59.000Z

197

Consumer perspectives on household hazardous waste management in Japan  

Science Journals Connector (OSTI)

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

Misuzu Asari; Shin-ichi Sakai

2011-02-01T23:59:59.000Z

198

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

199

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

Science Journals Connector (OSTI)

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

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

2006-01-01T23:59:59.000Z

200

Intra-Household Inequality in Transitional Russia Ekaterina Kalugina  

E-Print Network [OSTI]

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

Paris-Sud XI, Université de

Note: This page contains sample records for the topic "household characteristics total" 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

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

E-Print Network [OSTI]

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

Boyer, Edmond

202

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

Science Journals Connector (OSTI)

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

George Papachristos

2015-01-01T23:59:59.000Z

203

Rural household energy consumption and its implications for eco-environments in NW China: A case study  

Science Journals Connector (OSTI)

Abstract Rural household energy consumption plays an essential role in the daily life of farmers, especially in developing regions. In this paper, we present a study of household energy consumption in terms of energy sources and energy end uses, and analysis of technical and economic issues associated with the use of biomass and renewable energy and the replacement of fossil fuels. Results show that energy from biomass represents the largest share of total energy supply, and that 41.15% of total energy is consumed for home heating and cooking. The average cost of household energy is 1259 RMB ($US193.6) and this expense is no longer subsidized by the government. It takes less than one year to make a solar stove profitable and less than two years to pay back the household cost of biogas digesters. An 8 m3 digester can produce as much energy as 500–550 kg of standard coal or 940 kg of firewood, while a solar stove can generate 1.76 × 103 MJ heat each year. Moreover, it is estimated that in rural China the annual reduction of CO2 and SO2 emissions in 2020, due to the replacement of fossil fuel by biomass, will be 68.86 × 106 and 54.37 × 104 tons, respectively. Overall, the investigations and analyses have revealed that the structure of rural household energy consumption is undergoing a transformation from traditional low-efficiency biomass domination to integrated consumption of traditional and renewable energies. Renewable energy will significantly contribute to the sustainable development of rural households.

Hewen Niu; Yuanqing He; Umberto Desideri; Peidong Zhang; Hongyi Qin; Shijin Wang

2014-01-01T23:59:59.000Z

204

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

Science Journals Connector (OSTI)

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

Mark Ellis; Richard Wright

2005-01-01T23:59:59.000Z

205

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

Science Journals Connector (OSTI)

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

Richard Valliant; Frost Hubbard; Sunghee Lee; Chiungwen Chang

2014-06-01T23:59:59.000Z

206

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

E-Print Network [OSTI]

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

Liu, Jenny Hsing-I

2010-01-01T23:59:59.000Z

207

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

Science Journals Connector (OSTI)

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

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

2009-01-01T23:59:59.000Z

208

Chapter 2. Vehicle Characteristics  

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

2. Vehicle Characteristics 2. Vehicle Characteristics Chapter 2. Vehicle Characteristics U.S. households used a fleet of nearly 157 million vehicles in 1994. Despite remarkable growth in the number of minivans and sport-utility vehicles, passenger cars continued to predominate in the residential vehicle fleet. This chapter looks at changes in the composition of the residential fleet in 1994 compared with earlier years and reviews the effect of technological changes on fuel efficiency (how efficiently a vehicle engine processes motor fuel) and fuel economy (how far a vehicle travels on a given amount of fuel). Using data unique to the Residential Transportation Energy Consumption Survey, it also explores the relationship between residential vehicle use and family income.

209

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

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

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

210

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

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

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

211

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

E-Print Network [OSTI]

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

Lin, Jiang

2006-01-01T23:59:59.000Z

212

Household Vehicles Energy Consumption 1994 - Appendix C  

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

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

213

Projecting household energy consumption within a conditional demand framework  

SciTech Connect (OSTI)

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

Teotia, A.; Poyer, D.

1991-12-31T23:59:59.000Z

214

Projecting household energy consumption within a conditional demand framework  

SciTech Connect (OSTI)

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

Teotia, A.; Poyer, D.

1991-01-01T23:59:59.000Z

215

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

SciTech Connect (OSTI)

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

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

2011-03-15T23:59:59.000Z

216

Geographic Characteristics State land area (sq. mi): 53,927 % of U.S.: 1.52  

E-Print Network [OSTI]

.8% 7.3% 2.5% 2000 Race and Hispanic/Latino Ethnicity: Florida and Average of Selected Fishing Asian Native Hawaiian and other Pacific Islander Some other race Two or more races % Hispanic or Latino Compared to State Total Fishing Communities Total Population Median Household Income % Family Households

217

Geographic Characteristics State land area (sq. mi): 57,906 % of U.S.: 1.64  

E-Print Network [OSTI]

.5% 4.5% 1.8% 2000 Race and Hispanic/Latino Ethnicity: Georgia and Average of Selected Fishing Asian Native Hawaiian and other Pacific Islander Some other race Two or more races % Hispanic or Latino Compared to State Total Fishing Communities Total Population Median Household Income % Family Households

218

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.

219

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

220

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

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

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

Note: This page contains sample records for the topic "household characteristics total" 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

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

Broader source: Energy.gov [DOE]

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

222

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

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

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

223

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

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

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

224

Householder Symposium on Numerical Linear Algebra June 1721, 2002  

E-Print Network [OSTI]

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

Higham, Nicholas J.

225

The impact of retirement on household consumption in Japan  

Science Journals Connector (OSTI)

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

Melvin Stephens Jr.; Takashi Unayama

2012-01-01T23:59:59.000Z

226

Household energy consumption and its demand elasticity in Thailand  

Science Journals Connector (OSTI)

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

Montchai Pinitjitsamut

2012-01-01T23:59:59.000Z

227

Table 4  

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

7. Light Usage by Household Size, Million U.S. Households, 1993 Household Size Housing Unit and Household Characteristics Total 1 Person 2 Persons 3 Persons 4 Persons 5 Persons 6...

228

Barge Truck Total  

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

Barge Truck Total delivered cost per short ton Shipments with transportation rates over total shipments Total delivered cost per short ton Shipments with transportation rates over...

229

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

Science Journals Connector (OSTI)

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

Akira Hayami; Aoi Okada

2005-01-01T23:59:59.000Z

230

Energy Consumption of Refrigerators in Ghana - Outcomes of Household  

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

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

231

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

232

Water Related Energy Use in Households and Cities - an Australian  

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

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

233

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

234

An exploratory study of Spanish households' WEEE disposal behaviour  

Science Journals Connector (OSTI)

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

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

2011-01-01T23:59:59.000Z

235

Energy demand of German households and saving potential  

Science Journals Connector (OSTI)

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

Anke Eber; Dominik Most; Otto Rentz; Thomas Lutzkendorf

2008-01-01T23:59:59.000Z

236

Residential Energy Consumption Survey Results: Total Energy Consumption,  

Open Energy Info (EERE)

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

237

" 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

238

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

E-Print Network [OSTI]

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

Handy, Susan L; Tal, Gil

2005-01-01T23:59:59.000Z

239

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

Gasoline and Diesel Fuel Update (EIA)

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

240

THE DESIRE TO ACQUIRE: FORECASTING THE EVOLUTION OF HOUSEHOLD  

E-Print Network [OSTI]

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

Note: This page contains sample records for the topic "household characteristics total" 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

Greenhouse gas emissions from home composting of organic household waste  

SciTech Connect (OSTI)

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

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

2010-12-15T23:59:59.000Z

242

Household Segmentation in Food Insecurity and Soil Improving Practices in Ghana  

E-Print Network [OSTI]

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

Nata, Jifar T

2013-08-09T23:59:59.000Z

243

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

E-Print Network [OSTI]

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

Forrest, Timothy Lee

2007-04-25T23:59:59.000Z

244

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

Broader source: Energy.gov [DOE]

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

245

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

Broader source: Energy.gov [DOE]

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

246

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

Broader source: Energy.gov [DOE]

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

247

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

Science Journals Connector (OSTI)

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

Jessie X. Fan; Virginia Solis Zuiker

1998-06-01T23:59:59.000Z

248

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

Science Journals Connector (OSTI)

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

David Maddison; Katrin Rehdanz; Daiju Narita

2013-01-01T23:59:59.000Z

249

"Characteristic(a)","Total(b)","Electricity(c)","Fuel Oil","Fuel Oil(d)","Natural Gas(e)","NGL(f)","Coal","Breeze","Other(g)","Produced Onsite(h)"  

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

1.3 Relative Standard Errors for Table 1.3;" 1.3 Relative Standard Errors for Table 1.3;" " Unit: Percents." " "," "," "," "," "," "," "," "," "," " " "," ",," "," ",," "," ",," ","Shipments" "Economic",,"Net","Residual","Distillate",,"LPG and",,"Coke and"," ","of Energy Sources" "Characteristic(a)","Total(b)","Electricity(c)","Fuel Oil","Fuel Oil(d)","Natural Gas(e)","NGL(f)","Coal","Breeze","Other(g)","Produced Onsite(h)"

250

WEEE and portable batteries in residual household waste: Quantification and characterisation of misplaced waste  

SciTech Connect (OSTI)

Highlights: • We analyse 26.1 Mg of residual waste from 3129 Danish households. • We quantify and characterise misplaced WEEE and portable batteries. • We compare misplaced WEEE and batteries to collection through dedicated schemes. • Characterisation showed that primarily small WEEE and light sources are misplaced. • Significant amounts of misplaced batteries were discarded as built-in WEEE. - Abstract: A total of 26.1 Mg of residual waste from 3129 households in 12 Danish municipalities was analysed and revealed that 89.6 kg of Waste Electrical and Electronic Equipment (WEEE), 11 kg of batteries, 2.2 kg of toners and 16 kg of cables had been wrongfully discarded. This corresponds to a Danish household discarding 29 g of WEEE (7 items per year), 4 g of batteries (9 batteries per year), 1 g of toners and 7 g of unidentifiable cables on average per week, constituting 0.34% (w/w), 0.04% (w/w), 0.01% (w/w) and 0.09% (w/w), respectively, of residual waste. The study also found that misplaced WEEE and batteries in the residual waste constituted 16% and 39%, respectively, of what is being collected properly through the dedicated special waste collection schemes. This shows that a large amount of batteries are being discarded with the residual waste, whereas WEEE seems to be collected relatively successfully through the dedicated special waste collection schemes. Characterisation of the misplaced batteries showed that 20% (w/w) of the discarded batteries were discarded as part of WEEE (built-in). Primarily alkaline batteries, carbon zinc batteries and alkaline button cell batteries were found to be discarded with the residual household waste. Characterisation of WEEE showed that primarily small WEEE (WEEE directive categories 2, 5a, 6, 7 and 9) and light sources (WEEE directive category 5b) were misplaced. Electric tooth brushes, watches, clocks, headphones, flashlights, bicycle lights, and cables were items most frequently found. It is recommended that these findings are taken into account when designing new or improving existing special waste collection schemes. Improving the collection of WEEE is also recommended as one way to also improve the collection of batteries due to the large fraction of batteries found as built-in. The findings in this study were comparable to other western European studies, suggesting that the recommendations made in this study could apply to other western European countries as well.

Bigum, Marianne, E-mail: mkkb@env.dtu.dk [Technical University of Denmark, Department of Environmental Engineering, Miljøvej 113, 2500 Kgs. Lyngby (Denmark); Petersen, Claus, E-mail: claus_petersen@econet.dk [Econet A/S, Strandboulevarden 122, 5, 2100 København Ø (Denmark); Christensen, Thomas H., E-mail: thho@env.dtu.dk [Technical University of Denmark, Department of Environmental Engineering, Miljøvej 113, 2500 Kgs. Lyngby (Denmark); Scheutz, Charlotte, E-mail: chas@env.dtu.dk [Technical University of Denmark, Department of Environmental Engineering, Miljøvej 113, 2500 Kgs. Lyngby (Denmark)

2013-11-15T23:59:59.000Z

251

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

252

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

253

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

254

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

E-Print Network [OSTI]

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

Leistikow, Bruce N.

255

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

Science Journals Connector (OSTI)

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

Jane Golley; Xin Meng

2012-01-01T23:59:59.000Z

256

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

257

Table HC1-1a. Housing Unit Characteristics by Climate Zone,  

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

a. Housing Unit Characteristics by Climate Zone, a. Housing Unit Characteristics by Climate Zone, Million U.S. Households, 2001 Housing Unit Characteristics RSE Column Factor: Total Climate Zone 1 RSE Row Factors Fewer than 2,000 CDD and -- 2,000 CDD or More and Fewer than 4,000 HDD More than 7,000 HDD 5,500 to 7,000 HDD 4,000 to 5,499 HDD Fewer than 4,000 HDD 0.4 1.8 1.0 1.1 1.2 1.1 Total ............................................... 107.0 9.2 28.6 24.0 21.0 24.1 8.0 Census Region and Division Northeast ...................................... 20.3 1.9 10.0 8.4 Q Q 6.8 New England .............................. 5.4 1.4 4.0 Q Q Q 18.4 Middle Atlantic ............................ 14.8 0.5 6.0 8.4 Q Q 4.6 Midwest ......................................... 24.5 5.4 14.8 4.3 Q Q 19.0 East North Central ...................... 17.1

258

Table HC1-2a. Housing Unit Characteristics by Year of Construction,  

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

2a. Housing Unit Characteristics by Year of Construction, 2a. Housing Unit Characteristics by Year of Construction, Million U.S. Households, 2001 Housing Unit Characteristics RSE Column Factor: Total Year of Construction RSE Row Factors 1990 to 2001 1 1980 to 1989 1970 to 1979 1960 to 1969 1950 to 1959 1949 or Before 0.5 1.6 1.2 1.0 1.1 1.1 0.8 Total ............................................... 107.0 15.5 18.2 18.8 13.8 14.2 26.6 4.3 Census Region and Division Northeast ...................................... 20.3 1.5 2.4 2.1 2.8 3.0 8.5 8.8 New England .............................. 5.4 0.4 0.7 0.4 0.8 0.9 2.3 11.3 Middle Atlantic ............................ 14.8 1.1 1.7 1.7 2.0 2.2 6.2 11.2 Midwest ......................................... 24.5 2.8 3.7 3.6 2.9 3.5 8.1 10.2 East North Central ...................... 17.1 2.0 2.5 2.5 2.0 2.6 5.5 11.9

259

Table HC1-8a. Housing Unit Characteristics by Urban/Rural Location,  

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

8a. Housing Unit Characteristics by Urban/Rural Location, 8a. Housing Unit Characteristics by Urban/Rural Location, Million U.S. Households, 2001 Housing Unit Characteristics RSE Column Factor: Total Urban/Rural Location 1 RSE Row Factors City Town Suburbs Rural 0.5 0.8 1.3 1.3 1.4 Total .............................................................. 107.0 49.9 18.0 21.2 17.9 4.2 Census Region and Division Northeast ..................................................... 20.3 7.7 4.5 4.7 3.4 7.4 New England ............................................. 5.4 2.1 1.6 0.7 1.1 13.4 Middle Atlantic ........................................... 14.8 5.6 2.9 4.0 2.3 8.5 Midwest ....................................................... 24.5 11.1 4.9 4.8 3.7 10.1 East North Central ..................................... 17.1 8.3 3.0 3.4 2.5

260

Long-term behaviour of baled household waste  

Science Journals Connector (OSTI)

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

Fabian Robles-Mart??nez; Rémy Gourdon

2000-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "household characteristics total" 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

Variations of Total Domination  

Science Journals Connector (OSTI)

The study of locating–dominating sets in graphs was pioneered by Slater [186, 187...], and this concept was later extended to total domination in graphs. A locating–total dominating set, abbreviated LTD-set, in G

Michael A. Henning; Anders Yeo

2013-01-01T23:59:59.000Z

262

Interracial Marriage in Brazil: a discussion about local marriage market, parents' characteristics, and household chores  

E-Print Network [OSTI]

Identity: Comparing the United States and Brazil. ” Pp.Politics in Contemporary Brazil, edited by M Hanchard and NUnmixing for Race Making in Brazil. ” American Journal of

Tomas, Maria Carolina

2012-01-01T23:59:59.000Z

263

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

E-Print Network [OSTI]

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

Greenblatt, Jeffery

2013-01-01T23:59:59.000Z

264

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

E-Print Network [OSTI]

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

Greenblatt, Jeffery

2013-01-01T23:59:59.000Z

265

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

E-Print Network [OSTI]

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

Greenblatt, Jeffery

2013-01-01T23:59:59.000Z

266

Total Crude by Pipeline  

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

Product: Total Crude by All Transport Methods Domestic Crude by All Transport Methods Foreign Crude by All Transport Methods Total Crude by Pipeline Domestic Crude by Pipeline Foreign Crude by Pipeline Total Crude by Tanker Domestic Crude by Tanker Foreign Crude by Tanker Total Crude by Barge Domestic Crude by Barge Foreign Crude by Barge Total Crude by Tank Cars (Rail) Domestic Crude by Tank Cars (Rail) Foreign Crude by Tank Cars (Rail) Total Crude by Trucks Domestic Crude by Trucks Foreign Crude by Trucks Period: Product: Total Crude by All Transport Methods Domestic Crude by All Transport Methods Foreign Crude by All Transport Methods Total Crude by Pipeline Domestic Crude by Pipeline Foreign Crude by Pipeline Total Crude by Tanker Domestic Crude by Tanker Foreign Crude by Tanker Total Crude by Barge Domestic Crude by Barge Foreign Crude by Barge Total Crude by Tank Cars (Rail) Domestic Crude by Tank Cars (Rail) Foreign Crude by Tank Cars (Rail) Total Crude by Trucks Domestic Crude by Trucks Foreign Crude by Trucks Period: Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: Product Area 2007 2008 2009 2010 2011 2012 View

267

Hybrid application of biogas and solar resources to fulfill household energy needs: A potentially viable option in rural areas of developing countries  

Science Journals Connector (OSTI)

Abstract The absence of clean cooking facilities and electricity means billions of rural people are deprived of much needed socioeconomic development. Livestock residues (dung) and solar radiation are two renewable energy resources that are abundantly available in rural areas of developing countries. Although it is not feasible for these two resources separately to meet both thermal (cooking) and electricity demands, hybrid applications have not been given due attention. To facilitate integrating these two resources in rural energy planning, and to promote their dissemination through hybrid applications, it is necessary to evaluate their economic merits, and assess their ability to deal with the demands. In this paper, we examine the techno-economic performance of hybrid applications of these two resources by applying a simulation technique using the HOMER tool, and by giving derived cost-saving equations. We also quantify the monetary savings from replacing traditional fuels, and perform a sensitivity analysis on a number of variables (e.g. dung cost, fuelwood cost) to see how they affect the performance of different energy supply alternatives. Furthermore, we examine the practical applicability of the biogas system in the households through a structured survey of 72 ongoing household biogas plants. This study finds that households that have between three and six cattle can potentially meet their cooking and electricity loads through a hybrid implementation of biogas and solar PV (Photovoltaic) system. By replacing conventional fuels households can achieve savings that are more than the total annualized costs incurred for installing new services.

Md. Mizanur Rahman; Mohammad Mahmodul Hasan; Jukka V. Paatero; Risto Lahdelma

2014-01-01T23:59:59.000Z

268

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

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

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

269

Indoor Secondary Pollutants from Household Product Emissions in the  

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

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

270

Greenhouse Gas Implications of Household Energy Technology in Kenya  

Science Journals Connector (OSTI)

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

Rob Bailis; Majid Ezzati; Daniel M. Kammen

2003-04-01T23:59:59.000Z

271

Enhanced naphthenic refrigeration oils for household refrigerator systems  

SciTech Connect (OSTI)

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

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

1997-12-31T23:59:59.000Z

272

Total Space Heat-  

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

Buildings Energy Consumption Survey: Energy End-Use Consumption Tables Total Space Heat- ing Cool- ing Venti- lation Water Heat- ing Light- ing Cook- ing Refrig- eration...

273

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

E-Print Network [OSTI]

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

Raphael, S; Berube, A; Deakin, Elizabeth

2006-01-01T23:59:59.000Z

274

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

275

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

Science Journals Connector (OSTI)

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

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

2008-01-01T23:59:59.000Z

276

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

SciTech Connect (OSTI)

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

Poyer, D.A.

1992-01-01T23:59:59.000Z

277

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

SciTech Connect (OSTI)

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

Poyer, D.A.

1992-06-01T23:59:59.000Z

278

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

SciTech Connect (OSTI)

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

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

1999-07-01T23:59:59.000Z

279

Environmental attitudes and household consumption: an ambiguous relationship  

Science Journals Connector (OSTI)

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

Erling Holden; Kristin Linnerud

2010-01-01T23:59:59.000Z

280

Household demand and willingness to pay for hybrid vehicles  

Science Journals Connector (OSTI)

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

Yizao Liu

2014-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "household characteristics total" 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

Evolution of the household vehicle fleet: Anticipating fleet composition, PHEV adoption and GHG emissions in Austin, Texas  

Science Journals Connector (OSTI)

In today’s world of volatile fuel prices and climate concerns, there is little study on the relationship between vehicle ownership patterns and attitudes toward vehicle cost (including fuel prices and feebates) and vehicle technologies. This work provides new data on ownership decisions and owner preferences under various scenarios, coupled with calibrated models to microsimulate Austin’s personal-fleet evolution. Opinion survey results suggest that most Austinites (63%, population-corrected share) support a feebate policy to favor more fuel efficient vehicles. Top purchase criteria are price, type/class, and fuel economy. Most (56%) respondents also indicated that they would consider purchasing a Plug-in Hybrid Electric Vehicle (PHEV) if it were to cost $6000 more than its conventional, gasoline-powered counterpart. And many respond strongly to signals on the external (health and climate) costs of a vehicle’s emissions, more strongly than they respond to information on fuel cost savings. Twenty five-year simulations of Austin’s household vehicle fleet suggest that, under all scenarios modeled, Austin’s vehicle usage levels (measured in total vehicle miles traveled or VMT) are predicted to increase overall, along with average vehicle ownership levels (both per household and per capita). Under a feebate, HEVs, \\{PHEVs\\} and Smart Cars are estimated to represent 25% of the fleet’s VMT by simulation year 25; this scenario is predicted to raise total regional VMT slightly (just 2.32%, by simulation year 25), relative to the trend scenario, while reducing CO2 emissions only slightly (by 5.62%, relative to trend). Doubling the trend-case gas price to $5/gallon is simulated to reduce the year-25 vehicle use levels by 24% and CO2 emissions by 30% (relative to trend). Two- and three-vehicle households are simulated to be the highest adopters of \\{HEVs\\} and \\{PHEVs\\} across all scenarios. The combined share of vans, pickup trucks, sport utility vehicles (SUVs), and cross-over utility vehicles (CUVs) is lowest under the feebate scenario, at 35% (versus 47% in Austin’s current household fleet). Feebate-policy receipts are forecasted to exceed rebates in each simulation year. In the longer term, gas price dynamics, tax incentives, feebates and purchase prices along with new technologies, government-industry partnerships, and more accurate information on range and recharging times (which increase customer confidence in EV technologies) should have added effects on energy dependence and greenhouse gas emissions.

Sashank Musti; Kara M. Kockelman

2011-01-01T23:59:59.000Z

282

"Characteristic(a)","Total","Electricity(b)","Fuel Oil","Fuel...  

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

mines or wells." "During manufacturing processes, it is possible that the thermal energy content of" "an energy input is not completely consumed for the production of...

283

Table HC1-5a. Housing Unit Characteristics by Type of Owner-Occupied Housing Unit,  

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

5a. Housing Unit Characteristics by Type of Owner-Occupied Housing Unit, 5a. Housing Unit Characteristics by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 Housing Unit Characteristics RSE Column Factor: Total Owner- Occupied Units Type of Owner-Occupied Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Homes Two to Four Units Five or More Units 0.4 0.4 1.8 2.1 1.4 Total ............................................... 72.7 63.2 2.1 1.8 5.7 6.7 Census Region and Division Northeast ...................................... 13.0 10.8 1.1 0.5 0.6 11.4 New England .............................. 3.5 3.1 0.2 Q 0.1 16.9 Middle Atlantic ............................ 9.5 7.7 0.9 0.4 0.4 13.4 Midwest ......................................... 17.5 16.0 0.3 Q 1.0 10.3 East North Central ......................

284

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

E-Print Network [OSTI]

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

Sisk, Cheree L.

2010-10-12T23:59:59.000Z

285

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

E-Print Network [OSTI]

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

286

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

E-Print Network [OSTI]

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

Sekhon, Jasjeet S.

287

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

Science Journals Connector (OSTI)

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

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

2011-01-01T23:59:59.000Z

288

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

Science Journals Connector (OSTI)

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

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

2008-02-21T23:59:59.000Z

289

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

E-Print Network [OSTI]

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

Minnesota, University of

290

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

Science Journals Connector (OSTI)

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

Erika D. Schreder; Mark J. La Guardia

2014-09-17T23:59:59.000Z

291

Passive sampling methods to determine household and personal care product use  

E-Print Network [OSTI]

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

Leistikow, Bruce N.

292

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

293

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

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

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

294

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

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

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

295

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

Science Journals Connector (OSTI)

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

Hidetoshi Nakagami

1996-01-01T23:59:59.000Z

296

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

Science Journals Connector (OSTI)

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

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

2014-01-01T23:59:59.000Z

297

Table A39. Total Expenditures for Purchased Electricity and Steam  

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

9. Total Expenditures for Purchased Electricity and Steam" 9. Total Expenditures for Purchased Electricity and Steam" " by Type of Supplier, Census Region, Census Division, and" " Economic Characteristics of the Establishment, 1994" " (Estimates in Million Dollars)" ," Electricity",," Steam" ,,,,,"RSE" ,"Utility","Nonutility","Utility","Nonutility","Row" "Economic Characteristics(a)","Supplier(b)","Supplier(c)","Supplier(b)","Supplier(c)","Factors" ,"Total United States" "RSE Column Factors:",0.3,2,1.6,1.2

298

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

E-Print Network [OSTI]

This research, aimed at advancing the theory of environmental hazard adjustment processes by contrasting households from three cities in a high seismic hazard area with households from three other cities in a moderate seismic hazard area...

Arlikatti, Sudha S

2006-10-30T23:59:59.000Z

299

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

E-Print Network [OSTI]

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

Liskiewicz, Maciej

300

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

E-Print Network [OSTI]

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

Liskiewicz, Maciej

Note: This page contains sample records for the topic "household characteristics total" 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

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

E-Print Network [OSTI]

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

Liskiewicz, Maciej

302

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

Science Journals Connector (OSTI)

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

Michio Naoi; Miki Seko; Kazuto Sumita

2010-05-01T23:59:59.000Z

303

21 briefing pages total  

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

briefing pages total p. 1 briefing pages total p. 1 Reservist Differential Briefing U.S. Office of Personnel Management December 11, 2009 p. 2 Agenda - Introduction of Speakers - Background - References/Tools - Overview of Reservist Differential Authority - Qualifying Active Duty Service and Military Orders - Understanding Military Leave and Earnings Statements p. 3 Background 5 U.S.C. 5538 (Section 751 of the Omnibus Appropriations Act, 2009, March 11, 2009) (Public Law 111-8) Law requires OPM to consult with DOD Law effective first day of first pay period on or after March 11, 2009 (March 15 for most executive branch employees) Number of affected employees unclear p. 4 Next Steps

304

NON-CLOSED CURVES IN Rn WITH FINITE TOTAL FIRST  

E-Print Network [OSTI]

], and Kondo and Tanaka [14] have examined the global properties of the total curvature of a curveNON-CLOSED CURVES IN Rn WITH FINITE TOTAL FIRST CURVATURE ARISING FROM THE SOLUTIONS OF AN ODE P finite total first curvature. If all the roots of the associated characteristic polynomial are simple, we

Gilkey, Peter B

305

Barge Truck Total  

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

Barge Barge Truck Total delivered cost per short ton Shipments with transportation rates over total shipments Total delivered cost per short ton Shipments with transportation rates over total shipments Year (nominal) (real) (real) (percent) (nominal) (real) (real) (percent) 2008 $6.26 $5.77 $36.50 15.8% 42.3% $6.12 $5.64 $36.36 15.5% 22.2% 2009 $6.23 $5.67 $52.71 10.8% 94.8% $4.90 $4.46 $33.18 13.5% 25.1% 2010 $6.41 $5.77 $50.83 11.4% 96.8% $6.20 $5.59 $36.26 15.4% 38.9% Annual Percent Change First to Last Year 1.2% 0.0% 18.0% - - 0.7% -0.4% -0.1% - - Latest 2 Years 2.9% 1.7% -3.6% - - 26.6% 25.2% 9.3% - - - = No data reported or value not applicable STB Data Source: The Surface Transportation Board's 900-Byte Carload Waybill Sample EIA Data Source: Form EIA-923 Power Plant Operations Report

306

Summary Max Total Units  

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

Max Total Units Max Total Units *If All Splits, No Rack Units **If Only FW, AC Splits 1000 52 28 28 2000 87 59 35 3000 61 33 15 4000 61 33 15 Totals 261 153 93 ***Costs $1,957,500.00 $1,147,500.00 $697,500.00 Notes: added several refrigerants removed bins from analysis removed R-22 from list 1000lb, no Glycol, CO2 or ammonia Seawater R-404A only * includes seawater units ** no seawater units included *** Costs = (total units) X (estimate of $7500 per unit) 1000lb, air cooled split systems, fresh water Refrig Voltage Cond Unit IF-CU Combos 2 4 5 28 References Refrig Voltage C-U type Compressor HP R-404A 208/1/60 Hermetic SA 2.5 R-507 230/1/60 Hermetic MA 2.5 208/3/60 SemiHerm SA 1.5 230/3/60 SemiHerm MA 1.5 SemiHerm HA 1.5 1000lb, remote rack systems, fresh water Refrig/system Voltage Combos 12 2 24 References Refrig/system Voltage IF only

307

Total Precipitable Water  

SciTech Connect (OSTI)

The simulation was performed on 64K cores of Intrepid, running at 0.25 simulated-years-per-day and taking 25 million core-hours. This is the first simulation using both the CAM5 physics and the highly scalable spectral element dynamical core. The animation of Total Precipitable Water clearly shows hurricanes developing in the Atlantic and Pacific.

None

2012-01-01T23:59:59.000Z

308

Total Sustainability Humber College  

E-Print Network [OSTI]

1 Total Sustainability Management Humber College November, 2012 SUSTAINABILITY SYMPOSIUM Green An Impending Global Disaster #12;3 Sustainability is NOT Climate Remediation #12;Our Premises "We cannot, you cannot improve it" (Lord Kelvin) "First rule of sustainability is to align with natural forces

Thompson, Michael

309

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

SciTech Connect (OSTI)

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

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

1999-07-16T23:59:59.000Z

310

Influence of assumptions about household waste composition in waste management LCAs  

SciTech Connect (OSTI)

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

311

Total isomerization gains flexibility  

SciTech Connect (OSTI)

Isomerization extends refinery flexibility to meet changing markets. TIP (Total Isomerization Process) allows conversion of paraffin fractions in the gasoline boiling region including straight run naptha, light reformate, aromatic unit raffinate, and hydrocrackate. The hysomer isomerization is compared to catalytic reforming. Isomerization routes are graphed. Cost estimates and suggestions on the use of other feedstocks are given. TIP can maximize gas production, reduce crude runs, and complement cat reforming. In four examples, TIP reduces reformer severity and increases reformer yield.

Symoniak, M.F.; Holcombe, T.C.

1983-05-01T23:59:59.000Z

312

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

SciTech Connect (OSTI)

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

Not Available

1997-01-01T23:59:59.000Z

313

1999 Commercial Buildings Characteristics  

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

Data Reports > 2003 Building Characteristics Overview Data Reports > 2003 Building Characteristics Overview 1999 Commercial Buildings Energy Consumption Survey—Commercial Buildings Characteristics Released: May 2002 Topics: Energy Sources and End Uses | End-Use Equipment | Conservation Features and Practices Additional Information on: Survey methods, data limitations, and other information supporting the data The 1999 Commercial Buildings Energy Consumption Survey (CBECS) was the seventh in the series begun in 1979. The 1999 CBECS estimated that 4.7 million commercial buildings (± 0.4 million buildings, at the 95% confidence level) were present in the United States in that year. Those buildings comprised a total of 67.3 (± 4.6) billion square feet of floorspace. Additional information on 1979 to 1999 trends

314

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)

315

Analysis of household refrigerators for different testing standards  

SciTech Connect (OSTI)

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

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

1995-08-01T23:59:59.000Z

316

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

Science Journals Connector (OSTI)

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

Awrajaw Dessie; Esayas Alemayehu…

2014-01-01T23:59:59.000Z

317

Metering Campaign on All Cooking End-Uses in 100 Households  

Science Journals Connector (OSTI)

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

Olivier Sidler

2001-01-01T23:59:59.000Z

318

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

319

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

Science Journals Connector (OSTI)

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

Vincenzo Atella; Agar Brugiavini; Hao Chen; Noemi Pace

2014-01-01T23:59:59.000Z

320

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

Science Journals Connector (OSTI)

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

Xiaojun Zhang; Likoebe M. Maruping

2008-09-01T23:59:59.000Z

Note: This page contains sample records for the topic "household characteristics total" 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

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

322

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

Broader source: Energy.gov [DOE]

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

323

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

E-Print Network [OSTI]

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

Magana Lemus, David

2013-09-20T23:59:59.000Z

324

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

Science Journals Connector (OSTI)

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

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

2006-04-15T23:59:59.000Z

325

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

Science Journals Connector (OSTI)

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

Marta Tienda; Jennifer Glass

1985-08-01T23:59:59.000Z

326

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

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

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

327

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

E-Print Network [OSTI]

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

Sheng, Hongyan

1999-01-01T23:59:59.000Z

328

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

Science Journals Connector (OSTI)

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

Yoko Mimura

2014-02-01T23:59:59.000Z

329

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

Science Journals Connector (OSTI)

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

Zahra A. Barkhordar; Yadollah Saboohi

2014-10-01T23:59:59.000Z

330

Total Sales of Kerosene  

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

End Use: Total Residential Commercial Industrial Farm All Other Period: End Use: Total Residential Commercial Industrial Farm All Other Period: Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: End Use Area 2007 2008 2009 2010 2011 2012 View History U.S. 492,702 218,736 269,010 305,508 187,656 81,102 1984-2012 East Coast (PADD 1) 353,765 159,323 198,762 237,397 142,189 63,075 1984-2012 New England (PADD 1A) 94,635 42,570 56,661 53,363 38,448 15,983 1984-2012 Connecticut 13,006 6,710 8,800 7,437 7,087 2,143 1984-2012 Maine 46,431 19,923 25,158 24,281 17,396 7,394 1984-2012 Massachusetts 7,913 3,510 5,332 6,300 2,866 1,291 1984-2012 New Hampshire 14,454 6,675 8,353 7,435 5,472 1,977 1984-2012

331

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

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

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

332

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

SciTech Connect (OSTI)

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

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

2006-11-15T23:59:59.000Z

333

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

E-Print Network [OSTI]

that households? experience and government income support programs influence homeownership in Mexico. A secondary objective is to determine how socio-demographic variables influence homeownership in Mexico. Based on the Random Utility Model, logit models... of Direct Rural Support of Mexico (PROGRESA) and the Program of Direct Rural Support of Mexico (PROCAMPO), appear to be increasing iii homeownership. These social welfare programs provide cash transfers to households. For whatever reason, PROGRESA...

Lopez Cabrera, Jesus Antonio 1977-

2012-11-05T23:59:59.000Z

334

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

E-Print Network [OSTI]

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

Stockton, Matthew C.

2005-02-17T23:59:59.000Z

335

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

Science Journals Connector (OSTI)

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

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

2012-11-19T23:59:59.000Z

336

Determination of Total Solids in Biomass and Total Dissolved...  

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

Total Solids in Biomass and Total Dissolved Solids in Liquid Process Samples Laboratory Analytical Procedure (LAP) Issue Date: 3312008 A. Sluiter, B. Hames, D. Hyman, C. Payne,...

337

Total Marketed Production ..............  

Gasoline and Diesel Fuel Update (EIA)

billion cubic feet per day) billion cubic feet per day) Total Marketed Production .............. 68.95 69.77 70.45 71.64 71.91 71.70 71.46 71.57 72.61 72.68 72.41 72.62 70.21 71.66 72.58 Alaska ......................................... 1.04 0.91 0.79 0.96 1.00 0.85 0.77 0.93 0.97 0.83 0.75 0.91 0.93 0.88 0.87 Federal GOM (a) ......................... 3.93 3.64 3.44 3.82 3.83 3.77 3.73 3.50 3.71 3.67 3.63 3.46 3.71 3.70 3.62 Lower 48 States (excl GOM) ...... 63.97 65.21 66.21 66.86 67.08 67.08 66.96 67.14 67.92 68.18 68.02 68.24 65.58 67.07 68.09 Total Dry Gas Production .............. 65.46 66.21 66.69 67.79 68.03 67.83 67.61 67.71 68.69 68.76 68.50 68.70 66.55 67.79 68.66 Gross Imports ................................ 8.48 7.60 7.80 7.95 8.27 7.59 7.96 7.91 7.89 7.17 7.61 7.73 7.96 7.93 7.60 Pipeline ........................................

338

Total Space Heat-  

Gasoline and Diesel Fuel Update (EIA)

Released: September, 2008 Released: September, 2008 Total Space Heat- ing Cool- ing Venti- lation Water Heat- ing Light- ing Cook- ing Refrig- eration Office Equip- ment Com- puters Other All Buildings* ........................... 3,037 115 397 384 52 1,143 22 354 64 148 357 Building Floorspace (Square Feet) 1,001 to 5,000 ........................... 386 19 43 18 11 93 7 137 8 12 38 5,001 to 10,000 .......................... 262 12 35 17 5 83 4 56 6 9 35 10,001 to 25,000 ........................ 407 20 46 44 8 151 3 53 9 19 54 25,001 to 50,000 ........................ 350 15 55 50 9 121 2 34 7 16 42 50,001 to 100,000 ...................... 405 16 57 65 7 158 2 29 6 18 45 100,001 to 200,000 .................... 483 16 62 80 5 195 1 24 Q 31 56 200,001 to 500,000 .................... 361 8 51 54 5 162 1 9 8 19 43 Over 500,000 ............................. 383 8 47 56 3 181 2 12 8 23 43 Principal Building Activity

339

Comparative evaluation of crop water use efficiency, economic analysis and net household profit simulation in arid Northwest China  

Science Journals Connector (OSTI)

Abstract Decreasing water availability for agricultural production has prompted researchers to focus on comparing and evaluating water use efficiency (WUE) of different crops in various water management strategies. A field survey was conducted to investigate the amount of irrigation water, inputs and yields of eight crops (spring wheat, maize, onion, cotton, hot pepper, sunflower, melons and fennel) grown under furrow irrigation systems in an arid region, Minqin county, Northwestern China (NWC). Previous publications reporting crop WUE were identified and major statistics of evapotranspiration (ET), yield (Y) and WUE were calculated for each crop. By comparing with literature reporting, the mean WUE of onion (8.71 kg m?3), cotton (0.56 kg m?3), sunflower seed (0.78 kg m?3) and fennel (0.51 kg m?3) grown in NWC were at the same high levels; while WUE of wheat (0.87 kg m?3) and maize (1.17 kg m?3) were slightly lower and WUE of hot pepper (2.68 kg m?3) and melons (3.27 kg m?3) were extremely low. Great potential of saving water could be achieved to realize increased or ideal WUE values for crops in NWC. The total net profit per household of cotton (1606.62 $ hh?1) was significantly larger and of onion (?3132.30 $ hh?1) significantly lower than that of other crops. Cotton, sunflower seed, melons and hot pepper had significantly higher crop production values per unit water than other crops, 0.39 $ m?3, 0.36 $ m?3, 0.32 $ m?3 and 0.31 $ m?3, respectively. The net household profits were significantly higher when excluding onion production for its extremely low price in 2011. With simulation based on different combinations of onion production and increase of migrant workers, the average net household profit could be optimized to provide benefits to local farmers and policy makers regarding income increase and rural policy design.

Yubing Fan; Chenggang Wang; Zhibiao Nan

2014-01-01T23:59:59.000Z

340

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

Science Journals Connector (OSTI)

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

Yoshiaki Tsuzuki

2014-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "household characteristics total" 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

Determination of Total Petroleum Hydrocarbons (TPH) Using Total Carbon Analysis  

SciTech Connect (OSTI)

Several methods have been proposed to replace the Freon(TM)-extraction method to determine total petroleum hydrocarbon (TPH) content. For reasons of cost, sensitivity, precision, or simplicity, none of the replacement methods are feasible for analysis of radioactive samples at our facility. We have developed a method to measure total petroleum hydrocarbon content in aqueous sample matrixes using total organic carbon (total carbon) determination. The total carbon content (TC1) of the sample is measured using a total organic carbon analyzer. The sample is then contacted with a small volume of non-pokar solvent to extract the total petroleum hydrocarbons. The total carbon content of the resultant aqueous phase of the extracted sample (TC2) is measured. Total petroleum hydrocarbon content is calculated (TPH = TC1-TC2). The resultant data are consistent with results obtained using Freon(TM) extraction followed by infrared absorbance.

Ekechukwu, A.A.

2002-05-10T23:59:59.000Z

342

Total Space Heat-  

Gasoline and Diesel Fuel Update (EIA)

Revised: December, 2008 Revised: December, 2008 Total Space Heat- ing Cool- ing Venti- lation Water Heat- ing Light- ing Cook- ing Refrig- eration Office Equip- ment Com- puters Other All Buildings ............................. 91.0 33.0 7.2 6.1 7.0 18.7 2.7 5.3 1.0 2.2 7.9 Building Floorspace (Square Feet) 1,001 to 5,000 ........................... 99.0 30.7 6.7 2.7 7.1 13.9 7.1 19.9 1.1 1.7 8.2 5,001 to 10,000 .......................... 80.0 30.1 5.5 2.6 6.1 13.6 5.2 8.2 0.8 1.4 6.6 10,001 to 25,000 ........................ 71.0 28.2 4.5 4.1 4.1 14.5 2.3 4.5 0.8 1.6 6.5 25,001 to 50,000 ........................ 79.0 29.9 6.8 5.9 6.3 14.9 1.7 3.9 0.8 1.8 7.1 50,001 to 100,000 ...................... 88.7 31.6 7.6 7.6 6.5 19.6 1.7 3.4 0.7 2.0 8.1 100,001 to 200,000 .................... 104.2 39.1 8.2 8.9 7.9 22.9 1.1 2.9 Q 3.2 8.7 200,001 to 500,000 ....................

343

Total Space Heat-  

Gasoline and Diesel Fuel Update (EIA)

Revised: December, 2008 Revised: December, 2008 Total Space Heat- ing Cool- ing Venti- lation Water Heat- ing Light- ing Cook- ing Refrig- eration Office Equip- ment Com- puters Other All Buildings ............................. 91.0 33.0 7.2 6.1 7.0 18.7 2.7 5.3 1.0 2.2 7.9 Building Floorspace (Square Feet) 1,001 to 5,000 ........................... 99.0 30.7 6.7 2.7 7.1 13.9 7.1 19.9 1.1 1.7 8.2 5,001 to 10,000 .......................... 80.0 30.1 5.5 2.6 6.1 13.6 5.2 8.2 0.8 1.4 6.6 10,001 to 25,000 ........................ 71.0 28.2 4.5 4.1 4.1 14.5 2.3 4.5 0.8 1.6 6.5 25,001 to 50,000 ........................ 79.0 29.9 6.8 5.9 6.3 14.9 1.7 3.9 0.8 1.8 7.1 50,001 to 100,000 ...................... 88.7 31.6 7.6 7.6 6.5 19.6 1.7 3.4 0.7 2.0 8.1 100,001 to 200,000 .................... 104.2 39.1 8.2 8.9 7.9 22.9 1.1 2.9 Q 3.2 8.7 200,001 to 500,000 ....................

344

U.S. Total Exports  

Gasoline and Diesel Fuel Update (EIA)

Babb, MT Havre, MT Port of Morgan, MT Pittsburg, NH Grand Island, NY Massena, NY Niagara Falls, NY Waddington, NY Sumas, WA Sweetgrass, MT Total to Chile Sabine Pass, LA Total to China Kenai, AK Sabine Pass, LA Total to India Freeport, TX Sabine Pass, LA Total to Japan Cameron, LA Kenai, AK Sabine Pass, LA Total to Mexico Douglas, AZ Nogales, AZ Calexico, CA Ogilby Mesa, CA Otay Mesa, CA Alamo, TX Clint, TX Del Rio, TX Eagle Pass, TX El Paso, TX Hidalgo, TX McAllen, TX Penitas, TX Rio Bravo, TX Roma, TX Total to Portugal Sabine Pass, LA Total to Russia Total to South Korea Freeport, TX Sabine Pass, LA Total to Spain Cameron, LA Sabine Pass, LA Total to United Kingdom Sabine Pass, LA Period: Monthly Annual

345

"Table A28. Total Expenditures for Purchased Energy Sources by Census Region"  

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

Total Expenditures for Purchased Energy Sources by Census Region" Total Expenditures for Purchased Energy Sources by Census Region" " and Economic Characteristics of the Establishment, 1991" " (Estimates in Million Dollars)" " "," "," "," ",," "," "," "," "," ","RSE" " "," "," ","Residual","Distillate","Natural"," "," ","Coke"," ","Row" "Economic Characteristics(a)","Total","Electricity","Fuel Oil","Fuel Oil(b)","Gas(c)","LPG","Coal","and Breeze","Other(d)","Factors"

346

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

Science Journals Connector (OSTI)

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

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

2013-12-18T23:59:59.000Z

347

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

SciTech Connect (OSTI)

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

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

2005-05-31T23:59:59.000Z

348

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

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

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

349

Relation between total quanta and total energy for aquatic ...  

Science Journals Connector (OSTI)

Jan 22, 1974 ... havior of the ratio of total quanta to total energy (Q : W) within the spectral region of photosynthetic ..... For blue-green waters, where hRmax lies.

2000-01-02T23:59:59.000Z

350

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

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

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

351

Competition Helps Kids Learn About Energy and Save Their Households Some  

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

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

352

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

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

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

353

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

Science Journals Connector (OSTI)

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

Charles Yuji Horioka

2006-01-01T23:59:59.000Z

354

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

Science Journals Connector (OSTI)

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

Jia Yang; Mimi Tian; Tomio Miwa; Takayuki Morikawa

2014-01-01T23:59:59.000Z

355

Mujeres Hombres Total Hombres Total 16 5 21 0 10  

E-Print Network [OSTI]

Julio de 2011 Tipo de Discapacidad Sexo CENTRO 5-Distribución del estudiantado con discapacidad por centro, tipo de discapacidad, sexo y totales. #12;

Autonoma de Madrid, Universidad

356

Relation between total quanta and total energy for aquatic ...  

Science Journals Connector (OSTI)

Jan 22, 1974 ... ment of the total energy and vice versa. From a measurement of spectral irradi- ance ... unit energy (for the wavelength region specified).

2000-01-02T23:59:59.000Z

357

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

E-Print Network [OSTI]

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

Paris-Sud XI, Université de

358

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

Science Journals Connector (OSTI)

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

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

2014-11-12T23:59:59.000Z

359

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

SciTech Connect (OSTI)

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

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

1985-04-01T23:59:59.000Z

360

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

SciTech Connect (OSTI)

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

Poyer, D.A.

1991-09-01T23:59:59.000Z

Note: This page contains sample records for the topic "household characteristics total" 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

Exploring nonresponse bias in a health survey using neighborhood characteristics.  

E-Print Network [OSTI]

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

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

2009-01-01T23:59:59.000Z

362

Total.................................................................  

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

49.2 49.2 15.1 15.6 11.1 7.0 5.2 8.0 Have Cooling Equipment............................... 93.3 31.3 15.1 15.6 11.1 7.0 5.2 8.0 Use Cooling Equipment................................ 91.4 30.4 14.6 15.4 11.1 6.9 5.2 7.9 Have Equipment But Do Not Use it............... 1.9 1.0 0.5 Q Q Q Q Q Do Not Have Cooling Equipment................... 17.8 17.8 N N N N N N Air-Conditioning Equipment 1, 2 Central System............................................. 65.9 3.9 15.1 15.6 11.1 7.0 5.2 8.0 Without a Heat Pump................................ 53.5 3.5 12.9 12.7 8.6 5.5 4.2 6.2 With a Heat Pump..................................... 12.3 0.4 2.2 2.9 2.5 1.5 1.0 1.8 Window/Wall Units........................................ 28.9 27.5 0.5 Q 0.3 Q Q Q 1 Unit......................................................... 14.5 13.5 0.3 Q Q Q N Q 2 Units.......................................................

363

Total........................................................................  

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

7.1 7.1 7.0 8.0 12.1 Do Not Have Space Heating Equipment............... 1.2 Q Q Q 0.2 Have Main Space Heating Equipment.................. 109.8 7.1 6.8 7.9 11.9 Use Main Space Heating Equipment.................... 109.1 7.1 6.6 7.9 11.4 Have Equipment But Do Not Use It...................... 0.8 N Q N 0.5 Main Heating Fuel and Equipment Natural Gas.......................................................... 58.2 3.8 0.4 3.8 8.4 Central Warm-Air Furnace................................ 44.7 1.8 Q 3.1 6.0 For One Housing Unit................................... 42.9 1.5 Q 3.1 6.0 For Two Housing Units................................. 1.8 Q N Q Q Steam or Hot Water System............................. 8.2 1.9 Q Q 0.2 For One Housing Unit................................... 5.1 0.8 Q N Q For Two Housing Units.................................

364

Total........................................................................  

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

5.6 5.6 17.7 7.9 Do Not Have Space Heating Equipment............... 1.2 Q Q N Have Main Space Heating Equipment.................. 109.8 25.6 17.7 7.9 Use Main Space Heating Equipment.................... 109.1 25.6 17.7 7.9 Have Equipment But Do Not Use It...................... 0.8 N N N Main Heating Fuel and Equipment Natural Gas.......................................................... 58.2 18.4 13.1 5.3 Central Warm-Air Furnace................................ 44.7 16.2 11.6 4.7 For One Housing Unit................................... 42.9 15.5 11.0 4.5 For Two Housing Units................................. 1.8 0.7 0.6 Q Steam or Hot Water System............................. 8.2 1.6 1.2 0.4 For One Housing Unit................................... 5.1 1.1 0.9 Q For Two Housing Units.................................

365

Total...........................................................................  

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

4.2 4.2 7.6 16.6 Do Not Have Cooling Equipment............................. 17.8 10.3 3.1 7.3 Have Cooling Equipment.......................................... 93.3 13.9 4.5 9.4 Use Cooling Equipment........................................... 91.4 12.9 4.3 8.5 Have Equipment But Do Not Use it.......................... 1.9 1.0 Q 0.8 Air-Conditioning Equipment 1, 2 Central System........................................................ 65.9 10.5 3.9 6.5 Without a Heat Pump........................................... 53.5 8.7 3.2 5.5 With a Heat Pump............................................... 12.3 1.7 0.7 1.0 Window/Wall Units.................................................. 28.9 3.6 0.6 3.0 1 Unit................................................................... 14.5 2.9 0.5 2.4 2 Units.................................................................

366

Total....................................................................................  

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

Personal Computers Personal Computers Do Not Use a Personal Computer.................................. 35.5 14.2 7.2 2.8 4.2 Use a Personal Computer.............................................. 75.6 26.6 14.5 4.1 7.9 Most-Used Personal Computer Type of PC Desk-top Model......................................................... 58.6 20.5 11.0 3.4 6.1 Laptop Model............................................................. 16.9 6.1 3.5 0.7 1.9 Hours Turned on Per Week Less than 2 Hours..................................................... 13.6 5.0 2.6 1.0 1.3 2 to 15 Hours............................................................. 29.1 10.3 5.9 1.6 2.9 16 to 40 Hours........................................................... 13.5 4.1 2.3 0.6 1.2 41 to 167 Hours.........................................................

367

Total..............................................................  

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

,171 ,171 1,618 1,031 845 630 401 Census Region and Division Northeast................................................... 20.6 2,334 1,664 562 911 649 220 New England.......................................... 5.5 2,472 1,680 265 1,057 719 113 Middle Atlantic........................................ 15.1 2,284 1,658 670 864 627 254 Midwest...................................................... 25.6 2,421 1,927 1,360 981 781 551 East North Central.................................. 17.7 2,483 1,926 1,269 999 775 510 West North Central................................. 7.9 2,281 1,930 1,566 940 796 646 South.......................................................... 40.7 2,161 1,551 1,295 856 615 513 South Atlantic......................................... 21.7 2,243 1,607 1,359 896 642 543 East South Central.................................

368

Total.........................................................................................  

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

..... ..... 111.1 7.1 7.0 8.0 12.1 Personal Computers Do Not Use a Personal Computer...................................... 35.5 3.0 2.0 2.7 3.1 Use a Personal Computer.................................................. 75.6 4.2 5.0 5.3 9.0 Most-Used Personal Computer Type of PC Desk-top Model............................................................. 58.6 3.2 3.9 4.0 6.7 Laptop Model................................................................. 16.9 1.0 1.1 1.3 2.4 Hours Turned on Per Week Less than 2 Hours......................................................... 13.6 0.7 0.9 0.9 1.4 2 to 15 Hours................................................................. 29.1 1.7 2.1 1.9 3.4 16 to 40 Hours............................................................... 13.5 0.9 0.9 0.9 1.8 41 to 167 Hours.............................................................

369

Total.............................................................................  

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

Cooking Appliances Cooking Appliances Frequency of Hot Meals Cooked 3 or More Times A Day......................................... 8.2 2.6 0.7 1.9 2 Times A Day...................................................... 24.6 6.6 2.0 4.6 Once a Day........................................................... 42.3 8.8 2.9 5.8 A Few Times Each Week...................................... 27.2 4.7 1.5 3.1 About Once a Week.............................................. 3.9 0.7 Q 0.6 Less Than Once a Week....................................... 4.1 0.7 0.3 0.4 No Hot Meals Cooked........................................... 0.9 0.2 Q Q Conventional Oven Use an Oven......................................................... 109.6 23.7 7.5 16.2 More Than Once a Day..................................... 8.9 1.7 0.4 1.3 Once a Day.......................................................

370

Total..............................................................................  

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

0.7 0.7 21.7 6.9 12.1 Do Not Have Cooling Equipment................................ 17.8 1.4 0.8 0.2 0.3 Have Cooling Equipment............................................. 93.3 39.3 20.9 6.7 11.8 Use Cooling Equipment.............................................. 91.4 38.9 20.7 6.6 11.7 Have Equipment But Do Not Use it............................. 1.9 0.5 Q Q Q Air-Conditioning Equipment 1, 2 Central System........................................................... 65.9 32.1 17.6 5.2 9.3 Without a Heat Pump.............................................. 53.5 23.2 10.9 3.8 8.4 With a Heat Pump................................................... 12.3 9.0 6.7 1.4 0.9 Window/Wall Units..................................................... 28.9 8.0 3.4 1.7 2.9 1 Unit......................................................................

371

Total....................................................................................  

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

25.6 25.6 40.7 24.2 Personal Computers Do Not Use a Personal Computer.................................. 35.5 6.9 8.1 14.2 6.4 Use a Personal Computer.............................................. 75.6 13.7 17.5 26.6 17.8 Most-Used Personal Computer Type of PC Desk-top Model......................................................... 58.6 10.4 14.1 20.5 13.7 Laptop Model............................................................. 16.9 3.3 3.4 6.1 4.1 Hours Turned on Per Week Less than 2 Hours..................................................... 13.6 2.4 3.4 5.0 2.9 2 to 15 Hours............................................................. 29.1 5.2 7.0 10.3 6.6 16 to 40 Hours........................................................... 13.5 3.1 2.8 4.1 3.4 41 to 167 Hours.........................................................

372

Total....................................................................................  

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

4.2 4.2 7.6 16.6 Personal Computers Do Not Use a Personal Computer.................................. 35.5 6.4 2.2 4.2 Use a Personal Computer.............................................. 75.6 17.8 5.3 12.5 Most-Used Personal Computer Type of PC Desk-top Model......................................................... 58.6 13.7 4.2 9.5 Laptop Model............................................................. 16.9 4.1 1.1 3.0 Hours Turned on Per Week Less than 2 Hours..................................................... 13.6 2.9 0.9 2.0 2 to 15 Hours............................................................. 29.1 6.6 2.0 4.6 16 to 40 Hours........................................................... 13.5 3.4 0.9 2.5 41 to 167 Hours......................................................... 6.3

373

Total..................................................................  

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

33.0 33.0 8.0 3.4 5.9 14.4 1.2 Do Not Have Cooling Equipment..................... 17.8 6.5 1.6 0.9 1.3 2.4 0.2 Have Cooling Equipment................................. 93.3 26.5 6.5 2.5 4.6 12.0 1.0 Use Cooling Equipment.................................. 91.4 25.7 6.3 2.5 4.4 11.7 0.8 Have Equipment But Do Not Use it................. 1.9 0.8 Q Q 0.2 0.3 Q Type of Air-Conditioning Equipment 1, 2 Central System.............................................. 65.9 14.1 3.6 1.5 2.1 6.4 0.6 Without a Heat Pump.................................. 53.5 12.4 3.1 1.3 1.8 5.7 0.6 With a Heat Pump....................................... 12.3 1.7 0.6 Q 0.3 0.6 Q Window/Wall Units....................................... 28.9 12.4 2.9 1.0 2.5 5.6 0.4 1 Unit.......................................................... 14.5 7.3 1.2 0.5 1.4 3.9 0.2 2 Units.........................................................

374

Total....................................................................................  

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

Cooking Appliances Cooking Appliances Frequency of Hot Meals Cooked 3 or More Times A Day................................................. 8.2 3.7 1.6 1.4 1.5 2 Times A Day.............................................................. 24.6 10.8 4.1 4.3 5.5 Once a Day................................................................... 42.3 17.0 7.2 8.7 9.3 A Few Times Each Week............................................. 27.2 11.4 4.7 6.4 4.8 About Once a Week..................................................... 3.9 1.7 0.6 0.9 0.8 Less Than Once a Week.............................................. 4.1 2.2 0.6 0.8 0.5 No Hot Meals Cooked................................................... 0.9 0.4 Q Q Q Conventional Oven Use an Oven................................................................. 109.6 46.2 18.8

375

Total.............................................................................  

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

Do Not Have Cooling Equipment............................... Do Not Have Cooling Equipment............................... 17.8 2.1 1.8 0.3 Have Cooling Equipment............................................ 93.3 23.5 16.0 7.5 Use Cooling Equipment............................................. 91.4 23.4 15.9 7.5 Have Equipment But Do Not Use it............................ 1.9 Q Q Q Type of Air-Conditioning Equipment 1, 2 Central System........................................................ 65.9 17.3 11.3 6.0 Without a Heat Pump............................................. 53.5 16.2 10.6 5.6 With a Heat Pump................................................. 12.3 1.1 0.8 0.4 Window/Wall Units.................................................. 28.9 6.6 4.9 1.7 1 Unit..................................................................... 14.5 4.1 2.9 1.2 2 Units...................................................................

376

Total..............................................................................  

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

20.6 20.6 25.6 40.7 24.2 Do Not Have Cooling Equipment................................ 17.8 4.0 2.1 1.4 10.3 Have Cooling Equipment............................................. 93.3 16.5 23.5 39.3 13.9 Use Cooling Equipment.............................................. 91.4 16.3 23.4 38.9 12.9 Have Equipment But Do Not Use it............................. 1.9 0.3 Q 0.5 1.0 Air-Conditioning Equipment 1, 2 Central System........................................................... 65.9 6.0 17.3 32.1 10.5 Without a Heat Pump.............................................. 53.5 5.5 16.2 23.2 8.7 With a Heat Pump................................................... 12.3 0.5 1.1 9.0 1.7 Window/Wall Units..................................................... 28.9 10.7 6.6 8.0 3.6 1 Unit......................................................................

377

Total....................................................................................  

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

5.6 5.6 17.7 7.9 Personal Computers Do Not Use a Personal Computer.................................. 35.5 8.1 5.6 2.5 Use a Personal Computer.............................................. 75.6 17.5 12.1 5.4 Most-Used Personal Computer Type of PC Desk-top Model......................................................... 58.6 14.1 10.0 4.0 Laptop Model............................................................. 16.9 3.4 2.1 1.3 Hours Turned on Per Week Less than 2 Hours..................................................... 13.6 3.4 2.5 0.9 2 to 15 Hours............................................................. 29.1 7.0 4.8 2.3 16 to 40 Hours........................................................... 13.5 2.8 2.1 0.7 41 to 167 Hours......................................................... 6.3

378

Total...................................................................  

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

15.2 15.2 7.8 1.0 1.2 3.3 1.9 For Two Housing Units............................. 0.9 Q N Q 0.6 N Heat Pump.................................................. 9.2 7.4 0.3 Q 0.7 0.5 Portable Electric Heater............................... 1.6 0.8 Q Q Q 0.3 Other Equipment......................................... 1.9 0.7 Q Q 0.7 Q Fuel Oil........................................................... 7.7 5.5 0.4 0.8 0.9 0.2 Steam or Hot Water System........................ 4.7 2.9 Q 0.7 0.8 N For One Housing Unit.............................. 3.3 2.9 Q Q Q N For Two Housing Units............................. 1.4 Q Q 0.5 0.8 N Central Warm-Air Furnace........................... 2.8 2.4 Q Q Q 0.2 Other Equipment......................................... 0.3 0.2 Q N Q N Wood..............................................................

379

Total...............................................................  

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

Do Not Have Cooling Equipment................. 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 13.0 31.1 Use Cooling Equipment............................... 91.4 21.0 23.5 17.4 11.0 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 Air-Conditioning Equipment 1, 2 Central System............................................ 65.9 11.0 16.5 13.5 8.7 16.1 6.4 17.2 Without a Heat Pump.............................. 53.5 9.4 13.6 10.7 7.1 12.7 5.4 14.5 With a Heat Pump................................... 12.3 1.7 2.8 2.8 1.6 3.4 1.0 2.7 Window/Wall Units...................................... 28.9 10.5 8.1 4.5 2.7 3.1 6.7 14.1 1 Unit....................................................... 14.5 5.8 4.3 2.0 1.1 1.3 3.4 7.4 2 Units.....................................................

380

Total.............................................................................  

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

Cooking Appliances Cooking Appliances Frequency of Hot Meals Cooked 3 or More Times A Day......................................... 8.2 1.4 1.0 0.4 2 Times A Day...................................................... 24.6 5.8 3.5 2.3 Once a Day........................................................... 42.3 10.7 7.8 2.9 A Few Times Each Week...................................... 27.2 5.6 4.0 1.6 About Once a Week.............................................. 3.9 0.9 0.6 0.3 Less Than Once a Week....................................... 4.1 1.1 0.7 0.4 No Hot Meals Cooked........................................... 0.9 Q Q N Conventional Oven Use an Oven......................................................... 109.6 25.3 17.6 7.7 More Than Once a Day..................................... 8.9 1.3 0.8 0.5 Once a Day.......................................................

Note: This page contains sample records for the topic "household characteristics total" 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

Total...............................................................  

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

26.7 26.7 28.8 20.6 13.1 22.0 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 18.0 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 2.......................................................... 16.2 0.9 2.6 3.7 2.9 6.2 0.8 2.6 3 or More............................................. 9.0 0.4 1.2 1.3 1.2 5.0 0.3 1.1 Number of Laptop PCs 1.......................................................... 22.5 2.2 4.6 4.5 2.9 8.3 1.4 4.0 2.......................................................... 4.0 Q 0.4 0.6 0.4 2.4 Q 0.5 3 or More............................................. 0.7 Q Q Q Q 0.4 Q Q Type of Monitor Used on Most-Used PC Desk-top

382

Total...............................................................  

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

20.6 20.6 25.6 40.7 24.2 Personal Computers Do Not Use a Personal Computer ........... 35.5 6.9 8.1 14.2 6.4 Use a Personal Computer......................... 75.6 13.7 17.5 26.6 17.8 Number of Desktop PCs 1.......................................................... 50.3 9.3 11.9 18.2 11.0 2.......................................................... 16.2 2.9 3.5 5.5 4.4 3 or More............................................. 9.0 1.5 2.1 2.9 2.5 Number of Laptop PCs 1.......................................................... 22.5 4.7 4.6 7.7 5.4 2.......................................................... 4.0 0.6 0.9 1.5 1.1 3 or More............................................. 0.7 Q Q Q 0.3 Type of Monitor Used on Most-Used PC Desk-top CRT (Standard Monitor)................... 45.0 7.9 11.4 15.4 10.2 Flat-panel LCD.................................

383

Total................................................................  

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

111.1 26.7 28.8 20.6 13.1 22.0 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 13.0 21.8 16.3 37.9 Use Main Space Heating Equipment............ 109.1 25.9 28.1 20.3 12.9 21.8 16.0 37.3 Have Equipment But Do Not Use It.............. 0.8 0.3 0.3 Q Q N 0.4 0.6 Main Heating Fuel and Equipment Natural Gas.................................................. 58.2 12.2 14.4 11.3 7.1 13.2 7.6 18.3 Central Warm-Air Furnace........................ 44.7 7.5 10.8 9.3 5.6 11.4 4.6 12.0 For One Housing Unit........................... 42.9 6.9 10.3 9.1 5.4 11.3 4.1 11.0 For Two Housing Units......................... 1.8 0.6 0.6 Q Q Q 0.4 0.9 Steam or Hot Water System..................... 8.2 2.4 2.5 1.0 1.0 1.3 1.5 3.6 For One Housing Unit...........................

384

Total........................................................................  

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

25.6 25.6 40.7 24.2 Do Not Have Space Heating Equipment............... 1.2 Q Q Q 0.7 Have Main Space Heating Equipment.................. 109.8 20.5 25.6 40.3 23.4 Use Main Space Heating Equipment.................... 109.1 20.5 25.6 40.1 22.9 Have Equipment But Do Not Use It...................... 0.8 N N Q 0.6 Main Heating Fuel and Equipment Natural Gas.......................................................... 58.2 11.4 18.4 13.6 14.7 Central Warm-Air Furnace................................ 44.7 6.1 16.2 11.0 11.4 For One Housing Unit................................... 42.9 5.6 15.5 10.7 11.1 For Two Housing Units................................. 1.8 0.5 0.7 Q 0.3 Steam or Hot Water System............................. 8.2 4.9 1.6 1.0 0.6 For One Housing Unit................................... 5.1 3.2 1.1 0.4

385

Total...........................................................................  

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

0.6 0.6 15.1 5.5 Do Not Have Cooling Equipment............................. 17.8 4.0 2.4 1.7 Have Cooling Equipment.......................................... 93.3 16.5 12.8 3.8 Use Cooling Equipment........................................... 91.4 16.3 12.6 3.7 Have Equipment But Do Not Use it.......................... 1.9 0.3 Q Q Air-Conditioning Equipment 1, 2 Central System........................................................ 65.9 6.0 5.2 0.8 Without a Heat Pump........................................... 53.5 5.5 4.8 0.7 With a Heat Pump............................................... 12.3 0.5 0.4 Q Window/Wall Units.................................................. 28.9 10.7 7.6 3.1 1 Unit................................................................... 14.5 4.3 2.9 1.4 2 Units.................................................................

386

Total.......................................................................  

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

4.2 4.2 7.6 16.6 Personal Computers Do Not Use a Personal Computer ................... 35.5 6.4 2.2 4.2 Use a Personal Computer................................ 75.6 17.8 5.3 12.5 Number of Desktop PCs 1.................................................................. 50.3 11.0 3.4 7.6 2.................................................................. 16.2 4.4 1.3 3.1 3 or More..................................................... 9.0 2.5 0.7 1.8 Number of Laptop PCs 1.................................................................. 22.5 5.4 1.5 3.9 2.................................................................. 4.0 1.1 0.3 0.8 3 or More..................................................... 0.7 0.3 Q Q Type of Monitor Used on Most-Used PC Desk-top CRT (Standard Monitor)...........................

387

Total....................................................................................  

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

111.1 47.1 19.0 22.7 22.3 Personal Computers Do Not Use a Personal Computer.................................. 35.5 16.9 6.5 4.6 7.6 Use a Personal Computer.............................................. 75.6 30.3 12.5 18.1 14.7 Most-Used Personal Computer Type of PC Desk-top Model......................................................... 58.6 22.9 9.8 14.1 11.9 Laptop Model............................................................. 16.9 7.4 2.7 4.0 2.9 Hours Turned on Per Week Less than 2 Hours..................................................... 13.6 5.7 1.8 2.9 3.2 2 to 15 Hours............................................................. 29.1 11.9 5.1 6.5 5.7 16 to 40 Hours........................................................... 13.5 5.5 2.5 3.3 2.2 41 to 167 Hours.........................................................

388

Total........................................................................  

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

7.1 7.1 19.0 22.7 22.3 Do Not Have Space Heating Equipment............... 1.2 0.7 Q 0.2 Q Have Main Space Heating Equipment.................. 109.8 46.3 18.9 22.5 22.1 Use Main Space Heating Equipment.................... 109.1 45.6 18.8 22.5 22.1 Have Equipment But Do Not Use It...................... 0.8 0.7 Q N N Main Heating Fuel and Equipment Natural Gas.......................................................... 58.2 27.0 11.9 14.9 4.3 Central Warm-Air Furnace................................ 44.7 19.8 8.6 12.8 3.6 For One Housing Unit................................... 42.9 18.8 8.3 12.3 3.5 For Two Housing Units................................. 1.8 1.0 0.3 0.4 Q Steam or Hot Water System............................. 8.2 4.4 2.1 1.4 0.3 For One Housing Unit................................... 5.1 2.1 1.6 1.0

389

Total........................................................................  

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

15.1 15.1 5.5 Do Not Have Space Heating Equipment............... 1.2 Q Q Q Have Main Space Heating Equipment.................. 109.8 20.5 15.1 5.4 Use Main Space Heating Equipment.................... 109.1 20.5 15.1 5.4 Have Equipment But Do Not Use It...................... 0.8 N N N Main Heating Fuel and Equipment Natural Gas.......................................................... 58.2 11.4 9.1 2.3 Central Warm-Air Furnace................................ 44.7 6.1 5.3 0.8 For One Housing Unit................................... 42.9 5.6 4.9 0.7 For Two Housing Units................................. 1.8 0.5 0.4 Q Steam or Hot Water System............................. 8.2 4.9 3.6 1.3 For One Housing Unit................................... 5.1 3.2 2.2 1.0 For Two Housing Units.................................

390

Total..........................................................  

Gasoline and Diesel Fuel Update (EIA)

... 2.8 0.7 0.5 0.2 Million U.S. Housing Units Home Electronics Usage Indicators Table HC12.12 Home Electronics Usage Indicators by Midwest Census Region,...

391

Total..........................................................  

Gasoline and Diesel Fuel Update (EIA)

... 13.2 1.8 1.2 0.5 Table HC11.10 Home Appliances Usage Indicators by Northeast Census Region, 2005 Million U.S. Housing Units Home Appliances...

392

Total..........................................................  

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

... 2.8 1.1 0.7 Q 0.4 Million U.S. Housing Units Home Electronics Usage Indicators Table HC13.12 Home Electronics Usage Indicators by South Census Region,...

393

Total..........................................................  

Gasoline and Diesel Fuel Update (EIA)

... 13.2 3.1 1.0 2.2 Table HC14.10 Home Appliances Usage Indicators by West Census Region, 2005 Million U.S. Housing Units Home Appliances...

394

Total..........................................................  

Gasoline and Diesel Fuel Update (EIA)

States New York Florida Texas California Million U.S. Housing Units Home Electronics Usage Indicators Table HC15.12 Home Electronics Usage Indicators by Four Most Populated...

395

Total..........................................................  

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

... 13.2 3.4 2.0 1.4 Table HC12.10 Home Appliances Usage Indicators by Midwest Census Region, 2005 Million U.S. Housing Units Home Appliances...

396

Total..........................................................  

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

Census Region Northeast Midwest South West Million U.S. Housing Units Home Electronics Usage Indicators Table HC10.12 Home Electronics Usage Indicators by U.S. Census Region, 2005...

397

Total..........................................................  

Gasoline and Diesel Fuel Update (EIA)

(as Self-Reported) City Town Suburbs Rural Million U.S. Housing Units Home Electronics Usage Indicators Table HC8.12 Home Electronics Usage Indicators by UrbanRural Location,...

398

Total..........................................................  

Gasoline and Diesel Fuel Update (EIA)

... 13.2 4.4 2.5 3.0 3.4 Table HC8.10 Home Appliances Usage Indicators by UrbanRural Location, 2005 Million U.S. Housing Units UrbanRural...

399

Total..........................................................  

Gasoline and Diesel Fuel Update (EIA)

... 2.8 0.6 Q 0.5 Million U.S. Housing Units Home Electronics Usage Indicators Table HC14.12 Home Electronics Usage Indicators by West Census Region, 2005...

400

Total..........................................................  

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

... 13.2 4.9 2.3 1.1 1.5 Table HC13.10 Home Appliances Usage Indicators by South Census Region, 2005 Million U.S. Housing Units South Census Region...

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


401

Total..........................................................  

Gasoline and Diesel Fuel Update (EIA)

... 51.9 7.0 4.8 2.2 Not Asked (Mobile Homes or Apartment in Buildings with 5 or More Units)... 23.7...

402

Total..........................................................  

Gasoline and Diesel Fuel Update (EIA)

0.7 21.7 6.9 12.1 Do Not Have Space Heating Equipment... 1.2 Q Q N Q Have Main Space Heating Equipment... 109.8 40.3 21.4 6.9 12.0 Use Main Space Heating...

403

Total  

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

Normal ButaneButylene Other Liquids Oxygenates Fuel Ethanol MTBE Other Oxygenates Biomass-based Diesel Other Renewable Diesel Fuel Other Renewable Fuels Gasoline Blending...

404

Total  

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

Normal ButaneButylene Other Liquids Oxygenates Fuel Ethanol MTBE Other Oxygenates Biomass-based Diesel Fuel Other Renewable Diesel Fuel Other Renewable Fuels Gasoline Blending...

405

Total.............................................................................  

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

Cooking Appliances Cooking Appliances Frequency of Hot Meals Cooked 3 or More Times A Day......................................... 8.2 1.2 1.0 0.2 2 Times A Day...................................................... 24.6 4.0 2.7 1.2 Once a Day........................................................... 42.3 7.9 5.4 2.5 A Few Times Each Week...................................... 27.2 6.0 4.8 1.2 About Once a Week.............................................. 3.9 0.6 0.5 Q Less Than Once a Week....................................... 4.1 0.6 0.4 Q No Hot Meals Cooked........................................... 0.9 0.3 Q Q Conventional Oven Use an Oven......................................................... 109.6 20.3 14.9 5.4 More Than Once a Day..................................... 8.9 1.4 1.2 0.3 Once a Day.......................................................

406

Total...............................................................  

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

47.1 47.1 19.0 22.7 22.3 Personal Computers Do Not Use a Personal Computer ........... 35.5 16.9 6.5 4.6 7.6 Use a Personal Computer......................... 75.6 30.3 12.5 18.1 14.7 Number of Desktop PCs 1.......................................................... 50.3 21.1 8.3 10.7 10.1 2.......................................................... 16.2 6.2 2.8 4.1 3.0 3 or More............................................. 9.0 2.9 1.4 3.2 1.6 Number of Laptop PCs 1.......................................................... 22.5 9.1 3.6 6.0 3.8 2.......................................................... 4.0 1.5 0.6 1.3 0.7 3 or More............................................. 0.7 0.3 Q Q Q Type of Monitor Used on Most-Used PC Desk-top CRT (Standard Monitor)................... 45.0 17.7 7.5 10.2 9.6 Flat-panel LCD.................................

407

Total........................................................  

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

111.1 24.5 1,090 902 341 872 780 441 Census Region and Division Northeast............................................. 20.6 6.7 1,247 1,032 Q 811 788 147 New England.................................... 5.5 1.9 1,365 1,127 Q 814 748 107 Middle Atlantic.................................. 15.1 4.8 1,182 978 Q 810 800 159 Midwest................................................ 25.6 4.6 1,349 1,133 506 895 810 346 East North Central............................ 17.7 3.2 1,483 1,239 560 968 842 351 West North Central........................... 7.9 1.4 913 789 329 751 745 337 South................................................... 40.7 7.8 881 752 572 942 873 797 South Atlantic................................... 21.7 4.9 875 707 522 1,035 934 926 East South Central........................... 6.9 0.7 Q Q Q 852 826 432 West South Central..........................

408

Total...............................................................  

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

0.7 0.7 21.7 6.9 12.1 Personal Computers Do Not Use a Personal Computer ........... 35.5 14.2 7.2 2.8 4.2 Use a Personal Computer......................... 75.6 26.6 14.5 4.1 7.9 Number of Desktop PCs 1.......................................................... 50.3 18.2 10.0 2.9 5.3 2.......................................................... 16.2 5.5 3.0 0.7 1.8 3 or More............................................. 9.0 2.9 1.5 0.5 0.8 Number of Laptop PCs 1.......................................................... 22.5 7.7 4.3 1.1 2.4 2.......................................................... 4.0 1.5 0.9 Q 0.4 3 or More............................................. 0.7 Q Q Q Q Type of Monitor Used on Most-Used PC Desk-top CRT (Standard Monitor)................... 45.0 15.4 7.9 2.8 4.8 Flat-panel LCD.................................

409

Total.................................................................  

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

26.7 26.7 28.8 20.6 13.1 22.0 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 1.0 2.4 4.6 2 Times A Day........................................... 24.6 6.5 7.0 4.3 3.2 3.6 4.8 10.3 Once a Day................................................ 42.3 8.8 9.8 8.7 5.1 10.0 5.0 12.9 A Few Times Each Week........................... 27.2 5.6 7.2 4.7 3.3 6.3 3.2 7.5 About Once a Week................................... 3.9 1.1 1.1 0.6 0.5 0.6 0.4 1.4 Less Than Once a Week............................ 4.1 1.3 1.0 0.9 0.5 0.4 0.7 1.4 No Hot Meals Cooked................................ 0.9 0.5 Q Q Q Q 0.2 0.5 Conventional Oven Use an Oven.............................................. 109.6 26.1 28.5 20.2 12.9 21.8 16.3 37.8 More Than Once a Day..........................

410

Total..................................................................  

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

. . 111.1 14.7 7.4 12.5 12.5 18.9 18.6 17.3 9.2 Do Not Have Cooling Equipment..................... 17.8 3.9 1.8 2.2 2.1 3.1 2.6 1.7 0.4 Have Cooling Equipment................................. 93.3 10.8 5.6 10.3 10.4 15.8 16.0 15.6 8.8 Use Cooling Equipment.................................. 91.4 10.6 5.5 10.3 10.3 15.3 15.7 15.3 8.6 Have Equipment But Do Not Use it................. 1.9 Q Q Q Q 0.6 0.4 0.3 Q Type of Air-Conditioning Equipment 1, 2 Central System.............................................. 65.9 3.7 2.6 6.1 6.8 11.2 13.2 13.9 8.2 Without a Heat Pump.................................. 53.5 3.6 2.3 5.5 5.8 9.5 10.1 10.3 6.4 With a Heat Pump....................................... 12.3 Q 0.3 0.6 1.0 1.7 3.1 3.6 1.7 Window/Wall Units....................................... 28.9 7.3 3.2 4.5 3.7 4.8 3.0 1.9 0.7 1 Unit..........................................................

411

Total..............................................  

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

111.1 86.6 2,720 1,970 1,310 1,941 1,475 821 1,059 944 554 Census Region and Division Northeast.................................... 20.6 13.9 3,224 2,173 836 2,219 1,619 583 903 830 Q New England.......................... 5.5 3.6 3,365 2,154 313 2,634 1,826 Q 951 940 Q Middle Atlantic........................ 15.1 10.3 3,167 2,181 1,049 2,188 1,603 582 Q Q Q Midwest...................................... 25.6 21.0 2,823 2,239 1,624 2,356 1,669 1,336 1,081 961 778 East North Central.................. 17.7 14.5 2,864 2,217 1,490 2,514 1,715 1,408 907 839 553 West North Central................. 7.9 6.4 2,729 2,289 1,924 1,806 1,510 1,085 1,299 1,113 1,059 South.......................................... 40.7 33.0 2,707 1,849 1,563 1,605 1,350 954 1,064 970 685 South Atlantic......................... 21.7 16.8 2,945 1,996 1,695 1,573 1,359 909 1,044 955

412

Total.................................................................................  

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

... ... 111.1 20.6 15.1 5.5 Do Not Have Cooling Equipment................................. 17.8 4.0 2.4 1.7 Have Cooling Equipment............................................. 93.3 16.5 12.8 3.8 Use Cooling Equipment............................................... 91.4 16.3 12.6 3.7 Have Equipment But Do Not Use it............................. 1.9 0.3 Q Q Type of Air-Conditioning Equipment 1, 2 Central System.......................................................... 65.9 6.0 5.2 0.8 Without a Heat Pump.............................................. 53.5 5.5 4.8 0.7 With a Heat Pump................................................... 12.3 0.5 0.4 Q Window/Wall Units.................................................... 28.9 10.7 7.6 3.1 1 Unit.......................................................................

413

Total.............................................................................  

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

Do Not Have Cooling Equipment............................... Do Not Have Cooling Equipment............................... 17.8 8.5 2.7 2.6 4.0 Have Cooling Equipment............................................ 93.3 38.6 16.2 20.1 18.4 Use Cooling Equipment............................................. 91.4 37.8 15.9 19.8 18.0 Have Equipment But Do Not Use it............................ 1.9 0.9 0.3 0.3 0.4 Type of Air-Conditioning Equipment 1, 2 Central System........................................................ 65.9 25.8 10.9 16.6 12.5 Without a Heat Pump............................................. 53.5 21.2 9.7 13.7 8.9 With a Heat Pump................................................. 12.3 4.6 1.2 2.8 3.6 Window/Wall Units.................................................. 28.9 13.4 5.6 3.9 6.1 1 Unit.....................................................................

414

Total.............................................................................  

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

Do Not Have Cooling Equipment............................... Do Not Have Cooling Equipment............................... 17.8 10.3 3.1 7.3 Have Cooling Equipment............................................ 93.3 13.9 4.5 9.4 Use Cooling Equipment............................................. 91.4 12.9 4.3 8.5 Have Equipment But Do Not Use it............................ 1.9 1.0 Q 0.8 Type of Air-Conditioning Equipment 1, 2 Central System........................................................ 65.9 10.5 3.9 6.5 Without a Heat Pump............................................. 53.5 8.7 3.2 5.5 With a Heat Pump................................................. 12.3 1.7 0.7 1.0 Window/Wall Units.................................................. 28.9 3.6 0.6 3.0 1 Unit..................................................................... 14.5 2.9 0.5 2.4 2 Units...................................................................

415

Total..................................................................  

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

78.1 78.1 64.1 4.2 1.8 2.3 5.7 Do Not Have Cooling Equipment..................... 17.8 11.3 9.3 0.6 Q 0.4 0.9 Have Cooling Equipment................................. 93.3 66.8 54.7 3.6 1.7 1.9 4.8 Use Cooling Equipment.................................. 91.4 65.8 54.0 3.6 1.7 1.9 4.7 Have Equipment But Do Not Use it................. 1.9 1.1 0.8 Q N Q Q Type of Air-Conditioning Equipment 1, 2 Central System.............................................. 65.9 51.7 43.9 2.5 0.7 1.6 3.1 Without a Heat Pump.................................. 53.5 41.1 34.8 2.1 0.5 1.2 2.6 With a Heat Pump....................................... 12.3 10.6 9.1 0.4 Q 0.3 0.6 Window/Wall Units....................................... 28.9 16.5 12.0 1.3 1.0 0.4 1.7 1 Unit.......................................................... 14.5 7.2 5.4 0.5 0.2 Q 0.9 2 Units.........................................................

416

Total.............................................................................  

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

Do Not Have Cooling Equipment............................... Do Not Have Cooling Equipment............................... 17.8 1.4 0.8 0.2 0.3 Have Cooling Equipment............................................ 93.3 39.3 20.9 6.7 11.8 Use Cooling Equipment............................................. 91.4 38.9 20.7 6.6 11.7 Have Equipment But Do Not Use it............................ 1.9 0.5 Q Q Q Type of Air-Conditioning Equipment 1, 2 Central System........................................................ 65.9 32.1 17.6 5.2 9.3 Without a Heat Pump............................................. 53.5 23.2 10.9 3.8 8.4 With a Heat Pump................................................. 12.3 9.0 6.7 1.4 0.9 Window/Wall Units.................................................. 28.9 8.0 3.4 1.7 2.9 1 Unit.....................................................................

417

Total........................................................................  

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

4.2 4.2 7.6 16.6 Do Not Have Space Heating Equipment............... 1.2 0.7 Q 0.7 Have Main Space Heating Equipment.................. 109.8 23.4 7.5 16.0 Use Main Space Heating Equipment.................... 109.1 22.9 7.4 15.4 Have Equipment But Do Not Use It...................... 0.8 0.6 Q 0.5 Main Heating Fuel and Equipment Natural Gas.......................................................... 58.2 14.7 4.6 10.1 Central Warm-Air Furnace................................ 44.7 11.4 4.0 7.4 For One Housing Unit................................... 42.9 11.1 3.8 7.3 For Two Housing Units................................. 1.8 0.3 Q Q Steam or Hot Water System............................. 8.2 0.6 0.3 0.3 For One Housing Unit................................... 5.1 0.4 0.2 0.1 For Two Housing Units.................................

418

Total..............................................................  

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

Do Not Have Cooling Equipment................ 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 13.0 31.1 Use Cooling Equipment.............................. 91.4 21.0 23.5 17.4 11.0 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 Type of Air-Conditioning Equipment 1, 2 Central System.......................................... 65.9 11.0 16.5 13.5 8.7 16.1 6.4 17.2 Without a Heat Pump.............................. 53.5 9.4 13.6 10.7 7.1 12.7 5.4 14.5 With a Heat Pump................................... 12.3 1.7 2.8 2.8 1.6 3.4 1.0 2.7 Window/Wall Units................................... 28.9 10.5 8.1 4.5 2.7 3.1 6.7 14.1 1 Unit...................................................... 14.5 5.8 4.3 2.0 1.1 1.3 3.4 7.4 2 Units....................................................

419

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.

420

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

Science Journals Connector (OSTI)

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

Joakim Munkhammar; Jesper Rydén; Joakim Widén

2014-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "household characteristics total" 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

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

E-Print Network [OSTI]

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

Feigon, Brooke

422

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

Science Journals Connector (OSTI)

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

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

2000-02-01T23:59:59.000Z

423

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

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

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

424

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

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

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

425

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

E-Print Network [OSTI]

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

Birmingham, University of

426

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

Science Journals Connector (OSTI)

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

Edgar G. Hertwich; Charlotte Roux

2011-08-30T23:59:59.000Z

427

Using Circuit-Level Power Measurements in Household Energy Management Systems  

E-Print Network [OSTI]

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

Han, Qi "Chee"

428

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

E-Print Network [OSTI]

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

Kammen, Daniel M.

429

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

E-Print Network [OSTI]

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

Aickelin, Uwe

430

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

E-Print Network [OSTI]

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

Rothman, Daniel

431

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

Broader source: Energy.gov [DOE]

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

432

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

Science Journals Connector (OSTI)

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

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

2008-05-01T23:59:59.000Z

433

Idle Operating Total Stream Day  

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

3 3 Idle Operating Total Stream Day Barrels per Idle Operating Total Calendar Day Barrels per Atmospheric Crude Oil Distillation Capacity Idle Operating Total Operable Refineries Number of State and PAD District a b b 11 10 1 1,293,200 1,265,200 28,000 1,361,700 1,329,700 32,000 ............................................................................................................................................... PAD District I 1 1 0 182,200 182,200 0 190,200 190,200 0 ................................................................................................................................................................................................................................................................................................ Delaware......................................

434

" Million U.S. Housing Units"  

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

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

435

total energy | OpenEI  

Open Energy Info (EERE)

total energy total energy Dataset Summary Description This dataset comes from the Energy Information Administration (EIA), and is part of the 2011 Annual Energy Outlook Report (AEO2011). This dataset is table 1, and contains only the reference case. The dataset uses quadrillion BTUs, and quantifies the energy prices using U.S. dollars. The data is broken down into total production, imports, exports, consumption, and prices for energy types. Source EIA Date Released April 26th, 2011 (3 years ago) Date Updated Unknown Keywords 2011 AEO consumption EIA export import production reference case total energy Data application/vnd.ms-excel icon AEO2011: Total Energy Supply, Disposition, and Price Summary - Reference Case (xls, 112.8 KiB) Quality Metrics Level of Review Peer Reviewed

436

Total Sky Imager (TSI) Handbook  

SciTech Connect (OSTI)

The total sky imager (TSI) provides time series of hemispheric sky images during daylight hours and retrievals of fractional sky cover for periods when the solar elevation is greater than 10 degrees.

Morris, VR

2005-06-01T23:59:59.000Z

437

Microsoft Word - 20050821_Appendix_A.doc  

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

9. U.S. Average Vehicle-Miles Traveled by EIA Household Composition 9. U.S. Average Vehicle-Miles Traveled by EIA Household Composition 1 , 2001 (Thousand Miles per Household) ENERGY INFORMATION ADMINISTRATION / HOUSEHOLD VEHICLES ENERGY USE: LATEST A N D TRENDS 118 Households With Children Households Without Children Age of Oldest Child One Adult--Age of Householder Two or More Adults--Age of Householder 2001 Household Characteristics Total Under 7 Years 7 to 15 Years 16 or 17 Years Total Under 35 Years 35 to 59 Years 60 Years or Over Under 35 Years 35 to 59 Years 60 Years or Over Household Characteristics Total.............................. 29.0 27.0 28.3 34.1 19.6 14.5 13.8 8.1 28.1 27.9 18.6 Census Region and Division

438

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

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

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

439

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

E-Print Network [OSTI]

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

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

1997-08-29T23:59:59.000Z

440

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

Science Journals Connector (OSTI)

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

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

2015-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "household characteristics total" 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

Quantitative evaluation of effects of the soft interventions or cleaner production in households and the hard interventions: A Social Experiment Programme in a large river basin in Japan  

Science Journals Connector (OSTI)

Efforts have been made to reduce municipal wastewater pollutant discharge and improve river water quality in the Yamato-gawa River basin since 2005, as part of a Social Experiment Programme. The Programme was the first one in Japan to disseminate soft interventions in households, measurements to reduce pollutant discharge, in a large river basin with more than two million population. The soft interventions in households are similar to cleaner production in industrial sector because they are not the wastewater treatment and changing of lifestyles. This paper presents several methods for quantification of the pollutant discharge reduction. Two hypothetical soft intervention combinations were defined, the effects of 16 soft interventions were estimated using their proliferation rates, and estimated pollutant discharge reduction was compared with changes in river water quality during the Programme events. For the first method, environmental accounting housekeeping (EAH) books were applied to estimate a 38–53% reduction in biological oxygen demand (BOD), 26–40% reduction in total nitrogen (TN), and 21–32% reduction in total phosphorus (TP). These estimation results were comparable with the field survey results of approximately 100 person population, which were conducted in the late 1980s. Soft interventions were found to be several times more cost effective than hard interventions, such as development of municipal wastewater treatment and river water purification systems. The BOD discharge reduction effects of soft interventions initiated during Programme events increased from 0.3–2.3% in 2005–2007 to 2.4–4.7% in 2007–2009. The questionnaire surveys found that participants in the Programme events in average newly implemented three or four soft interventions in addition to those already implemented at normal times.

Yoshiaki Tsuzuki; Minoru Yoneda; Ryohei Tokunaga; Shinsuke Morisawa

2012-01-01T23:59:59.000Z

442

"Table A37. Total Expenditures for Purchased Energy Sources by Census Region,"  

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

7. Total Expenditures for Purchased Energy Sources by Census Region," 7. Total Expenditures for Purchased Energy Sources by Census Region," " Census Division, and Economic Characteristics of the Establishment, 1994" " (Estimates in Million Dollars)" " "," "," "," ",," "," "," "," "," ","RSE" " "," "," ","Residual","Distillate","Natural"," "," ","Coke"," ","Row" "Economic Characteristics(a)","Total","Electricity","Fuel Oil","Fuel Oil(b)","Gas(c)","LPG","Coal","and Breeze","Other(d)","Factors"

443

Table A19. Components of Total Electricity Demand by Census Region and  

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

Components of Total Electricity Demand by Census Region and" Components of Total Electricity Demand by Census Region and" " Economic Characteristics of the Establishment, 1991" " (Estimates in Million Kilowatthours)" " "," "," "," ","Sales/"," ","RSE" " "," ","Transfers","Onsite","Transfers"," ","Row" "Economic Characteristics(a)","Purchases","In(b)","Generation(c)","Offsite","Net Demand(d)","Factors" ,"Total United States" "RSE Column Factors:",0.5,1.4,1.3,1.9,0.5 "Value of Shipments and Receipts" "(million dollars)"

444

Table A26. Components of Total Electricity Demand by Census Region, Census Di  

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

Components of Total Electricity Demand by Census Region, Census Division, and" Components of Total Electricity Demand by Census Region, Census Division, and" " Economic Characteristics of the Establishment, 1994" " (Estimates in Million Kilowatthours)" " "," "," "," ","Sales/"," ","RSE" " "," ","Transfers","Onsite","Transfers"," ","Row" "Economic Characteristics(a)","Purchases","In(b)","Generation(c)","Offsite","Net Demand(d)","Factors" ,"Total United States" "RSE Column Factors:",0.5,2.1,1.2,2,0.4 "Value of Shipments and Receipts"

445

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

Science Journals Connector (OSTI)

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

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

1982-01-01T23:59:59.000Z

446

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

Science Journals Connector (OSTI)

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

Benjamin Anabori Mmadu; David Chuks Akan

2013-01-01T23:59:59.000Z

447

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

SciTech Connect (OSTI)

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

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

1990-02-01T23:59:59.000Z

448

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

Science Journals Connector (OSTI)

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

Makoto Tanaka; Takanori Ida

2013-01-01T23:59:59.000Z

449

An Analysis of the Price Elasticity of Demand for Household Appliances  

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

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

450

Geographic Characteristics State land area (sq. mi): 30,109 % of U.S.: 0.85  

E-Print Network [OSTI]

.9% 8.5% 5.3% 1.5% 2000 Race and Hispanic/Latino Ethnicity: South Carolina and Average of Selected % Hispanic or Latino (of any race) South Carolina 4,012,012 67.2% 29.5% 0.3% 0.9% 0.0% 1.0% 1.0% 2.4% Fishing Communities Compared to State Total Fishing Communities Total Population Median Household Income % Family

451

Geographic Characteristics State land area (sq. mi): 48,711 % of U.S.: 1.38  

E-Print Network [OSTI]

.5% 14.8% 11.0% 9.0% 5.6% 2.4% 2000 Race and Hispanic/Latino Ethnicity: North Carolina and Average races % Hispanic or Latino (of any race) North Carolina 8,049,313 72.1% 21.6% 1.2% 1.4% 0.0% 2.3% 1.3% 4 Fishing Communities Compared to State Total Fishing Communities Total Population Median Household Income

452

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

Science Journals Connector (OSTI)

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

Nicole B. Simpson; Jill Tiefenthaler; Jameson Hyde

2010-12-01T23:59:59.000Z

453

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

454

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

Science Journals Connector (OSTI)

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

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

2014-08-01T23:59:59.000Z

455

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

E-Print Network [OSTI]

efficiency standards. Total energy consumption (TEC) is thusarrived as follows, Total Energy Consumption = ? Stock(i) *Retirement) And total energy consumption for a particular

Lin, Jiang

2006-01-01T23:59:59.000Z

456

Commercial Buildings Characteristics 1992  

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

Buildings Characteristics 1992 Buildings Characteristics Overview Full Report Tables National and Census region estimates of the number of commercial buildings in the U.S. and...

457

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

Science Journals Connector (OSTI)

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

Ignacio Cazcarro; Rosa Duarte; Julio Sánchez-Chóliz

2012-05-21T23:59:59.000Z

458

Characteristics of Cleanroom  

Science Journals Connector (OSTI)

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

Zhonglin Xu

2014-01-01T23:59:59.000Z

459

Performance Period Total Fee Paid  

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

Period Period Total Fee Paid 4/29/2012 - 9/30/2012 $418,348 10/1/2012 - 9/30/2013 $0 10/1/2013 - 9/30/2014 $0 10/1/2014 - 9/30/2015 $0 10/1/2015 - 9/30/2016 $0 Cumulative Fee Paid $418,348 Contract Type: Cost Plus Award Fee Contract Period: $116,769,139 November 2011 - September 2016 $475,395 $0 Fee Information Total Estimated Contract Cost $1,141,623 $1,140,948 $1,140,948 $5,039,862 $1,140,948 Maximum Fee $5,039,862 Minimum Fee Fee Available Portage, Inc. DE-DT0002936 EM Contractor Fee Site: MOAB Uranium Mill Tailings - MOAB, UT Contract Name: MOAB Uranium Mill Tailings Remedial Action Contract September 2013 Contractor: Contract Number:

460

Buildings","Total  

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

L1. Floorspace Lit by Lighting Type for Non-Mall Buildings, 1995" L1. Floorspace Lit by Lighting Type for Non-Mall Buildings, 1995" ,"Floorspace (million square feet)" ,"Total (Lit or Unlit) in All Buildings","Total (Lit or Unlit) in Buildings With Any Lighting","Lighted Area Only","Area Lit by Each Type of Light" ,,,,"Incan- descent","Standard Fluor-escent","Compact Fluor- escent","High Intensity Discharge","Halogen" "All Buildings*",54068,51570,45773,6746,34910,1161,3725,779 "Building Floorspace" "(Square Feet)" "1,001 to 5,000",6272,5718,4824,986,3767,50,22,54 "5,001 to 10,000",7299,6667,5728,1240,4341,61,169,45 "10,001 to 25,000",10829,10350,8544,1495,6442,154,553,"Q"

Note: This page contains sample records for the topic "household characteristics total" 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

ARM - Measurement - Total cloud water  

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

cloud water cloud water ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Measurement : Total cloud water The total concentration (mass/vol) of ice and liquid water particles in a cloud; this includes condensed water content (CWC). Categories Cloud Properties Instruments The above measurement is considered scientifically relevant for the following instruments. Refer to the datastream (netcdf) file headers of each instrument for a list of all available measurements, including those recorded for diagnostic or quality assurance purposes. External Instruments NCEPGFS : National Centers for Environment Prediction Global Forecast System Field Campaign Instruments CSI : Cloud Spectrometer and Impactor PDI : Phase Doppler Interferometer

462

Buildings","Total  

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

L2. Floorspace Lit by Lighting Types (Non-Mall Buildings), 1999" L2. Floorspace Lit by Lighting Types (Non-Mall Buildings), 1999" ,"Floorspace (million square feet)" ,"Total (Lit or Unlit) in All Buildings","Total (Lit or Unlit) in Buildings With Any Lighting","Lighted Area Only","Area Lit by Each Type of Light" ,,,,"Incan- descent","Standard Fluor-escent","Compact Fluor- escent","High Intensity Discharge","Halogen" "All Buildings* ...............",61707,58693,49779,6496,37150,3058,5343,1913 "Building Floorspace" "(Square Feet)" "1,001 to 5,000 ...............",6750,5836,4878,757,3838,231,109,162 "5,001 to 10,000 ..............",7940,7166,5369,1044,4073,288,160,109 "10,001 to 25,000 .............",10534,9773,7783,1312,5712,358,633,232

463

Buildings","Total  

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

L3. Floorspace Lit by Lighting Type (Non-Mall Buildings), 2003" L3. Floorspace Lit by Lighting Type (Non-Mall Buildings), 2003" ,"Floorspace (million square feet)" ,"Total (Lit or Unlit) in All Buildings","Total (Lit or Unlit) in Buildings With Any Lighting","Lighted Area Only","Area Lit by Each Type of Light" ,,,,"Incan- descent","Standard Fluor-escent","Compact Fluor- escent","High Intensity Discharge","Halogen" "All Buildings* ...............",64783,62060,51342,5556,37918,4004,4950,2403 "Building Floorspace" "(Square Feet)" "1,001 to 5,000 ...............",6789,6038,4826,678,3932,206,76,124 "5,001 to 10,000 ..............",6585,6090,4974,739,3829,192,238,248 "10,001 to 25,000 .............",11535,11229,8618,1197,6525,454,506,289

464

Acculturation in Hispanics and childhood poisoning: Are medicines and household cleaners stored properly?  

Science Journals Connector (OSTI)

Background Unintentional poisonings are a major public health issue in the United States (US). With the increasing number of Hispanics in the US, childhood poisoning is a salient public health issue to address within this population. There is a paucity of research examining the relationship between acculturation in Hispanics and the safe storage of medicines and cleaners. The purpose of the study was to determine if demographic variables, such as acculturation in Hispanics, age, gender and education, were predictive of incorrectly storing medicines and household cleaners. Methods We conducted a study among parents/guardians of small children at two pediatric primary care clinics in the Dallas/Fort Worth (DFW) Metropolitan area. We enrolled 201 parents to identify where they stored medicines and household cleaners, and measured acculturation with the Short Acculturation Scale for Hispanics. Results Of Hispanic participants, 49% were categorized as less acculturated (n = 99) while 21% were more acculturated (n = 42). Less acculturated participants were over 4 times more likely to store medicines incorrectly, and participants with a high school education or less were over 3 times more likely to improperly store cleaners. With each additional child in the household, the risk for improper storage of cleaners increased by 44%. Conclusion The fact that children of less acculturated families are at greater risk for poisoning and have lower levels of education demonstrates the need for readable educational materials on this salient topic. Because social networks are integral in Hispanic culture, especially among new immigrants, poison prevention messages should be disseminated by interpersonal communications.

Katie L. Crosslin; Ray Tsai; Claudia V. Romo; Adela Tsai

2011-01-01T23:59:59.000Z

465

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

SciTech Connect (OSTI)

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.

Not Available

1991-10-01T23:59:59.000Z

466

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

SciTech Connect (OSTI)

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.

Not Available

1991-10-01T23:59:59.000Z

467

Halogenated Volatile Organic Compounds from the Use of Chlorine-Bleach-Containing Household Products  

Science Journals Connector (OSTI)

A number of household cleaning products (bleaches, mildew stain removers, toilet cleaners, cleaning sprays, gels, and scouring powders) contain sodium hypochlorite (NaOCl, ?5%). ... Each tube was packed at the upstream (sampling) end with 3 mm silanized glass-wool followed by a series of sections of 150 mg Tenax TA (60/80 mesh) (Supelco, Bellefonte, PA, USA), 3 mm silanized glass-wool, 100 mg Carboxen 1000 (Supelco, Bellefonte, PA), and finally, 3 mm silanized glass-wool at the downstream end. ...

Mustafa Odabasi

2008-02-01T23:59:59.000Z

468

Determinants of households’ inflation expectations in Japan and the United States  

Science Journals Connector (OSTI)

Using a VAR model that includes survey data on households’ inflation expectations for Japan and the US, we investigate their determinants and influences on the economy and compare their properties in two countries. Short-term non-recursive restrictions are imposed taking account of simultaneous co-dependence between realized and expected inflation. We find that responding to changes in exogenous prices and to monetary policy shocks, inflation expectations adjust more quickly than does realized inflation. Compared with Japan, the effects of exogenous prices on inflation and inflation expectations in the US are not only large but also long lasting and shocks to expectations have self-fulfilling effects on inflation.

Kozo Ueda

2010-01-01T23:59:59.000Z

469

Microsoft Word - 20050821_Appendix_A.doc  

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

8. U.S. Vehicles by EIA Household Composition 8. U.S. Vehicles by EIA Household Composition 1 , 2001 (Million Vehicles) ENERGY INFORMATION ADMINISTRATION / HOUSEHOLD VEHICLES ENERGY USE: LATEST A N D TRENDS 114 Households With Children Households Without Children Age of Oldest Child One Adult--Age of Householder Two or More Adults--Age of Householder 2001 Household and Vehicle Characteristics Total Under 7 Years 7 to 15 Years 16 or 17 Years Total Under 35 Years 35 to 59 Years 60 Years or Over Under 35 Years 35 to 59 Years 60 Years or Over Household Characteristics Total.............................. 79.8 20.0 41.5 18.2 111.2 3.7 11.5 11.4 13.4 41.0 30.3 Census Region and Division Northeast......................... 13.4 3.4 7.0

470

On the consumption insurance effects of long-term care insurance in Japan: Evidence from micro-level household data  

Science Journals Connector (OSTI)

Using micro-level household data in the 2001 Comprehensive Survey of the Living Conditions of the People on Health and Welfare compiled by the Japanese Ministry of Health, Labor and Welfare, this paper examines how having a household member in need of long-term nursing care can result in welfare losses measured in terms of consumption. In so doing, this study evaluates the role of the public long-term care insurance scheme implemented in Japan in April 2000. The results indicate that when households include a disabled family member, household consumption net of long-term care costs do not decrease as much as before the introduction of long-term care insurance. Further, when compared with the surveys conducted in 1998, the adverse effects on consumption net of long-term care costs have become much weaker. These findings suggest that the introduction of social insurance in 2000 helped Japanese households to reduce the welfare losses associated with a disabled family member.

Yasushi Iwamoto; Miki Kohara; Makoto Saito

2010-01-01T23:59:59.000Z

471

Total Adjusted Sales of Kerosene  

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

End Use: Total Residential Commercial Industrial Farm All Other Period: End Use: Total Residential Commercial Industrial Farm All Other Period: Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: End Use Area 2007 2008 2009 2010 2011 2012 View History U.S. 492,702 218,736 269,010 305,508 187,656 81,102 1984-2012 East Coast (PADD 1) 353,765 159,323 198,762 237,397 142,189 63,075 1984-2012 New England (PADD 1A) 94,635 42,570 56,661 53,363 38,448 15,983 1984-2012 Connecticut 13,006 6,710 8,800 7,437 7,087 2,143 1984-2012 Maine 46,431 19,923 25,158 24,281 17,396 7,394 1984-2012 Massachusetts 7,913 3,510 5,332 6,300 2,866 1,291 1984-2012 New Hampshire 14,454 6,675 8,353 7,435 5,472 1,977 1984-2012

472

Solar total energy project Shenandoah  

SciTech Connect (OSTI)

This document presents the description of the final design for the Solar Total Energy System (STES) to be installed at the Shenandoah, Georgia, site for utilization by the Bleyle knitwear plant. The system is a fully cascaded total energy system design featuring high temperature paraboloidal dish solar collectors with a 235 concentration ratio, a steam Rankine cycle power conversion system capable of supplying 100 to 400 kW(e) output with an intermediate process steam take-off point, and a back pressure condenser for heating and cooling. The design also includes an integrated control system employing the supervisory control concept to allow maximum experimental flexibility. The system design criteria and requirements are presented including the performance criteria and operating requirements, environmental conditions of operation; interface requirements with the Bleyle plant and the Georgia Power Company lines; maintenance, reliability, and testing requirements; health and safety requirements; and other applicable ordinances and codes. The major subsystems of the STES are described including the Solar Collection Subysystem (SCS), the Power Conversion Subsystem (PCS), the Thermal Utilization Subsystem (TUS), the Control and Instrumentation Subsystem (CAIS), and the Electrical Subsystem (ES). Each of these sections include design criteria and operational requirements specific to the subsystem, including interface requirements with the other subsystems, maintenance and reliability requirements, and testing and acceptance criteria. (WHK)

None

1980-01-10T23:59:59.000Z

473

Grantee Total Number of Homes  

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

Grantee Grantee Total Number of Homes Weatherized through November 2011 [Recovery Act] Total Number of Homes Weatherized through November 2011 (Calendar Year 2009 - November 2011) [Recovery Act + Annual Program Funding] Alabama 6,704 7,867 1 Alaska 443 2,363 American Samoa 304 410 Arizona 6,354 7,518 Arkansas 5,231 6,949 California 41,649 50,002 Colorado 12,782 19,210 Connecticut 8,940 10,009 2 Delaware** 54 54 District of Columbia 962 1,399 Florida 18,953 20,075 Georgia 13,449 14,739 Guam 574 589 Hawaii 604 1,083 Idaho** 4,470 6,614 Illinois 35,530 44,493 Indiana** 18,768 21,689 Iowa 8,794 10,202 Kansas 6,339 7,638 Kentucky 7,639 10,902 Louisiana 4,698 6,946 Maine 5,130 6,664 Maryland 8,108 9,015 Massachusetts 17,687 21,645 Michigan 29,293 37,137 Minnesota 18,224 22,711 Mississippi 5,937 6,888 Missouri 17,334 20,319 Montana 3,310 6,860 Navajo Nation

474

A Juxtaposition of rational choice and socio-cultural approaches to explain changes in family size throughout the process of economic development using household survey data from Brazil.  

E-Print Network [OSTI]

??This research juxtaposes empirical approaches to analyze the relationship between fertility and economic development. Using household survey data from Brazil in the mid 1990’s, separate… (more)

Delfino, Daniel

2010-01-01T23:59:59.000Z

475

Role of household factors in parental attitudes to pandemic influenza-related school closure in Japan: a cross-sectional study  

Science Journals Connector (OSTI)

Subjects comprised households of schoolchildren attending six schools (one kindergarten ... ) all attached to Shinshu University, Nagano, Japan. Because these six schools had been investigated...11, 12...], this ...

Mitsuo Uchida; Minoru Kaneko; Shigeyuki Kawa

2014-10-01T23:59:59.000Z

476

Total Number of Operable Refineries  

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

Data Series: Total Number of Operable Refineries Number of Operating Refineries Number of Idle Refineries Atmospheric Crude Oil Distillation Operable Capacity (B/CD) Atmospheric Crude Oil Distillation Operating Capacity (B/CD) Atmospheric Crude Oil Distillation Idle Capacity (B/CD) Atmospheric Crude Oil Distillation Operable Capacity (B/SD) Atmospheric Crude Oil Distillation Operating Capacity (B/SD) Atmospheric Crude Oil Distillation Idle Capacity (B/SD) Vacuum Distillation Downstream Charge Capacity (B/SD) Thermal Cracking Downstream Charge Capacity (B/SD) Thermal Cracking Total Coking Downstream Charge Capacity (B/SD) Thermal Cracking Delayed Coking Downstream Charge Capacity (B/SD Thermal Cracking Fluid Coking Downstream Charge Capacity (B/SD) Thermal Cracking Visbreaking Downstream Charge Capacity (B/SD) Thermal Cracking Other/Gas Oil Charge Capacity (B/SD) Catalytic Cracking Fresh Feed Charge Capacity (B/SD) Catalytic Cracking Recycle Charge Capacity (B/SD) Catalytic Hydro-Cracking Charge Capacity (B/SD) Catalytic Hydro-Cracking Distillate Charge Capacity (B/SD) Catalytic Hydro-Cracking Gas Oil Charge Capacity (B/SD) Catalytic Hydro-Cracking Residual Charge Capacity (B/SD) Catalytic Reforming Charge Capacity (B/SD) Catalytic Reforming Low Pressure Charge Capacity (B/SD) Catalytic Reforming High Pressure Charge Capacity (B/SD) Catalytic Hydrotreating/Desulfurization Charge Capacity (B/SD) Catalytic Hydrotreating Naphtha/Reformer Feed Charge Cap (B/SD) Catalytic Hydrotreating Gasoline Charge Capacity (B/SD) Catalytic Hydrotreating Heavy Gas Oil Charge Capacity (B/SD) Catalytic Hydrotreating Distillate Charge Capacity (B/SD) Catalytic Hydrotreating Kerosene/Jet Fuel Charge Capacity (B/SD) Catalytic Hydrotreating Diesel Fuel Charge Capacity (B/SD) Catalytic Hydrotreating Other Distillate Charge Capacity (B/SD) Catalytic Hydrotreating Residual/Other Charge Capacity (B/SD) Catalytic Hydrotreating Residual Charge Capacity (B/SD) Catalytic Hydrotreating Other Oils Charge Capacity (B/SD) Fuels Solvent Deasphalting Charge Capacity (B/SD) Catalytic Reforming Downstream Charge Capacity (B/CD) Total Coking Downstream Charge Capacity (B/CD) Catalytic Cracking Fresh Feed Downstream Charge Capacity (B/CD) Catalytic Hydro-Cracking Downstream Charge Capacity (B/CD) Period:

477

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

SciTech Connect (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

478

The stem family and labour markets: Reflections on households and firms in Japan's economic development  

Science Journals Connector (OSTI)

This paper examines a view that the traditional stem family system was one of the preconditions for Japan's modern economic development, focusing on labour markets and skill formation practices. The paper begins with a brief look at the Japanese stem family household formation rules. Then, exploration is made, first, on the self-employed, the largest sector of the early modern economy; second, the merchant house and its employment patterns as an origin of present day large corporations' employment system and skill formation and human capital management practices; and third, workshop industries, which formed middle and lower layers of the manufacturing sector in the period of industrialisation. Finally, women's marriage behaviour is examined in relation to labour markets, especially changes in real wages. All this is an attempt to go some way towards a better understanding of the ways in which the family economy and corporate firms worked in economic development, rather than to suggest an alternative hypothesis on the relationship between family and household factors and subsequent economic development.

Osamu Saito

2011-01-01T23:59:59.000Z

479

Total quality management implementation guidelines  

SciTech Connect (OSTI)

These Guidelines were designed by the Energy Quality Council to help managers and supervisors in the Department of Energy Complex bring Total Quality Management to their organizations. Because the Department is composed of a rich mixture of diverse organizations, each with its own distinctive culture and quality history, these Guidelines are intended to be adapted by users to meet the particular needs of their organizations. For example, for organizations that are well along on their quality journeys and may already have achieved quality results, these Guidelines will provide a consistent methodology and terminology reference to foster their alignment with the overall Energy quality initiative. For organizations that are just beginning their quality journeys, these Guidelines will serve as a startup manual on quality principles applied in the Energy context.

Not Available

1993-12-01T23:59:59.000Z

480

An input-output approach to analyze the ways to increase total output of energy sectors: The case of Japan  

Science Journals Connector (OSTI)

The purpose of this study is to analyze the ways to increase total output of Japanese energy sectors in future time. In this study, Input-Output (IO) analysis is employed as a tool of analysis. This study focuses on petroleum refinery products and non-ferrous metals as analyzed sectors. The results show that positive impact observed in export and outside households consumption modifications while opposite impact is given by modification of import. The recommendations suggested based on these results are Japanese government should make breakthroughs so analyzed sector's export activities can increase and they have to careful in conducting import activities related to these sectors.

Ubaidillah Zuhdi

2014-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "household characteristics total" 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

"Table A48. Total Expenditures for Purchased Electricity, Steam, and Natural"  

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

8. Total Expenditures for Purchased Electricity, Steam, and Natural" 8. Total Expenditures for Purchased Electricity, Steam, and Natural" " Gas by Type of Supplier, Census Region, and Economic Characteristics of the" " Establishment, 1991" " (Estimates in Million Dollars)" ," Electricity",," Steam",," Natural Gas" ,"-","-----------","-","-----------","-","------------","-----------","RSE" " ","Utility","Nonutility","Utility","Nonutility","Utility","Transmission","Other","Row" "Economic Characteristics(a)","Supplier(b)","Supplier(c)","Supplier(b)","Supplier(c)","Supplier(b)","Pipelines","Supplier(d)","Factors"," "

482

Total Heart Transplant: A Modern Overview  

E-Print Network [OSTI]

use of the total artificial heart. New England Journal ofJ. (1997). Artificial heart transplants. British medicala total artificial heart as a bridge to transplantation. New

Lingampalli, Nithya

2014-01-01T23:59:59.000Z

483

Residential energy consumption across different population groups : comparative analysis for latino and non-latino households in USA.  

SciTech Connect (OSTI)

Residential energy cost is an important part of the household budget and could vary significantly across different population groups in many countries. In the United States, many studies have analyzed household fuel consumption by fuel type, including electricity, natural gas, fuel oil, and liquefied petroleum gas (LPG), and by geographic areas. Past research has also demonstrated significant variation in residential energy use across various population groups, including white, black, and Latino. However, our research shows that residential energy demand by fuel type for Latinos, the fastest growing population group, has not been explained by economic and non-economic factors in any statistical model in public domain. The purpose of this paper was to discuss energy demand and expenditure patterns for Latino and non-Latino households in the United States as a case example of analyzing residential energy consumption across different population groups in a country. The linear expenditure system model developed by Stone and Geary is the basis of the statistical model developed to explain fuel consumption and expenditures for Latino households. For comparison, the models are also developed for non-Latino, black, and non-black households. These models estimate energy consumption of and expenditures for electricity, natural gas, fuel oil, and LPG by various households at the national level. Significant variations in the patterns of these fuels consumption for Latinos and non-Latinos are highlighted. The model methodology and results of this research should be useful to energy policymakers in government and industry, researches, and academicians who are concerned with economic and energy issues related to various population groups in their country.

Poyer, D. A.; Henderson, L.; Teotia, A. P. S.; Energy Systems; Univ. of Baltimore

1997-01-01T23:59:59.000Z

484

PressurePressure Indiana Coal Characteristics  

E-Print Network [OSTI]

TimeTime PressurePressure · Indiana Coal Characteristics · Indiana Coals for Coke · Coal Indiana Total Consumption Electricity 59,664 Coke 4,716 Industrial 3,493 Major Coal- red power plantsTransportation in Indiana · Coal Slurry Ponds Evaluation · Site Selection for Coal Gasification · Coal-To-Liquids Study, CTL

Fernández-Juricic, Esteban

485

Electricity Production from Anaerobic Digestion of Household Organic Waste in Ontario: Techno-Economic and GHG Emission Analyses  

Science Journals Connector (OSTI)

Electricity Production from Anaerobic Digestion of Household Organic Waste in Ontario: Techno-Economic and GHG Emission Analyses ... The life cycle greenhouse gas (GHG) emissions and economics of electricity generation through anaerobic digestion (AD) of household source-separated organic waste (HSSOW) are investigated within the FiT program. ... AD can potentially provide considerable GHG emission reductions (up to 1 t CO2eq/t HSSOW) at relatively low to moderate cost (-$35 to 160/t CO2eq) by displacing fossil electricity and preventing the emission of landfill gas. ...

David Sanscartier; Heather L. MacLean; Bradley Saville

2011-12-14T23:59:59.000Z

486

Marriage relationships among households in the mid 19th century Tama, Japan: Socioeconomic homogamy, geographical endogamy and kinship networks  

Science Journals Connector (OSTI)

This paper studies the formation of marriage relationships between households in 19th century, Tama, Japan. Previous studies on marriage market or partner selection in the Japanese past tended to rely either on information from a single village in case of statistical analysis, or on collection of oral histories. By using the information from a household register that covers 35 villages, and applying a method of social network analysis, this paper goes beyond the limitation of previous studies. Our empirical results show that there was a tendency for socioeconomic homogamy and endogamy (within kinship and within village) among peasants in the mid 19th century Tama, Japan.

Nobuyuki Hanaki; Satomi Kurosu

2010-01-01T23:59:59.000Z

487

Total Imports of Residual Fuel  

Gasoline and Diesel Fuel Update (EIA)

May-13 Jun-13 Jul-13 Aug-13 Sep-13 Oct-13 View May-13 Jun-13 Jul-13 Aug-13 Sep-13 Oct-13 View History U.S. Total 5,752 5,180 7,707 9,056 6,880 6,008 1936-2013 PAD District 1 1,677 1,689 2,008 3,074 2,135 2,814 1981-2013 Connecticut 1995-2009 Delaware 1995-2012 Florida 359 410 439 392 704 824 1995-2013 Georgia 324 354 434 364 298 391 1995-2013 Maine 65 1995-2013 Maryland 1995-2013 Massachusetts 1995-2012 New Hampshire 1995-2010 New Jersey 903 756 948 1,148 1,008 1,206 1995-2013 New York 21 15 14 771 8 180 1995-2013 North Carolina 1995-2011 Pennsylvania 1995-2013 Rhode Island 1995-2013 South Carolina 150 137 194 209 1995-2013 Vermont 5 4 4 5 4 4 1995-2013 Virginia 32 200 113 1995-2013 PAD District 2 217 183 235 207 247 179 1981-2013 Illinois 1995-2013

488

U.S. Total Exports  

Gasoline and Diesel Fuel Update (EIA)

Noyes, MN Warroad, MN Babb, MT Port of Del Bonita, MT Port of Morgan, MT Sweetgrass, MT Whitlash, MT Portal, ND Sherwood, ND Pittsburg, NH Champlain, NY Grand Island, NY Massena, NY Niagara Falls, NY Waddington, NY Sumas, WA Highgate Springs, VT U.S. Pipeline Total from Mexico Ogilby, CA Otay Mesa, CA Galvan Ranch, TX LNG Imports from Algeria LNG Imports from Australia LNG Imports from Brunei LNG Imports from Canada Highgate Springs, VT LNG Imports from Egypt Cameron, LA Elba Island, GA Freeport, TX Gulf LNG, MS LNG Imports from Equatorial Guinea LNG Imports from Indonesia LNG Imports from Malaysia LNG Imports from Nigeria Cove Point, MD LNG Imports from Norway Cove Point, MD Freeport, TX Sabine Pass, LA LNG Imports from Oman LNG Imports from Peru Cameron, LA Freeport, TX LNG Imports from Qatar Elba Island, GA Golden Pass, TX Sabine Pass, LA LNG Imports from Trinidad/Tobago Cameron, LA Cove Point, MD Elba Island, GA Everett, MA Freeport, TX Gulf LNG, MS Lake Charles, LA Sabine Pass, LA LNG Imports from United Arab Emirates LNG Imports from Yemen Everett, MA Freeport, TX Sabine Pass, LA LNG Imports from Other Countries Period: Monthly Annual

489

Natural Gas Total Liquids Extracted  

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

Thousand Barrels) Thousand Barrels) Data Series: Natural Gas Processed Total Liquids Extracted NGPL Production, Gaseous Equivalent Period: Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: Data Series Area 2007 2008 2009 2010 2011 2012 View History U.S. 658,291 673,677 720,612 749,095 792,481 873,563 1983-2012 Alabama 13,381 11,753 11,667 13,065 1983-2010 Alaska 22,419 20,779 19,542 17,798 18,314 18,339 1983-2012 Arkansas 126 103 125 160 212 336 1983-2012 California 11,388 11,179 11,042 10,400 9,831 9,923 1983-2012 Colorado 27,447 37,804 47,705 57,924 1983-2010 Florida 103 16 1983-2008 Illinois 38 33 24 231 705 0 1983-2012

490

U.S. Department of Energy, Energy Information Administration (EIA  

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

8 - Vehicles by HH Comp EIA ","Table A18. U.S. Vehicles by Household Composition1 (EIA), 2001 8 - Vehicles by HH Comp EIA ","Table A18. U.S. Vehicles by Household Composition1 (EIA), 2001 (Million Vehicles)" "Std Errors for A18","Relative Standard Errors for Table A18. U.S. Vehicles by Household Composition1 (EIA), 2001 (Percent)" "N Cells for A18","Number of Sample Cases Contributing to Estimates in Table A18. U.S. Vehicles by Household Composition1 (EIA), 2001" " Page A-1 of A-N" "Table A18. U.S. Vehicles by Household Composition1 (EIA), 2001 (Million Vehicles)" "2001 Household and Vehicle Characteristics","Households With Children",,,,"Households Without Children" ,"Total","Age of Oldest Child",,,"Total","One Adult--Age of Householder",,,"Two or More Adults--Age of Householder"

491

Total Petroleum Systems and Assessment Units (AU)  

E-Print Network [OSTI]

Total Petroleum Systems (TPS) and Assessment Units (AU) Field type Surface water Groundwater X X X X X X X X AU 00000003 Oil/ Gas X X X X X X X X Total X X X X X X X Total Petroleum Systems (TPS) and Assessment Units (AU) Field type Total undiscovered petroleum (MMBO or BCFG) Water per oil

Torgersen, Christian

492

Locating and total dominating sets in trees  

Science Journals Connector (OSTI)

A set S of vertices in a graph G = ( V , E ) is a total dominating set of G if every vertex of V is adjacent to a vertex in S. We consider total dominating sets of minimum cardinality which have the additional property that distinct vertices of V are totally dominated by distinct subsets of the total dominating set.

Teresa W. Haynes; Michael A. Henning; Jamie Howard

2006-01-01T23:59:59.000Z

493

Who is eating seafood? On an annual basis, results from the survey screener showed that 65% of U.S. households purchased  

E-Print Network [OSTI]

Who is eating seafood? On an annual basis, results from the survey screener showed that 65% of U.S. households purchased seafood for at-home consumption at least once in the previous year while 83% of households purchased seafood in a restaurant during the same period. As shown in Figures 1a-c, retail seafood

494

Locating-total domination in graphs  

Science Journals Connector (OSTI)

In this paper, we continue the study of locating-total domination in graphs. A set S of vertices in a graph G is a total dominating set in G if every vertex of G is adjacent to a vertex in S . We consider total dominating sets S which have the additional property that distinct vertices in V ( G ) ? S are totally dominated by distinct subsets of the total dominating set. Such a set S is called a locating-total dominating set in G , and the locating-total domination number of G is the minimum cardinality of a locating-total dominating set in G . We obtain new lower and upper bounds on the locating-total domination number of a graph. Interpolation results are established, and the locating-total domination number in special families of graphs, including cubic graphs and grid graphs, is investigated.

Michael A. Henning; Nader Jafari Rad

2012-01-01T23:59:59.000Z

495

Characteristics of Strong Programs  

Broader source: Energy.gov [DOE]

Existing financing programs offer a number of important lessons on effective program design. Some characteristics of strong financing programs drawn from past program experience are described below.

496

An Analysis of the Price Elasticity of Demand for Household Appliances  

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

497

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

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

498

Mineral fiber content of lung tissue in patients with environmental exposures: household contacts vs building occupants  

SciTech Connect (OSTI)

Analysis of tissue mineral fiber content in patients with environmental exposures has seldom been reported in the past. Our studies of six