Record Display for the EPA National Library Catalog

RECORD NUMBER: 34 OF 127

OLS Field Name OLS Field Data
Main Title Development of residential wood consumption estimation models : project summary /
Author Ramadan, Walid,
Other Authors
Author Title of a Work
Smith, Mark G.,
McCrillis, Robert C.,
Publisher U.S. Environmental Protection Agency, Air and Energy Engineering, Research Laboratory,
Year Published 1993
Report Number EPA/600-SR-93-096
OCLC Number 904016736
Subjects Fuelwood crops--United States.
Internet Access
Description Access URL
http://nepis.epa.gov/Exe/ZyPDF.cgi?Dockey=30003WG0.PDF
Holdings
Library Call Number Additional Info Location Last
Modified
Checkout
Status
EJBD ARCHIVE EPA 600-SR-93-096 In Binder Headquarters Library/Washington,DC 03/28/2018
EJBD  EPA 600-SR-93-096 In Binder Headquarters Library/Washington,DC 10/25/2018
ELBD RPS EPA 600-SR-93-096 repository copy AWBERC Library/Cincinnati,OH 08/01/2017
ELBD  EPA 600-SR-93-096 AWBERC Library/Cincinnati,OH 08/16/2017
Collation 2 pages ; 28 cm
Notes
At head of title: Project Summary. "EPA/600-SR-93-096." "July 1993."
Contents Notes
Data on the distribution and usage of firewood were obtained from a pool of household wood use surveys. Base on a series of regression models developed using the STEPWISE procedure in the SAS statistical package, two variables appear to be most predictive of wood use per household: (1) heating degree days, and (2) percentage of households that burn wood as a main heat source. The average number of cords burned in fireplaces is estimated as a function of the total number of cords burned per household, availability of wood, and population density. Models were also developed to estimate the distribution of wood-burning devices. Variables that appear to be most predictive of the percentage of wood stoves are percentage of households that burn wood as a main heat source, heating degree days, availability of wood, and percentage of urban population. input data, predicted values, and deviations from actual values are tabulated for each model. Graphs for each model show both actual and predicted values for the variables being estimated.