United States
Environmental Protection
Agency
Air and Energy Engineering
Research Laboratory
Research Triangle Park, NC 27711
Research and Development
EPA/600/SR-93/096 July 1993
Project Summary
Development of Residential
Wood Consumption Estimation
Models
Walid Ramadan and Mark G. Smith
Data on the distribution and usage
of firewood were obtained from a pool
of household wood use surveys. Based
on a series of regression models de-
veloped using the STEPWISE proce-
dure in the SAS statistical package,
two variables appear to be most pre-
dictive of wood use per household: (1)
heating degree days, and (2) percent-
age of households that burn wood as a
main heat source. The average number
of cords burned in fireplaces is esti-
mated as a function of the total num-
ber 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, avail-
ability of wood, and percentage of ur-
ban population. Input data, predicted
values, and deviations from actual val-
ues are tabulated for each model.
Graphs for each model show both ac-
tual and predicted values for the vari-
ables being estimated.
This Project Summary was developed
by EPA's Air and Energy Engineering
Research Laboratory, Research Tri-
angle Park, NC, to announce key find-
ings of the research project that is fully
documented in a separate report of the
same title (see Project Report ordering
information at back).
Introduction
This report presents several statistical
models that have been developed to pre-
dict wood fuel use in residential applica-
tions based on a review of available resi-
dential wood use surveys conducted for
local area planning or State Implementa-
tion Plan (SIP) inventory development
These models could be used to improve
the emissions estimates for residentia
wood fuel consumption in areas that aro
not required, and therefore are not likely
to conduct household surveys. The mod
els may also be included in the Area an; I
Mobile Source Subsystem (AMS) of tru-
Aerometric Information Retrieval Systen
(AIRS).
Database Development
Data on the distribution and usage o
firewood are needed in order to accu
rately characterize the resulting air pollu
tion impacts. Currently, the most accurate •
means of estimating residential wood com
bustion levels in a given area is througT
direct surveys of households. Wood use
surveys were obtained from several states
including Colorado, Connecticut, Idaho
Maine, Montana, Nevada, New Hampshire
Oregon, Vermont, and Washington. Whik
most surveys reviewed were oonductec
specifically to evaluate wood use in ar
area, some were conducted for other pur
poses, but still included questions pertain
ing to wood burning. Most of the survey?
reviewed were from and within Montana
Colorado, and Washington. The geo
graphic levels at which the surveys wen
conducted ranged from small towns tc
entire states. Only a fraction of the sur
veys clearly defined the boundaries of the
survey area. Of the surveys, 58% wen
conducted prior to 1985; the remaining
42% were conducted during or after 1985
State-level survey results were collectec
for Colorado, Michigan, and Washington
These surveys were not used in the anaiy
sis because the focus of this effort was tc
develop models applicable at the county
level. Many other surveys collected were
not usable due primarily to a lack of infer
mation on the surveys' boundaries, and/or
Printed on Recycled Pape<
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the lack of questions in the Surveys that
would result in estimates of fuel wood
use. Finally, in areas where more than
one survey had been conducted, only the
most recently complete was used. Over-
all, 68 surveys were obtained, of which 40
were used in the analysis.
Statistical Analysis
Before designing new models, several
existing models were examined that quan-
tify residential wood combustion. Two stud-
ies in particular were reviewed which esti-
mate firewood usage at the county level.
One, conducted by Brookhaven National
Laboratory, performed a regression analy-
sis on survey data collected by the U.S.
Forest Service. The other study, by Skog
and Watterson, performed a regression
analysis on the survey data collected as
part of the New England Fuelwood Sur-
vey. The models and their results are
briefly described and their application to
the surveys collected presented.
Conclusions
Based on a series of regression models
developed to estimate wood use and dis-
tribution of wood-burning devices, the two
variables that appear to be most predic-
tive are heating degree days and percent-
age of households that burn wood as a
main source of heat. A variety of local
factors can directly impact the number of
wood-burning households and the quan-
tity of wood burned by each. Such factors
include the historical availability and rela-
tive price of other heating fuels, and the
heat content of firewood in the area where
the survey was conducted. The latter fac-
tor is important because wood use is mea-
sured by cords, a volume measurement.
A cord of pine contains approximately 65%
of the heat content of a cord of oak.
Limitations on the estimates of wood
use presented here do not necessarily lie
in the methodology but with the data used
as inputs for the models. The accuracy of
the data collected is in doubt because
there was no independent verification. It
is likely that the variability in the data is
due in large part to the respondents' inac-
curate impression of how much wood is in
a cord. Another limitation is that the geo-
graphical boundaries of many of the sur-
vey areas were poorly defined. Finally,
the validity of the surveys themselves is
questionable especially in those areas that
showed large discrepancies between the
reported estimates of households using
wood as a main heating fuel and the cor-
responding Census statistics.
The residential wood consumption mod-
els developed here may be improved by
Walid Ramadan and Mark G. Smith are with TRC Environmental Corp., Chapel Hill,
NC27514.
Robert C. McCrillis is the EPA Project Officer (see below)
The complete report, entitled "Development of Residential Wood Consumption
Estimation Models," (Order No. PB93-199 248/AS; Cost: $19.50, subject to
change) will be available only from:
National Technical Information Service
5285 Port Royal Road
Springfield, VA 22161
Telephone: 703-487-4650
The EPA Project Officer can be contacted at:
Air and Energy Engineering Research Laboratory
U.S. Environmental Protection Agency
Research Triangle Park, NC 27711
United States
Environmental Protection Agency
Center for Environmental Research Information
Cincinnati, OH 45268
Official Business
Penalty for Private Use
$300
including a number of socioeconomic vari-
ables such as cost of other energy forms
in comparison to wood energy and aver-
age household income. The models can
also be improved by conducting more sim-
plified and specialized wood use surveys.
Future guidance on the development and
use of surveys of residential wood use
should attempt to gather more detailed
information specifically on appliance char-
acteristics (i.e., catalytic, EPA-certified),
wood characteristics, and wood-burning
practices. Simplified surveys reduce the
number of nonrespondents and the num-
ber of unanswered questions. Missing an-
swers in surveys present problems when
the data collected in a survey are subject
to statistical analysis because statistical
procedures cannot be immediately used if
there are missing values. In addition, the
models can be further improved by incor-
porating cross-sectional data from areas
that conduct surveys periodically. Cross-
sectional data may be used to develop
wood use projection models and will cap-
ture the effects of changing socioeconomic
factors on wood use patterns. Finally, the
wood use models presented in the report
can be validated, using field surveys to
show how accurately the models estimate
wood use in areas where no surveys are
planned.
'U.S. Government Printing Office: 1993 — 750-071/80027
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EPA/600/SR-93/096
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