TABLE
OF
CONTENTS
Page
No.

17.
RESIDENTIAL
BUILDING
CHARACTERISTICS
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
1
17.1.
INTRODUCTION
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
1
17.2.
BUILDING
CHARACTERISTICS
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
2
17.2.1.
Key
Volumes
of
Residence
Studies
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
2
17.2.2.
Volumes
and
Surface
Areas
of
Rooms
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
4
17.2.3.
Mechanical
System
Configurations
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
6
17.2.4.
Type
of
Foundation
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
7
17.3.
TRANSPORT
RATES
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
8
17.3.1.
Background
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
8
17.3.2.
Air
Exchange
Rates
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
10
17.3.3.
Infiltration
Models
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
12
17.3.4.
Deposition
and
Filtration
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
14
17.3.5.
Interzonal
Airflows
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
15
17.3.6.
Water
Uses
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
15
17.3.7.
House
Dust
and
Soil
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
19
17.4.
SOURCES
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
20
17.4.1.
Source
Descriptions
for
Airborne
Contaminants
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
20
17.4.2.
Source
Descriptions
for
Waterborne
Contaminants
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
22
17.4.3.
Soil
and
House
Dust
Sources
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
22
17.5.
ADVANCED
CONCEPTS
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
23
17.5.1.
Uniform
Mixing
Assumption
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
23
17.5.2.
Reversible
Sinks
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
23
17.6
RECOMMENDATIONS
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
23
17.7.
REFERENCES
FOR
CHAPTER
17
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
24
Air
In
Water
In
Soil
In
Out
Concentration,
C
Exposure,
E
for
Occupant(
s)

Decay
Removal
Resuspension
Source
Reversible
Sinks
Volume
III
­
Activity
Factors
Chapter
17
­
Residential
Building
Characteristics
Exposure
Factors
Handbook
Page
August
1997
17­
1
Figure
17­
1.
Elements
of
Residential
Exposure
17.
RESIDENTIAL
BUILDING
CHARACTERISTICS
17.1.
INTRODUCTION
Unlike
previous
chapters
in
this
handbook
which
a
wide
range
of
indoor
materials.
In
addition,
the
activity
of
focus
on
human
behavior
or
characteristics
that
affect
human
receptors
greatly
affects
their
exposure
as
they
move
exposure,
this
chapter
focuses
on
residence
characteristics.
from
room
to
room,
entering
and
leaving
the
exposure
Assessment
of
exposure
in
residential
settings
requires
scene.
information
on
the
availability
of
the
chemical(
s)
of
concern
Inhalation
exposure
assessments
in
residential
and
at
the
point
of
exposure,
characteristics
of
the
structure
and
other
indoor
settings
are
modeled
by
considering
the
microenvironment
that
affect
exposure,
and
human
presence
building
as
an
assemblage
of
one
or
more
well­
mixed
within
the
residence.
The
purpose
of
this
chapter
is
to
zones.
A
zone
is
defined
as
one
room,
a
group
of
provide
data
that
are
available
on
residence
characteristics
interconnected
rooms,
or
an
entire
building.
This
that
affect
exposure
in
an
indoor
environment.
Source­
macroscopic
level,
well­
mixed
perspective
forms
the
basis
receptor
relationships
in
residential
exposure
scenarios
can
for
interpretation
of
measurement
data
as
well
as
simulation
be
complex
due
to
interactions
among
sources,
and
of
hypothetical
scenarios.
Exposure
assessment
models
on
transport/
transformation
processes
that
result
from
a
macroscopic
level
incorporate
important
physical
factors
chemical­
specific
and
building­
specific
factors.
Figure
17­
and
processes.
These
well­
mixed,
macroscopic
models
1
illustrates
the
complex
factors
that
must
be
considered
have
been
used
to
perform
indoor
air
quality
simulations
when
conducting
exposure
assessments
in
a
residential
(
Axley,
1989),
as
well
as
indoor
air
exposure
assessments
setting.
In
addition
to
sources
within
the
building,
(
McKone,
1989;
Ryan,
1991).
Nazzaroff
and
Cass
(
1986)
chemicals
of
concern
may
enter
the
indoor
environment
and
Wilkes
et
al.
(
1992)
have
used
code­
intensive
computer
from
outdoor
air,
soil,
gas,
water
supply,
tracked­
in
soil,
and
programs
featuring
finite
difference
or
finite
element
industrial
work
clothes
worn
by
the
residents.
Indoor
numerical
techniques
to
model
mass
balance.
A
simplified
concentrations
are
affected
by
loss
mechanisms,
also
approach
using
desk
top
spreadsheet
programs
has
been
illustrated
in
Figure
17­
1,
involving
chemical
reactions,
used
by
Jennings
et
al.
(
1985).
deposition
to
and
re­
emission
from
surfaces,
and
transport
out
of
the
building.
Particle­
bound
chemicals
can
enter
indoor
air
through
resuspension.
Indoor
air
concentrations
of
gas­
phase
organic
chemicals
are
affected
by
the
presence
of
reversible
sinks
formed
by
Volume
III
­
Activity
Factors
Chapter
17
­
Residential
Building
Characteristics
Page
Exposure
Factors
Handbook
17­
2
August
1997
In
order
to
model
mass
balance
of
indoor
waterborne
sources,
and
soil/
house
dust
sources.
Section
contaminants,
the
indoor
air
volume
is
represented
as
a
17.5
summarizes
advanced
concepts.
network
of
interconnected
zones.
Because
conditions
in
a
given
zone
are
determined
by
interactions
with
other
connecting
zones,
the
multizone
model
is
stated
as
a
system
of
simultaneous
equations.
The
mathematical
framework
for
modeling
indoor
air
has
been
reviewed
by
Sinden
(
1978)
and
Sandberg
(
1984).
Indoor
air
quality
models
typically
are
not
software
products
that
can
be
purchased
as
"
off­
the­
shelf"
items.
Most
existing
software
models
are
research
tools
that
have
been
developed
for
specific
purposes
and
are
being
continuously
refined
by
researchers.
Leading
examples
of
indoor
air
models
implemented
as
software
products
are
as
follows:

°
CONTAM
­­
developed
at
the
National
Institute
of
Standards
and
Technology
(
NIST)
with
support
from
U.
S.
EPA
and
the
U.
S.
Department
of
Energy
(
DOE)
(
Axley,
1988;
Grot,
1991;
Walton,
1993);

°
EXPOSURE
­­
developed
at
the
Indoor
Air
Branch
of
U.
S.
EPA
Air
and
Energy
Engineering
Research
Laboratory
(
EPA/
AEERL)
(
Sparks,
1988,
1991);

°
MCCEM
­­
the
Multi­
Chamber
Consumer
Exposure
Model
developed
for
U.
S
EPA
Office
of
Pollution
Prevention
and
Toxics
(
EPA/
OPPT)
(
GEOMET,
1989;
Koontz
and
Nagda,
1991);
and
°
THERdbASE
­­
the
Total
Human
Exposure
Relational
Data
Base
and
Advanced
Simulation
Environment
software
developed
by
researchers
at
the
Harry
Reid
Center
for
Environmental
Studies
at
University
Nevada,
Las
Vegas
(
UNLV)
(
Pandian
et
al.,
1993).

Section
17.2
of
this
chapter
summarizes
existing
data
on
building
characteristics
(
volumes,
surface
areas,
mechanical
systems,
and
types
of
foundations).
Section
17.3
summarizes
transport
phenomena
that
affect
chemical
transport
(
airflow,
chemical­
specific
deposition
and
filtration,
and
effects
of
water
supply
and
soil
tracking).
Section
17.4
provides
information
on
various
types
of
indoor
sources
associated
with
airborne
exposure,
17.2.
BUILDING
CHARACTERISTICS
17.2.1.
Key
Volumes
of
Residence
Studies
Versar
(
1990)
­
Database
on
Perfluorocarbon
Tracer
(
PFT)
Ventilation
Measurements
­
A
database
of
time­
averaged
air
exchange
and
interzonal
airflow
measurements
in
more
than
4,000
residences
has
been
compiled
by
Versar
(
1990)
to
allow
researchers
to
access
these
data
(
see
Section
17.3.2).
These
data
were
collected
between
1982
and
1987.
The
residences
that
appear
in
this
database
are
not
a
random
sample
of
U.
S.
homes;
however,
they
do
represent
a
compilation
of
homes
visited
in
about
100
different
field
studies,
some
of
which
involved
random
sampling.
In
each
study,
the
house
volumes
were
directly
measured
or
estimated.
The
collective
homes
visited
in
these
field
projects
are
not
geographically
balanced;
a
large
fraction
of
these
homes
are
located
in
southern
California.
Statistical
weighting
techniques
were
applied
in
developing
estimates
of
nationwide
distributions
(
see
Section
17.3.2)
to
compensate
for
the
geographic
imbalance.
U.
S.
DOE
(
1995)
­
Housing
Characteristics
1993,
Residential
Energy
Consumption
Survey
(
RECS)
­
Measurement
surveys
have
not
been
conducted
to
directly
characterize
the
range
and
distribution
of
volumes
for
a
random
sample
of
U.
S.
residences.
Related
data,
however,
are
regularly
collected
through
the
U.
S.
DOE's
RECS
(
U.
S.
DOE,
1995).
In
addition
to
collecting
information
on
energy
use,
this
triennial
survey
collects
data
on
housing
characteristics
including
direct
measurements
of
total
and
heated
floor
space
for
buildings
visited
by
survey
specialists.
For
the
most
recent
survey
(
1993),
a
multistage
probability
sample
of
over
7,000
residences
was
surveyed,
representing
96
million
residences
nationwide.
The
survey
response
rate
was
81.2
percent.
Volumes
were
estimated
from
the
RECS
measurements
by
multiplying
the
heated
floor
space
area
by
an
assumed
ceiling
height
of
8
feet,
recognizing
that
this
assumed
height
may
not
apply
universally
to
all
homes.
Results
for
residential
volume
distributions
from
the
RECS
(
Thompson,
1995)
are
presented
in
Table
17­
1.
Estimated
parameters
of
residential
volume
distributions
(
in
cubic
meters)
from
the
PFT
database
(
Versar,
1990)
are
also
summarized
in
Table
17­
1,
for
comparison
to
the
RECS
data.
The
arithmetic
means
from
the
two
sources
are
identical
(
369
cubic
meters).
The
medians
(
50th
percentiles)
are
very
similar:
310
cubic
meters
for
the
RECS
data,
and
321
cubic
meters
for
the
PFT
database.
Volume
III
­
Activity
Factors
Chapter
17
­
Residential
Building
Characteristics
Exposure
Factors
Handbook
Page
August
1997
17­
3
Figure
17­
2.
Cumulative
Frequency
Distributions
for
Residential
Volumes
from
the
PFT
Data
Base
and
the
U.
S.
DOE's
RECs.
Cumulative
frequency
distributions
from
the
two
sources
predominant
housing
type­­
single­
family
detached
homes­­
(
Figure
17­
2)
also
are
quite
similar,
especially
between
the
also
has
the
largest
average
volume
(
Table
17­
2).
50th
and
75th
percentiles.
Multifamily
units
and
mobile
homes
have
volumes
Table
17­
1.
Summary
of
Residential
Volume
Distributions
in
Cubic
Metersa
Parameter
RECS
PFT
Database
(
2)
Data
(
1)

Arithmetic
Mean
369
369
Standard
Deviation
258
209
10th
Percentile
147
167
25th
Percentile
209
225
50th
Percentile
310
321
75th
Percentile
476
473
90th
Percentile
672
575
In
cubic
meters
a
Sources:
(
1)
Thompson,
1995;
(
2)
Versar,
1990
The
RECS
also
provides
relationships
between
average
residential
floor
areas
and
factors
such
as
housing
type,
ownership,
household
size
and
structure
age.
The
averaging
about
half
that
of
single­
family
detached
homes,
with
single­
family
attached
homes
about
halfway
between
these
extremes.
Within
each
category
of
housing
type,
owner­
occupied
residences
average
about
50
percent
greater
volume
than
rental
units.
The
relationship
of
residential
volume
to
household
size
(
Table
17­
3)
is
of
particular
interest
for
purposes
of
exposure
assessment.
For
example,
one­
person
households
would
not
include
children,
and
the
data
in
the
table
indicate
that
multi­
person
households
occupy
residences
averaging
about
50
percent
greater
volume
than
residences
occupied
by
one­
person
households.
Volume
III
­
Activity
Factors
Chapter
17
­
Residential
Building
Characteristics
Page
Exposure
Factors
Handbook
17­
4
August
1997
Table
17­
2.
Average
Estimated
Volumes
of
U.
S.
Residences,
by
Housing
Type
and
Ownership
Ownership
Owner­
Occupied
Rental
All
Units
Housing
Type
(
m
)
of
Total
(
m
)
of
Total
(
m
)
of
Total
Volume
Percent
Volume
Percent
Volume
Percent
a
3
a
3
a
3
Single­
Family
471
53.1
323
8.5
451
61.7
(
Detached)

Single­
Family
406
4.6
291
2.9
362
7.5
(
Attached)

Multifamily
362
1.6
216
6.7
243
8.3
(
2­
4
units)

Multifamily
241
1.7
183
15.2
190
16.8
(
5+
Units)

Mobile
Home
221
4.6
170
1.2
210
5.8
All
Types
441
65.4
233
34.6
369
100.0
Volumes
calculated
from
floor
areas
assuming
a
ceiling
height
of
8
feet.
a
Source:
Adapted
from
U.
S.
DOE,
1995.

Table
17­
3.
Residential
Volumes
in
Relation
to
Household
Size
and
Year
of
Construction
Volumea
(
m
)
Percent
of
Total
3
Household
Size
1
Person
269
24.3
2
Persons
386
32.8
3
Persons
387
17.2
4
Persons
431
15.1
5
Persons
433
7.0
from
the
mean
of
369
m
given
in
Table
17­
1.
Murray's
6
or
More
Persons
408
3.6
All
Sizes
369
100.0
Year
of
Construction
1939
or
before
385
21.1
1940
to
1949
338
7.1
1950
to
1959
365
13.5
1960
to
1969
358
15.5
1970
to
1979
350
18.7
1980
to
1984
344
8.8
1985
to
1987
387
5.7
1988
to
1990
419
4.9
1991
to
1993
438
4.7
All
Years
369
100.0
Volumes
calculated
from
floor
areas
assuming
a
ceiling
height
a
of
8
feet.
Source:
U.
S.
DOE,
1995.

Data
on
year
of
construction
indicate
a
slight
decrease
in
residential
volumes
between
1950
and
1984,
followed
by
an
increasing
trend
over
the
next
decade.
A
ceiling
height
of
8
feet
was
assumed
in
estimating
the
average
volumes,
whereas
there
may
have
been
some
timerelated
trends
in
ceiling
height.
Murray
(
1996)
­
Analysis
of
RECS
and
PFT
Databases.
Using
a
database
from
the
1993
RECS
and
an
assumed
ceiling
height
of
8
feet,
Murray
(
1996)
estimated
a
mean
residential
volume
of
382
m
using
RECS
estimates
3
of
heated
floor
space.
This
estimate
is
slightly
different
3
(
1996)
sensitivity
analysis
indicated
that
when
a
fixed
ceiling
height
of
8
feet
was
replaced
with
a
randomly
varying
height
with
a
mean
of
8
feet,
there
was
little
effect
on
the
standard
deviation
of
the
estimated
distribution.
From
a
separate
analysis
of
the
PFT
database,
based
on
1,751
individual
household
measure­
ments,
Murray
(
1996)
estimated
an
average
volume
of
369
m
,
the
same
as
3
previously
given
in
Table
17­
1.
In
performing
this
analysis,
the
author
carefully
reviewed
the
PFT
database
in
an
effort
to
use
each
residence
only
once,
for
those
residences
thought
to
have
multiple
PFT
measurements.

17.2.2.
Volumes
and
Surface
Areas
of
Rooms
Room
Volumes
­
Volumes
of
individual
rooms
are
dependent
on
the
building
size
and
configuration,
but
summary
data
are
not
readily
available.
The
exposure
assessor
is
advised
to
define
specific
rooms,
or
assemblies
of
rooms,
that
best
fit
the
scenario
of
interest.
Most
models
for
predicting
indoor­
air
concentrations
specify
airflows
in
Volume
III
­
Activity
Factors
Chapter
17
­
Residential
Building
Characteristics
Exposure
Factors
Handbook
Page
August
1997
17­
5
Table
17­
4.
Dimensional
Quantities
for
Residential
Rooms
Nominal
Dimensions
Length
(
m)
Width
(
m)
Height
(
m)
Volume
(
m
)
3
Wall
Area
(
m
)
2
Floor
Area
(
m
)
2
Total
Area
(
m
)
2
Eight
Foot
Ceiling
12'
x15'
4.6
3.7
2.4
41
40
17
74
12'
x12'
3.7
3.7
2.4
33
36
13
62
10'
x12'
3.0
3.7
2.4
27
33
11
55
9'
x12'
2.7
3.7
2.4
24
31
10
51
6'
x12'
1.8
3.7
2.4
16
27
7
40
4'
x12'
1.2
3.7
2.4
11
24
4
32
Twelve
Foot
Ceiling
12'
x15'
4.6
3.7
3.7
61
60
17
94
12'
x12'
3.7
3.7
3.7
49
54
13
80
10'
x12'
3.0
3.7
3.7
41
49
11
71
9'
x12'
2.7
3.7
3.7
37
47
10
67
6'
x12'
1.8
3.7
3.7
24
40
7
54
4'
x12'
1.2
3.7
3.7
16
36
4
44
cubic
meters
per
hour
and,
correspondingly,
express
surface
area­
to­
volume,
or
loading
ratio.
Table
17­
4
volumes
in
cubic
meters.
A
measurement
in
cubic
feet
can
provides
the
basis
for
calculating
loading
ratios
for
typicalbe
converted
to
cubic
meters
by
multiplying
the
value
in
sized
rooms.
Constant
features
in
the
examples
are:
a
room
cubic
feet
by
0.0283
m
/
ft
.
For
example,
a
bedroom
that
is
width
of
12
feet
and
a
ceiling
height
of
8
feet
(
typical
for
3
3
9
feet
wide
by
12
feet
long
by
8
feet
high
has
a
volume
of
residential
buildings),
or
a
ceiling
height
12
feet
(
typical
for
864
cubic
feet
or
24.5
cubic
meters.
Similarly,
a
living
commercial
buildings).
The
loading
ratios
for
the
8­
foot
room
with
dimensions
of
12
feet
wide
by
20
feet
long
by
8
ceiling
height
range
from
0.98
m
m
to
2.18
m
m
for
wall
feet
high
has
a
volume
of
1920
cubic
feet
or
54.3
cubic
area
and
from
0.36
m
m
to
0.44
m
m
for
floor
area.
In
meters,
and
a
bathroom
with
dimensions
of
5
feet
by
12
feet
comparison,
ASTM
Standard
E
1333
(
ASTM,
1990),
for
by
8
feet
has
a
volume
of
480
cubic
feet
or
13.6
cubic
large­
chamber
testing
of
formaldehyde
levels
from
wood
meters.
products,
specifies
the
following
loading
ratios:
(
1)
0.95
Murray
(
1996)
analyzed
the
distribution
of
selected
m
m
for
testing
plywood
(
assumes
plywood
or
paneling
on
residential
zones
(
i.
e.,
a
series
of
connected
rooms)
using
all
four
walls
of
a
typical
size
room);
and
(
2)
0.43
m
m
for
the
PFT
database.
The
author
analyzed
the
"
kitchen
zone"
testing
particleboard
(
assumes
that
particleboard
decking
or
and
the
"
bedroom
zone"
for
houses
in
the
Los
Angeles
area
underlayment
would
be
used
as
a
substrate
for
the
entire
that
were
labeled
in
this
manner
by
field
researchers,
and
floor
of
a
structure).
"
basement,"
"
first
floor,"
and
"
second
floor"
zones
for
houses
outside
of
Los
Angeles
for
which
the
researchers
labeled
individual
floors
as
zones.
The
kitchen
zone
contained
the
kitchen
in
addition
to
any
of
the
following
associated
spaces:
utility
room,
dining
room,
living
room
and
family
room.
The
bedroom
zone
contained
all
the
bedrooms
plus
any
bathrooms
and
hallways
associated
with
the
bedrooms.
The
following
summary
statistics
(
mean
±
standard
deviation)
were
reported
by
Murray
(
1996)
for
the
volumes
of
the
zones
described
above:
199
±
115
m
for
3
the
kitchen
zone,
128
±
67
m
for
the
bedroom
zone,
205
±
3
64
m
for
the
basement,
233
±
72
m
for
the
first
floor,
and
3
3
233
±
111
m
for
the
second
floor.
3
Surface
Areas
­
The
surface
areas
of
floors
are
Table
17­
5
also
are
not
scaled
to
any
particular
residential
commonly
considered
in
relation
to
the
room
or
house
volume.
In
some
cases,
it
may
be
preferable
for
the
volume,
and
their
relative
loadings
are
expressed
as
a
exposure
assessor
to
use
professional
judgment
in
2
­
3
2
­
3
2
­
3
2
­
3
2
­
3
2
­
3
Products
and
Materials
­
Table
17­
5
presents
examples
of
assumed
amounts
of
selected
products
and
materials
used
in
constructing
or
finishing
residential
surfaces
(
Tucker,
1991).
Products
used
for
floor
surfaces
include
adhesive,
varnish
and
wood
stain;
and
materials
used
for
walls
include
paneling,
painted
gypsum
board,
and
wallpaper.
Particleboard
and
chipboard
are
commonly
used
for
interior
furnishings
such
as
shelves
or
cabinets,
but
could
also
be
used
for
decking
or
underlayment.
It
should
be
noted
that
numbers
presented
in
Table
17­
5
for
surface
area
are
based
on
typical
values
for
residences,
and
they
are
presented
as
examples.
In
contrast
to
the
concept
of
loading
ratios
presented
above
(
as
a
surface
area),
the
numbers
in
Volume
III
­
Activity
Factors
Chapter
17
­
Residential
Building
Characteristics
Page
Exposure
Factors
Handbook
17­
6
August
1997
combination
with
the
loading
ratios
given
above.
For
mixing.
Without
a
blower,
these
heaters
still
have
the
example,
if
the
exposure
scenario
involves
residential
ability
to
induce
mixing
through
convective
heat
transfer.
carpeting,
either
as
an
indoor
source
or
as
an
indoor
sink,
If
the
heater
is
a
source
of
combustion
pollutants,
as
with
then
the
ASTM
loading
ratio
of
0.43
m
m
for
floor
unvented
gas
or
kerosene
space
heaters,
then
the
2
­
3
materials
could
be
multiplied
by
an
assumed
residential
combination
of
convective
heat
transfer
and
thermal
volume
and
assumed
fractional
coverage
of
carpeting
to
buoyancy
of
combustion
products
will
result
in
fairly
rapid
derive
an
estimate
of
the
surface
area.
More
specifically,
a
dispersal
of
such
pollutants.
The
pollutants
will
disperse
residence
with
a
volume
of
300
m
,
a
loading
ratio
of
0.43
throughout
the
floor
where
the
heater
is
located
and
to
floors
3
m
m
and
coverage
of
80%
would
have
103
m
of
above
the
heater,
but
will
not
disperse
to
floors
below.
2
­
3
2
carpeting.
The
estimates
discussed
here
relate
to
Central
forced­
air
HAC
systems
are
common
in
macroscopic
surfaces;
the
true
surface
area
for
carpeting,
many
residences.
Such
systems,
through
a
network
of
for
example,
would
be
considerably
larger
because
of
the
supply/
return
ducts
and
registers,
can
achieve
fairly
nature
of
its
fibrous
material.
complete
mixing
within
20
to
30
minutes
(
Koontz
et
al.,

Table
17­
5.
Examples
of
Products
and
Materials
Associated
with
Floor
and
Wall
Surfaces
in
Residences
Material
Sources
Surface
Covered
Assumed
Amount
of
a
Silicone
caulk
0.2
m2
Floor
adhesive
10.0
m2
Floor
wax
50.0
m2
Wood
stain
10.0
m2
Polyurethane
wood
finish
10.0
m2
Floor
varnish
or
lacquer
50.0
m2
Plywood
paneling
100.0
m2
Chipboard
100.0
m2
Gypsum
board
100.0
m2
Wallpaper
100.0
m2
Based
on
typical
values
for
a
residence.
a
Source:
Adapted
from
Tucker,
1991.

Furnishings
­
Information
on
the
relative
abundance
of
specific
types
of
indoor
furnishings,
such
as
draperies
or
upholstered
furniture,
was
not
readily
available.
The
exposure
assessor
is
advised
to
rely
on
common
sense
and
professional
judgment.
For
example,
the
number
of
beds
in
a
residence
is
usually
related
to
household
size,
and
information
has
been
provided
(
Table
17­
3)
on
average
house
volume
in
relation
to
household
size.

17.2.3.
Mechanical
System
Configurations
Mechanical
systems
for
air
movement
in
residences
can
affect
the
migration
and
mixing
of
pollutants
released
indoors
and
the
rate
of
pollutant
removal.
Three
types
of
mechanical
systems
are:
(
1)
systems
associated
with
heating
and
air
conditioning
(
HAC);
(
2)
systems
whose
primary
function
is
providing
localized
exhaust;
and
(
3)
systems
intended
to
increase
the
overall
air
exchange
rate
of
the
residence.
Portable
space
heaters
intended
to
serve
a
single
room,
or
a
series
of
adjacent
rooms,
may
or
may
not
be
equipped
with
blowers
that
promote
air
movement
and
1988).
The
air
handler
for
such
systems
is
commonly
equipped
with
a
filter
(
see
Figure
17­
3)
that
can
remove
particle­
phase
contaminants.
Further
removal
of
particles,
via
deposition
on
various
room
surfaces
(
see
Section
17.3.2),
is
accomplished
through
increased
air
movement
when
the
air
handler
is
operating.
Figure
17­
3
also
distinguishes
forced­
air
HAC
systems
by
the
return
layout
in
relation
to
supply
registers.
The
return
layout
shown
in
the
upper
portion
of
the
figure
is
the
type
most
commonly
found
in
residential
settings.
On
any
floor
of
the
residence,
it
is
typical
to
find
one
or
more
supply
registers
to
individual
rooms,
with
one
or
two
centralized
return
registers.
With
this
layout,
supply/
return
imbalances
can
often
occur
in
individual
rooms,
particularly
if
the
interior
doors
to
rooms
are
closed.
In
comparison,
the
supply/
return
layout
shown
in
the
lower
portion
of
the
figure
by
design
tends
to
achieve
a
balance
in
individual
rooms
or
zones.
Airflow
imbalances
can
also
be
caused
by
inadvertent
duct
leakage
to
unconditioned
spaces
such
as
attics,
basements,
and
crawl
spaces.
Such
imbalances
usually
depressurize
the
house,
thereby
increasing
the
likelihood
of
contaminant
entry
via
soil­
gas
transport
or
through
spillage
of
combustion
products
from
vented
fossilfuel
appliances
such
as
fireplaces
and
gas/
oil
furnaces.
Mechanical
devices
such
as
kitchen
fans,
bathroom
fans,
and
clothes
dryers
are
intended
primarily
to
provide
localized
removal
of
unwanted
heat,
moisture,
or
odors.
Operation
of
these
devices
tends
to
increase
the
air
exchange
rate
between
the
indoors
and
outdoors.
Because
Volume
III
­
Activity
Factors
Chapter
17
­
Residential
Building
Characteristics
Exposure
Factors
Handbook
Page
August
1997
17­
7
Figure
17­
3.
Configuration
for
Residential
Forced­
air
Systems
local
exhaust
devices
are
designed
to
be
near
certain
indoor
basements
provide
some
resistance,
but
still
have
numerous
sources,
their
effective
removal
rate
for
locally
generated
pathways
for
soil­
gas
entry.
By
comparison,
homes
with
pollutants
is
greater
than
would
be
expected
from
the
crawl
spaces
open
to
the
outside
have
significant
dilution
effect
of
increased
air
exchange.
Operation
of
these
opportunities
for
dilution
of
soil
gases
prior
to
transport
into
devices
also
tends
to
depressurize
the
house,
because
the
house.
replacement
air
usually
is
not
provided
to
balance
the
exhausted
air.
An
alternative
approach
to
pollutant
removal
is
one
which
relies
on
an
increase
in
air
exchange
to
dilute
pollutants
generated
indoors.
This
approach
can
be
accomplished
using
heat
recovery
ventilators
(
HRVs)
or
energy
recovery
ventilators
(
ERVs).
Both
types
of
ventilators
are
designed
to
provide
balanced
supply
and
exhaust
airflows
and
are
intended
to
recover
most
of
the
energy
that
normally
is
lost
when
additional
outdoor
air
is
introduced.
Although
ventilators
can
provide
for
more
rapid
dilution
of
internally
generated
pollutants,
they
also
increase
the
rate
at
which
outdoor
pollutants
are
brought
into
the
house.
A
distinguishing
feature
of
the
two
types
is
that
ERVs
provide
for
recovery
of
latent
heat
(
moisture)
in
addition
to
sensible
heat.
Moreover,
ERVs
typically
recover
latent
heat
using
a
moisture­
transfer
device
such
as
a
desiccant
wheel.
It
has
been
observed
in
some
studies
that
the
transfer
of
moisture
between
outbound
and
inbound
air
streams
can
result
in
some
re­
entrainment
of
indoor
pollutants
that
otherwise
would
have
been
exhausted
from
the
house
(
Andersson
et
al.,
1993).
Inadvertent
air
communication
between
the
supply
and
exhaust
air
streams
can
have
a
similar
effect.
Studies
quantifying
the
effect
of
mechanical
devices
on
air
exchange
using
tracer­
gas
measurements
are
uncommon
and
typically
provide
only
anecdotal
data.
The
common
approach
is
for
the
expected
increment
in
the
air
exchange
rate
to
be
estimated
from
the
rated
airflow
capacity
of
the
device(
s).
For
example,
if
a
device
with
a
rated
capacity
of
100
cubic
feet
per
minute
(
cfm),
or
170
cubic
meters
per
hour,
is
operated
continuously
in
a
house
with
a
volume
of
400
cubic
meters,
then
the
expected
increment
in
the
air
exchange
rate
of
the
house
would
be
170
m
h
/
400
m
,
or
approximately
0.4
air
changes
per
3
­
1
3
hour.

17.2.4.
Type
of
Foundation
The
type
of
foundation
of
a
residence
is
of
interest
in
residential
exposure
assessment.
It
provides
some
indication
of
the
number
of
stories
and
house
configuration,
and
provides
an
indication
of
the
relative
potential
for
soilgas
transport.
For
example,
such
transport
can
occur
readily
in
homes
with
enclosed
crawl
spaces.
Homes
with
Lucas
et
al.
(
1992)
­
National
Residential
Radon
Survey
­
The
National
Resdental
Radon
Survey,
sponsored
by
the
U.
S.
EPA,
was
conducted
by
Lucas
et
al.
(
1992)
in
about
5,700
households
nationwide.
In
addition
to
radon
measurements,
information
on
a
number
of
housing
characteristics
was
collected,
including
whether
each
house
had
a
basement.
The
estimated
percentage
(
45.2
percent)
of
homes
in
the
U.
S.
having
basements
(
Table
17­
6)
from
this
survey
is
the
same
as
found
by
the
RECS
(
Table
17­
7).
Volume
III
­
Activity
Factors
Chapter
17
­
Residential
Building
Characteristics
Page
Exposure
Factors
Handbook
17­
8
August
1997
Table
17­
6.
Percent
of
Residences
with
Basement,
by
Census
Region
and
EPA
Region
Census
Region
Region
with
Basements
EPA
Percent
of
Residences
Northeast
1
93.4
Northeast
2
55.9
Northeast
3
67.9
South
4
19.3
Midwest
5
73.5
South
6
4.1
Midwest
7
75.3
West
8
68.5
West
9
10.3
West
10
11.5
All
Regions
45.2
Source:
Lucas
et
al.,
1992.

The
National
Residential
Radon
Survey
provides
data
for
more
refined
geographical
areas,
with
a
breakdown
by
the
10
EPA
Regions.
The
New
England
region
(
i.
e.,
EPA
Region
1),
which
includes
Connecticut,
Maine,
Massachusetts,
New
Hampshire,
Rhode
Island,
and
Vermont,
had
the
highest
prevalence
of
basements
(
93
percent).
The
lowest
prevalence
(
4
percent)
was
for
the
South
Central
region
(
i.
e.,
EPA
Region
6),
which
includes
Arkansas,
Louisiana,
New
Mexico,
Oklahoma,
and
Texas.
Table
17­
8
presents
the
States
associated
with
each
Census
Region
and
EPA
Region.
U.
S.
DOE
(
1995)
­
Housing
Characteristics
1993
­
Residential
Energy
Consumption
Survey
(
RECS)
­
The
most
recent
RECS
(
described
in
Section
17.2.1)
was
administered
in
1993
to
over
7,000
households
(
U.
S.
DOE,
1995).
The
type
of
information
requested
by
the
survey
questionnaire
included
the
type
of
foundation
for
the
residence
(
i.
e.,
basement,
enclosed
crawl
space,
crawl
space
open
to
outside
or
concrete
slab).
This
information
was
not
obtained
for
multifamily
structures
with
five
or
more
dwelling
units
or
for
mobile
homes.
Table
17­
7
presents
estimates
from
the
survey
of
the
percentage
of
residences
with
each
foundation
type,
by
census
region,
and
for
the
entire
U.
S.
The
percentages
can
add
to
more
than
100
percent
because
some
residences
have
more
than
one
type
of
foundation;
for
example,
most
split­
level
structures
have
a
partial
basement
combined
with
some
crawlspace
that
typically
is
enclosed.
The
data
in
Table
17­
7
indicate
that
close
to
half
(
45
percent)
of
residences
nationwide
have
a
basement,
and
that
fewer
than
10
percent
have
a
crawl
space
that
is
open
to
outside.
It
also
shows
that
a
large
fraction
of
homes
have
concrete
slabs
(
31
percent).
There
are
also
variations
by
census
region.
For
example,
nearly
80
percent
of
the
residences
in
the
Northeast
and
Midwest
regions
have
basements.
In
the
South
and
West
regions,
the
predominant
foundation
types
are
concrete
slabs
and
enclosed
crawl
spaces.
Table
17­
8
illustrates
the
four
Census
Regions.

17.3.
TRANSPORT
RATES
17.3.1.
Background
Major
air
transport
pathways
for
airborne
substances
in
residences
include
the
following:

°
Air
exchange
­
Air
leakage
through
windows,
doorways,
intakes
and
exhausts,
and
"
adventitious
openings"
(
i.
e.,
cracks
and
seams)
that
combine
to
form
the
leakage
configuration
of
the
building
envelope
plus
natural
and
mechanical
ventilation;

°
Interzonal
airflows
­
Transport
through
doorways,
ductwork,
and
service
chaseways
that
interconnect
rooms
or
zones
within
a
building;
and
°
Local
circulation
­
Convective
and
advective
air
circulation
and
mixing
within
a
room
or
within
a
zone.

The
distribution
of
airflows
across
the
building
envelope
that
contribute
to
air
exchange
and
the
interzonal
airflows
along
interior
flowpaths
is
determined
by
the
interior
pressure
distribution.
The
forces
causing
the
airflows
are
temperature
differences,
the
actions
of
wind,
and
mechanical
ventilation
systems.
Basic
concepts
have
been
reviewed
by
ASHRAE
(
1993).
Indoor­
outdoor
and
room­
to­
room
temperature
differences
create
density
differences
that
help
determine
basic
patterns
of
air
motion.
During
the
heating
season,
warmer
indoor
air
tends
to
rise
to
exit
the
building
at
upper
levels
by
stack
action.
Exiting
air
is
replaced
at
lower
levels
by
an
influx
of
colder
outdoor
air.
During
the
cooling
season,
this
pattern
is
reversed:
stack
forces
during
the
cooling
season
are
generally
not
as
strong
as
in
the
heating
season
because
the
indoor­
outdoor
temperature
differences
are
not
pronounced.
In
examining
a
data
base
of
air
leakage
measurements,
Sherman
and
Dickerhoff
(
1996)
observed
that
houses
built
prior
to
1980
showed
a
clear
increase
in
leakage
with
increasing
age
and
were
leakier,
on
average,
Volume
III
­
Activity
Factors
Chapter
17
­
Residential
Building
Characteristics
Exposure
Factors
Handbook
Page
August
1997
17­
9
Table
17­
7.
Percent
of
Residences
with
Certain
Foundation
Types
by
Census
Region
Census
Region
Percent
of
Residencesa
With
With
With
Crawlspace
With
Basement
Enclosed
Crawlspace
Open
to
Outside
Concrete
Slab
Northeast
78.0
12.6
2.8
15.8
Midwest
78.1
19.5
5.6
14.7
South
18.6
31.8
11.0
44.6
West
19.4
36.7
8.1
43.5
All
Regions
45.2
26.0
7.5
31.3
Percentage
may
add
to
more
than
100
percent
because
more
than
one
foundation
type
may
apply
to
a
given
residence.
a
Source:
U.
S.
DOE,
1995.

Table
17­
8.
States
Associated
with
EPA
Regions
and
Census
Regions
US
EPA
Regions
Region
1
Region
4
Region
6
Region
9
Connecticut
Alabama
Arkansas
Arizona
Maine
Florida
Louisiana
California
Massachusetts
Georgia
New
Mexico
Hawaii
New
Hampshire
Kentucky
Oklahoma
Nevada
Rhode
Island
Mississippi
Texas
Vermont
North
Carolina
Region
10
Region
2
Tennessee
Iowa
Idaho
New
Jersey
Kansas
Oregon
New
York
Region
5
Missouri
Washington
Region
3
Indiana
Delaware
Michigan
Region
8
District
of
Columbia
Minnesota
Colorado
Maryland
Ohio
Montana
Pennsylvania
Wisconsin
North
Dakota
Virginia
South
Dakota
West
Virginia
Utah
South
Carolina
Region
7
Alaska
Illinois
Nebraska
Wyoming
US
Bureau
of
Census
Regions
Northeast
Region
Midwest
Region
South
Region
West
Region
Connecticut
Illinois
Alabama
Alaska
Maine
Indiana
Arkansas
Arizona
Massachusetts
Iowa
Delaware
California
New
Hampshire
Kansas
District
of
Columbia
Colorado
New
Jersey
Michigan
Florida
Hawaii
New
York
Minnesota
Georgia
Idaho
Pennsylvania
Missouri
Kentucky
Montana
Rhode
island
Nebraska
Louisiana
Nevada
Vermont
North
Dakota
Maryland
New
Mexico
Ohio
Mississippi
Oregon
South
Dakota
North
Carolina
Utah
Wisconsin
Oklahoma
Washington
South
Carolina
Wyoming
Tennessee
Texas
Virginia
West
Virginia
Volume
III
­
Activity
Factors
Chapter
17
­
Residential
Building
Characteristics
Page
Exposure
Factors
Handbook
17­
10
August
1997
than
newer
houses.
They
further
observed
that
the
post­
years,
there
has
been
a
diversity
of
protocols
and
study
1980
houses
did
not
show
any
trend
in
leakiness
with
age.
objectives.
Since
the
early
1980s,
however,
an
inexpensive
The
position
of
the
neutral
pressure
level
(
i.
e.,
the
perfluorocarbon
tracer
(
PFT)
technique
has
been
used
to
point
where
indoor­
outdoor
pressures
are
equal)
depends
on
measure
time­
averaged
air
exchange
and
interzonal
airflows
the
leakage
configuration
of
the
building
envelope.
The
in
thousands
of
occupied
residences
using
essentially
stack
effect
arising
from
indoor­
outdoor
temperature
similar
protocols
(
Dietz
et
al.,
1986).
The
PFT
technique
differences
is
also
influenced
by
the
partitioning
of
the
utilizes
miniature
permeation
tubes
as
tracer
emitters
and
building
interior.
When
there
is
free
communication
passive
samplers
to
collect
the
tracers.
The
passive
between
floors
or
stories,
the
building
behaves
as
a
single
samplers
are
returned
to
the
laboratory
for
analysis
by
gas
volume
affected
by
a
generally
rising
current
during
the
chromatography.
These
measurement
results
have
been
heating
season
and
a
generally
falling
current
during
the
compiled
to
allow
various
researchers
to
access
the
data
cooling
season.
When
vertical
communication
is
restricted,
(
Versar,
1990).
each
level
essentially
becomes
an
independent
zone.
As
the
wind
flows
past
a
building,
regions
of
positive
and
negative
pressure
(
relative
to
indoors)
are
created
within
the
building;
positive
pressures
induce
an
influx
of
air,
whereas
negative
pressures
induce
an
outflow.
Wind
effects
and
stack
effects
combine
to
determine
a
net
inflow
or
outflow.
The
final
element
of
indoor
transport
involves
the
actions
of
mechanical
ventilation
systems
that
circulate
indoor
air
through
the
use
of
fans.
Mechanical
ventilation
systems
may
be
connected
to
heating/
cooling
systems
that,
depending
on
the
type
of
building,
recirculate
thermally
treated
indoor
air
or
a
mixture
of
fresh
air
and
recirculated
air.
Mechanical
systems
also
may
be
solely
dedicated
to
exhausting
air
from
a
designated
area,
as
with
some
kitchen
range
hoods
and
bath
exhausts,
or
to
recirculating
air
in
designated
areas
as
with
a
room
fan.
Local
air
circulation
also
is
influenced
by
the
movement
of
people
and
the
operation
of
local
heat
sources.

17.3.2.
Air
Exchange
Rates
standard
deviation
of
2.01.
Air
exchange
is
the
balanced
flow
into
and
out
of
a
building,
and
is
composed
of
three
processes:
(
1)
infiltration
­
air
leakage
through
random
cracks,
interstices,
and
other
unintentional
openings
in
the
building
envelope;
(
2)
natural
ventilation
­
airflows
through
open
windows,
doors,
and
other
designed
openings
in
the
building
envelope;
and
(
3)
forced
or
mechanical
ventilation
­
controlled
air
movement
driven
by
fans.
For
nearly
all
indoor
exposure
scenarios,
air
exchange
is
treated
as
the
principal
means
of
diluting
indoor
concentrations.
The
air
exchange
rate
is
generally
expressed
in
terms
of
air
changes
per
hour
(
ACH,
with
units
of
h
),
the
ratio
of
the
airflow
­
1
(
m
h
)
to
the
volume
(
m
).
3
­
1
3
No
measurement
surveys
have
been
conducted
to
directly
evaluate
the
range
and
distribution
of
residential
air
exchange
rates.
Although
a
significant
number
of
air
exchange
measurements
have
been
carried
out
over
the
Nazaroff
et
al.
(
1988)
­
Prior
to
the
Koontz
and
Rector
(
1995)
study,
Nazaroff
et
al.
(
1988)
aggregated
the
data
from
two
studies
conducted
earlier
using
tracer­
gas
decay.
At
the
time
these
studies
were
conducted,
they
were
the
largest
U.
S.
studies
to
include
air
exchange
measurements.
The
first
(
Grot
and
Clark,
1981)
was
conducted
in
255
dwellings
occupied
by
low­
income
families
in
14
different
cities.
The
geometric
mean
±
standard
deviation
for
the
air
exchange
measurements
in
these
homes,
with
a
median
house
age
of
45
years,
was
0.90
±
2.13
ACH.
The
second
study
(
Grimsrud
et
al.,
1983)
involved
312
newer
residences,
with
a
median
age
of
less
than
10
years.
Based
on
measurements
taken
during
the
heating
season,
the
geometric
mean
±
standard
deviation
for
these
homes
was
0.53
±
1.71
ACH.
Based
on
an
aggregation
of
the
two
distributions
with
proportional
weighting
by
the
respective
number
of
houses
studied,
Nazaroff
et
al.
(
1988)
developed
an
overall
distribution
with
a
geometric
mean
of
0.68
ACH
and
a
geometric
Versar
(
1990)
­
Database
of
PFT
Ventilation
Measurements
­
The
residences
included
in
the
PFT
database
do
not
constitute
a
random
sample
across
the
United
States.
They
represent
a
compilation
of
homes
visited
in
the
course
of
about
100
separate
field­
research
projects
by
various
organizations,
some
of
which
involved
random
sampling
and
some
of
which
involved
judgmental
or
fortuitous
sampling.
The
larger
projects
in
the
PFT
database
are
summarized
in
Table
17­
9,
in
terms
of
the
number
of
measurements
(
samples),
states
where,
and
months
when,
samples
were
taken,
and
summary
statistics
for
their
respective
distributions
of
measured
air
exchange
rates.
For
selected
projects
(
LBL,
RTI,
SOCAL),
multiple
measurements
were
taken
for
the
same
house,
usually
during
different
seasons.
A
large
majority
of
the
Volume
III
­
Activity
Factors
Chapter
17
­
Residential
Building
Characteristics
Exposure
Factors
Handbook
Page
August
1997
17­
11
Table
17­
9.
Summary
of
Major
Projects
Providing
Air
Exchange
Measurements
in
the
PFT
Database
Project
Code
State
Month(
s)
Measurements
Exchange
Rate
SD
a
Number
of
Mean
Air
Percentiles
b
10th
25th
50th
75th
90th
ADM
CA
5­
7
29
0.70
0.52
0.29
0.36
0.48
0.81
1.75
BSG
CA
1,8­
12
40
0.53
0.30
0.21
0.30
0.40
0.70
0.90
GSS
AZ
1­
3,8­
9
25
0.39
0.21
0.16
0.23
0.33
0.49
0.77
FLEMING
NY
1­
6,8­
12
56
0.24
0.28
0.05
0.12
0.22
0.29
0.37
GEOMET1
FL
1,6­
8,10­
12
18
0.31
0.16
0.15
0.18
0.25
0.48
0.60
GEOMET2
MD
1­
6
23
0.59
0.34
0.12
0.29
0.65
0.83
0.92
GEOMET3
TX
1­
3
42
0.87
0.59
0.33
0.51
0.71
1.09
1.58
LAMBERT1
ID
2­
3,10­
11
36
0.25
0.13
0.10
0.17
0.23
0.33
0.49
LAMBERT2
MT
1­
3,11
51
0.23
0.15
0.10
0.14
0.19
0.26
0.38
LAMBERT3
OR
1­
3,10­
12
83
0.46
0.40
0.19
0.26
0.38
0.56
0.80
LAMBERT4
WA
1­
3,10­
12
114
0.30
0.15
0.14
0.20
0.30
0.39
0.50
LBL1
OR
1­
4,10­
12
126
0.56
0.37
0.28
0.35
0.45
0.60
1.02
LBL2
WA
1­
4,10­
12
71
0.36
0.19
0.18
0.25
0.32
0.42
0.52
LBL3
ID
1­
5,11­
12
23
1.03
0.47
0.37
0.73
0.99
1.34
1.76
LBL4
WA
1­
4,11­
12
29
0.39
0.27
0.14
0.18
0.36
0.47
0.63
LBL5
WA
2­
4
21
0.36
0.21
0.13
0.19
0.30
0.47
0.62
LBL6
ID
3­
4
19
0.28
0.14
0.11
0.17
0.26
0.38
0.55
NAHB
MN
1­
5,9­
12
28
0.22
0.11
0.11
0.16
0.20
0.24
0.38
NYSDH
NY
1­
2,4,12
74
0.59
0.37
0.28
0.37
0.50
0.68
1.07
PEI
MD
3­
4
140
0.59
0.45
0.15
0.26
0.49
0.83
1.20
PIERCE
CT
1­
3
25
0.80
1.14
0.20
0.22
0.38
0.77
2.35
RTI1
CA
2
45
0.90
0.73
0.38
0.48
0.78
1.08
1.52
RTI2
CA
7
41
2.77
2.12
0.79
1.18
2.31
3.59
5.89
RTI3
NY
1­
4
397
0.55
0.37
0.26
0.33
0.44
0.63
0.94
SOCAL1
CA
3
551
0.81
0.66
0.29
0.44
0.66
0.94
1.43
SOCAL2
CA
7
408
1.51
1.48
0.35
0.59
1.08
1.90
3.11
SOCAL3
CA
1
330
0.76
1.76
0.26
0.37
0.48
0.75
1.11
UMINN
MN
1­
4
35
0.36
0.32
0.17
0.20
0.28
0.40
0.56
UWISC
WI
2­
5
57
0.82
0.76
0.22
0.33
0.55
1.04
1.87
1
=
January,
2
=
February,
etc.
a
Standard
deviation
b
Source:
Adapted
from
Versar,
1990.

measurements
are
from
the
SOCAL
project
that
was
such
a
way
that
the
resultant
number
of
cases
would
conducted
in
Southern
California.
The
means
of
the
represent
each
state
in
proportion
to
its
share
of
occupied
respective
studies
generally
range
from
0.2
to
1.0
ACH,
housing
units,
as
determined
from
the
1990
U.
S.
Census
of
with
the
exception
of
two
California
projects­­
RTI2
and
Population
and
Housing.
SOCAL2.
Both
projects
involved
measurements
in
Summary
statistics
from
the
Koontz
and
Rector
Southern
California
during
a
time
of
year
(
July)
when
(
1995)
analysis
are
shown
in
Table
17­
10,
for
the
country
windows
would
likely
be
opened
by
many
occupants.
as
a
whole
and
by
census
regions.
Based
on
the
statistics
Koontz
and
Rector
(
1995)
­
Estimation
of
Distributions
for
Residential
Air
Exchange
Rates
­
In
analyzing
the
composite
data
from
various
projects
(
2,971
measurements),
Koontz
and
Rector
(
1995)
assigned
weights
to
the
results
from
each
state
to
compensate
for
the
geographic
imbalance
in
locations
where
PFT
measurements
were
taken.
The
results
were
weighted
in
for
all
regions
combined,
the
authors
suggested
that
a
10th
percentile
value
of
0.18
ACH
would
be
appropriate
as
a
conservative
estimator
for
air
exchange
in
residential
settings,
and
that
the
50th
percentile
value
of
0.45
ACH
would
be
appropriate
as
a
typical
air
exchange
rate.
In
applying
conservative
or
typical
values
of
air
exchange
rates,
it
is
important
to
realize
the
limitations
of
the
Volume
III
­
Activity
Factors
Chapter
17
­
Residential
Building
Characteristics
Page
Exposure
Factors
Handbook
17­
12
August
1997
Table
17­
10.
Summary
Statistics
for
Air
Exchange
Rates
(
air
changes
per
hour­
ACH),
by
Region
West
Region
North
Central
Region
Northeast
Region
South
Region
All
Regions
Arithmetic
Mean
0.66
0.57
0.71
0.61
0.63
Arithmetic
Standard
Deviation
0.87
0.63
0.60
0.51
0.65
Geometric
Mean
0.47
0.39
0.54
0.46
0.46
Geometric
Standard
Deviation
2.11
2.36
2.14
2.28
2.25
10th
Percentile
0.20
0.16
0.23
0.16
0.18
50th
Percentile
0.43
0.35
0.49
0.49
0.45
90th
Percentile
1.25
1.49
1.33
1.21
1.26
Maximum
23.32
4.52
5.49
3.44
23.32
Source:
Koontz
and
Rector,
1995.
underlying
data
base.
Although
the
estimates
are
based
on
and
February
were
defined
as
winter,
March,
April
and
May
thousands
of
measurements,
the
residences
represented
in
were
defined
as
spring,
and
so
on.
The
results
of
Murray
the
database
are
not
a
random
sample
of
the
United
States
and
Burmaster
(
1995)
are
summarized
in
Table
17­
11.
housing
stock.
The
sample
population
is
not
balanced
in
Neglecting
the
summer
results
in
the
colder
regions
which
terms
of
geography
or
time
of
year.
Statistical
techniques
have
only
a
few
observations,
the
results
indicate
that
the
were
applied
to
compensate
for
some
of
these
imbalances.
highest
air
exchange
rates
occur
in
the
warmest
climate
In
addition,
PFT
measurements
of
air
exchange
rates
region
during
the
summer.
As
noted
earlier
(
Section
assume
uniform
mixing
of
the
tracer
within
the
building.
17.3.2),
many
of
the
measurements
in
the
warmer
climate
This
is
not
always
so
easily
achieved.
Furthermore,
the
region
were
from
field
studies
conducted
in
Southern
degree
of
mixing
can
vary
from
day
to
day
and
house
to
California
during
a
time
of
year
(
July)
when
windows
would
house
because
of
the
nature
of
the
factors
controlling
mixing
tend
to
be
open
in
that
area.
Data
for
this
region
in
(
e.
g.,
convective
air
monitoring
driven
by
weather,
and
type
particular
should
be
used
with
caution
since
other
areas
and
operation
of
the
heating
system).
The
relative
within
this
region
tend
to
have
very
hot
summers
and
placement
of
the
PFT
source
and
the
sampler
can
also
cause
residences
use
air
conditioners,
resulting
in
lower
air
variability
and
uncertainty.
It
should
be
noted
that
sampling
exchange
rates.
The
lowest
rates
generally
occur
in
the
is
typically
done
in
a
single
location
in
a
house
which
may
colder
regions
during
the
fall
(
Table
17­
11).
not
represent
the
average
from
that
house.
In
addition,
very
high
and
very
low
values
of
air
exchange
rates
based
on
PFT
measurements
have
greater
uncertainties
than
those
in
A
variety
of
mathematical
models
exist
for
prediction
the
middle
of
the
distribution.
Despite
such
limitations,
the
of
air
infiltration
rates
in
individual
buildings.
A
number
of
estimates
in
Table
17­
10
are
believed
to
represent
the
best
these
models
have
been
reviewed,
for
example,
by
available
information
on
the
distribution
of
air
exchange
Liddament
and
Allen
(
1983),
and
by
Persily
and
Linteris
rates
across
United
States
residences
throughout
the
year.
(
1984).
Basic
principles
are
concisely
summarized
in
the
Murray
and
Burmaster
(
1995)
­
Residential
Air
Exchange
Rates
in
the
United
States:
Empirical
and
Estimated
Parametric
Distributions
by
Season
and
Climatic
Region
­
Murray
and
Burmaster
(
1995)
analyzed
the
PFT
database
using
2,844
measurements
(
essentially
the
same
cases
as
analyzed
by
Koontz
and
Rector
(
1995),
but
without
the
compensating
weights).
These
authors
summarized
distributions
for
subsets
of
the
data
defined
by
climate
region
and
season.
The
coldest
region
was
defined
as
having
7,000
or
more
heating
degree
days,
the
colder
region
as
5,500­
6,999
degree
days,
the
warmer
region
as
2,500­
5,499
degree
days,
and
the
warmest
region
as
fewer
than
2,500
degree
days.
The
months
of
December,
January
17.3.3.
Infiltration
Models
ASHRAE
Handbook
of
Fundamentals
(
ASHRAE,
1993).
These
models
have
a
similar
theoretical
basis;
all
address
indoor­
outdoor
pressure
differences
that
are
maintained
by
the
actions
of
wind
and
stack
(
temperature
difference)
effects.
The
models
generally
incorporate
a
network
of
airflows
where
nodes
representing
regions
of
different
pressure
are
interconnected
by
leakage
paths.
Individual
models
differ
in
details
such
as
the
number
of
nodes
they
A
'
a
%
b
*
T
i
&
T
o
*
%
cU
n
A
'
L
0.006
)
T
%
0.03
C
U1.5
Volume
III
­
Activity
Factors
Chapter
17
­
Residential
Building
Characteristics
Exposure
Factors
Handbook
Page
August
1997
17­
13
Table
17­
11.
Distributions
of
Residential
Air
Exchange
Rates
by
Climate
Region
and
Season
a
Climate
Region
Season
Sample
Size
Arithmetic
Mean
Standard
Deviation
Percentiles
10th
25th
50th
75th
90th
Coldest
Winter
Spring
Summer
Fall
161
254
5
47
0.36
0.44
0.82
0.25
0.28
0.31
0.69
0.12
0.11
0.18
0.27
0.10
0.18
0.24
0.41
0.15
0.27
0.36
0.57
0.22
0.48
0.53
1.08
0.34
0.71
0.80
2.01
0.42
Colder
Winter
Spring
Summer
Fall
428
43
2
23
0.57
0.52
1.31
0.35
0.43
0.91
­­
0.18
0.21
0.13
­­
0.15
0.30
0.21
­­
0.22
0.42
0.24
­­
0.33
0.69
0.39
­­
0.41
1.18
0.83
­­
0.59
Warmer
Winter
Spring
Summer
Fall
96
165
34
37
0.47
0.59
0.68
0.51
0.40
0.43
0.50
0.25
0.19
0.18
0.27
0.30
0.26
0.28
0.36
0.30
0.39
0.48
0.51
0.44
0.58
0.82
0.83
0.60
0.78
1.11
1.30
0.82
Warmest
Winter
Spring
Summer
Fall
454
589
488
18
0.63
0.77
1.57
0.72
0.52
0.62
1.56
1.43
0.24
0.28
0.33
0.22
0.34
0.42
0.58
0.25
0.48
0.63
1.10
0.42
0.78
0.92
1.98
0.46
1.13
1.42
3.28
0.74
In
air
changes
per
hour
a
Source:
Murray
and
Burmaster,
1995.

(
Eqn.
17­
1)

where:
A
=
air
infiltration
rate
(
h
)
­
1
T
=
indoor
temperature
(
E
C)
i
T
=
outdoor
temperature
(
E
C)
o
U
=
windspeed
(
ms
)
­
1
n
is
an
exponent
with
a
value
typically
between
1
and
2
a,
b
and
c
are
parameters
to
be
estimated
(
Eqn.
17­
2)

where:
A
=
average
air
changes
per
hour
or
infiltration
rate,
h­
1
L
=
generalized
house
leakiness
factor
(
1
<
L
<
5)
C
=
terrain
sheltering
factor
(
1
<
C
<
10)
)
T
=
indoor­
outdoor
temperature
difference
(
C
E
)
U
=
windspeed
(
ms
)
­
1
can
treat
or
the
specifics
of
leakage
paths
(
e.
g.,
individual
estimates
for
making
such
predictions.
components
such
as
cracks
around
doors
or
windows
versus
A
reasonable
compromise
between
the
theoretical
a
combination
of
components
such
as
an
entire
section
of
a
and
empirical
approaches
has
been
developed
in
the
model
building).
Such
models
are
not
easily
applied
by
exposure
specified
by
Dietz
et
al.
(
1986).
The
model,
drawn
from
assessors,
however,
because
the
required
inputs
(
e.
g.,
correlation
analysis
of
environmental
measurements
and
air
inferred
leakage
areas,
crack
lengths)
for
the
model
are
not
infiltration
data,
is
formulated
as
follows:
easy
to
gather.
Another
approach
for
estimating
air
infiltration
rates
is
developing
empirical
models.
Such
models
generally
rely
on
collection
of
infiltration
measurements
in
a
specific
building
under
a
variety
of
weather
conditions.
The
relationship
between
the
infiltration
rate
and
weather
conditions
can
then
be
estimated
through
regression
analysis,
and
is
usually
stated
in
the
following
form:

Relatively
good
predictive
accuracy
usually
can
be
conditions
where
the
indoor
temperature
is
20
E
C
(
68
E
F),
obtained
for
individual
buildings
through
this
approach.
the
outdoor
temperature
is
0
E
C
(
32
E
F)
and
the
windspeed
However,
exposure
assessors
often
do
not
have
the
is
5
ms
,
the
predicted
infiltration
rate
for
that
house
would
information
resources
required
to
develop
parameter
be
3
(
0.006
x
20
+
0.03/
5
x
51.5),
or
0.56
air
changes
per
The
value
of
L
is
greater
as
house
leakiness
increases
and
the
value
of
C
is
greater
as
terrain
sheltering
(
reflects
shielding
of
nearby
wind
barrier)
increases.
Although
the
above
model
has
not
been
extensively
validated,
it
has
intuitive
appeal
and
it
is
possible
for
the
user
to
develop
reasonable
estimates
for
L
and
C
with
limited
guidance.
Historical
data
from
various
U.
S.
airports
are
available
for
estimation
of
the
temperature
and
windspeed
parameters.
As
an
example
application,
consider
a
house
that
has
central
values
of
3
and
5
for
L
and
C,
respectively.
Under
­
1
Volume
III
­
Activity
Factors
Chapter
17
­
Residential
Building
Characteristics
Page
Exposure
Factors
Handbook
17­
14
August
1997
Figure
17­
4.
Idealized
Patterns
of
Particle
Deposition
Indoors
Source:
Adapted
from
Nazaroff
and
Cass,
1989.
hour.
This
prediction
applies
under
the
condition
that
air
exchange.
Theoretical
considerations
specific
to
indoor
exterior
doors
and
windows
are
closed,
and
does
not
include
environments
have
been
summarized
in
comprehensive
the
contributions,
if
any,
from
mechanical
systems
(
see
reviews
by
Nazaroff
and
Cass
(
1989)
and
Nazaroff
et
al.
Section
17.2.3).
Occupant
behavior,
such
as
opening
(
1993).
windows,
can,
of
course,
overwhelm
the
idealized
effects
of
For
airborne
particles,
deposition
rates
depend
on
temperature
and
wind
speed.
aerosol
properties
(
size,
shape,
density)
as
well
as
room
17.3.4.
Deposition
and
Filtration
Deposition
refers
to
the
removal
of
airborne
gravitational
settling;
the
motions
of
smaller
particles
are
substances
to
available
surfaces
that
occurs
as
a
result
of
subject
to
convection
and
diffusion.
Consequently,
larger
gravitational
settling
and
diffusion,
as
well
as
particles
tend
to
accumulate
more
rapidly
on
floors
and
upelectrophoresis
and
thermophoresis.
Filtration
is
driven
by
facing
surfaces
while
smaller
particles
may
accumulate
on
similar
processes,
but
is
confined
to
material
through
which
surfaces
facing
in
any
direction.
Figure
17­
4
illustrates
the
air
passes.
Filtration
is
usually
a
matter
of
design,
whereas
general
trend
for
particle
deposition
across
the
size
range
of
deposition
is
a
matter
of
fact.
general
concern
for
inhalation
exposure
(<
10
F
m).
The
17.3.4.1.
Deposition
The
deposition
of
particulate
matter
and
reactive
gas­
knowledge
gaps
relating
to
near­
surface
air
motions
and
phase
pollutants
to
indoor
surfaces
is
often
stated
in
terms
other
sources
of
inhomogeneity
(
Nazaroff
et
al.,
1993).

of
a
characteristic
deposition
velocity
(
m
h
)
allied
to
the
­
1
surface­
to­
volume
ratio
(
m
m
)
of
the
building
or
room
2
­
3
interior,
forming
a
first
order
loss
rate
(
h
)
similar
to
that
of
­
1
factors
(
thermal
gradients,
turbulence,
surface
geometry).
The
motions
of
larger
particles
are
dominated
by
current
thought
is
that
theoretical
calculations
of
deposition
rates
are
likely
to
provide
unsatisfactory
results
due
to
Wallace
(
1996)
­
Indoor
Particles:
A
Review
­
In
a
major
review
of
indoor
particles,
Wallace
(
1996)
cited
overall
particle
deposition
rates
for
respirable
(
PM
),
2.5
Volume
III
­
Activity
Factors
Chapter
17
­
Residential
Building
Characteristics
Exposure
Factors
Handbook
Page
August
1997
17­
15
inhalable
(
PM
),
and
coarse
(
difference
between
PM
and
10
10
PM
)
size
fractions
determined
from
EPA's
PTEAM
study.
Residential
structures
consist
of
a
number
of
rooms
2.5
These
values,
listed
in
Table
17­
12,
were
derived
from
that
may
be
connected
horizontally,
vertically,
or
both
measurements
conducted
in
nearly
200
residences.
horizontally
and
vertically.
Before
considering
residential
Table
17­
12.
Deposition
Rates
for
Indoor
Particles
Size
Fraction
Deposition
Rate
PM
0.39
h
2.5
PM
0.65
h
10
Coarse
1.0
h
­
1
­
1
­
1
Source:
Adapted
from
Wallace,
1996.

Thatcher
and
Layton
(
1995)
­
Deposition,
Resuspension,
and
Penetration
of
Particles
Within
a
Residence
­
Thatcher
and
Layton
(
1995)
evaluated
removal
rates
for
indoor
particles
in
four
size
ranges
(
1­
5,
5­
10,
10­
25,
and
>
25
F
m)
in
a
study
of
one
house
occupied
by
a
family
of
four.
These
values
are
listed
in
Table
17­
13.
In
a
subsequent
evaluation
of
data
collected
in
100
Dutch
residences,
Layton
and
Thatcher
(
1995)
estimated
settling
velocities
of
2.7
m
h
for
lead­
bearing
particles
captured
in
­
1
total
suspended
particulate
matter
(
TSP)
samples.

Table
17­
13.
Particle
Deposition
During
Normal
Activities
Particle
Size
Range
Particle
Removal
Rate
(
h
)
­
1
1­
5
0.5
5­
10
1.4
10­
25
2.4
>
25
4.1
Source:
Adapted
from
Thatcher
and
Layton,
1995.

17.3.4.2.
Filtration
A
variety
of
air
cleaning
techniques
have
been
applied
to
residential
settings.
Basic
principles
related
to
residential­
scale
air
cleaning
technologies
have
been
summarized
in
conjunction
with
reporting
early
test
results
(
Offerman
et
al.,
1984).
General
engineering
principles
are
summarized
in
ASHRAE
(
1988).
In
addition
to
fibrous
filters
integrated
into
central
heating
and
air
conditioning
systems,
extended
surface
filters
and
High
Efficiency
Particle
Arrest
(
HEPA)
filters
as
well
as
electrostatic
systems
are
available
to
increase
removal
efficiency.
Freestanding
air
cleaners
(
portable
and/
or
console)
are
also
being
used.
Product­
by­
product
test
results
reported
by
Hanley
et
al.
(
1994);
Shaughnessy
et
al.
(
1994);
and
Offerman
et
al.
(
1984)
exhibit
considerable
variability
across
systems,
ranging
from
ineffectual
(<
1%
efficiency)
to
nearly
complete
removal.
17.3.5.
Interzonal
Airflows
structures
as
a
detailed
network
of
rooms,
it
is
convenient
to
divide
them
into
one
or
more
zones.
At
a
minimum,
each
floor
is
typically
defined
as
a
separate
zone.
For
indoor
air
exposure
assessments,
further
divisions
are
sometimes
made
within
a
floor,
depending
on
(
1)
locations
of
specific
contaminant
sources
and
(
2)
the
presumed
degree
of
air
communication
among
areas
with
and
without
sources.
Defining
the
airflow
balance
for
a
multiple­
zone
exposure
scenario
rapidly
increases
the
information
requirements
as
rooms
or
zones
are
added.
As
shown
in
Figure
17­
5,
a
single­
zone
system
(
considering
the
entire
building
as
a
single
well­
mixed
volume)
requires
only
two
airflows
to
define
air
exchange.
Further,
because
air
exchange
is
balanced
flow
(
air
does
not
"
pile
up"
in
the
building,
nor
is
a
vacuum
formed),
only
one
number
(
the
air
exchange
rate)
is
needed.
With
two
zones,
six
airflows
are
needed
to
accommodate
interzonal
airflows
plus
air
exchange;
with
three
zones,
twelve
airflows
are
required.
In
some
cases,
the
complexity
can
be
reduced
using
judicious
(
if
not
convenient)
assumptions.
Interzonal
airflows
connecting
nonadjacent
rooms
can
be
set
to
zero,
for
example,
if
flow
pathways
do
not
exist.
Symmetry
also
can
be
applied
to
the
system
by
assuming
that
each
flow
pair
is
balanced.

17.3.6.
Water
Uses
Among
indoor
water
uses,
showering,
bathing
and
handwashing
of
dishes
or
clothes
provide
the
primary
opportunities
for
dermal
exposure.
Virtually
all
indoor
water
uses
will
result
in
some
volatilization
of
chemicals,
leading
to
inhalation
exposure.
The
exposure
potential
for
a
given
situation
will
depend
on
the
source
of
water,
the
types
and
extents
of
water
uses,
and
the
extent
of
volatilization
of
specific
chemicals.
According
to
the
results
of
the
1987
Annual
Housing
Survey
(
U.
S.
Bureau
of
the
Census,
1992),
84.7
percent
of
all
U.
S.
housing
units
receive
water
from
a
public
system
or
private
company
(
as
opposed
to
a
well).
Across
the
four
major
regions
defined
by
the
U.
S.
Census
Bureau
Volume
III
­
Activity
Factors
Chapter
17
­
Residential
Building
Characteristics
Page
Exposure
Factors
Handbook
17­
16
August
1997
Figure
17­
5.
Air
Flows
for
Multiple­
zone
Systems
(
Northeast,
South,
Midwest,
and
West),
the
percentage
a
20­
month
period.
The
household
selection
process
for
varies
from
82.5
in
the
Midwest
region
to
93.2
in
the
West
this
study
was
not
random;
it
involved
volunteers
from
region
(
the
Northeast
and
South
regions
both
are
very
close
water
companies
and
engineering
organizations,
most
of
to
the
national
percentage).
which
were
located
in
large
metropolitan
areas.
Nazaroff
et
The
primary
types
of
water
use
indoors
can
be
al.
(
1988)
also
assembled
the
results
of
several
smaller
classified
as
showering/
bathing,
toilet
use,
clothes
washing,
surveys,
typically
involving
between
5
and
50
households
dishwashing,
and
faucet
use
(
e.
g.,
for
drinking,
cooking,
each.
general
cleaning,
or
washing
hands).
Substantial
A
common
feature
of
the
various
studies
cited
above
information
on
water
use
has
been
collected
in
California
is
that
the
results
were
all
reported
in
gallons
per
capita
per
households
by
the
Metropolitan
Water
District
of
Southern
day
(
gcd),
or
in
units
that
could
be
easily
converted
to
gcd.
California
(
MWD,
1991)
and
by
the
East
Bay
Municipal
Most
studies
also
provided
estimates
by
type
of
use­­
Utility
District
(
EBMUD,
1992).
An
earlier
study
by
the
shower/
bath,
toilet,
laundry,
dishwashing,
and
other
(
e.
g.,
U.
S.
Department
of
Housing
and
Urban
Development
(
U.
S.
faucets).
A
summary
of
the
various
study
results
is
DHUD,
1984)
monitored
water
use
in
200
households
over
Volume
III
­
Activity
Factors
Chapter
17
­
Residential
Building
Characteristics
Exposure
Factors
Handbook
Page
August
1997
17­
17
provided
in
Table
17­
14.
There
is
generally
about
a
threefold
variation
across
studies
for
total
Table
17­
14.
In­
house
Water
Use
Rates
(
gcd),
by
Study
and
Type
of
Use
Study
All
Uses
or
Bath
Toilet
Laundry
Dishwashing
Other
Total,
Shower
MWD
93
26
30
20
5
12
1
EBMUD
67
20
28
9
4
6
2
U.
S.
DHUD
40
15
10
13
2
­­
3
Nazaroff
et
al.,
1988
52
6
17
11
18
­­
Study
1
Study
2
­
Rural
46
11
18
14
3
­­
­
Urban
43
10
18
11
4
­­
Study
3
42
9
20
7
4
2
Study
4
45
9
15
11
4
6
Study
5
70
21
32
7
7
3
Study
6
59
20
24
8
4
3
Study
7
40
10
9
11
5
5
Study
8
52­
86
20­
40
4­
6
20­
30
8­
10
­­

Mean
Across
Studies
59
17
18
13
6
5
5
Median
Across
Studies
53
15
18
11
4
5
5
Metropolitan
Water
District
of
Southern
California,
1991.
1
East
Bay
Municipal
Utility
District,
1992.
2
U.
S.
Department
of
Housing
and
Urban
Development,
1984.
3
Results
of
eight
separate
studies.
4
The
average
value
from
each
range
reported
in
Study
No.
8
was
used
to
calculate
the
median
across
studies.
The
mean
and
median
for
the
5
"
Total,
all
Uses"
column
were
obtained
by
summing
across
the
means
and
medians
for
individual
types
of
water
use.

in­
house
water
use
as
well
as
each
type
of
use.
Central
The
following
sections
provide
a
summary
of
the
values
for
total
use,
were
obtained
by
taking
the
mean
and
water
use
characteristics
for
the
primary
types
of
water
uses
median
across
the
studies
for
each
type
of
water
use
and
indoors.
To
the
extent
found
in
the
literature,
each
water
then
summing
these
means/
medians
across
uses.
These
use
is
described
in
terms
of
the
frequency
of
use;
flowrate
central
values
are
shown
at
the
bottom
of
the
table.
The
during
the
use;
quantity
of
water
used
during
each
means
and
medians
were
summed
across
types
of
uses
to
occurrence
of
the
water
use;
and
quantity
used
by
an
obtain
the
mean
for
all
uses
combined
because
only
a
subset
average
person.
Table
17­
15
summarizes
the
studies
of
of
the
studies
reported
values
for
other
uses.
U.
S.
DHUD
and
the
Power
Authorities
by
locations
and
number
of
households.

Table
17­
15.
Summary
of
Selected
HUD
and
Power
Authority
Water
Use
Studies
Number
of
Households
Location
Reference
U.
S.
DHUD
Studies
Study
1
37
Los
Angeles,
CA
a,
b
Study
2
7
Sacramento,
CA
a,
c
Study
3
40
Walnut
Creek,
CA
a,
c
Study
4
7
Washington,
DC
a
Study
5
21
Sacramento,
CA
a
Study
6
19
Los
Angeles,
CA
a
Power
Authority
Studies
Study
1
32
Seattle,
WA
a
Study
2
23
Denver,
CO
a
Study
3
15
Aurora,
CO
a
Study
4
10
Fairfax,
VA
a
TOTAL
211
Volume
III
­
Activity
Factors
Chapter
17
­
Residential
Building
Characteristics
Page
Exposure
Factors
Handbook
17­
18
August
1997
Sources:
U.
S.
Department
of
Housing
and
Urban
Development,
1984.
a
Metropolitan
Water
District
of
Southern
California,
1991.
b
East
Bay
Municipal
Utility
District,
1992.
c
Caution
should
be
exercised
when
using
the
data
collected
in
these
studies
and
shown
here.
The
participants
in
these
studies
are
not
a
representative
sample
of
the
general
population.
The
participants
consisted
of
volunteers,
mostly
from
large
metropolitan
areas.
Showering
and
Bathing
Water
Use
Characteristics
­
1984,
the
newer
(
post
1984)
conserving
toilets
that
are
The
HUD
study
(
U.
S.
DHUD,
1984)
monitored
162
designed
to
use
approximately
1.6
gallons
per
flush
were
households
for
shower
duration.
The
individuals
were
also
not
tested.
subdivided
by
people
who
only
shower
or
only
bath.
The
The
frequency
of
use
for
toilets
in
households
was
results
are
given
in
Table
17­
16.
The
flowrates
of
various
examined
in
several
studies
(
U.
S.
DHUD,
1984;
Ligman,
types
of
shower
heads
were
also
evaluated
in
the
study
et
al.,
1974;
Siegrist,
1976).
The
observed
mean
(
Table
17­
17).
frequencies
in
these
studies
are
given
in
Table
17­
19.
Toilet
Water
Use
Characteristics
­
The
HUD
study
(
U.
S.
DHUD,
1984)
reported
water
volume
per
flush
for
various
types
of
toilets
and
monitored
162
households
for
shower
duration.
The
results
of
this
study
are
shown
in
Table
17­
18.
Since
the
HUD
study
was
conducted
prior
to
Tables
17­
20
through
17­
24
present
indoor
water
use
frequencies
for
dishwashers
and
clothes
washers.

Table
17­
16.
Showering
and
Bathing
Water
Use
Characteristics
Characteristic
Mean
Duration
Mean
Frequency
Individuals
who
Shower
only
10.4
minutes/
shower
0.74
showers/
day/
person
Individuals
who
Bath
only
NA
0.41
baths/
day/
person
Individuals
who
Shower
and
Bath
NA
NA
Source:
Adapted
from
U.
S.
DHUD,
1984.

Table
17­
17.
Showering
Characteristics
for
Various
Types
of
Shower
Heads
Shower
Head
Type
Mean
Flow
Rate
(
gpm)

Non­
Conserving
(>
3
gpm)
3.4
Low
Flow
(
#
3
gpm)
1.9
Restrictor
(
#
3
gpm)
2.1
Zinplas
1.8
a
Turbojector
1.3
a
Types
of
low
flow
water
fixtures.
a
Source:
Adapted
from
U.
S.
DHUD,
1984.

Table
17­
18.
Toilet
Water
Use
Characteristics
Average
Water
Use
(
gallons/
flush)
Toilet
Type
Non­
Conserving
5.5
Bottles
5.0
Bags
4.8
Dams
4.5
Low­
flush
3.5
Source:
Adapted
from
U.
S.
DHUD,
1984.
Volume
III
­
Activity
Factors
Chapter
17
­
Residential
Building
Characteristics
Exposure
Factors
Handbook
Page
August
1997
17­
19
Table
17­
19.
Toilet
Frequency
Use
Characteristics
Study
(
flushes/
person/
day)
Flush
Frequency
U.
S.
DHUD,
1984
4.2
flushes/
household/
day
a
Ligman,
et
al.,
1974
Rural,
M­
F
3.6
flushes/
person/
day
Ligman,
et
al.,
1974
Rural,
Sat­
Sun
3.8
flushes/
person/
day
Ligman,
et
al.,
1974
Urban,
M­
F
3.6
flushes/
person/
day
Ligman,
et
al.,
1974
Urban,
Sat­
Sun
3.1
flushes/
person/
day
Siegrist,
1976
2.3
flushes/
person/
day
Unweighted
Mean
3.43
flushes/
person/
day
The
HUD
value
may
in
fact
be
flushes/
household/
day
a
Table
17­
20.
Dishwasher
Frequency
Use
Characteristics
Study
Use
Frequency
U.
S.
DHUD,
1984
0.47
loads/
person/
day
Ligman,
et
al.,
1974
Rural
1.3
loads/
day
Siegrist,
1976
0.39
loads/
person/
day
Unweighted
Mean
0.92
loads/
day
Table
17­
21.
Dishwasher
Water
Use
Characteristics
Brand
(
gallons/
regular
(
minutes)
Average
Water
Use
Cycle
Duration
cycle)
140
E
F
120
E
F
Maytag
11.5
75
­­
Frigidaire
12
75
75
General
Electric
10.5
80
95
Sears
10
75
95
Whirlpool
9.5
60
110
White/
Westinghouse
12
75
75
Waste
King
11.5
65
85
Kitchen
Aid
9.5
80
80
Magic
Chef
11.5
70
­­

Unweighted
Mean
10.9
72.8
87.9
Source:
Adapted
from
Consumer
Reports,
1987.

Table
17­
22.
Clothes
Washer
Frequency
Use
Characteristics
Study
Use
Frequency
U.
S.
DHUD,
1984
0.3
loads/
person/
day
Ligman,
et
al.,
1974
Rural
0.34
loads/
person/
day
Ligman,
et
al.,
1974
Urban
0.27
loads/
person/
day
Siegrist,
1976
0.31
loads/
day
Table
17­
23.
Clothes
Washer
Water
Use
Characteristics
Brand
(
gallons/
regular
cycle)
(
minutes)
Average
Water
Use
Cycle
Duration
Maytag
41
32
Frigidaire
48
40
General
Electric
51
48
Hotpoint
51
48
Sears
49
40
Whirlpool
53
44
White/
Westinghouse
54
47
Kelvinator
46
52
Norge
55
49
Source:
Adapted
from
Consumer
Reports,
1982.

Table
17­
24.
Range
of
Water
Uses
for
Clothes
Washers
Type
of
Clothes
Washer
Range
of
Water
Use
Conventional
27­
59
gallons/
load
Low
Water
16­
19
gallons/
load
All
Clothes
Washers
16­
59
gallons/
load
Source:
Adapted
from
Consumer
Reports,
1982.

17.3.7.
House
Dust
and
Soil
House
dust
is
a
complex
mixture
of
biologicallyderived
material
(
animal
dander,
fungal
spores,
etc.),
particulate
matter
deposited
from
the
indoor
aerosol,
and
soil
particles
brought
in
by
foot
traffic.
House
dust
may
Volume
III
­
Activity
Factors
Chapter
17
­
Residential
Building
Characteristics
Page
Exposure
Factors
Handbook
17­
20
August
1997
contain
VOCs
(
see,
for
example,
Wolkoff
and
Wilkins,
1994;
Hirvonen
et
al.,
1995),
pesticides
from
imported
soil
particles
as
well
as
from
direct
applications
indoors
(
see,
for
example,
Roberts
et
al.,
1991),
and
trace
metals
derived
from
outdoor
sources
(
see,
for
example,
Layton
and
Thatcher,
1995).
The
indoor
abundance
of
house
dust
depends
on
the
interplay
of
deposition
from
the
airborne
state,
resuspension
due
to
various
activities,
direct
accumulation,
and
infiltration.
In
the
absence
of
indoor
sources,
indoor
concentrations
of
particulate
matter
are
significantly
lower
than
outdoor
levels.
For
some
time,
this
observation
supported
the
idea
that
a
significant
fraction
of
the
outdoor
aerosol
is
filtered
out
by
the
building
envelope.
More
recent
data,
however,
have
shown
that
deposition
(
incompletely
addressed
in
earlier
studies)
accounts
for
the
indoor­
outdoor
contrast,
and
outdoor
particles
smaller
than
10
F
m
aerodynamic
diameter
penetrate
the
building
Particle
Deposition
Particle
Resuspension
envelope
as
completely
as
nonreactive
gases
(
Wallace,
1996).
Roberts
et
al.
(
1991)
­
Development
and
Field
Testing
of
a
High
Volume
Sampler
for
Pesticides
and
Toxics
in
Dust
­
Dust
loadings,
reported
by
Roberts
et
al.
(
1991)
were
also
measured
in
conjunction
with
the
Non­
Occupational
Pesticide
Exposure
Study
(
NOPES).
In
this
study
house
dust
was
sampled
from
a
representative
grid
using
a
specially
constructed
high­
volume
surface
sampler
(
HVS2).
The
surface
sampler
collection
efficiency
was
verified
in
conformance
with
ASTM
F608
(
ASTM,
1989).
The
data
summarized
in
Table
17­
25
were
collected
from
carpeted
areas
in
volunteer
households
in
Florida
encountered
during
the
course
of
NOPES.
Seven
of
the
nine
sites
were
single­
family
detached
homes,
and
two
were
mobile
homes.
The
authors
noted
that
the
two
houses
exhibiting
the
highest
dust
loadings
were
only
those
homes
where
a
vacuum
cleaner
was
not
used
for
housekeeping.

Table
17­
25.
Total
Dust
Loading
for
Carpeted
Areas
Household
Total
Dust
Load
Fine
Dust
(<
150
F
m)
(
g­
m
)
Load
(
g­
m
)
­
2
­
2
1
10.8
6.6
2
4.2
3.0
3
0.3
0.1
4
2.2;
0.8
1.2;
0.3
5
1.4;
4.3
1.0;
1.1
6
0.8
0.3
7
6.6
4.7
8
33.7
23.3
9
812.7
168.9
Source:
Adapted
from
Roberts
et
al.,
1991.

Thatcher
and
Layton
(
1995)
­
Deposition,
Resuspension
and
Penetration
of
Particles
Within
a
Residence
­
Relatively
few
studies
have
been
conducted
at
the
level
of
detail
needed
to
clarify
the
dynamics
of
indoor
aerosols.
One
intensive
study
of
a
California
residence
(
Thatcher
and
Layton,
1995),
however,
provides
instructive
results.
Using
a
model­
based
analysis
for
data
collected
under
controlled
circumstances,
the
investigators
verified
penetration
of
the
outdoor
aerosol
and
estimated
rates
for
particle
deposition
and
resuspension
(
Table
17­
26).
The
investigators
stressed
that
normal
household
activities
are
a
significant
source
of
airborne
particles
larger
than
5
F
m.
During
the
study,
they
observed
that
just
walking
into
and
out
of
a
room
could
momentarily
double
the
concentration.
The
airborne
abundance
of
submicrometer
particles,
on
the
other
hand,
was
unaffected
by
either
cleaning
or
walking.

Table
17­
26.
Particle
Deposition
and
Resuspension
During
Normal
Activities
Particle
Size
Range
Rate
Rate
(
F
m)
(
h
)
(
h
)
­
1
­
1
0.3­
0.5
(
not
measured)
9.9
x
10
0.6­
1
(
not
measured)
4.4
x
10
1­
5
0.5
1.8
x
10
5­
10
1.4
8.3
x
10
10­
25
2.4
3.8
x
10
>
25
4.1
3.4
x
10
­
7
­
7
­
5
­
5
­
4
­
5
Source:
Adapted
from
Thatcher
and
Layton,
1995.

Mass
loading
of
floor
surfaces
(
Table
17­
27)
was
measured
in
the
study
of
Thatcher
and
Layton
(
1995)
by
thoroughly
cleaning
the
house
and
sampling
accumulated
dust,
after
one
week
of
normal
habitation.
Methodology,
validated
under
ASTM
F608
(
ASTM,
1989),
showed
fine
dust
recovery
efficiencies
of
50
percent
with
new
carpet
and
72
percent
for
linoleum.
Tracked
areas
showed
consistently
higher
accumulations
than
untracked
areas,
confirming
the
importance
of
tracked­
in
material.
Differences
between
tracked
areas
upstairs
and
downstairs
show
that
tracked­
in
material
is
not
readily
transported
upstairs.
The
consistency
of
untracked
carpeted
areas
throughout
the
house,
suggests
that,
in
the
absence
of
tracking,
particle
transport
processes
are
similar
on
both
floors.
Volume
III
­
Activity
Factors
Chapter
17
­
Residential
Building
Characteristics
Exposure
Factors
Handbook
Page
August
1997
17­
21
Table
17­
27.
Dust
Mass
Loading
After
One
Week
Without
Vacuum
Cleaning
Location
in
Test
House
Dust
Loading
(
g­
m
)
­
2
Tracked
area
of
downstairs
carpet
2.20
Untracked
area
of
downstairs
carpet
0.58
Tracked
area
of
linoleum
0.08
Untracked
area
of
linoleum
0.06
Tracked
area
of
upstairs
carpet
1.08
Untracked
area
of
upstairs
carpet
0.60
Front
doormat
43.34
Source:
Adapted
from
Thatcher
and
Layton,
1995.

17.4.
SOURCES
Product­
and
chemical­
specific
mechanisms
for
indoor
sources
can
be
described
using
simple
emission
factors
to
represent
instantaneous
releases,
as
well
as
constant
releases
over
defined
time
periods;
more
complex
formulations
may
be
required
for
time­
varying
sources.
Guidance
documents
for
characterizing
indoor
sources
within
the
context
of
the
exposure
assessment
process
are
limited
(
see,
for
example,
Jennings
et
al.,
1987;
Wolkoff,
1995).
Fairly
extensive
guidance
exists
in
the
technical
literature,
however,
provided
that
the
exposure
assessor
has
the
means
to
define
(
or
estimate)
key
mechanisms
and
chemical­
specific
parameters.
Basic
concepts
are
summarized
below
for
the
broad
source
categories
that
relate
to
airborne
contaminants,
waterborne
contaminants,
and
for
soil/
house
dust
indoor
sources.

17.4.1.
Source
Descriptions
for
Airborne
Contaminants
Table
17­
28
summarizes
simplified
indoor
source
descriptions
for
airborne
chemicals
for
direct
discharge
sources
(
e.
g.,
combustion,
pressurized
propellant
products),
as
well
as
emanation
sources
(
e.
g.,
evaporation
from
"
wet"
films,
diffusion
from
porous
media),
and
transport­
related
sources
(
e.
g.,
infiltration
of
outdoor
air
contaminants,
soil
gas
entry).
Direct­
discharge
sources
can
be
approximated
using
simple
formulas
that
relate
pollutant
mass
released
to
characteristic
process
rates.
Combustion
sources,
for
example,
may
be
stated
in
terms
of
an
emission
factor,
fuel
content
(
or
heating
value),
and
fuel
consumption
(
or
carrier
delivery)
rate.
Emission
factors
for
combustion
products
of
general
concern
(
e.
g.,
CO,
NO
)
have
been
measured
for
a
x
number
of
combustion
appliances
using
room­
sized
chambers
(
see,
for
example,
Relwani
et
al.,
1986).
Other
direct­
discharge
sources
would
include
volatiles
released
from
water
use
and
from
pressurized
consumer
products.
Resuspension
of
house
dust
(
see
Section
17.3.7)
would
take
on
a
similar
form
by
combining
an
activity­
specific
rate
constant
with
an
applicable
dust
mass.

Table
17­
28.
Simplified
Source
Descriptions
for
Airborne
Contaminants
Description
Components
Dimensions
Direct
Discharge
Combustion
E
H
M
g
h
Volume
Q
C
_
,
g
h
Discharge
Q
=
volume
delivery
rate
m
h
Mass
M
w
,
g
h
Discharge
M
=
mass
delivery
rate
g
h
f
f
f
E
=
emission
factor
g
J
f
H
=
fuel
content
J
mol
f
M
=
fuel
consumption
rate
mol
h
f
p
p
p
C
=
concentration
in
carrier
g
m
p
,
=
transfer
efficiency
g
g
p
e
p
w
=
weight
fraction
g
g
e
,
=
transfer
efficiency
g
g
­
1
­
1
­
1
­
1
­
1
3
­
1
­
3
­
1
­
1
­
1
­
1
­
1
Diffusion
Limited
(
D
*
)
(
C
­
C
)
A
g
h
Exponential
f
s
i
i
­
1
D
=
diffusivity
m
h
f
*
=
boundary
layer
thickness
m
­
1
C
=
vapor
pressure
of
surface
g
m
s
C
=
room
concentration
g
m
i
A
=
area
m
i
A
E
e
g
h
i
o
­
k
t
A
=
area
m
i
E
=
initial
unit
emission
rate
g
h
m
o
k
=
emission
decay
factor
h
t
=
time
h
­
1
2
­
1
­
3
­
3
2
­
1
2
­
1
­
2
­
1
Transport
Infiltration
Q
C
g
h
Interzonal
Q
=
air
flow
from
zone
j
m
h
Soil
Gas
C
=
air
concentration
in
zone
j
g
m
ji
j
ji
j
­
1
3
­
1
­
3
Diffusion­
limited
sources
(
e.
g.,
carpet
backing,
furniture,
flooring,
dried
paint)
represent
probably
the
greatest
challenge
in
source
characterization
for
indoor
air
quality.
Vapor­
phase
organics
dominate
this
group,
offering
great
complexity
because
(
1)
there
is
a
fairly
long
list
of
chemicals
that
could
be
of
concern,
(
2)
ubiquitous
consumer
products,
building
materials,
coatings,
and
furnishings
contain
varying
amounts
of
different
chemicals,
(
3)
source
dynamics
may
include
nonlinear
mechanisms,
and
(
4)
for
many
of
the
chemicals,
emitting
as
well
as
nonemitting
materials
evident
in
realistic
settings
may
promote
reversible
and
irreversible
sink
effects.
Very
detailed
descriptions
for
diffusion­
limited
sources
can
be
constructed
to
link
specific
properties
of
the
chemical,
the
source
material,
and
the
receiving
environment
to
calculate
expected
behavior
(
see,
for
example,
Schwope
et
al.,
1992;
Cussler,
1984).
Validation
to
actual
circumstances,
however,
suffers
practical
shortfalls
because
many
parameters
simply
cannot
be
measured
directly.
The
exponential
formulation
listed
in
Table
17­
28
was
derived
based
on
a
series
of
papers
generated
during
M
'
m
4
o
E
o
e
&
k
s
t
dt
'
E
o
k
s
E
c
E
o
'
e
&
kstc
or
M
c
M
'
1
&
e
&
kst
Volume
III
­
Activity
Factors
Chapter
17
­
Residential
Building
Characteristics
Page
Exposure
Factors
Handbook
17­
22
August
1997
(
Eqn.
17­
4)
the
development
of
chamber
testing
methodology
by
EPA
(
Dunn,
1987;
Dunn
and
Tichenor,
1988;
Dunn
and
Chen,
1993).
This
framework
represents
an
empirical
alternative
Residential
water
supplies
may
convey
chemicals
to
that
works
best
when
the
results
of
chamber
tests
are
which
occupants
can
be
exposed
through
ingestion,
dermal
available.
Estimates
for
the
initial
emission
rate
(
E
)
and
contact,
or
inhalation.
These
chemicals
may
appear
in
the
o
decay
factor
(
k
)
can
be
developed
for
hypothetical
sources
form
of
contaminants
(
e.
g.,
trichloroethylene)
as
well
as
s
from
information
on
pollutant
mass
available
for
release
naturally­
occurring
byproducts
of
water
system
history
(
e.
g.,
(
M)
and
supporting
assumptions.
chloroform,
radon).
Among
indoor
water
uses,
showering,
Assuming
that
a
critical
time
period
(
t
)
coincides
bathing
and
handwashing
of
dishes
or
clothes
provide
the
c
with
reduction
of
the
emission
rate
to
a
critical
level
(
E
)
or
primary
opportunities
for
dermal
exposure.
The
escape
of
c
with
the
release
of
a
critical
fraction
of
the
total
mass
(
M
),
volatile
chemicals
to
the
gas
phase
associates
water
use
c
the
decay
factor
can
be
estimated
by
solving
either
of
these
with
inhalation
exposure.
The
exposure
potential
for
a
given
relationships:
situation
will
depend
on
the
source
of
water,
the
types
and
(
Eqn.
17­
3)

The
critical
time
period
can
be
derived
from
productspecific
considerations
(
e.
g.,
equating
drying
time
for
a
paint
to
90
percent
emissions
reduction).
Given
such
an
estimate
for
k
,
the
initial
emission
rate
can
be
estimated
by
s
integrating
the
emission
formula
to
infinite
time
under
the
assumption
that
all
chemical
mass
is
released:
The
basis
for
the
exponential
source
algorithm
has
also
been
extended
to
the
description
of
more
complex
diffusion­
limited
sources.
With
these
sources,
diffusive
or
evaporative
transport
at
the
interface
may
be
much
more
rapid
than
diffusive
transport
from
within
the
source
material,
so
that
the
abundance
at
the
source/
air
interface
becomes
depleted,
limiting
the
transfer
rate
to
the
air.
Such
effects
can
prevail
with
skin
formation
in
"
wet"
sources
like
stains
and
paints
(
see,
for
example,
Chang
and
Guo,
1992).
Similar
emission
profiles
have
been
observed
with
the
emanation
of
formaldehyde
from
particleboard
with
"
rapid"
decline
as
formaldehyde
evaporates
from
surface
sites
of
the
particleboard
over
the
first
few
weeks.
It
is
then
followed
by
a
much
slower
decline
over
ensuing
years
as
formaldehyde
diffuses
from
within
the
matrix
to
reach
the
surface
(
see,
for
example,
Zinn
et
al.,
1990).
Transport­
based
sources
bring
contaminated
air
from
other
areas
into
the
airspace
of
concern.
Examples
include
infiltration
of
outdoor
contaminants,
and
soil
gas
entry.
Soil
gas
entry
is
a
particularly
complex
phenomenon,
and
is
frequently
treated
as
a
separate
modeling
issue
(
Little
et
al.,
1992;
Sextro,
1994).
Room­
to­
room
migration
of
indoor
contaminants
would
also
fall
under
this
category,
but
this
concept
is
best
considered
using
the
multiple­
zone
model.
17.4.2.
Source
Descriptions
for
Waterborne
Contaminants
extents
of
water
uses,
and
the
extent
of
volatilization
of
specific
chemicals.
Primary
types
of
residential
water
use
(
summarized
in
Section
17.3)
include
showering/
bathing,
toilet
use,
clothes
washing,
dishwashing,
and
faucet
use
(
e.
g.,
for
drinking,
cooking,
general
cleaning,
or
washing
hands).
Upper­
bounding
estimates
of
chemical
release
rates
from
water
use
can
be
formulated
as
simple
emission
factors
by
combining
the
concentration
in
the
feed
water
(
g
m
)
with
the
flow
rate
for
the
water
use
(
m
h
),
and
­
3
3
­
1
assuming
that
the
chemical
escapes
to
the
gas
phase.
For
some
chemicals,
however,
not
all
of
the
chemical
escapes
in
realistic
situations
due
to
diffusion­
limited
transport
and
solubility
factors.
For
inhalation
exposure
estimates,
this
may
not
pose
a
problem
because
the
bounding
estimate
would
overestimate
emissions
by
no
more
than
approximately
a
factor
of
two.
For
multiple
exposure
pathways,
the
chemical
mass
remaining
in
the
water
may
be
of
importance.
Refined
estimates
of
volatile
emissions
are
usually
considered
under
two­
resistance
theory
to
accommodate
mass
transport
aspects
of
the
water­
air
system
(
see,
for
example,
Little,
1992;
Andelman,
1990;
McKone,
1987).
Release
rates
are
formulated
as:
S
'
K
m
F
W
C
w
&
C
a
H
1
K
D
Li
D
Lr
1/
2
'
1
K
Lr
'
1
K
Gr
&
1
H
D
Gr
D
Gi
2/
3
D
Li
D
Lr
1/
2
S
d
'
M
d
R
d
A
f
Volume
III
­
Activity
Factors
Chapter
17
­
Residential
Building
Characteristics
Exposure
Factors
Handbook
Page
August
1997
17­
23
(
Eqn.
17­
5)

where:
S
=
chemical
release
rate
(
g
h
)
­
1
K
=
dimensionless
mass­
transfer
coefficient
m
F
=
water
flow
rate
(
m
h
)
w
3
­
1
C
=
concentration
in
feed
water
(
g
m
)
w
­
3
C
=
concentration
in
air
(
g
m
)
a
­
3
H
=
dimensionless
Henry's
Law
constant
(
Eqn.
17­
6)

where:
D
=
liquid
diffusivity
(
m
s
)
L
2
­
1
D
=
gas
diffusivity
(
m
s
)
G
2
­
1
K
=
liquid­
phase
mass
transfer
coefficient
L
K
=
gas­
phase
mass
transfer
coefficient
G
H
=
dimensionless
Henry's
Law
constant
Because
the
emission
rate
is
dependent
on
the
air
indicates
that,
for
an
instantaneous
release
from
a
point
concentration,
recursive
techniques
are
required.
The
mass
source
in
a
room,
fairly
complete
mixing
is
achieved
within
transfer
coefficient
is
a
function
of
water
use
characteristics
10
minutes
when
convective
flow
is
induced
by
solar
(
e.
g.,
water
droplet
size
spectrum,
fall
distance,
water
film)
radiation.
However,
up
to
100
minutes
may
be
required
for
and
chemical
properties
(
diffusion
in
gas
and
liquid
phases).
complete
mixing
under
quiescent
(
nearly
isothermal)
Estimates
of
practical
value
are
based
on
empirical
tests
to
conditions.
While
these
experiments
were
conducted
at
incorporate
system
characteristics
into
a
single
parameter
extremely
low
air
exchange
rates
(<
0.1
ACH),
based
on
the
(
see,
for
example,
Giardino
et
al.,
1990).
Once
results,
attention
is
focused
on
mixing
within
a
room.
characteristics
of
one
chemical­
water
use
system
are
known
The
situation
changes
if
a
human
invokes
a
point
(
reference
chemical,
subscript
r),
the
mass
transfer
source
for
a
longer
period
and
remains
in
the
immediate
coefficient
for
another
chemical
(
index
chemical,
subscript
vicinity
of
that
source.
Personal
exposure
in
the
near
i)
delivered
by
the
same
system
can
be
estimated
using
vicinity
of
a
source
can
be
much
higher
than
the
well­
mixed
formulations
identified
in
the
review
by
Little
(
1992):
assumption
would
suggest.
A
series
of
experiments
17.4.3.
Soil
and
House
Dust
Sources
The
rate
process
descriptions
compiled
for
soil
and
exceeded
those
several
meters
away
by
a
factor
that
varied
house
dust
in
Section
17.3
provide
inputs
for
estimating
inversely
with
the
ventilation
intensity
in
the
room.
At
indoor
emission
rates
(
S
,
g
h
)
in
terms
of
dust
mass
typical
room
ventilation
rates,
the
ratio
of
source­
proximate
d
­
1
loading
(
M
,
g
m
)
combined
with
resuspension
rates
(
R
,
to
slightly­
removed
concentration
was
on
the
order
of
2:
1.
d
d
­
2
h
)
and
floor
area
(
A
,
m
):
­
1
2
f
(
Eqn.
17­
7)
Because
house
dust
is
a
complex
mixture,
transfer
of
particle­
bound
constituents
to
the
gas
phase
may
be
of
concern
for
some
exposure
assessments.
For
emission
estimates,
one
would
then
need
to
consider
particle
mass
residing
in
each
reservoir
(
dust
deposit,
airborne).

17.5.
ADVANCED
CONCEPTS
17.5.1.
Uniform
Mixing
Assumption
Many
exposure
measurements
are
predicated
on
the
assumption
of
uniform
mixing
within
a
room
or
zone
of
a
house.
Mage
and
Ott
(
1994)
offers
an
extensive
review
of
the
history
of
use
and
misuse
of
the
concept.
Experimental
work
by
Baughman
et
al.
(
1994)
and
Drescher
et
al.
(
1995)

conducted
by
GEOMET
(
1989)
for
the
U.
S.
EPA
involved
controlled
point­
source
releases
of
carbon
monoxide
tracer
(
CO),
each
for
30
minutes.
"
Breathing­
zone"
measurements
located
within
0.4
m
of
the
release
point
were
ten
times
higher
than
for
other
locations
in
the
room
during
early
stages
of
mixing
and
transport.
Similar
investigations
conducted
by
Furtaw
et
al.
(
1995)
involved
a
series
of
experiments
in
a
controlledenvironment
room­
sized
chamber.
Furtaw
et
al.
(
1995)
studied
spatial
concentration
gradients
around
a
continuous
point
source
simulated
by
sulfur
hexafluoride
(
SF
)
tracer
6
with
a
human
moving
about
the
room.
Average
breathingzone
concentrations
when
the
subject
was
near
the
source
17.5.2.
Reversible
Sinks
For
some
chemicals,
the
actions
of
reversible
sinks
are
of
concern.
For
an
initially
"
clean"
condition
in
the
sink
material,
sorption
effects
can
greatly
deplete
indoor
concentrations.
However,
once
enough
of
the
chemical
has
Volume
III
­
Activity
Factors
Chapter
17
­
Residential
Building
Characteristics
Page
Exposure
Factors
Handbook
17­
24
August
1997
been
adsorbed,
the
diffusion
gradient
will
reverse,
allowing
(
i.
e.,
holding
constant
the
pollutant
generation
rate
and
the
chemical
to
escape.
For
persistent
indoor
sources,
such
effect
of
indoor
sinks),
lower
values
for
either
the
indoor
effects
can
serve
to
reduce
indoor
levels
initially
but
once
volume
or
the
air
exchange
rate
will
result
in
higher
indoorthe
system
equilibrates,
the
net
effect
on
the
average
air
concentrations.
Thus,
values
near
the
lower
end
of
the
concentration
of
the
reversible
sink
is
negligible.
Over
distribution
(
e.
g.,
10th
percentile)
for
either
parameter
are
suitably
short
time
frames,
this
can
also
affect
integrated
appropriate
in
developing
conservative
estimates
of
exposure.
For
indoor
sources
whose
emission
profile
exposure.
declines
with
time
(
or
ends
abruptly),
reversible
sinks
can
For
the
volume
of
a
residence,
both
key
studies
(
U.
S.
serve
to
extend
the
emissions
period
as
the
chemical
DOE
(
1995)
and
Versar
(
1990)
PFT
database)
have
the
desorbs
long
after
direct
emissions
are
finished.
Reversible
same
mean
value
­­
369
m
(
see
Table
17­
1).
This
mean
sink
effects
have
been
observed
for
a
number
of
chemicals
value
is
recommended
as
a
central
estimate
residential
in
the
presence
of
carpeting,
wall
coverings,
and
other
volume.
Intuitively,
the
10th
percentile
of
the
distribution
materials
commonly
found
in
residential
environments.
from
either
study
­­
147
m
for
RECS
survey
or
167
m
for
Interactive
sinks
(
and
models
of
the
processes)
are
the
PFT
database
­­
is
too
conservative
a
value,
as
both
of
a
special
importance;
while
sink
effects
can
greatly
these
values
are
lower
than
the
mean
volume
for
multifamily
reduce
indoor
air
concentrations,
re­
emission
at
lower
rates
dwelling
units
(
see
Table
17­
2).
Instead,
the
25th
over
longer
time
periods
could
greatly
extend
the
exposure
percentile
­­
209
m
for
RECS
survey
or
225
m
for
PFT
period
of
concern.
For
completely
reversible
sinks,
the
database,
averaging
217
m
across
the
two
key
studies
­­
is
extended
time
could
bring
the
cumulative
exposure
to
levels
recommended
(
Table
17­
1).
approaching
the
sink­
free
case.
Recent
publications
(
Axley
For
the
residential
air
exchange
rate,
the
median
et
al.,
1993;
Tichenor
et
al.,
1991)
show
that
first
principles
value
of
0.45
air
changes
per
hour
(
ACH)
from
the
PFT
provide
useful
guidance
in
postulating
models
and
setting
database
(
see
Table
17­
9)
is
recommended
as
a
typical
assumptions
for
reversible/
irreversible
sink
models.
value
(
Koontz
and
Rector,
1995).
This
median
value
is
Sorption/
desorption
can
be
described
in
terms
of
Langmuir
very
close
to
the
geometric
mean
of
the
measurements
in
the
(
monolayer)
as
well
as
Brunauer­
Emmet­
Teller
(
BET,
PFT
database
analyzed
by
Koontz
and
Rector
(
1995).
The
multilayer)
adsorption.
arithmetic
mean
is
not
preferred
because
it
is
influenced
17.6
RECOMMENDATIONS
Table
17­
29
presents
a
summary
of
volume
of
for
the
PFT
database
­­
0.18
ACH
­­
is
recommended
residence
surveys
and
Table
17­
30
presents
a
summary
of
(
Table
17­
10).
air
exchange
rates
surveys.
Table
17­
31
presents
the
There
are
some
uncertainties
in,
or
limitations
on,
the
recommended
values.
Tables
17­
32
and
17­
33
provide
the
distribution
for
volumes
and
air
exchange
rates
that
are
confidence
in
recommendations
for
house
volume
and
air
presented
in
this
chapter.
For
example,
the
RECS
used
to
exchange
rates,
respectively.
Key
studies
or
analyses
infer
volume
distributions
used
a
nationwide
probability
described
in
this
chapter
were
used
in
selecting
sample,
but
measured
floor
area
rather
than
total
volume.
recommended
values
for
residential
volume.
The
air
By
comparison,
field
studies
contributing
to
the
PFT
data
exchange
rate
data
presented
in
the
studies
are
extremely
base
measured
house
volumes
directly,
but
the
aggregate
limited.
Therefore,
studies
have
not
been
classified
as
key
sampling
frame
for
these
studies
is
not
statistically
or
relevant
studies.
However,
recommendations
have
been
representative
of
the
national
housing
stock.
provided
for
air
exchange
rates
and
the
confidence
Although
the
PFT
methodology
is
relatively
simple
recommendation
has
been
assigned
a
"
low"
overall
rating.
to
implement,
it
is
subject
to
errors
and
uncertainties.
The
Therefore,
these
values
should
be
used
with
caution.
Both
general
performance
of
the
sampling
and
analytical
aspects
central
and
conservative
values
are
provided.
These
two
of
the
system
are
quite
good.
That
is,
laboratory
analysis
parameters
­­
volume
and
air
exchange
rate
­­
can
be
used
will
measure
the
correct
time­
weighted­
average
tracer
by
exposure
assessors
in
modeling
indoor­
air
concentration
to
within
a
few
percent
(
Dietz
et
al.,
1986).
concentrations
as
one
of
the
inputs
to
exposure
estimation.
Nonetheless,
significant
errors
can
arise
when
conditions
in
Other
inputs
to
the
modeling
effort
include
rates
of
indoor
the
measurement
scene
greatly
deviate
from
idealizations
pollutant
generation
and
losses
to
(
and,
in
some
cases,
re­
calling
for
constant,
well­
mixed
conditions.
Principal
emissions
from)
indoor
sinks.
Other
things
being
equal
concerns
focus
on
the
effects
of
naturally
varying
air
3
3
3
3
3
3
fairly
heavily
by
extreme
values
at
the
upper
tail
of
the
distribution.
For
a
conservative
value,
the
10th
percentile
Volume
III
­
Activity
Factors
Chapter
17
­
Residential
Building
Characteristics
Exposure
Factors
Handbook
Page
August
1997
17­
25
exchange
and
the
effects
of
temperature
in
the
permeation
ASHRAE.
(
1993)
ASHRAE
Handbook:
Fundamentals.
source.
American
Society
of
Heating,
Refrigerating,
and
Air­
Sherman
(
1989)
carried
out
an
error
analysis
of
the
Conditioning
Engineers.
Atlanta,
GA.
PFT
methodology
using
mathematical
models
combined
ASTM.
(
1989)
Standard
laboratory
test
method
for
with
typical
weather
data
to
calculate
how
an
ideal
sampling
evaluation
of
carpet­
embedded
dirt
removal
system
would
perform
in
a
time­
varying
environment.
He
effectiveness
of
household
vacuum
cleaners.
found
that
for
simple
single­
story
(
ranch)
and
two­
story
plus
Designation:
F
608­
89.
American
Society
for
Testing
basement
(
colonial)
layouts,
seasonal
measurements
would
and
Materials,
Philadelphia,
PA.
underpredict
seasonal
average
air
exchange
by
20
to
30
ASTM.
(
1990)
Test
method
for
determining
percent.
Underprediction
can
occur
because
the
PFT
formaldehyde
levels
from
wood
products
under
methodology
is
measuring
the
effective
ventilation
(
the
defined
conditions
using
a
large
chamber.
Standard
E
product
of
ventilation
efficiency
and
air
exchange),
and
the
1333
90.
American
Society
for
Testing
and
temporal
efficiency
will
generally
be
less
than
unity
over
Materials:
Philadelphia.
averaging
periods
of
this
length.
Sherman
(
1989)
also
Axley,
J.
W.
(
1988)
Progress
toward
a
general
analytical
noted,
however,
that
while
the
bias
could
have
an
impact
on
method
for
predicting
indoor
air
pollution
in
determining
air
exchange
(
absent
knowledge
of
ventilation
buildings:
indoor
air
quality
modeling
phase
III
efficiency)
for
calculating
energy
loads,
the
effective
air
report.
NBSIR
88­
3814.
National
Bureau
of
exchange
term
is
directly
relevant
to
determining
average
Standards,
Gaithersberg,
MD.
indoor
concentrations
resulting
from
constant
sources.
Axley,
J.
W.
(
1989)
Multi­
zone
dispersal
analysis
by
Leaderer
et
al.
(
1985)
conducted
a
series
of
element
assembly.
Building
and
Environment.
experiments
in
a
room­
sized­
environmental
chamber
to
24(
2):
113­
130.
evaluate
the
practical
impacts
of
varying
air
exchange
and
Axley,
J.
W.;
Lorenzetti,
D.
(
1993)
Sorption
transport
the
temperature
response
of
the
permeation
sources.
The
models
for
indoor
air
quality
analysis.
In:
Nagda,
N.
L.
negative
bias
anticipated
in
the
measured
(
effective)
versus
Ed.,
Modeling
of
Indoor
Air
Quality
and
Exposure.
actual
air
exchange
as
conditions
varied
diurnally
between
ASTM
STP
1205.
Philadelphia,
PA:
American
0.4
and
1.5.
ACH
was
evident
but
minor
(
3
to
6
percent),
Society
for
Testing
and
Materials,
pp.
105­
127.
most
likely
due
to
the
mechanical
mixing
in
the
chamber
Baughman,
A.
V.;
Gadgil,
A.
J.;
Nazaroff,
W.
W.
(
1994)
and
the
relatively
short
integration
time
(
72
h).
Similarly,
Mixing
of
a
point
source
pollutant
by
natural
cycling
temperature
diurnally
over
an
8
E
C
range
(
holding
convection
flow
within
a
room.
Indoor
Air.
4:
114­
air
exchange
steady
at
0.6
ACH)
would
cause
122.
concentrations
changes
of
about
20
percent
as
emissions
Chang,
J.
C.
S.;
Guo,
Z.
(
1992)
Characterization
of
organic
fluctuated.
The
investigators
found,
however,
that
using
a
emissions
from
a
wood
finishing
product
­­
wood
time­
weighted
average
temperature
to
define
the
emission
stain.
Indoor
Air.
2(
3):
146­
53.
rate
reduced
the
temperature
bias
to
essentially
zero.
Consumer
Reports.
(
1982)
Washing
machines.
Consumer
17.7.
REFERENCES
FOR
CHAPTER
17
Andelman,
J.
B.
(
1990)
Total
exposure
to
volatile
organic
Cussler,
E.
L.
(
1984)
Diffusion.
Cambridge
University
compounds
in
potable
water.
In:
Ram,
N,
et
al.,
eds.
Press,
New
York,
NY.
Significance
and
Treatment
of
Volatile
Organic
Dietz,
R.
N.;
Goodrich,
R.
W.;
Cote,
E.
A.;
Wieser,
R.
F.
Compounds
in
Water
Supplies.
pp
485­
504,
Lewis
(
1986)
Detailed
description
and
performance
of
a
Publishers,
Chelsea,
MI.
passive
perfluorocarbon
tracer
system
for
building
Andersson,
B.,
K.
Andersson,
J.
Sundell,
and
P.­
A.
ventilation
and
air
exchange
measurements.
H.
R.
Zingmark.
(
1993)
Mass
transfer
of
contaminants
in
Trechsel
and
P.
L.
Lagus,
Eds.
In:
Measured
Air
rotary
enthalpy
heat
exchangers.
Indoor
Air.
3:
143­
Leakage
of
Buildings.
ASTM
STP
904.
148.
Philadelphia,
PA:
American
Society
for
Testing
and
ASHRAE.
(
1988)
ASHRAE
Handbook:
Equipment.
Materials,
pp.
203­
264.
American
Society
of
Heating,
Refrigerating,
and
Air­
Conditioning
Engineers.
Atlanta,
GA.
Reports
Magazine.
47(
10).
Consumer
Reports.
(
1987)
Dishwashers.
Consumer
Reports
Magazine.
52(
6).
Volume
III
­
Activity
Factors
Chapter
17
­
Residential
Building
Characteristics
Page
Exposure
Factors
Handbook
17­
26
August
1997
Drescher,
A.
C.;
Lobascio,
C.;
Gadgil,
A.
J.;
Nazaroff,
Grot,
R.
A.
(
1991)
User
manual
NBS/
AVIS
W.
W.
(
1995)
Mixing
of
a
Point­
Source
Indoor
CONTAM88.
NISTIR
4585,
Gaithersberg,
MD:
Pollutant
by
Forced
Convection.
Indoor
Air.
5:
204­
214.
National
Institute
of
Standards
and
Technology.
Dunn,
J.
E.
(
1987)
Models
and
statistical
methods
for
Grot,
R.
A.;
Clark,
R.
E.
(
1981)
Air
leakage
characteristics
gaseous
emission
testing
of
finite
sources
in
well­
and
weatherization
techniques
for
low­
income
mixed
chambers.
Atmospheric
Environment.
housing.
In:
Proceedings
of
the
American
Society
of
(
21)
2:
425­
430.
Heating,
Refrigerating
and
Air­
Conditioning
Dunn,
J.
E.;
Chen,
T.
(
1993)
Critical
evaluation
of
the
Engineers
Conference.
Thermal
Performance
of
diffusion
hypothesis
in
the
theory
of
porous
media
Exterior
Envelopes
of
Buildings.
ASHRAE
SP28,
volatile
organic
compounds
(
VOC)
sources
and
sinks.
Atlanta,
GA,
pp.
178­
194.
In:
Nagda,
N.
L.
Ed.,
Modeling
of
Indoor
Air
Quality
Hanley,
J.
T.;
Ensor,
D.
S.;
Smith,
D.
D.;
Sparks,
L.
E.
and
Exposure.
ASTM
STP
1205.
Philadelphia,
PA.:
(
1994)
Fractional
aerosol
filtration
efficiency
of
in­
American
Society
for
Testing
and
Materials,
pp.
64­
duct
ventilation
air
cleaners.
Indoor
Air.
4(
3):
179­
80.
188.
Dunn,
J.
E.;
Tichenor,
B.
A.
(
1988)
Compensating
for
sink
Hirvonen,
A.;
Pasanen,
P.;
Tarhanen,
J.;
Ruuskanen,
J.
effects
in
emissions
test
chambers
by
mathematical
(
1995)
Thermal
desorption
of
organic
compounds
modeling.
Atmospheric
Environ.,
22(
5)
885­
894.
associated
with
settled
household
dust.
Indoor
Air.
EBMUD.
(
1992)
Urban
water
management
plan.
East
5:
255­
264.
Bay
Municipal
Utility
Water
District,
in
written
Jennings,
P.
D.;
Carpenter,
C.
E.;
Krishnan,
M.
S.
(
1985)
communication
to
J.
B.
Andelman,
July
1992.
Methods
for
assessing
exposure
to
chemical
Furtaw,
E.
J.;
Pandian,
M.
D.;
Nelson,
D.
R;
Behar,
J.
V.
substances
volume
12:
methods
for
estimating
the
(
1995)
Modeling
indoor
air
concentrations
near
concentration
of
chemical
substances
in
indoor
air.
emission
sources
in
perfectly
mixed
rooms.
EPA
560/
5­
85­
016,
U.
S.
Environmental
Protection
Engineering
Solutions
to
Indoor
Air
Quality
Agency,
Office
of
Pesticides
and
Toxic
Substances,
Problems.
Presented
at
Sixth
Conference
of
the
Washington,
DC.
International
Society
for
Environmental
Epidemiology
Jennings,
P.
D.;
Hammerstrom,
K.
A.;
Adkins,
L.
C.;
and
Fourth
Conference
of
the
International
Society
for
Chambers,
T.;
Dixon,
D.
A.
(
1987)
Methods
for
Exposure
Analysis
(
Joint
Conference),
Research
assessing
exposure
to
chemical
substances
volume
7:
Triangle
Park,
NC,
September
1994.
methods
for
assessing
consumer
exposure
to
chemical
GEOMET.
(
1989)
Assessment
of
indoor
air
pollutant
substances.
EPA
560/
5­
85­
007,
U.
S.
Environmental
exposure
within
building
zones.
Report
Number
IE­
Protection
Agency,
Office
of
Pesticides
and
Toxic
2149,
prepared
for
USEPA
Office
of
Health
and
Substances,
Washington,
DC.
Environmental
Assessment
under
Contract
No.
68­
Koontz,
M.
D.;
Nagda,
N.
L.
(
1991)
A
multichamber
02­
4254,
Task
No.
235.
Germantown,
MD.:
model
for
assessing
consumer
inhalation
exposure.
GEOMET
Technologies,
Inc.
Indoor
Air.
1(
4):
593­
605.
Giardino,
N.
J.;
Gummerman,
E.;
Andelman,
J.
B.;
Wilkes,
Koontz,
M.
D.;
Rector,
H.
E.
(
1995)
Estimation
of
C.
R.;
Small,
M.
J.
(
1990)
Real­
time
measurements
of
distributions
for
residential
air
Exchange
rates,
EPA
trichloroethylene
in
domestic
bathrooms
using
Contract
No.
68­
D9­
0166,
Work
Assignment
No.
3­
contaminated
water.
Proceedings
of
the
5th
19,
U.
S.
Environmental
Protection
Agency,
Office
of
International
Conference
on
Indoor
Air
Quality
and
Pollution
Prevention
and
Toxics,
Washington,
DC.
Climate,
Toronto,
2:
707­
712.
Koontz,
M.
D.;
Rector,
H.
E.;
Fortmann,
R.
C.;
Nagda,
N.
L.
Grimsrud,
D.
T.;
Sherman,
M.
H.;
Sondereggen,
R.
C.
(
1988)
Preliminary
experiments
in
a
research
house
to
(
1983)
Calculating
infiltration:
implications
for
a
investigate
contaminant
migration
in
indoor
air.
EPA
construction
quality
standard.
In:
Proceedings
of
the
560/
5­
88­
004.
U.
S.
Environmental
Protection
American
Society
of
Heating,
Refrigerating
and
Air­
Agency,
Office
of
Pesticides
and
Toxic
Substances,
Conditioning
Engineers
Conference.
Thermal
Washington,
DC.
Performance
of
Exterior
Envelopes
of
Buildings
II.
Layton,
D.
W.;
Thatcher,
T.
L.
(
1995)
Movement
of
ASHRAE
SP38,
Atlanta,
GA,
pp.
422­
449.
outdoor
particles
to
the
indoor
environment:
An
analysis
of
the
Arnhem
Lead
Study.
Paper
No.
95­
Volume
III
­
Activity
Factors
Chapter
17
­
Residential
Building
Characteristics
Exposure
Factors
Handbook
Page
August
1997
17­
27
MP4.02.
Annual
Meeting
of
the
Air
and
Waste
Nazaroff,
W.
W.;
Cass,
G.
R.
(
1986)
Mathematical
Management
Association,
San
Antonio,
TX.
modeling
of
chemically
reactive
pollutants
in
indoor
Leaderer,
B.
P.;
Schaap,
L.;
Dietz,
R.
N.
(
1985)
air.
Environ.
Sci.
and
Technol.
20:
924­
934.
Evaluation
of
perfluorocarbon
tracer
technique
for
Nazaroff,
W.
W.;
Cass,
G.
R.
(
1989)
Mass­
transport
determining
infiltration
rates
in
residences.
Environ.
aspects
of
pollutant
removal
at
indoor
surfaces.
Sci.
and
Technol.
19(
12):
1225­
1232.
Environment
International,
15:
567­
584.
Liddament,
M.;
Allen,
C.
(
1983)
Validation
and
Nazaroff,
W.
W.;
Doyle,
S.
M.;
Nero,
A.
V.;
Sextro,
R.
G.
comparison
of
mathematical
models
of
air
infiltration.
(
1988).
Radon
entry
via
potable
water.
In:
Nazaroff,
Technical
Note
AIC
11.
Air
Infiltration
Centre,
Great
W.
W.
and
Nero,
A.
V.,
Eds.,
Radon
and
Its
Decay
Britain.
Products
in
Indoor
Air.
John
Wiley
and
Sons,
NY.
Ligman,
K.;
Hutzler,
N.;
Boyle,
W.
C.
(
1974)
Household
pp.
131­
157.
wastewater
characterization.
J.
Environ.
Eng.
Nazaroff,
W.
W.;
Gadgil,
A.
J.;
Weschler,
C.
J.
(
1993)
100:
201­
213.
Critique
of
the
use
of
deposition
velocity
in
modeling
Little,
J.
C.
(
1992)
Applying
the
two­
resistance
theory
to
indoor
air
quality.
In:
Nagda,
N.
L.
Ed.,
Modeling
of
contaminant
volatilization
in
showers.
Environ.
Sci.
Indoor
Air
Quality
and
Exposure,
ASTM
STP
1205,
and
Technol.
26(
7):
1341­
1349.
American
Society
for
Testing
and
Materials.
Little,
J.
C.;
Daisey,
J.
M.;
Nazaroff,
W.
W.
(
1992)
Philadelphia,
PA,
pp.
148­
165.
Transport
of
subsurface
contaminants
into
buildings
­­
Offerman,
F.
J.;
Sextro,
R.
G.;
Fisk,
W.;
Nazaroff,
W.
W.;
an
exposure
Pathway
for
Volatile
Organics.
Environ.
Nero,
A.
V.;
Revzan,
K.
L.;
Yater,
J.
(
1984)
Control
of
Sci.
and
Technol.
(
26)
11:
2058­
2066.
respirable
particles
and
radon
progeny
with
portable
Lucas,
R.
M.;
Grillo,
R.
B.;
Perez­
Michael,
A.;
Kemp,
S.
air
cleaners.
Report
No.
LBL­
16659,
Lawrence
(
1992)
National
residential
radon
survey
statistical
Berkley
Laboratory,
Berkley,
CA.
analysis
­­
volume
2:
summary
of
the
questionnaire
Pandian,
M.
H.;
Behar,
J.
V.;
Thomas,
J.
(
1993)
Use
of
a
data.
RTI/
5158/
49­
2F.
Research
Triangle
Institute,
relational
database
to
predict
human
population
Research
Triangle
Park,
NC.
exposures
for
different
time
periods.
Proceedings
of
Mage,
D.
T.;
Ott,
W.
R.
(
1994)
The
correction
for
Indoor
Air
`
93,
Helsinki
3:
283­
288.
nonuniform
mixing
in
indoor
environments.
ASTM
Persily,
A.
K.;
Linteris,
G.
T.
(
1984)
A
comparison
of
Symposium
on
Methods
for
Characterizing
Indoor
measured
and
predicted
infiltration
rates.
ASHRAE
Sources
and
Sinks,
Washington,
DC.
Transactions
89(
2):
183­
199.
McKone,
T.
E.
(
1987)
Human
exposure
to
volatile
Relwani,
S.
M.;
Moschandreas,
D.
J.;
Billick,
I.
H.
(
1986)
organic
compounds
in
household
tap
water:
The
Effects
of
operational
factors
on
pollutant
emission
inhalation
pathway.
Environ.
Sci.
and
Technol.
rates
from
residential
gas
appliances.
J.
Air
Poll.
21(
12):
1194­
1201.
Control
Assoc.
36:
1233­
1237.
McKone,
T.
E.
(
1989)
Household
exposure
models.
Roberts,
J.
W.;
Budd,
W.
T.;
Ruby,
M.
G.;
Bond,
A.
E.;
Toxicol.
Letters.
49:
321­
339.
Lewis,
R.
G.;
Wiener,
R.
W.;
Camann,
D.
E.
(
1991)
MWD.
(
1991)
Urban
water
use
characteristics
in
the
Development
and
field
testing
of
a
high
volume
metropolitan
water
district
of
southern
california.
sampler
for
pesticides
and
toxics
in
dust.
J.
Exposure
Draft
Report.
Metropolitan
Water
District
of
Anal.
and
Environ.
Epidemiol.
(
1)
2:
143­
155
Southern
California,
August
1991.
Ryan,
P.
B.
(
1991)
An
overview
of
human
exposure
Murray,
D.
M.
(
1996)
residential
house
and
zone
volumes
modeling.
J.
Exposure
Anal.
and
Environ.
Epidemiol.
in
the
United
States:
Empirical
and
Estimated
(
1)
4:
453­
474.
Parametric
Distributions.
Submitted
to
Risk
Analysis
Sandberg,
M.
(
1984)
The
Multi­
chamber
theory
in
1996.
reconsidered
from
the
viewpoint
of
air
quality
studies.
Murray,
D.
M.;
Burmaster,
D.
E.
(
1995)
Residential
air
Building
and
Environment
(
19)
4:
221­
233.
exchange
rates
in
the
United
States:
Empirical
and
Sextro,
R.
G.
(
1994)
Radon
and
the
natural
environment.
Estimated
Parametric
Distribution
by
Season
and
IN:
Nagda,
N.
L.
Ed.,
Radon
­­
Prevalence,
Climatic
Region.
Submitted
to
Risk
Analysis
in
1995.
Measurements,
Health
Risks
and
Control,
ASTM
MNL
15,
American
Society
for
Testing
and
Materials,
Philadelphia,
PA,
pp.
9­
32.
Volume
III
­
Activity
Factors
Chapter
17
­
Residential
Building
Characteristics
Page
Exposure
Factors
Handbook
17­
28
August
1997
Shaughnessy,
R.
J.;
Levetin,
E.;
Blocker,
J.;
Sublette,
K.
L.
Housing
and
Urban
Development,
Office
of
Policy
(
1994)
Effectiveness
of
portable
air
cleaners:
sensory
Development
and
Research.
testing
results.
Indoor
Air
4(
3):
179­
188.
U.
S.
DOE.
(
1995)
Housing
characteristics
1993,
Sherman,
M.
H.
(
1989)
Analysis
of
errors
associated
with
Residential
Energy
Consumption
Survey
(
RECS)
passive
ventilation
measurement
techniques.
Building
Report
No.
DOE/
EIA­
0314
(
93),
Washington,
DC:
and
Environment
24(
2):
131­
139.
U.
S.
Department
of
Energy,
Energy
Information
Sherman,
M.;
Dickerhoff,
D.
(
1996)
Air
tightness
of
Administration.
U.
S.
dwellings.
In:
The
Role
of
Ventilation
15th
AIVC
Conference
Proceedings.
Buxton,
Great
Britain,
September
27­
30,
1994.
Siegrist,
R.
(
1976)
Characteristics
of
rural
household
wastewater.
J.
Environ.
Eng.
1:
533­
548.
Sinden,
F.
W.
(
1978)
Multi­
chamber
theory
of
infiltration.
Building
and
Environment.
13:
21­
28.
Sparks,
L.
E.
(
1988)
Indoor
air
quality
model
version
1.0.
Report
No.
EPA­
600/
8­
88­
097a..
Research
Triangle
Park,
NC.
U.
S.
Environmental
Protection
Agency.
Sparks,
L.
E.
(
1991)
Exposure
­
Version
2.,
U.
S.
Environmental
Protection
Agency,
Office
of
Research
and
Development,
Research
Triangle
Park,
NC.
Swope,
A.
D.;
Goydan,
R.;
Reid,
R.
C.
(
1992)
Methods
for
assessing
exposure
to
chemical
substances
Volume
11:
Methodology
for
Estimating
the
Migration
of
Additives
and
Impurities
from
Polymeric
Substances.
EPA
560/
5­
85­
015,
U.
S.
Environmental
Protection
Agency,
Office
of
Pollution
Prevention,
Pesticides,
and
Toxic
Substances,
Washington,
DC.
Thatcher,
T.
L.;
Layton,
D.
W.
(
1995)
Deposition,
resuspension,
and
penetration
of
particles
within
a
residence.
Atmos.
Environ.
29(
13):
1487­
1497.
Thompson,
W.
(
1995)
U.
S.
Department
of
Energy
(
U.
S.
DOE)
and
Energy
Information
Administration.
Personal
communication
on
distribution
of
heated
floor
space
area
from
the
1993
RECS.
Tichenor,
B.
A.;
Guo,
Z.;
Dunn,
J.
E.;
Sparks,
L.
E.;
Mason,
M.
A.
(
1991)
The
interaction
of
vapor
phase
organic
compounds
with
indoor
sinks.
Indoor
Air
1:
23­
35.
Tucker,
W.
G.
(
1991)
Emission
of
organic
substances
from
indoor
surface
materials.
Environ.
Internat.
17:
357­
363.
U.
S.
Bureau
of
the
Census.
(
1992)
Statistical
abstract
of
the
United
States:
1992
(
112th
edition).
Table
No.
1230,
p.
721.
Washington,
DC.:
U.
S.
Department
of
Commerce.
U.
S.
DHUD.
(
1984)
Residential
water
conservation
projects:
summary
report.
Report
Number
HUDPDR
903.
Washington,
DC:
U.
S.
Department
of
Volume
III
­
Activity
Factors
Chapter
17
­
Residential
Building
Characteristics
Exposure
Factors
Handbook
Page
August
1997
17­
29
Versar.
(
1990)
Database
of
perfluorocarbon
tracer
(
PFT)
ventilation
measurements:
description
and
user's
manual.
USEPA
Contract
No.
68­
02­
4254,
Task
No.
39.
Washington,
D.
C:
U.
S.
Environmental
Protection
Agency,
Office
of
Toxic
Substances.
Wallace,
L.
A.
(
1996)
Indoor
particles:
A
review.
J.
Air
and
Waste
Management
Assoc.
(
46)
2:
98­
126.
Walton,
G.
N.
(
1993)
CONTAM
93
User
Manual.
NISTIR
5385.
Gaithersburg,
MD:
National
Institute
of
Standards
and
Technology.
Wilkes,
C.
R.;
Small,
M.
J.;
Andelman,
J.
B.;
Giardino,
N.
J.;
Marshall,
J.
(
1992)
Inhalation
exposure
model
for
volatile
chemicals
from
indoor
uses
of
water.
Atmospheric
Environment
(
26A)
12:
2227­
2236.
Wolkoff,
P.
(
1995)
Volatile
organic
compounds:
sources,
measurements,
emissions,
and
the
impact
on
indoor
air
quality.
Indoor
Air
Supplement
No.
3/
95,
pp
1­
73.
Wolkoff,
P.;
Wilkins,
C.
K.
(
1994)
Indoor
VOCs
from
household
floor
dust:
comparison
of
headspace
with
desorbed
VOCs;
Method
for
VOC
release
determination.
Indoor
Air
4:
248­
254.
Zinn,
T.
W.;
Cline,
D.;
Lehmann,
W.
F.
(
1990)
Long­
term
study
of
formaldehyde
emission
decay
from
particleboard.
Forest
Products
Journal
(
40)
6:
15­
18.
Volume
III
­
Activity
Factors
Chapter
17
­
Residential
Building
Characteristics
Page
Exposure
Factors
Handbook
17­
30
August
1997
Table
17­
29.
Volume
of
Residence
Surveys
Study
Number
of
Residences
Survey
Type
Areas
Surveyed
Comments
Key
Studies
U.
S.
DOE,
1995
(
RECS)
Over
7,000
Direct
measurement
of
floor
area;

estimation
of
volume
Nationwide
(
random
sample)
Volumes
were
estimated
assuming
8
ft.

ceiling
height.
Provides
relationships
between
average
residential
volumes
and
facilities
such
as
housing
type,
ownership,

household
size,
and
structure
age.

Versar,
1990
(
PFT
database)
Over
2,000
Direct
measurement
and
estimated
Nationwide
(
not
random
sample);
a
large
fraction
located
in
CA
Sample
was
not
geographically
balanced;

statistical
weighting
was
applied
to
develop
nationwide
distributions
Murray,
1996
7,041
(
RECS)

1,751
(
PFT)
Direct
measurements
and
estimated
RECS­
Nationwide
(
random
sample);
PFT
­
Nationwide
(
not
random
sample);
a
large
fraction
located
in
CA
Duplicate
measurement
were
eliminated;

tested
the
effects
of
using
8
ft.
assumption
on
ceiling
height
to
calculate
volume;
data
from
both
databases
were
analyzed.

Table
17­
30.
Air
Exchange
Rates
Surveys
Study
Number
of
Residences/
Measurements
Survey
Type
Areas
Surveyed
Comments
Versar,
1990
(
PFT
database)
Over
2,000
residences
Measurements
using
PFT
technique
Nationwide
(
not
random
sample);
a
large
fraction
located
in
CA
Multiple
measurements
on
the
same
home
were
included.

Koontz
&
Rector,
1995
(
PFT
database)
2,971
measurements
Measurements
using
PFT
technique
Nationwide
(
not
random
sample);
a
large
fraction
located
in
CA
Multiple
measurements
on
the
same
home
were
included.
Compensated
for
geographic
imbalances.
Data
are
presented
by
region
of
the
country
and
season.

Murray
and
Burmaster,
1995
(
PFT
database)
2,844
measurements
Measurements
using
PFT
technique
Nationwide
(
not
random
sample);
a
large
fraction
located
in
CA
Multiple
measurements
on
the
same
home
were
included.
Did
not
compensate
for
geographical
imbalances.
Data
are
presented
by
climate
region
and
season.

Nazaroff
et
al.,
1988
255
(
Grot
and
Clark,
1981)
Direct
measurement
255,
low­
income
families
in
14
cities
Sample
size
was
small
and
not
representative
of
the
U.
S.

312
(
Grimsrud,
1983)
Direct
measurement
321,
newer
residences,
median
age
<
10
years
Sample
size
was
small
and
not
representative
of
the
U.
S.
Volume
III
­
Activity
Factors
Chapter
17
­
Residential
Building
Characteristics
Exposure
Factors
Handbook
Page
August
1997
17­
31
Table
17­
31.
Recommendations
­
Residential
Parameters
Volume
of
Residence
369
m
(
central
estimate)
217
m
(
mean)
Air
Exchange
Rate
0.45
ACH
(
median)
0.18
ACH
(
10th
percentile)
3
a
c
3
b
d
a
Same
mean
value
presented
in
two
studies
(
Table
17­
1)
­
recommended
to
be
used
as
the
central
estimate.
b
Mean
of
two
25th
percentile
values
(
Table
17­
1)
­
recommended
to
be
used
as
the
mean
value.
c
Recommended
to
be
used
as
a
typical
value
(
Table
17­
10).
d
Recommended
to
be
used
as
a
conservative
value
(
Table
17­
10).

Table
17­
32.
Confidence
in
House
Volume
Recommendations
Considerations
Rationale
Rating
Study
Elements
°
Level
of
peer
review
All
key
studies
are
from
peer
reviewed
literature.
High
°
Accessibility
Papers
are
widely
available
from
peer
review
journals.
High
°
Reproducibility
Direct
measurements
were
made.
High
°
Focus
on
factor
of
The
focus
of
the
studies
was
on
estimating
house
volume
High
interest
as
well
as
other
factors.

°
Data
pertinent
to
U.
S.
Residences
in
the
U.
S.
was
the
focus
of
the
key
studies.
High
°
Primary
data
All
the
studies
were
based
on
primary
data.
High
°
Currency
Measurements
in
the
PFT
database
were
taken
between
Medium
1982­
1987.
The
RECS
survey
was
conducted
in
1993.

°
Adequacy
of
data
Not
applicable
collection
period
°
Validity
of
approach
For
the
RECS
survey,
volumes
were
estimated
assuming
Medium
an
8
ft.
ceiling
height.
The
effect
of
this
assumption
has
been
tested
by
Murray
(
1996)
and
found
to
be
insignificant.

°
Study
size
The
sample
sizes
used
in
the
key
studies
were
fairly
large,
Medium
although
only
1
study
(
RECS)
was
representative
of
the
whole
U.
S.
Not
all
samples
were
selected
at
random;
however,
RECS
samples
were
selected
at
random.

°
Representativeness
of
the
RECS
sample
is
representative
of
the
U.
S.
Medium
population
°
Characterization
of
Distributions
are
presented
by
housing
type
and
regions;
Medium
variability
although
some
of
the
sample
sizes
for
the
subcategories
were
small.

°
Lack
of
bias
in
study
design
Selection
of
residences
was
random
for
RECS.
Medium
(
high
rating
is
desirable)

°
Measurement
error
Some
measurement
error
may
exist
since
surface
areas
Medium
were
estimated
using
the
assumption
of
8
ft.
ceiling
height.

Other
Elements
°
Number
of
studies
There
are
3
key
studies;
however
there
are
only
2
data
Low
sets.

°
Agreement
between
researchers
There
is
good
agreement
among
researchers.
High
Overall
Rating
Results
were
consistent;
1
study
(
RECS)
was
Medium
representative
of
residences
in
the
whole
U.
S.;
volumes
were
estimated
rather
than
measured
in
some
cases.
Volume
III
­
Activity
Factors
Chapter
17
­
Residential
Building
Characteristics
Page
Exposure
Factors
Handbook
17­
32
August
1997
Table
17­
33.
Confidence
in
Air
Exchange
Rate
Recommendations
Considerations
Rationale
Rating
Study
Elements
°
Level
of
peer
review
The
studies
appear
in
peer
reviewed
literature.
Although
High
there
are
3
studies,
they
are
all
based
on
the
same
database
(
PFT
database).

°
Accessibility
Papers
are
widely
available
from
government
reports
and
High
peer
review
journals.

°
Reproducibility
Precision
across
repeat
analyses
has
been
documented
to
Medium
be
acceptable.

°
Focus
on
factor
of
The
focus
of
the
studies
was
on
estimating
air
exchange
High
interest
rates
as
well
as
other
factors.

°
Data
pertinent
to
U.
S.
Residences
in
the
U.
S.
was
the
focus
of
the
PFT
database.
High
°
Primary
data
All
the
studies
were
based
on
primary
data.
High
°
Currency
Measurements
in
the
PFT
database
were
taken
between
Medium
1982­
1987.

°
Adequacy
of
data
Only
short
term
data
were
collected;
some
residences
were
Medium
collection
period
measured
during
different
seasons;
however,
long
term
air
exchange
rates
are
not
well
characterized.

°
Validity
of
approach
Although
the
PFT
technology
is
an
EPA
standard
method
Low
(
Method
IP­
4A),
it
has
some
major
limitations
(
e.
g.,
uniform
mixing
assumption).

°
Study
size
The
sample
sizes
used
in
the
key
studies
were
fairly
large,
Medium
although
not
representative
of
the
whole
U.
S.
Not
all
samples
were
selected
at
random.

°
Representativeness
of
the
Sample
is
not
representative
of
the
U.
S..
Low
population
°
Characterization
of
Distributions
are
presented
by
U.
S.
regions,
seasons,
and
Low
variability
climatic
regions;
although
some
of
the
sample
sizes
for
the
subcategories
were
small
and
not
representative
of
U.
S.
The
utility
is
limited..

°
Lack
of
bias
in
study
design
Bias
may
result
since
the
selection
of
residences
was
not
Low
(
high
rating
is
desirable)
random.

°
Measurement
error
Some
measurement
error
may
exist.
Medium
Other
Elements
°
Number
of
studies
There
are
3
key
studies;
however
there
are
only
1
data
set.
Medium
However,
the
database
contains
results
of
20
projects
of
varying
scope.

°
Agreement
between
researchers
Not
applicable
Overall
Rating
Sample
was
not
representative
of
residences
in
the
whole
Low
U.
S.,
but
covered
the
range
of
occurrence.
PFT
methodology
has
limitations.
Uniform
mixing
assumption
may
not
be
adequate.
Results
will
vary
depending
on
placement
of
samples
and
on
whether
windows
and
doors
are
closed
or
opened.
