10/
02
Miscellaneous
Sources
13.2.1­
1
13.2.1
Paved
Roads
13.2.1.1
General
Particulate
emissions
occur
whenever
vehicles
travel
over
a
paved
surface
such
as
a
road
or
parking
lot.
Particulate
emissions
from
paved
roads
are
due
to
direct
emissions
from
vehicles
in
the
form
of
exhaust,
brake
wear
and
tire
wear
emissions
and
resuspension
of
loose
material
on
the
road
surface.
In
general
terms,
resuspended
particulate
emissions
from
paved
roads
originate
from,
and
result
in
the
depletion
of,
the
loose
material
present
on
the
surface
(
i.
e.,
the
surface
loading).
In
turn,
that
surface
loading
is
continuously
replenished
by
other
sources.
At
industrial
sites,
surface
loading
is
replenished
by
spillage
of
material
and
trackout
from
unpaved
roads
and
staging
areas.
Figure
13.2.1­
1
illustrates
several
transfer
processes
occurring
on
public
streets.

Various
field
studies
have
found
that
public
streets
and
highways,
as
well
as
roadways
at
industrial
facilities,
can
be
major
sources
of
the
atmospheric
particulate
matter
within
an
area.
1­
9
Of
particular
interest
in
many
parts
of
the
United
States
are
the
increased
levels
of
emissions
from
public
paved
roads
when
the
equilibrium
between
deposition
and
removal
processes
is
upset.
This
situation
can
occur
for
various
reasons,
including
application
of
granular
materials
for
snow
and
ice
control,
mud/
dirt
carryout
from
construction
activities
in
the
area,
and
deposition
from
wind
and/
or
water
erosion
of
surrounding
unstabilized
areas.
In
the
absence
of
continuous
addition
of
fresh
material
(
through
localized
trackout
or
application
of
antiskid
material),
paved
road
surface
loading
should
reach
an
equilibrium
value
in
which
the
amount
of
material
resuspended
matches
the
amount
replenished.
The
equilibrium
surface
loading
value
depends
upon
numerous
factors.
It
is
believed
that
the
most
important
factors
are:
mean
speed
of
vehicles
traveling
the
road;
the
average
daily
traffic
(
ADT);
the
number
of
lanes
and
ADT
per
lane;
the
fraction
of
heavy
vehicles
(
buses
and
trucks);
and
the
presence/
absence
of
curbs,
storm
sewers
and
parking
lanes.
10
EPA's
Office
of
Transportation
and
Air
Quality
plans
to
release
the
MOBILE6.1
model
soon.
This
model
will
calculate
particulate
emissions
from
on
road
mobile
sources
from
the
engine
exhaust,
brake
wear
and
tire
wear.
The
emission
factors
in
this
section
of
AP­
42
implicitly
include
the
emissions
of
exhaust,
brake
wear,
and
tire
wear
that
occurred
in
the
field
testing
that
produced
the
data
used
to
develop
the
emission
factor
equation,
in
addition
to
resuspended
particulate
matter
from
the
road
surface.
Therefore,
adding
the
emission
factors
in
this
section
to
those
calculated
by
MOBILE6.1
poses
the
problem
of
double
counting.
The
double
counting
problem
is
of
most
concern
when
estimating
the
emissions
on
high
traffic
volume
roads
with
low
surface
silt
loadings.
The
following
modifications
should
be
made
if
double
counting
is
a
substantial
issue
for
a
particular
application
of
this
section.
Where
MOBILE6.1
predicts
higher
emissions
of
particulate
matter
than
the
equations
in
this
section
for
a
given
combination
of
road
and
traffic
variables,
then
only
the
MOBILE6.1
results
should
be
used
and
resuspended
particulate
matter
should
be
considered
negligible.
Where
MOBILE6.1
predictions
are
less
than
the
emissions
that
would
be
predicted
from
the
equation
in
this
section,
then
the
emissions
calculated
with
the
equation
in
this
section
can
be
taken
as
a
reasonable
representation
of
total
particulate
emissions.
If
in
such
a
case
it
is
desired
to
separate
emissions
into
resuspended
particulate
matter
versus
exhaust,
brake
and
tire
wear
matter,
then
the
MOBILE6.1
estimates
can
be
subtracted
from
the
estimates
made
using
the
equation
in
this
section
with
the
remainder
taken
as
the
resuspended
portion
of
the
emissions.
13.2.1­
2
EMISSION
FACTORS
10/
02
13.2.1.2
Emissions
And
Correction
Parameters
Dust
emissions
from
paved
roads
have
been
found
to
vary
with
what
is
termed
the
"
silt
loading"
present
on
the
road
surface
as
well
as
the
average
weight
of
vehicles
traveling
the
road.
The
term
silt
loading
(
sL)
refers
to
the
mass
of
silt­
size
material
(
equal
to
or
less
than
75
micrometers
[
:
m]
in
physical
diameter)
per
unit
area
of
the
travel
surface.
The
total
road
surface
dust
loading
consists
of
loose
material
that
can
be
collected
by
broom
sweeping
and
vacuuming
of
the
traveled
portion
of
the
paved
road.
The
silt
fraction
is
determined
by
measuring
the
proportion
of
the
loose
dry
surface
dust
that
passes
through
a
200­
mesh
screen,
using
the
ASTM­
C­
136
method.
Silt
loading
is
the
product
of
the
silt
fraction
and
the
total
loading,
and
is
abbreviated
"
sL".
Additional
details
on
the
sampling
and
analysis
of
such
material
are
provided
in
AP­
42
Appendices
C.
1
and
C.
2.

The
surface
sL
provides
a
reasonable
means
of
characterizing
seasonal
variability
in
a
paved
road
emission
inventory.
In
many
areas
of
the
country,
road
surface
loadings
11­
21
are
heaviest
during
the
late
winter
and
early
spring
months
when
the
residual
loading
from
snow/
ice
controls
is
greatest.
As
noted
earlier,
once
replenishment
of
fresh
material
is
eliminated,
the
road
surface
loading
can
be
expected
to
reach
an
equilibrium
value,
which
is
substantially
lower
than
the
late
winter/
early
spring
values.
10/
02
Miscellaneous
Sources
13.2.1­
3
Figure
13.2.1­
1.
Deposition
and
removal
processes.
13.2.1­
4
EMISSION
FACTORS
10/
02
Table
13.2­
1.1.
PARTICLE
SIZE
MULTIPLIERS
FOR
PAVED
ROAD
EQUATION
Size
rangea
Particle
Size
Multiplier
kb
g/
VKT
g/
VMT
lb/
VMT
PM­
2.5c
1.1
1.8
0.0040
PM­
10
4.6
7.3
0.016
PM­
15
5.5
9.0
0.020
PM­
30d
24
38
0.082
a
Refers
to
airborne
particulate
matter
(
PM­
x)
with
an
aerodynamic
diameter
equal
to
or
less
than
x
micrometers.

b
Units
shown
are
grams
per
vehicle
kilometer
traveled
(
g/
VKT),
grams
per
vehicle
mile
traveled
(
g/
VMT),
and
pounds
per
vehicle
mile
traveled
(
lb/
VMT).
The
multiplier
k
includes
unit
conversions
to
produce
emission
factors
in
the
units
shown
for
the
indicated
size
range
from
the
mixed
units
required
in
Equation
1.

c
Ratio
of
PM­
2.5
to
PM­
10
taken
from
Reference
22.

d
PM­
30
is
sometimes
termed
"
suspendable
particulate"
(
SP)
and
is
often
used
as
a
surrogate
for
TSP.
13.2.1.3
Predictive
Emission
Factor
Equations10
The
quantity
of
particulate
emissions
from
vehicle
traffic
on
a
dry
paved
road
may
be
estimated
using
the
following
empirical
expression:
E=
k
(
sL/
2)
0.65
(
W/
3
)
1.5
(
1)
where:
E
=
particulate
emission
factor
(
having
units
matching
the
units
of
k)
k
=
particle
size
multiplier
for
particle
size
range
and
units
of
interest
(
see
below)
sL
=
road
surface
silt
loading
(
grams
per
square
meter)
(
g/
m2)
W
=
average
weight
(
tons)
of
the
vehicles
traveling
the
road
It
is
important
to
note
that
Equation
1
calls
for
the
average
weight
of
all
vehicles
traveling
the
road.
For
example,
if
99
percent
of
traffic
on
the
road
are
2
ton
cars/
trucks
while
the
remaining
1
percent
consists
of
20
ton
trucks,
then
the
mean
weight
"
W"
is
2.2
tons.
More
specifically,
Equation
1
is
not
intended
to
be
used
to
calculate
a
separate
emission
factor
for
each
vehicle
weight
class.
Instead,
only
one
emission
factor
should
be
calculated
to
represent
the
"
fleet"
average
weight
of
all
vehicles
traveling
the
road.

The
particle
size
multiplier
(
k)
above
varies
with
aerodynamic
size
range
as
shown
in
Table
13.2.1­
1.
To
determine
particulate
emissions
for
a
specific
particle
size
range,
use
the
appropriate
value
of
k
shown
in
Table
13.2.1­
1.

The
above
equation
is
based
on
a
regression
analysis
of
numerous
emission
tests,
including
65
tests
for
PM­
10.10
Sources
tested
include
public
paved
roads,
as
well
as
controlled
and
uncontrolled
industrial
paved
roads.
All
sources
tested
were
of
freely
flowing
vehicles
traveling
at
constant
speed
on
relatively
level
roads
.
No
tests
of
"
stop­
and­
go"
traffic
or
vehicles
under
load
were
available
for
inclusion
in
the
data
base.
The
equations
retain
the
quality
rating
of
A
(
B
for
PM­
2.5),
if
applied
within
the
range
of
source
conditions
that
were
tested
in
developing
the
equation
as
follows:
10/
02
Miscellaneous
Sources
13.2.1­
5
Silt
loading:
0.02
­
400
g/
m2
0.03
­
570
grains/
square
foot
(
ft2)
Mean
vehicle
weight:
1.8
­
38
megagrams
(
Mg)
2.0
­
42
tons
Mean
vehicle
speed:
16
­
88
kilometers
per
hour
(
kph)
10
­
55
miles
per
hour
(
mph)

To
retain
the
quality
rating
for
the
emission
factor
equation
when
it
is
applied
to
a
specific
paved
road,
it
is
necessary
that
reliable
correction
parameter
values
for
the
specific
road
in
question
be
determined.
With
the
exception
of
limited
access
roadways,
which
are
difficult
to
sample,
the
collection
and
use
of
site­
specific
silt
loading
(
sL)
data
for
public
paved
road
emission
inventories
are
strongly
recommended.
The
field
and
laboratory
procedures
for
determining
surface
material
silt
content
and
surface
dust
loading
are
summarized
in
Appendices
C.
1
and
C.
2.
In
the
event
that
site­
specific
values
cannot
be
obtained,
an
appropriate
value
for
a
paved
public
road
may
be
selected
from
the
values
given
in
Table
13.2.1­
2,
but
the
quality
rating
of
the
equation
should
be
reduced
by
2
levels.
Also,
recall
that
Equation
1
refers
to
emissions
due
to
freely
flowing
(
not
stop­
and­
go)
traffic
at
constant
speed
on
level
roads.

Equation
1
may
be
extrapolated
to
average
uncontrolled
conditions
(
but
including
natural
mitigation)
under
the
simplifying
assumption
that
annual
(
or
other
long­
term)
average
emissions
are
inversely
proportional
to
the
frequency
of
measurable
(>
0.254
mm
[
0.01
inch])
precipitation
by
application
of
a
precipitation
correction
term.
The
precipitation
correction
term
can
be
applied
on
a
daily
or
an
hourly
basis.
For
the
daily
basis,
equation
1
becomes:

Eext
=
k
(
sL/
2)
0.65
(
W/
3
)
1.5
(
1­
P/
4N)
(
2)

where
k,
sL,
and
W
are
as
defined
in
Equation
1
and
Eext
=
annual
or
other
long­
term
average
emission
factor
in
the
same
units
as
k
P
=
number
of
"
wet"
days
with
at
least
0.254
mm
(
0.01
in)
of
precipitation
during
the
averaging
period
N
=
number
of
days
in
the
averaging
period
(
e.
g.,
365
for
annual,
91
for
seasonal,
30
for
monthly)

Note
that
the
assumption
leading
to
Equation
2
is
based
on
analogy
with
the
approach
used
to
develop
long­
term
average
unpaved
road
emission
factors
in
Section
13.2.2.
However,
Equation
2
above
incorporates
an
additional
factor
of
"
4"
in
the
denominator
to
account
for
the
fact
that
paved
roads
dry
more
quickly
than
unpaved
roads
and
that
the
precipitation
may
not
occur
over
the
complete
24­
hour
day.

For
the
hourly
basis,
equation
1
becomes:

Eext
=
k
(
sL/
2)
0.65
(
W/
3
)
1.5
(
1­
1.2P/
N)
(
3)

where
k,
sL,
and
W
are
as
defined
in
Equation
1
and
Eext
=
annual
or
other
long­
term
average
emission
factor
in
the
same
units
as
k
P
=
number
of
hours
with
at
least
0.254
mm
(
0.01
in)
of
precipitation
during
the
averaging
period
N
=
number
of
hours
in
the
averaging
period
(
e.
g.,
8760
for
annual,
2124
for
seasonal,
720
for
monthly)
13.2.1­
6
EMISSION
FACTORS
10/
02
Note:
In
the
hourly
moisture
correction
term
(
1­
1.2P/
N)
for
equation
3,
the
1.2
multiplier
is
applied
to
account
for
the
residual
mitigative
effect
of
moisture.
For
most
applications,
this
equation
will
produce
satisfactory
results.
However,
if
the
time
interval
for
which
the
equation
is
applied
is
short,
e.
g.,
for
one
hour
or
one
day,
the
application
of
this
multiplier
makes
it
possible
for
the
moisture
correction
term
to
become
negative.
This
will
result
in
calculated
negative
emissions
which
is
not
realistic.
Users
should
expand
the
time
interval
to
include
sufficient
"
dry"
hours
such
that
negative
emissions
are
not
calculated.
For
the
special
case
where
this
equation
is
used
to
calculate
emissions
on
an
hour
by
hour
basis,
such
as
would
be
done
in
some
emissions
modeling
situations,
the
moisture
correction
term
should
be
modified
so
that
the
moisture
correction
"
credit"
is
applied
to
the
first
hours
following
cessation
of
precipitation.
In
this
special
case,
it
is
suggested
that
this
20%
"
credit"
be
applied
on
a
basis
of
one
hour
credit
for
each
hour
of
precipitation
up
to
a
maximum
of
12
hours.

Note
that
the
assumption
leading
to
Equation
3
is
based
on
analogy
with
the
approach
used
to
develop
long­
term
average
unpaved
road
emission
factors
in
Section
13.2.2.

Figure
13.2.1­
2
presents
the
geographical
distribution
of
"
wet"
days
on
an
annual
basis
for
the
United
States.
Maps
showing
this
information
on
a
monthly
basis
are
available
in
the
Climatic
Atlas
of
the
United
States23
.
Alternative
sources
include
other
Department
of
Commerce
publications
(
such
as
local
climatological
data
summaries).
The
National
Climatic
Data
Center
(
NCDC)
offers
several
products
that
provide
hourly
precipitation
data.
In
particular,
NCDC
offers
Solar
and
Meteorological
Surface
Observation
Network
1961­
1990
(
SAMSON)
CD­
ROM,
which
contains
30
years
worth
of
hourly
meteorological
data
for
first­
order
National
Weather
Service
locations.
Whatever
meteorological
data
are
used,
the
source
of
that
data
and
the
averaging
period
should
be
clearly
specified.

It
is
emphasized
that
the
simple
assumption
underlying
Equations
2
and
3
has
not
been
verified
in
any
rigorous
manner.
For
that
reason,
the
quality
ratings
for
Equations
2
and
3
should
be
downgraded
one
letter
from
the
rating
that
would
be
applied
to
Equation
1.

During
the
preparation
of
the
background
document
(
Reference
10),
public
road
silt
loading
values
from
1992
and
earlier
were
assembled
into
a
data
base.
This
data
base
is
available
in
the
file
named
"
r13s03­
1b.
zip"
located
at
the
Internet
URL
"
http://
www.
epa.
gov/
ttn/
chief/
ap42/
ch13/
related/
c13s02­
1.
html"
on
the
World
Wide
Web.
Although
hundreds
of
public
paved
road
silt
loading
measurements
had
been
collected,
there
was
no
uniformity
in
sampling
equipment
and
analysis
techniques,
in
roadway
classification
schemes,
and
in
the
types
of
data
reported.
Not
surprisingly,
the
data
set
did
not
yield
a
coherent
relationship
between
silt
loading
and
road
class,
average
daily
traffic
(
ADT),
etc.,
even
though
an
inverse
relationship
between
silt
loading
and
ADT
has
been
found
for
a
subclass
of
curbed
paved
roads
in
urban
areas.
Further
complicating
the
analysis
is
the
fact
that,
in
many
parts
of
the
country,
paved
road
silt
loading
varies
greatly
over
the
course
of
the
year,
probably
because
of
cyclic
variations
in
mud/
dirt
carryout
and
in
use
of
anti­
skid
materials.
Although
there
were
strong
reasons
to
suspect
that
the
assembled
data
base
was
skewed
towards
high
values,
independent
data
were
not
available
to
confirm
the
suspicions.
10/
02
Miscellaneous
Sources
13.2.1­
7
Figure
13.2.1­
2.
Mean
number
of
days
with
0.01
inch
or
more
of
precipitation
in
the
United
States.
13.2.1­
8
EMISSION
FACTORS
10/
02
Table
13.2.1­
2
(
Metric
Units).
RECOMMENDED
DEFAULT
SILT
LOADING
(
g/
m2)
VALUES
FOR
PUBLIC
PAVED
ROADSa
High
ADT
roadsb
Low
ADT
roads
Normal
conditions
0.1
0.4
Worst­
case
conditionsc
0.5
3
a
Excluding
limited
access
roads.
See
discussion
in
text.
1
g/
m2
is
equal
to
1.43
grains/
ft2
b
High
ADT
refers
to
roads
with
at
least
5,000
vehicles
per
day.
c
For
conditions
such
as
post­
winter­
storm
or
areas
with
substantial
mud/
dirt
carryout.
Since
the
time
that
the
background
document
was
prepared,
new
field
sampling
programs
have
shown
that
the
assembled
silt
loading
data
set
is
biased
high
for
"
normal"
situations.
24
Just
as
importantly,
however,
the
newer
programs
confirm
that
substantially
higher
than
"
normal"
silt
loadings
can
occur
on
public
paved
roads.
As
a
result,
two
sets
of
default
values
are
provided
in
Table
13.2.1­
2,
one
for
"
normal"
conditions
and
another
for
worst­
case
conditions
(
such
as
after
winter
storm
seasons
or
in
areas
with
substantial
mud/
dirt
trackout).
The
"
normal"
silt
loading
data
base
is
available
in
the
file
"
r13s03­
1a.
zip"
located
at
the
Internet
URL
"
http://
www.
epa.
gov/
ttn/
chief/
ap42/
ch13/
related/
c13s02­
1.
html"
on
the
World
Wide
Web.

The
range
of
silt
loading
values
in
the
data
base
for
normal
conditions
is
0.01
to
1.0
for
high­
ADT
roads
and
0.054
to
6.8
for
low­
ADT
roads.
Consequently
the
use
of
a
default
value
from
Table
13.2.1­
2
should
be
expected
to
yield
only
an
order­
of­
magnitude
estimate
of
the
emission
factor.
Public
paved
road
silt
loadings
are
dependent
upon:
traffic
characteristics
(
speed,
ADT,
and
fraction
of
heavy
vehicles);
road
characteristics
(
curbs,
number
of
lanes,
parking
lanes);
local
land
use
(
agriculture,
new
residential
construction)
and
regional/
seasonal
factors
(
snow/
ice
controls,
wind
blown
dust).
As
a
result,
the
collection
and
use
of
site­
specific
silt
loading
data
is
highly
recommended.
In
the
event
that
default
silt
loading
values
are
used,
the
quality
ratings
for
the
equation
should
be
downgraded
2
levels.

Limited
access
roadways
pose
severe
logistical
difficulties
in
terms
of
surface
sampling,
and
few
silt
loading
data
are
available
for
such
roads.
Nevertheless,
the
available
data
do
not
suggest
great
variation
in
silt
loading
for
limited
access
roadways
from
one
part
of
the
country
to
another.
For
annual
conditions,
a
default
value
of
0.015
g/
m2
is
recommended
for
limited
access
roadways.
9,22
Even
fewer
of
the
available
data
correspond
to
worst­
case
situations,
and
elevated
loadings
are
observed
to
be
quickly
depleted
because
of
high
traffic
speeds
and
high
ADT
rates.
A
default
value
of
0.2
g/
m2
is
recommended
for
short
periods
of
time
following
application
of
snow/
ice
controls
to
limited
access
roads.
22
The
limited
data
on
silt
loading
values
for
industrial
roads
have
shown
as
much
variability
as
public
roads.
Because
of
the
variations
of
traffic
conditions
and
the
use
of
preventive
mitigative
controls,
the
data
probably
do
not
reflect
the
full
extent
of
the
potential
variation
in
silt
loading
on
industrial
roads.
However,
the
collection
of
site
specific
silt
loading
data
from
industrial
roads
is
easier
and
safer
than
for
public
roads.
Therefore,
the
collection
and
use
of
site­
specific
silt
loading
data
is
preferred
and
is
highly
recommended.
In
the
event
that
site­
specific
values
cannot
be
obtained,
an
appropriate
value
for
an
industrial
road
may
be
selected
from
the
mean
values
given
in
Table
13.2.1­
3,
but
the
quality
rating
of
the
equation
should
be
reduced
by
2
levels.
10/
02
Miscellaneous
Sources
13.2.1­
9
Table
13.2.1­
3
(
Metric
And
English
Units).
TYPICAL
SILT
CONTENT
AND
LOADING
VALUES
FOR
PAVED
ROADS
AT
INDUSTRIAL
FACILITIESa
Industry
No.
Of
Sites
No.
Of
Sample
s
Silt
Content
(%)
No.
Of
Travel
Lanes
Total
Loading
x
10
!
3
Silt
Loading
(
g/
m2)

Range
Mean
Range
Mean
Unitsb
Range
Mean
Copper
smelting
1
3
15.4­
21.7
19.0
2
12.9­
19.5
45.8­
69.2
15.9
55.4
kg/
km
lb/
mi
188­
400
292
Iron
and
steel
production
9
48
1.1­
35.7
12.5
2
0.006­
4.77
0.020­
16.9
0.495
1.75
kg/
km
lb/
mi
0.09­
79
9.7
Asphalt
batching
1
3
2.6­
4.6
3.3
1
12.1­
18.0
43.0­
64.0
14.9
52.8
kg/
km
lb/
mi
76­
193
120
Concrete
batching
1
3
5.2­
6.0
5.5
2
1.4­
1.8
5.0­
6.4
1.7
5.9
kg/
km
lb/
mi
11­
12
12
Sand
and
gravel
processing
1
3
6.4­
7.9
7.1
1
2.8­
5.5
9.9­
19.4
3.8
13.3
kg/
km
lb/
mi
53­
95
70
Municipal
solid
waste
landfill
2
7
 
 
2
 
 
 
1.1­
32.0
7.4
Quarry
1
6
 
 
2
 
 
 
2.4­
14
8.2
a
References
1­
2,5­
6,11­
13.
Values
represent
samples
collected
from
industrial
roads.
Public
road
silt
loading
values
are
presented
in
Table­
13.2.1­
2.
Dashes
indicate
information
not
available.

b
Multiply
entries
by
1000
to
obtain
stated
units;
kilograms
per
kilometer
(
kg/
km)
and
pounds
per
mile
(
lb/
mi).
13.2.1­
10
EMISSION
FACTORS
10/
02
13.2.1.4
Controls6,25
Because
of
the
importance
of
the
silt
loading,
control
techniques
for
paved
roads
attempt
either
to
prevent
material
from
being
deposited
onto
the
surface
(
preventive
controls)
or
to
remove
from
the
travel
lanes
any
material
that
has
been
deposited
(
mitigative
controls).
Covering
of
loads
in
trucks,
and
the
paving
of
access
areas
to
unpaved
lots
or
construction
sites,
are
examples
of
preventive
measures.
Examples
of
mitigative
controls
include
vacuum
sweeping,
water
flushing,
and
broom
sweeping
and
flushing.
Actual
control
efficiencies
for
any
of
these
techniques
can
be
highly
variable.
Locally
measured
silt
loadings
before
and
after
the
application
of
controls
is
the
preferred
method
to
evaluate
controls.
It
is
particularly
important
to
note
that
street
sweeping
of
gutters
and
curb
areas
may
actually
increase
the
silt
loading
on
the
traveled
portion
of
the
road.
Redistribution
of
loose
material
onto
the
travel
lanes
will
actually
produce
a
short­
term
increase
in
the
emissions.

In
general,
preventive
controls
are
usually
more
cost
effective
than
mitigative
controls.
The
costeffectiveness
of
mitigative
controls
falls
off
dramatically
as
the
size
of
an
area
to
be
treated
increases.
The
cost­
effectiveness
of
mitigative
measures
is
also
unfavorable
if
only
a
short
period
of
time
is
required
for
the
road
to
return
to
equilibrium
silt
loading
condition.
That
is
to
say,
the
number
and
length
of
public
roads
within
most
areas
of
interest
preclude
any
widespread
and
routine
use
of
mitigative
controls.
On
the
other
hand,
because
of
the
more
limited
scope
of
roads
at
an
industrial
site,
mitigative
measures
may
be
used
quite
successfully
(
especially
in
situations
where
truck
spillage
occurs).
Note,
however,
that
public
agencies
could
make
effective
use
of
mitigative
controls
to
remove
sand/
salt
from
roads
after
the
winter
ends.

Because
available
controls
will
affect
the
silt
loading,
controlled
emission
factors
may
be
obtained
by
substituting
controlled
silt
loading
values
into
the
equation.
(
Emission
factors
from
controlled
industrial
roads
were
used
in
the
development
of
the
equation.)
The
collection
of
surface
loading
samples
from
treated,
as
well
as
baseline
(
untreated),
roads
provides
a
means
to
track
effectiveness
of
the
controls
over
time.

13.2.1.5
Changes
since
Fifth
Edition
The
following
changes
were
made
since
the
publication
of
the
Fifth
Edition
of
AP­
42:

1)
The
particle
size
multiplier
was
reduced
by
approximately
55%
as
a
result
of
emission
testing
specifically
to
evaluate
the
PM­
2.5
component
of
the
emissions.

2)
Default
silt
loading
values
were
included
in
Table
13.2.1­
2
replacing
the
Tables
and
Figures
containing
silt
loading
statistical
information.

3)
Editorial
changes
within
the
text
were
made
indicating
the
possible
causes
of
variations
in
the
silt
loading
between
roads
within
and
among
different
locations.
The
uncertainty
of
using
the
default
silt
loading
value
was
discussed.

4)
Section
13.2.1.1
was
revised
to
clarify
the
role
of
dust
loading
in
resuspension.
Additional
minor
text
changes
were
made.

5)
Equations
2
and
3,
Figure
13.2.1­
2,
and
text
were
added
to
incorporate
natural
mitigation
into
annual
or
other
long­
term
average
emission
factors.

6)
Discussion
was
added
to
the
text
on
the
application
of
the
MOBILE6.1
model
and
this
section
of
AP­
42.
10/
02
Miscellaneous
Sources
13.2.1­
11
7)
References
were
rearranged
and
renumbered.

References
For
Section
13.2.1
1.
D.
R.
Dunbar,
Resuspension
Of
Particulate
Matter,
EPA­
450/
2­
76­
031,
U.
S.
Environmental
Protection
Agency,
Research
Triangle
Park,
NC,
March
1976.

2.
R.
Bohn,
et
al.,
Fugitive
Emissions
From
Integrated
Iron
And
Steel
Plants,
EPA­
600/
2­
78­
050,
U.
S.
Environmental
Protection
Agency,
Cincinnati,
OH,
March
1978.

3.
C.
Cowherd,
Jr.,
et
al.,
Iron
And
Steel
Plant
Open
Dust
Source
Fugitive
Emission
Evaluation,
EPA­
600/
2­
79­
103,
U.
S.
Environmental
Protection
Agency,
Cincinnati,
OH,
May
1979.

4.
C.
Cowherd,
Jr.,
et
al.,
Quantification
Of
Dust
Entrainment
From
Paved
Roadways,
EPA­
450/
3­
77­
027,
U.
S.
Environmental
Protection
Agency,
Research
Triangle
Park,
NC,
July
1977.

5.
Size
Specific
Particulate
Emission
Factors
For
Uncontrolled
Industrial
And
Rural
Roads,
EPA
Contract
No.
68­
02­
3158,
Midwest
Research
Institute,
Kansas
City,
MO,
September
1983.

6.
T.
Cuscino,
Jr.,
et
al.,
Iron
And
Steel
Plant
Open
Source
Fugitive
Emission
Control
Evaluation,
EPA­
600/
2­
83­
110,
U.
S.
Environmental
Protection
Agency,
Cincinnati,
OH,
October
1983.

7.
J.
P.
Reider,
Size­
specific
Particulate
Emission
Factors
For
Uncontrolled
Industrial
And
Rural
Roads,
EPA
Contract
68­
02­
3158,
Midwest
Research
Institute,
Kansas
City,
MO,
September
1983.

8.
C.
Cowherd,
Jr.,
and
P.
J.
Englehart,
Paved
Road
Particulate
Emissions,
EPA­
600/
7­
84­
077,
U.
S.
Environmental
Protection
Agency,
Cincinnati,
OH,
July
1984.

9.
C.
Cowherd,
Jr.,
and
P.
J.
Englehart,
Size
Specific
Particulate
Emission
Factors
For
Industrial
And
Rural
Roads,
EPA­
600/
7­
85­
038,
U.
S.
Environmental
Protection
Agency,
Cincinnati,
OH,
September
1985.

10.
Emission
Factor
Documentation
For
AP­
42,
Sections
11.2.5
and
11.2.6
 
Paved
Roads,
EPA
Contract
No.
68­
D0­
0123,
Midwest
Research
Institute,
Kansas
City,
MO,
March
1993.

11.
Evaluation
Of
Open
Dust
Sources
In
The
Vicinity
Of
Buffalo,
New
York,
EPA
Contract
No.
68­
02­
2545,
Midwest
Research
Institute,
Kansas
City,
MO,
March
1979.

12.
PM­
10
Emission
Inventory
Of
Landfills
In
The
Lake
Calumet
Area,
EPA
Contract
No.
68­
02­
3891,
Midwest
Research
Institute,
Kansas
City,
MO,
September
1987.

13.
Chicago
Area
Particulate
Matter
Emission
Inventory
 
Sampling
And
Analysis,
Contract
No.
68­
02­
4395,
Midwest
Research
Institute,
Kansas
City,
MO,
May
1988.

14.
Montana
Street
Sampling
Data,
Montana
Department
Of
Health
And
Environmental
Sciences,
Helena,
MT,
July
1992.

15.
Street
Sanding
Emissions
And
Control
Study,
PEI
Associates,
Inc.,
Cincinnati,
OH,
October
1989.
13.2.1­
12
EMISSION
FACTORS
10/
02
16.
Evaluation
Of
PM­
10
Emission
Factors
For
Paved
Streets,
Harding
Lawson
Associates,
Denver,
CO,
October
1991.

17.
Street
Sanding
Emissions
And
Control
Study,
RTP
Environmental
Associates,
Inc.,
Denver,
CO,
July
1990.

18.
Post­
storm
Measurement
Results
 
Salt
Lake
County
Road
Dust
Silt
Loading
Winter
1991/
92
Measurement
Program,
Aerovironment,
Inc.,
Monrovia,
CA,
June
1992.

19.
Written
communication
from
Harold
Glasser,
Department
of
Health,
Clark
County
(
NV).

20.
PM­
10
Emissions
Inventory
Data
For
The
Maricopa
And
Pima
Planning
Areas,
EPA
Contract
No.
68­
02­
3888,
Engineering­
Science,
Pasadena,
CA,
January
1987.

21.
Characterization
Of
PM­
10
Emissions
From
Antiskid
Materials
Applied
To
Ice­
And
Snow­
Covered
Roadways,
EPA
Contract
No.
68­
D0­
0137,
Midwest
Research
Institute,
Kansas
City,
MO,
October
1992.

22.
Fugitive
Particulate
Matter
Emissions,
EPA
Contract
No.
68­
D2­
0159,
Work
Assignment
No.
4­
06,
Midwest
Research
Institute,
Kansas
City,
MO,
April
1997.

23.
Climatic
Atlas
Of
The
United
States,
U.
S.
Department
of
Commerce,
Washington,
D.
C.,
June
1968.

24.
Written
communication
from
G.
Muleski,
Midwest
Research
Institute,
Kansas
City,
MO,
to
R.
Myers,
U.
S.
Environmental
Protection
Agency,
Research
Triangle
Park,
NC,
September
30,
1997.

25.
C.
Cowherd,
Jr.,
et
al.,
Control
Of
Open
Fugitive
Dust
Sources,
EPA­
450/
3­
88­
008,
U.
S.
Environmental
Protection
Agency,
Research
Triangle
Park,
NC,
September
1988.
