PBT
Profiler
Methodology
[Persistence][
Bioaccumulation][
Toxicity][
Results]
Introduction
The
PBT
profiler
uses
a
well­
defined
set
of
procedures
to
predict
the
persistence,
bioaccumulation,
and
toxicity
of
chemical
compounds
when
experimental
data
are
not
available.
The
only
user­
required
inputs
for
the
PBT
profiler
are
a
unique
identifier
(e.
g.,
a
CAS
Registry
Number,
product
ID,
or
acronym)
and
a
chemical
structure.
Chemical
structures
are
entered
into
the
PBT
profiler
using
a
SMILES
notation
[Weininger,
D.
SMILES,
A
Chemical
and
Information
System.
1.
Introduction
to
Methodology
and
Encoding
Rules.
Journal
of
Chemical
Information
and
Computer
Sciences
28:
31­
6
(1988)].
An
automatic
look­
up
function
based
on
the
CAS
Registry
number
simplifies
this
process
by
automatically
retrieving
a
chemical's
SMILES
notation
using
a
pre­
existing
database
containing
over
100,000
records.
The
chemical
structure
is
then
passed
to
nine
separate
estimation
modules,
and
the
results
are
converted
electronically
to
a
persistence,
bioaccumulation,
and
toxicity
value.
The
methodology
used
by
the
PBT
profiler
and
its
estimation
modules
is
discussed
in
this
section.

The
persistence,
bioaccumulation,
and
toxicity
values
estimated
by
the
PBT
profiler
are
automatically
compared
to
criteria
published
by
the
EPA
and
other
international
agencies.
Those
values
that
that
meet
or
exceed
the
criteria
are
flagged
for
the
user
on
the
PBT
Profiler
results
page.
A
discussion
of
the
persistence,
bioaccumulation,
and
toxicity
criteria
used
by
the
PBT
Profiler
is
provided.

Persistence
Air
The
PBT
profiler
calculates
an
atmospheric
half­
life
by
determining
the
importance
of
a
chemical's
reaction
with
two
of
the
most
prevalent
atmospheric
oxidants,
hydroxyl
radicals
and
ozone.
The
half­
life
is
calculated
directly
from
gas­
phase
hydroxyl
radical
and
ozone
reaction
rate
constants.
These
rate
constants
are
obtained
from
a
database
of
measured
values
or,
if
no
experimental
values
are
available,
they
are
estimated
using
the
method
of
Atkinson
[Meylan,
W.
M.
and
Howard.
P.
H.
Computer
Estimation
of
the
Atmospheric
Gas­
Phase
Reaction
Rate
of
Organic
Compounds
with
Hydroxyl
Radicals
and
Ozone.
Chemosphere
26:
2293­
9
(1993)].
The
half­
life
is
calculated
from
the
rate
constant
and
an
average
atmospheric
concentration
of
these
oxidants
based
on
a
24hourday[
Prinn,
R.,
Cunnold,
P.,
Simmonds,
R.,
Alyea,
R.,
Boldi,
A.,
Crawford,
P.,
Fraser,
D.,
Gutzler,
D.,
Hartley,
R.,
Rosen,
R.,
and
Rasmussen
R.
Global
Average
Concentration
and
Trend
for
Hydroxyl
Radicals
Deduced
From
ALE/
GAGE
Trichloroethane
(Methyl
Chloroform)
Data
for
1978­
1990.
Journal
of
Geophysical
Research
97:
2445­
61
(1992);
Atkinson,
R
and
Carter,
W.
P.
L.
Kinetics
and
Mechanisms
of
the
Gas­
Phase
Reactions
of
Ozone
with
Organic
Compounds
under
Atmospheric
Conditions.
Chemical
Reviews
84:
437­
70
(1984)].

The
atmoshperic
half­
life
for
each
process
is
calculated
as
follows:

Hydroxyl
radicals
t1/
2
=
0.
693/(
rate
constant
cm
3
/molecule­
sec
x
5x10
5
molecules/
cm
3
*
86400
sec/
day)

Ozone
t1/
2
=
0.
693/(
rate
constant
cm
3
/molecule­
sec
x
7x10
11
molecules/
cm
3
*
86400
sec/
day)

and
the
overall
half­
life
is
obtained
as:

1/
t1/
2overall
=
1/
t1/
2
Hydroxyl
radicals
+
1/
t1/
2
Ozone
Water,
Soil,
and
Sediment
Half­
lives
for
water,
soil,
and
sediment
are
determined
using
the
ultimate
biodegradation
expert
survey
module
of
the
BIOWIN
estimation
program
[Boethling,
R.
S.,
Howard,
P.
H.,
Meylan,
W.
M.,
Stiteler,
W.,
Beauman,
J.,
and
Tirado,
N.,
Group
Contribution
Method
for
Predicting
Probability
and
Rate
of
Aerobic
Biodegradation.
Environmental
Science
and
Technology
28:
459­
65
(1994)].
This
estimation
program
provides
an
indication
of
a
chemical's
environmental
biodegradation
rate
in
relative
terms
such
as
hours,
hours
to
days,
days,
days
to
weeks,
and
so
on;
the
terms
represent
the
approximate
amount
of
time
needed
for
degradation
to
be
"complete".
This
output
cannot
be
directly
compared
to
established
half­
life
criteria
for
purposes
of
identifying
chemicals
with
PBT
characteristics,
nor
can
it
be
used
directly
by
the
Level
III
fugacity
model.
These
conversion
factors
consider
that
6
half­
lives
constitute
"complete"
degradation
of
a
chemical
substance
to
occur
(assuming
first­
order
kinetics)
and
are
based
on
the
mean
value
within
the
estimated
time
range.
The
resulting
conversion
factors
for
water
are
provided
below.

BIOWIN
Output
Converted
Half­
Life
(days)

Hours
0.
17
Hours
to
Days
1.
25
Days
2.33
Days
to
Weeks
8.
67
Weeks
15
Weeks
to
Months
37.5
Months
60
Recalcitrant
180
Note
that
the
maximum
value
returned
by
this
model
is
180
days
even
though
the
half­
life
of
recalcitrant
molecules
in
the
environment
is
likely
to
be
substant
ially
longer.

It
is
known
that
ultimate
biodegradation
is
generally
slower
under
anaerobic
condit
ions
than
under
aerobic
condit
ions.
The
BIOWIN
ult
imate
survey
model
that
is
used
in
this
Profiler
assumes
aerobic
conditions,
but
deeper
layers
of
aquatic
sediments
are
usually
anaerobic.
To
account
for
the
slower
rate
of
ultimate
biodegradation
in
sediment,
the
PBT
Profiler
uses
a
conversion
factor
developed
in
EPA's
P2
framework.
The
PBT
Profiler
assumes
that
sediments
are
anaerobic
and
that
the
rate
of
ultimate
biodegradation
in
sediment
is
on
average
one­
ninth
(1/
9)
of
that
in
the
water
column
(which
is
assumed
to
be
aerobic).

Similarly,
the
PBT
Profiler
makes
an
adjustment
for
the
biodegradation
rate
for
soil.
It
is
generally
believed
that
the
biodegradation
rate
for
a
chemical
in
soil
is,
on
average,
one­
half
(1/
2)
that
in
water.
The
PBT
Profiler,
therefore,
assigns
the
half­
life
in
soil
to
be
twice
that
estimated
for
water.

Percentage
in
Each
Medium
The
PBT
profiler
uses
the
Level
III
fugacity
model
of
Mackay
[Mackay
D.,
Paterson
S.,
and
Shiu
W.
Y.
Generic
Models
for
Evaluating
the
Regional
Fate
of
Chemical.
Chemosphere
24:
695­
718
(1992)]
to
determine
the
percentage
of
a
chemical
in
each
medium.
The
Level
III
fugacity
model
is
a
multimedia
model
that
uses
a
chemical's
physical/
chemical
properties
and
degradation
half­
lives
for
air,
water,
soil
and
sediment.
The
Level
III
fugacity
model
was
chosen
for
the
PBT
profiler
because
it
is
available
in
an
electronic
format,
could
be
readily
modified
for
use
in
a
web­
based
application,
and
has
been
validated
in
several
studies
[for
example,
see
Kuhne
R.
et
al.
Environmental
Toxicology
and
Chemistry
16:
2067­
9
(1997);
Matoba
Y
et
al.
Journal
of
the
Air
and
Waste
Management
Association
48:
969­
78;
Suzuki
N
et
al.
Chemosphere
37:
2239­
59
(1998)].

The
Level
III
fugacity
model
is
a
non­
equilibrium,
steady­
state
multimedia
fate
model
that
is
designed
to
provide
information
on
environmental
partitioning
and
intermedia
transport
at
the
screening
level.
This
additional
information
is
consistent
with
the
basic
purpose
of
the
Profiler,
which
is
to
provide
the
user
with
valuable
information
to
help
establish
whether
a
more
rigorous
investigation
of
PBT
characteristics
is
required.

The
fugacity
model
requires
a
series
of
physical/
chemical
properties
and
environmental
half­
lives
as
input.
Environmental
half­
lives
are
determined
for
air,
water,
soil,
and
sediment
as
discussed
above.
Physical/
chemical
properties
are
provided
by
SRC's
suite
of
structure­
based
estimation
programs.
Physical
properties
are
used
directly
by
the
fugacity
model
to
determine
the
transport
between
environmental
compartments.
These
properties,
and
citations
to
the
methodology
used
for
each,
are:

 
Henry's
Law
constant
[Meylan,
W.
M.
and
Howard,
P.
H.
Bond
contribution
method
for
estimating
Henry's
Law
Constants.
Environmental
Toxicology
and
Chemistry
10:
1283­
93
(1991)];
 
Vapor
pressure
[Lyman,
W.
J.,
Reehl,
W.
F.
and
Rosenblatt,
D.
H.
Handbook
of
Chemical
Property
Estimation
Methods.
Washington,
DC:
American
Chemical
Society
(1990)];
 
Melting
point
[Stein,
S.
E.
and
Brown,
R.
L.
Estimation
of
Normal
Boiling
Points
from
Group
Contributions.
Journal
of
Chemical
Information
and
Computer
Sciences
34:
581­
7
(1994);
Reid,
R.
C.,
Prausnitz,
J.
M.,
and
Poling,
B.
E.
The
Properties
of
Gases
and
Liquids.
Fourth
edition.
NY:
McGraw­
Hill,
Inc.,
Chapter
2
(1987)];
 
Water
solubility
[Meylan,
W.
M.
and
Howard,
P.
H.
Improved
Method
for
Estimating
Water
Solubility
from
Octanol/
Water
Partition
Coefficient.
Environmental
Toxicology
and
Chemistry
15:
100­
6
(1996)];
 
Octanol/
water
partition
coefficient
[Meylan,
W.
M.
and
Howard,
P.
H.
Atom/
Fragment
Contribution
Method
for
Estimating
Octanol­
Water
Partition
Coefficients.
Journal
of
Pharmaceutical
Science
84:
83­
92
(1996)];
and
 
Molecular
weight
(determined
from
the
SMILES
notation).

The
PBT
profiler
will
automatically
use
experimental
values
for
Henry's
Law
constant
and
octanol/
water
partition
coefficient
through
an
automatic
database
look­
up
function
in
preference
to
estimated
values.
Future
versions
will
indicate
when
an
experimental
value
was
used
in
the
persistence
estimation.

If
the
Henry's
Law
constant
can
not
be
estimated
from
chemical
structure,
the
PBT
Profiler
then
determines
if
a
water
solubility
and
vapor
pressure
are
available.
If
they
are,
the
Henry's
Law
constant
is
determined
by
dividing
the
vapor
pressure
by
the
water
solubility
(after
converting
each
value
to
the
proper
units).

The
PBT
profiler
uses
the
default
settings
of
the
Level
III
fugacity
model
[Mackay
D.,
Paterson
S.,
and
Shiu
W.
Y.
Generic
Models
for
Evaluating
the
Regional
Fate
of
Chemical.
Chemosphere
24:
695­
718
(1992)]
for
its
calculations,
and
displays
the
results
of
these
calculations
as
the
percentage
of
the
chemical
expected
at
steady
state
in
the
different
environmental
media.
Default
emission
rates
are
equal
amounts
(1,
000
kg/
hr)
to
air,
soil,
and
water
(direct
discharges
to
sediment
are
unlikely).
The
model
treats
a
generic
environment
of
100,000
square
km
with
10%
water;
90%
soil
surface;
water
depth
20
m;
soil
depth
20
cm;
sediment
depth
5
cm;
atmospheric
height
1000
m.

The
PBT
Profiler
also
provides
the
user
with
different
release
scenarios
for
a
chemical
to
aid
in
identifying
P2
opportunities
that
may
be
more
consistent
with
it's
expected
life
cycle.
On
the
P2
considerations
page,
the
emission
rate
is
set
at
either
1
or
1,
000
kg/
hr
for
soil,
water,
and
air,
and
the
resulting
distribution
and
half­
life
in
each
environmental
compartment
is
provided.

The
Level
III
fugacity
model,
by
design,
does
not
consider
a
chemical's
potential
to
migrate
to
groundwater.
Therefore,
the
PBT
Profiler
does
not
explicitly
consider
the
fate
of
a
chemical
substance
in
groundwater.
Because
a
complete
P2
assessment
should
consider
a
chemical's
potential
to
migrate
to
groundwater,
the
PBT
Profiler
contains
a
simple
set
of
algorithms
to
highlight
chemicals
that
may
travel
through
soil
into
an
underground
aquifer
based
on
its
octanol
water
partition
coefficient
(Kow).
The
PBT
Profiler
only
highlights
chemicals
that
are
expected
to
have
the
potential
to
persist
in
groundwater.
If
the
log
Kow
of
an
individual
chemical
is
<
4
and
it
is
found
to
be
persistent
in
sediment
(half­
life
>
60
days),
then
the
PBT
Profiler
flags
this
chemical
as
one
that
has
the
potential
to
migrate
to
and
be
persistent
in
groundwater.
This
information
is
provided
to
the
user
on
the
P2
considerations
page.

Persistence
Ranking
The
PBT
Profiler
provides
a
persistence
summary
(also
called
the
persistence
ranking)
as
the
initial
level
of
its
integrated
output.
The
persistence
ranking
is
based
on
the
results
of
the
physical/
chemical
properties
estimates
(excluding
those
for
toxicity
and
bioconcentration)
as
summarized
in
the
second
level
of
the
PBT
Profiler
output
­
the
quantitative
estimate
of
a
chemical's
persistence
in
and
partitioning
to
the
four
environmental
media.
The
persistence
ranking
is
derived
used
the
following
methodology.

PBT
strategies
typically
consider
the
persistence
of
a
chemical
in
water,
soil,
and
sediment
because
these
are
the
media
associated
with
bioaccumulation.
The
PBT
Profiler
first
determines
the
amount
of
the
chemical
expected
to
be
found
in
water,
soil,
and
sediment
(expressed
as
a
percentage
of
the
total
amount
in
the
environment)
using
the
fugacity
model.
It
then
determines
which
of
these
three
compartments
the
chemical
is
most
likely
to
partition
to
(the
one
with
the
highest
percentage).
Using
this
predominant
compartment,
the
half­
life
in
that
compartment
is
then
compared
to
the
PBT
Profiler
criteria
to
determine
the
persistence
ranking.
If
the
half­
life
in
the
predominant
compartment
exceeds
the
PBT
Profiler
criteria,
the
chemical
is
designated
as
persistent
or
very
persistent
in
the
summary
output.

The
advantage
of
this
methodology
is
that
it
considers
the
two
most
important
components
of
a
chemical's
fate
in
the
environment;
its
removal
and
its
partitioning.
If
only
one
aspect
of
a
chemical's
likely
fate
were
considered,
the
potential
for
misclassification
increases.
For
example,
a
chemical
that
partitions
only
to
water
and
soil
may
have
an
estimated
half­
life
in
water
of
15
days,
an
estimated
half­
life
in
soil
of
30
days,
and
an
estimated
half­
life
in
sediment
of
135
days.
This
chemical
would
exceed
the
PBT
Profiler
persistence
criteria
for
sediment
based
upon
its
half­
life;
however,
the
results
of
the
fugacity
model
indicate
that
it
is
not
expected
to
be
present
in
sediment.
Its
ranking
in
either
soil
and
water,
therefore,
are
more
representative
of
its
persistence
in
the
environment.

The
PBT
Profiler
methodology
was
developed
with
the
aid
of
a
database
of
experimental
biodegradation
rates
for
136
chemicals.
Comparison
of
the
PBT
Profiler
results
to
an
evaluated
data
set
is
provided
in
the
results
section.

Overall
Persistence
It
is
important
to
distinguish
between
persistence
in
a
single
medium
and
overall
environmental
persistence.
Persistence
in
an
individual
medium
is
controlled
by
transport
of
the
substance
to
other
media,
as
well
as
transformation
to
other
molecular
species.
Persistence
in
the
environment
as
a
whole
is
a
distinct
concept.
It
is
based
on
the
observations
that
the
environment
behaves
as
a
set
of
interconnected
media,
and
that
a
chemical
substance
released
to
the
environment
will
become
distributed
in
these
media
in
accordance
with
its
intrinsic
(physical/
chemical)
properties
and
reactivity.
Multimedia
mass
balance
models
offer
the
most
convenient
means
to
estimate
overall
environmental
persistence
from
information
on
sources
and
loadings,
chemical
properties
and
transformation
processes,
and
intermedia
partitioning.

The
PBT
Profiler
uses
a
model
similar
to
the
TaPL3
model,
available
from
the
Trent
University
website,
to
obtain
an
estimate
of
overall
persistence
in
which
all
net
loss
from
the
defined
model
environment
is
due
to
reaction
(e.
g.,
biodegradation)
only;
i.
e.,
there
are
no
advective
losses
from
the
model
environment.
This
is
appropriate
in
screening­
level
review
for
PBT
potential
since
advective
losses
merely
relocate
a
chemical
rather
than
alter
it
chemically.
Overall
persistence
can
be
thought
of
as
the
integration
of
medium­
specific
halfliveswith
intermedia
transportand
partitioning
to
give
a
weighted
averageofthe
persistences
in
the
individual
media.
The
results
are
expressed
as
the
environmental
residence
time
tauR,
which
is
equivalent
to
the
total
amount
of
the
chemical
in
the
defined
environment
divided
by
the
total
loss
rate
due
to
reaction
(or
the
input
rate,
since
these
are
equal
in
a
steady­
state,
level
III
model).
The
overall
persistence
provides
a
meaningful
way
of
expressing
relative
persistence
when,
for
example,
a
chemical
is
discharged
to
one
medium
but
rapidly
partitions
to
another,
where
the
half­
life
is
very
different.
Users
should
consult
the
recent
work
by
Webster
et
al.
for
further
details
[Webster
E.,
Mackay,
D.,
and
Wania,
F.
Evaluating
Environmental
Persistence.
Environmental
Science
and
Technology
17:
2148­
2158
(1998)].
Characteristic
Travel
Distance
(CTD)

Characteristic
Travel
Distance
is
an
expression
of
a
chemical's
long­
range
transport
(LRT)
potential.
LRT
refers
to
the
ability
of
a
substance
to
be
transported
long
distances
(generally,
on
a
continental
or
global
scale)
via
advection,
potentially
resulting
in
widespread
distribution
and
deposition
in
regions
far
from
where
the
chemical
was
produced
or
used.
Most
attention
to
LRT
potential
focuses
on
atmospheric
transport.
LRT
potential
is
linked
to
overall
environmental
persistence,
but
no
simple
relationship
between
the
two
exists
because
the
medium
or
media
of
transport
may
not
be
the
media
in
which
persistence
is
longest.
The
PBT
Profiler
uses
a
model
similar
to
the
TaPL3
model
to
calculate
a
chemical's
CTD
in
air
over
soil
and
water,
LA,
expressedin
kilometers.
The
model
assumes
release
is
ent
irely
to
air,
but
otherwise
uses
the
same
defaults
as
in
the
Level
III
fugacity
model
with
advection
off.
For
further
details
users
should
consult
the
recent
work
by
Beyer
et
al.
[Beyer
A.,
Mackay,
D.,
Matthies,
M.,
Wania,
F.
and
Webster,
W.
Assessing
Long­
range
Transport
Potential
of
Persistent
Organic
Pollutants.
Environmental
Science
and
Technology.
34:
699­
703
(2000)].

Bioaccumulation
The
PBT
profiler
determines
a
chemical's
potential
to
bioaccumulate
directly
from
an
estimated
bioconcentration
factor
(BCF).
The
bioconcentration
factor
is
estimated
using
SRC's
BCFWIN
estimation
program
[Meylan,
W.
M.,
Howard,
P.
H.,
Boethling,
R.
S.,
Aronson,
D.,
Printup,
H.,
and
Gouchie,
S.
Improved
Method
for
Estimating
Bioconcentration
Factor
(BCF)
from
Octanol­
Water
Partition
Coefficient.
Environmental
Toxicology
and
Chemistry
18:
664­
72
(1997)].
The
estimated
bioconcentration
factors
are
compared
to
those
contained
in
the
PBT
Profiler
Criteria.
The
BCFWIN
program
yields
a
screening­
level
prediction
of
BCF
based
on
a
chemical's
octanol/
water
partition
coefficient
and
one
or
more
chemical
structure­
based
correction
factors,
if
applicable.
The
model
does
not
explicitly
address
a
variety
of
factors
that
may
influence
bioaccumulation
under
field
conditions,
such
as
possible
metabolism
of
the
chemical
in
exposed
organisms,
which
could
lead
to
actual
bioaccumulation
being
lower
than
predicted.
The
user
needs
to
exercise
due
caution
when
interpreting
BCFWIN
results.

Toxicity
The
PBT
Profiler
considers
only
aquatic
toxicity
and
estimates
it
using
the
ECOSAR
(Ecological
Structure
Activity
Relationships)
program.
ECOSAR
predicts
the
toxicity
of
industrial
chemicals
to
aquatic
organisms
such
as
fish,
invertebrates,
and
algae
by
using
Structure
Activity
Relationships
(SARs).
ECOSAR
uses
SARs
to
predict
the
aquatic
toxicity
of
chemicals
based
on
their
structural
similarity
to
chemicals
for
which
aquatic
toxicity
data
are
available.
SARs
express
the
correlations
between
a
compound's
physical/
chemical
properties
and
its
aquatic
toxicity.
SARs
measured
for
one
compound
can
be
used
to
predict
the
toxicity
of
similar
compounds
belonging
to
the
same
chemical
class.
The
SARs
contained
within
the
ECOSAR
are
based
on
test
data
and
many
of
the
SAR
predictions
have
been
validated.
More
information
on
ECOSAR,
as
well
as
the
program
itself,
is
available
from
the
EPA.

ECOSAR
estimates
a
chemical's
acute
(short­
term)
aquatic
toxicity
and,
when
available,
chronic
(long­
term
or
delayed)
toxicity.
For
the
PBT
Profiler,
the
fish
chronic
(ChV)
values
are
used
to
predict
toxicity.
If
the
ChV
cannot
be
estimated
using
the
QSAR
equations
available
in
ECOSAR,
the
PBT
Profiler
will
return
"not
estimated."
The
PBT
Profiler
identifies
chemicals
that
exceed
the
log
octanol/
water
partition
coefficient
cutoffs
for
the
QSARs
used
by
ECOSAR.
If
the
cutoffs
are
exceeded
for
a
specific
chemical,
the
PBT
Profiler
will
return
a
ChV
value
of
"Not
Estimated"
and
it
will
not
run
the
ECOSAR
estimation.
Because
of
the
algorithms
used
by
ECOSAR,
this
program
estimates
a
water
solubility
separately
using
the
octanol/
water
partition
coefficient.

The
PBT
Profiler
compares
the
ChV
(in
mg/
l)
of
each
chemical
to
its
water
solubility.
If
the
water
solubility
is
less
than
the
ChV,
then
there
are
no
effects
at
saturation.
For
chemicals
that
the
PBT
Profiler
identifies
as
potentially
persistent
and
bioaccumulative,
the
no
effects
at
saturation
flag
is
not
used
in
the
overall
ranking
as
these
chemicals
may
accumulate
to
higher
levels
over
time.
For
all
other
chemicals
that
may
display
no
effects
at
saturation,
the
PBT
Profiler
returns
a
green
Toxicity
ranking.

The
PBT
Profiler
uses
QSARs
for
neutral
organic
compounds
for
estimating
the
fish
ChV.
For
a
comprehensive
description
of
how
these
QSARs
were
developed,
please
see
the
ECOSAR
technical
manual.

Results
PBTs
and
POPs
The
results
of
the
PBT
profiler
were
compared
to
organic
chemicals
generally
recognized
as
being
PBTs;
the
64
chemicals
in
EPA's
final
rule
on
Persistent
Bioaccumulative
Toxic
(PBT)
Chemicals
and
the
12
United
Nations
Environment
Programme
(UNEP)
Persistent
Organic
Pollutants
(POPs)
.

For
the
64
chemicals
in
EPA's
TRI
Rule,
the
PBT
Profiler
flagged
49
as
PBTs
and
13
as
persistent
and
bioaccumulative
with
the
toxicity
"not
estimated."
As
indicated
on
the
"Interpreting
the
PBT
Profiler
Results"
Page,
persistent
and
bioaccumulate
chemicals
may
accumulate
in
the
environment
to
relatively
high
levels.
Therefore,
persistent
and
bioaccumulative
chemicals
without
an
estimated
toxicity
should
be
reviewed
carefully
(and
using
the
same
techniques
as
one
estimated
to
be
a
PBT)
when
identifying
P2
opportunities.
Similar
results
were
obtained
for
the
12
POPs
(using
a
representative
structure
for
the
PCBs,
polychlorinated
dioxins,
and
polychlorinated
furans).
All
but
3
of
the
POPs
are
listed
in
the
final
TRI
rule.

The
results
described
above
are
summarized
in
the
following
tables.

Persistent,
bioaccumulative,
and
toxic
organic
chemicals
in
EPA's
final
PBT
Rule
for
TRI.

CAS
Name
PBT
Profiler
Results
1
115­
32­
2
Dicofol
P
B
T
2
118­
74­
1
Hexachlorobenzene
P
B
T
3
1582­
09­
8
Trifluralin
P
B
T
4
1746­
01­
6
2,
3,
7,
8­
Tetrachlorodibenzo­
p­
dioxin
P
B
T
5
189­
55­
9
Benzo(
r,
s,
t)
pentaphene
P
B
T
6
189­
64­
0
Dibenzo(
a,
h)
pyrene
P
B
T
7
191­
24­
2
Benzo(
g,
h,
i)
perylene
P
B
T
8
191­
30­
0
Dibenzo(
a,
i)
pyrene
P
B
T
9
192­
65­
4
Dibenzo(
a,
e)
pyrene
P
B
T
10
193­
39­
5
Indeno(
1,2,
3­
cd)
pyrene
P
B
T
11
19408­
74­
3
1,2,3,
7,8,
9­
Hexachlorodibenzo­
p­
dioxin
P
B
T
12
194­
59­
2
7H­
Dibenzo(
c,
g)
carbazole
P
B
T
13
205­
82­
3
Benzo(
j)
fluoranthene
P
B
T
14
205­
99­
2
Benzo(
b)
fluoranthene
P
B
T
15
206­
44­
0
Benzo(
j,
k)
fluorene
(fluoranthene)
P
BT
16
207­
08­
9
Benzo(
k)
fluoranthene
P
B
T
17
218­
01­
9
Benzo(
a)
phenanthrene
P
B
T
18
224­
42­
0
Dibenz(
a,
j)
acridine
P
B
T
19
226­
36­
8
Dibenz(
a,
h)
acridine
P
B
T
20
29082­
74­
4
Octachlorostyrene
P
BT
21
309­
00­
2
Aldrin
P
BT
22
31508­
00­
6
2,3',
4,
4',
5­
Pentachlorobiphenyl
P
B
T
23
32598­
13­
3
3,3',
4,
4'­
Tetrachlorobiphenyl
P
B
T
24
32598­
14­
4
2,3,3',
4,
4'­
Pentachlorobiphenyl
P
B
T
25
3268­
87­
9
1,2,3,
4,6,
7,8,
9­
Octachlorodibenzo­
pdioxin
P
B
T
26
32774­
16­
6
3,3',
4,
4',
5,5'­
Hexachlorobiphenyl
P
B
T
27
35822­
46­
9
1,2,3,
4,6,
7,8­
Heptachlorodibenzo­
pdioxin
P
B
T
28
3697­
24­
3
5­
Methylchrysene
P
B
T
29
38380­
08­
4
2,3,3',
4,
4',
5­
Hexachlorobiphenyl
P
B
T
30
39001­
02­
0
1,2,3,
4,6,
7,8,
9­
Octachlorodibenzofuran
P
B
T
31
39227­
28­
6
1,2,3,
4,7,
8­
Hexachlorodibenzo­
p­
dioxin
P
BT
32
39635­
31­
9
2,3,3',
4,
4',
5,5'­
Heptachlorobiphenyl
P
B
T
33
40321­
76­
4
1,2,3,
7,8­
Pentachlorodibenzo­
p­
dioxin
P
B
T
34
40487­
42­
1
Pendimethalin
P
BT
35
465­
73­
6
Isodrin
P
BT
36
50­
32­
8
Benzo(
a)
pyrene
P
B
T
37
51207­
31­
9
2,3,7,
8­
Tetrachlorodibenzofuran
P
B
T
38
52663­
72­
6
2,3',
4,
4',
5,5'­
Hexachlorobiphenyl
P
B
T
39
53­
70­
3
Dibenzo(
a,
h)
anthracene
P
B
T
40
5385­
75­
1
Dibenzo(
a,
e)
fluoranthene
P
B
T
41
5522­
43­
0
1­
Nitropyrene
P
B
T
42
55673­
89­
7
1,2,3,
4,7,
8,9­
Heptachlorodibenzofuran
P
B
T
43
56­
49­
5
3­
Methylcholanthrene
P
B
T
44
56­
55­
3
Benzo(
a)
anthracene
P
B
T
45
57117­
31­
4
2,3,4,
7,8­
Pentachlorodibenzofuran
P
B
T
46
57117­
41­
6
1,2,3,
7,8­
Pentachlorodibenzofuran
P
B
T
47
57117­
44­
9
1,2,3,
6,7,
8­
Hexachlorodibenzofuran
P
B
T
48
57465­
28­
8
3,3',
4,
4',
5­
Pentachlorobiphenyl
P
B
T
49
57653­
85­
7
1,2,3,
6,7,
8­
Hexachlorodibenzo­
p­
dioxin
P
B
T
50
57­
74­
9
Chlordane
P
BT
51
57­
97­
6
7,
12­
Dimethylbenz(
a)
anthracene
P
B
T
52
60851­
34­
5
2,3,4,
6,7,
8­
Hexachlorodibenzofuran
P
B
T
53
608­
93­
5
Pentachlorobenzene
P
B
T
54
65510­
44­
3
2',
3,
4,
4',
5­
Pentachlorobiphenyl
P
B
T
55
67562­
39­
4
1,2,3,
4,6,
7,8­
Heptachlorodibenzofuran
P
B
T
56
69782­
90­
7
2,3,3',
4,
4',
5'­
Hexachlorobiphenyl
P
B
T
57
70648­
26­
9
1,2,3,
4,7,
8­
Hexachlorodibenzofuran
P
B
T
58
72­
43­
5
Methoxychlor
P
B
T
59
72918­
21­
9
1,2,3,
7,8,
9­
Hexachlorodibenzofuran
P
B
T
60
74472­
37­
0
2,3,4,
4',
5­
Pentachlorobiphenyl
P
B
T
61
76­
44­
8
Heptachlor
P
BT
62
79­
94­
7
Tetrabromobisphenol
A
P
B
T
63
8001­
35­
2
Toxaphene
P
B
T
64
1336­
36­
3
Polychlorinated
Biphenyls
(PCBs)
P
B
T
Persistent
Organic
Pollutants
(POPs)

#
CAS
Name
PBT
Profiler
Results
1
309­
00­
2
Aldrin
P
BT
2
57­
74­
9
Chlordane
P
BT
3
50­
29­
3
DDT
P
BT
4
60­
57­
1
Dieldrin
P
B
T
5
72­
20­
8
Endrin
P
B
T
6
76­
44­
8
Heptachlor
P
BT
7
118­
74­
1
Hexachlorobenzene
P
B
T
8
8001­
35­
2
Toxaphene
P
B
T
9
2385­
85­
5
Mirex
P
B
T
10
1336­
36­
3
Polychlorinated
biphenyls
(PCBs)
P
B
T
11
57653­
85­
7
Polychlorinated
dibenzo­
p­
dioxins
P
B
T
12
60851­
34­
5
Polychlorinated
dibenzofurans
P
B
T
PBT
Profiler
Results
for
Chemicals
in
an
Evaluated
Data
Set
Introduction
The
persistence
estimates
from
the
PBT
Profiler
were
compared
to
a
published
data
set
containing
environmental
persistence
summaries
[Mackay,
D;
Shiu,
W.
Y.;
Ma,
K.
Physical­
Chemical
Properties
&
Environmental
Fate
on
CD­
ROM.
CRC
Press
.
ISBN/
ISSN:
0849321921
(2000)].
In
this
compilation,
published
data
were
used
to
place
a
chemical's
half­
life
into
one
of
nine
evaluated
persistence
classes
as
shown
in
the
following
table
(for
water,
soil,
and
sediment).

Evaluated
Class
Mean
Half­
Life
(d)
Half­
Life
Range
(d)

1
0.
21
<0.42
2
0.
71
0.
42­
1.2
3
2.
3
1.2­
4.2
4
7.
0
4.2­
12.5
5
23
12.5­
42
6
70.8
42­
125
7
229
125­
417
8
708
417­
1250
9
2292
>1250
Classes
1­
5
correspond
to
the
PBT
Profiler
"not
persistent"
criteria
(Green,
half­
life
<
60
days
)
and
classes
8
and
9
correspond
to
the
"very
persistent"
(Red,
>
180
days
)criteria.
The
half­
life
ranges
for
classes
6
&
7
overlap
more
than
one
Profiler
criteria
and,
therefore,
chemicals
in
these
classes
can
not
be
compared
directly
to
the
"persistent"
category
(Yellow,
>60
days
and
<
180
days).

Comparison
of
the
evaluated
data
set
to
the
PBT
Profiler
results
Initial
results
were
obtained
by
running
the
293
chemicals
in
this
data
set
through
the
PBT
Profiler.
The
predominant
compartment
returned
by
the
PBT
Profiler
was
identified
and
the
evaluated
half­
life
class
for
that
compartment
was
determined.
The
resulting
halflife
was
then
compared
to
the
persistence
ranking
estimated
by
the
PBT
Profiler.
For
example,
the
PBT
Profiler
predicts
that
acetone
will
be
found
predominately
in
water
and
that
it
is
not
persistent
(half­
life
<
60
days).
The
evaluated
pertsitence
class
for
acetone
in
water
is
4,
which
corresponds
to
a
mean
half­
life
of
7
days
(range
~4­
12
days).
Therefore,
the
results
for
the
evaluated
data
and
the
PBT
Profiler
are
in
agreement
for
acetone
and
this
chemical
is
represented
in
the
area
shaded
green
in
the
following
pie
chart.
The
results
for
all
293
chemicals
in
the
data
set
are
summarized
in
the
following
pie
charts
(using
the
PBT
Profiler
paradigm)
by
evaluated
class
(or
combined
classes,
as
appropriate).

Of
the
164
chemicals
in
the
not
persistent
category,
133
(81%)
were
shown
to
have
a
half­
life
of
<
60
days
for
both
the
evaluated
data
set
and
the
PBT
Profiler
estimate.
However,
if
one
reviews
the
likely
fate
of
the
chemicals
that
are
categorized
differently,
the
literatue
indicates
that
biodegradation
is
not
their
primary
removal
process
in
the
environment.
For
the
2
chemicals
(1%)
predicted
by
the
PBT
Profiler
to
be
very
persistent
and
the
30
chemicals
(18%)
predicted
to
be
persistent,
all
but
3
can
be
put
into
one
of
six
chemical
groups
based
on
common
functionality:
chlorephenols
and
chlorophenyl
ethers;
beta­
chloroethers;
aromatic
amines;
carbothiomate
pesticides;
thiophosphates;
and
aromatic
carbamates.
These
chemical
classes,
as
well
as
the
remaing
three
chemicals,
are
expected
to
undergo
rapid
(half­
life
<60
days)
chemical
degradation
in
the
environment
via
hydrolysis
and/
or
photolysis
(either
direct
or
indirect
phtooxidation)
based
on
the
available
literature.
Even
though
chemcials
that
undergo
hdyrolysis
or
other
chemical
degradation
processes
should
not
be
run
through
the
PBT
Profiler,
it
is
cuurrently
the
responsibility
of
the
user
to
identify
those
chemicals
that
meet
this
criteria.
For
a
screening
level
method
developed
for
a
wide
range
of
potential
users,
it
is,
therfore,
not
appropriate
to
remove
these
20
chemicals
from
this
exercise.
Nevertheless,
it
emphaisizes
the
high
degree
of
agreement
between
the
PBT
Profiler
estimates
and
the
evaluated
data
set
for
this
category
of
chemicals.
Future
versions
of
the
PBT
Profiler
may
incorporate
structure
recognition
capabilities
that
will
be
able
to
identify
functional
groups
that
are
known
to
undergo
rapid
chemical
degradation.
Analysis
of
the
PBT
Profiler
estimates
for
very
persistent
chemicals
from
classes
8
and
9
was
also
performed.
For
these
42
chemicals,
the
Profiler
estimated
that
36
chemicals
would
be
very
persistent
and
6
would
be
persistent.

The
6
chemicals
that
the
PBT
Profiler
estimated
to
be
persistent
include
3
chlorinated
biphenyls
(a
mono,
di,
and
trichloro
congenor),
pyrene,
flouranthene,
and
trichlorofluoromethane.
All
of
these
chemicals
should
be
reviewed
carefully
when
considering
P2
opportunies
and,
from
this
standpoint,
the
PBT
Profiler
estimates
are
in
excellent
agreement
with
the
evaluated
data.

The
pie
charts
for
the
chemicals
in
evaluated
classes
6
and
7
are
also
provided.
The
halflife
range
in
class
6
overlap
the
not
persistent
and
persistent
categories
and
those
in
class
7
overlap
the
persistent
and
very
persistent
categories.
Because
these
two
classes
do
not
directly
correspond
to
PBT
Profiler
criteria,
the
results
should
be
viewed
with
caution
and
a
thorough
analysis
is
not
warranted.
The
general
trend
from
class
6
to
7
is
consistent
with
what
one
would
expect
in
that
there
was
a
decrease
in
the
percentage
of
chemicals
that
the
PBT
Profiler
predicted
to
be
not
persistent
with
a
concomitant
(but
smaller)
increase
in
the
number
predicted
to
be
very
persistent.

Comparison
of
the
PBT
Profiler
Results
with
the
Evaluated
Data
Set
The
PBT
Profiler
estimates
were
compared
with
293
chemicals
from
the
evaluated
data
set
containing
environmental
persistence
summaries
[Mackay,
D;
Shiu,
W.
Y.;
Ma,
K.
Physical­
Chemical
Properties
&
Environmental
Fate
on
CD­
ROM.
CRC
Press.
ISBN/
ISSN:
0849321921
(2000)]
discussed
above.
The
purpose
of
this
exercise
was
to
evaluate
the
water,
soil,
and
sediment
half­
life
multipliers
(1,
4
and
9)
used
by
the
PBT
Profiler
as
well
as
using
the
predominant
compartment
instead
of
the
media­
specific
halflife
for
the
persistence
ranking
(see
the
PBT
Profiler
Methodology
section
on
persistence).

The
PBT
Profiler
results
were
used
to
separate
the
293
chemicals
into
three
groups
(not
persistent,
persistent,
and
very
persistent)
and
the
evaluated
half­
life
class
for
water,
soil,
and
sediment
were
plotted
for
each
chemical.
The
predominate
compartment,
as
determined
by
the
PBT
Profiler
for
each
chemical,
is
also
provided
for
each
chemical.
These
graphs
were
then
reorganized
for
presentation
(using
a
primary
sort
on
water
halflife
secondary
sort
on
soil
half­
life,
tertiary
sort
on
sediment
half­
life).
The
numbers
on
the
x­
axis
are
simply
place
holders
and
each
graph
tick
represents
a
different
chemical.

As
discussed
above,
the
results
must
be
interpreted
with
caution
because
some
of
the
evaluated
classes
do
not
directly
correspond
with
the
PBT
Profiler
criteria.
In
the
following
graphs,
the
area
shaded
red
corresponds
with
the
very
persistent
PBT
Profiler
category
and
the
area
shaded
green
corresponds
with
the
not
persistent
category.
The
PBT
Profiler
persistent
category
does
not
directly
correspond
to
the
evaluated
classes
6
and
7.
Analysis
of
these
data
reveals
that,
in
general,
the
PBT
Profiler
estimates
are
in
very
good
agreement
with
the
evaluated
data.
The
results
also
indicate
that
the
chemicals
in
the
persistent
category
overwhelmingly
(94%)
had
soil
as
the
predominant
compartment
while
those
in
the
very
persistent
and
not
persistent
category
had
essentially
an
even
split
of
soil
or
sediment
and
soil
or
water
as
the
predominant
compartment,
respectively.
These
graphs
suggest
that
using
the
predominant
compartment
to
determine
the
persistence
ranking
is
not
an
overwhelming
factor
for
assigning
the
overall
persistence
ranking.
For
the
majority
of
the
chemicals
in
this
data
set,
selecting
the
half­
life
in
soil
instead
of
sediment
would
not
have
changed
the
persistence
ranking.
Similarly,
selecting
the
half­
life
in
soil
instead
of
water
would
not
have
changed
the
ranking
for
the
not
persistent
chemicals.

Using
the
predominant
compartment
to
determine
the
persistence
ranking,
however,
appears
to
increase
the
overall
predictive
accuracy
of
the
methodology.
This
is
most
evident
when
the
half­
life
in
one
(or
more)
of
the
three
environmental
compartments
fall
into
different
persistence
categories.
For
example,
chemicals
10­
15
in
the
very
persistent
group
could
be
placed
in
either
the
very
persistent
or
not
persistent
category
based
on
their
medium­
specific
half­
lives
in
sediment
and
water,
respectively.
Given
that
these
chemicals
partition
predominantly
to
sediment,
their
half­
life
in
this
media
(>
180
days)
is
likely
more
representative
of
thier
persistence
in
the
environment.
An
opposite
trend
is
observed
for
chemicals
in
the
not
persistent
group
that
have
estimated
sediment
half­
lives
greater
than
60
days
and
water
(and
possibly
soil)
halflives
less
than
60
days.
If
the
persistence
ranking
was
based
solely
on
the
highest
estimated
half­
life
in
water,
soil,
or
sediment,
the
environmental
persistence
would
likely
be
overestimated
for
these
chemicals.
This
arises
directly
from
the
water:
soil:
sediment
half­
life
multipliers
of
1:
2:
9
used
by
the
PBT
Profiler.
If
the
persistence
ranking
were
based
on
the
highest
medium­
specific
half­
life,
the
value
for
sediment
(a
factor
of
9
that
of
water)
would
always
be
used.
The
expected
outcome,
therefore,
would
be
a
general
trend
that
overestimates
a
chemical's
persistence
in
the
environment.
Analysis
of
the
available
data
indicates
that
using
the
predominant
compartment
half­
life
attenuates
this
bias
and
reduces
the
potential
for
overestimating
a
chemical's
persistence
in
the
environment.

Developed
by
the
Environmental
Science
Center
under
contract
to
the
Office
of
Pollution
Prevention
and
Toxics
,
U.
S.
Environmental
Protection
Agency
Computer
Resources
Donated
by
Syracuse
Research
Corporation
Ver
0.
911
BetaR
Restricted
Access
Last
Updated
April
18,
2001
