Page
1
of
12
UNITED
STATES
ENVIRONMENTAL
PROTECTION
AGENCY
WASHINGTON
D.
C.,
20460
OFFICE
OF
PREVENTION,
PESTICIDES
AND
TOXIC
SUBSTANCES
August
8,
2005
MEMORANDUM
Subject:
Transmission
of
the
Preliminary
Cumulative
Risk
Assessment
for
the
NMethyl
Carbamate
Pesticides
for
review
by
the
FIFRA
Scientific
Advisory
Panel.

To:
Myrta
Christian,
Designated
Federal
Official
FIFRA
SAP
Office
of
Science
Coordination
and
Policy
(
7101C)

From:
Anna
B.
Lowit
and
David
J.
Miller
Office
of
Pesticide
Programs,
Health
Effects
Division
(
7509C)

Through:
George
Herndon,
Associate
Director
Office
of
Pesticide
Programs,
Health
Effects
Division
(
7509C)

A
meeting
of
the
FIFRA
SAP
is
scheduled
for
August
23­
26,
2005.
This
meeting
will
focus
on
the
Preliminary
Cumulative
Risk
Assessment
for
the
N­
Methyl
Carbamate
Pesticides.
This
memo
provides
the
charge
questions
to
the
Panel.
Page
2
of
12
Questions
for
the
SAP
HAZARD
EPA's
hazard
and
dose­
response
chapter
(
I.
B)
and
associated
appendices
(
II.
B.
1­
6)
of
the
Preliminary
Cumulative
Risk
Assessment
describe
the
application
of
the
Relative
Potency
Factor
(
RPF)
method
to
the
N­
methyl
carbamate
pesticides.
These
documents
a)
outline
the
steps
in
developing
the
dose­
response
relationships
for
each
pesticide
and
its
capacity
to
inhibit
AChE
in
rats;
b)
describe
the
data
used
in
the
assessment;
c)
summarize
the
empirical
dose­
response
modeling
which
provides
the
basis
for
the
relative
potency
factors
(
RPFs),
points
of
departure
(
PoDs),
and
estimates
of
AChE
inhibition
half
life;
and
d)
provide
the
rationale
for
selecting
oxamyl
as
the
index
chemical.

HAZARD
QUESTION
#
1
Empirical
Dose­
Response
and
Time
Course
Modeling
At
the
February,
2005
meeting
of
the
FIFRA
SAP,
EPA
proposed
an
empirical
model
for
use
in
the
cumulative
risk
assessment
of
the
N­
methyl
carbamates.
This
model
contains
a
dose­
response
and
a
time
to
recovery
component.
Based
on
the
comments
from
the
Panel
and
following
experience
with
its
application
EPA
made
some
modifications
to
this
proposed
model.
EPA
has
applied
this
revised
empirical
model
to
the
available
RBC
and
brain
cholinesterase
data
for
the
N­
methyl
carbamates.
BMD
and
BMDL
estimates
provided
in
the
preliminary
assessment
were
derived
from
cholinesterase
data
from
multiple
studies
and
in
some
cases,
using
different
cholinesterase
measurement
techniques.

H1a.
Please
comment
on
the
mathematical/
statistical
approach
to
modeling
cholinesterase
data
used
to
estimate
benchmark
dose
values
and
time
to
half­
life
recovery
in
the
preliminary
cumulative
risk
assessment.
Please
address
biological
and
mathematical/
statistical
considerations
in
your
response.

H1b.
Please
comment
on
the
adequacy,
clarity,
and
transparency
of
the
documentation
provided
for
the
empirical
dose­
response
and
time
course
modeling.
Page
3
of
12
HAZARD
QUESTION
#
2
Selection
of
the
Index
Chemical
EPA's
cumulative
risk
assessment
guidance
indicates
that
the
index
chemical
should
be
selected
based
on
the
availability
of
high
quality
toxicity
database
for
the
common
mechanism
endpoint.
The
selection
of
the
index
chemical
is
an
important
step
in
the
cumulative
risk
assessment;
the
BMD
for
oxamyl
was
used
to
calculate
RPFs
and
the
BMDL
for
oxamyl
was
used
as
the
PoD
for
extrapolating
cumulative
risk.

H2.
Please
comment
on
the
rationale
provided
for
the
selection
of
the
index
chemical.
Should
any
additional
factors
be
included
in
the
rationale
for
the
selection
of
oxamyl
as
the
index
chemical?

HAZARD
QUESTION
#
3
Selection
of
Brain
ChE
data
for
developing
RPFs
and
PoDs
EPA
has
used
data
for
brain
ChE
as
the
basis
for
the
RPFs
and
PoDs.
The
rationale
for
this
selection
was
provided
in
I.
B.

H3.
Please
comment
on
the
rationale
provided
for
the
selection
of
the
brain
ChE
as
the
basis
for
RPFs
and
PoDs
in
the
preliminary
cumulative
risk
assessment.
Should
any
additional
factors
be
considered?
Page
4
of
12
WATER
WATER
QUESTION
#
1
Revised
Conceptual
Model
for
Ground
Water
Based
on
recommendations
of
the
February
2005
SAP,
OPP
revised
its
ground
water
modeling
approach
to
estimate
pesticide
concentrations
in
the
upper
meter
of
a
fixed
saturated
zone
(
ground
water)
that
starts
at
3.5
m
below
the
surface.
The
Agency
has
included
two
additional
adjustments
to
the
original
conceptual
model
since
the
earlier
SAP.
The
models
consider
variable
degradation
rates
with
depth
and
account
for
setback
distances
between
the
well
and
the
application
area
by
using
lateral
velocity
to
estimate
the
additional
travel
time
for
a
pesticide
to
reach
the
well.

W1.
Please
comment
on
the
Agency's
revisions
to
the
ground
water
modeling
approach
to
account
for
variable
degradation
rates
with
depth
and
varying
setback
distances
between
the
well
and
treated
fields.

WATER
QUESTION
#
2
Comparisons
of
the
Three
Models
The
three
models
used
by
the
Agency
(
PRZM,
RZWQM,
and
LEACHP)
provided
predicted
concentrations
that
were
similar
on
average,
but
short­
term
concentration
differences
among
the
models
varied
considerably.
Differences
in
peak
concentration
estimates
ranged
from
a
factor
of
2
to
5
in
Florida
to
as
much
as
a
factor
of
20
in
North
Carolina;
however,
there
was
no
consistency
with
regard
to
which
model
gave
the
highest
or
lowest
predictions.
Some
of
these
differences
may
due
to
differences
in
the
way
the
models
handle
degradation­
temperature
relationships,
evapotranspiration,
and
weather
generation.

W2.
Given
that
no
model
stands
out
as
superior
when
compared
to
the
monitoring
data
evaluated
so
far,
can
the
SAP
suggest
criteria
for
further
evaluation
of
the
models?
Page
5
of
12
WATER
QUESTION
#
3
Evaluation
of
the
Ground
Water
Model
Estimates
The
Agency
compared
NMC
concentrations
in
ground
water
estimated
with
the
three
models
(
PRZM,
RZWQM,
LEACHP)
to
results
of
available
prospective
ground
water
monitoring
studies
(
oxamyl
in
NC
and
MD
and
methomyl
in
GA),
two
well­
monitoring
studies
along
the
central
ridge
of
FL,
and
published
literature
on
in­
field
monitoring
studies.
Using
the
FL
well
monitoring
data,
known
fate
characteristics
of
the
NMC
pesticides,
and
soil
and
hydrologic
data,
the
Agency
identified
the
conditions
under
which
exposures
similar
to
that
estimated
in
the
NMC
CRA
may
occur:
private
wells
drawing
from
shallow,
acidic
ground
water
with
high
to
very
high
saturated
hydraulic
conductivities
in
the
soil
and
vadose
zone.
This
has
allowed
the
Agency
to
move
toward
a
spatially­
explicit
characterization
of
potential
high
exposure
areas.

W3.
Please
comment
on
the
performance
of
the
models
against
the
available
monitoring
data.
What
additional
considerations
should
be
taken
when
applying
modeled
estimates
to
risk
assessments
for
areas
where
monitoring
data
are
not
available?
Page
6
of
12
FOOD
FOOD
QUESTION
#
1
The
food
portion
of
the
N­
methyl
carbamate
cumulative
risk
assessment
used
similar
data
sources
and
techniques
to
those
used
for
the
organophosphate
pesticide
for
estimating
cumulative
risk
from
food.
This
included
use
of
both
the
USDA's
Continuing
Survey
of
Food
Intakes
by
Individuals
(
CSFII)
as
a
data
source
for
food
consumption
and
Pesticide
Data
Program
Data
(
PDP)
as
a
data
source
for
food
residues.

F1.
Please
comment
on
the
planned
intermediate­
and
longer­
term
activities
associated
with
sensitivity
analyses
identified
in
Section
I
of
the
document.
Does
the
Panel
have
any
suggestions
for
other
or
additional
activities
which
the
Agency
should
consider?
Page
7
of
12
RESIDENTIAL
RESIDENTIAL
QUESTION
#
1
Use
of
REJV
Data
and
Professional
Judgment
To
generate
estimates
of
exposure
from
residential
use
of
NMC
pesticides,
the
probabilistic
models
use
a
variety
of
inputs
to
address
potential
exposure
from
multiple
use
scenarios.
Critical
inputs
include
the
percent
of
households
applying
the
various
pesticide
products,
and
the
timing
of
those
applications.
These
two
inputs,
coupled
with
potential
exposure
from
pesticide
residues
in
drinking
water
and
the
diet,
directly
impact
per
capita
estimates
of
cumulative
exposure.
In
its
February
Case
Study,
the
Agency
presented
background
information
on
the
Residential
Exposure
Joint
Venture
(
REJV)
survey.
The
Agency
used
this
database
as
the
primary
source
for
data
on
the
inputs
relating
to
timing
of
applications
and
percent
of
households
using
NMC
products.
Details
regarding
the
empirical
details
of
the
REJV
survey
are
presented
in
Appendix
II.
E.
1.

In
February
2005,
the
SAP
expressed
reservations
regarding
the
REJV
data.
In
response
to
SAP
concerns,
EPA
used
other
non­
survey
information
in
this
preliminary
CRA,
in
addition
to
estimates
from
REJV,
to
develop
use/
usage
inputs
and
seasonal
timelines
of
pesticide
use
which
were
representative
of
the
Southern
region
of
the
U.
S.

As
previously
mentioned,
the
REJV
survey
can
be
used
to
generate
empirically­
based
estimates
of
percent
of
household
use
and
the
frequency
of
product
specific
applications.
But,
because
the
REJV
did
not
collect
information
regarding
the
reason
for
the
reported
pesticide
use
(
pest
treated)
or
how
much
of
the
product
was
used,
the
empirical
timing
and
frequency
information
(
based
on
a
national
survey)
may
not
provide
a
clear
picture
of
regional
use.
Therefore,
to
establish
the
timing
of
pesticide
applications
for
the
scenarios
likely
to
result
in
the
highest
exposure,
OPP
made
these
estimates
based
on
a
combination
of
REJV
data,
product
label
information,
professional
judgment,
and
pest
pressure
information
available
from
the
Cooperative
State
Extension
Services.
Specific
examples
of
how
these
sources
were
used
to
determine
timing
and
frequency
of
pesticide
use
for
PNMC
residential
assessment
are
presented
in
Section
E
of
the
preliminary
NMC
CRA
document.

R1.
Please
comment
on
the
use
of
information
sources
other
than
REJV
to
establish
periods
of
pesticide
use
and
other
use/
usage
information.
Does
the
Panel
suggest
an
alternative
method
to
improve
the
use
of
REJV
in
the
NMC
assessment?
Does
the
Panel
know
of
other
data
sources
that
may
be
available?
Page
8
of
12
RESIDENTIAL
QUESTION
#
2
Uncertainties
Associated
with
the
Hand­
To­
Mouth
Assessment
To
assess
non­
dietary
ingestion
(
mg/
day),
the
following
four
key
factors
are
used
in
the
models:


Residue
Concentration
(
turf
residues,
pet
fur
residues,
and
residues
from
hard
indoor
surfaces)


Hand
to
mouth
frequency
(
number
of
events
per
hour)


Surface
area
of
the
inserted
hand
parts
(
cm2)


Exposure
time
(
hours/
day)

Other
factors
include
both
saliva
extraction
efficiency
and
wet
hand
adjustment
factor.
This
exposure
estimate
is
then
used
along
with
the
Relative
Potency
Factor
(
RPF)
and
Benchmark
Dose
to
estimate
risk.
In
the
Preliminary
N­
methyl
carbamate
assessment,
risk
estimates
for
non­
dietary
oral
exposure
result
in
the
lowest
Margins
of
Exposure
(
MOEs),
and
would
therefore
be
of
greatest
concern
to
the
Agency;
however,
these
low
MOEs
appear
to
be
due
in
part
to
the
incorporation
of
micro­
activity
data
into
our
macro
activity
models.
As
a
result,
the
non­
dietary
ingestion
scenarios
in
the
Preliminary
Nmethyl
carbamate
cumulative
risk
assessment
are
the
least
refined.

The
residue
concentration
values
are
derived
from
individual
residue
dissipation
or
deposition
studies
which
are
discussed
in
the
Residential
Chapter
(
Section
E)
of
the
Cumulative
Risk
Assessment
document.
The
exposure
durations
are
taken
from
the
Agency's
Exposure
Factors
Handbook.
The
hand
to
mouth
frequencies
and
hand
surface
areas
come
from
behavior
studies
relying
either
on
observational
data
of
young
children
using
video
tape
analysis,
trained
observers,
or
parental
observers.
However,
study
data
that
evaluated
hand­
to­
mouth
frequency
and
surface
area
mouthed
is
difficult
to
interpret.
Specifically,
comparison
of
study
results
can
be
difficult
due
to
differences
in
study
practices
and
methodologies.
For
example,
there
are
no
standard
definitions
of
mouthing
(
superficial
contact,
licking,
biting,
fraction
of
hand
inserted)
and
thus
the
data
for
these
behaviors
likely
differs
among
studies
as
a
result
of
the
investigators
definitions.
In
addition,
the
degree
to
which
ancillary
data
(
such
as
surface
area
of
hand
contacted
or
inserted,
the
duration
of
contact,
and
the
length
of
videotaping)
are
collected
and
reported
differ
among
studies.
This
makes
broad­
based
and
generallyapplicable
interpretation
difficult.
Nevertheless,
Drs.
Zartarian
and
Xue
allowed
us
the
use
their
preliminary
distributional
analyses
of
these
children's
video
data
in
this
assessment.
The
studies
used
in
the
hand
to
mouth
frequency
analysis
performed
by
Zartarian
and
Xue
are
briefly
summarized
in
a
table
provided
in
a
memorandum
dated
August
8,
2005
and
provided
to
the
Panel
under
separate
cover.
Page
9
of
12
The
distributions
of
hand­
to­
mouth
frequencies
and
surface
area
mouthed
used
in
the
Preliminary
NMC
CRA
were
based
on
the
analysis
performed
by
Zartarian
and
Xue
(
as
detailed
above).
In
the
aggregate
models
used
in
the
NMC
cumulative
assessment,
each
separate
iteration
selects
a
single
value
for
the
hand
to
mouth
events
variable
from
a
distribution
of
hand
to
mouth
frequency
values.
Also,
each
separate
iteration
of
the
model
selects
a
single
surface
area
from
a
distribution
of
the
fraction
of
hand
mouthed.
These
values
are
multiplied
by
the
residues
and
exposure
durations
which
are
similarly
selected
from
a
distribution
of
residue
and
exposure
durations
as
described
above.
This
relatively
simple
selection
process,
however,
ignores
the
numerous
complexities
and
interrelationships
involved
in
this
critical
behavior
pattern.
(
For
example,
the
fraction
of
a
hand
which
is
mouthed
during
each
mouthing
event
may
be
inversely
correlated
with
the
frequency
with
which
the
hand
is
mouthed.
Specifically,
a
high
frequency
of
hand­
to­
mouth
events
may
be
associated
with
a
smaller
fraction
of
the
hand
which
is
mouthed.
The
algorithms
used
in
the
NMC
CRA
however,
(
as
established
by
the
OPP
Residential
Standard
Operating
Procedures
(
SOP's))
assume
independence
between
these
two
parameters.
This
assumption
likely
leads
to
overestimates
of
exposures
when
upper
percentiles
of
the
hand­
to­
mouth
frequency
and
area
of
hand
mouthed
distributions
are
combined.
In
addition,
the
macroactivity
approach
used
in
the
NMC
CRA
aggregate
models
is
based
on
the
following
assumptions:


The
mouthing
frequency
(
events
per
hour),
as
recorded
during
the
course
of
observational
studies,
continue
at
the
same
rate
for
the
entire
exposure
duration
selected;
in
reality,
a
high­
end
mouthing
frequency
recorded
over
a
short
time
interval
(
e.
g.,
one
hour)
may
not
be
likely
to
continue
at
the
same
intensity
over
a
longer
time
period
(
e.
g.,
6
or
8
hours)


The
hand
is
fully
replenished
with
residues
from
a
contaminated
surface
(
e.
g.,
the
lawn,
pet
or
hard
flooring)
between
each
hand
to
mouth
event

The
contact
frequency
and
surface
area
data
used
in
this
assessment
are
taken
from
observational
studies
in
which
all
hand
contacts
were
recorded
as
hand­
tomouth
events,
regardless
of
the
fraction
of
hand
mouthed.
Additionally,
no
adjustment
was
made
for
the
duration
of
time
the
hand
remained
in
the
mouth.

R2a.
The
methodology
used
in
the
NMC
CRA
in
which
micro­
activity
data
are
used
in
macro­
activity
approach
likely
leads
to
systematic
overestimates
of
exposure
when
upper
percentiles
of
mouthing
frequency
and
surface
area
of
hand
mouthed
are
combined.
Does
the
Panel
agree
that
this
methodology
does
indeed
overestimate
exposure?
Can
the
Panel
suggest
improvements
to
this
methodology
to
further
refine
exposure
estimates?

R2b.
Does
the
Panel
have
suggestions
for
an
alternative
approach
than
the
one
used
to
estimate
the
non­
dietary
oral
exposure
pathway
in
the
Preliminary
NMC
CRA?
For
example,
would
the
use
of
a
time
weighted
frequency
value
based
on
random
hourly
draws
of
hand
frequency
distributions
more
accurately
estimate
hand­
to­
mouth
exposures?
Page
10
of
12
RESIDENTIAL
QUESTION
#
3
Distributional
Analysis
Assessing
residential
exposure
to
pesticides
is
a
complex
process
that
must
consider
exposure
from
a
variety
of
sources
via
multiple
routes.
To
account
for
exposure
from
different
sources,
the
PNMC
residential
exposure
assessment
identifies
scenarios
where
significant
exposure
may
occur.
Each
of
these
scenarios
is
defined
by
a
specific
type
of
activity
or
set
of
activities
that
may
result
in
exposure.
Generally
the
relationships
between
these
activities
and
the
resulting
exposures
are
well­
defined
in
that
algorithms,
equations,
and
standard
operating
procedures
exist
for
calculating
exposure
based
on
the
activity
being
performed.
However
the
supporting
data
sets
used
to
estimate
exposure
for
various
residential
scenarios
range
from
robust
(
e.
g.
unit
exposure
values)
to
limited
or
sparse
(
e.
g.
lawn
sizes,
area
treated,
duration
of
exposure,
and
saliva
extraction
factors).
Additionally,
information
characterizing
the
extent
to
which
each
activity
contributes
to
exposure
for
a
particular
scenario
does
not
always
exists
(
e.
g.
the
amount
of
time
spent
in
home
gardens
performing
activities
such
as
hand
weeding
versus
staking
tomatoes
or
harvesting
sweet
corn).

In
general,
the
Agency
has
attempted
to
fit
distributions
(
as
described
in
Appendix
II.
E.
2
of
the
NMC
CRA)
to
the
exposure
measurements
for
residential
activities
when
supporting
information
exists
to
characterize
the
extent
to
which
the
activity
contributes
to
exposure
for
the
residential
scenario
of
interest.
However,
the
Agency
has
employed
uniform
distributions
to
the
data
sets
for
which
such
supporting
information
does
not
exist,
(
e.
g.
lawn
sizes,
area
treated,
duration
of
exposure,
and
saliva
extraction
factors).
The
Agency
has
elected
to
create
such
distributions
when
the
available
data
are
limited
to
such
an
extent
that
it
is
uncertain
how
well
they
represent
national
variability.
The
Agency
believes
use
of
uniform
distributions
to
be
conservative
in
estimating
potential
exposure
since
uniform
distributions
tend
to
overestimate
exposure.

R3a.
Please
comment
specifically
on
the
Agency's
use
of
lognormal
distributions
to
estimate
residential
exposure
and
the
statistical
methods
and
procedures
by
which
the
Agency
has
selected
particular
distributions
(
e.
g.
probability
plots
and
goodness­
of­
fit
statistics).

R3b.
Does
the
Panel
agree
that
the
Agency's
approach
to
creating
and
using
of
uniform
distributions
(
i.
e.
ranges
of
values)
for
residential
scenarios
lacking
adequate
supporting
information
tends
to
overestimate
exposure?
Is
the
Panel
aware
of
other
data
sources
that
may
be
better
suited
for
assessing
residential
exposure
scenarios
of
interest?
Does
the
Panel
have
any
suggestions
regarding
alternative
distributions
to
use
for
scenarios
where
supporting
exposure
information
is
inadequate?
To
what
extent
should
sensitivity
analyses
be
used
to
assess
the
appropriateness
of
alternative
distributions?
Page
11
of
12
R3c.
When
the
Agency
fits
distributions
to
various
exposure
values,
the
maximum
value
entered
into
the
probabilistic
models
for
a
particular
distribution
is
usually
defined
to
be
an
upper
percentile
value
such
as
the
99th
percentile
in
order
to
ensure
realistic
input
parameters.
Recognizing
that
the
Agency
intends
to
perform
sensitivity
analyses
to
evaluate
the
effects
of
this
truncation,
please
comment
on
the
Agency's
approach
of
truncating
distributions
that
are
input
to
the
probabilistic
models.
Please
comment
on
any
other
approaches
that
the
Agency
might
use
to
evaluate
uncertainties
associated
with
choices
about
whether
and
where
to
truncate
distributions.
Page
12
of
12
INTEGRATION
INTEGRATION
QUESTION
#
1
The
cumulative
risk
assessment
guidance
describes
key
principles
for
conducting
these
risk
assessments.
One
such
principle
is
the
need
to
consider
the
time
frame
of
both
the
exposure
(
e.
g.,
When
does
exposure
occur?
What
is
the
exposure
duration?)
and
of
the
toxic
effect
(
e.
g.,
What
are
the
time
to
peak
effects
and
the
time
to
recovery?
How
quickly
is
the
effect
reversed?).
EPA's
Preliminary
Cumulative
Risk
Assessment
for
the
N­
methyl
carbamates
describes
the
current
limitations
in
data
and
software
to
fully
characterize
the
dynamic
nature
of
exposure,
effect,
and
recovery
for
this
common
mechanism
group.
In
order
to
address
these
limitations,
OPP
performed
an
examination
of
the
exposure
patterns
for
records
from
the
high
end
of
exposure
distribution
and
found
that
that
a
large
fraction
(~
70%)
of
daily
records
contributing
to
the
upper
tail
of
the
food
exposure
distribution
represent
single
eating
occasions.
Regarding
drinking
water
and
residential/
nonoccupational
exposure,
EPA's
preliminary
assessment
provided
a
characterization
of
the
current
availability
regarding
datasets
and
models
and
a
description
of
the
impact
of
these
limitations
on
the
risk
estimates
from
specific
exposure
pathways
(
i.
e.,
drinking
water,
residential).

I1a.
Please
comment
on
clarity
and
adequacy
of
the
risk
characterization
provided
in
the
preliminary
cumulative
risk
assessment.
Are
there
important
aspects
with
respect
to
the
strengths
and
weaknesses
of
the
risk
characterization
other
than
the
ones
we
identified?

I1b.
Is
the
Panel
aware
of
additional
data
which
would
aid
the
Agency
in
its
cumulative
risk
characterization
for
the
N­
methyl
carbamate
pesticides?
For
example,
is
the
Panel
aware
of
any
available
data
on
the
timing
of
water
consumption
events
or
can
the
Panel
make
any
recommendations
regarding
reasonable
assumptions
that
could
be
made
to
help
characterize
the
estimated
risk?
Are
there
other
sensitivity
analyses
and
further
investigations
that
would
be
equally
or
more
important
than
the
ones
we
identified?
