Document ID: EPA-HQ-OPP-2006-0201-0008
Agency: epa
Document Type: Supporting & Related Material
Title: 
Posted Date: 2006-04-05T04:00Z

UNITED
STATES
ENVIRONMENTAL
PROTECTION
AGENCY
WASHINGTON
D.
C.,
20460
OFFICE
OF
PREVENTION,
PESTICIDES
AND
TOXIC
SUBSTANCES
PC
Codes:
012501,
012502,
013802,
013803,
013806
DP
Barcode:
D309097
Date:
March
29,
2006
DRINKING
WATER
ASSESSMENT
SUBJECT:
Response
to
Registrant
Phase
I
Error
Only
Comments:
Drinking
Water
Assessment
for
Organic
Arsenical
Herbicides
for
the
Reregistration
Eligibility
Decision
(
RED)

TO:
Diana
Locke,
Risk
Assessor
Reregistration
Branch
II
Health
Effects
Division
(
7509C)

Lance
Wormell,
Chemical
Review
Manager
Reregistration
Branch
II
Special
Review
and
Reregistration
Division
(
7508C)

FROM:
Keara
Moore,
Chemist
Environmental
Risk
Branch
III
Environmental
Fate
and
Effects
Division
(
7507C)

THROUGH:
Mark
Corbin,
Senior
Environmental
Scientist
Environmental
Risk
Branch
III
Environmental
Fate
and
Effects
Division
(
7505C)

APPROVED
Daniel
Rieder,
Branch
Chief
BY:
Environmental
Risk
Branch
III
Environmental
Fate
and
Effects
Division
(
7507C)
2
Attached,
please
find
the
revised
Drinking
Water
Assessment
for
organic
arsenical
herbicides.
Revisions
have
been
made
to
the
previous
Drinking
Water
Assessment
(
DP
Barcode
309098;
February
3,
2006)
to
correct
any
mathematical/
typographical
errors
and
provide
clarification
in
areas
identified
by
the
registrants
in
their
Phase
1
response.
Additional
comments
were
received
regarding
EPA's
methodology
and
environmental
fate
results;
these
comments
will
be
addressed
after
the
60­
day
Phase
3
public
comment
period
scheduled
to
begin
in
April
2006.

The
revisions
made
in
this
document
do
not
alter
any
EFED
conclusions
from
the
previous
assessment.
Where
appropriate,
references
to
"
degradation"
have
been
replaced
with
the
more
suitable
term
"
metabolism."
Language
has
been
added
to
clarify
the
discussion
of
the
potential
for
transformation
of
organic
arsenicals
to
inorganic
arsenic
and
for
transformation
of
dimethylated
arsenical
species
to
monomethylated
species.
Clarification
has
also
been
added
in
discussion
of
the
application
rates
and
half
lives
used
in
modeling
and
in
discussion
of
the
sorption
properties
of
arsenicals.
Uncertainty
in
estimates
of
surface
water
exposure
resulting
from
use
on
turf
has
been
emphasized
by
adding
further
discussion
of
the
issue
in
the
executive
summary
of
the
document.
3
EXECUTIVE
SUMMARY
This
memorandum
presents
the
results
of
the
Environmental
Fate
and
Effects
Division's
(
EFED)
drinking
water
assessment,
conducted
to
support
the
human
health
aggregate
risk
assessment
for
the
reregistration
of
organic
arsenicals.
Five
individual
herbicides
are
included
in
this
assessment:
cacodylic
acid
(
DMA;
dimethylarsinic
acid),
sodium
cacodylate
(
DMA­
Na),
monosodium
methanearsonate
(
MSMA),
disodium
methanearsonate
(
DSMA),
and
calcium
acid
methanearsonate
(
CAMA).
Past
assessments
have
handled
cacodylic
acid
and
sodium
cacodylate
separately
from
the
methylarsonate
salts
(
MSMA,
DSMA,
CAMA).
The
current
assessment
considers
all
of
these
pesticides
together
as
the
"
organic
arsenicals."
These
pesticides
are
all
alike
in
that
they
contain
arsenic
in
a
methylated
form.
They
have
similar
chemical
structures
and
environmental
fate
properties.
All
have
the
potential
to
metabolize
to
the
more
toxic
inorganic
arsenic.
Because
arsenic
is
elemental
and
does
not
degrade,
application
of
any
organic
arsenical
pesticide
may
contribute
to
total
arsenic
loading,
whether
as
parent
compound
or
inorganic
arsenic,
in
surface
water,
groundwater,
soil,
or
plants,
depending
on
environmental
conditions.
In
light
of
these
considerations,
the
environmental
fates
of
these
pesticides
are
discussed
as
a
group.
In
addition
to
estimating
concentrations
resulting
from
application
of
individual
compounds,
situations
where
multiple
organic
arsenicals
may
be
applied
to
the
same
field
are
considered,
and
the
uncertainty
resulting
from
the
possibility
of
multiple
uses
in
a
single
watershed
is
discussed.

The
estimated
drinking
water
concentrations
(
EDWC)
are
based
on
application
rates
from
the
set
of
master
labels
provided
by
the
Methanearsonic
Acid
Research
Task
Force
(
MAATF),
dated
November
14,
2005.
These
encompass
all
uses
except
for
application
of
DMA
to
turf
and
non­
crop
areas,
which
will
be
addressed
in
a
future
label.
It
is
the
assumption
that
any
labels
for
formulated
products
which
exceed
these
maximum
application
rates
will
be
revised
to
comply
with
the
master
labels.
Nearly
3.5
million
pounds
of
these
pesticides
are
applied
annually,
with
approximately
70%
of
the
total
use
as
an
herbicide
or
a
desiccant
on
cotton
and
another
27%
as
an
herbicide
on
turf.
These
use
data
do
not
include
residential
uses,
which
are
expected
to
be
a
small
percentage
of
the
total
use.
Because
of
the
predominance
of
the
cotton
and
turf
uses,
EDWCs
are
based
on
those
uses.

EFED
estimated
drinking
water
concentrations
for
exposure
to
surface
water
are
presented
in
Table
1.
These
values
were
modeled
using
the
Pesticide
Root
Zone
Model
(
PRZM
3.12)
and
the
Exposure
Analysis
Modeling
System,
(
EXAMS
2.98.04)
with
the
pe4v01
graphical
interface
and
represent
the
two
most
vulnerable
available
scenarios.
The
species
of
concern
in
this
assessment
 
the
methylarsonate
salts,
DMA,
and
inorganic
arsenic
 
all
have
distinct
toxicities;
exposure
to
each
needs
to
be
considered
individually.
Individual
EDWCs
are
therefore
provided
for
each,
including
DMA
and
inorganic
arsenic
as
potential
metabolites
as
well
as
the
parent
compounds.
The
total
arsenic
value
incorporates
all
arsenical
species
that
may
be
present
as
a
result
of
pesticide
application,
including
inorganic
arsenic.
The
total
arsenic
EDWC
can
be
compared
to
regulatory
levels,
all
of
which
are
defined
by
total
arsenic.
For
drinking
water,
the
4
Table
1.
EDWCs
(
ppb)
from
maximum
labeled
rates
for
major
uses
of
arsenicals.

Acute
Chronic
Cancer
TURF
MMA1
250.5
127.5
74.6
DMA
102.3
46.5
28.1
Total
As2
135.2
68.8
40.3
COTTON
MMA1
37.4
11.0
5.3
DMA
23.6
7.4
4.3
Total
As2
20.9
7.2
3.9
1
Monomethyl
arsonic
acid
(
MMA)
is
the
acid
equivalent
form
of
the
methylarsonate
salts.
2
Total
arsenic
is
the
sum
of
arsenic
(
as
ppb
As)
that
may
be
present
from
all
applied
and
metabolite
species.
It
also
represents
the
maximum
EDWC
of
inorganic
arsenic.

Maximum
Contaminant
Level
(
MCL)
for
total
arsenic
is
10
ppb
and
is
based
on
concerns
for
long­
term
exposure.
As
a
conservative
assumption,
the
entire
estimated
total
arsenic
EDWC
may
be
present
as
inorganic
arsenic.
No
EDWCs
are
provided
for
exposure
to
groundwater.
Based
on
the
environmental
fate
properties
of
organic
arsenicals,
leaching
to
groundwater
is
not
expected
to
contribute
significantly
to
the
already
existing
burden
of
arsenic
in
groundwater
except
in
highly
vulnerable
situations.

Organic
arsenicals
are
stable
to
hydrolysis
and
photolysis
but
in
many
conditions,
they
can
be
subject
to
microbial
metabolism
in
soil
under
aerobic
and
anaerobic
conditions.
The
occurrence,
rate,
and
products
of
this
metabolism
are
variable,
dependent
on
environmental
conditions.
Persistence
of
applied
parent
compounds
can
range
from
days
to
years,
depending
on
environmental
conditions.
Although
it
may
convert
to
different
forms,
however,
the
arsenic
in
these
pesticides
does
not
disappear;
arsenic
from
pesticides
is
not
lost
but
redistributed
and
transformed
throughout
the
environment.
Organic
arsenicals
and
their
metabolites
are
strongly
sorbing
and
are
expected
to
be
relatively
immobile
in
soil
in
most
conditions.

Arsenic
occurs
in
the
environment
naturally
in
variable
concentrations.
A
USGS
statistical
analysis
of
50,000
groundwater
samples
from
30,000
locations
found
that
nearly
half
of
the
groundwater
samples
had
total
arsenic
concentrations
<
1
ppb
while
about
10%
exceeded
10
ppb.
Areas
of
high
arsenic
groundwater
are
scattered
throughout
the
country
but
are
more
likely
to
be
found
in
the
Intermountain
West
and
Pacific
Coast
regions.
A
less
thorough
consideration
of
a
USGS
dataset
including
40,000
samples
from
4500
lake
and
stream
locations
found
that
in
surface
water
also,
half
of
the
samples
had
total
arsenic
concentrations
 
1.1
ppb
and
10%
of
the
samples
exceeded
10
ppb.
The
limited
data
available
for
speciated
arsenic
suggest
that
in
both
surface
and
groundwater,
natural
arsenic
is
present
primarily
in
the
inorganic
form.

Potential
exposure
to
arsenic
in
drinking
water
from
pesticide
application,
separate
from
natural
background
levels,
was
assessed
through
evaluation
of
targeting
monitoring
data
from
surface
and
groundwater
in
pesticide
use
areas
as
well
as
through
the
surface
water
5
modeling
discussed
above.
A
summary
of
groundwater
monitoring
in
areas
in
North
Dakota,
South
Dakota,
Wisconsin,
and
Minnesota
where
high
arsenic
concentrations
regionally
coincided
with
agricultural
use
found
that
in
these
areas,
the
groundwater
concentrations
were
largely
unaffected
by
use
of
arsenical
pesticides.
In
Florida
golf
courses,
however,
groundwater
detections
of
total
arsenic
as
high
as
123
ppb,
significantly
higher
than
local
background,
have
been
attributed
to
use
of
MSMA.
Targeted
surface
water
monitoring
has
been
conducted
in
cotton
use
areas
as
well
as
in
golf
course
ponds
in
Florida.
In
cotton
growing
regions
of
Mississippi,
surface
water
concentrations
up
to
5.5
ppb
total
arsenic
were
measured.
This
appears
to
be
higher
than
natural
background
arsenic
levels,
but
the
results
are
inconclusive.
In
limited
sampling
of
Florida
golf
course
ponds,
the
highest
total
arsenic
level
found
was
24
ppb.
For
all
arsenic
monitoring
data,
there
is
some
uncertainty
in
determining
the
source
of
elevated
levels.

Uncertainties,
limitations,
and
assumptions
in
the
drinking
water
assessment
include
the
following:

 
Environmental
fate
data
for
DSMA
and
CAMA
are
primarily
based
on
studies
for
MSMA
because
all
of
these
methylarsonate
salts
dissociate
to
monomethyl
arsonic
acid
(
MMA)
in
aqueous
solution.
Environmental
fate
studies
for
both
MMA
and
DMA
are
included
in
a
single
discussion
based
on
the
assumption
that
general
fate
processes
are
similar,
even
if
specific
rates
and
sorption
coefficients
are
not
identical.

 
For
fate
discussions
and
modeling,
environmental
fate
data
for
all
organic
arsenicals
are
based
on
open
literature
studies
as
well
as
registrant
submitted
data.
The
majority
of
metabolism
data
are
from
non­
GLP
studies
that
were
conducted
for
less
than
one
year.
Transformation
of
applied
organic
arsenicals
to
volatile
alkylarsines
is
assumed
to
be
a
minor
dissipation
route.

 
Modeling
to
estimate
drinking
water
concentrations
is
based
on
application
of
pesticide
to
an
entire
watershed.
The
results
are
then
modified
using
a
percent
cropped
area
factor
(
PCA).
Because
of
the
variety
of
sites
where
use
on
turf
is
possible,
no
PCA
has
been
developed
and
the
estimated
concentration
is
based
on
the
unmodified,
entire
watershed
result.
This
is
likely
an
overestimation
of
exposure
but
the
extent
of
overestimation
is
undefined.
Comparing
the
modeled
result
to
the
very
limited
monitoring
data
which
are
available,
the
highest
concentration
observed
is
approximately
one
half
of
the
chronic
concentration
estimated
by
modeling.
For
the
cotton
use,
the
cotton
PCA
was
used
in
estimating
exposure
despite
the
fact
that
arsenicals
may
be
applied
to
other
crops
in
the
same
watershed.
The
cotton
exposure
estimate
may
therefore
be
an
underestimate,
but
limited
monitoring
data
suggest
that
the
results
are
reasonable.

 
Several
additional
assumptions
are
made
in
modeling
exposure
to
arsenic
species
other
than
the
parent
compound.
The
estimate
of
metabolism
to
DMA
is
based
on
the
assumption
that
35%
is
the
maximum
amount
of
MMA
that
may
be
present
as
6
DMA
at
any
one
time.
Because
significant
transformation
from
DMA
to
MMA
has
not
been
confirmed
in
field
or
laboratory
studies,
in
modeling
it
is
assumed
that
no
transformation
occurs.
.
Maximum
potential
concentrations
of
inorganic
arsenic
are
represented
by
the
total
arsenic
EDWCs,
calculated
as
a
molar
conversion
of
the
EDWCs
of
parent
compounds.
This
is
a
general
estimate
of
the
amount
of
inorganic
arsenic
that
may
reach
surface
water
rather
than
a
direct
calculation
based
on
specific
physical
processes.

 
Because
of
the
multiple
potential
sources
of
arsenic,
both
natural
and
anthropogenic,
it
can
be
difficult
to
determine
the
source
of
arsenic
found
in
monitoring
studies.
Sampling
in
studies
of
background
arsenic
is
typically
not
uniformly
distributed
and
not
designed
to
limit
consideration
to
only
uncontaminated
regions.
In
targeted
studies,
detailed
land
use
histories
and
pesticide
application
information
are
not
always
available
and
conclusions
are
based
primarily
on
general
trends.
7
TABLE
OF
CONTENTS
PESTICIDE
USE
AND
APPLICATION.....................................................................
9
MSMA
and
DSMA
....................................................................................................
9
CAMA.....................................................................................................................
11
Cacodylic
Acid
.......................................................................................................
11
Co­
occurrence
........................................................................................................
11
ENVIRONMENTAL
FATE
AND
TRANSPORT
CHARACTERIZATION...........
12
GROUNDWATER
EXPOSURE................................................................................
15
Groundwater
Monitoring........................................................................................
15
Background
Arsenic
(
Non­
targeted
Monitoring)
.....................................................
15
Pesticide
Impacts
(
Targeted
Monitoring)................................................................
18
SURFACE
WATER
EXPOSURE..............................................................................
21
Surface
Water
Monitoring
......................................................................................
21
Background
Arsenic
(
Non­
targeted
Monitoring)
.....................................................
21
Pesticide
Impacts
(
Targeted
Monitoring)................................................................
23
Surface
Water
Modeling..........................................................................................
24
Input
Parameters:
Metabolism
Rates
.....................................................................
26
Input
Parameters:
Soil
Mobility.............................................................................
29
Calculation
of
Metabolites......................................................................................
30
Percent
Cropped
Area
............................................................................................
31
Characterization.....................................................................................................
31
SOIL
ACCUMULATION...........................................................................................
35
UNCERTAINTY.........................................................................................................
36
8
Monitoring
...............................................................................................................
36
Surface
Water
Modeling..........................................................................................
36
REFERENCES............................................................................................................
39
Appendix
A:
PRZM/
EXAMS
Input
Files
................................................................
42
Appendix
B:
PRZM/
EXAMS
Output
Files..............................................................
62
9
PESTICIDE
USE
AND
APPLICATION
Organic
arsenicals
are
nonselective
contact
herbicides
used
to
control
grasses
and
broadleaf
weeds
in
a
variety
of
agricultural
and
non­
agricultural
applications.
This
assessment
is
based
on
master
labels
provided
by
the
registrants
on
11/
14/
05
which
have
not
yet
been
finalized
but
which
are
assumed
to
invalidate
all
previous
labels.
Variance
from
these
rates
could
change
the
conclusions
of
this
assessment.
Table
2
provides
a
summary
of
maximum
application
rates
allowed
by
these
master
labels.

MSMA
and
DSMA
Monosodium
methanearsonate
(
MSMA)
and
disodium
methanearsonate
(
DSMA)
are
used
in
a
wide
variety
of
applications.
Although
applied
as
different
parent
compounds,
MSMA
and
DSMA
end
up
as
the
same
chemical
in
the
environment,
monomethyl
arsonic
acid
(
MMA).
For
this
reason,
labels
for
all
uses
specify
that
the
maximum
number
of
applications
applies
to
"
either
DSMA
or
MSMA
or
their
combination
per
crop,
per
year."
Rates
for
both
are
reported
here
in
acid
equivalents
(
ae)
to
represent
the
amount
applied
as
MMA.
The
main
agricultural
application
for
both
is
as
a
pre/
postemergent
herbicide
on
cotton
applied
prior
to
the
first
bloom.
The
major
use
area
for
both
MSMA
and
DSMA
is
in
the
southeastern
US,
including
Georgia,
Arkansas,
Mississippi,
Alabama,
Louisiana,
and
North
and
South
Carolina.
USGS
pesticide
maps,
based
on
data
from
1995­
1998,
show
use
of
MSMA,
but
not
DSMA,
in
Texas,
New
Mexico,
Arizona,
and
California
as
well
(
USGS,
2003).

The
only
other
agricultural
uses
of
MSMA
and
DSMA
supported
by
master
labels
are
in
non­
bearing
orchards,
citrus,
and
vineyards.
Non­
agricultural
uses
of
MSMA
and
DSMA
include
use
on
turf
and
non­
crop
uses.
The
turf
use
is
both
residential
and
commercial,
including
residential
lawns,
sod
farms,
golf
courses,
parks,
and
other
areas.
The
non­
crop
use
includes
drainage
ditch
banks,
rights­
of­
way,
storage
yards
and
similar
areas.
The
maximum
application
rates
for
all
of
these
uses
are
included
in
Table
2.

BEAD
estimates
that
100%
of
agricultural
use
of
DSMA
is
on
cotton
at
approximately
200,000
lbs/
yr,
based
on
use
data
from
1998
to
2003
(
BEAD,
2005b).
Limited
information
on
non­
agricultural
uses
of
DSMA
is
available
but
it
is
expected
to
be
a
small
percentage
of
total
use.
Use
of
MSMA
is
much
higher,
for
both
agricultural
and
non­
agriculture
uses,
and
so
more
data
are
available
to
quantify
non­
agricultural
use.
On
cotton,
use
of
MSMA
is
estimated
at
2
million
lb/
yr,
two­
thirds
of
the
total
MSMA
usage
of
3
million
lbs/
yr.
The
remaining
one­
third
of
use
is
primarily
on
turf,
estimated
at
930,000
lb/
yr
and
including
sod
farms,
golf
courses,
lawn
care
operators,
and
other
turf
uses.
This
estimate
does
not
include
individual
residential
use.
Golf
courses
account
for
approximately
half
of
the
MSMA
applied
on
turf.
Interestingly,
lawn
care
operators
treated
almost
as
many
acres
as
golf
courses
but
used
around
a
quarter
of
the
pounds.
Estimates
of
non­
agricultural
use
of
MSMA
are
based
on
proprietary
data
from
2000.
Other
uses
found
for
MSMA,
in
order
of
decreasing
percentage,
include
pasture,
citrus,
pistachios,
walnuts,
watermelon,
apples,
and
pecans.
Combined,
these
uses
contributed
less
than
3%
of
total
annual
use
(
BEAD,
2005a
&
b).
10
Table
2.
Application
Rates
for
Organic
Arsenicals,
based
on
11/
14
Master
Labels
Use
Maximum
App.
Rate
(
lb
ai/
A)
Max.
No.
Apps.
Application
Interval
Application
Method
DSMA1
1.7
1
n/
a
g
round
or
aerial
Cotton
1.7
2
1
 
3
weeks
ground
(
directed)

Turf
2
2.5
4
14
days
g
round
spray
Orchards,
Citrus,
Vineyards
3
3.7
3
not
specified
g
round
(
directed)

Non­
crop
4
3.9
4
10
 
14
days
ground
spray
Grass
for
seed
5
3.3
1
n/
a
n
ot
specified
MSMA1
1.7
1
n/
a
g
round
or
aerial
Cotton
1.7
2
not
specified
g
round
(
directed)

Turf
­
Sod
Farms6
­
Golf
Course6
3.4
2.2
4
10
 
14
days
ground
spray
Orchards,
Citrus,
Vineyards
3
3.7
3
10
 
14
days
ground
spray
Non­
crop
4
3.4
4
10
 
14
days
ground
spray
Grass
for
seed
5
5.3
1
n/
a
n
ot
specified
CAMA1
3.6
4
not
specified
ground
spray
Turf
2.2
 
4.4
2
not
specified
ground
spray
Cacodylic
Acid
/
Sodium
Cacodylate
Cotton
1.2
1
n/
a
g
round
or
aerial
Citrus
3
5.0
3
not
specified
g
round
spray
Non­
crop
4
8.1
3
not
specified
g
round
spray
Turf
­
general
­
lawn
renovation
5
lb/
100gal
8.4
­
21
not
specified
not
specified
not
specified
5
days
ground
spray
ground
spray
1
Reported
as
lbs
acid
equivalent/
A.
2
Prohibited
on
golf
course
greens.
3
Non­
bearing
only
­
not
to
be
used
within
one
year
of
harvest.
Restricted
to
spot
treatments
in
Florida.
4
Non­
crop
=
"
drainage
ditchbanks,
rights­
of­
way,
storage
yards
and
similar
areas".
5
Pacific
Northwest
only.
6
Sod
farm
rate
allowed
on
sod
farms
and
established
Bermuda
and
Zoysiagrass.
Golf
course
rate
allowed
on
athletic
fields,
golf
courses,
and
parks.
5
Pacific
Northwest
only.
11
CAMA
Calcium
acid
methanearsonate
(
CAMA)
is
a
minor
use
contact
herbicide
applied
to
control
crabgrass
in
residential
areas.
It
is
only
sold
at
the
retail
level
and
not
to
commercial
or
industrial
applicators.
As
with
DSMA
and
MSMA,
in
aqueous
solution
CAMA
dissociates
to
MMA
and
so
rates
are
reported
as
acid
equivalents.
The
maximum
labeled
application
rate
for
CAMA
is
4
applications
at
3.6
lb
ae/
A.
Limited
usage
data
are
available
for
residential
uses,
but
the
total
usage
of
CAMA
is
estimated
to
account
for
less
than
1%
of
total
national
usage
of
the
methanearsonate
salts.

Cacodylic
Acid
Cacodylic
acid
(
DMA),
sometimes
formulated
with
its
sodium
salt,
sodium
cacodylate
(
DMA­
Na),
is
used
primarily
as
a
defoliant
on
cotton.
Current
labels
for
irrigated
and
dryland
cotton
allow
application
of
up
to
1.2
lb
ai/
A
annually
by
either
aerial
or
ground
spray.
Treatment
on
cotton
is
made
when
50%
or
more
of
the
bolls
have
opened
(
7
to
10
days
prior
to
the
anticipated
picking
date).
The
most
recent
USGS
pesticide
use
maps,
based
on
data
from
1995­
1998,
indicate
that
use
of
DMA
on
cotton
is
limited
to
California
and
Arizona
(
USGS,
2003).
Based
on
use
data
from
1998­
2003,
BEAD
estimates
average
annual
use
of
DMA
on
cotton
of
80,000
lbs/
yr
and
for
DMA­
Na,
use
is
estimated
at
100,000
lbs/
yr.
The
total
use
of
cacodylate
on
cotton,
then,
is
180,000
lb/
yr.
The
current
BEAD
analysis
also
estimates
that
20,000
lb/
yr
of
DMA
is
used
on
corn.
EFED
is
not
aware
of
any
labeled
uses
on
corn;
it
is
not
a
use
supported
under
the
proposed
master
label
(
BEAD,
2005b).

A
small
proportion
of
DMA/
DMA­
Na
use
is
on
non­
crop
sites,
including
utilities,
residential
outdoor,
and
weed
treatment
around
the
bases
of
citrus
trees.
Application
rates
for
DMA/
DMA­
Na
to
non­
crop
sites
are
mostly
higher
than
for
cotton;
for
many
products,
however,
directions
simply
specify
mixing
a
certain
amount
of
product
in
a
specified
number
of
gallons
of
water
and
applying
the
spray
solution
to
the
point
of
runoff.
The
labels
imply,
however,
that
in
these
uses
DMA
is
expected
to
be
applied
to
a
very
small
area,
with
most
labeled
rates
described
in
terms
of
how
much
product
to
apply
to
areas
from
40
to
1000
square
feet.
Application
for
non­
crop
sites
is
by
ground
only.
Because
DMA/
DMA­
Na
produces
a
top­
kill
only,
repeat
applications
are
needed
for
season
long
weed
control.
Some
labels
limit
the
number
of
applications
to
three
per
year
but
many
simply
state
that
repeat
applications
can
be
made
as
needed.
The
registrants
are
preparing
a
master
label
for
these
uses
also;
that
label
was
not
complete
at
the
time
of
the
current
assessment
and
so
has
not
been
considered
here.
No
national
use
data
are
available
for
non­
crop
applications.
BEAD's
agricultural
usage
analysis
found
no
use
on
citrus
(
BEAD,
2005b).

Co­
occurrence
On
cotton,
it
is
possible
that
DSMA
or
MSMA,
as
early­
season
herbicides,
and
DMA,
as
a
late­
season
desiccant,
could
be
applied
to
the
same
field.
BEAD
estimates
that
this
cooccurrence
is
likely
to
affect
less
than
1%
of
the
cotton
crop.
It
is
also
possible
that
DMA,
MSMA,
DSMA,
and
CAMA
could
be
applied
to
multiple
crops
within
the
same
watershed.
12
ENVIRONMENTAL
FATE
AND
TRANSPORT
CHARACTERIZATION
Note:
What
follows
is
a
summary
of
the
environmental
fate
and
transport
characteristics
of
organic
arsenicals.
A
detailed
discussion
of
these
complex
processes
is
included
as
an
appendix
in
the
Ecological
Risk
Assessment
document
(
DP
Barcode
D309100).
That
discussion
includes
references
to
all
registrant
conducted
and
open
literature
reports
considered.

MSMA,
DSMA,
and
CAMA
are
salts
of
the
dibasic
weak
acid
MMA.
In
aqueous
solution,
they
dissociate
to
MMA
and
the
associated
companion
cations.
DMA
is
a
weak
acid
with
two
methyl
groups
attached
to
the
central
arsenic
atom,
rather
than
one
as
in
MMA.
These
pesticides
are
all
non­
volatile
solids
that
are
highly
soluble
in
water.
Physicochemical
properties
of
these
compounds
are
listed
in
Tables
3a
and
3b.

Table
3a.
Physicochemical
Properties
for
MSMA
and
DSMA.

DSMA
MSMA
Molecular
Structure
As
O
O
O
C
H
3
Na
+
Na
+
As
OH
O
O
C
H
3
Na
+

Empirical
Formula
CH3AsNa2O3
CH4AsNaO3
Molecular
Weight
183.92
161.94
CAS
No.
144­
21­
8
2163­
80­
6
PC
Code
013802
013803
Melting
Point
(
º
C)
>
300
116­
121
Density
(
g/
mL)
1.04
1.65
Vapor
Pressure
(
mm
Hg)
1
x
10­
7
7.5
x
10­
7
log
Kow
<
1
<
1
Solubility:
Water
(
mg/
L)
3.4
x
105
104
Methanol
2.6
x
105
16
Hexanol
25
0.005
pKa1,2
(
approx.)
4.0,
9.0
4.0,
9.0
13
Table
3b.
Physicochemical
Properties
for
Cacodylic
Acid
and
Sodium
Cacodylate.

Cacodylic
Acid
(
DMA)
Sodium
Cacodylate
(
DMA­
Na)

Molecular
Structure
O
||
CH3 
As 
OH
|
CH3
O
||
CH3 
As 
O­
Na+
|
CH3
Empirical
Formula
C2H7AsO2
C2H6AsNaO2
Molecular
Weight
138.0
160.0
CAS
No.
75­
60­
5
124­
65­
2
PC
Code
012501
012502
Melting
Point
(
º
C)
192­
194
77
 
79.5
Density
(
g/
mL)
1.10
1.10
Vapor
Pressure
(
mm
Hg)
Non­
volatile
No
data
Kow
<
0.028
No
data
Solubility:
Water
(
mg/
L)
~
1
to
3
x
106
No
data
Methanol
3.63
x
105
No
data
Hexanol
1.02
x
10­
1
No
data
pKa
6.2
6.2
Environmental
fate
laboratory
studies
show
that
organic
arsenicals
are
stable
under
all
tested
abiotic
conditions;
they
do
not
degrade
by
hydrolysis
or
by
aquatic
or
soil
photolysis.
Arsenicals
can
be
subject
to
microbial
metabolism
in
soil
under
aerobic
and
anaerobic
conditions.
The
occurrence,
rate,
and
products
of
this
metabolism
are
variable,
dependent
on
environmental
conditions.
Persistence
of
applied
parent
compounds
can
range
from
days
to
years,
depending
on
soil
properties
and
ambient
conditions
such
as
soil
moisture,
temperature,
chemical
concentration,
bacterial
population,
and
amount
of
organic
matter.
Regardless
of
the
form
it
takes,
however,
the
total
amount
of
arsenic
present
does
not
change;
these
arsenicals
and
their
transformation
products,
in
combination
with
arsenic
from
the
natural
background
and
from
other
anthropogenic
sources,
maintain
the
total,
immutable
arsenic
load.
Arsenic
from
pesticides
is
not
lost
but
redistributed
and
transformed
throughout
the
environment
(
plants,
animals,
air,
soil,
sediment,
water)
into
other
arsenic
containing
substances.

Metabolism
rates
do
not
appear
to
depend
linearly
on
arsenical
concentration;
the
kinetics
are
therefore
not
necessarily
first­
order
and
so
"
half­
life"
may
not
be
an
appropriate
14
constant
for
all
concentrations.
Despite
the
uncertainty,
first­
order
half­
lives
have
been
calculated
for
modeling
purposes
and
as
a
convenient
measure
to
compare
laboratory
results.
The
estimated
half­
lives,
used
in
EFED's
current
models,
may
underestimate
the
faster
initial
rate
of
metabolism
but
adequately
portray
the
overall
transformation
and
so
are
assumed
to
be
protective
for
chronic
exposure,
a
major
concern
for
arsenicals.
The
modeled
aerobic
soil
half­
life
for
MMA,
based
on
two
studies
with
similar
results,
is
240
days.
No
anaerobic
soil
half­
life
was
determined
for
MMA.
For
DMA,
the
Agency
derived
aerobic
soil
half­
life
is
173
±
115
days
with
a
standard
upper
90%
confidence
limit
on
the
mean
of
240
days.
The
anaerobic
soil
half­
life
for
DMA
was
calculated
to
be
128
±
38
days
with
a
standard
upper
90%
confidence
limit
on
the
mean
of
168
days.

The
effects
of
environmental
factors
on
the
rate
of
arsenical
metabolism
are
complex
and
poorly
defined,
with
different
studies
leading
to
conflicting
results.
An
increase
in
temperature
leads
to
increased
transformation.
The
observed
influences
of
soil
organic
matter
or
applied
arsenical
concentrations
are
contradictory.
The
effect
of
aerobic
versus
anaerobic
conditions
on
metabolism
rates
is
also
ambiguous.

Potential
metabolites
of
applied
arsenicals
include
volatile
alkylarsines
and
inorganic
arsenic
(
as
arsenate
or
arsenite)
along
with
carbon
dioxide.
Additionally,
DMA
may
be
present
as
a
metabolite
of
MMA
as
well
as
applied
directly.
As
with
the
rate,
the
metabolism
pathway
is
sensitive
to
environmental
conditions
in
indeterminate
ways
with
the
major
metabolites
occurring
in
widely
variable
proportions.
Transformation
to
volatile
alkylarsines,
the
only
metabolism
route
that
would
directly
reduce
soil
arsenic
loading,
has
been
shown
to
be
possible
in
certain
circumstances
but
is
generally
not
expected
to
be
a
major
route
of
dissipation.
A
maximum
of
35%
of
applied
MMA
is
expected
to
be
present
as
DMA
at
any
one
time.
Theoretically,
there
is
some
possibility
for
MMA
to
metabolize
to
DMA,
but
significant
transformation
has
not
been
observed
in
current
acceptable
field
or
laboratory
studies.
Observed
metabolism
of
MMA
and
DMA
to
inorganic
arsenic
has
ranged
from
undetected
after
several
years
to
more
than
80%
transformation
in
several
months.
Generally,
arsenate
[
As(
V)]
is
expected
to
be
the
dominant
species
of
inorganic
arsenic,
but
in
reducing
conditions,
arsenite
[
As(
III)]
may
be
more
stable.

Some
of
the
variability
in
metabolism
processes
is
associated
with
variability
in
sorption,
because
microbial
degradation
is
only
likely
to
occur
while
compounds
remain
dissolved
in
pore
water.
Mobility
of
arsenicals
is
typically
very
low
to
intermediate
and
appears
to
be
independent
of
organic
matter
content.
Instead,
sorption
is
higher
in
soils
with
higher
percentage
of
clay
or
with
more
iron
or
aluminum
content.
Laboratory
studies
have
shown
that
in
some
situations,
significant
sorption
of
arsenic
compounds
may
occur
within
hours
of
application,
while
in
others,
a
large
portion
of
applied
arsenic
remains
in
water­
soluble
forms
for
days
or
months
after
application.
Remobilization
of
sorbed
arsenic
with
changing
environmental
conditions
is
also
possible.
One
study
found
by
direct
comparison
that
all
arsenicals
were
more
strongly
sorbed
than
phosphate
in
the
increasing
order:
phosphate
<
DMA
<
arsenate
~
MMA.
The
lowest
non­
sand
Kd
for
MMA
is
11.4
mL/
g.
For
20
tested
soils,
the
range
of
Kds
spans
two
orders
of
magnitude
15
(
0.5
to
95
mL/
g,
mean
37
mL/
g).
For
DMA,
the
lowest
non­
sand
Kd
from
16
soils
is
8.2
mL/
g
(
range
8.2
to
33
mL/
g,
mean
18
mL/
g).

GROUNDWATER
EXPOSURE
Arsenic
compounds
sorb
strongly
to
soil
and
are
relatively
immobile
in
most
environments,
as
discussed
in
the
Environmental
Fate
Summary.
Significant
leaching
of
organic
arsenicals
applied
according
to
the
labels
is
therefore
unlikely
in
most
conditions.
This
conclusion
is
supported
by
several
field
studies
which
have
not
detected
arsenic
from
pesticide
application
below
the
top
layers
of
soil.
Natural
background
levels
of
arsenic
in
groundwater
are
extremely
variable
and
can
reach
levels
greater
than
100
ppb.
National
monitoring
has
found
no
relationship
between
agricultural
use
of
arsenicals
and
widespread
high
arsenic
concentrations,
but
recent
investigations
in
Florida
have
detected
elevated
arsenic
levels
in
groundwater
below
golf
courses.
In
most
situations,
organic
arsenical
pesticides
should
not
contribute
significantly
to
the
already
existing
burden
of
arsenic
in
groundwater
from
all
sources,
natural
and
anthropogenic.
In
certain
vulnerable
circumstances
in
areas
with
low
background
arsenic,
application
of
organic
arsenicals
may
lead
to
an
increase
in
groundwater
total
arsenic.

Modeling
of
estimated
groundwater
concentrations
was
not
conducted.
SCI­
GROW,
the
Agency's
current
screening
level
groundwater
model,
is
based
on
data
from
groundwater
studies
for
a
number
of
organic
pesticides.
The
environmental
behavior
of
arsenicals
is
quite
different
from
that
of
typical
organic
pesticides.
A
primary
difference
is
that
arsenical
sorption
tends
to
correlate
with
soil
mineral
properties
rather
than
the
amount
of
organic
matter.
For
this
reason,
SCI­
GROW
is
not
an
appropriate
tool
for
estimating
the
groundwater
concentrations
that
may
result
from
application
of
organic
arsenical
pesticides.

Groundwater
Monitoring
Background
Arsenic
(
Non­
targeted
Monitoring)
Data
on
arsenic
in
groundwater
are
abundant,
but
the
majority
of
sampling
is
not
targeted
specifically
to
determine
the
impacts
of
organic
arsenicals
applied
as
herbicides.
Additionally,
most
monitoring
is
conducted
for
total
arsenic,
consistent
with
the
regulatory
limits,
rather
than
for
speciated
forms
of
arsenic.
These
non­
targeted,
unspeciated
results
are
most
useful
as
a
measure
of
background
concentrations.

The
most
extensive
consideration
of
groundwater
arsenic
has
been
done
by
the
USGS.
A
USGS
map
of
total
arsenic
distribution
in
ground
waters
of
the
U.
S.
is
shown
below
in
Figure
1
(
Ryker,
2001).
In
one
study,
USGS
authors
retrieved
water­
quality
data
from
the
National
Water
Information
System
(
which
includes
National
Water
Quality
Assessment
[
NAWQA]
data)
and
other
sources
totaling
about
50,000
samples
from
about
30,000
locations
(
Welch,
2000).
A
subset
of
about
20,000
analyses
from
the
years
1973­
1997
which
met
certain
criteria
were
selected
for
statistical
testing.
Only
a
single
analysis
for
a
particular
well
or
spring
was
used
to
avoid
bias
towards
frequently
sampled
16
Figure
1.
Arsenic
in
Groundwater
in
the
United
States.
Equal­
area
map
representing
arsenic
concentrations
found
in
at
least
25%
of
ground­
water
samples
within
a
moving
50km
radius,
based
on
USGS
NAWQA
data.
(
Ryker,
2001).
17
sources.
Sample
sites
were
not
uniformly
distributed
across
the
country
and
were
not
specifically
targeted
for
areas
where
arsenical
pesticides
were
applied.

Based
on
this
statistical
analysis,
nearly
half
of
the
groundwater
samples
were
found
to
have
total
arsenic
concentrations
<
1
ppb
while
about
10%
exceeded
10
ppb
(
Welch,
2000).
The
authors
conclude
that
natural
arsenic
concentrations
exceeding
10
ppb
are
more
widespread
than
previously
recognized,
although
they
still
find
that
"
ground
water
in
the
U.
S.
typically
contains
low
to
very
low
arsenic
concentrations,
particularly
in
[
the
East]."
Some
areas
of
high
arsenic
concentrations
were
associated
with
point
source
pollution
but
most
appeared
to
be
natural.
High
arsenic
concentrations
were
found
throughout
the
study,
but
in
general,
the
Appalachian
Highlands
and
the
Atlantic
Plain
had
very
low
levels
with
somewhat
greater
concentrations
in
the
Rocky
Mountain
System
and
Interior
Plains
and
the
highest
concentrations
found
most
frequently
in
the
Intermontane
Plateaus
and
the
Pacific
Mountain
System.
The
survey
authors
report
that
even
in
areas
that
tend
to
have
naturally
high
arsenic
concentrations
there
exists
some
ground
water
with
low
to
very
low
arsenic
concentrations.
Steep
lateral
and
vertical
concentration
gradients
exist,
showing
inherent
local
spatial
variability.
This
article
provides
a
thorough
review
of
the
environmental
geochemistry
of
arsenic
and
arsenic
occurrence
in
relation
to
natural
sources.

Speciated
monitoring
data
are
limited.
The
Welch
report
cites
groundwater
sampling
in
northwestern
Nevada
in
an
area
where
organic
arsenical
herbicides
are
not
applied
(
2000).
In
30
samples
tested
for
MMA
and
DMA,
all
results
were
<
0.3
ppb.
An
additional
USGS
study
analyzed
6
groundwater
samples
from
Idaho,
10
from
Illinois,
and
8
from
Nevada
(
total
of
24
sites)
for
arsenite
[
As(
III)],
arsenate
[
As(
V)],
MMA
and
DMA
(
Garbarino
and
Burkhardt,
1998).
Again,
none
of
the
sites
were
associated
with
the
application
of
arsenical
pesticides.
With
a
detection
limit
of
approximately
0.2
ppb,
there
were
no
measurable
concentrations
of
the
methylated
compounds
in
ground
water.
In
contrast,
arsenite
or
arsenate
concentrations
in
these
groundwater
samples
ranged
from
less
than
the
method
detection
limit
to
a
concentration
as
high
as
approximately
900
ppb.
Their
data
show
that
either
arsenite
or
arsenate
or
both
were
detected
in
all
samples,
typically
at
10­
50
ppb.

The
USGS
water
resources
database
was
found
to
include
798
groundwater
samples
with
speciated
measurement
of
organic
arsenicals,
collected
between
2002
and
2004.
(
The
NWISWeb
database
is
available
online
at
http://
waterdata.
usgs.
gov/
nwis.
Information
about
data
quality
procedures
and
about
the
studies
represented
in
the
database
can
be
found
at
this
site.)
More
than
half
of
the
samples
were
from
Kansas
(
56%)
with
nearly
a
third
from
Idaho
(
27%).
The
remaining
samples
were
from
Maryland,
Nevada,
New
Jersey,
Oklahoma,
and
West
Virginia.
No
information
is
available
about
the
land
uses
in
the
areas
sampled;
the
sites
are
not
evenly
distributed
and
are
not
targeted
to
pesticide
use.
For
both
DMA
and
MMA,
the
median
result
was
less
than
the
detection
limit,
which
were
generally
between
0.1
and
1.2
ppb.
All
values
are
reported
as
arsenic.
The
averages
were
0.23
and
0.15
ppb
and
the
90th
percentile
values
were
0.5
and
0.3
ppb
for
DMA
and
MMA,
respectively.
The
maximum
concentrations
for
DMA
and
MMA,
14.9
and
34.8
ppb,
respectively,
were
both
from
the
same
site
in
Idaho.
On
the
same
date,
18
total
arsenic
at
this
site
was
measured
at
858
ppb.
Generally,
no
data
were
available
about
total
arsenic
at
these
sites.

Pesticide
Impacts
(
Targeted
Monitoring)
The
USGS
report
on
background
arsenic
in
groundwater
includes
a
discussion
of
monitoring
done
in
study
areas
where
"
high
arsenic
concentrations
regionally
coincide
with
agricultural
use"
(
Welch,
2000).
Based
on
studies
of
agricultural
use
of
inorganic
arsenical
pesticides
in
North
Dakota,
South
Dakota,
Wisconsin,
and
Minnesota,
the
authors
find
that
"
although
some
contribution
of
arsenic
from
historic
uses
is
possible,
[
these
studies]
all
conclude
that
ground
water
is
largely
unaffected
by
use
of
arsenical
pesticides."
In
the
several
sites
where
groundwater
was
determined
to
be
affected
by
anthropogenic
arsenic
sources,
the
detections
were
associated
with
disposal
or
other
types
of
point
source
pollution.

The
EPA
Pesticides
in
Groundwater
Database
includes
monitoring
data
for
two
sites,
both
of
which
show
high
concentrations
of
total
arsenic
in
a
high
percentage
of
water
wells
(
USEPA,
1992).
In
localized
areas
of
Texas,
concentrations
of
10­
680
ppb
were
found
in
91
of
247
wells
with
limits
of
detection
(
LODs)
of
10­
25
ppb.
The
Agency
independently
concluded
that
these
detections
were
associated
with
use
of
cacodylic
acid,
but
not
from
non­
point
source,
labeled
pesticidal
application
(
Aurelius,
1988).
Rather,
the
high
concentrations
were
most
likely
caused
by
cacodylic
acid­
treated
cotton
gin
waste
which
was
spread
in
the
vicinity
of
poorly
cased
wells,
and
by
somewhat
higher
natural
concentrations
of
arsenic.
In
the
State
of
Washington,
where
total
arsenic
was
found
at
1.6­
13.3
ppb
in
15
of
20
wells
(
LOD
0.2
ppb),
no
connection
was
found
with
organic
arsenical
pesticides
(
Erickson,
1990).
In
this
area,
natural
conditions
including
historical
volcanic
activity;
strongly
alkaline,
sandy
soils;
hydrology
favorable
to
the
migration
of
soluble
constituents;
and
thermal
waters
may
have
contributed
to
the
elevated
concentrations,
as
well
as
possible
inputs
from
former
heavy
use
of
calcium
or
lead
arsenates
in
orchards
(
sometimes
hundreds
of
lbs/
A
annually)
or
wastes
from
mining
operations.

All
of
the
targeted
monitoring
studies
reviewed
below
were
conducted
in
Florida,
an
area
of
concern
because
of
its
very
sandy
soils
and
shallow
water
tables.
Although
arsenicals
are
strongly
sorbing,
lab
studies
have
shown
that
leaching
in
typical
Florida
soils
may
be
important.
Golf
courses,
major
users
of
MMA,
may
be
particularly
susceptible
to
leaching
because
they
typically
have
well­
drained
soils
and
are
heavily
irrigated.

Given
the
variability
of
natural
arsenic,
it
is
useful
to
have
information
about
regional
background
levels
to
compare
with
targeted
results.
The
USGS
water
resources
database
included
322
arsenic
groundwater
samples
from
Florida
collected
at
235
sites
between
1990
and
2004.
This
sampling
found
an
average
arsenic
concentration
of
1.1
ppb
with
a
90th
percentile
value
of
2.5
ppb.
(
All
arsenic
concentrations
in
this
discussion
of
monitoring
data
are
unspeciated,
reported
as
total
arsenic,
unless
otherwise
specified.)
This
sampling
is
not
uniformly
distributed
and
not
directed
to
specifically
capture
only
control,
non­
use
areas.
When
available,
background
data
specific
to
targeted
monitoring
locations
are
included
in
this
discussion.
19
One
Florida
monitoring
study,
while
not
targeted
to
specific
uses,
found
higher
arsenic
in
groundwater
in
an
urban
area
than
a
control
region
in
the
same
aquifer
(
German,
1996).
In
the
control
area
there
were
no
detections
of
arsenic
in
10
samples
while
around
the
Orlando
urban
area,
arsenic
was
detected
in
6
of
23
samples
with
a
maximum
of
13
ppb.
This
demonstrates
that
anthropogenic
inputs
of
arsenic
may
reach
groundwater
but
provides
no
information
about
the
specific
source.
In
urban
areas,
possible
inputs
include
but
are
not
limited
to
application
of
organic
arsenicals
to
golf
courses
and
residential
lawns.

Several
other
Florida
monitoring
studies
focus
on
groundwater
that
may
be
impacted
by
golf
course
uses.
The
2
studies
reviewed
here
look
at
groundwater
at
14
golf
courses.
The
first
study,
conducted
by
the
USGS
in
conjunction
with
the
Florida
Department
of
Environmental
Protection
(
FDEP),
was
designed
to
determine
if
pesticides
used
in
turfgrass
management
were
migrating
to
shallow
groundwater
(
Swancar,
1996).
Most
of
the
9
golf
courses
tested
were
in
central
Florida
with
one
to
the
south
in
Broward
County
and
one
in
the
panhandle,
in
Pensacola.
Samples
were
taken
quarterly
for
a
year
at
39
wells,
most
at
tees
and
greens
with
3
wells
in
pesticide
mixing
and
loading
areas.
Arsenic
was
detected
in
6
wells
on
4
golf
courses.
On
greens,
4
wells
at
3
golf
courses
had
detections,
with
concentrations
ranging
from
11
 
120
ppb.
The
average
arsenic
concentrations
from
the
4
samples
taken
at
each
well
were
21,
28,
30,
and
64
ppb.
Arsenic
was
detected
in
wells
from
1
tee
site
and
1
mixing/
loading
area,
with
average
concentrations
of
3
and
32
ppb,
respectively
(
Swancar,
1996).

This
is
not
a
controlled
study
and
detailed
pesticide
application
histories
are
not
available.
The
study
shows
that
in
general,
pesticides
applied
to
Florida
golf
courses
may
reach
groundwater,
finding
that
of
the
more
than
40
pesticides
and
metabolites
tested
for,
13
were
detected
in
golf
course
groundwater.
Specific
to
arsenic,
recent
pesticide
application
data
coupled
to
concentration
trends,
along
with
known
historical
uses,
point
to
MSMA
application
as
a
likely
source
of
groundwater
arsenic
at
these
golf
courses.
At
Ventura
Golf
Course,
where
arsenic
was
detected
at
1
green
well
at
an
average
of
28
ppb,
MSMA
had
been
applied
10
days
prior
to
the
2nd
sampling
event,
when
arsenic
concentrations
were
found
to
have
increased
from
11
ppb
to
48
ppb.
Concentrations
steadily
decreased
at
the
following
2
sampling
events,
reaching
22
ppb
by
the
last
sample,
taken
approximately
6
months
later.
This
concentration
trend
provides
evidence
that
MSMA
application
resulted
in
elevated
groundwater
arsenic
levels.
Historically,
at
least
12
years
prior
to
monitoring,
part
of
this
site
was
a
dairy
farm.
MSMA
was
applied
monthly
at
the
Highland
Golf
Course,
where
arsenic
was
detected
at
1
green
well
at
levels
as
high
as
120
ppb
with
a
mean
of
64
ppb.
Prior
to
development
as
a
golf
course,
this
was
open
land
or
pasture
with
citrus
groves
nearby.
Bonaventura
Golf
Course,
in
south
Florida,
had
the
most
arsenic
detections,
in
2
green
wells
and
1
mixing/
loading
area.
The
first
application
of
MSMA
during
the
sampling
period
was
between
the
2nd
and
3rd
sampling
events
in
areas
not
specific
to
the
greens.
There
is
no
particular
trend
in
arsenic
levels
at
these
wells.
Before
the
golf
course
was
established,
this
land
was
part
of
Everglades
National
Park
(
Swancar,
1996).
20
The
results
of
this
study,
along
with
documented
violations
of
soil
cleanup
target
levels
for
arsenic,
led
the
Miami­
Dade
County
Department
of
Environmental
Resources
Management
(
DERM)
to
conduct
monitoring
at
5
county
golf
courses
(
2002).
At
each
golf
course,
three
well
clusters
were
installed
including
one
shallow
(
10­
15
ft)
and
one
deep
(
21­
28
ft)
well.
All
golf
courses
had
one
well
cluster
in
a
pesticide
mixing
and
loading
area
with
the
other
wells
evenly
divided
between
tees,
greens,
and
fairways,
and
wells
were
sampled
quarterly
for
one
year.
In
shallow
wells,
76%
of
all
samples
exceeded
10
ppb
as
arsenic
with
32%
exceeding
50
ppb
as
arsenic.
Groundwater
arsenic
concentrations
at
greens
were
not
found
to
be
significantly
higher
than
those
at
tees
and
fairways,
although
there
were
higher
concentrations
at
mixing
and
loading
areas.
In
greens,
the
median
concentration
was
13.6
ppb
with
a
maximum
of
55
ppb.
On
fairways,
the
median
was
17.8
ppb
and
the
maximum
was
56
ppb.
In
tee
areas,
the
median
was
81.8
ppb
and
a
maximum
of
123
ppb.
In
mixing/
loading
areas,
concentrations
reached
as
high
as
815
ppb
with
a
median
of
31.8
ppb
(
DERM,
2002).
Concentrations
were
much
lower
in
deeper
wells,
with
a
maximum
of
44
ppb.
Arsenic
was
only
detected
in
deeper
groundwater
at
3
of
the
5
golf
courses,
with
18%
of
the
samples
having
concentrations
greater
than
10
ppb.
The
highest
concentrations
were
found
in
mixing/
loading
areas.
Only
tees,
with
a
maximum
of
11
ppb
and
a
median
of
3
ppb,
exceeded
the
detection
limit
in
more
than
50%
of
the
samples
(
DERM,
2002).

To
establish
background
levels,
three
pre­
existing
shallow
monitoring
wells
in
nearby
residential
areas
were
monitored
concurrently.
Based
on
10
total
samples,
the
maximum
concentration
was
5
ppb
and
the
median
was
less
than
the
detection
limit.
Additionally,
historical
data
was
gathered
from
wells
at
similar
depths
in
the
Ambient
Water
Quality
Monitoring
network.
Based
on
22
total
samples,
the
maximum
was
13.9
ppb
and
the
median
was
2.0
ppb
(
DERM,
2002).
These
data
indicate
that
the
golf
course
arsenic
levels
are
higher
than
background
levels.

Other
potential
arsenic
sources
in
these
areas
are
discussed,
including
historical
land
uses
and
arsenic
from
fertilizers.
All
golf
courses
in
the
study
were
established
prior
to
1975
with
some
more
than
50
years
old.
One
course
was
built
on
undeveloped
land,
one
on
farmland,
and
a
portion
of
one
was
used
as
a
municipal
dump
25
years
prior
to
sampling.
No
historical
land
use
information
is
provided
for
the
other
two
courses.
The
highest
shallow
groundwater
concentrations
in
mixing/
loading
areas
and
fairways
are
from
the
previously
undeveloped
site
while
the
landfill
site
had
more
detections
of
arsenic
in
deep
groundwater
than
most
other
golf
courses.
These
past
uses
are
potential
arsenic
sources,
but
at
those
courses,
the
available
data
are
not
sufficient
to
rule
out
modern
or
historical
contributions
to
arsenic
contamination.
Fertilizer
samples
were
collected
from
the
participating
golf
courses
and
analyzed
for
arsenic.
Arsenic
concentrations
in
fertilizer
ranged
from
below
detection
limit
to
15
mg/
kg,
with
a
mean
of
3.27
mg/
kg
(
DERM,
2002).

A
third
report,
by
the
Florida
Department
of
Environmental
Protection,
describes
investigations
done
at
golf
course
sites
where
levels
of
arsenic
have
been
found
to
exceed
local
regulatory
limits
(
FDEP,
2002).
In
some
cases,
FDEP
was
able
to
rule
out
pesticide
applications
as
a
primary
source
of
arsenic
contamination,
but
in
at
least
3
sites,
pesticide
21
application
was
linked
to
contamination.
This
report
focuses
on
soil
arsenic
levels,
but
groundwater
arsenic
is
measured
as
well.
At
two
golf
courses,
although
groundwater
levels
reach
472
ppb
at
one
and
1300
ppb
at
the
other,
concentrations
are
only
reported
for
maintenance
areas,
so
it
cannot
be
determined
whether
there
are
impacts
from
nonpoint
sources.
At
the
Palm
Beach
Lakes
Golf
Course,
two
sets
of
shallow
groundwater
sampling
were
conducted.
The
first,
focusing
on
former
green
areas,
found
arsenic
levels
exceeding
10
ppb
in
all
20
samples.
The
second
set,
in
a
different
parcel
of
the
course,
consisted
only
of
playing
areas
and
found
exceedances
of
the
10
ppb
MCL
in
22
of
27
samples.

These
are
not
controlled
studies.
Nevertheless,
considered
as
a
group,
they
show
a
trend
of
groundwater
arsenic
at
Florida
golf
courses
well
above
local
background
levels
and
in
many
cases
exceeding
the
federal
MCL.
Although
evidence
of
the
source
of
arsenic
is
generally
not
conclusive,
pesticide
application
is
a
probable
contributor
to
these
levels,
and
in
some
cases,
appears
to
be
the
likely
source.
The
registrants
and
the
State
of
Florida
are
currently
negotiating
a
plan
for
a
prospective
groundwater
study
designed
to
investigate
potential
leaching
of
organic
arsenicals
in
this
vulnerable
setting.
This
study
is
expected
to
lead
to
more
conclusive
evidence
of
whether
or
not
applied
arsenicals
may
reach
groundwater.

SURFACE
WATER
EXPOSURE
Arsenical
pesticides
and
their
metabolites
may
be
transported
to
surface
waters
and
sediments
through
runoff
water,
eroding
soils,
or
drift
during
application.
Both
monitoring
data
and
modeling
results,
discussed
below,
suggest
that
these
routes
of
exposure
are
likely
to
lead
to
local
elevations
above
background
arsenic
levels
in
surface
water
bodies.
This
is
true
for
both
the
turf
and
the
cotton
uses,
although
the
higher
application
rates
for
turf
and
potentially
more
widespread
application
lead
to
higher
estimated
concentrations.

Surface
Water
Monitoring
Background
Arsenic
(
Non­
targeted
Monitoring)
As
with
groundwater,
unspeciated
surface
water
arsenic
data
not
targeted
to
pesticide
use
areas
are
abundant.
Unlike
groundwater,
no
major
statistical
effort
has
been
undertaken
to
interpret
these
surface
water
data.
A
less
complete
consideration
of
these
data
can
still
provide
useful
information
about
typical
arsenic
concentrations.
Unless
otherwise
specified,
all
USGS
data
discussed
in
this
section
is
from
the
publicly
available
NWISWeb
database.
The
database,
as
well
as
information
about
data
quality
procedures
and
about
the
studies
represented,
can
be
accessed
at
http://
waterdata.
usgs.
gov/
nwis.
The
USGS
dataset
includes
nearly
40,000
lake
and
stream
samples
collected
nationally
between
1990
and
2004
at
around
4500
locations.
Sample
sites
were
not
uniformly
distributed
across
the
country
and
these
data
have
not
been
corrected
for
bias
resulting
from
frequently
sampled
sources.
The
data
also
include
sampling
from
point
sources
such
as
mine
waste
but
specific
land
use
information
has
not
been
considered.
Half
of
the
samples
had
total
arsenic
concentrations
 
1.1
ppb
and
10%
of
the
samples
exceeded
22
the
MCL
of
10
ppb.
With
the
exception
of
a
mine
in
Pennsylvania,
the
very
high
arsenic
concentrations,
greater
than
100
ppb,
are
all
in
the
western
U.
S.
with
New
Mexico
and
North
Dakota
as
the
furthest
east
samples.
For
concentrations
between
50
and
100
ppb,
there
are
only
2
sites
in
the
eastern
region
not
obviously
associated
with
a
point
source.
Perhaps
coincidentally,
both
are
in
heavy
cotton
producing
areas,
one
in
Texas
and
one
in
Mississippi.
The
USGS
groundwater
report
included
a
brief
consideration
of
surface
water
arsenic,
finding
that
the
most
common
natural
cause
of
elevated
arsenic
in
surface
water
is
discharge
of
geothermal
water
(
Welch,
2002).

The
BASINS
and
STORET
databases
maintained
by
the
US
EPA
also
provide
a
large
body
of
data
(
many
tens
of
thousands
of
entries)
on
total
arsenic
concentrations
in
surface
waters
of
the
U.
S.
As
with
the
USGS
surface
water
data,
the
wide
ranging
concentrations
in
space
and
time
and
the
multiplicity
of
possible
major
sources
of
arsenic
make
any
attempt
to
associate
these
with
pesticide
use
impractical.
Nevertheless,
even
casual
inspection
of
the
data
from
the
databases
shows
that
it
is
not
unusual
for
total
arsenic
concentrations
in
raw
surface
water
in
many
different
sites
to
be
several
parts
per
billion.
Spatial
variability
is
the
rule.
The
data
for
Georgia
and
Texas
are
discussed
here
as
illustrative
of
this
variability
and
are
not
meant
to
imply
a
special
situation.
In
Georgia,
as
presented
in
BASINS,
upper
85th
percentile
concentrations
of
total
arsenic
at
different
sites
ranged
from
less
than
1
ppb
to
338
ppb.
More
typical
high
values
fall
in
the
range
of
10
to
50
ppb.
The
most
probable
concentration
appears
to
fall
in
the
range
of
<
1
to
2
or
3
ppb.
The
STORET
database
for
Georgia
and
Texas
show
similar
results,
with
Texas
seeming
to
average
several
parts
per
billion
more.
Some
of
the
highest
values
reported
in
STORET
for
Georgia
and
Texas
(
79,000
entries)
approach
1000
ppb
and
can
often
be
associated
with
anthropogenic
point
source
pollution.
As
previously
mentioned,
natural
sources
(
especially
in
places
in
the
western
U.
S.)
also
produce
such
high
concentrations.

Speciated
data
on
arsenic
in
surface
waters
are
sparse.
A
search
of
the
USGS
database
found
only
26
samples,
not
enough
to
overcome
the
limitations
of
the
dataset
with
regard
to
site
distribution
and
unknown
land
uses.
One
open
literature
study
tested
10
natural
waters
in
the
vicinity
of
Tampa,
Florida
(
Braman
and
Foreback,
1973).
There
were
six
surface
fresh
water
bodies
(
two
rivers,
two
ponds,
two
lakes)
and
three
saline
waters
(
two
bays,
one
tidal
flat)
included
in
the
study.
One
groundwater
site
was
also
included,
a
well
in
a
remote
camping
area.
Analysis
was
for
the
four
arsenic
species:
DMA,
MMA,
arsenite,
and
arsenate.
All
concentrations
reported
below
are
as
arsenic
equivalents.
Concentrations
of
DMA
in
the
natural
waters
ranged
up
to
1.0
ppb.
At
one
site,
the
Hillsborough
River,
concentrations
were
below
a
remarkably
low
detection
limit
of
0.02
ppb,
while
the
median
value
for
DMA
at
the
other
nine
sites
was
approximately
0.3
ppb
As.
Concentrations
of
arsenate,
detected
at
all
ten
sites,
were
similar
to
cacodylic
acid.
Arsenite
was
detected
at
only
six
of
the
ten
sites,
but
had
the
highest
concentration
(
2.7
ppb)
of
all
species.
MMA,
detected
in
eight
of
the
ten
sites,
was
generally
present
at
lower
concentrations,
the
highest
being
0.22
ppb
As.
However,
in
a
broader
sense,
considering
the
few
samples,
surface
water
concentrations
of
all
four
were
similar.
Total
arsenic
concentrations
ranged
from
approximately
0.3
to
3.6
ppb.
The
extent
to
which
these
concentrations
represent
the
natural
background
in
the
Tampa
area
or
are
influenced
23
by
introduction
of
artificial
sources
is
unknown.
However,
the
study
authors
considered
the
sampled
sites
as
"
natural"
waters.

A
California
study
measured
speciated
arsenic
in
14
water
bodies
(
10
lakes,
estuaries,
or
reservoirs,
and
4
rivers
or
creeks)
in
order
to
compare
concentrations
of
methylated
arsenical
forms
to
inorganic
forms
(
Anderson,
1991).
The
authors
indicate
that
the
sampling
represents
drainage
basins
both
affected
and
unaffected
by
agricultural
runoff
but
do
not
distinguish
between
the
two.
All
sites
had
measurable
arsenic,
although
in
8
of
the
14
sites,
total
arsenic
was
less
than
2
ppb
and
in
1
site,
Mono
Lake,
inorganic
arsenic
was
extremely
high
(
17
ppm),
likely
due
to
its
unique
hydrogeology.
At
Mono
Lake,
analysis
for
organic
arsenic
was
impossible
and
so
this
site
will
not
be
considered
further
in
this
discussion.
The
highest
measured
concentrations
of
MMA
and
DMA
were
equivalent
to
0.6
ppb
and
2.5
ppb
as
arsenic,
respectively.
These
were
found
in
the
Salton
Sea,
where
the
total
arsenic
concentration
was
12.8
ppb.
The
Salton
Sea
receives
a
substantial
amount
of
agricultural
runoff,
including
from
cotton­
growing
areas,
but
also
has
geothermal
activity,
a
possible
source
of
natural
arsenic.
The
stream
sites
had
total
arsenic
concentrations
ranging
from
0.7
to
7.4
ppb
but
had
no
detectable
concentrations
(<
0.1
nM)
of
MMA
or
DMA.
Of
the
9
other
sites,
7
had
measurable
concentrations
of
MMA
and
all
9
had
measurable
concentrations
of
DMA.
In
these
sites,
the
average
concentration
of
MMA,
as
arsenic,
was
0.15
ppb
with
a
standard
deviation
of
0.2
ppb.
The
average
concentration
of
DMA
was
higher,
at
0.62
ppb
with
a
standard
deviation
of
0.8
ppb.
Except
for
one
site,
which
had
57%
of
total
arsenic
present
in
methylated
form,
inorganic
arsenic
was
found
in
much
higher
concentrations
than
organic,
which
ranged
from
1%
to
39%
of
total
arsenic.

Pesticide
Impacts
(
Targeted
Monitoring)
There
are
several
monitoring
studies
available
targeted
to
measure
the
impact
of
organic
arsenical
herbicides
on
surface
water.
One
study
collected
surface
water
samples
at
one
or
two
week
intervals
from
early
March
through
the
middle
of
September
of
1997
from
two
drainage
basins
in
high
cotton
producing
areas
of
Mississippi
(
Bednar,
2002).
Sampling
dates
and
times
varied
between
sites
and
were
not
correlated.
A
total
of
24
samples
were
analyzed
from
each
the
Yazoo
and
the
Bogue
Philia
drainages.
Analyses
were
for
MMA,
DMA,
arsenite,
and
arsenate.
Maximum
concentrations,
as
arsenic,
of
MMA
at
Yazoo
and
Bogue
Philia
were
approximately
2
ppb
and
5
ppb,
respectively,
and
were
relatively
short­
lived.
The
highest
concentrations
were
seen
in
June
and
July,
at
the
end
of
the
period
when
MSMA
is
most
likely
to
be
applied.
Concentrations
of
DMA
were
at
or
below
the
detection
limit
of
0.2
ug/
L,
except
for
one
sample
which
registered
approximately
0.6
ug/
L.
Arsenate
and
arsenite
reached
maximum
concentrations
similar
to
those
from
MMA;
both
approximately
2
ppb
at
Yazoo
and
approximately
3.5
ppb
(
arsenite)
and
5.5
ppb
(
arsenate)
at
Bogue
Philia.
The
higher
concentrations
of
inorganic
arsenic
were
measured
more
frequently
than
those
for
MMA.
In
all
samples,
one
species
tended
to
dominate;
the
comparable
concentrations
of
arsenite
and
arsenate
is
also
noteworthy.
At
the
Bogue
Philia
site,
inorganic
arsenic
concentrations
increased
after
the
MMA
maximum
was
measured,
possibly
indicating
transformation
of
the
organic
arsenical
or
a
secondary
source
of
arsenic
(
Bednar,
2002;
in
previous
REDs,
the
same
data
were
cited
from
Garbarino,
1998).
24
Detailed
histories
of
MSMA
application
in
this
area
are
not
available
and
the
location
of
water
bodies
relative
to
application
sites
was
not
published.
Without
baseline
data
for
arsenic
concentrations
in
areas
without
arsenical
application,
which
are
not
provided
in
this
study,
it
cannot
be
concluded
whether
the
fluctuations
seen
here
are
part
of
the
natural
arsenic
cycle
or
influenced
by
pesticide
application.
For
comparison,
the
Agency
retrieved
surface
water
arsenic
concentrations
from
the
USGS
database,
which
included
65
samples
in
Mississippi.
The
samples
are
not
uniformly
distributed
and
information
about
land
use
patterns
is
not
available.
The
average
total
arsenic
concentration
found
was
3.4
ppb
with
a
90th
percentile
value
of
4
ppb.
All
samples
with
arsenic
concentrations
higher
than
4
ppb
were
from
a
single
water
body
where
levels
reached
as
high
as
72
ppb.
Presumably
this
water
body
is
impacted
by
a
pollution
source
and
therefore
not
representative
of
background
levels.
If
these
data
are
not
included,
the
average
of
the
60
remaining
samples
is
1.1
ppb
with
a
90th
percentile
of
2
ppb.
While
still
not
conclusive,
this
suggests
that
at
least
the
higher
arsenic
concentrations
found
in
the
Bednar
report,
above
5
ppb,
are
higher
than
would
be
expected
from
background
arsenic
alone.

Limited
monitoring
has
been
done
in
surface
water
bodies
on
golf
courses
as
well.
Golf
course
ponds
are
relatively
small
water
bodies
and
are
typically
completely
surrounded
by
potential
application
areas,
and
therefore
runoff
sources.
Consequently,
these
ponds
are
likely
to
represent
the
upper
end
of
possible
surface
water
concentrations.
Limited
monitoring,
however,
cannot
be
expected
to
capture
peak
concentrations.
One
USGS
study,
also
discussed
in
the
groundwater
monitoring
section,
sampled
ponds
at
6
golf
courses,
all
in
central
Florida,
for
multiple
pesticide
residues
(
Swancar,
1996).
Ponds
were
sampled
4
or
5
times
over
the
course
of
one
year.
Arsenic
was
below
the
detection
limit
(
1
ppb)
at
2
of
the
golf
courses
and
at
a
third,
was
detected
in
only
1
out
of
5
samples,
measured
at
the
MCL
of
10
ppb.
At
the
other
3
golf
course
ponds,
concentrations
ranged
from
5
to
24
ppb.
Of
the
13
samples
from
these
3
ponds,
the
mean
total
arsenic
concentration
was
11.6
ppb.
It
is
interesting
to
note
that
detectable
levels
of
arsenic
were
not
found
in
any
of
the
groundwater
samples
collected
at
these
3
locations.

Surface
Water
Modeling
Modeling
of
the
application
of
arsenical
pesticides
was
performed
to
predict
acute
and
chronic
concentrations
that
may
reach
drinking
water.
Although
there
are
extensive
monitoring
data
available
for
arsenic,
some
of
it
even
targeted
to
heavy
use
areas,
modeling
remains
a
valuable
tool
to
supplement
the
limitations
of
monitoring.
Most
monitoring
measures
total
arsenic
and
does
not
provide
information
on
speciation.
Monitoring
data
do
not
generally
allow
for
determination
of
the
source
of
contamination.
This
is
particularly
important
for
arsenic,
which
has
multiple
potential
sources,
both
from
natural
background
and
from
various
anthropogenic
activities.
Even
for
those
monitoring
studies
targeted
to
heavy
use
areas,
specific
information
about
application
rates
and
land
use
history
are
not
always
available.
Additionally,
even
targeted
studies
cannot
be
expected
to
capture
short­
lived
peak
concentrations.
In
light
of
these
factors,
and
considering
the
variability
of
arsenic's
environmental
behavior
with
variable
environmental
conditions,
modeling
is
useful
for
providing
high­
end
estimates
of
25
speciated
arsenic
concentrations
resulting
from
pesticide
applications
under
the
most
vulnerable
conditions.

To
determine
estimated
drinking
water
concentrations
(
EDWCs)
in
surface
water,
the
Pesticide
Root
Zone
Model
(
PRZM
3.12;
5/
7/
98),
which
simulates
transport
off
the
agricultural
field,
is
run
in
tandem
with
the
Exposure
Analysis
Modeling
System,
(
EXAMS
2.98.04;
6/
13/
97),
which
simulates
the
fate
of
chemicals
in
the
water
body.
These
are
operated
using
the
pe4v01
shell
program
(
8/
13/
03).
Additional
information
about
these
models
can
be
found
at
the
EPA's
water
modeling
website,
http://
www.
epa.
gov/
oppefed1/
models/
water/.
The
simulated
watershed
is
based
on
an
Index
Reservoir
(
IR)
scenario,
and
a
percent
cropped
area
(
PCA)
adjustment
factor
is
used
to
adjust
for
the
area
within
the
watershed
that
is
planted
to
the
modeled
crop
(
OPP,
2000).
Models
are
run
for
30
years
and
the
reported
EDWCs
represent
the
values
that
are
expected
once
every
ten
years,
based
on
the
30
years
of
daily
values
generated
during
the
simulation.

The
crop
scenarios
used
in
PRZM/
EXAMS
represent
sites
that
are
highly
vulnerable
to
runoff.
In
this
assessment,
the
Mississippi
cotton
and
Florida
turf
scenarios
are
modeled
to
represent
the
major
uses
of
arsenicals.
Other
cotton
and
turf
scenarios
were
run
to
confirm
that
these
are
the
most
vulnerable
of
available
scenarios.
The
Mississippi
cotton
scenario
is
located
in
Yazoo
County,
the
number
one
county
in
a
state
that
ranks
fourth
in
cotton
production
(
EFED,
2003).
The
Florida
turf
scenario
is
located
in
Osceola
County.
Golf
courses
and
other
areas
of
turf
cultivation
in
Florida
use
a
significant
amount
of
arsenical
pesticides
each
year
(
Swancar,
1995;
Ma,
2002).
Minor
crop
scenarios,
including
those
for
orchards
and
citrus,
were
also
modeled
to
provide
characterization.

All
species
of
concern
in
this
assessment
(
MMA,
DMA,
and
iAs)
have
distinct
toxicities;
exposure
to
each
needs
to
be
considered
individually.
Estimated
concentrations
of
each
of
these
compounds
are
therefore
provided
for
each
use.
Compounds
resulting
from
metabolism
are
considered
as
well
as
directly
applied
pesticides.
Applied
MMA
may
metabolize
to
DMA.
On
cotton,
MMA
and
DMA
can
be
applied
to
the
same
field.
Reported
cotton
MMA
EDWCs,
therefore,
result
from
direct
application
while
cotton
DMA
EDWCs
result
both
from
direct
application
and
from
transformation
of
MMA.
On
turf,
all
EDWCs
are
the
result
of
MMA
application.
Both
MMA
and
DMA
may
also
metabolize
to
inorganic
arsenic.
It
is
impossible
to
determine
the
exact
concentration
of
each
species
that
will
be
present
at
any
one
time
and
each
species
will
reach
its
highest
level
at
different
times;
the
reported
EDWCs
for
parent
and
metabolite
compounds
represent
maximum
potential
concentrations
for
each
species
and
are
not
additive
to
a
total
possible
concentration.
When
the
concentration
of
one
species
is
at
its
highest,
the
other
species'
concentration
will
be
lower.
An
EDWC
for
"
total
arsenic"
has
been
reported
to
indicate
the
maximum
amount
of
arsenic
that
may
be
in
surface
water
as
a
sum
of
all
species
present.
It
is
this
EDWC
that
would
be
compared
to
regulatory
levels,
which
are
set
as
total
arsenic.
Since
it
is
possible
that
all
arsenic
would
be
present
in
the
form
of
inorganic
arsenic,
this
EDWC
also
represents
the
maximum
potential
concentration
of
inorganic
arsenic.
EDWCs
resulting
from
the
maximum
labeled
application
rates
for
cotton
and
turf
are
presented
in
Table
4.
The
input
parameters
used
26
Table
4.
EDWCs
(
ppb)
from
maximum
labeled
rates
for
major
uses
of
arsenicals.

Acute
Chronic
Cancer
TURF1
MMA
250.5
127.5
74.6
DMA
102.3
46.5
28.1
Total
As3
135.2
68.8
40.3
COTTON2
MMA
37.4
11.0
5.3
DMA
23.6
7.4
4.3
Total
As3
20.9
7.2
3.9
1
MSMA
applied
4
times
at
3.35
lbs
ae/
A.
2
DSMA
applied
2
times
at
1.74
lbs
ae/
A
&
DMA
applied
1
time
at
1.2
lb/
A.
3
Total
arsenic
is
the
sum,
reported
as
ppb
As,
of
arsenic
that
may
be
present
from
all
applied
and
metabolite
species.
It
also
represents
the
maximum
EDWC
of
inorganic
arsenic.

are
presented
in
Tables
5
and
6
and
more
detailed
discussion
of
parameter
selection,
methods
of
determining
metabolites,
and
uncertainty
is
included
below.
The
PRZM/
EXAMS
input
files
are
provided
in
Appendix
A
and
the
output
files
in
Appendix
B.

Input
Parameters:
Metabolism
Rates
The
input
parameters
used
in
PRZM/
EXAMS
modeling
in
this
assessment
(
Tables
5
and
6)
are
based
primarily
on
the
values
determined
for
the
most
recent
REDs
(
DP
Barcodes
D210451,
D212449,
D255226
and
DP
Barcode
D277223).
The
validity
of
each
parameter
has
been
considered
individually
and,
while
most
have
been
confirmed,
several
have
been
adjusted
to
take
into
account
new
data
or
different
interpretations
of
older
data.
In
part,
this
process
has
been
a
response
to
concerns
expressed
by
the
registrant
regarding
the
parameterization
of
the
original
modeling.
In
particular,
the
registrant
argues
that
thesoil
metabolism
half­
life
inputs
used
do
not
account
for
the
biphasic
nature
of
arsenical
metabolism
(
MAATF,
2005).
It
is
true
that
arsenical
metabolism
appears
to
be
biphasic,
occurring
more
rapidly
prior
to
sorption.
Current
EFED
modeling
requires
first
order
linear
rate
constants.
Even
if
biphasic
rates
could
be
incorporated,
because
of
the
variability
of
sorption
processes
there
are
insufficient
data
to
allow
for
determination
of
two
separate
rates.
Because
chronic
exposure
is
a
major
concern
for
arsenicals,
it
is
assumed
to
be
protective
to
use
a
long
term
half­
life
that
is
less
accurate
in
representing
the
faster
initial
rate
of
metabolism
but
that
better
portrays
the
overall
transformation.

For
MSMA
and
DSMA,
the
modeled
half­
lives
are
unchanged
from
those
used
in
the
2001
RED
(
DP
Barcode
D277223).
The
aerobic
soil
and
aquatic
metabolism
half­
lives
are
based
on
one
registrant
study
(
MRID
44767601;
Acceptable)
and
on
a
non­
GLP
open
literature
study
reviewed
in
the
previous
RED
(
Gao
and
Burau,
1997).
The
registrant
submitted
a
review
of
additional
literature
which
includes
several
studies
that
quantify
shorter
half­
lives
than
those
used
in
the
initial
RED
(
MAATF,
2005).
Even
if
those
values
are
included
in
the
calculation,
the
90%
confidence
half­
life
only
changes
from
240
days
to
220
days,
which
has
a
minimal
effect
on
the
outcome
and
does
not
justify
the
27
Table
5.
PRZM/
EXAMS
Input
Parameters
for
DSMA/
MSMA
on
Cotton
and
Turf
Model
Parameter
Value
Comments
Source
Single
Application
Rate
(#
of
applications)
Cotton:
1.95
kg
ae/
ha
(
2
apps)
Turf:
3.75
kg
ae/
ha
(
4
apps)
Master
Label
Application
Date
(
Intervals)
Cotton:
5/
7
(
7
days)

Turf:
3/
14
(
10
days)
Cotton:
USDA­
NASS
Planting
&
Harvest
Dates
(
12/
97)
1
Turf
2
Application
Method
Cotton
&
Turf:
Foliar;
ground
applied3
Leads
to
default
values
of
6.4%
Spray
drift
99%
App.
efficiency
Incorporation
Depth
Cotton
&
Turf:
0
cm
Aerobic
Soil
Metabolism
Half­
Life
240
days
90%
upper
confidence
bound,
based
on
2
values.
Gao
&
Burau,
1997
MRID
44767601
Anaerobic
Soil
Metabolism
Half­
Life
­­­
No
reported
data,
not
used
as
input
parameter
Aerobic
Aquatic
Metabolism
Half­
life
480
days
No
reported
data,
use
½
of
aerobic
soil
rate
Input
Parameter
Guidance4
Anaerobic
Aquatic
Metabolism
Half­
life
2300
days
3
times
single
reported
value
MRID
44767602
Aqueous
Photolysis
Half­
life
Stable
MRID
41903902
Hydrolysis
Half­
life
Stable
Stable
at
all
pH
MRID
42363001
Kd
11.4
ml/
g
5
Lowest
non­
sand
Kd
from
19
soils.
Wauchope,
1975
MRID
41651906
Molecular
Weight
139
g/
mol
5
as
MMA
Water
Solubility
1
x
106
mg/
L
2001
RED
(
D277223)

Vapor
Pressure
1
x
10­
7
torr
2001
RED
(
D277223)

Percent
Cropped
Area
(
PCA)
Cotton:
20%
Turf:
100%
Drinking
Water
Screening
Level
Assessment
Guidance,
Part
B
6
1
http://
usda.
mannlib.
cornell.
edu/
reports/
nassr/
field/
planting/
uph97.
html
2
A
spring
application
date
was
chosen
to
represent
the
period
when
crabgrass
and
goosegrass
are
most
prevalent.
MSMA
can
be
applied
at
any
time
of
year.
3
Cotton
is
labeled
for
aerial
application
but
ground
application
leads
to
more
conservative
EDWCs.
4
http://
www.
epa.
gov/
oppefed1/
models/
water/
input_
guidance2_
28_
02.
htm
5
Different
from
input
for
2001
RED
(
DP
Barcode
D277223).
6
http://
www.
epa.
gov/
oppfead1/
trac/
science/
reservoir.
pdf
28
Table
6.
PRZM/
EXAMS
Input
Parameters
for
Cacodylic
Acid
on
Cotton
Model
Parameter
Value
Comments
Source
Single
Application
Rate
(#
of
applications)
1.34
kg/
ha
(
1
application)
Master
Label
Application
Date
10/
10
USDA­
NASS
Planting
and
Harvest
Dates
(
12/
97)
1
Application
Method
Foliar;
aerial
applied
Leads
to
default
values
of
16%
Spray
drift
95%
App.
efficiency
Incorporation
Depth
0
cm
Aerobic
Soil
Metabolism
Half­
Life
240
days2
90%
upper
confidence
bound,
based
on
6
values.
Woolson
&
Kearney,
1973
Woolson,
1982
Gao
&
Burau,
1997
MRID
44767601
Anaerobic
Soil
Metabolism
Half­
Life
168
days
90%
upper
confidence
bound,
based
on
3
values.
Woolson
&
Kearney,
1973
Aerobic
Aquatic
Metabolism
Half­
life
480
days2
No
reported
data,
use
½
of
aerobic
soil
rate
Input
Parameter
Guidance3
Anaerobic
Aquatic
Metabolism
Half­
life
336
days
No
reported
data,
use
½
of
anaerobic
soil
rate
Input
Parameter
Guidance3
Aqueous
Photolysis
Half­
life
Stable
MRID
41662601
Hydrolysis
Half­
life
Stable
Stable
at
all
pH
MRID
42059201
Kd
8.2
ml/
g
Lowest
non­
sand
Kd
from
16
soils.
Reviewer
calculated.
Wauchope,
1975
Molecular
Weight
138
g/
mol
Water
Solubility
1
x
106
mg/
L
2000
RED
(
D210451,
D212449,
255226)

Vapor
Pressure
0
2000
RED
(
D210451,
D212449,
255226)

Percent
Cropped
Area
(
PCA)
20%
Drinking
Water
Screening
Level
Assessment
Guidance,
Part
B
4
1
http://
usda.
mannlib.
cornell.
edu/
reports/
nassr/
field/
planting/
uph97.
html
2
Different
from
input
for
2000
RED
(
DP
Barcodes
D210451,
D212449,
255226).
3
http://
www.
epa.
gov/
oppefed1/
models/
water/
input_
guidance2_
28_
02.
htm
4
http://
www.
epa.
gov/
oppfead1/
trac/
science/
reservoir.
pdf
29
inclusion
of
unreviewed
non­
GLP
studies
from
an
incomplete
literature
review.
The
anaerobic
aquatic
metabolism
half­
life
is
based
on
the
value
from
one
registrant
study
(
MRID
44767602;
Acceptable)
which
is
multiplied
by
three
to
account
for
the
uncertainty
when
only
a
single
value
is
available,
as
directed
by
the
input
guidance
(
EFED,
2002).
This
leads
to
a
half­
life
that
is
significantly
longer
than
the
aerobic
values.
Although
this
is
not
entirely
supported
by
the
literature,
which
indicates
that
anaerobic
metabolism
may
be
faster
than
aerobic
metabolism
(
Akkari,
1986;
Gao
and
Burau,
1997),
adjusting
this
value
makes
no
difference
in
the
results
and
so
no
change
was
made.

For
DMA,
the
soil
and
aquatic
metabolism
half­
lives
are
all
based
on
non­
GLP
data.
Although
these
values
have
uncertainty,
there
are
no
acceptable
GLP
studies
of
DMA
available.
The
aerobic
soil
metabolism
half­
life
is
based
on
the
same
3
literature
studies
considered
in
the
2000
RED
(
DP
Barcodes
D210451,
D212449,
D255226)
as
well
as
data
on
DMA
as
a
metabolite
from
a
GLP
study
of
MSMA
(
MRID
44767601).
For
one
study,
the
half­
lives
used
were
recalculated
based
on
data
from
the
complete
32
week
study
rather
than
data
from
the
first
24
weeks,
as
was
originally
used
(
Woolson
&
Kearney,
1973).
Because
of
decreasing
transformation
with
time,
this
leads
to
a
longer
half­
life.
A
half­
life
for
DMA
was
derived
from
the
MSMA
study
by
performing
non­
linear
regression
on
its
formation
and
decline
using
StatMost
software
(
StatMost,
1994).
The
half­
life
was
calculated
using
the
simplifying
assumption
that
metabolism
occurred
as
two
individual
first
order
processes:
MMA
transforming
to
DMA
followed
by
transformation
to
inorganic
arsenic.
Although
there
is
some
uncertainty
in
this
approach,
this
is
the
only
GLP
study
with
data
for
DMA
metabolism
and
the
only
study
available
that
was
carried
out
for
a
full
year
so
it
still
provides
valuable
information.
The
aerobic
aquatic
metabolism
half­
life
is
based
on
the
aerobic
soil
value,
as
per
EFED
guidance
(
EFED,
2002)
and
so
increased
as
well.
The
anaerobic
aquatic
metabolism
half­
life
was
calculated
based
on
anaerobic
soil
metabolism
data
from
one
literature
study
(
Woolson
&
Kearney,
1973).
Another
study
was
discussed
in
the
2000
RED
(
Woolson,
1982),
but
because
it
was
carried
out
in
atypical
conditions
it
was
not
included
in
calculations.

Input
Parameters:
Soil
Mobility
For
MMA,
the
Kd
value
used
in
the
2000
RED,
13
mL/
g,
was
not
referenced
and
so
could
not
be
confirmed.
Data
from
a
registrant
study
(
MRID
41651906;
Supplemental)
were
considered
along
with
data
reported
by
Wauchope
(
1975)
leading
to
a
lowest
non­
sand
Kd
value
of
11.4
mL/
g.
For
DMA,
the
original
Kd
value
of
8.2
mL/
g
was
not
changed.
It
is
the
lowest
non­
sand
value
calculated
from
data
reported
by
Wauchope
(
1975).

Use
of
the
lowest
non­
sand
Kd
provides
a
conservative
estimate
of
potential
runoff
in
agricultural
soils
that
do
not
promote
sorption.
The
effect
of
variable
Kd
values
on
modeling
results
was
examined.
For
MMA,
the
median
of
the
19
Kd
values
considered
was
28
and
the
average
was
37
mL/
g
(
Wauchope,
1975;
MRID
41651906).
For
DMA,
16
values
were
considered
with
a
median
of
15
and
an
average
of
18
mL/
g
(
Wauchope,
1975).
To
estimate
exposure
from
typical
soils,
a
Kd
of
20
was
used
for
modeling
DMA
and
30
for
MMA.
This
led
to
decreased
peak
EDWCs
for
cotton
and
had
less
of
an
impact
on
chronic
values.
Little
change
was
seen
in
turf
peak
or
chronic
EDWCs,
while
30
the
cancer
EDWCs
actually
increased
slightly.
See
the
characterization
discussion
for
more
detail.

Calculation
of
Metabolites
MMA
metabolism
to
DMA
was
simulated
by
modeling
DMA
applied
at
35%
of
the
MMA
rate
with
DMA
input
parameters.
For
cotton,
where
DMA
and
MMA
can
both
be
applied
to
the
same
field
at
different
times
in
the
same
season,
the
time
series
of
concentrations
resulting
from
DMA
applied
directly
was
added
to
that
resulting
from
DMA
as
a
metabolite
of
MMA.
The
upper
90%
confidence
limit
was
determined
for
peak
and
average
annual
values
from
this
30
year
time
series.

This
simulation
is
based
on
the
assumption
that
a
maximum
of
35%
of
applied
MMA
may
be
present
as
DMA
at
any
one
time.
This
is
based
on
one
registrant
aerobic
soil
study
submitted
in
2001
(
MRID
44767601;
Acceptable).
After
1
year,
32%
of
the
applied
MSMA
was
present
as
DMA.
At
the
end
of
this
study,
the
amount
of
DMA
present
was
still
rising,
so
it
is
possible
that
after
1
year,
a
greater
percentage
of
the
applied
amount
is
present
as
DMA.
The
35%
estimate
is
supported
by
calculations
of
the
formation
and
decline
of
DMA
using
the
same
half­
lives
as
included
in
the
PRZM/
EXAMS
modeling.

There
is
uncertainty
associated
with
this
assumption,
which
is
based
on
the
results
of
a
lab
study
on
the
metabolism
of
MMA
and
on
calculations
using
the
modeled
half­
lives
of
MMA
and
DMA.
In
both
of
these
approaches,
the
DMA
present
is
being
metabolized
as
it
is
formed
and
so,
without
metabolism,
would
be
present
in
higher
amounts.
The
estimate
of
35%,
therefore,
already
takes
into
account
some
amount
of
transformation.
The
model
then
simulates
metabolism
as
well,
possibly
leading
to
an
underestimation
of
the
maximum
amount
of
DMA
present
at
any
time.
Despite
this
uncertainty,
35%
is
considered
sufficiently
conservative
because
even
incorporating
some
transformation,
it
is
still
significantly
higher
than
the
amount
of
DMA
seen
in
any
other
field
or
lab
study
reviewed,
many
of
which
found
no
DMA
at
all.
Additional
uncertainty
results
from
modeling
the
DMA
metabolite
as
if
it
were
applied
at
the
same
time
as
the
MMA
parent.
Metabolism
to
DMA
is
not
a
rapid
transformation
and
so
in
fact,
when
present,
the
metabolite
will
appear
at
a
later
date
dependent
on
the
environmental
conditions.

Total
arsenic
was
estimated
as
a
direct
molar
conversion
of
the
EDWC
predicted
for
the
applied,
parent
organic
arsenical(
s).
(
The
reported
EDWCs
for
parent
and
metabolite
compounds
represent
maximum
potential
concentrations
for
each
species
and
are
not
additive
to
a
total
possible
concentration.
When
the
concentration
of
one
species
is
at
its
highest,
the
other
species'
concentration
will
be
lower.)
The
total
arsenic
value
is
also
used
as
the
inorganic
arsenic
EDWC.
For
maximum
inorganic
arsenic,
a
direct
molar
conversion
of
the
parent
compound's
aquatic
concentration
does
not
necessarily
represent
the
actual
physical
process
 
inorganic
arsenic
is
likely
formed
through
metabolism
in
the
soil,
rather
than
after
reaching
surface
water.
This
calculation
still
provides
a
conservative
estimate
of
the
amount
of
inorganic
arsenic
that
may
reach
surface
water.
The
estimate
is
supported
by
a
targeted
monitoring
study
in
cotton
growing
areas
which
found
that
typically,
one
arsenic
species
at
a
time
was
dominant.
Immediately
following
31
the
period
of
typical
application,
MMA
was
the
dominant
species
and
several
weeks
to
months
later
it
the
primary
form
of
arsenic
was
inorganic,
present
at
approximately
the
same
total
arsenic
concentration
as
the
earlier
MMA
(
Bednar,
2002).

Percent
Cropped
Area
For
cotton,
a
20%
PCA
is
applied
to
the
modeling
results,
according
to
division
policy
which
estimates
that
20%
is
the
maximum
area
of
any
watershed
planted
in
cotton
(
OPP,
2000).
It
is
possible
that
arsenicals
are
applied
to
other
crops
within
the
same
watershed,
which
could
lead
to
higher
amounts
of
pesticide
reaching
surface
water.
Use
as
an
herbicide
on
turf
is
the
only
other
application
of
arsenicals
extensive
enough
to
potentially
increase
watershed
scale
concentrations.
Monitoring
data
suggest,
however,
that
the
20%
PCA
still
leads
to
protective
estimates
of
exposure.
A
study
targeted
to
estimate
the
impacts
of
arsenical
use
on
cotton
sampled
surface
water
weekly
from
May
to
September
in
heavy
cotton
growing
areas
in
Yazoo
County,
Mississippi
(
site
of
the
Mississippi
cotton
scenario),
and
in
Arkansas
(
Bednar,
2002).
The
highest
concentration
of
total
arsenic
found
in
any
of
those
samples
(
6
ppb
as
arsenic
=
11
ppb
as
MMA)
is
similar
to
the
modeled
chronic
EDWC
for
MMA
on
cotton
as
parent
compound
only
and
so
is
less
than
the
chronic
total
arsenic
concentrations,
which
would
include
metabolites
as
well.
Weekly
targeted
monitoring
of
this
type
can
be
expected
to
capture
chronic
concentrations
but
not
acute
concentrations.
These
monitoring
values,
in
the
range
of
modeled
chronic
concentrations
and
less
than
modeled
acute
concentrations,
suggest
that
the
EDWCs
are
reasonable.

No
appropriate
PCA
has
been
determined
for
application
of
pesticides
to
turf.
In
order
to
be
protective,
at
this
time
division
policy
is
to
not
apply
any
PCA
for
turf.
The
modeled
EDWCs
for
turf
are
therefore
based
on
the
assumption
that
the
entire
modeled
watershed
has
been
treated
with
pesticide,
which
may
lead
to
overestimation
of
potential
exposure.
Limited
surface
water
monitoring
data
targeted
to
golf
course
use
are
available.
Two
studies
measured
arsenic
in
golf
course
ponds.
In
one
study,
6
ponds
were
sampled
with
arsenic
concentrations
ranging
from
below
detection
limits
to
24
ppb
(
as
total
arsenic;
Swancar,
1996).
In
the
other
study,
arsenic
concentrations
at
four
ponds
ranged
from
below
detection
limits
to
30
ppb
with
a
median
of
19.75
ppb
(
as
total
arsenic).
These
values
were
reported
to
be
an
order
of
magnitude
higher
than
other
surface
water
concentrations
in
the
same
area
(
DERM,
2002).
This
monitoring
involves
relatively
small
surface
water
bodies
that
are
completely
surrounded
by
turf
that
may
be
treated
with
arsenicals,
so
they
represent
high
potential
exposure
relative
to
the
index
reservoir.
Nevertheless,
they
demonstrate
that
a
significant
amount
of
arsenic
may
reach
surface
water
from
turf
applications
of
arsenicals
and
that
modeled
turf
EDWCs
are
on
the
same
scale
as
concentrations
that
have
been
measured
in
monitoring.
The
chronic
turf
total
arsenic
EDWC
is
68.8
ppb,
approximately
twice
that
found
in
monitoring.
These
data
are
discussed
in
more
detail
in
the
monitoring
section.

Characterization
The
reported
EDWCs
are
based
on
maximum
labeled
application
rates
under
the
most
vulnerable
circumstances.
A
variety
of
management
practices,
environmental
conditions,
and
application
rates
are
possible
and
can
lead
to
different
concentrations.
This
section
32
characterizes
how
exposure
to
arsenicals
may
be
affected
by
less
vulnerable
soils,
typical
application
rates,
application
to
minor
crops,
or
practices
such
as
irrigation
or
spot
treatment.

Sorption
of
arsenical
pesticides
varies
with
soil
characteristics.
Sorption
is
expected
to
be
higher
in
soils
with
a
higher
percentage
of
clay
or
with
more
iron
or
aluminum
content
(
Matera,
2001).
Surface
water
concentrations
were
estimated
using
higher
Kd
values
to
characterize
possible
exposure
from
application
to
less
vulnerable
soils.
Considering
the
parent
compound
only,
for
application
of
MMA
or
DMA
to
cotton,
the
typical
Kd
led
to
peak
concentrations
approximately
30%
less
than
those
from
more
vulnerable
soils.
Kd
had
less
of
an
effect
on
chronic
exposure
from
cotton
application
with
a
15%
decrease
for
MMA
and
a
3%
decrease
for
DMA.
There
was
little
change
for
cancer
EDWCs.
For
MMA
applied
to
turf,
a
higher
Kd
led
to
less
than
a
10%
decrease
for
peak
and
chronic
exposures
and
actually
led
to
a
slight
increase
in
estimated
cancer
concentrations.

EDWCs
are
modeled
using
the
maximum
labeled
application
rates.
For
turf,
this
maximum
rate
is
allowed
for
sod
farms
and
other
well
established
Bermudagrass
and
Zoysiagrass,
but
use
on
golf
courses,
parks,
and
athletic
fields
is
limited
by
the
label
to
a
lower
application
rate.
For
MSMA,
the
"
golf
course"
rate
is
2.6
lb/
A,
compared
to
the
maximum
rate
of
3.9
lb/
A.
Additionally,
the
new
master
label
specifies
that
arsenicals
cannot
be
applied
to
golf
course
greens.
While
greens
generally
make
up
less
than
3%
of
golf
course
area
(
EFED,
2005),
they
are
typically
the
areas
treated
most
heavily
with
pesticides
and
are
also
designed
to
promote
drainage,
so
limiting
application
to
greens
may
lead
to
lower
concentrations.
A
2002
report
by
the
Florida
Center
for
Solid
and
Hazardous
Waste
Management
at
the
University
of
Florida
estimated
that
typical
use
of
MSMA
on
golf
courses
was
3
annual
applications
at
3
lbs/
A.
Based
on
responses
from
15%
of
Florida
golf
courses,
the
report
estimated
that
80%
of
golf
courses
apply
MSMA
Table
7.
Surface
water
concentrations
(
ppb)
from
applications
of
MSMA
to
turf
at
less
than
the
maximum
labeled
rate.
Acute
Chronic
Cancer
Golf
course
rate1
MMA
166.7
85.2
49.7
DMA
68.0
33.7
18.9
Total
As
89.9
46.0
26.8
"
Typical"
use
rate2
MMA
180.6
80.5
45.2
DMA
64.6
27.6
14.8
Total
As
97.4
43.4
24.4
Single
app.;
max
rate3
MMA
77.7
34.8
18.5
DMA
33.2
13.4
7.0
Total
As
41.9
18.9
10.0
1
On
golf
courses,
parks,
and
athletic
fields,
maximum
rate
is
4
applications
at
2.49
lbs
ae/
A
.
2
"
Typical
use"
on
golf
courses
=
3
applications
MSMA
at
2.57lbs
ae/
A.
(
Ma,
2002)
3
One
application
of
MSMA
at
3.35
lbs
ae/
A.
33
at
this
rate
or
lower
(
Ma,
2002).
These
application
rates
were
modeled
with
PRZM/
EXAMS
and
the
estimated
concentrations
are
presented
in
Table
7.
It
should
be
emphasized
that
modeling
at
the
maximum
labeled
rate
is
the
most
protective
and
these
concentrations
are
provided
for
characterization
only.

The
most
conservative
estimate
of
use
of
arsenicals
on
cotton
assumes
that
DSMA
or
MSMA
is
applied
as
an
early
season
herbicide
followed
by
DMA
as
a
late
season
defoliant
on
the
same
field.
This
combined
use
is
allowed
by
the
labels
and
is
known
to
be
used
in
some
areas.
It
is
more
common
that
either
one
or
the
other
product
is
used
individually
(
BEAD,
2005a)
and
so
these
uses
were
modeled
as
well
for
characterization.
Table
8
includes
estimated
concentrations
for
maximum
labeled
applications
to
cotton
of
only
one
type
of
arsenical,
either
MMA
as
an
herbicide
or
DMA
as
a
defoliant.
These
values
are
based
on
the
same
input
parameters
described
in
Table
5
and
Table
6
including
the
20%
PCA
adjustment.

Table
8.
Surface
water
concentrations
(
ppb)
from
applications
of
individual
arsenicals
to
cotton.
Acute
Chronic
Cancer
Max
rate,
DMA
only1
MMA
­­­
­­­
­­­

DMA
18.3
2.9
2.0
Total
As
9.9
1.6
1.1
Max
rate,
MMA
only2
MMA
37.4
11.0
5.3
DMA
17.8
5.1
2.3
Total
As
20.2
5.9
2.9
Single
app.,
MMA
only3
MMA
18.4
5.4
2.6
DMA
8.7
2.5
1.2
Total
As
9.9
2.9
1.4
1
Based
on
1
application
of
DMA
as
a
defoliant
at
1.2
lb/
A.
2
Based
on
2
applications
of
DSMA
as
an
herbicide
at
1.74
lbs
ae/
A.
3
Based
on
1
application
of
DSMA
as
an
herbicide
at
1.74
lbs
ae/
A.

Labels
for
DSMA
and
MSMA
also
allow
application
to
orchards,
citrus,
and
vineyards
and
the
DMA
label
includes
a
use
on
citrus,
although
this
is
prohibited
in
Florida.
All
available
scenarios
were
modeled
to
characterize
concentrations
resulting
from
application
to
these
minor
crops.
The
Oregon
grass
seed
scenario
was
modeled
as
well
to
account
for
the
labeled
application
of
DSMA
and
MSMA
to
grass
seed
in
the
Pacific
Northwest.
Concentrations
resulting
from
application
of
arsenicals
to
the
most
vulnerable
of
these
scenarios
are
presented
in
Table
9.
Although
application
rates
for
some
of
these
crops
are
higher
than
for
use
on
turf
or
cotton,
turf
and
cotton
represent
at
least
97%
of
the
total
national
use
of
arsenicals
and
so
those
uses
are
expected
to
have
the
greatest
impact
(
BEAD,
2005a
&
b).
34
The
values
in
Table
9
are
screening
estimates
that
do
not
account
for
the
labeled
restriction
that
arsenicals
can
only
be
applied
to
non­
bearing
fields
of
orchards,
citrus,
and
vineyards
and
cannot
be
applied
within
one
year
of
harvest.
As
a
worst­
case
scenario,
then,
arsenicals
would
only
be
applied
to
these
crops
every
second
or
third
year
so
a
refined
estimate
would
limit
the
years
of
application,
leading
to
much
lower
estimated
concentrations.
Additionally,
these
estimated
concentrations
use
the
default
PCA
adjustment
of
87%.
Given
the
low
estimated
usage
of
arsenicals
on
these
crops,
the
actual
usage
area
within
a
watershed
is
likely
notably
lower
than
that.
These
modeled
values
therefore
overestimate
the
likely
concentrations
of
arsenicals
on
orchards,
citrus,
and
vineyards.
The
EDWCs
from
application
to
turf
are
considered
protective
relative
to
these
uses.

Table
9.
Screening
estimate
of
surface
water
concentrations
(
ppb)
of
parent
compound
from
application
of
MMA
or
DMA
to
minor
crops.

Acute
Chronic
Cancer
MMA1
CA
almond
193.0
128.2
80.0
GA
pecan
330.6
81.4
44.5
MI
cherry
191.4
143.2
102.2
OR
grass
seed
145.9
102.5
76.4
DMA2
CA
citrus
116.3
93.7
76.8
1
Orchard,
citrus,
and
vineyard
based
on
3
applications
of
DSMA
at
3.7
lb
ae/
A.
Grass
seed
based
on
1
application
of
MSMA
at
5.3
lb
ae/
A.
2
Based
on
2
applications
of
DMA
at
4.96
lbs/
A.

The
reported
EDWCs
do
not
account
for
the
potential
impact
of
irrigation
because
it
is
not
calculated
effectively
by
the
model
versions
currently
available.
Irrigation
tends
to
be
very
important
in
turf
cultivation;
golf
courses
often
irrigate
at
rates
of
over
100,000
gallons
per
day
(
Swancar,
1996)
with
some
estimates
of
average
irrigation
as
high
as
350,000
gpd
(
Ma,
2002).
A
provisional
version
of
PRZM
has
been
designed
to
account
for
the
effects
of
irrigation,
although
this
irrigated
model
is
currently
approved
only
to
provide
characterization
of
modeling
results
and
not
to
quantify
EDWCs.
This
model,
run
using
a
version
of
the
Florida
turf
scenario
edited
to
include
irrigation,
estimated
that
surface
water
concentrations
of
MMA
from
irrigated
turf
can
be
expected
to
be
8
to
33%
lower
than
those
from
non­
irrigated
fields.
Using
the
inputs
listed
in
Table
5,
the
irrigated
model
estimates
MMA
surface
water
concentrations
of
230
ppb
(
acute),
102
ppb
(
chronic),
and
50
ppb
(
cancer).
Especially
on
well
drained
soils
like
those
in
Florida
golf
courses,
irrigation
can
decrease
runoff
by
increasing
the
potential
for
leaching
to
groundwater.
35
Turf
EDWCs
are
also
expected
to
be
lower
if
arsenicals
are
applied
as
spot
treatments
rather
than
as
broadcast
sprays,
which
appears
to
be
a
common
practice.
There
is
a
possibility
that
this
will
be
included
as
a
restriction
on
the
labels
for
DSMA
and
MSMA.
Spot
treatments
are
applied
to
less
area
than
broadcast
sprays
and
so
lead
to
lower
exposure.
If
application
rate
or
area
is
limited
on
the
label
by
a
quantifiable
amount,
the
estimated
concentrations
will
be
reduced
by
a
proportional
amount.
For
example,
if
treatment
of
arsenicals
on
all
turf
uses
is
limited
to
50%
of
a
field,
the
EDWCs
will
go
down
to
one
half
of
the
original
value.

SOIL
ACCUMULATION
Accumulation
of
persistent
pesticides
in
soil
is
not
typically
addressed
in
drinking
water
assessments.
Because
of
the
possible
implications
for
human
health,
a
summary
of
the
issue
is
presented
here.
A
more
detailed
discussion
of
potential
buildup
of
arsenic
in
soil
resulting
from
pesticide
application
can
be
found
in
the
Ecological
Risk
Assessment
(
DP
Barcode
D309100).
The
relative
immobility
of
arsenicals
along
with
arsenic's
elemental
nature
make
buildup
in
soil
after
repeated
applications
an
important
consideration.
Field
studies,
monitoring
of
soil
in
use
areas,
and
modeling
all
suggest
that
it
is
likely
that
applied
arsenicals
will
build
up
in
soil
over
time.
Arsenic
accumulation
is
likely
to
be
limited
to
the
top
layers
of
soil,
with
studies
suggesting
that
it
is
unlikely
to
occur
at
depths
greater
than
30
cm.

Registrant
terrestrial
field
dissipation
studies
have
measured
the
impact
of
one
season
of
pesticide
applications
on
soil
concentrations.
Two
studies
at
rates
similar
to
the
maximum
labeled
cotton
and
turf
rates
found
that
a
single
year
of
application
is
unlikely
to
lead
to
significantly
elevated
soil
arsenic
levels
but,
since
most
of
the
applied
arsenic
remained
in
the
top
6
inches
of
soil,
repeated
application
may
lead
to
significant
accumulation.
Higher
application
rates,
possible
in
some
of
the
non­
crop
uses,
led
to
elevated
soil
arsenic
levels
after
a
single
year
of
application.
Few
studies
have
evaluated
the
longer
term
impact
of
repeated
application
of
organic
arsenicals.
Those
that
have
been
conducted
have
conflicting
results,
with
some
reporting
no
arsenic
buildup
despite
very
high
application
rates
and
others
finding
substantial
buildup
at
rates
similar
to
current
labels,
although
most
reports
do
not
contain
adequate
explanations
to
account
for
observed
loss
of
arsenic.
Monitoring
of
soil
in
areas
where
arsenicals
are
known
to
have
been
applied,
including
golf
courses
and
roadside
areas,
has
found
significant
increases
of
arsenic
levels
relative
to
background
concentrations.
In
Miami,
an
area
with
low
background
arsenic
levels,
arsenic
was
the
most
common
contaminant
found
in
documented
soil
violations
at
golf
courses.

Soil
modeling
based
on
median
sorption
and
maximum
application
rates
suggest
that
over
the
long
term,
the
buildup
of
total
arsenic
in
the
top
10
cm
of
soil
for
MMA
would
level
off
at
chronic
concentrations
of
approximately
13
ppm
and
45
ppm
on
cotton
and
turf,
respectively.
The
higher
application
rates
allowed
for
DMA
in
non­
crop
and
some
turf
uses
would
be
expected
to
lead
to
higher
soil
concentrations,
assuming
annual
application
at
those
rates.
Routes
of
dissipation
accounted
for
in
the
modeling
include
runoff,
36
leaching,
and
soil
erosion.
The
field
and
monitoring
studies
support
these
modeling
results
as
a
reasonable
representation
of
potential
accumulation.

UNCERTAINTY
Monitoring
For
arsenic,
monitoring
data
serve
two
separate
functions
 
to
establish
natural
background
arsenic
levels
in
surface
and
groundwater
and
to
provide
information
about
potential
impacts
from
pesticide
applications.
The
uncertainty
associated
with
the
monitoring
data
is
different
for
these
different
roles.

For
most
of
the
data
used
in
discussing
natural
background
arsenic
levels,
data
collection
sites
are
not
uniformly
distributed
and
have
not
been
specifically
selected
to
exclude
anthropogenic
arsenic
sources
 
some
sites
even
represent
known
point
sources
of
arsenic.
The
percentage
of
sites
impacted
by
these
sources,
however,
is
quite
small
relative
to
the
large
national
USGS
datasets,
each
with
more
than
30,000
samples.
For
groundwater,
the
uncertainty
was
further
reduced
by
using
statistical
criteria
to
limit
the
data
incorporated
and
therefore
minimizing
potential
bias.
This
was
not
done
for
the
surface
water
dataset
which
therefore
may
include
some
bias
towards
more
frequently
sampled
sites.
The
data
on
individual
arsenic
species,
rather
than
total
arsenic,
are
not
nationally
representative,
for
surface
or
groundwater.
There
is
uncertainty
in
extrapolating
the
results
from
these
sites
to
a
wider
assumption
regarding
background
levels.

There
is
greater
uncertainty
in
the
targeted
monitoring
data.
Specific
sources
of
uncertainty
are
included
in
the
discussion
of
each
individual
study.
In
general,
even
targeted
sampling
is
likely
to
underestimate
both
acute
exposures
and
the
frequency
of
occurrence
due
to
the
limited
number
of
samples
and
the
extended
time
between
sampling
events.
For
arsenic,
additional
uncertainty
comes
from
the
multiple
possible
arsenic
sources.
In
most
cases,
detailed
pesticide
application
and
land
use
history
information
are
not
available.
Natural
background
arsenic
levels
are
not
well
defined
in
all
areas.

Surface
Water
Modeling
Modeling
relies
on
estimated
fate
parameters
and
assumed
agricultural
practices
to
predict
concentrations
of
pesticides
to
which
humans
may
be
exposed.
There
is
uncertainty
in
all
fate
inputs
used
in
this
assessment.
The
values
used
as
half­
lives
include
uncertainty
both
due
to
the
limited
available
data
and
due
to
the
complexity
of
arsenic's
environmental
fate.
The
majority
of
data
are
from
non­
GLP
studies
that
were
conducted
for
less
than
one
year,
ranging
in
length
from
60
days
to
32
weeks.
Additionally,
in
most
cases
complete
time
series
were
not
available,
so
rates
were
calculated
based
on
initial
and
final
concentrations
only.
One
set
of
values
included
in
calculations
was
normalized
by
the
reviewer
to
standard
conditions,
based
on
up
to
six
replications
performed
under
a
variety
of
conditions
(
Gao,
1997).
All
of
these
factors
37
could
have
an
impact
on
the
calculated
half­
lives.
Modeling
with
infinite
half­
lives
provides
an
upper
boundary
of
the
extent
to
which
a
modification
in
half­
life
inputs
could
change
estimated
results.
Using
infinite
half­
lives,
acute
EDWCs
are
increased
by
up
to
17%
while
chronic
and
cancer
EDWCs
are
increased
by
approximately
one­
third.

As
discussed
above,
there
is
also
uncertainty
associated
with
the
method
of
estimating
concentrations
of
the
major
metabolites,
DMA
and
inorganic
arsenic.
The
estimate
of
metabolism
to
DMA
is
based
on
the
assumption
that
35%
is
the
maximum
amount
of
MAA
that
may
be
present
as
DMA
at
any
one
time.
Because
this
value
is
based
on
data
that
already
includes
some
transformation,
it
may
lead
to
some
underestimation
of
DMA
concentrations.
The
estimation
of
concentrations
of
inorganic
arsenic
is
also
uncertain.
Maximum
potential
concentrations
of
inorganic
arsenic
are
represented
by
the
total
arsenic
EDWCs,
calculated
as
a
molar
conversion
of
the
EDWCs
of
parent
compounds.
This
is
a
general
estimate
of
the
amount
of
inorganic
arsenic
that
may
reach
surface
water
rather
than
a
direct
calculation
based
on
specific
physical
processes.
Transformation
of
applied
organic
arsenicals
to
inorganic
arsenic
is
a
long
term
process
that
occurs
primarily
through
microbial
activity
in
the
soil,
not
a
rapid
conversion
upon
reaching
water.
Because
of
the
nature
of
these
transformation
processes
and
because
of
inorganic
arsenic's
tendency
to
bind
more
strongly
to
soil
than
the
organic
arsenicals
do,
the
EDWC
of
the
parent
compounds
represents
a
reasonable
upper
bound
on
the
EDWCs
of
inorganic
arsenic.
This
assumption
is
supported
by
empirical
evidence
from
a
targeted
monitoring
study
which
found
that
the
maximum
concentrations
of
inorganic
arsenic
found
in
surface
water
in
areas
of
heavy
application
was
similar
to
the
total
arsenic
resulting
from
parent
compounds
(
Bednar,
2002).

PRZM/
EXAMS
requires
information
on
agricultural
practices
as
inputs,
such
as
specific
application
dates
and
rates
to
be
applied.
In
reality,
application
dates
and
rates
applied
across
the
United
States
and
even
within
a
single
watershed
will
vary
depending
on
geography,
pest
pressure,
climatic
factors,
and
changes
in
agricultural
cropping
patterns.
EFED
attempts
to
capture
some
of
this
variability
by
modeling
as
many
representative
scenarios
as
possible
and
by
using
meteorological
data
which
covers
a
time
span
sufficient
to
capture
climatic
variations
which
are
likely
to
occur.
However,
the
model
is
limited
in
its
ability
to
capture
all
of
the
natural
variation
which
occurs
for
any
pesticide
application
and
this
adds
uncertainty
to
the
drinking
water
assessment.
This
is
of
particular
importance
for
the
turf
scenario,
because
the
application
of
pesticides
to
turf
is
not
limited
to
a
specific
planting
season.
It
can
be
applied
most
of
the
year,
especially
in
areas
like
that
modeled,
where
winter
dormancy
is
not
expected.
In
this
case,
a
spring
application
date
was
chosen
because
the
primary
use
of
arsenicals
on
turf
is
to
control
crabgrass
and
goosegrass,
pests
which
emerge
in
the
spring
months.
Application
of
arsenicals
to
turf
at
other
times
of
year
is
possible
and
could
lead
to
higher
exposure,
especially
if
applied
during
periods
of
heavier
rainfall
which
would
increase
runoff
and
leaching.
For
use
on
cotton,
the
application
dates
within
the
typical
use
season
that
led
to
the
most
conservative
EDWCs
were
chosen.

The
area
of
a
watershed
which
is
treated
with
a
pesticide
is
another
factor
influencing
the
estimated
exposure.
As
discussed
previously,
for
cotton,
a
PCA
of
20%
was
applied.
If
38
arsenicals
are
applied
to
additional
crops
within
the
same
watershed,
this
may
lead
to
higher
EDWCs
than
those
reported.
For
turf,
no
PCA
was
applied,
which
likely
leads
to
some
overestimation
of
the
EDWC,
although
the
probable
extent
of
the
overestimation
is
undefined.
39
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2002.
http://
fdep.
ifas.
ufl.
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MSMA%
20Dec%
2027%
202002.
pdf
Garbarino,
J.
R.;
Burkhardt,
M.
R.
Determination
of
Four
Arsenicals
in
Natural
Water
Samples
by
HPLC­
Hydride
Generation­
ICPMS:
40th
Rocky
Mountain
Conference
on
Analytical
Chemistry;
Denver,
Colorado,
1998.

Gao,
S.;
Burau,
R.
G.
Environmental
factors
affecting
rates
of
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evolution
from
and
mineralization
of
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in
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J.
Environ.
Qual.,
1997,
26,
753­
763.

German,
E.
R.
Analysis
of
Nonpoint­
Source
Ground­
WaterContamination
in
Relation
to
Land
Use:
Assessment
of
Nonpoint­
Source
Contamination
in
Central
Florida:
U.
S.
Geological
Survey
Water
Supply
Paper
2381­
F;
U.
S.
Geological
Survey:
Reston,
1996.
http://
fl.
water.
usgs.
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PDF_
files/
wsp2381_
german.
pdf
Ma,
L.
Q.;
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R.
X.;
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D.;
Chen,
M.;
Harris,
W.
G.;
Sartain,
J.
Environmental
Impacts
of
Lead
Pellets
at
Shooting
Ranges
and
Arsencial
Herbicides
on
Golf
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in
Florida,
Report
#
02­
01.
University
of
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Florida
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for
Solid
and
Hazardous
Waste
Management,
Gainesville.
May,
2002.
http://
www.
floridacenter.
org/
publications/
ma_
0201_
shooting_
ranges.
pdf
MAATF,
2005.
The
Environmental
Fate
of
Monosodium
Methane
Arsonate
(
MSMA):
A
Review
of
Important
Processes.
MAA
Research
Task
Force,
Washington,
D.
C.
2005.

Matera,
V;
Le
Hecho,
I.
2001.
Arsenic
behavior
in
contaminated
soils:
Mobility
and
speciation.
In
Heavy
Metals
Release
in
Soils
(
Eds:
Selim,
H.
M.;
Sparks,
D.
M.),
CRC
Press,
Boca
Raton,
pp.
207­
235.

Office
of
Pesticide
Programs.
2000.
Drinking
Water
Screening
Level
Asssessments.
September
1,
2000.
Office
of
Pesticide
Programs,
U.
S.
Environmental
Protection
Agency,
Washington,
D.
C
http://
www.
epa.
gov/
oppfead1/
trac/
science/
reservoir.
pdf
Ryker,
S.
J.,
Mapping
arsenic
in
groundwater.
Geotimes
2001,
46(
11),
34­
36.
http://
water.
usgs.
gov/
nawqa/
trace/
pubs/
geo_
v46n11/
fig3.
html
StatMost.
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Statistical
Analysis
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41
Swancar,
A.
Water
Quality,
Pesticide
Occurrence,
and
Effects
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Irrigation
with
Reclaimed
Water
at
Golf
Courses
in
Florida:
U.
S.
Geological
Survey
Water
Resources
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Report
95­
4250;
U.
S.
Geological
Survey:
Tallahassee,
1996.
http://
fl.
water.
usgs.
gov/
PDF_
files/
wri95_
4250_
swancar.
pdf
USEPA,
1992.
Pesticides
in
Ground
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(
EPA
734­
12­
92­
001).
USEPA,
Washington,
DC.

U.
S.
Department
of
Agriculture.
1997.
Usual
Planting
and
Harvesting
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for
U.
S.
Field
Crops.
Agricultural
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No.
628.
National
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U.
S.
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of
Agriculture,
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D.
C.
http://
usda.
mannlib.
cornell.
edu/
reports/
nassr/
field/
planting/
uph97.
html
U.
S.
Geological
Survey.
2003.
1997
Pesticide
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NAWQA
Pesticide
National
Synthesis
Project.
September
3,
2003.
http://
ca.
water.
usgs.
gov/
pnsp/
pesticide_
use_
maps_
1997/

Welch,
A.
H.;
Westjohn,
D.
B.;
Helsel,
D.
R.;
Wanty,
R.
B.
Arsenic
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2000,
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Wauchope,
R.
D.
Fixation
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herbicides,
phosphate,
and
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in
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(
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260782
and
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Nos.
259582
and
260061.)

Woolson,
E.
A.;
Kearney,
P.
C.
Persistence
and
reactions
of
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1973,
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47­
50.
(
EPA
Accession
Nos.
259582.)

Woolson,
E.
A.;
Aharonson,
N.;
Iadevaia,
R.
Application
of
high­
performance
liquid
chromatography
­
flameless
atomic
absorption
method
to
the
study
of
alkyl
arsenical
herbicide
metabolism
in
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Agric.
Food
Chem.,
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580­
584.
(
EPA
Accession
Nos.
259582,
260061,
260782.)
42
Appendix
A:
PRZM/
EXAMS
Input
Files
43
MMA
on
Cotton;
Parent
Compound
MS
Cotton;
8/
13/
2001
"
Yazoo
County;
MLRA
134;
Metfile:
W03940.
dvf
(
old:
Met131.
met),"
***
Record
3:
0.74
0.15
0
17
1
1
***
Record
6
­­
ERFLAG
4
***
Record
7:
0.49
0.4
0.75
172.8
4
6
600
***
Record
8
3
***
Record
9
1
0.2
125
98
3
99
93
92
0
120
2
0.2
125
98
3
94
84
83
0
120
3
0.2
125
98
3
99
83
83
0
120
***
Record
9a­
d
1
25
0101
1601
0102
1602
0103
1603
0104
1604
2504
0105
1605
0106
1606
0107
1607
0108
.500
.517
.532
.549
.567
.591
.617
.667
.705
.718
.699
.620
.496
.354
.303
.305
.014
.014
.014
.014
.014
.014
.014
.014
.014
.014
.014
.014
.014
.014
.014
.014
1608
0109
1609
0110
1610
0111
1611
0112
1612
.289
.343
.359
.223
.327
.376
.425
.465
.494
.014
.014
.014
.014
.014
.014
.014
.014
.014
2
25
0101
1601
0102
1602
0103
1603
0104
1604
2504
0105
1605
0106
1606
0107
1607
0108
.500
.517
.532
.549
.567
.591
.617
.667
.705
.718
.699
.620
.496
.354
.303
.305
.014
.014
.014
.014
.014
.014
.014
.014
.014
.014
.014
.014
.014
.014
.014
.014
1608
0109
1609
0110
1610
0111
1611
0112
1612
.289
.343
.359
.223
.327
.376
.425
.465
.494
.014
.014
.014
.014
.014
.014
.014
.014
.014
3
25
0101
1601
0102
1602
0103
1603
0104
1604
2504
0105
1605
0106
1606
0107
1607
0108
.500
.517
.532
.549
.567
.591
.617
.667
.705
.718
.699
.620
.496
.354
.303
.305
.014
.014
.014
.014
.014
.014
.014
.014
.014
.014
.014
.014
.014
.014
.014
.014
1608
0109
1609
0110
1610
0111
1611
0112
1612
.289
.343
.359
.223
.327
.376
.425
.465
.494
.014
.014
.014
.014
.014
.014
.014
.014
.014
***
Record
10
­­
NCPDS,
the
number
of
cropping
periods
30
***
Record
11
010561
070961
220961
1
010562
070962
220962
2
010563
070963
220963
3
010564
070964
220964
1
010565
070965
220965
2
010566
070966
220966
3
010567
070967
220967
1
010568
070968
220968
2
010569
070969
220969
3
010570
070970
220970
1
010571
070971
220971
2
010572
070972
220972
3
010573
070973
220973
1
010574
070974
220974
2
010575
070975
220975
3
44
010576
070976
220976
1
010577
070977
220977
2
010578
070978
220978
3
010579
070979
220979
1
010580
070980
220980
2
010581
070981
220981
3
010582
070982
220982
1
010583
070983
220983
2
010584
070984
220984
3
010585
070985
220985
1
010586
070986
220986
2
010587
070987
220987
3
010588
070988
220988
1
010589
070989
220989
2
010590
070990
220990
3
***
Record
12
­­
PTITLE
MAA
­
2
applications
@
1.95
kg/
ha
***
Record
13
60
1
0
0
***
Record
15
­­
PSTNAM
MAA
***
Record
16
070561
0
2
0.0
1.95
0.990.064
140561
0
2
0.0
1.95
0.990.064
070562
0
2
0.0
1.95
0.990.064
140562
0
2
0.0
1.95
0.990.064
070563
0
2
0.0
1.95
0.990.064
140563
0
2
0.0
1.95
0.990.064
070564
0
2
0.0
1.95
0.990.064
140564
0
2
0.0
1.95
0.990.064
070565
0
2
0.0
1.95
0.990.064
140565
0
2
0.0
1.95
0.990.064
070566
0
2
0.0
1.95
0.990.064
140566
0
2
0.0
1.95
0.990.064
070567
0
2
0.0
1.95
0.990.064
140567
0
2
0.0
1.95
0.990.064
070568
0
2
0.0
1.95
0.990.064
140568
0
2
0.0
1.95
0.990.064
070569
0
2
0.0
1.95
0.990.064
140569
0
2
0.0
1.95
0.990.064
070570
0
2
0.0
1.95
0.990.064
140570
0
2
0.0
1.95
0.990.064
070571
0
2
0.0
1.95
0.990.064
140571
0
2
0.0
1.95
0.990.064
070572
0
2
0.0
1.95
0.990.064
140572
0
2
0.0
1.95
0.990.064
070573
0
2
0.0
1.95
0.990.064
140573
0
2
0.0
1.95
0.990.064
070574
0
2
0.0
1.95
0.990.064
140574
0
2
0.0
1.95
0.990.064
070575
0
2
0.0
1.95
0.990.064
140575
0
2
0.0
1.95
0.990.064
070576
0
2
0.0
1.95
0.990.064
140576
0
2
0.0
1.95
0.990.064
070577
0
2
0.0
1.95
0.990.064
140577
0
2
0.0
1.95
0.990.064
45
070578
0
2
0.0
1.95
0.990.064
140578
0
2
0.0
1.95
0.990.064
070579
0
2
0.0
1.95
0.990.064
140579
0
2
0.0
1.95
0.990.064
070580
0
2
0.0
1.95
0.990.064
140580
0
2
0.0
1.95
0.990.064
070581
0
2
0.0
1.95
0.990.064
140581
0
2
0.0
1.95
0.990.064
070582
0
2
0.0
1.95
0.990.064
140582
0
2
0.0
1.95
0.990.064
070583
0
2
0.0
1.95
0.990.064
140583
0
2
0.0
1.95
0.990.064
070584
0
2
0.0
1.95
0.990.064
140584
0
2
0.0
1.95
0.990.064
070585
0
2
0.0
1.95
0.990.064
140585
0
2
0.0
1.95
0.990.064
070586
0
2
0.0
1.95
0.990.064
140586
0
2
0.0
1.95
0.990.064
070587
0
2
0.0
1.95
0.990.064
140587
0
2
0.0
1.95
0.990.064
070588
0
2
0.0
1.95
0.990.064
140588
0
2
0.0
1.95
0.990.064
070589
0
2
0.0
1.95
0.990.064
140589
0
2
0.0
1.95
0.990.064
070590
0
2
0.0
1.95
0.990.064
140590
0
2
0.0
1.95
0.990.064
***
Record
17
0
2
0
***
Record
18
0
0
0.5
***
Record
19
­­
STITLE
Loring
Silt
Loam;
HYDG:
C
***
Record
20
155
0
0
0
0
0
0
0
0
0
***
Record
26
0
0
0
***
Record
33
6
1
13
1.4
0.385
0
0
0
0.0028880.002888
0
0.1
0.385
0.151
2.18
11.4
2
23
1.4
0.37
0
0
0
0.0028880.002888
0
1
0.37
0.146
0.49
11.4
3
33
1.4
0.37
0
0
0
0.0028880.002888
0
3
0.37
0.146
0.16
11.4
4
30
1.45
0.34
0
0
0
0.0028880.002888
0
5
0.34
0.125
0.124
11.4
5
23
1.49
0.335
0
0
0
0.0028880.002888
0
1
0.335
0.137
0.07
11.4
6
33
1.51
0.343
0
0
0
0.0028880.002888
0
3
0.343
0.147
0.06
11.4
46
***
Record
40
0
YEAR
10
YEAR
10
YEAR
10
1
1
1
­­­­­
7
YEAR
PRCP
TCUM
0
0
RUNF
TCUM
0
0
INFL
TCUM
1
1
ESLS
TCUM
0
0
1.0E3
RFLX
TCUM
0
0
1.0E5
EFLX
TCUM
0
0
1.0E5
RZFX
TCUM
0
0
1.0E5
47
DMA
on
Cotton;
Parent
Compound
MS
Cotton;
8/
13/
2001
"
Yazoo
County;
MLRA
134;
Metfile:
W03940.
dvf
(
old:
Met131.
met),"
***
Record
3:
0.74
0.15
0
17
1
1
***
Record
6
­­
ERFLAG
4
***
Record
7:
0.49
0.4
0.75
172.8
4
6
600
***
Record
8
3
***
Record
9
1
0.2
125
98
3
99
93
92
0
120
2
0.2
125
98
3
94
84
83
0
120
3
0.2
125
98
3
99
83
83
0
120
***
Record
9a­
d
1
25
0101
1601
0102
1602
0103
1603
0104
1604
2504
0105
1605
0106
1606
0107
1607
0108
.500
.517
.532
.549
.567
.591
.617
.667
.705
.718
.699
.620
.496
.354
.303
.305
.014
.014
.014
.014
.014
.014
.014
.014
.014
.014
.014
.014
.014
.014
.014
.014
1608
0109
1609
0110
1610
0111
1611
0112
1612
.289
.343
.359
.223
.327
.376
.425
.465
.494
.014
.014
.014
.014
.014
.014
.014
.014
.014
2
25
0101
1601
0102
1602
0103
1603
0104
1604
2504
0105
1605
0106
1606
0107
1607
0108
.500
.517
.532
.549
.567
.591
.617
.667
.705
.718
.699
.620
.496
.354
.303
.305
.014
.014
.014
.014
.014
.014
.014
.014
.014
.014
.014
.014
.014
.014
.014
.014
1608
0109
1609
0110
1610
0111
1611
0112
1612
.289
.343
.359
.223
.327
.376
.425
.465
.494
.014
.014
.014
.014
.014
.014
.014
.014
.014
3
25
0101
1601
0102
1602
0103
1603
0104
1604
2504
0105
1605
0106
1606
0107
1607
0108
.500
.517
.532
.549
.567
.591
.617
.667
.705
.718
.699
.620
.496
.354
.303
.305
.014
.014
.014
.014
.014
.014
.014
.014
.014
.014
.014
.014
.014
.014
.014
.014
1608
0109
1609
0110
1610
0111
1611
0112
1612
.289
.343
.359
.223
.327
.376
.425
.465
.494
.014
.014
.014
.014
.014
.014
.014
.014
.014
***
Record
10
­­
NCPDS,
the
number
of
cropping
periods
30
***
Record
11
010561
070961
220961
1
010562
070962
220962
2
010563
070963
220963
3
010564
070964
220964
1
010565
070965
220965
2
010566
070966
220966
3
010567
070967
220967
1
010568
070968
220968
2
010569
070969
220969
3
010570
070970
220970
1
010571
070971
220971
2
010572
070972
220972
3
010573
070973
220973
1
010574
070974
220974
2
010575
070975
220975
3
48
010576
070976
220976
1
010577
070977
220977
2
010578
070978
220978
3
010579
070979
220979
1
010580
070980
220980
2
010581
070981
220981
3
010582
070982
220982
1
010583
070983
220983
2
010584
070984
220984
3
010585
070985
220985
1
010586
070986
220986
2
010587
070987
220987
3
010588
070988
220988
1
010589
070989
220989
2
010590
070990
220990
3
***
Record
12
­­
PTITLE
DMA
­
1
applications
@
1.34
kg/
ha
***
Record
13
30
1
0
0
***
Record
15
­­
PSTNAM
DMA
***
Record
16
101061
0
2
0.0
1.34
0.95
0.16
101062
0
2
0.0
1.34
0.95
0.16
101063
0
2
0.0
1.34
0.95
0.16
101064
0
2
0.0
1.34
0.95
0.16
101065
0
2
0.0
1.34
0.95
0.16
101066
0
2
0.0
1.34
0.95
0.16
101067
0
2
0.0
1.34
0.95
0.16
101068
0
2
0.0
1.34
0.95
0.16
101069
0
2
0.0
1.34
0.95
0.16
101070
0
2
0.0
1.34
0.95
0.16
101071
0
2
0.0
1.34
0.95
0.16
101072
0
2
0.0
1.34
0.95
0.16
101073
0
2
0.0
1.34
0.95
0.16
101074
0
2
0.0
1.34
0.95
0.16
101075
0
2
0.0
1.34
0.95
0.16
101076
0
2
0.0
1.34
0.95
0.16
101077
0
2
0.0
1.34
0.95
0.16
101078
0
2
0.0
1.34
0.95
0.16
101079
0
2
0.0
1.34
0.95
0.16
101080
0
2
0.0
1.34
0.95
0.16
101081
0
2
0.0
1.34
0.95
0.16
101082
0
2
0.0
1.34
0.95
0.16
101083
0
2
0.0
1.34
0.95
0.16
101084
0
2
0.0
1.34
0.95
0.16
101085
0
2
0.0
1.34
0.95
0.16
101086
0
2
0.0
1.34
0.95
0.16
101087
0
2
0.0
1.34
0.95
0.16
101088
0
2
0.0
1.34
0.95
0.16
101089
0
2
0.0
1.34
0.95
0.16
101090
0
2
0.0
1.34
0.95
0.16
***
Record
17
0
2
0
***
Record
18
0
0
0.5
49
***
Record
19
­­
STITLE
Loring
Silt
Loam;
HYDG:
C
***
Record
20
155
0
0
0
0
0
0
0
0
0
***
Record
26
0
0
0
***
Record
33
6
1
13
1.4
0.385
0
0
0
0.0028880.002888
0
0.1
0.385
0.151
2.18
8.2
2
23
1.4
0.37
0
0
0
0.0028880.002888
0
1
0.37
0.146
0.49
8.2
3
33
1.4
0.37
0
0
0
0.0028880.002888
0
3
0.37
0.146
0.16
8.2
4
30
1.45
0.34
0
0
0
0.0028880.002888
0
5
0.34
0.125
0.124
8.2
5
23
1.49
0.335
0
0
0
0.0028880.002888
0
1
0.335
0.137
0.07
8.2
6
33
1.51
0.343
0
0
0
0.0028880.002888
0
3
0.343
0.147
0.06
8.2
***
Record
40
0
YEAR
10
YEAR
10
YEAR
10
1
1
1
­­­­­
7
YEAR
PRCP
TCUM
0
0
RUNF
TCUM
0
0
INFL
TCUM
1
1
ESLS
TCUM
0
0
1.0E3
RFLX
TCUM
0
0
1.0E5
EFLX
TCUM
0
0
1.0E5
RZFX
TCUM
0
0
1.0E5
50
DMA
on
Cotton;
Metabolite
of
Parent
MMA
MS
Cotton;
8/
13/
2001
"
Yazoo
County;
MLRA
134;
Metfile:
W03940.
dvf
(
old:
Met131.
met),"
***
Record
3:
0.74
0.15
0
17
1
1
***
Record
6
­­
ERFLAG
4
***
Record
7:
0.49
0.4
0.75
172.8
4
6
600
***
Record
8
3
***
Record
9
1
0.2
125
98
3
99
93
92
0
120
2
0.2
125
98
3
94
84
83
0
120
3
0.2
125
98
3
99
83
83
0
120
***
Record
9a­
d
1
25
0101
1601
0102
1602
0103
1603
0104
1604
2504
0105
1605
0106
1606
0107
1607
0108
.500
.517
.532
.549
.567
.591
.617
.667
.705
.718
.699
.620
.496
.354
.303
.305
.014
.014
.014
.014
.014
.014
.014
.014
.014
.014
.014
.014
.014
.014
.014
.014
1608
0109
1609
0110
1610
0111
1611
0112
1612
.289
.343
.359
.223
.327
.376
.425
.465
.494
.014
.014
.014
.014
.014
.014
.014
.014
.014
2
25
0101
1601
0102
1602
0103
1603
0104
1604
2504
0105
1605
0106
1606
0107
1607
0108
.500
.517
.532
.549
.567
.591
.617
.667
.705
.718
.699
.620
.496
.354
.303
.305
.014
.014
.014
.014
.014
.014
.014
.014
.014
.014
.014
.014
.014
.014
.014
.014
1608
0109
1609
0110
1610
0111
1611
0112
1612
.289
.343
.359
.223
.327
.376
.425
.465
.494
.014
.014
.014
.014
.014
.014
.014
.014
.014
3
25
0101
1601
0102
1602
0103
1603
0104
1604
2504
0105
1605
0106
1606
0107
1607
0108
.500
.517
.532
.549
.567
.591
.617
.667
.705
.718
.699
.620
.496
.354
.303
.305
.014
.014
.014
.014
.014
.014
.014
.014
.014
.014
.014
.014
.014
.014
.014
.014
1608
0109
1609
0110
1610
0111
1611
0112
1612
.289
.343
.359
.223
.327
.376
.425
.465
.494
.014
.014
.014
.014
.014
.014
.014
.014
.014
***
Record
10
­­
NCPDS,
the
number
of
cropping
periods
30
***
Record
11
010561
070961
220961
1
010562
070962
220962
2
010563
070963
220963
3
010564
070964
220964
1
010565
070965
220965
2
010566
070966
220966
3
010567
070967
220967
1
010568
070968
220968
2
010569
070969
220969
3
010570
070970
220970
1
010571
070971
220971
2
010572
070972
220972
3
010573
070973
220973
1
010574
070974
220974
2
51
010575
070975
220975
3
010576
070976
220976
1
010577
070977
220977
2
010578
070978
220978
3
010579
070979
220979
1
010580
070980
220980
2
010581
070981
220981
3
010582
070982
220982
1
010583
070983
220983
2
010584
070984
220984
3
010585
070985
220985
1
010586
070986
220986
2
010587
070987
220987
3
010588
070988
220988
1
010589
070989
220989
2
010590
070990
220990
3
***
Record
12
­­
PTITLE
DMA
­
2
applications
@
.90
kg/
ha
***
Record
13
60
1
0
0
***
Record
15
­­
PSTNAM
DMA
***
Record
16
070561
0
2
0.0
0.9
0.990.064
140561
0
2
0.0
0.9
0.990.064
070562
0
2
0.0
0.9
0.990.064
140562
0
2
0.0
0.9
0.990.064
070563
0
2
0.0
0.9
0.990.064
140563
0
2
0.0
0.9
0.990.064
070564
0
2
0.0
0.9
0.990.064
140564
0
2
0.0
0.9
0.990.064
070565
0
2
0.0
0.9
0.990.064
140565
0
2
0.0
0.9
0.990.064
070566
0
2
0.0
0.9
0.990.064
140566
0
2
0.0
0.9
0.990.064
070567
0
2
0.0
0.9
0.990.064
140567
0
2
0.0
0.9
0.990.064
070568
0
2
0.0
0.9
0.990.064
140568
0
2
0.0
0.9
0.990.064
070569
0
2
0.0
0.9
0.990.064
140569
0
2
0.0
0.9
0.990.064
070570
0
2
0.0
0.9
0.990.064
140570
0
2
0.0
0.9
0.990.064
070571
0
2
0.0
0.9
0.990.064
140571
0
2
0.0
0.9
0.990.064
070572
0
2
0.0
0.9
0.990.064
140572
0
2
0.0
0.9
0.990.064
070573
0
2
0.0
0.9
0.990.064
140573
0
2
0.0
0.9
0.990.064
070574
0
2
0.0
0.9
0.990.064
140574
0
2
0.0
0.9
0.990.064
070575
0
2
0.0
0.9
0.990.064
140575
0
2
0.0
0.9
0.990.064
070576
0
2
0.0
0.9
0.990.064
140576
0
2
0.0
0.9
0.990.064
070577
0
2
0.0
0.9
0.990.064
52
140577
0
2
0.0
0.9
0.990.064
070578
0
2
0.0
0.9
0.990.064
140578
0
2
0.0
0.9
0.990.064
070579
0
2
0.0
0.9
0.990.064
140579
0
2
0.0
0.9
0.990.064
070580
0
2
0.0
0.9
0.990.064
140580
0
2
0.0
0.9
0.990.064
070581
0
2
0.0
0.9
0.990.064
140581
0
2
0.0
0.9
0.990.064
070582
0
2
0.0
0.9
0.990.064
140582
0
2
0.0
0.9
0.990.064
070583
0
2
0.0
0.9
0.990.064
140583
0
2
0.0
0.9
0.990.064
070584
0
2
0.0
0.9
0.990.064
140584
0
2
0.0
0.9
0.990.064
070585
0
2
0.0
0.9
0.990.064
140585
0
2
0.0
0.9
0.990.064
070586
0
2
0.0
0.9
0.990.064
140586
0
2
0.0
0.9
0.990.064
070587
0
2
0.0
0.9
0.990.064
140587
0
2
0.0
0.9
0.990.064
070588
0
2
0.0
0.9
0.990.064
140588
0
2
0.0
0.9
0.990.064
070589
0
2
0.0
0.9
0.990.064
140589
0
2
0.0
0.9
0.990.064
070590
0
2
0.0
0.9
0.990.064
140590
0
2
0.0
0.9
0.990.064
***
Record
17
0
2
0
***
Record
18
0
0
0.5
***
Record
19
­­
STITLE
Loring
Silt
Loam;
HYDG:
C
***
Record
20
155
0
0
0
0
0
0
0
0
0
***
Record
26
0
0
0
***
Record
33
6
1
13
1.4
0.385
0
0
0
0.0028880.002888
0
0.1
0.385
0.151
2.18
8.2
2
23
1.4
0.37
0
0
0
0.0028880.002888
0
1
0.37
0.146
0.49
8.2
3
33
1.4
0.37
0
0
0
0.0028880.002888
0
3
0.37
0.146
0.16
8.2
4
30
1.45
0.34
0
0
0
0.0028880.002888
0
5
0.34
0.125
0.124
8.2
5
23
1.49
0.335
0
0
0
0.0028880.002888
0
1
0.335
0.137
0.07
8.2
6
33
1.51
0.343
0
0
0
0.0028880.002888
0
53
3
0.343
0.147
0.06
8.2
***
Record
40
0
YEAR
10
YEAR
10
YEAR
10
1
1
1
­­­­­
7
YEAR
PRCP
TCUM
0
0
RUNF
TCUM
0
0
INFL
TCUM
1
1
ESLS
TCUM
0
0
1.0E3
RFLX
TCUM
0
0
1.0E5
EFLX
TCUM
0
0
1.0E5
RZFX
TCUM
0
0
1.0E5
54
MMA
on
Turf;
Parent
Compound
FL
Turf
8/
09/
2001
Osceola
County;
Representation
of
the
Lake
Kissimmee/
Indian
River
Region;
MLRA
156A;
Metfile:
W12834.
dvf
[
Daytona
Beach]
(
old:
Met156A.
met)
***
Record
3:
0.78
0
0
25
1
3
***
Record
6
­­
ERFLAG
4
***
Record
7:
0.04
0.303
1
172.8
4
2
600
***
Record
8
1
***
Record
9
1
0.1
10
100
3
74
74
74
0
5
***
Record
9a­
d
1
25
0101
1601
0102
1602
0103
1603
0104
1604
0105
1605
0106
1606
0107
1507
1607
0108
.023
.026
.030
.035
.042
.050
.056
.060
.063
.068
.074
.079
.082
.125
.148
.189
.023
.023
.023
.023
.023
.023
.023
.023
.023
.023
.023
.023
.023
.023
.023
.023
1608
0109
1609
0110
1610
0111
1611
0112
1612
.229
.265
.294
.314
.326
.017
.018
.019
.021
.023
.023
.023
.023
.023
.023
.023
.023
.023
***
Record
10
­­
NCPDS,
the
number
of
cropping
periods
30
***
Record
11
010261
150261
151261
1
010262
150262
151262
1
010263
150263
151263
1
010264
150264
151264
1
010265
150265
151265
1
010266
150266
151266
1
010267
150267
151267
1
010268
150268
151268
1
010269
150269
151269
1
010270
150270
151270
1
010271
150271
151271
1
010272
150272
151272
1
010273
150273
151273
1
010274
150274
151274
1
010275
150275
151275
1
010276
150276
151276
1
010277
150277
151277
1
010278
150278
151278
1
010279
150279
151279
1
010280
150280
151280
1
010281
150281
151281
1
010282
150282
151282
1
010283
150283
151283
1
010284
150284
151284
1
010285
150285
151285
1
010286
150286
151286
1
010287
150287
151287
1
010288
150288
151288
1
010289
150289
151289
1
55
010290
150290
151290
1
***
Record
12
­­
PTITLE
MAA
­
4
applications
@
3.75
kg/
ha
***
Record
13
120
1
0
0
***
Record
15
­­
PSTNAM
MAA
***
Record
16
140361
0
2
0.0
3.75
0.990.064
240361
0
2
0.0
3.75
0.990.064
030461
0
2
0.0
3.75
0.990.064
130461
0
2
0.0
3.75
0.990.064
140362
0
2
0.0
3.75
0.990.064
240362
0
2
0.0
3.75
0.990.064
030462
0
2
0.0
3.75
0.990.064
130462
0
2
0.0
3.75
0.990.064
140363
0
2
0.0
3.75
0.990.064
240363
0
2
0.0
3.75
0.990.064
030463
0
2
0.0
3.75
0.990.064
130463
0
2
0.0
3.75
0.990.064
140364
0
2
0.0
3.75
0.990.064
240364
0
2
0.0
3.75
0.990.064
030464
0
2
0.0
3.75
0.990.064
130464
0
2
0.0
3.75
0.990.064
140365
0
2
0.0
3.75
0.990.064
240365
0
2
0.0
3.75
0.990.064
030465
0
2
0.0
3.75
0.990.064
130465
0
2
0.0
3.75
0.990.064
140366
0
2
0.0
3.75
0.990.064
240366
0
2
0.0
3.75
0.990.064
030466
0
2
0.0
3.75
0.990.064
130466
0
2
0.0
3.75
0.990.064
140367
0
2
0.0
3.75
0.990.064
240367
0
2
0.0
3.75
0.990.064
030467
0
2
0.0
3.75
0.990.064
130467
0
2
0.0
3.75
0.990.064
140368
0
2
0.0
3.75
0.990.064
240368
0
2
0.0
3.75
0.990.064
030468
0
2
0.0
3.75
0.990.064
130468
0
2
0.0
3.75
0.990.064
140369
0
2
0.0
3.75
0.990.064
240369
0
2
0.0
3.75
0.990.064
030469
0
2
0.0
3.75
0.990.064
130469
0
2
0.0
3.75
0.990.064
140370
0
2
0.0
3.75
0.990.064
240370
0
2
0.0
3.75
0.990.064
030470
0
2
0.0
3.75
0.990.064
130470
0
2
0.0
3.75
0.990.064
140371
0
2
0.0
3.75
0.990.064
240371
0
2
0.0
3.75
0.990.064
030471
0
2
0.0
3.75
0.990.064
130471
0
2
0.0
3.75
0.990.064
140372
0
2
0.0
3.75
0.990.064
240372
0
2
0.0
3.75
0.990.064
030472
0
2
0.0
3.75
0.990.064
130472
0
2
0.0
3.75
0.990.064
56
140373
0
2
0.0
3.75
0.990.064
240373
0
2
0.0
3.75
0.990.064
030473
0
2
0.0
3.75
0.990.064
130473
0
2
0.0
3.75
0.990.064
140374
0
2
0.0
3.75
0.990.064
240374
0
2
0.0
3.75
0.990.064
030474
0
2
0.0
3.75
0.990.064
130474
0
2
0.0
3.75
0.990.064
140375
0
2
0.0
3.75
0.990.064
240375
0
2
0.0
3.75
0.990.064
030475
0
2
0.0
3.75
0.990.064
130475
0
2
0.0
3.75
0.990.064
140376
0
2
0.0
3.75
0.990.064
240376
0
2
0.0
3.75
0.990.064
030476
0
2
0.0
3.75
0.990.064
130476
0
2
0.0
3.75
0.990.064
140377
0
2
0.0
3.75
0.990.064
240377
0
2
0.0
3.75
0.990.064
030477
0
2
0.0
3.75
0.990.064
130477
0
2
0.0
3.75
0.990.064
140378
0
2
0.0
3.75
0.990.064
240378
0
2
0.0
3.75
0.990.064
030478
0
2
0.0
3.75
0.990.064
130478
0
2
0.0
3.75
0.990.064
140379
0
2
0.0
3.75
0.990.064
240379
0
2
0.0
3.75
0.990.064
030479
0
2
0.0
3.75
0.990.064
130479
0
2
0.0
3.75
0.990.064
140380
0
2
0.0
3.75
0.990.064
240380
0
2
0.0
3.75
0.990.064
030480
0
2
0.0
3.75
0.990.064
130480
0
2
0.0
3.75
0.990.064
140381
0
2
0.0
3.75
0.990.064
240381
0
2
0.0
3.75
0.990.064
030481
0
2
0.0
3.75
0.990.064
130481
0
2
0.0
3.75
0.990.064
140382
0
2
0.0
3.75
0.990.064
240382
0
2
0.0
3.75
0.990.064
030482
0
2
0.0
3.75
0.990.064
130482
0
2
0.0
3.75
0.990.064
140383
0
2
0.0
3.75
0.990.064
240383
0
2
0.0
3.75
0.990.064
030483
0
2
0.0
3.75
0.990.064
130483
0
2
0.0
3.75
0.990.064
140384
0
2
0.0
3.75
0.990.064
240384
0
2
0.0
3.75
0.990.064
030484
0
2
0.0
3.75
0.990.064
130484
0
2
0.0
3.75
0.990.064
140385
0
2
0.0
3.75
0.990.064
240385
0
2
0.0
3.75
0.990.064
030485
0
2
0.0
3.75
0.990.064
130485
0
2
0.0
3.75
0.990.064
140386
0
2
0.0
3.75
0.990.064
240386
0
2
0.0
3.75
0.990.064
030486
0
2
0.0
3.75
0.990.064
130486
0
2
0.0
3.75
0.990.064
57
140387
0
2
0.0
3.75
0.990.064
240387
0
2
0.0
3.75
0.990.064
030487
0
2
0.0
3.75
0.990.064
130487
0
2
0.0
3.75
0.990.064
140388
0
2
0.0
3.75
0.990.064
240388
0
2
0.0
3.75
0.990.064
030488
0
2
0.0
3.75
0.990.064
130488
0
2
0.0
3.75
0.990.064
140389
0
2
0.0
3.75
0.990.064
240389
0
2
0.0
3.75
0.990.064
030489
0
2
0.0
3.75
0.990.064
130489
0
2
0.0
3.75
0.990.064
140390
0
2
0.0
3.75
0.990.064
240390
0
2
0.0
3.75
0.990.064
030490
0
2
0.0
3.75
0.990.064
130490
0
2
0.0
3.75
0.990.064
***
Record
17
0
2
0
***
Record
18
0
0
0.5
***
Record
19
­­
STITLE
Adamsville
Sand;
Hydrologic
Group
C
***
Record
20
102
0
0
0
0
0
0
0
0
0
***
Record
26
0
0
0
***
Record
33
4
1
2
0.37
0.47
0
0
0
0.0028880.002888
0
0.1
0.47
0.27
7.5
11.4
2
10
1.44
0.086
0
0
0
0.0028880.002888
0
0.1
0.086
0.036
0.58
11.4
3
10
1.44
0.086
0
0
0
0.0028880.002888
0
0.1
0.086
0.036
0.58
11.4
4
80
1.58
0.03
0
0
0
0.0028880.002888
0
5
0.03
0.023
0.116
11.4
***
Record
40
0
YEAR
10
YEAR
10
YEAR
10
1
1
1
­­­­­
7
YEAR
PRCP
TCUM
0
0
RUNF
TCUM
0
0
INFL
TCUM
1
1
ESLS
TCUM
0
0
1.0E3
RFLX
TCUM
0
0
1.0E5
EFLX
TCUM
0
0
1.0E5
RZFX
TCUM
0
0
1.0E5
58
DMA
on
Turf;
Metabolite
of
Parent
MMA
FL
Turf
8/
09/
2001
Osceola
County;
Representation
of
the
Lake
Kissimmee/
Indian
River
Region;
MLRA
156A;
Metfile:
W12834.
dvf
[
Daytona
Beach]
(
old:
Met156A.
met)
***
Record
3:
0.78
0
0
25
1
3
***
Record
6
­­
ERFLAG
4
***
Record
7:
0.04
0.303
1
172.8
4
2
600
***
Record
8
1
***
Record
9
1
0.1
10
100
3
74
74
74
0
5
***
Record
9a­
d
1
25
0101
1601
0102
1602
0103
1603
0104
1604
0105
1605
0106
1606
0107
1507
1607
0108
.023
.026
.030
.035
.042
.050
.056
.060
.063
.068
.074
.079
.082
.125
.148
.189
.023
.023
.023
.023
.023
.023
.023
.023
.023
.023
.023
.023
.023
.023
.023
.023
1608
0109
1609
0110
1610
0111
1611
0112
1612
.229
.265
.294
.314
.326
.017
.018
.019
.021
.023
.023
.023
.023
.023
.023
.023
.023
.023
***
Record
10
­­
NCPDS,
the
number
of
cropping
periods
30
***
Record
11
010261
150261
151261
1
010262
150262
151262
1
010263
150263
151263
1
010264
150264
151264
1
010265
150265
151265
1
010266
150266
151266
1
010267
150267
151267
1
010268
150268
151268
1
010269
150269
151269
1
010270
150270
151270
1
010271
150271
151271
1
010272
150272
151272
1
010273
150273
151273
1
010274
150274
151274
1
010275
150275
151275
1
010276
150276
151276
1
010277
150277
151277
1
010278
150278
151278
1
010279
150279
151279
1
010280
150280
151280
1
010281
150281
151281
1
010282
150282
151282
1
010283
150283
151283
1
010284
150284
151284
1
010285
150285
151285
1
010286
150286
151286
1
010287
150287
151287
1
010288
150288
151288
1
010289
150289
151289
1
010290
150290
151290
1
59
***
Record
12
­­
PTITLE
DMA
­
4
applications
@
1.53
kg/
ha
***
Record
13
120
1
0
0
***
Record
15
­­
PSTNAM
DMA
***
Record
16
140361
0
2
0.0
1.53
0.990.064
240361
0
2
0.0
1.53
0.990.064
030461
0
2
0.0
1.53
0.990.064
130461
0
2
0.0
1.53
0.990.064
140362
0
2
0.0
1.53
0.990.064
240362
0
2
0.0
1.53
0.990.064
030462
0
2
0.0
1.53
0.990.064
130462
0
2
0.0
1.53
0.990.064
140363
0
2
0.0
1.53
0.990.064
240363
0
2
0.0
1.53
0.990.064
030463
0
2
0.0
1.53
0.990.064
130463
0
2
0.0
1.53
0.990.064
140364
0
2
0.0
1.53
0.990.064
240364
0
2
0.0
1.53
0.990.064
030464
0
2
0.0
1.53
0.990.064
130464
0
2
0.0
1.53
0.990.064
140365
0
2
0.0
1.53
0.990.064
240365
0
2
0.0
1.53
0.990.064
030465
0
2
0.0
1.53
0.990.064
130465
0
2
0.0
1.53
0.990.064
140366
0
2
0.0
1.53
0.990.064
240366
0
2
0.0
1.53
0.990.064
030466
0
2
0.0
1.53
0.990.064
130466
0
2
0.0
1.53
0.990.064
140367
0
2
0.0
1.53
0.990.064
240367
0
2
0.0
1.53
0.990.064
030467
0
2
0.0
1.53
0.990.064
130467
0
2
0.0
1.53
0.990.064
140368
0
2
0.0
1.53
0.990.064
240368
0
2
0.0
1.53
0.990.064
030468
0
2
0.0
1.53
0.990.064
130468
0
2
0.0
1.53
0.990.064
140369
0
2
0.0
1.53
0.990.064
240369
0
2
0.0
1.53
0.990.064
030469
0
2
0.0
1.53
0.990.064
130469
0
2
0.0
1.53
0.990.064
140370
0
2
0.0
1.53
0.990.064
240370
0
2
0.0
1.53
0.990.064
030470
0
2
0.0
1.53
0.990.064
130470
0
2
0.0
1.53
0.990.064
140371
0
2
0.0
1.53
0.990.064
240371
0
2
0.0
1.53
0.990.064
030471
0
2
0.0
1.53
0.990.064
130471
0
2
0.0
1.53
0.990.064
140372
0
2
0.0
1.53
0.990.064
240372
0
2
0.0
1.53
0.990.064
030472
0
2
0.0
1.53
0.990.064
130472
0
2
0.0
1.53
0.990.064
140373
0
2
0.0
1.53
0.990.064
60
240373
0
2
0.0
1.53
0.990.064
030473
0
2
0.0
1.53
0.990.064
130473
0
2
0.0
1.53
0.990.064
140374
0
2
0.0
1.53
0.990.064
240374
0
2
0.0
1.53
0.990.064
030474
0
2
0.0
1.53
0.990.064
130474
0
2
0.0
1.53
0.990.064
140375
0
2
0.0
1.53
0.990.064
240375
0
2
0.0
1.53
0.990.064
030475
0
2
0.0
1.53
0.990.064
130475
0
2
0.0
1.53
0.990.064
140376
0
2
0.0
1.53
0.990.064
240376
0
2
0.0
1.53
0.990.064
030476
0
2
0.0
1.53
0.990.064
130476
0
2
0.0
1.53
0.990.064
140377
0
2
0.0
1.53
0.990.064
240377
0
2
0.0
1.53
0.990.064
030477
0
2
0.0
1.53
0.990.064
130477
0
2
0.0
1.53
0.990.064
140378
0
2
0.0
1.53
0.990.064
240378
0
2
0.0
1.53
0.990.064
030478
0
2
0.0
1.53
0.990.064
130478
0
2
0.0
1.53
0.990.064
140379
0
2
0.0
1.53
0.990.064
240379
0
2
0.0
1.53
0.990.064
030479
0
2
0.0
1.53
0.990.064
130479
0
2
0.0
1.53
0.990.064
140380
0
2
0.0
1.53
0.990.064
240380
0
2
0.0
1.53
0.990.064
030480
0
2
0.0
1.53
0.990.064
130480
0
2
0.0
1.53
0.990.064
140381
0
2
0.0
1.53
0.990.064
240381
0
2
0.0
1.53
0.990.064
030481
0
2
0.0
1.53
0.990.064
130481
0
2
0.0
1.53
0.990.064
140382
0
2
0.0
1.53
0.990.064
240382
0
2
0.0
1.53
0.990.064
030482
0
2
0.0
1.53
0.990.064
130482
0
2
0.0
1.53
0.990.064
140383
0
2
0.0
1.53
0.990.064
240383
0
2
0.0
1.53
0.990.064
030483
0
2
0.0
1.53
0.990.064
130483
0
2
0.0
1.53
0.990.064
140384
0
2
0.0
1.53
0.990.064
240384
0
2
0.0
1.53
0.990.064
030484
0
2
0.0
1.53
0.990.064
130484
0
2
0.0
1.53
0.990.064
140385
0
2
0.0
1.53
0.990.064
240385
0
2
0.0
1.53
0.990.064
030485
0
2
0.0
1.53
0.990.064
130485
0
2
0.0
1.53
0.990.064
140386
0
2
0.0
1.53
0.990.064
240386
0
2
0.0
1.53
0.990.064
030486
0
2
0.0
1.53
0.990.064
130486
0
2
0.0
1.53
0.990.064
140387
0
2
0.0
1.53
0.990.064
61
240387
0
2
0.0
1.53
0.990.064
030487
0
2
0.0
1.53
0.990.064
130487
0
2
0.0
1.53
0.990.064
140388
0
2
0.0
1.53
0.990.064
240388
0
2
0.0
1.53
0.990.064
030488
0
2
0.0
1.53
0.990.064
130488
0
2
0.0
1.53
0.990.064
140389
0
2
0.0
1.53
0.990.064
240389
0
2
0.0
1.53
0.990.064
030489
0
2
0.0
1.53
0.990.064
130489
0
2
0.0
1.53
0.990.064
140390
0
2
0.0
1.53
0.990.064
240390
0
2
0.0
1.53
0.990.064
030490
0
2
0.0
1.53
0.990.064
130490
0
2
0.0
1.53
0.990.064
***
Record
17
0
2
0
***
Record
18
0
0
0.5
***
Record
19
­­
STITLE
Adamsville
Sand;
Hydrologic
Group
C
***
Record
20
102
0
0
0
0
0
0
0
0
0
***
Record
26
0
0
0
***
Record
33
4
1
2
0.37
0.47
0
0
0
0.0028880.002888
0
0.1
0.47
0.27
7.5
8.2
2
10
1.44
0.086
0
0
0
0.0028880.002888
0
0.1
0.086
0.036
0.58
8.2
3
10
1.44
0.086
0
0
0
0.0028880.002888
0
0.1
0.086
0.036
0.58
8.2
4
80
1.58
0.03
0
0
0
0.0028880.002888
0
5
0.03
0.023
0.116
8.2
***
Record
40
0
YEAR
10
YEAR
10
YEAR
10
1
1
1
­­­­­
7
YEAR
PRCP
TCUM
0
0
RUNF
TCUM
0
0
INFL
TCUM
1
1
ESLS
TCUM
0
0
1.0E3
RFLX
TCUM
0
0
1.0E5
EFLX
TCUM
0
0
1.0E5
RZFX
TCUM
0
0
1.0E5
62
Appendix
B:
PRZM/
EXAMS
Output
Files
63
MMA
on
Cotton;
Parent
Compound
stored
as
MAActMX1.
out
Chemical:
MAA
PRZM
environment:
MScottonC.
txt
modified
Wedday,
22
January
2003
at
10:
52:
38
EXAMS
environment:
ir298.
exv
modified
Thuday,
29
August
2002
at
14:
34:
12
Metfile:
w03940.
dvf
modified
Wedday,
3
July
2002
at
08:
05:
46
Water
segment
concentrations
(
ppb)

Year
Peak
96
hr
21
Day
60
Day
90
Day
Yearly
1961
65.09
62.95
58.61
55.19
49.39
21.69
1962
11.76
11.51
10.55
8.766
7.704
5.322
1963
39.1
37.74
32.69
24.42
20.28
8.135
1964
39.24
38.21
35.12
33.3
30.67
15.94
1965
24.54
23.7
20.69
15.77
13.14
7.627
1966
53.72
52.96
48
36.46
30.86
12.39
1967
79.49
76.86
70.48
63.01
56.87
23.95
1968
32.32
31.29
29.01
24.31
20.64
10.02
1969
8.928
8.628
7.512
5.693
5.159
3.291
1970
41.59
40.26
37.83
33.71
30.94
13.87
1971
55.31
53.5
46.74
36.49
31.1
14.29
1972
12.54
12.14
10.91
9.013
7.794
4.129
1973
50.35
49.42
45.43
38.9
33.64
15.21
1974
20.38
19.72
17.22
13.07
11.55
7.581
1975
18.72
18.32
17.09
14.53
13.64
6.486
1976
108
104
96.52
84.24
75.78
30.98
1977
18.52
17.93
15.72
13.82
12.86
8.962
1978
45.52
44.07
39.88
32.76
28.01
11.07
1979
114
111
102
86.49
77.08
34.07
1980
36.1
34.97
32.37
25.62
21.9
11.78
1981
32.85
31.96
29.2
27.15
24.76
9.833
1982
92.91
89.77
82.39
72.41
67.74
27.25
1983
83.45
80.74
71.43
55.14
46.57
20.21
1984
10.25
9.927
8.799
8.587
8.277
5.447
1985
52.59
50.76
44.34
35.22
31.06
13.37
1986
50.6
48.88
43.71
34.32
29.2
12.58
1987
29.07
28.1
25.2
19.43
16.51
7.632
1988
33.78
32.72
29.22
26.81
24.77
11.24
1989
46.29
44.76
40.74
35.72
31.46
14.67
1990
31.71
30.68
27.61
22.76
19.2
8.016
Sorted
results
Prob.
Peak
96
hr
21
Day
60
Day
90
Day
Yearly
0.032258
114
111
102
86.49
77.08
34.07
0.064516
108
104
96.52
84.24
75.78
30.98
0.096774
92.91
89.77
82.39
72.41
67.74
27.25
64
0.129032
83.45
80.74
71.43
63.01
56.87
23.95
0.16129
79.49
76.86
70.48
55.19
49.39
21.69
0.193548
65.09
62.95
58.61
55.14
46.57
20.21
0.225806
55.31
53.5
48
38.9
33.64
15.94
0.258065
53.72
52.96
46.74
36.49
31.46
15.21
0.290323
52.59
50.76
45.43
36.46
31.1
14.67
0.322581
50.6
49.42
44.34
35.72
31.06
14.29
0.354839
50.35
48.88
43.71
35.22
30.94
13.87
0.387097
46.29
44.76
40.74
34.32
30.86
13.37
0.419355
45.52
44.07
39.88
33.71
30.67
12.58
0.451613
41.59
40.26
37.83
33.3
29.2
12.39
0.483871
39.24
38.21
35.12
32.76
28.01
11.78
0.516129
39.1
37.74
32.69
27.15
24.77
11.24
0.548387
36.1
34.97
32.37
26.81
24.76
11.07
0.580645
33.78
32.72
29.22
25.62
21.9
10.02
0.612903
32.85
31.96
29.2
24.42
20.64
9.833
0.645161
32.32
31.29
29.01
24.31
20.28
8.962
0.677419
31.71
30.68
27.61
22.76
19.2
8.135
0.709677
29.07
28.1
25.2
19.43
16.51
8.016
0.741935
24.54
23.7
20.69
15.77
13.64
7.632
0.774194
20.38
19.72
17.22
14.53
13.14
7.627
0.806452
18.72
18.32
17.09
13.82
12.86
7.581
0.83871
18.52
17.93
15.72
13.07
11.55
6.486
0.870968
12.54
12.14
10.91
9.013
8.277
5.447
0.903226
11.76
11.51
10.55
8.766
7.794
5.322
0.935484
10.25
9.927
8.799
8.587
7.704
4.129
0.967742
8.928
8.628
7.512
5.693
5.159
3.291
0.1
91.964
88.867
81.294
71.47
66.653
26.92
Average
of
yearly
averages:
13.2347
with
20%
PCA
applied
18.3928
17.7734
16.2588
14.294
13.3306
5.384
2.64694
Inputs
generated
by
pe4.
pl
­
8­
August­
2003
65
DMA
on
Cotton;
Sum
of
Parent
Compound
and
Metabolite
of
MMA
Note:
This
table
was
generated
by
adding
together
the
time
series
produced
by
the
DMA
on
Cotton
(
Parent)
input
file
and
the
DMA
on
Cotton
(
Metabolite
of
MMA)
input
file.
The
resulting
time
series
was
sorted
to
determine
the
annual
peak
and
averages
and
the
upper
90th
percentile
values
were
established.

ppb
year
Peak
Average
1961
89.5
28.16038
1962
69.42
17.99364
1963
40.051
12.09472
1964
73
23.41964
1965
60.7
17.7723
1966
61.01
16.63727
1967
87.76
31.17746
1968
43.38
17.07995
1969
16.2
6.104696
1970
138.9
30.85104
1971
57.7
22.94463
1972
25.57
9.780566
1973
50
20.20716
1974
42.84
16.23299
1975
97.82
20.10098
1976
121.86
41.19082
1977
37.18
17.25269
1978
38.75
14.82005
1979
118.76
44.91417
1980
65.2
24.9073
1981
37.39
15.14247
1982
110.6
37.03625
1983
95.8
36.35403
1984
50.3
14.68191
1985
68
22.61434
1986
55.92
21.73297
1987
33.68
12.55942
1988
64.7
19.76704
1989
51.72
24.68408
1990
22.88
11.99881
Sorted
ppb
Peak
Average
0.032258
138.9
44.91417
0.064516
121.86
41.19082
0.096774
118.76
37.03625
0.129032
110.6
36.35403
0.16129
97.82
31.17746
0.193548
95.8
30.85104
0.225806
89.5
28.16038
0.258065
87.76
24.9073
66
0.290323
73
24.68408
0.322581
69.42
23.41964
0.354839
68
22.94463
0.387097
65.2
22.61434
0.419355
64.7
21.73297
0.451613
61.01
20.20716
0.483871
60.7
20.10098
0.516129
57.7
19.76704
0.548387
55.92
17.99364
0.580645
51.72
17.7723
0.612903
50.3
17.25269
0.645161
50
17.07995
0.677419
43.38
16.63727
0.709677
42.84
16.23299
0.741935
40.051
15.14247
0.774194
38.75
14.82005
0.806452
37.39
14.68191
0.83871
37.18
12.55942
0.870968
33.68
12.09472
0.903226
25.57
11.99881
0.935484
22.88
9.780566
0.967742
16.2
6.104696
peak
yearly
average
0.1
117.944
36.96803
21.67379
with
20%
PCA
23.6
7.4
4.3
67
MMA
on
Turf;
Parent
Compound
stored
as
MAAtfKG.
out
Chemical:
MAA
PRZM
environment:
FLturfC.
txt
modified
Monday,
16
June
2003
at
13:
48:
06
EXAMS
environment:
ir298.
exv
modified
Thuday,
29
August
2002
at
14:
34:
12
Metfile:
w12834.
dvf
modified
Wedday,
3
July
2002
at
08:
04:
28
Water
segment
concentrations
(
ppb)

Year
Peak
96
hr
21
Day
60
Day
90
Day
Yearly
1961
35.05
34.56
32.64
30.57
30.08
17.63
1962
95.81
94.98
90.32
81.15
74.69
41.93
1963
102
101
98.16
89.8
83.47
54.22
1964
251
248
237
211
193
106
1965
161
159
152
137
128
86.19
1966
246
243
230
208
203
123
1967
163
160
152
138
128
88.32
1968
150
148
141
126
116
77.03
1969
131
129
126
117
109
70.91
1970
101
99.32
95.67
88.69
84.05
55.32
1971
139
137
130
125
121
74.93
1972
227
224
218
201
191
111
1973
108
107
103
95.21
89.06
62.47
1974
88.47
87.39
83.96
79.21
77.31
51.76
1975
102
101
96.52
86.52
80.16
48.8
1976
358
353
338
313
292
154
1977
135
134
129
116
109
88.19
1978
313
309
291
262
247
138
1979
135
133
127
116
110
81.84
1980
99.32
98.1
94.06
85.59
82.1
56.64
1981
73.58
72.69
68.99
63.6
62.01
46.41
1982
227
223
216
195
183
103
1983
160
158
153
142
137
90.96
1984
246
243
235
220
216
128
1985
135
133
127
115
107
76.08
1986
61.87
61.22
58.59
54.48
51.79
39.7
1987
113
111
108
102
96.25
56.06
1988
56.32
55.69
53.79
51.32
51.05
37.19
1989
97.04
95.68
90.59
80.42
73.87
43.78
1990
52.06
51.46
49.05
45.18
42.62
29.24
Sorted
results
Prob.
Peak
96
hr
21
Day
60
Day
90
Day
Yearly
0.032258065
358
353
338
313
292
154
0.064516129
313
309
291
262
247
138
0.096774194
251
248
237
220
216
128
0.129032258
246
243
235
211
203
123
0.161290323
246
243
230
208
193
111
68
0.193548387
227
224
218
201
191
106
0.225806452
227
223
216
195
183
103
0.258064516
163
160
153
142
137
90.96
0.290322581
161
159
152
138
128
88.32
0.322580645
160
158
152
137
128
88.19
0.35483871
150
148
141
126
121
86.19
0.387096774
139
137
130
125
116
81.84
0.419354839
135
134
129
117
110
77.03
0.451612903
135
133
127
116
109
76.08
0.483870968
135
133
127
116
109
74.93
0.516129032
131
129
126
115
107
70.91
0.548387097
113
111
108
102
96.25
62.47
0.580645161
108
107
103
95.21
89.06
56.64
0.612903226
102
101
98.16
89.8
84.05
56.06
0.64516129
102
101
96.52
88.69
83.47
55.32
0.677419355
101
99.32
95.67
86.52
82.1
54.22
0.709677419
99.32
98.1
94.06
85.59
80.16
51.76
0.741935484
97.04
95.68
90.59
81.15
77.31
48.8
0.774193548
95.81
94.98
90.32
80.42
74.69
46.41
0.806451613
88.47
87.39
83.96
79.21
73.87
43.78
0.838709677
73.58
72.69
68.99
63.6
62.01
41.93
0.870967742
61.87
61.22
58.59
54.48
51.79
39.7
0.903225806
56.32
55.69
53.79
51.32
51.05
37.19
0.935483871
52.06
51.46
49.05
45.18
42.62
29.24
0.967741935
35.05
34.56
32.64
30.57
30.08
17.63
0.1
250.5
247.5
236.8
219.1
214.7
127.5
Average
of
yearly
averages:
74.62
Inputs
generated
by
pe4.
pl
­
8­
August­
2003
69
DMA
on
Turf;
Metabolite
of
MMA
stored
as
DMAhikMX.
out
Chemical:
DMA
PRZM
environment:
FLturfC.
txt
modified
Monday,
16
June
2003
at
13:
48:
06
EXAMS
environment:
ir298.
exv
modified
Thuday,
29
August
2002
at
14:
34:
12
Metfile:
w12834.
dvf
modified
Wedday,
3
July
2002
at
08:
04:
28
Water
segment
concentrations
(
ppb)

Year
Peak
96
hr
21
Day
60
Day
90
Day
Yearly
1961
16.97
16.69
15.87
14
12.95
8.062
1962
41.33
40.87
38.61
36.3
33.46
18.43
1963
44.22
43.53
41.21
39.63
37.62
23.93
1964
103
101
95.74
83.25
76.23
41.49
1965
72.51
71.31
66.86
58.88
54.2
34.64
1966
91.73
90.25
84.53
77.33
73.65
45.62
1967
57.18
56.28
52.93
48.2
45.02
31.48
1968
82.33
80.88
76.01
66.38
60.32
34.97
1969
55.37
54.52
52.78
49.27
45.69
30.25
1970
37.82
37.26
35.77
32.7
30.76
20.35
1971
50.96
50.16
47.07
44.5
43.6
27.89
1972
87.75
86.23
83.22
75.86
72.3
42.64
1973
40.1
39.57
37.94
34.81
32.41
22.78
1974
31.01
30.55
29.16
27.37
27.17
19
1975
36.12
35.81
33.9
29.85
27.88
17.16
1976
122
120
113
105
98.21
50.73
1977
47.97
47.31
45.3
40.19
38.54
30.83
1978
106
104
96.81
87.36
83.81
46.93
1979
67.25
66.4
62.34
54.7
50.26
33.62
1980
37.54
37.01
35.28
32.22
31.21
22.03
1981
26.13
25.77
24.27
22.45
22.3
17.39
1982
86.59
85.07
81.68
72.2
68.05
37.94
1983
57.08
56.28
54.39
50.38
49.44
32.99
1984
96.51
95
89.08
78.18
78.22
46.59
1985
48.15
47.49
44.92
40.31
37.88
26.8
1986
27.12
26.71
25.41
23.37
21.58
16.68
1987
45.73
45.01
43.9
40.72
37.73
22.03
1988
23.46
23.13
21.83
19.66
19.78
14.45
1989
35.62
35.02
32.8
28.55
25.96
15.42
1990
19.29
19.02
17.94
16.34
15.31
10.34
Sorted
results
Prob.
Peak
96
hr
21
Day
60
Day
90
Day
Yearly
0.032258
122
120
113
105
98.21
50.73
0.064516
106
104
96.81
87.36
83.81
46.93
70
0.096774
103
101
95.74
83.25
78.22
46.59
0.129032
96.51
95
89.08
78.18
76.23
45.62
0.16129
91.73
90.25
84.53
77.33
73.65
42.64
0.193548
87.75
86.23
83.22
75.86
72.3
41.49
0.225806
86.59
85.07
81.68
72.2
68.05
37.94
0.258065
82.33
80.88
76.01
66.38
60.32
34.97
0.290323
72.51
71.31
66.86
58.88
54.2
34.64
0.322581
67.25
66.4
62.34
54.7
50.26
33.62
0.354839
57.18
56.28
54.39
50.38
49.44
32.99
0.387097
57.08
56.28
52.93
49.27
45.69
31.48
0.419355
55.37
54.52
52.78
48.2
45.02
30.83
0.451613
50.96
50.16
47.07
44.5
43.6
30.25
0.483871
48.15
47.49
45.3
40.72
38.54
27.89
0.516129
47.97
47.31
44.92
40.31
37.88
26.8
0.548387
45.73
45.01
43.9
40.19
37.73
23.93
0.580645
44.22
43.53
41.21
39.63
37.62
22.78
0.612903
41.33
40.87
38.61
36.3
33.46
22.03
0.645161
40.1
39.57
37.94
34.81
32.41
22.03
0.677419
37.82
37.26
35.77
32.7
31.21
20.35
0.709677
37.54
37.01
35.28
32.22
30.76
19
0.741935
36.12
35.81
33.9
29.85
27.88
18.43
0.774194
35.62
35.02
32.8
28.55
27.17
17.39
0.806452
31.01
30.55
29.16
27.37
25.96
17.16
0.83871
27.12
26.71
25.41
23.37
22.3
16.68
0.870968
26.13
25.77
24.27
22.45
21.58
15.42
0.903226
23.46
23.13
21.83
19.66
19.78
14.45
0.935484
19.29
19.02
17.94
16.34
15.31
10.34
0.967742
16.97
16.69
15.87
14
12.95
8.062
0.1
102.351
100.4
95.074
82.743
78.021
46.493
Average
of
yearly
averages:
28.1154
Inputs
generated
by
pe4.
pl
­
8­
August­
2003