UNITED
STATES
ENVIRONMENTAL
PROTECTION
AGENCY
WASHINGTON,
D.
C.
20460
OFFICE
OF
PREVENTION,
PESTICIDES
AND
TOXIC
SUBSTANCES
RE:
Revised
Drinking
Water
Assessment
for
DDVP
(
PC
Code
084001),
from
Naled
(
PC
Code34401),
and
from
Trichlorfon
(
PC
Code
057901);
DP
Barcode:
D288834
TO:
Eric
Olson
SRRD/
SRB
(
7508C)

Susan
Hummel
HED/
RB
IV
(
7509C)

From:
Ibrahim
Abdel­
Saheb,
Agronomist
Environmental
Fate
and
Effects
Division
Environmental
Risk
Branch
II
7507C
Peer
review:
Dana
Spatz,
Senior
Chemist
Environmental
Fate
and
Effects
Division
Environmental
Risk
Branch
II
7507C
THRU
:
Tom
Bailey,
Branch
Chief
Environmental
Risk
Branch
II
Environmental
Fate
and
Effects
Division
(
7507C)

DATE:
March
16,
2003
This
memo
reflects
revision
to
EFED
Drinking
water
assessment
for
DDVP
submitted
on
November
13,
2001
to
include
the
use
of
Tier
II
PRZM/
EXAMS
turf
scenario.
No
other
changes
to
the
DDVP
exposure
assessment
are
warranted
based
on
a
review
of
DDVP
use
as
an
active
ingredient
as
well
as
other
sources
of
DDVP.
If
you
have
any
question,
please
feel
free
to
contact
Ibrahim
Abdel­
Saheb
at
(
703)
305­
5463.
2
CONCLUSIONS:

The
Tier
II
screening
models
PRZM
and
EXAMS
with
the
Index
Reservoir
and
Percent
Crop
Area
adjustment
(
IR­
PCA
PRZM/
EXAMS)
were
used
to
determine
estimated
surface
water
concentrations
of
DDVP.
Modeling
results
are
shown
in
Table
1.

Table
1.
Estimated
environmental
concentrations
in
surface
for
DDVP,
DDVP
from
naled,
and
DDVP
from
trichlorfon
use
on
turf.

model
EECs
(
µ
g/
L)

Turf
DDVP
from
Naled
from
Trichchlorfon
Surface
water/
peak
(
90th
percentile
annual
daily
max.)
3.46
33.0
235
Surface
water/
90th
percentile
annual
mean)
0.17
1.83
6.24
Surface
water/
36­
year
overall
mean
0.085
0.89
3.15
use(
s)
modeled
4
applications
@
0.20
lb
ai/
acre,
spray
appl.
5
applications
@
1.87
lb
ai/
acre,
spray
appl.
3
applications
@
8.2
lb
ai/
acre,
spray
appl.

PCA
0.87
The
IR­
PCA
PRZM/
EXAMS
modeling
results
indicate
that
DDVP
has
the
potential
to
contaminate
surface
waters
by
spray
drift,
and
runoff
in
areas
with
large
amounts
of
annual
rainfall.

2,2­
Dichlorovinyl
dimethyl
phosphate
(
DDVP)
residues
can
be
present
as
a
result
of
use
of
three
pesticides:
dichlorvos
(
DDVP),
naled,
and
trichlorfon.
DDVP
is
a
degradate
of
naled
and
trichlorfon.
According
to
the
Quantitative
Usage
Analysis
(
QUA)
for
DDVP,
use
of
DDVP
on
lawns
and
turf
is
estimated
to
be
less
than
6,000
lb
ai
per
year
(
Source:
J.
Faulkner,
BEAD;
combined
total
for
recreational
and
residential
sites
is
6,000
lb
ai
per
year)
3.
For
the
use
of
trichlorfon
on
turf,
the
estimate
is
significantly
higher,
500,000
to
1,000,000
lb
ai/
yr6.
Naled
is
used
primarily
on
agricultural
crops.
The
United
States
Geological
Survey
estimates
the
use
of
naled
on
various
crops
at
approximately
254,000
lb
ai/
yr5.
Based
on
this
information,
it
is
evident
that
the
major
3
sources
of
DDVP
in
the
environment
are
use
of
naled
and
trichlorfon.
This
assessment
discusses
the
potential
for
DDVP
to
contaminate
water
from
the
use
of
these
three
sources
of
DDVP.

Screening
models
were
used
to
determine
estimated
concentrations
of
DDVP
in
surface
water.
Although
these
estimates
are
only
for
DDVP,
there
are
several
DDVP
degradates
that
have
been
identified
including
desmethyl
DDVP
(
Methyl
O­(
2,2­
dichlorovinyl)
phosphate),
dichlorethanol,
and
dichloroacetic
acid;
this
later
degradate
is
very
mobile.
Concentrations
of
these
compounds
were
calculated
based
on
a
maximum
annual
application
rate
of
1.87
lb
a.
i/
acre
for
naled,
8.2
lb
a.
i./
acre
for
trichlorfon
(
turf),
and
0.2
lb
a.
i./
acre
for
DDVP.
The
maximum
amount
of
DDVP
formed
from
naled
is
approximately
20
percent
of
the
amount
of
naled
originally
applied.
Therefore,
a
conservative
DDVP
use
rate
was
selected
as
naled's
use
rate
multiplied
by
0.20.
The
application
rate
for
DDVP
formed
from
trichlorfon
was
estimated
by
assuming
100%
conversion
adjusted
for
differences
in
molecular
weight
(
MW).

The
Tier
II
screening
models
PRZM
and
EXAMS
with
the
Index
Reservoir
and
Percent
Crop
Area
adjustment
(
IR­
PCA
PRZM/
EXAMS)
were
used
to
determine
estimated
surface
water
concentrations
of
DDVP,
from
naled,
DDVP,
and
trichlorfon.
The
modeling
results
indicate
that
all
these
compounds
have
the
potential
to
contaminate
surface
waters
by
runoff,
for
short
periods
of
time
especially
in
areas
with
large
amounts
of
annual
rainfall.
However,
based
on
its
environmental
fate
characteristics,
naled
will
degrade/
dissipate
rapidly
(
t1/
2
<
1
day),
trichlorfon
and
DDVP
will
persist
slightly
longer
(
t1/
2
1.4
and
­

5
days,
respectively).
Mitigation
practices
that
reduce
runoff
could
be
effective
in
reduction
of
these
chemicals
transport
into
surface
waters.

DDVP
may
reach
surface
water
as
a
result
of
use
of
three
pesticides:
dichlorvos
(
DDVP),
naled
and
trichlorfon.
In
the
event
that
all
of
these
pesticides
are
used
in
the
same
use
area,
then
the
contribution
for
each
chemical
should
be
incorporated
in
any
risk
assessment.

ENVIRONMENTAL
FATE:

A
major
route
of
dissipation
is
volatilization
(
vapor
pressure
=
1.2
X
10­
2
mmHg).
DDVP
also
appears
to
degrade
through
aerobic
soil
metabolism
and
abiotic
hydrolysis
as
well,
but
is
secondary
to
volatilization.
Hydrolysis
is
pH
dependant
where
the
half­
lives
were
11
days
at
pH
5,
5
days
at
pH
7
and
21
hours
at
pH
9.
The
major
degradates
were
2,2­
dichloroacetic
acid
(
DCA),
2,2­
dichloroacetaldehyde
(
DAA),
desmethyl
DDVP,
and
glyoxylic
acid.
4
Aerobic
soil
metabolism
data
showed
a
half­
life
of
10
hours
with
the
major
metabolite
being
2,2­
dichloroacetic
acid
(
62.8%
of
applied
at
48
hours).
Other
metabolites
present
at
less
than
12%
of
applied
were
2,2­
dichloroacetaldehyde,
and
dichloroethanol.
Extensive
mineralization
took
place
as
CO2
accounted
for
60%
of
applied
at
360
hours
post­
treatment.
Due
to
rapid
degradation
of
DDVP
leaching/
adsorption/
desorption
data
were
declared
supplemental
due
to
the
inability
to
establish
a
soil/
solution
phase
equilibrium.
However,
a
soil
TLC
study
(
MRID
41354105)
indicates
that
DDVP
is
moderately
mobile
(
Kd's
ranging
0.3
to
1.2)
based
on
the
Heiling
and
Turner's
mobility
classification.
The
potential
of
DDVP
to
leach
to
ground
water
is
mitigated
by
its
rapid
degradation.
However,
DDVP
does
have
the
potential
to
contaminate
surface
waters
because
of
a
low
Koc
value
and
high
water
solubility
(
10
X
103
ppm).
Substantial
fractions
of
run­
off
will
more
than
likely
occur
via
dissolution
in
run­
off
water
rather
than
adsorption
to
eroding
soil.
DDVP
should
not
be
persistent
in
any
surface
waters
due
to
its
susceptibility
to
rapid
hydrolysis.
Chemical
hydrolysis
and
biodegradation
are
the
major
processes
involved
in
the
transformation
of
naled
and
its
degradates
in
the
environment.
While
direct
photolysis
in
water
is
not
a
major
degradative
pathway
for
naled,
indirect
photolysis
in
the
presence
of
photosensitizer
may
play
an
important
role
in
the
photodegradation
of
naled
in
aqueous
media
and
soils.
The
degradate
DDVP
does
not
form
under
abiotic
hydrolysis
nor
by
direct
photolysis
in
water,
but
forms
by
indirect
photolysis
in
water
and
soils.
In
the
presence
of
photosensitizer
in
water,
as
much
as
20%
of
the
applied
dose
of
naled
can
be
found
as
DDVP
after
1
day,
with
rapid
decline
of
DDVP
residues
afterwards.
Under
aerobic
conditions,
naled
mineralizes
rapidly
to
CO2
and
degrades
to
dichloroacetic
acid
and
dichloroethanol,
but
DDVP
is
not
detected.
This
is
likely
to
be
the
result
of
the
rapid
degradation
and
mineralization
of
any
DDVP
that
may
form
from
naled.
However,
under
anaerobic
aquatic
conditions,
DDVP
can
be
as
high
as
15%
of
the
applied
naled
dose
after
1
day.
The
degradation
of
dichlorvos,
once
formed,
was
slower
than
that
of
parent
naled.
During
the
first
1­
2
days
after
application
of
naled,
the
half­
life
of
dichlorvos
was
about
0.9
days.

DDVP
is
formed
from
trichlorfon
in
both
soil
and
water
by
aerobic
soil
metabolism
and
hydrolysis.
Environmental
fate
data
indicate
that
trichlorfon
degrades
rapidly
in
aerobic
soil
(
t1/
2
­

1.8
days)
under
non­
sterile
conditions;
however,
in
a
sterile
soil,
trichlorfon
was
stable
(
t1/
2
>
40
days).
Abiotic
hydrolysis
studies
indicate
that
trichlorfon
degrades
rapidly
in
aqueous
media
and
that
the
rate
of
hydrolysis
is
pH
dependent.
The
estimated
hydrolysis
half­
life
of
trichlorfon
is
31
minutes
at
pH
7,
and
34
hours
at
pH
9,
and
104
days
at
pH
5.
This
indicates
the
stability
of
trichlorfon
to
hydrolysis
under
acidic
conditions.
The
maximum
5
amount
of
DDVP
formed
from
trichlorfon
by
aerobic
aquatic
metabolism
is
approximately
56
percent
of
the
amount
of
trichlorfon
originally
applied
at
pH
8.5.

Surface
Water:

The
EFED
has
limited
monitoring
data
on
the
concentrations
of
DDVP
in
surface
water
at
the
present
time.

The
US
Geological
Survey
(
USGS)
National
Water
Quality
Assessment
Program
(
NAWQA)
collected
surface
water
samples
in
New
York
and
Indiana
during
June,
2001.
DDVP
was
detected
with
a
maximum
concentration
of
0.01180
ppb7.

The
frequency
of
sampling
and
the
length
of
sampling
period
of
both
of
the
USGS
studies
were
not
sufficient
to
represent
the
temporal
and
spatial
requirements
for
use
in
making
regulatory
determinations
concerning
drinking
water.

Tier
II
surface
water
modeling
was
done
using
the
Index
Reservoir
(
IR)
and
Percent
Crop
Area
(
PCA)
modifications
to
PRZM
and
EXAMS.

The
maximum
amount
of
DDVP
formed
from
naled
is
approximately
20%
of
the
applied
naled.
Therefore,
a
conservative
DDVP
use
rate
was
selected
as
naled's
use
rate
multiplied
by
0.20.

The
application
rate
used
on
turf
for
trichlorfon
based
on
100
percent
conversion
to
DDVP
adjusted
for
differences
in
MW.

Table
2
shows
the
input
parameter
values
used
in
PRZM/
EXAMS.

Table
2.
Input
parameters
for
DDVP,
DDVP
from
naled,
and
DDVP
from
trichlorfon
used
in
PRZM/
EXAMS
models.

Chemical
From
Naled
From
Trichlorfon
DDVP
PC
Code
for
parent
chemical
34401
57901
84001
Molecular
weight
(
g/
mole)
220.9
220.9
220.9
Solubility
(
ppm)
10000
10000
10000
Hydrolysis
half­
life,
pH
7
(
days)
5.2
5.2
5.2
Soil
Photolysis
half­
life
(
days)
0.65
0.65
0.65
Aerobic
Soil
Metabolism
half­
life
(
days)
0.42
0.42
0.42
Aerobic
Aquatic
Metabolism
half­
life
(
days)
no
data
no
data
no
data
Soil
Organic
Carbon
Partitioning
(
K
oc
)(
l/
kg)
37
37
37
6
Use
Turf
Turf
Turf
Application
Rate
(
lb
a.
i.
/
acr/
yr)
1.87
8.2
0.20
Number
Of
Applications/
year
5
3
4
Interval
between
appl.
(
day)
30
7
30
Application
Method
Spray
Spray
Spray
Assumptions
and
Uncertainties11,12
Index
Reservoir
The
results
from
the
index
reservoir
represent
potential
drinking
water
exposure
from
a
specific
area
(
Illinois)
with
specific
cropping
patterns,
weather,
soils,
and
other
factors.
Use
of
the
index
reservoir
for
areas
with
different
climates,
crops,
pesticides
used,
sources
of
water
(
e.
g.
rivers
instead
of
reservoirs,
etc),
and
hydrogeology
creates
uncertainties.
In
general,
because
the
index
reservoir
represents
a
fairly
vulnerable
watershed,
the
exposure
estimated
with
the
index
reservoir
will
likely
be
higher
than
the
actual
exposure
for
most
drinking
water
sources.
However,
the
index
reservoir
is
not
a
worst
case
scenario,
communities
that
derive
their
drinking
water
from
smaller
bodies
of
water
with
minimal
outflow,
or
with
more
runoff
prone
soils
would
likely
get
higher
drinking
water
exposure
than
estimated
using
the
index
reservoir.
Areas
with
a
more
humid
climate
that
use
a
similar
reservoir
and
cropping
patterns
may
also
get
more
pesticides
in
their
drinking
water
than
predicted
using
this
scenario.

A
single
steady
flow
has
been
used
to
represent
the
flow
through
the
reservoir.
Discharge
from
the
reservoir
also
removes
chemical
so
this
assumption
will
underestimate
removal
from
the
reservoir
during
wet
periods
and
overestimates
removal
during
dry
periods.
This
assumption
can
underestimate
or
overestimate
the
concentration
in
the
pond
depending
upon
the
annual
precipitation
pattern
at
the
site.

The
index
reservoir
scenario
uses
the
characteristics
of
a
single
soil
to
represent
the
soil
in
the
basin.
In
fact,
soils
can
vary
substantially
across
even
small
areas,
and
this
variation
is
not
reflected
in
these
simulations.

The
index
reservoir
scenario
does
not
consider
tile
drainage.
Areas
that
are
prone
to
substantial
runoff
are
often
tile
drained.
Tile
drainage
contributes
additional
water
and
in
some
cases,
additional
pesticide
loading
to
the
reservoir.
This
may
cause
either
an
increase
or
decrease
in
the
pesticide
concentration
in
the
reservoir.
Tile
drainage
also
causes
the
surface
soil
to
dry
7
out
faster.
This
will
reduce
runoff
of
the
pesticide
into
the
reservoir.
The
watershed
used
as
the
model
for
the
index
reservoir
(
Shipman
City
Lake)
does
not
have
tile
drainage
in
the
cropped
areas.

EXAMS
is
unable
to
easily
model
spring
and
fall
turnover.
Turnover
occurs
when
the
temperature
drops
in
the
fall
and
the
thermal
stratification
of
the
reservoir
is
removed.
Turnover
occurs
again
in
the
spring
when
the
reservoir
warms
up.
This
results
in
complete
mixing
of
the
chemical
through
the
water
column
at
these
times.
Because
of
this
inability,
the
Index
Reservoir
has
been
simulated
without
stratification.
There
is
data
to
suggest
that
Shipman
City
Lake,
upon
which
the
Index
Reservoir
is
based,
does
indeed
stratify
in
the
deepest
parts
of
the
lake
at
least
in
some
years.
This
may
result
in
over
or
underestimation
of
the
concentration
in
drinking
water
depending
upon
the
time
of
the
year
and
the
depth
the
drinking
water
intake
is
drawing
from.

Percent
Crop
Area
Correction
Factor
The
PCA
is
a
watershed­
based
modification.
Implicit
in
its
application
is
the
assumption
that
currently­
used
field­
scale
models
reflect
basin­
scale
processes
consistently
for
all
pesticides
and
uses.
In
other
words,
we
assume
that
the
field
scale
processes
simulated
by
the
coupled
PRZM
and
EXAMS
models
are
a
reasonable
approximation
of
pesticide
fate
and
transport
within
a
watershed
that
contains
a
drinking
water
reservoir.
If
the
models
fail
to
capture
pertinent
basin­
scale
fate
and
transport
processes
consistently
for
all
pesticides
and
all
uses,
the
application
of
a
factor
that
reduces
the
estimated
concentrations
predicted
by
modeling
could,
in
some
instances,
result
in
inadvertently
passing
a
chemical
through
the
screen
that
may
actually
pose
a
risk.
Some
preliminary
assessments
made
in
the
development
of
the
PCA
suggest
that
PRZM/
EXAMS
may
not
be
realistically
capturing
basin­
scale
processes
for
all
pesticides
or
for
all
uses.
A
preliminary
survey
of
water
assessments
which
compared
screening
model
estimates
to
readily
available
monitoring
data
suggest
uneven
model
results.
In
some
instances,
the
screening
model
estimates
are
more
than
an
order
of
magnitude
greater
than
the
highest
concentrations
reported
in
available
monitoring
data;
in
other
instances,
the
model
estimates
are
less
than
monitoring
concentrations.
Because
of
these
concerns,
the
SAP
recommended
using
the
PCA
only
for
"
major"
crops
in
the
Midwest.
For
other
crops,
development
of
PCA's
will
depend
on
the
availability
of
relevant
monitoring
data
that
could
be
used
to
evaluate
the
result
of
the
PCA
adjustment.

The
spatial
data
used
for
the
PCA
came
from
readily­
available
sources
and
have
a
number
of
inherent
limitations:
8
°
The
size
of
the
8­
digit
HUC
[
mean
=
366,989
ha;
range
=
6.7­
2,282,081
ha;
n
=
2,111]
may
not
provide
reasonable
estimates
of
actual
PCA's
for
smaller
watersheds.
The
watersheds
that
drain
into
drinking
water
reservoirs
are
generally
smaller
than
the
8­
digit
HUC
and
may
be
better
represented
by
watersheds
defined
for
drinking
water
intakes.
°
The
conversion
of
the
county
level
data
to
watershed­
based
percent
crop
areas
assumes
the
distribution
of
the
crops
within
a
county
is
uniform
and
homogeneous
throughout
the
county
area.
Distance
between
the
treated
fields
and
the
water
body
is
not
addressed.
°
The
PCA's
were
generated
using
data
from
the
1992
Census
of
Agriculture.
However,
recent
changes
in
the
agriculture
sector
from
farm
bill
legislation
may
significantly
impact
the
distribution
of
crops
throughout
the
country.
The
methods
described
in
this
report
can
rapidly
be
updated
as
more
current
agricultural
crops
data
are
obtained.
The
assumption
that
yearly
changes
in
cropping
patterns
will
cause
minimal
impact
needs
to
be
evaluated.

The
PCA
adjustment
is
only
applicable
to
pesticides
applied
to
agricultural
crops.
Contributions
to
surface
waters
from
nonagricultural
uses
such
as
urban
environments
are
not
well­
modeled.
Currently,
non­
agricultural
uses
are
not
included
in
the
screening
model
assessments
for
drinking
water.

The
PCA
does
not
consider
percent
crop
treated
because
detailed
pesticide
usage
data
are
extremely
limited
at
this
time.
Detailed
pesticide
usage
data
are
currently
available
for
only
a
few
states.

REFERENCES
9
1.
Carsel,
R.
F.,
J.
C.
Imhoff,
P.
R.
Hummel,
J.
M.
Cheplick
and
J.
S.
Donigian,
Jr.
1997.
PRZM­
3,
A
Model
for
Predicting
Pesticide
and
Nitrogen
Fate
in
Crop
Root
and
Unsaturated
Soil
Zones:
Users
Manual
for
Release
3.0;
Environmental
Research
Laboratory,
Office
of
Research
and
Development,
U.
S.
Environmental
Protection
Agency,
Athens,
GA.

2.
Burns,
L.
A.
March
1997.
Exposure
Analysis
Modeling
System
(
EXAMSII)
Users
Guide
for
Version
2.97.5,
Environmental
Research
Laboratory,
Office
of
Research
and
Development,
U.
S.
Environmental
Protection
Agency,
Athens,
GA.
i
3.
U.
S.
EPA.
1998.
Quantitative
Usage
Analysis
(
AUQ)/
Dichlorvos.
Case
No.
310,
AI
No.
8400.
Analyst:
John
Faulkner.
March
30,
1998.

4.
U.
S.
EPA.
1997.
Reregistration
Eligibility
Decision
(
RED):
Trichlorfon.
Office
of
Prevention,
Pesticides,
and
Toxic
Substances,
EPA
738­
R­
96­
017.

5.
U.
S
GS.
1992.
National
Water
Quality
Assessment
(
NWQA),
Pesticides
National
Synthesis
Project,
Annual
Use:
Naled.

6.
U.
S
GS.
1992.
National
Water
Quality
Assessment
(
NWQA),
Pesticides
National
Synthesis
Project,
Annual
Use:
Trichlorfon.

7.
U.
S
GS.
1992.
National
Water
Quality
Assessment
(
NWQA),
NWQA
Data
Warehouse
[
Online].
Available
at
http://
orxddwimdn.
er.
usgs.
gov/
servlet/
page?_
pageid=
1713,1721
&_
dad=
portal30&_
schema=
PORTAL30&
2862_
RETRIEVE_
DATA_
2533437.
p
_
subid=
8543&
2862_
RETRIEVE_
DATA_
2533437.
p_
sub_
siteid=
47&
2862_
RETRIEVE_
DATA_
2533437.
p_
edit=
0
(
verified
16
March.
2003).
10
APPENDIX
I
IR­
PCA
PRZM/
EXAMS
INPUT
FILE
FOR
THE
USE
OF
DDVP
ON
TURF
IN
FLORIDA
stored
as
DDVP.
out
Chemical:
DDVP
PRZM
environment:
FLturfC.
txt
modified
Satday,
12
October
EXAMS
environment:
ir298.
exv
modified
Thuday,
29
August
Metfile:
w12834.
dvf
modified
Wedday,
3
July
2002
Water
segment
concentrations
(
ppb)

Year
Peak
96hr
21Day
60Day
90Day
Yearly
1961
0.5419
0.42
0.1874
0.1424
0.1384
0.05007
1962
0.6501
0.5039
0.3133
0.2088
0.1899
0.06483
1963
0.6673
0.5172
0.2455
0.1746
0.1757
0.06085
1964
2.338
1.852
0.8265
0.4351
0.3441
0.1143
1965
1.463
1.134
0.489
0.2449
0.2059
0.0687
1966
0.5369
0.4161
0.2434
0.1576
0.1478
0.05318
1967
1.556
1.206
0.6095
0.3117
0.2599
0.097
1968
0.8035
0.6227
0.3013
0.1992
0.179
0.0632
1969
2.57
2.025
0.9346
0.4397
0.496
0.1643
1970
0.7637
0.5919
0.2553
0.1597
0.1491
0.05541
1971
0.8706
0.6747
0.3895
0.2756
0.2296
0.08099
1972
6.976
5.672
2.474
1.027
0.7322
0.2172
1973
0.6245
0.5065
0.2773
0.2028
0.1793
0.06247
1974
1.582
1.226
0.5877
0.303
0.2447
0.08037
1975
1.721
1.414
0.7183
0.3622
0.2842
0.092
1976
0.5968
0.4625
0.2888
0.2077
0.1848
0.067
1977
0.8266
0.6406
0.3401
0.2047
0.2029
0.07089
1978
4.081
3.163
1.441
0.6713
0.5156
0.1521
1979
3.093
2.531
1.172
0.8127
0.6561
0.1966
1980
0.5259
0.4076
0.1831
0.1328
0.1312
0.04795
1981
1.084
0.8993
0.4728
0.2526
0.2114
0.0719
1982
0.5465
0.4737
0.2236
0.1522
0.1504
0.05275
1983
2.775
2.212
0.9604
0.4948
0.4113
0.1884
1984
0.9393
0.728
0.4667
0.2395
0.2425
0.08847
1985
1.869
1.449
0.6589
0.3146
0.2569
0.08203
1986
1.375
1.065
0.5317
0.2955
0.245
0.07955
1987
1.1
0.8775
0.4551
0.2769
0.2687
0.08836
1988
1.272
1.04
0.6277
0.2994
0.2492
0.08707
1989
10.54
8.166
3.567
1.429
1.008
0.287
1990
0.5304
0.4111
0.2035
0.1409
0.1366
0.05031
Sorted
results
Prob.
Peak
96hr
21Day
60Day
90Day
Yearly
0.032258
10.54
8.166
3.567
1.429
1.008
0.287
11
0.064516
6.976
5.672
2.474
1.027
0.7322
0.2172
0.096774
4.081
3.163
1.441
0.8127
0.6561
0.1966
0.129032
3.093
2.531
1.172
0.6713
0.5156
0.1884
0.16129
2.775
2.212
0.9604
0.4948
0.496
0.1643
0.193548
2.57
2.025
0.9346
0.4397
0.4113
0.1521
0.225806
2.338
1.852
0.8265
0.4351
0.3441
0.1143
0.258065
1.869
1.449
0.7183
0.3622
0.2842
0.097
0.290323
1.721
1.414
0.6589
0.3146
0.2687
0.092
0.322581
1.582
1.226
0.6277
0.3117
0.2599
0.08847
0.354839
1.556
1.206
0.6095
0.303
0.2569
0.08836
0.387097
1.463
1.134
0.5877
0.2994
0.2492
0.08707
0.419355
1.375
1.065
0.5317
0.2955
0.245
0.08203
0.451613
1.272
1.04
0.489
0.2769
0.2447
0.08099
0.483871
1.1
0.8993
0.4728
0.2756
0.2425
0.08037
0.516129
1.084
0.8775
0.4667
0.2526
0.2296
0.07955
0.548387
0.9393
0.728
0.4551
0.2449
0.2114
0.0719
0.580645
0.8706
0.6747
0.3895
0.2395
0.2059
0.07089
0.612903
0.8266
0.6406
0.3401
0.2088
0.2029
0.0687
0.645161
0.8035
0.6227
0.3133
0.2077
0.1899
0.067
0.677419
0.7637
0.5919
0.3013
0.2047
0.1848
0.06483
0.709677
0.6673
0.5172
0.2888
0.2028
0.1793
0.0632
0.741935
0.6501
0.5065
0.2773
0.1992
0.179
0.06247
0.774194
0.6245
0.5039
0.2553
0.1746
0.1757
0.06085
0.806452
0.5968
0.4737
0.2455
0.1597
0.1504
0.05541
0.83871
0.5465
0.4625
0.2434
0.1576
0.1491
0.05318
0.870968
0.5419
0.42
0.2236
0.1522
0.1478
0.05275
0.903226
0.5369
0.4161
0.2035
0.1424
0.1384
0.05031
0.935484
0.5304
0.4111
0.1874
0.1409
0.1366
0.05007
0.967742
0.5259
0.4076
0.1831
0.1328
0.1312
0.04795
0.1
3.9822
3.0998
1.4141
0.79856
0.64205
0.19578
Average
of
yearly
averages:
0.097842
Inputs
generaged
by
pe3.
pl
1.2
­
15­
Oct­
02
IR­
PCA
PRZM/
EXAMS
INPUT
FILE
FOR
THE
USE
OF
DDVP
(
FROM
12
NALED)
ON
TURF
IN
FLORIDA
stored
as
naled.
out
Chemical:
DDVP
PRZM
environment:
FLturfC.
txt
modified
Satday,
12
October
EXAMS
environment:
ir298.
exv
modified
Thuday,
29
August
Metfile:
w12834.
dvf
modified
Wedday,
3
July
2002
Water
segment
concentrations
(
ppb)

Year
Peak
96hr
21Day
60Day
90Day
Yearly
1961
5.156
3.969
1.746
1.324
1.285
0.5146
1962
6.149
4.734
2.92
1.94
1.765
0.708
1963
6.342
4.882
2.292
1.624
1.632
0.6687
1964
22.26
17.51
7.737
4.043
3.198
1.164
1965
13.95
10.74
4.561
2.275
1.913
0.7444
1966
5.105
3.931
2.273
1.464
1.373
0.5992
1967
14.81
11.4
5.689
2.896
2.417
1.01
1968
7.67
5.904
2.816
1.854
1.664
0.6929
1969
24.49
19.16
8.744
4.085
4.625
1.639
1970
7.281
5.605
2.38
1.484
1.386
0.6288
1971
8.258
6.358
3.644
2.565
2.134
0.8579
1972
66.53
53.74
23.07
9.541
6.805
2.124
1973
5.946
4.805
2.587
1.887
1.667
0.6868
1974
15.06
11.59
5.504
2.816
2.274
0.8529
1975
16.39
13.38
6.707
3.366
2.641
0.96
1976
5.659
4.357
2.695
1.932
1.717
0.7291
1977
7.848
6.042
3.178
1.903
1.889
0.7759
1978
38.9
29.95
13.45
6.237
5.066
1.664
1979
29.37
23.95
10.94
7.555
6.1
2.127
1980
5.009
3.856
1.71
1.234
1.219
0.551
1981
10.27
8.492
4.426
2.348
1.964
0.7827
1982
5.18
4.486
2.085
1.414
1.398
0.5984
1983
26.44
20.94
9.958
4.604
3.971
1.889
1984
8.873
6.831
4.356
2.229
2.258
0.9578
1985
17.82
13.72
6.155
2.925
2.388
0.8669
1986
13.06
10.06
4.971
2.748
2.277
0.8559
1987
10.43
8.27
4.245
2.573
2.498
0.925
1988
12.09
9.852
5.86
2.787
2.316
0.9111
1989
101
77.39
33.29
13.28
9.362
2.758
1990
5.049
3.887
1.898
1.309
1.269
0.5777
Sorted
results
Prob.
Peak
96hr
21Day
60Day
90Day
Yearly
0.032258
101
77.39
33.29
13.28
9.362
2.758
0.064516
66.53
53.74
23.07
9.541
6.805
2.127
0.096774
38.9
29.95
13.45
7.555
6.1
2.124
0.129032
29.37
23.95
10.94
6.237
5.066
1.889
0.16129
26.44
20.94
9.958
4.604
4.625
1.664
13
0.193548
24.49
19.16
8.744
4.085
3.971
1.639
0.225806
22.26
17.51
7.737
4.043
3.198
1.164
0.258065
17.82
13.72
6.707
3.366
2.641
1.01
0.290323
16.39
13.38
6.155
2.925
2.498
0.96
0.322581
15.06
11.59
5.86
2.896
2.417
0.9578
0.354839
14.81
11.4
5.689
2.816
2.388
0.925
0.387097
13.95
10.74
5.504
2.787
2.316
0.9111
0.419355
13.06
10.06
4.971
2.748
2.277
0.8669
0.451613
12.09
9.852
4.561
2.573
2.274
0.8579
0.483871
10.43
8.492
4.426
2.565
2.258
0.8559
0.516129
10.27
8.27
4.356
2.348
2.134
0.8529
0.548387
8.873
6.831
4.245
2.275
1.964
0.7827
0.580645
8.258
6.358
3.644
2.229
1.913
0.7759
0.612903
7.848
6.042
3.178
1.94
1.889
0.7444
0.645161
7.67
5.904
2.92
1.932
1.765
0.7291
0.677419
7.281
5.605
2.816
1.903
1.717
0.708
0.709677
6.342
4.882
2.695
1.887
1.667
0.6929
0.741935
6.149
4.805
2.587
1.854
1.664
0.6868
0.774194
5.946
4.734
2.38
1.624
1.632
0.6687
0.806452
5.659
4.486
2.292
1.484
1.398
0.6288
0.83871
5.18
4.357
2.273
1.464
1.386
0.5992
0.870968
5.156
3.969
2.085
1.414
1.373
0.5984
0.903226
5.105
3.931
1.898
1.324
1.285
0.5777
0.935484
5.049
3.887
1.746
1.309
1.269
0.551
0.967742
5.009
3.856
1.71
1.234
1.219
0.5146
0.1
37.947
29.35
13.199
7.4232
5.9966
2.1005
Average
of
yearly
averages:
1.027357
Inputs
generaged
by
pe3.
pl
1.2
­
15­
Oct­
02
14
IR­
PCA
PRZM/
EXAMS
INPUT
FILE
FOR
THE
USE
OF
DDVP
(
FROM
TRICHLORFON)
ON
TURF
IN
FLORIDA
stored
as
trichrfn.
out
Chemical:
DDVP
PRZM
environment:
FLturfC.
txt
modified
Satday,
12
October
EXAMS
environment:
ir298.
exv
modified
Thuday,
29
August
Metfile:
w12834.
dvf
modified
Wedday,
3
July
2002
Water
segment
concentrations
(
ppb)

Year
Peak
96hr
21Day
60Day
90Day
Yearly
1961
27.95
21.55
16.63
8.07
5.388
1.577
1962
161
132
59.48
27.9
18.66
5.324
1963
36.21
28.24
18.73
10.43
6.976
2.015
1964
492
387
171
66.41
44.34
13.95
1965
27.95
21.51
15.32
7.419
4.959
1.354
1966
27.95
21.51
15.32
6.791
4.533
1.258
1967
320
246
105
41.99
28.04
7.336
1968
57.61
46
26.17
12.13
8.099
2.267
1969
270
208
88.4
38.12
25.53
7.202
1970
27.95
21.51
15.32
6.86
4.582
1.252
1971
172
133
63.23
26.65
17.84
4.898
1972
27.95
21.51
15.32
7.013
5.412
1.475
1973
187
144
61.42
26.6
17.76
4.724
1974
171
132
70.55
33.67
22.51
6.233
1975
255
207
89.19
36.28
24.23
6.872
1976
267
205
87.16
35.52
23.72
6.088
1977
37.68
29.01
21.2
9.42
6.295
1.778
1978
33.72
25.96
19.69
11.71
7.98
2.214
1979
64.19
51.79
33.25
14.9
9.945
2.988
1980
29.71
22.87
16.15
7.02
4.685
1.311
1981
126
104
54.41
22.07
14.73
4.281
1982
27.95
21.51
15.32
7.102
4.743
1.31
1983
87.56
69.42
41.14
17.39
11.6
3.399
1984
103
82.02
43.09
24.39
16.33
4.648
1985
71.32
55.26
40.54
19.25
12.85
3.871
1986
58.63
45.14
25.9
13.35
8.939
2.405
1987
37.85
29.14
21.11
9.458
6.368
1.805
1988
57.48
44.25
26.9
11.72
7.841
2.245
1989
27.95
21.51
15.32
7.479
5.017
1.403
1990
27.95
21.51
15.32
6.86
4.587
1.242
Sorted
results
Prob.
Peak
96hr
21Day
60Day
90Day
Yearly
0.03225806
492
387
171
66.41
44.34
13.95
0.06451613
320
246
105
41.99
28.04
7.336
0.09677419
270
208
89.19
38.12
25.53
7.202
15
0.12903226
267
207
88.4
36.28
24.23
6.872
0.16129032
255
205
87.16
35.52
23.72
6.233
0.19354839
187
144
70.55
33.67
22.51
6.088
0.22580645
172
133
63.23
27.9
18.66
5.324
0.25806452
171
132
61.42
26.65
17.84
4.898
0.29032258
161
132
59.48
26.6
17.76
4.724
0.32258065
126
104
54.41
24.39
16.33
4.648
0.35483871
103
82.02
43.09
22.07
14.73
4.281
0.38709677
87.56
69.42
41.14
19.25
12.85
3.871
0.41935484
71.32
55.26
40.54
17.39
11.6
3.399
0.4516129
64.19
51.79
33.25
14.9
9.945
2.988
0.48387097
58.63
46
26.9
13.35
8.939
2.405
0.51612903
57.61
45.14
26.17
12.13
8.099
2.267
0.5483871
57.48
44.25
25.9
11.72
7.98
2.245
0.58064516
37.85
29.14
21.2
11.71
7.841
2.214
0.61290323
37.68
29.01
21.11
10.43
6.976
2.015
0.64516129
36.21
28.24
19.69
9.458
6.368
1.805
0.67741935
33.72
25.96
18.73
9.42
6.295
1.778
0.70967742
29.71
22.87
16.63
8.07
5.412
1.577
0.74193548
27.95
21.55
16.15
7.479
5.388
1.475
0.77419355
27.95
21.51
15.32
7.419
5.017
1.403
0.80645161
27.95
21.51
15.32
7.102
4.959
1.354
0.83870968
27.95
21.51
15.32
7.02
4.743
1.311
0.87096774
27.95
21.51
15.32
7.013
4.685
1.31
0.90322581
27.95
21.51
15.32
6.86
4.587
1.258
0.93548387
27.95
21.51
15.32
6.86
4.582
1.252
0.96774194
27.95
21.51
15.32
6.791
4.533
1.242
0.1
269.7
207.9
89.111
37.936
25.4
7.169
Average
of
yearly
averages:
3.624167
Inputs
generaged
by
pe3.
pl
1.2
­
15­
Oct­
02
