UNITED
STATES
ENVIRONMENTAL
PROTECTION
AGENCY
WASHINGTON
D.
C.,
20460
OFFICE
OF
PREVENTION,
PESTICIDES
AND
TOXIC
SUBSTANCES
March
22,
2006
DP
Barcode:
D292331
PC
Code:
121601
MEMORANDUM
Subject:
Revised
Drinking
Water
Exposure
Assessment
for
Acetochlor
To:
Felecia
Fort,
Chemical
Review
Manager
Reregistration
Branch
3
(
RB3)
Special
Review
and
Reregistration
Division
(
7508C)

Donald
Stubbs,
Chief
Herbicide
Branch
Registration
Division
(
7505C)

From:
Michael
R.
Barrett,
Ph.
D.,
Senior
Chemist
Ronald
Parker,
Ph.
D.,
Senior
Environmental
Engineer
Environmental
Risk
Branch
V
Environmental
Fate
and
Effects
Division
(
7507C)

Through:
Mah
Shamim,
Ph.
D.,
Chief
Environmental
Risk
Branch
V
Environmental
Fate
and
Effects
Division
(
7507C)

Steven
P.
Bradbury,
Ph.
D.
Director
Environmental
Fate
and
Effects
Division
(
7507C)

Attached
is
the
revised
drinking
water
exposure
assessment
for
acetochlor.
It
has
been
updated
to
include
the
EFED
response
to
comments
from
the
Acetochlor
Registration
Partnership
(
ARP).

Emphasis
in
this
assessment
is
placed
on
acetochlor
parent
because
of
its
important
in
the
dietary
risk
assessment;
however,
data
on
exposure
to
acetochlor
degradates
are
also
reviewed
in
this
assessment.
Note
that
this
assessment
covers
only
the
one
major
field
use
site
(
corn
for
grain
or
forage)
that
is
currently
registered;
registration
applications
for
other
major
field
uses
of
acetochlor
are
pending;
additional
field
uses
for
acetochlor
will
require
significant
additions
and
revisions
to
the
exposure
assessment.
­
2­
[
This
page
left
intentionally
blank]
­
3­

Table
of
Contents
1.
List
of
Tables
......................................................................................................................
6
2.
Table
of
Figures
..................................................................................................................
8
3.
Abbreviations....................................................................................................................
10
4.
Executive
Summary
..........................................................................................................
11
4.1.
Purpose..............................................................................................................
11
4.2.
Acetochlor
Usage,
Monitoring
Locations,
and
the
Exposure
Assessment
...........
11
4.3.
Time
Weighted
Annualized
Means
and
95th
Percentile
Calculations
..................
12
4.4.
Mitigation/
Cancellation
Endpoints.....................................................................
12
4.4.1.
ARP
Surface
Water
Monitoring
Endpoints
.............................................
12
4.4.2.
ARP
Ground
Water
Monitoring
Endpoints
 
PGW
Study.......................
13
4.4.3.
ARP
Ground
Water
Monitoring
Endpoints
 
SGW
Study.......................
13
4.5.
Exposure
Summary............................................................................................
13
5.
Introduction.......................................................................................................................
14
5.1.
Overview
of
ARP
Monitoring
Programs
............................................................
15
5.1.1.
Surface
Water
Monitoring
(
SDWS)........................................................
15
5.1.1.1.
Scope
of
the
SDWS
................................................................
15
5.1.1.2.
Site
Selection
for
Surface
Drinking
Water
Sites
......................
17
5.1.2.
Prospective
Ground
Water
(
PGW)
Studies
.............................................
19
5.1.3.
"
State
Ground
Water"
(
SGW)
Monitoring
Program................................
22
5.2.
Design
and
Scope
of
Exposure
Assessment........................................................
23
5.3.
Documents
and
Data..........................................................................................
24
5.4.
Data
Gaps
..........................................................................................................
24
5.5.
Uncertainties
in
the
Drinking
Water
Assessment................................................
24
5.6.
Environmental
Fate............................................................................................
25
5.6.1.
Degradation
Pathways
............................................................................
25
5.6.2.
Soil
Mobility..........................................................................................
26
5.6.3.
Dissipation
Pathways
.............................................................................
26
5.7.
Acetochlor
Usage
..............................................................................................
26
5.7.1.
Summary
of
Registered
/
Proposed
Uses
................................................
26
5.7.2.
Usage
Targets
in
the
Original
Acetochlor
Conditional
Registration
........
27
5.7.3.
Geographic
Patterns
of
Acetochlor
Use
..................................................
28
5.8.
Overview
of
Exposure
Assessment
....................................................................
30
6.
Residues
­
Acetochlor
Parent.............................................................................................
31
6.1.
Data
Files
Used..................................................................................................
31
6.2.
Time
Weighted
Annualized
Means
and
95th
Percentile
Calculations
..................
32
6.2.1.
ARP
Weighting
Methodology
................................................................
32
6.2.2.
USGS
WARP
Beta
Model
Weighting
Methodology...............................
33
6.2.3.
95th
Percentile
Calculations
....................................................................
34
6.3.
Surface
Water
....................................................................................................
34
6.3.1.
ARP
Data...............................................................................................
34
6.3.1.1.
Regulatory
Action
Endpoints
..................................................
34
6.3.1.2.
Acute
Exposure.......................................................................
37
6.3.1.3.
Acute
and
Chronic
Exposure
Distribution
by
Population.........
39
6.3.1.4.
Chronic
Exposure
Distribution
by
System...............................
41
­
4­

6.3.2.
Surface
Water
Factorial
Analysis
...........................................................
42
6.3.3.
Characterization
of
Exposure
to
Surface
Water.......................................
44
6.3.4.
Comparison
of
ARP
and
WARP
beta
Model
Results..............................
48
6.3.5.
Summary
Results
of
National
Water
Quality
Assessment
(
NAWQA)
Results
48
6.3.6.
USGS
/
EPA
Pilot
Reservoir
Monitoring
Program..................................
50
6.4.
Ground
Water
....................................................................................................
51
6.4.1.
PGW
Leaching
Summary.......................................................................
52
6.4.2.
Comparison
of
PGW
Results
to
the
Acetochlor
Regulatory
Action
Endpoints
...............................................................................................
52
6.4.3.
SGW
Summary
......................................................................................
54
6.4.3.1.
Comparison
of
SGW
Results
to
Regulatory
Action
Endpoints.
55
6.4.3.2.
SGW
Acute
Exposure
.............................................................
55
6.4.3.3.
SGW
Annual
Means
...............................................................
56
6.4.3.4.
Ground
Water
Factor
Analysis
................................................
57
7.
Residues
­
Acetochlor
Degradates
.....................................................................................
57
7.1.
Surface
Water
....................................................................................................
57
7.1.1.
Acute
Exposure
Distributions
by
SDWS
Sites
........................................
57
7.1.2.
Chronic
Exposure
Distributions..............................................................
59
7.2.
Ground
Water
....................................................................................................
60
7.2.1.
Comparison
of
Ground
Water
Degradate
Monitoring
results
to
Cancellation
/
Mitigation
Endpoints.
......................................................
60
7.2.2.
PGW
Acute
Exposure
by
Site.................................................................
61
7.2.3.
Chronic
Exposure...................................................................................
65
7.3.
Summary
Assessment
of
Exposure
to
Acetochlor
Degradates
............................
65
8.
Other
Chemicals................................................................................................................
71
9.
Conclusions.......................................................................................................................
75
9.1.
Parent
Acetochlor
..............................................................................................
75
9.2.
Acetochlor
Degradates.......................................................................................
76
10.
References.........................................................................................................................
78
11.
Bibliography
.....................................................................................................................
79
12.
Appendices
.......................................................................................................................
93
12.1.
Chemical
Names
and
Structures.........................................................................
93
12.2.
Acetochlor
Registration
Agreement
 
Cancellation
/
Mitigation
Endpoints
........
96
12.3.
Acetochlor
Usage
 
Detailed
Summary............................................................
101
12.4.
Locations
of
Monitoring
Sites
for
the
ARP
SDWS
Study.................................
102
12.5.
Site
Selection
for
ARP
Monitoring
Studies
......................................................
121
12.5.1.
Surface
Drinking
Water
Site
Selection
(
SDWS
Study)
.........................
121
12.5.2.
Site
Selection
 
SGW
Study.................................................................
134
12.5.3.
PGW
Study
Site
Selection
and
Characterization...................................
136
12.6.
Analytical
Method
Summary
Descriptions
for
the
ARP
Monitoring
Programs
.144
12.7.
Statistical
Analyses
for
the
ARP
monitoring
Studies
........................................
147
12.7.1.
SDWS
147
12.7.1.1.
Pearson
Product
Moment
Correlation
Coefficients
for
Raw
vs.
Finished
Water
Samples
...........................................................
147
12.7.1.2.
Analysis
of
Factors
Related
to
Occurrence
of
Acetochlor....
150
­
5­

12.7.2.
CORRELATION
MATRICES
(
r2)
FOR
FACTORS
RELATED
TO
THE
OCCURRENCE
OF
ACETOCHLOR
IN
SURFACE
DRINKING
WATER
SUPPLIES.............................................................................
151
Time­
weighted
means
over
time...........................................................
155
12.7.3.
MAXIMUM
OBSERVED
CONCENTRATIONS
(
PER
YEAR)
OVER
TIME
FOR
THE
PGW
STUDIES.
.......................................................
156
12.7.4.
TIME­
WEIGHTED
ANNUALIZED
MEANS
OVER
TIME
FOR
THE
PGW
STUDIES.
..................................................................................
158
12.7.5.
CORRELATION
MATRICES
(
r2)
FOR
FACTORS
RELATED
TO
ACETOCHLOR
ACUTE
EXPOSURE
IN
THE
PROSPECTIVE
GROUND
WATER
STUDIES.............................................................
160
12.8.
Data
Tables
for
the
ARP
Monitoring
Studies
Related
to
Mitigation
Endpoints
.161
­
6­

1.
LIST
OF
TABLES
Table
1.
Summary
presentation
of
chronic
exposure
to
parent
acetochlor:
Time­
weighted
annualized
mean
concentrations
(
ppb)
in
surface
and
ground
water
from
the
ARP
monitoring
program
(
based
on
maximum
TWAM
values
observed
at
each
site
by
calendar
year)
along
with
WARP
model
predictions
for
streams
and
rivers.
..
14
Table
2.
Number
of
community
drinking
water
supply
sites
sampled
for
the
parent
acetochlor
in
each
year..................................................................................
16
Table
3.
PGW
sites:
Selected
soil
and
aquifer
characteristics........................................
20
Table
4.
Well
characteristic
summary
for
the
SGM
program.
Values
expressed
in
meters
below
ground
surface
(
bgs).
..........................................................................
23
Table
5.
Key
data
files
submitted
by
the
ARP
used
in
this
assessment..........................
32
Table
6.
Frequency
of
time­
weighted
annualized
mean
concentrations
(
ppb)
for
the
parent
acetochlor
herbicide
in
raw
and
finished
water
drinking
water.
.....................
35
Table
7.
Frequency
of
occurrence
for
all
instantaneous
parent
acetochlor
concentrations
(
ppb)
in
raw
and
finished
water
drinking
water.
............................................
36
Table
8.
Ten
highest
raw
(
untreated)
water
concentrations
of
parent
acetochlor
at
community
water
system
(
CWS)
intake
locations.
........................................
45
Table
9.
Ten
highest
finished
(
treated)
water
concentrations
of
parent
acetochlor
at
community
water
system
(
CWS)
outflow
locations.......................................
45
Table
10.
Watershed
characteristics
for
the
ten
highest
finished
(
treated)
water
concentrations
of
parent
acetochlor
at
community
water
system
(
CWS)
outflow
locations.
......................................................................................................
46
Table
11.
Highest
raw
(
untreated)
water
concentrations
of
parent
acetochlor
at
community
water
system
(
CWS)
intake
locations
in
each
state
(
sorted
by
Max
TWAM).
47
Table
12.
Highest
finished
(
treated)
water
concentrations
of
parent
acetochlor
at
community
water
system
(
CWS)
outflow
locations
in
each
state.
....................................
47
Table
13.
Top
ten
highest
raw
water
concentrations
(
ppb)
of
parent
acetochlor
modeled
by
WARP
multi­
compound
regression
model
and
measured
by
ARP
at
community
water
system
(
CWS)
intakes.
........................................................................
48
Table
14.
Acetochlor
monitoring
concentrations
at
NAWQA
study
unit
locations........
50
Table
15.
Maximum
acetochlor
concentration
values
in
pilot
reservoir
monitoring
study
(
Bloomquist
et
al.,
2001)...............................................................................
51
Table
16.
PGW
Sites
exceeding
0.1
ppb
at
9
feet
depth
(
exceedences
only
occurred
at
1
of
the
8
sites).
...................................................................................................
52
Table
17.
Concentrations
of
AC
observed
in
3­
foot
lysimeters
from
the
eight
prospective
ground
water
studies.
....................................................................................
53
Table
18.
Concentrations
of
AC
observed
in
9­
foot
lysimeters
from
the
eight
prospective
ground
water
studies.
....................................................................................
53
Table
19.
Concentrations
of
AC
observed
in
Shallow
ground
water
from
the
eight
prospective
ground
water
studies.
.................................................................
53
Table
20.
Concentrations
of
AC
observed
in
Deep
ground
water
from
the
eight
prospective
ground
water
studies.
....................................................................................
54
Table
21.
Concentrations
of
ESA
observed
in
9­
foot
lysimeters
from
the
eight
prospective
ground
water
studies.
....................................................................................
62
­
7­

Table
22.
Concentrations
of
ESA
observed
in
shallow
ground
water
from
the
eight
prospective
ground
water
studies.
.................................................................
62
Table
23.
Comparison
of
Acetochlor
ESA
and
bromide
breakthrough
in
9­
foot
lysimeters
at
the
eight
prospective
ground­
water
monitoring
sites:
Normalized
concentrations.
1
.....................................................................................................................
63
Table
24.
Comparison
of
Acetochlor
ESA
and
bromide
breakthrough
(
with
months
after
treatment)
in
shallow
ground
water
at
the
eight
prospective
ground­
water
monitoring
sites:
Normalized
concentrations.
1
..............................................
63
Table
25.
Concentrations
of
acetochlor
OXA
observed
in
9­
foot
lysimeters
from
the
eight
prospective
ground
water
studies.
.................................................................
64
Table
26.
.
Concentrations
of
acetochlor
OXA
observed
in
shallow
ground
water
from
the
eight
prospective
ground
water
studies..........................................................
64
Table
27.
Summary
presentation
of
time­
weighted
annualized
mean
concentrations
(
ppb)
for
the
combined
residues
of
acetochlor
(
parent
+
ESA
and
OXA
degradates)
in
surface
and
ground
water
(
based
on
maximum
TWAM
values
observed
at
each
site
by
calendar
year).
...................................................................................
67
Table
28.
Acute
Exposure
to
ESA.
Summary
presentation
of
acute
concentrations
(
ppb)
for
the
residues
of
acetochlor
ethanesulfonic
acid
in
surface
and
ground
water.
..
68
Table
29.
Acute
Exposure
to
OXA.
Summary
presentation
of
acute
concentrations
(
ppb)
for
the
residues
of
acetochlor
oxanilic
acid
in
surface
and
ground
water.......
69
Table
30.
Chronic
Exposure
to
ESA.
Summary
presentation
of
time­
weighted
annualized
mean
concentrations
(
ppb)
for
the
residues
of
acetochlor
ethanesulfonic
acid
in
surface
and
ground
water
(
based
on
maximum
TWAM
values
observed
at
each
site
by
calendar
year).
...................................................................................
69
Table
31.
Chronic
Exposure
to
OXA.
Summary
presentation
of
time­
weighted
annualized
mean
concentrations
(
ppb)
for
the
residues
of
acetochlor
oxanilic
acid
in
surface
and
ground
water
(
based
on
maximum
TWAM
values
observed
at
each
site
by
calendar
year).
..............................................................................................
70
Table
32.
Occurrence
(%)
of
TWAMs
in
Finished
Drinking
Water
at
Various
Concentrations
by
Sampling
Stratum............................................................
71
Table
33.
Summary
of
the
Distribution
of
Degradate
Residues
for
ARP
SGW
Analytes
 
2001
Data
only.
............................................................................................
74
Table
34.
Summary
of
the
Distribution
of
Parent
Residues
for
ARP
SGW
Analytes
 
2001
data
only.
......................................................................................................
74
Table
35.
Pearson
product­
moment
correlation
coefficients
for
raw
versus
finished
water
parent
acetochlor
concentrations
observed
at
the
P­
1
sites
in
the
SDWS
monitoring
data
set.
......................................................................................
147
Table
36.
Paired
t­
test
for
raw
versus
finished
water
samples.
.......................................
149
Table
37.
SGW
acetochlor
numeric
response
samples
exceeding
0.1
ppb
for
detection
of
"
pattern
of
movement"..................................................................................
161
Table
38.
Acetochlor
degradate
samples
exceeding
0.1
ppb
in
the
state
monitoring
program.
.......................................................................................................
163
Table
39.
Acetochlor
and
degradate
detections
in
PGW
studies
greater
than
1.0
ppb
at
nine
foot
lysimter
depth
consistent
with
three
and
six
foot
lysimeters
in
that
cluster
as
defined
by
"
pattern
of
movement"
criteria.
MAT
=
months
after
treatment.
..
178
­
8­

2.
TABLE
OF
FIGURES
Figure
1.
States
involved
in
the
Surface
Water
Monitoring
Program
for
Acetochlor.
..................................................................................................
16
Figure
2.
Locations
of
ARP
surface
water
monitoring
sites
(
blue
circles)
in
relation
to
maximum
observed
concentrations
of
acetochlor
in
surface
water
(
SW)
by
county
based
on
available
NAWQA
data..............................
17
Figure
3.
States
with
prospective
ground
water
(
PGW)
studies
for
acetochlor...............
20
Figure
4.
States
involved
in
the
"
SGW"
ground­
water
monitoring
program
for
acetochlor
and
locations
of
wells.
Source:
De
Guzman
et
al.
(
2005).
............
23
Figure
5.
Corn
production
intensity
(
2002
Census
of
Agriculture
data)
and
general
locations
of
drinking
water
intakes
sampled
in
the
ARP's
SDWS
monitoring
program
(
white
=
no
reported
corn
acreage,
green
=
lowest
intensity
category,
red
=
highest
corn
intensity
category).
.................
29
Figure
6.
USGS
estimated
acetochlor
use
for
1997.
......................................................
30
Figure
7.
Cumulative
frequency
distribution
for
all
acetochlor
observations
for
each
study.
PGW
data
represented
include
separate
distributions
for
the
9­
foot
depth
lysimeter
data
and
the
shallow
groundwater
wells
for
each
study.
...................................................................................................
37
Figure
8.
Cumulative
frequency
distribution
for
acetochlor
acute
exposure
in
all
ARP
studies,
based
on
the
maximum
observed
concentration
at
each
site.
PGW
data
maximum
exposures
are
provided
for
each
lysimeter
and
each
depth.
............................................................................................
38
Figure
9.
Distribution
of
acute
exposure,
based
on
the
maximum
observed
concentration
at
each
site.
PGW
data
maximum
exposures
are
provided
for
each
lysimeter
and
each
depth.................................................................
38
Figure
10.
Acute
acetochlor
exposure
distribution
by
population
served
for
raw
(
A)
and
finished
(
B)
water
samples.
.............................................................
39
Figure
11.
Chronic
exposure
to
parent
acetochlor
in
raw
surface
drinking
water
(
SDWS)
using
the
average
time­
weighted
mean
at
each
site.........................
40
Figure
12.
Cumulative
frequency
distribution
for
parent
acetochlor
chronic
exposure,
based
on
the
highest
time­
weighted
annual
mean
at
each
site.
PGW
chronic
exposures
are
the
maximum
TWAM
for
each
cluster
at
9­
foot
depth
for
lysimeters
and
shallow
monitoring
wells
for
ground
water............................................................................................................
41
Figure
13.
Percent
reduction
in
acetochlor
from
pre­
treatment
(
raw)
to
post
treatment
(
finished)
sample.
.........................................................................
43
Figure
14.
Distribution
of
maximum
acetochlor
concentrations
observed
at
each
site
in
the
state
ground
water
program.
.........................................................
56
Figure
15.
Distribution
of
all
time­
weighted
annualized
means
for
sites
in
the
state
ground
water
(
SGW)
monitoring
program............................................
56
Figure
16.
Maximum
observed
concentrations
(
acute)
of
the
two
acetochlor
degradates
and
Total
Combined
residues
(
parent
+
ESA
+
OXA)
in
raw
(
dashed)
and
finished
(
solid)
surface
drinking
water
samples.
......................
58
Figure
17.
Percent
reduction
of
acetochlor
degradates
in
surface
drinking
water
supplies........................................................................................................
59
­
9­

Figure
18.
Chronic
exposure
distribution
for
acetochlor
degradates
(
ESA
and
OXA)
in
surface
drinking
water
supplies
using
the
maximum
timeweighted
annualized
mean
for
each
site.
Summary
of
USGS
monitoring
results
for
acetochlor
degradates
................................................
60
Figure
19.
Chronic
exposure
distribution
for
acetochlor
degradates
(
ESA
and
OXA)
in
the
state
ground
water
monitoring
program
using
the
maximum
time­
weighted
annualized
mean
for
each
site.
..............................
65
Figure
20.
Box
plot
of
annualized
mean
concentrations
(
AMCs)
of
parent
herbicides
in
finished
drinking
water
from
the
SDWS
study
(
Hackett
et
al.,
2005)......................................................................................................
72
Figure
21.
Co­
occurrence
of
(
a)
sulfonic
acid
(
ESA)
degradate
residues
and
(
b)
oxanilic
acid
(
OXA)
degradate
residues
for
acetochlor,
alachlor,
and
metolachlor
in
the
SGW
study.
Values
reflect
the
number
of
SGW
wells
with
observed
residues
(
Minimum
detection
limit
was
0.2
ppb
for
the
sulfonic
acid
degradates
and
0.1
ppb
for
the
oxanilic
acid
degradates).
No
ESA
soil
degradate
residues
were
observed
in
49
of
the
182
wells
and
no
OXA
soil
degradate
residues
were
observed
in
110
of
the
182
wells.
Source:
de
Guzman
et
al.
(
2005).
................................
73
­
10­

3.
ABBREVIATIONS
AC
Acetochlor
Ac_
ESA
Acetochlor
ethanesulfonic
acid
Ac_
OXA
Acetochlor
oxanilic
acid
ARP
Acetochlor
Registration
Partnership
BEAD/
OPP
Biological
and
Economic
Analysis
Division
of
OPP
CDF
Cumulative
frequency
distribution
CWS
Community
water
system
ESA
Acetochlor
ethanesulfonic
acid
EFED/
OPP
Environmental
Fate
and
Effects
Division
of
OPP
FIFRA
Federal
Insecticide,
Fungicide
and
Rodenticide
Act
FQPA
Food
Quality
Protection
Act
of
1996
GAC
Granular
activated
carbon
treatment
GWM
Ground
Water
Monitoring
(
ARP
Reference)

NAWQA
National
Water
Quality
Assessment
Program
of
USGS
NCFAP
National
Center
for
Food
and
Agricultural
Policy
(
pesticide
usage
monitoring
program)

OPP
Office
of
Pesticide
Programs
of
USEPA
OXA
Acetochlor
oxanilic
acid
PAC
Powdered
activated
carbon
treatment
PGW
Prospective
ground
water
study
(
monitoring
program)

SDWS
Surface
drinking
water
supply
(
monitoring
program)

SGW
State
ground
water
(
monitoring
program)

SWM
Surface
water
monitoring
(
ARP
Reference)

TWAM
Time­
weighted
annualized
mean
USEPA
United
States
Environmental
Protection
Agency
USGS
United
States
Geological
Survey
WARP
Watershed
Regression
for
Pesticides
 
USGS
Pesticide
Concentration
Model
­
11­

4.
EXECUTIVE
SUMMARY
4.1.
Purpose
In
March
of
1994,
USEPA
and
ARP
entered
into
a
conditional
registration
agreement
(
USEPA,
1994)
for
the
chemical
acetochlor
(
2­
chloro­
N­(
ethoxymethyl)­
N­(
2­
ethyl­
6­
methylphenyl)­
acetamide),
the
active
ingredient
in
a
number
of
herbicides
used
on
corn
(
Zea
maize)
crops
to
control
annual
grasses
and
certain
broadleaf
weeds
(
Hackett
et
al.,
2004).
Under
the
agreement,
USEPA
required
ARP
to
conduct
several
acetochlor
monitoring
programs
and
specified
a
number
of
cancellation
or
mitigation
endpoints
aimed
at
protecting
the
environment
and
limiting
potential
risks
to
human
health
(
USEPA,
1994).
The
purpose
of
this
assessment
is,
therefore,
to
estimate
exposure
to
acetochlor
(
in
support
of
a
human
health
dietary
risk
assessment)
and
to
summarize
the
status
of
mitigation
/
cancellation
endpoints
encapsulated
in
the
acetochlor
conditional
registration
agreement.

The
primary
source
data
for
both
this
exposure
assessment
and
evaluation
of
the
registration
agreement
compliance
are
the
three
major
acetochlor
data
sets
generated
by
the
Acetochlor
Registration
Partnership
(
ARP).
Two
data
sets
are
ground
water
source
based
and
include
the
"
State"
Ground
Water
(
SGW)
monitoring
program
and
the
Prospective
Ground
Water
studies
(
PGW)
and
one
is
surface
water
source
based
referred
to
as
Surface
Drinking
Water
Supplies
(
SDWS)
monitoring
program.
The
ARP
provided
a
fourth
acetochlor
data
set
that
consists
of
incident
investigation
of
ground
water
primarily
around
pesticide
dealer
and
storage
facilities.
The
incident
data
are
only
indirectly
related
to
impacts
from
registered
uses
of
acetochlor
therefore
these
data
have
not
been
explicitly
included
in
the
direct
exposure
assessment.
When
relevant
to
the
exposure
assessment,
additional
publicly
available
water
monitoring
data
for
acetochlor
are
discussed
in
this
document.

4.2.
Acetochlor
Usage,
Monitoring
Locations,
and
the
Exposure
Assessment
Acetochlor
is
now
registered
in
42
states
as
well
as
the
District
of
Columbia
(
Hackett
et
al.,
2004).
It
is
also
used
in
corn
growing
areas
of
several
countries
including
China,
Europe,
and
Argentina.
Presently,
roughly
80%
of
the
total
use
of
acetochlor
in
the
United
States
occurs
in
the
Midwest.
Detailed
countylevel
sales
maps
for
acetochlor
from
1994
to
2003
are
provided
in
Appendix
section
12.3
Acetochlor
Usage
 
Detailed
Summary.
These
sales
data
have
been
provided
separately
by
members
of
the
acetochlor
registration
partnership
(
ARP)
as
confidential
information
and
cannot
be
shared
with
unauthorized
individuals.

The
sales
data
are
presented
as
a
surrogate
for
the
location
of
acetochlor
usage.
Pesticide
sales
data
may
not
be
a
consistent
estimator
of
usage
in
any
particular
watershed
because
usage
may
not
occur
near
the
location
of
purchase.
The
maps
of
acetochlor
sales
data
and
surface
water
monitoring
locations
show
that
the
set
of
monitoring
sites
selected
does
not
coincide
well
with
all
of
the
areas
where
high
sales
have
been
reported.
A
lower
rate
of
utilization
of
surface
water
sources
by
drinking
water
facilities
and
lower
overall
numbers
of
CWS'
utilizing
surface
water
in
some
high
acetochlor
use
regions
appears
to
be
a
factor
in
the
paucity
of
sites
in
these
regions
that
were
eventually
selected
for
monitoring
in
the
SDWS.
For
these
reasons
of
facility
location
and
sampling
design,
it
is
possible
therefore
that
the
drinking
water
intake
locations
that
were
monitored
do
not
fully
represent
the
sites
where
highest
concentrations
in
then
current
or
potential
surface
source
drinking
water
occurred.

The
lack
of
monitoring
in
some
of
the
high
acetochlor
use
areas
is
especially
problematic
for
broader
interpretation
of
the
SDWS
monitoring
results
where
the
lack
of
sampling
of
raw
(
pre­
facility
treatment)
­
12­

water
at
most
locations
makes
it
difficult
to
isolate
the
effects
of
site­
specific
usage,
vulnerability
factors,
and
water
treatment
processes
on
the
observed
residue
levels.

4.3.
Time
Weighted
Annualized
Means
and
95th
Percentile
Calculations
Time­
weighted
annualized
means
(
TWAMs)
were
calculated
for
each
site
in
the
three
major
monitoring
programs
(
SDWS,
SGW,
and
PGW).
Two
separate
weighting
methods
were
implemented
using
a
custom­
built
TWAM
computer
program
to
verify
the
TWAMs
computed
by
the
ARP.
The
weighting
method
used
by
the
ARP
(
described
later
in
this
report)
was
cross­
checked
with
a
slightly
different
method
implemented
in
the
WARP
beta
model
developed
by
the
USGS
(
USGS
2004).
Both
weighting
methods
assign
a
weight
to
each
discrete
sample
observation
based
upon
the
fraction
of
the
time
during
a
year
that
each
sample
represents.
Weighted
concentrations
were
then
summed
to
provide
an
annualized
mean.

4.4.
Mitigation/
Cancellation
Endpoints
In
addition
to
providing
a
drinking
water
exposure
assessment
for
application
to
a
dietary
risk
assessment
for
acetochlor,
this
document
also
addresses
the
endpoints
or
triggers
for
regulatory
action
incorporated
into
the
acetochlor
registration
agreement
are
provided
in
Appendix
1
(
see
USEPA,
1994;
for
a
full
copy
of
the
agreement).
These
endpoints
are
directly
tied
to
each
of
the
major
monitoring
programs
required
of
the
ARP
in
the
Acetochlor
Registration
Agreement;
the
reader
may
need
to
refer
to
the
Appendix
for
a
complete
understanding
of
the
reasons
for
the
way
in
which
these
endpoints
are
discussed
in
this
document.
The
triggers
varied
between
monitoring
programs,
the
following
is
a
comparison
of
the
results
to
the
triggers
for
each
program.
Discussion
of
both
parent
and
degradate
occurrence
and
their
relation
to
the
triggers
is
separately
provided
in
this
document,
however,
only
parent
residues
are
clearly
classified
as
residues
of
concern
for
which
the
triggers
for
mitigation
measures
in
the
Registration
Agreement
apply.
At
the
time
acetochlor
was
registered
monitoring
data
for
the
major
degradation
products
of
acetochlor
was
virtually
non­
existent
and
specific
toxicity
studies
had
not
yet
been
conducted.
Consequently,
no
informed
determination
could
have
been
made
at
the
time
of
the
registration
agreement
about
whether
any
significant
risk
could
potentially
arise
from
exposure
to
acetochlor
ESA
or
OXA
in
water.

4.4.1.
ARP
Surface
Water
Monitoring
Endpoints
Acetochlor
was
detected
above
8.0
ppb
trigger
for
individual
detections
in
2
samples
in
the
surface
drinking
water
supply
(
SDWS)
monitoring
program.
Two
finished
(
treated
water)
samples
were
detected
above
8.0
ppb,
however
the
twelve
month
time­
weighted
annualized
mean
did
not
exceed
the
2.0
ppb
regulatory
action
trigger
for
these
or
any
of
the
other
water
supply
systems
included
in
the
SDWS.
No
raw
(
untreated)
concentrations
were
detected
above
8.0
ppb.
For
both
raw
and
finished
surface
drinking
water,
roughly
99%
of
the
time­
weighted
­
13­

annualized
means
were
below
0.5
ppb.
Maximum
acetochlor
instantaneous
concentrations,
95th
percentiles,
and
time­
weighted
annualized
means
were
observed
in
Illinois.

4.4.2.
ARP
Ground
Water
Monitoring
Endpoints
 
PGW
Study
For
the
PGW,
the
triggers
for
regulatory
action
were
tied
to
both
soil
pore­
water
(
lysimeter)
and
ground
water
detections.
Acetochlor
was
detected
above
0.1
ppb
at
only
one
site
in
nine
foot
lysimeters
in
the
prospective
ground
water
(
PGW)
studies.
The
maximum
concentration
of
acetochlor
in
soil
pore
water
was
3.2
ppb
observed
in
the
nine
foot
lysimeters
in
Iowa.
The
maximum
residue
detected
in
ground
water
wells
was
0.06
ppb
observed
in
Iowa.
The
acetochlor
degradates
ethanesulfonic
acid
(
Ac_
ESA)
and
oxanilic
acid
(
Ac_
OXA)
were
generally
detected
more
frequently
than
parent
acetochlor.
In
the
PGW
studies
for
example,
ESA
demonstrated
a
pattern
of
movement
as
defined
by
concentrations
greater
than
or
equal
to
1.0
ppb
at
three,
six,
and
nine
foot
lysimeter
depths.
In
293
instances
ESA
was
detected
above
1.0
ppb
at
all
three
lysimeter
depths.
These
exceedences
occurred
in
seven
out
of
the
eight
states.

4.4.3.
ARP
Ground
Water
Monitoring
Endpoints
 
SGW
Study
For
the
SGW,
the
trigger
for
regulatory
action
was
a
pattern
of
detections
in
20
or
more
wells
at
or
above
0.10
ppb
"
followed
by
two
subsequent
detections
of
at
least
0.10
ppb
in
monthly
sampling
of
each
of
those
wells,
conducted
over
a
period
of
six
months"
(
this
language
did
not
anticipate
the
impact
of
a
large
number
of
missing
samples
as
in
the
reduced
sample
collection
regime
resulting
in
a
maximum
of
four
samples
per
well
per
year
being
collected
during
the
last
two
years
of
the
monitoring
program).
See
Appendix
12.2
for
details.
Parent
acetochlor
exhibited
a
pattern
of
detection
in
the
required
number
of
samples
in
seven
wells,
or
thirteen
wells
short
of
the
trigger
for
regulatory
action
based
on
SGW
results.
Residues
of
acetochlor
degradates
were
much
more
widespread
in
the
SGW
wells,
but
these
compounds
have
not
been
deemed
residues
of
concern.

Aproximately
10%
of
the
site
maximum
instantaneous
concentrations
in
the
SGW
wells
were
above
0.5
ppb
and
15%
of
all
time­
weighted
annualized
means
were
greater
than
or
equal
to
0.03
ppb
(
i.
e.,
the
minimum
detection
limit).
If
the
degradates
are
included
in
an
exposure
calculation,
then
the
number
of
wells
with
a
pattern
of
detections
increases
to
approximately
36
(
requires
a
modification
of
the
"
pattern
of
movement"
definition
to
2
of
3
consecutive
detections
greater
than
0.1
ppb
(
0.2
ppb
for
ESA
since
the
detection
limit
was
0.2
ppb)
since
sampling
of
degradates
never
occurred
more
frequently
than
a
quarterly
basis.

4.5.
Exposure
Summary
Acetochlor
parent
residue
exposure
is
generally
higher
and
more
widespread
through
surface
water
sources
than
ground
water
(
Table
1).
Available
data
indicate
that
water
treatment
involving
the
use
of
activated
carbon
may
reduce
exposure
by
close
to
50%
on
average;
however
limitations
on
the
data
preclude
generalizing
this
as
a
predictable
effect
of
water
treatment.
In
particular,
no
data
are
available
that
match
the
same
water
in
raw
and
finished
water,
the
ARP
SDWS
dataset
did
not
measure
samples
in
intake
water
from
those
systems
using
other
types
of
water
treatment,
and
most
of
the
highest
concentrations
observed
in
the
SDWS
study
occurred
in
­
14­

finished
(
not
raw)
samples.
EFED
is
aware
that
while
specific
matching
of
raw
and
finished
water
is
not
available
for
the
ARP
study,
other
studies
of
treatment
effects
are
available
such
as
that
by
Gustafson
et
al.
(
2003).

Table
1.
Summary
presentation
of
chronic
exposure
to
parent
acetochlor:
Timeweighted
annualized
mean
concentrations
(
ppb)
in
surface
and
ground
water
from
the
ARP
monitoring
program
(
based
on
maximum
TWAM
values
observed
at
each
site
by
calendar
year)
along
with
WARP
model
predictions
for
streams
and
rivers.

Study
N
Maximum
95th
Percentile
Median
Surface
Water
­
SDWS
raw
44
0.591
0.355
0.042
Surface
Water
­
SDWS
finished
189
1.428
0.347
0.032
Surface
Water
­
WARP
model
(
raw)
a
470
0.812
0.435
0.042
Ground
Water
(
shallow)
­
PGW
site
averages
8
<
0.03
<
0.03
<
0.03
Ground
Water
(
shallow)
­
PGW
cluster
maximums
8
<
0.03
<
0.03
<
0.03
Ground
Water
­
SGW
182
0.520
0.039
<
0.03
a
Includes
TWAMs
calculated
by
the
WARP
model.
The
WARP
results
are
provided
for
comparison
to
the
ARP
monitoring
results
and
include
WARP
results
only
for
states
where
ARP
also
had
surface
water
monitoring
stations.
N
=
total
number
of
sites
included
in
the
statistics.

Should
a
toxicological
concern
arise
from
exposure
anywhere
near
these
levels
(
up
to
3x
the
levels
reported
in
Table
1),
a
refined
exposure
assessment
can
be
done
adjusting
the
ARP
exposure
values
for
any
disparity
between
usage
intensity
at
the
ARP
monitoring
sites
and
other
watersheds
with
surface
water
serving
as
drinking
water
sources
with
higher
use
intensities.
A
requirement
for
this
would
be
acquisition
from
the
ARP
or
independent
calculation
by
EPA
of
acetochlor
usage
by
watershed
based
on
the
overlap
of
county
and
watershed
boundaries
(
the
best
available
data
representing
acetochlor
spatially
have
all
been
reported
at
the
county
level).

Finally,
the
results
of
this
monitoring
analysis
only
apply
to
acetochlor
use
on
field
corn
(
significant
new
field
uses
are
currently
under
review
by
EPA).

5.
INTRODUCTION
Pesticide
substances
in
the
United
States
are
regulated
under
the
Federal
Insecticide,
Fungicide
and
Rodenticide
Act
(
FIFRA),
later
amended
by
the
Food
Quality
Protection
Act
of
1996
(
FQPA).
Under
FIFRA,
any
pesticide,
be
it
a
single
active
ingredient
or
a
mixture,
must
be
registered
for
use
as
a
pesticide
before
a
person
may
distribute
or
sell
the
product.
Pesticides
are
also
regulated
at
the
state
level
(
usually
by
U.
S.
Department
of
Agriculture);
however,
state
regulations
must
be
at
least
as
stringent
as
federal
regulations.
In
order
to
register
a
pesticide
in
­
15­

the
US,
the
USEPA
must
ensure
that
the
pesticide,
when
used
according
to
the
product
label,
will
not
pose
an
unreasonable
risk
to
human
health
or
the
environment.
Under
FQPA,
regulators
must
also
consider
threats
to
human
health
through
food
residues
and
via
pesticides
in
drinking
water.
The
latter
requirement
has
created
a
need
to
monitor
and
estimate
pesticides
in
drinking
water
supplies,
including
both
surface
water
and
ground
water
sources.

In
March
of
1994,
USEPA
and
ARP
entered
into
a
conditional
registration
agreement
(
USEPA,
1994)
for
the
chemical
acetochlor
(
2­
chloro­
N­(
ethoxymethyl)­
N­(
2­
ethyl­
6­
methylphenyl)­
acetamide),
the
active
ingredient
in
a
number
of
herbicides
used
on
corn
(
Zea
maize)
crops
to
control
annual
grasses
and
certain
broadleaf
weeds
(
Hackett
et
al.,
2004).
Under
the
agreement,
USEPA
required
ARP
to
conduct
several
acetochlor
monitoring
programs
and
specified
a
number
of
cancellation
or
mitigation
endpoints
aimed
at
limiting
potential
risks
to
human
health
and
endangered
species
5.1.
Overview
of
ARP
Monitoring
Programs
As
part
of
the
conditional
registration
agreement,
the
USEPA
mandated
ARP
to
develop
an
"
early
warning"
detection
system
that
would
alert
health
officials
if
acetochlor
is
found
migrating
toward
surface
or
ground
water
resources
or
may
have
the
potential
to
migrate
to
receiving
waters.
This
early
warning
system
consists
of
rigorous
surface
and
ground
water
monitoring
programs,
specifically:
(
1)
Surface
Drinking
Water
Supplies
(
SDWS)
as
measured
at
water
supply
intakes
for
roughly
175
sites,
(
2)
Prospective
Ground
Water
(
PGW)
studies
at
eight
sites
in
eight
states
that
are
geographically
diverse
and
generally
representative
of
U.
S.
corn
production
regions,
and
(
3)
State
Ground
Water
(
SGW)
studies
that
included
monitoring
approximately
175
ground
water
wells
located
near
treated
cornfields.
Appendices
0,
12.5,
and
12.6
provide
further
details
on
the
monitoring
locations,
site
selection
procedures
and
site
descriptions,
and
the
analytical
methods
used
in
the
ARP
programs.

5.1.1.
Surface
Water
Monitoring
(
SDWS)

5.1.1.1.
Scope
of
the
SDWS
The
surface
drinking
water
supply
(
SDWS)
program
is
intended
to
detect
the
presence
of
acetochlor
or
any
of
its
degradates
of
toxicological
concern
in
surface
water
bodies
that
may
be
used
for
community
drinking
water
supplies.
The
program
is
funded
by
ARP
and
is
focused
on
states
that
were
anticipated
to
be
major
use
areas
(
Figure
1).
Specific
details
regarding
the
program
are
provided
in
Hackett
et
al.
(
2004).
States
involved
in
the
surface
water
monitoring
program
are
shown
in
Figure
1.
In
general,
"
finished"
(
or
treated)
water
samples
were
collected
from
approximately
175
sampling
stations
each
year
at
biweekly
to
monthly
intervals
(
roughly
14
samples
per
year),
although
some
sites
were
dropped
and
replaced
by
others
in
some
years
resulting
in
a
total
of
189
individual
stations
sampled
over
the
seven
year
period
(
Table
2).
"
Raw"
or
untreated
samples
were
also
collected
for
a
total
of
44
stations
and
ranged
from
26
to
38
individual
stations
per
year
(
Table
2).
Similar
to
finished
water
samples,
some
stations
were
dropped
and
others
added
throughout
the
seven
year
monitoring
period.
Specific
details
can
be
found
in
ARP
annual
reports
as
well
as
Hacket
et
al.
(
2005).
Under
the
conditional
registration
agreement
(
USEPA
1994),
the
need
for
monitoring
is
reassessed
every
five
years.
Concentrations
of
acetochlor
(
and,
potentially,
acetochlor
degradates,
which
were
monitored
for
­
16­

only
from
1999
to
2001)
from
drinking
water
intakes
are
then
compared
to
target
levels
to
determine
if
mitigation
or
cancellation
actions
are
required.

Figure
1.
States
involved
in
the
Surface
Water
Monitoring
Program
for
Acetochlor.

Table
2.
Number
of
community
drinking
water
supply
sites
sampled
for
the
parent
acetochlor
in
each
year.

YEAR
#
Raw
Water
Sites
#
Finished
Water
Sites
1995
26
175
1996
32
175
1997
35
175
1998
37
175
1999
38
175
2000
33
156
2001
37
152
TOTAL
44
a
189b
a
Total
number
of
individual
sites
sampled.
Raw
water
(
untreated
surface
water)
samples
were
collected
from
all
community
water
systems
(
CWSs)
that
use
granular
activated
carbon
(
GAC),
and
from
several
systems
that
use
powdered
activated
carbon
(
PAC)
(
Hacket
et
al.
2005).
b
Total
number
of
individual
sites
sampled.
Some
sites
were
added
in
subsequent
years
while
others
were
dropped.
"
The
total
number
of
CWSs
was
kept
at
175
for
the
first
five
years
with
fewer
than
three
sites
requiring
replacement
in
any
year.
Sites
were
always
replaced
by
CWSs
from
the
same
or
a
higher
vulnerability
stratum.
Several
CWSs
chose
not
to
continue
when
the
monitoring
was
extended
for
a
final
two
years,
dropping
the
number
of
sites
to
156
in
2000,
and
to
152
in
2001"
(
Hacket
et
al,
2005).
­
17­

Figure
1
shows
the
locations
of
ARP
surface
water
monitoring
locations
overlaid
on
the
maximum
concentration
observed
by
county
based
on
NAWQA
data.
The
blue
circles
represent
locations
of
community
water
supply
intakes
where
ARP
sampled
finished
(
treated)
water
and
in
some
locations
raw
water
samples
were
additionally
sampled.

Figure
2.
Locations
of
ARP
surface
water
monitoring
sites
(
blue
circles)
in
relation
to
maximum
observed
concentrations
of
acetochlor
in
surface
water
(
SW)
by
county
based
on
available
NAWQA
data.

Figure
2
shows
the
locations
of
ARP
surface
water
monitoring
locations
overlaid
on
the
maximum
concentration
observed
by
county
based
on
NAWQA
data.
The
blue
circles
represent
locations
of
community
water
supply
intakes
where
ARP
sampled
finished
(
treated)
water
and
in
some
locations
raw
water
samples
were
additionally
sampled.

5.1.1.2.
Site
Selection
for
Surface
Drinking
Water
Sites
A
particularly
important
issue
in
the
assessment
of
exposure
to
parent
acetochlor
is
how
well
the
ARP
SDWS
study
assesses
the
most
vulnerable
watersheds
to
acetochlor
exposure
(
parent
exposure
levels
in
ground
water
sources
were
generally
significantly
lower).
Included
here
is
a
summary
of
the
SDWS
site
selection
procedures,
and,
additionally,
an
excerpt
from
the
ARP
report
describing
the
SDWS
site
selection
process
in
more
detail
is
provided
in
Appendix
12.5.

A
site
selection
process
was
conducted
to
identify
175
CWSs
in
12
states.
Data
regarding
population
and
CWS
source(
s)
were
collected,
and
watershed
areas
and
corn
intensities
were
determined.
Each
of
the
175
systems
was
visited,
inspected,
and
data
confirmed.
Watersheds
for
the
175
systems
were
mapped.
The
selected
CWSs
represent
a
broad
spectrum
based
on
geographic
diversity,
general
size
and
corn
intensity
of
the
watersheds.
The
data
for
the
selected
­
18­

systems
demonstrate
the
extensive
diversity
of
the
ARP
surface
water
monitoring
program.
The
watersheds
are
representative
of
the
key
acetochlor­
use
states,
with
a
few
extending
into
numerous
states
not
included
in
the
program.
The
CWSs
are
supplied
by
surface
water
from
a
variety
of
sources
including
small
rivers
and
lakes,
larger
rivers
and
lakes,
and
reservoirs,
and
employ
a
wide
variety
of
treatment
methods.
The
selected
watersheds
span
a
large
range
of
watershed
area,
and
serve
a
large
range
of
populations.

A
total
of
175
CWSs
in
nine
mid­
western
and
three
mid­
Atlantic
states
were
selected
for
the
program.
The
selection
process
was
designed
to
include
a
wide
array
of
CWSs
with
watersheds
in
areas
of
corn
production,
with
an
emphasis
on
including
worst­
case
watersheds
i.
e.,
smaller
watersheds
(
not
on
the
Great
Lakes
and
Continental
Rivers)
in
areas
of
high
corn
production.
These
watersheds
are
expected
to
have
higher
concentrations
of
acetochlor
after
runoff
events
than
larger
watersheds
which
drain
areas
of
both
high
and
low
corn
production,
because
dilution
would
be
greater
for
CWSs
taking
water
from
the
Great
Lakes
and
Continental
Rivers.
Data
were
collected
to
characterize
each
community
water
system
included
in
the
program.

The
steps
for
the
CWS
selection
and
characterization
process
are
summarized
below:

1)
Identification
of
all
public
CWSs
that
use
surface
water
in
the
following
12
states:
Illinois,
Indiana,
Iowa,
Minnesota,
Nebraska,
Kansas,
Wisconsin,
Ohio,
Missouri,
Pennsylvania,
Maryland,
and
Delaware.

2)
Identification
of
all
CWSs
that
belong
to
the
target
population.

Target
Population
­
All
CWSs
in
the
12
states
that:

 
use
only
surface
water,
or
can
discretely
sample
surface
water,
 
are
willing
to
cooperate
and
 
have
a
corn
intensity
(
for
smaller
watersheds
that
do
not
have
an
intake
on
a
Great
Lake
or
Continental
River)
greater
than
or
equal
to
5%,
where
corn
intensity
is
the
ratio
of
acreage
of
harvested
corn
to
total
acreage
in
the
upstream
watershed.

3)
Separation
of
the
target
population
of
CWSs
into
disjoint
(
non­
overlapping)
strata
based
on
the
size
of
the
watershed,
the
corn
intensity
(
for
smaller
watersheds),
and
State
that
the
system
is
in:
 
State
 
size
of
watershed
(
three
major
subdivisions)
o
Great
Lakes
o
Continental
Rivers
(
Missouri,
Mississippi,
Ohio
Rivers)
o
Smaller
Rivers
and
Lakes
 
corn
intensity
(%
corn
planted
in
total
area
of
watershed)
(
three
major
subdivisions)
o
5­
10%
CI
o
11­
20%
CI
o
>
20%
CI
­
19­

4)
Determination
of
the
number
of
CWSs
to
be
selected
from
each
stratum.
The
focus
was
on
strata
containing
CWS
watersheds
which
are
expected
to
have
higher
levels
of
acetochlor
after
runoff
events,
based
on
the
size
of
the
watershed
and
its
corn
intensity.
A
higher
percentage
of
CWSs
from
these
strata
were
chosen.

5)
Random
selection
(
using
random
number
generation)
of
the
appropriate
number
of
CWSs
from
each
stratum.
All
CWSs
meeting
the
target
population
criteria
were
selected
from
the
identified
strata
(
for
example,
the
>
20%
corn
intensity,
smaller
watershed
strata).
A
total
of
175
CWSs
were
required
for
the
study.

6)
Collection
of
information
for
each
selected
CWS
regarding
intake
location,
sources
of
water,
treatment,
customer
information,
point
of
finished
water
sampling,
soil
types,
and
corn
intensity
of
the
watershed(
s)
for
that
system.

7)
Removal
of
systems
that
did
not
meet
target
population
criteria
based
on
additional
data
collected.
Systems
were
replaced
in
the
same
stratum
and
state,
if
possible,
by
additional
random
selection
from
the
stratum.
If
there
were
no
systems
available
in
the
same
stratum,
then
a
system
was
randomly
selected
from
another
stratum
with
available
CWSs.

8)
Generation
of
maps
of
watersheds
for
each
CWS.
Data
entry
into
a
Geographical
Information
System
(
GIS).

The
highest
percentage
of
CWSs,
100%
of
the
available
CWSs,
was
selected
from
the
>
20%
corn
intensity
strata,
66%
were
selected
from
the
11­
20%
corn
intensity
strata,
49%
from
the
5­
10%
corn
intensity
strata,
43%
from
the
Continental
River
strata,
and
14%
from
the
Great
Lakes
strata.
Almost
50%
of
the
sites
were
selected
from
smaller
watersheds
with
>
20%
corn
intensity,
the
watersheds
expected
to
have
the
highest
concentrations
of
acetochlor
after
runoff
events.
The
focus
on
more
vulnerable
watersheds
with
higher
corn
intensity
combined
with
the
diversity
of
watersheds
selected
for
this
study
will
allow
us
to
obtain
both
a
worst­
case
and
representative
evaluation
of
the
impact
of
acetochlor
and
other
corn
herbicide
usage
on
surface
drinking
water
in
significant
corn­
growing
areas
of
the
United
States.

5.1.2.
Prospective
Ground
Water
(
PGW)
Studies
ARP
was
also
required
to
conduct
eight
Prospective
Ground
Water
(
PGW)
studies
according
to
the
protocol
approved
for
other
herbicides
in
order
to
determine
the
potential
for
pesticide
transport,
or
a
"
pattern
of
movement".
Specific
details
regarding
the
program
are
provided
by
Newcombe
et
al.
(
2005).
In
general,
sites
were
geographically
located
based
on
representative
product
label
uses,
or
"
in
accordance
with
widespread
and
commonly
recognized
practice,
including
vulnerable
and
typical
use
situations,"
as
outlined
in
the
registration
agreement.
Sites
were
required
to
be
located
on
a
wide
variety
of
soil
textures
as
per
the
product
label,
and
an
effort
was
made
to
include
a
broad
geographical
representation.
Test
sites
were
located
in
the
following
states:
Wisconsin,
Ohio,
Minnesota,
Nebraska,
Iowa,
Indiana,
Pennsylvania,
and
Delaware
(
Figure
3).
Specifics
of
the
study
design
are
provided
in
Table
4.
Newcombe
et
al.,
2005
cites
that
these
areas
corresponded
to
areas
of
significant
acetochlor
use.
Further
details
­
20­

regarding
the
geographic
distribution
of
acetochlor
can
be
found
in
the
"
Acetochlor
Usage"
section
of
this
report.

Figure
3.
States
with
prospective
ground
water
(
PGW)
studies
for
acetochlor.

Table
3.
PGW
sites:
Selected
soil
and
aquifer
characteristics.

PGW
Study
Location
NRCS
Soil
Series;

On­
site
surface
soil
%
O.
M.
&
pH
Subsoil
Textures1
Avg.
Hydraulic
Conductivity2
(
mm/
hr)
Aquifer
soil
textures
determined1
Depth
to
ground
water
3
(
m)
Pore­
water
velocity
(
m/
day)
4
Wisconsin
Richford
loamy
sand
OM
=
1.6%
pH
=
6.4
Loamy
Sand
Sand
Sandy
loam
0­
1.2
m
1.2­
2.4
m
2.4­
3.6
m
3.6­
4.8
m
>
4.8
m
177
358
810
1482
776
Loamy
sand
Sandy
loam
Sand
7.6­
10
1.9
x
10­
3
Ohio
Genessee
silt
loam
Fox
silt
loam
OM
=
2.9%
pH
=
7.7
Clay
loam
Loam
Sandy
loam
0­
1.2
m
1.2­
2.4
m
2.4­
3.6
m
3.6­
4.8
m
>
4.8
m
293
153
NA
NA
NA
Sandy
loam
Loamy
sand
0.6­
5.2
0.8
x
10­
1
Minnesota
Estherville
sandy
loam
OM
=
3.5%
pH
=
6.3
Sandy
loam
Loamy
sand
Sand
0­
1.2
m
1.2­
2.4
m
2.4­
3.6
m
3.6­
4.8
m
>
4.8
m
180
331
NA
NA
NA
Sand
Loamy
sand
Sandy
loam
4.8­
6.4
0.4
x
10­
1
Nebraska
Kenesaw
silt
loam
Coly­
Kenesaw
silt
loam
OM
=
1.8%
pH
=
5.7
Loam
Silt
loam
0­
1.2
m
1.2­
2.4
m
2.4­
3.6
m
3.6­
4.8
m
>
4.8
m
75
45
28
18
84
Silt
loam
Loam
Sandy
loam
7.0­
9.7
0.4
x
10­
2
Iowa
Marshall
silty
Silty
0­
1.2
m
207
Sand
1.2­
8.5
0.9
x
10­
1
­
21­

Table
3.
PGW
sites:
Selected
soil
and
aquifer
characteristics.

PGW
Study
Location
NRCS
Soil
Series;

On­
site
surface
soil
%
O.
M.
&
pH
Subsoil
Textures1
Avg.
Hydraulic
Conductivity2
(
mm/
hr)
Aquifer
soil
textures
determined1
Depth
to
ground
water
3
(
m)
Pore­
water
velocity
(
m/
day)
4
clay
loam
Minden
silty
clay
loam
OM
=
3.9%
pH
=
5.6
clay
loam
Silt
loam
1.2­
2.4
m
2.4­
3.6
m
3.6­
4.8
m
>
4.8
m
84
172
87
1.0
Silt
loam
Loam
Indiana
Door
loam
Lydick
loam
OM
=
3.0%
pH
=
6.7
Sandy
clay
loam
Sandy
loam
Sand
0­
1.2
m
1.2­
2.4
m
2.4­
3.6
m
3.6­
4.8
m
>
4.8
m
64
190
244
742
978
Sand
7­
9.1
0.6
x
10­
1
Pennsylvania
Clarksburg
silt
loam
Duffield
silt
loam
OM
=
2.7%
pH
=
6.3
Loam
Sandy
loam
0­
1.2
m
1.2­
2.4
m
2.4­
3.6
m
3.6­
4.8
m
>
4.8
m
NA
382
138
95
19
NA
Sandy
loam
Loam
1.8 
7.3
0.4
x
10­
1
Delaware
Sassafras
sandy
loam
OM
=
2.9%
pH
=
5.8
Sandy
loam
Loamy
sand
Sand
0­
1.2
m
1.2­
2.4
m
2.4­
3.6
m
3.6­
4.8
m
>
4.8
m
30
86
30
129
NA
Sand
Sandy
loam
Loamy
sand
3.3­
6.1
0.6
x
10­
2
1
Soil
texture
determined
by
3­
fraction
analysis
(%
sand,
silt,
and
clay)
2
Vertical
saturated
hydraulic
conductivity
determined
by
constant
head
permeability
method
3
Depth
to
ground
water
listed
is
below
ground
surface,
and
the
minimum
and
maximum
values
are
of
all
measurements
made
in
the
test
plot
piezometers
during
the
course
of
the
study
4
Average
value
determined
during
the
course
of
the
study
This
table
is
modified
from
a
more
extended
version
by
the
ARP
found
in
Newcombe
et
al.
(
2005).
­
22­

5.1.3.
"
State
Ground
Water"
(
SGW)
Monitoring
Program
In
addition
to
PGW
studies,
the
ARP,
as
part
of
the
"
State
Ground
Water"
Monitoring
program,
was
required
to
monitor
25
ground
water
wells
in
each
of
the
expected
seven
high
use
states
(
WI,
IL,
IA,
MN,
IN,
NE,
KS)
in
Figure
4
all
located
adjacent
to
fields
with
contractually
guaranteed
use
of
acetochlor
and
located
in
areas
representing
a
variety
of
use
conditions
based
on
soil
characteristics,
local
hydrogeology,
and
climatic
conditions.
The
monitoring
data
serve
as
an
early
indication
that
pesticide
residues
may
be
reaching
ground
water.
Risk
managers
can
then
use
this
information
to
assess
the
potential
threat
to
humans.
Specific
details
regarding
the
program
are
provided
in
de
Guzman
et
al.,
(
2004),
but
a
brief
description
of
the
program
design
follows
here.

The
SGW
study
was
set
up
through
the
establishment
of
a
network
of
175
monitoring
sites
in
regions
of
high
corn
production
in
each
of
the
seven
states
chosen
for
this
study.
A
site
selection
scheme
for
the
SGW
wells
was
set
up
using
corn
production
data,
soils
database
information,
and
consultations
with
state
regulatory
officials
to
obtain
a
set
of
wells
representing
a
range
of
soil
textures
typical
of
corn
agriculture
in
those
regions.
Soil
classification
was
not
a
direct
component
of
the
site
selection
procedure.
Soil
survey
data
were
collected
for
each
site
and
are
available
in
the
documents
submitted
to
the
EPA
by
the
ARP.
The
soil
classification
data
are
not
available
in
a
readily
summarized
form
and
are
not
presented
here,
but
details
can
be
found
in
the
ARP
Site
Selection
submission
(
MRID
43899601).

In
general,
ground
water
monitoring
wells
were
to
be
located
down
gradient
of
acetochlor
use
areas
at
a
distance
agreed
upon
by
the
states.
States
participating
in
the
SGW
are
shown
in
Figure
4.
Where
technically
feasible,
ARP
is
required
to
provide
assistance
to
water
system
operators
in
monitoring
for
acetochlor
residues
at
drinking
water
wells.
­
23­

Figure
4.
States
involved
in
the
"
SGW"
ground­
water
monitoring
program
for
acetochlor
and
locations
of
wells.
Source:
De
Guzman
et
al.
(
2005).

Table
4.
Well
characteristic
summary
for
the
SGW
program.
Values
expressed
in
meters
below
ground
surface
(
bgs).

State
Buffer
distance2
T
Screen
length
Depth
to
water
Screening
Depth
Interval3
­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­
meters­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­
Minimums
Maximums
Mean
DTW
 
DTS
Illinois
9.1
­
45.7
4.6
3
­
22.8
2.7­
4.6
7.3­
9.1
2.5
Indiana
15.2
­
45.7
3
<
7.6
­
22.8
5.8­
23.5
8.8­
26.5
3.1
Iowa
9.1
­
45.7
4.6
1.5
­
15.2
1.5­
7.0
6.1­
11.6
6.5
Kansas
9.1
­
30.5
3
4.6
­
22.8
4.0­
22.9
7.0­
25.9
1.2
Minnesota
15.2
­
45.7
3
7.6
­
22.8
4.9­
21.3
7.9­
24.4
3.4
Nebraska
15.2
­
45.7
4.6
3
­
22.8
4.6­
20.4
9.1­
25.0
1.8
Wisconsin
9.1
3
<
7.6
­
15.2
1.2­
14.9
4.3­
18.0
1.4
1
Table
is
adapted
from
Newcombe
et
al.
(
2005);
state
average
difference
between
average
screening
interval
(
DTS)
and
average
depth
to
ground
water
(
DTW)
has
been
added.
2
Distance
between
wellhead
and
nearest
point
of
the
acetochlor
treatment
area.
3
Screening
depth
interval
data
were
extracted
from
master
ground
water
database
submitted
by
ARP.
The
screening
interval
represents
the
positions
of
the
top
and
bottom
of
the
screen
measured
during
installation.
The
first
pair
is
the
minimum
top
of
screen
and
the
maximum
top
of
screen,
the
second
pair
is
the
minimum
bottom
of
screen
and
the
maximum
bottom
of
screen.

5.2.
Design
and
Scope
of
Exposure
Assessment
The
purpose
of
this
assessment
is
to
evaluate
exposure
to
acetochlor
by
reviewing
results
from
the
three
major
acetochlor
data
sets
generated
by
the
ARP
as
described
above
(
two
ground
water
source
based
and
one
surface
water
source
based)
in
the
context
of
other
available
monitoring
data.
The
assessment
focuses
on
the
status
of
acetochlor
in
ground
and
surface
water
with
respect
to
specific
endpoints
triggering
mandatory
requirements
for
implementation
of
mitigation
measures
or
cancellation
of
acetochlor
uses
(
detailed
in
the
conditional
registration
agreement,
USEPA
1994)
and
evaluation
of
the
impact
of
acetochlor
on
drinking
water
sources
in
support
of
human
health
risk
assessments.
ARP
provided
a
fourth
acetochlor
data
set
that
consists
of
incident
investigation
of
ground
water
primarily
around
pesticide
dealer
and
storage
facilities.
The
incident
data
are
only
indirectly
related
to
impacts
from
registered
uses
of
acetochlor
therefore
these
data
have
not
been
included
in
the
direct
exposure
assessment.

Primary
focus
of
this
exposure
assessment
is
on
the
parent
acetochlor,
with
secondary
emphasis
on
acetochlor
degradates
in
water
 
widespread
occurrence.
This
section
deals
with
exposure
to
acetochlor
parent
residues
in
water
and
serves
as
the
basis
of
the
current
Drinking
Water
­
24­

Assessment.
Conclusions
made
about
exposure
to
the
parent
acetochlor
apply
to
the
parent
chemical
only.
Although
this
assessment
is
focused
on
the
parent
acetochlor,
exposure
levels
to
degradates
can
be
quite
significant
and
has
been
characterized
with
secondary
emphasis.
Some
of
the
ARP
monitoring
studies
also
contain
data
on
the
occurrence
of
other
chloroacetanilide
herbicides
(
alachlor
and
metolachlor
and
/
or
other
corn
herbicides
(
atrazine)
 
a
limited
discussion
on
these
data
and
their
utility
for
other
exposure
assessments
will
also
follow
this
section.
A
portion
of
these
data
were
reviewed
for
a
previous
drinking
water
assessment
for
another
pesticide
­
atrazine
(
Environmental
Fate
and
Effects
Division,
OPP,
EPA,
2001).

5.3.
Documents
and
Data
This
assessment
is
based
primarily
on
extensive
surface
water
and
ground
water
monitoring
programs
submitted
in
support
of
acetochlor
registration
and
intended
to
provide
a
reasonably
comprehensive
portrait
of
exposure
levels
possible
in
ground
and
surface
water.
Discussion
of
the
most
relevant
outside
monitoring
programs
for
acetochlor,
most
notably
the
NAWQA
monitoring
program
by
the
USGS,
is
also
provided.
Since
there
were
many
hundreds
of
interim
documents
and
reports
submitted,
only
selected
references
(
but
including
all
final
reports)
are
included
in
the
bibliography.

5.4.
Data
Gaps
The
ARP
monitoring
program
was
designed
to
assess
exposure
or
exposure
potential
to
acetochlor
in
the
context
of
an
evaluation
of
the
compliance
of
the
ongoing
usage
of
acetochlor
with
exposure
limits,
and
other
regulatory
requirements
contained
in
the
Acetochlor
Registration
Agreement
(
USEPA,
1994).

5.5.
Uncertainties
in
the
Drinking
Water
Assessment
A
number
of
uncertainties
must
be
recognized
when
interpreting
this
exposure
assessment.
These
include
the
following:

 
The
surface
drinking
water
supply
(
SDWS)
and
state
ground
water
(
SGW)
monitoring
programs
were
designed
to
focus
on
areas
of
high
acetochlor
use.
The
monitoring
does
not
cover
the
entire
geographic
distribution
of
acetochlor
use.
Geographic
analysis
of
the
SDWS
site
locations
and
acetochlor
use
patterns
seems
to
indicate
that
even
a
number
of
high
acetochlor
use
areas
were
not
monitored.
Conclusions
drawn
in
this
report
apply
only
to
those
areas
monitored
by
the
ARP
and
it
may
not
be
possible
to
generalize
to
all
acetochlor
usage
areas.
This
is
especially
true
for
the
SDWS
where
the
lack
of
sampling
of
raw
(
pre­
facility
treatment)
water
at
most
locations
makes
it
difficult
to
isolate
the
effects
of
site­
specific
usage
and
vulnerability
factors
and
water
treatment
processes
on
the
observed
residue
levels.

 
County
level
sales
data
submitted
separately
by
members
of
the
ARP
from
1994
­
2003
is
arguably
some
of
the
most
extensive
data
available
as
a
close
approximation
of
acetochlor
usage
across
the
US.
As
such,
it
has
been
incorporated
in
this
exposure
assessment
as
a
surrogate
for
acetochlor
use
in
the
mapping
and
statistical
analyses.
It
is
assumed
that
acetochlor
sold
in
an
individual
county
is,
in
general,
also
applied
in
the
­
25­

same
county
and
in
the
same
watershed.
However,
the
exposure
characterization
recognizes
that
inter­
county
as
well
as
inter­
watershed
transfer
of
acetochlor
does
occur
in
some
cases.

 
Acute
exposure
in
this
risk
assessment
is
defined
as
the
overall
maximum
observed
concentration
at
a
site.
The
actual
peak
concentration,
however,
may
have
occurred
between
sampling
times.
Thus,
the
maximum
observed
concentrations
reported
in
this
study
may
underestimate
the
true
maximum
acute
exposure.

5.6.
Environmental
Fate
5.6.1.
Degradation
Pathways
Acetochlor
persistence
in
a
confined
soil
system
appears
to
increase
with
coarser
soil
texture
and
increased
application
rate.
The
half­
lives
in
aerobic
soils
for
the
3,
4.5,
10.5,
41,
and
50
ppm
application
rates
were
8­
12,
14,
110­
245,
55,
and
300
days,
respectively.
However,
the
most
representative
aerobic
soil
half­
life
is
8­
14
days
determined
in
the
Monsanto
study
conducted
in
Ray
silt
loam
(
1.2
X
OM),
Drummer
silty
clay
loam
(
3.4
%
OM),
and
Spinks
sandy
loam
(
2.4
%
OM)
soils
treated
with
3
ppm
( 
2X
label
rate)
of
acetochlor.
The
8­
14
day
half­
life
represents
the
labeled
application
rate
and
the
soils
to
be
treated
with
acetochlor.
The
longer
half­
lives
were
found
only
at
exaggerated
application
rates
(
7.5­
36X)
labeled
rates
to
coarse,
low
organic
matter
soils.
The
aerobic
soil
metabolism
degradates
oxanilic
acid
(
oxamic
acid),
sulfonic
acid,
and
thioacetic
acid
sulfoxide
degradates
of
acetochlor.
These
degradates
are
rearrangement
products
of
one
amino
moiety
of
the
acetochlor
molecule.

Relevant
to
this
discussion
are
label
restrictions
to
which
the
ARP
has
previously
implemented
on
all
product
labels
to
prohibit
acetochlor
use
in
certain
areas
with
ground
water
that
is
highly
vulnerable
to
contamination
by
pesticides
such
as
acetochlor.
Acetochlor
product
use
is
restricted
on
coarse­
textured,
low­
organic­
matter
soils
where
groundwater
is
within
30
feet
of
the
surface.

The
following
language
is
included
with
all
acetochlor
product
labels:

Acetochlor
products
may
not
be
applied
to
the
following
soils,
if
depth
to
groundwater
is
30
feet
or
less:

 
Sands
with
less
than
3%
organic
matter.
 
Loamy
sands
with
less
than
2%
organic
matter.
 
Sandy
loams
with
less
than
1%
organic
matter.

Acetochlor
herbicides
may
be
applied
to
the
above
soils
if
depth
to
groundwater
is
more
than
30
feet.
­
26­

5.6.2.
Soil
Mobility
Parent
acetochlor
has
a
reported
water
solubility
of
223
mg/
l
and
Kd
values
of
0.4­
2.7
ml/
g
in
various
soils
texturally
classified
as
sandy
loam,
loamy
sand,
silt
loam
and
silty
clay
soils.
Acetochlor
also
leached
through
soil
columns.

The
degradates
are
expected
to
have
even
higher
mobility
based
on
structural
features.
Kd
values
for
the
degradates
were
0.15
to
0.97
for
ESA,
0.13
to
0.86
for
OXA,
and
0.10
to
0.90
for
a
third
degradate
(
acetochlor
thioacetic
acid
sulphoxide)
not
included
in
this
exposure
assessment
because
of
the
low
levels
detected
in
environmental
samples
in
previous
studies.
Koc
values
were
21
to
68
in
9
of
10
soils
tested
and
430
in
the
other
soil
(
median
=
57)
for
ESA
and
17
 
124
(
median
=
45)
for
OXA.

The
results
of
studies
submitted
to
support
Subdivision
N
requirements
for
registration
appear
to
be
inconsistent
with
the
laboratory
data
with
respect
to
mobility.
In
at
least
one
study,
leaching
of
oxamic
acid
(
oxanilic
acid)
and
sulfonic
acid
and
thioacetic
acid
sulfoxide
was
observed
to
a
depth
of
18
inches
in
a
silt
loam
soil
in
Illinois
containing
1.7%
organic
matter.
No
leaching
was
detected
in
another
silt
loam
soil
in
Mississippi
containing
only
0.5%
organic
matter.

5.6.3.
Dissipation
Pathways
The
major
routes
of
dissipation
for
acetochlor
appear
to
be
microbially­
mediated
degradation,
runoff,
and
leaching.
Although
acetochlor
generally
degrades
rapidly
when
applied
to
soil,
in
some
field
situations
it
can
be
relatively
persistent
(
e.
g.,
field
dissipation
half­
lives
were
up
to
36
days)
and
it
has
been
found
in
ground
water
at
numerous
locations.
There
is
variable
evidence
as
to
the
persistence
of
acetochlor
in
subsoil
horizons
(
often
persistence
is
increased
substantially
for
organic
pesticides
that
are
subject
to
microbial
degradation)
with
a
published
study
by
the
registrant
reporting
only
a
modest
increase
in
persistence
from
surface
soils
at
two
sites
using
in
situ
methods
(
Mills
et
al.,
2001).
Lavy
et
al.
(
1996)
have
reported
a
much
more
substantial
increase
in
persistence
at
two
sites
(
also
in
situ
studies)
for
alachlor,
a
herbicide
that
is
chemically
related
to
acetochlor
and
tends
to
have
a
very
similar
environmental
fate
profile.
Laboratory
degradation
data
indicate
that
acetochlor
does
not
degrade
by
abiotic
processes
(
hydrolysis
and
photolysis);
this
may
be
to
the
higher
application
rates
than
used
in
the
Mills
et
al.
study.
While
acetochlor
has
relatively
short
half
lives
in
fine­
textured
aerobic
soil,
it
may
be
moderately
persistent
in
coarser
soils
(
this
may
be
related
to
the
lower
rate
of
microbial
activity
in
sandy,
low
organic
matter
soils).

5.7.
Acetochlor
Usage
5.7.1.
Summary
of
Registered
/
Proposed
Uses
Acetochlor
is
restricted
for
direct
use
only
on
field
corn
and
corn
grown
only
for
silage
or
seed.
Labels
allowing
direct
application
to
pop
corn
should
be
amended
to
prevent
such
application
until
the
registrant
formally
petitions
for
the
use.
Although
several
of
the
labels
also
allow
for
a
­
27­

fall
application
to
soybean
stubble
after
crop
harvest,
replanting
the
following
spring
is
restricted
to
field
corn.
Generally,
acetochlor
can
be
applied
as
either
a
single
broadcast
or
banded
application,
preplant,
preemergence,
or
early
post­
emergence.
Preplant
applications
can
be
made
as
either
a
single
or
split
application
that
is
either
surface
applied
or
incorporated.
The
early
post­
emergence
application
is
allowed
only
on
corn
up
to
eleven
inches
in
height.
For
application,
acetochlor
may
be
either
diluted
with
water
or
liquid
fertilizers
or
impregnated
onto
dry
bulk
fertilizers.
Only
applications
using
ground
equipment
are
allowed;
applications
through
irrigation
systems
and
using
aerial
equipment
are
prohibited.

Application
rates
for
acetochlor
are
dependent
on
the
soil
type
and
the
type
of
weeds
to
be
controlled.
However,
the
maximum
single
use
rate
for
any
soil
type
is
3.0
lb
ai/
A,
which
is
also
the
maximum
seasonal
use
rate.
Formulations
containing
only
acetochlor
do
not
specify
pregrazing
(
PGI)
or
preharvest
intervals
(
PHI);
however,
the
multiple
active
ingredient
formulations
contain
PGI
and
PHI
restrictions
that
are
based
on
the
other
active
ingredients
included
in
the
formulation.
Following
application
with
acetochlor,
the
labels
only
allow
for
rotation
to
soybeans,
corn
(
all
types),
grain
sorghum
(
milo),
wheat,
or
tobacco.

Due
to
concerns
about
ground
water
contamination,
at
the
time
of
the
original
registration
on
corn
the
ARP
volunteered
to
prohibit
use
in
certain
areas
with
ground
water
that
is
highly
vulnerable
to
contamination
by
pesticides
such
as
acetochlor.
Acetochlor
product
use
was
and
is
restricted
on
coarse­
textured,
low­
organic­
matter
soils
where
groundwater
is
within
30
feet
of
the
surface.
The
following
language
is
included
with
all
acetochlor
product
labels:

Acetochlor
products
may
not
be
applied
to
the
following
soils,
if
depth
to
groundwater
is
30
feet
or
less:

°
Sands
with
less
than
3%
organic
matter.
°
Loamy
sands
with
less
than
2%
organic
matter.
°
Sandy
loams
with
less
than
1%
organic
matter.
°
Acetochlor
herbicides
may
be
applied
to
the
above
soils
if
depth
to
groundwater
is
more
than
30
feet.

Acetochlor
is
now
registered
in
42
states
as
well
as
the
District
of
Columbia
(
Hackett
et
al.,
2004).
It
is
also
used
in
corn
growing
areas
of
several
countries
including
China,
Europe,
and
Argentina.
In
the
United
States,
the
ARP
has
submitted
petitions
for
other
direct
field
uses
of
acetochlor
including
application
to
sweet
corn
and
sorghum
for
grain
or
silage
/
forage.

5.7.2.
Usage
Targets
in
the
Original
Acetochlor
Conditional
Registration
Acetochlor
is
effective
on
a
broad
spectrum
of
weeds
in
corn
fields
and
it
therefore
was
expected
that
reductions
in
overall
corn
herbicides
would
occur.
As
such,
the
conditional
registration
agreement
mandated
a
33
percent
reduction
in
the
aggregate
use
of
the
selected
corn
herbicides
(
alachlor,
metolachlor,
atrazine,
EPTC,
butylate,
and
2,4­
D)
over
a
five
year
period.
Cancellation
of
the
conditional
registration
agreement
would
be
triggered
if
any
one
of
the
following
usage
target
levels
were
not
met:
­
28­

1.
At
the
end
of
18
months
from
the
date
of
registration,
a
net
cumulative
reduction
of
the
six
corn
herbicides
by
4
million
pounds
(
4
M
lbs)
from
1992
levels,
adjusted
for
planted
acreage
differences;
or
2.
At
the
end
of
three
years
from
the
date
of
registration,
a
net
cumulative
reduction
of
the
six
corn
herbicides
of
22.6
M
lbs
from
1992
levels,
adjusted
for
planted
acreage
differences;
or
3.
At
the
end
of
five
years
from
the
date
of
registration,
a
net
cumulative
reduction
of
the
six
corn
herbicides
of
66.3
M
lbs
from
1992
levels,
adjusted
for
planted
acreage
differences.

Based
on
OPPs
Biological
and
Economic
Analysis
Division's
analysis,
it
appears
that
increased
use
of
acetochlor
did
result
in
a
decrease
in
the
combined
use
of
the
six
selected
herbicides.
OPP/
BEAD's
review
of
the
usage
data
submitted
by
ARP
concluded
that
the
18
month,
three
year,
and
five
year
target
reductions
were
achieved.
The
cumulative
net
reduction
for
the
three
year
target
(
22.6
M
lbs)
was
exceeded
by
1996,
and
the
five
year
target
(
66.3
M
lbs)
was
exceeded
by
4
M
lbs
in
1998.
Overall,
the
proportion
of
acetochlor
used
relative
to
other
pesticides
steadily
increased
based
on
USDA
and
Doane
Marketing
Research
surveys.
These
research
surveys
indicate
that
the
percent
of
field
corn
treated
specifically
with
acetochlor
increased
from
7
percent
in
1994
to
24
percent
in
1997.
This
increase
amounted
to
an
increase
in
total
acetochlor
use
(
based
on
surveys
of
39
states)
from
7.4
M
lbs
in
1994
to
31.8
M
lbs
by
1998.

At
the
time
of
its
registration,
the
increase
in
acetochlor
use
was
of
particular
concern
since
it
was
listed
as
a
probable
human
carcinogen
(
a
classification
which
it
still
maintains),
and
therefore
exposure
to
acetochlor
in
drinking
water
contamination
may
pose
a
human
health
risk.
In
anticipation
of
its
widespread
use,
several
use
restrictions
were
implemented
as
preventative
measures.
Specifically,
acetochlor
may
only
be
applied
by
certified
applicators.
It
may
not
be
applied
to
coarse
soils
(
e.
g.,
sands
with
less
than
3%
organic
matter)
where
depth
to
ground
water
is
less
than
30
feet.
Acetochlor
cannot
be
applied
through
any
irrigation
system
(
including
flood
irrigation),
nor
via
aerial
application.
Acetochlor
may
not
be
applied
directly
to
water
or
areas
where
surface
water
is
present.
In
addition,
acetochlor
must
not
be
mixed
or
loaded
within
50
feet
of
surface
water
or
wells,
unless
proper
containment
and
disposal
measures
are
in
place.
Each
of
these
measures
is
intended
to
prevent
acetochlor
from
migrating
to
ground
water
and/
or
surface
water
resources.

5.7.3.
Geographic
Patterns
of
Acetochlor
Use
This
summary
only
presents
selected
data
on
acetochlor
usage
from
non­
confidential
sources.
Presently,
roughly
80%
of
the
total
use
of
acetochlor
in
the
United
States
occurs
in
the
Midwest.
The
usage
areas
generally
mirror
the
production
areas
for
field
corn
(
Figure
5
and
Figure
6
).

Detailed
annual
county­
level
sales
maps
for
1994
to
2003
are
provided
in
Appendix
section
12.3
Acetochlor
Usage
 
Detailed
Summary.
These
sales
data
have
been
provided
separately
by
members
of
the
acetochlor
registration
partnership
(
ARP)
as
confidential
information
and
cannot
be
shared
with
unauthorized
individuals.
These
sales
data
are
presented
as
a
surrogate
for
the
location
of
acetochlor
usage.
It
should
be
noted
that
pesticide
sales
data
may
not
be
a
consistent
­
29­

estimator
of
usage
in
any
particular
watershed
because
usage
does
not
necessarily
occur
near
the
location
of
purchase
and
watershed
boundaries
do
not
coincide
with
county
boundaries
(
all
sales
data
were
reported
by
county
units).

The
following
language
is
included
with
all
acetochlor
product
labels:

Acetochlor
products
may
not
be
applied
to
the
following
soils,
if
depth
to
groundwater
is
30
feet
or
less:

 
Sands
with
less
than
3%
organic
matter.
 
Loamy
sands
with
less
than
2%
organic
matter.
 
Sandy
loams
with
less
than
1%
organic
matter.

Acetochlor
herbicides
may
be
applied
to
the
above
soils
if
depth
to
groundwater
is
more
than
30
feet.

Figure
5.
Corn
production
intensity
(
2002
Census
of
Agriculture
data)
and
general
locations
of
drinking
water
intakes
sampled
in
the
ARP's
SDWS
monitoring
program
(
white
=
no
reported
corn
acreage,
green
=
lowest
intensity
category,
red
=
highest
corn
intensity
category).

Figure
5
shows
corn
production
intensity
and
the
generalized
locations
of
the
ARP
SWDS
monitoring
locations
(
2002
Census
of
Agriculture
data,
see
Appendix
B
for
maps
based
on
1992
and
1997
Census
of
Agriculture
data).
Figure
6
provides
the
USGS
estimate
of
acetochlor
usage
­
30­

in
the
United
States
for
1997.
Note
that
this
map
is
a
coarse
estimate
and
should
not
be
used
for
decision
making
at
the
county
level.
The
USGS
provides
the
following
caveat
with
the
data:
"
The
pesticide
use
map
shows
regional­
scale
patterns
of
use
intensity
within
the
United
States
and
[
is]
not
intended
for
making
local­
scale
estimates
of
pesticide
use,
such
as
for
individual
counties.
The
USGS
maps
are
based
on
state­
level
estimates
of
pesticide
use
rates
for
individual
crops,
which
have
been
compiled
by
the
National
Center
for
Food
and
Agricultural
Policy
(
NCFAP)
for
1995­
1998,
and
on
1997
Census
of
Agriculture
county
crop
acreage.
Key
limitations
include:
(
1)
state
use­
coefficients
represent
an
average
for
the
entire
state
and
consequently
do
not
reflect
the
local
variability
of
pesticide
management
practices
found
within
many
states
and
counties,
and
(
2)
the
county­
level
acreage
are
based
on
the
1997
Census
of
Agriculture
and
may
not
represent
all
crop
acreage
due
to
Census
non­
disclosure
rules.

Figure
6.
USGS
estimated
acetochlor
use
for
1997.

5.8.
Overview
of
Exposure
Assessment
This
exposure
assessment
is
based
primarily
on
an
extensive
monitoring
program
submitted
by
the
ARP
as
a
requirement
for
registration
of
acetochlor.
Other
monitoring
data
and
modeling
results
are
also
discussed
in
order
to
provide
a
more
complete
picture
of
exposure
to
acetochlor.
Section
6
deals
with
parent
acetochlor
exposure,
Section
7
evaluates
exposure
to
degradates
of
acetochlor,
and
Section
8
provides
an
overview
of
the
extensive
body
of
monitoring
data
for
other
herbicides
and
herbicide
degradates
(
including
parent
atrazine,
and
parent
+
degradates
of
­
31­

alachlor
and
metolachlor)
that
the
ARP
compiled
in
the
course
of
conducting
some
major
surface
water
and
ground
water
studies
to
support
the
acetochlor
registration.

Uniquely
relevant
to
OPP's
exposure
assessment
for
acetochlor
is
an
evaluation
of
the
detection
rates
and
amounts
in
the
ARP
monitoring
studies
relevant
to
endpoints
identified
in
the
original
Acetochlor
Registration
Agreement
which
could
trigger
requirements
for
mitigation
or
cancellation
of
uses
should
the
endpoints
be
exceeded.
There
are
unique
endpoints
identified
for
each
of
the
three
major
ARP
monitoring
programs
(
SDWS,
PGW,
and
SGW)
as
well
as
for
outside
monitoring;
these
are
discussed
separately
for
each
of
these
monitoring
programs.
At
this
time,
only
acetochlor
parent
residues
have
been
identified
as
relevant
to
the
regulatory
triggers.

Precedence
in
the
review
of
the
monitoring
data
is
given
to
acetochlor
parent
based
upon
a
presumption
that
the
current
risk
assessment
will
focus
on
exposure
to
acetochlor
parent.
The
Health
Effects
Division
(
HED)
of
the
Office
of
Pesticide
Programs
has
evaluated
currently
available
toxicity
and
carcinogenicity
data
and
determined
that
the
dietary
drinking
water
risk
assessment
should
be
based
upon
parent
acetochlor
alone
(
HED,
2004).

Although
not
anticipated
to
be
included
in
the
current
drinking
water
risk
assessment
the
degradate
data
are
also
included
in
this
exposure
assessment
in
a
separate
section
of
this
document.
The
primary
reason
for
this
is
to
document
the
data
submitted
by
the
ARP
which
show
exposure
levels
to
acetochlor
degradates
that
are
frequently
higher
than
acetochlor
and
many
other
pesticide
residues
and
are
widespread
(
Table
27
and
Table
1);
see
below
for
a
complete
characterization).
Some
of
the
ARP
monitoring
studies
also
contain
data
on
the
occurrence
of
other
chloroacetanilide
herbicides
(
alachlor
and
metolachlor)
and
/
or
other
corn
herbicides
(
atrazine)
 
a
limited
discussion
on
these
data
and
their
utility
for
other
exposure
assessments
also
follows
this
section
(
See
"
Other
Chemicals"
section
of
this
document).
A
portion
of
these
data
were
reviewed
for
a
previous
drinking
water
assessment
for
atrazine
(
Environmental
Fate
and
Effects
Division,
OPP,
EPA,
2001).

6.
RESIDUES
­
ACETOCHLOR
PARENT
The
focus
of
the
current
risk
assessment
is
on
the
parent
acetochlor,
with
secondary
emphasis
on
acetochlor
degradates
in
water
and
their
widespread
occurrence.
The
assessment
focuses
on
the
status
of
acetochlor
in
ground
and
surface
water
with
respect
to
specific
endpoints
triggering
mandatory
requirements
for
implementation
of
mitigation
measures
or
cancellation
of
acetochlor
uses
(
detailed
in
the
conditional
registration
agreement,
USEPA
1994)
and
to
evaluate
the
impact
of
acetochlor
on
drinking
water
sources
in
support
of
human
health
risk
assessments.
The
following
sections
present
time­
weighted
annualized
means
an
95th
percentile
values,
as
well
as
the
methodology
implemented
to
compute
these
values.
Assessments
of
acute
and
chronic
exposure
are
also
provided
for
each
of
the
three
surfaces
and
ground
water
monitoring
programs.

6.1.
Data
Files
Used
­
32­

Table
5
lists
the
data
files
used
for
computing
annualized
means
and
summary
statistics
for
each
data
set.

Table
5.
Key
data
files
submitted
by
the
ARP
used
in
this
assessment
Data
set
File
Name
Modified
SDWS
Data:
Surface
water
monitoring
concentrations
File
Name:
swm_
conc.
xls
Datswm_
anc.
xls
cws­
population­
served.
xls
2/
10/
2003
2/
10/
2003
9/
17/
04
SGW
master
SGM
reporting
dbase.
mdb;
Table
"
tblGWM_
all"
6/
25/
2002
PGW
http://
www.
arpinfo.
com/
download/
pgw/
PGW_
NUM_
FINAL.
TXT
(
All
observed
concentrations
in
the
PGW
studies)
http://
www.
arpinfo.
com/
download/
pgw/
pgw_
uncensored.
xls
(
Uncensored
data
provided
ARP
for
computation
of
TWAMs
and
Percentiles)
4/
22/
04
10/
2/
04
6.2.
Time
Weighted
Annualized
Means
and
95th
Percentile
Calculations
Time­
weighted
annualized
means
(
TWAMs)
were
calculated
for
each
site
in
the
three
major
monitoring
programs
(
SDWS,
SGW,
and
PGW).
Two
separate
weighting
methods
were
implemented
using
a
custom­
built
TWAM
computer
program
to
verify
the
TWAMs
computed
by
the
ARP.
The
weighting
method
used
by
the
ARP
(
described
below)
was
cross­
checked
with
a
slightly
different
method
implemented
in
the
WARP
beta
model
developed
by
the
USGS
(
USGS
2004).
Both
weighting
methods
assign
a
weight
to
each
discrete
sample
observation
based
upon
the
fraction
of
the
time
during
a
year
that
each
sample
represents.
Weighted
concentrations
are
then
summed
to
provide
an
annualized
mean.

6.2.1.
ARP
Weighting
Methodology
The
weighting
method
implemented
by
the
ARP
(
equation
1)
calculates
annual
means
based
on
the
calendar
year.
January
1
­
December
31).
Separate
time­
weighted
annualized
means
are
computed
for
each
combination
of
analyte,
site
id,
sample
type,
and
year.
Weighted
concentrations
are
computed
based
on
a
two­
step
process.
First,
an
average
concentration
is
calculated
as
the
sum
of
a
value
and
the
previous
value
divided
by
two.
A
weighting
factor
is
then
calculated
as
the
time
interval
between
a
value
and
the
previous
value,
divided
by
the
time
in
1
year.
The
final
weighted
concentration
is
the
product
of
the
average
concentration
and
the
corresponding
weight
factor.
­
33­

Equation
1
:

TWAM=
(
c1+
c0)
(
t1­
t0)/
2
+
(
c2+
c1)
(
t2­
t1)/
2
+  .+(
cn+
cn­
1)
(
tn­
tn­
1)/
2
+(
cn)
(
tf­
tn)
Daysyr
Where
"
c"
is
the
observed
concentration,
"
t"
is
the
sample
date,
"
Daysyr"
is
the
total
number
of
days
in
the
given
year
(
accounts
for
leap
years),
and
"
n"
is
the
total
number
of
observations
in
the
given
year.
The
subscripts
represent
the
observation
number
where
"
0"
is
Jan
1st
at
0
hours,
and
"
f"
is
December
31st
at
2400
hrs,
note
that
this
is
slightly
different
than
ARP's
code,
which
does
not
include
the
time
from
0
hrs
to
2400
hrs
on
December
31st.
Each
annualized
mean
begins
January
1st.
Therefore,
for
each
new
year,
a
January
1st
concentration
must
be
calculated.
This
is
done
based
on
linear
interpolation
between
the
last
record
of
the
previous
year
and
the
first
record
of
next
consecutive
year.
For
the
first
record
in
the
set,
there
is
no
previous
year
for
the
first
sample
of
a
new
site.
The
first
concentration
is
used
as
the
mean
concentration
from
January
1st
to
the
first
observation
at
that
site.
Similarly,
for
the
last
year
in
record
in
a
data
set
("
Cn"
and
"
tf"),
the
last
concentration
is
used
as
the
mean
concentration
through
the
end
of
the
year.

6.2.2.
USGS
WARP
Beta
Model
Weighting
Methodology
The
USGS
beta
model
weighting
method
(
equation
2)
also
calculates
time
weighted
annualized
means
based
on
the
calendar
year
(
January
1
­
December
31).
This
method
is
different
from
the
ARP
method,
as
individual
weights
are
computed
as
"
the
amount
of
time
extending
from
onehalf
the
time
interval
between
a
value
and
the
preceding
value
and
one­
half
the
time
interval
extending
from
the
value
to
the
subsequent
value,
divided
by
the
total
time
in
1
year....
The
annual
mean
concentration
is
simply
the
sum
of
the
sample
weight
times
the
sample
concentrations"
(
USGS
2004).

Equation
2:

TWAM=
(
c1)
[(
t1­
t0)
+(
t2­
t1)/
2]
+
(
c2)
([(
t3­
t2
)
+
(
t4­
t3)]
/
2)
+  .+
(
cn)
[(
tn­
tn­
1
)/
2
+
(
tf­
tn)]
Daysyr
Where
"
c"
is
the
observed
concentration,
"
t"
is
the
sample
date,
"
Daysyr"
is
the
total
number
of
days
in
the
given
year
(
accounts
for
leap
years),
and
"
n"
is
the
total
number
of
observations
in
the
given
year.
The
subscripts
represent
the
observation
number
where
"
0"
is
Jan
1st
at
0
hours,
and
"
f"
is
December
31st
at
2400
hrs.
Each
annualized
mean
begins
January
1.

This
method
requires
special
conditions
to
handle
leap
years
as
well
as
the
first
and
last
records
of
a
subset
(
e.
g.,
unique
combination
of
site,
type,
and
year).
The
Visual
Basic
for
Applications
(
VBA)
workbook
developed
for
the
TWAM
calculations
automatically
accounts
for
leap
years
using
a
custom­
built
visual
basic
procedure.
In
cases
of
leap
years,
the
weighting
factors
are
divided
by
366
rather
than
365.
Additionally,
for
the
first
record
of
a
year,
the
weighting
factor
is
calculated
as
the
time
interval
between
a
value
and
January
1st
of
the
corresponding
year,
and
one­
half
the
time
interval
extending
from
the
value
to
the
subsequent
value,
divided
by
the
total
time
in
1
year.
For
the
last
record
of
a
year
in
a
subset
the
weighting
factor
is
calculated
as
one
­
34­

half
the
time
interval
between
a
value
and
the
preceding
value
plus
the
time
interval
extending
from
the
value
to
December
31st
of
the
corresponding
year,
divided
by
the
total
time
in
1
year.

6.2.3.
95th
Percentile
Calculations
The
95th
percentile
concentration
was
also
computed
for
each
calendar
year
of
observations
at
a
site.
In
this
analysis,
a
given
percentile
represents
the
fraction
of
the
year
that
the
concentration
was
at
or
below
the
given
percentile
of
the
distribution
of
concentration
values.
This
method
is
based
on
the
method
implemented
in
the
USGS
WARP
beta
model
(
USGS
2004).
In
general,
the
95th
percentile
indicates
that
95%
of
the
time
the
value
was
at
or
below
the
given
concentration.
Percentiles
were
calculated
in
several
steps.
First,
the
observed
concentrations
within
a
year
for
a
given
site
and
sample
type
are
ranked
from
low
to
high.
The
corresponding
weighting
factors
(
calculated
as
the
fraction
of
the
year
the
individual
concentration
represents
based
on
one
of
the
weighting
methods
described
above)
are
then
summed
to
obtain
a
cumulative
distribution
function
(
CDF),
the
sum
of
which
equals
1.
The
concentration
for
each
percentile
is
then
obtained
by
matching
the
percentile
values
to
the
CDF.
If
a
percentile
falls
between
two
values
in
the
CDF,
the
corresponding
weight
and
concentration
is
then
linearly
interpolated.
In
some
cases,
the
weight
corresponding
to
the
lowest
observed
concentration
is
greater
than
a
desired
percentile;
in
these
cases,
exact
percentiles
could
not
be
calculated.
Specific
details
for
each
weighting
method
are
described
in
the
following
sections.

6.3.
Surface
Water
6.3.1.
ARP
Data
Time
weighted
annualized
means
were
calculated
using
the
method
described
in
the
prior
section
(
implemented
by
TWAM
Tool
version
2.0).
The
weighting
method
used
was
the
same
method
as
that
used
by
the
ARP
in
the
data
submission
to
USEPA,
with
the
exception
of
one
modification
in
the
code
to
account
for
the
last
day
of
the
year
in
each
site
subset.
As
described
earlier,
Table
3
lists
the
files
used
in
computing
TWAMs.
For
the
surface
drinking
water
supplies
(
SDWS),
separate
TWAMs
were
computed
for
"
finished",
"
raw"
sample
types.
Finished
(
or
treated)
water
samples
were
sampled
post­
treatment
and
the
water
treatment
system
outflow.
Raw
(
or
untreated)
samples
were
collected
prior
to
treatment
at
the
treatment
system
intake.
A
total
of
189
individual
drinking
water
supplies
were
monitored
(
Table
2).

6.3.1.1.
Regulatory
Action
Endpoints
The
conditional
registration
agreement
includes
a
number
of
regulatory
action
endpoints
that,
if
exceeded
by
acetochlor
or
its
related
degradates
of
toxicological
concern,
would
trigger
mitigation
measures
or
the
cancellation
of
acetochlor
registration
(
USEPA
1994).
These
endpoints
are
discussed
in
detail
in
the
"
Regulatory
History"
report
provided
in
an
earlier
­
35­

deliverable.
A
brief
list
of
the
cancellation
triggers
and
the
results
of
the
ARP
monitoring
program
are
provided
below.

In
addition
to
mitigation/
cancellation
endpoints,
acute
and
chronic
exposure
to
acetochlor
and
its
degradates
in
surface
drinking
water
was
also
of
concern.
For
the
purposes
of
this
analysis,
acute
exposure
was
defined
as
the
overall
maximum
instantaneous
concentration
observed
at
a
site.
This
approach
may
underestimate
actual
acute
exposure
since
typically
only
14
samples
were
collected
each
year
(
generally
bi­
weekly
samples
collected
during
late
winter
to
late
fall)
and
it
is
unlikely
that
the
sampling
times
coincided
with
peak
annual
acetochlor
concentrations.
Chronic
exposure
was
defined
using
both
the
maximum
time­
weighted
average
and
mean
time­
weighted
annual
average
for
a
site.

6.3.1.1.1.
Endpoint
1:
2.0
ppb
TWAM
The
conditional
registration
agreement
states
that
"
If
one
(
1)
community
water
supply
system,
that
derives
its
water
primarily
from
surface
water,
detects
an
annual
time­
weighted
mean
concentration
of
2.0
ppb,
then
the
use
of
acetochlor
in
the
related
watershed
will
be
prohibited.......
or;
the
ARP
will
absorb
100%
of
the
costs
required
to
restore
the
community
water
supply
system
to
compliance."
Cancellation
would
automatically
occur
if
two
large
community
water
supply
systems
or
ten
community
water
supply
systems
of
any
size
observed
time­
weighted
mean
concentrations
of
2.0
ppb
or
were
out
of
compliance.

No
time­
weighted
annualized
means
for
acetochlor
exceeded
2.0
ppb
(
Table
6).
For
both
raw
and
finished
surface
drinking
water,
roughly
99%
of
the
time­
weighted
annualized
means
were
below
0.5
ppb.

Table
6.
Frequency
of
time­
weighted
annualized
mean
concentrations
(
ppb)
for
the
parent
acetochlor
herbicide
in
raw
and
finished
water
drinking
water.

Raw
Finished
Bin
Frequency
Cumulative
%
Frequency
Cumulative
%

0
0
0.00%
12
1.01%

0
 
0.003
33
13.87%
395
34.40%

0.003
 
0.005
48
34.03%
115
44.13%

0.005
 
0.01
34
48.32%
138
55.79%

0.0
 
0.05
63
74.79%
333
83.94%

0.05
 
0.1
25
85.29%
93
91.80%

0.1
 
0.5
34
99.58%
94
99.75%

0.5
 
1.0
1
100.00%
2
99.92%

1.0
­
2.0
0
100.00%
1
100.00%

>
2
0
100.00%
0
100.00%

Total
238
1183
6.3.1.1.2.
Endpoint
2:
8.0
ppb
Instantaneous
Concentration
­
36­

The
conditional
registration
agreement
(
USEPA
2004)
also
states
that
"
If
any
community
water
supply
system
that
derives
its
water
primarily
from
surface
water
detects
a
single
peak
acetochlor
concentration
of
8.0
ppb,
the
ARP
will
make
biweekly
sampling
of
that
system
throughout
the
following
12
months
to
determine
whether
the
2.0
ppb
annual
time­
weighted
mean
concentration
has
been
exceeded."
Acetochlor
was
detected
above
8.0
ppb
in
2
cases
for
the
finished
water
samples
(
Table
7),
however,
the
twelve
month
annualized
mean
did
not
exceed
2.0
ppb
(
Table
6)
since
none
of
the
sites
exceeded
an
acetochlor
TWAM
of
2.0
ppb.
Acetochlor
concentrations
in
SDWS
were
the
highest
of
all
three
studies,
followed
by
raw
surface
water
samples,
state
ground
water
samples,
and
PGW
studies
as
indicated
by
the
cumulative
frequency
distribution
(
CDF)
for
all
sample
observations
(
Figure
7).
The
lines
on
the
CDF
represent
the
percent
of
samples
(
frequency)
that
were
detected
at
or
below
the
corresponding
concentration.
For
example,
roughly
80%
of
all
raw
(
untreated)
water
samples
in
the
SDWS
drinking
water
program
were
less
than
or
equal
to
0.05
ppb.

Table
7.
Frequency
of
occurrence
for
all
instantaneous
parent
acetochlor
concentrations
(
ppb)
in
raw
and
finished
water
drinking
water.

Finished
Water
RAW
Water
Bin
Frequency
Cumulative
%
Frequency
Cumulative
%

0
4297
26.00%
530
15.94%

0.0
 
0.003
3107
44.80%
538
32.12%

0.003
­
0.005
1502
53.88%
325
41.89%

0.005
­
0.01
2084
66.49%
536
58.02%

0.01
­
0.05
3279
86.33%
808
0
0.05
­
0.1
832
91.37%
188
87.97%

0.1
­
0.5
1096
98.00%
279
96.36%

0.5
­
1
183
99.10%
71
98.50%

1
­
4
136
99.93%
47
99.91%

4
­
8
10
99.99%
3
100.00%

>
8
2
100.00%
0
100.00%

Total
16528
3325
­
37­

Cumulative
Frequency
of
Acetochlor
Observations
0%
20%
40%
60%
80%
100%
120%

0
0.003
0.005
0.01
0.05
0.1
0.5
1
2
4
8
>
8
Concentration
(
ppb)
Cumulative
Frequency
PGW
Shallow
Wells
PGW
9ft
Lysimeter
SGW
SDWS
finished
SDWS
Raw
Figure
7.
Cumulative
frequency
distribution
for
all
acetochlor
observations
for
each
study.
PGW
data
represented
include
separate
distributions
for
the
9­
foot
depth
lysimeter
data
and
the
shallow
groundwater
wells
for
each
study.

6.3.1.2.
Acute
Exposure
Maximum
exposures
for
acetochlor
parent
were
generally
higher
at
the
SDWS
sites
than
the
PGW
and
SGW
sites
(
Figure
8).
Roughly
85%
of
the
SDWS
maximum
overall
peak
finished
observations
for
each
site
were
below
2.0
ppb
and
80%
of
maximum
overall
peak
raw
water
observations
for
each
site
were
below
2.0
ppb.
Approximately
99%
of
the
PGW
and
SGW
peak
observations
were
below
2.0
ppb.
Median
values
were
0.3
for
SDWS
raw
water,
0.25
for
SDWS
finished
water,
0.02
for
SGW
ground
water,
and
0.004
for
PGW
ground
water
studies.
The
majority
of
overall
maximum
peak
acetochlor
concentrations
for
each
site
in
the
state
ground
water
(
SGW)
program
were
less
than
0.05
ppb.
­
38­

Cumulative
Acute
Exposure
Based
on
Maximum
Acetochlor
Concentrations
0.0%
20.0%
40.0%
60.0%
80.0%
100.0%
120.0%

0
0.003
0.005
0.01
0.05
0.1
0.5
1
2
4
8
>
8
Concentration
(
ppb)
Cumulative
Frequency
PGW
SGW
SDWS
Finished
SDWS
Raw
Figure
8.
Cumulative
frequency
distribution
for
acetochlor
acute
exposure
in
all
ARP
studies,
based
on
the
maximum
observed
concentration
at
each
site.
PGW
data
maximum
exposures
are
provided
for
each
lysimeter
and
each
depth.

Acute
Exposure
Based
on
Maximum
Acetochlor
Concentrations
0
20
40
60
80
100
120
0
0.003
0.005
0.01
0.05
0.1
0.5
1
2
4
8
>
8
Concentration
(
ppb)
Frequency
SDWS
Finished
SDWS
Raw
SGW
PGW
Figure
9.
Distribution
of
acute
exposure,
based
on
the
maximum
observed
concentration
at
each
site.
PGW
data
maximum
exposures
are
provided
for
each
lysimeter
and
each
depth.
­
39­

6.3.1.3.
Acute
and
Chronic
Exposure
Distribution
by
Population.

Acute
Exposure
by
Population
Served
(
Finished
Water)

214­
GI­
IL
(
18.2)
157­
MA­
IL
(
7.9)

455­
MO­
OH
(
11.1)
330­
LO­
IN
(
7.4)

0
5
10
15
20
0.2
1.0
2.0
3.2
5.0
8.0
16.0
36.5
82.0
Population
Served
(
thousands)

Maximum
Concent
ration
(
ppb)
Acute
Exposure
by
Population
Served
(
Raw
Water)

168­
PA­
IL
7.2
228­
SA­
IL
7.1
0
1
2
3
4
5
6
7
8
0.4
1.7
3.6
4.5
10.0
12.0
18.0
32.0
50.0
76.0
125.0
Population
Served
(
thousands)
A
B
Figure
10.
Acute
acetochlor
exposure
distribution
by
population
served
for
raw
(
A)
and
finished
(
B)
water
samples.
­
40­

Chronic
Exposure
by
Population
Served
(
Raw
Water)

0
0.05
0.1
0.15
0.2
0.25
0.3
0.2
1.0
1.7
3.0
4.5
6.5
10.0
20.0
42.5
89.5
Population
Served
(
thousands)

Ave
rage
Time­
We
ighted
Annual
iz
ed
Mean
(
ppb)
B
Chronic
Exposure
by
Population
Served
(
Raw
Water)

345­
RI­
IN
0.14
168­
PA­
IL
0.19
0
0.05
0.1
0.15
0.2
0.4
1.7
3.6
4.5
10.0
12.0
18.0
32.0
50.0
76.0
125.0
Population
Served
(
thousands)
A
Figure
11.
Chronic
exposure
to
parent
acetochlor
in
raw
surface
drinking
water
(
SDWS)
using
the
average
time­
weighted
mean
at
each
site.
­
41­

6.3.1.4.
Chronic
Exposure
Distribution
by
System
Figure
12.
Cumulative
frequency
distribution
for
parent
acetochlor
chronic
exposure,
based
on
the
highest
timeweighted
annual
mean
at
each
site.
PGW
chronic
exposures
are
the
maximum
TWAM
for
each
cluster
at
9­
foot
depth
for
lysimeters
and
shallow
monitoring
wells
for
ground
water.
Cumulative
Chronic
Exposure
Based
on
Maximum
Acetochlor
TWAMs
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%

0
0.003
0.005
0.01
0.05
0.1
0.5
1
2
4
8
>
8
TWAM
(
ppb)
Cumulative
Frequency
PGW­
Shallow
Ground
Water
PGW
9
ft
lysimeters
SDWS­
Finished
SDWS­
Raw
SGW
Maximum
Observed
TWAMs:
PGW,
9
ft.
=
0.178
PGW,
gw
=
0.008
SDWS,
fin.
=
1.428
SDWS,
raw
=
0.591
SGW
=
0.520
­
42­

6.3.2.
Surface
Water
Factorial
Analysis
For
parent
acetochlor,
the
most
toxic
of
residues,
surface
water
is
the
dominant
medium
of
exposure.
Consequently,
the
focus
of
statistical
analysis
was
on
factors
related
to
occurrence
in
surface
drinking
water
supplies.
Statistical
analyses
examined
environmental
variables
that
could
potentially
explain
the
spatial
variability
among
sites
(
e.
g.,
watershed
size,
corn
intensity,
etc.).
In
addition,
the
relationship
between
raw
and
finished
samples
was
examined
to
determine
the
effects
of
water
treatment.

Appendix
12.7
presents
correlation
matrices
for
surface
drinking
water
sites,
individually
for
raw
and
finished
water
samples.
A
number
of
hypothesized
explanatory
variables
were
examined
including
watershed
area,
average
watershed
sales
(
1994­
2003),
the
mean
sales
(
1994)
for
the
county
with
the
overall
highest
sales
in
each
watershed,
watershed
runoff,
watershed
corn
intensity,
30­
yr
average
precipitation,
and
30­
yr
average
spring
precipitation
(
April
 
June).
In
general,
the
ancillary
variables
that
were
available
were
unable
to
explain
a
significant
amount
of
the
variability
in
maximum
observed
concentrations
(
acute
exposure),
average
TWAMS,
and
maximum
TWAMs
(
chronic
exposure).
It
was
originally
expected
that
acetochlor
acute
and
chronic
exposure
would
be
moderately
to
strongly
correlated
with
the
variability
in
acetochlor
sales
in
the
associated
watersheds,
however
sales
were
only
weakly
correlated
(
r
<
0.5).

Some
associations
were
observed
between
ancillary
variables
as
expected.
For
example,
watershed
corn
intensity
was
moderately
to
strongly
correlated
with
the
watershed
runoff
curve
number
(
RCN)
with
correlation
coefficients
(
r)
ranging
from
0.78
for
all
sites
where
raw
water
samples
were
collected
to
0.82
for
only
those
sites
where
finished
water
samples
were
collected.
The
correlation
between
runoff
curve
number
and
watershed
corn
intensity
is
not
surprising,
since
land
cover
is
a
factor
in
generating
the
curve
number.

Statistical
analysis
of
time­
weighted
means
revealed
no
significant
increase
or
decrease
in
annualized
mean
concentrations
for
acetochlor
over
time,
nor
did
ARP's
analysis
detect
a
change
in
annualized
means
over
the
seven
year
monitoring
period.
Scatter
plots
for
raw
and
finished
time­
weighted
means
can
be
found
in
Appendix
section
12.7.

Raw
water
concentrations
in
the
SDWS
program
were
significantly
(
p
<
0.05)
greater
than
treated
water
concentrations.
A
paired
two
sample
t­
test
for
means
was
performed
on
those
sites
and
sample
dates
that
had
both
raw
and
finished
water
observations.
Results
of
the
t­
test
are
provided
in
the
Appendix
section
entitled
Statistical
Analyses
for
the
ARP
monitoring
Studies.
Statistical
analysis
indicates
that
water
treatment
plants
that
use
granulated
activated
carbon
(
GAC)
or
powdered
activated
carbon
(
PAC)
significantly
reduce
acetochlor
concentrations
in
drinking
water
(
p
<
0.001)

In
nearly
half
the
cases
(
43%),
finished
water
samples
were
moderately
to
strongly
associated
(
r
>=
0.75)
with
observed
raw
water
concentrations,
suggesting
that
finished
water
samples
are
moderately
predictive
of
raw
water
concentrations.
Raw
water
concentrations
explained
at
least
75%
of
the
variability
in
finished
water
concentrations
for
30%
of
the
sites.
Raw
water
concentrations
explained
at
least
50
%
(
r2
>=
0.5)
of
the
variability
in
finished
water
concentrations
using
a
simple
linear
model.
In
general
increasing
the
sample
size
(
N)
did
not
result
in
an
increase
in
correlation
between
raw
and
finished
water
concentrations.
Lack
of
­
43­

correspondence
for
some
sites
may
be
partially
a
result
of
differences
in
sampling
times
for
raw
and
finished
samples
and
the
uncertainty
in
residence
time
for
each
of
the
water
treatment
facilities.
Because
there
is
a
time
lag
from
when
water
enters
the
intake
(
raw
water)
to
when
the
treatment
processes
in
completed
(
finished
water)
it
is
unlikely
that
raw
and
finished
samples
were
taken
from
the
same
volume
of
water.

Percent
reduction
due
to
treatment
was
also
calculated
to
assess
the
relative
success
of
treatment.
Percent
reduction
was
computed
for
those
observations
that
had
non­
zero
raw
values
using
the
following
formula:

Percent
Reduction
=
((
Raw­
Finished)/
Raw)*
100.

Figure
13
summarizes
the
percent
reduction
in
acetochlor
parent
in
surface
drinking
water
supplies
sampled.
Values
on
the
x­
axis
represent
percent
reduction;
a
value
of
100%
indicates
that
all
of
the
acetochlor
was
eliminated.
A
negative
value
means
that
the
concentration
went
up
between
pre
and
post­
treatment.
Based
on
the
chart
roughly
35%
of
the
non­
zero
samples
had
complete
elimination
of
Acetochlor,
another
15%
had
about
an
80%
reduction,
another
10%
had
about
a
60%
reduction
and
so
forth.
About
12.5%
of
surface
water
samples
had
concentrations
that
increased
after
treatment.

Percent
Reduction
in
Acetochlor
Due
to
Treatment
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
­
10
0
­
80
­
60
­
40
­
20
0
20
40
60
80
100
Acetochlor
Percent
Reduction
Relative
Frequency
Figure
13.
Percent
reduction
in
acetochlor
from
pre­
treatment
(
raw)
to
post
treatment
(
finished)
sample.
­
44­

6.3.3.
Characterization
of
Exposure
to
Surface
Water
Exposure
to
acetochlor
parent
was
significantly
higher
in
the
surface
water
monitoring
sites
than
the
ground
water
monitoring
sites
(
see
Figure
7,
Figure
8,
and
Figure
12).
Only
the
surface
water
monitoring
samples
represented
water
from
existing
drinking
water
intakes.

While
most
of
the
factors
for
selection
for
the
ground
water
sites
would
tend
to
make
these
sites
susceptible
to
higher
levels
of
contamination
than
occurring
in
samples
from
actual
drinking
water
wells,
this
is
not
an
assumption
which
is
directly
verifiable.
The
preponderance
of
the
evidence
does
indicate
that
it
is
proper
to
base
the
parent
exposure
assessment
on
the
surface
water
monitoring
results,
nonetheless,
there
are
still
some
unknowns
with
regard
to
the
relative
conservativeness
(
i.
e.,
degree
of
tendency
to
overestimate
exposure)
of
the
ground
water
monitoring
studies
by
the
ARP.
For
example,
a
major
limitation
in
a
monitoring
survey
for
a
new
pesticide
is
that
the
full
impact
of
the
use
of
the
pesticide
on
ground
water
quality
may
not
be
observed
for
a
number
of
years.
The
number
of
years
required
for
residues
to
reach
ground
water
at
each
SGW
sampling
site
is
not
knowable.
Data
from
the
PGW
studies
show,
that
even
with
higher
than
average
rainfall
supplemented
by
irrigation
it
can
take
several
years
for
some
residues
to
reach
shallow
ground
water,
witness
the
Nebraska
PGW
site
where
residues
of
the
acetochlor
ethanesulfonic
acid
degradates
were
still
moving
through
the
soil
pore­
water
at
a
9­
foot
depth
when
the
study
was
terminated
more
than
seven
years
after
the
only
acetochlor
application.

The
ten
overall
highest
single
acetochlor
concentrations,
time­
weighted
annualized
means,
and
95th
percentiles
for
the
community
water
systems
were
determined
for
both
raw
(
Table
8)
and
finished
(
Table
9)
water
samples.
These
systems
generally
draw
water
from
watersheds
with
high
corn
crop
intensity
(
ca.
20
to
35%)
and
include
both
reservoir
and
river
water
sources
(
Table
10).
Acetochlor
concentrations
were
highest
in
Illinois.
Eight
of
the
ten
highest
raw
water
concentrations,
time­
weighted
annualized
means,
and
95th
percentiles
were
observed
in
Illinois,
including
the
overall
highest
raw
water
concentration
(
7.19
ppb),
TWAM
(
0.59
ppb),
and
95th
percentile
(
3.31
ppb)
were
observed
at
a
single
site
(
168­
PA­
IL)
in
Illinois.
Similarly,
six
of
the
ten
highest
finished
water
concentrations
were
observed
in
Illinois,
including
the
overall
highest
finished
water
concentration
(
18.21
ppb),
TWAM
(
1.43
ppb),
and
95th
percentile
(
6.97
ppb)
observed
at
214­
GI­
IL.
Most
of
the
ten
highest
observations
occurred
between
the
years
1996­
1998.

Statistical
analysis
of
raw
versus
finished
water
concentrations
indicates
that
treatment
does
indeed
on
average
significantly
decrease
acetochlor
concentrations,
the
top
ten
finished
(
treated)
water
concentrations
exceed
the
top
ten
raw
(
untreated)
concentrations
suggesting
that
paired
sampling
of
raw
and
finished
water
at
all
sites
would
have
provided
a
much
more
reliable
indication
of
the
level
of
impact
of
acetochlor
residues
on
surface
waters
and
the
degree
of
mitigation
provided
by
treatment
systems
with
and
without
carbon
filtration
(
that
is,
in
general,
with
the
recognition
that
it
is
generally
not
possible
to
exactly
match
the
water
sampled
prior
to
and
post­
treatment).
Without
these
data,
we
have
no
possibility
of
determining,
for
example,
whether
the
treatment
systems
that
did
not
use
carbon
filtration
reduced
exposure
and
we
have
an
inadequate
ability
to
determine
the
impact
on
acetochlor
residue
levels
of
treatment
systems
that
include
GAC
(
because
most
of
these
CWS
also
did
not
sample
pre­
treatment
water).
In
fact,
the
SDWS
was
set
up
with
paired
raw
and
finished
water
sampling
at
only
about
25
(
initially
in
­
45­

1995)
to
44
(
overall,
for
one
or
more
years)
of
the
up
to
175
sites
sampled
each
year
during
this
seven­
year
study.

To
further
isolate
treatment
effects
in
the
SDWS
it
would
have
been
worthwhile
to
attempt
to
match,
to
the
extent
it
can
be
determined
and
is
feasible,
the
volumes
of
water
that
are
sampled
for
the
raw
and
finished
water
analyses
at
each
sampling
date.
Future
studies
of
this
nature
should
detail
results
of
the
investigation
of
water
handling
practices
and
a
determination
on
a
site­
by­
site
basis
of
the
degree
to
which
this
is
feasible.
If
attempts
to
more
closely
pair
the
raw
and
finished
water
are
deemed
to
be
futile,
the
reasons
for
this
determination
should
at
least
be
specifically
documented.

Table
8.
Ten
highest
raw
(
untreated)
water
concentrations
of
parent
acetochlor
at
community
water
system
(
CWS)
intake
locations.

Maximum
Single
Concentration
(
ppb)
Maximum
TWAM
(
ppb)
Maximum
95th
%
tile
Concentration
(
ppb)
a
CWS
Name
Value
Year
CWS
Name
Value
Year
CWS
Name
Value
Year
168­
PA­
IL
7.19
1998
168­
PA­
IL
0.59
1998
168­
PA­
IL
3.31
1998
228­
SA­
IL
7.09
1996
168­
PA­
IL
0.43
1996
222­
HI­
IL
2.10
1998
168­
PA­
IL
5.89
1996
228­
SA­
IL
0.40
1996
1070­
WY­
MO
1.81
1997
228­
SA­
IL
3.45
1998
222­
HI­
IL
0.36
1998
228­
SA­
IL
1.56
1996
606­
KA­
IL
2.88
1998
1070­
WY­
MO
0.32
1997
259­
SP­
IL
1.44
1998
1070­
WY­
MO
2.50
1997
345­
RI­
IN
0.30
1997
168­
PA­
IL
1.39
1996
222­
HI­
IL
2.36
1998
222­
HI­
IL
0.26
1996
225­
CE­
IL
1.38
1998
345­
RI­
IN
2.27
1997
259­
SP­
IL
0.25
1998
228­
SA­
IL
1.37
1998
259­
SP­
IL
2.22
1998
606­
KA­
IL
0.23
1996
603­
BL­
IL
1.28
1995
225­
CE­
IL
2.01
1999
603­
BL­
IL
0.23
1995
557­
DM­
IA
1.13
2001
a
Max
95%
tile
indicates
that
95%
of
the
time
the
value
was
less
than
or
equal
to
the
specified
value
(
USGS
2004).

Table
9.
Ten
highest
finished
(
treated)
water
concentrations
of
parent
acetochlor
at
community
water
system
(
CWS)
outflow
locations.

Maximum
Single
Concentration
(
ppb)
Maximum
TWAM
(
ppb)
Maximum
95th
%
tile
Concentration
(
ppb)
a
CWS
Name
Value
Year
CWS
Name
Value
Year
CWS
Name
Value
Year
214­
GI­
IL
18.21
1996
214­
GI­
IL
1.43
1996
214­
GI­
IL
6.97
1996
455­
MO­
OH
11.14
1997
455­
MO­
OH
0.58
1997
168­
PA­
IL
3.01
1998
157­
MA­
IL
7.93
1996
166­
NE­
IL
0.53
1996
340­
NV­
IN
2.87
1996
330­
LO­
IN
7.35
1997
214­
GI­
IL
0.49
1998
182­
GE­
IL
2.70
1998
168­
PA­
IL
5.43
1998
168­
PA­
IL
0.48
1998
166­
NE­
IL
2.67
1996
455­
MO­
OH
5.17
1996
157­
MA­
IL
0.46
1996
143­
SO­
IL
2.65
1998
340­
NV­
IN
4.31
1996
330­
LO­
IN
0.42
1997
214­
GI­
IL
2.21
1998
214­
GI­
IL
4.28
1998
182­
GE­
IL
0.39
1998
518­
US­
OH
2.03
1996
537­
WM­
OH
4.16
2000
518­
US­
OH
0.37
1996
330­
LO­
IN
1.94
1996
168­
PA­
IL
4.14
1996
340­
NV­
IN
0.37
1996
242­
CO­
IL
1.71
1996
a
Max
95%
tile
indicates
that
95%
of
the
time
the
value
was
less
than
or
equal
to
the
specified
value
(
USGS
2004).
­
46­

Table
10.
Watershed
characteristics
for
the
ten
highest
finished
(
treated)
water
concentrations
of
parent
acetochlor
at
community
water
system
(
CWS)
outflow
locations.
CWS
Name
Watershed
Area,
acres
Type
Reservoir
Volume
or
Area2
Chronic
Rank1
Acute
Rank1
%
Corn
Intensity
214­
GI­
IL
2996
Reservoir
250
mg
1,4
1,
8
25.0
455­
MOOH
138245
River
NA
2
2,
6
18.7
157­
MA­
IL
11916
Reservoir
900
mg
6
3
34.5
330­
LO­
IN
524144
River
NA
7
4
28.3
340­
NV­
IN
68241
River
NA
10
7
21.0
537­
WMOH
427302
River
NA
NC
9
28.3
168­
PA­
IL
11733
Reservoir
900
mg
5
5,
10
38.7
166­
NE­
IL
34849
Reservoir
NA
3
NC
33.5
182­
GE­
IL
724
Reservoir
50
acres,
9
ft
deep
8
NC
29.1
518­
USOH
894
Reservoir
90
mg
9
NC
23.8
1
Ranking
by
TWAM
(
Chronic)
or
single
highest
concentration
(
acute)
as
presented
in
Table
9.
NC
=
Not
in
top
ten.
2
mg
=
million
gallons,
NA
=
not
available
or
unknown.

The
highest
overall
maximum
TWAM,
single
concentration,
and
95th
percentile
was
observed
in
Illinois,
followed
by
Missouri
at
nearly
half
the
maximum
concentrations
observed
in
Illinois
(
Table
11
and
Table
12).
The
top
ten
raw
(
untreated)
water
TWAMs,
peak
concentrations,
and
peak
95th
percentile
concentrations
ranged
from
ranged
from
0.007
ppb
in
WI
to
0.591
ppb
in
IL,
0.044
ppb
in
OH
to
7.186
ppb
in
IL,
0.019
ppb
in
PA
to
3.313
ppb
in
IL,
respectively.
Peak
finished
(
treated)
water
concentrations
were
again
sometimes
higher
than
pre­
treated
water
samples.
The
top
ten
treated
water
TWAMs,
peak
concentrations,
and
peak
95th
percentile
concentrations
ranged
from
0.004
in
MD
to
1.428
ppb
in
IL,
0.034
ppb
in
MD
to
18.21
ppb
in
IL,
0.011
in
DE
to
6.973
in
IL,
respectively.
The
highest
maximum
TWAM
for
MD
occurred
three
times
at
two
different
sites
(
Table
12).
­
47­

Table
11.
Highest
raw
(
untreated)
water
concentrations
of
parent
acetochlor
at
community
water
system
(
CWS)
intake
locations
in
each
state
(
sorted
by
Max
TWAM).
Max
TWAM
(
ppb)
Maximum
Single
Concentration
(
ppb)
Max.
95th
%
tile
Concentration
(
ppb)
a
State
Value
Year
CWS
Name
State
Value
Year
CWS
Name
State
Value
Year
CWS
Name
IL
0.591
1998
168­
PA­
IL
IL
7.186
1998
168­
PA­
IL
IL
3.313
1998
168­
PA­
IL
MO
0.317
1997
1070­
WY­
MO
MO
2.504
1997
1070­
WY­
MO
MO
1.807
1997
1070­
WY­
MO
IN
0.304
1997
345­
RI­
IN
IN
2.265
1997
345­
RI­
IN
IN
1.118
1997
345­
RI­
IN
IA
0.217
1996
574­
OS­
IA
IA
1.762
2001
557­
DM­
IA
IA
1.129
2001
557­
DM­
IA
KS
0.085
1999
89­
MI­
KS
KS
0.426
1999
89­
MI­
KS
KS
0.272
1999
89­
MI­
KS
NE
0.045
2001
301­
BL­
NE
NE
0.161
2001
301­
BL­
NE
NE
0.131
2001
301­
BL­
NE
MN
0.019
1999
296­
SC­
MN
MN
0.251
1999
296­
SC­
MN
MN
0.066
1999
296­
SC­
MN
OH
0.010
2001
452­
MC­
OH
OH
0.044
2001
452­
MC­
OH
OH
0.033
2001
452­
MC­
OH
PA
0.010
1996
737­
AW­
PA
PA
0.241
1996
737­
AW­
PA
PA
0.019
1998
737­
AW­
PA
WI
0.007
1996
13­
AP­
WI
WI
0.046
1996
18­
OK­
WI
WI
0.024
1996
18­
OK­
WI
a
Max
95%
tile
indicates
that
95%
of
the
time
the
value
was
less
than
or
equal
to
the
specified
value
(
USGS
2004).

Table
12.
Highest
finished
(
treated)
water
concentrations
of
parent
acetochlor
at
community
water
system
(
CWS)
outflow
locations
in
each
state.

Max
TWAM
(
ppb)
Maximum
Single
Concentration
(
ppb)
Max.
95th
%
tile
Concentration
(
ppb)

State
Value
Year
CWS
Name
State
Value
Year
CWS
Name
State
Value
Year
CWS
Name
IL
1.428
1996
214­
GI­
IL
IL
18.21
1996
214­
GI­
IL
IL
6.973
1996
214­
GI­
IL
OH
0.584
1997
455­
MO­
OH
OH
11.14
1997
455­
MO­
OH
OH
2.03
1996
518­
US­
OH
IN
0.416
1997
330­
LO­
IN
IN
7.353
1997
330­
LO­
IN
IN
2.872
1996
340­
NV­
IN
MO
0.258
1998
1098­
GE­
MO
MO
1.289
1997
1070­
WY­
MO
MO
1.114
1998
1098­
GE­
MO
IA
0.207
1996
570­
MO­
IA
IA
2.328
1998
572­
MP­
IA
IA
1.402
1998
572­
MP­
IA
KS
0.133
2001
125­
TO­
KS
KS
1.88
1999
25­
AT­
KS
KS
0.983
1999
71­
KC­
KS
PA
0.092
1995
729­
PH­
PA
PA
2.34
1995
729­
PH­
PA
PA
0.045
1995
769­
RE­
PA
NE
0.088
1999
301­
BL­
NE
NE
1.116
1995
303­
OM­
NE
NE
0.288
2001
303­
OM­
NE
WI
0.039
1997
17­
ME­
WI
WI
0.192
1997
17­
ME­
WI
WI
0.167
1997
17­
ME­
WI
DE
0.025
1998
652­
WI­
DE
DE
0.598
1998
652­
WI­
DE
DE
0.011
1998
651­
NE­
DE
MN
0.006
1999
296­
SC­
MN
MN
0.043
1997
277­
MI­
MN
MN
0.03
1999
296­
SC­
MN
MD**
0.004
2001
702­
LA­
MD
MD
0.034
1996
699­
HG­
MD
MD
0.012
1996
699­
HG­
MD
a
Max
95%
tile
indicates
that
95%
of
the
time
the
value
was
less
than
or
equal
to
the
specified
value
(
USGS
2004).

**
There
are
also
two
other
Maryland
sites
with
concentration
values
of
0.004
ppb
­
48­

6.3.4.
Comparison
of
ARP
and
WARP
beta
Model
Results
Table
13
presents
the
highest
acetochlor
concentrations
estimated
by
the
WARP
beta
model
(
USGS
2004)
for
states
where
ARP
also
had
surface
water
monitoring
locations.
For
comparison,
the
top
ten
peak
raw
water
concentrations
measured
by
the
ARP
for
community
water
supply
systems
are
also
provided.
In
both
data
sets,
the
majority
of
the
top
ten
peak
concentrations
were
located
in
Illinois.
In
general,
the
maximum
time­
weighted
annualized
means
measured
by
the
ARP
are
close
to
those
modeled
by
WARP,
as
are
the
95%
tile
values.
Recall
that
the
95th
percentile
values
represent
the
fraction
of
the
year
(
e.
g.,
95
percent
of
the
time)
that
the
concentration
was
equal
to
or
less
than
the
listed
value
(
USGS
2004).

The
modeling
results
are
based
on
use
estimates
provided
by
the
National
Center
for
Food
and
Agricultural
Policy
(
http://
www.
ncfap.
org/
database/
default.
php
)
These
data
are
different
than
the
annual
sales
data
provided
by
the
ARP.
The
USGS
modeling
is
based
on
nationally
available
hydrologic
and
soils
data.

Table
13.
Top
ten
highest
raw
water
concentrations
(
ppb)
of
parent
acetochlor
modeled
by
WARP
multicompound
regression
model
and
measured
by
ARP
at
community
water
system
(
CWS)
intakes.

WARP
results
(
Beta
version,
results
supplied
by
USGS)
are
only
for
states
where
ARP
also
had
surface
water
monitoring
locations.
WARP
data
are
ranked
by
maximum
95%
tile
and
measured
results
by
ARP
are
ranked
separately
by
maximum
time­
weighted
mean
and
95%
tile.

WARP
ARP
Max
TWAM
Max
95%
tile
Conc.
a
Site
TWAM
95%
tile
Conc.
Max
Single
Conc.
Value
CWS
Name
Value
CWS
Name
KASKASKIA
RIVER
(
E.
FORK)
FARINA,
IL
0.81
3.77
7.19
0.59
168­
PA­
IL
3.31
168­
PA­
IL
LITTLE
WABASH
RIVER
FLORA,
IL
0.56
2.64
7.09
0.43
168­
PA­
IL
2.10
222­
HI­
IL
LITTLE
WABASH
RIVER
CLAY
CITY,
IL
0.55
2.60
5.89
0.40
228­
SA­
IL
1.81
1070­
WY­
MO
LITTLE
WABASH
RIVER
FAIRFIELD,
IL
0.54
2.59
3.45
0.36
222­
HI­
IL
1.56
228­
SA­
IL
KASKASKIA
RIVER
(
E.
FORK)
FARINA,
IL
0.54
2.50
2.88
0.32
1070­
WY­
MO
1.44
259­
SP­
IL
WILDCAT
CREEK
KOKOMO,
IN
0.52
2.31
2.50
0.30
345­
RI­
IN
1.39
168­
PA­
IL
WHITE
RIVER
NORTH
INDIANAPOLIS,
IN
0.50
2.28
2.36
0.26
222­
HI­
IL
1.38
225­
CE­
IL
KASKASKIA
RIVER
EVANSVILLE,
IL
0.48
2.24
2.27
0.25
259­
SP­
IL
1.37
228­
SA­
IL
KASKASKIA
RIVER
FAYETTEVILLE
TWP,
IL
0.48
2.22
2.22
0.23
606­
KA­
IL
1.28
603­
BL­
IL
KASKASKIA
RIVER
NEW
ATHENS
TWP,
IL
0.47
2.22
2.01
0.23
603­
BL­
IL
1.13
557­
DM­
IA
a
Max
95%
tile
indicates
that
95%
of
the
time
the
value
was
less
than
or
equal
to
the
specified
value
(
USGS
2004).

6.3.5.
Summary
Results
of
National
Water
Quality
Assessment
(
NAWQA)
Results
NAWQA
data
(
NAWQA
a
long­
term
multi­
faceted
monitoring
program
being
conducted
by
the
USGS)
have
included
serial
monitoring
for
a
large
schedule
of
pesticides,
including
acetochlor
in
­
49­

multiple
study
areas
across
the
United
States.
NAWQA
monitoring
sites
are
not
selected
to
represent
the
locations
of
drinking
water
intakes
nor
are
they
directly
selected
to
represent
sites
at
which
specific
pesticides
are
used.
They
do,
however,
represent
ambient
pesticide
concentrations
in
the
environment,
include
many
watersheds
where
agriculture
is
the
documented
dominant
land
use,
and
may
be
an
indication
of
vulnerability
of
sites
to
runoff
of
acetochlor
(
These
data
are
used
as
an
indication
of
the
occurrence
pattern
and
concentration
of
pesticides
in
surface
source
water).
Table
14
summarizes
acetochlor
monitoring
concentrations
measured
in
NAWQA
study
unit
locations.
The
two
columns
of
data
represent
overall
(
non­
time
weighted)
mean
and
maximum
concentration
data
at
all
sites
for
which
the
maximum
concentration
value
is
above
1.00
ppb.
­
50­

Table
14.
Acetochlor
monitoring
concentrations
at
NAWQA
study
unit
locations.
(
Notes:
`
Mean
Conc'
values
are
not
Time
Weighted
Annual
Mean
(
TWAM)
concentration
values;
`
Max
Conc'
values
occurred,
for
the
most
part,
at
different
times
[
dates
and
years]
during
the
monitoring
period
which
also
varied
from
site
to
site.)

Site
Name
Mean
Max
Conc
Conc
(
ppb)
(
ppb)

MAPLE
CREEK
NEAR
NICKERSON,
NE
1.359
61.00
SUGAR
CREEK
AT
MILFORD,
IL
0.993
35.90
ELKHORN
RIVER
AT
WATERLOO,
NE
1.304
31.00
PLATTE
R
AT
LOUISVILLE
NE
0.416
14.20
LA
MOINE
RIVER
AT
COLMAR,
IL
0.532
11.60
LITTLE
COBB
RIVER
NEAR
BEAUFORD,
MN
0.361
10.70
MAUMEE
RIVER
AT
WATERVILLE
OH
0.596
10.60
SKUNK
RIVER
AT
AUGUSTA,
IA
0.768
10.60
SANGAMON
RIVER
AT
MONTICELLO,
IL
0.510
9.71
MAUMEE
RI
AT
NEWHAVEN
IN
0.710
8.88
OLD
MANS
CREEK
NEAR
IOWA
CITY,
IA
0.636
8.16
WEST
FORK
CEDAR
RIVER
AT
FINCHFORD,
IA
0.366
7.62
SUGAR
CREEK
AT
CO
RD
400
S
AT
NEW
PALESTINE,
IN
0.238
7.17
CEDAR
RIVER
NEAR
CONESVILLE,
IA
0.376
7.10
ST
JOSEPH
RIVER
NEAR
NEWVILLE
IN
0.373
5.61
AUGLAIZE
RIVER
NEAR
FORT
JENNINGS
OH
0.515
5.13
LITTLE
BUCK
CREEK
NEAR
INDIANAPOLIS,
IN
0.053
4.20
MAD
RIVER
AT
ST
PARIS
PIKE
AT
EAGLE
CITY
OH
0.065
4.02
BLACK
RIVER
NR
JEDDO
MI
0.292
3.80
CLEAR
CK
NR
SANGER,
TX
0.115
3.59
WHITE
RIVER
AT
HAZLETON,
IN
0.194
3.56
IOWA
RIVER
NEAR
ROWAN,
IA
0.116
3.50
WAPSIPINICON
RIVER
NEAR
TRIPOLI,
IA
0.188
3.09
DUCK
CREEK
AT
SEMINARY
ROAD
NEAR
ONEIDA,
WI
0.124
2.90
IOWA
RIVER
AT
WAPELLO,
IA
0.159
2.89
FLOOD
CREEK
NEAR
POWERSVILLE,
IA
0.164
2.56
WAPSIPINICON
RIVER
NEAR
DE
WITT,
IA
0.360
2.30
BOGUE
PHALIA
NR
LELAND,
MS
0.068
2.28
ENGLISH
RIVER
AT
RIVERSIDE,
IA
0.117
2.23
ILLINOIS
RIVER
AT
VALLEY
CITY
0.240
2.01
ILLINOIS
RIVER
AT
OTTAWA,
IL
0.260
2.00
BIG
SUNFLOWER
RIVER
NR
ANGUILLA,
MS
0.104
1.68
CEDAR
RIVER
AT
GILBERTVILLE,
IA
0.111
1.66
IOWA
RIVER
AT
MARENGO,
IA
0.184
1.50
MINNESOTA
RIVER
NEAR
JORDAN,
MN
0.143
1.50
YAZOO
RIVER
BL
STEELE
BAYOU
NR
LONG
LAKE,
MS
0.036
1.45
PLATTE
RIVER
NEAR
GRAND
ISLAND,
NEBR.
0.133
1.40
SOUTH
FORK
IOWA
RIVER
NE
OF
NEW
PROVIDENCE,
IA
0.090
1.36
WOLF
CREEK
NEAR
DYSART,
IA
0.121
1.25
6.3.6.
USGS
/
EPA
Pilot
Reservoir
Monitoring
Program
The
highest
levels
of
chronic
exposure
to
acetochlor
parent
most
often
occur
in
reservoirs
(
compared
to
streams
and
rivers
and
to
ground
water,
Table
10),
and
a
significant
source
of
­
51­

additional
monitoring
for
a
number
of
pesticides
in
settings
of
high
vulnerability
is
provided
in
Bloomquist
et
al.
(
2001).
Each
sampling
site
included
in
the
USGS
reservoir
monitoring
study
consisted
of
both
a
reservoir
(
raw
water
sample
source)
and
a
Community
Water
System
(
finished
water
source).
The
study
focused
on
small
drinking­
water
supply
reservoirs
in
areas
with
high
pesticide
use
(
not
necessarily
high
acetochlor
use
areas).
The
program
was
implemented
with
a
NAWQA
design
structure
and
strong
consideration
in
site
selection
was
given
to
sites
within
existing
NAWQA
Study
Units.
One
drinking
water
reservoir
was
chosen
in
each
of
12
states:
California,
Indiana,
Ohio,
Oklahoma,
Louisiana,
Missouri,
South
Carolina,
South
Dakota,
New
York,
North
Carolina,
North
Carolina,
Pennsylvania
and
Texas.
No
samples
were
taken
in
Illinois,
a
high
acetochlor
usage
state.

Table
15.
Maximum
acetochlor
concentration
values
in
pilot
reservoir
monitoring
study
(
Blomquist
et
al.,
2001).

The
maximum
concentration
in
the
intake
water
at
the
Mitchell,
South
Dakota
site
was
0.334
ppb
and
the
concentrations
in
both
the
outflow
from
the
CWS
treatment
facility
and
the
reservoir
were
0.395
ppb.
The
highest
67
concentration
values
were
all
found
at
the
South
Dakota,
Ohio
and
Indiana
sites.

6.4.
Ground
Water
­
52­

6.4.1.
PGW
Leaching
Summary
Two
separate
data
files
were
used
in
this
analysis
(
Table
5).
One
file
contained
all
the
concentration
values
observed
in
the
PGW
studies
provided
by
the
ARP,
while
the
second
contained
raw
uncensored
concentrations
also
provided
by
the
ARP.
Because
of
the
overwhelming
number
of
censored
values
(
defined
in
this
context
as
values
that
were
not
reported
numerically
 
generally
because
of
the
precision
and
accuracy
limitations
of
the
analytical
method
for
low
residue
levels),
the
PGW
uncensored
file
was
used
to
compute
timeweighted
annualized
means
and
percentiles.
The
underlying
assumption
here
is
that
the
uncensored
data
represent
the
best
available
estimates
of
unmeasured
values
(
any
substitution
method
for
nondetects
would
be
arbitrary).

6.4.2.
Comparison
of
PGW
Results
to
the
Acetochlor
Regulatory
Action
Endpoints
The
conditional
registration
agreement
states
that
automatic
cancellation
of
acetochlor
will
occur
if
"
out
of
the
eight
sites,
4
sites
in
a
variety
of
geographic,
and
climatic
conditions
under
both
vulnerable
and
general
use
conditions
(
as
determined
by
EPA)
in
corn
growing
states
indicate
a
pattern
of
movement
of
acetochlor
toward
ground
water"
(
USEPA
1994).
".
In
the
PGW
studies,
one
indication
of
a
pattern
of
movement
was
defined
as
the
detection
of
acetochlor
greater
than
or
equal
to
1.0
ppb
at
nine
foot
lysimeter
depth
as
well
as
corresponding
three
and
6
foot
depths
in
that
cluster.
Table
16
indicates
that
only
one
site
(
Iowa)
had
detections
greater
than
1.0
ppb,
and
moreover
it
was
the
only
site
to
have
detected
concentrations
greater
than
0.1
ppb
in
the
nine
foot
lysimeters.

Peak
concentrations
of
the
parent
acetochlor
were
determined
for
each
state
and
are
presented
separately
for
three
foot
lysimeters
(
Table
17),
nine
foot
lysimeters
(
Table
18),
shallow
ground
water
(
Table
19),
and
deep
ground
water
(
Table
20).
The
maximum
soil­
pore
water
residue
for
parent
acetochlor
was
measured
as
3.2
ppb,
which
was
observed
in
the
9
ft
(
2.7
m)
lysimeters
in
Iowa
(
Table
18).
According
to
the
pgw_
num_
final.
txt
file
provided
by
the
registrant,
the
maximum
residue
observed
in
ground
water
was
0.06
ppb,
observed
in
Iowa.
Concentrations
in
the
deep
ground
water
monitoring
wells
(
Table
20)
were
only
slightly
lower
than
concentrations
in
the
shallow
ground
water
wells.

Table
16.
PGW
Sites
exceeding
0.1
ppb
at
9
feet
depth
(
exceedences
only
occurred
at
1
of
the
8
sites).

MAT
DATEa
STATE
DEVICE
DEPTH
CLUSTER
RAW
CONCENTRATION
0.5
6/
24/
1996
IA
LY
9
1
2.6
1
7/
9/
1996
IA
LY
9
1
0.195
0.5
6/
24/
1996
IA
LY
9
3
3.2
1
7/
9/
1996
IA
LY
9
3
0.628
1.5
7/
24/
1996
IA
LY
9
3
0.208
2
8/
8/
1996
IA
LY
9
3
0.102
0.5
6/
24/
1996
IA
LY
9
4
0.132
0.5
6/
24/
1996
IA
LY
9
6
0.365
a
Date
was
not
provided,
but
was
approximated
using
the
initial
treatment
date,
months
after
treatment,
and
assuming
average
of
30
days
per
month.
­
53­

Table
17.
Concentrations
of
AC
observed
in
3­
foot
lysimeters
from
the
eight
prospective
ground
water
studies.

Max
TWAM
Max
95
%
tile
Max
Concentration
STATE
Cluster
Average
Single
Cluster
Cluster
Average
Single
Cluster
Cluster
Average
Single
Cluster
Max
Moving
Average
DE
0.004
0.009
0.008
0.019
0.009
0.024
0.012
IA
0.000
0.000
0.000
0.000
0.000
0.003
0.000
IN
0.006
0.045
0.028
0.195
0.047
0.330
0.228
MN
0.001
0.001
0.000
0.000
0.001
0.001
NA
NE
0.004
0.007
0.010
0.017
0.011
0.018
0.011
OH
NA
NA
NA
NA
NA
0.025
NA
PA
0.009
0.068
0.016
0.129
0.020
0.156
0.118
WI
NA
NA
NA
NA
NA
0.003
NA
Single
Cluster
=
Statistic
applies
to
all
observed
values
for
the
given
depth;
Cluster
Average
=
Statistic
applies
to
concentrations
averaged
across
all
cluster
for
a
given
date
for
the
depth
listed;
Max
TWAM
=
Maximum
timeweighted
average
observed
based
on
uncensored
data
file;
Max
95%
tile
=
Represents
the
amount
of
time
during
the
calendar
year
the
concentration
was
below
the
listed
value;
Maximum
Moving
Average
=
The
single
highest
average
for
3
consecutive
values
(
separately
by
cluster
and
depth)
across
all
clusters;
NA
=
Insufficient
uncensored
concentrations
to
compute
the
value
Table
18.
Concentrations
of
AC
observed
in
9­
foot
lysimeters
from
the
eight
prospective
ground
water
studies.

Max
TWAM
Max
95
%
tile
Max
Concentration
STATE
Cluster
Average
Single
Cluster
Cluster
Average
Single
Cluster
Cluster
Average
Single
Cluster
Max
Moving
Average
DE
0.004
0.006
0.006
0.013
0.006
0.014
0.009
IA
0.458
1.639
0.820
2.931
0.900
3.200
1.345
IN
0.000
0.000
0.000
0.000
0.000
0.003
0.000
MN
0.000
0.001
0.000
0.000
0.000
0.003
NA
NE
0.003
0.007
0.006
0.018
0.010
0.018
0.011
OH
NA
NA
NA
NA
0.003
0.003
NA
PA
0.003
0.013
0.010
0.061
0.015
0.072
0.062
WI
NA
NA
NA
NA
0.003
0.003
NA
Single
Cluster
=
Statistic
applies
to
all
observed
values
for
the
given
depth;
Cluster
Average
=
Statistic
applies
to
concentrations
averaged
across
all
cluster
for
a
given
date
for
the
depth
listed;
Max
TWAM
=
Maximum
timeweighted
average
observed;
Max
95%
tile
=
Represents
the
amount
of
time
during
the
calendar
year
the
concentration
was
below
the
listed
value;
Maximum
Moving
Average
=
The
single
highest
average
for
3
consecutive
values
(
separately
by
cluster
and
depth)
across
all
clusters;
the
ARP
provided
no
uncensored
data
implying
the
data
was
all
below
detection
;
NA
=
Insufficient
uncensored
concentrations
to
compute
the
value
Table
19.
Concentrations
of
AC
observed
in
Shallow
ground
water
from
the
eight
prospective
ground
water
studies.

Max
TWAM
Max
95
%
tile
Max
Concentration
­
54­

STATE
Cluster
Average
Single
Cluster
Cluster
Average
Single
Cluster
Cluster
Average
Single
Cluster
Max
Moving
Average
DE
0.002
0.003
0.005
0.008
0.005
0.008
0.004
IA
0.000
0.000
0.000
0.000
0.000
0.025
0.002
IN
0.001
0.000
0.000
0.000
0.003
0.005
0.002
MN
NA
NA
NA
NA
0.003
0.003
NA
NE
0.003
0.008
0.006
0.014
0.007
0.027
0.011
OH
NA
NA
NA
NA
NA
0.003
NA
PA
0.002
0.005
0.003
0.009
0.004
0.011
0.005
WI
NA
NA
NA
NA
NA
0.003
NA
Single
Cluster
=
Statistic
applies
to
all
observed
values
for
the
given
depth;
Cluster
Average
=
Statistic
applies
to
concentrations
averaged
across
wells
for
a
given
date
for
the
depth
listed;
Max
TWAM
=
Maximum
time­
weighted
average
observed;
Max
95%
tile
=
Represents
the
amount
of
time
during
the
calendar
year
the
concentration
was
below
the
listed
value;
Maximum
Moving
Average
=
The
single
highest
average
for
3
consecutive
values
(
separately
by
cluster
and
depth)
across
all
clusters;
NA
=
Insufficient
uncensored
concentrations
to
compute
the
value
Table
20.
Concentrations
of
AC
observed
in
Deep
ground
water
from
the
eight
prospective
ground
water
studies.

Max
TWAM
Max
95
%
tile
Max
Concentration
STATE
Cluster
Average
Single
Cluster
Cluster
Average
Single
Cluster
Cluster
Average
Single
Cluster
Max
Moving
Average
DE
0.002
0.003
0.006
0.007
0.006
0.008
0.005
IA
0.001
0.003
NA
NA
0.002
0.06
NA
IN
0.002
0.004
NA
NA
0.003
0.006
NA
MN
0.005
0.010
NA
NA
0.007
0.014
NA
NE
0.002
0.003
0.007
0.010
0.007
0.012
0.008
OH
NA
NA
NA
NA
NA
0.003
NA
PA
0.001
0.002
0.003
0.008
0.005
0.013
0.005
WI
NA
NA
NA
NA
NA
0.003
NA
Single
Cluster
=
Statistic
applies
to
all
observed
values
for
the
given
depth;
Cluster
Average
=
Statistic
applies
to
concentrations
averaged
across
wells
for
a
given
date
for
the
depth
listed;
Max
TWAM
=
Maximum
time­
weighted
average
observed;
Max
95%
tile
=
Represents
the
amount
of
time
during
the
calendar
year
the
concentration
was
below
the
listed
value;
Maximum
Moving
Average
=
The
single
highest
average
for
3
consecutive
values
(
separately
by
cluster
and
depth)
across
all
clusters;
NA
=
Insufficient
uncensored
concentrations
to
compute
the
value
6.4.3.
SGW
Summary
In
addition
to
PGW
studies,
the
ARP
was
required
to
monitor
25
wells
in
each
of
the
expected
seven
high
use
states
(
WI,
IL,
IA,
MN,
IN,
NE,
KS)
shown
in
Figure
4.
Sites
ranged
from
vulnerable
to
general
use
conditions,
including
diverse
geographic,
soil,
and
climatic
conditions.
Numerous
studies
have
demonstrated
that
the
time
to
recharge
of
shallow
superficial
aquifer
from
the
land
surface
can
be
several
years
or
more
(
including
the
results
at
some
of
the
ARP's
PGW
sites
­
for
acetochlor
degradates).
Therefore,
the
7
years
of
state
ground
water
monitoring
data
may
under­
estimate
the
full
potential
leaching
of
acetochlor
and
its
degradates
to
ground
water
if
this
chemical
is
used
annually
and
with
significant
frequency
for
the
next
10
or
20
years.
Additional
concerns
relate
to
the
lack
of
definitive
confirmation
by
the
ARP
of
a
hydraulic
connection
between
the
ARP
monitoring
sites
and
­
55­

the
sampled
ground
water
(
i.
e.,
data
were
not
collected
specifically
to
confirm
the
direction
of
vadose
zone
flow
and
transport
during
the
course
of
the
SGW
study).
The
ARP
states
the
following
about
how
they
obtained
adequate
justification
of
the
locations
of
their
wells
in
relation
to
fields
treated
with
acetochlor
as
part
of
the
SGW
program:

Monitoring
wells
were
sited
within
or
closely
adjacent
to,
and
down­
gradient
of
the
study
plot.
Various
sources
of
published
ground
water
data
were
used
(
for
example,
the
Department
of
Natural
Resources
Hydrologic
Assessment,
the
USGS
Hydrologic
Atlas
and
local
university
data)
to
assess
ground
water
flow
direction
for
most
sites.
At
sites
where
published
ground
water
data
were
not
available,
trained
hydrogeologists
evaluated
topography
in
conjunction
with
surface
water
drainage
features
in
order
to
assess
ground
water
flow
direction.
(
Source:
De
Guzman
et
al.,
in
press).

The
ARP
did
not
attempt
to
determine
the
age
of
the
ground
water
sampled
at
any
location
or
confirm
the
travel
times
for
water
from
the
treated
field
to
the
sampled
ground
water
via
use
of
tracers.
Some
indication,
at
least,
may
be
obtained
of
the
intrinsic
vulnerability
of
the
ground
water
sampled
to
contamination
from
leachable
pesticides
by
evaluation
of
the
patterns
of
detection
of
other
corn
herbicides
at
the
SGW
sites
(
atrazine,
alachlor,
metolachlor,
and
metabolites
of
alachlor
and
metolachlor
were
routinely
analyzed
along
with
acetochlor
residues
for
in
all
well
water
samples).

The
monitoring
data
serve
as
an
early
indication
that
pesticide
residues
may
be
reaching
ground
water.
ARP
found
that
parent
acetochlor
demonstrated
a
confirmed
pattern
of
movement
to
ground
water
above
0.1
ppb
at
only
seven
sites.
However,
Table
1
of
Appendix
12.8
indicates
that
acetochlor
was
detected
above
0.1
ppb
in
14
individual
wells
located
across
five
states.

6.4.3.1.
Comparison
of
SGW
Results
to
Regulatory
Action
Endpoints
In
the
SGW
study
parent
acetochlor
in
seven
of
the
approximately
175
wells
(
there
were
some
wells
replaced
and
lost
during
the
coarse
of
the
study)
exceeded
a
literal
interpretation
of
the
SGW
regulatory
trigger
involving
a
pattern
of
detections
at
0.10
ppb
or
greater
(
20
wells
with
such
a
pattern
of
detection
would
have
triggered
regulatory
action
to
mitigate
ground
water
contamination).
The
rate
of
detection
of
both
acetochlor
degradates
was
much
higher
than
for
parent
over
the
1999
to
2001
6.4.3.2.
SGW
Acute
Exposure
The
distribution
of
maximum
observed
acetochlor
concentrations
for
each
site
is
given
in
Figure
14.
Overall,
the
majority
of
values
were
reported
as
0.05
ppb.
No
sites
had
detections
of
acetochlor
greater
than
8.0
ppb,
and
only
one
site
had
a
maximum
concentration
between
4
and
8
ppb.
Roughly
90%
of
the
peak
acetochlor
values
observed
for
each
site
were
less
than
or
equal
to
0.5
ppb.
­
56­

Frequency
Distribution
for
Acetochlor
Numeric
Re
spons
e
(
SGW)

0
1
1
48
114
4
10
2
0
1
1
0
0
20
40
60
80
100
120
140
0
0.003
0.005
0.01
0.05
0.1
0.5
1
2
4
8
>
8
Concentration
(
ppb)
Frequency
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%

Frequency
Cumulative
%

Figure
14.
Distribution
of
maximum
acetochlor
concentrations
observed
at
each
site
in
the
state
ground
water
program.

6.4.3.3.
SGW
Annual
Means
Time­
weighted
annualized
means
were
computed
for
each
site
in
the
SGW
data
set
based
on
numeric
response
data
submitted
by
the
ARP.
Figure
15
shows
the
frequency
of
each
timeweighted
annualized
mean
as
well
as
the
cumulative
frequency
distribution.
A
total
of
1,207
annualized
means
were
calculated,
with
roughly
85%
of
the
TWAMs
less
than
or
equal
to
0.003.

Frequency
Distribution
of
all
Time­
Weighted
Annualized
Means
for
the
SGW
sites.

27
1008
116
23
19
5
8
1
0
0
0
200
400
600
800
1000
1200
0
0.003
0.005
0.01
0.05
0.1
0.5
1
2
>
2
Concentrat
ion
(
ppb)
Frequency
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%

Frequency
Cumulative
%

Figure
15.
Distribution
of
all
time­
weighted
annualized
means
for
sites
in
the
state
ground
water
(
SGW)
monitoring
program.
­
57­

6.4.3.4.
Ground
Water
Factor
Analysis
Several
environmental
variables
in
the
PGW
studies
were
examined
to
assess
their
role
in
observed
acetochlor
concentrations.
Given
that
at
most
sites
acetochlor
was
only
applied
in
the
first
year
of
the
study,
this
analysis
used
acute
concentrations
as
the
dependent
variable.
Acute
exposure
was
analyzed
individually
for
three
and
six
foot
lysimeters,
as
well
as
shallow
groundwater.
Several
hydrogeologic
and
meteorological
factors
were
selected
as
independent
variables.
Factors
included
average
pore
water
velocity
at
each
site,
average
hydraulic
conductivity,
average
hydraulic
gradient,
precipitation
for
the
first
three
months
after
treatment,
annual
precipitation
for
the
1st
year
after
treatment,
2nd
year,
3rd
year,
and
4th
year
after
treatment,
as
well
as
total
precipitation
during
the
monitoring
period.
Results
of
the
analysis
are
provided
in
Appendix
Acute
exposure
in
nine
foot
lysimeters
was
weakly
correlated
with
annual
precipitation
2
years
after
treatment.
Acute
exposure
in
shallow
ground
water
was
weakly
correlated
with
total
precipitation
during
the
monitoring
period,
as
well
as
acute
exposure
in
nine
foot
lysimeters.
None
of
the
correlations
were
statistically
significant
at
p
=
0.05.

ARP's
analysis
of
the
state
ground
water
monitoring
program
indicated
that
soil
texture
was
originally
hypothesized
to
be
a
factor
in
the
geographic
distribution
of
detections.
Rather,
the
detection
of
acetochlor
in
shallow
ground
water
was
more
influenced
by
site­
specific
factors
related
to
site
topography,
irrigation
practices,
surface
water
drainages,
and
the
vertical
location
of
the
well­
screen.
Based
on
the
limited
availability
of
data,
and
given
that
the
scope
of
the
current
risk
assessment
does
not
attempt
to
predict
concentrations
in
ground
water,
no
further
statistical
analysis
is
warranted
at
this
time.

7.
RESIDUES
­
ACETOCHLOR
DEGRADATES
Although
the
purpose
of
this
assessment
is
primarily
to
focus
on
exposure
to
the
parent
acetochlor,
some
attention
was
given
to
the
two
acetochlor
degradates,
ethanesulfonic
acid
(
ESA)
and
oxanilic
acid
(
OXA),
monitored
in
this
study.
The
Health
Effects
Division
of
OPP
has
determined
that
the
toxicological
profiles
of
parent
acetochlor,
ESA,
and
OXA
Each
of
the
two
degradates
were
measured
in
all
three
monitoring
programs.
In
addition
to
results
for
the
individual
degradates,
total
combined
residues
were
computed
for
acetochlor.
Each
of
the
degradates
were
given
the
same
weight
as
the
parent
acetochlor
using
equation
three.

Equation
3:

CCombined
Residue
=
Cparent
+
CESA
+
COXA,
where
C
is
the
concentration
in
ppb.

Note
that
if
at
some
point
a
risk
assessment
for
combined
residues
would
be
needed,
these
calculations
would
have
to
be
converted
to
a
molar
basis
before
application
of
any
relevant
potency
factors
to
such
an
assessment.

7.1.
Surface
Water
7.1.1.
Acute
Exposure
Distributions
by
SDWS
Sites
Acute
exposure
of
acetochlor
ethanesulfonic
acid
and
oxanilic
acid,
as
well
as
the
combined
residues
and
are
presented
as
a
cumulative
distribution
function
in
Figure
16.
The
lines
indicate
the
frequency
at
­
58­

which
the
degradates
or
combined
residues
concentration
were
detected
at
or
below
a
given
concentration.
In
addition,
as
the
CDF
line
shifts
to
the
right
it
indicates
a
higher
concentration
at
a
given
frequency.
In
general,
maximum
raw
water
concentrations
were
greater
than
finished
water
samples
for
both
degradates
and
combined
residues
up
to
approximately
0.5
ppb.
However,
finished
water
concentrations
exceeded
maximum
raw
water
once
concentrations
exceeded
roughly
0.5
ppb.
This
shift
in
raw
versus
finished
concentrations
can
be
seen
at
the
point
where
the
dotted
line
intersects
the
solid
line.

Degradate
Acute
Exposure
in
Finished
Samples
(
SDWS)

0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%

0
0.003
0.005
0.010
0.05
0.1
0.5
1
2
4
8
>
8
Concentration
(
ppb)
Frequency
ESA
­
RAW
ESA
­
FIN
OXA
­
RAW
OXA
­
FIN
Total
Res
idue
­
RAW
Total
Res
idue
­
FIN
Figure
16.
Maximum
observed
concentrations
(
acute)
of
the
two
acetochlor
degradates
and
Total
Combined
residues
(
parent
+
ESA
+
OXA)
in
raw
(
dashed)
and
finished
(
solid)
surface
drinking
water
samples.
­
59­

Percent
reduction
of
ESA
and
OXA
(
Figure
17)
was
also
computed
for
dates
where
both
a
raw
and
finished
water
sample
pair
was
available.
In
general
OXA
had
a
higher
percent
reduction
than
ESA.
As
with
the
parent
acetochlor,
in
some
cases
the
finished
water
sample
was
higher
than
the
raw
water
sample
as
indicated
by
a
negative
percent
reduction
on
the
chart.

Degredate
Percent
Reduction
0
50
100
150
200
250
300
350
400
450
­
100
­
85
­
75
­
50
­
25
0
25
50
75
85
100
Percent
Reduction
Frequency
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
AcOXA
Frequency
AcESA
Frequency
AcOXA
Cumulative
%

AcESA
Cumulative
%

Figure
17.
Percent
reduction
of
acetochlor
degradates
in
surface
drinking
water
supplies.

7.1.2.
Chronic
Exposure
Distributions
Chronic
exposure
for
acetochlor
degradates
and
combined
residues
were
also
determined
for
the
surface
drinking
water
supplies.
Figure
18
presents
the
cumulative
distribution
of
chronic
exposure
based
on
the
maximum
time­
weighted
annualized
mean
for
each
site.
The
total
residue
was
computed
by
summing
the
concentrations
for
the
parent
and
degradates.
Therefore,
the
chart
only
reflects
sample
observations
where
a
sample
was
analyzed
for
both
the
parent
and
degradates.

The
chart
demonstrates
that
overall,
TWAMs
for
each
of
the
degradates
and
total
combined
residues
were
higher
in
raw
water
samples
(
dotted
lines)
than
in
finished
water
samples
(
solid
lines).
This
again
emphasizes
the
importance
of
surface
water
treatment
in
reducing
exposure
to
acetochlor
degradates.
­
60­

Frequency
Distribution
for
MAX
TWAM
SDWS
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%

0
0.003
0.005
0.01
0.05
0.1
0.5
1
2
4
8
>
8
Concentration
(
ppb)
Frequency
AcESA
Finished
AcESA
Raw
AcOxa
Finished
AcOxa
Raw
Total
residue­
Finished
Total
residue­
Raw
Figure
18.
Chronic
exposure
distribution
for
acetochlor
degradates
(
ESA
and
OXA)
in
surface
drinking
water
supplies
using
the
maximum
time­
weighted
annualized
mean
for
each
site.
Summary
of
USGS
monitoring
results
for
acetochlor
degradates
7.2.
Ground
Water
Two
separate
data
files
were
used
in
this
analysis
(
Table
5).
One
file
contained
all
the
concentration
values
observed
in
the
PGW
studies
provided
by
the
ARP,
while
the
second
contained
raw
uncensored
concentrations
also
provided
by
the
ARP.
Under
the
assumption
that
it
represented
the
best
available
estimates
of
unmeasured
values
(
any
substitution
method
for
nondetects
would
be
arbitrary),
the
PGW
uncensored
file
was
used
to
compute
time­
weighted
annualized
means
and
percentiles.

7.2.1.
Comparison
of
Ground
Water
Degradate
Monitoring
results
to
Cancellation
/
Mitigation
Endpoints.

The
degradate
data
are
discussed
here
with
regard
to
the
mitigation
endpoints
included
in
the
acetochlor
registration
agreement,
however,
it
is
not
anticipated
that
the
compounds
will
needed
to
be
included
in
the
residues
of
concern
for
the
drinking
water
risk
assessment.
The
conditional
registration
agreement
only
requires
mitigation
or
cancellation
of
acetochlor
"
residues
of
concern"
once
the
presence
of
a
"
pattern
of
movement"
as
specified
in
the
agreement
is
established.
In
the
PGW
studies,
one
indication
of
a
pattern
of
movement
was
defined
as
the
detection
of
acetochlor
or
any
of
its
degradates
greater
than
or
equal
to
1.0
ppb
at
nine
foot
lysimeter
depth
as
well
as
corresponding
three
and
6
foot
depths
in
that
cluster.
The
Appendix
(
Section
12.8
of
this
report)
lists
all
the
sites
where
acetochlor
or
either
of
its
degradates
equaled
or
exceeded
1.0
ppb
at
three,
six,
and
nine
foot
depths.
The
acetochlor
degradate
OXA
did
not
exceed
1.0
ppb
at
three,
six,
and
nine
foot
depths
in
any
cluster.
However
in
293
instances,
ESA
equaled
­
61­

or
exceeded
1.0
ppb
at
the
nine
foot
lysimeter
depth
in
clusters
where
ESA
also
exceeded
1.0
ppb
at
the
three
and
six
foot
depths
at
some
time
over
the
course
of
investigation.

Seven
out
of
the
eight
states
in
the
PGW
studies
demonstrated
a
pattern
of
movement
of
ESA
as
defined
by
exceedence
of
1.0
ppb
in
at
least
one
cluster
of
lysimeters
at
three,
six,
and
nine
foot
depths
(
see
"
Data
Tables
for
the
ARP
Monitoring
Studies
Related
to
Mitigation
Endpoints"
in
the
Appendix).
Although
the
cancellation
triggers
apply
only
to
the
parent
acetochlor,
the
pattern
of
movement
demonstrated
by
the
acetochlor
degradates
would
be
important
if
one
of
the
degradates
becomes
a
toxicological
concern.

A
cancellation
endpoint
for
the
parent
acetochlor
was
the
detection
of
acetochlor
at
0.10
ppb
or
above
in
20
or
more
wells
in
the
state
ground
water
monitoring
program
followed
by
two
subsequent
detections
in
monthly
follow
up
samples
within
six
months.
Again,
this
does
not
presently
apply
to
acetochlor
degradates,
however
degradate
data
was
compared
to
the
endpoint
for
parent.
A
number
of
sites
in
the
state
ground
water
monitoring
program
had
acetochlor
degradate
detections
of
at
least
0.10
ppb
as
well
as
in
two
monthly
follow
up
samples
(
see
Appendix,
section
12.7).

7.2.2.
PGW
Acute
Exposure
by
Site.

Distributions
of
peak
concentrations
by
site
using
the
maximum
of
any
individual
cluster
are
provided
in
Table
25.
Data
are
summarized
by
the
peak
value
across
all
clusters,
as
well
as
the
average
of
all
clusters
for
each
depth.
Because
of
the
overwhelming
number
of
censored
values,
maximum
TWAMs
as
well
as
maximum
95th
percentiles
were
computed
based
on
the
uncensored
data
file
provided
by
the
ARP
(
Table
5).
In
addition,
the
maximum
three
consecutive
sample
running
average
for
each
of
the
eight
PGW
sites
is
included.
A
three
consecutive
running
average
was
used
to
reduce
the
likelihood
that
the
assessment
would
be
based
upon
statistical
outliers.
A
three
value
running
average
was
chosen
over
a
three
month
running
average
due
to
the
frequency
of
sampling.
In
some
cases
observations
were
spaced
more
than
one
month
apart
as
a
result
of
sampling
limitations,
such
as
inclement
weather
or
inadequate
sample
volume
in
the
well
or
lysimeter.
­
62­

Table
21.
Concentrations
of
ESA
observed
in
9­
foot
lysimeters
from
the
eight
prospective
ground
water
studies.

Max
TWAM
Max
95
%
tile
Max
Concentration
STATE
Cluster
Average
Single
Cluster
Cluster
Average
Single
Cluster
Cluster
Average
Single
Cluster
Max
Moving
Average
DE
0.77
2.48
1.31
3.90
1.70
4.30
3.73
IA
0.94
3.17
1.58
5.09
1.68
5.40
3.13
IN
5.79
18.29
9.79
23.39
13.00
24.00
22.67
MN
6.58
13.42
8.84
23.39
9.70
24.00
19.33
NE
2.26
9.21
2.32
11.19
2.33
11.40
11.03
OH
0.36
2.11
1.88
5.81
2.96
6.50
5.87
PA
1.13
2.53
1.41
3.50
1.42
3.59
3.39
WI
9.69
14.44
16.71
29.60
17.00
36.00
22.67
All
values
are
as
ppb
(
ug/
L).
Values
below
0.2
ppb
are
not
verifiable
because
of
the
detection
limit
of
the
analytical
method.
Single
Cluster
=
Statistic
applies
to
all
observed
values
for
the
given
depth;
Cluster
Average
=
Statistic
applies
to
concentrations
averaged
across
all
clusters
for
a
given
date
for
the
depth
listed;
Max
TWAM
=
Maximum
time­
weighted
average
based
on
uncensored
data
file;
Max
95%
tile
=
The
amount
of
time
during
the
calendar
year
the
concentration
was
below
the
listed
value
based
on
uncensored
data
file;
Maximum
Moving
Average
=
The
single
highest
average
for
3
consecutive
values
(
separately
by
cluster
and
depth)
across
all
clusters
based
on
uncensored
data
file;
NA
=
Insufficient
uncensored
data
to
compute
the
value
Table
22.
Concentrations
of
ESA
observed
in
shallow
ground
water
from
the
eight
prospective
ground
water
studies.

Max
TWAM
Max
95
%
tile
Max
Concentration
STATE
Cluster
Average
Single
Cluster
Cluster
Average
Single
Cluster
Cluster
Average
Single
Cluster
Max
Moving
Average
DE
1.179
2.519
1.370
3.148
1.443
3.220
3.013
IA
0.123
0.240
0.287
0.728
0.312
0.766
0.644
IN
1.237
9.241
1.684
13.470
1.775
14.200
13.400
MN
1.523
3.015
2.592
6.423
2.698
7.700
6.067
NE
<
0.2
<
0.2
<
0.2
<
0.2
<
0.2
<
0.2
<
0.2
OH
<
0.2
<
0.2
<
0.2
<
0.2
<
0.2
<
0.2
<
0.2
PA
1.567
6.848
1.924
8.056
1.962
8.300
7.980
WI
3.533
8.054
4.590
10.679
4.736
11.000
8.133
All
values
are
as
ppb
(
ug/
L).
Values
below
0.2
ppb
are
not
verifiable
because
of
the
detection
limit
of
the
analytical
method.
Single
Cluster
=
Statistic
applies
to
all
observed
values
for
the
given
depth;
Cluster
Average
=
Statistic
applies
to
concentrations
averaged
across
all
clusters
for
a
given
date
for
the
depth
listed;
Max
TWAM
=
Maximum
time­
weighted
average
based
on
uncensored
data
file;
Max
95%
tile
=
The
amount
of
time
during
the
calendar
year
the
concentration
was
below
the
listed
value
based
on
uncensored
data
file;
Maximum
Moving
Average
=
The
single
highest
average
for
3
consecutive
values
(
separately
by
cluster
and
depth)
across
all
clusters
based
on
uncensored
data
file;
NA
=
Insufficient
uncensored
data
to
compute
the
value
­
63­

Table
23.
Comparison
of
Acetochlor
ESA
and
bromide
breakthrough
in
9­
foot
lysimeters
at
the
eight
prospective
ground­
water
monitoring
sites:
Normalized
concentrations.
1
Application
rates
lb
a.
i.
/
acre
Acetochlor
ESA
Max
Concentration
Bromide
Max
Concentration
Acetochlor
ESA
Bromide
STATE
Acetochlor
Bromide
Cluster
Average
Single
Cluster
Cluster
Average
Single
Cluster
Max
Moving
Average
Max
Moving
Average
DE
2.05
89
0.829
2.098
40
80
1.820
52
IA
3.12
98
0.538
1.731
28
58
1.003
16
IN
2.5
98
5.200
9.600
31
61
9.068
23
MN
2.14
82
4.533
11.215
61
107
9.033
13
NE
3.12
98
0.747
3.654
80
133
3.535
125
OH
2.05
98
1.444
3.171
60
112
2.863
NA
PA
3.12
89
0.455
1.151
18
28
1.087
12
WI
1.78
125
9.551
20.225
95
136
12.736
NA
1
Calculated
concentration
in
ug/
L
divided
by
the
application
rate
as
pound
active
ingredient
per
acre.
This
gives
a
comparable
concentration
for
the
tracer
and
pesticide
degradate
if
the
observed
concentration
is
proportional
to
the
application
rate;
Single
Cluster
=
Statistic
applies
to
all
observed
values
for
the
given
depth;
Cluster
Average
=
Statistic
applies
to
concentrations
averaged
across
all
cluster
for
a
given
date
for
the
depth
listed;
Max
TWAM
=
Maximum
timeweighted
average
observed;
Max
95%
tile
=
Represents
the
amount
of
time
during
the
calendar
year
the
concentration
was
below
the
listed
value;
Maximum
Moving
Average
=
The
single
highest
average
for
3
consecutive
values
(
separately
by
cluster
and
depth)
across
all
clusters;
NA
=
Insufficient
uncensored
data
to
compute
the
value
Table
24.
Comparison
of
Acetochlor
ESA
and
bromide
breakthrough
(
with
months
after
treatment)
in
shallow
ground
water
at
the
eight
prospective
ground­
water
monitoring
sites:
Normalized
concentrations.
1
Application
rates
(
as
lb
ai/
A
or
lb
Br/
A)
ESA
Max
Concentration
Bromide
Max
Concentration
ESA
Bromide
STATE
Acetochlor
Bromide
Cluster
Average
Single
Cluster
Cluster
Average
Single
Cluster
Max
Moving
Average
Max
Moving
Average
DE
2.05
59.8
0.702
1.571
98.0
120.6
1.868
114.7
(
33)
(
33)
(
39)
(
29)
(
13.5)
(
31)

IA
3.12
65.8
0.112
0.160
31.3
62.6
1.003
65.5
(
24)
(
22)
(
23)
(
23)
(
1.5)
(
28)

IN
2.5
65.8
0.684
5.200
29.8
86.4
9.068
81.9
(
6)
(
6)
(
34)
(
34)
(
15)
(
15)

MN
2.14
55.1
1.280
3.598
38.7
73.0
9.033
146.0
(
27)
(
30)
(
38)
(
27&
28)
(
13)
(
23)

NE
3.12
65.8
0.048
0.160
13.4
71.5
3.535
186.2
(
34)
(
34)
(
54)
(
54)
(
83)
(
87)

OH
2.05
65.8
0.049
0.049
16.4
20.9
2.863
105.7
(
7)
(­­)
(
11)
(
11)
(
4)
(
14)

PA
3.12
59.8
0.628
2.660
11.9
26.8
2.558
40.2
(
55)
(
51)
(
41)
(
53)
(
54)
(
28)

WI
1.78
83.9
2.584
6.180
70.0
131.1
12.736
186.2
(
24)
(
24)
(
24)
(
23)
(
14)
(
16)
1
Calculated
concentration
in
ug/
L
divided
by
the
application
rate
as
pound
active
ingredient
per
acre.
This
gives
a
comparable
concentration
for
the
tracer
and
pesticide
degradate
if
the
observed
concentration
is
proportional
to
the
application
rate;
single
cluster
=
statistic
applies
to
all
observed
values
for
the
given
depth;
cluster
average
=
statistic
applies
to
concentrations
averaged
across
all
cluster
for
a
given
date
for
the
depth
listed;
max
TWAM
=
maximum
timeweighted
average
observed;
max
95%
tile
represents
the
amount
of
time
during
the
calendar
year
the
concentration
was
below
the
listed
value;
maximum
moving
average
=
the
single
highest
average
for
3
consecutive
values
(
separately
by
cluster
and
depth)
across
all
clusters;
NA
=
insufficient
data
in
the
uncensored
file
to
compute
the
value.
Italicized
values
in
parenthesis
for
each
site
are
the
months
after
treatment
that
the
ESA
or
Br
concentration
was
observed.
­
64­

Table
25.
Concentrations
of
acetochlor
OXA
observed
in
9­
foot
lysimeters
from
the
eight
prospective
ground
water
studies.

Max
TWAM
Max
95
%
tile
Max
Concentration
STATE
Cluster
Average
Single
Cluster
Cluster
Average
Single
Cluster
Cluster
Average
Single
Cluster
Max
Moving
Average
DE
<
0.1
<
0.1
<
0.1
<
0.1
<
0.1
<
0.1
<
0.1
IA
<
0.1
0.23
0.12
0.37
0.13
0.40
0.13
IN
0.58
1.16
0.69
1.38
0.75
1.50
0.50
MN
0.16
0.18
0.19
<
0.1
0.20
2.70
0.90
NE
<
0.1
0.12
<
0.1
0.13
<
0.1
0.13
0.11
OH
<
0.1
0.40
0.14
1.53
0.37
2.20
1.10
PA
<
0.1
<
0.1
0.10
0.26
0.15
0.30
0.17
WI
<
0.1
<
0.1
<
0.1
<
0.1
<
0.1
<
0.1
<
0.1
All
values
are
as
ppb
(
ug/
L).
Values
below
0.1
ppb
are
not
verifiable
because
of
the
detection
limit
of
the
analytical
method.
Single
Cluster
=
Statistic
applies
to
all
observed
values
for
the
given
depth
Cluster
Average
=
Statistic
applies
to
concentrations
averaged
across
all
clusters
for
a
given
date
for
the
depth
listed
Max
TWAM
=
Maximum
time­
weighted
average
based
on
uncensored
data
file
Max
95%
tile
=
The
amount
of
time
during
the
calendar
year
the
concentration
was
below
the
listed
value
based
on
uncensored
data
file.
Maximum
Moving
Average
=
The
single
highest
average
for
3
consecutive
values
(
separately
by
cluster
and
depth)
across
all
clusters
based
on
uncensored
data
file.
NA
=
Insufficient
data
in
the
uncensored
file
to
compute
the
value
Table
26.
.
Concentrations
of
acetochlor
OXA
observed
in
shallow
ground
water
from
the
eight
prospective
ground
water
studies.

Max
TWAM
Max
95
%
tile
Max
Concentration
STATE
Cluster
Average
Single
Cluster
Cluster
Average
Single
Cluster
Cluster
Average
Single
Cluster
Max
Moving
Average
DE
<
0.1
<
0.1
<
0.1
<
0.1
<
0.1
<
0.1
<
0.1
IA
<
0.1
<
0.1
<
0.1
0.176
<
0.1
0.200
<
0.1
IN
<
0.1
<
0.1
<
0.1
<
0.1
<
0.1
<
0.1
<
0.1
MN
0.207
0.296
0.874
1.339
1.300
1.400
1.100
NE
<
0.1
<
0.1
<
0.1
<
0.1
<
0.1
<
0.1
<
0.1
OH
<
0.1
<
0.1
<
0.1
<
0.1
<
0.1
<
0.1
<
0.1
PA
<
0.1
<
0.1
<
0.1
<
0.1
<
0.1
<
0.1
<
0.1
WI
<
0.1
<
0.1
<
0.1
<
0.1
<
0.1
<
0.1
<
0.1
All
values
are
as
ppb
(
ug/
L).
Values
below
0.1
ppb
are
not
verifiable
because
of
the
detection
limit
of
the
analytical
method.
Single
Cluster
=
Statistic
applies
to
all
observed
values
for
the
given
depth
Cluster
Average
=
Statistic
applies
to
concentrations
averaged
across
all
clusters
for
a
given
date
for
the
depth
listed
Max
TWAM
=
Maximum
time­
weighted
average
based
on
uncensored
data
file
Max
95%
tile
=
The
amount
of
time
during
the
calendar
year
the
concentration
was
below
the
listed
value
based
on
uncensored
data
file.
Maximum
Moving
Average
=
The
single
highest
average
for
3
consecutive
values
(
separately
by
cluster
and
depth)
across
all
clusters
based
on
uncensored
data
file.
NA
=
Insufficient
data
in
the
uncensored
file
to
compute
the
value
­
65­

7.2.3.
Chronic
Exposure
Chronic
exposure
for
acetochlor
degradates
and
combined
residues
were
also
determined
for
the
state
ground
water
monitoring
program.
Figure
19
presents
the
cumulative
distribution
of
chronic
exposure
based
on
the
maximum
time­
weighted
annualized
mean
for
each
site.
The
total
residue
was
computed
by
summing
the
concentrations
for
the
parent
and
degradates.
As
such,
chart
only
reflects
sample
observations
where
a
sample
was
analyzed
for
both
the
parent
and
degradates.
Peak
time­
weighted
annualized
means
concentrations
for
acetochlor
ESA
in
ground
water
were
higher
than
those
for
acetochlor
OXA
in
the
state
monitoring
program
(
Figure
19).

Chronic
Exposure
Cumulative
Frequency
Distribution
Maximum
TWAM
for
SGW
Sites
0%
20%
40%
60%
80%
100%
120%

0
0.003
0.005
0.01
0.05
0.1
0.5
1
2
4
8
>
8
Concentration
(
ppb)
Frequency
ESA
OXA
Total
residue
Figure
19.
Chronic
exposure
distribution
for
acetochlor
degradates
(
ESA
and
OXA)
in
the
state
ground
water
monitoring
program
using
the
maximum
time­
weighted
annualized
mean
for
each
site.

7.3.
Summary
Assessment
of
Exposure
to
Acetochlor
Degradates
Unlike
exposure
to
acetochlor
parent
alone,
the
concentration
profiles
for
the
ARP
studies
show
that
exposure
to
combined
residues
can
be
higher
in
ground
water
than
surface
water
(
Table
27).
The
maximum
annual
mean
concentrations
in
ground
water
were
up
to
8x
greater
than
in
surface
water
and
the
95th
percentile
annual
mean
concentrations
were
up
to
about
5x
greater
than
in
surface
water.
The
combined
exposure
levels
however
have
not
been
used
for
the
OPP
human
health
risk
assessment
(
ACETOCHLOR.
Revised
HED
Chapter
of
the
Tolerance
Reassessment
Eligibility
Decision
(
TRED)
Document.
PC
Code:
121601,
DP
Barcode:
D306535,
D292338;
dated
11/
8/
2005).
In
the
HED
chapter
the
following
is
stated:
­
66­

"
based
on
comparison
of
the
available
toxicity
data
for
acetochlor
and
the
ESA
and
OXA
degradates.
(
summarized
in
Tables
3.2­
3.4
of
the
ACETOCHLOR
HED
Chapter
of
the
TRED)
and
structure­
activity
relationships,
the
MARC
concluded
that:
the
ESA
and
OXA
degradates
of
acetochlor
should
not
be
included
in
the
water
risk
assessment
with
the
parent."

HED
has,
however
calculated
the
risk
contribution
from
drinking
water
separately
each
for
ESA
and
OXA
for
their
respective,
distinctively
different
acute
and
chronic
toxicological
endpoints.
Again
quoting
from
the
HED
Chapter
of
the
TRED
for
acetochlor:

"
Comparison
of
the
toxicities
of
the
ESA
and
OXA
degradates
with
the
toxicity
of
the
parent
acetochlor
[
See
Tables
3.2
and
3.3
of
the
ACETOCHLOR
HED
Chapter
of
the
TRED]
indicated
that
the
degradates
had
distinct,
different,
toxicological
profiles
from
the
parent.
Thus,
endpoints
for
the
risk
assessment
of
the
ESA
and
OXA
degradates
were
searched
within
their
respective
databases."

EFED
has
therefore
separately
evaluated
exposure
to
acetochlor
ESA
and
acetochlor
OXA
by
analysis
of
all
of
the
ARP
surface
water
and
ground
water
monitoring
studies
(
unlike
with
parent
acetochlor,
ground
water
and
surface
water
exposure
are
both
frequently
at
relatively
significant
levels
(
in
terms
of
exposure
frequency
and
amount,
not
in
terms
of
risk
level).

Key
points
to
consider
in
the
interpretation
of
these
results
are:

1.
The
surface
water
data,
unlike
the
ground
water
data,
represent
actual
drinking
water
intakes
or
finished
water;
however,
many
of
the
highest
acetochlor
use
watersheds
were
not
included
in
the
monitoring
program.
2.
Since
this
monitoring
program
started
immediately
after
the
registration
of
acetochlor,
the
full
extent
of
contamination
of
ground
water
possible
from
the
use
of
acetochlor
could
not
be
assessed
with
confidence
in
the
SGW
program
since
it
may
take
many
years
to
observe
the
maximum
extent
of
ground
water
contamination
from
the
use
of
a
pesticide.
Even
in
the
PGW
program,
there
was
one
site
(
Nebraska)
where
the
leaching
of
an
acetochlor
degradate
(
ESA)
was
still
moving
downward
through
the
vadose
zone
when
sampling
was
terminated
seven
years
after
the
original
(
and
only)
acetochlor
application.
3.
In
both
the
SGW
and
PGW
ground
water
monitoring
programs,
the
water
sampled
was
more
vulnerable
than
most
(
but
not
all)
water
used
for
drinking
water.
4.
The
results
of
this
monitoring
analysis
only
apply
to
acetochlor
use
on
field
corn
(
significant
new
field
uses
are
currently
under
review
by
EPA).
­
67­

The
highest
monitored
values
for
acetochlor
ESA
were:

Acute
exposure
(
Table
28):

20.0
ppb
ESA
in
a
sample
from
one
of
the
approximately
175
SGW
study
sites.

14.2
ppb
ESA
in
a
sample
from
one
of
the
shallow
wells
from
one
of
the
eight
PGW
study
sites.

4.8
ppb
ESA
in
a
sample
from
one
of
the
approximately
175
SDWS
study
sites.

Chronic
exposure
(
Table
30):

12.7
ppb
ESA
TWAM
from
one
of
the
SGW
study
sites.

9.2
ppb
ESA
TWAM
from
one
of
the
shallow
wells
from
one
of
the
PGW
study
sites.

1.0
ppb
ESA
TWAM
from
one
of
the
SDWS
study
sites.

The
highest
monitored
values
for
acetochlor
OXA
were:

Acute
exposure
(
Table
29):

19.1
ppb
OXA
in
a
sample
from
a
shallow
well
from
one
of
the
SGW
study
sites.

1.4
ppb
OXA
in
a
sample
from
one
of
the
shallow
wells
from
one
of
the
PGW
study
sites.

6.3
ppb
OXA
in
a
sample
from
one
of
the
SDWS
study
sites.

Chronic
exposure
(
Table
31):

5.9
ppb
OXA
TWAM
from
a
shallow
well
from
one
of
the
SGW
study
sites.

Not
calculated
(
TWAM
<
1
ppb
for
all
wells)
OXA
for
the
eight
PGW
study
sites.

1.7
ppb
TWAM
OXA
from
one
of
the
approximately
175
SDWS
study
sites.

In
general
acetochlor
ESA
was
detected
more
frequently
at
higher
concentrations
in
both
of
the
ground
water
studies
than
in
the
SDWS.
The
highest
acetochlor
OXA
acute
and
chronic
exposure
levels
occurred
in
ground
water,
but
there
was
less
overall
difference
in
the
residue
levels
between
ground
and
surface
than
there
was
for
ESA
and
the
median
acute
and
chronic
values
were
actually
higher
in
the
SDWS
than
in
the
PGW
or
SGW
studies.

Table
27.
Summary
presentation
of
time­
weighted
annualized
mean
concentrations
(
ppb)
for
the
combined
residues
of
acetochlor
(
parent
+
ESA
and
OXA
degradates)
in
surface
and
ground
water
(
based
on
maximum
TWAM
values
observed
at
each
site
by
calendar
year).

Study
N
Maximum
95th
Percentile
Median
­
68­

Table
27.
Summary
presentation
of
time­
weighted
annualized
mean
concentrations
(
ppb)
for
the
combined
residues
of
acetochlor
(
parent
+
ESA
and
OXA
degradates)
in
surface
and
ground
water
(
based
on
maximum
TWAM
values
observed
at
each
site
by
calendar
year).

Study
N
Maximum
95th
Percentile
Median
Surface
Water
­
SDWS
raw
43
2.04
1.67
0.31
Surface
Water
­
SDWS
finished
175
2.91
1.39
0.25
Ground
Water
(
shallow)
 
PGW
site
averages
8
3.51
2.83
1.12
Ground
Water
(
shallow)
 
PGW
cluster
maximums
8
8.11
7.57
2.85
Ground
Water
 
SGW
176
24.11
3.24
0.08
Table
28.
Acute
Exposure
to
ESA.
Summary
presentation
of
acute
concentrations
(
ppb)
for
the
residues
of
acetochlor
ethanesulfonic
acid
in
surface
and
ground
water.
Sample
/
Study
Type
(#
of
sites)
N1
Maximu
m
99th
Percentile
95th
Percentile
Median
Surface
Water
 
SDWS
raw
2
(
ca.
43
sites)
1496
2.310
1.000
0.633
<
0.200
Surface
Water
 
SDWS
finished
2
(
ca.
175
sites)
6774
3.320
1.133
0.571
<
0.200
Ground
Water
(
shallow)
 
PGW
site
averages
by
date
(
8
sites)
670
4.736
2.471
3
1.488
3
<
0.200
3
Ground
Water
(
shallow)
 
PGW
single
cluster
basis
(
8
sites)
NC
14.200
6.100
3
2.640
3
<
0.200
3
Ground
Water
 
SGW
(
ca.
175
sites)
1983
20.000
6.418
1.790
<
0.200
1
Number
of
samples
represented.
NC
=
Not
calculated.
2
Comparisons
between
raw
and
finished
water
concentration
distributions
should
be
made
with
caution
since
most
SDWS
sites
never
had
raw
water
sampled.
Statistics
based
on
monitoring
for
only
the
last
three
years
of
the
study
(
1999
to
2001);
this
is
also
true
for
the
SGW
study.
3
Statistics
here
are
less
meaningful
for
the
PGW
studies
because
of
the
small
number
of
study
sites
(
8),
the
lag
time
between
the
start
of
sampling
of
ground
water
after
application
and
breakthrough
of
any
residues
into
ground
water,
and
the
lack
of
reproduction
of
long­
term
use
patterns
in
PGW
studies
(
i.
e.,
generally
only
a
one­
time
application
of
acetochlor
was
made
during
the
first
growing
season
of
­
69­

Table
28.
Acute
Exposure
to
ESA.
Summary
presentation
of
acute
concentrations
(
ppb)
for
the
residues
of
acetochlor
ethanesulfonic
acid
in
surface
and
ground
water.
Sample
/
Study
Type
(#
of
sites)
N1
Maximu
m
99th
Percentile
95th
Percentile
Median
the
study).

Table
29.
Acute
Exposure
to
OXA.
Summary
presentation
of
acute
concentrations
(
ppb)
for
the
residues
of
acetochlor
oxanilic
acid
in
surface
and
ground
water.
Sample
/
Study
Type
(#
of
sites)
N1
Maximu
m
99th
Percentile
95th
Percentile
Median
Surface
Water
 
SDWS
raw
2
(
ca.
43
sites)
1496
3.320
1.634
0.898
0.118
Surface
Water
 
SDWS
finished
2
(
ca.
175
sites)
6774
6.340
1.593
0.761
<
0.1
Ground
Water
(
shallow)
 
PGW
site
averages
by
date
(
8
sites)
670
Low
4
Low
Low
Low
Ground
Water
(
shallow)
 
PGW
single
cluster
basis
(
8
sites)
NC
1.400
Low
Low
Low
Ground
Water
 
SGW
(
ca.
175
sites)
1983
19.100
1.98
0.177
<
0.1
1
Number
of
samples
represented.
NC
=
Not
calculated.
2
Comparisons
between
raw
and
finished
water
concentration
distributions
should
be
made
with
caution
since
most
SDWS
sites
never
had
raw
water
sampled.
Statistics
based
on
monitoring
for
only
the
last
three
years
of
the
study
(
1999
to
2001);
this
is
also
true
for
the
SGW
study.
3
Statistics
here
are
less
meaningful
for
the
PGW
studies
because
of
the
small
number
of
study
sites
(
8),
the
lag
time
between
the
start
of
sampling
of
ground
water
after
application
and
breakthrough
of
any
residues
into
ground
water,
and
the
lack
of
reproduction
of
long­
term
use
patterns
in
PGW
studies
(
i.
e.,
generally
only
a
one­
time
application
of
acetochlor
was
made
during
the
first
growing
season
of
the
study).
4
Low
=
Two
few
detections
to
calculate
accurately.

Table
30.
Chronic
Exposure
to
ESA.
Summary
presentation
of
time­
weighted
annualized
mean
concentrations
(
ppb)
for
the
residues
of
acetochlor
ethanesulfonic
acid
in
surface
and
ground
water
(
based
on
maximum
TWAM
values
observed
at
each
site
by
calendar
year).
­
70­

Sample
/
Study
Type
N1
(#
of
sites)
Maximu
m
99th
Percentile
95th
Percentile
Median
Surface
Water
­
SDWS
raw
2
111
(
43)
0.752
0.726
0.525
<
0.200
Surface
Water
­
SDWS
finished
2
486
(
175)
1.008
0.701
0.477
<
0.200
Ground
Water
(
shallow)
­
PGW
site
averages
by
date
8
(
8)
3.53
NA
3
NA
1.21
Ground
Water
(
shallow)
 
PGW
single
cluster
maximums
58
(
8)
9.24
NA
NA
NA
Ground
Water
 
SGW
495
(
176)
12.658
6.713
1.819
<
0.200
1
Number
of
TWAMs
included
in
statistics;
followed
by
number
of
study
sites
represented
in
parenthesis.
Number
of
sites
for
SDWS
and
SGW
does
not
include
direct
replacement
sites.
2
Comparisons
between
raw
and
finished
water
concentration
distributions
should
be
made
with
caution
since
most
SDWS
sites
never
had
raw
water
sampled.
Statistics
based
on
monitoring
for
only
the
last
three
years
of
the
study
(
1999
to
2001);
this
is
also
true
for
the
SGW
study.
3
NA
=
calculation
not
appropriate
because
of
the
small
number
of
PGW
study
sites
(
8)
and
the
lack
of
reproduction
of
long­
term
use
patterns
at
the
study
sites.
This
is
also
why
only
the
PGW
maximum
single
TWAM
at
each
site
was
calculated
and
is
a
more
appropriate
endpoint
for
chronic
exposure
than
multi­
year
means.

Table
31.
Chronic
Exposure
to
OXA.
Summary
presentation
of
time­
weighted
annualized
mean
concentrations
(
ppb)
for
the
residues
of
acetochlor
oxanilic
acid
in
surface
and
ground
water
(
based
on
maximum
TWAM
values
observed
at
each
site
by
calendar
year).
Sample
/
Study
Type
N1
(#
of
sites)
Maximu
m
99th
Percentile
95th
Percentile
Median
Surface
Water
­
SDWS
raw
2
111
(
43)
1.289
1.220
0.766
0.140
Surface
Water
­
SDWS
finished
2
486
(
175)
1.697
0.935
0.628
<
0.100
Ground
Water
(
shallow)
­
PGW
site
averages
by
date
8
(
8)
Lower
3
NA
4
NA
NA
Ground
Water
(
shallow)
 
PGW
single
cluster
maximums
58
(
8)
Lower
NA
NA
NA
Ground
Water
 
SGW
495
(
176)
5.860
1.852
0.224
<
0.100
1
Number
of
TWAMs
included
in
statistics;
followed
by
number
of
study
sites
represented
in
parenthesis.
Number
of
sites
for
SDWS
and
SGW
does
not
include
direct
replacement
sites.
2
Comparisons
between
raw
and
finished
water
concentration
distributions
should
be
made
with
caution
since
most
SDWS
sites
never
had
raw
water
sampled.
Statistics
based
on
monitoring
for
only
the
last
three
years
of
the
study
(
1999
to
2001);
this
is
also
true
for
the
SGW
study.
3
Lower
=
Chronic
exposure
was
not
calculated
for
the
PGW
because
the
exposure
level
was
clearly
lower
than
for
the
SDWS
or
SGW
studies
and
the
quantification
detection
frequency
was
too
low
for
accurate
calculation.
4
NA
=
calculation
not
appropriate
because
of
the
small
number
of
PGW
study
sites
(
8)
and
the
lack
of
reproduction
of
long­
term
use
patterns
at
the
study
sites.
This
is
also
why
only
the
PGW
maximum
single
TWAM
at
each
site
was
calculated
and
is
a
more
appropriate
endpoint
for
chronic
exposure
than
­
71­

Table
31.
Chronic
Exposure
to
OXA.
Summary
presentation
of
time­
weighted
annualized
mean
concentrations
(
ppb)
for
the
residues
of
acetochlor
oxanilic
acid
in
surface
and
ground
water
(
based
on
maximum
TWAM
values
observed
at
each
site
by
calendar
year).
Sample
/
Study
Type
N1
(#
of
sites)
Maximu
m
99th
Percentile
95th
Percentile
Median
multi­
year
means.

The
ARP
studies
demonstrate
that
the
degradates
of
acetochlor
(
and
two
other
acetanilide
herbicides,
see
the
following
section)
can
significantly
impact
ground
and
surface
waters
and
that
exposure
to
some
mobile
and
persistent
degradates
can
be
significantly
higher
and
more
widespread
in
ground
water
than
the
respective
parent
compounds
or
than
in
surface
waters.
Similar
results
have
been
obtained
by
Kalkhoff
et
al.
(
1998),
Kolpin
et
al.
(
1996,
1997,
and
1998),
and
Rheineck
and
Postle
(
2000).

8.
OTHER
CHEMICALS
The
ARP
collected
a
wealth
of
monitoring
data
for
three
other
pesticides
in
both
the
SDWS
and
SGW
studies.
Virtually
every
sample
collected
in
these
studies
for
acetochlor
analysis
was
also
analyzed
for
atrazine,
alachlor,
and
metolachlor.
The
ethanesulfonic
acid
and
oxanilic
acid
degradates
of
both
alachlor
and
metolachlor
were
also
included
in
the
analytical
plan.

Sample
results
for
these
other
analytes
are
given
in
Tables
28
to
30
Figures
20
to
22
taken
from
de
Guzman
et
al.
(
2005),
MRID
45722701,
and
Hackett
et
al.
(
2005).
In
general,
the
detection
frequency
was
atrazine
>
metolachor
>
alachlor
or
acetochlor
in
both
studies;
changes
in
usage
pattern
over
the
course
of
the
studies
had
a
marked
impact
on
the
detection
frequency
of
alachlor
(
declining
use
over
the
7
years
of
monitoring
in
the
SDWS)
and
acetochlor
(
increasing
use
over
the
7­
year
monitoring
period
in
the
SDWS).
Metolachlor
degradates
were
generally
detected
with
greater
frequency
than
alachlor
or
acetochlor
degradates.
The
sulfonic
acid
degradates
were
detected
more
frequently
than
the
oxanilic
acid
degradates
of
the
same
parent
herbicide
in
ground
water;
the
detection
frequency
was
generally
similar
for
the
two
degradates
in
surface
waters.

Table
32.
Occurrence
(%)
of
TWAMs
in
Finished
Drinking
Water
at
Various
Concentrations
by
Sampling
Stratum
Percent
Occurrence
AMC
(
µ
g
L­
1
)
Great
Continental
Smaller
Watersheds
and
Analyte
Lakes
Rivers
5­
10%
CI1
11­
20%
CI
>
20%
CI
Overall
­
72­

>
0.1
Acetochlor
0.0
5.0
2.4
8.5
12.8
8.1
>
1.0
Acetochlor
0.0
0.0
0.0
0.0
0.2
0.1
>
0.5
Ac_
ESA
0.0
0.0
0.9
1.0
10.6
4.9
>
0.5
Ac_
OXA
0.0
0.0
5.2
5.2
15.0
8.5
>
0.1
Alachlor
0.0
0.0
3.1
5.8
2.6
2.9
>
1.0
Alachlor
0.0
0.0
0.0
0.0
0.0
0.0
>
0.5
AlESA
0.0
0.0
0.9
3.1
1.5
1.4
>
0.5
AlOXA
0.0
0.0
2.6
0.0
0.5
0.8
>
0.1
Atrazine
7.6
70.3
58.7
85.7
86.2
74.4
>
1.0
Atrazine
0.0
0.8
12.5
30.5
25.8
19.8
>
0.1
Metolachlor
0.0
36.4
25.4
44.0
44.7
37.1
>
1.0
Metolachlor
0.0
0.0
1.7
2.7
3.0
2.2
>
0.5
MeESA
0.0
5.8
15.5
29.9
45.9
29.4
>
0.5
MeOXA
0.0
0.0
6.0
20.6
16.4
12.4
1
CI
=
Corn
production
intensity
in
the
watershed.

Figure
20.
Box
plot
of
annualized
mean
concentrations
(
AMCs)
of
parent
herbicides
in
finished
drinking
water
from
the
SDWS
study
(
Hackett
et
al.,
2005).
­
73­

Figure
21.
Co­
occurrence
of
(
a)
sulfonic
acid
(
ESA)
degradate
residues
and
(
b)
oxanilic
acid
(
OXA)
degradate
residues
for
acetochlor,
alachlor,
and
metolachlor
in
the
SGW
study.
Values
reflect
the
number
of
SGW
wells
with
observed
residues
(
Minimum
detection
limit
was
0.2
ppb
for
the
sulfonic
acid
degradates
and
0.1
ppb
for
the
oxanilic
acid
degradates).
No
ESA
soil
degradate
residues
were
observed
in
49
of
the
182
wells
and
no
OXA
soil
degradate
residues
were
observed
in
110
of
the
182
wells.
Source:
de
Guzman
et
al.
(
2005).

0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%

0
0.2
0.4
0.6
0.8
1
Nationwide
Use
on
Corn
(
kg/
ha)
Detection
Frequency
Atrazine
Metolachlor
Acetochlor
Alachlor
1995
1995
1995
1995
2001
2001
2001
2001
Figure
22.
.
Frequency
of
drinking
water
detections
by
year
for
parent
herbicides
as
a
function
of
use
(
relative
use
on
the
x
axis)
 
SDWS
study.
­
74­

Table
33.
Summary
of
the
Distribution
of
Degradate
Residues
for
ARP
SGW
Analytes
 
2001
Data
only.

The
values
represent
the
numbers
of
samples
with
residues
fitting
the
specified
criteria.

Compound
Not
Detected
OR
"
NR"
LOD
to
0.499
0.50
to
0.999
ppb
1.0
to
1.999
ppb
2.0
to
9.999
ppb
>=
10.0
ppb
Total
Ac_
ESA
475
56
31
32
28
2
624
AlESA
435
48
45
40
51
5
624
MeESA
311
74
59
55
114
11
624
Ac_
OXA
578
27
6
7
5
1
624
AlOXA
599
18
0
3
4
0
624
MeOXA
506
80
16
10
12
0
624
Ac_
ESA
=
Acetochlor
sulfonic
acid
Ac_
OXA
=
Acetochlor
oxanilic
acid
AlESA
=
Alachlor
sulfonic
acid
AlOXA
=
Alachlor
oxanilic
acid
MeESA
=
Metolachlor
sulfonic
acid
MeOXA
=
Metolachlor
oxanilic
acid
OXA
Limit
of
Detection
(
LOD)
=
0.10
ppb
ESA
Limit
of
Detection
(
LOD)
=
0.20
ppb
Limit
of
Quantitation
(
LOQ)
=
0.50
ppb.

Source:
MRID
45722701.

Table
34.
Summary
of
the
Distribution
of
Parent
Residues
for
ARP
SGW
Analytes
 
2001
data
only.

Compound
Not
Detected
(
ND)
OR
"
NR"
0.03
to
0.049
ppb
0.05
to
0.099
ppb
0.10
to
0.249
ppb
0.25
to
0.499
ppb
0.50
to
4.999
ppb
>=
5.0
ppb
Total
Acetochlor
611
3
2
2
3
3
0
624
Alachlor
623
ND
1
0
0
0
0
624
Atrazine
400
38
58
87
28
13
0
624
Metolachlor
611
1
9
3
0
0
0
624
The
values
represent
the
numbers
of
samples
with
residues
fitting
the
specified
criteria.

Limit
of
Detection
(
LOD)
=
0.03
ppb
for
acetochlor,
atrazine,
and
metolachlor.

Alachlor
LOD
=
0.05
ppb
Limit
of
Quantitation
(
LOQ)
=
0.05
ppb.

Source:
MRID
45722701.
­
75­

9.
CONCLUSIONS
This
analysis
characterized
the
overall
detection
of
acetochlor
and
its
degradates
(
ethanesulfonic
acid,
and
oxanilic
acid)
with
an
emphasis
on
parent
acetochlor,
given
its
inclusion
by
the
Office
of
Pesticide
Programs
in
the
residues
of
concern
for
human
exposure.

9.1.
Parent
Acetochlor
Surface
water
sources
are
the
driver
for
exposure
to
parent
acetochlor
(
Table
1).
There
is
a
potential
for
underestimation
of
chronic
exposure
to
acetochlor
parent
from
the
ARP
study
because
of:
 
The
lack
of
raw
water
analyses
at
most
of
the
sites
makes
it
difficult
to
extrapolate
the
results
to
estimate
exposure
in
additional
(
or
new)
use
areas
or
to
predict
the
impact
of
changes
in
the
type
of
water
treatment
used
on
exposure
levels.
 
Some
areas
with
fewer
CWS
that
utilize
surface
waters
present
(
or
use
a
mixture
of
sources)
were
largely
unrepresented
in
the
SDWS
Available
data
indicate
that
water
treatment
involving
the
use
of
activated
carbon
may
reduce
exposure
by
close
to
50%
on
average;
limitations
on
the
SDWS
data
preclude
generalizing
this
as
a
predictable
effect
of
water
treatment.
Others
have
found
that
GAC
treatment
may
remove
60
to
90%
of
the
acetochlor
parent
residues
originally
present
in
the
raw
water
(
Bloomquist
et
al.,
2001;
Coupe
et
al.,
2004).

The
ARP
data
that
are
available
match
raw
and
finished
water
samples
at
selected
sites
only
in
the
sense
that
they
were
taken
on
the
same
day.
Matching
of
the
same
volume
of
water
is
difficult,
but
the
publications
by
Blomquist
et
al.
and
Coupe
et
al.
provide
a
description
of
an
attempt
to
match
such
samples
as
closely
as
possible.
the
ARP
SDWS
dataset
did
not
measure
samples
in
intake
water
from
those
systems
using
other
types
of
water
treatment,
and
most
of
the
highest
concentrations
observed
in
the
SDWS
study
occurred
in
finished
(
not
raw)
samples.

Maximum
acetochlor
instantaneous
concentrations,
95th
percentiles,
and
time­
weighted
annualized
means
in
the
SDWS
were
all
observed
from
the
Gillespie,
Illinois
reservoir
(
Table
9).
The
highest
acetochlor
parent
concentrations
observed
in
the
ARP
monitoring
program
were
1.428
for
chronic
exposure
(
Table
1)
and
the
highest
finished
water
acute
exposure
was
18.21
(
Table
9);
all
these
values
were
from
the
surface
water
monitoring
program
(
SDWS
study).
Significantly
higher
concentrations
were
observed
in
the
NAWQA
monitoring
program
(
Table
14),
although
these
sites
did
not
necessarily
represent
source
water
for
drinking.

Geographic
analysis
of
the
SDWS
monitoring
locations,
CWS
intake
locations,
and
acetochlor
usage
intensity
indicates
that
the
SDWS
monitoring
program
may
have
missed
some
of
the
watersheds
in
the
Midwestern
US
with
the
highest
acetochlor
usage
intensities
over
the
monitoring
program.
A
lower
rate
of
utilization
and
lower
overall
numbers
of
surface
water
­
76­

sources
by
drinking
water
facilities
in
these
high
acetochlor
use
regions
appears
to
be
a
factor
in
the
paucity
of
sites
in
these
regions
that
were
eventually
selected
for
monitoring
in
the
SDWS
(
probably
a
sample
selection
algorithm
that
placed
greater
emphasis
on
a
preference
for
geographic
diversity
in
the
higher
corn
density
strata
could
have
prevented
this).
The
lack
of
monitoring
in
some
of
the
high
acetochlor
use
areas
is
especially
problematic
for
the
SDWS
where
the
lack
of
sampling
of
raw
(
pre­
facility
treatment)
water
at
most
locations
makes
it
difficult
to
isolate
the
effects
of
site­
specific
usage
and
vulnerability
factors
and
water
treatment
processes
on
the
observed
residue
levels.

We
conclude
therefore,
there
is
a
potential
that
exposure
could
be
somewhat
higher
in
areas
other
than
those
monitored
if
treatment
systems
at
the
locality
do
not
remove
a
significant
portion
of
the
acetochlor
residues,
utilization
of
surface
water
sources
for
drinking
water
increases
in
some
high
use
areas,
and/
or
the
usage
of
acetochlor
expands
in
some
areas
through
changing
patterns
of
corn
production
or
registration
and
use
of
acetochlor
on
additional
crop
sites.
Further
analysis
may
be
needed
if
the
reported
acetochlor
concentrations
are
within
a
factor
of
3
of
levels
of
concern
for
drinking
water.

Besides
the
above
described
difficulties
in
isolating
the
effects
of
water
treatment
on
observed
residues
from
the
ARP
SDWS
study,
a
number
of
uncertainties
must
be
recognized
when
interpreting
this
exposure
assessment.
These
include
the
following:

°
The
surface
drinking
water
supply
(
SDWS)
and
state
ground
water
(
SGW)
monitoring
programs
were
designed
to
focus
on
areas
of
high
acetochlor
use.
The
monitoring
does
not
cover
the
entire
geographic
distribution
of
acetochlor
use.
Conclusions
drawn
in
this
report
apply
only
to
those
areas
monitored
by
the
ARP
and
it
may
not
be
possible
to
generalize
to
all
acetochlor
usage
areas.
Additional
data
analysis
and
modeling
would
be
needed
to
expand
this
exposure
assessment
to
cover
the
unmonitored
areas.

°
County
level
sales
data
submitted
separately
by
members
of
the
ARP
from
1994
­
2003
is
arguably
some
of
the
most
extensive
data
available
as
a
close
approximation
of
acetochlor
usage
across
the
US.
As
such,
it
has
been
incorporated
in
this
exposure
assessment
as
a
surrogate
for
acetochlor
use
in
the
mapping
and
statistical
analyses.
It
is
assumed
that
acetochlor
sold
in
an
individual
county
is,
in
general,
also
applied
in
the
same
county
and
in
the
same
watershed.
However,
the
exposure
characterization
recognizes
that
inter­
county
as
well
as
inter­
watershed
transfer
of
acetochlor
does
occur
in
some
cases.

°
Acute
exposure
in
this
risk
assessment
is
defined
as
the
overall
maximum
observed
concentration
at
a
site.
The
actual
peak
concentration,
however,
may
have
occurred
between
sampling
times.
Thus,
the
maximum
observed
concentrations
reported
in
this
study
may
underestimate
the
true
maximum
acute
exposure.

9.2.
Acetochlor
Degradates
The
Health
Effects
Division
of
OPP
has
determined
that
the
available
toxicological
data
indicates
that
degradates
do
not
have
similar
toxicological
endpoints
to
parent
acetochlor
nor
to
­
77­

each
other.
Consequently,
the
emphasis
on
our
analysis
has
been
on
separate
examination
of
exposure
levels
for
each
of
these
compounds.

The
highest
monitored
values
for
acetochlor
ESA
were:

Acute
exposure:
20.0
ppb
ESA
in
a
sample
from
one
of
the
approximately
175
SGW
study
sites.

Chronic
exposure:
12.7
ppb
ESA
TWAM
from
one
of
the
SGW
study
sites.

The
highest
monitored
values
for
acetochlor
OXA
were:

Acute
exposure:
19.1
ppb
OXA
in
a
sample
from
a
shallow
well
from
one
of
the
SGW
study
sites.

Chronic
exposure:
5.9
ppb
OXA
TWAM
from
a
shallow
well
from
one
of
the
SGW
study
sites.

Acetochlor
degradates
ethanesulfonic
acid
(
ESA)
and
oxanilic
acid
(
OXA)
were
detected
more
frequently
and
at
higher
concentrations
than
the
parent
acetochlor
in
ground
water;
chronic
levels
of
the
degradates
in
surface
water
tended
to
be
similar
to
that
of
parent
(
Compare
Table
1
with
Table
27,
Table
30,
and
Table
31).
Peak
levels
of
degradates
in
surface
waters
were
generally
lower
or
similar
to
peak
levels
of
parent
acetochlor
(
Compare
Table
11
and
Table
12
with
Table
28
and
Table
29).
­
78­

10.
REFERENCES
Blomquist,
J.
D.,
Denis,
J.
M.,
Cowles,
J.
P.,
Hetrick,
J.
A.,
Jones,
R.
D.,
and
Birchfield,
N.
B.
2001.
Pesticides
in
Selected
Water­
Supply
Reservoirs
and
Finished
Drinking
Water,
1999­
2000:
Summary
of
Results
from
a
Pilot
Monitoring
Program,
Open
File
Report
01­
456,
U.
S.
Geological
Survey.

Coupe,
R.
H,
and
Blomquist,
J.
D.,
2004.
Water­
soluble
pesticides
in
finished
water
of
community
water
supplies.
Journal
American
Water
Works
Association,
v.
96(
10):
56­
68.

De
Guzman,
N.
P,
Hendley,
P.,
Gustafson,
D.
I.,
van
Wesenbeeck,
I.,
Klein,
A.
J.,
Fuhrman,
J.
D.,
Travis,
K.,
Simmons,
N.
D.,
Teskey,
W.
E.,
and
R.
B.
Durham.
2005.
The
Acetochlor
State
Ground
water
Monitoring
Program.
J.
Env.
Qual.
34:
793­
803.

Hackett,
A.
G.,
J.
D.
Fuhrman,
and
C.
Van
Bellinghen.
2003.
Chloroacetanilide
Herbicides.
p.
344­
388.
In
P.
W.
Lee
(
ed.)
Handbook
of
Residue
Analytical
Methods
for
Agrochemicals,
Volume
1,
John
Wiley
&
Sons,
West
Sussex,
UK.

Hackett,
A.
G.,
Gustafson,
D.
I.,
Moran,
S.
J.,
Hendley,
P.,
van
Wesenbeeck,
I.,
Simmons,
N.
D.,
Klein,
A.
J.,
Kronenberg,
J.
M.,
Fuhrman,
J.
D.,
Hanzas,
J.,
Healy,
D.,
and
C.
T.
Stone.
2005.
The
Acetochlor
Surface
Drinking
Water
Monitoring
Program.
J.
Env.
Qual.
34:
877­
889.

Lavy,
T.
L.
Mattice,
J.
D.
Massey,
J.
H.
Skulman,
B.
W.
Senseman,
S.
A.
Gbur,
E.
E
Jr.,
Barrett,
M.
R.
Long­
term
in
situ
leaching
and
degradation
of
six
herbicides
aged
in
subsoils.
Journal
of
Environmental
Quality.
v
25
n
6
Nov­
Dec
1996.
p1268­
1279.

Mills,
M.
S.,
I.
R.
Hill,
A.
C.
Newcombe,
N.
D.
Simmons,
P.
C.
Vaughan,
and
A.
A.
Verity.
2001.
Quantification
of
acetochlor
degradation
in
the
unsaturated
zone
using
two
novel
in
situ
field
techniques:
comparisons
with
laboratory­
generated
data
and
implications
for
groundwater
risk
assessments.
Pest
Management
Science
57(
4):
351­
359.

Newcombe,
A.
C.,
Gustafson,
D.
I.,
Fuhrman,
J.
D.,
van
Wesenbeeck,
I.
J.,
Simmons,
N.
D.,
Klein,
A.
J.,
Travis,
K.
Z.,
and
K.
J.
Harradine.
2004.
The
Acetochlor
Prospective
Ground
Water
Monitoring
Program.
J.
Env.
Qual.
34:
1004­
1015.

USEPA.
1994.
Acetochlor
Registration
Agreement
and
Addendums.
http://
www.
epa.
gov/
oppefed1/
aceto/
regagree.
htm
U.
S.
Environmental
Protection
Agency.
1998.
Reregistration
Eligibility
Decision
(
RED):
Alachlor.
No.
738­
R­
98­
020.
Available
online
at:
http://
www.
epa.
gov/
oppsrrd1/
REDs/
0063.
pdf.

USEPA.
2004.
Office
of
Pesticide
Programs.
Acetochlor
Homepage:
Desk
Statement,
Talking
Points,
and
Usage
Targets
and
Results.
http://
www.
epa.
gov/
oppefed1/
aceto/
index.
htm
(
visited:
3
August
2004).
­
79­

USGS.
2004.
Development
and
Application
of
Watershed
Regressions
for
Pesticides
(
WARP)
for
Estimating
Atrazine
Concentration
Distributions
in
Streams.
Water­
Resources
Investigations
Report
03­
4047.
68
pp.

11.
BIBLIOGRAPHY
EPA
Reviews
and
Documents
Environmental
Fate
and
Ground
Water
Branch,
OPP,
EPA.
1993.
Review
of
environmental
fate
data
submitted
in
support
of
Section
3
registration.
Memorandum
dated
June
17,
1993
from
Paul
Mastradone
to
J.
Miller
/
J.
Mays,
PM
23,
Registration
Division.
DP
Barcode
D168599.

Environmental
Fate
and
Ground
Water
Branch,
OPP,
EPA.
1993.
Review
of
162­
1,
162­
2
and
164­
1
studies
for
registration;
also
request
for
extension
of
EUP
on
corn.
Memorandum
dated
December
6,
1993
from
Akiva
Abramovitch
to
Robert
Taylor,
PM
25,
Registration
Division.
DP
Barcodes
D174457,
D182799,
D187736,
D193537,
and
D194713.

Environmental
Fate
and
Ground
Water
Branch,
OPP,
EPA.
1994.
Review
of
162­
1,
162­
2
and
164­
1
studies
for
registration;
response
to
registrant's
response
to
12/
6/
93
review.
Memorandum
dated
January
26,
1994
from
Akiva
Abramovitch
to
Robert
Taylor,
PM
25,
Registration
Division.
DP
Barcode
D197606.

Environmental
Fate
and
Effects
Division,
OPP,
EPA.
2001.
Drinking
water
assessment
for
atrazine
and
various
chloro­
triazine
and
hydroxyl­
triazine
degradates.
Memorandum
dated
January
23,
2001
from
Henry
Nelson,
James
Lin
and
Mary
Frankenberry
to
Pam
Noyes,
Triazine
Manager,
Special
Review
and
Reregistration
Division.
Available
on
the
web
at:
http://
www.
epa.
gov/
oppsrrd1/
reregistration/
atrazine/
drinkingwater.
pdf
(
visited
November
11,
2004).

Health
Effects
Division,
OPP,
EPA.
2004.
Acetochlor.
Report
of
the
Metabolism
Assessment
Review
Committee.
Health
Effects
Division
internal
memorandum
dated
August
31,
2004
from
Albert
Protzel
to
Yan
Donovan,
Executive
Secretary,
Metabolism
Assessment
Review
Committee.

Official
Submissions
to
EPA
ARP
error
correction
comments
on
the
12/
31/
04
actochlor
drinking
water
assessment:
ARP
2005
(
MRID
unknown).
Response
to
Preliminary
Human
Health
Risk
Assessment
for
the
Tolerance
Reassessment
Progress
and
Risk
Management
Decision
(
TRED)
for
Acetochlor.
­
80­

Letter
dated
9/
13/
05
from
Dawn
Fee­
White
(
ARP)
to
Rosanna
Louie
(
EPA).
DP
Barcode
293329.

ARP
Submissions
­
Section
1:
ENVIRONMENTAL
FATE
STUDIES
(
Grouped
by
study
type.)

Guideline:
161­
1
Hydrolysis
­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­
MRID:
00064805
Campbell,
D.
H.;
Hamilton,
D.
E.;
Kloek,
J.
A.;
et
al.
(
1980).
The
Environmental
Studies
of
Acetochlor:
Report
No.
MSL­
1255.
Final
rept.
(
Unpublished
study
received
Dec
12,
1980
under
524­
EX­
56;
submitted
by
Monsanto
Co.,
Washington,
D.
C.;
CDL:
099814­
C)

MRID:
41565144
Myers,
H.
(
1989)
ICIA­
5676:
Hydrolysis
Studies:
Lab
Project
Number:
WRC
88­
70.
Unpublished
study
prepared
by
ICI
Americas
Inc.
17
p.

MRID:
41613301
Howe,
R.
(
1990)
New
Information
on
MON
4660
Environmental
Fate
Studies,
Addendum
to
MSL
4383:
Lab
Project
Number:
RD
1010.
Un­
Published
study
prepared
by
Monsanto
Agricultural
Co.
49
p.

Guideline:
161­
2
Photodegradation­
water
­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­
MRID:
00131388
Letendre,
L.;
Klemm,
G.;
Singh,
H.
(
1982)
The
Environmental
Photo­
chemistry
of
Acetochlor:
Project
No.
7827;
Report
No.
MSL­
2748.
(
Unpublished
study
received
Sep
22,
1983
under
524­
348;
submit­
ted
by
Monsanto
Co.,
Washington,
DC;
071961­
C)

MRID:
41565145
Chotalia,
R.;
Weissler,
M.
(
1989)
Acetochlor:
Photolysis
in
Aqueous
Solution
at
pH
7:
Lab
Project
Number:
88JH448:
RJ0726B.
Unpub­
lished
study
prepared
by
ICI
Agrochemicals.
63
p.

Guideline:
161­
3
Photodegradation­
soil
­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­
MRID:
00131388
Letendre,
L.;
Klemm,
G.;
Singh,
H.
(
1982)
The
Environmental
Photo­
chemistry
of
Acetochlor:
Project
No.
7827;
Report
No.
MSL­
2748.
(
Unpublished
study
received
Sep
22,
1983
under
524­
348;
submit­
ted
by
Monsanto
Co.,
Washington,
DC;
071961­
C)

MRID:
00160233
Groya,
F.,
comp.
(
1986)
Information
to
Support
the
Registration
of
Harness
Herbicide
(
Acetochlor):
Response
to
Review
of
Environmental
Fate
Data:
Special
Report
MSL­
5570.
Unpublished
compilation
prepared
by
Monsanto
Agricultural
Co.
15
p.
­
81­

MRID:
41565146
Hawkins,
D.;
Kirkpatrick,
D.;
Dean,
G.
(
1990)
The
Photodegradation
of
carbon
14|­
Acetochlor
on
Soil:
Lab
Project
Number:
HRC/
ISN
187/
891375.
Unpublished
study
prepared
by
Huntingdon
Research
Centre
Ltd.
62
p.

Guideline:
162­
1
Aerobic
soil
metabolism
­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­
MRID:
00064805
Campbell,
D.
H.;
Hamilton,
D.
E.;
Kloek,
J.
A.;
et
al.
(
1980)
The
Environmental
Studies
of
Acetochlor:
Report
No.
MSL­
1255.
Final
rept.
(
Unpublished
study
received
Dec
12,
1980
under
524­
EX­
56;
submitted
by
Monsanto
Co.,
Washington,
D.
C.;
CDL:
099814­
C)

MRID:
41565147
Hawkins,
D.;
Kirkpatrick,
D.;
Dean,
G.
(
1989)
The
Metabolism
of
carbon
14­
Acetochlor
in
Silty
Clay
Loam
Soil
under
Aerobic
Conditions:
Lab
Project
Number:
HRC/
STR
19/
881751.
Unpublished
prepared
by
Huntingdon
Research
Centre
Ltd.
84
p.

MRID:
41613301
Howe,
R.
(
1990)
New
Information
on
MON
4660
Environmental
Fate
Studies,
Addendum
to
MSL
4383:
Lab
Project
Number:
RD
1010.
Un­
Published
study
prepared
by
Monsanto
Agricultural
Co.
49
p.

MRID:
41963316
Hawkins,
D.;
Kirkpatrick,
D.;
Dean,
G.;
et
al.
(
1991).
The
Metabolism
of
Carbon
14
Acetochlor
in
Silty
Clay
Loam
Soil
under
Aerobic
Conditions:
Lab
Project
Number:
HRC/
STR
19/
901756.
Unpublished
study
prepared
by
Huntingdon
Research
Centre
Ltd.
29
p.

MRID:
41963317
Hawkins,
D.;
Kirkpatrick,
D.;
Dean,
G.
(
1991)
The
Metabolism
of
carbon
14|­
Acetochlor
in
Sandy
Loam
Soil
under
Aerobic
Conditions:
Lab
Project
Number:
HRC/
ISN
185/
90535.
Unpublished
study
prepared
by
Huntingdon
Research
Centre
Ltd.
57
p.

Guideline:
162­
2
Anaerobic
soil
metabolism
­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­
MRID:
41338501
Campbell,
D.;
Hamilton,
D.
(
1989)
Anaerobic
Soil
Metabolism
Studies
of
Acetochlor:
Final
Report:
Study
No.
MSL­
9183;
RD
971;
Project
No.
207300.
Unpublished
study
prepared
by
Monsanto
Agricultural
Co.
52
p.

MRID:
41565148
Hawkins,
D.;
Kirkpatrick,
D.;
Dean,
G.
(
1989)
The
Metabolism
of
carbon
14|­
Acetochlor
in
Sandy
Loam
Soil
under
Anaerobic
Conditions:
Lab
Project
Number:
HRC/
ISN
184/
89619.
Unpublished
study
prepared
by
Huntingdon
Research
Centre
Ltd.
45
p.

MRID:
41613301
­
82­

Howe,
R.
(
1990)
New
Information
on
MON
4660
Environmental
Fate
Studies,
Addendum
to
MSL
4383:
Lab
Project
Number:
RD
1010.
Un­
Published
study
prepared
by
Monsanto
Agricultural
Co.
49
p.

MRID:
41963318
Hawkins,
D.;
Kirkpatrick,
D.;
Dean,
G.;
et
al.
(
1991)
The
Metabolism
of
Carbon
14
Acetochlor
in
Sandy
Loam
Soil
Under
Aerobic
Conditions:
Part
II:
Lab
Project
Number:
HRC/
ISN
184/
89619.
Un­
published
study
prepared
by
Huntingdon
Research
Centre
Ltd.
24
p.

Guideline:
163­
1
Leaching
/
adsorption
/
desorption
­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­
MRID:
00031329
Jordan,
G.
L.;
Harvey,
R.
G.
(
1978)
Environmental
Factors
and
Soil
Relationships
Influencing
the
Activity
of
Acetanilide
Herbicides.
Doctoral
Thesis,
Univ.
of
Wisconsin,
Dept.
of
Agronomy.
(
pp.
22­
58
only;
unpublished
study
received
May
3,
1979
under
43142­
1;
submitted
by
Boots
Hercules
Agrochemicals
Co.,
Wilmington,
Del.;
CDL:
098274­
I)

MRID:
00064805
Campbell,
D.
H.;
Hamilton,
D.
E.;
Kloek,
J.
A.;
et
al.
(
1980)
The
Environmental
Studies
of
Acetochlor:
Report
No.
MSL­
1255.
Final
rept.
(
Unpublished
study
received
Dec
12,
1980
under
524­
EX­
56;
submitted
by
Monsanto
Co.,
Washington,
D.
C.;
CDL:
099814­
C)

MRID:
41338502
Campbell,
D.;
Hamilton,
D.
(
1989)
Leaching
and
Adsorption/
Desorption
Studies
of
Acetochlor:
Final
Report:
Study
No.
MSL­
9184;
RD
971;
Project
No.
207300.
Unpublished
study
prepared
by
Monsanto
Agricultural
Co.
72
p.

MRID:
41565149
Hartfield,
R.
(
1990)
Acetochlor
and
its
Two
Major
Metabolites:
Adsorption/
Desorption
in
Soil:
Lab
Project
Number:
89JH375:
RJ0837B.
Unpublished
study
prepared
by
ICI
Agrochemicals.
44
p.

MRID:
41613301
Howe,
R.
(
1990)
New
Information
on
MON
4660
Environmental
Fate
Studies,
Addendum
to
MSL
4383:
Lab
Project
Number:
RD
1010.
Un­
Published
study
prepared
by
Monsanto
Agricultural
Co.
49
p.

MRID:
41963319
Robbins,
A.;
Lane,
M.
(
1991)
Acetochlor:
Adsorption
and
Desorption
of
5676/
48,
the
Thioacetic
Acid
Sulphoxide
Metabolite,
in
Soil:
Lab
Project
Number:
RJ0887B.
Unpublished
study
prepared
by
ICI
Agrochemicals.
45
p.

Guideline:
164­
1
Terrestrial
field
dissipation
­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­
MRID:
00064803
­
83­

Horner,
L.
M.;
Purdum,
W.
R.;
Campbell,
D.
H.
(
1980)
Residues
of
Acetochlor
in
Field
Soils
following
Preemergent
Treatment
with
Acetochlor
Alone
or
in
Tank
Mix
Combinations
with
Atrazine,
Dyanap,
Linuron
and
Metribuzin:
Report
No.
MSL­
1260.
Interim
rept.
(
Unpublished
study
received
Dec
12,
1980
under
524­
EX­
56;
submitted
by
Monsanto
Co.,
Washington,
D.
C.;
CDL:
099814­
A)

MRID:
00130838
Monsanto
Co.
(
1983)
Residue
Studies
on
Harness:
Executive
Summary.
(
Compilation;
unpublished
study
received
Sep
22,
1983
under
524­
348;
CDL:
071958­
B;
071959;
071960)

MRID:
40811901
Lottman,
C.
(
1988)
Residues
of
Acetochlor
in
Field
Soils
following
Preemergent
Treatment
with
Acetochlor
Alone
or
in
Tank
Mix
Combinations
with
Atrazine,
Dyanap,
Linuron,
and
Metribuzin­­
Addendum
to
MSL­
1260
and
MSL­
1717:
Laboratory
Project
No.
MSL­
8095:
R.
D.
No.
887.
Unpublished
study
prepared
by
Monsanto
Agricultural
Co.
324
p.

MRID:
40811902
Lottman,
C.
(
1988)
Terrestrial
Field
Soil
Dissipation
Study­­
Determination
of
Acetochlor
Residues
following
Preemergent
Application
of
Top­
hand
Herbicide:
Laboratory
Project
No.
MSL­
8118:
R.
D.
No.
887.
Unpublished
study
prepared
by
Monsanto
Agricultural
Co.
165
p.

MRID:
41089204
Gustafson,
D.;
Lauer,
R.;
Horner,
L.
(
1988)
Terrestrial
Field
Dissipation
of
MON
4660
When
Applied
as
MON
8460
to
Field
Corn:
Project
No.
MSL­
8024.
Unpublished
study
prepared
by
Monsanto
Agricultural
Co.
in
cooperation
with
MetaTrace,
Inc.
273
p.

MRID:
41565152
Zilka,
S.;
Wilson,
B.;
Hoag,
H.;
Coombes
et
al.
(
1990)
Acetochlor:
Dissipation
of
Residues
in
USA
Soil
under
Field
Conditions­­
Leland,
Mississippi,
1988:
Lab
Project
Number:
5676­
88­
SD­
01.
Unpublished
study
prepared
by
ICI
Agrochemicals.
109
p.

MRID:
41565153
Wilson,
B.;
Dhillon,
P.;
Bolygo,
E.;
et
al.
(
1990)
Acetochlor:
Residues
of
Oxanilic
Acid
and
Sulphonic
Acid
Metabolite
under
Field
Conditions
in
Leland,
Mississippi,
1988:
Lab
Project
No:
5676­
88­
SD­
01.
Unpublished
study
prepared
by
ICI
Agrochemicals.
119
p.

MRID:
41592012
Zilka,
S.;
Wilson,
B.;
Hoag,
R.;
et
al.
(
1990)
Acetochlor:
Dissipation
of
Residues
in
USA
Soil
under
Field
Conditions­
Champaign,
Illinois,
1988:
Lab
Project
Number:
5676­
88­
SD­
01.
Unpublished
study
prepared
by
ICI
Agrochemicals.
113
p.

MRID:
41592013
Wilson,
B.;
Dhillon,
P.;
Bolygo,
E.;
et
al.
(
1990)
Acetochlor:
Residues
of
Oxanilic
Acid
and
Sulphonic
Acid
Metabolites
in
USA
under
Field
Conditions
in
Champaign,
Illinois,
1988:
Lab
Project
Number:
5676­
88­
SD­
01:
RJ0850B.
Unpublished
study
prepared
by
ICI
Agrochemicals.
124
p.
­
84­

MRID:
42549907
Lauer,
R.
(
1992)
Stability
of
Acetochlor
and
Its
Metabolites
in
Soil
During
Frozen
Storage:
Lab
Project
Number:
MSL­
11981.
Unpublished
study
prepared
by
Monsanto
Company.
160
p.

MRID:
42549915
Zilka,
S.;
Wilson,
B.;
Hoag,
R.;
et.
al
(
1990)
Acetochlor:
Dissipation
of
Residues
in
USA
Soil
under
Field
Conditions­­
Visalia,
California,
1988:
Lab
Project
Number:
5676­
88­
SD­
01:
RJ0821B.
Unpublished
study
prepared
by
ICI
Agrochemicals.
106
p.

MRID:
42549916
Zilka,
S.;
Wilson,
B.;
Hoag,
R.;
et.
al
(
1990)
Acetochlor:
Dissipation
of
Residues
in
USA
Soil
under
Field
Conditions­­
Goldsboro,
North
Carolina,
1988:
Lab
Project
Number:
5676­
88­
SD­
01:
RJ0822B.
Unpublished
study
prepared
by
ICI
Agrochemicals.
108
p.

MRID:
42549917
Veal,
P.;
Grout,
S.;
Simmons,
N.
(
1992)
Acetochlor:
Residues
of
Thioacetic
Acid
Sulphoxide
Soil
Metabolite
under
Field
Conditions
in
Champaign,
Illinois,
1988:
Lab
Project
Number:
5676­
88­
SD­
01:
RJ1031B.
Unpublished
study
prepared
by
ICI
Agrochemicals.
114
p.

MRID:
42549918
Veal,
P.;
Grout,
S.;
Simmons,
N.
(
1992)
Acetochlor:
Residues
of
Thioacetic
Acid
Sulphoxide
Soil
Metabolite
under
Field
Conditions
in
Leland,
Mississippi,
1988:
Lab
Project
Number:
5676­
88­
SD­
01:
RJ1030B.
Unpublished
study
prepared
by
ICI
Agrochemicals.
110
p.

MRID:
42573402
Lauer,
R.;
Lau,
P.
(
1992)
Terrestrial
Field
Dissipation
Study
of
Acetochlor
and
Its
Soil
Metabolites
following
Preemergent
Application
of
MON
8437
to
Field
Corn:
Lab
Project
Number:
MSL­
12089.
Unpublished
study
prepared
by
Monsanto
and
Stewart
Agricultural
Research
Services,
Inc.
765
p.

MRID:
42831608
Lauer,
R.;
Gibson,
K.
(
1992)
Terrestrial
Field
Dissipation
Study
of
Acetochlor
and
its
Soil
Metabolites
Following
Application
of
MON
8422
to
Field
Corn:
Lab
Project
Number:
MSL­
12166:
90­
42­
R­
2:
RD
1130.
Unpublished
study
prepared
by
Monsanto
Co.
and
Stewart
Agricultural
Research
Services,
Inc.
1079
p.

MRID:
42964801
Lauer,
R.
(
1992)
Stability
of
Microencapsulated
Acetochlor
in
Soil
During
Frozen
Storage:
Lab
Project
Number:
MSL­
12219.
Unpublished
study
prepared
by
Monsanto
Company.
76
p.

MRID:
43255008
Wilson,
B.;
French,
D.;
Roper,
E.;
et
al.
(
1993)
Acetochlor
&
(
inert
ingredient):
Dissipation
of
Residue
Levels
in
Soil
from
Trials
Carried
out
in
the
USA
During
1992:
Lab
Project
Number:
ACET/
92/
SD/
03.
Unpublished
study
prepared
by
Zeneca
Agrochemicals
Jealotts
Hill
Research
Station.
100
p.
­
85­

Guideline:
164­
2
Aquatic
field
dissipation
­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­
MRID:
45449502
Davis,
K.
(
2001)
Independent
Laboratory
Validation
of
"
Determination
of
Soil
Degradates
of
Acetochlor,
Alachlor,
and
Metolachlor
in
Aqueous
Environmental
Specimens
by
LC/
MS/
MS":
Lab
Project
Number:
852­
565:
46482:
ES­
ME­
0330­
02.
Unpublished
study
prepared
by
ABC
Laboratories,
Inc.
47
p.
{
OPPTS
850.7100}

ARP
Submissions
­
Section
2:
MONITORING
STUDIES
 
GENERAL
MRID:
44002501
Fuhrman,
J.
(
1996)
Analytical
Method
Development
and
First
Year
Performance:
GC/
MS
Analytical
Methodology
to
Support
the
Acetochlor
Registration
Partnership
Surface
Water
and
Ground
Water
Monitoring
Studies:
Progress
Report:
Lab
Project
Number:
MSL­
14562:
M001/
1:
ACET­
95­
GW­
02.
Unpublished
study
prepared
by
Ceregen,
a
Unit
of
Monsanto
Co.
344
p.

MRID:
44529801
Fuhrman,
J.
(
1998)
GC/
MS
Analytical
Methodology
to
Support
the
Acetochlor
Registration
Partnership
Surface
Water
and
Ground
Water
Monitoring
Studies:
Progress
Report:
Analytical
Methodology
and
Cumulative
Interim
Performance
July
1994­
December
1996:
Lab
Project
Number:
MSL­
15191:
94­
27­
R­
3:
ACET­
95­
GW­
02.
Unpublished
study
prepared
by
Monsanto
Co.
502
p.
OPP
Barcode
D245339.

MRID:
45180401
Harradine,
K.
(
2000)
Acetochlor
Registration
Partnership:
Acetochlor
Oxanilic
Acid
Retrospective
Analysis­
Ground
Water
Study
Analytical
Data
Summary
Report:
Lab
Project
Number:
BJK25.
Unpublished
study
prepared
by
Acetochlor
Registration
Partnership.
54
p.

ARP
Submissions
­
Section
3:
MONITORING
STUDIES
 
SURFACE
WATER
MRID:
45316601
Hackett,
A.
(
2000)
ARP
SWM
Program
Analytical
Results
of
the
ARP
Program
Year
2000
through
August
for
Parent
Herbicides
and
Year
2000
Samples
Analyzed
to
Date
for
Degradates:
Lab
Project
Number:
SWM1100.
Unpublished
study
prepared
by
Monsanto
Company.
81
p.

MRID:
?
Hackett,
A.
(
2000)
Surface
Drinking
Water
Monitoring
Program
for
Acetochlor
and
Other
Corn
Herbicides:
Site
Selection
and
Data
Collection.
Lab
Project
Number:
SWM1100.
Unpublished
study
prepared
by
Monsanto
Company.
81
p.

MRID:
43924301
Citation:
Hackett,
A.
(
1996)
Surface
Drinking
Water
Monitoring
Program
for
Acetochlor
and
Other
Corn
Herbicides:
First
Year
Sampling
and
Analytical
Results:
(
Progress
Report):
Lab
­
86­

ARP
Submissions
­
Section
3:
MONITORING
STUDIES
 
SURFACE
WATER
Project
Number:
94­
27­
R­
3:
94­
310:
MSL­
14486.
Unpublished
study
prepared
by
Ceregen,
Unit
of
Monsanto
Co.
and
Stone
Environmental,
Inc.
354
p.

MRID:
44299501
Citation:
Hackett,
A.
(
1997)
Surface
Drinking
Water
Monitoring
Program
for
Acetochlor
and
Other
Corn
Herbicides:
Second
Year
Sampling
and
Analytical
Results
Progress
Report:
Lab
Project
Number:
94­
27­
R­
3:
94­
310:
MSL­
15108.
Unpublished
study
prepared
by
Monsanto
Co.
and
Stone
Environmental,
Inc.
237
p.

MRID:
44869401
Citation:
Hackett,
A.
(
1999)
Surface
Drinking
Water
Monitoring
Program
for
Acetochlor
and
Other
Corn
Herbicides
Fourth
Year
Sampling
and
Analytical
Results:
Lab
Project
Number:
MSL­
16039:
94­
27­
R­
3:
94­
310.
Unpublished
study
prepared
by
Stone
Environmental
and
Monsanto
Company.
238
p.

MRID:
45226301
Hackett,
A.
(
2000)
Surface
Drinking
Water
Monitoring
Program
for
Acetochlor
and
Other
Corn
Herbicides:
Fifth
Year
Sampling
and
Analytical
Results:
Lab
Project
Number:
94­
27­
R­
3:
94­
310:
MONMO01A­
02.
Unpublished
study
prepared
by
Monsanto
Co.,
Stone
Environmental,
Inc.
and
Alta
Analytical
Lab.,
Inc.
315
p.

MRID:
45446201
Hackett,
A.
(
2001)
Surface
Drinking
Water
Monitoring
Program
for
Acetochlor
and
Other
Corn
Herbicides.
Sixth
Year
Sampling
and
Analytical
Results:
Lab
Project
Number:
94­
27­
R­
3:
94­
310:
MSL­
17227.
Unpublished
study
prepared
by
Monsanto
Company
and
Stone
Environmental
Inc.
320
p.

MRID:
45716901
Citation:
Hackett,
A.
(
2002)
Surface
Drinking
Water
Monitoring
Program
for
Acetochlor
and
Other
Corn
Herbicides:
Seventh
Year
Sampling
and
Analytical
Results:
Final
Report:
Lab
Project
Number:
94­
27­
R­
3:
94­
310:
MSL­
17756.
Unpublished
study
prepared
by
Monsanto
Company
and
Stone
Environmental,
Inc.
360
p.

MRID:
44592401
Hackett,
A.
(
1998)
Surface
Drinking
Water
Monitoring
Program
for
Acetochlor
and
Other
Corn
Herbicides:
Lab
Project
Number:
94­
27­
R­
3:
94­
310:
MSL­
15395.
Unpublished
study
prepared
by
Monsanto
Company
and
Stone
Environmental,
Inc.
233
p
MRID:
45103001
Simmons,
N.
(
2000)
Occurrence
of
Acetochlor
Soil
Degradates
in
the
ARP
State
Ground
and
Surface
Water
Monitoring
Programs
During
1999:
Anticipated
Human
Exposure
to
these
Materials
via
Drinking
Water:
Lab
Project
Number:
BJK23.
Unpublished
study
prepared
by
Acetochlor
Registration
Partnership.
30
p.
­
87­

ARP
Submissions
­
Section
3:
MONITORING
STUDIES
 
SURFACE
WATER
MRID:
44590401
Hackett,
A.
(
1998)
1997
Annualized
Mean
Concentrations
(
AMC's)
and
1997
and
Early
1998
Analytical
Results:
Surface
Water
Monitoring
Program:
Monsanto
Study
No.
94­
27­
R­
3.
Unpublished
study
prepared
by
Monsanto
Co.
and
the
Acetochlor
Registration
Partnership.
92
p.

MRID:
45564101
Citation:
Hackett,
A.
(
2001)
ARP
Surface
Water
Monitoring
(
SWM)
Program
Analytical
Results
of
the
ARP
Program
Year
2001
Through
August
for
Parent
Herbicides
and
Degradates:
Lab
Project
Number:
SWM1201:
94­
27­
R­
3.
Unpublished
study
prepared
by
Monsanto
Company.
104
p.

MRID:
45714801
Citation:
Hackett,
A.
(
2002)
ARP
Surface
Water
Monitoring
Program
Annualized
Means
and
Analytical
Results
for
the
ARP
Program
in
2001:
Lab
Project
Number:
SWM0702:
852­
573:
94­
27­
R­
3.
Unpublished
study
prepared
by
Monsanto
Company.
173
p.

ARP
Submissions
­
Section
4:
MONITORING
STUDIES
 
PROSPECTIVE
GROUND
WATER
MRID:
43944901
Dwinell,
S.;
French,
D.;
Moore,
W.
et
al.
(
1996)
Acetochlor:
USA
Prospective
Ground
Water
Study­­
Series
I
(
WI
&
OH):
1st
Interim
Report­­
December
1995:
Lab
Project
Number:
ACET­
95­
PG­
02:
3277:
RR
95­
094B.
Unpublished
study
prepared
by
Zeneca
Agrochemicals
and
Levine
Fricke,
Inc.
404
p.

MRID:
44193101
Dwinell,
S.;
French,
D.;
Moore,
W.
et
al.
(
1996)
Acetochlor:
USA
Prospective
Ground
Water
Study­­
Series
1
(
WI
&
OH):
2nd
Interim
Report­­
December,
1996:
Lab
Project
Number:
ACET­
95­
PG­
02:
3277:
RR
96­
081
B
INT.
Unpublished
study
prepared
by
Zeneca
Agrochemicals
and
Levine.
Fricke.
Recon
Inc.
512
p.

MRID:
44221601
Freiwald,
R.;
Friet,
S.;
Harradine,
K.
(
1997)
Acetochlor:
USA
Prospective
Ground
Water
Study­­
Series
II
(
MN,
NE,
IA,
and
IN):
1st
Interim
Report­­
February,
1997:
Lab
Project
Number:
ACET­
96­
PG­
05:
3277:
RR
96­
104B
INT.
Unpublished
study
prepared
by
Zeneca
Agrochemicals
and
Levine.
Fricke.
Recon
Inc.
762
p.\

MRID:
44402801
Durham,
R.;
Harradine,
K.;
Johnson,
R.
et
al.
(
1997)
Acetochlor:
USA
Prospective
Ground
Water
Study­­
Series
I
(
WI
&
OH):
Final
Report­­
October,
1997:
Lab
Project
Number:
ACET
­
88­

ARP
Submissions
­
Section
4:
MONITORING
STUDIES
 
PROSPECTIVE
GROUND
WATER
95­
PG­
02:
3277:
RR
96­
081B
FIN.
Unpublished
study
prepared
by
Zeneca
Agrochemicals
(
Jealott's
Hill
Research
Station)
and
Levine.
Fricke.
Recon
Inc.
578
p.

MRID:
44402801
Durham,
R.;
Harradine,
K.;
Johnson,
R.
et
al.
(
1997)
Acetochlor:
USA
Prospective
Ground
Water
Study­­
Series
I
(
WI
&
OH):
Final
Report­­
October,
1997:
Lab
Project
Number:
ACET­
95­
PG­
02:
3277:
RR
96­
081B
FIN.
Unpublished
study
prepared
by
Zeneca
Agrochemicals
(
Jealott's
Hill
Research
Station)
and
Levine.
Fricke.
Recon
Inc.
578
p.

MRID:
44492401
Bedosky,
S.;
Harradine,
K.;
Johnson,
R.;
et
al.
(
1997)
Acetochlor:
USA
Prospective
Ground
Water
Study­
Series
III
(
PA)
1st
Interim
Report­
November,
1997:
Lab
Project
Number:
RR
97­
061B
INT1:
3277:
ACET­
96­
PG­
06.
Unpublished
study
prepared
by
Zeneca
Agrochemicals
and
Levine
Fricke
Recon
Inc.
287
p.

MRID:
44523101
Durham,
R.;
Freiwald,
R.;
Friet,
S.
et
al.
(
1998)
Acetochlor:
USA
Prospective
Ground
Water
Study­­
Series
II
(
MN,
NE,
IA
and
IN)
2nd
Interim
Report­­
March,
1998:
Lab
Project
Number:
ACET­
96­
PG­
05:
3277:
RR
96­
104B
INT2.
Unpublished
study
prepared
by
Zeneca
Ag
Products
and
Levine.
Fricke.
Recon
Inc.
1152
p.

MRID:
44752801
Bedosky,
S.;
Harradine,
K.;
Newcombe,
A.
(
1999)
Acetochlor:
USA
Prospective
Ground
Water
Study­­
Series
III
(
PA)
2nd
Interim
Report­­
January,
1999:
Lab
Project
Number:
3277:
ACET­
96­
PG­
06:
RR97­
061BINT2.
Unpublished
study
prepared
by
Zeneca
Ag
Products
and
Levine.
Fricke
Inc.
412
p.

MRID:
44757501
Newcombe,
A.
(
1999)
Acetochlor
Registration
Partnership:
Acetochlor:
USA
Prospective
Ground
Water
Study
Series
I
(
WI
&
OH):
Analytical
Data
Summary
Report:
(
Pre­
Application
to
40
Months):
Lab
Project
Number:
PGWQ13A.
Unpublished
study
prepared
by
Acetochlor
Registration
Partnership.
62
p.

MRID:
44875701
Bedosky,
S.;
Harradine,
K.;
Robinson,
G.
et
al.
(
1999)
ACETOCHLOR:
USA
Prospective
Ground
Water
Study­­
Series
IV
(
DE)
1st
Interim
Report­­
March,
1999:
Lab
Project
Number:
RR
99­
005B
INT1:
ACET­
98­
PG­
07:
3277.
Unpublished
study
prepared
by
ZENECA
Agrochemicals
and
Levine.
Fricke
Inc.
301
p.

MRID:
45216501
Bedosky,
S.;
Robinson,
G.;
Harradine,
K.
et
al.
(
2000)
ACETOCHLOR:
USA
Prospective
Ground
Water
Study­
Series
IV
(
DE)
2nd
Interim
Report­
September,
2000:
Lab
Project
Number:
3277:
ACET­
98­
PG­
07:
RR
99­
005B
INT2.
Unpublished
study
prepared
by
ZENECA
­
89­

ARP
Submissions
­
Section
4:
MONITORING
STUDIES
 
PROSPECTIVE
GROUND
WATER
Agrochemicals
and
LFR
Levine­
Fricke
Inc.
470
p.

MRID:
46138601
Newcombe,
A.;
Gustafson,
D.;
van
Wesenbeeck,
I.
(
2003)
Acetochlor
Registration
Partnership
Minnesota
Prospective
Groundwater
Trial
­
Final
Report.
Project
Number:
ACET/
96/
PG/
05,
004/
03277/
88/
435,
852/
594.
Unpublished
study
prepared
by
Monsanto
Company,
Zeneca
Agrochemicals,
and
Covance
Laboratories,
Ltd.
238
p.

MRID:
46204201
Newcombe,
A.;
Gustafson,
D.;
van
Wesenbeeck,
I.
(
2004)
Acetochlor
Registration
Partnership
Indiana
Prospective
Groundwater
Trial
­
Final
Report.
Project
Number:
ARP
#
ACET/
96/
PG/
05,
Levine­
Fricke
#
004/
03277/
88/
433.
Unpublished
study
prepared
by
Monsanto
Company,
Zeneca
Agrochemicals,
and
Covance
Laboratories,
Ltd.
258
p.

MRID:
45181901;
Amendment
(
New
MRID?)
Newcombe,
A.;
Gustafson,
D.;
van
Wesenbeeck,
I.
(
2004)
Acetochlor
Registration
Partnership
Ohio
Prospective
Groundwater
Trial
 
Amended
Final
Report.
Project
Number:
ARP
#
ACET/
95/
PG/
02,
Levine­
Fricke
#
004/
03277/
88/
437.
Unpublished
study
prepared
by
Monsanto
Company,
Zeneca
Agrochemicals,
and
Natural
Resource
Management,
Ltd.
244
p.

MRID:
46290201;
Amendment
(
New
MRID,
replaces
#
45181901)
Newcombe,
A.;
Gustafson,
D.;
van
Wesenbeeck,
I.
(
2004)
Acetochlor
Registration
Partnership
Wisconsin
Prospective
Groundwater
Trial
 
Amended
Final
Report.
Project
Number:
ARP
#
ACET/
95/
PG/
02,
Levine­
Fricke
#
004/
03277/
88/
436.
Unpublished
study
prepared
by
Monsanto
Company,
Zeneca
Agrochemicals,
and
Natural
Resource
Management,
Ltd.
239
p.

MRID:
46188701
Newcombe,
A.;
Gustafson,
D.;
van
Wesenbeeck,
I.
(
2004)
Acetochlor
Registration
Partnership
Minnesota
Prospective
Groundwater
Trial
 
Amended
Final
Report.
Project
Number:
ARP
#
ACET/
96/
PG/
05,
Levine­
Fricke
#
004/
03277/
88/
435.
Unpublished
study
prepared
by
Monsanto
Company,
Zeneca
Agrochemicals,
and
Covance
Laboratories,
Ltd.
255
p.
DP
#
301795.

MRID:
46274201
Newcombe,
A.;
Gustafson,
D.;
van
Wesenbeeck,
I.
(
2004)
Acetochlor
Registration
Partnership
Delaware
Prospective
Groundwater
Trial
 
Final
Report
(
dated
5/
5/
2004).
Project
Number:
ARP
#
ACET/
98/
PG/
07,
Levine­
Fricke
#
004/
03277/
88/
432.
Unpublished
study
prepared
by
Monsanto
Company,
Zeneca
Agrochemicals,
and
Natural
Resource
Management,
Ltd.
306
p.
DP
#
304735.

MRID:
46232801
Newcombe,
A.;
Gustafson,
D.;
van
Wesenbeeck,
I.
(
2004)
Acetochlor
Registration
Partnership
Pennsylvania
Prospective
Groundwater
Trial
 
Final
Report
(
dated
3/
18/
2004).
Project
Number:
ARP
#
ACET/
96/
PG/
06,
Levine­
Fricke
#
004/
03277/
88/
431.
Unpublished
study
prepared
by
­
90­

ARP
Submissions
­
Section
4:
MONITORING
STUDIES
 
PROSPECTIVE
GROUND
WATER
Monsanto
Company,
Zeneca
Agrochemicals,
and
Covance
Laboratories,
Ltd.
306
p.
DP
#
302847.

ARP
Submissions
­
Section
5:
MONITORING
STUDIES
 
STATE
GROUND
WATER
MRID:
43899601
Hendley,
P.
(
1995)
State
Ground
Water
Monitoring
Program
for
Acetochlor
and
Other
Corn
Herbicides­­
Part
1:
Site
Selection
and
Site
Details:
Lab
Project
Number:
ACET­
94­
GW­
01:
RR
95­
087B:
GWMSIT05.
DOC.
Unpublished
study
prepared
by
Zeneca
Ag
Products
and
Levine­
Fricke,
Inc.
3217
p.

MRID:
?
Hendley,
P.
(
1996)
State
Ground
Water
Monitoring
Program
for
Acetochlor
and
Other
Corn
Herbicides­­
Part
2.
1995
Progress
Report:
Lab
Project
Number:
Zeneca
#
ACET­
95­
GW­
02;
Levine­
Fricke
#
3276.101;
Report
#
RR
96­
019B.
Unpublished
study
prepared
by
Zeneca
Ag
Products;
Monsanto;
Levine,
Fricke.
261
p.

MRID:
44422501
Hendley,
P.
(
1997)
State
Ground
Water
Monitoring
Program
for
Acetochlor
and
Other
Corn
Herbicides­­
Part
3.
1996
Progress
Report:
Lab
Project
Number:
ACET­
95­
GW­
02:
3276.101:
RR
97­
034B.
Unpublished
study
prepared
by
Zeneca
Ag
Products;
Monsanto;
Levine,
Fricke,
Recon
Inc.
138
p.
OPP
DP
Barcode
D252465.

MRID:
44599201
Hendley,
P.
(
1998)
State
Ground
Water
Monitoring
Program
for
Acetochlor
and
other
Corn
Herbicides­­
Part
4.
1997
Progress
Report:
Lab
Project
Number:
RR
98­
026B:
ACET­
95­
GW­
02:
3276.
101.
Unpublished
study
prepared
by
Zeneca
Ag
Products
and
Monsanto.
137
p.

MRID:
44948701
De
Guzman,
N.
(
1999)
State
Groundwater
Monitoring
Program
for
Acetochlor
and
Other
Corn
Herbicides­­
Part
5:
1998
Progress
Report:
Lab
Project
Number:
ACET­
95­
GW­
02:
3276.101:
RR
99­
031B.
Unpublished
study
prepared
by
Zeneca
Ag
Products;
Monsanto
and
LFR
Levine­
Fricke.
143
p.

MRID:
45208501
De
Guzman,
N.
(
2000)
State
Ground
Water
Monitoring
Program
for
Acetochlor
and
Other
Corn
Herbicides­
Part
6:
Lab
Project
Number:
ACET­
95­
GW­
02:
3276.101:
RR
00­
100B.
Unpublished
study
prepared
by
Levine­
Fricke,
Zeneca,
and
Alta
Analytical
Laboratory,
Inc.
191
p.

MRID:
45449601
­
91­

ARP
Submissions
­
Section
5:
MONITORING
STUDIES
 
STATE
GROUND
WATER
De
Guzman,
N.
(
2001)
State
Ground
Water
Monitoring
Program
for
Acetochlor
and
Other
Corn
Herbicides­­
Part
7:
2000
Progress
Report:
Lab
Project
Number:
852­
562:
ACET­
95­
GW­
02:
3276.101.
Unpublished
study
prepared
by
LFR
Levine­
Fricke,
Monsanto,
and
Dow
AgroSciences
LLC.
15
p.

MRID:
45722701
de
Guzman,
N.;
Fuhrman,
J.;
Gustafson,
D.;
et
al.
(
2002)
State
Ground
Water
Monitoring
Program
For
Acetochlor
and
Other
Corn
Herbicides­­
Part
8.
2001
Progress
Report:
Lab
Project
Number:
ACET­
95­
GW­
02:
3276.101:
ARP­
GWM­
01.
Unpublished
study
prepared
by
LFR
Levine
Fricke
(
LFR),
Dow
AgroSciences
LLC
and
Monsanto.
158
p.

MRID:
45728401
van
Wesenbeeck,
I.;
De
Guzman,
N.;
Fuhrman,
J.;
et
al.
(
2002)
State
Ground
Water
Monitoring
Program
for
Acetochlor
and
Other
Corn
Herbicides­­
Part
9:
Final
Study
Report:
Lab
Project
Number:
ARP­
GWM­
02:
852­
577:
ACET­
95­
GW­
02.
Unpublished
study
prepared
by
LFR
Levine­
Fricke
and
Monsanto.
121
p.

MRID:
45730201
De
Guzman,
N.;
Wesenbeeck,
I.
(
2002)
State
Ground
Water
Monitoring
Program
for
Acetochlor
and
Other
Corn
Herbicides­­
Part
10
Amendment
to
the
Final
Study
Report:
Lab
Project
Number:
ACET­
94­
GW­
01:
3276.101:
852­
578.
Unpublished
study
prepared
by
LFR
Levine
Fricke,
Monsanto
and
Dow
AgroSciences
LLC.
300
p.

Barcodes
of
actions
completed
with
this
review:
D245339
D249062
D257732
D257889
D257961
D257976:
D257982
D258421
D258783
D258856
D260167
D260372
D260831
D260917
D262987
D263614
D265250
D265265
D265617
D265628
D266400
D268225
D269431
D269432
D269661
D269664
D269888
D271012
D271883
D272255
D272343
D272347
D275586
D275593
D275890
D278534
D278837
D279225
D279306
D280431
D280479
D284563
D284868
D284868
D284868
D288177
D301788
D301823
D305544
D275887
Pertinent
Outside
Literature
­
92­

Barbash,
J.
E.,
G.
P.
Thelin,
D.
W.
Kolpin,
and
R.
J.
Gilliom.
1999.
Distribution
of
major
herbicides
in
ground
water
of
the
United
States.
Water­
Resource
Investigations
Rep.
98­
4245.
Available
online
at
http://
ca.
water.
usgs.
gov/
pnsp/
rep/
wrir984245/
(
verified
7
Jan.
2003).
U.
S.
Geol.
Survey,
Sacramento,
CA.

Battaglin,
W.
A.,
and
D.
A.
Goolsby.
1999.
Are
shifts
in
herbicide
use
reflected
in
concentration
changes
in
midwestern
rivers.
Environ.
Sci.
Technol.
33:
2917 
2925.

Coupe,
R.
H.
and
J.
D.
Blomquist.
2004.
Water­
soluble
pesticides
in
finished
water
of
community
water
supplies.
Journal
AWWA
96:
56­
68.

Kalkhoff,
S.
J.
1994.
National
Water­
Quality
Assessment
Program 
Eastern
Iowa
basins.
Factsheet
FS
94­
031.
Available
online
at
http://
iowa.
usgs.
gov/
nawqa/
factsheets/
factsheet.
html
(
verified
7Jan.
2003).
U.
S.
Geol.
Survey,
Iowa
City,
IA.

Kalkhoff,
S.
J.,
D.
W.
Kolpin,
and
E.
M.
Thurman.
1998.
Degradation
of
chloroacetanilide
herbicides:
The
prevalence
of
sulfonic
and
oxanilic
acid
degradation
products
in
Iowa
ground
and
surface
waters.
Environ.
Sci.
Technol.
32:
1738 
1740.

Kalkhoff,
S.;
Kolpin,
D.;
Thurman,
E.
et
al.
(
1998)
Degradation
of
Chloroacetanilide
Herbicides:
The
Prevalence
of
Sulfonic
and
Oxanilic
Acid
Metabolites
in
Iowa
Ground
and
Surface
Waters.
Unpublished
study
prepared
by
U.
S.
Geological
Survey.
13
p.
EPA
MRID:
44512601.

Kolpin,
D.
W.,
S.
J.
Kalkhoff,
D.
A.
Goolsby,
D.
A.
Sneck­
Fahrer,
and
E.
M.
Thurman.
1997.
Occurrence
of
selected
herbicides
and
herbicide
degradation
products
in
Iowa's
ground
water,
1995.
Ground
Water
35:
679 
688.

Kolpin,
D.
W.,
E.
M.
Thurman,
and
D.
A.
Goolsby.
1996.
Occurrence
of
selected
pesticides
and
their
metabolites
in
near­
surface
aquifers
of
the
midwestern
United
States.
Environ.
Sci.
Technol.
30:
335 
340.

Kolpin,
D.
W.,
E.
M.
Thurman,
and
S.
M.
Linhart.
1998.
The
environmental
occurrence
of
herbicides:
The
importance
of
degradation
products
in
ground
water.
Arch.
Environ.
Contam.
Toxicol.
35:
385 
390.

Rheineck,
B.
and
J.
Postle.
2000.
Chloroacetanilide
Herbicide
Metabolites
in
Wisconsin
Groundwater.
Wisconsin
Department
of
Agriculture,
Trade
and
Consumer
Protection,
ARM
Division
 
Groundwater
Unit;
ARM
publication
82.
­
93­

12.
APPENDICES
APPENDIX
12.1.
Chemical
Names
and
Structures
Table
A­
1.
Chemical
names
and
structures
of
acetochlor
and
its
degradates
discussed
in
this
exposure
assessment.

N
CH
3
Cl
O
O
CH
3
C
H
3
Acetochlor
2'­
Ethyl­
6'­
methyl­
N­(
ethoxymethyl)­
2­
chloroacetanilide
N
CH
3
SO
3
H
O
O
CH
3
C
H
3
Acetochlor
ethanesulfonic
acid
2­[(
2­
ethyl­
6­
methylphenyl)(
ethoxymethyl)
amino]­
2­
oxoethanesulfonic
acid
N
CH
3
O
CH
3
C
H
3
O
O
H
O
Acetochlor
oxanilic
acid
2­[(
2­
ethyl­
6­
methylphenyl)(
ethoxymethyl)
amino]­
2­
oxoacetic
acid]
­
94­
­
95­

Table
A­
2.
Structures
of
the
chloroacetanilide
herbicides
and
their
major
degradates
(
Source:
ARP
pre­
publication
journal
article).

Both
the
SDWS
and
the
SGW
studies
conducted
by
the
ARP
simultaneously
monitored
for
each
of
these
three
parent
compounds
(
plus
the
corn
herbicide
atrazine)
during
the
full
7
years
of
monitoring
and
for
each
of
the
degradation
products
listed
during
the
last
3
years
of
monitoring.
R2
R1
N
R3
O
R4
R1
R2
R3
R4
Common
Name
Abbr.
Chemical
Name
(
CAS)
LOD/
LOQ
(
µ
g
L­
1)
CAS
Number
CH3
CH3CH2
CH2OCH2CH3
CH2Cl
acetochlor
Acet
2­
chloro­
N­(
ethoxymethyl)­
N­(
2­
ethyl­
6­

methylphenyl)­
acetamide
0.03/
0.05
34256­
82­
1
CH3CH2
CH3CH2
CH2OCH3
CH2Cl
alachlor
Alac
2­
chloro­
N­(
2,6­
diethylphenyl)­
N­

(
methoxymethyl)
acetamide
0.05/
0.05
15972­
60­
8
CH3
CH3CH2
CH(
CH3)
CH2OCH3
CH2Cl
metolachlor
Meto
2­
chloro­
N­(
2­
ethyl­
6­
methylphenyl)­
N­(
2­

methoxy­
1­
methylethyl)­
acetamide
0.03/
0.05
51218­
45­
2
CH3
CH3CH2
CH2OCH2CH3
CH2SO3H
acetochlor
sulfonic
acid
Ac_
ESA
2­[(
ethoxymethyl)(
2­
ethyl­
6­
methyl
phenyl)
amino]­
2­
oxoethanesulfonic
acid
0.20/
0.50
187022­
11­
3
CH3
CH3CH2
CH2OCH2CH3
CO2H
acetochlor
oxanilic
acid
Ac_
OXA
2[(
ethoxymethyl)(
2­
ethyl­
6­

methylphenyl)
amino]
oxoacetic
acid
0.10/
0.50
194992­
44­
4
CH3CH2
CH3CH2
CH2OCH3
CH2SO3H
alachlor
sulfonic
acid
AlESA
[
2­(
2,6­
diethylphenyl)(
methoxymethyl)
amino]­
2­

oxoethanesulfonic
acid
0.20/
0.50
142363­
53­
9
CH3CH2
CH3CH2
CH2OCH3
CO2H
alachlor
oxanilic
acid
AlOXA
[
2­(
2,6­
diethylphenyl)(
methoxymethyl)
amino]­
2­

oxoacetic
acid
0.10/
0.50
171262­
17­
2
CH3
CH3CH2
CH(
CH3)
CH2OCH3
CH2SO3H
metolachlor
sulfonic
acid
MeESA
2­[(
2­
ethyl­
6­
methylphenyl)(
2­
methoxy­
1­

methylethyl)
amino]­
2­
oxoethane
sulfonic
acid
0.20/
0.50
171118­
09­
5
CH3
CH3CH2
CH(
CH3)
CH2OCH3
CO2H
metolachlor
oxanilic
acid
MeOXA
[(
2­
ethyl­
6­
methylphenyl)(
2­
methoxy­
1­

methylethyl)
amino]
oxoacetic
acid
0.10/
0.50
152019­
73­
3
Atrazine,
which
is
not
a
chloroacetanilide
herbicide,
was
also
monitored
in
this
study,
and
is
denoted
by
the
abbreviation:
Atra.
Its
chemical
name
is
6­
chloro­
N­
ethyl­
N'­(
1­
methylethyl)­
1,3,5­
triazine­

2,4­
diamine,
and
its
CAS
number
is
1912­
24­
9.
Its
LOD
and
LOQ
were
0.03
and
0.05
µ
g
L­
1,
respectively.
­
96­

APPENDIX
12.2.
Acetochlor
Registration
Agreement
 
Cancellation
/
Mitigation
Endpoints
The
following
text
is
excerpted
from
the
registration
agreement
(
section
numbering
retained
from
the
agreement):

Excerpt1,
Regarding
Ground
Water
Detections:

5.1.3.
Response
to
Ground
Water
Detections
5.1.3.1
Investigation
of
Cause
of
Detections
Any
information
pertaining
to
detection
of
acetochlor
and
any
degradates
of
toxicological
concern
which
become
known
to
the
ARP,
Monsanto,
Zeneca
or
their
agents
will
be
reported
to
EPA
within
15
days
of
the
date
such
information
becomes
known
to
the
ARP,
Monsanto,
Zeneca,
or
their
agents.
The
ARP
may
respond
to
any
detections
of
acetochlor
or
its
degradates
of
toxicological
concern
reported
by
investigators,
using
confirmed
analytical
methods,
by
sending
a
qualified
third
party
representative
to
investigate
the
incident.
The
investigation
shall
be
completed
within
60
days
of
receipt
of
the
report
and
the
results
reported
to
EPA
within
30
days
of
completion
of
the
investigation,
unless
the
ARP
and
EPA
agree
to
extend
those
deadlines.
The
investigation
may
include
any
additional
sampling
useful
in
determining
if
the
detection
is
due
to
a
point
source
or
intentional
contamination.
The
EPA
shall
consider
the
results
of
any
such
investigation
in
determining
whether
a
reported
and
investigated
detection
will
be
considered
a
"
detection"
for
the
purpose
of
establishing
a
pattern
of
movement,
or
the
need
for
additional
mitigation,
or
for
triggering
suspension
or
cancellation
under
this
Section
5.1.3.

5.1.3.2
Exposure
Reduction
For
detections
verified
by
the
ARP's
GC/
MS
method
(
at
ARP's
expense),
occurring
at
a
level
at
or
above
1.0
ppb
in
rural
drinking
water
wells,
the
ARP
will
offer
without
conditions
a
Well
Assistance
Program
to
compensate
rural
well
owners
by
paying
for
the
cost
of
drilling
the
new
well,
or
installing
and
maintaining
filters,
or
connecting
to
public
water
supplies,
and
other
appropriate
measures.
The
ARP
will
unconditionally
pay
for
all
costs
associated
with
this
remediation
up
to
$
5,000
per
well
(
in
1994
dollars).
All
private
rural
drinking
water
wells
and
community
drinking
water
supply
wells
in
rural
areas
are
eligible
for
the
ARP
well
assistance
program.

Public
wells
in
rural
areas
which
have
verified
detections
(
using
the
ARP's
GC­
MS
method)
at
ARP's
expense
of
acetochlor
at
a
level
at
or
above
1.0
ppb,
that
are
not
associated
with
product
mishandling
will
be,
at
ARP's
expense,
remediated
to
provide
drinking
water
below
a
detection
limit
of
0.10
ppb.

5.1.3.3.
Detection
Criteria
The
data
from
either
the
PGW
or
other
sampling/
monitoring
programs
may
indicate
a
pattern
of
movement
of
acetochlor
or
degradates
of
toxicological
concern
toward
ground
water,
as
a
result
of
use
according
to
label
directions
or
in
accordance
with
widespread
and
commonly
recognized
practice.
At
present,
the
ARP
is
not
aware
of
any
degradates
of
toxicological
concern.
If,
in
the
future,
EPA
determines
there
are
degradates
of
toxicological
concern,
the
detection
concentrations
noted
below
will
be
reviewed
and
will
be
revised,
if
appropriate,
based
upon
the
toxicologic
effect
of
the
degradate.
A
pattern
of
movement
is
defined
as
being:
­
97­

 
detections
of
acetochlor
or
degradates
of
toxicological
concern
confirmed
by
the
approved
and
validated
GC­
MS
method,
and
 
IN
THE
PGW
STUDIES.
Detections
of
acetochlor
or
degradates
of
toxicological
concern
that
are
greater
than
or
equal
to
0.10
ppb
in
ground
water
which
are
consistent
with
recharge
as
measured
with
tracers
and/
or
suction
lysimeters;
OR
Detections
of
acetochlor
or
degradates
of
toxicologic
concern
at
a
concentration
greater
than
or
equal
to
1.0
ppb
in
soil
water
collected
by
suction
lysimeters
at
a
depth
of
9
feet
below
the
land
surface.
Such
soil
water
detections
must
be
consistent
with
the
movement
of
soil
water
as
determined
by
conservative
tracers,
and
consistent
with
detections
in
the
three
and
six
foot
lysimeters
in
that
cluster.
Lysimeter
samples
from
the
same
depth
will
be
composited
to
ensure
adequate
sample
size
(
for
the
purpose
of
analysis)
when
necessary;
or
 
IN
THE
STATE
MONITORING
PROGRAMS.
For
reports
of
detections
of
acetochlor
or
degradates
of
toxicological
concern
in
the
state
monitoring
programs
described
in
section
5.1.2,
a
detection
greater
than
or
equal
to
a
concentration
of
0.10
ppb
in
ground
water
subsequently
detected
at
greater
than
or
equal
to
0.10
ppb
in
two
follow­
up
samples
collected
monthly
over
a
period
of
six
months;
or
 
OTHER
MONITORING
STUDIES
(
outside
of
the
PGW
study
or
State
Monitoring
Programs
(
defined
in
section
5.1.2)).
For
reports
of
any
other
detections
of
acetochlor,
a
detection
greater
than
or
equal
to
a
concentration
of
0.20
ppb
in
ground
water,
subsequently
detected
at
greater
than
or
equal
to
0.20
ppb
in
two
or
more
follow­
up
samples
collected
monthly
over
a
period
of
six
months.

If
the
ARP
does
not
take
appropriate
steps
to
secure
follow­
up
sampling,
the
initial
report
of
the
detection
shall
be
treated
as
sufficient
to
define
a
pattern
of
movement.
The
determination
of
what
constitutes
appropriate
steps
to
be
taken
is
a
"
reserved
issue"
subject
to
the
provisions
of
Section
7A.

5.1.3.4.
Additional
Mitigation
Measures
If
EPA
determines
that
a
pattern
of
movement,
as
defined
in
5.1.3.3.
has
occurred
from
use
in
accordance
with
label
directions
or
in
accordance
with
widespread
and
commonly
recognized
practice,
then
the
ARP,
in
conjunction
with
EPA,
will
determine
whether
the
movement
is
limited
to
a
geographical
area
or
soil
type.
In
that
case,
the
ARP
will
revise
the
acetochlor
label
to
include
geographic
or
additional
soil
type
label
restrictions.

5.1.3.5.
Automatic
Suspension
If
EPA
determines
that
a
pattern
of
movement
toward
ground
water
as
defined
in
5.1.3.3.,
above
has
occurred
arising
from
use
in
accordance
with
label
directions
or
in
accordance
with
widespread
and
commonly
recognized
practice,
and
if
within
30
days
EPA
and
the
ARP
cannot
agree
on
an
immediate
mitigation
option,
the
registration
shall
be
automatically
suspended
on
a
geographic
basis.
This
suspension
will
terminate
if
EPA
determines
that
the
ARP
has
taken
adequate
steps
to
implement
appropriate
mitigation
measures.
The
determination
of
appropriate
mitigation
options
shall
be
governed
by
the
provisions
of
Section
7.

5.1.3.6.
Cancellation
 
GW
Scenario
1
­
98­

For
the
PGW
studies,
if
EPA
determines
that
out
of
the
8
sites,
4
sites
in
a
variety
of
geographic,
and
climatic
conditions
under
both
vulnerable
and
general
use
conditions,
(
as
determined
by
EPA)
in
corn
growing
areas
indicate
a
pattern
of
movement
of
acetochlor
toward
ground
water,
as
defined
in
5.1.3.3.
from
use
in
accordance
with
label
directions
or
in
accordance
with
widespread
and
commonly
recognized
practice,
registration
shall
be
automatically
canceled.
The
sites
at
which
a
pattern
of
movement
occurs
shall
represent
a
range
of
vulnerable
and
general
use
soil
textures
consistent
with
labeled
use.

 
GW
Scenario
2
For
monitoring
programs
outside
the
PGW
studies,
the
registration
of
acetochlor
will
be
automatically
canceled
if
EPA
determines
that
either
of
the
criteria
specified
below
have
been
met.
All
detections
shall
be
verified
by
the
ARP's
GC­
MS
method
at
the
ARP's
expense.

o
Criterion
1:

Detections
occur
in
20
or
more
wells
included
in
the
State
Monitoring
Program
at
or
above
0.10
ppb
followed
by
two
subsequent
detections
of
at
least
0.10
ppb
in
monthly
sampling
of
each
of
those
wells,
conducted
over
a
period
of
six
months.

o
Criterion
2:

Detections
occur
in
150
or
more
individual
wells
at
or
above
0.20
ppb,
followed
 
by
two
subsequent
detections
of
at
least
0.20
ppb
in
monthly
sampling
of
each
of
those
wells,
conducted
over
a
period
of
six
months
across
a
wide
variety
of
geographic,
soil,
and
climatic
conditions
in
corn
growing
area.

 
GW
Scenario
3
For
monitoring
programs
outside
the
PGW
studies,
the
registration
of
acetochlor
will
be
automatically
canceled
if
EPA
determines
that
detections
occur
in
twenty
(
20)
or
more
wells
across
a
wide
variety
of
geographic,
soil,
and
climatic
conditions
in
corn
growing
areas
at
a
concentration
of
at
least
1.0
ppb,
followed
by
two
subsequent
detections
of
at
least
1.0
ppb
in
monthly
sampling
of
each
of
those
wells,
conducted
over
a
period
of
six
months.
All
detections
shall
be
verified
by
the
ARP's
GC­
MS
method
at
the
ARP's
expense.

An
initial
detection
shall
be
treated
as
sufficient
to
meet
these
cancellation
criteria
if
the
ARP
has
failed
to
take
timely
and
appropriate
steps
to
secure
follow­
up
samples.

If
EPA
determines
at
any
time
that
mitigation
measures
have
been
or
will
be
undertaken
which
are
likely
to
be
effective,
the
Agency
may
treat,
for
a
period
of
up
to
18
months,
some
or
all
detections
within
the
area
subject
to
such
mitigation
measures
(
mitigation
area)
as
insufficient
to
meet
the
cancellation
criteria
in
section
5.1.3.6.
No
later
than
18
months
after
such
mitigation
measures
have
been
initiated,
EPA
shall
make
a
final
determination
whether
the
mitigation
measures
have
been
or
are
likely
to
be
effective.
During
this
time,
the
ARP
may
investigate
whether
such
mitigation
measures
have
been,
or
are
likely
to
be,
effective.
The
EPA
shall
notify
the
ARP
60
days
prior
to
making
its
determination,
and
shall
consider
the
results
of
any
such
investigation,
if
timely
received,
in
making
that
determination.
If
EPA's
final
determination
is
that
the
mitigation
measures
have
not
been
or
are
not
likely
to
be
successful,
all
detections
within
the
mitigation
area
shall
be
subject
to
the
provisions
of
sections
5.1.3.3.,
5.1.3.5.,
and
5.1.3.6.
If
EPA's
final
determination
is
that
the
mitigation
measures
have
been
or
are
likely
to
be
successful,
­
99­

some
or
all
detections
within
the
mitigation
area
may
be
designated
by
EPA
as
insufficient
to
meet
the
cancellation
provisions
of
Section
5.1.3.6.
Such
final
determination
will
be
consistent,
to
the
extent
feasible,
with
relevant
existing
policies
and
procedures.

Point
source
contamination
detections
shall
be
treated
as
sufficient
to
meet
these
cancellation
criteria
unless
EPA
determines
that
such
contamination:
(
i)
does
not
result
from
use
in
accordance
with
label
directions
or
widespread
and
commonly
recognized
practice,
or
(
ii)
results
from
use
in
accordance
with
label
directions
or
in
accordance
with
widespread
and
commonly
recognized
practice,
but
that
the
general
cause
of
the
contamination
can
be
mitigated
with
product
stewardship,
label
language
or
repair/
replacement
of
damaged
or
inadequately
installed
wells.

5.2.
State
Management
Plans
If
at
any
time
after
the
registration
EPA
decides
to
nominate
acetochlor
for
inclusion
in
State
Management
Plans,
the
ARP
will
not
file
any
objection
to
such
inclusion,
nor
will
it
challenge
such
action
in
any
court
or
administrative
forum.

5.3.
Continued
Stewardship
Regardless
of
whether
the
data
indicate
any
pattern
of
movement
toward
groundwater,
the
ARP
will
continue
its
product
stewardship
commitment
and
cooperate
with
the
Agency
to
develop
and
implement
additional
product
stewardship
measures
considered
appropriate.

Excerpt
2,
Regarding
Surface
Water
Detections:

6.2
Response
to
Surface
Water
Detections
The
ARP
agrees
in
principle
to
provisions
relating
to
surface
water,
which
include
a
sampling
program,
investigation
of
the
source
of
surface
water
detections,
and
mitigation
measures.
The
elements
of
the
response
to
surface
water
detections
will
parallel
those
described
in
Section
5
for
ground
water
protection.

6.2.1
Investigation
of
Cause
of
Detections
The
ARP
may
respond
to
any
detections
of
acetochlor
or
degradates
of
toxicological
concern,
using
confirmed
analytical
methods,
by
sending
a
qualified
third
party
representative
to
investigate
the
incident.
The
investigation
shall
be
completed
within
60
days
of
the
incident
becoming
known
to
the
ARP
and
the
results
reported
to
EPA
within
30
days
of
completion
of
the
investigation,
unless
the
ARP
and
EPA
agree
to
extend
those
deadlines.
The
investigation
may
include
any
additional
sampling
useful
in
determining
if
the
detection
is
due
to
a
point
source
or
intentional
contamination.
The
EPA
shall
consider
the
results
of
any
such
investigation
in
determining
whether
a
reported
and
investigated
detection
will
be
considered
a
"
detection"
for
the
purpose
of
establishing
the
need
for
mitigation
or
for
triggering
cancellation
under
Section
6.2.2.

6.2.2
Mitigation
and
Cancellation
At
present,
the
ARP
is
not
aware
of
any
degradates
of
toxicological
concern.
If,
in
the
future,
EPA
determines
there
are
degradates
of
toxicological
concern,
the
detection
concentrations
noted
below
will
be
reviewed
and
will
be
revised,
if
appropriate,
based
upon
the
toxicologic
effect
of
the
degradate.

 
SW
Scenario
I:
­
100­

If
one
(
1)
community
water
supply
system,
that
derives
its
water
primarily
from
surface
water,
detects
an
annual
time­
weighted
mean
concentration
of
2.0
ppb,
acetochlor,
then
either;

o
The
use
of
acetochlor
in
the
related
watershed
will
be
prohibited.
Such
prohibition
will
be
implemented
by
means
of
amendment
of
the
acetochlor
registration
to
prohibit
sale,
distribution,
and
use
in
the
specified
watershed.
The
timing,
content,
and
implementation
of
such
restriction
shall
be
governed
by
the
provisions
of
Section
7;
or
o
The
ARP
will
absorb
100%
of
costs
required
to
restore
the
community
water
supply
system
to
compliance.
If
EPA
determines
that
the
ARP
has
failed
to
meet
this
obligation,
it
may
cancel
the
registration
without
opportunity
for
hearing.
 
SW
Scenario
II:

If
EPA
determines
that
two
(
2)
large
(
serving
100,000
people)
community
water
supply
systems,
or
ten
(
10)
community
water
supply
systems
of
any
size
across
a
wide
variety
of
corn
growing,
soil,
and
climatic
have
an
annual
time­
weighted
mean
concentration
of
2.0
ppb
or
are
otherwise
determined
to
be
out
of
compliance
based
on
Office
of
Water
criteria,
the
registration
will
be
automatically
canceled.

If
any
community
water
supply
system
that
derives
its
water
primarily
from
surface
water
detects
a
single
peak
concentration
of
8.0
ppb
of
acetochlor,
the
ARP
will
make
biweekly
sampling
of
that
water
system
throughout
the
following
12
months
to
determine
whether
the
2.0
ppb
annual
time­
weighted
mean
concentration
has
been
exceeded.
­
101­

APPENDIX
12.3.
Acetochlor
Usage
 
Detailed
Summary
CONFIDENTIAL
BUSINESS
INFORMATION,
NOT
INCLUDED
HERE
­
102­

APPENDIX
12.4.
Locations
of
Monitoring
Sites
for
the
ARP
SDWS
Study
(
Acetochlor
Surface
Drinking
Water
Supply
Study)

P1
(
primary)
Community
Water
Systems
only
CITY
STATE
SUPPLY
SYSTEM
NAME
TYPE
WATERSHE
D
AREA
(
acres)
WATERSHED
RUNOFF
RATING
WATERS
HED
%

CORN
INTENSIT
Y
STATISTICA
L
STRATUM
ACTIVATE
CARBON
Treatment
?

Corning
IA
Lake
Binder
Lake
2126
15.3
23.0
>
20%
CI
YES
Des
Moines
IA
Raccoon
River
and
Infiltration
Galleries
River
2304810
31.1
39.4
>
20%
CI
YES
Iowa
City
IA
Iowa
River
River
2099081
30.6
40.3
>
20%
CI
YES
Milford
IA
West
Lake
Okoboji
Lake
14866
22.9
32.6
>
20%
CI
YES
Montezuma
IA
Diamond
Lake
Reservoir
2724
31.8
33.3
>
20%
CI
YES
Mount
Pleasant
IA
Skunk
River
River
2599367
15.6
34.2
>
20%
CI
YES
Okoboji
IA
West
Okoboji
Lake
Lake
14866
22.9
32.6
>
20%
CI
NO
Ottumwa
IA
Des
Moines
River
River
8569564
31.7
35.5
>
20%
CI
YES
Panora
IA
Middle
Racoon
River
River
265272
32.5
41.1
>
20%
CI
NO
Spirit
Lake
IA
Spirit
Lake
Lake
43135
25.0
36.2
>
20%
CI
NO
Winterset
IA
Cedar
Lake
Reservoir
10443
35.5
21.7
>
20%
CI
YES
Altamont
IL
Altamont
New
Reservoir
Reservoir
521
26.7
28.5
>
20%
CI
YES
Blandinsville
IL
LaHarpe
Creek
River
8779
33.7
35.5
>
20%
CI
NO
Breese
IL
Shoal
Creek
River
480358
35.7
25.2
>
20%
CI
YES
Carlinville
IL
Carlinville
Lake
I
Reservoir
15706
28.8
25.0
>
20%
CI
YES
Carthage
IL
Carthage
Lake
Reservoir
1756
33.6
28.4
>
20%
CI
YES
Charleston
IL
Lake
Charleston
Reservoir
1198
28.7
34.4
>
20%
CI
YES
Clay
City
IL
Little
Wabash
River
River
518175
36.3
26.9
>
20%
CI
YES
Decatur
IL
Lake
Decatur
Reservoir
602057
30.1
41.5
>
20%
CI
YES
Elgin
IL
Fox
River
River
953176
23.4
20.3
>
20%
CI
YES
Fairfield
IL
Little
Wabash
River
River
1169567
35.4
25.0
>
20%
CI
YES
Flora
IL
Little
Wabash
River
River
491311
36.5
27.3
>
20%
CI
YES
Georgetown
IL
Little
Vermillion
River
River
106395
35.7
39.5
>
20%
CI
YES
­
103­

P1
(
primary)
Community
Water
Systems
only
CITY
STATE
SUPPLY
SYSTEM
NAME
TYPE
WATERSHE
D
AREA
(
acres)
WATERSHED
RUNOFF
RATING
WATERS
HED
%

CORN
INTENSIT
Y
STATISTICA
L
STRATUM
ACTIVATE
CARBON
Treatment
?

Gillespie
IL
Old
Gillespie
Lake
Reservoir
2966
30.3
25.0
>
20%
CI
YES
Greenfield
IL
Greenfield
Lake
Reservoir
724
28.1
29.1
>
20%
CI
YES
Hudson
IL
Lake
Bloomington
Reservoir
41942
28.7
44.4
>
20%
CI
YES
Kankakee
IL
Kankakee
River
River
2952111
27.1
37.4
>
20%
CI
YES
Litchfield
IL
Lake
Lou
Yeager
Reservoir
69219
23.3
30.1
>
20%
CI
YES
Mascoutah
IL
Kaskaskia
River
River
2844480
29.7
26.3
>
20%
CI
YES
Mattoon
IL
Lake
Paradise
Reservoir
11916
29.3
34.5
>
20%
CI
YES
Nashville
IL
City
of
Nashville
Reservoir
Reservoir
1013
21.1
23.1
>
20%
CI
YES
Neoga
IL
Lake
Mattoon
Reservoir
34849
32.7
33.5
>
20%
CI
YES
New
Athens
IL
Kaskaskia
River
River
3274132
30.6
25.4
>
20%
CI
YES
New
Berlin
IL
Spring
Creek
River
16852
34.1
35.2
>
20%
CI
YES
Oakland
IL
Lake
Oakland
Reservoir
6909
26.5
39.7
>
20%
CI
YES
Olney
IL
East
Fork
Lake
Reservoir
6644
28.1
28.8
>
20%
CI
YES
Palmyra
IL
Palmyra­
Modesto
Lake
Reservoir
826
40.0
25.0
>
20%
CI
YES
Pana
IL
Lake
Pana
Reservoir
4545
33.8
32.3
>
20%
CI
YES
Paris
IL
Twin
Lakes
Reservoir
11733
30.3
38.7
>
20%
CI
YES
Pittsfield
IL
Lake
Pittsfield
Reservoir
6971
40.6
22.6
>
20%
CI
NO
Shipman
IL
Shipman
Reservoir
Reservoir
427
28.6
25.0
>
20%
CI
NO
Sparta
IL
South
City
Lake
Reservoir
480
32.0
15.2
>
20%
CI
YES
Springfield
IL
Lake
Springfield
Lake
162178
29.7
34.9
>
20%
CI
YES
West
Salem
IL
West
Salem
Reservior
&

shale
pit
Reservoir
614
27.2
26.1
>
20%
CI
NO
White
Hall
IL
White
Hall
Reservoir
Reservoir
613
29.8
29.1
>
20%
CI
YES
Ferdinand
IN
Old
Lake
(
No.
1)
Reservoir
105
29.7
26.2
>
20%
CI
NO
Holland
IN
New
Holland
Lake
Reservoir
348
27.4
26.2
>
20%
CI
YES
Kokomo
IN
Wildcat
Creek
River
121637
37.4
38.0
>
20%
CI
YES
Logansport
IN
Eel
River
River
524144
24.9
28.3
>
20%
CI
NO
Mitchell
IN
East
Fork
of
the
White
River
River
2470938
39.5
26.9
>
20%
CI
YES
North
Vernon
IN
Vernon
Fork
of
Muscatatuck
River
River
68241
26.3
21.0
>
20%
CI
YES
­
104­

P1
(
primary)
Community
Water
Systems
only
CITY
STATE
SUPPLY
SYSTEM
NAME
TYPE
WATERSHE
D
AREA
(
acres)
WATERSHED
RUNOFF
RATING
WATERS
HED
%

CORN
INTENSIT
Y
STATISTICA
L
STRATUM
ACTIVATE
CARBON
Treatment
?

Oakland
City
IN
Old
Lake
Lake
83
31.9
33.8
>
20%
CI
YES
Richmond
IN
Middle
Fork
Reservoir
Lake
30825
25.3
27.2
>
20%
CI
YES
Santa
Claus
IN
Christmas
Lake
Reservoir
1583
37.4
21.8
>
20%
CI
NO
Seymour
IN
East
Fork
of
the
White
River
River
1516709
33.2
33.8
>
20%
CI
YES
Speedway
IN
Big
Eagle
Creek
River
119080
29.2
26.8
>
20%
CI
YES
Warsaw
IN
Center
Lake
Reservoir
444
20.3
30.3
>
20%
CI
NO
Westport
IN
Sand
Creek
River
60170
30.2
43.1
>
20%
CI
YES
Concordia
MO
Edwin
A.
Pape
Lake
Reservoir
5507
23.8
20.6
>
20%
CI
YES
Higginsville
MO
Higginsville
City
Lake
Reservoir
3547
23.5
20.6
>
20%
CI
YES
Plattsmouth
NE
Beaver
Lake
Reservoir
7397
33.5
26.1
>
20%
CI
YES
Archbold
OH
Tiffin
River
River
208202
29.8
23.9
>
20%
CI
YES
Attica
OH
Honey
Creek
River
46710
28.9
24.2
>
20%
CI
YES
Bowling
Green
OH
Maumee
River
River
3977343
26.0
23.1
>
20%
CI
YES
Cedarville
OH
Massies
Creek
River
31764
30.4
27.2
>
20%
CI
NO
Celina
OH
Grand
Lake
St
Marys
Reservoir
72549
32.8
30.9
>
20%
CI
NO
Columbus
OH
Scioto
River
River
665366
27.4
21.4
>
20%
CI
YES
Defiance
OH
Maumee
River
River
1395515
26.8
21.5
>
20%
CI
YES
Delta
OH
Bad
Creek
River
22000
22.0
33.6
>
20%
CI
YES
Lima
OH
Auglaize
River
River
131174
25.2
24.3
>
20%
CI
NO
McClure
OH
Maumee
River
River
3777748
26.0
23.0
>
20%
CI
YES
McComb
OH
Rader
Creek
River
668
30.3
23.4
>
20%
CI
YES
Metamora
OH
Ten
Mile
Creek
River
3174
31.5
32.4
>
20%
CI
YES
Ottawa
OH
Blanchard
River
River
394516
27.2
23.5
>
20%
CI
YES
Upper
Sandusky
OH
Upper
Sandusky
Reservoir
Reservoir
894
29.7
23.8
>
20%
CI
YES
Van
Wert
OH
Town
Creek
River
16385
33.3
29.2
>
20%
CI
NO
West
Milton
OH
Stillwater
River
River
427302
28.9
28.3
>
20%
CI
NO
Wilmington
OH
Caesar's
Creek
Lake
Reservoir
147651
36.9
27.1
>
20%
CI
YES
Denver
PA
Cocalico
Creek
River
12201
30.6
26.4
>
20%
CI
NO
­
105­

P1
(
primary)
Community
Water
Systems
only
CITY
STATE
SUPPLY
SYSTEM
NAME
TYPE
WATERSHE
D
AREA
(
acres)
WATERSHED
RUNOFF
RATING
WATERS
HED
%

CORN
INTENSIT
Y
STATISTICA
L
STRATUM
ACTIVATE
CARBON
Treatment
?

New
Holland
PA
New
Holland
Reservoir
Reservoir
704
8.0
27.4
>
20%
CI
NO
Appleton
WI
Lake
Winnebago
Lake
3776966
14.6
12.9
>
20%
CI
YES
Menasha
WI
Lake
Winnebago
Lake
3776966
14.6
12.9
>
20%
CI
YES
Oshkosh
WI
Lake
Winnebago
Lake
3776966
14.6
12.9
>
20%
CI
YES
Bloomfield
IA
Lake
Fisher
Reservoir
1458
40.3
13.9
11­
20%
CI
NO
Centerville
IA
Lake
Rathbun
Reservoir
353792
37.4
13.2
11­
20%
CI
YES
Chariton
IA
Lake
Ellis
and
Lake
Morris
Reservoir
6453
38.0
10.6
11­
20%
CI
YES
Lenox
IA
Lenox
West
Lake
Reservoir
100
28.4
19.8
11­
20%
CI
NO
Mount
Ayr
IA
Loch
Ayr
Reservoir
Reservoir
2563
11.3
13.5
11­
20%
CI
YES
Osceola
IA
West
Lake
Reservoir
6241
24.2
13.5
11­
20%
CI
YES
Centralia
IL
Raccoon
Lake
Reservoir
30293
32.0
12.2
11­
20%
CI
YES
Coulterville
IL
Coulterville
Lake
Reservoir
449
45.3
15.2
11­
20%
CI
YES
Farina
IL
East
Fork
of
Kaskaskia
River
River
2959
30.6
17.1
11­
20%
CI
YES
Highland
IL
Silver
Lake
Reservoir
30593
31.0
17.5
11­
20%
CI
YES
Salem
IL
Salem
Reservoir
Reservoir
2452
29.6
12.2
11­
20%
CI
YES
Sorento
IL
Sorento
Lake
Reservoir
376
40.2
15.8
11­
20%
CI
NO
Austin
IN
Muscatatuck
River
River
223967
28.1
11.8
11­
20%
CI
NO
Batesville
IN
Biscoff
Reservoir
Reservoir
2916
23.1
19.5
11­
20%
CI
NO
Fort
Wayne
IN
St.
Joseph
River
River
657980
27.0
18.6
11­
20%
CI
YES
Salem
IN
Lake
John
Hay
Reservoir
5797
27.6
11.9
11­
20%
CI
YES
Scottsburg
IN
Scottsburg
Reservoir
Reservoir
1977
26.9
11.3
11­
20%
CI
NO
Horton
KS
Delaware
River
River
91634
33.7
11.5
11­
20%
CI
NO
Ewing
MO
Lewis
County
Water
District
Lake
Reservoir
684
30.8
14.0
11­
20%
CI
YES
Trenton
MO
Thompson
River
River
963925
26.8
10.8
11­
20%
CI
YES
Wyaconda
MO
Wyaconda
City
Lake
Reservoir
208
13.0
15.3
11­
20%
CI
YES
Galena
OH
Alum
Creek
Reservoir
Reservoir
82605
23.4
16.5
11­
20%
CI
NO
Monroeville
OH
West
Branch
Huron
River
River
138245
29.9
18.7
11­
20%
CI
YES
New
London
OH
Buck
Creek
River
40614
29.1
17.3
11­
20%
CI
NO
­
106­

P1
(
primary)
Community
Water
Systems
only
CITY
STATE
SUPPLY
SYSTEM
NAME
TYPE
WATERSHE
D
AREA
(
acres)
WATERSHED
RUNOFF
RATING
WATERS
HED
%

CORN
INTENSIT
Y
STATISTICA
L
STRATUM
ACTIVATE
CARBON
Treatment
?

Paulding
OH
Flatrock
Creek
River
109270
36.5
21.4
11­
20%
CI
YES
Sunbury
OH
Big
Walnut
Creek
River
50886
27.8
16.5
11­
20%
CI
YES
Westerville
OH
Alum
Creek
River
95314
32.1
16.4
11­
20%
CI
YES
Willard
OH
Huron
River
River
46081
28.2
18.2
11­
20%
CI
NO
Williamsburg
OH
East
Fork
of
the
Little
Miami
River
River
149474
35.3
18.1
11­
20%
CI
NO
Carlisle
PA
Conodoguinet
Creek
River
242629
24.8
12.6
11­
20%
CI
YES
Hummelston
PA
Swatara
River
River
284337
31.0
12.1
11­
20%
CI
YES
Mechanicsburg
PA
Conodoguinet
Creek
River
293855
25.4
12.5
11­
20%
CI
YES
Norristown
PA
Schuylkill
River
River
1133118
28.7
9.2
11­
20%
CI
YES
Reading
PA
Lake
Ontellaunee
Reservoir
120883
34.1
13.1
11­
20%
CI
YES
Newark
DE
White
Clay
Creek
River
43629
26.8
10.4
5­
10%
CI
YES
Wilmington
DE
Red
&
White
Clay
Creek
River
100409
27.9
10.6
5­
10%
CI
YES
Lamoni
IA
Home
Lake
(
Pond)
Reservoir
321
31.8
8.7
5­
10%
CI
YES
Alto
Pass
IL
Little
Cedar
Lake
Reservoir
19625
17.8
7.3
5­
10%
CI
YES
Borden
IN
Packwood
Branch
Reservoir
Reservoir
1275
28.9
10.8
5­
10%
CI
YES
Dubois
IN
Patoka
Lake
Reservoir
108655
31.7
8.4
5­
10%
CI
YES
Paoli
IN
Lick
Creek
River
13424
28.1
8.8
5­
10%
CI
YES
St.
Meinrad
IN
Lake
Benet
Reservoir
135
23.7
4.5
5­
10%
CI
NO
Garnett
KS
Crystal
Lake
Reservoir
386
35.8
6.1
5­
10%
CI
YES
Milford
KS
Milford
Lake
Reservoir
15963347
35.3
9.6
5­
10%
CI
YES
Richmond
KS
Richmond
City
Lake
Reservoir
557
29.1
5.1
5­
10%
CI
YES
Topeka
KS
Kansas
River
River
36446269
28.2
8.8
5­
10%
CI
NO
Valley
Falls
KS
Delaware
River
River
570021
26.1
7.5
5­
10%
CI
NO
Westphalia
KS
Lake
(
No
Name)
Reservoir
1652
42.9
4.8
5­
10%
CI
NO
Bel
Air
MD
Winter's
Run
River
23264
38.5
8.2
5­
10%
CI
YES
Elkton
MD
Big
Elk
Creek
River
39985
30.2
9.7
5­
10%
CI
YES
Frederick
MD
Monocacy
River
River
456687
30.0
12.0
5­
10%
CI
YES
Frederick
MD
Monocacy
River
River
456040
27.2
8.9
5­
10%
CI
YES
­
107­

P1
(
primary)
Community
Water
Systems
only
CITY
STATE
SUPPLY
SYSTEM
NAME
TYPE
WATERSHE
D
AREA
(
acres)
WATERSHED
RUNOFF
RATING
WATERS
HED
%

CORN
INTENSIT
Y
STATISTICA
L
STRATUM
ACTIVATE
CARBON
Treatment
?

Havre
de
Grace
MD
Susquehanna
River
River
17629428
15.0
5.5
5­
10%
CI
YES
Silver
Spring
MD
Howard
Duckett
Reservoir
(
Rocky
Gorge
Re
Reservoir
85109
31.9
5.6
5­
10%
CI
YES
Moorhead
MN
Red
River
River
4309787
20.0
10.8
5­
10%
CI
YES
Armstrong
MO
Armstrong
City
Lake
Reservoir
342
28.6
10.4
5­
10%
CI
YES
Bethany
MO
Old
City
Lake
Reservoir
191
39.7
10.2
5­
10%
CI
NO
Butler
MO
Butler
City
Lake
Reservoir
1965
31.5
6.6
5­
10%
CI
YES
Cameron
MO
Reservoirs
#
1
#
2
and
#
3
Reservoir
3274
26.7
8.2
5­
10%
CI
YES
Edina
MO
New
Lake
Reservoir
781
38.5
8.6
5­
10%
CI
YES
Freeman
MO
South
Grand
River
River
63850
36.2
5.6
5­
10%
CI
NO
Gallatin
MO
Lake
Viking
Reservoir
9049
32.3
7.1
5­
10%
CI
YES
Garden
City
MO
Lake
1
Reservoir
455
35.2
5.8
5­
10%
CI
YES
Gentry
MO
Middle
Fork
Water
Co.
Lake
Reservoir
4233
29.7
9.5
5­
10%
CI
NO
Labelle
MO
LaBelle
City
Lake
#
1
Reservoir
140
34.2
14.0
5­
10%
CI
YES
Lancaster
MO
North
Lake
Reservoir
728
29.5
6.1
5­
10%
CI
NO
Marceline
MO
New
Marceline
Reservoir
Reservoir
2455
24.3
12.6
5­
10%
CI
YES
Monroe
City
MO
South
Lake
Reservoir
668
25.5
6.2
5­
10%
CI
YES
Perryville
MO
Saline
Creek
River
36335
26.3
8.6
5­
10%
CI
NO
Shelbina
MO
Shelbina
Lake
Reservoir
1521
43.0
8.8
5­
10%
CI
YES
Smithville
MO
Smithville
Lake
Reservoir
133182
23.5
8.8
5­
10%
CI
YES
Vandalia
MO
Vandalia
Reservoir
Reservoir
3654
28.1
11.8
5­
10%
CI
YES
Alliance
OH
Deer
Creek
Lake
Reservoir
162028
21.9
8.5
5­
10%
CI
YES
Glouster
OH
Burr
Oak
Lake
Reservoir
20596
27.0
3.7
5­
10%
CI
YES
Somerset
OH
Somerset
Reservoir
Reservoir
572
31.9
8.3
5­
10%
CI
YES
Wellsville
OH
Little
Yellow
Creek
River
10832
29.5
9.2
5­
10%
CI
YES
Beavertown
PA
PL
638
Reservoir
3339
8.4
10.4
5­
10%
CI
NO
Phoenixville
PA
Schuylkill
River
River
771279
28.7
10.4
5­
10%
CI
NO
West
Chester
PA
East
Branch
of
Brandywine
River
River
72185
28.3
10.3
5­
10%
CI
YES
Davenport
IA
Mississippi
River
River
56626192
11.1
15.9
Cntl.
River
YES
­
108­

P1
(
primary)
Community
Water
Systems
only
CITY
STATE
SUPPLY
SYSTEM
NAME
TYPE
WATERSHE
D
AREA
(
acres)
WATERSHED
RUNOFF
RATING
WATERS
HED
%

CORN
INTENSIT
Y
STATISTICA
L
STRATUM
ACTIVATE
CARBON
Treatment
?

Moline
IL
Mississippi
River
River
56626192
11.1
15.9
Cntl.
River
YES
Rock
Island
IL
Mississippi
River
River
56626192
11.1
15.9
Cntl.
River
YES
Shipman
IL
Mississippi
River
River
115258084
23.1
24.2
Cntl.
River
YES
Evansville
IN
Ohio
River
River
68358056
21.8
5.6
Cntl.
River
YES
Mount
Vernon
IN
Ohio
River
River
68778138
21.8
5.7
Cntl.
River
YES
Atchison
KS
Missouri
River
River
266847707
10.1
5.1
Cntl.
River
NO
Kansas
City
KS
Missouri
River
River
268749082
10.2
5.1
Cntl.
River
YES
Leavenworth
KS
Missouri
River
River
267061176
10.1
5.1
Cntl.
River
YES
Minneapolis
MN
Mississippi
River
River
12527540
14.6
7.5
Cntl.
River
YES
St.
Cloud
MN
Mississippi
River
River
8774874
12.6
4.0
Cntl.
River
YES
Jefferson
City
MO
Missouri
River
River
319081997
13.1
5.7
Cntl.
River
YES
Louisiana
MO
Mississippi
River
River
90230044
17.9
22.1
Cntl.
River
YES
St.
Louis
MO
Mississippi
River
River
443533492
15.3
10.1
Cntl.
River
YES
St.
Louis
MO
Missouri
River
River
332845687
29.2
5.6
Cntl.
River
YES
Blair
NE
Missouri
River
River
203739516
9.3
3.3
Cntl.
River
YES
Hartington
NE
Lewis
&
Clark
Lake
(
Missouri
River)
Reservoir
177705449
7.4
0.8
Cntl.
River
NO
Omaha
NE
Missouri
River
River
204687766
9.4
3.5
Cntl.
River
YES
East
Liverpool
OH
Ohio
River
River
14999469
17.7
2.5
Cntl.
River
YES
Chicago
IL
Lake
Michigan
Lake
28845270
14.4
8.9
Great
Lakes
YES
Michigan
City
IN
Lake
Michigan
Lake
28845270
14.4
8.9
Great
Lakes
YES
Beaver
Bay
MN
Lake
Superior
Lake
10719768
7.2
0.0
Great
Lakes
NO
Cleveland
OH
Lake
Erie
Lake
63168475
14.2
8.2
Great
Lakes
YES
Willoughby
OH
Lake
Erie
Lake
63168475
14.2
8.2
Great
Lakes
YES
Cudahy
WI
Lake
Michigan
Lake
28845270
14.4
8.9
Great
Lakes
YES
­
109­

P1
(
primary)
Community
Water
Systems
only
CITY
STATE
SUPPLY
SYSTEM
NAME
TYPE
WATERSHE
D
AREA
(
acres)
WATERSHED
RUNOFF
RATING
WATERS
HED
%

CORN
INTENSIT
Y
STATISTICA
L
STRATUM
ACTIVATE
CARBON
Treatment
?

Oak
Creek
WI
Lake
Michigan
Lake
28845270
14.4
8.9
Great
Lakes
YES
Port
Washington
WI
Lake
Michigan
Lake
28845270
14.4
8.9
Great
Lakes
YES
P1
(
primary)
Community
Water
Systems
only
Site
ID
(
ARP)
CITY
STATE
SUPPLY
SYSTEM
NAME
TYPE
WATERSH
ED
AREA
(
acres)
WATERSHED
RUNOFF
RATING
WATERS
HED
%

CORN
INTENSIT
Y
STATISTICAL
STRATUM
ACTIVATE
CARBON
Treatment
?

651­

NE­
DE
Newark
DE
White
Clay
Creek
River
43629
NA
10.4
5­
10%
CI
652­

WI­
DE
Wilmington
DE
Red
&
White
Clay
Creek
River
100409
NA
10.6
5­
10%
CI
544­

BL­
IA
Bloomfield
IA
Lake
Fisher
Reservoir
1458
390
mg
13.9
11­
20%
CI
577­

RA­
IA
Centerville
IA
Lake
Rathbun
Reservoir
353792
Unknown
13.2
11­
20%
CI
548­

CH­
IA
Chariton
IA
Lake
Ellis
and
Lake
Morris
Reservoir
6453
598
mg
10.6
11­
20%
CI
553­

CO­
IA
Corning
IA
Lake
Binder
Lake
2126
85
acres
23
>
20%
CI
556­

DA­
IA
Davenport
IA
Mississippi
River
River
56626192
NA
15.9
Continental
Rivers
557­

DM­
IA
Des
Moines
IA
Raccoon
River
and
Infiltration
Galleries
River
2304810
Unknown
39.4
>
20%
CI
562­
ICIA
Iowa
City
IA
Iowa
River
River
2099081
NA
40.3
>
20%
CI
565­

LA­
IA
Lamoni
IA
Home
Lake
(
Pond)
Reservoir
321
65
mg
8.7
5­
10%
CI
566­

LE­
IA
Lenox
IA
Lenox
West
Lake
Reservoir
100
13
acres
19.8
11­
20%
CI
­
110­

569­
MIIA
Milford
IA
West
Lake
Okoboji
Lake
14866
NA
32.6
>
20%
CI
570­

MO­
IA
Montezuma
IA
Diamond
Lake
Reservoir
2724
125
acres
250
mg
33.3
>
20%
CI
571­

MA­
IA
Mount
Ayr
IA
Loch
Ayr
Reservoir
Reservoir
2563
78
acres
13.5
11­
20%
CI
572­

MP­
IA
Mount
Pleasant
IA
Skunk
River
River
2599367
NA
34.2
>
20%
CI
547­

CW­
IA
Okoboji
IA
West
Okoboji
Lake
Lake
14866
NA
32.6
>
20%
CI
574­

OS­
IA
Osceola
IA
West
Lake
Reservoir
6241
300
acres
13.5
11­
20%
CI
575­

OT­
IA
Ottumwa
IA
Des
Moines
River
River
8569564
NA
35.5
>
20%
CI
576­

PA­
IA
Panora
IA
Middle
Racoon
River
River
265272
NA
41.1
>
20%
CI
579­

SL­
IA
Spirit
Lake
IA
Spirit
Lake
Lake
43135
6000
acres
36.2
>
20%
CI
582­

WI­
IA
Winterset
IA
Cedar
Lake
Reservoir
10443
886
acreft
21.7
>
20%
CI
170­

AL­
IL
Altamont
IL
Altamont
New
Reservoir
Reservoir
521
56
acres
28.5
>
20%
CI
261­

AP­
IL
Alto
Pass
IL
Little
Cedar
Lake
Reservoir
19625
115
acres
7.3
5­
10%
CI
601­

BL­
IL
Blandinsville
IL
LaHarpe
Creek
River
8779
7
acre­
ft
35.5
>
20%
CI
152­

BR­
IL
Breese
IL
Shoal
Creek
River
480358
15
mg
25.2
>
20%
CI
213­

CA­
IL
Carlinville
IL
Carlinville
Lake
I
Reservoir
15706
Unknown
25
>
20%
CI
184­

CA­
IL
Carthage
IL
Carthage
Lake
Reservoir
1756
48
acres
28.4
>
20%
CI
225­

CE­
IL
Centralia
IL
Raccoon
Lake
Reservoir
30293
Unknown
12.2
11­
20%
CI
155­

CH­
IL
Charleston
IL
Lake
Charleston
Reservoir
1198
935
mg
34.4
>
20%
CI
159­

CH­
IL
Chicago
IL
Lake
Michigan
Lake
28845270
NA
8.9
Great
Lakes
149­

CC­
IL
Clay
City
IL
Little
Wabash
River
River
518175
3.4
mg
26.9
>
20%
CI
­
111­

242­

CO­
IL
Coulterville
IL
Coulterville
Lake
Reservoir
449
61
mg
15.2
11­
20%
CI
212­

DE­
IL
Decatur
IL
Lake
Decatur
Reservoir
602057
6500
mg
41.5
>
20%
CI
197­

EL­
IL
Elgin
IL
Fox
River
River
953176
NA
20.3
>
20%
CI
269­

FA­
IL
Fairfield
IL
Little
Wabash
River
River
1169567
90
mg
25
>
20%
CI
172­

FA­
IL
Farina
IL
East
Fork
of
Kaskaskia
River
River
2959
30
mg
17.1
11­
20%
CI
150­

FL­
IL
Flora
IL
Little
Wabash
River
River
491311
Unknown
27.3
>
20%
CI
263­

GO­
IL
Georgetown
IL
Little
Vermillion
River
River
106395
NA
39.5
>
20%
CI
214­
GIIL
Gillespie
IL
Old
Gillespie
Lake
Reservoir
2966
250
mg
25
>
20%
CI
182­

GE­
IL
Greenfield
IL
Greenfield
Lake
Reservoir
724
50
acres
9
ft
deep
29.1
>
20%
CI
222­
HIIL
Highland
IL
Silver
Lake
Reservoir
30593
550
acres
17.5
11­
20%
CI
603­

BL­
IL
Hudson
IL
Lake
Bloomington
Reservoir
41942
7380
acre­
ft
44.4
>
20%
CI
198­

KA­
IL
Kankakee
IL
Kankakee
River
River
2952111
1.25
mg
37.4
>
20%
CI
233­
LIIL
Litchfield
IL
Lake
Lou
Yeager
Reservoir
69219
1500
acres
30.1
>
20%
CI
608­

SU­
IL
Mascoutah
IL
Kaskaskia
River
River
2844480
Unknown
26.3
>
20%
CI
157­

MA­
IL
Mattoon
IL
Lake
Paradise
Reservoir
11916
900
mg
34.5
>
20%
CI
248­

MO­
IL
Moline
IL
Mississippi
River
River
56626192
NA
15.9
Continental
Rivers
268­

NA­
IL
Nashville
IL
City
of
Nashville
Reservoir
Reservoir
1013
77
mg
23.1
>
20%
CI
166­

NE­
IL
Neoga
IL
Lake
Mattoon
Reservoir
34849
Unknown
33.5
>
20%
CI
606­

KA­
IL
New
Athens
IL
Kaskaskia
River
River
3274132
NA
25.4
>
20%
CI
258­

NB­
IL
New
Berlin
IL
Spring
Creek
River
16852
38
mg
35.2
>
20%
CI
­
112­

158­

OA­
IL
Oakland
IL
Lake
Oakland
Reservoir
6909
26
acres
28
mg
39.7
>
20%
CI
245­

OL­
IL
Olney
IL
East
Fork
Lake
Reservoir
6644
5500
mg
28.8
>
20%
CI
217­

PA­
IL
Palmyra
IL
Palmyra­
Modesto
Lake
Reservoir
826
35
acres
25
>
20%
CI
147­

PA­
IL
Pana
IL
Lake
Pana
Reservoir
4545
890
mg
32.3
>
20%
CI
168­

PA­
IL
Paris
IL
Twin
Lakes
Reservoir
11733
900
mg
38.7
>
20%
CI
239­
PIIL
Pittsfield
IL
Lake
Pittsfield
Reservoir
6971
Unknown
22.6
>
20%
CI
249­

RO­
IL
Rock
Island
IL
Mississippi
River
River
56626192
Unknown
15.9
Continental
Rivers
228­

SA­
IL
Salem
IL
Salem
Reservoir
Reservoir
2452
75
acres
12.2
11­
20%
CI
219­

SH­
IL
Shipman
IL
Shipman
Reservoir
Reservoir
427
13
acres
(
x
9
ft)
25
>
20%
CI
221­

AL­
IL
Shipman
IL
Mississippi
River
River
11525808
4
NA
24.2
Continental
Rivers
143­

SO­
IL
Sorento
IL
Sorento
Lake
Reservoir
376
Unknown
15.8
11­
20%
CI
244­

SP­
IL
Sparta
IL
South
City
Lake
Reservoir
480
33
acres
15.2
>
20%
CI
259­

SP­
IL
Springfield
IL
Lake
Springfield
Lake
162178
17
000
mg
34.9
>
20%
CI
169­

WS­
IL
West
Salem
IL
West
Salem
Reservior
&
shale
pit
Reservoir
614
22
acres/
2
acres
26.1
>
20%
CI
183­

WH­
IL
White
Hall
IL
White
Hall
Reservoir
Reservoir
613
200
mg
51
acres
29.1
>
20%
CI
355­

SC­
IN
Austin
IN
Muscatatuck
River
River
223967
NA
11.8
11­
20%
CI
307­

BA­
IN
Batesville
IN
Biscoff
Reservoir
Reservoir
2916
700
mg
200
acres
19.5
11­
20%
CI
310­

BO­
IN
Borden
IN
Packwood
Branch
Reservoir
Reservoir
1275
445
acreft
10.8
5­
10%
CI
344­

DU­
IN
Dubois
IN
Patoka
Lake
Reservoir
108655
8800
acres
8.4
5­
10%
CI
314­
Evansville
IN
Ohio
River
River
68358056
NA
5.6
Continental
­
113­

EV­
IN
Rivers
315­

FE­
IN
Ferdinand
IN
Old
Lake
(
No.
1)
Reservoir
105
15
mg
26.2
>
20%
CI
362­

FW­
IN
Fort
Wayne
IN
St.
Joseph
River
River
657980
Unknown
18.6
11­
20%
CI
320­

HO­
IN
Holland
IN
New
Holland
Lake
Reservoir
348
20
acres
x
12
feet
26.2
>
20%
CI
328­

KO­
IN
Kokomo
IN
Wildcat
Creek
River
121637
NA
38
>
20%
CI
330­

LO­
IN
Logansport
IN
Eel
River
River
524144
NA
28.3
>
20%
CI
332­

MC­
IN
Michigan
City
IN
Lake
Michigan
Lake
28845270
NA
8.9
Great
Lakes
334­
MIIN
Mitchell
IN
East
Fork
of
the
White
River
River
2470938
NA
26.9
>
20%
CI
335­

MV­
IN
Mount
Vernon
IN
Ohio
River
River
68778138
NA
5.7
Continental
Rivers
340­

NV­
IN
North
Vernon
IN
Vernon
Fork
of
Muscatatuck
River
River
68241
NA
21
>
20%
CI
341­

OC­
IN
Oakland
City
IN
Old
Lake
Lake
83
Unknown
33.8
>
20%
CI
343­

PA­
IN
Paoli
IN
Lick
Creek
River
13424
NA
8.8
5­
10%
CI
345­
RIIN
Richmond
IN
Middle
Fork
Reservoir
Lake
30825
1.01
bg
27.2
>
20%
CI
346­

SA­
IN
Salem
IN
Lake
John
Hay
Reservoir
5797
211
acres
11.9
11­
20%
CI
348­

SC­
IN
Santa
Claus
IN
Christmas
Lake
Reservoir
1583
210
acreft
21.8
>
20%
CI
350­

SC­
IN
Scottsburg
IN
Scottsburg
Reservoir
Reservoir
1977
100
acres
11.3
11­
20%
CI
351­

SE­
IN
Seymour
IN
East
Fork
of
the
White
River
River
1516709
NA
33.8
>
20%
CI
352­

SP­
IN
Speedway
IN
Big
Eagle
Creek
River
119080
24
000
acre
ft
26.8
>
20%
CI
354­

SM­
IN
St.
Meinrad
IN
Lake
Benet
Reservoir
135
Unknown
4.5
5­
10%
CI
321­

WA­
IN
Warsaw
IN
Center
Lake
Reservoir
444
120
acres
30.3
>
20%
CI
359­
Westport
IN
Sand
Creek
River
60170
Unknown
43.1
>
20%
CI
­
114­

WE­
IN
25­
ATKS
Atchison
KS
Missouri
River
River
26684770
7
NA
5.1
Continental
Rivers
58­
GAKS
Garnett
KS
Crystal
Lake
Reservoir
386
80
acre­
ft
6.1
5­
10%
CI
73­
HOKS
Horton
KS
Delaware
River
River
91634
Unknown
11.5
11­
20%
CI
71­
KCKS
Kansas
City
KS
Missouri
River
River
26874908
2
NA
5.1
Continental
Rivers
77­
LEKS
Leavenworth
KS
Missouri
River
River
26706117
6
11
mg
5.1
Continental
Rivers
89­
MIKS
Milford
KS
Milford
Lake
Reservoir
15963347
16
000
acres
9.6
5­
10%
CI
114­
RIKS
Richmond
KS
Richmond
City
Lake
Reservoir
557
11
acres
X
35
ft
max
5.1
5­
10%
CI
125­

TO­
KS
Topeka
KS
Kansas
River
River
36446269
NA
8.8
5­
10%
CI
129­

VF­
KS
Valley
Falls
KS
Delaware
River
River
570021
Unknown
7.5
5­
10%
CI
23­
WEKS
Westphalia
KS
Lake
(
No
Name)
Reservoir
1652
Unknown
4.8
5­
10%
CI
696­

BA­
MD
Bel
Air
MD
Winter's
Run
River
23264
NA
8.2
5­
10%
CI
676­

EL­
MD
Elkton
MD
Big
Elk
Creek
River
39985
Unknown
9.7
5­
10%
CI
683­

FR­
MD
Frederick
MD
Monocacy
River
River
456687
NA
12
5­
10%
CI
684­

FR­
MD
Frederick
MD
Monocacy
River
River
456040
NA
8.9
5­
10%
CI
699­

HG­
MD
Havre
de
Grace
MD
Susquehanna
River
River
17629428
NA
5.5
5­
10%
CI
702­

LA­
MD
Silver
Spring
MD
Howard
Duckett
Reservoir
(
Rocky
Gorge
Re
Reservoir
85109
6500
mg
5.6
5­
10%
CI
279­

BB­
MN
Beaver
Bay
MN
Lake
Superior
Lake
10719768
Unknown
0
Great
Lakes
277­
MIMN
Minneapolis
MN
Mississippi
River
River
12527540
Unknown
7.5
Continental
Rivers
275­
MOMoorhead
MN
Red
River
River
4309787
Unknown
10.8
5­
10%
CI
­
115­

MN
296­

SC­
MN
St.
Cloud
MN
Mississippi
River
River
8774874
Unknown
4
Continental
Rivers
1039­

AR­
MO
Armstrong
MO
Armstrong
City
Lake
Reservoir
342
5­
7
acres
10.4
5­
10%
CI
1003­

BE­
MO
Bethany
MO
Old
City
Lake
Reservoir
191
17
acres
10.2
5­
10%
CI
1005­

BU­
MO
Butler
MO
Butler
City
Lake
Reservoir
1965
60
acres
200
mg
6.6
5­
10%
CI
1006­

CA­
MO
Cameron
MO
Reservoirs
#
1
#
2
and
#
3
Reservoir
3274
#
3
:
115
acres
8.2
5­
10%
CI
1009­

CO­
MO
Concordia
MO
Edwin
A.
Pape
Lake
Reservoir
5507
1120
mg
20.6
>
20%
CI
1046­

ED­
MO
Edina
MO
New
Lake
Reservoir
781
60.6
acres
8.6
5­
10%
CI
1071­

EWMO
Ewing
MO
Lewis
County
Water
District
Lake
Reservoir
684
140
mg
14
11­
20%
CI
1035­

FR­
MO
Freeman
MO
South
Grand
River
River
63850
130.68
mg
/
20
acres
5.6
5­
10%
CI
1038­

GA­
MO
Gallatin
MO
Lake
Viking
Reservoir
9049
640
acres
7.1
5­
10%
CI
1013­

GC­
MO
Garden
City
MO
Lake
1
Reservoir
455
65
mg
5.8
5­
10%
CI
1098­

GE­
MO
Gentry
MO
Middle
Fork
Water
Co.
Lake
Reservoir
4233
160
acres
9.5
5­
10%
CI
1016­

HI­
MO
Higginsville
MO
Higginsville
City
Lake
Reservoir
3547
550
mg
20.6
>
20%
CI
1076­

JC­
MO
Jefferson
City
MO
Missouri
River
River
31908199
7
N/
A
5.7
Continental
Rivers
1053­

LA­
MO
Labelle
MO
LaBelle
City
Lake
#
1
Reservoir
140
Unknown
14
5­
10%
CI
1054­

LA­
MO
Lancaster
MO
North
Lake
Reservoir
728
30
acres
6.1
5­
10%
CI
1058­

LO­
MO
Louisiana
MO
Mississippi
River
River
90230044
NA
22.1
Continental
Rivers
1060­

MA­
MO
Marceline
MO
New
Marceline
Reservoir
Reservoir
2455
759
mg
12.6
5­
10%
CI
1065­
Monroe
City
MO
South
Lake
Reservoir
668
304.3
6.2
5­
10%
CI
­
116­

MCMO
acre­
ft
1082­

PE­
MO
Perryville
MO
Saline
Creek
River
36335
NA
8.6
5­
10%
CI
1066­

SH­
MO
Shelbina
MO
Shelbina
Lake
Reservoir
1521
209
mg
8.8
5­
10%
CI
1032­

SM­
MO
Smithville
MO
Smithville
Lake
Reservoir
133182
1
145
acres
8.8
5­
10%
CI
1091­

SL­
MO
St.
Louis
MO
Mississippi
River
River
44353349
2
NA
10.1
Continental
Rivers
1092­

SL­
MO
St.
Louis
MO
Missouri
River
River
33284568
7
NA
5.6
Continental
Rivers
1067­

TR­
MO
Trenton
MO
Thompson
River
River
963925
200
mg
10.8
11­
20%
CI
1069­

VA­
MO
Vandalia
MO
Vandalia
Reservoir
Reservoir
3654
13
mg
43
acres
11.8
5­
10%
CI
1070­

WYMO
Wyaconda
MO
Wyaconda
City
Lake
Reservoir
208
74
acre­
ft
15.3
11­
20%
CI
305­

BL­
NE
Blair
NE
Missouri
River
River
20373951
6
NA
3.3
Continental
Rivers
304­

LC­
NE
Hartington
NE
Lewis
&
Clark
Lake
(
Missouri
River)
Reservoir
17770544
9
31000
acre­
ft
0.8
Continental
Rivers
303­

OM­
NE
Omaha
NE
Missouri
River
River
20468776
6
NA
3.5
Continental
Rivers
301­

BL­
NE
Plattsmouth
NE
Beaver
Lake
Reservoir
7397
325
acres
26.1
>
20%
CI
371­

AL­
OH
Alliance
OH
Deer
Creek
Lake
Reservoir
162028
1000
mg
8.5
5­
10%
CI
372­

AR­
OH
Archbold
OH
Tiffin
River
River
208202
300
mg
23.9
>
20%
CI
374­

AT­
OH
Attica
OH
Honey
Creek
River
46710
15
mg
24.2
>
20%
CI
386­

BG­
OH
Bowling
Green
OH
Maumee
River
River
3977343
170
mg
23.1
>
20%
CI
394­

CE­
OH
Cedarville
OH
Massies
Creek
River
31764
16­
18
mg
27.2
>
20%
CI
395­

CE­
OH
Celina
OH
Grand
Lake
St
Marys
Reservoir
72549
17
500
acres
6­
7
ft
30.9
>
20%
CI
­
117­

400­

CM­
OH
Cleveland
OH
Lake
Erie
Lake
63168475
NA
8.2
Great
Lakes
403­

CD­
OH
Columbus
OH
Scioto
River
River
665366
15000
mg
and
4000
mg
21.4
>
20%
CI
408­

DE­
OH
Defiance
OH
Maumee
River
River
1395515
NA
21.5
>
20%
CI
412­

DE­
OH
Delta
OH
Bad
Creek
River
22000
400
mg
and
108
mg
33.6
>
20%
CI
413­

EL­
OH
East
Liverpool
OH
Ohio
River
River
14999469
NA
2.5
Continental
Rivers
410­

DA­
OH
Galena
OH
Alum
Creek
Reservoir
Reservoir
82605
6300
acres
16.5
11­
20%
CI
470­

BO­
OH
Glouster
OH
Burr
Oak
Lake
Reservoir
20596
5800
acre­
ft
3.7
5­
10%
CI
443­
LIOH
Lima
OH
Auglaize
River
River
131174
5000
mg
24.3
>
20%
CI
451­

ML­
OH
McClure
OH
Maumee
River
River
3777748
NA
23
>
20%
CI
452­

MC­
OH
McComb
OH
Rader
Creek
River
668
163
mg
23.4
>
20%
CI
454­

ME­
OH
Metamora
OH
Ten
Mile
Creek
River
3174
70
mg
32.4
>
20%
CI
455­

MO­
OH
Monroeville
OH
West
Branch
Huron
River
River
138245
NA
18.7
11­
20%
CI
461­

NL­
OH
New
London
OH
Buck
Creek
River
40614
1500
mg
17.3
11­
20%
CI
485­

OT­
OH
Ottawa
OH
Blanchard
River
River
394516
116
mg
23.5
>
20%
CI
487­

PA­
OH
Paulding
OH
Flatrock
Creek
River
109270
NA
21.4
11­
20%
CI
506­

SO­
OH
Somerset
OH
Somerset
Reservoir
Reservoir
572
22
mg
8.3
5­
10%
CI
511­

SU­
OH
Sunbury
OH
Big
Walnut
Creek
River
50886
62
mg
16.5
11­
20%
CI
518­

US­
OH
Upper
Sandusky
OH
Upper
Sandusky
Reservoir
Reservoir
894
90
mg
23.8
>
20%
CI
519­

VW­
OH
Van
Wert
OH
Town
Creek
River
16385
780
mg
29.2
>
20%
CI
­
118­

527­

WE­
OH
Wellsville
OH
Little
Yellow
Creek
River
10832
180
mg
9.2
5­
10%
CI
537­

WMOH
West
Milton
OH
Stillwater
River
River
427302
NA
28.3
>
20%
CI
530­

WE­
OH
Westerville
OH
Alum
Creek
River
95314
NA
16.4
11­
20%
CI
531­

WI­
OH
Willard
OH
Huron
River
River
46081
2200
mg
18.2
11­
20%
CI
532­

WI­
OH
Williamsburg
OH
East
Fork
of
the
Little
Miami
River
River
149474
13
mg
18.1
11­
20%
CI
437­

LC­
OH
Willoughby
OH
Lake
Erie
Lake
63168475
NA
8.2
Great
Lakes
534­

WI­
OH
Wilmington
OH
Caesar's
Creek
Lake
Reservoir
147651
40
000
mg
27.1
>
20%
CI
865­

SP­
PA
Beavertown
PA
PL
638
Reservoir
3339
81
mg
10.4
5­
10%
CI
636­

CA­
PA
Carlisle
PA
Conodoguinet
Creek
River
242629
NA
12.6
11­
20%
CI
596­

DE­
PA
Denver
PA
Cocalico
Creek
River
12201
Unknown
26.4
>
20%
CI
593­

HE­
PA
Hummelston
PA
Swatara
River
River
284337
NA
12.1
11­
20%
CI
997­

WE­
PA
Mechanicsburg
PA
Conodoguinet
Creek
River
293855
NA
12.5
11­
20%
CI
622­

NH­
PA
New
Holland
PA
New
Holland
Reservoir
Reservoir
704
30
mg
27.4
>
20%
CI
737­

AW­
PA
Norristown
PA
Schuylkill
River
River
1133118
NA
9.2
11­
20%
CI
729­

PH­
PA
Phoenixville
PA
Schuylkill
River
River
771279
NA
10.4
5­
10%
CI
769­

RE­
PA
Reading
PA
Lake
Ontellaunee
Reservoir
120883
3880
mg
13.1
11­
20%
CI
730­

WC­
PA
West
Chester
PA
East
Branch
of
Brandywine
River
River
72185
Unknown
10.3
5­
10%
CI
13­
APWI
Appleton
WI
Lake
Winnebago
Lake
3776966
NA
12.9
>
20%
CI
4­
SMIWI
Cudahy
WI
Lake
Michigan
Lake
28845270
2
mg
8.9
Great
Lakes
17­
ME­
Menasha
WI
Lake
Winnebago
Lake
3776966
Unknown
12.9
>
20%
CI
­
119­

WI
7­
OCWI
Oak
Creek
WI
Lake
Michigan
Lake
28845270
NA
8.9
Great
Lakes
18­
OKWI
Oshkosh
WI
Lake
Winnebago
Lake
3776966
NA
12.9
>
20%
CI
10­
PWWI
Port
Washington
WI
Lake
Michigan
Lake
28845270
NA
8.9
Great
Lakes
­
120­
­
121­

APPENDIX
12.5.
Site
Selection
for
ARP
Monitoring
Studies
12.5.1.
Surface
Drinking
Water
Site
Selection
(
SDWS
Study)

Language
and
subject
headings
below
are
directly
extracted
from:
Hackett,
A.
(
2000)
Surface
Drinking
Water
Monitoring
Program
for
Acetochlor
and
Other
Corn
Herbicides:
Site
Selection
and
Data
Collection.
Lab
Project
Number:
SWM1100.
Unpublished
study
prepared
by
Monsanto
Company.

1.0
INTRODUCTION
AND
SUMMARY
Acetochlor
is
a
selective
herbicide
for
control
of
annual
grasses
and
broadleaf
weeds
in
corn.
Acetochlor
was
registered
on
March
11,
1994,
by
the
Acetochlor
Registration
Partnership
(
ARP),
consisting
of
Monsanto
Co.
and
Zeneca,
Inc.,
and
is
marketed
under
trade
names
such
as
Harness7
(
Monsanto)
and
Surpass7
(
Zeneca).
Acetochlor
is
registered
for
use
in
42
states
and
the
District
of
Columbia,
and
about
80%
of
yearly
production
is
in
the
mid­
western
United
States.

EPA
and
the
ARP
defined
conditions
of
registration
for
acetochlor.
One
requirement
of
these
conditions
was
to
conduct
a
monitoring
program
to
evaluate
the
extent
of
contamination
of
surfacedrinking
water
with
acetochlor
over
a
five­
year
period.
EPA
and
the
ARP
agreed
that
if
acetochlor
was
found
above
mutually
agreed
trigger
levels
at
a
site,
mitigation
would
be
required.
If
found
at
numerous
sites,
its
registration
could
be
canceled.

The
objective
of
the
monitoring
program
is
to
determine
seasonal
and
annualized
mean
concentrations
of
acetochlor
and
other
major
corn
herbicides
in
finished
drinking
water
derived
from
surface
water
sources.
The
program
consists
of
several
phases
including:
community
water
system
(
CWS)
selection
and
data
collection;
sampling
mechanics;
execution
of
sampling;
residue
analysis;
and
reporting
of
results.
This
report
describes
the
CWS
selection
and
data
collection
phase
of
the
program.
This
portion
of
the
study
was
conducted
by
Stone
Environmental
Inc.
(
SEI,
Montpelier,
VT)
in
conjunction
with
the
ARP.
Details
of
sampling
mechanics,
execution
of
sampling,
and
initial
analytical
results
will
be
reported
in
the
first
annual
interim
report
due
to
EPA
by
January
31,
1996.

A
total
of
175
CWSs
in
nine
mid­
western
and
three
mid­
Atlantic
states
were
selected
for
the
program.
The
selection
process
was
designed
to
include
a
wide
array
of
CWSs
with
watersheds
in
areas
of
corn
production,
with
an
emphasis
on
including
worst­
case
watersheds
i.
e.,
smaller
watersheds
(
not
on
the
Great
Lakes
and
Continental
Rivers)
in
areas
of
high
corn
production.
These
watersheds
are
expected
to
have
higher
concentrations
of
acetochlor
after
runoff
events
than
larger
watersheds
which
drain
areas
of
both
high
and
low
corn
production,
because
dilution
would
be
greater
for
CWSs
taking
water
from
the
Great
Lakes
and
Continental
Rivers.
Data
were
collected
to
characterize
each
community
water
system
included
in
the
program.

The
steps
for
the
CWS
selection
and
characterization
process
are
summarized
below:
­
122­

1)
Identification
of
all
public
CWSs
that
use
surface
water
in
the
following
12
states:
Illinois,
Indiana,
Iowa,
Minnesota,
Nebraska,
Kansas,
Wisconsin,
Ohio,
Missouri,
Pennsylvania,
Maryland,
and
Delaware.

2)
Identification
of
all
CWSs
that
belong
to
the
target
population.

Target
Population
­
All
CWSs
in
the
12
states
that:

$
use
only
surface
water,
or
can
discretely
sample
surface
water,

$
are
willing
to
cooperate
and
$
have
a
corn
intensity
(
for
smaller
watersheds
that
do
not
have
an
intake
on
a
Great
Lake
or
Continental
River)
greater
than
or
equal
to
5%,
where
corn
intensity
is
the
ratio
of
acreage
of
harvested
corn
to
total
acreage
in
the
upstream
watershed.

3)
Separation
of
the
target
population
of
CWSs
into
disjoint
(
nonoverlapping)
strata
based
on
the
size
of
the
watershed,
the
corn
intensity
(
for
smaller
watersheds),
and
State
that
the
system
is
in:

$
State
$
size
of
watershed
(
three
major
subdivisions)
Great
Lakes
Continental
Rivers
(
Missouri,
Mississippi,
Ohio
Rivers)
Smaller
Rivers
and
Lakes
$
corn
intensity
(%
corn
planted
in
total
area
of
watershed)
(
three
major
subdivisions)
5­
10%
CI
11­
20%
CI
>
20%
CI
4)
Determination
of
the
number
of
CWSs
to
be
selected
from
each
stratum.
The
focus
was
on
strata
containing
CWS
watersheds
which
are
expected
to
have
higher
levels
of
acetochlor
after
runoff
events,
based
on
the
size
of
the
watershed
and
its
corn
intensity.
A
higher
percentage
of
CWSs
from
these
strata
were
chosen.

5)
Random
selection
(
using
random
number
generation)
of
the
appropriate
number
of
CWSs
from
each
stratum.
All
CWSs
meeting
the
target
population
criteria
were
selected
from
the
identified
strata
(
for
example,
the
>
20%
corn
intensity,
smaller
watershed
strata).
A
total
of
175
CWSs
were
required
for
the
study.

6)
Collection
of
information
for
each
selected
CWS
regarding
intake
location,
sources
of
water,
treatment,
customer
information,
point
of
finished
water
sampling,
soil
types,
and
corn
intensity
of
the
watershed(
s)
for
that
system.

7)
Removal
of
systems
that
did
not
meet
target
population
criteria
based
on
additional
data
collected.
Systems
were
replaced
in
the
same
stratum
and
state,
if
possible,
by
additional
random
selection
from
the
stratum.
If
there
were
no
systems
available
in
the
same
stratum,
then
a
system
was
randomly
selected
from
another
stratum
with
available
CWSs.

8)
Generation
of
maps
of
watersheds
for
each
CWS.
Data
entry
into
a
Geographical
Information
System
(
GIS).
­
123­

The
final
distribution
of
selected
CWSs
by
state,
size,
and
corn
intensity
is
presented
in
Table
1.
The
top
number
in
each
stratum
(
delineated
by
a
box)
is
the
total
number
of
CWSs
meeting
the
target
population
criteria
in
that
stratum.
The
middle
number
in
each
stratum
is
the
number
of
CWSs
selected
from
that
stratum,
and
the
bottom
percentage
is
the
percentage
of
CWSs
selected
from
the
total
population
in
that
stratum.
The
highest
percentage
of
CWSs,
100%
of
the
available
CWSs,
were
selected
from
the
>
20%
corn
intensity
strata,
66%
were
selected
from
the
11­
20%
corn
intensity
strata,
49%
from
the
5­
10%
corn
intensity
strata,
43%
from
the
Continental
River
strata,
and
14%
from
the
Great
Lakes
strata.
The
bulk
of
the
selected
CWSs
are
located
on
watersheds
with
higher
corn
intensity,
but
the
program
also
includes
CWSs
representative
of
other
watersheds
in
corn
growing
areas.
Data
regarding
population
and
CWS
source(
s)
were
collected,
watersheds
for
the
175
selected
CWSs
were
mapped,
and
watershed
areas
and
corn
intensities
were
determined.
Each
of
the
175
systems
was
visited
and
inspected
to
confirm
data.
Characteristics
of
the
175
selected
CWSs
including
total
population
for
all
the
CWSs,
watershed
areas
and
corn
intensities
for
all
watersheds,
are
summarized
in
Table
2.
The
175
CWSs
serve
populations
ranging
from
167
to
5,100,000
people.
The
watersheds
associated
with
the
175
CWSs
cover
areas
ranging
from
83
to
443,533,492
acres.
All
of
the
175
CWSs
in
the
program
use
some
type
of
conventional
treatment
(
coagulation,
flocculation,
sedimentation,
and
filtration)
for
their
water.
There
are
21
CWSs
using
a
granular
activated
carbon
(
GAC)
treatment
and
111
CWSs
using
a
powdered
activated
carbon
(
PAC)
treatment.
Most
of
the
GAC
units
are
used
by
systems
in
the
>
20%
and
11­
20%
corn
intensity
strata,
strata
that
cover
the
higher
corn­
growing
areas.
A
total
of
124
CWSs
have
at
least
one
reservoir.
Maps
showing
corn
intensity
in
the
12
states,
watershed
boundaries,
and
intake
locations
are
displayed
in
Figures
1,
2,
and
3,
respectively.
A
table
of
CWSs
and
their
characteristics
is
in
Appendix
A.
State
maps,
individual
site
data
sheets
and
maps
for
each
system
are
in
Appendix
C,
and
are
grouped
by
state.
The
state
maps
include
a
map
of
watershed
boundaries,
and
a
map
of
intake
locations
with
site
codes
for
each
state.
The
site
data
sheets
provide
information
on
treatment
method,
surface
water
source
(
s),
population
served,
training
dates
of
CWS
samplers,
corn
intensity,
location
of
intake,
soil
texture
and
hydrologic
group.
Maps
of
all
watersheds
are
included
with
each
site
data
sheet.
Based
on
the
watershed
maps
and
the
data
collected
on
CWS
sources,
watershed
areas,
corn
intensities,
population,
and
treatment
methods,
the
175
selected
CWSs
represent
a
diverse
group
of
sampling
sites.

2.0
MATERIALS
AND
METHODS
2.1
Site
Selection
A
total
of
175
surface
water
CWSs
in
12
states
(
IL,
IN,
IA,
KS,
MN,
NE,
WI,
OH,
MO,
PA,
MD,
and
DE)
were
selected
for
the
surface
water
program.
Procedures
for
the
identification
and
selection
of
CWSs
are
described
in
sections
2.1.1
­
2.1.4
of
this
report.

2.1.1
Identification
of
Public
CWSs
Lists
of
public
Community
Water
Systems
that
use
surface
water
in
the
12
states
were
obtained
from
state
agencies
and
the
American
Water
Works
Association
(
AWWA).
1
The
total
number
of
surface
water
CWSs
originally
identified
in
each
of
the
12
states
is
shown
in
Table
3.

2.1.2
Identification
of
CWSs
in
the
Target
Population
­
124­

Two
procedures
were
used
to
identify
which
of
the
CWSs
in
each
state
fell
into
the
target
population:

1)
Information
was
obtained
by
telephone
interviews
with
operators
from
each
of
the
CWSs.

2)
Subsequently,
for
smaller
watersheds,
corn
intensity
for
each
CWS
watershed
was
determined.
Corn
intensity
was
used
as
a
surrogate
for
acetochlor
usage
for
two
principal
reasons.
Firstly,
acetochlor
was
only
registered
in
1994
and
use
of
first­
year
sales
data
would
not
be
an
accurate
predictor
of
1995
and
following
years=
use.
To
achieve
the
use­
reduction
targets
specified
in
the
agreement,
acetochlor
will
eventually
become
a
major
corn
herbicide,
so
corn
use
is
an
excellent
surrogate.
Secondly,
because
Monsanto
and
Zeneca
are
competing
in
the
market
place
with
separate
products,
sharing
sales
data
on
a
local
level
could
be
viewed
as
anti­
competitive
and
thereby
prohibited
by
United
States=
law.

Operator
Interview
Process
Telephone
interviews
were
conducted
by
SEI
staff
with
CWS
operators
to
provide
a
general
overview
of
the
program,
determine
if
operators
were
willing
to
cooperate
in
a
five­
year
monitoring
study,
confirm
preliminary
information
obtained
during
the
identification
of
CWSs
that
use
surface
water,
and
to
collect
additional
information
needed
to
determine
if
the
system
fitted
the
target
population.
A
standard
operating
procedure
(
SOP)
was
developed
for
the
interview
procedure
in
order
to
obtain
consistent
information
from
all
CWS
personnel.
The
procedure
for
the
operator
interview
process
is
described
in
the
following
paragraphs.

Initial
contact
with
operators
was
conducted
by
telephone.
The
interviewer
attempted
to
contact
an
individual
in
a
managerial
position
for
the
water
system
to
ensure
that
cooperation
was
obtained
from
an
employee
with
authority.
If
a
manager
was
difficult
to
reach,
an
operator
was
interviewed.
An
overview
of
the
program,
and
the
program
requirements
regarding
sampling
and
shipping
were
described
to
the
operator.
Every
effort
was
made
to
encourage
participation
in
the
program
by
emphasizing
the
benefits
to
the
CWS
to
be
derived
from
receiving
additional
data
on
water
quality.
If
the
system
was
willing
to
participate,
the
following
information
was
obtained
or
confirmed:

a)
name
of
system,
operator,
telephone
and
fax
numbers,
and
address;
b)
whether
the
CWS
uses
surface
water
year
round,
or
if
it
is
an
emergency
or
back­
up
source;
c)
whether
the
system
uses
ground
water
in
addition
to
surface
water,
and
if
so,
whether
it
is
possible
to
sample
the
surface
water
discretely;
d)
whether
the
source
is
indeed
a
surface
water
source,
and
not
a
pit
or
static
water
body
fed
in
the
­
125­

e)
number
of
sources
supplying
the
CWS,
name
of
each
source
and
whether
a
particular
source
is
a
river,
lake,
reservoir,
or
some
other
type;
f)
general
location
of
intake(
s),
the
specific
location
was
determined
at
a
later
date
if
the
system
was
selected.

Communication
was
continued
with
sites
initially
meeting
the
target
population
criteria
to
provide
detailed
information
about
the
monitoring
program,
confirm
information
listed
above,
and
obtain
additional
information
regarding
treatment
of
water,
flow
measurement,
and
population
served.

Calculation
of
Corn
Intensity
(
CI)

During
the
CWS
selection
process,
CI
values
for
each
CWS
meeting
the
criteria
were
determined
manually
using
the
procedure
outlined
below.
However,
the
CI
values
provided
in
the
Table
of
CWSs
and
Characteristics
in
Appendix
A
reflect
more
accurate
values
computed
using
GIS.
For
the
selection
process,
the
approximate
corn
intensity
of
a
watershed
was
determined
for
watersheds
associated
with
CWSs
that
initially
met
the
target
population
criteria
based
on
the
operator
interview
process,
and
also
did
not
draw
water
from
a
Continental
River
or
one
of
the
Great
Lakes
(
henceforth
?
smaller
watersheds@).
First,
the
watersheds
were
drawn
for
each
CWS
according
to
the
process
described
below:

1)
If
possible,
the
intake
of
the
CWS
was
located
on
a
USGS
Hydrologic
Unit
Map
(
HUM)
based
on
information
obtained
from
the
CWS
contact
during
the
operator
interview
process.
Landmarks,
such
as
roads,
railroad
tracks,
bridges,
towns,
and
rivers,
were
identified
to
aid
in
location
of
intakes.
Intakes
on
smaller
water
bodies
could
not
be
located
on
the
1:
500,000
scale
HUM,
because
the
water
bodies
were
not
shown
on
these
maps.
Therefore,
their
locations
were
marked
on
a
larger­
scale
map2,
and
transferred
to
the
HUM.
For
instance,
if
the
intake
was
located
on
a
reservoir
which
did
not
appear
on
the
HUM,
the
reservoir
would
be
located
on
a
larger­
scale
map.
Its
distance
from
a
town
or
another
landmark
was
noted
and
using
that
information,
its
location
was
identified
on
the
HUM
based
on
the
location
of
the
landmark.
If
the
site
was
in
Illinois,
Ohio,
Minnesota,
Wisconsin,
Pennsylvania,
Maryland,
or
Delaware,
a
state
atlas
at
a
scale
of
1:
150,000
was
used.
For
the
remaining
states
where
such
an
atlas
was
unavailable,
a
road
atlas,
with
a
more
detailed
scale,
was
used.

2)
The
direction
of
water
flow
was
determined
by
examining
the
hydrology
and/
or
topography
of
the
surrounding
area.

3)
The
watershed
was
drawn
to
encompass
all
areas
upstream
or
draining
to
the
lake,
reservoir,
or
point
of
intake
on
the
river.
Where
possible
the
USGS
Hydrologic
Unit
Code
(
HUC)
­
126­

boundaries
(
regional,
subregional,
accounting
unit,
cataloging
unit)
were
used
to
define
the
watershed.

Corn
intensity
(
CI)
values
for
each
county
were
calculated
by
dividing
the
acreage
of
harvested
corn
for
each
county3
by
the
total
acreage
of
the
county4.
Harvested
acres
of
corn
for
grain
and
silage
were
added
to
give
total
acreage
of
harvested
corn.
Corn
cropping
data
from
1992
were
used
in
this
study.
Calculations
of
corn
intensity
for
a
few
sample
counties
are
shown
in
the
table
below:

1992
1992
Total
Harvested
Harvested
Corn
State
County
County
Acres
of
Acres
of
Intensity
Name
Name
Acres
Corn
Grain
Corn
Silage
(%)

(
a)
(
b)
(
c)
(
d)
[(
c+
d)/
b]
x
100
Indiana
Allen
437852.5
84154
1987
19.67
Iowa
Adair
361858.5
102811
1577
28.85
Ohio
Adams
379027.9
15792
1154
4.47
Illinois
Alexander
158236.6
11253
50
7.14
Mylar
overlay
maps
with
county
outlines
were
generated
using
ArcInfo
software.
Counties
were
shaded
on
the
mylar
according
to
their
corn
intensity
value.
A
unique
color
was
assigned
to
each
of
the
following
categories:

a)
0­
5%
CI
b)
5­
10%
CI
c)
11­
20%
CI
d)
>
20%
CI
The
Mylar
overlays
with
county
outlines
were
on
the
same
scale
as
the
Hydrologic
Unit
Code
maps
on
which
the
watersheds
were
drawn.
The
appropriate
Mylar
overlay
and
map
were
superimposed
in
order
to
visually
estimate
the
CI
of
each
watershed.
If
a
particular
watershed
was
dominantly
one
color,
the
watershed
was
considered
to
be
in
that
corn
intensity
category.
If
no
predominant
color
was
discernable,
then
the
approximate
area
of
each
county
within
the
watershed
was
estimated
to
the
nearest
1x
105
acres
using
a
transparent
grid
graduated
in
inches
and
fractions
of
inches.
Each
0.5
inch
square
(
0.25
square
inches)
is
equivalent
to
approximately
10,000
acres
at
the
1:
500,000
scale
of
the
HUC
maps.
The
corn
intensity
of
the
watershed
was
then
estimated
using
the
following
formula:

(
Pa
x
CIa)
+
(
Pb
x
CIb)
=
Average
CI
percentage
for
the
watershed,
where
Pa
=
percentage
of
watershed
in
county
a
CIa
=
corn
intensity
of
county
a
Pb
=
percentage
of
watershed
in
county
b=
CIb
=
corn
intensity
of
county
b
The
formula
was
modified
to
include
all
counties
that
made
up
a
significant
portion
of
the
area
of
the
watershed.
For
CWSs
with
more
than
one
watershed,
only
the
primary
water
sources
were
included
in
the
CI
determination.
If
more
than
one
watershed
or
source
CI
was
determined
and
the
­
127­

two
sources
did
not
have
the
same
CI
category,
then
a
weighted
average
was
used
to
determine
the
CI
for
the
system.

After
estimation
of
corn
intensity,
smaller
watersheds
were
placed
in
the
appropriate
corn
intensity
category.
All
smaller
watersheds
with
less
than
5%
CI
were
removed
from
the
target
population.

2.1.3
Separation
of
Target
Population
of
CWSs
into
Disjoint
Strata
The
CWSs
meeting
the
criteria
of
the
target
population
were
separated
into
disjoint
strata
based
on
their
state,
the
size
of
their
watershed,
and
for
smaller
watersheds,
their
corn
intensity
(
CI).
There
are
five
strata
for
each
of
the
twelve
states:

1.
Great
Lakes
(
Erie,
Superior,
Michigan)
2.
Three
Continental
Rivers
(
Missouri,
Mississippi,
and
Ohio)

Smaller
Watersheds
with
3.
5­
10%
CI
4.
11­
20%
CI
5.
>
20%
CI
There
are
a
total
of
60
strata
for
the
12
states.
The
disjoint
strata
structure
is
displayed
in
Table
1.

2.1.4
Random
Selection
of
CWSs
from
each
Stratum
Concentrations
of
acetochlor
and
other
corn
herbicides
are
likely
to
be
higher
in
smaller
watersheds
with
higher
corn
intensity.
Acetochlor
concentrations
are
expected
to
be
lower
in
major
rivers
and
lakes
where
herbicide
levels
will
be
diluted
after
runoff
events.
Therefore,
CWSs
on
smaller
watersheds
with
>
20%
CI
are
expected
to
potentially
have
the
highest
concentrations
of
acetochlor
after
runoff
events,
while
CWSs
on
the
Great
Lakes
are
expected
to
potentially
have
the
lowest
concentrations
of
acetochlor
after
runoff
events.
A
higher
percentage
of
CWSs
were
selected
from
strata
expected
to
have
higher
concentrations
of
acetochlor
after
runoff
events.
However,
all
strata
are
represented
in
this
program.

Computer­
generated
random
numbers
were
assigned
to
CWSs
in
each
stratum.
A
certain
number
of
CWSs
from
each
stratum
was
selected
by
choosing
the
sites
with
the
lowest
random
numbers.
If
a
system
subsequently
needed
to
be
removed
due
to
unwillingness
to
participate,
or
some
other
reason
which
eliminated
the
system
from
the
target
population,
then
where
possible,
another
system
was
randomly
selected
from
the
same
stratum.
If
no
systems
were
available
in
the
same
stratum
for
use
as
replacements,
then
a
system
was
randomly
selected
from
another
stratum
with
available
CWSs,
where
possible,
from
the
next
stratum
in
the
same
state.
In
general,
the
replacement
CWSs
were
selected
from
strata
with
available
CWSs,
expected
to
have
the
highest
concentrations
of
acetochlor
after
runoff
events.

2.2
Data
Collection
for
Selected
CWSs
Specific
data
for
each
selected
CWS
was
collected
and
verified
using
a
standard
operating
procedure
and
data
collection
forms.
Each
CWS
representative
was
contacted
by
telephone,
and
subsequently
during
a
site
visit,
and
asked
to
verify
data
previously
obtained
and
to
supply
additional
information
about
their
system.
­
128­

Detailed
information
was
obtained
on
the
location
of
each
CWS
intake,
and
the
location
was
marked
on
a
7.5
minute
USGS
topographic
map.
Other
data
obtained
are
listed
below:

1)
name
of
system
and
owner
2)
contact
name
3)
telephone
and
fax
number
4)
address
and
county
5)
description
and
name(
s)
of
primary
source(
s)
of
water
6)
whether
there
is
a
reservoir,
and
if
so,
the
approximate
volume
of
the
reservoir
7)
description,
name(
s),
and
location(
s)
of
alternative
source(
s)
of
water
8)
frequency
of
backup
supply
use
and
date
last
used
9)
treatment
method
and
filtration
type
10)
whether
system
uses
granular
activated
carbon
treatment
and
is
willing
to
collect
raw
water
11)
whether
system
measures
river
flow
and
how
12)
location
of
any
nearby
gaging
stations
13)
whether
system
measures
stage
height
14)
peak
and
average
volumes
of
surface
water
treated
daily
15)
whether
system
sells
water
to
other
CWSs,
and
the
names
of
the
customer
CWSs
16)
population
served,
population
served
by
water
sold
to
other
CWSs
17)
location
of
any
pesticide
storage/
shipping
facilities
in
watershed
18)
whether
system
has
a
refrigerator/
freezer
to
freeze
ice
packs
19)
proximity
of
available
shipping
services
20)
whether
system
is
capable
of
collecting
samples
Mon.­
Thurs,
year
round
21)
number
of
staff
available
to
collect
samples,
names(
s)
and
title(
s)
22)
whether
CVs/
resumes
are
available
for
samplers
23)
whether
the
intake
was
located
and
reference
provided
24)
comments
for
system
participants
2.3
Drawing
of
Watersheds
Watersheds
were
drawn
for
each
selected
CWS
following
a
standard
procedure.
Watershed
boundaries
provided:
1)
a
basis
for
the
maps
of
all
watersheds
included
in
the
program,
and
2)
the
points
and
lines
used
to
create
Geographical
Information
System
(
GIS)
coverages.
The
process
for
drawing
watersheds
is
summarized
below.

C
The
intake
location
was
marked
on
a
7.5
minute
USGS
topographic
map
based
on
detailed
information
obtained
during
the
telephone
interview
and
confirmed
during
site
visits.

C
The
intake
location
was
transcribed
from
the
7.5
minute
USGS
topographic
map
onto
the
map
of
appropriate
scale
for
drawing
the
watershed.
The
appropriate
scale
map
was
selected
by
choosing
a
USGS
topographic
or
hydrologic
unit
map
that
provided
the
most
detail
possible
and
also
was
suitable
for
reduction
to
an
8.5
x
11
inch
page.

C
The
watershed
was
drawn
by
connecting
points
of
highest
elevation
upstream
from
the
intake.
This
was
done
by
following
the
drainage
divide,
a
continuous
line
joining
the
points
from
which
surface
water
will
flow
in
different
directions.
These
points
can
be
determined
from
the
contour
lines
of
a
topographic
map
by
observing
the
slope
of
the
land
and
thus,
noting
­
129­

which
way
the
water
will
flow.
The
highest
points
surrounding
land
that
slopes
towards
all
tributaries
of
a
water
body
are
joined
together
to
delineate
the
drainage
divide.
With
few
exceptions,
the
drainage
divide
cannot
cross
any
bodies
of
water.
The
area
within
the
drainage
divide
defines
the
watershed.

C
The
watershed
was
drawn
initially
in
pencil
and
then
traced
onto
Mylar.
Geographic
reference
points
(
latitude
and
longitude)
were
also
marked
on
the
Mylar.

For
systems
with
more
than
one
intake,
the
individual
intakes
and
their
associated
watersheds
were
designated
as
primary
(
P1,
P2,
etc),
or
as
backup
(
B1,
B2,
etc).
Watersheds
were
drawn
for
all
primary
intakes.
Back­
up
source
watersheds
were
drawn
only
if
the
back­
up
source
was
likely
to
provide
more
than
20%
of
the
volume
on
sampling
weekdays
between
March
15
and
August
31,
the
time
period
when
peak
concentrations
of
herbicides
due
to
field
runoff
are
expected.
All
primary
and
significant
backup
watersheds
were
drawn
in
order
to
obtain
realistic
watershed
data
for
the
surface
water
used
by
the
system.

For
systems
with
watersheds
on
the
Great
Lakes
or
Continental
Rivers,
the
watersheds
were
drawn
on
appropriate
small
scale
maps
(
referenced
on
each
map
in
the
site
data
section
in
Appendix
C)
to
provide
the
individual
site
map.
The
intake
locations
for
Great
Lake
watersheds
were
traced
onto
Mylar
along
with
geographic
reference
points
(
latitude
and
longitude)
and
existing
ArcInfo
polygon
lines
from
EPA
sources5
were
used
to
delineate
the
watersheds
for
GIS.
The
watershed
was
drawn
initially
in
pencil
and
then
traced
onto
Mylar.
Geographic
reference
points
(
latitude
and
longitude)
were
marked
on
the
Mylar.

Watersheds
for
Continental
Rivers
are
available
on
the
USGS
1:
500,000
Hydrologic
Unit
Maps
(
HUMs).
The
HUMs
are
available
for
each
state,
and
the
Continental
Rivers
commonly
extend
through
several
state
maps.
To
use
existing
data,
watershed
boundaries
were
drawn
using
both
the
HUMs
and
the
USGS
State
Series
1:
500,000
Topographic
Maps.
Both
maps
are
of
the
same
scale.
The
procedure
for
drawing
the
Continental
River
watersheds
is
described
below:

C
Locate
the
intake
on
the
Topographic
Map
C
Overlay
the
appropriate
Hydrologic
Unit
Map
with
the
Topographic
Map,
and
draw
the
watershed
boundaries
on
the
Topographic
Map
until
they
connect
with
a
hydrologic
unit
code
boundary.

C
Reverse
the
maps
so
the
Hydrologic
Unit
Map
is
over
the
Topographic
Map,
and
trace
the
intake
location
and
watershed
boundaries
onto
the
Hydrologic
Unit
Map.
The
Hydrologic
Unit
Map
was
used
as
the
base
map
for
the
Mylar
trace.

C
Trace
the
watershed
onto
Mylar.
Geographic
reference
points
(
latitude
and
longitude)
were
also
marked
on
the
Mylar.

The
boundaries
of
all
watersheds
traced
on
Mylar
were
scanned
and
converted
to
digitized
polygons
to
serve
as
a
basis
for
a
Geographic
Information
System
(
GIS)
database.
This
allows
other
data
(
e.
g.
soil
texture
and
hydrologic
group,
and
weather
data)
to
be
overlaid
and
compared
to
specific
watersheds.
Corn
intensity
(
based
on
county
data)
3,4
and
watershed
area
were
calculated
for
each
watershed
using
GIS.
Corn
intensity
had
been
previously
estimated
using
the
method
described
in
Section
2.1.2.
in
order
to
determine
if
watersheds
belonged
to
the
target
population,
and
to
assign
watersheds
to
categories
of
corn
intensity.
GIS
provided
a
more
accurate
determination
of
corn
intensity.
Most
of
the
GIS­
calculated
corn
intensities
are
within
the
range
of
the
stratum
of
the
associated
CWS,
but
as
can
be
seen
in
Table
2
and
in
more
detail
in
the
Table
of
CWSs
and
­
130­

Characteristics
in
Appendix
A,
some
of
the
watersheds
have
GIS­
calculated
corn
intensities
that
are
higher
or
lower
than
their
CWS
stratum
corn­
intensity
range.
Both
determinations
of
corn
intensity
are
based
on
county
corn
data.
An
area
index,
that
is
a
relative
measure
of
the
proportion
of
each
county
contained
in
a
watershed,
was
calculated
for
each
watershed.
This
provides
information
on
the
reliability
of
the
corn
intensity
based
on
county
data.
Details
regarding
calculation
of
corn
intensity,
area
index,
and
watershed
area
using
GIS
are
provided
below
in
Section
2.4.
Details
regarding
GIS
databases
and
mapping
are
provided
in
Appendix
B.

2.4
GIS
Calculation
of
Corn
Intensity
and
Watershed
Area
2.4.1
Corn
Intensity
ArcInfo
GIS
software
is
used
to
assist
in
the
calculation
of
watershed
corn
intensity
(
WCI)
for
each
watershed.
County
corn
intensities
are
used
to
calculate
this
number.
An
intersection
is
made
of
the
county
(
polygon)
ArcInfo
GIS
coverage
(
database)
with
the
watershed
ArcInfo
GIS
coverage
using
ArcInfo
=

s
"
Union"
command.
This
process
results
in
the
creation
of
county
watershed
(
polygon)
coverage.
A
new
item
in
the
PAT
file
(
the
polygon
attribute
table­
the
database
file)
is
then
created
using
the
ArcInfo
"
Additem"
command
to
accept
the
values
for
the
percentage
of
watershed
within
each
county.
To
calculate
this
percentage,
the
following
formula
is
used
in
the
ArcInfo
program:

P
=
WSCTY
*
100
TOTAL
where:
P
=
Percentage
of
watershed
within
the
county
WSCTY
=
area
of
watershed
in
the
county
TOTAL
=
total
area
of
watershed
polygon
Another
item
in
the
PAT
file
is
created
to
accept
values
for
the
average
CI
of
each
watershed.
The
average
CI
for
each
watershed
is
calculated
in
ArcInfo
using
the
following
formula:

WCI
Percentage
=
(
Pa
x
CIa)
+
(
Pb
x
CIb)
+
...
+
(
Pnth
x
CInth)

where:
WCI
=
Watershed
Corn
Intensity
Pa
=
percentage
of
watershed
in
county
a
CIa
=
corn
intensity
of
county
a
Pb
=
percentage
of
watershed
in
county
b
CIb
=
corn
intensity
of
county
b
Pnth
=
percentage
of
watershed
in
nth
county
CInth
=
corn
intensity
of
the
nth
county
For
each
watershed
an
"
area
index"
is
calculated.
The
index
is
a
relative
measure
of
the
proportion
of
each
county
contained
in
the
watershed
and
thus,
provides
information
regarding
the
reliability
of
the
calculated
WCI.
For
example,
if
a
watershed
has
three
counties
and
each
county
has
greater
than
50%
of
its
area
within
the
watershed,
the
calculated
watershed
corn
intensity
is
likely
more
­
131­

accurate
than
for
a
watershed
in
which
the
counties
have
only
20%
of
their
areas
within
the
watershed.
The
formula
for
calculating
the
index
is:

23
where:
WSCTY
=
acreage
of
watershed
in
county
i
CTY
=
acreage
of
county
i
2.4.2
Watershed
Area
Geographic
locations
are
stored
as
vector
data
in
ArcInfo.
The
ArcInfo
software
is
able
to
perform
precise
planimetric
area
calculations
on
polygons
delineated
by
these
vectors.
The
area
is
calculated
through
preprogrammed
algorithms
in
the
software.

The
watershed
areas
for
the
Great
Lakes
do
not
include
the
area
of
the
lake
itself.
This
has
an
impact
on
the
calculation
of
the
CI.
Because
of
the
smaller
areas,
the
GIS­
calculated
CI
will
be
a
higher
number
than
if
the
calculation
had
included
area
of
the
lake.
Also
some
of
the
Great
Lakes'
watersheds
extend
into
Canada
where
county
corn
intensities
are
not
available,
and
are
not
included
in
the
calculation.

3.0
RESULTS
AND
DISCUSSION
3.1
CWS
Distribution
The
distribution
of
CWSs
in
the
surface
water
program
is
displayed
in
Table
1.

3.1.1
States
A
total
of
175
CWSs
were
required
for
inclusion
in
the
surface
water
program.
Initially,
all
175
sites
were
to
be
located
in
the
seven
core
states
(
IL,
IN,
IA,
KS,
MN,
NE,
and
WI)
as
defined
by
the
March,
1994,
registration
agreement.
The
rationale
was
that
these
seven
states
accounted
for
over
80%
of
the
corn
production,
and
therefore,
acetochlor
would
be
used
predominantly
in
these
states.
However,
based
on
data
collected
in
the
Fall
of
1994
by
the
ARP,
it
was
clear
that
several
of
the
core
states,
KS,
MN,
NE,
and
WI,
had
very
few
surface
water
CWSs
in
areas
of
greater
than
5%
corn
intensity.
The
ARP
and
EPA
discussed
these
data
and
the
possibility
of
expanding
the
surface
water
program
to
include
additional
states,
in
order
to
avoid
over­
sampling
in
several
of
the
originally
identified
states.
The
outcome
of
these
discussions
resulted
in
inclusion
of
five
more
states,
OH,
MO,
PA,
MD,
and
DE.
By
including
these
states,
the
ARP
was
able
to
identify
hundreds
of
additional
CWSs
that
used
surface
water.
Many
of
these
were
smaller
CWSs
in
areas
of
greater
than
­
132­

5%
intensity.
The
expansion
to
additional
states
is
likely
to
benefit
interpretation
of
the
data
obtained
from
this
study.

3.1.2
Watershed
Size
and
Corn
Intensity
Watersheds
were
separated
into
three
size
strata:

1)
Great
Lakes
2)
Continental
Rivers
3)
Smaller
Watersheds
An
objective
of
the
selection
process
was
to
represent
all
three
sizes
of
watersheds,
but
focus
on
the
watersheds
expected
to
have
the
highest
concentrations
of
acetochlor
after
runoff
events.
Therefore,
the
highest
percentage
of
watersheds
was
selected
from
the
Smaller
Watershed
strata
and
the
lowest
percentage
from
the
Great
Lakes
strata.
A
total
of
150
CWSs
(
71%
of
the
available
CWSs
were
selected
from
the
Smaller
Watershed
strata,
a
total
of
17
were
selected
from
the
Continental
River
strata
(
43%
of
the
available
CWSs),
and
a
total
of
8
from
the
Great
Lakes
strata
(
14%
of
the
available
CWSs).

The
Smaller
Watershed
strata
were
further
separated
by
their
corn
intensity
into
three
additional
strata:

1)
5­
10%
Corn
Intensity
2)
11­
20%
Corn
Intensity
3)
>
20%
Corn
Intensity
A
second
objective
of
the
selection
process
was
to
represent
all
three
corn
intensity
ranges
but
focus
on
the
watersheds
expected
to
have
the
highest
concentrations
of
acetochlor
after
runoff
events.
Therefore,
the
highest
percentage
of
watersheds
was
selected
from
the
>
20%
Corn
Intensity
strata
and
the
lowest
percentage
from
the
5­
10%
Corn
Intensity
strata.
A
total
of
76
CWSs
were
selected
from
the
>
20%
Corn
Intensity
strata
(
100%
of
the
available
CWSs),
a
total
of
31
CWSs
from
the
11­
20%
Corn
Intensity
strata
(
66%
of
the
available
CWSs),
and
a
total
of
43
CWSs
from
the
5­
10%
strata
(
49%
of
the
available
CWSs).

Corn
intensity
is
used
as
a
surrogate
for
acetochlor
usage,
and
the
strata
expected
to
have
the
highest
levels
of
acetochlor
are
the
Smaller
Watershed,
>
20%
Corn
Intensity
strata.

3.2
Characterization
of
CWSs
Corn
intensity
(
for
the
12
states
included
in
the
program),
watershed
boundaries,
and
CWS
intake
locations
are
displayed
on
maps
in
Figures
1­
3.

The
watersheds
associated
with
the
175
selected
CWSs
are
in
the
12
states
included
in
the
program,
and
also
extend
into
12
other
states
and
Canada.
The
watersheds
extending
into
Canada
and
the
12
other
states
are
listed
below:

Great
Lakes:
Canada,
New
York,
Michigan
Mississippi
River:
Canada,
Colorado,
Wyoming,
Montana,
North
Dakota,
South
Dakota
­
133­

Ohio
River:
New
York,
West
Virginia,
Kentucky,
Tennessee,
North
Carolina
Missouri
River:
Canada,
Colorado,
Wyoming,
Montana,
North
Dakota,
South
Dakota
Kansas
and
Republican
Rivers:
Colorado
Red
Rivers:
North
Dakota,
South
Dakota
CWSs
were
generally
characterized
by
their
size
and
corn
intensity,
population
served,
watershed
area,
treatment
type,
and
whether
a
reservoir
is
used.
An
overview
of
the
characteristics
of
the
175
CWSs
in
the
surface
water
program
is
provided
in
Table
2.

All
of
the
175
CWSs
in
the
program
use
some
type
of
conventional
treatment
(
coagulation,
flocculation,
sedimentation,
and
filtration)
for
their
water.
There
are
21
CWSs
using
a
granular
activated
carbon
(
GAC)
treatment
and
111
CWSs
using
a
powdered
activated
carbon
(
PAC)
treatment.
Most
of
the
GAC
units
are
used
by
systems
in
the
>
20%
and
11­
20%
corn
intensity
strata,
strata
that
cover
the
higher
corn­
growing
areas.
A
total
of
124
CWSs
have
at
least
one
reservoir.
The
175
CWSs
serve
populations
ranging
from
167
to
5,100,000
people.
The
watersheds
associated
with
the
175
CWSs
cover
areas
ranging
from
83
to
443,533,492
acres.
An
overview
of
CWS
distribution
by
population
and
strata
is
presented
in
Figure
4.
The
distribution
of
watershed
area
by
strata
is
presented
in
Figure
5.
This
data
includes
watershed
area
for
all
watersheds
(
primary:
P1,
P2
and
back­
up:
B1,
B2)
for
a
given
CWS
that
are
likely
to
provide
more
than
20%
of
the
volume
on
sampling
weekdays
between
March
15
and
August
31.
The
number
of
CWSs
with
reservoirs
and
GAC
treatment
is
compared
to
the
total
number
of
CWSs
in
each
stratum
in
Figure
6.

A
table
of
the
175
CWSs
and
200
watersheds,
sorted
by
state,
strata
and
site
code,
with
system
name
and
address,
total
population
served
(
including
population
served
by
sales
to
other
systems),
GIScalculated
corn
intensity
and
watershed
area(
s)
for
all
watersheds
for
a
given
CWS,
whether
system
uses
GAC
and/
or
PAC,
or
has
a
reservoir,
source
code,
is
in
Appendix
A.
Detailed
information
on
each
of
the
175
selected
CWSs
is
presented
in
site
data
sheets
in
Appendix
C
and
organized
by
state
and
site
code.
A
state
map
with
watershed
boundaries,
and
a
state
map
with
intake
locations
marked
and
identified
by
site
code
are
included
with
the
site
data
sheets
for
each
state.
Maps
of
all
watersheds
associated
with
a
site
are
also
included
with
each
site
data
sheet.
The
site
data
sheets
provide
the
following
information:

1)
system
name,
delivery
address,
mailing
address,
telephone,
fax
2)
treatment
information
including
type
of
treatment,
and
peak
and
average
volume
treated/
day
3)
watershed
stratum
4)
population
served
and
population
sold
5)
names
of
CWS
samplers
and
dates
of
training
6)
source
information
including
source
name,
watershed
area,
source
type,
volume/
area
for
reservoirs,
backup
frequency,
and
whether
stage
height
is
measured
7)
corn
intensity
for
each
watershed
calculated
by
GIS
using
county
data,
and
area
index
providing
information
on
the
proportion
of
the
counties
within
the
watershed
8)
location
of
intake,
latitude
and
longitude,
for
each
watershed
9)
hydrologic
group
and
soil
texture
information
for
all
watersheds
that
are
not
Great
Lake
or
Continental
River
watersheds
4.0
CONCLUSIONS
­
134­

A
site
selection
process
was
conducted
to
identify
175
CWSs
in
12
states.
Data
regarding
population
and
CWS
source(
s)
were
collected,
and
watershed
areas
and
corn
intensities
were
determined.
Each
of
the
175
systems
was
visited,
inspected,
and
data
confirmed.
Watersheds
for
the
175
systems
were
mapped.
The
selected
CWSs
represent
a
broad
spectrum
based
on
geographic
diversity,
general
size
and
corn
intensity
of
the
watersheds.
The
data
for
the
selected
systems
demonstrate
the
extensive
diversity
of
the
ARP
surface
water
monitoring
program.
The
watersheds
are
representative
of
the
key
acetochlor­
use
states,
with
a
few
extending
into
numerous
states
not
included
in
the
program.
The
CWSs
are
supplied
by
surface
water
from
a
variety
of
sources
including
small
rivers
and
lakes,
larger
rivers
and
lakes,
and
reservoirs,
and
employ
a
wide
variety
of
treatment
methods.
The
selected
watersheds
span
a
large
range
of
watershed
area,
and
serve
a
large
range
of
populations.

The
highest
percentage
of
CWSs,
100%
of
the
available
CWSs,
was
selected
from
the
>
20%
corn
intensity
strata,
66%
were
selected
from
the
11­
20%
corn
intensity
strata,
49%
from
the
5­
10%
corn
intensity
strata,
43%
from
the
Continental
River
strata,
and
14%
from
the
Great
Lakes
strata.
Almost
50%
of
the
sites
were
selected
from
smaller
watersheds
with
>
20%
corn
intensity,
the
watersheds
expected
to
have
the
highest
concentrations
of
acetochlor
after
runoff
events.
The
focus
on
more
vulnerable
watersheds
with
higher
corn
intensity
combined
with
the
diversity
of
watersheds
selected
for
this
study
will
allow
us
to
obtain
both
a
worst­
case
and
representative
evaluation
of
the
impact
of
acetochlor
and
other
corn
herbicide
usage
on
surface
drinking
water
in
significant
corngrowing
areas
of
the
United
States.

12.5.2.
Site
Selection
 
SGW
Study
The
description
below
is
taken
from
De
Guzman
et
al
(
2005),
a
more
comprehensive
description
is
available
in:
MRID:
43899601
Hendley,
P.
(
1995)
State
Ground
Water
Monitoring
Program
for
Acetochlor
and
Other
Corn
Herbicides­­
Part
1:
Site
Selection
and
Site
Details:
Lab
Project
Number:
ACET­
94­
GW­
01:
RR
95­
087B:
GWMSIT05.
DOC.
Unpublished
study
prepared
by
Zeneca
Ag
Products
and
Levine­
Fricke,
Inc.
3217
p.

Site
Selection
Criteria
The
goal
of
the
first
phase
of
the
study
was
to
establish
a
network
of
175
monitoring
sites
in
regions
of
high
corn
production
in
each
of
the
seven
states
representing
a
range
of
soil
textures
typical
of
corn
agriculture
in
those
regions.
Each
site
was
expected
to
have
shallow
ground
water,
as
defined
by
each
state
(
Table
1),
unprotected
by
restrictive
subsurface
layers.
A
new
monitoring
well
was
installed
within
or
closely
adjacent
to
and
down­
gradient
of
each
site.
Initially,
the
seven­
state
area
was
evaluated
to
determine
the
counties
with
significant
corn
production.
The
evaluation
was
based
on
the
most
recent
(
1987)
United
States
Department
of
Agriculture
(
USDA)
Agricultural
Product
Statistics
available
at
that
time.
An
area­
weighted
distribution
of
soil
textures
across
the
selected
counties
in
each
state
was
obtained
from
STATSGO,
a
USDA­
National
Resources
Conservation
Service
(
NRCS)
spatial
soils
database
(
USDA,
2004).
This
distribution
was
used
to
develop
initial
targets
for
the
numbers
of
sites
to
­
135­

be
assigned
to
each
soil
texture
in
each
state.
Table
2
details
the
planned
and
actual
distribution
of
SGM
sites
by
soil
texture.
Potential
monitoring
sites
were
also
required
to:
1)
be
representative
of
the
irrigation
and
crop
rotation
practices
performed
on
the
particular
soil
type
and
region;
2)
be
able
to
accommodate
a
new
monitoring
well
installed
within
or
adjacent
to,
and
down­
gradient
of
a
4.0­
hectare
(
minimum)
treated
study
plot;
3)
be
free
of
any
historical
application
of
acetochlor;
4)
not
be
prone
to
flooding,
runoff
or
run­
on;
5)
be
relatively
flat
(<
8%
slope);
6)
accommodate
the
installation
of
a
monitoring
well
without
drilling
into
bedrock;
and
7)
have
a
site
landowner
who
agreed,
via
a
formal
agreement
with
the
ARP,
to
follow
a
specific
acetochlor
use
plan.
Site
Characterization
and
Well
Installation
Once
a
SGM
site
was
confirmed
to
meet
the
above
criteria,
it
was
visited
by
ARP
personnel
to
collect
additional
characterization
data.
A
topographical
survey,
hydrogeological
assessment,
soil
characterization
and
a
cooperator
interview
were
conducted.
If
available,
published
maps
of
the
site
and
vicinity
were
obtained,
including
county
roadmaps,
plat
maps,
USGS
7.5­
minute
quadrangles,
NRCS
County
Soils
maps,
and
aerial
photos.
Furthermore,
a
detailed
map
of
each
site
was
produced
in
order
to
identify
site­
specific
features,
such
as
access
lanes,
study
plot
location,
irrigation
and
other
farming
equipment,
tile
drains,
ditches
and
other
waterway
features.
Historical
pesticide
use,
dating
back
to
1990
(
when
available),
cropping
and
other
agronomic
practices
were
obtained
by
interviewing
the
cooperators.
A
minimum
4.0­
hectare
portion
of
the
farm
was
designated
as
the
study
plot.
Ten
soil
cores
(
0
 
0.15
m)
were
collected
from
representative
locations
in
the
study
plot.
These
soil
cores
were
composited
and
a
subsample
was
analyzed
(
A&
L
Great
Lakes
Laboratories
Inc.,
Fort
Wayne,
IN)
for
pH,
organic
carbon/
organic
matter,
cation
exchange
capacity,
USDA
texture
classification
and
bulk
density.
Monitoring
wells
were
sited
within
or
closely
adjacent
to,
and
down­
gradient
of
the
study
plot.
Various
sources
of
published
ground
water
data
were
used
(
for
example,
the
Department
of
Natural
Resources
Hydrologic
Assessment,
the
USGS
Hydrologic
Atlas
and
local
university
data)
to
assess
ground
water
flow
direction
for
most
sites.
At
sites
where
published
ground
water
data
were
not
available,
trained
hydrogeologists
evaluated
topography
in
conjunction
with
surface
water
drainage
features
in
order
to
assess
ground
water
flow
direction.
Monitoring
wells
were
installed
by
licensed
commercial
drilling
contractors
under
the
direct
supervision
of
a
professional
geologist/
hydrogeologist
and
in
compliance
with
state
and
local
guidelines.
Each
boring
was
drilled
using
a
hollow­
stem
auger
advanced
by
a
rotary
drill
rig.
Continuous
core
soil
samples
were
collected
from
each
boring
and
lithologic
descriptions
were
recorded
using
the
Unified
Soil
Classification
System
(
USCS).
Each
monitoring
well
was
constructed
with
0.05
m
(
inside
diameter)
polyvinyl
chloride
(
PVC)
casing
with
flush­
threaded
joints
and
0.254­
mm
machine­
slotted
screen.
A
filter
pack
of
coarse
sand
to
fine
gravel
was
placed
in
the
annular
space
surrounding
and
up
to
approximately
0.6
m
above
the
well
screen.
The
length
and
position
of
the
well
screen
was
defined
by
each
state
(
Table
1).
A
minimum
0.9
m
bentonite
seal
was
installed
in
the
annular
space
above
the
filter
pack.
The
remaining
annular
space
from
0.6
to
0.9
m
bgs
was
sealed
using
a
Portland
cement
grout
or
a
bentonite
grout.
The
PVC
casing
extended
up
to
approximately
0.9
m
above
the
surface
grade
and
was
protected
by
a
0.1
m
inside
diameter
steel
protective
casing
and
a
locking
cap.
Wooden
posts
were
installed
in
a
square
formation
0.2
m
from
the
monitoring
well
for
added
protection
against
farm
equipment.
Figure
1
illustrates
the
typical
well
construction
details
of
the
SGM
wells.
After
well
installation,
each
monitoring
well
was
thoroughly
developed
and
equipped
with
a
dedicated
­
136­

bladder
pump.
Each
of
the
175
monitoring
wells
was
locked
and
access
was
limited
to
ARP
personnel.
Each
monitoring
well
was
surrounded
by
an
`
acetochlor­
free'
buffer
zone
to
minimize
the
chance
of
direct
spray
drift
contamination
of
the
monitoring
wellhead
and
sampling
area.
Acceptable
buffer
zones
were
defined
by
each
state
and
ranged
from
9.1
­
45.7
m
(
Table
1).
Each
of
the
175
wells
was
given
a
unique
ID,
which
followed
a
standard
SSnn
format
where
"
SS"
reflected
the
state
abbreviation
and
the
"
nn"
represented
a
sequential
number
within
the
state
(
e.
g.
IL01
­
IL25).
Figure
2
shows
the
approximate
location
of
the
sites.
Exact
locations
of
the
sites
and
wells
were
held
confidential
in
order
to
minimize
the
risk
of
vandalism
or
sabotage
and
to
protect
the
privacy
of
the
cooperator.
Monitoring
began
in
1995
with
every
cooperator
expected
to
plant
corn
and
treat
the
study
plot
with
an
acetochlor
product
that
spring.
In
later
years,
the
cooperators
were
expected
to
follow
their
typical
cropping
plans
(
e.
g.
continuous
corn
or
a
crop
rotation),
provided
that
by
the
end
of
the
5­
year
monitoring
program,
each
of
the
175
sites
would
be
cropped
to
corn
three
times,
and
therefore,
would
receive
at
least
three
acetochlor
applications.
In
order
to
accommodate
the
2­
year
extension,
a
new
agreement
was
made
between
the
ARP
and
the
cooperators
in
1999,
which
specified
that
another
corn
crop
be
planted
and
treated
with
an
acetochlor
formulation
during
at
least
one
of
the
two
additional
growing
seasons.
Therefore,
each
cooperator
was
required
to
make
at
least
four
acetochlor
treatments
during
the
course
of
the
7­
year
study.

12.5.3.
PGW
Study
Site
Selection
and
Characterization
The
following
description
is
taken
from
Newcombe
et
al.
(
2005),
more
detailed
descriptions
are
found
in
the
Final
Reports
and
Site
Characterization
reports
for
each
of
the
eight
studies
(
see
Bibliography
section).

PGW
site
selection
criteria
Careful
selection
of
PGW
monitoring
sites
is
critical
to
ensure
that
study
results
are
useful
in
risk
assessments
and
pesticide
regulatory
decisions.
A
combination
of
US
EPA
(
US
EPA
1995
and
1998)
and
ARP­
specific
site
selection
criteria
were
followed
to
locate
candidate
sites
for
the
acetochlor
PGW
program.
These
criteria
included;

 
Uniform
soil
characteristics
 
Unconfined
aquifer
 
Less
than
9
m
depth
to
the
water
table
 
Less
than
or
equal
to
2%
topographic
slope
 
Sufficient
distance
from
drainage
features
to
ensure
stable
hydraulic
gradient
conditions
 
No
impeding
low­
permeability
layers
between
the
surface
and
water
table
 
No
prior
acetochlor
use
 
Absence
of
seasonally
high
water
tables
 
Farmer
and/
or
landowner
cooperation
 
Adherence
to
the
acetochlor
soil
use
restriction
in
the
United
States.
This
restriction
prohibits
the
use
of
acetochlor
on
sands
with
less
than
3%
organic
matter,
loamy
sands
­
137­

with
less
than
2%
organic
matter,
or
sandy
loams
with
less
than
1%
organic
matter,
when
ground
water
is
less
than
9
m
below
land
surface.

The
US
EPA
required
that
studies
be
conducted
on
the
following
soil
textures;
loamy
sand
(
1),
sandy
loam
(
2),
loam
(
1)
silt
loam
(
3),
and
clay
loam
(
1).
This
distribution
includes
most
soils
on
which
corn
is
grown
in
the
United
States,
but
is
weighted
towards
coarser­
textured
soils.
Site
identification
Preliminary
site
identification
activities
included
a
review
of
available
soils,
agronomy,
and
hydrogeologic
data.
Geographic
Information
System
overlays
of
land
use
and
soil
type
were
created
to
identify
sub­
county
areas
for
further
investigation.
During
visits
to
candidate
sites,
preliminary
surface­
soil
samples
were
collected
for
laboratory
characterization,
and
hand
auger
borings
collected
to
determine
the
nature
of
vadose
zone
material,
and
if
possible,
to
determine
depth
to
ground
water
at
each
site.

Site
characterization
Site
characterization
activities
included
surface
soil
and
subsoil
characterization,
aquifer
characterization,
and
the
conduct
of
a
site
survey.
Surface
soil
(
0­
15
cm)
was
collected
from
each
proposed
PGW
study
location
to
assess
variability
of
surface­
soil
texture,
pH,
organic
matter,
cation
exchange
capacity,
and
disturbed
bulk
density.
Soil
samples
were
collected
using
a
stainless
steel
trowel
or
hand
auger
and
shipped
to
a
contract
laboratory
for
characterization.
Subsurface
soil
at
each
study
location
was
characterized
during
piezometer
or
monitoring
well
installation
activities.
Boreholes
for
piezometer
and
monitoring
well
installation
were
advanced
using
11­
cm
inner
diameter,
150
cm­
long
hollow
stem
augers
mounted
on
a
drilling
rig.
Soil
samples
were
collected
during
drilling
operations
using
a
5­
cm
outer­
diameter,
61­
cm­
long
split­
spoon
sampling
device.
Split­
spoon
samples
were
placed
on
plastic
sheeting
for
lithologic
description
and
partitioned
into
discrete
lithologic
horizons,
sub­
sampled,
then
shipped
to
a
contract
laboratory
for
soil
characterization.
Shelby
tube
sampling
was
conducted
to
obtain
relatively
undisturbed
soil
samples
for
the
measurement
of
vertical
saturated
hydraulic
conductivity
and
undisturbed
bulk
density.
Soil
samples
were
collected
using
8­
cm
o.
d.,
76­
cm­
long
steel
Shelby
tubes.
A
hollow­
stem
augerdrilling
rig
was
used
to
advance
the
Shelby
tube
into
the
soil
profile.
Samples
were
scheduled
to
be
collected
in
61­
cm
increments
from
land
surface
to
ground
water;
however
the
presence
of
coarse
materials
(
cobbles
and
stones)
in
the
vadose
zone
prevented
the
collection
of
continuous
cores
at
two
PGW
study
locations.

Aquifer
properties
were
assessed
by
observations
made
during
piezometer
and
monitoring­
well
drilling
activities,
and
by
measurements
recorded
after
instrumentation.
Aquifer
characterization
included
the
types
of
materials
encountered
below
the
water
table,
depths
to
ground
water,
ground
water
flow
direction,
hydraulic
gradient,
hydraulic
conductivity,
porosity,
and
pore­
water
velocity.
­
138­

Table
1:
Topography
and
Soil
Characterization
Summary
PGW
Study
Location
Slope
(%)
NRCS
Soil
Series
*
Surface
Soil
Organic
Matter
(%)*
Surface
Soil
pH
Subsoil
Textures
*
Avg.
Hydraulic
Conductivity
§

(
mm/
hr)

Wisconsin
<
0.5
Richford
loamy
sand
1.6
¶
6.4
Loamy
Sand
Sand
Sandy
loam
0­
1.2
m
1.2­
2.4
m
2.4­
3.6
m
3.6­
4.8
m
>
4.8
m
177
358
810
1482
776
Ohio
<
0.5
Genessee
silt
loam
Fox
silt
loam
2.9
7.7
Clay
loam
Loam
Sandy
loam
0­
1.2
m
1.2­
2.4
m
2.4­
3.6
m
3.6­
4.8
m
>
4.8
m
293
153
NA
NA
NA
Minnesota
<
0.5
Estherville
sandy
loam
3.5
6.3
Sandy
loam
Loamy
sand
Sand
0­
1.2
m
1.2­
2.4
m
2.4­
3.6
m
3.6­
4.8
m
>
4.8
m
180
331
NA
NA
NA
Nebraska
<
0.5
Kenesaw
silt
loam
Coly­
Kenesaw
silt
loam
1.8
5.7
Loam
Silt
loam
0­
1.2
m
1.2­
2.4
m
2.4­
3.6
m
3.6­
4.8
m
>
4.8
m
75
45
28
18
84
Iowa
<
2
Marshall
silty
clay
loam
Minden
silty
clay
loam
3.9
5.6
Silty
clay
loam
Silt
loam
0­
1.2
m
1.2­
2.4
m
2.4­
3.6
m
3.6­
4.8
m
>
4.8
m
207
84
172
87
1.0
Indiana
<
0.5
Door
loam
Lydick
loam
3.0
6.7
Sandy
clay
loam
Sandy
loam
Sand
0­
1.2
m
1.2­
2.4
m
2.4­
3.6
m
3.6­
4.8
m
>
4.8
m
64
190
244
742
978
­
139­

Pennsylvania
<
2
Clarksburg
silt
loam
Duffield
silt
loam
2.7
6.3
Loam
Sandy
loam
0­
1.2
m
1.2­
2.4
m
2.4­
3.6
m
3.6­
4.8
m
>
4.8
m
NA
382
138
95
19
NA
Delaware
<
1
Sassafras
sandy
loam
2.9
5.8
Sandy
loam
Loamy
sand
Sand
0­
1.2
m
1.2­
2.4
m
2.4­
3.6
m
3.6­
4.8
m
>
4.8
m
30
86
30
129
NA
­
140­

Depths
to
ground
water
were
recorded
to
assess
ground
water
flow
direction
and
hydraulic
gradients
at
each
study
location.
Monitoring
wells
were
instrumented
with
dedicated
submersible
pumps;
consequently
depths
to
ground
water
were
only
measured
in
the
piezometers
located
at
the
corners
of
the
test
plot
and
on
the
periphery
of
the
study
location.
Depths
to
ground
water
were
measured
manually
from
a
fixed
surveyed
point
on
the
top
of
the
casing
of
each
piezometer.

The
depths
to
ground
water
and
corresponding
elevations
were
used
to
create
ground
water
elevation
contour
maps
for
each
ground
water­
sampling
event
at
each
study
location.
Ground
water
flow
direction
and
hydraulic
gradient
were
assessed
from
these
contour
maps.

Hydraulic
gradients
were
estimated
by
calculating
the
difference
in
ground
water
elevation
(
m)
between
two
points
along
a
line­
oriented
perpendicular
to
the
ground
water
elevation
contour
lines.
The
difference
between
ground
water
elevations
was
divided
by
the
horizontal
distance
between
the
two
points
to
obtain
a
resulting
gradient
(
m/
m).
­
141­

Table
2:
Aquifer
Characterization
Summary
PGW
Study
Aquifer
soil
textures
determined*
Depth
to
ground
water
*

(
m)
Hydraulic
Gradient
(
m/
m)
§
Hydraulic
Conductivity
(
m/
day)
Porosity
(%)
Pore­
water
velocity
(
m/
day)
¶

Wisconsin
Loamy
sand
Sandy
loam
Sand
7.6­
10
1.5
x
10­
3
0.16
40
1.9
x
10­
3
Ohio
Sandy
loam
Loamy
sand
0.6­
5.2
4.5
x
10­
4
17.9
35
0.8
x
10­
1
Minnesota
Sand
Loamy
sand
Sandy
loam
4.8­
6.4
2.5
x
10­
4
14.5
32
0.4
x
10­
1
Nebraska
Silt
loam
Loam
Sandy
loam
7.0­
9.7
5.4
x
10­
4
0.8
38
0.4
x
10­
2
Iowa
Sand
Silt
loam
Loam
1.2­
8.5
6.6
x
10­
4
13.1
32
0.9
x
10­
1
Indiana
Sand
7­
9.1
1.0
x
10­
3
6.0
32
0.6
x
10­
1
Pennsylvania
Sandy
loam
Loam
1.8 
7.3
2.6
x
10­
3
1.7
40
0.4
x
10­
1
Delaware
Sand
Sandy
loam
Loamy
sand
3.3­
6.1
4.2
x
10­
4
1.4
32
0.6
x
10­
2
*
Soil
texture
determined
by
3­
fraction
analysis
(%
sand,
silt,
and
clay)
*
Depth
to
ground
water
listed
is
below
ground
surface,
and
minimum
and
maximum
value
determined
in
the
test
plot
corner
piezometers
during
the
course
of
the
study
§
Hydraulic
gradient
listed
is
the
average
value
determined
during
the
course
of
the
study
¶
Pore­
water
velocity
listed
is
the
average
value
determined
during
the
course
of
the
study
Hydraulic
conductivity
of
the
aquifer
was
estimated
by
conducting
rising
or
falling­
head
slug
tests
in
randomly
selected
monitoring
wells
located
in
the
test
plot.
The
slug
test
data
were
used
to
calculate
the
hydraulic
conductivity
of
the
aquifer
in
the
vicinity
of
the
well,
using
standard
formulae
for
monitoring
wells
screened
in
unconfined
aquifers
(
Bouwer
et
al.,
1976
and
1989).

Porosity
of
the
aquifer
material
was
not
measured
directly,
but
was
estimated
empirically
based
on
the
types
of
sediments
(
Driscoll,
1986)
encountered
below
the
water
table
during
monitoring
well
installation.
Pore­
water
velocity
values
were
calculated
using
hydraulic
conductivity,
hydraulic
gradient,
and
porosity
data.

Study
design
and
instrumentation
­
142­

Each
PGW
site
was
instrumented
in
accordance
with
the
US
EPA
draft
guidance
document
on
the
conduct
of
PGW
studies
(
US
EPA,
1995
and
1998)
with
the
exception
of
the
Wisconsin
and
Ohio
PGW
studies,
which
were
initiated
prior
to
the
issue
of
US
EPA's
1995
guidance
document.
The
US
EPA
agreed
to
the
instrumentation
configuration
for
these
studies
prior
to
instrumentation.

Each
PGW
study
consisted
of
an
approximately
1.2­
ha
test
plot
adjacent
to
a
0.2­
ha
control
plot.
The
control
plot
was
located
hydrogeologically
upgradient
from
the
test
plot
(
Fig.
1).
The
test
and
control
plots
were
instrumented
with
suction
lysimeters
(
for
sampling
soil­
pore
water)
installed
at
varying
depths
within
the
vadose
zone,
and
ground
water
monitoring
wells
screened
at
varying
depths
within
the
aquifer
(
Fig.
1).
Figure
1:
PGW
Study
Layout
and
Instrumentation
In
summary,
each
PGW
site
was
instrumented
with
seven
piezometers
to
measure
depths
to
ground
water
and
to
monitor
variations
in
ground
water
flow
direction
and
hydraulic
gradient.
A
single
piezometer
was
installed
at
each
of
the
four­
corners
of
the
test
plot
(
Fig.
1),
and
three
piezometers
were
located
around
the
periphery
of
the
PGW
study
location.

Piezometers
were
constructed
with
flush­
threaded,
5­
cm­
i.
d.,
Schedule
40
polyvinyl
chloride
(
PVC)
casing
and
0.25
mm
slotted
screen.
Piezometers
were
completed
above
ground
with
a
concrete
pad,
steel
protective
outer
casing,
and
locking
cap.
Horizontal
coordinates
and
top­
ofcasing
elevations
of
each
piezometer
were
professionally
surveyed.

Monitoring
wells
were
installed
to
collect
ground
water
samples
and
were
arranged
in
clusters
within
each
test
plot.
For
the
Wisconsin
and
Ohio
PGW
studies,
ten
monitoring
wells
were
installed
at
each
PGW
study
location.
One
monitoring
well
was
installed
in
each
control
plot,
and
three
clusters
of
three
monitoring
wells
were
installed
in
each
test
plot.
The
clusters
consisted
of
one
shallow,
one
deep,
and
one
extra
deep
monitoring
well
(
Fig.
2).

For
the
six
remaining
PGW
studies,
17
monitoring
wells
were
installed
at
each
PGW
study
location.
One
monitoring
well
was
installed
in
each
control
plot,
and
eight
clusters
of
two
Test
Plot
Control
Plot
Piezometer(
4)

Typical
Monitoring
Well
Cluster
Typical
Suction
Lysimeter
Cluster
Typical
Groundwater
Elevation
­
143­

monitoring
wells
were
installed
in
each
test
plot.
The
clusters
consisted
of
one
shallow
and
one
deep
monitoring
well
(
Fig.
3).

Approximate
monitoring
well
screen
lengths
and
positions
were
as
follows:

Control
plot
well:
4.5
m
screen
positioned
with
approximately
1.5
m
of
screen
above
the
water
table
at
the
time
of
well
installation.

Test
plot
shallow
wells:
3
m
screen
positioned
with
approximately
1.5
m
of
screen
above
the
water
table
at
the
time
of
well
installation.

Test
plot
deep
wells:
1.5
m
screen
positioned
approximately
1.5
m
below
the
water
table
at
the
time
of
well
installation.

Test
plot
extra­
deep
wells:
(
Wisconsin
and
Ohio
only):
1.5
m
screen
positioned
approximately
3
m
below
the
water
table
at
the
time
of
well
installation.

The
positioning
of
each
monitoring
well
screen
at
each
PGW
site
was
dictated
by
the
depth
to
ground
water
encountered
during
monitoring
well
borehole
advancement.
Screens
for
the
shallow
monitoring
wells
were
3
m
in
length,
to
enable
ground
water
samples
to
be
collected
in
the
event
the
depth
to
ground
water
increased
after
monitoring
well
installation.
Monitoring
well
clusters
were
installed
in
a
linear
arrangement,
with
a
3­
meter
distance
between
each
monitoring
well
within
a
cluster.
Monitoring
wells
were
constructed
as
described
for
the
piezometers.
­
144­

APPENDIX
12.6.
Analytical
Method
Summary
Descriptions
for
the
ARP
Monitoring
Programs
SDWS
Study
(
from
Hackett
et
al.,
2005)

Sample
Analysis
We
employed
two
analytical
methods,
one
for
parent
compounds
and
the
other
for
degradates.
Both
relied
on
mass
spectrometry
for
detection.
Samples
were
generally
not
filtered
prior
to
analysis,
although
raw
water
samples
occasionally
required
the
use
of
a
sea
sand
filtration
step.
Parent
herbicides
were
analyzed
using
stable
isotope
dilution
gas
chromatography/
mass
spectrometry
(
GC/
MS),
preceded
by
solid
phase
extraction
for
cleanup
and
concentration
(
Fuhrman
et
al.
1996).
The
method
involved
addition
of
deuterated
analogs
of
each
analyte,
as
internal
standards,
to
a
200
mL
water
sample
prior
to
extraction,
concentration,
and
analysis.
We
analyzed
for
the
oxanilic
and
sulfonic
acid
degradates
of
acetochlor,
alachlor,
and
metolachlor
by
direct
aqueous
injection
reversed­
phase
liquid
chromatography
tandem
mass
spectrometry
(
LC/
MS/
MS).
The
samples
were
injected
directly
into
an
LC/
MS/
MS
(
HP1100/
Sciex
API­
3000)
without
prior
concentration,
cleanup
or
filtration
(
Hackett
et
al.
2003).
All
surface
water
samples
were
refrigerated
at
2­
10
°
C
upon
receipt
at
Monsanto,
before
extraction
or
preparation
for
analysis.
Replicate
samples
were
transferred
to
a
freezer
at
 
20

5
°
C.
Sample
extracts
were
either
analyzed
immediately
or
refrigerated
at
2­
10
°
C
until
analysis.
All
reported
analytes
demonstrated
acceptable
storage
stability
under
these
conditions,
which
was
confirmed
both
through
separate
storage
stability
studies
and
by
analysis
of
field­
fortified
samples.
The
median
times
from
collection
to
extraction
and
collection
to
analysis
were
7
and
9
days,
respectively.

SGW
Study
(
from
de
Guzman
et
al.,
2005)

Analytical
Methodology
Ground
water
samples
were
analyzed
for
parent
acetochlor,
alachlor,
atrazine
and
metolachlor
during
the
first
four
years
of
the
SGM.
For
the
final
three
years,
samples
were
also
analyzed
for
the
tertiary
amide
soil
degradates
of
acetochlor,
alachlor
and
metolachlor,
specifically
tertiary
amide
sulfonic
acid
(
ESA)
and
tertiary
amide
oxanilic
acid
(
OXA).
A
complete
list
of
the
target
compounds,
including
common
name,
chemical
name
and
CAS
number,
is
as
follows:
acetochlor
(
2­
chloro­
N­(
ethoxylmethyl)­
N­(
2­
ethyl­
6­
methylphenyl)­
acetamide),
CAS
No.
34256­
82­
1,
alachlor
(
2­
chloro­
N­(
2,6­
diethylphenyl)­
N­(
methoxymethyl)­
acetamide),
CAS
No.
15972­
60­
8,
atrazine
(
6­
chloro­
N­
ethyl­
N'­(
1­
methylethyl)­
1,3,5­
triazine­
2,4­
diamine),
CAS
No.
1912­
24­
9,
metolachlor
(
2­
chloro­
N­(
2­
ethyl­
6­
methylphenyl)­
N­(
2­
methoxy­
1­
methylethyl)­
acetamide),
CAS
No.
51218­
45­
2,
acetochlor
oxanilic
acid
([(
ethoxymethyl)(
2­
ethyl­
6­
methylphenyl)
amino]­
oxoacetic
acid,
sodium
salt),
CAS
No.
194992­
44­
4
(
free
acid),
acetochlor
sulfonic
acid
(
2­[(
ethoxymethyl)(
2­
ethyl­
6­
methylphenyl)
amino]­
2­
oxoethanesulfonic
acid,
­
145­

sodium
salt),
CAS
No.
187022­
11­
3
(
free
acid),
alachlor
oxanilic
acid
([(
2,6­
diethylphenyl)(
methoxymethyl)
amino]­
oxoacetic
acid,
sodium
salt),
CAS
Nos.
140939­
14­
6
(
free
acid)
and
171262­
17­
2
(
free
acid),
alachlor
sulfonic
acid
(
2­[(
2,6­
diethylphenyl)(
methoxymethyl)
amino]­
2­
oxoethanesulfonic
acid,
sodium
salt),
CAS
Nos.
140939­
15­
7
(
sodium
salt)
and
142363­
53­
9
(
free
acid),
metolachlor
oxanilic
acid
([(
2­
ethyl­
6­
methylphenyl)(
2­
methoxy­
1­
methylethyl)
amino]
oxoacetic
acid,
sodium
salt),
CAS
No.
152019­
73­
3
(
free
acid),
and
metolachlor
sulfonic
acid
(
2­[(
2­
ethyl­
6­
methylphenyl)(
2­
methoxy­
1­
methylethyl))
amino]­
2­
oxoethanesulfonic
acid,
sodium
salt),
CAS
No.
171118­
09­
5
(
free
acid).
GC/
MS
method
for
parent
herbicides.
Parent
herbicides
were
analyzed
using
stable
isotope
dilution
gas
chromatography/
mass
spectrometry
(
GC/
MS),
which
was
preceded
by
solid
phase
extraction
for
cleanup
and
concentration.
The
method
involved
addition
of
deuterated
analogs
of
each
analyte,
as
surrogates,
to
the
200­
mL
sample
prior
to
extraction,
concentration,
and
analysis
(
Fuhrman
et
al.,
1996).
Based
on
actual
prior
fortification
data,
the
Limit
of
Detection
(
LOD)
and
Limit
of
Quantification
(
LOQ)
of
this
method
was
determined
to
be
0.03
µ
g
L­
1
and
0.05
µ
g
L­
1,
respectively,
for
all
non­
polar
analytes
(
Hackett
et
al.,
2003),
with
the
exception
of
alachlor,
whose
LOD
was
0.05
µ
g
L­
1
due
to
higher
background
levels
of
this
compound.
LC/
MS/
MS
method
for
chloroacetanilide
degradates.
The
ESA
and
OXA
soil
degradates
of
acetochlor,
alachlor,
and
metolachlor
were
analyzed
by
direct
aqueous
injection
reversed­
phase
liquid
chromatography
tandem
mass
spectrometry
(
LC/
MS/
MS).
The
samples
were
injected
directly
into
the
LC/
MS/
MS
(
HP1100/
Sciex
API­
3000)
without
prior
concentration,
cleanup
or
filtration
(
Hackett
et
al.,
2003).
Based
on
actual
prior
fortification
data,
the
LOQ
of
all
six
polar
degradates
was
determined
to
be
0.50
µ
g
L­
1.
The
LOD
for
the
three
OXA
soil
degradates
was
0.10
µ
g
L­
1,
and
for
the
three
ESA
soil
degradates,
the
LOD
was
0.20
µ
g
L­
1.
Storage
stability.
All
ground
water
samples
were
stored
in
a
refrigerator
at
2
­
10
°
C
upon
receipt
at
Monsanto,
before
extraction
or
preparation
for
analysis.
Replicate
samples
were
transferred
to
a
freezer
at
 
20
°
C

5
°
C.
Sample
extracts
were
either
analyzed
immediately
or
stored
in
a
refrigerator
at
2
­
10
°
C
before
analysis.
All
reported
analytes
demonstrated
acceptable
storage
stability
under
these
conditions.

PGW
Study
(
from
Newcombe
et
al.,
2005)

Analytical
methodology
Three
laboratory
facilities
were
used
to
analyze
acetochlor
PGW
program
samples;
(
1)
Zeneca
Agrochemicals,
Jealott's
Hill
Research
Centre,
Bracknell,
United
Kingdom,
(
2)
Covance
Laboratories,
Harrogate,
United
Kingdom,
(
3)
Monsanto
Company
St.
Louis,
MO,
USA.
Limits
of
detection
(
LOD)
and
LOQ
varied
slightly
among
the
methods
used
at
the
various
laboratories
and
are
briefly
summarized
below.
The
common
names,
chemical
names
and
structures,
and
CAS
registry
numbers
of
the
analytes
of
interest
are
provided
in
Table
4.

Potassium
bromide
 
soil­
pore
water
and
ground
water
Bromide
residues
in
water
were
determined
using
ion
chromatography
(
IC)
with
conductivity
detection.
Water
samples
were
analyzed
directly
by
IC
with
no
sample
pre­
treatment
required.
The
LOQ
of
the
analytical
method
was
100
µ
g
L­
1
and
the
LOD
approximately
30
µ
g
L­
1.
Acetochlor
 
soil
­
146­

Acetochlor
residues
in
soil
were
determined
by
gas­
liquid
chromatography
(
GC)
using
a
Mass
Selective
Detector
(
MSD).
The
LOQ
of
the
analytical
method
was
0.01
mg
kg­
1
and
the
LOD
was
approximately
0.005
mg
kg­
1.
For
the
application
rate
verification
analysis,
where
acetochlor
residues
were
significantly
higher,
the
LOD
was
calculated
as
0.02
mg
kg­
1.
­
147­

APPENDIX
12.7.
Statistical
Analyses
for
the
ARP
monitoring
Studies
12.7.1.
SDWS
12.7.1.1.
Pearson
Product
Moment
Correlation
Coefficients
for
Raw
vs.
Finished
Water
Samples
Correlation
coefficients
and
coefficients
of
determination
for
raw
versus
finished
water
samples
for
each
of
the
P­
1
study
sites
in
the
surface
drinking
water
data
set
were
derived
using
the
CORR
procedure
in
SAS
version
9.1
(
SAS
2004).
This
analysis
was
aimed
at
determining
whether
finished
water
concentrations
observed
at
facilities
that
utilize
activated
charcoal
in
water
treatment
(
the
only
sites
for
which
the
raw
water
analytical
results
are
available)
could
be
predicted
by
raw
water
concentrations
observed
at
that
facility.
Finished
and
raw
water
observations
were
paired
by
site
and
by
the
date
the
sample
was
collected.

A
correlation
coefficient
(
r)
is
an
index
of
the
degree
linear
association
of
two
variables,
X
and
Y
generated
using
a
simple
linear
regression
model
to
predict
variable
Y
from
variable
X.
Correlation
coefficients
are
directional
in
that
variables
exhibit
positive
and
negative
correlations.
The
coefficient
of
determination
(
r2)
provides
an
estimate
of
how
well
the
relationship
can
be
defined
by
a
straight
line
and
is
neither
positive
nor
negative.

Table
35
provides
correlation
coefficients
for
raw
versus
finished
surface
water
samples
for
all
P­
1
sites
in
the
SDWS
data
set.
In
nearly
half
the
cases
(
43%),
finished
water
samples
were
moderately
to
strongly
associated
(
r
>=
0.75)
with
observed
raw
water
concentrations.
For
30%
of
the
sites,
raw
water
concentrations
explained
at
least
75%
of
the
variability
in
finished
water
concentrations,
and
in
50
%
of
the
cases
raw
water
concentrations
explained
at
least
half
(
r2
>=
0.5)
of
the
variability
in
finished
water
concentrations
using
a
simple
linear
model.
In
general
increasing
the
sample
size
(
N)
did
not
result
in
an
increase
in
correlation
between
raw
and
finished
water
concentrations.
Lack
of
correspondence
for
some
sites
may
be
partially
a
result
of
differences
in
sampling
times
for
raw
and
finished
samples
and
the
uncertainty
in
residence
time
for
each
of
the
water
treatment
facilities.
Because
there
is
a
time
lag
from
when
water
enters
the
intake
(
raw
water)
to
when
the
treatment
processes
in
completed
(
finished
water)
it
is
unlikely
that
raw
and
finished
samples
were
taken
from
the
same
volume
of
water.

Table
35.
Pearson
product­
moment
correlation
coefficients
for
raw
versus
finished
water
parent
acetochlor
concentrations
observed
at
the
P­
1
sites
in
the
SDWS
monitoring
data
set.

Site
ID
N
Correlation
Coefficient
(
r)
Coefficient
of
Determination
(
r2)

168­
PA­
IL
98
0.9932
0.9864
1009­
CO­
MO
83
0.9895
0.9792
­
148­

Table
35.
Pearson
product­
moment
correlation
coefficients
for
raw
versus
finished
water
parent
acetochlor
concentrations
observed
at
the
P­
1
sites
in
the
SDWS
monitoring
data
set.

Site
ID
N
Correlation
Coefficient
(
r)
Coefficient
of
Determination
(
r2)

346­
SA­
IN
28
0.9841
0.9684
89­
MI­
KS
71
0.9739
0.9484
301­
BL­
NE
14
0.9696
0.9401
1070­
WY­
MO
84
0.9692
0.9393
228­
SA­
IL
98
0.9552
0.9124
225­
CE­
IL
70
0.9409
0.8853
606­
KA­
IL
98
0.9276
0.8604
582­
WI­
IA
98
0.9039
0.8171
344­
DU­
IN
98
0.9016
0.8128
556­
DA­
IA
70
0.8858
0.7847
152­
BR­
IL
83
0.8745
0.7648
603­
BL­
IL
98
0.8545
0.7302
259­
SP­
IL
98
0.8478
0.7188
557­
DM­
IA
91
0.8390
0.7039
351­
SE­
IN
43
0.7851
0.6164
245­
OL­
IL
98
0.7773
0.6042
577­
RA­
IA
98
0.7551
0.5702
268­
NA­
IL
98
0.7346
0.5397
1092­
SL­
MO
27
0.7324
0.5365
574­
OS­
IA
98
0.7101
0.5042
197­
EL­
IL
98
0.6670
0.4449
1016­
HI­
MO
70
0.6544
0.4282
155­
CH­
IL
42
0.6101
0.3722
328­
KO­
IN
57
0.5966
0.3559
222­
HI­
IL
98
0.5764
0.3323
244­
SP­
IL
98
0.5636
0.3177
296­
SC­
MN
98
0.4836
0.2338
170­
AL­
IL
98
0.4469
0.1997
345­
RI­
IN
43
0.4403
0.1938
593­
HE­
PA
98
0.3897
0.1519
997­
WE­
PA
98
0.3806
0.1449
452­
MC­
OH
14
0.3340
0.1116
242­
CO­
IL
56
0.3283
0.1078
18­
OK­
WI
98
0.2517
0.0633
548­
CH­
IA
28
0.2080
0.0433
1069­
VA­
MO
84
0.2036
0.0414
569­
MI­
IA
83
0.1976
0.0390
1038­
GA­
MO
14
0.1393
0.0194
­
149­

Table
35.
Pearson
product­
moment
correlation
coefficients
for
raw
versus
finished
water
parent
acetochlor
concentrations
observed
at
the
P­
1
sites
in
the
SDWS
monitoring
data
set.

Site
ID
N
Correlation
Coefficient
(
r)
Coefficient
of
Determination
(
r2)

737­
AW­
PA
98
0.1008
0.0102
332­
MC­
IN
98
0.0935
0.0087
13­
AP­
WI
98
0.0517
0.0027
371­
AL­
OH
14
0.0146
0.0002
The
effect
of
water
treatment
on
acetochlor
concentrations
in
the
surface
drinking
water
supplies
was
also
examined.
A
paired
two
sample
t­
test
for
means
was
performed
on
those
sites
and
sample
dates
that
had
both
raw
and
finished
water
observations.
Results
of
the
ttest
are
provided
in
Table
36.
Statistical
analysis
indicates
that
water
treatment
plants
that
use
granulated
activated
carbon
(
GAC)
or
powdered
activated
carbon
(
PAC)
significantly
reduce
acetochlor
concentrations
in
drinking
water
(
p
<
0.001)

Table
36.
Paired
t­
test
for
raw
versus
finished
water
samples.

RAW
FINISHED
Mean
0.076
0.030
Variance
0.097
0.030
Observations
3325
3325
Pearson
Correlation
0.858
Hypothesized
Mean
Difference
0.000
df
3324.000
t
Stat
14.296
P(
T<=
t)
one­
tail
<
0.001
t
Critical
one­
tail
1.645
P(
T<=
t)
two­
tail
<
0.001
t
Critical
two­
tail
1.961
­
150­

12.7.1.2.
Analysis
of
Factors
Related
to
Occurrence
of
Acetochlor
For
parent
acetochlor,
the
most
toxic
of
residues,
surface
water
is
the
dominant
medium
of
exposure.
Consequently,
the
focus
of
statistical
analysis
was
on
factors
related
to
occurrence
in
surface
drinking
water
supplies.
Two
levels
of
analysis
were
required.
The
first
analysis
examined
environmental
variables
could
potentially
explain
the
temporal
variability
in
acetochlor
concentrations
within
a
site
(
e.
g,
rainfall
amounts).
The
second
level
of
analysis
examined
environmental
variables
that
could
potentially
explain
the
spatial
variability
among
sites
(
e.
g.,
watershed
size,
corn
intensity,
etc.,).

The
tables
in
the
following
section
present
Pearson's
correlation
matrices
for
surface
drinking
water
sites,
individually
for
raw
and
finished
water
samples.
Correlation
coefficients
greater
than
0.5
are
shown
in
shaded
cells
and
bold
font.

In
general,
the
ancillary
variables
that
were
available
were
unable
to
explain
a
significant
amount
of
the
variability
in
maximum
observed
concentrations
(
acute
exposure),
average
TWAMS,
and
maximum
TWAMs
(
chronic
exposure).
It
was
originally
expected
that
acetochlor
acute
and
chronic
exposure
would
be
moderately
to
strongly
correlated
with
the
variability
in
acetochlor
sales
in
the
associated
watersheds,
however
sales
were
only
weakly
correlated
(
r
<
0.5).

Some
associations
were
observed
between
ancillary
variables
as
expected.
For
example,
watershed
corn
intensity
was
moderately
to
strongly
correlated
with
the
watershed
runoff
curve
number
(
RCN)
with
correlation
coefficients
(
r2)
ranging
from
0.78
for
all
sites
where
raw
water
samples
were
collected
to
0.82
for
only
those
sites
where
finished
water
samples
were
collected.
The
correlation
between
runoff
curve
number
and
watershed
corn
intensity
is
not
surprising,
since
land
cover
is
a
factor
in
generating
the
curve
number.

The
lack
of
correlation
between
watershed
corn
intensity
(%
of
watershed
cropped
as
corn)
and
watershed
sales
was
unexpected.
Part
of
the
explanation
may
be
related
to
violations
of
the
assumption
that
acetochlor
sold
in
a
county
is
actually
applied
in
the
same
county.
Additionally,
the
total
area
cropped
in
a
watershed
is
likely
to
be
more
correlated
to
total
sales
in
a
watershed.
Refining
the
sales
estimate
to
be
more
reflective
of
actual
usage
in
the
county
is
also
likely
to
improve
the
correlation.
In
the
current
analysis,
maximum
and
average
watershed
sales
were
determined
using
GIS
to
compute
an
average
and
maximum
sales
value
for
all
counties
that
were
wholly
or
partially
within
the
drainage
area
for
a
site.
This
is
only
a
coarse
estimate
that
could
be
refined
by
weighting
the
values
in
each
county
by
the
fraction
of
the
county
that
is
within
the
drainage
area.
One
option
would
be
to
employ
the
methodology
used
by
the
USGS
to
generate
pesticide
usage.
Additional
analysis
may
be
necessary
to
investigate
the
relationship
between
watershed
sales
and
watershed
corn
intensity.
This
may
­
151­

12.7.2.
CORRELATION
MATRICES
(
r2)
FOR
FACTORS
RELATED
TO
THE
OCCURRENCE
OF
ACETOCHLOR
IN
SURFACE
DRINKING
WATER
SUPPLIES.
­
152­

TYPE=
RAW
ANALYTE=
ACETOCHLOR
MAX
CONC
MAX
TWAM
AVG
TWAM
MAX_
WS_
SALES
AVG_
WS_
SALES
WS_
CORN_
INT
WSHED_
AREA_
ACRES
WS_
RUNOFF_
RATING
WS_
RCN
AVE_
PPT
AVE_
SPR(
APR_
MAY_
JUN
E)

MAX
CONC
1
0.90968
0.80287
­
0.03763
0.0155
0.02844
­
0.099
0.19272
­
0.03778
0.09178
0.12141
p=
<.
0001
<.
0001
0.8201
0.9254
0.8414
0.5488
0.1711
0.7903
0.5441
0.4215
MAX
TWAM
1
0.91683
0.10095
0.14664
0.04916
­
0.07858
0.31534
0.03282
­
0.03133
0.10452
p=
<.
0001
0.5409
0.373
0.7293
0.6344
0.0228
0.8173
0.8363
0.4894
AVG
TWAM
1
0.16822
0.2084
0.1089
­
0.1052
0.39726
0.13515
­
0.05047
0.0989
p=
0.306
0.203
0.4422
0.5239
0.0035
0.3394
0.739
0.5132
MAX_
WS_
SALES
1
0.91023
­
0.06938
0.04003
0.69005
0.01621
­
0.23407
­
0.18546
p=
<.
0001
0.6747
0.8088
<.
0001
0.922
0.1515
0.2583
AVG_
WS_
SALES
1
­
0.02849
­
0.14627
0.76207
0.02463
­
0.08057
­
0.00725
p=
0.8633
0.3743
<.
0001
0.8817
0.6258
0.9651
WS_
CORN_
INT
1
0.0049
0.18291
0.78228
0.09362
0.28261
p=
0.9764
0.1943
<.
0001
0.536
0.057
WSHED_
AREA_
ACRES
1
­
0.22928
­
0.05634
­
0.66987
­
0.64615
p=
0.1603
0.7334
<.
0001
<.
0001
WS_
RUNOFF_
RATING
1
0.2287
­
0.1193
0.02634
p=
0.1029
0.4297
0.862
WS_
RCN
1
0.26665
0.25775
p=
0.0732
0.0837
AVE_
PPT
1
0.70699
p=
<.
0001
AVE_
SPR(
APR_
MAY_
JUNE)
1
p=

TYPE=
RAW
ANALYTE=
AC_
ESA
MAX
CONC
MAX
TWAM
AVG
TWAM
MAX_
WS_
SALES
AVG_
WS_
SALES
WS_
CORN_
INT
WSHED_
AREA_
ACRES
WS_
RUNOFF_
RATING
WS_
RCN
AVE_
PPT
AVE_
SPR(
APR_
MAY_
JUN
E)

MAX
CONC
1
0.93765
0.92534
0.35044
0.40398
­
0.00239
­
0.18141
0.50226
0.04886
0.08075
0.03614
p=
<.
0001
<.
0001
0.031
0.0119
0.9867
0.2757
0.0002
0.7335
0.598
0.8137
MAX
TWAM
1
0.98928
0.38003
0.46886
0.0824
­
0.22055
0.51583
0.13918
0.08355
0.05036
p=
<.
0001
0.0186
0.003
0.5654
0.1833
0.0001
0.33
0.5853
0.7425
AVG
TWAM
1
0.36782
0.44719
0.08639
­
0.2176
0.53202
0.16759
0.07717
0.02955
p=
0.0231
0.0049
0.5466
0.1894
<.
0001
0.2398
0.6144
0.8472
MAX_
WS_
SALES
1
0.90986
­
0.07213
0.03606
0.6861
0.01931
­
0.21605
­
0.17224
p=
<.
0001
0.6669
0.8298
<.
0001
0.9084
0.1927
0.3011
AVG_
WS_
SALES
1
­
0.03033
­
0.14992
0.76113
0.02693
­
0.06323
0.00493
p=
0.8566
0.369
<.
0001
0.8725
0.7061
0.9766
WS_
CORN_
INT
1
0.00394
0.1833
0.78283
0.10375
0.29088
p=
0.9813
0.1979
<.
0001
0.4976
0.0526
WSHED_
AREA_
ACRES
1
­
0.23749
­
0.0552
­
0.68354
­
0.6485
p=
0.1511
0.742
<.
0001
<.
0001
WS_
RUNOFF_
RATING
1
0.23354
­
0.09106
0.04801
p=
0.0991
0.5519
0.7541
WS_
RCN
1
0.27109
0.25881
p=
0.0717
0.086
AVE_
PPT
1
0.69863
p=
<.
0001
AVE_
SPR(
APR_
MAY_
JUNE)
1
p=

MAX
CONC
=
maximum
observed
concentration
at
each
site;
MAX
TWAM
=
maximum
time­
weighted
annualized
mean
for
each
site;
AVG
TWAM
=
average
time­
weighted
annualized
mean
for
each
site;
MAX_
WS_
SAL
=
average
sales
(
94­
03)
for
the
county
with
the
highest
average
sales
in
the
watershed;
AVG_
WS_
SAL
=
average
sales
(
94­
03)
for
all
counties
located
in
the
intake
drainage
area;
WS_
CORN_
IN
=
watershed
corn
intensity
(
defined
as
the
percent
of
total
watershed
area
planted
in
corn
based
on
area­
weighted
county
level
USDA
data
for
1992
(
USDA,
1994);
WSHED_
AREA
=
watershed
area
draining
to
surface
water
intake
location;
WS_
RUNOFF
=
watershed
runoff
rating;
WS_
RCN
=
watershed
runoff
curve
number;
AVE_
PPT
=
30­
yr
average
precipitation
for
the
site;
AVE_
SPR
=
30­
yr
average
spring
rainfall
(
April
­
June).
­
153­

TYPE=
RAW
ANALYTE=
AC_
OXA
MAX
CONC
MAX
TWAM
AVG
TWAM
MAX_
WS_
SALES
AVG_
WS_
SALES
WS_
CORN_
INT
WSHED_
AREA_
ACRES
WS_
RUNOFF_
RATING
WS_
RCN
AVE_
PPT
AVE_
SPR(
APR_
MAY_
JUN
E)

MAX
CONC
1
0.93301
0.91866
0.13114
0.18678
­
0.0324
­
0.16615
0.25298
0.05454
0.13176
0.01277
p=
<.
0001
<.
0001
0.4326
0.2615
0.8214
0.3188
0.0733
0.7039
0.3883
0.9337
MAX
TWAM
1
0.98943
0.18408
0.26059
0.08263
­
0.19169
0.26467
0.13518
0.13598
0.06509
p=
<.
0001
0.2686
0.1141
0.5643
0.2489
0.0605
0.3443
0.3731
0.671
AVG
TWAM
1
0.20066
0.2704
0.09252
­
0.18483
0.28301
0.16429
0.12939
0.0396
p=
0.2271
0.1006
0.5184
0.2666
0.0442
0.2493
0.3969
0.7962
MAX_
WS_
SALES
1
0.90986
­
0.07213
0.03606
0.6861
0.01931
­
0.21605
­
0.17224
p=
<.
0001
0.6669
0.8298
<.
0001
0.9084
0.1927
0.3011
AVG_
WS_
SALES
1
­
0.03033
­
0.14992
0.76113
0.02693
­
0.06323
0.00493
p=
0.8566
0.369
<.
0001
0.8725
0.7061
0.9766
WS_
CORN_
INT
1
0.00394
0.1833
0.78283
0.10375
0.29088
p=
0.9813
0.1979
<.
0001
0.4976
0.0526
WSHED_
AREA_
ACRES
1
­
0.23749
­
0.0552
­
0.68354
­
0.6485
p=
0.1511
0.742
<.
0001
<.
0001
WS_
RUNOFF_
RATING
1
0.23354
­
0.09106
0.04801
p=
0.0991
0.5519
0.7541
WS_
RCN
1
0.27109
0.25881
p=
0.0717
0.086
AVE_
PPT
1
0.69863
p=
<.
0001
AVE_
SPR(
APR_
MAY_
JUNE)
1
TYPE=
FINISHED
ANALYTE=
ACETOCHLOR
MAX
CONC
MAX
TWAM
AVG
TWAM
MAX_
WS_
SALES
AVG_
WS_
SALES
WS_
CORN_
INT
WSHED_
AREA_
ACRES
WS_
RUNOF
F_
RATI
NG
WS_
RCN
AVE_
PPT
AVE_
SPR(
APR_
MAY_
JUN
E)

MAX
CONC
1
0.9427
0.86867
0.14362
0.16023
0.09696
­
0.04165
0.21547
0.12951
­
0.01151
­
0.05418
p=
<.
0001
<.
0001
0.0746
0.0464
0.1537
0.6069
0.0014
0.0562
0.8774
0.4676
MAX
TWAM
1
0.89153
0.1383
0.16995
0.14409
­
0.04334
0.24343
0.17299
­
0.05567
­
0.07242
p=
<.
0001
0.0861
0.0345
0.0335
0.5923
0.0003
0.0105
0.4554
0.3313
AVG
TWAM
1
0.22615
0.20047
0.09705
­
0.03819
0.31138
0.18002
­
0.07154
­
0.1104
p=
0.0047
0.0124
0.1533
0.6371
<.
0001
0.0077
0.3372
0.1379
MAX_
WS_
SALES
1
0.89329
­
0.00252
0.0892
0.71138
0.01268
­
0.28792
­
0.26106
p=
<.
0001
0.9752
0.2697
<.
0001
0.8755
0.0003
0.001
AVG_
WS_
SALES
1
0.02687
­
0.0681
0.74732
­
0.01835
­
0.2415
­
0.18251
p=
0.74
0.3998
<.
0001
0.8207
0.0025
0.023
WS_
CORN_
INT
1
­
0.08315
0.2414
0.81822
0.07058
0.26884
p=
0.3037
0.0003
<.
0001
0.3438
0.0002
WSHED_
AREA_
ACRES
1
­
0.08321
­
0.10273
­
0.46226
­
0.44379
p=
0.3033
0.2034
<.
0001
<.
0001
WS_
RUNOFF_
RATING
1
0.22106
­
0.1422
­
0.19303
p=
0.001
0.0555
0.009
WS_
RCN
1
0.11193
0.15593
p=
0.1325
0.0356
AVE_
PPT
1
0.60527
p=
<.
0001
AVE_
SPR(
APR_
MAY_
JUNE)
1
p=

MAX
CONC
=
maximum
observed
concentration
at
each
site;
MAX
TWAM
=
maximum
time­
weighted
annualized
mean
for
each
site;
AVG
TWAM
=
average
time­
weighted
annualized
mean
for
each
site;
MAX_
WS_
SAL
=
average
sales
(
94­
03)
for
the
county
with
the
highest
average
sales
in
the
watershed;
AVG_
WS_
SAL
=
average
sales
(
94­
03)
for
all
counties
located
in
the
intake
drainage
area;
WS_
CORN_
IN
=
watershed
corn
intensity
(
defined
as
the
percent
of
total
watershed
area
planted
in
corn
based
on
area­
weighted
county
level
USDA
data
for
1992
(
USDA,
1994);
WSHED_
AREA
=
watershed
area
draining
to
surface
water
intake
location;
WS_
RUNOFF
=
watershed
runoff
rating;
WS_
RCN
=
watershed
runoff
curve
number;
AVE_
PPT
=
30­
yr
average
precipitation
for
the
site;
AVE_
SPR
=
30­
yr
average
spring
rainfall
(
April
­
June).
­
154­

TYPE=
FINISHED
ANALYTE=
AC_
ESA
MAX
C
ONC
MAX
TWAM
AVG
TWAM
MAX_
WS_
SALES
AVG
_
WS_
SALES
WS_
CORN_
INT
WSHED_
AREA_
ACRES
WS_
RUNOFF_
RATING
WS_
RCN
AVE_
PPT
AVE_
SPR(
APR_
MAY_
JUN
E)

MAX
CONC
1
0.83489
0.81411
0.28225
0.2827
0.15449
­
0.08288
0.42043
0.22937
­
0.07571
­
0.13567
p=
<.
0001
<.
0001
0.0007
0.0007
0.0278
0.3303
<.
0001
0.001
0.3308
0.0804
MAX
TWAM
1
0.9757
0.32186
0.35346
0.20089
­
0.10542
0.44736
0.27
­
0.12625
­
0.17281
p=
<.
0001
0.0001
<.
0001
0.0041
0.2151
<.
0001
<.
0001
0.104
0.0255
AVG
TWAM
1
0.37042
0.40565
0.20608
­
0.09916
0.50223
0.26727
­
0.13097
­
0.18918
p=
<.
0001
<.
0001
0.0032
0.2437
<.
0001
0.0001
0.0916
0.0143
MAX_
WS_
SALES
1
0.89848
0.00297
0.09208
0.71218
0.01218
­
0.30334
­
0.26312
p=
<.
0001
0.9722
0.2792
<.
0001
0.8864
0.0003
0.0017
AVG_
WS_
SALES
1
0.02455
­
0.07068
0.74803
­
0.01119
­
0.23449
­
0.17726
p=
0.7734
0.4067
<.
0001
0.8956
0.0053
0.0362
WS_
CORN_
INT
1
­
0.0814
0.24167
0.82681
0.07485
0.27167
p=
0.339
0.0005
<.
0001
0.3363
0.0004
WSHED_
AREA_
ACRES
1
­
0.0874
­
0.09998
­
0.48056
­
0.44911
p=
0.3045
0.2399
<.
0001
<.
0001
WS_
RUNOFF_
RATING
1
0.23259
­
0.1407
­
0.18504
p=
0.0008
0.0697
0.0167
WS_
RCN
1
0.11822
0.16063
p=
0.1281
0.0381
AVE_
PPT
1
0.62157
p=
<.
0001
AVE_
SPR(
APR_
MAY_
JUNE)
1
p=

FINISHED
ANALYTE=
AC_
OXA
MAX
C
ONC
MAX
TWAM
AVG
TWAM
MAX_
WS_
SALES
AVG
_
WS_
SALES
WS_
CORN_
INT
WSHED_
AREA_
ACRES
WS_
RUNOFF_
RATING
WS_
RCN
AVE_
PPT
AVE_
SPR(
APR_
MAY_
JUN
E)

MAX
CONC
1
0.73401
0.72528
0.20807
0.21914
0.15941
­
0.07487
0.32559
0.22749
0.00018
­
0.04199
p=
<.
0001
<.
0001
0.0136
0.0093
0.0231
0.3793
<.
0001
0.0011
0.9982
0.59
MAX
TWAM
1
0.96304
0.21535
0.27765
0.25049
­
0.10435
0.31642
0.28598
­
0.08452
­
0.07366
p=
<.
0001
0.0106
0.0009
0.0003
0.2198
<.
0001
<.
0001
0.2775
0.3441
AVG
TWAM
1
0.2776
0.3396
0.24915
­
0.09597
0.38097
0.27995
­
0.08497
­
0.09639
p=
0.0009
<.
0001
0.0003
0.2593
<.
0001
<.
0001
0.275
0.2153
MAX_
WS_
SALES
1
0.89848
0.00297
0.09208
0.71218
0.01218
­
0.30334
­
0.26312
p=
<.
0001
0.9722
0.2792
<.
0001
0.8864
0.0003
0.0017
AVG_
WS_
SALES
1
0.02455
­
0.07068
0.74803
­
0.01119
­
0.23449
­
0.17726
p=
0.7734
0.4067
<.
0001
0.8956
0.0053
0.0362
WS_
CORN_
INT
1
­
0.0814
0.24167
0.82681
0.07485
0.27167
p=
0.339
0.0005
<.
0001
0.3363
0.0004
WSHED_
AREA_
ACRES
1
­
0.0874
­
0.09998
­
0.48056
­
0.44911
p=
0.3045
0.2399
<.
0001
<.
0001
WS_
RUNOFF_
RATING
1
0.23259
­
0.1407
­
0.18504
p=
0.0008
0.0697
0.0167
WS_
RCN
1
0.11822
0.16063
p=
0.1281
0.0381
AVE_
PPT
1
0.62157
p=
<.
0001
AVE_
SPR(
APR_
MAY_
JUNE)
1
p=

MAX
CONC
=
maximum
observed
concentration
at
each
site;
MAX
TWAM
=
maximum
time­
weighted
annualized
mean
for
each
site;
AVG
TWAM
=
average
time­
weighted
annualized
mean
for
each
site;
MAX_
WS_
SAL
=
average
sales
(
94­
03)
for
the
county
with
the
highest
average
sales
in
the
watershed;
AVG_
WS_
SAL
=
average
sales
(
94­
03)
for
all
counties
located
in
the
intake
drainage
area;
WS_
CORN_
IN
=
watershed
corn
intensity
(
defined
as
the
percent
of
total
watershed
area
planted
in
corn
based
on
area­
weighted
county
level
USDA
data
for
1992
(
USDA,
1994);
WSHED_
AREA
=
watershed
area
draining
to
surface
water
intake
location;
WS_
RUNOFF
=
watershed
runoff
rating;
WS_
RCN
=
watershed
runoff
curve
number;
AVE_
PPT
=
30­
yr
average
precipitation
for
the
site;
AVE_
SPR
=
30­
yr
average
spring
rainfall
(
April
­
June).
­
155­

Time­
weighted
means
over
time
PGW
maximum
observations
for
each
lysimeter
as
well
as
time­
weighted
means
derived
from
the
censored
data
file
were
examined
for
trends
over
time.
Plots
of
time­
weighted
means
versus
year
are
provided
in
the
subsequent
section.
In
general,
peak
concentrations
of
acetochlor,
ESA,
and
OXA
were
greatest
in
the
early
years
of
monitoring
from
1996
to
1998.
Bromide
peak
concentrations
tended
to
be
highest
during
1998.
Highest
time
weighted
means
for
acetochlor,
ESA,
and
OX
were
observed
between
1996
and
1998.
­
156­

12.7.3.
MAXIMUM
OBSERVED
CONCENTRATIONS
(
PER
YEAR)
OVER
TIME
FOR
THE
PGW
STUDIES.

Correlations
Plots
Scatter
plot
of
'
MAX
OBS'
by
YEAR
TYPE=
AC
TYPE=
AC_
ESA
­
157­

Correlations
Plots
Scatter
plot
of
'
MAX
OBS'
by
YEAR
TYPE=
AC_
OXA
TYPE=
BR
­
158­

12.7.4.
TIME­
WEIGHTED
ANNUALIZED
MEANS
OVER
TIME
FOR
THE
PGW
STUDIES.

Correlations
Plots
Scatter
plot
of
TWAM
by
YEAR
TYPE=
AC
TYPE=
AC_
ESA
­
159­

Correlations
Plots
Scatter
plot
of
TWAM
by
YEAR
TYPE=
AC_
OXA
TYPE=
BR
­
160­

12.7.5.
CORRELATION
MATRICES
(
r2)
FOR
FACTORS
RELATED
TO
ACETOCHLOR
ACUTE
EXPOSURE
IN
THE
PROSPECTIVE
GROUND
WATER
STUDIES.

AE_
3FT
AE_
9FT
AE_
SHGW
PPT3MOS
PPT1YR
PPT2YR
PPT3YR
PPT4YR
PPT_
TOT
AVG_
HC
AVG_
PWV
AVG_
HG
AE_
3FT
1
­
0.22757
­
0.31336
­
0.07682
0.40856
0.1471
0.05601
0.09501
0.05572
­
0.18503
­
0.12216
0.53558
p=
0.5878
0.4938
0.8565
0.3149
0.7281
0.8952
0.8229
0.8957
0.6609
0.7732
0.1713
AE_
9FT
1
0.5803
­
0.12632
0.04307
0.59107
0.30713
0.32253
0.076
0.33555
0.17678
­
0.03546
p=
0.172
0.7657
0.9194
0.1228
0.4593
0.4359
0.858
0.4165
0.6754
0.9336
AE_
SHGW
1
­
0.09752
­
0.41872
0.31223
­
0.1394
0.062
0.54038
­
0.04658
­
0.39305
0.02066
p=
0.8352
0.3498
0.4954
0.7656
0.8949
0.2105
0.921
0.3831
0.9649
PPT3MOS
1
­
0.35631
­
0.2604
­
0.66558
­
0.63715
­
0.4388
0.20764
0.41885
­
0.53312
p=
0.3863
0.5334
0.0716
0.0893
0.2768
0.6217
0.3017
0.1737
PPT1YR
1
0.62496
0.77424
0.73588
0.43935
­
0.03077
­
0.1655
0.62
p=
0.0976
0.0241
0.0374
0.2761
0.9423
0.6953
0.1011
PPT2YR
1
0.72921
0.84462
0.60217
­
0.05395
­
0.20217
0.15564
p=
0.0401
0.0083
0.1142
0.899
0.6311
0.7129
PPT3YR
1
0.95157
0.45759
0.11494
­
0.2965
0.31123
p=
0.0003
0.2543
0.7864
0.4758
0.453
PPT4YR
1
0.67654
­
0.05389
­
0.45033
0.30683
p=
0.0654
0.8992
0.2628
0.4598
PPT_
TOT
1
­
0.4631
­
0.72074
0.41897
p=
0.2478
0.0437
0.3015
AVG_
HC
1
0.03648
­
0.25309
p=
0.9317
0.5453
AVG_
PWV
1
­
0.27042
p=
0.5171
AVG_
HG
1
p=
Pearson
Correlation
Coefficients
Prob
>
|
r|
under
H0:
Rho=
0
Number
of
Observations
Generated
by
the
SAS
System
(
Local,
XP_
PRO)
on
16NOV2004
at
4:
57
PM
AE_
3FT
=
Acute
exposure
for
3
foot
depth
lysimeters
AE_
9FT
=
Acute
exposure
for
9
foot
depth
lysimeters
AE_
SHGW
=
Acute
exposure
for
shallow
ground
water
PPT3MOS
=
precipitation
for
the
first
three
months
of
study
PPT1YR
=
precipitation
for
the
first
year,
second
year,
etc.,
of
study
PPT_
TOT
=
total
precipitation
for
the
study
AVG_
HC
=
Average
hydraulic
conductivity
AVG_
PWV
=
Average
pore
water
velocity
AVG_
HG
=
Average
hydraulic
gradient
­
161­

APPENDIX
12.8.
Data
Tables
for
the
ARP
Monitoring
Studies
Related
to
Mitigation
Endpoints
State
Ground
Water
Monitoring
Program.

Table
37.
SGW
acetochlor
numeric
response
samples
exceeding
0.1
ppb
for
detection
of
"
pattern
of
movement".

Site
Date
Conc
(
ppb)
IA07
6/
1/
1995
0.8
IA07
7/
1/
1995
0.391
IA07
8/
1/
1995
0.131
IA07
5/
1/
1997
4.354
IA07
6/
1/
1997
1.266
IA07
7/
1/
1997
0.283
IA07
8/
1/
1997
0.143
IA07
9/
1/
1997
0.106
IA07
6/
1/
1999
0.396
IA07
7/
1/
1999
0.132
IA07
6/
1/
2001
0.23
IA09
5/
1/
1997
0.14
IL08
5/
1/
1995
0.268
IL08
6/
1/
1995
0.105
IL24
5/
1/
1995
2.168
IL24
6/
1/
1995
1.036
IL24
7/
1/
1995
0.379
IL24
8/
1/
1995
0.246
IL24
9/
1/
1995
0.305
IL24
10/
1/
1995
0.313
IL24
11/
1/
1995
0.246
IL24
12/
1/
1995
0.144
KS06
8/
1/
1998
0.112
KS06
10/
1/
1998
0.139
KS06
11/
1/
1998
0.105
KS06
12/
1/
1998
0.24
KS09
3/
1/
2001
0.453
KS14
4/
1/
1996
0.12
KS14
5/
1/
1996
0.145
KS14
6/
1/
1996
0.122
KS14
7/
1/
1996
0.135
KS14
8/
1/
1996
0.291
KS14
9/
1/
1996
0.171
KS14
10/
1/
1996
0.26
KS14
11/
1/
1996
0.177
­
162­

Table
37.
SGW
acetochlor
numeric
response
samples
exceeding
0.1
ppb
for
detection
of
"
pattern
of
movement".

Site
Date
Conc
(
ppb)
KS14
12/
1/
1996
0.158
KS14
1/
1/
1997
0.319
KS14
2/
1/
1997
0.206
KS14
3/
1/
1997
0.152
KS14
4/
1/
1997
0.133
KS14
5/
1/
1997
0.132
KS14
6/
1/
1997
0.137
KS14
7/
1/
1997
0.148
KS14
8/
1/
1997
0.218
KS14
9/
1/
1997
0.221
KS14
10/
1/
1997
0.214
KS14
11/
1/
1997
0.171
KS17
3/
1/
1998
0.159
KS17
4/
1/
1998
0.143
KS17
7/
1/
1998
0.108
KS17
8/
1/
1998
0.131
KS17
9/
1/
1998
0.163
KS17
10/
1/
1998
0.188
KS17
11/
1/
1998
0.106
KS17
12/
1/
1998
0.155
KS17
1/
1/
1999
0.109
KS17
3/
1/
1999
0.125
KS17
4/
1/
1999
0.181
KS17
5/
1/
1999
0.16
KS17
9/
1/
1999
0.135
KS19
10/
1/
1998
0.107
KS19
11/
1/
1998
0.109
KS19
12/
1/
1998
0.131
KS19
1/
1/
1999
0.149
KS19
2/
1/
1999
0.145
KS19
3/
1/
1999
0.178
KS19
4/
1/
1999
0.215
KS19
5/
1/
1999
0.2
KS19
6/
1/
1999
0.153
KS19
7/
1/
1999
0.11
KS19
10/
1/
1999
0.107
KS19
11/
1/
1999
0.106
KS25
7/
1/
1998
0.118
MN13
9/
1/
1995
0.101
MN24
5/
1/
1995
0.105
MN25
6/
1/
2001
0.741
MN25
7/
1/
2001
0.456
MN25
9/
1/
2001
0.611
MN25
10/
1/
2001
0.694
MN25
11/
1/
2001
0.499
­
163­

Table
37.
SGW
acetochlor
numeric
response
samples
exceeding
0.1
ppb
for
detection
of
"
pattern
of
movement".

Site
Date
Conc
(
ppb)
MN25
12/
1/
2001
0.168
NE16
6/
1/
1999
0.186
NE16
8/
1/
1999
0.534
Table
38.
Acetochlor
degradate
samples
exceeding
0.1
ppb
in
the
state
monitoring
program.

Ac_
ESA
numeric
response
AcOX
numeric
response
Site
Date
Conc
Site
Date
Conc
IA01
3/
1/
1999
0.367
IA01
3/
1/
2001
0.242
IA01
6/
1/
1999
0.547
IA01
6/
1/
2001
0.154
IA01
9/
1/
1999
0.528
IA07
6/
1/
1999
19.1
IA01
12/
1/
1999
0.471
IA07
9/
1/
1999
2.55
IA01
3/
1/
2000
0.178
IA07
12/
1/
1999
1.3
IA01
6/
1/
2000
0.819
IA07
3/
1/
2000
0.819
IA01
9/
1/
2000
0.438
IA07
9/
1/
2000
0.251
IA01
12/
1/
2000
0.645
IA07
12/
1/
2000
0.224
IA01
3/
1/
2001
1.33
IA07
3/
1/
2001
0.112
IA01
6/
1/
2001
5.38
IA07
6/
1/
2001
10.4
IA01
9/
1/
2001
1.6
IA07
9/
1/
2001
3.36
IA01
12/
1/
2001
1.56
IA07
12/
1/
2001
0.324
IA02
3/
1/
1999
0.176
IA09
6/
1/
1999
3.15
IA02
6/
1/
1999
0.36
IA09
6/
1/
2001
2.72
IA02
12/
1/
1999
0.913
IA23
9/
1/
1999
0.118
IA02
3/
1/
2000
0.445
IA23
12/
1/
1999
0.115
IA02
6/
1/
2000
0.22
IA23
3/
1/
2000
0.132
IA02
3/
1/
2001
0.147
IA23
9/
1/
2000
0.178
IA02
6/
1/
2001
0.104
IA23
12/
1/
2000
0.117
IA02
9/
1/
2001
0.188
IL04
3/
1/
1999
6.48
IA02
12/
1/
2001
0.147
IL04
6/
1/
1999
4.6
IA03
3/
1/
1999
0.134
IL04
9/
1/
1999
7.32
IA03
6/
1/
1999
0.421
IL04
12/
1/
1999
4.72
IA03
9/
1/
1999
0.214
IL04
3/
1/
2000
5.56
IA03
12/
1/
1999
0.205
IL04
6/
1/
2000
0.662
IA04
6/
1/
1999
0.274
IL04
9/
1/
2000
0.628
IA04
9/
1/
1999
0.474
IL04
12/
1/
2000
0.702
IA04
12/
1/
1999
0.187
IL04
3/
1/
2001
0.462
IA04
3/
1/
2000
0.167
IL04
6/
1/
2001
0.47
IA04
6/
1/
2000
0.204
IL04
9/
1/
2001
0.345
IA04
9/
1/
2000
0.105
IL04
12/
1/
2001
0.23
IA04
9/
1/
2001
0.128
IN16
3/
1/
1999
0.1
IA07
6/
1/
1999
20
IN16
12/
1/
2001
0.392
IA07
9/
1/
1999
4.84
KS10
3/
1/
1999
0.794
IA07
12/
1/
1999
3.27
KS10
6/
1/
1999
0.574
­
164­

Table
38.
Acetochlor
degradate
samples
exceeding
0.1
ppb
in
the
state
monitoring
program.

Ac_
ESA
numeric
response
AcOX
numeric
response
Site
Date
Conc
Site
Date
Conc
IA07
3/
1/
2000
2.03
KS10
9/
1/
1999
0.846
IA07
6/
1/
2000
0.262
KS10
12/
1/
1999
0.723
IA07
9/
1/
2000
0.891
KS10
3/
1/
2000
1.13
IA07
12/
1/
2000
0.688
KS10
6/
1/
2000
1.3
IA07
3/
1/
2001
0.119
KS10
9/
1/
2000
2.15
IA07
6/
1/
2001
10.8
KS10
12/
1/
2000
1.43
IA07
9/
1/
2001
7.92
KS10
3/
1/
2001
1.29
IA07
12/
1/
2001
1.68
KS10
6/
1/
2001
2.17
IA07­
2
3/
1/
1999
3.85
KS10
9/
1/
2001
1.27
IA07­
2
6/
1/
1999
2.11
KS10
12/
1/
2001
0.971
IA07­
2
9/
1/
1999
0.464
KS14
3/
1/
1999
0.184
IA07­
2
12/
1/
1999
0.163
KS14
6/
1/
1999
0.183
IA07­
2
3/
1/
2000
0.302
MN05
12/
1/
2001
0.153
IA07­
2
6/
1/
2000
0.237
MN06
9/
1/
2001
0.235
IA07­
2
9/
1/
2000
0.131
MN13
12/
1/
1999
0.107
IA07­
2
12/
1/
2000
0.14
MN13
6/
1/
2001
0.103
IA07­
2
3/
1/
2001
0.168
MN17
6/
1/
2001
0.819
IA07­
2
6/
1/
2001
0.13
MN17
9/
1/
2001
0.559
IA09
6/
1/
1999
2.68
MN17
12/
1/
2001
0.176
IA09
12/
1/
1999
0.213
MN25
6/
1/
1999
0.339
IA09
6/
1/
2001
1.6
MN25
12/
1/
1999
0.156
IA09
12/
1/
2001
0.128
MN25
3/
1/
2000
0.191
IA10
9/
1/
2001
0.844
MN25
6/
1/
2000
0.177
IA10
12/
1/
2001
0.144
MN25
9/
1/
2000
0.145
IA11
9/
1/
1999
0.277
MN25
12/
1/
2000
0.101
IA11
12/
1/
1999
0.326
MN25
6/
1/
2001
6.17
IA11
3/
1/
2000
0.23
MN25
7/
1/
2001
1
IA11
6/
1/
2000
0.224
MN25
9/
1/
2001
1.56
IA11
9/
1/
2000
0.524
MN25
10/
1/
2001
2.45
IA11
12/
1/
2000
0.4
MN25
11/
1/
2001
1.98
IA12
3/
1/
1999
0.113
MN25
12/
1/
2001
0.868
IA12
12/
1/
1999
0.124
NE07
9/
1/
2000
0.109
IA12
6/
1/
2000
0.104
NE07
12/
1/
2000
0.111
IA12
9/
1/
2000
0.157
NE07
6/
1/
2001
0.133
IA12
9/
1/
2001
0.114
NE07
9/
1/
2001
0.143
IA12
12/
1/
2001
0.1
NE07
12/
1/
2001
0.158
IA13
12/
1/
1999
0.12
NE13
9/
1/
1999
0.172
IA13
3/
1/
2000
0.269
NE16
3/
1/
1999
0.193
IA13
9/
1/
2000
0.147
NE16
6/
1/
1999
0.248
IA13
12/
1/
2000
0.271
NE16
9/
1/
1999
0.221
IA13
3/
1/
2001
0.201
NE25
3/
1/
2001
0.383
IA13
6/
1/
2001
0.128
NE25
6/
1/
2001
0.132
IA13
9/
1/
2001
0.144
WI03
3/
1/
2001
0.486
IA13
12/
1/
2001
0.206
WI03
6/
1/
2001
1.01
­
165­

Table
38.
Acetochlor
degradate
samples
exceeding
0.1
ppb
in
the
state
monitoring
program.

Ac_
ESA
numeric
response
AcOX
numeric
response
Site
Date
Conc
Site
Date
Conc
IA14
3/
1/
1999
0.249
WI03
9/
1/
2001
1.36
IA14
6/
1/
1999
0.245
WI03
12/
1/
2001
0.412
IA14
12/
1/
1999
0.102
WI04
3/
1/
1999
0.332
IA14
3/
1/
2000
0.778
WI04
6/
1/
1999
0.421
IA14
6/
1/
2000
0.216
WI04
9/
1/
1999
0.234
IA14
9/
1/
2000
0.694
WI05
3/
1/
1999
0.121
IA14
3/
1/
2001
0.738
WI05
6/
1/
1999
0.103
IA14
6/
1/
2001
0.554
WI11
3/
1/
1999
2.7
IA14
9/
1/
2001
0.585
WI11
6/
1/
1999
1.61
IA14
12/
1/
2001
0.831
WI11
9/
1/
1999
1.15
IA15
3/
1/
1999
1.88
WI11
12/
1/
1999
1.45
IA15
6/
1/
1999
2.12
WI11
1/
1/
2000
0.364
IA15
9/
1/
1999
1.39
WI11
2/
1/
2000
0.427
IA15
12/
1/
1999
1.79
WI11
3/
1/
2000
0.427
IA15
3/
1/
2000
1.82
WI11
6/
1/
2000
0.759
IA15
6/
1/
2000
1.25
WI11
9/
1/
2000
0.118
IA15
9/
1/
2000
1.33
WI11
12/
1/
2000
0.556
IA15
12/
1/
2000
1.64
WI11
3/
1/
2001
0.336
IA15
3/
1/
2001
1.61
WI11
6/
1/
2001
0.921
IA15
6/
1/
2001
1.63
WI11
9/
1/
2001
0.183
IA15
9/
1/
2001
1.31
WI12
9/
1/
1999
0.148
IA15
12/
1/
2001
1.49
WI12
12/
1/
1999
0.724
IA16
3/
1/
1999
0.135
WI12
1/
1/
2000
0.738
IA16
12/
1/
1999
0.162
WI12
2/
1/
2000
0.57
IA16
3/
1/
2000
0.136
WI12
3/
1/
2000
0.57
IA16
6/
1/
2000
0.216
WI12
6/
1/
2000
0.133
IA16
9/
1/
2000
0.21
WI12
12/
1/
2000
0.36
IA16
12/
1/
2000
0.129
WI23
3/
1/
1999
3.7
IA16
3/
1/
2001
0.149
WI23
6/
1/
1999
3.06
IA16
6/
1/
2001
0.139
WI25
6/
1/
2000
0.1
IA16
9/
1/
2001
0.168
WI25
9/
1/
2000
0.14
IA17
3/
1/
1999
0.304
WI25
12/
1/
2000
0.121
IA17
6/
1/
1999
0.952
WI27
3/
1/
1999
0.587
IA17
9/
1/
1999
0.567
WI27
6/
1/
1999
0.261
IA17
12/
1/
1999
0.577
WI27
9/
1/
1999
0.127
IA17
3/
1/
2000
0.166
WI27
12/
1/
1999
0.138
IA17
6/
1/
2000
0.16
WI27
9/
1/
2000
0.101
IA17
9/
1/
2000
0.223
WI27
9/
1/
2001
0.232
IA17
12/
1/
2000
0.397
WI27
12/
1/
2001
0.326
IA17
3/
1/
2001
0.126
WI28
3/
1/
1999
0.325
IA17
6/
1/
2001
0.375
WI28
6/
1/
1999
0.909
IA17
9/
1/
2001
0.468
WI28
9/
1/
1999
0.78
IA17
12/
1/
2001
0.354
WI28
12/
1/
1999
1.02
IA18
6/
1/
1999
0.876
WI28
2/
1/
2000
1.53
­
166­

Table
38.
Acetochlor
degradate
samples
exceeding
0.1
ppb
in
the
state
monitoring
program.

Ac_
ESA
numeric
response
AcOX
numeric
response
Site
Date
Conc
Site
Date
Conc
IA18
9/
1/
1999
0.304
WI28
3/
1/
2000
1.53
IA18
12/
1/
1999
0.125
WI28
6/
1/
2000
0.466
IA19
6/
1/
1999
0.665
WI28
9/
1/
2000
0.535
IA19
6/
1/
2000
0.254
WI28
12/
1/
2000
0.554
IA20
3/
1/
1999
0.107
WI28
3/
1/
2001
0.526
IA20
6/
1/
1999
0.183
WI28
6/
1/
2001
0.258
IA20
9/
1/
1999
0.204
WI28
9/
1/
2001
0.202
IA20
12/
1/
1999
0.195
WI28
12/
1/
2001
0.237
IA20
3/
1/
2000
0.135
IA21
6/
1/
1999
0.452
IA21
9/
1/
1999
0.177
IA21
12/
1/
1999
0.176
IA22
3/
1/
1999
0.512
IA22
6/
1/
1999
0.515
IA22
9/
1/
1999
0.312
IA22
12/
1/
1999
0.119
IA22
6/
1/
2001
0.119
IA22
9/
1/
2001
0.194
IA23
9/
1/
1999
0.287
IA23
12/
1/
1999
0.337
IA23
3/
1/
2000
0.442
IA23
6/
1/
2000
0.445
IA23
9/
1/
2000
0.931
IA23
12/
1/
2000
0.528
IA23
3/
1/
2001
0.51
IA23
6/
1/
2001
0.505
IA23
9/
1/
2001
0.481
IA23
12/
1/
2001
0.543
IA24
6/
1/
1999
0.374
IA24
9/
1/
1999
0.858
IA24
12/
1/
1999
0.892
IA24
3/
1/
2000
0.311
IA25
6/
1/
2000
0.125
IA25
3/
1/
2001
0.509
IA25
6/
1/
2001
0.225
IL01
3/
1/
1999
0.632
IL01
6/
1/
1999
0.754
IL01
9/
1/
1999
0.577
IL01
12/
1/
1999
0.51
IL01
3/
1/
2000
0.458
IL01
6/
1/
2000
0.428
IL01
9/
1/
2000
0.516
IL01
12/
1/
2000
0.478
IL01
3/
1/
2001
0.332
­
167­

Table
38.
Acetochlor
degradate
samples
exceeding
0.1
ppb
in
the
state
monitoring
program.

Ac_
ESA
numeric
response
AcOX
numeric
response
Site
Date
Conc
Site
Date
Conc
IL01
6/
1/
2001
0.338
IL01
9/
1/
2001
0.347
IL01
12/
1/
2001
0.342
IL02
3/
1/
1999
0.219
IL02
6/
1/
1999
0.194
IL02
6/
1/
2000
0.155
IL04
3/
1/
1999
12.6
IL04
6/
1/
1999
9.25
IL04
9/
1/
1999
14.7
IL04
12/
1/
1999
14.4
IL04
3/
1/
2000
14.3
IL04
6/
1/
2000
1.79
IL04
9/
1/
2000
3.17
IL04
12/
1/
2000
6.62
IL04
3/
1/
2001
1.89
IL04
6/
1/
2001
5.44
IL04
9/
1/
2001
5.21
IL04
12/
1/
2001
5.56
IL05
6/
1/
1999
2.31
IL05
12/
1/
1999
0.14
IL05
3/
1/
2000
0.147
IL08
6/
1/
1999
0.137
IL08
3/
1/
2000
0.203
IL08
6/
1/
2000
0.111
IL08
9/
1/
2001
0.544
IL08
12/
1/
2001
0.173
IL10
3/
1/
1999
1.22
IL10
6/
1/
1999
0.942
IL10
9/
1/
1999
0.412
IL10
12/
1/
1999
0.14
IL10
6/
1/
2000
0.116
IL10
6/
1/
2001
0.167
IL10
9/
1/
2001
1.62
IL10
12/
1/
2001
1.26
IL14
3/
1/
1999
0.203
IL14
6/
1/
1999
0.112
IL15
3/
1/
1999
0.172
IL15
6/
1/
1999
0.163
IL15
9/
1/
1999
0.155
IL15
12/
1/
1999
0.112
IL17
9/
1/
1999
0.114
IL18
3/
1/
1999
0.233
IL18
6/
1/
1999
0.217
IL18
9/
1/
1999
0.103
­
168­

Table
38.
Acetochlor
degradate
samples
exceeding
0.1
ppb
in
the
state
monitoring
program.

Ac_
ESA
numeric
response
AcOX
numeric
response
Site
Date
Conc
Site
Date
Conc
IL18
12/
1/
1999
0.11
IL18
3/
1/
2000
0.207
IL18
6/
1/
2000
0.256
IL18
9/
1/
2000
0.111
IL18
9/
1/
2001
0.126
IL18
12/
1/
2001
0.142
IL24
9/
1/
1999
0.156
IL24
3/
1/
2000
0.146
IN02
9/
1/
2000
0.102
IN02
3/
1/
2001
0.101
IN08
9/
1/
1999
0.109
IN08
12/
1/
1999
0.133
IN08
6/
1/
2000
0.124
IN08
9/
1/
2000
0.143
IN08
12/
1/
2000
0.153
IN08
3/
1/
2001
0.289
IN08
6/
1/
2001
0.199
IN08
9/
1/
2001
0.225
IN08
12/
1/
2001
0.299
IN14
6/
1/
2000
0.158
IN14
3/
1/
2001
0.112
IN14
6/
1/
2001
0.23
IN14
9/
1/
2001
0.163
IN14
12/
1/
2001
0.139
IN16
3/
1/
1999
0.848
IN16
6/
1/
1999
0.721
IN16
9/
1/
1999
0.594
IN16
12/
1/
1999
0.466
IN16
6/
1/
2000
0.262
IN16
9/
1/
2000
0.233
IN16
12/
1/
2000
0.175
IN16
3/
1/
2001
0.226
IN16
6/
1/
2001
0.18
IN16
12/
1/
2001
0.2
IN17
3/
1/
2000
0.285
KS04
3/
1/
1999
0.312
KS04
6/
1/
1999
1.5
KS04
9/
1/
1999
1.94
KS04
12/
1/
1999
1.31
KS04
3/
1/
2000
0.869
KS04
6/
1/
2000
0.985
KS04
9/
1/
2000
0.816
KS04
12/
1/
2000
0.828
KS04
3/
1/
2001
0.494
­
169­

Table
38.
Acetochlor
degradate
samples
exceeding
0.1
ppb
in
the
state
monitoring
program.

Ac_
ESA
numeric
response
AcOX
numeric
response
Site
Date
Conc
Site
Date
Conc
KS04
6/
1/
2001
0.373
KS04
9/
1/
2001
0.366
KS04
12/
1/
2001
0.237
KS08
12/
1/
1999
0.118
KS09
3/
1/
2001
0.134
KS09
6/
1/
2001
0.239
KS10
3/
1/
1999
1.28
KS10
6/
1/
1999
1.31
KS10
9/
1/
1999
2.23
KS10
12/
1/
1999
2.1
KS10
3/
1/
2000
4.08
KS10
6/
1/
2000
4.23
KS10
9/
1/
2000
7.37
KS10
12/
1/
2000
5.95
KS10
3/
1/
2001
7.55
KS10
6/
1/
2001
11.1
KS10
9/
1/
2001
8.56
KS10
12/
1/
2001
9.08
KS11
6/
1/
2001
0.163
KS12
9/
1/
2000
0.21
KS12
12/
1/
2000
0.112
KS13
3/
1/
1999
0.202
KS13
6/
1/
1999
0.534
KS13
9/
1/
1999
0.237
KS13
12/
1/
1999
0.212
KS13
3/
1/
2000
0.283
KS13
9/
1/
2000
0.174
KS13
12/
1/
2000
0.487
KS13
6/
1/
2001
0.198
KS13
9/
1/
2001
0.225
KS14
3/
1/
1999
1.4
KS14
6/
1/
1999
1.43
KS14
9/
1/
1999
1.11
KS14
12/
1/
1999
1.34
KS14
3/
1/
2000
0.875
KS17
9/
1/
1999
0.23
KS17
12/
1/
1999
0.131
KS17
3/
1/
2000
0.179
KS17
6/
1/
2000
0.196
KS17
9/
1/
2000
0.226
KS17
12/
1/
2000
0.182
KS17
3/
1/
2001
0.209
KS17
6/
1/
2001
0.235
KS17
9/
1/
2001
0.201
­
170­

Table
38.
Acetochlor
degradate
samples
exceeding
0.1
ppb
in
the
state
monitoring
program.

Ac_
ESA
numeric
response
AcOX
numeric
response
Site
Date
Conc
Site
Date
Conc
KS17
12/
1/
2001
0.171
KS19
3/
1/
1999
0.263
KS19
6/
1/
1999
0.206
KS19
9/
1/
1999
0.242
KS19
12/
1/
1999
0.121
KS19
9/
1/
2000
0.125
KS19
12/
1/
2001
0.107
KS21
3/
1/
2000
0.35
KS25
3/
1/
1999
0.546
KS25
6/
1/
1999
0.614
KS25
9/
1/
1999
0.522
KS25
12/
1/
1999
0.485
KS25
3/
1/
2000
0.672
KS25
6/
1/
2000
0.492
KS25
9/
1/
2000
0.392
KS25
12/
1/
2000
0.371
KS25
3/
1/
2001
0.271
KS25
6/
1/
2001
0.167
KS25
9/
1/
2001
0.153
KS25
12/
1/
2001
0.185
MN05
3/
1/
1999
0.226
MN05
6/
1/
1999
0.149
MN05
9/
1/
1999
0.255
MN05
12/
1/
1999
0.3
MN05
3/
1/
2000
0.26
MN05
6/
1/
2000
0.266
MN05
3/
1/
2001
0.399
MN05
6/
1/
2001
0.549
MN05
9/
1/
2001
0.307
MN05
12/
1/
2001
1.32
MN06
12/
1/
1999
0.264
MN06
6/
1/
2001
0.112
MN06
9/
1/
2001
0.901
MN06
12/
1/
2001
1.29
MN08
3/
1/
1999
0.858
MN08
6/
1/
1999
0.844
MN08
9/
1/
1999
0.253
MN08
12/
1/
1999
0.541
MN08
3/
1/
2000
1.28
MN08
6/
1/
2000
1.03
MN08
3/
1/
2001
0.508
MN08
6/
1/
2001
0.318
MN13
3/
1/
1999
0.152
MN13
6/
1/
1999
0.229
­
171­

Table
38.
Acetochlor
degradate
samples
exceeding
0.1
ppb
in
the
state
monitoring
program.

Ac_
ESA
numeric
response
AcOX
numeric
response
Site
Date
Conc
Site
Date
Conc
MN13
9/
1/
1999
0.172
MN13
12/
1/
1999
0.206
MN13
3/
1/
2000
0.217
MN13
6/
1/
2000
0.212
MN13
9/
1/
2000
0.188
MN13
6/
1/
2001
0.311
MN13
9/
1/
2001
0.337
MN13
12/
1/
2001
0.205
MN14
9/
1/
1999
0.106
MN17
3/
1/
1999
0.755
MN17
6/
1/
1999
0.827
MN17
9/
1/
1999
1.65
MN17
12/
1/
1999
0.952
MN17
3/
1/
2000
0.941
MN17
6/
1/
2000
0.797
MN17
9/
1/
2000
0.917
MN17
12/
1/
2000
0.983
MN17
3/
1/
2001
0.471
MN17
6/
1/
2001
3.04
MN17
9/
1/
2001
4.31
MN17
12/
1/
2001
4.29
MN18
3/
1/
1999
0.552
MN18
6/
1/
1999
0.298
MN18
9/
1/
1999
0.568
MN18
12/
1/
1999
1
MN18
3/
1/
2000
1.05
MN18
6/
1/
2000
0.416
MN18
6/
1/
2001
0.535
MN25
3/
1/
1999
0.387
MN25
6/
1/
1999
1.62
MN25
9/
1/
1999
3.76
MN25
12/
1/
1999
4.06
MN25
3/
1/
2000
2.52
MN25
6/
1/
2000
1.75
MN25
9/
1/
2000
1.69
MN25
12/
1/
2000
1.67
MN25
3/
1/
2001
0.731
MN25
7/
1/
2001
2.71
MN25
9/
1/
2001
3.39
MN25
10/
1/
2001
5.29
MN25
11/
1/
2001
4.42
MN25
12/
1/
2001
2.36
NE01
9/
1/
2000
0.119
NE01
3/
1/
2001
0.187
­
172­

Table
38.
Acetochlor
degradate
samples
exceeding
0.1
ppb
in
the
state
monitoring
program.

Ac_
ESA
numeric
response
AcOX
numeric
response
Site
Date
Conc
Site
Date
Conc
NE01
6/
1/
2001
0.197
NE01
9/
1/
2001
0.248
NE01
12/
1/
2001
0.365
NE02
3/
1/
1999
6.85
NE02
6/
1/
1999
6.4
NE02
9/
1/
1999
6.65
NE02
12/
1/
1999
7.72
NE02
3/
1/
2000
6.5
NE02
6/
1/
2000
5.7
NE02
9/
1/
2000
2.78
NE02
12/
1/
2000
4.06
NE02
3/
1/
2001
3.61
NE02
6/
1/
2001
3.14
NE02
9/
1/
2001
3.11
NE02
12/
1/
2001
3.06
NE03
3/
1/
1999
0.911
NE03
6/
1/
1999
0.802
NE03
9/
1/
1999
0.941
NE03
12/
1/
1999
1.53
NE03
3/
1/
2000
0.491
NE03
6/
1/
2000
0.281
NE03
9/
1/
2000
0.479
NE03
12/
1/
2000
0.339
NE03
3/
1/
2001
0.228
NE03
6/
1/
2001
0.381
NE03
9/
1/
2001
0.605
NE03
12/
1/
2001
1.45
NE04
3/
1/
1999
0.25
NE04
6/
1/
1999
0.691
NE04
9/
1/
1999
0.319
NE04
12/
1/
1999
0.514
NE04
3/
1/
2000
0.384
NE04
6/
1/
2000
1.41
NE04
9/
1/
2000
0.773
NE04
12/
1/
2000
0.926
NE04
3/
1/
2001
1.37
NE04
6/
1/
2001
1.01
NE04
9/
1/
2001
0.711
NE04
12/
1/
2001
0.888
NE05
3/
1/
1999
3.38
NE05
6/
1/
1999
2.74
NE05
9/
1/
1999
2.53
NE05
12/
1/
1999
3.56
NE05
3/
1/
2000
4.27
­
173­

Table
38.
Acetochlor
degradate
samples
exceeding
0.1
ppb
in
the
state
monitoring
program.

Ac_
ESA
numeric
response
AcOX
numeric
response
Site
Date
Conc
Site
Date
Conc
NE05
6/
1/
2000
4.08
NE05
9/
1/
2000
2.23
NE05
12/
1/
2000
2.44
NE05
3/
1/
2001
0.54
NE05
6/
1/
2001
0.641
NE05
9/
1/
2001
0.975
NE05
12/
1/
2001
1.27
NE06
6/
1/
1999
0.147
NE06
9/
1/
1999
0.167
NE06
12/
1/
1999
0.123
NE06
6/
1/
2000
0.141
NE06
9/
1/
2000
0.119
NE06
12/
1/
2000
0.112
NE06
3/
1/
2001
0.124
NE06
12/
1/
2001
0.181
NE07
9/
1/
1999
0.141
NE07
12/
1/
1999
0.109
NE07
6/
1/
2000
0.149
NE07
9/
1/
2000
0.211
NE07
12/
1/
2000
0.146
NE07
3/
1/
2001
0.304
NE07
6/
1/
2001
0.363
NE07
9/
1/
2001
0.411
NE07
12/
1/
2001
0.513
NE10
9/
1/
2001
0.1
NE10
12/
1/
2001
0.153
NE12
12/
1/
2000
0.115
NE12
9/
1/
2001
0.272
NE12
12/
1/
2001
0.377
NE13
3/
1/
1999
0.262
NE13
6/
1/
1999
0.269
NE13
9/
1/
1999
0.553
NE13
12/
1/
1999
0.352
NE13
3/
1/
2000
0.36
NE16
3/
1/
1999
0.833
NE16
6/
1/
1999
0.477
NE16
9/
1/
1999
0.716
NE17
3/
1/
1999
0.875
NE17
6/
1/
1999
0.929
NE17
9/
1/
1999
1.01
NE17
12/
1/
1999
0.597
NE17
3/
1/
2000
0.516
NE17
6/
1/
2000
0.315
NE17
9/
1/
2000
0.502
­
174­

Table
38.
Acetochlor
degradate
samples
exceeding
0.1
ppb
in
the
state
monitoring
program.

Ac_
ESA
numeric
response
AcOX
numeric
response
Site
Date
Conc
Site
Date
Conc
NE17
12/
1/
2000
0.534
NE17
3/
1/
2001
0.497
NE17
6/
1/
2001
0.8
NE17
9/
1/
2001
0.604
NE17
12/
1/
2001
0.609
NE18
9/
1/
1999
0.301
NE18
12/
1/
1999
0.138
NE18
3/
1/
2001
0.154
NE18
6/
1/
2001
0.184
NE19
3/
1/
1999
0.752
NE19
6/
1/
1999
0.843
NE19
9/
1/
1999
2.44
NE19
12/
1/
1999
1.64
NE19
3/
1/
2000
2.09
NE19
6/
1/
2000
2.15
NE19
9/
1/
2000
1.33
NE19
12/
1/
2000
0.928
NE19
3/
1/
2001
1.66
NE19
6/
1/
2001
1.64
NE19
9/
1/
2001
1.56
NE19
12/
1/
2001
1.08
NE23
6/
1/
1999
0.164
NE23
9/
1/
1999
0.103
NE23
12/
1/
1999
0.126
NE25
3/
1/
2001
0.959
NE25
6/
1/
2001
0.325
NE25
9/
1/
2001
0.183
NE25
12/
1/
2001
0.22
WI01
3/
1/
1999
1.02
WI01
6/
1/
1999
0.5
WI01
9/
1/
1999
0.206
WI01
12/
1/
1999
0.864
WI01
2/
1/
2000
0.565
WI01
3/
1/
2000
0.565
WI01
6/
1/
2000
0.112
WI01
9/
1/
2000
0.116
WI01
6/
1/
2001
0.409
WI01
9/
1/
2001
0.766
WI01
12/
1/
2001
1.89
WI03
3/
1/
1999
1.38
WI03
6/
1/
1999
1.5
WI03
9/
1/
1999
0.817
WI03
12/
1/
1999
1.17
WI03
2/
1/
2000
1.13
­
175­

Table
38.
Acetochlor
degradate
samples
exceeding
0.1
ppb
in
the
state
monitoring
program.

Ac_
ESA
numeric
response
AcOX
numeric
response
Site
Date
Conc
Site
Date
Conc
WI03
3/
1/
2000
1.13
WI03
6/
1/
2000
0.879
WI03
9/
1/
2000
1.04
WI03
12/
1/
2000
1.11
WI03
3/
1/
2001
1.2
WI03
6/
1/
2001
2.27
WI03
9/
1/
2001
1.93
WI03
12/
1/
2001
2.91
WI04
3/
1/
1999
1.98
WI04
6/
1/
1999
2.09
WI04
9/
1/
1999
2.44
WI04
12/
1/
1999
2.44
WI04
2/
1/
2000
2.05
WI04
3/
1/
2000
2.05
WI04
6/
1/
2000
1.79
WI04
9/
1/
2000
0.999
WI04
12/
1/
2000
0.801
WI04
3/
1/
2001
0.639
WI04
6/
1/
2001
0.496
WI04
9/
1/
2001
0.282
WI04
12/
1/
2001
0.582
WI05
3/
1/
1999
2.41
WI05
6/
1/
1999
2.59
WI05
9/
1/
1999
0.382
WI05
12/
1/
1999
0.892
WI05
2/
1/
2000
0.107
WI05
3/
1/
2000
0.107
WI05
6/
1/
2000
0.827
WI05
9/
1/
2000
0.153
WI05
12/
1/
2000
0.18
WI05
3/
1/
2001
0.498
WI05
6/
1/
2001
0.119
WI05
12/
1/
2001
0.113
WI06
3/
1/
1999
2.77
WI06
6/
1/
1999
2.31
WI06
9/
1/
1999
0.519
WI06
12/
1/
1999
0.477
WI08
3/
1/
1999
0.215
WI08
9/
1/
1999
0.142
WI08
2/
1/
2000
0.124
WI08
3/
1/
2000
0.124
WI09
6/
1/
1999
2.7
WI09
9/
1/
1999
1.64
WI09
12/
1/
1999
0.514
­
176­

Table
38.
Acetochlor
degradate
samples
exceeding
0.1
ppb
in
the
state
monitoring
program.

Ac_
ESA
numeric
response
AcOX
numeric
response
Site
Date
Conc
Site
Date
Conc
WI09
2/
1/
2000
0.372
WI09
3/
1/
2000
0.372
WI10
3/
1/
1999
0.1
WI10
6/
1/
1999
0.125
WI10
9/
1/
1999
0.13
WI10
6/
1/
2001
0.248
WI10
9/
1/
2001
0.24
WI11
3/
1/
1999
3.2
WI11
6/
1/
1999
2.84
WI11
9/
1/
1999
1.62
WI11
12/
1/
1999
3.12
WI11
1/
1/
2000
0.848
WI11
2/
1/
2000
0.798
WI11
3/
1/
2000
0.798
WI11
6/
1/
2000
1.86
WI11
9/
1/
2000
0.434
WI11
12/
1/
2000
0.89
WI11
3/
1/
2001
1.1
WI11
6/
1/
2001
1.67
WI11
9/
1/
2001
5.26
WI11
12/
1/
2001
1.67
WI12
3/
1/
1999
0.15
WI12
12/
1/
1999
0.168
WI12
1/
1/
2000
0.122
WI12
2/
1/
2000
0.118
WI12
3/
1/
2000
0.118
WI12
9/
1/
2000
0.105
WI12
12/
1/
2001
0.341
WI15
9/
1/
1999
0.133
WI15
12/
1/
1999
0.101
WI20
3/
1/
1999
0.343
WI20
6/
1/
1999
0.456
WI20
9/
1/
1999
0.275
WI20
9/
1/
2000
0.121
WI20
3/
1/
2001
0.136
WI20
6/
1/
2001
0.11
WI20
9/
1/
2001
0.167
WI20
12/
1/
2001
0.171
WI21
3/
1/
1999
0.221
WI21
6/
1/
1999
0.28
WI21
9/
1/
1999
0.273
WI21
12/
1/
1999
0.128
WI21
9/
1/
2000
0.456
WI21
12/
1/
2000
0.235
­
177­

Table
38.
Acetochlor
degradate
samples
exceeding
0.1
ppb
in
the
state
monitoring
program.

Ac_
ESA
numeric
response
AcOX
numeric
response
Site
Date
Conc
Site
Date
Conc
WI21
3/
1/
2001
0.111
WI21
6/
1/
2001
0.124
WI21
9/
1/
2001
0.211
WI22
3/
1/
1999
0.162
WI22
2/
1/
2000
0.16
WI22
3/
1/
2000
0.16
WI22
6/
1/
2000
0.147
WI22
9/
1/
2000
0.221
WI22
12/
1/
2000
0.145
WI22
3/
1/
2001
0.216
WI22
12/
1/
2001
0.156
WI23
3/
1/
1999
11.7
WI23
6/
1/
1999
10.5
WI25
9/
1/
1999
0.159
WI25
12/
1/
1999
0.168
WI25
2/
1/
2000
0.168
WI25
3/
1/
2000
0.168
WI25
6/
1/
2000
0.194
WI25
9/
1/
2000
0.215
WI25
12/
1/
2000
0.22
WI25
3/
1/
2001
0.188
WI25
6/
1/
2001
0.12
WI25
9/
1/
2001
0.164
WI25
12/
1/
2001
0.174
WI26
3/
1/
1999
0.265
WI26
6/
1/
1999
0.294
WI26
9/
1/
1999
0.374
WI26
12/
1/
1999
0.378
WI26
2/
1/
2000
0.263
WI26
3/
1/
2000
0.263
WI26
6/
1/
2000
0.364
WI26
9/
1/
2000
0.56
WI26
12/
1/
2000
0.365
WI26
3/
1/
2001
0.447
WI26
6/
1/
2001
1.79
WI26
9/
1/
2001
2.87
WI26
12/
1/
2001
2.73
WI27
3/
1/
1999
1.76
WI27
6/
1/
1999
1.33
WI27
9/
1/
1999
1.08
WI27
12/
1/
1999
1.25
WI27
2/
1/
2000
0.785
WI27
3/
1/
2000
0.785
WI27
6/
1/
2000
1
­
178­

Table
38.
Acetochlor
degradate
samples
exceeding
0.1
ppb
in
the
state
monitoring
program.

Ac_
ESA
numeric
response
AcOX
numeric
response
Site
Date
Conc
Site
Date
Conc
WI27
9/
1/
2000
1.51
WI27
3/
1/
2001
1.56
WI27
6/
1/
2001
2.2
WI27
9/
1/
2001
5.16
WI27
12/
1/
2001
3.33
WI28
3/
1/
1999
0.303
WI28
6/
1/
1999
1.09
WI28
9/
1/
1999
1.01
WI28
12/
1/
1999
1.2
WI28
2/
1/
2000
1.4
WI28
3/
1/
2000
1.4
WI28
6/
1/
2000
0.655
WI28
9/
1/
2000
1.12
WI28
12/
1/
2000
0.943
WI28
3/
1/
2001
0.977
WI28
6/
1/
2001
1.48
WI28
9/
1/
2001
0.942
WI28
12/
1/
2001
1.04
PGW
Table
39.
Acetochlor
and
degradate
detections
in
PGW
studies
greater
than
1.0
ppb
at
nine
foot
lysimter
depth
consistent
with
three
and
six
foot
lysimeters
in
that
cluster
as
defined
by
"
pattern
of
movement"
criteria.
MAT
=
months
after
treatment.

ANALYTE
STATE
CLUSTER
9
Feet
6
Feet
3
Feet
#

Obs
Conc
MAT
Max
Max
1
ESA
DE
6
1
9
2.61
3
2
ESA
DE
6
2.4
10
2.61
3
3
ESA
DE
6
3.9
12.5
2.61
3
4
ESA
DE
6
3.9
13
2.61
3
5
ESA
DE
6
3.7
13.5
2.61
3
6
ESA
DE
6
3.6
14
2.61
3
7
ESA
DE
6
2.1
14.5
2.61
3
8
ESA
DE
6
4.3
15
2.61
3
9
ESA
DE
6
3.5
15.5
2.61
3
10
ESA
DE
6
3.1
16
2.61
3
11
ESA
DE
6
2.4
16.5
2.61
3
12
ESA
DE
6
2.6
17
2.61
3
13
ESA
DE
3
1.1
17.5
9.9
1.1
14
ESA
DE
6
2.7
17.5
2.61
3
­
179­

Table
39.
Acetochlor
and
degradate
detections
in
PGW
studies
greater
than
1.0
ppb
at
nine
foot
lysimter
depth
consistent
with
three
and
six
foot
lysimeters
in
that
cluster
as
defined
by
"
pattern
of
movement"
criteria.
MAT
=
months
after
treatment.

ANALYTE
STATE
CLUSTER
9
Feet
6
Feet
3
Feet
#

Obs
Conc
MAT
Max
Max
15
ESA
DE
3
1.2
18
9.9
1.1
16
ESA
DE
6
2.5
18
2.61
3
17
ESA
DE
3
1.3
19
9.9
1.1
18
ESA
DE
6
2.9
19
2.61
3
19
ESA
DE
3
1.4
20
9.9
1.1
20
ESA
DE
3
1.3
21
9.9
1.1
21
ESA
DE
3
1.7
22
9.9
1.1
22
ESA
DE
6
1.4
22
2.61
3
23
ESA
DE
3
2.5
23
9.9
1.1
24
ESA
DE
6
4.3
23
2.61
3
25
ESA
DE
3
1.9
24
9.9
1.1
26
ESA
DE
6
2.8
24
2.61
3
27
ESA
DE
3
2
25
9.9
1.1
28
ESA
DE
6
2.6
25
2.61
3
29
ESA
DE
3
2.3
26
9.9
1.1
30
ESA
DE
6
2.5
26
2.61
3
31
ESA
DE
3
3.1
27
9.9
1.1
32
ESA
DE
6
1.7
27
2.61
3
33
ESA
DE
1
1.1
28
1.2
1.4
34
ESA
DE
3
3.2
28
9.9
1.1
35
ESA
DE
1
1.3
29
1.2
1.4
36
ESA
DE
3
3.5
29
9.9
1.1
37
ESA
DE
3
2.85
30
9.9
1.1
38
ESA
DE
3
2.94
31
9.9
1.1
39
ESA
DE
1
1.06
33
1.2
1.4
40
ESA
DE
1
1.13
34
1.2
1.4
41
ESA
DE
3
1.45
36
9.9
1.1
42
ESA
DE
1
1.15
36
1.2
1.4
43
ESA
DE
3
1.43
37
9.9
1.1
44
ESA
DE
1
1.05
37
1.2
1.4
45
ESA
DE
3
1.13
38
9.9
1.1
46
ESA
DE
3
1.05
39
9.9
1.1
47
ESA
DE
1
1.01
39
1.2
1.4
48
ESA
DE
6
1.7
11
2.61
3
49
ESA
DE
6
3.2
12
2.61
3
50
ESA
IN
6
3.6
2
12
2.2
51
ESA
IN
4
1.2
2.5
3.3
1.3
52
ESA
IN
6
8.1
2.5
12
2.2
53
ESA
IN
4
1.1
3.5
3.3
1.3
54
ESA
IN
6
13
3.5
12
2.2
55
ESA
IN
6
16
4
12
2.2
­
180­

Table
39.
Acetochlor
and
degradate
detections
in
PGW
studies
greater
than
1.0
ppb
at
nine
foot
lysimter
depth
consistent
with
three
and
six
foot
lysimeters
in
that
cluster
as
defined
by
"
pattern
of
movement"
criteria.
MAT
=
months
after
treatment.

ANALYTE
STATE
CLUSTER
9
Feet
6
Feet
3
Feet
#

Obs
Conc
MAT
Max
Max
56
ESA
IN
6
16
4.5
12
2.2
57
ESA
IN
6
21
5
12
2.2
58
ESA
IN
6
22
5.5
12
2.2
59
ESA
IN
4
13
9
3.3
1.3
60
ESA
IN
6
10
9
12
2.2
61
ESA
IN
7
15
9
6.9
4.5
62
ESA
IN
2
1.7
10
18
17
63
ESA
IN
4
10
10
3.3
1.3
64
ESA
IN
6
7
10
12
2.2
65
ESA
IN
7
19
10
6.9
4.5
66
ESA
IN
2
2.3
11
18
17
67
ESA
IN
4
10
11
3.3
1.3
68
ESA
IN
6
6.8
11
12
2.2
69
ESA
IN
7
16
11
6.9
4.5
70
ESA
IN
2
3.1
12
18
17
71
ESA
IN
4
11
12
3.3
1.3
72
ESA
IN
6
6.7
12
12
2.2
73
ESA
IN
7
18
12
6.9
4.5
74
ESA
IN
8
3.3
12
4.6
7.3
75
ESA
IN
2
3.6
13
18
17
76
ESA
IN
4
10
13
3.3
1.3
77
ESA
IN
6
3.1
13
12
2.2
78
ESA
IN
7
21
13
6.9
4.5
79
ESA
IN
2
5.4
14
18
17
80
ESA
IN
4
10
14
3.3
1.3
81
ESA
IN
6
6.2
14
12
2.2
82
ESA
IN
7
24
14
6.9
4.5
83
ESA
IN
8
7.6
14
4.6
7.3
84
ESA
IN
2
5.4
15
18
17
85
ESA
IN
4
6.3
15
3.3
1.3
86
ESA
IN
6
5.2
15
12
2.2
87
ESA
IN
7
23
15
6.9
4.5
88
ESA
IN
8
5.8
15
4.6
7.3
89
ESA
IN
2
5.4
16
18
17
90
ESA
IN
4
3.8
16
3.3
1.3
91
ESA
IN
6
4.6
16
12
2.2
92
ESA
IN
7
20
16
6.9
4.5
93
ESA
IN
8
4.3
16
4.6
7.3
94
ESA
IN
2
6.9
18
18
17
95
ESA
IN
4
5.7
18
3.3
1.3
96
ESA
IN
6
4.3
18
12
2.2
­
181­

Table
39.
Acetochlor
and
degradate
detections
in
PGW
studies
greater
than
1.0
ppb
at
nine
foot
lysimter
depth
consistent
with
three
and
six
foot
lysimeters
in
that
cluster
as
defined
by
"
pattern
of
movement"
criteria.
MAT
=
months
after
treatment.

ANALYTE
STATE
CLUSTER
9
Feet
6
Feet
3
Feet
#

Obs
Conc
MAT
Max
Max
97
ESA
IN
7
22
18
6.9
4.5
98
ESA
IN
8
2.8
18
4.6
7.3
99
ESA
IN
2
1.7
22
18
17
100
ESA
IN
3
3.5
22
7
6.1
101
ESA
IN
4
2.2
22
3.3
1.3
102
ESA
IN
6
6.6
22
12
2.2
103
ESA
IN
7
5.1
22
6.9
4.5
104
ESA
IN
2
19
23
18
17
105
ESA
IN
3
1.8
23
7
6.1
106
ESA
IN
4
1.1
23
3.3
1.3
107
ESA
IN
5
2.3
23
7.6
3.6
108
ESA
IN
6
1.4
23
12
2.2
109
ESA
IN
7
16
23
6.9
4.5
110
ESA
IN
8
8.2
23
4.6
7.3
111
ESA
IN
2
18
24
18
17
112
ESA
IN
3
2
24
7
6.1
113
ESA
IN
5
1.9
24
7.6
3.6
114
ESA
IN
7
14
24
6.9
4.5
115
ESA
IN
8
6.9
24
4.6
7.3
116
ESA
IN
2
17
27
18
17
117
ESA
IN
3
1.2
27
7
6.1
118
ESA
IN
5
1
27
7.6
3.6
119
ESA
IN
7
10
27
6.9
4.5
120
ESA
IN
8
4.3
27
4.6
7.3
121
ESA
IN
2
17
28
18
17
122
ESA
IN
7
8.6
28
6.9
4.5
123
ESA
IN
8
3.3
28
4.6
7.3
124
ESA
IN
2
12
29
18
17
125
ESA
IN
7
6.6
29
6.9
4.5
126
ESA
IN
8
2.4
29
4.6
7.3
127
ESA
IN
7
6.1
30
6.9
4.5
128
ESA
IN
2
13
33
18
17
129
ESA
IN
2
8.8
34
18
17
130
ESA
IN
7
1.7
34
6.9
4.5
131
ESA
IN
8
1.1
34
4.6
7.3
132
ESA
IN
2
10
35
18
17
133
ESA
IN
7
1.9
35
6.9
4.5
134
ESA
IN
8
1.3
35
4.6
7.3
135
ESA
IN
2
8.9
36
18
17
136
ESA
IN
7
1.4
36
6.9
4.5
137
ESA
IN
7
1.2
37
6.9
4.5
­
182­

Table
39.
Acetochlor
and
degradate
detections
in
PGW
studies
greater
than
1.0
ppb
at
nine
foot
lysimter
depth
consistent
with
three
and
six
foot
lysimeters
in
that
cluster
as
defined
by
"
pattern
of
movement"
criteria.
MAT
=
months
after
treatment.

ANALYTE
STATE
CLUSTER
9
Feet
6
Feet
3
Feet
#

Obs
Conc
MAT
Max
Max
138
ESA
IN
2
8.1
45
18
17
139
ESA
IN
2
6.7
46
18
17
140
ESA
IN
2
2.8
50
18
17
141
ESA
IN
2
1.94
52
18
17
142
ESA
MN
4
3.8
4.5
13
6.1
143
ESA
MN
6
3.7
4.5
4.5
20
144
ESA
MN
3
2
5
7
10
145
ESA
MN
4
10
5
13
6.1
146
ESA
MN
5
1.1
5
3
21
147
ESA
MN
6
7.5
5
4.5
20
148
ESA
MN
7
3.3
5
11
19
149
ESA
MN
1
1.7
11
9.7
13
150
ESA
MN
2
5.6
11
9.4
22
151
ESA
MN
3
5.7
11
7
10
152
ESA
MN
4
12
11
13
6.1
153
ESA
MN
5
5.1
11
3
21
154
ESA
MN
6
9.2
11
4.5
20
155
ESA
MN
7
11
11
11
19
156
ESA
MN
8
2.1
11
14
21
157
ESA
MN
1
4
12
9.7
13
158
ESA
MN
2
6.4
12
9.4
22
159
ESA
MN
3
3.9
12
7
10
160
ESA
MN
5
7.5
12
3
21
161
ESA
MN
6
8
12
4.5
20
162
ESA
MN
7
24
12
11
19
163
ESA
MN
8
3.1
12
14
21
164
ESA
MN
1
5
13
9.7
13
165
ESA
MN
2
8
13
9.4
22
166
ESA
MN
4
2.8
13
13
6.1
167
ESA
MN
5
7.5
13
3
21
168
ESA
MN
6
8.1
13
4.5
20
169
ESA
MN
7
23
13
11
19
170
ESA
MN
8
2.6
13
14
21
171
ESA
MN
2
16
14
9.4
22
172
ESA
MN
7
11
14
11
19
173
ESA
MN
8
2.1
14
14
21
174
ESA
MN
1
5.7
15
9.7
13
175
ESA
MN
2
20
15
9.4
22
176
ESA
MN
3
4.8
15
7
10
177
ESA
MN
4
6.7
15
13
6.1
178
ESA
MN
5
9.4
15
3
21
­
183­

Table
39.
Acetochlor
and
degradate
detections
in
PGW
studies
greater
than
1.0
ppb
at
nine
foot
lysimter
depth
consistent
with
three
and
six
foot
lysimeters
in
that
cluster
as
defined
by
"
pattern
of
movement"
criteria.
MAT
=
months
after
treatment.

ANALYTE
STATE
CLUSTER
9
Feet
6
Feet
3
Feet
#

Obs
Conc
MAT
Max
Max
179
ESA
MN
6
2.6
15
4.5
20
180
ESA
MN
7
11
15
11
19
181
ESA
MN
8
2.3
15
14
21
182
ESA
MN
1
4.6
16
9.7
13
183
ESA
MN
2
21
16
9.4
22
184
ESA
MN
3
4
16
7
10
185
ESA
MN
4
6
16
13
6.1
186
ESA
MN
5
6.6
16
3
21
187
ESA
MN
6
1.8
16
4.5
20
188
ESA
MN
7
14
16
11
19
189
ESA
MN
1
5.3
17
9.7
13
190
ESA
MN
3
4.4
17
7
10
191
ESA
MN
4
4.9
17
13
6.1
192
ESA
MN
5
7.6
17
3
21
193
ESA
MN
6
1.4
17
4.5
20
194
ESA
MN
7
16
17
11
19
195
ESA
MN
1
4
18
9.7
13
196
ESA
MN
1
1.8
22
9.7
13
197
ESA
MN
3
3.1
22
7
10
198
ESA
MN
4
3.1
22
13
6.1
199
ESA
MN
5
5.7
22
3
21
200
ESA
MN
7
12
22
11
19
201
ESA
MN
8
2.2
22
14
21
202
ESA
MN
1
2.2
23
9.7
13
203
ESA
MN
2
14
23
9.4
22
204
ESA
MN
3
2.2
23
7
10
205
ESA
MN
4
1.7
23
13
6.1
206
ESA
MN
5
3.5
23
3
21
207
ESA
MN
7
6.3
23
11
19
208
ESA
MN
8
1.5
23
14
21
209
ESA
MN
1
2.4
24
9.7
13
210
ESA
MN
2
12
24
9.4
22
211
ESA
MN
3
2
24
7
10
212
ESA
MN
4
1.6
24
13
6.1
213
ESA
MN
5
3.6
24
3
21
214
ESA
MN
7
7.5
24
11
19
215
ESA
MN
8
1.4
24
14
21
216
ESA
MN
1
1.6
27
9.7
13
217
ESA
MN
3
1.9
27
7
10
218
ESA
MN
4
1.6
27
13
6.1
219
ESA
MN
5
1.9
27
3
21
­
184­

Table
39.
Acetochlor
and
degradate
detections
in
PGW
studies
greater
than
1.0
ppb
at
nine
foot
lysimter
depth
consistent
with
three
and
six
foot
lysimeters
in
that
cluster
as
defined
by
"
pattern
of
movement"
criteria.
MAT
=
months
after
treatment.

ANALYTE
STATE
CLUSTER
9
Feet
6
Feet
3
Feet
#

Obs
Conc
MAT
Max
Max
220
ESA
MN
7
5.4
27
11
19
221
ESA
MN
1
1.7
28
9.7
13
222
ESA
MN
3
2
28
7
10
223
ESA
MN
4
1.7
28
13
6.1
224
ESA
MN
5
2.1
28
3
21
225
ESA
MN
7
6.7
28
11
19
226
ESA
MN
8
1
28
14
21
227
ESA
MN
1
1.2
29
9.7
13
228
ESA
MN
3
1.5
29
7
10
229
ESA
MN
4
1.2
29
13
6.1
230
ESA
MN
5
1.4
29
3
21
231
ESA
MN
7
5.3
29
11
19
232
ESA
MN
2
2
34
9.4
22
233
ESA
MN
2
3.7
35
9.4
22
234
ESA
MN
7
1.1
35
11
19
235
ESA
MN
2
2.2
36
9.4
22
236
ESA
MN
2
1.8
37
9.4
22
237
ESA
NE
2
1.3
23
11
5.9
238
ESA
NE
7
1.7
32
4.25
13
239
ESA
NE
6
1.03
44
23.1
22
240
ESA
NE
6
1.07
47
23.1
22
241
ESA
NE
8
2.33
64
18
24
242
ESA
NE
8
2.81
65
18
24
243
ESA
NE
8
3.65
66
18
24
244
ESA
NE
8
6.92
71
18
24
245
ESA
NE
8
9.3
72
18
24
246
ESA
NE
6
1.29
72
23.1
22
247
ESA
NE
8
11.1
73
18
24
248
ESA
NE
6
1.43
73
23.1
22
249
ESA
NE
8
9.26
74
18
24
250
ESA
NE
6
1.6
74
23.1
22
251
ESA
NE
8
10.5
75
18
24
252
ESA
NE
6
1.84
75
23.1
22
253
ESA
NE
8
11.2
77
18
24
254
ESA
NE
6
3.28
77
23.1
22
255
ESA
NE
8
11.4
83
18
24
256
ESA
NE
6
4.19
83
23.1
22
257
ESA
NE
8
7.67
85
18
24
258
ESA
NE
6
7.74
85
23.1
22
259
ESA
NE
8
3.95
87
18
24
260
ESA
NE
7
2.72
87
4.25
13
­
185­

Table
39.
Acetochlor
and
degradate
detections
in
PGW
studies
greater
than
1.0
ppb
at
nine
foot
lysimter
depth
consistent
with
three
and
six
foot
lysimeters
in
that
cluster
as
defined
by
"
pattern
of
movement"
criteria.
MAT
=
months
after
treatment.

ANALYTE
STATE
CLUSTER
9
Feet
6
Feet
3
Feet
#

Obs
Conc
MAT
Max
Max
261
ESA
NE
6
9.42
87
23.1
22
262
ESA
NE
4
1.26
87
1.4
66
263
ESA
NE
2
1.08
87
11
5.9
264
ESA
OH
1
1.3
2.5
5.4
1.2
265
ESA
OH
1
6
3
5.4
1.2
266
ESA
OH
1
5.1
3.5
5.4
1.2
267
ESA
OH
1
6.5
4
5.4
1.2
268
ESA
OH
1
3.4
5
5.4
1.2
269
ESA
OH
1
1.3
11
5.4
1.2
270
ESA
OH
1
3.8
12
5.4
1.2
271
ESA
PA
4
1.2
7
2
1.2
272
ESA
PA
4
1.8
9
2
1.2
273
ESA
PA
3
1.3
10
1
3
274
ESA
PA
4
2.7
10
2
1.2
275
ESA
PA
8
2.7
10
2.8
2.4
276
ESA
PA
3
1.1
11
1
3
277
ESA
PA
4
1.7
11
2
1.2
278
ESA
PA
4
1.7
12
2
1.2
279
ESA
PA
4
1.4
13
2
1.2
280
ESA
PA
4
1.3
14
2
1.2
281
ESA
PA
4
1.4
15
2
1.2
282
ESA
PA
4
1.6
16
2
1.2
283
ESA
PA
4
1.7
18
2
1.2
284
ESA
PA
4
1.4
20
2
1.2
285
ESA
WI
2
1.7
4.5
13
1.8
286
ESA
WI
2
1.5
7
13
1.8
287
ESA
WI
2
4.1
11
13
1.8
288
ESA
WI
2
24
12
13
1.8
289
ESA
WI
2
25
13
13
1.8
290
ESA
WI
2
19
14
13
1.8
291
ESA
WI
2
11
15
13
1.8
292
ESA
WI
2
3
23
13
1.8
293
ESA
WI
2
3.6
24
13
1.8
­
186­
