Document ID: EPA-HQ-OW-2003-0002-0088
Agency: epa
Document Type: Supporting & Related Material
Title: 
Posted Date: 2003-03-12T05:00Z

DETERMINATION
OF
INTERLABORATORY
DETECTION
AND
QUANTIFICATION
LEVELS
FOR
POLYCHLORINATED
BIPHENYLS
MICHIGAN
MANUFACTURERS
ASSOCIATION
January
2002
John
H.
Phillips
Environmental
Quality
Office
Ford
Motor
Company
John
Gabrosek,
Ph.
D.
Department
of
Statistics
Grand
Valley
State
University
Richard
Rediske,
Ph.
D.
James
O'Keefe
Annis
Water
Resources
Institute
Grand
Valley
State
University
2
EXECUTIVE
SUMMARY
1.
The
Interlaboratory
Detection
Estimate
(
IDE)
for
two
PCB
Aroclors
(
1016
&
1260)
were
found
to
be
approximately
0.10
m
g/
L
in
reagent
water.

2.
The
best
achievable
Interlaboratory
Quantification
Estimate
(
IQE)
for
PCB
Aroclors
1016
&
1260
in
reagent
water
was
an
IQE30
(
30%
RSD)
that
is
approximately
equal
to
the
IDE.
The
IQE20
and
the
IQE10
were
not
achievable
because
the
model­
based
relative
standard
deviation
asymptotes
near
22%
at
concentration
0.25
 
m
g/
L.

3.
When
outlying
laboratories
are
removed
the
calculated
IDE
is
slightly
lower
(~
0.09
m
g/
L).
An
IQE30
still
holds
and
is
calculated
to
be
slightly
less
than
the
IDE
(~
0.08
 
m
g/
L).

4.
Reported
PCB
results
less
than
0.1
m
g/
L
by
this
pool
of
certified
laboratories
must
be
considered
questionable
especially
for
matrices
other
than
high
purity
reagent
water.

5.
Valid
EPA
interlaboratory
MDLs
calculated
from
study
data
ranged
from
0.028
m
g/
L
to
0.392
m
g/
L
for
Aroclor
1016
and
0.023
m
g/
L
to
0.445
m
g/
L
for
Aroclor
1260,
depending
upon
concentration.

6.
Routine
annual
MDLs
determined
by
each
participating
laboratory
were
significantly
lower
(
up
to
2100%)
than
within
laboratory
MDLs
determined
from
data
reported
during
the
study.

7.
Type
I
(
false
positive)
and
Type
II
(
false
negative)
error
rates
are
controlled
at
the
limit
of
detection
when
using
the
IDE,
but
are
not
controlled
when
using
the
MDL.

8.
Laboratories
reported
a
positive
result
for
the
presence
of
PCBs
in
reagent
water
blanks
ten
to
fifteen
percent
of
the
time.

9.
The
primary
source
of
variability
was
found
to
be
laboratory­
to­
laboratory
variability.
This
means
that
a
regulatory
limit
based
solely
on
within
lab
variability
would
not
be
achievable
under
routine
analysis
conditions
by
many
labs
currently
certified
to
perform
PCB
analysis.

10.
Many
sources
of
lab­
to­
lab
variability
persisted,
even
using
prequalified
laboratories
and
a
very
detailed
study
plan.

11.
We
make
the
following
recommendations
to
improve
accuracy
and
precision
for
low
level
PCB
analysis
in
water:

a.
Set
instrument
conditions
to
allow
first
surrogate
(
TCMX)
to
have
a
minimum
retention
time
of
4.00
minutes.
b.
Set
data
system
threshold
and
area
reject
to
allow
detection
of
all
peaks
greater
than
3­
5
times
the
background
noise.
c.
Check
for
proper
baseline
construction
for
all
chromatographic
runs.
d.
Select
the
appropriate
calibration
curve
and
quantify
results
using
this
calibration
curve.
e.
Add
additional
low­
level
calibration
curve
points
when
attempting
low
level
PCB
analysis.
f.
Calibration
standards
should
not
be
separated
by
more
than
2X
when
method
608
is
used.
g.
Run
a
low­
level
standard
in
addition
to
mid­
level
standard
on
a
daily
basis.
h.
Additional
clean­
up
steps
may
be
required
to
eliminate
small
interferences.
i.
Establish
quantification
procedures,
which
will
not
include
matrix
interferences
when
present.
3
1.
INTRODUCTION
In
1996­
1997
the
American
Automobile
Manufacturers
Association
(
AAMA)
undertook
a
study
to
determine
interlaboratory
detection
and
quantification
levels
for
thirteen
metals
and
two
polychlorinated
biphenyl
(
PCB)
Aroclors.
This
study
involved
nine
commercial
environmental
laboratories
and
took
approximately
six
months
to
complete.
Reasonable
interlaboratory
detection
and
quantification
levels
were
determined
in
reagent
water
and
four
other
matrices
of
interest
to
the
automobile
manufacturing
industry.
The
average
recovery
for
all
metals
was
approximately
100%
and
the
average
RSD
was
10%
for
concentrations
at
or
above
the
quantification
level.
In
comparison
detection
levels
greater
than
10
u
g/
L
were
determined
for
PCBs
and
the
relative
standard
deviation
never
fell
below
45%
even
at
the
highest
PCB
concentration
of
100
u
g/
L.
The
average
recovery
for
PCBs
was
only
11.2%
for
Aroclor
1242
and
21.5%
for
Aroclor
1260
with
recoveries
ranging
from
0%
to
95%
even
at
the
highest
concentration
(
Attachments
1.1
&
1.2).

A
key
finding
from
the
AAMA
study
was
that
variability
between
laboratories
was
the
single
greatest
source
of
error.
It
was
also
obvious
that
the
same
laboratories
that
could
successfully
analyze
blind
metals
samples
were
unable
to
consistently
analyze
blind
PCB
samples.
Sources
of
interlaboratory
variability
include
calibration
error,
instrument
instability
and
sample
preparation
variability.
Variability
is
inherently
greater
for
PCB
analysis
since
additional
sources
of
variability
also
come
into
play.
For
example,
the
Inductively
Couple
Plasma
Atomic
Emissions
Spectrophotometer
(
ICP/
AES)
used
for
most
metals
analyses
has
excellent
linearity
(
first
order
calibration
curve),
but
a
Gas
Chromatograph
with
an
Electron
Capture
Detector
(
GC/
ECD)
used
for
the
analysis
of
PCBs
is
nonlinear
and
prone
to
contamination.
Sample
preparation
for
organics
also
requires
several
additional
steps
including,
solvent
extraction,
multiple
transfers,
several
clean­
ups
and
a
concentration
step.
PCB
analysis
not
only
requires
the
integration
of
the
response
signal,
but
the
identification
of
congener
retention
times
and
Aroclor
patterns
(
congener
peak
ratios).
Analyst
practices
from
sample
handling
to
the
interpretation
of
results
all
become
significant
variables.

Beginning
in
2000
several
NPDES
permits
were
issued
in
the
State
of
Michigan,
which
incorporated
PCB
compliance
levels
that
may
be
below
interlaboratory
method
detection
capabilities
for
PCBs.
As
a
result
manufactures
could
be
at
risk
of
violating
permit
conditions
for
the
discharge
of
PCB
even
if
the
amount
in
their
discharge
(
even
if
absent)
is
below
the
water
quality
based
effluent
level.
In
these
instances
the
State's
permitting
approach
does
not
follow
State
Rules,
which
require
them
to
consider
the
achievability
by
competent
commercial
laboratories.
As
a
result
the
Michigan
Manufactures
Association
(
MMA)
undertook
a
new
PCB
interlaboratory
study
that
meets
the
intent
of
Michigan
Rules.
The
new
study
would
include
tighter
control
of
laboratory
procedures
in
an
effort
to
reduce
interlaboratory
variability.
We
also
hoped
to
learn
how
to
improve
interlaboratory
method
performance
when
using
EPA
method
608.2
for
measuring
PCBs.

1.1
Study
Participants
Laboratories
participating
in
the
study
included;

AA
Trinity,
Farmington
Hills,
MI
Ann
Arbor
Technical
Services,
Ann
Arbor,
MI
Clayton
Environmental,
Novi,
Michigan
CT&
E
Environmental
Services,
Ludington,
MI
Fire
and
Environmental
Laboratory,
East
Lansing,
MI
Severn
Trent
Laboratories
 
Buffalo,
NY
Severn
Trent
Laboratories
 
North
Canton,
OH
Test
America,
Dayton,
OH
TriMatrix
Laboratories,
Grand
Rapids,
MI
US
Filter,
Rothschild,
WI
4
Sample
preparation
was
carried
out
by
the
Annis
Water
Resources
Institute
(
AWRI)
at
Grand
Valley
State
University
(
GVSU)
which
is
located
in
Allendale,
Michigan.
Trace
Environmental
Laboratory
in
Muskegon,
Michigan
was
used
as
the
verification
test
laboratory.
Statistical
analysis
was
performed
by
the
Statistics
Department
at
GVSU
and
evaluation
of
laboratory
performance
was
done
by
AWRI.

2.
STUDY
DESIGN
AND
RESULTS
The
proposed
study
plan
details
the
initial
considerations
for
the
study
taking
into
account
lessons
learned
from
the
previous
AAMA
interlaboratory
study
for
PCBs
(
Attachment
2.1).

2.1
Laboratory
Selections
and
Qualification
To
get
a
sufficient
statistical
base
for
the
study
we
decided
to
select
ten
laboratories
to
participate
in
the
study.
The
initial
cut
of
laboratories
would
be
all
commercial
laboratories
performing
environmental
water
analysis
of
PCBs
using
EPA
method
608.2
in
the
State
of
Michigan.
The
laboratory
was
not
required
to
reside
in
Michigan,
but
must
perform
environmental
analysis
services
in
Michigan
on
a
routine
basis.
Notification
of
the
pending
study
and
a
request
for
participation
was
done
through
the
Michigan
Environmental
Laboratory
Association.
Laboratories
that
expressed
an
interest
in
participating
in
the
study
were
asked
to
furnish
the
following
information;

Ø
 
All
Performance
Evaluation
(
PE)
sample
results
for
PCBs
by
method
608
over
the
past
2
years.
Ø
 
A
list
of
all
current
certifications
for
PCB
analysis
in
water.
Ø
 
Whether
or
not
the
laboratory
was
pending
NELAP
accreditation
for
PCB
analysis
by
method
608.
Ø
 
Whether
or
not
the
laboratory
held
A2LA
accreditation
for
organics.
Ø
 
Whether
or
not
the
laboratory
was
in
the
Michigan
State
Drinking
Water
program.
Ø
 
Whether
or
not
the
laboratory
was
a
Michigan
State
Contract
Laboratory.

Laboratories
were
also
told
that
if
they
participated
in
the
study
they
would
be
paid
a
fixed
price
of
$
50.00
per
sample
and
that
we
anticipated
100­
120
samples
in
ten
to
twelve
sample
batches
over
about
a
threemonth
period.
Laboratory
identities
would
not
be
disclosed
in
the
final
report
and
each
participating
laboratory
would
receive
a
copy
of
the
final
report,
including
recommendations
for
improving
their
PCB
analysis.

All
laboratories
had
to
meet
the
following
minimum
criteria
to
be
selected
for
participation;

Ø
 
Hold
at
least
one
valid
State
or
Federal
certification
for
the
analysis
of
PCBs
by
method
608.
Ø
 
Have
successfully
completed
at
least
two
PE
samples
sets
for
PCBs
by
method
608
over
the
past
two
years.
Ø
 
Have
at
least
75%
of
all
PE
sample
results
over
the
past
two
years
fall
within
the
specified
warning
limits.

Eleven
laboratories
were
selected
to
participate
in
the
study,
one
verification
lab
and
ten
labs
for
the
determination
of
the
interlaboratory
detection
and
quantification
levels
for
PCBs
by
method
608.2
in
reagent
water
(
Attachment
2.2).

2.2
Initial
Information
on
PCB
Analysis
Before
the
study
began
each
of
the
ten
laboratories
participating
in
the
study
were
asked
to
provide
initial
information
regarding
the
PCB
analysis
procedures
and
capabilities.
A
compilation
of
the
information
5
provided
by
each
laboratory
is
included
in
Attachment
2.3
A­
J.
The
following
information
was
requested
from
each
laboratory;

Ø
 
Standard
Operating
Procedures
(
SOPs)
for
all
steps
in
the
PCB
analysis
process.
Ø
 
Most
recent
PCB
MDL
determinations
for
all
instruments
to
be
used
in
the
study.
Ø
 
Analyst
identification
designation
for
all
analysts
who
would
be
participating
in
the
study.
Ø
 
A
list
of
Surrogate
standards
used
for
PCB
analysis
by
method
608.2.
Ø
 
The
calibration
range
(
lowest
and
highest
calibration
standard)
for
PCBs.
Ø
 
PCB
clean­
up
procedures
utilized
on
a
routine
basis.
Ø
 
Procedure
for
the
identification
of
PCB
Aroclors.
Ø
 
Procedure
for
the
quantification
of
PCB
Aroclors.
Ø
 
Start­
up
demonstration
test
results
for
capillary
column
modification
of
method
608.

Note:
The
only
information
that
most
laboratories
were
unable
to
provide
was
the
start­
up
demonstration
test
results.
According
to
the
EPA
this
is
a
requirement
that
must
be
met
before
a
major
modification
of
a
test
method
is
made.
Switching
from
a
packed
column
to
a
capillary
column
is
considered
a
major
modification.
Apparently
most
laboratories
assume
that
capillary
column
precision
and
accuracy
is
superior
to
packed
column
precision
and
accuracy
without
doing
a
formal
initial
evaluation,
or
they
have
long
since
discarded
this
documentation.

2.3
Study
Kick­
Off
Meeting
On
November
20,
2000
a
Kick­
Off
meeting
was
held
with
all
participating
laboratories
and
the
verification
laboratory
to
go
over
the
study
requirements,
analysis
procedures
and
logistics
(
Attachment
2.4).
The
intent
of
the
Kick­
Off
meeting
was
to
give
adequate
guidance
to
acquire
high
quality
data
that
could
be
used
to
determine
interlaboratory
detection
and
quantification
levels.
However,
we
did
not
want
to
be
so
prescriptive
that
the
data
would
be
unrepresentative
of
the
normal
qualified
laboratory
population.
While
only
clean
reagent
water
would
be
used
in
this
phase
of
the
study,
we
still
felt
it
important
to
include
all
common
steps
of
the
PCB
clean­
up
and
analysis
process.
The
key
points
covered
in
the
Kick­
Off
meeting
were
the
following;

Ø
 
Ten
 
1,000
ml
whole
volume
samples
in
reagent
water
will
be
submitted
every
one
to
two
weeks.
Ø
 
Sample
concentrations
will
range
from
non­
detect
to
~
2.5
m
g/
L
and
each
sample
will
contain
two
PCB
Aroclors.
Ø
 
Each
sample
will
have
a
designation
code
indicating
the
sample
number,
batch
number
and
laboratory
code.
Sample
concentrations
will
be
randomized
and
must
be
analyzed
in
order
of
sample
code
(
Attachment
2.5).
Ø
 
Rinse
sample
container
and
lid
three
times
after
transferring
the
sample
and
specify
the
liquid/
liquid
extraction
procedure
you
use.
Ø
 
Initial
sample
volume
shall
be
1,000
ml
and
final
volume
of
extract
shall
be
1.0
ml.
Ø
 
Every
sample
must
go
through
a
Sulfuric
Acid
Clean­
up
with
only
one
acid
treatment.
Ø
 
Every
sample
must
go
through
a
Florisil
Clean­
up,
specify
the
method
you
use.
Ø
 
Every
sample
must
go
through
a
Sulfur
Clean­
up,
specify
the
method
you
use.
Ø
 
Do
not
perform
a
second
column
confirmation.
Ø
 
A
laboratory
method
blank
will
be
analyzed
and
reported
with
each
sample
batch.
Ø
 
A
laboratory
fortified
blank
(
LFB)
near
the
midpoint
of
your
calibration
curve
(
Aroclor
1254
or
1260)
will
be
analyzed
and
reported
for
each
sample
batch.
The
LFB
must
go
through
the
entire
extraction
and
clean­
up
process.
Ø
 
The
laboratory
shall
cycle
between
all
qualified
PCB
analysts
and
between
all
instruments
used
for
PCB
analysis
by
method
608.2.
Ø
 
A
calibration
curve
consisting
of
a
minimum
of
four
points
(
not
including
zero)
must
be
used.
Ø
 
The
ratios
of
the
five
major
Aroclor
congeners
must
be
within
20%
of
an
Aroclor
standard
to
be
identified
as
that
Aroclor.
Ø
 
Quantification
will
be
based
on
the
calibration
curve
response
factor.
6
Ø
 
Use
three
to
five
congener
peaks
per
Aroclor
for
quantification.
Ø
 
Continuing
calibration
verification
will
be
based
on
a
midrange
calibration
standard
and
the
instrument
will
be
recalibrated
if
>
15%
variance.
Ø
 
Report
results
for
each
batch
of
samples
electronically
to
Dr.
Gabrosek
in
the
standard
Excel
spreadsheet
provided
(
Attachment
2.6).
Ø
 
Report
all
results
as
low
as
you
can
see,
even
without
Aroclor
recognition.
Ø
 
Report
all
quantified
results
in
m
g/
L
to
the
10,000th
place
(
four
places
past
decimal).
Ø
 
If
a
minimum
of
three
congener
peaks
can't
be
quantified
then
report
a
blank
or
empty
field.
Ø
 
When
you
can
recognize
an
Aroclor
using
your
normal
Aroclor
identification
technique
then
include
this
information
with
the
numerical
result.
Ø
 
Report
the
batch
blank
result
last
and
designate
it
9YX
(
Y=
Batch
#
and
L=
Lab
#).
Ø
 
Two
copies
of
one
final
hard
copy
report
will
be
submitted
to
Dr.
Rediske
including
the
following
information:
o
A
summary
of
all
results
including
QC
(
Surrogate
%
Recovery,
LFB
%
Recovery
and
Blanks)
o
Calibration
curves
o
Raw
chromatograms
with
integration
o
Methods
used
for
sample
extraction
and
clean­
up
o
Raw
data
from
any
PCB
MDLs
generated
during
the
study
period
o
Analyst
identification
for
extractions,
clean­
ups
and
chromatographic
analyses
o
Instrument
identification
2.4
Sample
Preparation
and
Verification
Samples
were
prepared
by
the
staff
at
GVSU
AWRI
from
1,000
mg/
L
stock
solutions
of
PCB
Aroclors
in
methanol.
High
(
10
mg/
L)
and
low
(
1
mg/
L)
intermediate
level
standard
solutions
in
methanol
were
then
used
to
generate
the
high
and
low
concentration
range
of
regent
water
samples
respectively.
Intermediate
stock
solutions
were
diluted
directly
into
the
sample
jars
containing
reagent
water
to
avoid
any
transfer
steps
once
the
PCB
was
in
an
aqueous
solution.
Most
jars
supplied
had
a
capacity
of
1,000
ml,
but
a
few
laboratories
submitted
wide
mouth
sample
containers
that
could
only
accommodate
a
980
ml
sample.
Final
concentrations
were
corrected
when
smaller
containers
were
used.
Aroclors
1016
and
1260
were
present
at
approximately
the
same
concentration
in
each
sample.
All
dilutions
were
made
using
volumetric
glassware
and
calibrated
syringes.
Samples
for
all
laboratories
were
prepared
at
the
same
time
for
each
batch
and
batches
were
submitted
to
participating
labs
every
one
to
two
weeks.
Two
extra
sample
sets
(
full
concentration
range)
were
generated
each
week
so
that
any
samples
lost
due
to
breakage
during
shipment
could
be
replaced.
Every
other
week
the
concentration
of
PCB
Aroclors
alternated
between
Youden
pairs
as
follows:

Table
2.1
PCB
Aroclor
Concentration
in
m
g/
L
Week
A
Week
B
Low
Range
0.005
0.006
0.010
0.015
0.025
0.030
0.050
0.060
High
Range
0.100
0.120
0.200
0.240
0.500
0.600
1.000
1.200
Stock
standard
solutions
were
verified
prior
to
the
start
of
the
study
by
Trace
Analytical,
a
State
of
Michigan
Contract
Laboratory
located
in
Muskegon,
MI.
Two
random
samples
were
selected
each
week
(
batch)
and
sent
to
Trace
Analytical
for
verification
(
Attachment
2.7).
For
low
range
samples
Trace
Analytical
extracted
two
liters
of
sample,
did
not
perform
sample
clean­
up
and
concentrated
the
final
7
extract
to
0.5
ml,
yielding
a
4x
enhancement
in
sensitivity.
Twenty­
eight
high
range
samples
(
³
0.1
m
g/
L)
were
verified
with
a
mean
of
93.07%
recovery.
Even
with
the
4x
enhancement
in
method
sensitivity
many
low
range
samples
(<
0.1
m
g/
L)
were
still
not
detectable
by
the
verification
laboratory.
Of
the
low
range
samples
that
could
be
verified
the
recoveries
ranged
from
60%
to
200%.
As
we
will
see
later
a
concentration
of
approximately
0.1
m
g/
L
was
determined
to
be
the
interlaboratory
detection
limit
of
the
method.

2.5
Results
The
results
reported
from
each
of
the
laboratories
participating
in
the
study
along
with
the
true
values
are
provided
in
Attachment
2.8.
Attachment
2.9
summarizes
all
non­
zero
results
with
individual
outliers
removed
(
OR)
and
with
laboratory
outliers
removed
(
DL)
for
each
Aroclor
(
A1=
1016,
A2=
1260).

3.
DATA
ANALYSIS
 
STATISTICS
In
Section
2,
we
discussed
the
protocol
for
the
study
and
addressed
several
issues
related
to
analysis
of
the
data.
In
this
section,
we
detail
the
statistical
analysis
of
the
data.
In
Section
3.1,
we
begin
with
some
background
information
on
detection
and
quantitation
limits.
In
Section
3.2,
we
discuss
data
handling
and
data
cleaning.
Data
cleaning
is
used
to
prepare
the
data
for
statistical
analysis.
In
Section
3.3,
we
discuss
results
of
the
statistical
analysis
and
find
detection
and
quantitation
limits.
In
Section
3.4,
we
discuss
results
of
an
analysis
of
variance
for
determining
sources
of
variation
in
the
results.

3.1
Statistical
Issues
in
Detection
and
Quantitation
There
are
many
techniques
commonly
used
to
set
detection
and
quantitation
limits
for
laboratory
analysis
of
chemicals
in
industrial
effluents.
We
do
not
suggest
that
this
brief
review
is
exhaustive
of
available
statistical
techniques.
We
offer
it
as
a
broad
outline
of
the
field
of
setting
detection
and
quantitation
limits.

One
can
think
of
a
detection
limit
as
the
minimum
amount
of
a
chemical
(
often
measured
in
parts
per
million
or
parts
per
billion)
that
can
be
reliably
detected
by
common
laboratory
analysis.
There
are
several
seemingly
innocuous
phrases
in
this
definition
that
give
rise
to
a
wide
variety
of
approaches
for
setting
detection
limits.
Consider
the
"
minimum
amount
of
a
chemical."
Do
we
mean
the
minimum
amount
in
reagent
water?
Do
we
mean
the
minimum
amount
in
a
specific
stream,
river,
or
lake?
Do
we
mean
the
minimum
amount
in
a
specific
industrial
effluent?
The
answer
to
this
question
can
have
a
profound
impact
on
the
detection
limit.
Laboratories
are
able
to
identify
the
presence
of
a
chemical
in
reagent
water
at
much
lower
concentrations
than
in
actual
water
bodies
or
industrial
effluents.
Basing
detection
limits
on
the
analysis
of
reagent
water
may
require
an
industry
to
meet
a
standard
that
is
unattainable
for
a
laboratory
to
accurately
measure
in
practice.

Next,
consider
"
reliably
detected."
Different
detection
limit
measures
define
reliability
in
very
different
ways.
Statisticians
are
aware
of
the
intrinsic
conflict
between
limiting
the
chance
of
a
false
positive
(
Type
I
error)
and
a
false
negative
(
Type
II
error).
One
could
largely
eliminate
the
chance
of
a
false
positive,
but
only
at
the
increased
risk
of
a
false
negative,
and
vice
versa.
For
setting
detection
limits,
a
false
positive
occurs
if
a
laboratory
reports
the
presence
of
a
chemical
(
i.
e.,
a
result
above
the
detection
limit),
when
the
chemical
is
truly
absent
or
present
in
a
concentration
below
the
detection
limit.
A
false
positive
could
lead
regulators
to
require
a
cleanup
where
no
potential
environmental
consequences
exist;
thereby,
wasting
limited
resources.

For
setting
detection
limits,
a
false
negative
occurs
if
a
laboratory
reports
the
absence
of
a
chemical
(
i.
e.,
a
result
below
the
detection
limit),
when
the
chemical
concentration
is
truly
above
the
detection
limit.
A
false
negative
could
lead
regulators
to
overlook
a
polluted
site
until
after
the
environmental
consequences
occur.
Which
potential
error,
false
positive
or
false
negative,
is
more
serious
is
open
to
debate.
Ideally
a
detection
limit
would
represent
a
reasoned
balance
between
these
two
potential
errors.
Different
detection
limit
techniques
set
a
different
balance.
8
The
Method
Detection
Limit
(
MDL)
procedure
sets
the
false
negative
error
rate
at
1%.
Thus,
when
measuring
a
sample
containing
the
analyte
of
interest
at
the
MDL,
you
will
have
a
99%
probability
of
detecting
the
analyte.
The
Interlaboratory
Detection
Estimate
(
IDE)
and
the
Alternate
Minimum
Level
(
AML)
procedures
set
the
false
negative
error
rate
at
5%.
Thus,
when
measuring
a
sample
containing
the
analyte
of
interest
at
the
IDE
or
the
Limit
of
Detection
(
LD),
you
will
have
a
95%
probability
of
detecting
the
analyte.
The
IDE
and
the
AML
procedures
set
the
false
positive
error
rate
at
the
LD
at
1%.
Thus
when
measuring
a
blank
the
probability
of
not
detecting
the
analyte
would
be
99%.
The
false
positive
error
rate
at
the
Critical
Level
(
LC)
is
50%.
The
MDL
procedure
does
not
control
the
false
positive
error
rate.

Lastly,
consider
"
common
laboratory
analysis."
This
phrase
is
probably
the
least
represented
in
detection
limits
and,
potentially,
the
most
influential.
Different
laboratories
use
different
techniques
for
analyzing
the
presence
of
chemicals
in
samples.
Equipment,
analyst,
and
protocol
differences
can
lead
to
large
variations
in
accuracy
from
laboratory
to
laboratory.
In
Section
4.1,
we
discuss
some
of
the
discrepancies
we
saw
in
the
protocol
used
by
different
laboratories.
These
discrepancies
occurred
even
though
we
defined
a
common
protocol
for
all
the
labs
to
use
in
the
study!
Even
if
it
were
possible
to
define
an
agreed­
upon
protocol
for
all
laboratories,
the
variation
in
results
from
lab
to
lab
would
far
exceed
the
variation
in
results
for
a
specific
laboratory.
Since
most
detection
limits
are
a
function
of
the
variability
in
readings
for
known
concentrations,
detection
limits
could
be
an
order
of
magnitude
lower
for
a
specific
laboratory
than
for
laboratories
in
general.
We
suggest
that
inter­
laboratory
limits
are
preferred
for
applications
where
data
come
from
more
than
one
laboratory
because
they
account
for
the
real
differences
observed
in
techniques
used
by
laboratories
to
analyze
chemical
concentrations.
Intra­
laboratory
limits
may
be
more
appropriate
for
within
laboratory
quality
control
because
of
their
inherent
simplicity.

One
can
think
of
a
quantitation
limit
as
the
minimum
amount
of
a
chemical
(
often
measured
in
parts
per
million
or
parts
per
billion)
for
which
a
common
laboratory
analysis
can
specify
the
concentration
of
the
chemical.
Obviously,
a
quantitation
limit
should
always
be
greater
than
a
detection
limit,
since
not
only
does
the
lab
have
to
state
that
a
chemical
is
present,
but
also
it
has
to
determine
the
amount.
Many
of
the
issues
discussed
above
for
setting
detection
limits
apply
to
setting
quantitation
limits.
As
we
will
see,
the
quantitation
limit
is
often
two
to
three
times
the
detection
limit.

In
Section
3.2,
we
detail
issues
involved
in
preparing
the
data
for
statistical
analysis.
In
Section
3.3,
we
report
the
results
of
our
inter­
laboratory
study.
The
techniques
that
we
discuss
for
setting
the
detection
limit
include
the
Method
Detection
Limit
(
MDL),
the
Critical
Level
(
LC),
the
Limit
of
Detection
(
LD),
and
the
Interlaboratory
Detection
Estimate
(
IDE).
The
techniques
that
we
discuss
for
setting
the
quantitation
limit
include
the
Minimum
Level
(
ML),
the
Alternate
Minimum
Level
(
AML),
and
the
interlaboratory
quantitation
estimate
(
IQE).

3.2
Data
Handling
and
Data
Cleaning
Initial
data
cleaning
issues
must
be
resolved
prior
to
statistical
analysis
of
data.
Loosely
defined,
data
cleaning
involves
preparing
the
data
for
analysis.
The
following
procedure
was
used
to
clean
the
data:

·
 
Create
a
summary
sheet
(
Final
32)
that
includes
results
for
the
10
laboratories
for
each
of
the
two
aroclors
for
each
of
the
10
weeks
of
the
study.
Figure
3.1
is
a
portion
of
Final
32.
Table
3.1
defines
the
columns.

Figure
3.1
Portion
of
Final
32
data
summary
sheet.
I.
D.
Aroclor
1
Result
1
Aroclor
2
Result
2
Ext.
Clean
GC
Instrum.
C1
C2
D1
D2
D3
D4
11F
1016
0.1742
1260
0.1225
JRG
JRG
JDM
158.00
0.2400
0.2000
0.2400
0.2200
0.2000
0.2200
21F
Unknown
0.0220
Unknown
0.0085
JRG
JRG
JDM
158.00
0.0150
0.0100
0.0150
0.0125
0.0100
0.0125
31F
Unknown
0.0398
1260
0.0226
JRG
JRG
JDM
158.00
0.0300
0.0250
0.0300
0.0275
0.0250
0.2750
41F
1016
0.0609
1260
0.0405
JRG
JRG
JDM
158.00
0.0600
0.0500
0.0600
0.0550
0.0500
0.0550
9
Table
3.1
Final
32
columns.
Column
Label
Column
Meaning
I.
D.
A
three
number
code
(
bottle,
week,
lab)
for
each
sample.
Bottles
are
from
1­
9,
weeks
from
1­
10,
and
labs
from
A­
J.
Aroclor
1
The
lab
identified
PCB
aroclor
for
aroclor
1.
The
true
PCB
aroclor
for
aroclor
1
is
1016.
Result
1
The
measured
response
for
aroclor
1.
There
is
a
response
for
each
of
9
concentrations
for
each
week­
lab.
Aroclor
2
The
lab
identified
PCB
aroclor
for
aroclor
2.
The
true
PCB
aroclor
for
aroclor
2
is
1260.
Result
2
The
measured
response
for
aroclor
2.
There
is
a
response
for
each
of
9
concentrations
for
each
week­
lab.
Ext.
The
extraction
technique
utilized
by
the
lab.
Clean
The
clean­
up
technique
utilized
by
the
lab.
GC
The
Gas
Chromatography
analyst.
Instrum.
The
instrument
used
by
the
lab.
C1
The
concentration
for
aroclor
1.
The
different
values
are
blank,
.005
&
.006,
.010
&
.015,
.025
&
.030,
.050
&
.060,
.100
&
.120,
.200
&
.240,
.500
&
.600,
and
1.000
&
1.200.
The
pairs
of
similar
concentrations
are
Youden
pairs.
Only
one
of
the
two
Youden
pair
values
is
used
for
any
given
week.
Also,
there
is
a
bottle
effect
owing
to
whether
the
lab
used
wide­
mouthed
bottles.
The
bottle
choice
actually
modifies
the
concentration
multiplying
it
by
0.98.
We
will
ignore
this
effect.
However,
it
does
show
up
in
some
of
the
labs'
reports
as
a
different
concentration.
We
adjusted
for
this
below.
(
See
description
of
the
columns
labeled
D1,
D2,
D3,
and
D4.)
C2
Same
as
C1
except
for
aroclor
2.
D1
Concentration
1
eliminating
the
bottle
effect
but
keeping
the
Youden
pairs
separate.
D2
Concentration
1
eliminating
the
bottle
effect
and
averaging
the
Youden
pairs.
D3
Concentration
2
eliminating
the
bottle
effect
but
keeping
the
Youden
pairs
separate.
D4
Concentration
2
eliminating
the
bottle
effect
and
averaging
the
Youden
pairs.

·
 
Create
separate
summary
sheets
for
each
aroclor­
concentration
(
D1,
D2,
D3,
D4).
The
four
sheets
correspond
to
aroclor
1
(
PCB
1016)
with
the
16
concentrations
treated
separately
(
Final
16­
A1);
aroclor
2
(
PCB
1260)
with
the
16
concentrations
treated
separately
(
Final
16­
A2);
aroclor
1
with
the
eight
Youden
pair
averaged
concentrations
(
Final
8­
A1);
and,
aroclor
2
with
the
eight
Youden
pair
averaged
concentrations
(
Final
8­
A2).
Table
3.2
shows
the
Youden
pairs
and
the
average
of
the
Youden
pairs.

Table
3.2
Youden
pairs
and
their
averages.
Youden
pair
concentration
1
Youden
pair
concentration
2
Youden
pair
average
concentration
0.005
0.006
0.0055
0.010
0.015
0.0125
0.025
0.030
0.0275
0.050
0.060
0.055
0.100
0.120
0.110
0.200
0.240
0.220
0.500
0.600
0.550
1.000
1.200
1.100
10
We
found
no
significant
difference
in
IDE
or
IQE
results
between
8­
A1
&
16­
A1
or
between
8­
A2
&
16­
A2.
However,
we
found
that
when
we
averaged
the
Youden
pairs
and
performed
an
analysis
of
variance
(
ANOVA)
this
confounded
the
concentration
variable
with
weeks.
Therefore,
from
this
point
on,
we
will
focus
our
discussion
on
16­
A1
and
16­
A2
only.

·
 
For
Final
16­
A1
and
Final
16­
A2
create
two
new
files,
one
of
which
deletes
outlying
points
only
and
one
of
which
deletes
outlying
labs
and
then
outlying
points.
These
files
are
called
Final
16­
A1­
OR
(
outlying
points
deleted),
Final
16­
A1­
DL­
OR
(
outlying
labs
and
then
outlying
points
deleted),
Final
16­
A2­
OR,
and
Final
16­
A2­
DL­
OR.

To
delete
outlying
points,
we
apply
Grubb's
Test
as
described
in
ASTM
D2777,
Section
10.
The
procedure
is:

(
i)
Sort
by
Result
in
ascending
order.
(
ii)
Delete
all
non­
detects.
(
iii)
Sort
by
Concentration
(
ascending)
and
Result
(
ascending).
(
iv)
Calculate
standard
scores
(
call
them
t­
values)
for
each
result.
First,
take
the
result
minus
the
average
result
for
the
week­
concentration.
Then,
divide
this
difference
by
the
standard
deviation
of
the
results
for
the
week­
concentration.
(
v)
Determine
whether
the
largest
absolute
t­
value
is
beyond
the
outlier
critical
value.
The
critical
value
is
found
from
ASTM
D2777,
Table
2.
(
vi)
If
the
largest
absolute
t­
value
is
not
beyond
the
critical
value,
then
there
are
no
outliers.
If
the
largest
absolute
t­
value
is
beyond
the
critical
value,
then
the
result
is
an
outlier
and
it
should
be
deleted
from
further
analysis.
(
vii)
Iteratively
detect
outliers,
stopping
when
the
largest
absolute
t­
value
is
not
beyond
the
critical
value
or
if
one
more
outlier
would
lead
to
more
than
10%
of
the
reported
values
being
deleted.

See
Appendix
1
for
a
list
of
the
outlying
points
in
each
of
the
four
files.

To
delete
outlying
labs
apply
the
outlying
lab
identifier
test
as
described
in
ASTM
D2777,
Section
10.3.
The
procedure
is
as
follows:

(
i)
Sort
by
Week
(
ascending),
Concentration
(
ascending),
and
Result
(
descending).
(
ii)
Rank
data
within
each
week­
concentration.
The
highest
result
is
given
rank
1,
the
second
highest
rank
2,
and
so
on.
For
instance,
if
only
5
labs
report
a
result
for
a
certain
week­
concentration,
then
the
ranks
are
1,
2,
3,
4,
5.
If
there
are
ties
in
the
results,
then
use
midranks.
(
iii)
Sort
by
Week
(
ascending)
and
Lab
(
ascending).
(
iv)
Replace
each
non­
detect,
for
concentrations
other
than
the
blank,
within
each
weeklab
with
the
average
of
the
ranks
for
all
concentrations
for
which
the
lab
reported
a
result.
(
v)
Sum
the
ranks
over
the
eight
non­
blank
concentrations.
(
vi)
Determine
whether
the
rank
sum
is
beyond
one
of
the
outlying
lab
critical
values.
The
critical
values
are
found
from
ASTM
D2777,
Table
1.
(
vii)
No
more
than
20%
of
all
labs
may
be
deleted
for
a
week.
Thus,
if
more
than
20%
of
the
labs
are
detected
as
outlying,
then
remove
the
most
extreme
lab
(
farthest
from
the
critical
values)
first.
Continue
removing
most
extreme
labs
until
the
next
lab
removed
would
exceed
20%
of
all
the
labs.

See
Appendix
2
for
a
list
of
outlying
labs
for
each
of
the
files
Final
16­
A1
and
Final
16­
A2.
Recall
that
outlier
lab
removal
is
done
prior
to
outlying
point
removal.
The
outlying
lab
procedure
ranks
labs
relative
to
all
of
the
other
labs.
Thus,
an
outlying
lab
is
not
necessarily
reporting
highly
erroneous
results.
Rather,
the
outlying
lab
is
reporting
results
that
are
either
consistently
low
(
thus,
it
has
high
ranks)
or
consistently
high
(
thus,
it
has
low
ranks)
relative
to
the
other
labs.
It
is
also
true
that
outlying
points
are
determined
relative
to
the
other
points.
11
After
data
cleaning
has
been
completed,
the
four
separate
data
files
are
ready
for
statistical
analysis.
The
blank
concentration,
all
non­
detects,
and
outliers
have
been
removed.
The
resulting
detection
and
quantitation
limits
should
reflect
what
is
attainable
in
practice
in
reagent
water.
In
Section
3.3,
we
detail
results
of
the
statistical
analysis.

3.3
Statistical
Analysis
­
Detection
and
Quantitation
In
this
section,
we
discuss
detection
and
quantitation
results.
Results
for
four
files
(
16­
A1­
OR,
16­
A1­
DLOR
16­
A2­
OR,
and
16­
A2­
DL­
OR)
will
be
given,
though
we
will
focus
our
discussion
on
the
file
Final
16­
A1­
OR.
Recall
that
this
file
is
for
aroclor
1
(
PCB
aroclor
1016);
the
concentrations
for
the
Youden
pairs
are
treated
separately;
outlying
labs
have
not
been
removed;
and,
outlying
points
have
been
removed.
We
used
two
different
programs
for
setting
detection
and
quantitation
limits.
The
first
program
was
developed
by
David
Coleman
of
Alcoa
Inc.
His
IDE/
IQE
program
is
an
Excel
template
that
calculates
the
LC,
the
IDE,
the
IQE,
the
MDL,
and
the
ML.
The
second
program
was
developed
by
Robert
D.
Gibbons
Ltd.
and
Discerning
Systems
Inc.
The
AML
program
calculates
the
LC,
LD,
and
AML.
Both
programs
allow
for
a
choice
of
models
for
relating
the
standard
deviation
to
the
concentration.
The
resulting
curve
is
used
in
calculating
detection
and
quantitation
limits.
More
will
be
said
on
this
later.

To
utilize
the
IDE/
IQE
program,
the
data
are
entered
in
two
columns;
concentration
and
result.
Concentrations
are
entered
in
ascending
order
with
no
missing
values.
Thus,
non­
detects
are
not
used
in
the
calculation
of
the
detection
or
quantitation
limits.
The
program
assumes
a
linear
relationship
between
mean
response
and
concentration.
The
program
also
assumes
that
the
measurement
error
is
normally
distributed
(
Coleman,
2001).
The
program
produces
a
variety
of
detection
and
quantitation
results,
as
well
as
diagnostic
plots.
We
discuss
the
detection
and
quantitation
limits
and
the
diagnostic
plots
for
Final
16­
A1­
OR.

Figure
3.2
is
a
plot
of
the
response
versus
the
concentration
(
labeled
true
concentration
on
the
plot).
The
plot
is
used
to
check
the
assumption
that
the
straight­
line
model
holds
for
the
mean
response
versus
the
concentration.
From
Figure
3.2,
the
assumption
appears
to
be
reasonable.
Data
points
are
denoted
by
dark
blue
diamonds.
The
pink
horizontal
bar
at
each
concentration
is
the
mean
response.
There
are
two
lines
corresponding
to
ordinary
least­
squares
(
OLS)
and
weighted
least­
squares
(
WLS)
fits.
OLS
places
equal
weight
on
each
concentration
in
determining
the
mean
response
to
concentration
linear
relationship.
WLS
places
more
weight
on
those
concentrations
with
lower
standard
deviations.
We
need
not
concern
ourselves
with
choosing
between
these
lines
because
they
are
very
close
for
all
four
files.
If
there
were
outliers
that
had
not
been
removed
prior
to
analysis,
then
they
would
occur
as
isolated
points
far
from
the
cluster
of
points
at
a
given
concentration.
In
Figure
3.2,
you
will
note
that
the
point
(
1.200,
0.3090)
appears
to
be
quite
far
from
the
cluster
of
points
for
concentration
1.200.
However,
it
is
not
an
outlier
according
to
Grubb's
test.
There
were
22
outlying
points
deleted
from
the
file
Final
16­
A1­
OR
(
see
Table
A.
1.1
for
a
list
of
the
outlier
points).
For
example,
one
of
the
outliers
was
I.
D.
75I.
The
point
was
(
1.200,
0.0764).
This
point
would
be
well
below
the
cluster
of
points
for
concentration
1.200.
Recall
that
according
to
Grubb's
test
an
outlier
is
determined
relative
to
the
other
results
at
the
same
concentration,
not
relative
to
the
concentration.

A
second
point
is
that
the
standard
deviation
is
not
constant
from
concentration
to
concentration.
For
lower
concentrations,
the
standard
deviation
is
much
less
than
for
higher
concentrations.
In
Figure
3.2,
notice
how
much
tighter
are
the
clusters
of
points
at
the
lower
concentrations
than
at
the
higher
concentrations.

Finally,
for
low
concentrations
the
mean
response
is
higher
than
the
concentration.
(
For
example,
the
mean
response
is
0.0281
for
concentration
0.005.)
For
high
concentrations,
the
mean
response
is
lower
than
the
concentration.
(
For
example,
the
mean
response
is
0.8965
for
concentration
1.200).
Near
the
median
of
the
concentrations,
the
mean
response
is
quite
close
to
the
concentration.
(
For
example,
the
mean
response
is
0.0915
for
concentration
0.100).
This
is
partially
a
function
of
how
laboratories
set
their
calibration
curves,
as
we
discuss
in
Section
4.4.
Thus,
stating
that
a
straight
line
models
the
relationship
between
mean
response
and
concentration
does
not
imply
that
the
mean
response
is
roughly
equal
to
the
concentration.
12
Figure
3.2
Final
16­
A1­
OR
response
versus
concentration.

Figure
3.3
is
a
plot
of
the
residuals
versus
the
concentration.
Residuals
are
defined
as
the
result
minus
the
mean
response
at
the
concentration.
For
the
assumptions
underlying
the
IDE/
IQE
procedure
to
be
met,
the
plot
should
have
two
features;
(
i)
there
should
be
no
obvious
curvature
in
the
residuals,
which
would
suggest
the
need
for
a
quadratic
or
higher
order
term
in
the
model,
and
(
ii)
the
residuals
should
appear
to
be
roughly
normally
distributed
at
each
concentration.
Figure
3.3
is
consistent
with
both
of
these
assumptions.
An
obvious
funneling
out
suggests
that
the
constant
model
for
the
standard
deviation
is
not
appropriate.
(
Statisticians
call
this
heteroscedasticity.)

Figure
3.3
Final
16­
A1­
OR
residuals
versus
concentration.

Residuals
vs.
Conc
(
T)

­
0.8
­
0.6
­
0.4
­
0.2
0
0.2
0.4
0.6
0.000
0.200
0.400
0.600
0.800
1.000
1.200
1.400
True
Concentration
(
T)
Residuals
OLS
Residuals
WLS
Residuals
Response
(
Y)
vs.
True
Concentration
(
T)

0.0000
0.2000
0.4000
0.6000
0.8000
1.0000
1.2000
1.4000
0.000
0.200
0.400
0.600
0.800
1.000
1.200
1.400
True
Concentration
(
T)
Response
(
Y)

Data
OLS
(
Constant­
SD
Model)
WLS
Fit
13
Figure
3.4
is
a
plot
of
the
interlaboratory
standard
deviation
versus
the
concentration.
At
each
true
concentration,
the
standard
deviation
of
the
results
is
plotted.
For
example,
the
standard
deviation
of
the
results
for
concentration
0.600
is
0.0897.
If
the
standard
deviation
were
constant
over
concentrations
then
a
horizontal
line
would
fit
the
data.
Clearly,
such
is
not
the
case.
It
is
interesting
to
note
that
the
MDL
procedure
assumes
a
constant
standard
deviation.
The
standard
deviation
versus
concentration
model
is
chosen
from
among
three
alternative
models.
The
pink
line
corresponds
to
the
straight­
line
model
hT
g
s
+
=
,
where
s
is
the
standard
deviation
at
concentration
T
,
g
is
the
standard
deviation
at
0
=
T
,
and
h
is
the
slope.
The
green
line
corresponds
to
the
exponential
model
hT
e
g
s
*
=
,
where
s
,

g
,
and
T
are
as
above
and
h
is
related
to
the
curvature
of
the
model.
The
blue
line
is
the
hybrid
model
(
sometimes
called
the
"
hockey­
stick
model"
due
to
its
shape
or
the
"
Rocke
and
Lorenazto
model"
after
its
authors)
(
)
2
2
hT
g
s
+
=
,
where
s
,
g
,
and
T
are
as
above
and
h
is
related
to
the
curvature
of
the
model.
The
straight­
line
model
should
be
favored
over
the
hybrid
model,
which
should
be
favored
over
the
exponential
model,
unless
compelling
evidence
suggests
otherwise.
From
Figure
3.4,
it
appears
that
the
straight­
line
and
hybrid
models
each
fit
the
data
well.
(
Notice
how
poorly
the
exponential
model
fits
the
data
for
concentration
1.200,
where
it
severely
overestimates
the
standard
deviation.)

Figure
3.4
Final
16­
A1­
OR
standard
deviation
versus
concentration.

Figure
3.5
is
a
plot
of
the
residuals
versus
the
concentration
for
each
of
the
three
models.
We
look
for
obvious
curvature
in
the
residuals
as
the
concentration
increases.
There
is
no
obvious
pattern
for
either
the
straight­
line
or
hybrid
models.
For
the
exponential
model
(
the
triangles),
there
is
parabolic
curvature
in
the
residuals.
InterLab
Std
Dev
(
s)
&
ILSD
Models
vs.
True
Concentration
(
T)

0
0.05
0.1
0.15
0.2
0.25
0.3
0
0.2
0.4
0.6
0.8
1
1.2
1.4
True
Concentration
(
T)
Std
Dev
(
s)
&
ILSD
Models
Data
Straight­
Line
Fit
Exponential
Fit
Hybrid
14
Figure
3.5
Final
16­
A1­
OR
standard
deviation
residuals
versus
concentration.

Figure
3.6
is
a
plot
of
the
relative
standard
deviation
(
RSD)
versus
the
concentration.
The
relative
standard
deviation
is
the
standard
deviation
of
the
results
at
a
concentration
divided
by
the
concentration
multiplied
by
100%.
From
Figure
3.4,
we
saw
that
the
standard
deviation
increases
as
the
concentration
increases.
However,
from
Figure
3.6,
as
the
concentration
increases
the
relative
standard
deviation
decreases.
For
low
concentrations
the
relative
standard
deviation
is
high.
This
is
intuitively
logical.
For
low
concentrations,
any
variability
between
measurements
will
be
large
relative
to
the
true
concentration
because
the
true
concentration
is
so
low.
The
interesting
fact
is
that
near
concentration
0.200
the
relative
standard
deviation
appears
to
stabilize
at
slightly
more
than
20%.
(
See
the
asterisked
points
in
Figure
3.6.)
Again
the
constant
(
navy
blue),
straight­
line
(
pink),
exponential
(
green),
and
hybrid
(
blue)
models
are
shown.
The
constant
model
fits
the
data
poorly.
The
fit
of
the
exponential
model
is
a
some
improvement
over
the
constant
model,
however
the
fit
is
still
marginal.
Both
the
straight­
line
and
hybrid
models
fit
the
data
quite
well;
however,
there
is
a
noticeable
difference
at
the
lower
concentrations.
The
straight­
line
model
overestimates
the
RSD
at
concentrations
below
0.200.
Since,
the
detection
limit
and
quantitation
limits
are
below
0.200
this
argues
in
favor
of
the
hybrid
model.
Thus,
we
conclude
that
the
hybrid
model
is
to
be
used
for
Final
16­
A1­
OR.

Once
a
model
has
been
chosen,
Figure
3.6
can
be
used
to
find
the
IQE.
The
vertical
blue
line
is
the
IQE30
for
the
hybrid
model.
This
corresponds
to
the
concentration
at
which
the
RSD
is
30%.
The
IQE20
and
IQE10
are
not
achievable
because
the
RSD
for
the
hybrid
model
does
not
drop
down
to
20%.
The
RSD
asymptotes
near
22%
at
concentration
0.25
m
g/
L.
ILSD
Residuals
vs.
True
Concentration
(
T)

­
0.1
­
0.08
­
0.06
­
0.04
­
0.02
0
0.02
0.04
0
0.2
0.4
0.6
0.8
1
1.2
1.4
True
Concentration
(
T)
ILSD
Residuals
Resids
from
Straight­
Line
ILSD
Model
Resids
from
Expo
ILSD
Model
Resids
from
Hybrid
ILSD
Model
15
Figure
3.6
Final
16­
A1­
OR
relative
standard
deviation
versus
concentration.

Now
that
we
have
decided
on
the
hybrid
model,
we
can
give
detection
and
quantitation
limit
results
from
the
IDE/
IQE
program.
Table
3.3
contains
results
for
Final
16­
A1­
OR.
It
is
interesting
that
the
critical
level
(
LC)
is
much
lower
than
the
interlaboratory
detection
estimate
(
IDE).
The
main
difference
is
that
the
LC
controls
only
the
Type
I
error
(
false
positive)
rate
while
the
IDE
controls
both
the
Type
I
error
and
Type
II
error
(
false
negative)
rates
(
ASTM,
1997).
A
second
interesting
point
is
that
the
IDE
is
less
than
the
IQE30.
This
is
not
a
satisfying
result,
because
the
IDE
is
a
detection
estimate
and
the
IQE
is
a
quantitation
estimate.
This
implies
that
we
can
quantitate
at
a
lower
concentration
than
we
can
detect.
This
occurs
because
of
a
fundamental
difference
in
the
way
the
IDE
and
IQE
are
calculated.
The
IDE
is
set
via
an
iterative
process
using
the
estimated
standard
deviation
(
from
the
model
chosen,
here
the
hybrid
model)
at
zero
concentration
and
the
suggested
IDE
(
ASTM,
1997).
The
IQE
fits
a
model
(
here,
the
hybrid)
to
the
standard
deviation
versus
concentration
data
(
ASTM,
1998).
The
IQE30
is
the
point
on
the
curve
at
which
the
RSD
is
30%.
Thus,
it
utilizes
the
entire
curve
rather
than
just
two
values
as
does
the
IDE.
If
the
RSD
becomes
large
quickly
as
the
concentration
goes
to
zero,
then
the
IDE
can
exceed
the
IQE.
Such
is
the
case
here.
Therefore,
any
IQE
below
the
IDE
should
be
discarded
as
untenable.
Perhaps
it
would
be
more
appropriate
to
set
the
IQE
between
0.20
and
0.25
where
the
RSD
asymptotes.
It
is
important
to
note
that
the
IQE
only
defines
the
precision
with
which
a
measurement
can
be
made
and
makes
no
statement
about
the
accuracy
or
the
false
positive
/
false
negative
error
rates
at
that
value.
This
is
why
the
limit
of
detection
and
the
limit
of
quantification
are
two
distinctly
different
values.

Table
3.3
IDE/
IQE
program
results
for
Final
16­
A1­
OR
­
IDE
and
IQE's.
LC
IDE
IQE
10%
IQE
20%
IQE
30%
0.055
0.112
N/
A
N/
A
0.102
Table
3.4
gives
more
IDE/
IQE
program
results
for
Final
16­
A1­
OR.
An
MDL
is
considered
valid
if
it
falls
between
the
concentration
and
five
times
the
concentration.
The
MDL,
ML,
and
10sigma
are
simply
multiples
of
the
standard
deviation
at
a
given
concentration.
One
of
the
criticisms
of
these
summaries
is
that
only
under
the
assumption
that
the
standard
deviation
is
constant
will
the
MDL
be
the
same
value
for
each
concentration.
The
black
line
in
Figure
3.6
corresponds
to
the
constant
model.
Clearly
the
constant
model
is
a
very
poor
fit
to
the
points.
This
explains
the
large
variability
in
valid
MDL's
depending
on
the
RSD
vs.
True
Concentration
(
T)

1%
10%
100%

0
0.2
0.4
0.6
0.8
1
1.2
1.4
True
Concentration
(
T)
RSD
Data
Constant­
SD
Model
SL­
SD
Model
Expo­
SD
Model
Hybrid­
SD
Model
IQE10%
IQE20%
IQE30%
16
concentration
used
to
set
the
limit.
As
the
concentration
increases,
so
does
the
standard
deviation
(
see
Figure
3.4),
and
hence
the
MDL,
ML,
and
10sigma
also
increase.
Similar
to
the
LC,
the
MDL
only
controls
the
Type
I
error
rate.
The
ML
is
simply
3.18
times
the
MDL,
which
only
compounds
the
error.
When
the
MDL
is
calculated
using
n
=
7,
the
ML
will
equal
10sigma.
When
the
MDL
equals
the
spike
concentration
at
which
it
was
determined
then
the
MDL
is
equivalent
to
the
LC.
None
of
these
measures
are
highly
statistical
in
nature.
They
do
not
model
the
relationship
between
the
standard
deviation
and
the
concentration.
In
that
sense,
they
are
inferior
to
the
IDE
and
the
IQE.

Table
3.4
IDE/
IQE
program
results
for
Final
16­
A1­
OR
­
MDL's
and
ML's.
Concentration
Valid
MDL
Valid
ML
10sigma
0.010
0.028
0.089
0.110
0.015
0.029
0.091
0.116
0.025
0.041
0.129
0.166
0.030
0.044
0.138
0.180
The
MDL,
ML,
and
10sigma
have
been
criticized
by
many
statisticians
as
relying
too
heavily
upon
assumptions
that
are
usually
not
met
(
see,
for
example,
Zorn
et
al.,
1999).
Robert
D.
Gibbons
has
suggested
an
alternative
to
the
ML
that
he
calls
the
Alternative
Minimum
Level
(
AML)
(
Gibbons
et
al.,
1997).
Similar
to
the
IDE/
IQE
calculations,
the
AML
models
the
relationship
between
standard
deviation
and
concentration.
However,
the
AML
goes
beyond
the
IDE/
IQE
calculation
by
accounting
for
uncertainty
in
the
calibration
function
and
in
the
standard
deviation
at
the
AML.
The
resultant
value
for
the
AML
will
be
markedly
higher
than
the
IQE.
We
utilized
a
program
written
by
Gibbons
to
compute
the
AML.

Interestingly,
the
AML
program
chooses
the
exp
onential
model
over
the
hybrid
model,
even
though
the
hybrid
model
fits
the
standard
deviation
better,
particularly
at
high
concentrations.
Why,
then,
is
the
AML
program,
unlike
the
IDE/
IQE
program,
choosing
the
exponential
model
over
the
hybrid
model?
The
reason
is
that
the
AML
program
forces
the
hybrid
model
through
the
standard
deviation
at
the
lowest
concentration
(
Attachment
3.1).
Since
the
standard
deviation
of
the
lowest
concentration
point
is
atypically
large
relative
to
the
standard
deviations
nearby
(
see
Figure
3.4),
the
hybrid
model
is
fitting
the
lowest
concentrations
very
poorly.
Since
relative
standard
deviation
increases
exponentially
as
you
approach
zero
it
is
very
risky
to
force
your
model
through
the
lowest
concentration
point,
unless
you
have
many
replicates
at
that
concentration.
Robert
Gibbons
is
currently
working
on
a
modification
to
his
software
that
will
allow
the
user
to
specify
if
they
want
to
force
the
curve
through
the
lowest
concentration.

Attachments
3.1
and
3.2
show
the
hybrid,
exponential
and
linear
curve
fits
using
the
AML
software
plot,
which
makes
it
easier
to
see
the
curve
fit
in
the
low
concentration
range.
Superimposed
on
Attachment
3.1
is
the
hybrid
model
as
determined
using
the
IQE
software
(
dashed
line),
which
fits
the
data
well
over
the
entire
concentration
range.
Note
that
the
exponential
model
fits
the
data
well
at
the
low
concentrations,
but
poorly
at
high
concentrations.
Superimposed
on
Attachment
3.2
is
the
linear
model
(
dashed
line),
which
is
a
good
fit
at
high
concentrations,
but
a
poor
fit
at
low
concentrations.

Table
3.5
shows
results
from
the
AML
program
for
both
the
exponential
and
hybrid
models.
The
LC
is
very
different
using
the
hybrid
model
from
the
AML
program
than
it
was
for
the
hybrid
model
from
the
IDE/
IQE
program.
At
this
point,
we
are
uncomfortable
with
the
accuracy
of
the
LC
from
the
AML
program.
The
AML
program's
choice
of
the
exponential
model
is
worrisome
because
of
its
poor
fit
at
higher
concentrations.

Table
3.5
AML
program
results
for
Final
16­
A1­
OR.
Model
LC
LD
AML
Hybrid
0.119
0.306
0.739
Exponential
0.064
0.140
0.356
In
Appendices
3­
5,
we
give
both
IDE/
IQE
program
and
AML
program
results,
as
well
as
diagnostic
plots,
for
the
other
three
files
(
16­
A1­
DL­
OR,
16­
A2­
OR,
and
16­
A2­
DL­
OR).
In
Appendix
3
you
will
find
the
results
for
the
16­
A1­
DL­
OR
file.
For
this
set
of
data
the
IDE/
IQE
hybrid
model
results
compare
quite
well
17
with
the
AML
hybrid
model,
since
forcing
the
curve
through
the
lowest
concentration
point
does
not
significantly
distort
the
curve
fit
of
the
other
concentration
points.
It
is
interesting
to
note
that
for
files
where
outlying
labs
have
been
removed
(
16­
A1­
DL­
OR
&
16­
A2­
DL­
OR)
the
IQE
is
slightly
lower
(~
0.09
m
g/
L)
than
for
the
files
were
outlying
labs
have
not
been
removed
(
16­
A1­
OR
&
16­
A2­
OR).
However,
great
care
must
be
taken
before
discarding
outlying
labs.
We
must
consider
whether
a
certified
and
licensed
commercial
lab
can
truly
be
considered
an
"
outlier".
As
long
as
a
lab
can
legally
be
used
to
determine
regulatory
compliance,
how
can
we
ignore
it
when
evaluating
interlaboratory
capabilities?

Table
3.6
shows
the
model
chosen
for
the
interlaboratory
standard
deviation
versus
the
concentration
for
each
file.

Table
3.6
Standard
deviation
versus
concentration
model
choice.
File
IDE/
IQE
Model
Choice
AML
Model
Choice
Final
16­
A1­
OR
hybrid
Exponential
Final
16­
A1­
DL­
OR
hybrid
Hybrid
Final
16­
A2­
OR
hybrid
Hybrid
Final
16­
A2­
DL­
OR
hybrid
Hybrid
Note.
The
AML
program
does
not
allow
choice
of
the
constant
or
straight­
line
models.

Return
now
to
our
discussion
of
Final
16­
A1­
OR.
Once
a
detection
limit
has
been
set
we
can
determine
the
observed
Type
I
and
Type
II
error
rates.
A
Type
I
error
occurs
if
the
concentration
is
below
the
IDE
but
the
reported
result
is
above
the
IDE.
Table
3.7
shows
the
Type
I
error
rate
and
the
%
RSD
for
each
concentration
below
the
IDE.
For
the
lowest
concentrations
there
is
very
little
chance
of
a
result
greater
than
the
IDE.
For
example,
for
concentration
0.005
there
is
only
a
4%
chance
that
the
lab
will
return
a
result
above
0.112
and
hence
report
a
false
positive.
However,
as
we
get
close
to
the
IDE
the
chance
of
a
false
positive
increases
dramatically.
For
concentration
0.100
(
just
below
the
IDE),
the
chance
of
a
false
positive
is
22%.
Appendix
6
has
Type
I
error
rates
for
the
other
three
files.

Table
3.7
Final
16­
A1­
OR
Type
I
error
rate.
Concentration
IDE
Number
of
Samples
Samples
Reporting
a
Result
Samples
Above
IDE
Type
I
Error
Rate
%
RSD*

Blank
0.112
50
10
1
0.02
0.005
0.112
50
17
2
0.04
623.40
0.006
0.112
50
15
0
0
208.46
0.010
0.112
50
22
1
0.02
107.00
0.015
0.112
50
29
1
0.02
75.75
0.025
0.112
50
35
2
0.04
65.32
0.030
0.112
50
42
0
0
59.18
0.050
0.112
50
46
1
0.02
25.92
0.060
0.112
50
49
4
0.08
37.48
0.100
0.112
50
49
11
0.22
22.00
*
The
%
RSD
is
calculated
after
outliers
have
been
removed.

A
Type
II
error
occurs
if
the
concentration
is
above
the
IDE
but
the
reported
result
is
below
the
IDE.
Table
3.8
shows
the
Type
II
error
results.
For
the
highest
concentrations
there
is
very
little
chance
of
a
false
negative.
For
example,
for
concentration
1.200
there
is
only
a
2%
chance
that
the
lab
will
return
a
result
below
0.112
and
hence
report
a
false
negative.
However,
as
we
get
close
to
the
IDE
the
chance
of
a
false
negative
increases
dramatically.
For
concentration
0.120
(
just
above
the
IDE),
the
chance
of
a
false
negative
is
52%.
Appendix
7
has
Type
II
error
rates
for
the
other
three
files.
18
Table
3.8
Final
16­
A1­
OR
Type
II
error
rate.
Concentration
IDE
Number
of
Samples
Samples
Reporting
a
Result
Samples
Below
IDE
Type
II
Error
Rate
%
RSD*

0.120
0.112
50
49
26
0.52
20.15
0.200
0.112
50
49
0
0
13.85
0.240
0.112
50
50
2
0.04
18.98
0.500
0.112
50
50
1
0.02
17.38
0.600
0.112
50
49
0
0
14.95
1.000
0.112
50
49
0
0
15.40
1.200
0.112
50
49
1
0.02
15.78
*
The
%
RSD
is
calculated
after
outliers
have
been
removed.

3.4
Statistical
Analysis
­
Analysis
of
Variance
Before
we
report
the
results
from
an
analysis
of
variance
(
ANOVA),
we
discuss
some
interesting
features
of
the
data.
Figure
3.7
is
a
histogram
of
the
laboratory
results
for
concentration
0.005.
Notice
that
the
data
are
skewed
right
with
many
labs
reporting
values
well
above
the
concentration.
This
is
true
for
all
of
the
lower
concentrations.

Figure
3.7
Histogram
of
results
for
concentration
0.005
for
Final
16­
A1­
OR.

Figure
3.8
is
a
histogram
of
the
laboratory
results
for
concentration
0.060.
For
this
concentration
the
results
appear
to
be
symmetrically
distributed
about
the
concentration.
One
might
even
surmise
that
the
data
are
normally
distributed
if
it
were
not
for
the
atypically
small
value
between
.010
and
.020
and
the
atypically
large
values
between
.120
and
.130.
(
These
values
were
not
identified
as
outliers
by
Grubb's
test.)
A
symmetric
distribution
of
results
centered
at
the
concentration
is
characteristic
of
the
results
for
concentrations
near
the
median
of
the
range
of
concentrations
used
in
the
study.
RESULT
.125
.115
.105
.095
.085
.075
.065
.055
.045
.035
.025
.015
.005
Frequency
6
5
4
3
2
1
0
19
Figure
3.8
Histogram
of
results
for
concentration
0.060
for
Final
16­
A1­
OR.

Figure
3.9
is
a
histogram
of
the
laboratory
results
for
concentration
1.200.
For
this
concentration
the
results
appear
to
be
skewed
left
and
centered
well
below
the
concentration.
This
is
typical
of
the
highest
concentrations.

Figure
3.9
Histogram
of
results
for
concentration
1.200
for
Final
16­
A1­
OR.

Ideally,
the
data
would
be
normally
distributed
at
each
concentration.
The
histograms
show
that
there
is
a
concentration
effect
beyond
merely
stating
that
higher
concentrations
will
have
higher
results
than
will
lower
concentrations.
We
can
also
say
that
results
at
low
concentrations
are
skewed
right
and
centered
above
the
concentration,
results
at
middle
concentrations
are
roughly
symmetric
and
centered
near
the
concentration,
and
results
at
high
concentrations
are
skewed
left
and
centered
below
the
concentration.
We
now
detail
results
of
the
ANOVA,
where
we
quantify
the
various
impacts
of
the
lab,
week,
and
concentration
factors.
RESULT
.125
.115
.105
.095
.085
.075
.065
.055
.045
.035
.025
.015
.005
Frequency
14
12
10
8
6
4
2
0
RESULT
1.30
1.20
1.10
1.00
.90
.80
.70
.60
.50
.40
.30
Frequency
12
10
8
6
4
2
0
20
Analysis
of
variance
is
a
statistical
technique
used
to
assign
variation
in
results
to
a
set
of
factors.
(
One
can
think
of
factors
as
explanatory
variables.)
We
ran
a
different
ANOVA
for
each
of
the
four
files.
The
response
variable
is
the
laboratory
reported
result.
The
factor
variables
are
the
concentration,
the
lab,
and
the
week.
The
model
includes
these
factors
and
the
two­
way
interactions
conc*
lab,
conc*
week,
and
lab*
week.
An
interaction
effect
is
a
varying
impact
for
a
given
factor
dependent
on
the
value
of
another
factor.
For
example,
consider
the
interaction
of
lab
and
concentration.
It
is
possible
that
certain
labs
measure
accurately
at
low
concentrations,
but
inaccurately
at
high
concentrations.
An
interaction
can
account
for
this
variable
effect
of
the
lab
at
different
concentrations.

All
of
the
factor
variables
(
and
their
interactions)
are
treated
as
random
effects.
The
levels
of
a
random
effect
are
thought
to
be
drawn
from
a
normally
distributed
population
that
has
mean
0
and
variance
.
2
i
s
For
example,
we
think
of
the
10
labs
used
in
the
study
as
being
a
sample
from
among
all
labs.
Inference
is
not
made
to
compare
labs
to
each
other
but
rather
to
determine
the
overall
influence
of
labs
on
the
variability
in
reported
results.
Throughout
this
section,
we
detail
the
ANOVA
results
for
Final
16­
A1­
OR.

Table
3.9
shows
the
variance
components
for
each
term
in
the
ANOVA
model.
The
higher
the
variance
component,
the
more
of
the
overall
variation
in
the
laboratory
results
is
accounted
for
by
the
term.
We
can
see
that
concentration
is
the
single
most
important
term
in
the
model
with
a
variance
component
of
0.06970.
The
variability
in
concentrations
accounts
for
91.69%
of
the
total
variation
in
the
results.
This
is
expected,
since
different
concentrations
should
yield
different
results.
The
lab*
concentration
component
is
also
large
accounting
for
2.42%
of
the
total
variation.
This
suggests
that
labs
are
not
consistent
in
their
readings
from
concentration
to
concentration.
That
is,
just
because
a
lab
is
accurate
for
certain
concentrations
does
not
imply
that
the
lab
is
accurate
for
all
concentrations.
The
lab
component
appears
to
be
important
also.
It
accounts
for
1.18%
of
the
total
variation.
Thus,
there
are
differences
from
lab
to
lab.
The
other
terms
in
the
model
account
for
less
than
1%
of
the
total
variation.
Almost
4%
of
the
variation
is
left
unexplained
by
the
model.
Possible
causes
of
this
variation
include
analyst,
instrument,
extraction/
clean­
up
variability
and
procedural
differences.
Therefore,
we
can
conclude
that
to
control
variability
the
most
important
factors
(
after
concentration
effects)
are
lab*
concentration
and
lab­
to­
lab
variability.
Hence,
the
need
for
a
common
protocol.
Appendix
8
gives
variance
component
results
for
each
of
the
other
three
files.

Table
3.9
Variance
components
for
Final
16­
A1­
OR.
Component
Estimate
%
of
Total
Variation
Lab
0.0009034
1.18
Week
»
0
»
0
Concentration
0.0697000
91.69
Lab*
Week
0.0005902
0.77
Lab*
Concentration
0.0018403
2.42
Week*
Concentration
0.0000276
»
0
Error
0.0029522
3.88
4.
LABORATORY
PERFORMANCE
AND
RECOMMENDATIONS
4.1
Laboratory
Irregularities
A
summary
of
a
review
of
the
laboratory
reports
and
data
packages
can
be
found
in
Attachment
4.1.
The
main
areas
of
concern
that
resulted
from
a
review
of
the
laboratory
reports,
raw
data
packages
and
lab
procedures
were
the
following:
21
·
 
Standard
Operating
Procedures
were
not
followed
as
specified
in
the
submitted
SOPs
from
the
laboratories
in
the
study.
In
many
cases
the
calibration
procedure
differed
greatly
from
that
which
was
documented
in
the
SOP
and
defined
in
the
study
plan.

·
 
Clean­
up
procedures
that
were
required
by
the
study
plan
were
omitted
in
some
cases.
The
study
plan
stated
that
one
acid
clean­
up
plus
both
a
sulfur
and
florisil
clean­
up
were
required.
Some
labs
skipped
either
some
or
all
of
these
clean­
ups.
Due
to
the
extremely
low
levels
in
these
samples
the
clean­
up
methods
requested
were
necessary
even
though
the
sample
matrix
was
Type
I
water.
Variability
and
analyte
losses
due
to
the
clean­
up
step
were
not
fully
accounted
for,
since
these
steps
were
omitted
by
some
of
the
labs.
This
also
could
have
caused
the
calculated
IDE
and
IQE,
to
be
artificially
low.

·
 
The
final
volume
required
by
the
study
plan
was
1
ml.
One
lab
in
the
study
did
not
follow
this
requirement
and
used
a
final
volume
of
5
mls.
Since
the
study
spiking
amounts
were
at
a
level
that
made
detection
difficult
at
the
1ml
volume
the
5ml
final
volume
put
this
lab
at
a
significant
disadvantage.

·
 
Two
laboratories
in
the
study
had
cross
contamination
problems
that
resulted
from
high
concentration
samples
from
an
outside
source
contaminating
study
samples.
In
both
cases
the
data
was
released
without
an
initial
acknowledgement
of
contamination.
This
resulted
in
both
individual
data
points
and
laboratories
being
rejected
in
the
outlier
removal
process.
In
a
real
world
sample
this
could
lead
to
a
permit
violation
unless
the
source
of
contamination
can
be
identified.
Laboratories
should
establish
procedures
to
deal
with
this
common
problem.
One
possible
solution
would
be
for
the
lab
to
mark
all
glassware
and
identify
the
sample
and
associated
glassware
through
the
use
of
a
glassware
logbook.
A
second
suggestion
would
be
for
the
lab
to
set
aside
a
group
of
glassware
for
low
level
PCB
samples.
If
the
standard
Kuderna
Danish
solvent
concentration
procedure
is
used
the
lab
should
be
certain
not
to
overlook
the
concentrator
tubes
when
trying
to
identify
the
source
of
contamination.

·
 
Two
laboratories
submitted
results
that
strongly
suggest
that
sample
identities
were
transferred
resulting
in
data
significantly
different
than
expected.
Since
the
laboratory
could
not
verify
that
sample
identities
had
been
switched
these
data
points
were
eliminated
when
individual
outliers
were
removed
from
the
dataset.

4.2
Positives
Results
in
Laboratory
Blanks
There
were
a
total
of
100
blanks
reported
in
the
study
for
Aroclor
1016
and
1260.
Ten
percent
of
the
laboratory
blanks
contained
measurable
concentrations
of
Aroclor
1016
and
fifteen
percent
of
the
laboratory
blanks
contained
measurable
concentrations
of
Aroclor
1260.
A
laboratory
had
to
be
able
to
quantify
a
minimum
of
three
congener
peaks
to
report
a
result.
Depending
upon
a
laboratory's
reporting
practices
(
number
of
peaks
required
for
qualitative
Aroclor
identification)
these
sample
results
may
or
may
not
be
reported
as
a
PCB
hit.
Of
all
the
blank
results
reported
only
one
was
above
the
IDE
and
this
was
a
known
result
of
laboratory
contamination.
This
means
that
if
values
must
be
reported
for
results
below
the
interlaboratory
detection
limit
we
would
project
to
have
ten
to
fifteen
percent
positive
results
in
high
purity
reagent
water.

Blanks
with
Results
Reported
above
the
Lowest
Concentration
AROCLOR
1016
AROCLOR
1260
SAMPLE
ID
CONC.
(
m
g/
L)
CONC.
(
m
g/
L)
91G
0.005
92G
0.006
93G
0.006
22
96G
0.006
99G
0.006
0.011
910G
0.006
0.011
95G
0.007
94G
0.013
97G
0.024
98C
0.11*
99A
0.014
91H
0.016
93H
0.018
94H
0.019
96H
0.020
98H
0.024
910H
0.026
91E
0.031
93E
0.034
94E
0.037
95E
0.039
96E
0.071
97E
0.058*

*
Lab
Contamination
(
non­
study
samples
containing
high
levels
of
Aroclor
1016
were
extracted
during
this
sample
set)

4.3
Concentration
vs.
Detection
As
one
might
expect
the
ability
to
detect,
measure
and
quantify
a
PCB
Aroclor
is
directly
proportional
to
the
concentration
of
the
PCB.
Attachments
4.2
&
4.3
are
bar
graphs
showing
the
percent
of
samples
that
could
not
be
detected
(
Not
Detected),
measured
but
not
identified
(
Qualified),
and
reported
with
the
Aroclor
identified
(
Reported),
for
each
of
the
eight
Youden
pair
concentration
levels.
At
the
highest
concentration
(~
1.0
m
g/
L)
99­
100%
of
the
samples
were
measurable
and
identifiable.
At
the
IDE
(~
0.1
m
g/
L)
10­
12%
of
the
samples
could
not
be
identified
as
PCBs.
At
the
lowest
concentration
(~
0.005
m
g/
L)
approximately
85%
of
all
samples
could
not
be
identified
as
PCBs.

4.4
Laboratory
Accuracy
Attachments
4.4
&
4.5
show
the
accuracy
of
each
laboratory
for
each
Aroclor.
The
first
bar
indicates
the
percentage
of
reported
results
for
a
given
laboratory
that
were
within
+/­
25%
of
the
true
sample
value.
The
second
bar
indicates
the
percentage
of
reported
results
for
a
given
laboratory
that
were
within
+/­
50%
of
a
given
value.
The
third
bar
indicates
the
percentage
of
reported
results
for
a
given
laboratory
that
were
within
25%
to
200%
of
the
true
value.
If
the
third
bar
does
not
equal
100%
then
the
difference
would
be
the
percentage
of
values
that
were
not
reported
or
were
outside
the
25%­
200%
window.
Overall
labs
tended
to
be
slightly
more
accurate
when
measuring
Aroclor
1260.
None
of
the
labs
could
be
expected
to
be
within
+/­
25%
of
the
true
value
100%
of
the
time
for
ALL
concentrations,
especially
those
below
the
IDE.
However,
an
obvious
difference
in
accuracy
between
laboratories
can
be
seen,
with
some
labs
being
23
able
to
report
the
true
value
within
+/­
25%
as
much
as
70%
of
the
time
and
others
only
about
20%
of
the
time.

We
can
further
dissect
this
data
and
look
at
laboratory
accuracy
by
concentration
(
Attachment
4.6­
4.9).
The
graphs
show
that
once
you
get
above
the
IDE
a
clear
bias
can
be
seen
from
one
lab
to
another,
with
labs
E,
G
&
H
biased
lower
than
labs
A,
B,
C
&
D.
Note
that
the
high
bias
trend
becomes
extreme
at
lower
sample
concentrations.
The
graphs
only
show
the
second
to
the
lowest
sample
concentration
submitted,
but
if
you
refer
to
the
tables
(
Attachments
4.7
&
4.9)
you
can
see
that
the
bias
can
be
over
800%.
This
is
because
the
influence
of
instrument
noise,
interferences
and
laboratory
contamination
becomes
extreme
below
the
critical
level.

To
more
clearly
observe
the
laboratory
accuracy
bias
trend
we
plot
the
combined
laboratory
accuracy
(
percent
recovery)
verses
sample
concentration
(
Attachment
4.10
&
4.11).
If
the
laboratories
could
perform
with
perfect
accuracy
at
all
concentrations
we
would
see
a
flat
line
at
100%
recovery.
While
this
is
unrealistic
below
the
IDE,
we
would
expect
the
curve
to
be
fairly
flat
above
the
IDE.
Low
recoveries
for
higher
concentration
levels
may
be
the
result
of
calibration
curve
bias
resulting
from
linear
regression
or
average
response
factor
calibration.
These
calibration
types
fail
to
account
for
the
non­
linear
response
of
an
ECD
detector.
Losses
during
extraction
and
clean­
up
steps
must
also
be
considered
when
considering
values
falling
in
the
less
than
100
percent
range.
High
recoveries
for
lower
concentration
levels
may
also
be
the
result
of
calibration
curve
bias.
Higher
amounts
at
the
lower
levels
can
also
result
from
non­
PCB
matrix
interferences,
instrument
noise
and
laboratory
contamination
adding
peak
area
to
calibrated
PCB
congener
peaks.

Compare
the
behavior
of
PCB
interlaboratory
accuracy
with
concentration
to
that
of
Chromium
by
ICP/
AES
(
Attachment
4.12).
At
high
concentrations
the
accuracy
of
ICP/
AES
is
extremely
good,
very
close
to
100%.
The
IDE
for
Chromium
is
20
m
g/
L
as
determined
in
the
AAMA
interlaboratory
study.
At
the
IDE
the
accuracy
drops
off
severely,
only
for
Chromium
it
is
biased
low.
This
is
likely
due
to
calibration
error
or
loss
of
sensitivity
at
low
concentrations
for
the
ICP/
AES.
In
this
study
the
lowest
concentration
sample
was
only
2
m
g/
L.
If
lower
samples
were
analyzed
the
percent
recovery
would
again
shoot
toward
infinity
due
to
instrumental
noise.

4.5
Routine
Laboratory
MDL
vs.
Blind
MDL
We
next
turn
our
attention
to
the
determination
of
the
MDL.
We
have
already
shown
in
section
3.3
that
we
can
get
multiple
valid
MDLs
by
simply
varying
the
MDL
concentration.
This
is
particularly
true
for
analyses
that
have
a
high
degree
of
variability,
which
is
why
the
MDL
has
often
been
called
an
"
unanchored"
statistic.
We
now
compare
the
MDLs
determined
by
each
participating
laboratory
during
their
annual
determination
of
method
MDLs.
Typically
an
MDL
is
determined
following
the
40
CFR
Part
136,
Appendix
B
procedure
by
preparing
7
to
10
reagent
water
standards
at
the
estimated
MDL
for
the
method
being
evaluated.
After
the
instrument
is
calibrated
standards
are
placed
on
the
instrument
and
analyzed
sequentially
immediately
after
a
blank
or
batch
QC
samples.
Labs
may
or
may
not
run
the
samples
through
the
entire
method
including
sample
extraction,
clean­
ups
and
concentration.
Unfortunately
this
is
not
typical
of
how
normal
samples
are
analyzed
and
does
not
take
into
account
the
variability
of
the
instrument
over
time
or
from
calibration
to
calibration.

Attachments
4.13
&
4.14
list
the
lab
generated
MDL
for
each
laboratory
for
Aroclor
1016,
and
1260
respectively.
The
concentration
at
which
the
PCB
Aroclor
was
for
the
MDL
study
is
also
listed.
We
then
calculated
a
laboratory
study
MDL
from
the
results
each
laboratory
reported.
So
that
results
would
be
comparable
we
use
results
for
a
standard
as
close
to
the
lab
generated
MDL
concentration
as
possible.
This
MDL
is
based
on
blind
reagent
water
standards
analyzed
by
multiple
analysts
over
the
course
of
the
study.
Notice
that
in
almost
every
case
the
percent
difference
between
the
MMA
study
Lab
MDL
and
the
Lab
Generated
MDL
is
positive.
The
percent
differences
range
from
 
9%
to
2100%.
This
indicates
that
the
routine
laboratory
MDL
does
not
capture
all
of
the
variability
associated
with
a
typical
sample
analysis.
This
is
why
the
National
Water
Quality
Testing
Laboratory
has
adopted
the
use
of
a
Long
Term
MDL
(
LTMDL)
to
capture
variability
over
time
with
multiple
analysts.
The
Study
Generated
Lab
MDLs
range
approximately
one
order
of
magnitude
(
0.047­
0.49)
over
a
range
that
is
also
one
order
of
magnitude
(
0.055­
24
0.55).
The
Lab
Generated
MDLs
range
from
0.006
to
0.18
(
30x)
with
the
same
range,
which
again
shows
the
strong
dependency
of
the
MDL
upon
concentration.

4.5
Recommendations
to
Improve
Accuracy
and
Precision
for
Low
Level
Analysis
of
PCBs
A
review
of
the
information
gathered
from
the
interlaboratory
study
prompts
us
to
make
the
following
recommendations
to
improve
accuracy
and
precisions
for
low­
level
analysis
of
PCBs:

·
 
Set
instrument
conditions
to
allow
the
first
surrogate
(
TCMX)
to
have
a
minimum
retention
time
of
4.00
minutes.
Lab
C
and
G
were
impacted
by
a
TCMX
retention
time
of
less
than
2
minutes.
Due
to
this,
the
early
eluting
light
matrix
components
found
in
most
extracts
elevated
recoveries
significantly
or
would
not
allow
for
accurate
identification.
By
choosing
less
aggressive
run
conditions
the
early
matrix
interferences
will
better
separate
from
the
PCB
peaks
of
interest.

·
 
Set
data
system
threshold
to
allow
detection
of
all
peaks
above
the
background
noise
level.
The
lab
can
achieve
this
by
measuring
the
average
peak
height
observed
over
the
length
of
the
run
and
setting
the
threshold
at
a
value
that
detects
peaks
at
3­
5
times
the
average
background
peak
height.

·
 
The
lab
should
set
the
area
of
reject
in
the
data
system
so
that
all
peaks
of
interest
are
found.

·
 
Analysts
must
check
the
default
baseline
construction
of
all
chromatograms
and
correct
data
system
errors.
The
chromatogram
below
is
an
example
of
poor
baseline
construction
that
has
added
significant
area
and
height
to
certain
peaks.

·
 
If
the
lab
selects
a
curve
type
calibration
and
does
not
elect
to
extrapolate
the
curve
through
the
origin
then
it
is
critical
for
the
calibration
curve
levels
to
bracket
the
reporting
range.
Any
concentrations
reported
below
the
level
of
the
lowest
calibration
standard
should
be
flagged
with
a
qualifier.

·
 
Choose
a
calibration
curve
type
that
gives
the
best
results
for
both
precision
and
accuracy.
Study
results
suggest
that
a
quadratic
fit
curve
(
2nd
order)
may
give
the
best
results.
This
curve
type
will
reduce
the
effects
of
the
non­
linear
nature
of
the
Electron
Capture
Detector
(
ECD).

·
 
Run
a
separate
low
level
PCB
curve
when
analyzing
samples
targeted
for
low
level
results
or
add
additional
low
level
curve
points
to
your
existing
calibration
curve
if
both
low
level
and
normal
PCB
concentrations
are
expected.

·
 
Additional
procedures
such
as
clean­
up
steps
may
be
required
by
the
lab
to
eliminate
small
interferences
that
would
normally
have
minimal
effect
on
the
sample
values.
25
·
 
If
sample
results
show
matrix
interferences
affect
certain,
but
not
all
peaks
for
a
particular
Aroclor,
then
a
modified
calibration
curve
that
eliminates
the
affected
peaks
may
be
required
to
obtain
accurate
results.

·
 
Calibration
standards
should
not
be
separated
by
more
than
a
2X
range.

·
 
Average
response
factor
calibration
should
not
be
used
if
the
percent
relative
standard
deviation
is
above
10%.
This
is
the
criteria
for
method
608,
but
is
a
more
stringent
criteria
than
method
8082.
The
reason
for
this
is
that
the
ECD
shows
a
quenching
of
response
as
the
concentration
increases.
The
non­
linear
nature
of
this
detector
will
create
error
at
the
low
and
high
ends
of
the
calibration
range.
Below
is
an
example
of
a
typical
calibration
curve
that
was
submitted
for
five
peaks
in
Aroclor
1016.

0.05
0.10
0.20
0.40
0.80
1.6
MEAN
CF
%
RSD
95602
87811
80149
70623
63590
55619
75566
19.97
118557
108715
100079
89820
82649
73751
95595
17.49
270112
244187
220694
198205
177136
157080
211236
19.98
146846
138338
125439
112212
98027
86090
117825
19.91
81651
80035
72915
68398
62395
56040
70239
14.24
If
the
average
calibration
factor
were
used
on
the
lowest
standard
for
the
first
peak
the
results
would
be
126%
of
the
true
value.
If
the
average
response
were
used
on
the
highest
standard
for
the
first
peak
the
results
would
be
74%
of
the
true
value.

·
 
The
lab
should
run
a
low­
level
standard
daily
as
well
as
the
normal
mid­
level
standard
to
check
the
calibration
curve
for
accuracy
at
the
low
end
of
the
curve.

5.
STUDY
CONCLUSIONS
AND
FUTURE
WORK
The
study
has
determined
the
interlaboratory
detection
limit
to
be
approximately
0.1
m
g/
L
for
both
PCB
Aroclor
1016
and
1260
in
reagent
water
by
EPA
method
608.2
(
capillary
GC/
ECD).
The
best
achievable
quantification
limit
for
these
Aroclors
can
be
achieved
somewhere
between
0.2
m
g/
L
and
0.4
m
g/
L,
where
the
relative
standard
deviation
of
the
measurement
is
between
25%
and
30%.
We
believe
that
the
pool
of
laboratories
that
participated
in
the
study
is
representative
of
all
laboratories
that
perform
work
in
the
State
of
Michigan
and
hold
a
certification
for
the
analysis
of
PCBs
by
EPA
method
608.2.
We
also
believe
that
the
data
is
representative
of
the
routine
operating
conditions,
employing
commonly
used
extraction,
cleanup
and
data
analysis
procedures.
These
results
do
reflect
the
lowest
achievable
interlaboratory
limits,
since
only
reagent
water
matrix
was
evaluated.
Other
matrices
are
expected
to
significantly
raise
the
obtainable
detection
and
quantification
limits.

The
Rock
and
Lorenzato
(
Hybrid)
model
fitted
these
data
best
across
all
concentrations
for
both
Aroclors.
Other
models
including
the
constant,
straight
line
and
exponential
models
fitted
these
data
poorly
at
low,
high
or
all
concentrations.
In
many
instances,
the
hybrid
model
fit
poorly
at
low
concentration
if
it
was
forced
through
lowest
concentration
standard,
which
is
a
practice
sometimes
applied
by
the
AML
procedure.
Because
these
data
did
not
fit
the
constant
model
multiple
MDLs
and
MLs
could
be
obtained
depending
upon
the
spike
concentration
used.
Valid
interlaboratory
MDLs
ranged
from
0.02
m
g/
L,
(
1/
5
the
IDE)
to
0.45
m
g/
L
(>
IQE).

The
frequency
of
false
positives
(
type
I
error)
and
false
negatives
(
type
II
error)
increases
as
the
IDE
is
approached.
As
you
approach
zero
PCB
concentration
the
variability
relative
to
the
concentration
increases
exponentially
to
infinity.
Laboratories
reported
a
positive
result
for
the
presence
of
PCBs
for
10­
15%
of
all
reagent
water
blanks.
26
Lab
to
lab
variability
was
the
greatest
single
source
of
error.
Routine
annual
MDLs
performed
by
most
labs
do
not
adequately
reflect
either
lab
to
lab
variability
or
within
lab
variability.
Since
routine
lab
MDLs
do
not
reflect
routine
laboratory
performance
the
actual
lab
MDL
could
be
several
orders
of
magnitude
above
what
the
laboratory
reports.
For
this
reason
most
labs
use
"
laboratory
reporting
limits"
in
place
of
MDLs,
because
they
recognize
that
the
MDL
can
not
be
achieved
on
a
routine
basis.
A
major
source
of
laboratory
bias
in
the
reporting
of
PCB
results
is
associated
with
the
calibration
curve
used.
The
use
of
a
linear
calibration
curve
over
a
wide
range
generally
leads
to
low
bias
at
the
upper
end
of
the
calibration
curve
and
high
bias
at
the
bottom
end
of
the
curve.
A
quadratic
calibration
curve
or
calibration
over
a
much
smaller
concentration
range
is
recommended
when
employing
an
electron
capture
detector.
Several
other
recommendations
have
been
made
to
improve
the
accuracy
and
precision
of
low­
level
analysis
of
PCBs
in
water.

The
precision
and
accuracy
from
lab
to
lab
varied
substantially
for
the
ten
laboratories
participating
in
the
study.
Detection
capability
and
precision
can
vary
more
than
an
order
of
magnitude
from
one
lab
to
the
next.
Identification
and
quantification
accuracy
also
varies
substantially
between
labs.
Further
investigation
of
the
with­
in
laboratory
variability
may
be
able
to
pinpoint
the
greatest
sources
of
error.
Specific
attention
to
the
sources
of
with­
in
lab
variability
could
yield
a
substantial
improvement
in
precision
for
many
labs.
The
specific
lessons
learned
from
the
study
should
be
disseminated
to
the
participating
laboratories
and
the
lab
community
in
general.
Publication
of
these
findings
in
a
peer
reviews
scientific
journal
is
highly
recommended.

Now
that
a
reasonable
estimate
of
interlaboratory
detection
and
quantification
has
been
obtained
in
reagent
water,
we
highly
recommend
a
follow­
up
study
which
can
compare
the
detection
and
quantification
capability
in
real
world
matrices
including,
WWTP
effluents,
surface
waters,
storm
water
and
groundwater.
It
would
also
be
informative
to
evaluate
the
performance
of
the
same
laboratories
under
routine
sample
submission
conditions
(
not
as
part
of
an
organized
study).
A
brief
study
to
determine
if
laboratories
that
did
not
participate
in
the
study
can
achieve
the
IDE
and
IQE
would
also
be
insightful.
The
earlier
AAMA
interlaboratory
study
on
metals
found
no
correlation
between
laboratory
analytical
cost
and
performance.
While
analytical
cost
was
fixed
for
this
study
one
could
compare
laboratory
performance
to
analysis
cost
for
method
608.2
by
completing
a
brief
survey
of
routine
market
prices.

Acknowledgements
The
authors
would
like
to
acknowledge
and
thank
Pete
Stevens
for
assisting
with
the
preparation
of
samples.
We
also
acknowledge
the
hard
work
of
Kristin
(
Rench)
Vaughn
and
Ann
Hammond
for
assistance
with
the
statistical
analysis.
1
Appendix
1:
Outlying
Points.

A.
Final
(
16­
A1­
OR)
 
Atypically
large
outliers
(
I.
D.
given
here);
14I,
28C,
210C,
31I,
69C,
38C,
36I,
32C,
410C,
68C,
59C,
113,
88C,
710C,
8106,
83C,
49C,
48C,
78C,
and
98C.
Atypically
small
outliers;
610C
and
75I.

Table
A1.1
Outlying
points
for
Final
16­
A1­
OR.
Lab
High
Low
Total
A
0
0
0
B
1
0
1
C
15
1
16
D
0
0
0
E
0
0
0
F
0
0
0
G
0
0
0
H
1
0
1
I
3
1
4
J
0
0
0
Total
20
2
22
B.
Final
(
16­
A1­
DL­
OR)
­
Atypically
large
outliers;
510C,
210C,
31I,
36I,
410C,
11B,
78I,
710C,
and
810H.
Atypically
small
outliers;
610C,
75I,
and
13E.

Table
A1.2
Outlying
points
for
Final
16­
A1­
DL­
OR.
Lab
High
Low
Total
A
0
0
0
B
1
0
1
C
4
1
5
D
0
0
0
E
0
1
1
F
0
0
0
G
0
0
0
H
1
0
1
I
3
1
4
J
0
0
0
Total
9
3
12
C.
Final
(
16­
A2­
OR)
­
Atypically
large
outliers;
47B,
24E,
37H,
29A,
85E,
44E,
67E,
75E,
52E,
81D,
64E,
and
98C.
There
were
no
atypically
small
outliers.

Table
A1.3
Outlying
points
for
Final
16­
A2­
OR.
Lab
High
Low
Total
A
1
0
1
B
1
0
1
C
1
0
1
D
1
0
1
E
7
0
7
F
0
0
0
G
0
0
0
H
1
0
1
I
0
0
0
J
0
0
0
Total
12
0
12
2
D.
Final
(
16­
A2­
DL­
OR)
­
Atypically
large
outliers;
47B,
45E,
24E,
73E,
81E,
37H,
85E,
18E,
46E,
44E,
67E,
65E,
52E,
64E,
and
98C.
Atypically
small
outlier;
19E.

Table
A1.4
Outlying
points
for
Final
16­
A2­
DL­
OR.
Lab
High
Low
Total
A
0
0
0
B
1
0
1
C
1
0
1
D
0
0
0
E
12
1
13
F
0
0
0
G
0
0
0
H
1
0
1
I
0
0
0
J
0
0
0
Total
15
1
16
3
Appendix
2:
Outlying
labs
A.
Final
(
16­
A1)

Table
A2.1
Outlying
labs
for
Final
16­
A1.
Week
Outlying
High
Rank
Labs
Outlying
Low
Rank
Labs
1
none
none
2
E
C
3
none
G,
C
4
J
I
5
E
C
6
none
none
7
none
H
8
none
C
9
none
C
10
none
I
Note:
High
ranks
imply
low
results
relative
to
the
other
labs.
Low
ranks
imply
high
results
relative
to
the
other
labs.

B.
Final
(
16­
A2)

Table
A2.2
Outlying
labs
for
Final
16­
A2.
Week
Outlying
High
Rank
Labs
Outlying
Low
Rank
Labs
1
none
D
2
none
B
3
none
B,
C
4
none
none
5
I
none
6
G
none
7
none
none
8
F
none
9
none
B,
A
10
none
B
4
Appendix
3:
Results
for
Final
16­
A1­
DL­
OR
Figure
A3.1
Final
16­
A1­
DL­
OR
response
versus
concentration.

Figure
A3.2
Final
16­
A1­
DL­
OR
residuals
versus
concentration.
Response
(
Y)
vs.
True
Concentration
(
T)

0.0000
0.2000
0.4000
0.6000
0.8000
1.0000
1.2000
1.4000
0.0000
0.2000
0.4000
0.6000
0.8000
1.0000
1.2000
1.4000
True
Concentration
(
T)
Response
(
Y)

Data
OLS
(
Constant­
SD
Model)
WLS
Fit
Residuals
vs.
Conc
(
T)

­
0.5
­
0.4
­
0.3
­
0.2
­
0.1
0
0.1
0.2
0.3
0.4
0.0000
0.2000
0.4000
0.6000
0.8000
1.0000
1.2000
1.4000
True
Concentration
(
T)
Residuals
OLS
Residuals
WLS
Residuals
5
Figure
A3.3
Final
16­
A1­
DL­
OR
standard
deviation
versus
concentration.

Figure
A3.4
Final
16­
A1­
DL­
OR
residuals
versus
concentration.
InterLab
Std
Dev
(
s)
&
ILSD
Models
vs.
True
Concentration
(
T)

0
0.05
0.1
0.15
0.2
0.25
0
0.2
0.4
0.6
0.8
1
1.2
1.4
True
Concentration
(
T)
Std
Dev
(
s)
&
ILSD
Models
Data
Straight­
Line
Fit
Exponential
Fit
Hybrid
ILSD
Residuals
vs.
True
Concentration
(
T)

­
0.1
­
0.08
­
0.06
­
0.04
­
0.02
0
0.02
0.04
0
0.2
0.4
0.6
0.8
1
1.2
1.4
True
Concentration
(
T)
ILSD
Residuals
Resids
from
Straight­
Line
ILSD
Model
Resids
from
Expo
ILSD
Model
Resids
from
Hybrid
ILSD
Model
6
Figure
A3.5
Final
16­
A1­
DL­
OR
relative
standard
deviation
versus
concentration.

Table
A3.1
IDE/
IQE
program
results
for
Final
16­
A1­
DL­
OR
­
IDE
and
IQE's.
LC
IDE
IQE
10%
IQE
20%
IQE
30%
0.045
0.089
N/
A
0.212
0.075
Table
A3.2
IDE/
IQE
program
results
for
Final
16­
A1­
DL­
OR
­
MDL's
and
ML's.
Concentration
Valid
MDL
Valid
ML
10sigma
0.05
0.030
0.097
0.125
0.06
0.054
0.171
0.222
0.10
0.041
0.130
0.169
0.12
0.058
0.183
0.238
0.20
0.065
0.207
0.270
0.24
0.093
0.295
0.384
0.50
0.195
0.621
0.807
0.60
0.183
0.582
0.757
1.00
0.323
1.026
1.334
1.20
0.392
1.248
1.619
Table
A3.3
AML
program
results
for
Final
16­
A1­
DL­
OR.
Model
LC
LD
AML
Hybrid
0.041
0.098
0.245
Exponential
0.053
0.115
0.291
RSD
vs.
True
Concentration
(
T)

1%
10%
100%

0
0.2
0.4
0.6
0.8
1
1.2
1.4
True
Concentration
(
T)
RSD
Data
Constant­
SD
Model
SL­
SD
Model
Expo­
SD
Model
Hybrid­
SD
Model
IQE10%
IQE20%
IQE30%
1
Appendix
4:
Results
for
Final
16­
A2­
OR
Figure
A4.1
Final
16­
A2­
OR
response
versus
concentration.

Figure
A4.2
Final
16­
A2­
OR
residuals
versus
concentration.
Response
(
Y)
vs.
True
Concentration
(
T)

0.0000
0.2000
0.4000
0.6000
0.8000
1.0000
1.2000
1.4000
0.000
0.200
0.400
0.600
0.800
1.000
1.200
1.400
True
Concentration
(
T)
Response
(
Y)

Data
OLS
(
Constant­
SD
Model)
WLS
Fit
Residuals
vs.
Conc
(
T)

­
0.5
­
0.4
­
0.3
­
0.2
­
0.1
0
0.1
0.2
0.3
0.4
0.5
0.6
0.000
0.200
0.400
0.600
0.800
1.000
1.200
1.400
True
Concentration
(
T)
Residuals
OLS
Residuals
WLS
Residuals
2
Figure
A4.3
Final
16­
A2­
OR
standard
deviation
versus
concentration.

Figure
A4.4
Final
16­
A2­
OR
residuals
versus
concentration.
InterLab
Std
Dev
(
s)
&
ILSD
Models
vs.
True
Concentration
(
T)

0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0
0.2
0.4
0.6
0.8
1
1.2
1.4
True
Concentration
(
T)
Std
Dev
(
s)
&
ILSD
Models
Data
Straight­
Line
Fit
Exponential
Fit
Hybrid
ILSD
Residuals
vs.
True
Concentration
(
T)

­
0.12
­
0.1
­
0.08
­
0.06
­
0.04
­
0.02
0
0.02
0.04
0.06
0
0.2
0.4
0.6
0.8
1
1.2
1.4
True
Concentration
(
T)
ILSD
Residuals
Resids
from
Straight­
Line
ILSD
Model
Resids
from
Expo
ILSD
Model
Resids
from
Hybrid
ILSD
Model
3
Figure
A4.5
Final
16­
A2­
OR
relative
standard
deviation
versus
concentration.

Table
A4.1
IDE/
IQE
program
results
for
Final
16­
A2­
OR
­
IDE
and
IQE's.
LC
IDE
IQE
10%
IQE
20%
IQE
30%
0.049
0.102
N/
A
N/
A
0.096
Table
A4.2
IDE/
IQE
program
results
for
Final
16­
A2­
OR
­
MDL's
and
ML's.
Concentration
Valid
MDL
Valid
ML
10sigma
0.05
0.028
0.088
0.115
0.06
0.039
0.125
0.164
0.10
0.042
0.134
0.175
0.12
0.054
0.171
0.224
0.20
0.086
0.272
0.356
0.24
0.100
0.318
0.416
0.50
0.221
0.703
0.919
0.60
0.246
0.783
1.023
1.00
0.382
1.215
1.588
1.20
0.459
1.461
1.910
Table
A4.3
AML
program
results
for
Final
16­
A2­
OR
Model
LC
LD
AML
Hybrid
0.085
0.226
0.537
Exponential
0.060
0.133
0.388
RSD
vs.
True
Concentration
(
T)

1%
10%
100%

0
0.2
0.4
0.6
0.8
1
1.2
1.4
True
Concentration
(
T)
RSD
Data
Constant­
SD
Model
SL­
SD
Model
Expo­
SD
Model
Hybrid­
SD
Model
IQE10%
IQE20%
IQE30%
1
Appendix
5:
Results
for
Final
16­
A2­
DL­
OR
Figure
A5.1
Final
16­
A2­
DL­
OR
response
versus
concentration.

Figure
A5.2
Final
16­
A2­
DL­
OR
residuals
versus
concentration.
Response
(
Y)
vs.
True
Concentration
(
T)

0.0000
0.2000
0.4000
0.6000
0.8000
1.0000
1.2000
1.4000
0.0000
0.2000
0.4000
0.6000
0.8000
1.0000
1.2000
1.4000
True
Concentration
(
T)
Response
(
Y)

Data
OLS
(
Constant­
SD
Model)
WLS
Fit
Residuals
vs.
Conc
(
T)

­
0.4
­
0.3
­
0.2
­
0.1
0
0.1
0.2
0.3
0.4
0.5
0.0000
0.2000
0.4000
0.6000
0.8000
1.0000
1.2000
1.4000
True
Concentration
(
T)
Residuals
OLS
Residuals
WLS
Residuals
2
Figure
A5.3
Final
16­
A2­
DL­
OR
standard
deviation
versus
concentration.

Figure
A5.4
Final
16­
A2­
DL­
OR
residuals
versus
concentration.
InterLab
Std
Dev
(
s)
&
ILSD
Models
vs.
True
Concentration
(
T)

0
0.05
0.1
0.15
0.2
0.25
0.3
0
0.2
0.4
0.6
0.8
1
1.2
1.4
True
Concentration
(
T)
Std
Dev
(
s)
&
ILSD
Models
Data
Straight­
Line
Fit
Exponential
Fit
Hybrid
ILSD
Residuals
vs.
True
Concentration
(
T)

­
0.1
­
0.08
­
0.06
­
0.04
­
0.02
0
0.02
0.04
0.06
0
0.2
0.4
0.6
0.8
1
1.2
1.4
True
Concentration
(
T)
ILSD
Residuals
Resids
from
Straight­
Line
ILSD
Model
Resids
from
Expo
ILSD
Model
Resids
from
Hybrid
ILSD
Model
3
Figure
A5.5
Final
16­
A2­
DL­
OR
relative
standard
deviation
versus
concentration.

Table
A5.1
IDE/
IQE
program
results
for
Final
16­
A2­
DL­
OR
­
IDE
and
IQE's.
LC
IDE
IQE
10%
IQE
20%
IQE
30%
0.042
0.086
N/
A
N/
A
0.077
Table
A5.2
IDE/
IQE
program
results
for
Final
16­
A2­
DL­
OR
­
MDL's
and
ML's.
Concentration
Valid
MDL
Valid
ML
10sigma
0.025
0.023
0.074
0.096
0.030
0.027
0.086
0.112
0.050
0.026
0.083
0.107
0.060
0.038
0.122
0.159
0.100
0.040
0.127
0.165
0.120
0.051
0.163
0.213
0.200
0.063
0.200
0.260
0.240
0.098
0.312
0.407
0.500
0.201
0.640
0.833
0.600
0.228
0.725
0.945
1.000
0.337
1.073
1.396
1.200
0.429
1.363
1.777
Table
A5.3
AML
program
results
for
Final
16­
A2­
DL­
OR
Model
LC
LD
AML
Hybrid
0.084
0.212
0.520
Exponential
0.052
0.111
0.284
RSD
vs.
True
Concentration
(
T)

1%
10%
100%

0
0.2
0.4
0.6
0.8
1
1.2
1.4
True
Concentration
(
T)
RSD
Data
Constant­
SD
Model
SL­
SD
Model
Expo­
SD
Model
Hybrid­
SD
Model
IQE10%
IQE20%
IQE30%
4
Appendix
6:
Type
I
(
False
Positive)
Error
Rates
Table
A6.1
Final
16­
A1­
DL­
OR
Type
I
error
rate.
Concentration
IDE
Number
of
Samples
Samples
Reporting
a
Result
Samples
Above
IDE
Type
I
Error
Rate
%
RSD*

Blank
0.089
50
10
1
0.02
0.005
0.089
50
17
2
0.04
222.64
0.006
0.089
50
15
0
0
222.82
0.010
0.089
50
22
2
0.04
97.55
0.015
0.089
50
29
1
0.02
60.06
0.025
0.089
50
35
2
0.04
61.68
0.030
0.089
50
42
1
0.02
57.84
0.050
0.089
50
46
3
0.06
24.78
0.060
0.089
50
49
8
0.16
36.57
*
The
%
RSD
is
calculated
after
outliers
have
been
removed.

Table
A6.2
Final
16­
A2­
OR
Type
I
error
rate.
Concentration
IDE
Number
of
Samples
Samples
Reporting
a
Result
Samples
Above
IDE
Type
I
Error
Rate
%
RSD*

Blank
0.102
50
17
1
0.02
0.005
0.102
50
20
1
0.02
424.57
0.006
0.102
50
26
0
0
285.73
0.010
0.102
50
36
0
0
137.02
0.015
0.102
50
41
0
0
65.86
0.025
0.102
50
47
2
0.04
52.62
0.030
0.102
50
49
1
0.02
51.90
0.050
0.102
50
48
2
0.04
22.71
0.060
0.102
50
50
2
0.04
27.04
0.100
0.102
50
50
7
0.14
17.28
*
The
%
RSD
is
calculated
after
outliers
have
been
removed.

Table
A6.3
Final
16­
A2­
DL­
OR
Type
I
error
rate.
Concentration
IDE
Number
of
Samples
Samples
Reporting
a
Result
Samples
Above
IDE
Type
I
Error
Rate
%
RSD*

Blank
0.086
50
17
1
0.02
0.005
0.086
50
20
1
0.02
434.46
0.006
0.086
50
26
0
0
274.97
0.010
0.086
50
36
0
0
101.15
0.015
0.086
50
41
0
0
55.47
0.025
0.086
50
47
2
0.04
37.87
0.030
0.086
50
49
1
0.02
36.81
0.050
0.086
50
48
2
0.04
21.18
0.060
0.086
50
50
3
0.06
26.22
*
The
%
RSD
is
calculated
after
outliers
have
been
removed.
5
Appendix
7:
Type
II
(
False
Negative)
Error
Rates
Table
A7.1
Final
16­
A1­
DL­
OR
Type
II
error
rate.
Concentration
IDE
Number
of
Samples
Samples
Reporting
a
Result
Samples
Below
IDE*
Type
II
Error
Rate
%
RSD**

0.100
0.089
50
49
24
0.48
16.65
0.120
0.089
50
49
26
0.52
19.59
0.200
0.089
50
49
1
0.02
13.32
0.240
0.089
50
50
0
0
15.83
0.500
0.089
50
50
1
0.02
15.96
0.600
0.089
50
49
1
0.02
12.47
1.000
0.089
50
49
1
0.02
13.18
1.200
0.089
50
49
2
0.04
13.33
*
Samples
not
reporting
are
assumed
to
be
below
the
IDE
for
the
Type
II
error
calculation.
**
The
%
RSD
is
calculated
after
outliers
have
been
removed.

Table
A7.2
Final
16­
A2­
OR
Type
II
error
rate.
Concentration
IDE
Number
of
Samples
Samples
Reporting
a
Result
Samples
Below
IDE*
Type
II
Error
Rate
%
RSD**

0.120
0.102
50
50
21
0.42
18.44
0.200
0.102
50
50
2
0.04
17.63
0.240
0.102
50
49
1
0.02
17.14
0.500
0.102
50
50
0
0
18.20
0.600
0.102
50
50
0
0
16.89
1.000
0.102
50
50
0
0
15.72
1.200
0.102
50
50
0
0
15.75
*
Samples
not
reporting
are
assumed
to
be
below
the
IDE
for
the
Type
II
error
calculation.
**
The
%
RSD
is
calculated
after
outliers
have
been
removed.

Table
A7.3
Final
16­
A2­
DL­
OR
Type
II
error
rate.
Concentration
IDE
Number
of
Samples
Samples
Reporting
a
Result
Samples
Below
IDE*
Type
II
Error
Rate
%
RSD**

0.100
0.086
50
50
24
0.48
16.35
0.120
0.086
50
50
11
0.22
17.52
0.200
0.086
50
50
1
0.02
12.85
0.240
0.086
50
49
1
0.02
16.77
0.500
0.086
50
50
0
0
16.47
0.600
0.086
50
50
0
0
15.58
1.000
0.086
50
50
0
0
13.80
1.200
0.086
50
50
0
0
14.65
*
Samples
not
reporting
are
assumed
to
be
below
the
IDE
for
the
Type
II
error
calculation.
**
The
%
RSD
is
calculated
after
outliers
have
been
removed.
6
Appendix
8
Variance
Components
Table
A8.1
Variance
components
for
Final
16­
A1­
DL­
OR.
Component
Estimate
%
of
Total
Variation
Lab
0.000553
0.65
Week
0.000002
»
0
Concentration
0.068780
81.45
Lab*
Week
0.000367
0.43
Lab*
Concentration
0.012156
14.39
Week*
Concentration
0.000071
0.08
Error
0.002520
2.98
Table
A8.2
Variance
components
for
Final
16­
A2­
OR.
Component
Estimate
%
of
Total
Variation
Lab
0.000706
0.99
Week
0.000049
0.07
Concentration
0.065210
91.48
Lab*
Week
0.000412
0.58
Lab*
Concentration
0.002581
3.62
Week*
Concentration
0.000199
0.28
Error
0.002130
2.99
Table
A8.3
Variance
components
for
Final
16­
A2­
DL­
OR.
Component
Estimate
%
of
Total
Variation
Lab
0.000483
0.70
Week
0.000029
0.04
Concentration
0.064040
92.69
Lab*
Week
0.000226
0.33
Lab*
Concentration
0.002252
3.26
Week*
Concentration
0.000227
0.33
Error
0.001836
2.66
7
REFERENCES
ASTM
Designation:
D
2777­
96.
(
1996).
Standard
practice
for
determination
of
precision
and
bias
of
applicable
test
methods
of
committee
D­
19
on
water.
American
Society
for
Testing
and
Materials,
West
Conshohocken,
PA.

ASTM
Designation:
D
6091­
97.
(
1997).
Standard
practice
for
99%/
95%
interlaboratory
detection
estimate
(
IDE)
for
analytical
methods
with
negligible
calibration
error.
American
Society
for
Testing
and
Materials,
West
Conshohocken,
PA.

ASTM
Taskgroup
D19.02.04.04.
(
1998).
Proposed:
standard
practice
for
an
interlaboratory
quantitation
estimate.
American
Society
for
Testing
and
Materials,
West
Conshohocken,
PA.

Coleman,
David.
(
2001).
Instructions
for
the
IDE
and
IQE
excel
template.
Alcoa
Inc.,
Pittsburgh,
PA.

Gibbons,
Robert
D.,
Coleman,
David
E.,
and
Maddalone,
Raymond,
F.
(
1997).
An
alternative
minimum
level
definition
for
analytical
quantification.
Environmental
Science
&
Technology,
31,
2071­
2077.

U.
S.
Geological
Survey,
Open­
File
Report
99­
193.
(
1999).
New
reporting
procedures
based
on
long­
term
method
detection
levels
and
some
considerations
for
interpretations
of
water
quality
data
provided
by
the
U.
S.
geological
survey
national
water
quality
laboratory.
USGS,
Reston,
Virginia.

Zorn,
Michael
E.,
Gibbons,
Robert
D.,
and
Sonzogni,
William
C.
(
1999).
Evaluation
of
approximate
methods
for
calculating
the
limit
of
detection
and
limit
of
quantification.
Environmental
Science
&
Technology,
33,
2291­
2295.
ATTACHMENT
1.1
ATTACHMENT
1.2
AAMA
Interlaboratory
Study
PCB
1242
0
10
20
30
40
50
60
70
80
90
100
0
20
40
60
80
100
120
Reported
Laboratory
Results
Concentration
(
ug/
L)
Lab
Results
True
Conc.

Linear
(
Lab
Results)

AAMA
Interlaboratory
Study
PCB
1260
0
1
0
2
0
3
0
4
0
5
0
6
0
7
0
8
0
9
0
1
0
0
0
2
0
4
0
6
0
8
0
1
0
0
1
2
0
Laboratory
Results
Concentration
(
ug/
L)
L
a
b
R
e
s
u
l
t
s
T
r
u
e
C
o
n
c
e
n
t
r
a
t
i
o
n
L
i
n
e
a
r
(
L
a
b
R
e
s
u
l
t
s
)
ATTACHMENT
2.1
MMA
PROPOSED
STUDY
PLAN
PCB
Method
608.2
Interlaboratory
Study
 
Phase
I
I.
Number
of
laboratories
to
Participate
 
Recommendation
10
o
Laboratory
Selection
Criteria
Ø
 
Laboratories
that
perform
PCB
analysis
in
Michigan
·
 
MDEQ
Lab
·
 
Labs
used
by
GM;
FECL,
CT&
E
Anatech
·
 
Ford;
TriMatrix
Laboratoires
·
 
DiamlerChyrsler;
Lancaster
Labs,
CompuChem
·
 
Representative
WWTP
Laboratoires
·
 
Other
commercial
labs
Ø
 
Select
labs
based
on
PE
scores
for
PCBs
in
Water
over
the
past
three
years.
·
 
Lab
must
have
no
results
out
of
control
·
 
Lab
must
have
no
more
than
one
PCB
result
above
the
warning
limit.
Ø
 
Select
at
random
if
more
than
10
qualified
labs
interested
II.
Sample
Preparation
o
Prepared
by
GVSU­
WRI
(
Dr.
Richard
Rediske)
o
One
Liter
Whole
Volume
Samples
(
extra
available
if
breakage)
o
Reagent
Water
Only
for
Phase
I
o
Containing
PCB
Aroclors
1016
and
1260
o
Concentrations
(
ug/
L)
alternating
weeks;
Ø
 
0.01,
0.025,
0.05,
0.10,
0.20,
0.50,
1.0,
2.0
Ø
 
0.015,
0.030,
0.06,
0.12,
0.24,
0.60,
1.2,
2.4
Note:
If
two
or
more
of
the
lowest
samples
are
not
detected
by
all
laboratories
in
the
first
sample
set
then
one
or
more
low
standards
will
be
removed
and
additional
concentrations
added.
o
Time
Coverage
 
Ten
Weeks
Ø
 
One
set
of
all
concentrations
per
week
for
10
weeks
Ø
 
100
Replicates
at
each
concentration
o
Randomized
Ø
 
Analyzed
in
order
of
assigned
random
sample
number
o
Verification
by
Referee
Laboratory
Ø
 
For
each
sample
set
prepared
ATTACHMENT
2.1
(
Continued)

Ø
 
The
highest
concentration
sample
and
a
mid­
range
sample
Ø
 
Will
be
submitted
to;
______________
for
verification
Ø
 
Samples
will
be
extracted,
concentrated
and
analyzed,
no
clean­
ups
will
be
performed
III.
Laboratory
Conditions
and
Variables
o
EPA
Method
608.2
(
Capillary
GC/
ECD)
to
be
used
o
Florisil,
Silica
Gel
and
Activated
Copper
Powder
Cleanups
o
No
Second
Column
Confirmation
o
Sample
containers
and
lids
to
be
solvent
rinse
three
times
after
transfer
of
sample
to
separatory
funnel
o
1
L
to
be
extracted
and
Concentrate
to
a
final
volume
of
1.0
ml
o
A
laboratory
method
blank
will
be
analyzed
with
each
set
o
A
minimum
four
point
Calibration
curve
Ø
 
Ratios
of
5
major
Aroclor
congeners
within
20%
o
Quantification
based
on
the
Calibration
Curve
Ø
 
Three
to
five
congener
peaks
per
Aroclor
must
be
used
for
quantification
Ø
 
Continuing
calibration
verification
will
be
based
on
a
midrange
calibration
standard.
Recalibrate
if
>
15%
variance
o
Cycle
between
all
available
instruments
set
up
for
method
608.2
o
Cycle
between
all
qualified
analysts
for
method
608.2
IV.
Reporting
of
Analytical
Data
o
Report
ALL
results
as
low
as
you
can
see
(
even
without
Aroclor
recognition)
o
If
a
minimum
of
three
congener
peaks
can
not
be
quantified
then
report
a
blank
or
empty
field
o
When
you
can
recognize
an
Aroclor
using
your
normal
Aroclor
identification
techniques
then
include
this
information
with
the
numerical
result
o
Data
to
be
submitted
as
a
hard
copy
and
electronically
on
an
Excel
spreadsheet
of
predefined
format
o
Calibration
curves
will
be
provided
o
Raw
chromatograms
with
integration
will
be
included
in
each
analysis
report
o
Report
all
batch
QC
(
blanks,
CCVs,
duplicate
injection,
etc.)
o
Report
Analyst
Identification
for
ATTACHMENT
2.1
(
Continued)

Ø
 
Extraction
Ø
 
Cleanups
Ø
 
Chromatographic
Analysis
o
Report
the
extraction
technique
used
o
Report
Instrument
Identification
o
Reports
to
be
submitted
within
10
Business
days
of
receipt
of
each
sample
set
V.
Data
Analysis
by
GVSU
Statistics
Department
(
Dr.
John
Gabrosek)
o
Assign
Each
Laboratory
a
letter
to
maintain
confidentiality
o
Remove
outliers
Ø
 
Laboratory
Ranking
Test,
ASTM
D2777
Ø
 
Grubb's
Test
(
1950),
ASTM
D2777
o
Calculation
of
Interlaboratory
and
Intralaboratory
Detection
Limits
for
each
Aroclor
Ø
 
ASTM
IDE
Ø
 
EPA
MDL
o
Calculation
of
Interlaboratory
and
Intralaboratory
Quantification
Limits
each
Aroclor
Ø
 
ASTM
IQE
10%,
20%
and
30%
(
IQE10%
=
IUPAC)
Ø
 
EPA
ML
(
10
times
sigma)
o
Provide
Plots
Ø
 
Measured
Concentration
vs.
True
Concentration
Ø
 
Standard
Deviation
vs.
True
Concentration
Ø
 
Distribution
at
Each
Concentration
o
Analysis
of
Variance
(
ANOVA)
Ø
 
Laboratory
Variability
Ø
 
Analyst
Variability
Ø
 
Instrument
Variability
Ø
 
Extraction
Technique
Variability
IV.
Cost
of
Study
for
10
laboratories
o
Interlaboratory
Analysis
($
50/
sample)
$
40,000
o
Referee
Laboratory
Analysis
($
50/
sample)
$
1,000
o
Sample
Preparation
 
GVSU
WRI
$
20,000
o
Data
Analysis
 
GVSU
Math
&
Statistics
$
10,000
TOTAL
$
71,000
ATTACHMENT
2.1
(
Continued)

VII.
Time
Line
o
Laboratory
Selection
Aug
21
­
Sept
1,
2000
o
Kick­
off
Meeting
by
September
15,
2000
o
Sample
Preparation
Sept
18
­
Dec
15,
2000
o
Sample
Analysis
&
Data
Reporting
Sept
25
­
Jan
5,
2001
o
Data
Analysis
Jan
8
­
Feb
5,
2001
o
Final
Report
and
Recommendation
Feb
5
­
Feb
26,
2001
ATTACHMENT
2.4
PCB
Method
608
Interlaboratory
Study
Plan
20
November,
2000
Kick­
Off
Meeting
I.
Sample
Preparation
and
Submission
1.
Ten
One
Liter
Amber
Glass
Bottles
with
coolers
and
return
shipping
instructions
must
be
submitted
to
Dr.
Richard
Rediske
by
27
November,
2000
Grand
Valley
State
University
118
Padnos
Hall
1
Campus
Drive
Allendale,
MI
49401­
9403
Attn:
Dr.
Richard
Rediske
Phone:
(
616)
895­
3047
2.
Thereafter
you
should
submit
Ten
more
containers
each
time
you
receive
a
batch
for
analysis
until
you
are
instructed
to
stop
3.
You
may
either
pick
up
the
samples
(
provide
phone
number
to
call
for
pick­
up)
or
provide
shipping
paperwork
that
covers
the
cost
of
return
shipping
4.
Samples
will
be
Prepared
by
GVSU­
WRI
and
Verified
by
Trace
Analytical
in
Muskegon
5.
One
Liter
Whole
Volume
Samples
(
extra
available
if
breakage)
6.
Reagent
Water
Containing
two
PCB
Aroclors
for
Phase
I
7.
Each
Batch
of
Samples
will
Consist
of
Eight
Samples
at
Concentrations
ranging
from
non­
detect
to
~
2.5
(
ug/
L)
8.
Samples
will
be
Numbered
and
MUST
BE
ANALYZED
IN
THAT
ORDER
(
This
is
a
random
sequence
to
represent
real
sample
submission)
9.
We
Anticipate
10­
12
Batches
to
be
Submitted
over
about
a
Three
Month
Period
10.
One
or
Two
Batches
will
arrive
before
Christmas
and
The
remainder
of
the
Batches
will
arrive
in
over
a
Two
Month
Period
after
Christmas
ATTACHMENT
2.4
(
Continued)

11.
The
first
one
or
two
batches
will
be
used
to
Adjust
the
Spike
Levels
so
we
will
wait
until
results
are
returned
before
the
next
batch
is
submitted
II.
Sample
Extraction
and
Clean­
up
1.
Liquid/
Liquid
Extraction
(
Specify
Method
Used)
 
RINSE
SAMPLE
CONTAINER
AND
LID
THREE
TIMES
AFTER
TRANSFERING
SAMPLE
2.
Volume
of
Sample
1,000
ml
­
Final
Volume
of
Extract
1
ml
3.
Sulfuric
Acid
Clean­
up
with
only
one
acid
treatment
4.
Florisil
Clean­
up
(
Specify
Technique
Used)
5.
Sulfur
Cleanup
(
Specify
Method
Used)
6.
No
Second
Column
Confirmation
8.
A
laboratory
method
blank
will
be
analyzed
and
reported
with
each
batch
9.
A
Laboratory
Fortified
Blank
(
LFB)
near
the
midpoint
of
your
calibration
curve
(
Aroclor
1254
or
1260)
will
analyzed
with
each
batch
and
the
percent
recovery
reported.
The
blank
LFB
must
go
through
the
entire
extraction
and
clean­
up
process.
10.
No
MS/
MSD
will
be
required
11.
Cycle
between
all
trained/
qualified
analysts
(
Note
Extraction
and
Prep
Analyst
for
each
batch)

III.
Sample
Analysis
1.
EPA
Method
608
(
Capillary
GC/
ECD)
to
be
used
2.
A
minimum
four
point
Calibration
curve
3.
Ratios
of
5
major
Aroclor
congeners
within
20%
4.
Quantification
based
on
the
Calibration
Curve
Response
Factor
5.
Three
to
five
congener
peaks
per
Aroclor
must
be
used
for
quantification
6.
Continuing
calibration
verification
will
be
based
on
a
midrange
calibration
standard.
Recalibrate
if
>
15%
variance
7.
Cycle
between
all
available
instruments
set
up
for
method
608
(
Note
Instrument
used
for
Each
Batch)
8.
Cycle
between
all
qualified
analysts
for
method
608
(
Note
Analyst
for
Each
Batch)
ATTACHMENT
2.4
(
Continued)

IV.
Reporting
of
Analytical
Data
1.
Complete
the
Initial
Information
Sheet
before
you
begin
2.
Report
results
for
each
batch
on
the
Standard
Excel
Spreadsheet
provided
within
two
weeks
of
receipt
of
samples
3.
Submit
spreadsheet
by
e­
mail
to
gabrosej@
gvsu.
edu
4.
Report
ALL
results
as
low
as
you
can
see
(
even
without
Aroclor
recognition)
5.
Report
all
quantified
results
to
the
100th
place
(
two
places
past
decimal)
6.
If
a
minimum
of
three
congener
peaks
can
not
be
quantified
then
report
a
blank
or
empty
field
7.
When
you
can
recognize
an
Aroclor
using
your
normal
Aroclor
identification
techniques
then
include
this
information
with
the
numerical
result
8.
Report
Blank
Result
last
and
designate
9YX
(
Y=
Batch
Identifier
and
X=
Laboratory
Identifier)
9.
Two
copies
of
one
final
hard
copy
report
will
be
required.
8.
The
Final
Hard
Copy
Report
submitted
to
Dr.
Rediske
will
include
the
following:
§
 
A
Summary
of
all
Results
including
QC
(
Surrogate
%
Recovery,
LFB
%
Recovery
and
Blanks
at
a
minimum)
§
 
Calibration
curves
§
 
Raw
chromatograms
with
Integration
§
 
Methods
Used
for
Extraction
and
Clean­
ups
§
 
Raw
Data
from
any
MDLs
Generated
During
the
Study
§
 
Analyst
Identification
for
Extractions,
Cleanups
and
Chromatographic
Analyses
§
 
Instrument
Identification
V.
Billing
One
Invoice
may
be
submitted
each
month
for
work
completed
at
a
rate
not
to
exceed
$
50.00
per
sample
submitted.
Submit
invoice
to:

Michigan
Manufactures
Association
620
S.
Capitol
Avenue
Lansing,
MI
48933­
2308
Attn:
Mike
Johnston
ATTACHMENT
2.4
(
Continued)

VI.
Project
Time
Line
Laboratory
Selection
November
12,
2000
Kick­
off
Meeting
November
20,
2000
Sample
Prep
Verification
November
12­
30,
2000
Sample
Preparation
Dec
1­
Feb
19,
2000
Sample
Analysis
&
Data
Reporting
Dec
4­
Mar
5,
2001
Data
Analysis
Mar
5
­
Mar
30,
2001
Final
Report
and
Recommendation
April
1
­
14,
2001
VII.
For
more
information
or
questions
about
the
study
contact:
John
H.
Phillips
Ford
Motor
Company
Environmental
Quality
Office
Phone:
(
313)
845­
1648
E­
Mail:
jphill12@
ford.
com
ATTACHMENT
3.1
ATTACHMENT
3.2
Attachment
2.2
MMA
PCB
INTERLABORATORY
STUDY­
LABORATORY
CERTIFICATION/
QUALIFICATION
LIST
TriMatrix
FECL
STL
ATS
Trace
Test
America
Clayton
CTE
Enviroscan
AAC
Trinity
STL
AGENCY
Regulatory
Program
Grand
Rapids
Lansing
Amherst
Ann
Anbor
Muskegon
Dayton
Novi
Ludington
Rothschild
Farmington
Hills
N.
Canton
Alaska
Drinking
Water
(
SDWA)
X
Arkansas
Drinking
Water
(
SDWA)
X
Wastewater
X
California
Wastewater
(
CWA)
X
Laboratory
Certification
­
DHS
X
X
Connecticut
Wastewater
and/
or
Trade
Waste
X
X
Florida
Drinking
Water
(
SDWA)
X
Environmental
Water
X
X
Dept.
of
Env.
Protection
Comprehensive
QA
Plan
X
Illinois
State
Approval
X
Kentucky
Drinking
Water
(
SDWA)
X
Kansas
Wastewater
X
X
Louisiana
Drinking
Water
(
SDWA)
X
X
Maryland
Drinking
Water
(
SDWA)
X
Massachusetts
Potable
Water
X
Non­
Potable
Water
X
X
Michigan
Drinking
Water
(
SDWA)
X
X
Not
Org.
Not
Org.
Not
Org.
X
State
Contract
Laboratory
X
X
Minnesota
Drinking
Water
(
SDWA)
X
X
Wastewater
X
New
Jersey
Wastewater
(
CWA)
X
X
Hazardous
Waste
(
RCRA)

New
York
Department
of
Health
Drinking
Water
(
SDWA)
X
Non­
Potable
Water
(
CWA)
X
X
X
X
North
Carolina
Wastewater/
Groundwater
X
X
North
Dakota
Wastewater
(
CWA)
X
Ohio
Ohio
Voluntary
Action
Program
X
X
X
Potable
Water
(
SDWA)
X
Oklahoma
General
Water
Quality
Sludge
Testing
X
Pennnsylvania
Drinking
Water
(
SDWA)
X
South
Carolina
Drinking
Water
(
SDWA)
X
Wastewater
(
CWA)
X
Tennessee
Drinking
Water
(
SDWA)
X
X
Washington
Department
of
Ecology
Water
by
WW
and
Haz.
W.
Meth.
X
Wastewater
(
CWA)
X
West
Virginia
Drinking
Water
(
SDWA)
X
Wisconsin
Drinking
Water
(
SDWA)
X
X
X
Environmental
Analyses
X
X
X
X
X
X
National
NELAP
P
P
P
P
P
A
P
P
AALA
ISO
Guide
25
X
X
X
X
Army
(
U.
S.)
Corps
of
Engineers
X
X
DEFINITIONS
AALA
American
Association
for
Laboratory
Accreditation
CWA
Clean
Water
Act
NPDES
National
Pollution
Dishcharge
Elimination
System
SDWA
Safe
Drinking
Water
Act
X
Certifed
P
Pending
SOPs
EPA
Method
608
X
X
X
X
X
X
X
X
X
X
X
Acid
Clean
Up
X
X
X
X
X
X
X
X
X
Sulfur
Clean
Up
X
X
X
X
X
X
X
X
X
X
Florisil
Clean
Up
X
X
X
X
X
X
X
X
X
Silica
Gell
Clean
Up
X
X
X
X
X
X
X
X
Alumina
Clean
Up
X
X
Performance
Evaluation
Sample
Results
Total
No.
PCB
in
Water
Tests
past
2
years
26
17
10
5
15
5
19
16
2
9
12
Outside
of
Warning
Limits
0
2
0
0
0
0
0
0
0
0
0
Outside
of
Control
Limits
0
0
0
0
0
0
1
2
0
2
0
See
Comments
See
Comments
See
Comments
Comments
Clayton
had
one
transcription
error
Clayton
also
had
two
results
barely
in
Enviroscan
missed
one
oil
sample
for
PCB
FECL
uses
ASI
wide
acceptance
windows
Attachment
2.3A
Lab
A
1
Do
you
perform
cleanups
on
your
PE
Samples?
YES
2
Instruments
Used
for
Method
608
A
INSTRUMENT#
3
Most
Recent
MDL
Date
Aug­
99
Date
Aug­
99
Date
Date
Aroclor
1016
Aroclor
1221
Aroclor
Aroclor
Spike
(
ug/
L)
0.1
Spike
(
ug/
L)
0.1
Spike
(
ug/
L)
Spike
(
ug/
L)
Result
(
ug/
L)
0.05(
MDL)
Result
(
ug/
L)
0.02(
MDL)
Result
(
ug/
L)
Result
(
ug/
L)
Clean­
ups
Acid
YES
Clean­
ups
Acid
YES
Clean­
ups
Acid
Clean­
ups
Acid
Florisil
YES
Florisil
YES
Florisil
Florisil
Sulfur
YES
Sulfur
YES
Sulfur
Sulfur
Replicate
1
0.074
Replicate
1
0.089
Replicate
1
Replicate
1
Results
2
0.054
Results
2
0.066
Results
2
Results
2
ug/
L
3
0.111
ug/
L
3
0.081
ug/
L
3
ug/
L
3
4
0.067
4
0.08
4
4
5
0.064
5
0.076
5
5
6
0.065
6
0.072
6
6
7
0.059
7
0.071
7
7
8
0.077
8
0.082
8
8
9
9
9
9
10
10
10
10
B
INSTRUMENT#
3
Most
Recent
MDL
Date
Aug­
99
Date
Aug­
99
Date
Date
Aroclor
1232
Aroclor
1242
Aroclor
Aroclor
Spike
(
ug/
L)
0.1
Spike
(
ug/
L)
0.1
Spike
(
ug/
L)
Spike
(
ug/
L)
Result
(
ug/
L)
0.04(
MDL)
Result
(
ug/
L)
0.14(
MDL)
Result
(
ug/
L)
Result
(
ug/
L)
Clean­
ups
Acid
YES
Clean­
ups
Acid
YES
Clean­
ups
Acid
Clean­
ups
Acid
Florisil
YES
Florisil
YES
Florisil
Florisil
Sulfur
YES
Sulfur
YES
Sulfur
Sulfur
Replicate
1
0.104
Replicate
1
0.284
Replicate
1
Replicate
1
Results
2
0.084
Results
2
0.217
Results
2
Results
2
ug/
L
3
0.103
ug/
L
3
0.3
ug/
L
3
ug/
L
3
4
0.065
4
0.207
4
4
5
0.068
5
0.258
5
5
PCB
Interlaboratory
Study
Initial
Information
Sheet
Submit
to
John
Phillips
at
"
jphill12@
ford.
com"

Lab
Identifier
Lab
Identifier
Page
1
of
4
Attachment
2.3A
6
0.071
6
0.3
6
6
7
0.08
7
0.313
7
7
8
0.083
8
0.331
8
8
9
9
9
9
10
10
10
10
C
INSTRUMENT#
3
Most
Recent
MDL
Date
Aug­
99
Date
Aug­
99
Date
Date
Aroclor
1248
Aroclor
1254
Aroclor
Aroclor
Spike
(
ug/
L)
0.1
Spike
(
ug/
L)
0.1
Spike
(
ug/
L)
Spike
(
ug/
L)
Result
(
ug/
L)
0.06(
MDL)
Result
(
ug/
L)
0.02(
MDL)
Result
(
ug/
L)
Result
(
ug/
L)
Clean­
ups
Acid
YES
Clean­
ups
Acid
YES
Clean­
ups
Acid
Clean­
ups
Acid
Florisil
YES
Florisil
YES
Florisil
Florisil
Sulfur
YES
Sulfur
YES
Sulfur
Sulfur
Replicate
1
0.077
Replicate
1
0.107
Replicate
1
Replicate
1
Results
2
0.081
Results
2
0.097
Results
2
Results
2
ug/
L
3
0.079
ug/
L
3
0.1
ug/
L
3
ug/
L
3
4
0.036
4
0.097
4
4
5
0.076
5
0.114
5
5
6
0.082
6
0.108
6
6
7
0.043
7
0.109
7
7
8
0.054
8
0.108
8
8
9
9
9
9
10
10
10
10
D
INSTRUMENT#
3
Most
Recent
MDL
Date
Aug­
99
Date
Date
Date
Aroclor
1260
Aroclor
Aroclor
Aroclor
Spike
(
ug/
L)
0.1
Spike
(
ug/
L)
Spike
(
ug/
L)
Spike
(
ug/
L)
Result
(
ug/
L)
0.04(
MDL)
Result
(
ug/
L)
Result
(
ug/
L)
Result
(
ug/
L)
Clean­
ups
Acid
YES
Clean­
ups
Acid
Clean­
ups
Acid
Clean­
ups
Acid
Florisil
YES
Florisil
Florisil
Florisil
Sulfur
YES
Sulfur
Sulfur
Sulfur
Replicate
1
0.124
Replicate
1
Replicate
1
Replicate
1
Results
2
0.145
Results
2
Results
2
Results
2
ug/
L
3
0.153
ug/
L
3
ug/
L
3
ug/
L
3
4
0.143
4
4
4
5
0.127
5
5
5
6
0.134
6
6
6
7
0.162
7
7
7
Lab
Identifier
Lab
Identifier
Page
2
of
4
Attachment
2.3A
8
0.134
8
8
8
9
9
9
9
10
10
10
10
3
Analyst
Identification
A
EF
MO
EF
MO
PT
B
KD
JS
KD
JS
BP
C
BW
BW
D
JH
JH
E
AB
AB
F
LD
LD
4
Tetrachloro­
m­
Xylene
Decachlorobiphenyl
5
Lower
0.05
Upper
2
6
Acid
YES
Florisil
YES
Sulfur
YES
7
PCB
Aroclor
Identification
Describe
Your
Identification
Process
Pattern
Recognition
8
PCB
Quantification
Describe
Your
Quantification
Process
Using
5
peaks
that
are
at
least
25%
of
the
height
of
the
largest
Aroclor
peak
(
except
Aroclor
1221
only
3
peaks)
Clean­
up
Method
GC
Analyst
Lab
Identifier
Calibration
Range
in
ug/
L
Surrogates
Used
Extraction
Analyst
Lab
Identifier
Clean­
up
Analyst
Lab
Identifier
Page
3
of
4
Attachment
2.3A
9
Start­
Up
Demonstration
Test
Results
for
Capillary
Column
Modification
The
Following
Results
should
be
for
four
replicates
at
50
ug/
L
Before
After
Aroclor
1016
s
in
ug/
L
50
Mean
50
%
Recv.
100
Aroclor
1221
s
in
ug/
L
50
Mean
52
%
Recv.
104
Aroclor
1232
s
in
ug/
L
50
Mean
52
%
Recv.
104
Aroclor
1242
s
in
ug/
L
50
Mean
62
%
Recv.
124
Aroclor
1248
s
in
ug/
L
50
Mean
56
%
Recv.
112
Aroclor
1254
s
in
ug/
L
50
Mean
48
%
Recv.
96
Aroclor
1260
s
in
ug/
L
50
Mean
41
%
Recv.
82
Page
4
of
4
Attachment
2.3B
PCB
Interlaboratory
Study
Initial
Information
Sheet
Submit
to
John
Phillips
at
"
jphill12@
ford.
com"
Lab
B
1
Do
you
perform
cleanups
on
your
PE
Samples?
No
2
Instruments
Used
for
Method
608
A
Lab
Identifier
3800D
Most
Recent
MDL
Date
11/
15/
00
Date
11/
16/
00
Date
11/
17/
00
Date
Aroclor
1260
Aroclor
1248
Aroclor
1254
Aroclor
Spike
(
ug/
L)
0.2
Spike
(
ug/
L)
0.1
Spike
(
ug/
L)
0.1
Spike
(
ug/
L)
Result
(
ug/
L)
0.0422
Result
(
ug/
L)
0.0286
Result
(
ug/
L)
0.0233
Result
(
ug/
L)
Clean­
ups
Acid
N
Clean­
ups
Acid
N
Clean­
ups
Acid
N
Clean­
ups
Acid
Florisil
N
Florisil
N
Florisil
N
Florisil
Sulfur
N
Sulfur
N
Sulfur
N
Sulfur
Replicate
1
0.199
Replicate
1
0.113
Replicate
1
0.088
Replicate
1
Results
2
0.188
Results
2
0.102
Results
2
0.104
Results
2
ug/
L
3
0.190
ug/
L
3
0.095
ug/
L
3
0.099
ug/
L
3
4
0.173
4
0.114
4
0.095
4
5
0.161
5
0.101
5
0.093
5
6
0.192
6
0.091
6
0.094
6
7
0.194
7
0.094
7
0.110
7
8
8
8
8
9
9
9
9
10
10
10
10
B
Lab
Identifier
Most
Recent
MDL
Date
Date
Date
Date
Aroclor
Aroclor
Aroclor
Aroclor
Spike
(
ug/
L)
Spike
(
ug/
L)
Spike
(
ug/
L)
Spike
(
ug/
L)
Result
(
ug/
L)
Result
(
ug/
L)
Result
(
ug/
L)
Result
(
ug/
L)
Clean­
ups
Acid
Clean­
ups
Acid
Clean­
ups
Acid
Clean­
ups
Acid
Florisil
Florisil
Florisil
Florisil
Sulfur
Sulfur
Sulfur
Sulfur
Replicate
1
Replicate
1
Replicate
1
Replicate
1
Page
1
of
4
Attachment
2.3B
Results
2
Results
2
Results
2
Results
2
ug/
L
3
ug/
L
3
ug/
L
3
ug/
L
3
4
4
4
4
5
5
5
5
6
6
6
6
7
7
7
7
8
8
8
8
9
9
9
9
10
10
10
10
C
Lab
Identifier
Most
Recent
MDL
Date
Date
Date
Date
Aroclor
Aroclor
Aroclor
Aroclor
Spike
(
ug/
L)
Spike
(
ug/
L)
Spike
(
ug/
L)
Spike
(
ug/
L)
Result
(
ug/
L)
Result
(
ug/
L)
Result
(
ug/
L)
Result
(
ug/
L)
Clean­
ups
Acid
Clean­
ups
Acid
Clean­
ups
Acid
Clean­
ups
Acid
Florisil
Florisil
Florisil
Florisil
Sulfur
Sulfur
Sulfur
Sulfur
Replicate
1
Replicate
1
Replicate
1
Replicate
1
Results
2
Results
2
Results
2
Results
2
ug/
L
3
ug/
L
3
ug/
L
3
ug/
L
3
4
4
4
4
5
5
5
5
6
6
6
6
7
7
7
7
8
8
8
8
9
9
9
9
10
10
10
10
D
Lab
Identifier
Most
Recent
MDL
Date
Date
Date
Date
Aroclor
Aroclor
Aroclor
Aroclor
Spike
(
ug/
L)
Spike
(
ug/
L)
Spike
(
ug/
L)
Spike
(
ug/
L)
Result
(
ug/
L)
Result
(
ug/
L)
Result
(
ug/
L)
Result
(
ug/
L)
Clean­
ups
Acid
Clean­
ups
Acid
Clean­
ups
Acid
Clean­
ups
Acid
Florisil
Florisil
Florisil
Florisil
Sulfur
Sulfur
Sulfur
Sulfur
Replicate
1
Replicate
1
Replicate
1
Replicate
1
Page
2
of
4
Attachment
2.3B
Results
2
Results
2
Results
2
Results
2
ug/
L
3
ug/
L
3
ug/
L
3
ug/
L
3
4
4
4
4
5
5
5
5
6
6
6
6
7
7
7
7
8
8
8
8
9
9
9
9
10
10
10
10
3
Analyst
Identification
Extraction
Analyst
Clean­
up
Analyst
GC
Analyst
Lab
Identifier
Lab
Identifier
Lab
Identifier
A
A
A
A
B
B
B
B
C
C
C
D
4
Surrogates
Used
Decachlorobiphenyl
5
Calibration
Range
Lower
0.2
in
ug/
L
Upper
2
6
Clean­
up
Method
Acid
3650B
Florisil
3620B­
Micro
column
Sulfur
3660B­
Cu
7
PCB
Aroclor
Identification
Describe
Your
Identification
Process
See
attachment
8
PCB
Quantification
Describe
Your
Quantification
Process
Page
3
of
4
Attachment
2.3B
See
attachment
9
Start­
Up
Demonstration
Test
Results
for
Capillary
Column
Modification
The
Following
Results
should
be
for
four
replicates
at
50
ug/
L
Before
After
Aroclor
1016
s
in
ug/
L
Mean
%
Recv.

Aroclor
1221
s
in
ug/
L
Mean
%
Recv.

Aroclor
1232
s
in
ug/
L
Mean
%
Recv.

Aroclor
1242
s
in
ug/
L
Mean
%
Recv.

Aroclor
1248
s
in
ug/
L
1.65
Mean
54.7
%
Recv.
109
Aroclor
1254
s
in
ug/
L
4.88
Mean
43.2
%
Recv.
86
Aroclor
1260
s
in
ug/
L
0.62
Mean
50.4
%
Recv.
101
Page
4
of
4
Attachment
2.3C
Lab
C
1
Do
you
perform
cleanups
on
your
PE
Samples?
Yes.
A
minimum
of
one
acid
cleanup
for
every
PCB
sample.

2
Instruments
Used
for
Method
608
A
Instrument
HP
2
Most
Recent
MDL
Date
2/
24/
00
Date
2/
24/
00
Date
2/
24/
00
Date
2/
24/
00
Aroclor
AR1260
Front
Aroclor
AR1260
Rear
Aroclor
AR1016
Front
Aroclor
AR1016
Rear
Spike
(
ug/
L)
0.5
Spike
(
ug/
L)
0.5
Spike
(
ug/
L)
0.5
Spike
(
ug/
L)
0.5
Result
(
ug/
L)
0.064
Result
(
ug/
L)
0.065
Result
(
ug/
L)
0.14
Result
(
ug/
L)
0.18
Clean­
ups
Acid
x
Clean­
ups
Acid
x
Clean­
ups
Acid
x
Clean­
ups
Acid
x
Florisil
Florisil
Florisil
Florisil
Sulfur
Sulfur
Sulfur
Sulfur
Replicate
1
0.5246
Replicate
1
0.5788
Replicate
1
0.5734
Replicate
1
0.6297
Results
2
0.5421
Results
2
0.5908
Results
2
0.5904
Results
2
0.6212
ug/
L
3
0.5315
ug/
L
3
0.5515
ug/
L
3
0.5393
ug/
L
3
0.6363
4
0.5346
4
0.5533
4
0.5401
4
0.5774
5
0.5444
5
0.5527
5
0.4749
5
0.4984
6
0.549
6
0.5826
6
0.503
6
0.5408
7
0.4883
7
0.5339
7
0.4877
7
0.52
8
8
8
8
9
9
9
9
10
10
10
10
Most
Recent
MDL
Date
2/
24/
00
Date
2/
24/
00
Date
2/
24/
00
Date
2/
24/
00
Aroclor
AR1254
Front
Aroclor
AR1254
Rear
Aroclor
AR1221
Front
Aroclor
AR1221
Rear
Spike
(
ug/
L)
0.5
Spike
(
ug/
L)
0.5
Spike
(
ug/
L)
0.5
Spike
(
ug/
L)
0.5
Result
(
ug/
L)
0.086
Result
(
ug/
L)
0.096
Result
(
ug/
L)
0.093
Result
(
ug/
L)
0.094
Clean­
ups
Acid
x
Clean­
ups
Acid
x
Clean­
ups
Acid
x
Clean­
ups
Acid
x
Florisil
Florisil
Florisil
Florisil
Sulfur
Sulfur
Sulfur
Sulfur
Replicate
1
0.5337
Replicate
1
0.5593
Replicate
1
0.5169
Replicate
1
0.5164
Results
2
0.574
Results
2
0.6032
Results
2
0.5618
Results
2
0.5772
ug/
L
3
0.5329
ug/
L
3
0.577
ug/
L
3
0.4993
ug/
L
3
0.5082
4
0.5864
4
0.633
4
0.5428
4
0.5668
5
0.5866
5
0.6288
5
0.5582
5
0.5881
Lab
Identifier
PCB
Interlaboratory
Study
Initial
Information
Sheet
Submit
to
John
Phillips
at
"
jphill12@
ford.
com"

Page
1
of
4
Attachment
2.3C
6
0.5362
6
0.5855
6
0.5428
6
0.5582
7
0.5254
7
0.5589
7
0.4852
7
0.5575
8
8
8
8
9
9
9
9
10
10
10
10
Most
Recent
MDL
Date
2/
24/
00
Date
2/
24/
00
Date
2/
24/
00
Date
2/
24/
00
Aroclor
AR1248
Front
Aroclor
AR1248
Rear
Aroclor
AR1242
Front
Aroclor
AR1242
Rear
Spike
(
ug/
L)
0.5
Spike
(
ug/
L)
0.5
Spike
(
ug/
L)
0.5
Spike
(
ug/
L)
0.5
Result
(
ug/
L)
0.2
Result
(
ug/
L)
0.22
Result
(
ug/
L)
0.27
Result
(
ug/
L)
0.3
Clean­
ups
Acid
x
Clean­
ups
Acid
x
Clean­
ups
Acid
x
Clean­
ups
Acid
x
Florisil
Florisil
Florisil
Florisil
Sulfur
Sulfur
Sulfur
Sulfur
Replicate
1
0.4322
Replicate
1
0.4454
Replicate
1
0.512
Replicate
1
0.5536
Results
2
0.5431
Results
2
0.5846
Results
2
0.2713
Results
2
0.2915
ug/
L
3
0.4814
ug/
L
3
0.5121
ug/
L
3
0.4276
ug/
L
3
0.4644
4
0.4205
4
0.4461
4
0.4957
4
0.5359
5
0.5875
5
0.6254
5
0.53
5
0.5708
6
0.4368
6
0.4742
6
0.469
6
0.5146
7
0.4772
7
0.5204
7
0.4811
7
0.5237
8
8
8
8
9
9
9
9
10
10
10
10
D
Most
Recent
MDL
Date
2/
24/
00
Date
2/
24/
00
Date
Date
Aroclor
AR1232
Front
Aroclor
AR1232
Rear
Aroclor
Aroclor
Spike
(
ug/
L)
0.5
Spike
(
ug/
L)
0.5
Spike
(
ug/
L)
Spike
(
ug/
L)
Result
(
ug/
L)
0.16
Result
(
ug/
L)
0.16
Result
(
ug/
L)
Result
(
ug/
L)
Clean­
ups
Acid
x
Clean­
ups
Acid
x
Clean­
ups
Acid
Clean­
ups
Acid
Florisil
Florisil
Florisil
Florisil
Sulfur
Sulfur
Sulfur
Sulfur
Replicate
1
0.3997
Replicate
1
0.4139
Replicate
1
Replicate
1
Results
2
0.4921
Results
2
0.4976
Results
2
Results
2
ug/
L
3
0.4839
ug/
L
3
0.5063
ug/
L
3
ug/
L
3
4
0.436
4
0.474
4
4
5
0.4836
5
0.5201
5
5
6
0.4213
6
0.4648
6
6
Page
2
of
4
Attachment
2.3C
7
0.3532
7
0.378
7
7
8
8
8
8
9
9
9
9
10
10
10
10
3
Analyst
Identification
A
EM
RS
RS
B
DT
RR
RR
C
TF
D
DK
E
NP
F
4
TCMX
DCB
5
Lower
0.1ng/
uL
Upper
2
ng/
uL
6
Acid
Acid
clean
on
every
sample
Florisil
Silica
gel/
Florisil
column
as
needed.
Sulfur
Mercury,
TBA,
All
samples
are
screened
and
further
cleanup
is
determined
from
the
screen.
7
PCB
Aroclor
Identification
Describe
Your
Identification
Process
Pattern
matching
with
calibration
standards,
Peak
ratios,
and
retention
times
are
used.

8
PCB
Quantification
Describe
Your
Quantification
Process
3­
5
major
peaks
are
chosen.
Clean­
up
Analyst
Lab
Identifier
Clean­
up
Method
GC
Analyst
Lab
Identifier
Calibration
Range
in
ug/
L
Surrogates
Used
Extraction
Analyst
Lab
Identifier
Page
3
of
4
Attachment
2.3C
9
Start­
Up
Demonstration
Test
Results
for
Capillary
Column
Modification
The
Following
Results
should
be
for
four
replicates
at
50
ug/
L
Before
After
Aroclor
1016
s
in
ug/
L
10
Values
taken
from
Analyst
Demonstration
of
Capability
Mean
9.39
%
Recv.
93.9
Aroclor
1221
s
in
ug/
L
0.05
Values
taken
from
Instrument
IDL.
Mean
0.0695
Based
on
7
replicates
%
Recv.
139
Aroclor
1232
s
in
ug/
L
0.05
Values
taken
from
Instrument
IDL.
Mean
0.0625
Based
on
7
replicates
%
Recv.
125
Aroclor
1242
s
in
ug/
L
0.05
Values
taken
from
Instrument
IDL.
Mean
0.0625
Based
on
7
replicates
%
Recv.
125
Aroclor
1248
s
in
ug/
L
0.05
Values
taken
from
Instrument
IDL.
Mean
0.064
Based
on
7
replicates
%
Recv.
128
Aroclor
1254
s
in
ug/
L
0.05
Values
taken
from
Instrument
IDL.
Mean
0.064
Based
on
7
replicates
%
Recv.
128
Aroclor
1260
s
in
ug/
L
10
Values
taken
from
Analyst
Demonstration
of
Capability
Mean
9.26
%
Recv.
92.6
Page
4
of
4
Attachment
2.3D
Lab
D
1
Do
you
perform
cleanups
on
your
PE
Samples?
Acid
cleanup
only
2
Instruments
Used
for
Method
608
STL
Buffalo
is
currently
running
new
MDLs
for
method
608.
I
will
forward
the
results
as
soon
as
they
are
available.
A
HP5890­
16
The
MDLs
listed
below
are
our
2000
study
results.

Most
Recent
MDL
Date
Date
Date
Date
Aroclor
1016
Aroclor
1221
Aroclor
1232
Aroclor
1242
Spike
(
ug/
L)
0.02
Spike
(
ug/
L)
0.02
Spike
(
ug/
L)
0.02
Spike
(
ug/
L)
0.02
Result
(
ug/
L)
0.00599
Result
(
ug/
L)
0.0171
Result
(
ug/
L)
0.01375
Result
(
ug/
L)
0.041
Clean­
ups
Acid
x
Clean­
ups
Acid
x
Clean­
ups
Acid
x
Clean­
ups
Acid
x
Florisil
Florisil
Florisil
Florisil
Sulfur
Sulfur
Sulfur
Sulfur
Replicate
1
Replicate
1
Replicate
1
Replicate
1
Results
2
Results
2
Results
2
Results
2
ug/
L
3
ug/
L
3
ug/
L
3
ug/
L
3
4
4
4
4
5
5
5
5
6
6
6
6
7
7
7
7
8
8
8
8
9
9
9
9
10
10
10
10
A
HP5890­
16
Most
Recent
MDL
Date
Date
Date
Date
Aroclor
1248
Aroclor
1254
Aroclor
1260
Aroclor
Spike
(
ug/
L)
0.02
Spike
(
ug/
L)
0.02
Spike
(
ug/
L)
0.02
Spike
(
ug/
L)
Result
(
ug/
L)
0.00783
Result
(
ug/
L)
0.00648
Result
(
ug/
L)
0.00414
Result
(
ug/
L)
Clean­
ups
Acid
x
Clean­
ups
Acid
x
Clean­
ups
Acid
x
Clean­
ups
Acid
Florisil
Florisil
Florisil
Florisil
Sulfur
Sulfur
Sulfur
Sulfur
PCB
Interlaboratory
Study
Initial
Information
Sheet
Submit
to
John
Phillips
at
"
jphill12@
ford.
com"

Lab
Identifier
Lab
Identifier
Page
1
of
3
Attachment
2.3D
Replicate
1
Replicate
1
Replicate
1
Replicate
1
Results
2
Results
2
Results
2
Results
2
ug/
L
3
ug/
L
3
ug/
L
3
ug/
L
3
4
4
4
4
5
5
5
5
6
6
6
6
7
7
7
7
8
8
8
8
9
9
9
9
10
10
10
10
3
Analyst
Identification
A
BE
BJ
BJ
B
KM
KJ
KJ
C
RF
NH
NH
D
TB
GR
GR
EF
4
TMX
DCBP
5
Lower
0.05
Upper
2
6
Acid
3665A
Florisil
3620B
Sulfur
3660B
7
PCB
Aroclor
Identification
Describe
Your
Identification
Process
The
PCB
pattern
of
the
sample
is
compared
to
the
patterns
of
the
individual
Aroclors.
Clean­
up
Method
GC
Analyst
Lab
Identifier
Calibration
Range
in
ug/
L
Surrogates
Used
Extraction
Analyst
Lab
Identifier
Clean­
up
Analyst
Lab
Identifier
Page
2
of
3
Attachment
2.3D
8
PCB
Quantification
Describe
Your
Quantification
Process
The
average
concentration
of
5
individually
calibrated
peaks
of
the
identified
Aroclor
are
used
to
quantify
the
sample
concentration.

Page
3
of
3
Attachment
2.3E
Lab
E
1
Do
you
perform
cleanups
on
your
PE
Samples?
no
2
Instruments
Used
for
Method
608
A
GC­
1
Most
Recent
MDL
Date
11/
17/
2000
Date
11/
17/
2000
Date
11/
17/
2000
Date
11/
17/
2000
Aroclor
1016
Aroclor
1260
Aroclor
1248
Aroclor
1242
Spike
(
ug/
L)
0.1
Spike
(
ug/
L)
0.1
Spike
(
ug/
L)
0.1
Spike
(
ug/
L)
0.1
Result
(
ug/
L)
0.018
Result
(
ug/
L)
0.02
Result
(
ug/
L)
0.014
Result
(
ug/
L)
0.021
Clean­
ups
Acid
NO
Clean­
ups
Acid
NO
Clean­
ups
Acid
NO
Clean­
ups
Acid
NO
Florisil
NO
Florisil
NO
Florisil
NO
Florisil
NO
Sulfur
NO
Sulfur
NO
Sulfur
NO
Sulfur
NO
Replicate
1
0.051
Replicate
1
0.098
Replicate
1
0.136
Replicate
1
0.099
Results
2
0.041
Results
2
0.095
Results
2
0.141
Results
2
0.101
ug/
L
3
0.042
ug/
L
3
0.095
ug/
L
3
0.145
ug/
L
3
0.105
4
0.034
4
0.082
4
0.141
4
0.116
5
0.047
5
0.082
5
0.135
5
0.119
6
0.047
6
0.095
6
0.141
6
0.11
7
0.036
7
0.096
7
0.149
7
0.111
8
8
8
8
9
9
9
9
10
10
10
10
B
GC­
1
Most
Recent
MDL
Date
11/
17/
2000
Date
11/
17/
2000
Date
11/
17/
2000
Date
11/
17/
2000
Aroclor
1254
Aroclor
1232
Aroclor
1262
Aroclor
1268
Spike
(
ug/
L)
0.1
Spike
(
ug/
L)
0.1
Spike
(
ug/
L)
0.1
Spike
(
ug/
L)
0.1
Result
(
ug/
L)
0.018
Result
(
ug/
L)
0.013
Result
(
ug/
L)
0.024
Result
(
ug/
L)
0.027
Clean­
ups
Acid
NO
Clean­
ups
Acid
NO
Clean­
ups
Acid
NO
Clean­
ups
Acid
NO
Florisil
NO
Florisil
NO
Florisil
NO
Florisil
NO
Sulfur
NO
Sulfur
NO
Sulfur
NO
Sulfur
NO
Replicate
1
0.13
Replicate
1
0.075
Replicate
1
0.116
Replicate
1
0.147
Results
2
0.14
Results
2
0.072
Results
2
0.115
Results
2
0.15
ug/
L
3
0.147
ug/
L
3
0.082
ug/
L
3
0.123
ug/
L
3
0.147
4
0.144
4
0.078
4
0.118
4
0.147
5
0.144
5
0.082
5
0.122
5
0.173
Lab
Identifier
Lab
Identifier
PCB
Interlaboratory
Study
Initial
Information
Sheet
Submit
to
John
Phillips
at
"
jphill12@
ford.
com"

Page
1
of
4
Attachment
2.3E
6
0.149
6
0.081
6
0.14
6
0.152
7
0.14
7
0.085
7
0.122
7
0.151
8
8
8
8
9
9
9
9
10
10
10
10
C
GC­
1
Most
Recent
MDL
Date
11/
17/
2000
Date
Date
Date
Aroclor
1221
Aroclor
Aroclor
Aroclor
Spike
(
ug/
L)
0.1
Spike
(
ug/
L)
Spike
(
ug/
L)
Spike
(
ug/
L)
Result
(
ug/
L)
0.012
Result
(
ug/
L)
Result
(
ug/
L)
Result
(
ug/
L)
Clean­
ups
Acid
NO
Clean­
ups
Acid
Clean­
ups
Acid
Clean­
ups
Acid
Florisil
NO
Florisil
Florisil
Florisil
Sulfur
NO
Sulfur
Sulfur
Sulfur
Replicate
1
0.13
Replicate
1
Replicate
1
Replicate
1
Results
2
0.134
Results
2
Results
2
Results
2
ug/
L
3
0.123
ug/
L
3
ug/
L
3
ug/
L
3
4
0.134
4
4
4
5
0.127
5
5
5
6
0.133
6
6
6
7
0.129
7
7
7
8
8
8
8
9
9
9
9
10
10
10
10
D
Most
Recent
MDL
Date
Date
Date
Date
Aroclor
Aroclor
Aroclor
Aroclor
Spike
(
ug/
L)
Spike
(
ug/
L)
Spike
(
ug/
L)
Spike
(
ug/
L)
Result
(
ug/
L)
Result
(
ug/
L)
Result
(
ug/
L)
Result
(
ug/
L)
Clean­
ups
Acid
Clean­
ups
Acid
Clean­
ups
Acid
Clean­
ups
Acid
Florisil
Florisil
Florisil
Florisil
Sulfur
Sulfur
Sulfur
Sulfur
Replicate
1
Replicate
1
Replicate
1
Replicate
1
Results
2
Results
2
Results
2
Results
2
ug/
L
3
ug/
L
3
ug/
L
3
ug/
L
3
4
4
4
4
5
5
5
5
6
6
6
6
7
7
7
7
Lab
Identifier
Lab
Identifier
Page
2
of
4
Attachment
2.3E
8
8
8
8
9
9
9
9
10
10
10
10
3
Analyst
Identification
A
JE
JE
JT
B
KM
JT
C
JT
D
SS
E
F
4
Tetrachloro­
m­
xylene
Decachlorobiphenyl
5
Lower
0.1
Upper
4
6
Acid
yes
Florisil
yes
Sulfur
not
routine
7
PCB
Aroclor
Identification
Describe
Your
Identification
Process
All
major
congeners(
atleast
the
5­
8
largest
peaks
that
are
>
10%
of
biggest
peak)
must
be
present
in
sample
within
RT
window
for
that
congener
peak
(
default
0.05min
RT).
The
ratios
of
the
peaks
to
one
another
can
vary
within
reason
to
account
for
weathering,
but
not
to
the
point
that
the
pattern
begins
to
resemble
another
aroclor
ofr
a
non­
aroclor.
If
non­
target
peaks
or
a
raised
baseline
interfere
than
further
cleanup
of
extract
using
acid/
florisil
or
sulfur
in
necessary
prior
to
quantitation.
8
PCB
Quantification
Describe
Your
Quantification
Process
The
five
largest
peaks
(
minimum
3)
of
the
identified
aroclor,
that
do
not
have
interferences
present,
are
quantitated
individually.
These
five
results
are
then
averaged
to
determine
total
ng
of
PCB
per
ml
of
extract.
This
raw
value
(
final
instrument
value)
is
enetered
into
the
Omega
LIMS
system
and
the
prep
data,
dilutions,
cleanup
data,
and
other
applicable
data
are
factored
together
automatically
and
calculated
to
produce
the
final
result.
Clean­
up
Analyst
Lab
Identifier
Clean­
up
Method
GC
Analyst
Lab
Identifier
Calibration
Range
in
ug/
L
Surrogates
Used
Extraction
Analyst
Lab
Identifier
Page
3
of
4
Attachment
2.3E
9
Start­
Up
Demonstration
Test
Results
for
Capillary
Column
Modification
The
Following
Results
should
be
for
four
replicates
at
50
ug/
L
Before
After
Aroclor
1016
s
in
ug/
L
na
0.68
Mean
41.65
%
Recv.
83.3
Aroclor
1221
s
in
ug/
L
na
0.6
Mean
54.25
%
Recv.
108.5
Aroclor
1232
s
in
ug/
L
na
0.922
Mean
57.2
%
Recv.
114
Aroclor
1242
s
in
ug/
L
na
1.33
Mean
58.8
%
Recv.
118
Aroclor
1248
s
in
ug/
L
na
0.984
Mean
41.65
%
Recv.
83.3
Aroclor
1254
s
in
ug/
L
na
0.856
Mean
56.05
%
Recv.
112.1
Aroclor
1260
s
in
ug/
L
na
1.24
Mean
50.3
%
Recv.
100.6
Page
4
of
4
Attachment
2.3F
Lab
F
1
Do
you
perform
cleanups
on
your
PE
Samples?
Yes
2
Instruments
Used
for
Method
608
A
158
Most
Recent
MDL
Date
01/
19/
00
Date
01/
19/
00
Date
01/
21/
00
Date
01/
21/
00
Date
01/
12/
00
Date
01/
19/
00
Date
01/
19/
00
Aroclor
1016
Aroclor
1260
Aroclor
1232
Aroclor
1242
Aroclor
1248
Aroclor
1221
Aroclor
1254
Spike
(
ug/
L)
0.100
Spike
(
ug/
L)
0.1
Spike
(
ug/
L)
0.100
Spike
(
ug/
L)
0.100
Spike
(
ug/
L)
0.100
Spike
(
ug/
L)
0.100
Spike
(
ug/
L)
0.100
Result
(
ug/
L)
0.053
Result
(
ug/
L)
0.046
Result
(
ug/
L)
0.032
Result
(
ug/
L)
0.035
Result
(
ug/
L)
0.041
Result
(
ug/
L)
0.057
Result
(
ug/
L)
0.059
Clean­
ups
Acid
YES
Clean­
ups
Acid
YES
Clean­
ups
Acid
YES
Clean­
ups
Acid
YES
Clean­
ups
Acid
YES
Clean­
ups
Acid
YES
Clean­
ups
Acid
YES
Florisil
NO
Florisil
NO
Florisil
NO
Florisil
NO
Florisil
NO
Florisil
NO
Florisil
NO
Sulfur
YES
Sulfur
YES
Sulfur
YES
Sulfur
YES
Sulfur
YES
Sulfur
YES
Sulfur
YES
Replicate
1
0.130
Replicate
1
0.125
Replicate
1
0.137
Replicate
1
0.101
Replicate
1
0.096
Replicate
1
0.123
Replicate
1
0.097
Results
2
0.124
Results
2
0.126
Results
2
0.122
Results
2
0.112
Results
2
0.099
Results
2
0.141
Results
2
0.114
ug/
L
3
0.115
ug/
L
3
0.135
ug/
L
3
0.138
ug/
L
3
0.130
ug/
L
3
0.132
ug/
L
3
0.112
ug/
L
3
0.114
4
0.164
4
0.165
4
0.147
4
0.105
4
0.100
4
0.153
4
0.158
5
0.127
5
0.138
5
0.121
5
0.110
5
0.095
5
0.106
5
0.119
6
0.119
6
0.123
6
0.141
6
0.105
6
0.104
6
0.110
6
0.122
7
0.117
7
0.131
7
0.143
7
0.094
7
0.112
7
0.110
7
0.123
8
8
8
8
8
8
8
9
9
9
9
9
9
9
10
10
10
10
10
10
10
B
174
Most
Recent
MDL
Date
10/
12/
99
Date
10/
12/
99
Date
10/
28/
99
Date
10/
28/
99
Date
10/
28/
99
Date
10/
29/
99
Date
10/
29/
99
Aroclor
1016
Aroclor
1260
Aroclor
1232
Aroclor
1242
Aroclor
1248
Aroclor
1221
Aroclor
1254
Spike
(
ug/
L)
0.100
Spike
(
ug/
L)
0.100
Spike
(
ug/
L)
0.100
Spike
(
ug/
L)
0.100
Spike
(
ug/
L)
0.100
Spike
(
ug/
L)
0.100
Spike
(
ug/
L)
0.100
Result
(
ug/
L)
0.047
Result
(
ug/
L)
0.059
Result
(
ug/
L)
0.068
Result
(
ug/
L)
0.027
Result
(
ug/
L)
0.038
Result
(
ug/
L)
0.060
Result
(
ug/
L)
0.043
Clean­
ups
Acid
YES
Clean­
ups
Acid
YES
Clean­
ups
Acid
YES
Clean­
ups
Acid
YES
Clean­
ups
Acid
YES
Clean­
ups
Acid
YES
Clean­
ups
Acid
YES
Florisil
NO
Florisil
NO
Florisil
NO
Florisil
NO
Florisil
NO
Florisil
NO
Florisil
NO
Sulfur
YES
Sulfur
YES
Sulfur
YES
Sulfur
YES
Sulfur
YES
Sulfur
YES
Sulfur
YES
Replicate
1
0.043
Replicate
1
0.028
Replicate
1
0.161
Replicate
1
0.134
Replicate
1
0.129
Replicate
1
0.109
Replicate
1
0.109
Results
2
0.070
Results
2
0.049
Results
2
0.133
Results
2
0.126
Results
2
0.137
Results
2
0.112
Results
2
0.090
ug/
L
3
0.059
ug/
L
3
0.044
ug/
L
3
0.123
ug/
L
3
0.148
ug/
L
3
0.147
ug/
L
3
0.090
ug/
L
3
0.072
4
0.079
4
0.066
4
0.119
4
0.124
4
0.120
4
0.108
4
0.074
5
0.070
5
0.067
5
0.133
5
0.122
5
0.132
5
0.109
5
0.091
6
0.080
6
0.076
6
0.179
6
0.127
6
0.126
6
0.116
6
0.099
7
0.087
7
0.080
7
0.133
7
0.133
7
0.154
7
0.153
7
0.098
8
8
8
8
8
8
8
9
9
9
9
9
9
9
10
10
10
10
10
10
10
C
Most
Recent
MDL
Date
Date
Date
Date
Aroclor
Aroclor
Aroclor
Aroclor
Spike
(
ug/
L)
Spike
(
ug/
L)
Spike
(
ug/
L)
Spike
(
ug/
L)
Result
(
ug/
L)
Result
(
ug/
L)
Result
(
ug/
L)
Result
(
ug/
L)
Clean­
ups
Acid
Clean­
ups
Acid
Clean­
ups
Acid
Clean­
ups
Acid
Florisil
Florisil
Florisil
Florisil
Sulfur
Sulfur
Sulfur
Sulfur
Replicate
1
Replicate
1
Replicate
1
Replicate
1
Results
2
Results
2
Results
2
Results
2
ug/
L
3
ug/
L
3
ug/
L
3
ug/
L
3
4
4
4
4
5
5
5
5
6
6
6
6
7
7
7
7
PCB
Interlaboratory
Study
Initial
Information
Sheet
Submit
to
John
Phillips
at
"
jphill12@
ford.
com"

Lab
Identifier
Lab
Identifier
Lab
Identifier
Page
1
of
3
Attachment
2.3F
8
8
8
8
9
9
9
9
10
10
10
10
D
Most
Recent
MDL
Date
Date
Date
Date
Aroclor
Aroclor
Aroclor
Aroclor
Spike
(
ug/
L)
Spike
(
ug/
L)
Spike
(
ug/
L)
Spike
(
ug/
L)
Result
(
ug/
L)
Result
(
ug/
L)
Result
(
ug/
L)
Result
(
ug/
L)
Clean­
ups
Acid
Clean­
ups
Acid
Clean­
ups
Acid
Clean­
ups
Acid
Florisil
Florisil
Florisil
Florisil
Sulfur
Sulfur
Sulfur
Sulfur
Replicate
1
Replicate
1
Replicate
1
Replicate
1
Results
2
Results
2
Results
2
Results
2
ug/
L
3
ug/
L
3
ug/
L
3
ug/
L
3
4
4
4
4
5
5
5
5
6
6
6
6
7
7
7
7
8
8
8
8
9
9
9
9
10
10
10
10
3
Analyst
Identification
A
DJM
JDM
JDM
B
MCP
DJM
DLV
C
JRG
MCP
D
CMG
JRG
E
CMG
F
4
TCMX
DCB
5
Lower
0.005
Upper
1.6
6
Acid
3665A
Florisil
3620B
Sulfur
3660B
Silica
3630C
7
PCB
Aroclor
Identification
Describe
Your
Identification
Process
Pattern
recognition
is
used
for
identification,
with
great
detail
paid
to
congener
ratios
in
the
samples
compared
to
the
corresponding
standard.
Peak
overlaying
software
(
Turbochrom)
is
also
used
as
an
additional
tool
for
identification.
If
necessary,
second
column
confirmation
and
identification
will
also
be
used.

8
PCB
Quantification
Describe
Your
Quantification
Process
Typically,
five
congener
peaks
are
used
for
each
Aroclor.
When
a
mixture
of
Aroclors
is
present,
a
minimum
of
three
peaks
are
used
that
are
distinct
to
each
Aroclor.
In
addition,
the
peaks
selected
for
quantitation
must
be
in
the
correct
ratios,
within
25%
of
that
in
the
corresponding
standards.
If
the
routinely
used
congeners
have
inappropriate
ratios,
alternative
congers
will
be
used.

9
Start­
Up
Demonstration
Test
Results
for
Capillary
Column
Modification
Clean­
up
Method
GC
Analyst
Lab
Identifier
Calibration
Range
in
ug/
L
Surrogates
Used
Extraction
Analyst
Lab
Identifier
Clean­
up
Analyst
Lab
Identifier
Lab
Identifier
Page
2
of
3
Attachment
2.3F
The
Following
Results
should
be
for
four
replicates
at
50
ug/
L
Before
After
Aroclor
1016
s
in
ug/
L
Mean
%
Recv.

Aroclor
1221
s
in
ug/
L
Mean
%
Recv.

Aroclor
1232
s
in
ug/
L
Mean
%
Recv.

Aroclor
1242
s
in
ug/
L
Mean
%
Recv.

Aroclor
1248
s
in
ug/
L
Mean
%
Recv.

Aroclor
1254
s
in
ug/
L
Mean
%
Recv.

Aroclor
1260
s
in
ug/
L
Mean
%
Recv.

Page
3
of
3
Attachment
2.3G
Lab
G
1
Do
you
perform
cleanups
on
your
PE
Samples?
Yes
2
Instruments
Used
for
Method
608
A
Varian
3500/
DB­
5
Most
Recent
MDL
Date
1/
19/
00
Date
9/
14/
99
Date
9/
30/
99
Aroclor
1016
Aroclor
1221
Aroclor
1232
Spike
(
m
g/
L)
0.10
Spike
(
m
g/
L)
0.50
Spike
(
m
g/
L)
0.50
MDL
Result
(
m
g/
L)
0.0084
MDL
Result
(
m
g/
L)
0.0264
MDL
Result
(
m
g/
L)
0.0597
Clean­
ups
Acid
Yes
Clean­
ups
Acid
Yes
Clean­
ups
Acid
Yes
Florisil
No
Florisil
No
Florisil
No
Sulfur
Yes
Sulfur
Yes
Sulfur
Yes
Replicate
1
0.128
Replicate
1
0.553
Replicate
1
0.565
Results
2
0.126
Results
2
0.558
Results
2
0.536
m
g/
L
3
0.129
m
g/
L
3
0.558
m
g/
L
3
0.592
4
0.127
4
0.557
4
0.578
5
0.124
5
0.544
5
0.596
6
0.121
6
0.568
6
0.574
7
0.126
7
0.568
7
0.596
8
8
8
0.577
9
9
9
10
10
10
<
x>
(
m
g/
L)
0.126
<
x>
(
m
g/
L)
0.558
<
x>
(
m
g/
L)
0.577
s
(
m
g/
L)
0.00267
s
(
m
g/
L)
0.00839
s
(
m
g/
L)
0.01993
n
7
n
7
n
8
t­
value
3.142
t­
value
3.142
t­
value
2.997
Date
1/
19/
00
Date
1/
19/
00
Date
1/
17/
00
Aroclor
1242
Aroclor
1248
Aroclor
1254
PCB
Interlaboratory
Study
Initial
Information
Sheet
Submit
to
John
Phillips
at
"
jphill12@
ford.
com"

Lab
Identifier
Page
1
of
4
Attachment
2.3G
Spike
(
m
g/
L)
0.10
Spike
(
m
g/
L)
0.10
Spike
(
m
g/
L)
0.10
MDL
Result
(
m
g/
L)
0.0310
MDL
Result
(
m
g/
L)
0.0151
MDL
Result
(
m
g/
L)
0.0114
Clean­
ups
Acid
Yes
Clean­
ups
Acid
Yes
Clean­
ups
Acid
Yes
Florisil
No
Florisil
No
Florisil
No
Sulfur
Yes
Sulfur
Yes
Sulfur
Yes
Replicate
1
0.147
Replicate
1
0.110
Replicate
1
0.139
Results
2
0.147
Results
2
0.103
Results
2
0.137
m
g/
L
3
0.130
m
g/
L
3
0.102
m
g/
L
3
0.140
4
0.126
4
0.111
4
0.138
5
0.151
5
0.110
5
0.131
6
0.135
6
0.100
6
0.140
7
0.132
7
0.111
7
8
8
8
9
9
9
10
10
10
<
x>
(
m
g/
L)
0.138
<
x>
(
m
g/
L)
0.107
<
x>
(
m
g/
L)
0.138
s
(
m
g/
L)
0.00986
s
(
m
g/
L)
0.00482
s
(
m
g/
L)
0.00339
n
7
n
7
n
6
t­
value
3.142
t­
value
3.142
t­
value
3.364
Date
1/
19/
00
Date
1/
19/
00
Aroclor
1260
Aroclor
1016/
1260
Spike
(
m
g/
L)
0.10
Spike
(
m
g/
L)
0.10
MDL
Result
(
m
g/
L)
0.0227
MDL
Result
(
m
g/
L)
0.0216
Clean­
ups
Acid
Yes
Clean­
ups
Acid
Yes
Florisil
No
Florisil
No
Sulfur
Yes
Sulfur
Yes
Replicate
1
0.092
Replicate
1
0.141
Results
2
0.089
Results
2
0.144
m
g/
L
3
0.086
m
g/
L
3
0.139
4
0.082
4
0.133
5
0.080
5
0.132
6
0.073
6
0.124
7
0.074
7
0.131
Page
2
of
4
Attachment
2.3G
8
8
9
9
10
10
<
x>
(
m
g/
L)
0.082
<
x>
(
m
g/
L)
0.135
s
(
m
g/
L)
0.00723
s
(
m
g/
L)
0.00687
n
7
n
7
t­
value
3.142
t­
value
3.142
3
Analyst
Identification
A
JoB
JoB
JaB
B
JaB
C
D
E
F
4
TCX
DCBP
5
Lower
0.1
Upper
1.0
6
Acid
3665A
Florisil
Sulfur
3660B
7
PCB
Aroclor
Identification
Describe
Your
Identification
Process
Aroclors
are
identified
based
upon
a
matching
of
3­
5
reference
peaks
in
RT
window
corresponding
with
the
same
peaks
in
the
calibration
runs.
A
quantitative
measure
of
the
pattern
match
is
given
by
the
%
RSD
GC
Analyst
Lab
Identifier
Extraction
Analyst
Lab
Identifier
Clean­
up
Analyst
Lab
Identifier
Clean­
up
Method
Calibration
Range
in
m
g/
L
Surrogates
Used
Page
3
of
4
Attachment
2.3G
of
the
results
for
the
total
Aroclor
concentration,
as
determined
by
each
of
the
reference
peaks.

8
PCB
Quantification
Describe
Your
Quantification
Process
Each
of
the
reference
peaks
used
for
identification
is
calibrated
from
standard
data
relative
to
the
total
Aroclor
concentration.
The
equivalent
Aroclor
concentration
is
computed
for
each
reference
peak
and
the
mean
is
determined.

9
Start­
Up
Demonstration
Test
Results
for
Capillary
Column
Modification
The
following
results
are
for
27
blank
matrix
spike
analyses
of
a
1016/
1260
mixture
spiked
into
one
liter
of
laboratory
water
Before
Aroclor
1016/
1260
s
in
ug/
L
0.047
Mean
0.437
%
Recv.
87.4%
%
RSD
9.4%
Spike
(
m
g/
L)
0.50
n
27
Page
4
of
4
Attachment
2.3H
Lab
H
1
Do
you
perform
cleanups
on
your
PE
Samples?
No
2
Instruments
Used
for
Method
608
A
LSC
Most
Recent
MDL
Date
2/
23/
00
Date
1/
26/
00
Date
2/
16/
00
Date
11/
20/
00
Date
11/
20/
00
Aroclor
1016
Aroclor
1232
Aroclor
1242
Aroclor
1248
Aroclor
1260
Spike
(
ug/
L)
0.1
Spike
(
ug/
L)
0.1
Spike
(
ug/
L)
0.1
Spike
(
ug/
L)
0.1
Spike
(
ug/
L)
0.1
Result
(
ug/
L)
0.013
Result
(
ug/
L)
0.027
Result
(
ug/
L)
0.066
Result
(
ug/
L)
0.028
Result
(
ug/
L)
0.037
Clean­
ups
Acid
NA
Clean­
ups
Acid
NA
Clean­
ups
Acid
NA
Clean­
ups
Acid
NA
Clean­
ups
Acid
NA
Florisil
NA
Florisil
NA
Florisil
NA
Florisil
NA
Florisil
NA
Sulfur
NA
Sulfur
NA
Sulfur
NA
Sulfur
NA
Sulfur
NA
Replicate
1
0.089
Replicate
1
0.181
Replicate
1
0.164
Replicate
1
0.111
Replicate
1
0.136
Results
2
0.099
Results
2
0.185
Results
2
0.189
Results
2
0.113
Results
2
0.106
ug/
L
3
0.089
ug/
L
3
0.199
ug/
L
3
0.196
ug/
L
3
0.107
ug/
L
3
0.104
4
0.095
4
0.197
4
0.163
4
0.128
4
0.122
5
0.092
5
0.192
5
0.187
5
0.115
5
0.12
6
0.093
6
0.177
6
0.138
6
0.099
6
0.128
7
0.087
7
0.18
7
0.157
7
0.11
7
0.13
8
8
8
8
8
9
9
9
9
9
10
10
10
10
10
B
LSD
Most
Recent
MDL
Date
2/
23/
00
Date
11/
20/
00
Date
1/
7/
00
Date
11/
20/
00
Date
Aroclor
1016
Aroclor
1248
Aroclor
1254
Aroclor
1260
Aroclor
Spike
(
ug/
L)
0.1
Spike
(
ug/
L)
0.1
Spike
(
ug/
L)
0.1
Spike
(
ug/
L)
0.1
Spike
(
ug/
L)
Result
(
ug/
L)
0.029
Result
(
ug/
L)
0.093
Result
(
ug/
L)
0.097
Result
(
ug/
L)
0.055
Result
(
ug/
L)
Clean­
ups
Acid
NA
Clean­
ups
Acid
NA
Clean­
ups
Acid
NA
Clean­
ups
Acid
NA
Clean­
ups
Acid
Florisil
NA
Florisil
NA
Florisil
NA
Florisil
NA
Florisil
Sulfur
NA
Sulfur
NA
Sulfur
NA
Sulfur
NA
Sulfur
Replicate
1
0.079
Replicate
1
0.157
Replicate
1
0.125
Replicate
1
0.069
Replicate
1
Results
2
0.093
Results
2
0.073
Results
2
0.097
Results
2
0.067
Results
2
ug/
L
3
0.092
ug/
L
3
0.087
ug/
L
3
0.159
ug/
L
3
0.091
ug/
L
3
4
0.079
4
0.096
4
0.156
4
0.089
4
5
0.106
5
0.109
5
0.134
5
0.077
5
6
0.091
6
0.082
6
0.082
6
0.115
6
7
0.092
7
0.073
7
0.094
7
0.101
7
8
8
8
8
8
9
9
9
9
9
10
10
10
10
10
C
Most
Recent
MDL
Date
Date
Date
Date
Date
Date
Date
Aroclor
Aroclor
Aroclor
Aroclor
Aroclor
Aroclor
Aroclor
Spike
(
ug/
L)
Spike
(
ug/
L)
Spike
(
ug/
L)
Spike
(
ug/
L)
Spike
(
ug/
L)
Spike
(
ug/
L)
Spike
(
ug/
L)
Result
(
ug/
L)
Result
(
ug/
L)
Result
(
ug/
L)
Result
(
ug/
L)
Result
(
ug/
L)
Result
(
ug/
L)
Result
(
ug/
L)
Clean­
ups
Acid
Clean­
ups
Acid
Clean­
ups
Acid
Clean­
ups
Acid
Clean­
ups
Acid
Clean­
ups
Acid
Clean­
ups
Acid
Florisil
Florisil
Florisil
Florisil
Florisil
Florisil
Florisil
Sulfur
Sulfur
Sulfur
Sulfur
Sulfur
Sulfur
Sulfur
Replicate
1
Replicate
1
Replicate
1
Replicate
1
Replicate
1
Replicate
1
Replicate
1
Results
2
Results
2
Results
2
Results
2
Results
2
Results
2
Results
2
ug/
L
3
ug/
L
3
ug/
L
3
ug/
L
3
ug/
L
3
ug/
L
3
ug/
L
3
4
4
4
4
4
4
4
5
5
5
5
5
5
5
6
6
6
6
6
6
6
7
7
7
7
7
7
7
8
8
8
8
8
8
8
9
9
9
9
9
9
9
10
10
10
10
10
10
10
D
Most
Recent
MDL
Date
Date
Date
Date
Date
Date
Date
Lab
Identifier
Lab
Identifier
Lab
Identifier
Lab
Identifier
PCB
Interlaboratory
Study
Initial
Information
Sheet
Submit
to
John
Phillips
at
"
jphill12@
ford.
com"

Page
1
of
3
Attachment
2.3H
Aroclor
Aroclor
Aroclor
Aroclor
Aroclor
Aroclor
Aroclor
Spike
(
ug/
L)
Spike
(
ug/
L)
Spike
(
ug/
L)
Spike
(
ug/
L)
Spike
(
ug/
L)
Spike
(
ug/
L)
Spike
(
ug/
L)
Result
(
ug/
L)
Result
(
ug/
L)
Result
(
ug/
L)
Result
(
ug/
L)
Result
(
ug/
L)
Result
(
ug/
L)
Result
(
ug/
L)
Clean­
ups
Acid
Clean­
ups
Acid
Clean­
ups
Acid
Clean­
ups
Acid
Clean­
ups
Acid
Clean­
ups
Acid
Clean­
ups
Acid
Florisil
Florisil
Florisil
Florisil
Florisil
Florisil
Florisil
Sulfur
Sulfur
Sulfur
Sulfur
Sulfur
Sulfur
Sulfur
Replicate
1
Replicate
1
Replicate
1
Replicate
1
Replicate
1
Replicate
1
Replicate
1
Results
2
Results
2
Results
2
Results
2
Results
2
Results
2
Results
2
ug/
L
3
ug/
L
3
ug/
L
3
ug/
L
3
ug/
L
3
ug/
L
3
ug/
L
3
4
4
4
4
4
4
4
5
5
5
5
5
5
5
6
6
6
6
6
6
6
7
7
7
7
7
7
7
8
8
8
8
8
8
8
9
9
9
9
9
9
9
10
10
10
10
10
10
10
3
Analyst
Identification
A
LW
LW
TMJ
B
JAW
JAW
DDC
C
D
E
F
4
tetrachloro­
m­
xylene
decachlorobiphenyl
5
Lower
0.1
Upper
8
6
Acid
SW846­
3665
Florisil
SW846­
3620B
­
SPE
Sulfur
SW846­
3660
7
PCB
Aroclor
Identification
Describe
Your
Identification
Process
The
quantitation
of
PCB
residues
as
Aroclors
is
accomplished
by
comparison
of
the
sample
chromatogram
to
that
of
the
most
similar
Aroclor
standard.
This
comparison
is
made
utilizing
retention
times,
peak
ratios,
and
the
overall
Aroclor
pattern.

8
PCB
Quantification
Describe
Your
Quantification
Process
For
any
Aroclor,
3
to
5
well
resolved
peaks
which
are
at
least
25%
the
height
of
the
largest
peak
for
that
Aroclor
are
selected.
When
possible,
peaks
unique
to
that
Aroclor
are
included.
The
characteristic
Aroclor
peaks
are
summed
to
calculate
the
calibration
factor.

9
Start­
Up
Demonstration
Test
Results
for
Capillary
Column
Modification
The
Following
Results
should
be
for
four
replicates
at
50
ug/
L
Before
After
Aroclor
1016
s
in
ug/
L
Mean
%
Recv.

Aroclor
1232
s
in
ug/
L
Mean
%
Recv.

Aroclor
1242
s
in
ug/
L
Mean
Clean­
up
Analyst
Lab
Identifier
Clean­
up
Method
GC
Analyst
Lab
Identifier
Calibration
Range
in
ug/
L
Surrogates
Used
Extraction
Analyst
Lab
Identifier
Page
2
of
3
Attachment
2.3H
%
Recv.

Aroclor
1248
s
in
ug/
L
0.07
Mean
0.83
*
%
Recv.
83%

Aroclor
1254
s
in
ug/
L
Mean
%
Recv.

Aroclor
1260
s
in
ug/
L
Mean
%
Recv.

*
Capillary
samples
spike
at
1.0
µ
g/
L.

Page
3
of
3
Attachment
2.3I
Lab
I
1
Do
you
perform
cleanups
on
your
PE
Samples?
Y
2
Instruments
Used
for
Method
608
Varian
GC
3400
w/
dual
ECD's
A
Lab
Identifier
7
Most
Recent
MDL
Date
1/
20/
00
Date
12/
29/
99
Date
9/
3/
99
Date
1/
4/
00
Aroclor
1016
Aroclor
1221
Aroclor
1232
Aroclor
1242
Spike
(
ug/
L)
0.3
Spike
(
ug/
L)
0.3
Spike
(
ug/
L)
0.3
Spike
(
ug/
L)
0.3
Result
(
ug/
L)
0.054
Result
(
ug/
L)
0.054
Result
(
ug/
L)
0.055
Result
(
ug/
L)
0.034
Clean­
ups
Acid
X
Clean­
ups
Acid
X
Clean­
ups
Acid
X
Clean­
ups
Acid
X
Florisil
Florisil
Florisil
Florisil
Sulfur
Sulfur
Sulfur
Sulfur
X
Replicate
1
0.314
Replicate
1
0.29
Replicate
01/
01/
00
0.434
Replicate
1
0.3
Results
2
0.276
Results
2
0.242
Results
01/
02/
00
0.338
Results
2
0.28
ug/
L
3
0.254
ug/
L
3
0.246
ug/
L
01/
03/
00
0.352
ug/
L
3
0.296
4
0.278
4
0.248
01/
04/
00
0.336
4
0.282
5
0.262
5
0.234
01/
05/
00
0.316
5
0.298
6
0.27
6
0.264
01/
06/
00
0.312
6
0.296
7
0.286
7
0.27
01/
07/
00
0.358
7
0.284
8
0.28
8
0.258
01/
08/
00
0.354
8
0.314
9
9
01/
09/
00
9
10
10
01/
10/
00
10
B
Lab
Identifier
7
Most
Recent
MDL
Date
9/
16/
99
Date
2/
2/
00
Date
11/
3/
99
Date
Aroclor
1248
Aroclor
1254
Aroclor
1260
Aroclor
Spike
(
ug/
L)
0.3
Spike
(
ug/
L)
0.3
Spike
(
ug/
L)
0.3
Spike
(
ug/
L)
Result
(
ug/
L)
0.061
Result
(
ug/
L)
0.054
Result
(
ug/
L)
0.06
Result
(
ug/
L)
Clean­
ups
Acid
X
Clean­
ups
Acid
X
Clean­
ups
Acid
X
Clean­
ups
Acid
Florisil
Florisil
Florisil
Florisil
Sulfur
Sulfur
Sulfur
Sulfur
Replicate
1
0.292
Replicate
1
0.22
Replicate
1
0.21
Replicate
1
Results
2
0.268
Results
2
0.24
Results
2
0.248
Results
2
ug/
L
3
0.278
ug/
L
3
0.272
ug/
L
3
0.21
ug/
L
3
4
0.262
4
0.256
4
0.254
4
5
0.242
5
0.256
5
0.238
5
6
0.268
6
0.254
6
0.26
6
PCB
Interlaboratory
Study
Initial
Information
Sheet
Submit
to
John
Phillips
at
"
jphill12@
ford.
com"

Page
1
of
4
Attachment
2.3I
7
0.308
7
0.224
7
0.258
7
8
0.262
8
0.258
8
0.234
8
9
9
9
9
10
10
10
10
C
Lab
Identifier
Most
Recent
MDL
Date
Date
Date
Date
Aroclor
Aroclor
Aroclor
Aroclor
Spike
(
ug/
L)
Spike
(
ug/
L)
Spike
(
ug/
L)
Spike
(
ug/
L)
Result
(
ug/
L)
Result
(
ug/
L)
Result
(
ug/
L)
Result
(
ug/
L)
Clean­
ups
Acid
Clean­
ups
Acid
Clean­
ups
Acid
Clean­
ups
Acid
Florisil
Florisil
Florisil
Florisil
Sulfur
Sulfur
Sulfur
Sulfur
Replicate
1
Replicate
1
Replicate
01/
01/
00
Replicate
1
Results
2
Results
2
Results
01/
02/
00
Results
2
ug/
L
3
ug/
L
3
ug/
L
01/
03/
00
ug/
L
3
4
4
01/
04/
00
4
5
5
01/
05/
00
5
6
6
01/
06/
00
6
7
7
01/
07/
00
7
8
8
01/
08/
00
8
9
9
01/
09/
00
9
10
10
01/
10/
00
10
D
Lab
Identifier
Most
Recent
MDL
Date
Date
Date
Date
Aroclor
Aroclor
Aroclor
Aroclor
Spike
(
ug/
L)
Spike
(
ug/
L)
Spike
(
ug/
L)
Spike
(
ug/
L)
Result
(
ug/
L)
Result
(
ug/
L)
Result
(
ug/
L)
Result
(
ug/
L)
Clean­
ups
Acid
Clean­
ups
Acid
Clean­
ups
Acid
Clean­
ups
Acid
Florisil
Florisil
Florisil
Florisil
Sulfur
Sulfur
Sulfur
Sulfur
Replicate
1
Replicate
1
Replicate
01/
01/
00
Replicate
1
Results
2
Results
2
Results
01/
02/
00
Results
2
ug/
L
3
ug/
L
3
ug/
L
01/
03/
00
ug/
L
3
4
4
01/
04/
00
4
5
5
01/
05/
00
5
6
6
01/
06/
00
6
7
7
01/
07/
00
7
8
8
01/
08/
00
8
9
9
01/
09/
00
9
10
10
01/
10/
00
10
Page
2
of
4
Attachment
2.3I
3
Analyst
Identification
Extraction
Analyst
Clean­
up
Analyst
GC
Analyst
Lab
Identifier
Lab
Identifier
Lab
Identifier
A
CKV
CKV
CKV
B
JG
JG
JG
C
NS
NS
NS
D
MG
MG
MG
E
KM
KM
KM
F
4
Surrogates
Used
tetrachloro­
m­
xylene
decachlorobiphenyl
5
Calibration
Range
Lower
0.04
in
ug/
L
Upper
1
6
Clean­
up
Method
Acid
3665
Florisil
Sulfur
3660
7
PCB
Aroclor
Identification
Describe
Your
Identification
Process
The
process
of
qualitation
is
performed
by
analyzing
each
of
the
known
PCB
Arochlor
standards
to
develop
a
known
pattern
for
comparison
analyses
to
the
sample.
The
sample
is
then
identified
using
retention
times
of
significant
peaks
and
pattern
matching
for
comparison
to
the
known
standard.
When
the
screen
is
positive
for
a
PCB
detect
a
full
calibration
curve
is
generated
to
complete
the
identification.

8
PCB
Quantification
Describe
Your
Quantification
Process
5
peaks
are
chosen
and
quantitated
against
the
calibration
curve
for
the
identified
PCB.

9
Start­
Up
Demonstration
Test
Results
for
Capillary
Column
Modification
The
Following
Results
should
be
for
four
replicates
at
50
ug/
L
mg/
L
Before
After
Page
3
of
4
Attachment
2.3I
Aroclor
1016
[
X]
=
0.4
s
in
ug/
L
0.05
Mean
0.332
%
Recv.
83
Aroclor
1221
[
X]
=
2.0
s
in
ug/
L
0.04
Mean
1.83
%
Recv.
91.6
Aroclor
1232
[
X]
=
0.4
s
in
ug/
L
0.02
Mean
0.425
%
Recv.
106.4
Aroclor
1242
[
X]
=
0.4
s
in
ug/
L
0.06
Mean
0.333
%
Recv.
83.13
Aroclor
1248
[
X]
=
1.0
s
in
ug/
L
0.045
Mean
1.11
%
Recv.
111.1
Aroclor
1254
[
X]
=
0.4
s
in
ug/
L
0.03
Mean
0.449
%
Recv.
112.3
Aroclor
1260
[
X]
=
2.0
s
in
ug/
L
0.18
Mean
1.86
%
Recv.
93
Page
4
of
4
Attachment
2.3J
Lab
J
1
Do
you
perform
cleanups
on
your
PE
Samples?
Yes
2
Instruments
Used
for
Method
608
A
GC
#
5
Most
Recent
MDL
Date
7/
5/
00
Date
7/
5/
00
Date
6/
26/
00
Date
6/
26/
00
Date
3/
4/
00
Date
3/
4/
00
Date
6/
26/
00
Aroclor
1221
Aroclor
1254
Aroclor
1016
Aroclor
1232
Aroclor
1242
Aroclor
1260
Aroclor
1248
Spike
(
ug/
L)
0.2
Spike
(
ug/
L)
0.2
Spike
(
ug/
L)
0.2
Spike
(
ug/
L)
0.2
Spike
(
ug/
L)
0.2
Spike
(
ug/
L)
0.2
Spike
(
ug/
L)
0.2
Result
(
ug/
L)
0.1
Result
(
ug/
L)
0.07
Result
(
ug/
L)
0.05
Result
(
ug/
L)
0.07
Result
(
ug/
L)
0.052
Result
(
ug/
L)
0.086
Result
(
ug/
L)
0.1
Clean­
ups
Acid
yes
Clean­
ups
Acid
yes
Clean­
ups
Acid
yes
Clean­
ups
Acid
yes
Clean­
ups
Acid
yes
Clean­
ups
Acid
yes
Clean­
ups
Acid
yes
Florisil
no
Florisil
Florisil
Florisil
Florisil
Florisil
Florisil
Sulfur
no
Sulfur
Sulfur
Sulfur
Sulfur
Sulfur
Sulfur
Replicate
1
0.13
Replicate
1
0.07
Replicate
1
0.17
Replicate
1
0.21
Replicate
1
0.148
Replicate
1
0.252
Replicate
1
0.16
Results
2
0.16
Results
2
0.11
Results
2
0.2
Results
2
0.21
Results
2
0.174
Results
2
0.241
Results
2
0.17
ug/
L
3
0.15
ug/
L
3
0.14
ug/
L
3
0.15
ug/
L
3
0.25
ug/
L
3
0.199
ug/
L
3
0.241
ug/
L
3
0.23
4
0.18
4
0.11
4
0.18
4
0.22
4
0.172
4
0.167
4
0.22
5
0.17
5
0.08
5
0.18
5
0.25
5
0.158
5
0.204
5
0.23
6
0.17
6
0.13
6
0.18
6
0.22
6
0.175
6
0.226
6
0.18
7
0.23
7
0.1
7
0.18
7
0.26
7
0.166
7
0.199
7
0.15
8
0.13
8
0.12
8
0.17
8
0.25
8
0.196
8
0.237
8
0.21
9
9
9
9
9
9
9
10
10
10
10
10
10
10
B
GC
#
6
Most
Recent
MDL
Date
3/
2/
00
Date
3/
2/
00
Date
7/
7/
00
Date
7/
15/
00
Date
7/
13/
00
Date
7/
13/
00
Date
7/
6/
00
Aroclor
1242
Aroclor
1260
Aroclor
1248
Aroclor
1232
Aroclor
1221
Aroclor
1254
Aroclor
1016
Spike
(
ug/
L)
0.2
Spike
(
ug/
L)
0.2
Spike
(
ug/
L)
0.2
Spike
(
ug/
L)
0.2
Spike
(
ug/
L)
0.2
Spike
(
ug/
L)
0.2
Spike
(
ug/
L)
0.2
Result
(
ug/
L)
0.086
Result
(
ug/
L)
0.083
Result
(
ug/
L)
0.058
Result
(
ug/
L)
0.078
Result
(
ug/
L)
0.15
Result
(
ug/
L)
0.098
Result
(
ug/
L)
0.069
Clean­
ups
Acid
yes
Clean­
ups
Acid
yes
Clean­
ups
Acid
yes
Clean­
ups
Acid
yes
Clean­
ups
Acid
yes
Clean­
ups
Acid
yes
Clean­
ups
Acid
yes
Florisil
Florisil
Florisil
Florisil
Florisil
Florisil
Florisil
Sulfur
Sulfur
Sulfur
Sulfur
Sulfur
Sulfur
Sulfur
Replicate
1
0.178
Replicate
1
0.169
Replicate
1
0.259
Replicate
1
0.079
Replicate
1
0.146
Replicate
1
0.221
Replicate
1
0.097
Results
2
0.217
Results
2
0.232
Results
2
0.228
Results
2
0.058
Results
2
0.211
Results
2
0.158
Results
2
0.103
ug/
L
3
0.229
ug/
L
3
0.234
ug/
L
3
0.232
ug/
L
3
0.1
ug/
L
3
0.155
ug/
L
3
0.179
ug/
L
3
0.151
4
0.237
4
0.208
4
0.248
4
0.075
4
0.225
4
0.252
4
0.115
5
0.205
5
0.24
5
0.265
5
0.089
5
0.097
5
0.154
5
0.116
6
0.169
6
0.176
6
0.212
6
0.098
6
0.209
6
0.185
6
0.159
7
0.202
7
0.194
7
0.239
7
0.03
7
0.172
7
0.21
7
0.106
8
0.253
8
0.227
8
8
8
0.096
8
0.195
8
0.107
9
9
9
9
9
9
9
10
10
10
10
10
10
10
C
Most
Recent
MDL
Date
Date
Date
Date
Aroclor
Aroclor
Aroclor
Aroclor
Spike
(
ug/
L)
Spike
(
ug/
L)
Spike
(
ug/
L)
Spike
(
ug/
L)
Result
(
ug/
L)
Result
(
ug/
L)
Result
(
ug/
L)
Result
(
ug/
L)
Clean­
ups
Acid
Clean­
ups
Acid
Clean­
ups
Acid
Clean­
ups
Acid
Florisil
Florisil
Florisil
Florisil
Sulfur
Sulfur
Sulfur
Sulfur
Replicate
1
Replicate
1
Replicate
1
Replicate
1
Results
2
Results
2
Results
2
Results
2
ug/
L
3
ug/
L
3
ug/
L
3
ug/
L
3
4
4
4
4
5
5
5
5
6
6
6
6
7
7
7
7
Lab
Identifier
Lab
Identifier
Lab
Identifier
PCB
Interlaboratory
Study
Initial
Information
Sheet
Submit
to
John
Phillips
at
"
jphill12@
ford.
com"

Page
1
of
3
Attachment
2.3J
8
8
8
8
9
9
9
9
10
10
10
10
D
Most
Recent
MDL
Date
Date
Date
Date
Aroclor
Aroclor
Aroclor
Aroclor
Spike
(
ug/
L)
Spike
(
ug/
L)
Spike
(
ug/
L)
Spike
(
ug/
L)
Result
(
ug/
L)
Result
(
ug/
L)
Result
(
ug/
L)
Result
(
ug/
L)
Clean­
ups
Acid
Clean­
ups
Acid
Clean­
ups
Acid
Clean­
ups
Acid
Florisil
Florisil
Florisil
Florisil
Sulfur
Sulfur
Sulfur
Sulfur
Replicate
1
Replicate
1
Replicate
1
Replicate
1
Results
2
Results
2
Results
2
Results
2
ug/
L
3
ug/
L
3
ug/
L
3
ug/
L
3
4
4
4
4
5
5
5
5
6
6
6
6
7
7
7
7
8
8
8
8
9
9
9
9
10
10
10
10
3
Analyst
Identification
A
MEM
MEM
JC
B
EP
EP
BH
C
RC
RC
MB
D
LC
JC
E
MR
BH
F
MB
MB
MR
4
Tetrachloroxylene
(
TCX)
Dichlorobiphenyl
(
DCBP)

5
Lower
0.2
Upper
2.5­
5
6
Acid
3665*
Florisil
3620*
Using
prepared
Whatman
cartridges
Sulfur
3660*
(
Copper
powder)
*
SW­
846
methods
7
PCB
Aroclor
Identification
Describe
Your
Identification
Process
The
sample
peak
pattern
is
compared
to
the
current
reference
standard(
s)/
CCV
using
a
chromatograph
overlay.
Identification
is
based
on
a
peak­
to­
peak
comparison
of
retention
times
and
relative
peak
ratios.
Comparison
starts
with
the
CCV
(
1242/
1260)
but
will
involve
any
Aroclor
suspected
to
be
present.
Identification
is
verified
by
a
second
qualified
analyst.

8
PCB
Quantification
Describe
Your
Quantification
Process
Quantification
is
based
on
a
average
response
factor
generated
from
a
calibration
curve
of
3
to
6
points
of
the
Aroclor
of
interest.
Alternatively,
a
linear
regression
plot
may
be
used.
Typically,
four
peaks
are
selected
for
quantification
that
are
unique
to
that
Aroclor
when
possible,
have
a
signalto
noise
ratio
of
3+
and
are
adequately
resolved
from
surrounding
peaks.
The
nominal
value
is
equally
divided
among
the
four
peaks
and
the
software
automatically
reports
results
for
the
four.
peaks
and
a
total.
Different
peaks
may
need
to
be
selected
if
the
sample
matrix
interferences.
Clean­
up
Analyst
Lab
Identifier
Lab
Identifier
Clean­
up
Method
GC
Analyst
Lab
Identifier
Calibration
Range
in
ug/
L
Surrogates
Used
Extraction
Analyst
Lab
Identifier
Page
2
of
3
Attachment
2.3J
9
Start­
Up
Demonstration
Test
Results
for
Capillary
Column
Modification
The
Following
Results
should
be
for
four
replicates
at
50
ug/
L
Before
After
Aroclor
1016
s
in
ug/
L
Mean
%
Recv.

Aroclor
1221
s
in
ug/
L
Mean
%
Recv.

Aroclor
1232
s
in
ug/
L
Mean
%
Recv.

Aroclor
1242
s
in
ug/
L
0.16
Mean
3.98
%
Recv.
98.81
Aroclor
1248
s
in
ug/
L
Mean
%
Recv.

Aroclor
1254
s
in
ug/
L
Mean
%
Recv.

Aroclor
1260
s
in
ug/
L
0.19
Mean
4.41
%
Recv.
105
Page
3
of
3
Attachment
2.5
Character
Meaning
LAB
LAB
1
Bottle
0
5
2
Batch
1
6
3
LAB
2
7
3
8
4
9
BATCH
0
BATCH
1
BATCH
2
BATCH
3
BATCH
4
BATCH
5
Sample
Acroclor
Aroclor
Sample
Acroclor
Aroclor
Sample
Acroclor
Aroclor
Sample
Acroclor
Aroclor
Sample
Acroclor
Aroclor
Sample
Acroclor
Aroclor
I.
D.
1016
1260
I.
D.
1016
1260
I.
D.
1016
1260
I.
D.
1016
1260
I.
D.
1016
1260
I.
D.
1016
1260
400
0.005
0.006
411
0.006
0.005
422
0.005
0.006
433
0.006
0.005
444
0.005
0.006
455
0.006
0.005
200
0.010
0.015
211
0.015
0.010
222
0.010
0.015
233
0.015
0.010
244
0.010
0.015
255
0.015
0.010
100
0.025
0.030
111
0.030
0.025
122
0.025
0.030
133
0.030
0.025
144
0.025
0.030
155
0.030
0.025
800
0.050
0.060
811
0.060
0.050
822
0.050
0.060
833
0.060
0.050
844
0.050
0.060
855
0.060
0.050
300
0.100
0.120
311
0.120
0.100
322
0.100
0.120
333
0.120
0.100
344
0.100
0.120
355
0.120
0.100
600
0.200
0.240
611
0.240
0.200
622
0.200
0.240
633
0.240
0.200
644
0.200
0.240
655
0.240
0.200
700
0.500
0.600
711
0.600
0.500
722
0.500
0.600
733
0.600
0.500
744
0.500
0.600
755
0.600
0.500
500
1.000
1.200
511
1.200
1.000
522
1.000
1.200
533
1.200
1.000
544
1.000
1.200
555
1.200
1.000
601
0.005
0.006
612
0.006
0.005
623
0.005
0.006
634
0.006
0.005
645
0.005
0.006
656
0.006
0.005
301
0.010
0.015
312
0.015
0.010
323
0.010
0.015
334
0.015
0.010
345
0.010
0.015
356
0.015
0.010
801
0.025
0.030
812
0.030
0.025
823
0.025
0.030
834
0.030
0.025
845
0.025
0.030
856
0.030
0.025
401
0.050
0.060
412
0.060
0.050
423
0.050
0.060
434
0.060
0.050
445
0.050
0.060
456
0.060
0.050
701
0.100
0.120
712
0.120
0.100
723
0.100
0.120
734
0.120
0.100
745
0.100
0.120
756
0.120
0.100
101
0.200
0.240
112
0.240
0.200
123
0.200
0.240
134
0.240
0.200
145
0.200
0.240
156
0.240
0.200
501
0.500
0.600
512
0.600
0.500
523
0.500
0.600
534
0.600
0.500
545
0.500
0.600
556
0.600
0.500
201
1.000
1.200
212
1.200
1.000
223
1.000
1.200
234
1.200
1.000
245
1.000
1.200
256
1.200
1.000
202
0.005
0.006
213
0.006
0.005
224
0.005
0.006
235
0.006
0.005
246
0.005
0.006
257
0.006
0.005
402
0.010
0.015
413
0.015
0.010
424
0.010
0.015
435
0.015
0.010
446
0.010
0.015
457
0.015
0.010
602
0.025
0.030
613
0.030
0.025
624
0.025
0.030
635
0.030
0.025
646
0.025
0.030
657
0.030
0.025
302
0.050
0.060
313
0.060
0.050
324
0.050
0.060
335
0.060
0.050
346
0.050
0.060
357
0.060
0.050
502
0.100
0.120
513
0.120
0.100
524
0.100
0.120
535
0.120
0.100
546
0.100
0.120
557
0.120
0.100
802
0.200
0.240
813
0.240
0.200
824
0.200
0.240
835
0.240
0.200
846
0.200
0.240
857
0.240
0.200
102
0.500
0.600
113
0.600
0.500
124
0.500
0.600
135
0.600
0.500
146
0.500
0.600
157
0.600
0.500
702
1.000
1.200
713
1.200
1.000
724
1.000
1.200
735
1.200
1.000
746
1.000
1.200
757
1.200
1.000
203
0.005
0.006
214
0.006
0.005
225
0.005
0.006
236
0.006
0.005
247
0.005
0.006
258
0.006
0.005
303
0.010
0.015
314
0.015
0.010
325
0.010
0.015
336
0.015
0.010
347
0.010
0.015
358
0.015
0.010
403
0.025
0.030
414
0.030
0.025
425
0.025
0.030
436
0.030
0.025
447
0.025
0.030
458
0.030
0.025
603
0.050
0.060
614
0.060
0.050
625
0.050
0.060
636
0.060
0.050
647
0.050
0.060
658
0.060
0.050
503
0.100
0.120
514
0.120
0.100
525
0.100
0.120
536
0.120
0.100
547
0.100
0.120
558
0.120
0.100
703
0.200
0.240
714
0.240
0.200
725
0.200
0.240
736
0.240
0.200
747
0.200
0.240
758
0.240
0.200
103
0.500
0.600
114
0.600
0.500
125
0.500
0.600
136
0.600
0.500
147
0.500
0.600
158
0.600
0.500
803
1.000
1.200
814
1.200
1.000
825
1.000
1.200
836
1.200
1.000
847
1.000
1.200
858
1.200
1.000
704
0.005
0.006
715
0.006
0.005
726
0.005
0.006
737
0.006
0.005
748
0.005
0.006
759
0.006
0.005
404
0.010
0.015
415
0.015
0.010
426
0.010
0.015
437
0.015
0.010
448
0.010
0.015
459
0.015
0.010
204
0.025
0.030
215
0.030
0.025
226
0.025
0.030
237
0.030
0.025
248
0.025
0.030
259
0.030
0.025
504
0.050
0.060
515
0.060
0.050
526
0.050
0.060
537
0.060
0.050
548
0.050
0.060
559
0.060
0.050
604
0.100
0.120
615
0.120
0.100
626
0.100
0.120
637
0.120
0.100
648
0.100
0.120
659
0.120
0.100
104
0.200
0.240
115
0.240
0.200
126
0.200
0.240
137
0.240
0.200
148
0.200
0.240
159
0.240
0.200
304
0.500
0.600
315
0.600
0.500
326
0.500
0.600
337
0.600
0.500
348
0.500
0.600
359
0.600
0.500
804
1.000
1.200
815
1.200
1.000
826
1.000
1.200
837
1.200
1.000
848
1.000
1.200
859
1.200
1.000
105
0.005
0.006
116
0.006
0.005
127
0.005
0.006
138
0.006
0.005
149
0.005
0.006
150
0.006
0.005
405
0.010
0.015
416
0.015
0.010
427
0.010
0.015
438
0.015
0.010
449
0.010
0.015
450
0.015
0.010
805
0.025
0.030
816
0.030
0.025
827
0.025
0.030
838
0.030
0.025
849
0.025
0.030
850
0.030
0.025
505
0.050
0.060
516
0.060
0.050
527
0.050
0.060
538
0.060
0.050
549
0.050
0.060
550
0.060
0.050
305
0.100
0.120
316
0.120
0.100
327
0.100
0.120
338
0.120
0.100
349
0.100
0.120
350
0.120
0.100
205
0.200
0.240
216
0.240
0.200
227
0.200
0.240
238
0.240
0.200
249
0.200
0.240
250
0.240
0.200
605
0.500
0.600
616
0.600
0.500
627
0.500
0.600
638
0.600
0.500
649
0.500
0.600
650
0.600
0.500
705
1.000
1.200
716
1.200
1.000
727
1.000
1.200
738
1.200
1.000
749
1.000
1.200
750
1.200
1.000
506
0.005
0.006
517
0.006
0.005
528
0.005
0.006
539
0.006
0.005
540
0.005
0.006
551
0.006
0.005
206
0.010
0.015
217
0.015
0.010
228
0.010
0.015
239
0.015
0.010
240
0.010
0.015
251
0.015
0.010
806
0.025
0.030
817
0.030
0.025
828
0.025
0.030
839
0.030
0.025
840
0.025
0.030
851
0.030
0.025
306
0.050
0.060
317
0.060
0.050
328
0.050
0.060
339
0.060
0.050
340
0.050
0.060
351
0.060
0.050
106
0.100
0.120
117
0.120
0.100
128
0.100
0.120
139
0.120
0.100
140
0.100
0.120
151
0.120
0.100
606
0.200
0.240
617
0.240
0.200
628
0.200
0.240
639
0.240
0.200
640
0.200
0.240
651
0.240
0.200
706
0.500
0.600
717
0.600
0.500
728
0.500
0.600
739
0.600
0.500
740
0.500
0.600
751
0.600
0.500
406
1.000
1.200
417
1.200
1.000
428
1.000
1.200
439
1.200
1.000
440
1.000
1.200
451
1.200
1.000
807
0.005
0.006
818
0.006
0.005
829
0.005
0.006
830
0.006
0.005
841
0.005
0.006
852
0.006
0.005
607
0.010
0.015
618
0.015
0.010
629
0.010
0.015
630
0.015
0.010
641
0.010
0.015
652
0.015
0.010
107
0.025
0.030
118
0.030
0.025
129
0.025
0.030
130
0.030
0.025
141
0.025
0.030
152
0.030
0.025
707
0.050
0.060
718
0.060
0.050
729
0.050
0.060
730
0.060
0.050
741
0.050
0.060
752
0.060
0.050
307
0.100
0.120
318
0.120
0.100
329
0.100
0.120
330
0.120
0.100
341
0.100
0.120
352
0.120
0.100
507
0.200
0.240
518
0.240
0.200
529
0.200
0.240
530
0.240
0.200
541
0.200
0.240
552
0.240
0.200
207
0.500
0.600
218
0.600
0.500
229
0.500
0.600
230
0.600
0.500
241
0.500
0.600
252
0.600
0.500
407
1.000
1.200
418
1.200
1.000
429
1.000
1.200
430
1.200
1.000
441
1.000
1.200
452
1.200
1.000
508
0.005
0.006
519
0.006
0.005
520
0.005
0.006
531
0.006
0.005
542
0.005
0.006
553
0.006
0.005
408
0.010
0.015
419
0.015
0.010
420
0.010
0.015
431
0.015
0.010
442
0.010
0.015
453
0.015
0.010
208
0.025
0.030
219
0.030
0.025
220
0.025
0.030
231
0.030
0.025
242
0.025
0.030
253
0.030
0.025
708
0.050
0.060
719
0.060
0.050
720
0.050
0.060
731
0.060
0.050
742
0.050
0.060
753
0.060
0.050
108
0.100
0.120
119
0.120
0.100
120
0.100
0.120
131
0.120
0.100
142
0.100
0.120
153
0.120
0.100
608
0.200
0.240
619
0.240
0.200
620
0.200
0.240
631
0.240
0.200
642
0.200
0.240
653
0.240
0.200
308
0.500
0.600
319
0.600
0.500
320
0.500
0.600
331
0.600
0.500
342
0.500
0.600
353
0.600
0.500
808
1.000
1.200
819
1.200
1.000
820
1.000
1.200
831
1.200
1.000
842
1.000
1.200
853
1.200
1.000
409
0.005
0.006
410
0.006
0.005
421
0.005
0.006
432
0.006
0.005
443
0.005
0.006
454
0.006
0.005
609
0.010
0.015
610
0.015
0.010
621
0.010
0.015
632
0.015
0.010
643
0.010
0.015
654
0.015
0.010
309
0.025
0.030
310
0.030
0.025
321
0.025
0.030
332
0.030
0.025
343
0.025
0.030
354
0.030
0.025
209
0.050
0.060
210
0.060
0.050
221
0.050
0.060
232
0.060
0.050
243
0.050
0.060
254
0.060
0.050
809
0.100
0.120
810
0.120
0.100
821
0.100
0.120
832
0.120
0.100
843
0.100
0.120
854
0.120
0.100
509
0.200
0.240
510
0.240
0.200
521
0.200
0.240
532
0.240
0.200
543
0.200
0.240
554
0.240
0.200
709
0.500
0.600
710
0.600
0.500
721
0.500
0.600
732
0.600
0.500
743
0.500
0.600
754
0.600
0.500
109
1.000
1.200
110
1.200
1.000
121
1.000
1.200
132
1.200
1.000
143
1.000
1.200
154
1.200
1.000
Page
1
of
2
Attachment
2.5
BATCH
6
BATCH
7
BATCH
8
BATCH
9
BATCH
10
BATCH
11
Sample
Acroclor
Aroclor
Sample
Acroclor
Aroclor
Sample
Acroclor
Aroclor
Sample
Acroclor
Aroclor
Sample
Acroclor
Aroclor
Sample
Acroclor
Aroclor
I.
D.
1016
1260
I.
D.
1016
1260
I.
D.
1016
1260
I.
D.
1016
1260
I.
D.
1016
1260
I.
D.
1016
1260
466
0.005
0.006
477
0.006
0.005
488
0.005
0.006
499
0.006
0.005
4100
0.005
0.006
4111
0.006
0.005
266
0.010
0.015
277
0.015
0.010
288
0.010
0.015
299
0.015
0.010
2100
0.010
0.015
2111
0.015
0.010
166
0.025
0.030
177
0.030
0.025
188
0.025
0.030
199
0.030
0.025
1100
0.025
0.030
1111
0.030
0.025
866
0.050
0.060
877
0.060
0.050
888
0.050
0.060
899
0.060
0.050
8100
0.050
0.060
8111
0.060
0.050
366
0.100
0.120
377
0.120
0.100
388
0.100
0.120
399
0.120
0.100
3100
0.100
0.120
3111
0.120
0.100
666
0.200
0.240
677
0.240
0.200
688
0.200
0.240
699
0.240
0.200
6100
0.200
0.240
6111
0.240
0.200
766
0.500
0.600
777
0.600
0.500
788
0.500
0.600
799
0.600
0.500
7100
0.500
0.600
7111
0.600
0.500
566
1.000
1.200
577
1.200
1.000
588
1.000
1.200
599
1.200
1.000
5100
1.000
1.200
5111
1.200
1.000
667
0.005
0.006
678
0.006
0.005
689
0.005
0.006
690
0.006
0.005
6101
0.005
0.006
6112
0.006
0.005
367
0.010
0.015
378
0.015
0.010
389
0.010
0.015
390
0.015
0.010
3101
0.010
0.015
3112
0.015
0.010
867
0.025
0.030
878
0.030
0.025
889
0.025
0.030
890
0.030
0.025
8101
0.025
0.030
8112
0.030
0.025
467
0.050
0.060
478
0.060
0.050
489
0.050
0.060
490
0.060
0.050
4101
0.050
0.060
4112
0.060
0.050
767
0.100
0.120
778
0.120
0.100
789
0.100
0.120
790
0.120
0.100
7101
0.100
0.120
7112
0.120
0.100
167
0.200
0.240
178
0.240
0.200
189
0.200
0.240
190
0.240
0.200
1101
0.200
0.240
1112
0.240
0.200
567
0.500
0.600
578
0.600
0.500
589
0.500
0.600
590
0.600
0.500
5101
0.500
0.600
5112
0.600
0.500
267
1.000
1.200
278
1.200
1.000
289
1.000
1.200
290
1.200
1.000
2101
1.000
1.200
2112
1.200
1.000
268
0.005
0.006
279
0.006
0.005
280
0.005
0.006
291
0.006
0.005
2102
0.005
0.006
2113
0.006
0.005
468
0.010
0.015
479
0.015
0.010
480
0.010
0.015
491
0.015
0.010
4102
0.010
0.015
4113
0.015
0.010
668
0.025
0.030
679
0.030
0.025
680
0.025
0.030
691
0.030
0.025
6102
0.025
0.030
6113
0.030
0.025
368
0.050
0.060
379
0.060
0.050
380
0.050
0.060
391
0.060
0.050
3102
0.050
0.060
3113
0.060
0.050
568
0.100
0.120
579
0.120
0.100
580
0.100
0.120
591
0.120
0.100
5102
0.100
0.120
5113
0.120
0.100
868
0.200
0.240
879
0.240
0.200
880
0.200
0.240
891
0.240
0.200
8102
0.200
0.240
8113
0.240
0.200
168
0.500
0.600
179
0.600
0.500
180
0.500
0.600
191
0.600
0.500
1102
0.500
0.600
1113
0.600
0.500
768
1.000
1.200
779
1.200
1.000
780
1.000
1.200
791
1.200
1.000
7102
1.000
1.200
7113
1.200
1.000
269
0.005
0.006
270
0.006
0.005
281
0.005
0.006
292
0.006
0.005
2103
0.005
0.006
2114
0.006
0.005
369
0.010
0.015
370
0.015
0.010
381
0.010
0.015
392
0.015
0.010
3103
0.010
0.015
3114
0.015
0.010
469
0.025
0.030
470
0.030
0.025
481
0.025
0.030
492
0.030
0.025
4103
0.025
0.030
4114
0.030
0.025
669
0.050
0.060
670
0.060
0.050
681
0.050
0.060
692
0.060
0.050
6103
0.050
0.060
6114
0.060
0.050
569
0.100
0.120
570
0.120
0.100
581
0.100
0.120
592
0.120
0.100
5103
0.100
0.120
5114
0.120
0.100
769
0.200
0.240
770
0.240
0.200
781
0.200
0.240
792
0.240
0.200
7103
0.200
0.240
7114
0.240
0.200
169
0.500
0.600
170
0.600
0.500
181
0.500
0.600
192
0.600
0.500
1103
0.500
0.600
1114
0.600
0.500
869
1.000
1.200
870
1.200
1.000
881
1.000
1.200
892
1.200
1.000
8103
1.000
1.200
8114
1.200
1.000
760
0.005
0.006
771
0.006
0.005
782
0.005
0.006
793
0.006
0.005
7104
0.005
0.006
7115
0.006
0.005
460
0.010
0.015
471
0.015
0.010
482
0.010
0.015
493
0.015
0.010
4104
0.010
0.015
4115
0.015
0.010
260
0.025
0.030
271
0.030
0.025
282
0.025
0.030
293
0.030
0.025
2104
0.025
0.030
2115
0.030
0.025
560
0.050
0.060
571
0.060
0.050
582
0.050
0.060
593
0.060
0.050
5104
0.050
0.060
5115
0.060
0.050
660
0.100
0.120
671
0.120
0.100
682
0.100
0.120
693
0.120
0.100
6104
0.100
0.120
6115
0.120
0.100
160
0.200
0.240
171
0.240
0.200
182
0.200
0.240
193
0.240
0.200
1104
0.200
0.240
1115
0.240
0.200
360
0.500
0.600
371
0.600
0.500
382
0.500
0.600
393
0.600
0.500
3104
0.500
0.600
3115
0.600
0.500
860
1.000
1.200
871
1.200
1.000
882
1.000
1.200
893
1.200
1.000
8104
1.000
1.200
8115
1.200
1.000
161
0.005
0.006
172
0.006
0.005
183
0.005
0.006
194
0.006
0.005
1105
0.005
0.006
1116
0.006
0.005
461
0.010
0.015
472
0.015
0.010
483
0.010
0.015
494
0.015
0.010
4105
0.010
0.015
4116
0.015
0.010
861
0.025
0.030
872
0.030
0.025
883
0.025
0.030
894
0.030
0.025
8105
0.025
0.030
8116
0.030
0.025
561
0.050
0.060
572
0.060
0.050
583
0.050
0.060
594
0.060
0.050
5105
0.050
0.060
5116
0.060
0.050
361
0.100
0.120
372
0.120
0.100
383
0.100
0.120
394
0.120
0.100
3105
0.100
0.120
3116
0.120
0.100
261
0.200
0.240
272
0.240
0.200
283
0.200
0.240
294
0.240
0.200
2105
0.200
0.240
2116
0.240
0.200
661
0.500
0.600
672
0.600
0.500
683
0.500
0.600
694
0.600
0.500
6105
0.500
0.600
6116
0.600
0.500
761
1.000
1.200
772
1.200
1.000
783
1.000
1.200
794
1.200
1.000
7105
1.000
1.200
7116
1.200
1.000
562
0.005
0.006
573
0.006
0.005
584
0.005
0.006
595
0.006
0.005
5106
0.005
0.006
5117
0.006
0.005
262
0.010
0.015
273
0.015
0.010
284
0.010
0.015
295
0.015
0.010
2106
0.010
0.015
2117
0.015
0.010
862
0.025
0.030
873
0.030
0.025
884
0.025
0.030
895
0.030
0.025
8106
0.025
0.030
8117
0.030
0.025
362
0.050
0.060
373
0.060
0.050
384
0.050
0.060
395
0.060
0.050
3106
0.050
0.060
3117
0.060
0.050
162
0.100
0.120
173
0.120
0.100
184
0.100
0.120
195
0.120
0.100
1106
0.100
0.120
1117
0.120
0.100
662
0.200
0.240
673
0.240
0.200
684
0.200
0.240
695
0.240
0.200
6106
0.200
0.240
6117
0.240
0.200
762
0.500
0.600
773
0.600
0.500
784
0.500
0.600
795
0.600
0.500
7106
0.500
0.600
7117
0.600
0.500
462
1.000
1.200
473
1.200
1.000
484
1.000
1.200
495
1.200
1.000
4106
1.000
1.200
4117
1.200
1.000
863
0.005
0.006
874
0.006
0.005
885
0.005
0.006
896
0.006
0.005
8107
0.005
0.006
8118
0.006
0.005
663
0.010
0.015
674
0.015
0.010
685
0.010
0.015
696
0.015
0.010
6107
0.010
0.015
6118
0.015
0.010
163
0.025
0.030
174
0.030
0.025
185
0.025
0.030
196
0.030
0.025
1107
0.025
0.030
1118
0.030
0.025
763
0.050
0.060
774
0.060
0.050
785
0.050
0.060
796
0.060
0.050
7107
0.050
0.060
7118
0.060
0.050
363
0.100
0.120
374
0.120
0.100
385
0.100
0.120
396
0.120
0.100
3107
0.100
0.120
3118
0.120
0.100
563
0.200
0.240
574
0.240
0.200
585
0.200
0.240
596
0.240
0.200
5107
0.200
0.240
5118
0.240
0.200
263
0.500
0.600
274
0.600
0.500
285
0.500
0.600
296
0.600
0.500
2107
0.500
0.600
2118
0.600
0.500
463
1.000
1.200
474
1.200
1.000
485
1.000
1.200
496
1.200
1.000
4107
1.000
1.200
4118
1.200
1.000
564
0.005
0.006
575
0.006
0.005
586
0.005
0.006
597
0.006
0.005
5108
0.005
0.006
5119
0.006
0.005
464
0.010
0.015
475
0.015
0.010
486
0.010
0.015
497
0.015
0.010
4108
0.010
0.015
4119
0.015
0.010
264
0.025
0.030
275
0.030
0.025
286
0.025
0.030
297
0.030
0.025
2108
0.025
0.030
2119
0.030
0.025
764
0.050
0.060
775
0.060
0.050
786
0.050
0.060
797
0.060
0.050
7108
0.050
0.060
7119
0.060
0.050
164
0.100
0.120
175
0.120
0.100
186
0.100
0.120
197
0.120
0.100
1108
0.100
0.120
1119
0.120
0.100
664
0.200
0.240
675
0.240
0.200
686
0.200
0.240
697
0.240
0.200
6108
0.200
0.240
6119
0.240
0.200
364
0.500
0.600
375
0.600
0.500
386
0.500
0.600
397
0.600
0.500
3108
0.500
0.600
3119
0.600
0.500
864
1.000
1.200
875
1.200
1.000
886
1.000
1.200
897
1.200
1.000
8108
1.000
1.200
8119
1.200
1.000
465
0.005
0.006
476
0.006
0.005
487
0.005
0.006
498
0.006
0.005
4109
0.005
0.006
4110
0.006
0.005
665
0.010
0.015
676
0.015
0.010
687
0.010
0.015
698
0.015
0.010
6109
0.010
0.015
6110
0.015
0.010
365
0.025
0.030
376
0.030
0.025
387
0.025
0.030
398
0.030
0.025
3109
0.025
0.030
3110
0.030
0.025
265
0.050
0.060
276
0.060
0.050
287
0.050
0.060
298
0.060
0.050
2109
0.050
0.060
2110
0.060
0.050
865
0.100
0.120
876
0.120
0.100
887
0.100
0.120
898
0.120
0.100
8109
0.100
0.120
8110
0.120
0.100
565
0.200
0.240
576
0.240
0.200
587
0.200
0.240
598
0.240
0.200
5109
0.200
0.240
5110
0.240
0.200
765
0.500
0.600
776
0.600
0.500
787
0.500
0.600
798
0.600
0.500
7109
0.500
0.600
7110
0.600
0.500
165
1.000
1.200
176
1.200
1.000
187
1.000
1.200
198
1.200
1.000
1109
1.000
1.200
1110
1.200
1.000
Page
2
of
2
Attachment
2.6
Date
Aroclor
Sample
I.
D.
Aroclor
1
Result
1
Aroclor
2
Result
2
123456789
Character
Meaning
LAB
First
(
X)
Bottle
(
1­
8,
9=
blk)
0
TriMatrix
­
Grand
Rapids
Middle
(
Y)
Batch
(
0­
10)
1
FECL
­
Lansing
Last
(
Z)
LAB
(
0­
9)
2
STL
­
Amherst
3
ATS
­
Ann
Arbor
Note:
Sample
ID
=
XYZ
4
Test
America
­
Dayton
Designate
Blank
as
9YZ
5
Clayton
­
Novi
6
CTE
­
Ludington
7
Enviroscan
(
US
Filter)
­
Rothschild
8
AAC
Trinity
­
Farmington
Hills
9
STL
­
North
Canton
GC
Analyst
Arcolor
Identification
and
Sample
Results
in
ug/
L
"
0.0000"
PCB
Interlaboratory
Study
Batch
Data
Report
Sheet
Submit
to
Dr.
John
Gabrosek
at
"
gabrosej@
gvsu.
edu"

Extraction
Analyst
Clean­
Up
Analyst
Laboratory
GC
Instrument
LFB
%
Recovery
KEY
Attachment
2.7
REFEREE
LAB
RESULTS
­
MMA
PCB
STUDY
2001
TRUE
SAMPLE
CONC.
REFEREE
LAB
RESULTS
%
REC
UG/
L
UG/
L
SAMPLE
TR­
23
AROCLOR
1016
0.025
AROCLOR
1016
0.05
200
AROCLOR
1260
0.030
AROCLOR
1260
ND
N/
A
SAMPLE
TR­
27
AROCLOR
1016
0.50
AROCLOR
1016
0.44
88
AROCLOR
1260
0.60
AROCLOR
1260
0.50
83
SAMPLE
TR­
33
AROCLOR
1016
0.030
AROCLOR
1016
0.03
100
AROCLOR
1260
0.025
AROCLOR
1260
ND
N/
A
SAMPLE
TR­
38
AROCLOR
1016
1.2
AROCLOR
1016
1.11
93
AROCLOR
1260
1.0
AROCLOR
1260
0.93
93
SAMPLE
TR­
44
AROCLOR
1016
0.050
AROCLOR
1016
0.03
60
AROCLOR
1260
0.060
AROCLOR
1260
ND
N/
A
SAMPLE
TR­
47
AROCLOR
1016
0.50
AROCLOR
1016
0.48
96
AROCLOR
1260
0.60
AROCLOR
1260
0.57
95
SAMPLE
TR­
55
AROCLOR
1016
0.12
AROCLOR
1016
0.11
92
AROCLOR
1260
0.10
AROCLOR
1260
0.08
80
SAMPLE
TR­
58
AROCLOR
1016
1.2
AROCLOR
1016
0.92
77
AROCLOR
1260
1.0
AROCLOR
1260
0.93
93
SAMPLE
TR­
64
AROCLOR
1016
0.050
AROCLOR
1016
0.06
120
AROCLOR
1260
0.060
AROCLOR
1260
0.04
67
SAMPLE
TR­
67
AROCLOR
1016
0.50
AROCLOR
1016
0.44
88
AROCLOR
1260
0.60
AROCLOR
1260
0.52
87
SAMPLE
TR­
76
AROCLOR
1016
0.24
AROCLOR
1016
0.21
88
AROCLOR
1260
0.20
AROCLOR
1260
0.17
85
SAMPLE
TR­
78
AROCLOR
1016
1.2
AROCLOR
1016
1.1
92
AROCLOR
1260
1.0
AROCLOR
1260
0.91
91
SAMPLE
TR­
85
AROCLOR
1016
0.10
AROCLOR
1016
0.16
160
AROCLOR
1260
0.12
AROCLOR
1260
0.11
92
SAMPLE
TR­
87
AROCLOR
1016
0.50
AROCLOR
1016
0.46
92
AROCLOR
1260
0.60
AROCLOR
1260
0.48
80
SAMPLE
TR­
96
AROCLOR
1016
0.24
AROCLOR
1016
0.24
100
AROCLOR
1260
0.20
AROCLOR
1260
0.16
80
SAMPLE
TR­
98
AROCLOR
1016
1.2
AROCLOR
1016
1.22
102
AROCLOR
1260
1.0
AROCLOR
1260
0.94
94
SAMPLE
TR­
106
AROCLOR
1016
0.20
AROCLOR
1016
0.22
110
AROCLOR
1260
0.24
AROCLOR
1260
0.22
92
SAMPLE
TR­
107
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Attachment
2.8
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Batch
Lab
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Result
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Aroclor
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2
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Attachment
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0.0082
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2
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18
Attachment
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2
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1260
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7
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4
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5
7
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6
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7
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8
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9
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0.7517
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0.8503
1260
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8
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Page
3
of
18
Attachment
2.8
3
8
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4
8
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0.0957
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8
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6
8
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7
8
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2
9
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3
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1260
4
9
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0.0407
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5
9
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6
9
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7
9
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8
9
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0.0690
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9
9
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10
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10
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10
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1260
4
10
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5
10
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0.4197
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1260
6
10
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0.8573
1016
1.200
0.9773
1260
7
10
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0.0547
1016
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1260
8
10
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9
10
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1
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2
1
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0.1847
1016
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1260
3
1
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0.4811
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0.3524
1260
4
1
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1.200
1.1430
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0.8237
1260
5
1
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0.1423
1016
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0.0991
1260
6
1
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0.0943
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7
1
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0.0475
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0.0263
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8
1
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9
1
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2
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2
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2
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1260
4
2
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2
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6
2
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1260
7
2
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2
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2
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1.1490
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3
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3
3
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3
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6
3
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0.3352
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0.2167
1260
7
3
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0.5272
1260
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3
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0.2428
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0.1095
1260
9
3
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Page
4
of
18
Attachment
2.8
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4
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1260
2
4
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3
4
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4
4
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4
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4
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7
4
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4
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4
5
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5
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5
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5
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1260
8
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5
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6
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0.1845
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0.2122
1260
4
6
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5
6
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0.4105
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1260
6
6
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0.8035
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0.9331
1260
7
6
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0.0498
1016
0.060
0.0589
1260
8
6
C
0.025
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0.0279
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9
6
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0.0532
1260
2
7
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0.5431
1016
0.500
0.4450
1260
3
7
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0.120
0.1289
1016
0.100
0.1017
1260
4
7
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0.0330
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0.0274
1260
5
7
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0.0124
1260
6
7
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7
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11
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0.0299
1260
8
2
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0.2043
1260
9
2
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1
3
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1260
2
3
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0.0362
1242
0.010
0.0117
1260
3
3
I
1.176
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0.980
0.7273
1260
4
3
I
0.029
0.0646
1242
0.025
0.0293
1260
5
3
I
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6
3
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0.098
0.1073
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7
3
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1260
8
3
I
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9
3
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4
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2
4
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1242
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0.1179
1260
3
4
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1260
4
4
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0.0162
1260
5
4
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1242
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0.4436
1260
6
4
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1242
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0.9325
1260
7
4
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0.060
0.0603
1260
8
4
I
0.025
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1242
0.030
0.0288
1260
9
4
I
unknown
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1
5
I
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0.0680
1242
0.050
0.0339
1260
2
5
I
0.600
0.3617
1242
0.500
0.2779
1260
3
5
I
0.120
0.1139
1242
0.100
0.0672
1260
4
5
I
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1242
0.025
0.0215
1260
5
5
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0.010
0.0106
1260
6
5
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7
5
I
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1260
8
5
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0.1502
1242
0.200
0.1017
1260
9
5
I
unknown
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1
6
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1242
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2
6
I
0.010
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1242
0.015
0.0139
1260
3
6
I
0.025
0.4110
1242
0.030
0.0223
1260
4
6
I
0.200
0.240
5
6
I
0.500
0.2536
1242
0.600
0.2867
1260
6
6
I
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1242
0.060
0.0396
1260
7
6
I
1.000
0.6267
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1.200
0.6685
1260
8
6
I
0.100
0.1012
1242
0.120
0.0872
1260
9
6
I
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1
7
I
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0.025
0.0164
1260
2
7
I
0.006
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3
7
I
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1.000
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4
7
I
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0.1280
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0.100
0.0904
1260
Page
15
of
18
Attachment
2.8
5
7
I
0.060
0.0770
1242
0.050
0.0424
1260
6
7
I
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0.0338
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0.010
unkown
7
7
I
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1242
0.500
0.3317
1260
8
7
I
0.240
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1242
0.200
0.1425
1260
9
7
I
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1
8
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0.240
0.1764
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2
8
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0.010
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0.015
0.0167
1260
3
8
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1260
4
8
I
0.050
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0.060
0.0458
1260
5
8
I
0.005
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0.006
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6
8
I
0.500
0.3321
1242
0.600
0.3429
1260
7
8
I
0.100
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1242
0.120
0.1337
1260
8
8
I
1.000
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1242
1.200
0.9326
1260
9
8
I
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1
9
I
0.015
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0.010
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2
9
I
0.240
0.2616
1242
0.200
0.1862
1260
3
9
I
0.600
0.4063
1242
0.500
0.2953
1260
4
9
I
1.200
0.8755
1242
1.000
0.6531
1260
5
9
I
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0.1170
1242
0.100
0.0659
1260
6
9
I
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7
9
I
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1242
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0.0256
1260
8
9
I
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0.005
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9
9
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1
10
I
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1260
2
10
I
0.005
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3
10
I
0.050
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0.060
0.0329
1260
4
10
I
0.100
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0.0989
1260
5
10
I
0.200
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0.1843
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6
10
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0.9795
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7
10
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0.500
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0.464
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10
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9
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3
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4
1
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5
1
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1
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1.000
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7
1
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1
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1260
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1
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1
2
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2
2
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1016
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3
2
J
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4
2
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0.025
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0.028
1260
5
2
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0.010
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6
2
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1260
7
2
J
0.980
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1016
1.176
0.873
1260
8
2
J
0.196
0.165
1016
0.235
0.215
1260
9
2
J
Unknown
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1
3
J
0.006
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0.005
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2
3
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0.015
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0.010
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Page
16
of
18
Attachment
2.8
3
3
J
0.029
0.027
Unknown
0.025
0.040
1260
4
3
J
0.235
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1016
0.196
0.194
1260
5
3
J
0.588
0.433
1016
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0.409
1260
6
3
J
0.059
0.076
1016
0.049
0.066
1260
7
3
J
1.176
0.978
1016
0.980
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1260
8
3
J
0.118
0.117
1016
0.098
0.099
1260
9
3
J
Unknown
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1
4
J
0.025
Unknown
0.029
0.031
1260
2
4
J
0.005
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0.006
Unknown
3
4
J
0.980
0.629
1016
1.176
0.746
1260
4
4
J
0.098
0.067
1016
0.118
0.093
1260
5
4
J
0.049
0.033
Unknown
0.059
0.046
1260
6
4
J
0.010
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0.015
0.022
1260
7
4
J
0.490
0.349
1016
0.588
0.406
1260
8
4
J
0.196
0.166
1016
0.235
0.162
1260
9
4
J
Unknown
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1
5
J
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1016
0.196
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1260
2
5
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0.015
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1016
0.010
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3
5
J
0.029
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0.025
0.0304
1260
4
5
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0.059
0.0362
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0.049
0.0445
1260
5
5
J
0.006
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0.005
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6
5
J
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7
5
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1016
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0.0834
1260
8
5
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1.176
0.7073
1016
0.980
0.5476
1260
9
5
J
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1
6
J
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0.015
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1260
2
6
J
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0.240
0.2129
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3
6
J
0.500
0.4599
1016
0.600
0.4826
1260
4
6
J
1.000
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1016
1.200
0.7194
1260
5
6
J
0.100
0.0452
1016
0.120
0.0984
1260
6
6
J
0.050
0.0612
1016
0.060
0.0613
1260
7
6
J
0.025
0.0061
1016
0.030
0.0443
1260
8
6
J
0.005
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0.006
0.0116
1260
9
6
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1
7
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1260
2
7
J
0.006
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0.005
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3
7
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4
7
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5
7
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1260
6
7
J
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1016
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0.6673
1260
7
7
J
0.600
0.5022
1016
0.500
0.3718
1260
8
7
J
0.030
0.0377
1016
0.025
0.0311
1260
9
7
J
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1
8
J
1.000
1.0308
1016
1.200
0.9281
1260
2
8
J
0.025
0.0504
1016
0.030
0.0497
1260
3
8
J
0.010
0.0217
1016
0.015
0.0336
1260
4
8
J
0.005
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0.006
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5
8
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6
8
J
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1016
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0.2659
1260
7
8
J
0.500
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1016
0.600
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1260
8
8
J
0.100
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1016
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0.1212
1260
9
8
J
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Page
17
of
18
Attachment
2.8
1
9
J
1.176
1.0949
1016
0.980
0.8571
1260
2
9
J
0.006
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0.005
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3
9
J
0.015
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0.010
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4
9
J
0.118
0.1344
1016
0.098
0.0952
1260
5
9
J
0.059
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1016
0.049
0.0633
1260
6
9
J
0.588
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1016
0.490
0.3412
1260
7
9
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0.029
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1016
0.025
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1260
8
9
J
0.235
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0.196
0.1807
1260
9
9
J
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1
10
J
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0.2097
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2
10
J
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0.015
0.0171
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3
10
J
0.980
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1.176
0.8360
1260
4
10
J
0.025
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1016
0.029
0.0225
1260
5
10
J
0.005
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6
10
J
0.098
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1016
0.118
0.1172
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7
10
J
0.490
0.3744
1016
0.588
0.3795
1260
8
10
J
0.049
0.0538
1016
0.059
0.0492
1260
9
10
J
Unknown
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Page
18
of
18
Attachment
2.9
From
16­
A1­
OR
From
16­
A1­
DL­
OR
From
16­
A2­
OR
From
16­
A2­
DL­
OR
Conc
Result
Conc
Result
Conc
Result
Conc
Result
0.005
0.0060
0.0050
0.0060
0.005
0.0050
0.0050
0.0050
0.005
0.0070
0.0050
0.0070
0.005
0.0060
0.0050
0.0060
0.005
0.0078
0.0050
0.0078
0.005
0.0064
0.0050
0.0064
0.005
0.0082
0.0050
0.0082
0.005
0.0084
0.0050
0.0084
0.005
0.0090
0.0050
0.0090
0.005
0.0090
0.0050
0.0090
0.005
0.0111
0.0050
0.0111
0.005
0.0124
0.0050
0.0124
0.005
0.0130
0.0050
0.0130
0.005
0.0143
0.0050
0.0159
0.005
0.0140
0.0050
0.0146
0.005
0.0159
0.0050
0.0182
0.005
0.0146
0.0050
0.0194
0.005
0.0182
0.0050
0.0193
0.005
0.0194
0.0050
0.0220
0.005
0.0193
0.0050
0.0197
0.005
0.0220
0.0050
0.0230
0.005
0.0197
0.0050
0.0222
0.005
0.0230
0.0050
0.0456
0.005
0.0222
0.0050
0.0265
0.005
0.0456
0.0060
0.0110
0.005
0.0265
0.0050
0.0290
0.005
0.0575
0.0060
0.0130
0.005
0.0290
0.0050
0.0510
0.005
0.0711
0.0060
0.0141
0.005
0.0467
0.0050
0.0570
0.005
0.1198
0.0060
0.0160
0.005
0.0510
0.0050
0.0581
0.006
0.0110
0.0060
0.0167
0.005
0.0570
0.0050
0.0775
0.006
0.0130
0.0060
0.0179
0.005
0.0581
0.0060
0.0040
0.006
0.0141
0.0060
0.0180
0.005
0.0775
0.0060
0.0074
0.006
0.0160
0.0060
0.0182
0.006
0.0040
0.0060
0.0088
0.006
0.0167
0.0060
0.0185
0.006
0.0074
0.0060
0.0090
0.006
0.0179
0.0060
0.0200
0.006
0.0088
0.0060
0.0091
0.006
0.0180
0.0060
0.0309
0.006
0.0090
0.0060
0.0095
0.006
0.0182
0.0060
0.0503
0.006
0.0091
0.0060
0.0110
0.006
0.0185
0.0060
0.0517
0.006
0.0095
0.0060
0.0116
0.006
0.0200
0.0100
0.0085
0.006
0.0101
0.0060
0.0120
0.006
0.0200
0.0100
0.0110
0.006
0.0110
0.0060
0.0133
0.006
0.0290
0.0100
0.0117
0.006
0.0116
0.0060
0.0152
0.006
0.0309
0.0100
0.0122
0.006
0.0120
0.0060
0.0157
0.006
0.0503
0.0100
0.0140
0.006
0.0133
0.0060
0.0160
0.006
0.0517
0.0100
0.0153
0.006
0.0152
0.0060
0.0160
0.010
0.0085
0.0100
0.0160
0.006
0.0157
0.0060
0.0164
0.010
0.0110
0.0100
0.0165
0.006
0.0160
0.0060
0.0172
0.010
0.0117
0.0100
0.0181
0.006
0.0160
0.0060
0.0193
0.010
0.0122
0.0100
0.0190
0.006
0.0164
0.0060
0.0196
0.010
0.0140
0.0100
0.0204
0.006
0.0172
0.0060
0.0261
0.010
0.0153
0.0100
0.0217
0.006
0.0193
0.0060
0.0430
0.010
0.0160
0.0100
0.0240
0.006
0.0196
0.0060
0.0530
0.010
0.0165
0.0100
0.0250
0.006
0.0261
0.0060
0.0540
0.010
0.0181
0.0100
0.0270
0.006
0.0400
0.0060
0.0640
0.010
0.0190
0.0100
0.0340
0.006
0.0430
0.0100
0.0050
0.010
0.0204
0.0100
0.0361
0.006
0.0510
0.0100
0.0068
0.010
0.0217
0.0100
0.0455
0.006
0.0530
0.0100
0.0069
0.010
0.0240
0.0150
0.0078
0.006
0.0540
0.0100
0.0085
0.010
0.0250
0.0150
0.0096
0.006
0.0640
0.0100
0.0110
0.010
0.0270
0.0150
0.0116
0.010
0.0050
0.0100
0.0113
0.010
0.0340
0.0150
0.0149
0.010
0.0068
0.0100
0.0116
0.010
0.0361
0.0150
0.0151
0.010
0.0069
0.0100
0.0117
MMA
PCB
INTERLABORATORY
STUYD
RESULTS
­
WITH
OUTLIERS
REMOVED
Page
1
of
15
Attachment
2.9
From
16­
A1­
OR
From
16­
A1­
DL­
OR
From
16­
A2­
OR
From
16­
A2­
DL­
OR
Conc
Result
Conc
Result
Conc
Result
Conc
Result
0.010
0.0368
0.0150
0.0173
0.010
0.0085
0.0100
0.0118
0.010
0.0400
0.0150
0.0176
0.010
0.0106
0.0100
0.0122
0.010
0.0455
0.0150
0.0180
0.010
0.0110
0.0100
0.0124
0.015
0.0078
0.0150
0.0186
0.010
0.0113
0.0100
0.0140
0.015
0.0096
0.0150
0.0210
0.010
0.0116
0.0100
0.0143
0.015
0.0100
0.0150
0.0215
0.010
0.0117
0.0100
0.0150
0.015
0.0116
0.0150
0.0218
0.010
0.0118
0.0100
0.0155
0.015
0.0149
0.0150
0.0219
0.010
0.0122
0.0100
0.0166
0.015
0.0151
0.0150
0.0220
0.010
0.0124
0.0100
0.0170
0.015
0.0173
0.0150
0.0237
0.010
0.0140
0.0100
0.0172
0.015
0.0176
0.0150
0.0238
0.010
0.0143
0.0100
0.0174
0.015
0.0180
0.0150
0.0246
0.010
0.0150
0.0100
0.0179
0.015
0.0186
0.0150
0.0270
0.010
0.0155
0.0100
0.0213
0.015
0.0210
0.0150
0.0300
0.010
0.0166
0.0100
0.0220
0.015
0.0215
0.0150
0.0318
0.010
0.0170
0.0100
0.0234
0.015
0.0218
0.0150
0.0338
0.010
0.0172
0.0100
0.0243
0.015
0.0219
0.0150
0.0354
0.010
0.0174
0.0100
0.0269
0.015
0.0220
0.0150
0.0362
0.010
0.0179
0.0100
0.0290
0.015
0.0237
0.0150
0.0452
0.010
0.0213
0.0100
0.0303
0.015
0.0238
0.0250
0.0060
0.010
0.0220
0.0100
0.0330
0.015
0.0246
0.0250
0.0061
0.010
0.0234
0.0100
0.0330
0.015
0.0270
0.0250
0.0108
0.010
0.0243
0.0100
0.0420
0.015
0.0300
0.0250
0.0135
0.010
0.0269
0.0100
0.0460
0.015
0.0318
0.0250
0.0204
0.010
0.0290
0.0150
0.0110
0.015
0.0338
0.0250
0.0207
0.010
0.0303
0.0150
0.0129
0.015
0.0354
0.0250
0.0208
0.010
0.0330
0.0150
0.0130
0.015
0.0362
0.0250
0.0230
0.010
0.0330
0.0150
0.0138
0.015
0.0396
0.0250
0.0240
0.010
0.0403
0.0150
0.0139
0.015
0.0452
0.0250
0.0257
0.010
0.0408
0.0150
0.0143
0.015
0.0560
0.0250
0.0273
0.010
0.0420
0.0150
0.0145
0.025
0.0060
0.0250
0.0283
0.010
0.0460
0.0150
0.0150
0.025
0.0061
0.0250
0.0290
0.010
0.0560
0.0150
0.0150
0.025
0.0108
0.0250
0.0303
0.010
0.0570
0.0150
0.0159
0.025
0.0135
0.0250
0.0307
0.015
0.0110
0.0150
0.0162
0.025
0.0204
0.0250
0.0310
0.015
0.0125
0.0150
0.0163
0.025
0.0207
0.0250
0.0331
0.015
0.0129
0.0150
0.0167
0.025
0.0208
0.0250
0.0334
0.015
0.0130
0.0150
0.0171
0.025
0.0230
0.0250
0.0344
0.015
0.0138
0.0150
0.0175
0.025
0.0240
0.0250
0.0362
0.015
0.0139
0.0150
0.0178
0.025
0.0257
0.0250
0.0370
0.015
0.0143
0.0150
0.0190
0.025
0.0273
0.0250
0.0386
0.015
0.0145
0.0150
0.0194
0.025
0.0283
0.0250
0.0420
0.015
0.0150
0.0150
0.0194
0.025
0.0290
0.0250
0.0450
0.015
0.0150
0.0150
0.0200
0.025
0.0303
0.0250
0.0460
0.015
0.0159
0.0150
0.0203
0.025
0.0307
0.0250
0.0468
0.015
0.0162
0.0150
0.0213
0.025
0.0310
0.0250
0.0500
0.015
0.0163
0.0150
0.0213
0.025
0.0331
0.0250
0.0504
0.015
0.0167
0.0150
0.0218
0.025
0.0334
0.0250
0.0514
0.015
0.0171
0.0150
0.0220
0.025
0.0344
0.0250
0.0640
0.015
0.0175
0.0150
0.0226
0.025
0.0362
0.0250
0.0716
0.015
0.0178
0.0150
0.0229
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Attachment
2.9
From
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OR
From
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A2­
OR
From
16­
A2­
DL­
OR
Conc
Result
Conc
Result
Conc
Result
Conc
Result
0.025
0.0370
0.0300
0.0115
0.015
0.0190
0.0150
0.0240
0.025
0.0386
0.0300
0.0148
0.015
0.0194
0.0150
0.0258
0.025
0.0420
0.0300
0.0155
0.015
0.0194
0.0150
0.0268
0.025
0.0450
0.0300
0.0160
0.015
0.0200
0.0150
0.0290
0.025
0.0460
0.0300
0.0186
0.015
0.0203
0.0150
0.0321
0.025
0.0468
0.0300
0.0194
0.015
0.0213
0.0150
0.0336
0.025
0.0500
0.0300
0.0270
0.015
0.0213
0.0150
0.0365
0.025
0.0504
0.0300
0.0286
0.015
0.0218
0.0150
0.0366
0.025
0.0514
0.0300
0.0295
0.015
0.0220
0.0150
0.0400
0.025
0.0560
0.0300
0.0307
0.015
0.0226
0.0150
0.0458
0.025
0.0640
0.0300
0.0310
0.015
0.0229
0.0250
0.0056
0.025
0.0642
0.0300
0.0320
0.015
0.0240
0.0250
0.0084
0.025
0.0716
0.0300
0.0322
0.015
0.0258
0.0250
0.0164
0.030
0.0115
0.0300
0.0330
0.015
0.0268
0.0250
0.0173
0.030
0.0148
0.0300
0.0330
0.015
0.0290
0.0250
0.0185
0.030
0.0155
0.0300
0.0331
0.015
0.0321
0.0250
0.0190
0.030
0.0160
0.0300
0.0336
0.015
0.0336
0.0250
0.0216
0.030
0.0186
0.0300
0.0344
0.015
0.0365
0.0250
0.0220
0.030
0.0194
0.0300
0.0347
0.015
0.0366
0.0250
0.0226
0.030
0.0260
0.0300
0.0350
0.015
0.0400
0.0250
0.0231
0.030
0.0270
0.0300
0.0360
0.015
0.0437
0.0250
0.0240
0.030
0.0286
0.0300
0.0368
0.015
0.0458
0.0250
0.0240
0.030
0.0295
0.0300
0.0377
0.015
0.0497
0.0250
0.0250
0.030
0.0307
0.0300
0.0389
0.025
0.0029
0.0250
0.0250
0.030
0.0310
0.0300
0.0398
0.025
0.0056
0.0250
0.0250
0.030
0.0320
0.0300
0.0428
0.025
0.0084
0.0250
0.0256
0.030
0.0322
0.0300
0.0431
0.025
0.0164
0.0250
0.0262
0.030
0.0330
0.0300
0.0440
0.025
0.0173
0.0250
0.0263
0.030
0.0330
0.0300
0.0450
0.025
0.0185
0.0250
0.0265
0.030
0.0331
0.0300
0.0453
0.025
0.0190
0.0250
0.0269
0.030
0.0336
0.0300
0.0472
0.025
0.0215
0.0250
0.0274
0.030
0.0344
0.0300
0.0475
0.025
0.0216
0.0250
0.0280
0.030
0.0347
0.0300
0.0507
0.025
0.0220
0.0250
0.0287
0.030
0.0350
0.0300
0.0510
0.025
0.0226
0.0250
0.0287
0.030
0.0360
0.0300
0.0646
0.025
0.0231
0.0250
0.0293
0.030
0.0368
0.0300
0.0690
0.025
0.0240
0.0250
0.0301
0.030
0.0377
0.0300
0.0696
0.025
0.0240
0.0250
0.0304
0.030
0.0389
0.0300
0.0804
0.025
0.0250
0.0250
0.0308
0.030
0.0398
0.0300
0.0908
0.025
0.0250
0.0250
0.0311
0.030
0.0428
0.0500
0.0124
0.025
0.0250
0.0250
0.0341
0.030
0.0431
0.0500
0.0313
0.025
0.0256
0.0250
0.0343
0.030
0.0440
0.0500
0.0317
0.025
0.0262
0.0250
0.0360
0.030
0.0450
0.0500
0.0354
0.025
0.0263
0.0250
0.0365
0.030
0.0453
0.0500
0.0354
0.025
0.0265
0.0250
0.0370
0.030
0.0472
0.0500
0.0356
0.025
0.0269
0.0250
0.0400
0.030
0.0475
0.0500
0.0363
0.025
0.0274
0.0250
0.0420
0.030
0.0507
0.0500
0.0379
0.025
0.0280
0.0250
0.0445
0.030
0.0510
0.0500
0.0416
0.025
0.0287
0.0250
0.0447
0.030
0.0616
0.0500
0.0420
0.025
0.0293
0.0250
0.0540
0.030
0.0646
0.0500
0.0427
0.025
0.0301
0.0300
0.0093
Page
3
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Attachment
2.9
From
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OR
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OR
From
16­
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OR
From
16­
A2­
DL­
OR
Conc
Result
Conc
Result
Conc
Result
Conc
Result
0.030
0.0680
0.0500
0.0430
0.025
0.0304
0.0300
0.0105
0.030
0.0690
0.0500
0.0431
0.025
0.0308
0.0300
0.0122
0.030
0.0696
0.0500
0.0450
0.025
0.0311
0.0300
0.0220
0.030
0.0804
0.0500
0.0457
0.025
0.0341
0.0300
0.0223
0.030
0.0908
0.0500
0.0460
0.025
0.0343
0.0300
0.0223
0.050
0.0124
0.0500
0.0470
0.025
0.0360
0.0300
0.0225
0.050
0.0313
0.0500
0.0476
0.025
0.0365
0.0300
0.0228
0.050
0.0317
0.0500
0.0482
0.025
0.0370
0.0300
0.0236
0.050
0.0325
0.0500
0.0483
0.025
0.0400
0.0300
0.0250
0.050
0.0330
0.0500
0.0498
0.025
0.0407
0.0300
0.0263
0.050
0.0354
0.0500
0.0500
0.025
0.0420
0.0300
0.0268
0.050
0.0354
0.0500
0.0507
0.025
0.0445
0.0300
0.0273
0.050
0.0356
0.0500
0.0520
0.025
0.0447
0.0300
0.0279
0.050
0.0363
0.0500
0.0538
0.025
0.0470
0.0300
0.0280
0.050
0.0379
0.0500
0.0538
0.025
0.0540
0.0300
0.0280
0.050
0.0416
0.0500
0.0547
0.025
0.0646
0.0300
0.0288
0.050
0.0420
0.0500
0.0550
0.025
0.0686
0.0300
0.0290
0.050
0.0427
0.0500
0.0555
0.030
0.0062
0.0300
0.0297
0.050
0.0430
0.0500
0.0575
0.030
0.0093
0.0300
0.0299
0.050
0.0431
0.0500
0.0610
0.030
0.0105
0.0300
0.0300
0.050
0.0450
0.0500
0.0612
0.030
0.0122
0.0300
0.0310
0.050
0.0457
0.0500
0.0613
0.030
0.0216
0.0300
0.0310
0.050
0.0460
0.0500
0.0649
0.030
0.0220
0.0300
0.0310
0.050
0.0470
0.0500
0.0652
0.030
0.0223
0.0300
0.0313
0.050
0.0476
0.0500
0.0656
0.030
0.0223
0.0300
0.0318
0.050
0.0482
0.0500
0.0659
0.030
0.0225
0.0300
0.0324
0.050
0.0483
0.0500
0.0678
0.030
0.0228
0.0300
0.0325
0.050
0.0498
0.0500
0.0690
0.030
0.0236
0.0300
0.0328
0.050
0.0500
0.0500
0.0700
0.030
0.0250
0.0300
0.0333
0.050
0.0507
0.0600
0.0193
0.030
0.0263
0.0300
0.0337
0.050
0.0520
0.0600
0.0316
0.030
0.0268
0.0300
0.0346
0.050
0.0538
0.0600
0.0321
0.030
0.0273
0.0300
0.0359
0.050
0.0538
0.0600
0.0343
0.030
0.0279
0.0300
0.0368
0.050
0.0547
0.0600
0.0362
0.030
0.0280
0.0300
0.0383
0.050
0.0550
0.0600
0.0403
0.030
0.0280
0.0300
0.0392
0.050
0.0555
0.0600
0.0412
0.030
0.0288
0.0300
0.0397
0.050
0.0575
0.0600
0.0424
0.030
0.0290
0.0300
0.0443
0.050
0.0610
0.0600
0.0439
0.030
0.0297
0.0300
0.0497
0.050
0.0612
0.0600
0.0443
0.030
0.0299
0.0300
0.0580
0.050
0.0613
0.0600
0.0450
0.030
0.0300
0.0300
0.0590
0.050
0.0649
0.0600
0.0453
0.030
0.0310
0.0300
0.0607
0.050
0.0652
0.0600
0.0457
0.030
0.0310
0.0500
0.0241
0.050
0.0656
0.0600
0.0463
0.030
0.0310
0.0500
0.0245
0.050
0.0659
0.0600
0.0481
0.030
0.0313
0.0500
0.0330
0.050
0.0678
0.0600
0.0490
0.030
0.0318
0.0500
0.0341
0.050
0.0690
0.0600
0.0496
0.030
0.0324
0.0500
0.0346
0.050
0.0700
0.0600
0.0523
0.030
0.0325
0.0500
0.0372
0.050
0.0721
0.0600
0.0525
0.030
0.0328
0.0500
0.0380
0.060
0.0193
0.0600
0.0554
0.030
0.0333
0.0500
0.0386
0.060
0.0316
0.0600
0.0560
0.030
0.0337
0.0500
0.0389
Page
4
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Attachment
2.9
From
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OR
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A1­
DL­
OR
From
16­
A2­
OR
From
16­
A2­
DL­
OR
Conc
Result
Conc
Result
Conc
Result
Conc
Result
0.060
0.0321
0.0600
0.0570
0.030
0.0346
0.0500
0.0390
0.060
0.0343
0.0600
0.0575
0.030
0.0359
0.0500
0.0400
0.060
0.0362
0.0600
0.0580
0.030
0.0368
0.0500
0.0405
0.060
0.0403
0.0600
0.0609
0.030
0.0383
0.0500
0.0424
0.060
0.0412
0.0600
0.0640
0.030
0.0392
0.0500
0.0429
0.060
0.0424
0.0600
0.0653
0.030
0.0397
0.0500
0.0432
0.060
0.0439
0.0600
0.0659
0.030
0.0417
0.0500
0.0440
0.060
0.0443
0.0600
0.0660
0.030
0.0443
0.0500
0.0445
0.060
0.0450
0.0600
0.0660
0.030
0.0497
0.0500
0.0452
0.060
0.0453
0.0600
0.0680
0.030
0.0580
0.0500
0.0463
0.060
0.0457
0.0600
0.0690
0.030
0.0590
0.0500
0.0465
0.060
0.0463
0.0600
0.0699
0.030
0.0607
0.0500
0.0470
0.060
0.0480
0.0600
0.0704
0.030
0.0710
0.0500
0.0470
0.060
0.0481
0.0600
0.0720
0.030
0.0713
0.0500
0.0471
0.060
0.0490
0.0600
0.0760
0.030
0.0828
0.0500
0.0472
0.060
0.0496
0.0600
0.0770
0.050
0.0241
0.0500
0.0480
0.060
0.0523
0.0600
0.0871
0.050
0.0245
0.0500
0.0487
0.060
0.0525
0.0600
0.0943
0.050
0.0330
0.0500
0.0492
0.060
0.0554
0.0600
0.0958
0.050
0.0339
0.0500
0.0493
0.060
0.0560
0.0600
0.1206
0.050
0.0341
0.0500
0.0497
0.060
0.0570
0.0600
0.1255
0.050
0.0346
0.0500
0.0498
0.060
0.0575
0.1000
0.0452
0.050
0.0372
0.0500
0.0510
0.060
0.0580
0.1000
0.0547
0.050
0.0380
0.0500
0.0515
0.060
0.0609
0.1000
0.0621
0.050
0.0386
0.0500
0.0532
0.060
0.0640
0.1000
0.0680
0.050
0.0389
0.0500
0.0535
0.060
0.0653
0.1000
0.0716
0.050
0.0390
0.0500
0.0554
0.060
0.0659
0.1000
0.0720
0.050
0.0400
0.0500
0.0563
0.060
0.0660
0.1000
0.0730
0.050
0.0405
0.0500
0.0633
0.060
0.0660
0.1000
0.0757
0.050
0.0424
0.0500
0.0644
0.060
0.0680
0.1000
0.0760
0.050
0.0429
0.0500
0.0660
0.060
0.0690
0.1000
0.0764
0.050
0.0432
0.0500
0.0693
0.060
0.0699
0.1000
0.0764
0.050
0.0440
0.0500
0.0729
0.060
0.0704
0.1000
0.0790
0.050
0.0445
0.0600
0.0289
0.060
0.0720
0.1000
0.0814
0.050
0.0452
0.0600
0.0329
0.060
0.0760
0.1000
0.0820
0.050
0.0463
0.0600
0.0360
0.060
0.0770
0.1000
0.0830
0.050
0.0465
0.0600
0.0373
0.060
0.0804
0.1000
0.0838
0.050
0.0470
0.0600
0.0395
0.060
0.0816
0.1000
0.0840
0.050
0.0470
0.0600
0.0396
0.060
0.0871
0.1000
0.0860
0.050
0.0471
0.0600
0.0420
0.060
0.0910
0.1000
0.0875
0.050
0.0472
0.0600
0.0421
0.060
0.0943
0.1000
0.0880
0.050
0.0480
0.0600
0.0423
0.060
0.0958
0.1000
0.0880
0.050
0.0487
0.0600
0.0434
0.060
0.1007
0.1000
0.0902
0.050
0.0492
0.0600
0.0458
0.060
0.1206
0.1000
0.0913
0.050
0.0493
0.0600
0.0460
0.060
0.1255
0.1000
0.0929
0.050
0.0497
0.0600
0.0460
0.100
0.0452
0.1000
0.0931
0.050
0.0498
0.0600
0.0472
0.100
0.0547
0.1000
0.0953
0.050
0.0510
0.0600
0.0488
0.100
0.0621
0.1000
0.0953
0.050
0.0515
0.0600
0.0490
0.100
0.0650
0.1000
0.0960
0.050
0.0532
0.0600
0.0490
0.100
0.0670
0.1000
0.0970
0.050
0.0534
0.0600
0.0491
Page
5
of
15
Attachment
2.9
From
16­
A1­
OR
From
16­
A1­
DL­
OR
From
16­
A2­
OR
From
16­
A2­
DL­
OR
Conc
Result
Conc
Result
Conc
Result
Conc
Result
0.100
0.0680
0.1000
0.0981
0.050
0.0535
0.0600
0.0492
0.100
0.0716
0.1000
0.0987
0.050
0.0554
0.0600
0.0526
0.100
0.0720
0.1000
0.0996
0.050
0.0563
0.0600
0.0540
0.100
0.0730
0.1000
0.1012
0.050
0.0623
0.0600
0.0542
0.100
0.0757
0.1000
0.1024
0.050
0.0633
0.0600
0.0550
0.100
0.0760
0.1000
0.1101
0.050
0.0644
0.0600
0.0552
0.100
0.0764
0.1000
0.1107
0.050
0.0660
0.0600
0.0573
0.100
0.0764
0.1000
0.1152
0.050
0.0667
0.0600
0.0580
0.100
0.0790
0.1000
0.1160
0.050
0.0693
0.0600
0.0589
0.100
0.0814
0.1000
0.1161
0.050
0.0698
0.0600
0.0600
0.100
0.0820
0.1000
0.1180
0.050
0.0729
0.0600
0.0601
0.100
0.0830
0.1200
0.0487
0.060
0.0289
0.0600
0.0603
0.100
0.0838
0.1200
0.0514
0.060
0.0289
0.0600
0.0607
0.100
0.0840
0.1200
0.0697
0.060
0.0329
0.0600
0.0610
0.100
0.0860
0.1200
0.0713
0.060
0.0343
0.0600
0.0613
0.100
0.0875
0.1200
0.0770
0.060
0.0360
0.0600
0.0623
0.100
0.0880
0.1200
0.0799
0.060
0.0373
0.0600
0.0660
0.100
0.0880
0.1200
0.0817
0.060
0.0395
0.0600
0.0663
0.100
0.0902
0.1200
0.0830
0.060
0.0396
0.0600
0.0673
0.100
0.0913
0.1200
0.0867
0.060
0.0420
0.0600
0.0681
0.100
0.0929
0.1200
0.0875
0.060
0.0421
0.0600
0.0722
0.100
0.0931
0.1200
0.0880
0.060
0.0423
0.0600
0.0741
0.100
0.0953
0.1200
0.0881
0.060
0.0434
0.0600
0.0780
0.100
0.0953
0.1200
0.0883
0.060
0.0458
0.0600
0.0820
0.100
0.0960
0.1200
0.0887
0.060
0.0460
0.0600
0.0840
0.100
0.0970
0.1200
0.0912
0.060
0.0460
0.0600
0.0954
0.100
0.0981
0.1200
0.1015
0.060
0.0472
0.0600
0.1030
0.100
0.0987
0.1200
0.1020
0.060
0.0488
0.1000
0.0358
0.100
0.0996
0.1200
0.1022
0.060
0.0490
0.1000
0.0550
0.100
0.1012
0.1200
0.1037
0.060
0.0490
0.1000
0.0650
0.100
0.1024
0.1200
0.1074
0.060
0.0491
0.1000
0.0650
0.100
0.1101
0.1200
0.1085
0.060
0.0492
0.1000
0.0657
0.100
0.1107
0.1200
0.1100
0.060
0.0526
0.1000
0.0659
0.100
0.1152
0.1200
0.1118
0.060
0.0540
0.1000
0.0671
0.100
0.1154
0.1200
0.1136
0.060
0.0542
0.1000
0.0680
0.100
0.1160
0.1200
0.1139
0.060
0.0550
0.1000
0.0700
0.100
0.1161
0.1200
0.1165
0.060
0.0552
0.1000
0.0721
0.100
0.1180
0.1200
0.1170
0.060
0.0573
0.1000
0.0731
0.100
0.1319
0.1200
0.1170
0.060
0.0580
0.1000
0.0749
0.100
0.1432
0.1200
0.1170
0.060
0.0589
0.1000
0.0773
0.100
0.1576
0.1200
0.1180
0.060
0.0600
0.1000
0.0777
0.120
0.0487
0.1200
0.1200
0.060
0.0601
0.1000
0.0789
0.120
0.0514
0.1200
0.1208
0.060
0.0603
0.1000
0.0803
0.120
0.0600
0.1200
0.1222
0.060
0.0607
0.1000
0.0820
0.120
0.0697
0.1200
0.1250
0.060
0.0610
0.1000
0.0823
0.120
0.0713
0.1200
0.1257
0.060
0.0613
0.1000
0.0834
0.120
0.0770
0.1200
0.1280
0.060
0.0623
0.1000
0.0837
0.120
0.0799
0.1200
0.1289
0.060
0.0660
0.1000
0.0840
0.120
0.0817
0.1200
0.1303
0.060
0.0663
0.1000
0.0840
0.120
0.0830
0.1200
0.1342
0.060
0.0663
0.1000
0.0856
Page
6
of
15
Attachment
2.9
From
16­
A1­
OR
From
16­
A1­
DL­
OR
From
16­
A2­
OR
From
16­
A2­
DL­
OR
Conc
Result
Conc
Result
Conc
Result
Conc
Result
0.120
0.0867
0.1200
0.1344
0.060
0.0673
0.1000
0.0860
0.120
0.0875
0.1200
0.1354
0.060
0.0681
0.1000
0.0880
0.120
0.0880
0.1200
0.1423
0.060
0.0722
0.1000
0.0904
0.120
0.0881
0.1200
0.1500
0.060
0.0741
0.1000
0.0905
0.120
0.0883
0.2000
0.1152
0.060
0.0767
0.1000
0.0910
0.120
0.0887
0.2000
0.1310
0.060
0.0780
0.1000
0.0910
0.120
0.0910
0.2000
0.1337
0.060
0.0820
0.1000
0.0915
0.120
0.0912
0.2000
0.1360
0.060
0.0840
0.1000
0.0918
0.120
0.1015
0.2000
0.1360
0.060
0.0954
0.1000
0.0936
0.120
0.1020
0.2000
0.1380
0.060
0.1030
0.1000
0.0944
0.120
0.1022
0.2000
0.1390
0.100
0.0358
0.1000
0.0952
0.120
0.1037
0.2000
0.1480
0.100
0.0550
0.1000
0.0990
0.120
0.1043
0.2000
0.1539
0.100
0.0650
0.1000
0.0990
0.120
0.1074
0.2000
0.1557
0.100
0.0650
0.1000
0.0991
0.120
0.1085
0.2000
0.1560
0.100
0.0657
0.1000
0.0996
0.120
0.1100
0.2000
0.1600
0.100
0.0659
0.1000
0.1008
0.120
0.1118
0.2000
0.1650
0.100
0.0671
0.1000
0.1017
0.120
0.1136
0.2000
0.1672
0.100
0.0672
0.1000
0.1057
0.120
0.1139
0.2000
0.1700
0.100
0.0680
0.1000
0.1073
0.120
0.1165
0.2000
0.1713
0.100
0.0700
0.1000
0.1110
0.120
0.1170
0.2000
0.1725
0.100
0.0721
0.1000
0.1270
0.120
0.1170
0.2000
0.1740
0.100
0.0731
0.1200
0.0537
0.120
0.1170
0.2000
0.1761
0.100
0.0749
0.1200
0.0777
0.120
0.1180
0.2000
0.1763
0.100
0.0773
0.1200
0.0778
0.120
0.1200
0.2000
0.1769
0.100
0.0777
0.1200
0.0782
0.120
0.1208
0.2000
0.1780
0.100
0.0789
0.1200
0.0787
0.120
0.1222
0.2000
0.1788
0.100
0.0803
0.1200
0.0790
0.120
0.1250
0.2000
0.1795
0.100
0.0820
0.1200
0.0800
0.120
0.1257
0.2000
0.1845
0.100
0.0823
0.1200
0.0820
0.120
0.1280
0.2000
0.1860
0.100
0.0834
0.1200
0.0830
0.120
0.1289
0.2000
0.1891
0.100
0.0837
0.1200
0.0872
0.120
0.1303
0.2000
0.1903
0.100
0.0840
0.1200
0.0930
0.120
0.1342
0.2000
0.1903
0.100
0.0840
0.1200
0.0934
0.120
0.1344
0.2000
0.1945
0.100
0.0856
0.1200
0.0944
0.120
0.1354
0.2000
0.1948
0.100
0.0860
0.1200
0.0957
0.120
0.1423
0.2000
0.1952
0.100
0.0880
0.1200
0.0965
0.120
0.1430
0.2000
0.1955
0.100
0.0880
0.1200
0.0984
0.120
0.1500
0.2000
0.1960
0.100
0.0890
0.1200
0.0989
0.200
0.1152
0.2000
0.1970
0.100
0.0904
0.1200
0.0991
0.200
0.1250
0.2000
0.1977
0.100
0.0905
0.1200
0.1010
0.200
0.1310
0.2000
0.1990
0.100
0.0910
0.1200
0.1060
0.200
0.1337
0.2000
0.2005
0.100
0.0910
0.1200
0.1064
0.200
0.1360
0.2000
0.2010
0.100
0.0915
0.1200
0.1072
0.200
0.1360
0.2000
0.2067
0.100
0.0918
0.1200
0.1077
0.200
0.1380
0.2000
0.2120
0.100
0.0936
0.1200
0.1090
0.200
0.1390
0.2000
0.2212
0.100
0.0944
0.1200
0.1103
0.200
0.1480
0.2000
0.2400
0.100
0.0952
0.1200
0.1110
0.200
0.1539
0.2400
0.0976
0.100
0.0990
0.1200
0.1163
0.200
0.1557
0.2400
0.1030
0.100
0.0990
0.1200
0.1172
0.200
0.1560
0.2400
0.1260
0.100
0.0991
0.1200
0.1179
Page
7
of
15
Attachment
2.9
From
16­
A1­
OR
From
16­
A1­
DL­
OR
From
16­
A2­
OR
From
16­
A2­
DL­
OR
Conc
Result
Conc
Result
Conc
Result
Conc
Result
0.200
0.1600
0.2400
0.1373
0.100
0.0996
0.1200
0.1180
0.200
0.1650
0.2400
0.1377
0.100
0.1008
0.1200
0.1200
0.200
0.1660
0.2400
0.1422
0.100
0.1017
0.1200
0.1212
0.200
0.1672
0.2400
0.1502
0.100
0.1057
0.1200
0.1216
0.200
0.1700
0.2400
0.1513
0.100
0.1073
0.1200
0.1217
0.200
0.1713
0.2400
0.1682
0.100
0.1095
0.1200
0.1223
0.200
0.1725
0.2400
0.1690
0.100
0.1110
0.1200
0.1233
0.200
0.1740
0.2400
0.1690
0.100
0.1270
0.1200
0.1250
0.200
0.1761
0.2400
0.1733
0.100
0.1290
0.1200
0.1277
0.200
0.1763
0.2400
0.1742
0.120
0.0537
0.1200
0.1290
0.200
0.1769
0.2400
0.1771
0.120
0.0640
0.1200
0.1291
0.200
0.1780
0.2400
0.1774
0.120
0.0709
0.1200
0.1331
0.200
0.1788
0.2400
0.1810
0.120
0.0777
0.1200
0.1337
0.200
0.1795
0.2400
0.1810
0.120
0.0778
0.1200
0.1340
0.200
0.1845
0.2400
0.1828
0.120
0.0782
0.1200
0.1480
0.200
0.1860
0.2400
0.1847
0.120
0.0787
0.1200
0.1500
0.200
0.1891
0.2400
0.1861
0.120
0.0790
0.2000
0.1030
0.200
0.1903
0.2400
0.1870
0.120
0.0800
0.2000
0.1130
0.200
0.1903
0.2400
0.1944
0.120
0.0820
0.2000
0.1225
0.200
0.1945
0.2400
0.1986
0.120
0.0830
0.2000
0.1261
0.200
0.1948
0.2400
0.2027
0.120
0.0872
0.2000
0.1314
0.200
0.1952
0.2400
0.2030
0.120
0.0930
0.2000
0.1351
0.200
0.1955
0.2400
0.2059
0.120
0.0934
0.2000
0.1390
0.200
0.1960
0.2400
0.2090
0.120
0.0944
0.2000
0.1400
0.200
0.1970
0.2400
0.2090
0.120
0.0957
0.2000
0.1412
0.200
0.1977
0.2400
0.2100
0.120
0.0965
0.2000
0.1425
0.200
0.1990
0.2400
0.2110
0.120
0.0984
0.2000
0.1426
0.200
0.2005
0.2400
0.2120
0.120
0.0989
0.2000
0.1451
0.200
0.2010
0.2400
0.2164
0.120
0.0991
0.2000
0.1455
0.200
0.2067
0.2400
0.2170
0.120
0.1010
0.2000
0.1470
0.200
0.2082
0.2400
0.2176
0.120
0.1060
0.2000
0.1475
0.200
0.2095
0.2400
0.2200
0.120
0.1064
0.2000
0.1487
0.200
0.2120
0.2400
0.2228
0.120
0.1072
0.2000
0.1500
0.200
0.2143
0.2400
0.2243
0.120
0.1077
0.2000
0.1550
0.200
0.2212
0.2400
0.2294
0.120
0.1090
0.2000
0.1550
0.200
0.2400
0.2400
0.2346
0.120
0.1103
0.2000
0.1577
0.240
0.0976
0.2400
0.2373
0.120
0.1110
0.2000
0.1610
0.240
0.1030
0.2400
0.2396
0.120
0.1163
0.2000
0.1681
0.240
0.1150
0.2400
0.2497
0.120
0.1172
0.2000
0.1684
0.240
0.1260
0.2400
0.2500
0.120
0.1179
0.2000
0.1690
0.240
0.1373
0.2400
0.2616
0.120
0.1180
0.2000
0.1712
0.240
0.1377
0.5000
0.1660
0.120
0.1183
0.2000
0.1722
0.240
0.1422
0.5000
0.2536
0.120
0.1200
0.2000
0.1726
0.240
0.1502
0.5000
0.2552
0.120
0.1212
0.2000
0.1727
0.240
0.1513
0.5000
0.2580
0.120
0.1216
0.2000
0.1744
0.240
0.1682
0.5000
0.2830
0.120
0.1217
0.2000
0.1770
0.240
0.1690
0.5000
0.2840
0.120
0.1223
0.2000
0.1777
0.240
0.1690
0.5000
0.3013
0.120
0.1233
0.2000
0.1794
0.240
0.1733
0.5000
0.3090
0.120
0.1250
0.2000
0.1800
0.240
0.1742
0.5000
0.3321
0.120
0.1277
0.2000
0.1807
Page
8
of
15
Attachment
2.9
From
16­
A1­
OR
From
16­
A1­
DL­
OR
From
16­
A2­
OR
From
16­
A2­
DL­
OR
Conc
Result
Conc
Result
Conc
Result
Conc
Result
0.240
0.1771
0.5000
0.3360
0.120
0.1290
0.2000
0.1814
0.240
0.1774
0.5000
0.3377
0.120
0.1291
0.2000
0.1854
0.240
0.1810
0.5000
0.3390
0.120
0.1331
0.2000
0.1857
0.240
0.1810
0.5000
0.3390
0.120
0.1337
0.2000
0.1862
0.240
0.1828
0.5000
0.3469
0.120
0.1340
0.2000
0.1870
0.240
0.1847
0.5000
0.3540
0.120
0.1357
0.2000
0.1940
0.240
0.1861
0.5000
0.3642
0.120
0.1480
0.2000
0.1993
0.240
0.1870
0.5000
0.3647
0.120
0.1500
0.2000
0.2177
0.240
0.1944
0.5000
0.3732
0.200
0.0540
0.2000
0.2200
0.240
0.1986
0.5000
0.3744
0.200
0.1017
0.2400
0.1021
0.240
0.2027
0.5000
0.3746
0.200
0.1030
0.2400
0.1290
0.240
0.2030
0.5000
0.3877
0.200
0.1130
0.2400
0.1390
0.240
0.2059
0.5000
0.3890
0.200
0.1225
0.2400
0.1480
0.240
0.2090
0.5000
0.3893
0.200
0.1261
0.2400
0.1490
0.240
0.2090
0.5000
0.3937
0.200
0.1314
0.2400
0.1500
0.240
0.2100
0.5000
0.4000
0.200
0.1351
0.2400
0.1544
0.240
0.2110
0.5000
0.4036
0.200
0.1390
0.2400
0.1550
0.240
0.2120
0.5000
0.4105
0.200
0.1400
0.2400
0.1589
0.240
0.2164
0.5000
0.4120
0.200
0.1412
0.2400
0.1611
0.240
0.2170
0.5000
0.4124
0.200
0.1425
0.2400
0.1620
0.240
0.2176
0.5000
0.4197
0.200
0.1426
0.2400
0.1705
0.240
0.2200
0.5000
0.4250
0.200
0.1451
0.2400
0.1764
0.240
0.2228
0.5000
0.4274
0.200
0.1455
0.2400
0.1833
0.240
0.2243
0.5000
0.4409
0.200
0.1470
0.2400
0.1843
0.240
0.2294
0.5000
0.4448
0.200
0.1475
0.2400
0.1898
0.240
0.2346
0.5000
0.4585
0.200
0.1487
0.2400
0.1917
0.240
0.2373
0.5000
0.4599
0.200
0.1500
0.2400
0.1951
0.240
0.2396
0.5000
0.4709
0.200
0.1550
0.2400
0.1960
0.240
0.2471
0.5000
0.4767
0.200
0.1550
0.2400
0.1987
0.240
0.2482
0.5000
0.4797
0.200
0.1577
0.2400
0.2000
0.240
0.2497
0.5000
0.4930
0.200
0.1610
0.2400
0.2008
0.240
0.2500
0.5000
0.5035
0.200
0.1681
0.2400
0.2031
0.240
0.2526
0.5000
0.5047
0.200
0.1684
0.2400
0.2043
0.240
0.2616
0.5000
0.5600
0.200
0.1690
0.2400
0.2044
0.240
0.2630
0.6000
0.2270
0.200
0.1712
0.2400
0.2051
0.240
0.3352
0.6000
0.3110
0.200
0.1722
0.2400
0.2064
0.500
0.1570
0.6000
0.3318
0.200
0.1726
0.2400
0.2097
0.500
0.1660
0.6000
0.3340
0.200
0.1727
0.2400
0.2097
0.500
0.2536
0.6000
0.3495
0.200
0.1744
0.2400
0.2122
0.500
0.2552
0.6000
0.3503
0.200
0.1770
0.2400
0.2129
0.500
0.2580
0.6000
0.3543
0.200
0.1777
0.2400
0.2150
0.500
0.2830
0.6000
0.3617
0.200
0.1794
0.2400
0.2180
0.500
0.2840
0.6000
0.3636
0.200
0.1800
0.2400
0.2244
0.500
0.3013
0.6000
0.3880
0.200
0.1800
0.2400
0.2250
0.500
0.3090
0.6000
0.4050
0.200
0.1807
0.2400
0.2270
0.500
0.3321
0.6000
0.4063
0.200
0.1814
0.2400
0.2300
0.500
0.3360
0.6000
0.4121
0.200
0.1847
0.2400
0.2340
0.500
0.3377
0.6000
0.4144
0.200
0.1854
0.2400
0.2340
0.500
0.3390
0.6000
0.4190
0.200
0.1857
0.2400
0.2500
0.500
0.3390
0.6000
0.4330
0.200
0.1862
0.2400
0.2620
Page
9
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15
Attachment
2.9
From
16­
A1­
OR
From
16­
A1­
DL­
OR
From
16­
A2­
OR
From
16­
A2­
DL­
OR
Conc
Result
Conc
Result
Conc
Result
Conc
Result
0.500
0.3469
0.6000
0.4391
0.200
0.1870
0.2400
0.2659
0.500
0.3490
0.6000
0.4400
0.200
0.1940
0.2400
0.2664
0.500
0.3540
0.6000
0.4454
0.200
0.1993
0.2400
0.2702
0.500
0.3642
0.6000
0.4480
0.200
0.2123
0.2400
0.2885
0.500
0.3647
0.6000
0.4498
0.200
0.2167
0.5000
0.1760
0.500
0.3732
0.6000
0.4514
0.200
0.2177
0.5000
0.1847
0.500
0.3744
0.6000
0.4553
0.200
0.2200
0.5000
0.2110
0.500
0.3746
0.6000
0.4562
0.200
0.2700
0.5000
0.2596
0.500
0.3877
0.6000
0.4568
0.240
0.1021
0.5000
0.2630
0.500
0.3890
0.6000
0.4600
0.240
0.1236
0.5000
0.2660
0.500
0.3893
0.6000
0.4617
0.240
0.1290
0.5000
0.2690
0.500
0.3937
0.6000
0.4640
0.240
0.1390
0.5000
0.2738
0.500
0.4000
0.6000
0.4694
0.240
0.1480
0.5000
0.2931
0.500
0.4036
0.6000
0.4790
0.240
0.1490
0.5000
0.2953
0.500
0.4105
0.6000
0.4811
0.240
0.1500
0.5000
0.2976
0.500
0.4120
0.6000
0.4900
0.240
0.1544
0.5000
0.2979
0.500
0.4124
0.6000
0.4964
0.240
0.1550
0.5000
0.3001
0.500
0.4197
0.6000
0.4977
0.240
0.1589
0.5000
0.3019
0.500
0.4233
0.6000
0.5022
0.240
0.1611
0.5000
0.3110
0.500
0.4250
0.6000
0.5100
0.240
0.1620
0.5000
0.3115
0.500
0.4274
0.6000
0.5106
0.240
0.1705
0.5000
0.3249
0.500
0.4274
0.6000
0.5185
0.240
0.1764
0.5000
0.3317
0.500
0.4382
0.6000
0.5237
0.240
0.1833
0.5000
0.3384
0.500
0.4409
0.6000
0.5431
0.240
0.1841
0.5000
0.3384
0.500
0.4448
0.6000
0.5600
0.240
0.1843
0.5000
0.3400
0.500
0.4585
0.6000
0.5715
0.240
0.1898
0.5000
0.3400
0.500
0.4599
0.6000
0.5922
0.240
0.1917
0.5000
0.3412
0.500
0.4709
1.0000
0.4450
0.240
0.1951
0.5000
0.3488
0.500
0.4767
1.0000
0.5490
0.240
0.1960
0.5000
0.3524
0.500
0.4797
1.0000
0.5500
0.240
0.1987
0.5000
0.3710
0.500
0.4930
1.0000
0.5517
0.240
0.2000
0.5000
0.3718
0.500
0.5035
1.0000
0.5634
0.240
0.2008
0.5000
0.3750
0.500
0.5047
1.0000
0.5891
0.240
0.2031
0.5000
0.3793
0.500
0.5600
1.0000
0.5940
0.240
0.2043
0.5000
0.3932
0.500
0.5743
1.0000
0.6150
0.240
0.2044
0.5000
0.3946
0.600
0.2110
1.0000
0.6267
0.240
0.2051
0.5000
0.4084
0.600
0.2270
1.0000
0.6271
0.240
0.2064
0.5000
0.4090
0.600
0.3110
1.0000
0.6550
0.240
0.2097
0.5000
0.4175
0.600
0.3318
1.0000
0.6577
0.240
0.2097
0.5000
0.4257
0.600
0.3340
1.0000
0.6610
0.240
0.2122
0.5000
0.4370
0.600
0.3495
1.0000
0.6712
0.240
0.2129
0.5000
0.4400
0.600
0.3503
1.0000
0.6771
0.240
0.2150
0.5000
0.4419
0.600
0.3543
1.0000
0.6776
0.240
0.2180
0.5000
0.4450
0.600
0.3617
1.0000
0.7120
0.240
0.2210
0.5000
0.4563
0.600
0.3636
1.0000
0.7144
0.240
0.2244
0.5000
0.4740
0.600
0.3880
1.0000
0.7300
0.240
0.2250
0.5000
0.4768
0.600
0.4050
1.0000
0.7398
0.240
0.2270
0.5000
0.4826
0.600
0.4063
1.0000
0.7500
0.240
0.2300
0.5000
0.5547
0.600
0.4121
1.0000
0.7517
0.240
0.2340
0.6000
0.2867
0.600
0.4144
1.0000
0.7533
0.240
0.2340
0.6000
0.2930
Page
10
of
15
Attachment
2.9
From
16­
A1­
OR
From
16­
A1­
DL­
OR
From
16­
A2­
OR
From
16­
A2­
DL­
OR
Conc
Result
Conc
Result
Conc
Result
Conc
Result
0.600
0.4190
1.0000
0.7650
0.240
0.2500
0.6000
0.2930
0.600
0.4330
1.0000
0.7663
0.240
0.2587
0.6000
0.3020
0.600
0.4391
1.0000
0.7700
0.240
0.2620
0.6000
0.3027
0.600
0.4400
1.0000
0.7712
0.240
0.2659
0.6000
0.3241
0.600
0.4454
1.0000
0.7795
0.240
0.2664
0.6000
0.3280
0.600
0.4480
1.0000
0.8035
0.240
0.2702
0.6000
0.3429
0.600
0.4498
1.0000
0.8070
0.240
0.2885
0.6000
0.3430
0.600
0.4514
1.0000
0.8128
0.500
0.1760
0.6000
0.3535
0.600
0.4553
1.0000
0.8134
0.500
0.1847
0.6000
0.3756
0.600
0.4562
1.0000
0.8224
0.500
0.2110
0.6000
0.3795
0.600
0.4568
1.0000
0.8573
0.500
0.2596
0.6000
0.3850
0.600
0.4600
1.0000
0.8600
0.500
0.2630
0.6000
0.4000
0.600
0.4617
1.0000
0.8635
0.500
0.2660
0.6000
0.4032
0.600
0.4640
1.0000
0.8776
0.500
0.2690
0.6000
0.4060
0.600
0.4694
1.0000
0.8879
0.500
0.2738
0.6000
0.4074
0.600
0.4790
1.0000
0.8970
0.500
0.2779
0.6000
0.4130
0.600
0.4811
1.0000
0.9257
0.500
0.2931
0.6000
0.4217
0.600
0.4900
1.0000
0.9507
0.500
0.2953
0.6000
0.4313
0.600
0.4920
1.0000
1.0238
0.500
0.2976
0.6000
0.4400
0.600
0.4964
1.0000
1.0308
0.500
0.2979
0.6000
0.4436
0.600
0.4977
1.2000
0.4960
0.500
0.3001
0.6000
0.4447
0.600
0.5022
1.2000
0.5520
0.500
0.3019
0.6000
0.4578
0.600
0.5100
1.2000
0.6354
0.500
0.3110
0.6000
0.4640
0.600
0.5106
1.2000
0.6927
0.500
0.3115
0.6000
0.4666
0.600
0.5185
1.2000
0.6972
0.500
0.3249
0.6000
0.4680
0.600
0.5237
1.2000
0.7071
0.500
0.3317
0.6000
0.4701
0.600
0.5431
1.2000
0.7073
0.500
0.3384
0.6000
0.4728
0.600
0.5589
1.2000
0.7414
0.500
0.3384
0.6000
0.4730
0.600
0.5600
1.2000
0.7530
0.500
0.3400
0.6000
0.4806
0.600
0.5715
1.2000
0.7750
0.500
0.3400
0.6000
0.4816
0.600
0.5834
1.2000
0.7760
0.500
0.3412
0.6000
0.4826
0.600
0.5879
1.2000
0.8036
0.500
0.3488
0.6000
0.4877
0.600
0.5922
1.2000
0.8240
0.500
0.3524
0.6000
0.4960
0.600
0.6528
1.2000
0.8420
0.500
0.3710
0.6000
0.4994
1.000
0.3820
1.2000
0.8681
0.500
0.3718
0.6000
0.5060
1.000
0.4450
1.2000
0.8698
0.500
0.3750
0.6000
0.5123
1.000
0.5490
1.2000
0.8755
0.500
0.3793
0.6000
0.5304
1.000
0.5500
1.2000
0.8860
0.500
0.3932
0.6000
0.5450
1.000
0.5517
1.2000
0.9026
0.500
0.3946
0.6000
0.5799
1.000
0.5634
1.2000
0.9030
0.500
0.4084
0.6000
0.5806
1.000
0.5891
1.2000
0.9170
0.500
0.4090
0.6000
0.5930
1.000
0.5940
1.2000
0.9194
0.500
0.4100
0.6000
0.6200
1.000
0.6150
1.2000
0.9209
0.500
0.4175
0.6000
0.6215
1.000
0.6267
1.2000
0.9463
0.500
0.4257
0.6000
0.6486
1.000
0.6271
1.2000
0.9530
0.500
0.4370
1.0000
0.4630
1.000
0.6290
1.2000
0.9636
0.500
0.4383
1.0000
0.4860
1.000
0.6550
1.2000
0.9650
0.500
0.4400
1.0000
0.4887
1.000
0.6577
1.2000
0.9717
0.500
0.4419
1.0000
0.4980
1.000
0.6610
1.2000
0.9780
0.500
0.4450
1.0000
0.4990
1.000
0.6712
1.2000
0.9827
0.500
0.4554
1.0000
0.5027
Page
11
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15
Attachment
2.9
From
16­
A1­
OR
From
16­
A1­
DL­
OR
From
16­
A2­
OR
From
16­
A2­
DL­
OR
Conc
Result
Conc
Result
Conc
Result
Conc
Result
1.000
0.6771
1.2000
0.9843
0.500
0.4563
1.0000
0.5260
1.000
0.6776
1.2000
0.9876
0.500
0.4740
1.0000
0.5467
1.000
0.7120
1.2000
0.9900
0.500
0.4768
1.0000
0.5476
1.000
0.7144
1.2000
1.0060
0.500
0.4826
1.0000
0.5604
1.000
0.7300
1.2000
1.0074
0.500
0.5272
1.0000
0.5850
1.000
0.7398
1.2000
1.0949
0.500
0.5547
1.0000
0.5980
1.000
0.7500
1.2000
1.1000
0.500
0.6057
1.0000
0.6034
1.000
0.7517
1.2000
1.1030
0.600
0.2404
1.0000
0.6181
1.000
0.7533
1.2000
1.1145
0.600
0.2867
1.0000
0.6458
1.000
0.7650
1.2000
1.1430
0.600
0.2930
1.0000
0.6495
1.000
0.7663
1.2000
1.2338
0.600
0.2930
1.0000
0.6531
1.000
0.7700
0.600
0.3020
1.0000
0.6572
1.000
0.7712
0.600
0.3027
1.0000
0.6630
1.000
0.7795
0.600
0.3241
1.0000
0.6673
1.000
0.8035
0.600
0.3280
1.0000
0.6683
1.000
0.8070
0.600
0.3429
1.0000
0.6810
1.000
0.8128
0.600
0.3430
1.0000
0.6840
1.000
0.8134
0.600
0.3535
1.0000
0.6912
1.000
0.8181
0.600
0.3756
1.0000
0.7004
1.000
0.8224
0.600
0.3795
1.0000
0.7020
1.000
0.8573
0.600
0.3850
1.0000
0.7131
1.000
0.8600
0.600
0.3936
1.0000
0.7240
1.000
0.8635
0.600
0.4000
1.0000
0.7273
1.000
0.8776
0.600
0.4032
1.0000
0.7480
1.000
0.8879
0.600
0.4060
1.0000
0.7574
1.000
0.8970
0.600
0.4074
1.0000
0.7690
1.000
0.9032
0.600
0.4130
1.0000
0.8000
1.000
0.9257
0.600
0.4217
1.0000
0.8237
1.000
0.9507
0.600
0.4313
1.0000
0.8310
1.000
1.0238
0.600
0.4400
1.0000
0.8337
1.000
1.0308
0.600
0.4436
1.0000
0.8410
1.000
1.2030
0.600
0.4447
1.0000
0.8571
1.200
0.3090
0.600
0.4578
1.0000
0.8877
1.200
0.4960
0.600
0.4640
1.0000
0.8890
1.200
0.5520
0.600
0.4666
1.0000
0.8952
1.200
0.6354
0.600
0.4680
1.0000
0.9084
1.200
0.6630
0.600
0.4701
1.0000
0.9433
1.200
0.6927
0.600
0.4728
1.0000
0.9750
1.200
0.6972
0.600
0.4730
1.2000
0.6000
1.200
0.7071
0.600
0.4806
1.2000
0.6070
1.200
0.7073
0.600
0.4816
1.2000
0.6100
1.200
0.7414
0.600
0.4826
1.2000
0.6150
1.200
0.7530
0.600
0.4877
1.2000
0.6190
1.200
0.7750
0.600
0.4960
1.2000
0.6470
1.200
0.7760
0.600
0.4994
1.2000
0.6609
1.200
0.8036
0.600
0.5060
1.2000
0.6685
1.200
0.8240
0.600
0.5123
1.2000
0.6943
1.200
0.8420
0.600
0.5187
1.2000
0.7100
1.200
0.8681
0.600
0.5304
1.2000
0.7110
1.200
0.8698
0.600
0.5450
1.2000
0.7194
Page
12
of
15
Attachment
2.9
From
16­
A1­
OR
From
16­
A2­
OR
From
16­
A2­
DL­
OR
Conc
Result
Conc
Result
Conc
Result
1.200
0.8920
0.600
0.5930
1.2000
0.7385
1.200
0.9026
0.600
0.6200
1.2000
0.7460
1.200
0.9030
0.600
0.6215
1.2000
0.7673
1.200
0.9170
0.600
0.6486
1.2000
0.8343
1.200
0.9194
0.600
0.6900
1.2000
0.8360
1.200
0.9209
1.000
0.4630
1.2000
0.8496
1.200
0.9463
1.000
0.4860
1.2000
0.8503
1.200
0.9530
1.000
0.4887
1.2000
0.8648
1.200
0.9636
1.000
0.4980
1.2000
0.8650
1.200
0.9650
1.000
0.4990
1.2000
0.8662
1.200
0.9717
1.000
0.5027
1.2000
0.8730
1.200
0.9780
1.000
0.5260
1.2000
0.8746
1.200
0.9827
1.000
0.5467
1.2000
0.9078
1.200
0.9843
1.000
0.5476
1.2000
0.9281
1.200
0.9876
1.000
0.5529
1.2000
0.9325
1.200
0.9900
1.000
0.5604
1.2000
0.9326
1.200
1.0060
1.000
0.5850
1.2000
0.9331
1.200
1.0074
1.000
0.5980
1.2000
0.9337
1.200
1.0800
1.000
0.6034
1.2000
0.9496
1.200
1.0949
1.000
0.6181
1.2000
0.9521
1.200
1.1000
1.000
0.6458
1.2000
0.9564
1.200
1.1030
1.000
0.6495
1.2000
0.9567
1.200
1.1133
1.000
0.6531
1.2000
0.9640
1.200
1.1145
1.000
0.6572
1.2000
0.9795
1.200
1.1430
1.000
0.6630
1.2000
1.0200
1.200
1.1490
1.000
0.6673
1.2000
1.0290
1.200
1.2338
1.000
0.6683
1.2000
1.0320
1.200
1.2380
1.000
0.6810
1.2000
1.1430
1.000
0.6840
1.2000
1.1586
1.000
0.6912
1.2000
1.2298
1.000
0.7004
1.2000
1.2500
1.000
0.7020
1.2000
1.2634
1.000
0.7131
1.000
0.7240
1.000
0.7273
1.000
0.7443
1.000
0.7480
1.000
0.7574
1.000
0.7690
1.000
0.8000
1.000
0.8237
1.000
0.8310
1.000
0.8337
1.000
0.8410
1.000
0.8571
1.000
0.8877
1.000
0.8890
1.000
0.8952
1.000
0.9084
1.000
0.9086
Page
13
of
15
Attachment
2.9
From
16­
A2­
OR
Conc
Result
1.000
0.9400
1.000
0.9433
1.000
0.9448
1.000
0.9750
1.000
1.1667
1.200
0.5059
1.200
0.6000
1.200
0.6070
1.200
0.6100
1.200
0.6150
1.200
0.6190
1.200
0.6470
1.200
0.6609
1.200
0.6685
1.200
0.6943
1.200
0.7100
1.200
0.7110
1.200
0.7194
1.200
0.7293
1.200
0.7320
1.200
0.7385
1.200
0.7460
1.200
0.7673
1.200
0.7782
1.200
0.8343
1.200
0.8360
1.200
0.8496
1.200
0.8503
1.200
0.8648
1.200
0.8650
1.200
0.8662
1.200
0.8730
1.200
0.8746
1.200
0.9078
1.200
0.9281
1.200
0.9325
1.200
0.9326
1.200
0.9331
1.200
0.9337
1.200
0.9496
1.200
0.9521
1.200
0.9564
1.200
0.9567
1.200
0.9640
1.200
0.9773
1.200
0.9795
1.200
1.0200
1.200
1.0290
1.200
1.0320
1.200
1.1430
Page
14
of
15
Attachment
2.9
From
16­
A2­
OR
Conc
Result
1.200
1.1586
1.200
1.2298
1.200
1.2500
1.200
1.2634
1.200
1.3257
Page
15
of
15
Attachment
4.1
LAB
A
LAB
B
LAB
C
LAB
D
LAB
E
LAB
F
LAB
G
LAB
H
LAB
I
LAB
J
TYPE
OF
CALIBRATION
CURVE
1ST
ORDER
1ST
ORDER
AVG.
CALIB.
FACTOR
AVG.
CALIB.
FACTOR
1ST
ORDER/
2ND
ORDER
AVG.
CALIB.
FACTOR
AVG.
CALIB.
FACTOR
AVG.
CALIB.
FACTOR
AVG.
CALIB.
FACTOR
AVG.
CALIB.
FACTOR
OR
1ST
ORDER
OR
2ND
ORDER
OR
1ST
ORDER
IS
CURVE
EXTRAPOLATED
THROUGH
ZERO
YES
YES
NO
YES
NO
NO
NUMBER
OF
CALIBRATION
LEVELS
6
5
5
5
6
6
5
5
8
5
CONC.
OF
CURVE
POINTS
0.05/
0.1/
0.5/
1.0/
2.0/
3.0
0.2/
0.5/
1.0/
1.5/
2.0
0.1/
0.2/
0.5/
1.0/
2.0
0.05/
0.2/
0.5/
1.0/
2.0
0.1/
0.2/
0.5/
1.0/
2.0/
4.0
0.05/
0.1/
0.2/
0.4/
0.8/
1.6
0.2/
0.4/
0.6/
0.8/
1.0
0.1/
0.5/
2.0/
4.0/
8.0
.04/.
1/.
2/.
25/.
4/.
5/
1/
2
0.05/
0.1/
0.25/
0.50/
1.0
NUMBER
OF
PEAKS
CALIBRATED
5
3
OR
MORE
5
5
5
5
5
OR
6
5
5
5
CALIBRATION
BASED
ON
HEIGHT
OR
AREA
AREA
AREA
HEIGHT
AREA
AREA
HEIGHT
AREA
AREA
AREA
AREA
ARE
ALL
CALIBRATED
PEAKS
FULLY
RESOLVED
NO
NO
N/
A
NO
NO
YES
YES
NO
NO
NO
TYPE
OF
GC
BEING
USED
HP5890
VARIAN
3700
OR
3800
HP6890
HP5890
VARIAN
3400
HP5890
VARIAN
3400
VARIAN
3400
VARIAN
3400
HP5890
TYPE
OF
DATA
SYSTEM
USED
TURBOCHROM
WATERS
TARGET
TURBOCHROM
VARIAN
STAR
TURBOCHROM
LAB
DEVELOPED
CHROMPERFECT
ACCESS
CHROM
HP
CHEMSTATION
SYSTEM
CARRIER
GAS
N/
A
HELIUM
HYDROGEN
HELIUM
N/
A
HELIUM
HELIUM
HELIUM
N/
A
HYDROGEN
RUN
TIME
OF
PCB
METHOD
40
MIN
25
MIN
12
MIN
14­
17
MIN
40
MIN
20
MIN
16
MIN
25
MIN
42
MIN
25
MIN
SURROGATE
RTS
TCMX/
DCB
9.0
MIN/
38.5
MIN
DCB
21MIN
1.93
MIN/
8.42
MIN
8.8MIN/
24.5MIN
5.6
MIN/
16.8
MIN
1.2MIN/
12.8MIN
3.5
MIN/
22
MIN
10
MIN/
35
MIN
6.7MIN/
17.7MIN
CLEAN­
UPS
USED
ON
SAMPLES
IN
STUDY
ACID/
COPPER/
FLORISIL
ACID/
COPPER/
FLORISIL
ACID/
COPPER/
FLORISIL
ACID/
COPPER
NONE
ACID/
COPPER/
FLORISIL
ACID/
COPPER
ACID/
COPPER/
FLORISIL
ACID/
COPPER/
FLORISIL
ACID/
COPPER/
FLORISIL
CARBOPREP
90SPE
DOES
THE
LAB
MAKE
USE
OF
BASELINE
SOME
CASES
NO
SOME
CASES
NOT
OFTEN
YES
YES
YES
YES
YES
NO
CONSTRUCTON
OPTIONS
IN
DATA
SYSTEM
4.1MIN/
16.3MIN
MMA
PCB
DETECTION
LIMIT
STUDY
­
LABORATORY
REPORT
SUMMERY
SHEET
Attachment
4.2
Aroclor
1016
Detection
vs
Concentration
70
49
23
5
2
1
1
1
16
20
28
22
8
3
1
0
14
31
49
73
90
96
98
99
0
10
20
30
40
50
60
70
80
90
100
0.005/
0.006
0.01/.
015
0.025/
0.03
.05/.
06
0.1/
0.12
0.2/
0.24
0.5/
0.6
1.0/
1.2
Concentration
(
UG/
L)

Percentage
of
Observations
Not
Detected
Qualified
Reported
Attachment
4.3
Aroclor
1260
Detection
vs
Concentration
57
24
4
2
0
0
0
0
26
30
26
17
12
1
46
70
81
88
98
100
100
17
0
10
20
30
40
50
60
70
80
90
100
0.005/
0.006
0.01/.
015
0.025/
0.03
0.05/
0.06
0.1/
0.12
0.2/
0.24
0.5/
0.6
1.0/
1.2
Concentration
(
UG/
L)

Percentage
of
Observations
Not
Detected
Qualified
Reported
Attachment
4.4
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
LAB
A
LAB
B
LAB
C
LAB
D
LAB
E
LAB
F
LAB
G
LAB
H
LAB
I
LAB
J
AROCLOR
1016
INDAVIDUAL
LAB
ACCURACY
FOR
ALL
CONCENTRATIONS
VALUES
IN
75%
­
125%
RANGE
VALUES
IN
50%
­
150%
RANGE
VALUES
IN
25%­
200%
RANGE
Attachment
4.5
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
LAB
A
LAB
B
LAB
C
LAB
D
LAB
E
LAB
F
LAB
G
LAB
H
LAB
I
LAB
J
AROCLOR
1260
INDAVIDUAL
LAB
ACCURACY
FOR
ALL
CONCENTRATIONS
VALUES
IN
75%­
125%
RANGE
VALUES
IN
50%­
150%
RANGE
VALUES
IN
25%­
200%
RANGE
Attachment
4.6
AROCLOR
1016
ACCURACY
RELATED
TO
CONCENTRATION
0
50
100
150
200
250
300
350
400
0.010/
0.015
0.025/
0.030
0.050/.
060
0.10/
0.12
0.20/
0.24
0.50/
0.60
1.0/
1.2
SAMPLE
CONCENTRATION
(
UG/
L)
AVG
%
RECOVERY
OF
10
SAMPLING
EVENTS
LAB
A
LAB
B
LAB
C
LAB
D
LAB
E
LAB
F
LAB
G
LAB
H
LAB
I
LAB
J
Attachment
4.7
ACCURACY
RATINGS
AVERAGE
RECOVERY
FOR
AROCLOR
1016
CONC.
1
CONC.
2
CONC.
3
CONC.
4
CONC.
5
CONC.
6
CONC.
7
CONC.
8
202%
127%
122%
89%
82%
92%
82%
76%

558%
158%
122%
90%
81%
82%
78%
73%

646%
259%
187%
162%
137%
100%
91%
94%

156%
144%
131%
87%
90%
92%
92%
87%

297%
108%
142%
92%
78%
66%
56%
52%

N/
A
173%
93%
93%
96%
90%
82%
76%

315%
223%
150%
107%
84%
75%
61%
64%

N/
A
115%
110%
94%
103%
81%
75%
72%

836%
347%
214%
148%
114%
90%
70%
79%

N/
A
167%
106%
103%
89%
90%
74%
78%
LAB
I
LAB
J
LAB
D
LAB
E
LAB
F
LAB
G
LAB
A
LAB
B
LAB
C
LAB
H
Attachment
4.8
AROCLOR
1260
ACCURACY
RELATED
TO
CONCENTRATION
0
50
100
150
200
250
300
350
0.010/
0.015
0.025/
0.030
0.050/
0.060
0.10/
0.12
0.20/
0.24
0.50/
0.60
1.0/
1.2
SAMPLE
CONCENTRATION
(
UG/
L)
AVG
%
RECOVERY
OF
10
SAMPLE
EVENTS
LAB
A
LAB
B
LAB
C
LAB
D
LAB
E
LAB
F
LAB
G
LAB
H
LAB
I
LAB
J
Attachment
4.9
ACCURACY
RATINGS
AVERAGE
RECOVERY
FOR
AROCLOR
1260
CONC.
1
CONC.
2
CONC.
3
CONC.
4
CONC.
5
CONC.
6
CONC.
7
CONC.
8
219%
131%
122%
96%
96%
95%
86%
83%

620%
290%
145%
110%
99%
97%
94%
86%

220%
141%
120%
102%
95%
89%
82%
84%

158%
173%
108%
84%
95%
92%
92%
88%

779%
324%
230%
192%
142%
73%
57%
54%

131%
107%
65%
77%
83%
79%
75%
69%

235%
163%
107%
84%
76%
66%
57%
60%

481%
208%
148%
89%
72%
67%
61%
60%

N/
A
110%
93%
85%
85%
79%
66%
68%

172%
146%
122%
99%
91%
89%
69%
70%
LAB
I
LAB
J
LAB
D
LAB
E
LAB
F
LAB
G
LAB
A
LAB
B
LAB
C
LAB
H
Attachment
4.10
AROCLOR
1016
COMBINED
LAB
ACCURACY
RELATED
TO
CONCENTRATION
0
50
100
150
200
250
300
350
400
450
500
0.005/
0.006
0.010/
0.015
0.025/
0.030
0.050/
0.060
0.10/
0.12
0.20/
0.24
0.50/
0.60
1.0/
1.2
CONCENTRATION
(
ug/
l)
PERCENT
RECOVERY
Attachment
4.11
AROCLOR
1260
COMBINED
LAB
ACCURACY
RELATED
TO
CONCENTRATION
0
50
100
150
200
250
300
350
400
0.005/
0.006
0.010/
0.015
0.025/
0.030
0.050/
0.060
0.10/
0.12
0.20/
0.24
0.50/
0.60
1.0/
1.2
CONCENTRATION
LEVEL
(
ug/
l)
PERCENT
RECOVERY
Attachment
4.12
Accuracy
vs.
Concentration
for
Chromium
by
ICP/
AES
40%
50%
60%
70%
80%
90%
100%
110%

0
50
100
150
200
250
300
Concentration
(
ug/
L)
Percent
Recovery
Attachment
4.13
LAB
ID
LAB
GENERATED
MDL
AROCLOR
1016
(
UG/
L)
AMOUNT
SPIKED
FOR
MDL
STUDY(
UG/
L)
MDL
GENERATED
FROM
MMA
STUDY
AMOUNT
SPIKED
FOR
MMA
STUDY
%
DIFFERENCE
A
0.05
0.10
0.051
0.110
2
B
0.043
0.20
0.084
0.220
95
C
0.14
0.50
0.49
0.550
250
C
0.18
0.50
0.49
0.550
172
D
0.0060
0.02
0.075
0.0275
1150
D
0.037
0.05
0.047
0.0550
27
E
0.018
0.10
0.069
0.110
283
F
0.035
0.10
0.060
0.110
71
G
0.0084
0.10
0.064
0.110
662
H
0.013
0.10
0.180
0.110
1285
H
0.029
0.10
0.180
0.110
521
I
0.054
0.30
0.100
0.220
85
J
0.050
0.20
0.075
0.220
50
J
0.069
0.20
0.075
0.220
9
AROCLOR
1016
LAB
GENERATED
VS.
MMA
STUDY
GENERATED
MDLs
Attachment
4.14
LAB
ID
LAB
GENERATED
MDL
AROCLOR
1260
(
UG/
L)
AMOUNT
SPIKED
FOR
MDL
STUDY(
UG/
L)
MDL
GENERATED
FROM
MMA
STUDY
AMOUNT
SPIKED
FOR
MMA
STUDY
%
DIFFERENCE
A
0.04
0.10
0.063
0.110
58
B
0.042
0.20
0.095
0.220
126
C
0.064
0.50
0.17
0.550
166
C
0.065
0.50
0.17
0.550
162
D
0.0041
0.02
0.027
0.0275
559
D
0.022
0.05
0.040
0.0550
82
E
0.02
0.10
0.44
0.110
2100
F
0.042
0.10
0.047
0.110
12
G
0.023
0.10
0.044
0.110
91
H
0.037
0.10
0.050
0.110
35
H
0.055
0.10
0.050
0.110
­
9
I
0.06
0.30
0.093
0.220
55
J
0.086
0.20
0.094
0.220
9
AROCLOR
1260
LAB
GENERATED
VS.
MMA
STUDY
GENERATED
MDLs