Appendix
C
Computation
of
Detection
and
Quantitation
Limits
INTRODUCTION
This
appendix
supports
the
Technical
Support
Document
(
TSD)
for
EPA's
peer
review
of
detection
and
quantitation
concepts.
It
presumes
that
the
reader
has
read
Chapters
3
­
5
of
the
TSD.

This
appendix
compares
detection
and
quantitation
limits
computed
from
data
gathered
by
EPA.
The
comparison
shows
that,
in
general,
detection
limits
derived
from
a
single
concentration
such
as
EPA s
MDL
are,
on
average,
approximately
the
same
as
detection
limits
derived
from
similar
concepts
such
as
the
ACS
LOD
and
LOQ
and
ISO/
IUPAC
CRV
and
MDV,
and
are
approximately
three
times
lower
than
a
single­
laboratory
variant
of
ASTM s
IDE;
and
that
all
quantitation
limit
concepts,
such
as
EPA's
ML,
the
ACS
and
ISO/
IUPAC
LOQ,
and
a
single­
laboratory
variant
of
ASTM's
IQE,
produce
approximately
the
same
quantitation
limits.

BACKGROUND
The
regulated
industry
has
been
commenting
on
EPA s
method
detection
limit
(
MDL;
see
the
definition
at
40
CFR
136,
appendix
B)
since
1985
and
on
EPA s
minimum
level
of
quantitation
(
ML;
see,
e.
g.,
the
definition
in
the
glossary
at
the
end
of
EPA
Method
1631C
promulgated
at
40
CFR
136,
appendix
A)
since
about
1987.
In
the
early
1990s
members
of
the
regulated
industry
community
began
providing
suggestions
for
alternate
detection
and
quantitation
limit
concepts,
most
notably
the
compliance
monitoring
detection
level
(
CMDL),
compliance
monitoring
quantitation
level
(
CMQL)
and
the
alternate
minimum
level
(
AML).
Most
recently
the
industry
community
has
advanced
concepts
for
an
interlaboratory
detection
estimate
(
IDE)
and
interlaboratory
quantitation
estimate
(
IQE)
through
ASTM­
International
(
ASTM).

In
response
to
industry s
comments,
EPA
began
a
data
gathering
activity
designed
to
allow
evaluation
of
the
various
detection/
quantitation
limit
concepts.
The
data
would
be
used
to
characterize
measurement
variability
versus
concentration
for
the
analytes
most
commonly
measured
in,
and
the
analytical
technologies
most
commonly
employed
for,
environmental
measurements.

SETTLEMENT
AGREEMENT
In
October
of
2000,
EPA
signed
an
agreement
associated
with
promulgation
of
EPA
Method
1631
to
settle
a
lawsuit
brought
by
certain
members
of
the
regulated
industry
(
the
 
Settlement
Agreement ).
The
Settlement
Agreement
required
EPA
to,
among
other
things,
reassess
detection
and
quantitation
limit
concepts,
perform
a
peer
review
of
the
reassessment,
and
if
warranted,
propose
changes
to
the
MDL
and
ML
or
propose
alternate
concepts.
This
document
supports
EPA s
reassessment.

EPA'S
APPROACH
TO
ESTABLISHING
DETECTION
AND
QUANTITATION
LIMITS
IN
ANALYTICAL
METHODS
The
Engineering
and
Analysis
Division
(
EAD)
within
EPA's
Office
of
Science
and
Technology
develops
analytical
methods
for
use
in
EPA's
Clean
Water
Act
(
CWA)
programs.
In
developing
these
methods,
EAD
first
conducts
a
single­
laboratory
study
in
which
an
MDL
and
ML
are
determined
followed
by
multiple
single­
laboratory
studies
in
which
the
MDL
and
ML
are
either
verified
or
if
necessary,
revised.
Then,
if
resources,
time,
and
applications
of
the
method
warrant,
an
interlaboratory
study
is
conducted
in
which
the
MDL
and
ML
are
further
verified
or,
if
necessary,
revised.
To
establish
February
2003
C­
1
Assessment
of
Detection
and
Quantitation
Approaches
that
an
MDL
is
realistic,
EAD
generally
selects
the
highest
MDL
from
among
the
MDLs
determined
by
laboratories
in
the
various
studies
or
that
can
be
verified
by
laboratories
in
the
studies.
For
example,
EPA
determined
the
MDL
in
Method
1631
(
mercury
by
cold­
vapor
atomic
fluorescence)
as
0.05
ng/
L
in
a
single
laboratory
and
revised
this
MDL
to
0.2
ng/
L
based
on
multiple
single­
laboratory
studies.
All
laboratories
verified
the
MDL
of
0.2
ng/
L
in
an
interlaboratory
study.
Thus,
although
critics
of
the
MDL
have
complained
that
the
MDL
is
a
single­
laboratory
concept
that
is
highly
variable
and
produces
unrealistically
low
MDLs,
the
process
used
by
EAD
to
establish
the
MDL
and
resulting
ML
is
conservative
and
protects
against
unrealistically
low
MDLs
and
MLs.

EPA S
VARIABILITY
VERSUS
CONCENTRATION
STUDIES
("
EPISODE
6000")

In
1997
and
1998,
EPA
conducted
a
study
of
variability
vs.
concentration
for
a
number
of
analytical
methods.
Six
laboratories
were
employed
for
the
analyses;
each
analyte
and
method
combination
was
tested
by
one
of
these
laboratories.
Details
of
the
study
design
are
described
in
EPA s
Study
Plan
for
Characterizing
Variability
as
a
Function
of
Concentration
for
a
Variety
of
Analytical
Techniques
(
July
1998).
Based
on
the
sampling
episode
number
assigned
to
the
study
by
the
EPA
Sample
Control
Center,
the
study
and
results
have
become
known
as
the
Episode
6000
study
and
data.

The
analytes
and
analytical
techniques
studied
were:

C
Total
suspended
solids
(
TSS)
by
gravimetry,
C
Metals
by
graphite
furnace
atomic
absorption
spectroscopy
(
GFAA),
C
Metals
by
inductively­
coupled
plasma
atomic
emission
spectrometry
(
ICP/
AES),
C
Hardness
by
ethylene
diamine
tetraacetic
acid
(
EDTA)
titration,
C
Phosphorus
by
colorimetry,
C
Ammonia
by
ion­
selective
electrode,
C
Volatile
organic
compounds
by
purge­
and­
trap
capillary
column
gas
chromatography
with
a
photoionization
detector
(
GC/
PID)
and
electrolytic
conductivity
detector
(
GC/
ELCD)
in
series,
C
Volatile
organic
compounds
by
gas
chromatography
with
a
mass
spectrometer
(
GC/
MS),
C
Available
cyanide
by
flow­
injection/
ligand
exchange/
amperometric
detection,
C
Metals
by
inductively­
coupled
plasma
spectrometry
with
a
mass
spectrometer
(
ICP/
MS),

In
the
study,
an
initial
(
range
finding)
MDL
was
determined
for
each
combination
of
analyte
and
analytical
technique
using
a
revised
draft
of
the
MDL
procedure.
The
revised
draft
had
three
significant
changes:
1)
the
definition
was
more
closely
conformed
to
the
MDL
procedure;
2)
optional
iterative
step
7
of
the
MDL
procedure
was
made
mandatory;
and
3)
the
spike
concentration
to
MDL
ratio
was
reduced
from
5
to
3
in
an
attempt
to
narrow
the
resulting
MDL.
During
data
gathering
two
laboratories
complained
that
the
reduction
in
spike
to
determined
MDL
ratio
from
5
to
3
caused
a
large
number
of
iterations
and
stated
that
5
was
more
reasonable.
Subsequently,
EPA
returned
to
the
spike
to
MDL
ratio
of
5
published
in
the
40
CFR
136,
Appendix
B
procedure.

After
determining
the
initial
MDL,
each
laboratory
analyzed
7
replicates
of
samples
spiked
at
concentrations
of
100,
50,
20,
10,
7.5,
5.0,
3.5,
2.0,
1.5,
1.0,
0.75,
0.50,
0.35,
0.20,
0.15,
and
0.10
times
the
initial
MDL.
In
a
few
instances
laboratories
analyzed
more
than
7
replicates.
Results
associated
with
the
replicate
analyses
at
each
concentration
level
were
obtained,
as
often
as
possible,
using
the
same
calibration
that
was
used
in
determining
the
initial
MDL.
Where
laboratory
reports
indicated
that
multiple
calibrations
were
conducted,
the
association
between
each
result
and
its
calibration
was
used
in
the
data
analysis.

Spiked
aqueous
solutions
were
analyzed
in
order
from
the
highest
concentration
(
100
times
the
MDL)
to
the
concentration
at
which
3
or
more
non­
detects
(
zeros)
were
encountered
among
the
7
C­
2
February
2003
Appendix
C
replicates,
or
the
lowest
concentration
specified
(
0.1
times
the
MDL),
whichever
occurred
first.
This
analysis
order
(
1)
minimized
carryover
that
could
occur
in
some
methods
if
a
low­
concentration
sample
had
followed
a
high­
concentration
sample
(
as
may
happen
when
samples
are
analyzed
in
random
order),
and
(
2)
prevented
collection
of
a
large
number
of
zeros
if
the
signal
disappeared.

A
variant
of
the
iterative
MDL
procedure
was
used
for
organic
compounds
determined
by
chromatographic
methods.
Methods
for
organics
normally
list
many
(
15
to
100)
analytes,
and
the
response
for
each
analyte
is
different.
Therefore,
to
determine
an
MDL
for
each
analyte,
the
concentration
of
the
spike
would
need
to
be
inversely
proportional
to
the
response.
Making
a
spiking
solution
with
15
to
100
different
concentrations
is
cumbersome
and
error
prone.
The
approach
used
in
the
study
was
to
run
7
replicates
at
decreasing
concentrations
until
signal
extinction,
then
select
the
concentration(
s)
appropriate
for
the
MDL
for
each
analyte
according
to
the
MDL
procedure.
In
some
cases
the
laboratories
selected
the
concentrations,
in
others
cases,
EPA
did.
This
approach
was
generally
applied
for
organics
analysis.
However,
laboratories
also
had
the
option
of
using
some
combination
of
monotonically
decreasing
concentrations
described
above
and
a
few
selected
concentrations
to
achieve
the
desired
spiking
levels.

DATA
ANALYSIS
Data
from
the
study
were
used
to
evaluate
detection
and
quantitation
limit
concepts
that
employ
a
point
estimate
or
employ
a
model
of
variability
versus
concentration.
Concepts
that
were
evaluated
and
that
employ
a
point
estimate
were
the:

C
EPA
method
detection
limit
(
MDL)
and
minimum
level
of
quantitation
(
ML),
C
American
Chemical
Society
(
ACS)
limit
of
detection
(
LOD)
and
limit
of
quantitation
(
LOQ),
and
C
International
Standards
Organization/
International
Union
of
Pure
and
Applied
Chemistry
(
ISO/
IUPAC)
critical
value
(
CRV),
detection
limit
(
also
termed
"
minimum
detectable
value"
(
MDV)),
and
LOQ.

Concepts
that
were
evaluated
and
employ
a
model
of
variability
versus
concentration
were
the
ASTM
interlaboratory
detection
estimate
(
IDE)
and
interlaboratory
quantitation
estimate
(
IQE).

COMMONALITY
OF
CONCEPTS
The
EPA,
ACS,
and
ISO/
IUPAC
concepts
are
all
multiples
of
the
standard
deviation
of
either
replicate
measurements
of
a
blank
or
of
the
lowest
spike
concentration
that
produces
positive
(
non­
zero)
results
for
all
7
replicates.
Although
some
would
argue
that
this
difference
is
significant,
in
practice
they
are
functionally
analogous
because
a
non­
zero
result
is
needed
to
compute
any
concept
(
a
zero
result
will
return
zero
as
the
detection
or
quantitation
limit).

Other
subtle
distinctions
are
that
(
1)
ISO/
IUPAC
suggest
a
false
positive
rate
of
5
%
("
=
0.05)
for
the
CRV
and
MDV,
whereas
EPA
specifies
a
false
positive
rate
of
1
%
("
=
0.01)
for
the
MDL
and
(
2)
the
EPA
MDL
was
calculated
by
pooling
data
from
two
concentration
levels
after
determining
that
the
variabilities
of
the
two
concentration
levels
are
not
significantly
different
(
as
stipulated
in
step
7
of
the
revised
MDL
procedure),
thereby
increasing
the
degrees
of
freedom
to
12
from
the
6
used
in
computation
of
the
ISO/
IUPAC
CRV
and
ACS
LOD.
The
consequence
of
distinction
1)
is
that
a
concept
with
a
higher
allowed
false
positive
rate
("
=
0.05)
will
produce
a
lower
detection
limit
than
a
concept
with
a
lower
false
positive
rate
("
=
0.01).
The
consequence
of
distinction
2)
is
that
a
detection
limit
resulting
from
pooling
at
two
levels
will
be
lower
and
more
stable
than
a
detection
limit
at
a
single
level
(
given
the
same
variability
at
each
level)
because
the
degrees
of
freedom
are
increased
in
the
t
statistic.

February
2003
C­
3
Assessment
of
Detection
and
Quantitation
Approaches
The
ACS
and
ISO/
IUPAC
concepts
specify
replicate
measurements
of
a
blank.
In
computing
detection
and
quantitation
limits
from
the
Episode
6000
data,
if
the
blank
returned
non­
zero
results,
the
concepts
were
computed
using
replicate
measurements
of
the
blank.
If
the
blank
returned
a
zero
result
in
any
of
the
7
measurements,
the
lowest
spike
concentration
(
or,
in
the
case
of
the
MDL,
two
lowest
spike
concentrations)
that
produced
a
non­
zero
result
was
used
for
computation
of
all
concepts.
This
simplification
condensed
the
EPA
MDL
and
the
ACS
LOD
to
a
single
concept
subsequently
termed
the
EPA/
ACS
DL.
Similarly,
the
EPA
ML
and
ACS
LOQ
were
condensed
to
a
single
concept,
termed
the
EPA/
ACS
QL.

The
remaining
single­
point
concepts
were
the
ISO/
IUPAC
CRV,
MDV,
and
LOQ.
The
ISO/
IUPAC
CRV
differs
from
the
EPA/
ACS
DL
because
of
its
suggested
use
of
a
false
positive
rate
of
5%
("
=
0.05)
versus
use
of
a
false
positive
rate
of
1
%
("
=
.01)
in
the
EPA/
ACS
DL.
The
ISO/
IUPAC
MDV
also
differs
from
the
EPA/
ACS
DL
because
of
(
1)
its
suggested
use
of
a
false
positive
rate
of
5
%
("
=
0.05),
(
2)
its
false
negative
rate
of
5
%
($=
0.05),
and
(
3)
recovery
correction
(
estimated
using
a
linear
regression).
Therefore,
the
ISO/
IUPAC
CRV
and
MDV
were
each
treated
separately
(
were
not
combined
with
another
concept)
from
the
other
detection
limit
concepts
in
the
data
analysis.
The
ISO/
IUPAC
LOQ
is
also
different
from
the
other
quantitation
limit
concepts
and
was
treated
separately
from
these
concepts.

The
ASTM
IDE
and
IQE
were
treated
separately
because
they
are
constructed
by
fitting
a
model
to
variability
versus
concentration
data,
rather
than
being
derived
from
the
standard
deviation
of
replicate
measurements
of
a
single
concentration,
as
are
the
EPA,
ACS,
and
ISO/
IUPAC
concepts.
Similar
to
some
of
the
ISO/
IUPAC
concepts,
the
ASTM
IDE
and
IQE
include
protection
against
false
negatives
and
recovery
correction.
The
IQE,
but
not
IDE,
also
includes
an
added
correction
for
the
bias
associated
with
an
estimate
of
the
true
standard
deviation
at
each
concentration.
In
the
context
of
the
IQE,
the
word
"
bias"
means
the
amount
by
which
the
estimated
sample
standard
deviation
is
low
compared
to
the
true
population
standard
deviation,
and
should
not
be
confused
with
common
use
of
the
word
"
bias"
in
an
analytical
measurement.

SINGLE­
LABORATORY
VARIANTS
OF
INTERLABORATORY
CONCEPTS
EPA s
Episode
6000
database
contains
single­
laboratory
data
because
of
the
prohibitive
expense
that
would
have
been
incurred
in
gathering
interlaboratory
data.
Because
the
EPA,
ACS,
and
ISO/
IUPAC
concepts
are
single­
laboratory
concepts,
and
the
ASTM
IDE
and
IQE
are
interlaboratory
concepts,
the
ASTM
concepts
could
not
be
computed
using
the
single­
laboratory
data
in
the
Episode
6000
studies.
To
solve
this
problem,
single­
laboratory
variants
of
the
IDE
and
IQE
were
used.
These
single­
laboratory
variants
were
termed
the
SL­
IDE
and
SL­
IQE
for
 
single­
laboratory
IDE 
and
 
single­
laboratory
IQE. 
The
SL­
IDEs
and
SL­
IQEs
were
constructed
using
the
overall
standard
deviation
within
a
single
laboratory
at
each
concentration
rather
than
the
overall
standard
deviation
across
all
laboratories
at
each
concentration.

ATTEMPTED
APPLICATION
TO
INTERLABORATORY
DATA
EPA
attempted
to
apply
the
various
concepts
to
interlaboratory
study
data
in
response
to
a
request
by
the
Petitioners
to
the
Settlement
Agreement
and
so
that
detection
and
quantitation
limits
could
be
compared.
However,
because
the
EPA,
ACS,
and
ISO/
IUPAC
concepts
are
single­
laboratory
concepts
whereas
the
ASTM
concepts
are
interlaboratory
concepts,
it
was
not
possible
to
compute
directly
comparable
detection
and
quantitation
limits
from
the
same
data.

What
was
possible
was
to
compare
detection
and
quantitation
limits
produced
by
EPA
and
the
Electric
Power
Research
Institute
(
EPRI)
for
the
EPA
Method
1631
and
EPA
Method
1638
C­
4
February
2003
Appendix
C
interlaboratory
study
data.
Although
the
resulting
detection
and
quantitation
limits
are
single­
or
interlaboratory,
as
appropriate
to
the
particular
concept;
i.
e.,
apples
versus
oranges,
their
magnitudes
are
informative.
The
EPRI
detection
and
quantitation
limits
are
from
EPRI
reports
of
the
results
of
the
Method
1631
and
Method
1638
studies.

COMPUTATIONS
All
computations
were
carried
out
using
Statistical
Analysis
System
(
SAS)
version
8.01.
The
equations
for
all
concepts
were
programmed
into
the
SAS
software
by
a
senior
statistician,
with
assistance
from
senior
analysts.
There
is
some
ambiguity
in
the
IUPAC/
ISO
and
ASTM
detection
and
quantitation
limit
concepts
and
in
interpretation
of
results
from
the
ASTM
concepts.
Several
formulas
are
given
in
the
IUPAC/
ISO
documentation,
but
none
are
defined
to
be
the
official
ISO/
IUPAC
detection
and
quantitation
limit
concepts.
Therefore,
calculations
for
the
CRV,
MDV,
and
LOQ
were
chosen
because
they
were
most
representative
of
Lloyd
Currie s
definitions
of
a
critical
value,
detection
limit
and
quantitation
limit.
The
specific
equations
used
are
on
the
CD­
ROM
that
supports
this
Appendix.
Ambiguity
in
results
from
the
ASTM
concepts
is
attributable
to
the
subjective
nature
of
interpreting
residual
plots
for
each
analyte.
To
resolve
this
issue,
IDE
and
IQE
models
were
chosen
using
significance
tests
for
slope
and
curvature.

References
used
for
the
IUPAC/
ISO
concepts
were
those
published
by
Currie
in
Pure
and
Applied
Chemistry
67:
10,
1699­
1723
(
1995)
as
updated
by
Analytica
Chimica
Acta
391
105­
126
(
1999).
Where
needed,
the
ASTM
concepts
were
programmed
as
single­
laboratory
variants
of
the
Practices
D
6091
(
IDE)
and
D
6512
(
IQE).
EPA
has
included
the
SAS
program
code
on
the
CD­
ROM
that
supports
this
document.

DATA
SETS
EVALUATED
EPA
computed
EPA/
ACS
detection
limits
and
quantitation
limits;
ISO/
IUPAC
CRVs,
MDVs
and
LOQs;
and
single­
laboratory
variants
of
ASTM
IDEs
(
SL­
IDEs)
and
IQEs
(
SL­
IQEs)
for
the
Episode
6000
data.
EPA
also
computed
IDEs
and
IQEs
for
the
Method
1631
and
1638
interlaboratory
study
data.

DATA
SETS
NOT
EVALUATED
The
Petitioners
and
Intervenor
to
the
Settlement
Agreement
provided
the
list
of
data
sets
shown
in
Table
1
and
suggested
that
EPA
evaluate
detection/
quantitation
limit
concepts
using
the
data
sets
on
the
list.
However,
in
reviewing
the
data
sets
suggested,
EPA
determined
that
many
were
developed
for
characterizing
the
behavior
of
an
analyte
or
analytes
across
the
analytical
range
of
a
method,
rather
than
in
the
region
of
detection
and
quantitation,
while
others
did
not
result
from
the
IDE
and
IQE
procedures.
For
example,
any
data
set
developed
prior
to
the
advent
of
the
IDE
and
IQE
would
be
inappropriate
because
there
could
not
have
been
an
estimate
of
IDE0
or
IQE0
.
This
eliminates
all
data
sets
in
Table
1
except
the
EPA/
EPRI
Method
1631
and
Method
1638
data
set,
and
the
MMA
2001­
2
data
set.
It
is
possible
that
some
value
in
one
or
more
of
the
data
sets
developed
prior
to
the
advent
of
the
IDE
and
IQE
would
fortuitously
meet
the
IDE/
IQE
criteria.
But
the
IDE
and
IQE
can
be
circular;
i.
e.,
once
developed
from
a
given
data
set
there
may
be
a
value
in
the
data
set
than
can
be
construed
to
meet
the
criteria.
The
point
is
that
data
sets
developed
without
following
the
IDE
and
IQE
procedures,
particularly
without
making
an
a
priori
estimate
of
IDE0
or
IQE0
,
do
not
meet
the
requirements
of
the
IDE
and
IQE
procedures,
regardless
of
whether
the
data
in
them
can
be
construed
to
have
met
those
requirements
after
the
fact.

In
addition,
these
data
sets
do
not
lend
themselves
to
the
comparisons
used
in
this
report
because
1)
they
contain
interlaboratory
data
that
cannot
be
reduced
to
single­
laboratory
data
without
treating
each
February
2003
C­
5
Assessment
of
Detection
and
Quantitation
Approaches
laboratory
separately1
and
2)
the
developers
of
these
data
sets
did
not
apply
EPA's
procedure
and
measurements
for
establishing
an
MDL
and
ML,
so
an
MDL
and
ML
could
not
be
determined
for
making
comparisons
(
see
the
section
titled
"
EPA's
Approach
to
Establishing
Detection
and
Quantitation
Limits
in
Analytical
Methods").

Further,
the
EPA
6000
data
set
is
comprehensive
in
coverage
of
analytes,
analytical
techniques,
and
a
concentration
range
from
0.1
to
100
times
the
MDL,
whereas
the
data
sets
suggested
by
Petitioners
focus
on
metals,
one
organic
analyte
(
PCBs),
and
concentrations
across
the
analytical
range
of
the
method.
The
range
of
data
used
for
construction
of
an
IDE
or
IQE
is
particularly
important.
As
detailed
in
the
discussion
of
the
"
Effect
of
number
and
spacing
of
concentrations
for
determination
of
the
SL­
IDE
and
SL­
IQE"
below,
including
data
across
the
analytical
range
in
calculation
of
an
SL­
IDE
significantly
raises
the
SL­
IDE.

As
stated
in
the
section
titled
"
Attempted
Application
to
Interlaboratory
Data"
EPA
used
the
EPA
Method
1631
and
1638
data
sets
in
computations
of
detection
and
quantitation
limits,
with
the
qualifiers
given
in
that
section.
The
EPA
Method
1631
and
Method
1638
data
sets
were
the
only
data
sets
suggested
by
the
Petitioners
that
were
used.

RESULTS
OF
COMPUTATIONS
Detection
and
quantitation
limits
are
presented
in
a
set
of
tables
for
the
Episode
6000
study
and
a
single
table
for
the
Method
1631
and
Method
1638
studies.
Within
the
Episode
6000
data
set,
results
for
detection
limits
are
compared
followed
by
results
for
quantitation
limits.
Within
the
comparison
of
limits
(
detection
or
quantitation),
the
first
table
compares
the
actual
limits
followed
by
a
table
of
ratios
between
limits.
These
tables
are
followed
by
a
rank
comparison
table,
making
a
total
of
five
tables
for
this
data
set.

EPISODE
6000
DATA
Table
2
compares
detection
limits
produced
by
the
four
concepts
(
EPA/
ACS
DL;
ISO/
IUPAC
CRV;
ISO/
IUPAC
MDV;
and
ASTM
SL­
IDE)
and
Table
3
compares
the
ratio
between
these
concepts,
taking
the
EPA/
ACS
DL
as
reference.
The
ISO/
IUPAC
CRV
was
greater
than
the
corresponding
EPA/
ACS
DL
for
26%
of
the
analytes
and
methods.
The
median
ratio
of
ISO/
IUPAC
CRV
to
EPA/
ACS
DL
was
significantly
less
than
1
based
on
the
sign
test
with
"
=
0.05
(
p<
0.0001).
We
believe
that
the
major
reason
for
the
difference
is
the
different
Type
I
error
rate
for
the
two
concepts
("
=
0.01
for
the
EPA/
ACS
DL
and
"
=
0.05
for
the
ISO/
IUPAC
CRV).

The
median
ratio
between
the
ISO/
IUPAC
MDV
and
the
EPA/
ACS
DL
is
1.2;
i.
e.,
the
ISO/
IUPAC
MDV
is
a
median
of
1.4
times
higher
than
the
EPA
and
ACS
concepts.
The
ISO/
IUPAC
MDV
was
greater
than
the
corresponding
EPA/
ACS
DL
for
57%
of
the
analytes
and
methods.
The
median
ratio
of
ISO/
IUPAC
MDV
to
EPA/
ACS
DL
did
not
differ
significantly
from
1
based
on
the
sign
test
with
"
=
0.05
(
p=
0.055).
The
likely
reason
that
the
two
concepts
do
not
yield
significantly
different
results
is
that
the
correction
for
false
negatives
and
recovery
correction
in
the
MDV
($
=
0.05)
are
counteracted
by
the
smaller
Type
I
error
rate
for
the
EPA/
ACS
DL.

1
Treating
each
laboratory
separately
would
lead
to
further
ambiguities
because
results
from
some
laboratories
could
produce
detection
and
quantitation
limits
greater
than
the
single­
concentration
limits
whereas
results
from
other
laboratories
could
produce
detection
and
quantitation
limits
less
than
the
single­
concentration
limits.
Given
the
variability
of
the
data,
such
an
outcome
would
be
virtually
assured
and
would
provide
no
further
useful
information.

C­
6
February
2003
Appendix
C
The
median
ratio
between
the
ASTM
SL­
IDE
and
the
EPA/
ACS
DL
is
2.9;
i.
e.,
the
single­
laboratory
variant
of
the
ASTM
IDE
is
a
median
of
2.9
times
higher
than
the
EPA
and
ACS
concepts.
The
SL­
IDE
was
greater
than
the
corresponding
EPA/
ACS
DL
for
91%
of
the
analytes
and
methods.
The
median
ratio
differed
significantly
from
1
based
on
the
sign
test
with
"
=
0.05
(
p<
0.0001).
The
reason(
s)
for
the
difference
could
not
be
determined
easily
because
of
the
number
of
confounding
factors
included
in
the
ASTM
SL­
IDE.

Table
4
compares
quantitation
limits
produced
by
the
three
concepts
(
EPA/
ACS
QL;
ISO
LOQ;
and
ASTM
SL­
IQE)
and
Table
5
compares
the
ratio
between
these
concepts
taking
the
EPA/
ACS
QL
as
reference.
The
median
ratio
between
the
ISO/
IUPAC
LOQ
and
the
EPA/
ACS
QL
is
0.92,
and
the
median
ratio
between
the
ASTM
SL­
IQE
and
the
EPA/
ACS
QL
is
1.
The
ISO
LOQ
and
ASTM
SL­
IQE
are
greater
than
the
corresponding
EPA/
ACS
QL
for
43%
and
51%
of
the
analytes
and
methods,
respectively.
The
median
ratio
did
not
differ
significantly
from
1
based
on
the
sign
test
at
"
=
0.05
(
LOQ:
p=
0.062;
SL­
IQE:
p=
0.78)
The
reason(
s)
why
the
ASTM
SL­
IQE,
ISO
LOQ,
and
the
EPA/
ACS
QL
produce
nearly
identical
limits
could
not
be
determined
easily
because
of
the
number
of
confounding
factors
included
in
the
ASTM
SL­
IQE.

Some
of
the
differences
or
similarities
in
median
quantitation
limits
may
be
accounted
for
by
rounding
in
the
ML
procedure,
although
the
rounding
should
average
over
the
large
number
of
analytes
examined.

Table
6
gives
the
frequency
comparisons
for
the
detection
and
quantitation
limits;
i.
e.,
the
frequency
with
which
each
concept
produced
the
highest
or
lowest
quantitation
limit.

EPA/
EPRI
METHOD
1631
AND
1638
INTERLABORATORY
METHOD
VALIDATION
STUDY
DATA
Table
7
compares
detection
and
quantitation
limits
computed
from
data
generated
in
the
Method
1631
and
Method
1638
interlaboratory
studies.
MDLs
and
MLs
are
those
listed
in
EPA
Methods
1631
and
1638.
EPA
computed
IDEs
and
IQEs
for
the
purpose
of
preparing
this
report.
IDEs
and
IQEs
computed
by
EPRI
are
from
the
EPRI
reports
on
EPA
Method
1631
and
Method
1638
studies.

In
reviewing
these
data
it
must
be
recognized
that
the
EPA
MDLs
and
MLs
are
the
result
of
selecting
the
highest
MDL
in
EPA's
single­
laboratory
studies
or
among
MDLs
from
the
interlaboratory
study,
whereas
the
IDEs
and
IQEs
are
the
result
of
a
statistical
process
that
includes
recovery
correction,
correction
for
bias
in
the
sample
standard
deviation
(
IQE
only),
allowance
for
prediction
and
tolerance
intervals,
interlaboratory
variability,
and
model
selection.
The
most
significant
reason
for
the
instances
of
a
large
disparity
between
the
EPA­
determined
IDEs/
IQEs
and
the
EPRI­
determined
IDEs/
IQEs
is
model
selection.
EPA
selected
the
model
based
on
a
strict
application
of
the
IDE
and
IQE
procedures
by
a
senior
statistician.
For
those
instances
in
which
EPA
and
EPRI
selected
the
same
model,
the
IDEs
and
IQEs
are
nearly
the
same.

Table
8
compares
IDEs
resulting
from
the
four
main
model
types
described
in
the
ASTM
IDE
and
IQE
procedures.
IDEs
resulting
from
the
constant
model
were
the
highest
for
all
analytes.
IDEs
resulting
from
the
other
three
models
were
almost
equal
for
some
analytes
(
lead,
for
example),
and
differed
by
more
than
an
order
of
magnitude
for
others
(
mercury,
for
example).
For
two
analytes,
the
IDE
estimated
using
the
linear
model
was
negative.
This
was
due
to
a
negative
intercept
estimate
in
the
precision
model.
The
ASTM
IDE
and
IQE
procedures
dictate
that
the
linear
model
should
not
be
used
in
this
situation.
No
IDE
could
be
calculated
using
the
hybrid
model
for
silver,
because
the
IDE
did
not
February
2003
C­
7
Assessment
of
Detection
and
Quantitation
Approaches
converge
to
a
single
value
using
the
calculated
model
for
precision.
This
failure
to
converge
is
consistent
with
results
for
this
analyte
presented
by
EPRI.

DISCUSSION
Negative
detection
limits
for
the
ISO/
IUPAC
MDV
The
calculated
MDV
was
negative
for
26
analytes
in
the
Episode
6000
data.
Negative
MDVs
are
attributable
to
the
use
of
a
regression
model
to
estimate
recovery
at
each
concentration.
The
standard
errors
and
correlation
of
the
regression
parameters
are
included
in
the
calculation
of
the
MDV.
Analytes
for
which
the
MDV
was
negative
seemed
to
coincide
with
an
unusually
large
standard
error
of
the
regression
intercept,
which
generally
occurred
when
the
estimated
intercept
was
strongly
negative.
The
large
standard
error
of
the
intercept
was
likely
due
to
extrapolating
the
recovery
model
to
zero
concentration;
the
error
around
a
regression
line
is
greatest
for
concentrations
furthest
away
from
the
mean
spike
level.
The
effect
of
this
extrapolation
may
also
be
seen
in
the
Episode
6000
data.
No
negative
results
were
used
in
the
MDV
and
LOQ
calculations,
yet
the
median
recovery
intercept
for
these
analytes
was
equal
to
­
0.10.
The
standard
errors
of
the
intercept
and
slope
estimates
were
generally
high
(
intercept
median=
0.25,
slope
median=
0.010),
and
therefore
the
estimated
intercept
and
slope
terms
were
frequently
not
significantly
different
from
0
and
1,
respectively
(
intercept:
not
different
from
zero
for
166
analytes/
methods;
slope
not
significantly
different
from
1
for
106
analytes;
both
intercept
and
slope
not
significant
for
78
analytes).
Because
the
recovery
model
parameters
are
not
significant
for
the
majority
of
analytes,
and
both
the
estimated
slope
and
the
standard
errors
of
the
slope
and
intercept
are
included
in
the
calculation
of
the
MDV
and
LOQ,
the
inclusion
of
the
recovery
model
estimates
may
bias
the
calculated
limits,
to
the
point
that
the
resulting
MDV
can
be
negative.

Effect
of
number
and
spacing
of
concentrations
for
determination
of
the
SL­
IDE
and
SL­
IQE
Tests
in
the
Episode
6000
studies
were
conducted
at
16
concentration
levels.
The
IDE
procedure
suggests
5
concentration
levels.
Based
on
statistical
theory
we
would
the
expect
the
number
and
spacing
of
concentration
levels
to
affect
the
outcome,
with
a
larger
number
of
concentrations
producing
a
more
reliable
estimate.
We
used
the
Episode
6000
data
set
to
test
this
hypothesis.

The
IDE
procedure
suggests
spike
concentrations
at
0.5,
1.0,
2,
4,
and
8
times
an
initial
estimate
of
the
IDE
(
IDE0
).
IDE0
is
estimated
at
10
times
the
standard
deviation
of
replicates
of
a
blank
or
the
lowest
level
that
can
be
measured.
EPA s
Episode
6000
database
contain
results
of
analysis
of
7
replicates
at
16
concentration
levels
from
0.1
to
100
times
the
initial
estimate
of
the
MDL
(
a
factor
of
1000).
Between
0.1
and
10
times
the
MDL,
the
data
are
spaced
a
factor
of
approximately
1.5
apart.
Above
10
times
the
MDL,
the
data
are
spaced
at
10,
20,
50
and
100
times
the
MDL.
The
reason
for
the
narrow
spacing
between
0.1
to
10
times
the
MDL
was
to
attempt
to
allow
more
precise
characterization
of
variability
in
the
region
of
the
MDL.

The
SL­
IDEs
and
SL­
IQEs
in
Tables
2
and
4,
respectively,
were
computed
and
reported
using
all
16
concentration
levels
because
data
were
available
at
all
of
these
levels.
However,
to
determine
the
effect
of
the
IDE
procedure,
a
separate
data
analysis
was
performed.
In
this
separate
analysis,
concentration
levels
were
limited
to
a
total
of
5,
and
the
5
levels
were
selected
to
be
as
consistent
as
possible
with
the
levels
specified
in
the
IDE
procedure;
i.
e.,
at
5,
10,
20,
40,
and
80
times
the
standard
deviation
of
replicate
measurements
of
a
blank
or
the
lowest
level
at
which
measurements
could
be
made.
The
statement
 
lowest
level
at
which
measurements
can
be
made 
can
be
interpreted
to
mean
inclusion
or
exclusion
of
results
containing
zeros
and/
or
negative
numbers.
For
purposes
of
the
evaluation,

C­
8
February
2003
Appendix
C
concentrations
that
produced
results
containing
a
zero
or
negative
number
were
excluded;
i.
e.,
the
lowest
concentration
that
contained
no
zeros
or
negative
numbers
was
chosen
as
the
concentration
at
which
the
standard
deviation
would
be
calculated
for
the
purpose
of
estimating
IDE0
and
IQE0
.
Although
some
statisticians
may
argue
that
zeros
and
negative
numbers
should
be
included,
nearly
all
analytical
chemists
would
eliminate
such
numbers
because
they
have
no
physical
meaning.

The
SL­
IDE
was
calculated
after
selecting
the
levels
based
on
IDE0
and
the
results
were
compared
to
results
produced
when
all
16
levels
were
included
in
calculating
the
SL­
IDE.
Results
are
summarized
in
Table
9.
This
table
shows
that
the
median
16­
point
IDE
is
approximately
1.3
times
greater
than
the
median
5­
point
IDE.
For
those
instances
in
which
the
same
model
was
chosen
(
108
out
of
198),
the
median
16­
point
IDE
was
approximately
1.4
times
higher
than
the
median
5­
point
IDE,
which
was
significantly
different
from
1.0
based
on
a
sign
test
(
p
<
0.0001).
For
those
instances
in
which
a
different
model
was
chosen
(
90
out
of
198),
the
median
16­
point
IDE
was
approximately
0.9
times
the
median
5­
point
IDE,
which
was
not
significantly
different
from
1.0
(
p
=
0.83).
Because
the
choice
of
model
can
have
a
confounding
effect
on
any
differences
between
16­
point
and
5­
point
SL­
IDEs,
the
focus
should
be
on
the
instances
in
which
the
same
model
was
chosen.
For
these
instances,
the
results
indicate
that
only
data
in
the
region
of
detection
and
quantitation
should
be
used
to
establish
a
detection
or
quantitation
limit.

Parallel
reasoning
can
be
applied
to
the
IQE,
because
IQE0
is
specified
and
the
IQE
is
developed
in
a
way
analogous
to
that
for
the
IDE.

RSD
AT
THE
ML
IN
THE
EPISODE
6000
STUDY
The
minimum
level
of
quantitation
(
ML)
is
directed
at
the
level
at
which
10%
relative
standard
deviation
(
RSD)
is
attained.
However,
because
the
ML
is
not
established
at
exactly
10%
RSD,
but
is
determined
by
multiplying
the
standard
deviation
that
is
obtained
in
determination
of
an
MDL
by
10
(
as
recommended
by
both
ACS
and
Currie
for
ACS
and
ISO/
IUPAC
LOQs),
the
resulting
RSD
may
not
be
10%.
The
Episode
6000
data
provided
the
opportunity
to
determine
the
actual
value
of
the
RSD
at
the
ML.
Results
of
the
determination
showed
that
the
overall
median
RSD
at
the
ML
across
all
198
analytes
in
the
Episode
6000
study
was
7
%,
and
the
median
RSD
per
analytical
technique
ranged
between
6
and
16
percent
by
analytical
technique
for
analytes
in
the
10
analytical
techniques
in
the
study.
For
126
of
the
198
individual
analytes,
the
RSD
fell
between
5%
and
15%.
For
the
majority
of
the
analytes
that
fell
outside
this
range
(
56
out
of
72),
the
RSD
was
less
than
5%.

There
was
a
spike
concentration
at
the
ML
for
approximately
80
percent
of
the
analytes
in
the
Episode
6000
study
so
the
RSD
could
be
determined
directly
for
these
analytes.
For
a
few
analytes
there
was
not
a
spike
concentration
at
the
ML,
and
the
RSD
was
determined
by
interpolation
between
spike
levels
for
these
analytes.
However,
for
82
out
of
198
analytes,
the
concentration
at
the
ML
was
below
the
range
of
the
data;
i.
e.,
below
the
lowest
spike
concentration
that
returned
non­
zero
and
non­
negative
results.
These
instances
were
for
organic
analytes
determined
by
EPA
Methods
502.2
and
524.2.
The
reason
that
these
low
values
occur
is
because
hardware
and/
or
software
thresholds
in
chromatographic
instruments
that
are
set
to
eliminate
spurious
noise
signals
also
filter
out
responses
at
low
concentrations.
For
instances
in
which
this
occurred,
the
ML
was
calculated
as
the
lowest
concentration
at
which
non­
zero
and
non­
negative
results
were
not
reported,
and
the
RSD
was
calculated
at
this
concentration.
The
median
RSD
for
these
analytes
was
5%,
compared
to
a
median
of
9%
where
this
did
not
happen.

February
2003
C­
9
Assessment
of
Detection
and
Quantitation
Approaches
CONCLUSIONS
The
comparisons
of
detection
and
quantitation
limits
show
high
variability
among
the
limits
calculated
using
the
different
concepts,
even
with
data
containing
7
replicates
at
16
concentration
levels
(
see
the
summary
statistics
at
the
end
of
Tables
3
and
5,
Table
6,
and
the
final
conclusion
below).
The
net
effect
is
that
the
systematic
differences
among
detection
and
quantitation
limits
produced
by
the
various
concepts
are
overwhelmed
by
variability;
i.
e.,
there
is
a
small
systematic
difference
among
the
concepts
but
great
variability
in
the
detection
and
quantitation
limits
for
a
given
analyte.
This
result
is
not
surprising
given
the
variability
of
data
in
the
region
of
detection
and
quantitation.
However,
it
is
difficult
to
postulate
a
solution
to
the
problem.
Gathering
more
data
in
the
region
of
detection
and
quantitation
would
appear
to
be
a
solution,
but
91
data
points
were
gathered
for
each
analyte
in
the
region
between
0.1
and
10
times
the
MDL
in
the
Episode
6000
studies,
and
it
is
unlikely
that
any
organization
could
afford
to
gather
even
this
amount
of
data
for
determination
of
a
detection
limit.
Given
the
high
degree
of
variability
of
the
data,
EPA's
approach
of
conducting
single­
laboratory
study
to
gain
a
first
estimate,
then
multiple
single­
laboratory
studies
to
verify
or
revise
the
estimate,
then
an
interlaboratory
study,
where
warranted,
to
further
verify
and
revise
the
estimate,
is
a
reasonable
means
of
establishing
detection
and
quantitation
limits
because
of
the
checks
and
balances
that
occur
at
each
step.

A
second
conclusion
is
that
using
a
regression
line
to
estimate
a
recovery
correction
at
zero
concentration
causes
great
swings
in
the
resulting
detection
and
quantitation
limits
such
as
the
ISO/
IUPAC
MDV
and
LOQ.
The
estimated
regression
parameters
for
the
recovery
models
were
often
not
significant,
and
the
inclusion
of
the
estimated
slope
and
the
standard
errors
of
the
slope
and
intercept
will
therefore
unnecessarily
bias
the
calculated
MDV
and
LOQ,
such
that
the
calculated
MDVs
may
be
negative
(
see
Discussion
section
"
Negative
detection
limits
for
the
ISO/
IUPAC
MDV,
and
Table
2
for
instances
of
negative
detection
limits").
The
estimated
recovery
model
used
in
calculating
the
IDE
and
IQE
is
also
strongly
affected
by
the
chosen
model
of
variability
vs.
concentration
(
see
Table
8).
Even
though
a
linear
regression
is
used
to
model
recovery
in
each
case,
the
weights
used
in
the
model
are
calculated
based
on
the
variability
model,
and
can
vary
greatly
when
the
number
of
concentrations
used
is
low.
For
the
Episode
6000
data,
the
median
RSD
of
the
recovery
slopes
from
the
four
different
models
used
in
the
IDE
calculations
for
a
given
analyte
and
method
was
5%.
In
addition,
for
75
of
the
analytes
and
methods
(
38%),
at
least
one
estimated
recovery
slope
was
greater
than
1,
and
at
least
one
was
less
than
1.
This
suggests
that
the
method
could
be
considered
to
be
high
biased
(
and
the
final
IDE
and
IQE
would
be
decreased
by
the
recovery
correction)
and
low
biased
(
and
the
final
IDE
and
IQE
increased)
for
the
analyte,
depending
on
the
chosen
precision
model.
For
many
analytes
the
slopes
were
not
significantly
different
from
1,
suggesting
that
a
recovery
correction
may
not
be
appropriate
at
all.
This
is
in
addition
to
the
philosophical
issue
as
to
whether
recovery
correction
is
warranted.
If
there
is
to
be
a
correction
for
recovery,
it
may
be
better
to
use
some
average
or
median
value
than
a
regression,
or
use
a
measured
value
near
the
region
of
interest.

A
third
conclusion
is
that
further
work
will
need
to
be
done
on
the
ASTM
IDE
and
IQE
before
they
can
be
used
routinely,
not
only
because
of
the
complexity
of
the
procedures,
but
also
because
of
the
ambiguity
in
determining
that
the
correct
model
has
been
selected.
(
For
the
consequences
of
model
selection,
compare
the
IDEs
and
IQEs
determined
by
EPA
and
EPRI
in
Table
7,
and
the
IDEs
calculated
from
the
different
model
types
in
Table
8.
Some
differ
considerably
as
a
result
of
model
selection
in
application
of
the
IDE
and
IQE
procedures
by
different
statisticians.)

A
fourth
conclusion
is
that
quantitation
limit
concepts
such
as
EPA's
ML
and
the
ACS
and
ISO/
IUPAC
LOQ
that
are
directed
10%
RSD
actually
produce
RSDs
that
are
in
the
range
of
the
10%
intended
(
see
the
discussion
in
the
Section
titled
"
RSD
at
the
ML
in
the
Episode
6000
Study").
The
median
RSDs
for
each
method
in
the
Episode
6000
data
set
ranged
from
6%
to
16%,
and
64%
of
the
individual
analyte
RSDs
fell
between
5%
and
15%.

C­
10
February
2003
Appendix
C
Finally,
a
statement
needs
to
be
made
about
the
overall
philosophy
behind
the
concepts.
A
natural
progression
through
time
is
to
refine
any
theory
or
concept.
However,
in
the
case
of
detection
and
quantitation
in
analytical
chemistry
(
and
as
applied
to
other
disciplines),
the
effort
to
further
refine
concepts
may
be
futile,
given
the
variability
of
the
data
that
must
be
used
with
any
concept.
However,
it
is
clear
no
concept
produces
the
 
right 
answer.
Different
concepts
allow
for
different
sources
of
variability
resulting
in
shifts
in
the
magnitude
of
the
limit.
For
the
EPA,
ACS,
ISO/
IUPAC,
and
ASTM
concepts,
the
most
significant
causes
of
this
shift
appear
to
be
1)
the
false
positive
rate
("
=
0.01
or
0.05),
2)
the
allowance
for
false
negatives
($
=
0.05),
3)
recovery
correction,
4)
correction
for
the
bias
in
the
calculated
standard
deviation
(
IQE
only),
5)
interlaboratory
variability,
and
6)
model
selection
in
the
IDE
and
IQE.

Table
1.
Data
Sets
Suggested
by
Petitioners
Data
Set
and
Year
Analyte
and
Technology
AAMA
1996­
7
Metals
by
ICP/
AES
(
200.7)

AAMA
1996­
7
Mercury
by
CVAA
(
245.2)

AAMA
1996­
7
PCBs
by
GC/
ECD
(
608.2)

MMA
2000­
1
PCB
1216
and
1260
by
GC/
ECD
EPA/
EPRI
1997­
8
Mercury
by
CVAF
(
1631)

EPA/
EPRI
1997­
8
Metals
by
ICP/
MS
(
1638)

EPRI
1987
Metals
by
GFAA
(
EPA
200)

EPRI
1990
Metals
by
ICP/
AES
(
EPA
200.7)

EPRI
1994
Al,
Be,
Tl
by
GFAA
(
EPA
200)

EPRI
1996
Cd,
As,
Cr
by
GFAA
(
EPA
200)

February
2003
C­
11
Assessment
of
Detection
and
Quantitation
Approaches
Table
2.
Comparison
of
Detection
Limits
(
µ
g/
L
except
where
footnoted)
for
the
Episode
6000
Data
set
Analyte
Method
Procedure
EPA/
ACS
DL
ISO
CRV
ISO
MDV
ASTM
SL­
IDE
1,1,1,2­
tetrachloroethane
502.2
ELCD
0.041
0.028
0.054
0.028
1,1,1,2­
tetrachloroethane
524.2
0.052
0.039
­
0.030
0.206
1,1,1­
trichloroethane
502.2
ELCD
0.012
0.009
0.017
0.035
1,1,1­
trichloroethane
524.2
0.055
0.021
0.007
0.268
1,1,2,2­
tce+
1,2,3­
tcp
502.2
ELCD
0.064
0.225
0.417
0.170
1,1,2,2­
tetrachloroethane
524.2
0.132
0.131
0.139
0.377
ELCD
0.024
0.055
0.103
0.026502.21,1,2­
trichloroethane
524.2
502.2
524.2
502.2
0.075
0.043
0.045
0.284
ELCD
0.010
0.008
0.016
0.066
0.033
0.020
0.018
0.206
ELCD
0.038
0.013
0.032
0.193
1,1,2­
trichloroethane
1,1­
dichloroethane
1,1­
dichloroethane
1,1­
dichloroethene
524.2
524.2
0.054
0.035
­
0.030
0.278
5.184
3.146
5.657
6.032
1,1­
dichloroethene
1,1­
dichloropropanone
524.2
502.2
1,1­
dichloropropene
1,2,3­
trichlorobenzene
1,2,3­
trichlorobenzene
502.2
1,2,3­
trichlorobenzene
524.2
1,2,3­
trichloropropane
524.2
1,2,4­
trichlorobenzene
502.2
1,2,4­
trichlorobenzene
502.2
1,2,4­
trichlorobenzene
524.2
1,2,4­
trimethylbenzene
502.2
1,2,4­
trimethylbenzene
524.2
0.045
0.012
­
0.020
0.247
ELCD
0.048
0.308
0.599
0.122
PID
0.057
0.301
0.623
0.114
0.070
0.040
0.036
0.259
7.328
0.046
0.042
1.206
ELCD
0.022
0.189
0.393
0.077
PID
0.070
0.221
0.471
0.124
0.053
0.050
0.057
0.208
PID
0.095
0.075
0.167
0.123
0.012
0.009
0.017
0.129
1,2­
dibromo­
3­
chloropropane
524.2
1.457
0.391
0.702
1.619
ELCD
0.096
0.028
0.056
0.143502.21,2­
dibromoethane
524.2
502.2
502.2
524.2
0.127
0.117
0.175
0.289
ELCD
0.035
0.073
0.144
0.053
PID
0.033
0.024
0.054
0.147
0.030
0.023
­
0.010
0.112
1,2­
dibromoethane
1,2­
dichlorobenzene
1,2­
dichlorobenzene
1,2­
dichlorobenzene
502.2
524.2
502.2
524.2
ELCD
0.017
0.017
0.032
0.037
0.039
0.024
0.017
0.229
ELCD
0.023
0.196
0.393
0.037
0.056
0.031
0.029
0.221
1,2­
dichloroethane
1,2­
dichloroethane
1,2­
dichloropropane
1,2­
dichloropropane
1,3,5­
tmb+
4­
chlorotoluene
502.2
PID
0.067
0.201
0.449
0.108
C­
12
February
2003
Appendix
C
Table
2.
Comparison
of
Detection
Limits
(
µ
g/
L
except
where
footnoted)
for
the
Episode
6000
Data
set
Analyte
Method
Procedure
EPA/
ACS
DL
ISO
CRV
ISO
MDV
ASTM
SL­
IDE
1,3,5­
trimethylbenzene
524.2
0.011
0.008
0.009
0.117
1,3­
dichlorobenzene
502.2
ELCD
0.035
0.048
0.104
0.100
1,3­
dichlorobenzene
502.2
PID
0.093
0.134
0.297
0.123
1,3­
dichlorobenzene
524.2
0.023
0.016
­
0.010
0.126
1,3­
dichloropropane
502.2
ELCD
0.016
0.071
0.135
0.045
1,3­
dichloropropane
524.2
0.038
0.024
­
0.010
0.170
1,4­
dichlorobenzene
502.2
ELCD
0.026
0.101
0.198
0.054
1,4­
dichlorobenzene
524.2
0.023
0.017
­
0.040
0.110
1­
chlorobutane
524.2
0.020
0.016
0.019
0.200
2,2­
dichloropropane
524.2
2.376
0.103
­
0.120
0.700
2­
butanone
524.2
0.417
0.297
0.515
0.775
2­
chlorotoluene
502.2
ELCD
0.108
0.162
0.318
0.184
2­
chlorotoluene
502.2
PID
0.238
0.454
1.022
0.222
2­
chlorotoluene
524.2
0.016
0.009
0.003
0.121
2­
hexanone
524.2
1.316
0.148
0.234
0.815
2­
nitropropane
524.2
0.901
0.275
0.457
0.965
4­
chlorotoluene
502.2
ELCD
0.110
0.127
0.234
0.159
4­
chlorotoluene
524.2
0.010
0.008
0.008
0.102
4­
isopropyltoluene
524.2
0.010
0.008
0.005
0.102
4­
methyl­
2­
pentanone
524.2
0.812
0.480
0.740
1.060
Acetone
524.2
0.859
0.440
0.806
2.025
Acrylonitrile
524.2
0.863
0.444
0.658
1.197
Allyl
Chloride
524.2
0.032
0.026
0.010
0.203
Aluminum
1620
29.555
15.043
28.670
198.565
Aluminum
200.8
19.145
1.690
3.547
12.004
Ammonia
as
Nitrogen
1
350.3
0.010
0.007
0.014
0.013
Antimony
1620
1.552
0.801
1.754
4.087
Antimony
200.8
0.178
0.003
0.007
0.018
Arsenic
1620
1.065
0.917
1.375
1.463
Arsenic
200.8
0.226
0.137
0.272
0.346
Barium
1620
1.702
1.337
1.831
1.762
Barium
200.8
0.033
0.029
0.061
0.079
Benzene
502.2
PID
0.030
0.043
0.099
0.077
Benzene
524.2
0.014
0.014
0.027
0.115
February
2003
C­
13
Assessment
of
Detection
and
Quantitation
Approaches
Table
2.
Comparison
of
Detection
Limits
(
µ
g/
L
except
where
footnoted)
for
the
Episode
6000
Data
set
Analyte
Method
Procedure
EPA/
ACS
DL
ISO
CRV
ISO
MDV
ASTM
SL­
IDE
Beryllium
1620
0.528
0.339
0.408
0.428
Beryllium
200.8
0.007
0.004
0.006
0.019
Boron
1620
15.387
10.356
17.790
19.884
Bromobenzene
502.2
ELCD
0.131
0.093
0.187
0.729
Bromobenzene
502.2
PID
0.012
0.286
0.619
0.048
Bromobenzene
524.2
0.044
0.036
­
0.050
0.175
Bromochloromethane
502.2
ELCD
0.013
0.016
0.032
0.462
Bromochloromethane
524.2
0.125
0.113
0.165
0.309
Bromodichloromethane
502.2
ELCD
0.004
0.016
0.032
0.064
Bromodichloromethane
524.2
0.043
0.026
0.023
0.182
Bromoform
502.2
ELCD
0.006
0.009
0.016
1.450
Bromoform
524.2
0.123
0.065
0.040
0.350
Bromomethane
502.2
ELCD
0.267
0.047
0.010
6.993
Bromomethane
524.2
0.068
0.055
0.060
0.238
Cadmium
1620
0.127
0.079
0.134
0.184
Cadmium
200.8
0.004
0.007
0.012
0.011
Calcium
1620
36.726
35.822
72.400
39.651
Carbon
Disulfide
524.2
0.027
0.016
­
0.030
0.203
Carbon
Tetrachloride
524.2
0.038
0.027
­
0.030
0.258
Carbontet+
1,1­
dcp
502.2
ELCD
0.029
0.028
0.060
0.062
Chloroacetonitrile
524.2
0.919
0.773
1.535
1.535
Chlorobenzene
502.2
ELCD
0.011
0.016
0.034
0.440
Chlorobenzene
502.2
PID
0.030
0.080
0.178
0.062
Chlorobenzene
524.2
0.025
0.022
0.016
0.119
Chloroethane
502.2
ELCD
0.108
0.006
0.004
2.492
Chloroethane
524.2
0.066
0.041
0.042
0.336
Chloroform
502.2
ELCD
0.043
0.410
0.758
0.031
Chloroform
524.2
0.036
0.027
0.025
0.203
Chloromethane
502.2
ELCD
0.070
0.090
0.240
0.204
Chloromethane
524.2
0.045
0.036
0.066
0.215
Chromium
1620
0.310
0.254
0.386
0.478
Chromium
200.8
0.073
0.062
0.125
0.393
Cis­
1,2­
dce+
2,2­
dcp
502.2
ELCD
0.013
0.017
0.034
0.043
Cis­
1,2­
dichloroethene
524.2
0.040
0.033
­
0.010
0.203
C­
14
February
2003
Appendix
C
Table
2.
Comparison
of
Detection
Limits
(
µ
g/
L
except
where
footnoted)
for
the
Episode
6000
Data
set
Analyte
Method
Procedure
EPA/
ACS
DL
ISO
CRV
ISO
MDV
ASTM
SL­
IDE
Cis­
1,3­
dichloropropene
502.2
ELCD
0.007
0.016
0.031
0.059
Cis­
1,3­
dichloropropene
502.2
PID
0.057
0.048
0.099
0.077
Cis­
1,3­
dichloropropene
524.2
0.038
0.024
0.001
0.158
Cobalt
1620
9.820
4.017
8.094
15.560
Cobalt
200.8
0.001
0.001
­
0.070
0.008
Copper
1620
6.046
4.990
10.510
20.328
Copper
200.8
0.037
0.027
0.053
0.770
Dibromochloromethane
502.2
Dibromochloromethane
524.2
ELCD
0.009
0.019
0.039
0.418
0.051
0.031
0.011
0.253
Dibromomethane
502.2
ELCD
0.007
0.047
0.096
0.441
Dibromomethane
524.2
0.102
0.082
0.117
0.342
Dichlorodifluoromethane
502.2
Dichlorodifluoromethane
524.2
ELCD
0.009
1.453
1.715
0.087
0.083
0.054
0.046
0.420
Diethyl
Ether
524.2
0.120
0.114
0.169
0.340
Ethyl
Methacrylate
524.2
0.045
0.031
0.018
0.244
Ethylbenzene
502.2
PID
0.021
0.053
0.122
0.075
Ethylbenzene
524.2
0.033
0.028
­
0.020
0.167
Hardness
1
130.2
0.828
0.555
1.152
2.152
Hexachlorobutadiene
502.2
ELCD
0.043
0.240
0.502
0.090
Hexachlorobutadiene
524.2
0.068
0.035
­
0.020
0.263
Hexachloroethane
524.2
0.056
0.049
0.044
0.234
Hexchlobutadiene+
naphthalene
502.2
PID
0.649
0.924
2.083
0.598
Iron
1620
90.409
270.433
472.200
345.686
Isopropylbenzene
502.2
PID
0.020
0.051
0.120
0.059
Isopropylbenzene
524.2
0.011
0.010
0.012
0.113
Lead
1620
1.647
1.186
1.965
2.317
Lead
200.8
0.655
0.061
0.120
0.197
M+
p
Xylene
502.2
PID
0.090
0.099
0.225
0.116
M+
p
Xylene
524.2
0.013
0.008
0.006
0.127
Magnesium
1620
103.033
88.729
175.300
99.662
Manganese
1620
6.856
1.081
2.591
6.531
Manganese
200.8
0.031
0.030
0.049
0.106
Mercury
200.8
0.004
0.003
­
0.020
0.062
Methacrylonitrile
524.2
0.356
0.228
0.368
0.643
February
2003
C­
15
Assessment
of
Detection
and
Quantitation
Approaches
Table
2.
Comparison
of
Detection
Limits
(
µ
g/
L
except
where
footnoted)
for
the
Episode
6000
Data
set
Analyte
Method
Procedure
EPA/
ACS
DL
ISO
CRV
ISO
MDV
ASTM
SL­
IDE
Methyl
Iodide
524.2
0.025
0.023
­
0.010
0.173
Methyl
Tert­
butyl
Ether
524.2
Methylacrylate
524.2
Methylene
Chloride
502.2
Methylene
Chloride
524.2
0.026
0.016
­
0.030
0.195
0.220
0.202
0.356
0.549
ELCD
0.128
1.835
5.018
2.727
0.082
0.072
0.098
0.276
Methylmethacrylate
524.2
0.225
0.085
0.120
0.484
Molybdenum
1620
2.455
1.714
3.787
2.917
Molybdenum
200.8
0.004
0.003
0.000
0.262
N­
butylbenzene
502.2
PID
0.030
0.069
0.151
0.139
N­
butylbenzene
524.2
0.016
0.014
0.027
0.136
N­
propylbenzene
502.2
PID
0.040
0.597
1.340
0.089
N­
propylbenzene
524.2
0.038
0.026
­
0.040
0.231
Naphthalene
524.2
0.048
0.040
0.047
0.175
Nickel
1620
20.219
13.262
25.700
23.784
Nickel
200.8
0.146
0.058
0.107
0.076
o­
xylene
524.2
0.018
0.015
­
0.030
0.161
o­
xylene+
styrene
502.2
PID
0.059
0.118
0.263
0.111
P­
isoproptol+
1,4­
dcb
502.2
PID
0.073
0.152
0.332
0.153
Pentachloroethane
524.2
0.553
0.019
­
0.080
0.337
Sec­
butylbenzene
502.2
Sec­
butylbenzene
524.2
PID
0.055
0.058
0.133
0.079
0.014
0.011
­
0.010
0.132
Selenium
1620
0.849
0.619
1.493
1.915
Selenium
200.8
0.192
0.156
0.302
0.410
Silver
1620
4.907
3.588
6.495
10.219
Silver
200.8
0.004
0.002
0.004
0.010
Sodium
1620
69.530
49.595
97.650
133.007
Styrene
524.2
0.014
0.011
0.011
0.119
Tert­
butylbenzene
502.2
Tert­
butylbenzene
524.2
PID
0.029
0.058
0.137
0.073
0.022
0.012
0.023
0.170
Tetrachloroethene
502.2
ELCD
0.018
0.200
0.429
0.051
Tetrachloroethene
502.2
PID
0.062
0.319
0.753
0.157
Tetrachloroethene
524.2
0.085
0.084
0.058
0.379
Thallium
1620
0.512
0.651
1.406
1.208
Thallium
200.8
0.000
0.000
0.001
0.001
C­
16
February
2003
Appendix
C
Table
2.
Comparison
of
Detection
Limits
(
µ
g/
L
except
where
footnoted)
for
the
Episode
6000
Data
set
Analyte
Method
Procedure
EPA/
ACS
DL
ISO
CRV
ISO
MDV
ASTM
SL­
IDE
Thorium
200.8
0.001
0.001
0.000
0.003
Tin
1620
3.670
2.019
3.143
1.200
Titanium
1620
4.777
4.453
8.050
5.238
Toluene
502.2
PID
0.070
0.064
0.145
0.061
Toluene
524.2
0.020
0.006
0.000
0.130
Total
Phosphorus
1
365.2
Total
Suspended
Solids
1
160.2
Trans­
1,2­
dichloroethene
502.2
Trans­
1,2­
dichloroethene
524.2
Trans­
1,3­
dichloropropene
502.2
Trans­
1,3­
dichloropropene
502.2
Trans­
1,3­
dichloropropene
524.2
Trans­
1,4­
dichloro­
2­
butene
524.2
0.006
0.005
0.009
0.013
1.170
0.948
1.945
2.877
ELCD
0.041
0.174
0.382
0.065
0.038
0.032
­
0.010
0.255
ELCD
0.012
0.013
0.026
0.082
PID
0.058
0.037
0.079
0.085
0.051
0.025
0.000
0.204
0.512
0.348
0.589
1.182
Trichloroethene
502.2
ELCD
0.012
0.014
0.029
0.050
Trichloroethene
502.2
PID
0.027
0.043
0.098
0.096
Trichloroethene
524.2
0.061
0.058
0.062
0.288
Trichlorofluoromethane
502.2
ELCD
0.108
0.012
0.028
1.997
Trichlorofluoromethane
524.2
0.087
0.075
0.046
0.307
Uranium
200.8
0.000
0.000
0.000
0.001
Vanadium
1620
7.344
4.207
8.359
10.063
Vanadium
200.8
0.555
0.512
0.994
0.845
Vinyl
Chloride
502.2
ELCD
0.270
0.039
0.072
3.521
Vinyl
Chloride
524.2
0.043
0.031
0.000
0.295
WAD
Cyanide
1677
0.572
0.169
0.319
0.672
Xylene
(
Total)
524.2
0.009
0.005
0.008
0.111
Yttrium
1620
1.923
1.370
2.518
3.119
Zinc
1620
2.597
2.301
3.697
4.415
Zinc
200.8
0.900
0.461
0.806
1.497
1
Results
reported
as
mg/
L
Note:
ELCD
or
PID
in
the
Procedure
column
indicates
the
photo­
ionization
detector
(
PID)
or
electrolytic
conductivity
detector
(
ELCD)
in
EPA
Method
502.2
February
2003
C­
17
Assessment
of
Detection
and
Quantitation
Approaches
Table
3.
Ratios
ofDetection
Limits
to
the
EPA/
ACS
DL
for
the
Episode
6000
Data
Set
1,1,1,2­
tetrachloroethane
1,1,1­
trichloroethane
1,1,1­
trichloroethane
1,1,2,2­
tce+
1,2,3­
tcp
1,1,2,2­
tetrachloroethane
1,1,2­
trichloroethane
1,1,2­
trichloroethane
1,1­
dichloroethane
1,1­
dichloroethane
1,1­
dichloroethene
1,1­
dichloroethene
1,1­
dichloropropanone
1,1­
dichloropropene
1,2,3­
trichlorobenzene
1,2,3­
trichlorobenzene
1,2,3­
trichlorobenzene
1,2,3­
trichloropropane
1,2,4­
trichlorobenzene
1,2,4­
trichlorobenzene
1,2,4­
trichlorobenzene
1,2,4­
trimethylbenzene
1,2,4­
trimethylbenzene
1,2­
dibromo­
3­
chloropropane
1,2­
dibromoethane
1,2­
dibromoethane
1,2­
dichlorobenzene
1,2­
dichlorobenzene
1,2­
dichlorobenzene
1,2­
dichloroethane
1,2­
dichloroethane
1,2­
dichloropropane
1,2­
dichloropropane
1,3,5­
tmb+
4­
chlorotoluene
C­
18
Analyte
1,1,1,2­
tetrachloroethane
Method
Procedure
ISO
CRV/
MDL
ISO
MDV/
MDL
SL­
IDE/
MDL
502.2
ELCD
0.691
1.313
0.679
524.2
0.747
­
0.645
3.953
502.2
ELCD
0.707
1.387
2.861
524.2
0.382
0.135
4.843
502.2
ELCD
3.522
6.531
2.664
524.2
0.994
1.054
2.853
502.2
ELCD
2.266
4.207
1.062
524.2
0.580
0.602
3.796
502.2
ELCD
0.786
1.645
6.600
524.2
0.596
0.561
6.281
502.2
ELCD
0.348
0.845
5.018
524.2
0.647
­
0.477
5.102
524.2
0.607
1.091
1.164
524.2
0.261
­
0.536
5.525
502.2
ELCD
6.454
12.543
2.548
502.2
PID
5.268
10.902
1.988
524.2
0.578
0.517
3.706
524.2
0.006
0.006
0.165
502.2
ELCD
8.731
18.213
3.548
502.2
PID
3.143
6.704
1.773
524.2
0.951
1.069
3.921
502.2
PID
0.792
1.766
1.297
524.2
0.772
1.419
10.509
524.2
0.268
0.482
1.111
502.2
ELCD
0.297
0.582
1.496
524.2
0.918
1.378
2.275
502.2
ELCD
2.079
4.106
1.525
502.2
PID
0.734
1.649
4.514
524.2
0.755
­
0.319
3.729
502.2
ELCD
0.981
1.834
2.107
524.2
0.609
0.445
5.882
502.2
ELCD
8.543
17.176
1.602
524.2
0.540
0.519
3.915
502.2
PID
2.984
6.658
1.598
February
2003
Appendix
C
Table
3.
Ratios
ofDetection
Limits
to
the
EPA/
ACS
DL
for
the
Episode
6000
Data
Set
Analyte
Method
Procedure
ISO
CRV/
MDL
ISO
MDV/
MDL
SL­
IDE/
MDL
1,3,5­
trimethylbenzene
524.2
0.710
0.843
10.494
1,3­
dichlorobenzene
502.2
ELCD
1.375
2.980
2.850
1,3­
dichlorobenzene
502.2
PID
1.445
3.192
1.325
1,3­
dichlorobenzene
524.2
0.699
­
0.357
5.418
1,3­
dichloropropane
502.2
ELCD
4.518
8.588
2.839
1,3­
dichloropropane
524.2
0.628
­
0.212
4.457
1,4­
dichlorobenzene
502.2
ELCD
3.876
7.630
2.068
1,4­
dichlorobenzene
524.2
0.714
­
1.534
4.699
1­
chlorobutane
524.2
0.786
0.974
10.051
2,2­
dichloropropane
524.2
0.044
­
0.049
0.294
2­
butanone
524.2
0.713
1.235
1.860
2­
chlorotoluene
502.2
ELCD
1.498
2.947
1.705
2­
chlorotoluene
502.2
PID
1.907
4.290
0.931
2­
chlorotoluene
524.2
0.570
0.215
7.599
2­
hexanone
524.2
0.112
0.178
0.620
2­
nitropropane
524.2
0.305
0.507
1.071
4­
chlorotoluene
502.2
ELCD
1.152
2.135
1.445
4­
chlorotoluene
524.2
0.803
0.849
10.563
4­
isopropyltoluene
524.2
0.833
0.519
10.452
4­
methyl­
2­
pentanone
524.2
0.591
0.911
1.305
Acetone
524.2
0.512
0.938
2.358
Acrylonitrile
524.2
0.515
0.763
1.387
Allyl
Chloride
524.2
0.820
0.306
6.297
Aluminum
1620
0.509
0.970
6.718
Aluminum
200.8
0.088
0.185
0.627
Ammonia
as
Nitrogen
350.3
0.668
1.358
1.229
Antimony
1620
0.516
1.130
2.634
Antimony
200.8
0.018
0.037
0.102
Arsenic
1620
0.861
1.290
1.373
Arsenic
200.8
0.606
1.206
1.532
Barium
1620
0.786
1.076
1.035
Barium
200.8
0.885
1.855
2.421
Benzene
502.2
PID
1.435
3.283
2.537
Benzene
524.2
0.981
1.839
7.986
February
2003
C­
19
Assessment
of
Detection
and
Quantitation
Approaches
Table
3.
Ratios
ofDetection
Limits
to
the
EPA/
ACS
DL
for
the
Episode
6000
Data
Set
C­
20
Analyte
Method
Procedure
ISO
CRV/
MDL
ISO
MDV/
MDL
SL­
IDE/
MDL
Beryllium
1620
0.641
0.773
0.810
Beryllium
200.8
0.564
0.846
2.667
Boron
1620
0.673
1.156
1.292
Bromobenzene
502.2
ELCD
0.711
1.428
5.575
Bromobenzene
502.2
PID
23.364
50.631
3.947
Bromobenzene
524.2
0.834
­
1.041
4.021
Bromochloromethane
502.2
ELCD
1.166
2.381
34.635
Bromochloromethane
524.2
0.902
1.319
2.468
Bromodichloromethane
502.2
ELCD
3.804
7.753
15.209
Bromodichloromethane
524.2
0.614
0.538
4.229
Bromoform
502.2
ELCD
1.503
2.627
242.497
Bromoform
524.2
0.523
0.323
2.835
Bromomethane
502.2
ELCD
0.178
0.037
26.202
Bromomethane
524.2
0.810
0.893
3.516
Cadmium
1620
0.619
1.056
1.449
Cadmium
200.8
1.769
2.985
2.793
Calcium
1620
0.975
1.971
1.080
Carbon
Disulfide
524.2
0.582
­
1.199
7.610
Carbon
Tetrachloride
524.2
0.711
­
0.770
6.751
Carbontet+
1,1­
dcp
502.2
ELCD
0.986
2.089
2.162
Chloroacetonitrile
524.2
0.841
1.671
1.671
Chlorobenzene
502.2
ELCD
1.373
2.964
38.584
Chlorobenzene
502.2
PID
2.654
5.904
2.063
Chlorobenzene
524.2
0.880
0.643
4.864
Chloroethane
502.2
ELCD
0.051
0.041
23.132
Chloroethane
524.2
0.619
0.637
5.069
Chloroform
502.2
ELCD
9.595
17.716
0.722
Chloroform
524.2
0.745
0.692
5.610
Chloromethane
502.2
ELCD
1.292
3.452
2.934
Chloromethane
524.2
0.803
1.469
4.798
Chromium
1620
0.819
1.246
1.545
Chromium
200.8
0.847
1.713
5.391
Cis­
1,2­
dce+
2,2­
dcp
502.2
ELCD
1.334
2.619
3.344
Cis­
1,2­
dichloroethene
524.2
0.826
­
0.342
5.104
February
2003
Appendix
C
Table
3.
Ratios
ofDetection
Limits
to
the
EPA/
ACS
DL
for
the
Episode
6000
Data
Set
Cis­
1,3­
dichloropropene
Cis­
1,3­
dichloropropene
Cobalt
Cobalt
Copper
Copper
Dibromochloromethane
Dibromochloromethane
Dibromomethane
Dibromomethane
Dichlorodifluoromethane
Dichlorodifluoromethane
Diethyl
Ether
Ethyl
Methacrylate
Ethylbenzene
Ethylbenzene
Hardness
Hexachlorobutadiene
Hexachlorobutadiene
Hexachloroethane
Hexchlobutadiene+
naphthalene
Iron
Isopropylbenzene
Isopropylbenzene
Lead
Lead
M+
p
Xylene
M+
p
Xylene
Magnesium
Manganese
Manganese
Mercury
Methacrylonitrile
February
2003
Analyte
Cis­
1,3­
dichloropropene
Method
Procedure
ISO
CRV/
MDL
ISO
MDV/
MDL
SL­
IDE/
MDL
502.2
ELCD
2.183
4.379
8.267
502.2
PID
0.839
1.742
1.367
524.2
0.616
0.038
4.116
1620
0.409
0.824
1.585
200.8
0.790
­
64.641
8.058
1620
0.825
1.739
3.362
200.8
0.716
1.429
20.667
502.2
ELCD
2.077
4.211
45.610
524.2
0.600
0.208
4.953
502.2
ELCD
7.153
14.604
67.146
524.2
0.806
1.145
3.356
502.2
ELCD
163.453
192.935
9.771
524.2
0.651
0.551
5.027
524.2
0.952
1.412
2.837
524.2
0.681
0.401
5.391
502.2
PID
2.459
5.663
3.496
524.2
0.833
­
0.475
4.992
130.2
0.669
1.391
2.598
502.2
ELCD
5.586
11.673
2.097
524.2
0.519
­
0.293
3.866
524.2
0.883
0.782
4.186
502.2
PID
1.423
3.208
0.920
1620
2.991
5.223
3.824
502.2
PID
2.530
5.930
2.921
524.2
0.920
1.099
10.555
1620
0.720
1.193
1.407
200.8
0.093
0.183
0.301
502.2
PID
1.093
2.496
1.281
524.2
0.588
0.449
9.870
1620
0.861
1.702
0.967
1620
0.158
0.378
0.953
200.8
0.974
1.587
3.450
200.8
0.799
­
4.048
14.165
524.2
0.642
1.034
1.808
C­
21
Assessment
of
Detection
and
Quantitation
Approaches
Table
3.
Ratios
ofDetection
Limits
to
the
EPA/
ACS
DL
for
the
Episode
6000
Data
Set
Analyte
Methyl
Iodide
Methyl
Tert­
butyl
Ether
Methylacrylate
Methylene
Chloride
Methylene
Chloride
Methylmethacrylate
Molybdenum
Molybdenum
N­
butylbenzene
N­
butylbenzene
N­
propylbenzene
N­
propylbenzene
Naphthalene
Nickel
Nickel
o­
xylene
o­
xylene+
styrene
P­
isoproptol+
1,4­
dcb
Pentachloroethane
Sec­
butylbenzene
Sec­
butylbenzene
Selenium
Selenium
Silver
Silver
Sodium
Styrene
Tert­
butylbenzene
Tert­
butylbenzene
Tetrachloroethene
Tetrachloroethene
Tetrachloroethene
Thallium
Thallium
C­
22
Method
Procedure
ISO
CRV/
MDL
ISO
MDV/
MDL
SL­
IDE/
MDL
524.2
0.924
­
0.257
6.826
524.2
0.630
­
1.011
7.514
524.2
0.918
1.618
2.495
502.2
ELCD
14.312
39.130
21.261
524.2
0.875
1.196
3.367
524.2
0.376
0.535
2.153
1620
0.698
1.543
1.188
200.8
0.777
0.013
68.949
502.2
PID
2.322
5.050
4.676
524.2
0.890
1.694
8.614
502.2
PID
14.846
33.306
2.221
524.2
0.676
­
1.102
6.104
524.2
0.821
0.983
3.622
1620
0.656
1.271
1.176
200.8
0.397
0.736
0.524
524.2
0.802
­
1.396
8.734
502.2
PID
2.012
4.469
1.893
502.2
PID
2.090
4.573
2.107
524.2
0.035
­
0.153
0.610
502.2
PID
1.039
2.402
1.429
524.2
0.762
­
0.517
9.507
1620
0.729
1.759
2.256
200.8
0.815
1.577
2.139
1620
0.731
1.324
2.082
200.8
0.441
0.947
2.581
1620
0.713
1.404
1.913
524.2
0.797
0.815
8.467
502.2
PID
2.024
4.819
2.575
524.2
0.535
1.065
7.707
502.2
ELCD
11.204
23.979
2.831
502.2
PID
5.175
12.216
2.540
524.2
0.997
0.688
4.482
1620
1.273
2.747
2.361
200.8
1.038
1.964
3.125
February
2003
Appendix
C
Table
3.
Ratios
ofDetection
Limits
to
the
EPA/
ACS
DL
for
the
Episode
6000
Data
Set
Analyte
Method
Procedure
ISO
CRV/
MDL
ISO
MDV/
MDL
SL­
IDE/
MDL
Thorium
200.8
0.836
­
6.702
4.345
Tin
1620
0.550
0.856
0.327
Titanium
1620
0.932
1.685
1.097
Toluene
502.2
PID
0.923
2.068
0.873
Toluene
524.2
0.280
­
0.100
6.591
Total
Phosphorus
365.2
0.777
1.572
2.202
Total
Suspended
Solids
160.2
0.810
1.662
2.459
Trans­
1,2­
dichloroethene
502.2
ELCD
4.267
9.382
1.603
Trans­
1,2­
dichloroethene
524.2
0.834
­
0.210
6.695
Trans­
1,3­
dichloropropene
502.2
ELCD
1.098
2.183
6.938
Trans­
1,3­
dichloropropene
502.2
PID
0.641
1.358
1.454
Trans­
1,3­
dichloropropene
524.2
0.486
­
0.008
4.018
Trans­
1,4­
dichloro­
2­
butene
524.2
0.680
1.150
2.310
Trichloroethene
502.2
ELCD
1.157
2.435
4.169
Trichloroethene
502.2
PID
1.592
3.635
3.539
Trichloroethene
524.2
0.952
1.009
4.690
Trichlorofluoromethane
502.2
ELCD
0.114
0.256
18.504
Trichlorofluoromethane
524.2
0.858
0.527
3.516
Uranium
200.8
0.495
0.757
2.519
Vanadium
1620
0.573
1.138
1.370
Vanadium
200.8
0.923
1.791
1.522
Vinyl
Chloride
502.2
ELCD
0.144
0.268
13.063
Vinyl
Chloride
524.2
0.719
0.004
6.845
WAD
Cyanide
1677
0.296
0.558
1.175
Xylene
(
Total)
524.2
0.575
0.850
12.430
Yttrium
1620
0.712
1.310
1.622
Zinc
1620
0.886
1.423
1.700
Zinc
200.8
0.511
0.895
1.663
Note:
ELCD
or
PID
in
the
Procedure
column
indicates
the
photo­
ionization
detector
(
PID)
or
electrolytic
conductivity
detector
(
ELCD)
in
EPA
Method
502.2
February
2003
C­
23
Assessment
of
Detection
and
Quantitation
Approaches
Summary
Statistics
for
Table
3
ISO
CRV/
EPA/
ACS
DL
ISO
MDV/
EPA/
ACS
DL
SL­
IDE/
EPA/
ACS
DL
Minimum
0.01
­
64.64
0.10
25th
percentile
0.61
0.52
1.60
Median
0.80
1.17
2.86
75th
percentile
1.08
2.17
5.41
Maximum
163.45
192.93
242.50
Number
of
analytes
Percent
of
analytes
p­
value
for
percent=
50
CRV>
DL
52
26.26%
<
0.0001
MDV>
DL
113
57.07%
0.055
SL­
IDE>
DL
181
91.41%
<
0.0001
Table
4.
Comparison
Quantitation
Limits
for
the
Episode
6000
Data
Set
(
µ
g/
L
except
where
footnoted)

Analyte
Method
Procedure
EPA/
ACS
QL
ISO/
IUPAC
LOQ
ASTM
SL­
IQE
1,1,1,2­
tetrachloroethane
502.2
ELCD
0.2
0.152
0.030
1,1,1,2­
tetrachloroethane
524.2
0.2
0.183
0.181
1,1,1­
trichloroethane
502.2
ELCD
0.1
0.044
0.830
1,1,1­
trichloroethane
524.2
0.5
0.102
0.240
1,1,2,2­
tce+
1,2,3­
tcp
502.2
ELCD
0.5
1.110
5.514
1,1,2,2­
tetrachloroethane
524.2
0.5
0.596
0.569
1,1,2­
trichloroethane
502.2
ELCD
0.1
0.289
0.060
1,1,2­
trichloroethane
524.2
0.5
0.212
0.290
1,1­
dichloroethane
502.2
ELCD
0.05
0.047
0.527
1,1­
dichloroethane
524.2
0.2
0.099
0.115
1,1­
dichloroethene
502.2
ELCD
0.1
0.096
3.796
1,1­
dichloroethene
524.2
0.2
0.159
0.129
1,1­
dichloropropanone
524.2
20
15.396
12.705
1,1­
dichloropropene
524.2
0.5
0.057
0.180
1,2,3­
trichlorobenzene
502.2
ELCD
0.2
1.750
0.851
1,2,3­
trichlorobenzene
502.2
PID
0.2
1.818
0.248
1,2,3­
trichlorobenzene
524.2
0.2
0.192
0.216
1,2,3­
trichloropropane
524.2
20
0.267
11.316
C­
24
February
2003
Appendix
C
Table
4.
Comparison
Quantitation
Limits
for
the
Episode
6000
Data
Set
1,2­
dibromo­
3­
chloropropane
524.2
502.2
524.2
502.2
502.2
524.2
502.2
524.2
502.2
524.2
1,2­
dibromoethane
1,2­
dibromoethane
1,2­
dichlorobenzene
1,2­
dichlorobenzene
1,2­
dichlorobenzene
1,2­
dichloroethane
1,2­
dichloroethane
1,2­
dichloropropane
1,2­
dichloropropane
Analyte
Method
1,2,4­
trichlorobenzene
502.2
EPA/
Procedure
ACS
QL
ELCD
0.1
502.2
524.2
502.2
524.2
PID
0.2
0.2
PID
0.5
0.1
ISO/
IUPAC
LOQ
1.150
1.371
0.231
0.485
0.050
1.843
0.156
0.560
0.418
0.139
0.101
0.089
0.122
1.138
0.148
1.275
0.044
0.301
0.840
0.080
0.356
0.114
0.571
0.069
0.082
0.568
1.416
0.881
2.877
0.046
0.669
1.280
0.668
ASTM
SL­
IQE
0.401
0.439
0.141
0.653
20.896
71.182
0.592
0.417
0.183
0.346
0.085
0.065
0.222
0.102
0.196
0.189
23.744
0.936
0.465
0.076
0.054
0.139
0.101
0.078
29.943
38.009
0.893
0.493
0.849
0.053
0.442
0.590
0.142
1
1,2,4­
trichlorobenzene
1,2,4­
trichlorobenzene
1,2,4­
trimethylbenzene
1,2,4­
trimethylbenzene
0.5
ELCD
0.1
PID
0.1
0.1
ELCD
0.1
0.5
ELCD
0.1
0.5
10
ELCD
0.5
1,3,5­
tmb+
4­
chlorotoluene
502.2
1,3,5­
trimethylbenzene
524.2
1,3­
dichlorobenzene
502.2
ELCD
0.1
1,3­
dichlorobenzene
502.2
PID
0.2
1,3­
dichlorobenzene
524.2
0.1
1,3­
dichloropropane
502.2
ELCD
0.1
1,3­
dichloropropane
524.2
0.2
1,4­
dichlorobenzene
502.2
ELCD
0.1
1,4­
dichlorobenzene
524.2
0.1
1­
chlorobutane
524.2
0.1
2,2­
dichloropropane
524.2
10
2­
butanone
524.2
2
2­
chlorotoluene
502.2
ELCD
0.5
2­
chlorotoluene
502.2
PID
1
2­
chlorotoluene
524.2
0.1
2­
hexanone
524.2
10
2­
nitropropane
524.2
10
4­
chlorotoluene
502.2
ELCD
0.5
4­
chlorotoluene
524.2
0.1
0.037
23.810
PID
0.2
0.1
February
2003
(
µ
g/
L
except
where
footnoted)

C­
25
Assessment
of
Detection
and
Quantitation
Approaches
Table
4.
Comparison
Quantitation
Limits
for
the
Episode
6000
Data
Set
(
µ
g/
L
except
where
footnoted)

Analyte
Method
Procedure
EPA/
ACS
QL
4­
isopropyltoluene
524.2
0.1
4­
methyl­
2­
pentanone
524.2
5
Acetone
524.2
2
Acrylonitrile
524.2
5
Allyl
Chloride
524.2
0.2
Aluminum
1620
100
Aluminum
200.8
50
Ammonia
as
Nitrogen
2
350.3
0.05
Antimony
1620
5
Antimony
200.8
0.5
Arsenic
1620
5
Arsenic
200.8
1
Barium
1620
5
Barium
200.8
0.1
Benzene
502.2
PID
0.1
Benzene
524.2
0.05
Beryllium
1620
2
Beryllium
200.8
0.02
Boron
1620
100
Bromobenzene
502.2
ELCD
0.5
Bromobenzene
502.2
PID
0.05
Bromobenzene
524.2
0.2
Bromochloromethane
502.2
ELCD
0.1
Bromochloromethane
524.2
0.5
Bromodichloromethane
502.2
ELCD
0.05
Bromodichloromethane
524.2
0.2
Bromoform
502.2
ELCD
0.2
Bromoform
524.2
0.5
Bromomethane
502.2
ELCD
1
Bromomethane
524.2
0.2
Cadmium
1620
0.5
Cadmium
200.8
0.02
Calcium
1620
100
ISO/
IUPAC
LOQ
0.043
2.065
2.115
1.816
0.129
76.242
9.418
0.037
4.784
0.017
3.684
0.720
4.722
0.161
0.273
0.075
1.055
0.018
46.040
0.593
1.767
0.167
0.090
0.549
0.091
0.135
0.056
0.287
undefined
3
0.252
0.346
0.046
186.530
ASTM
SL­
IQE
0.016
1.785
2.741
28.056
29.674
464.069
29.684
0.035
9.551
0.034
3.097
0.798
4.118
0.211
0.182
0.044
0.980
0.044
51.134
3.529
0.100
0.140
1.598
0.368
0.424
0.128
3.393
0.482
16.351
0.226
0.410
0.063
99.975
Carbon
Disulfide
524.2
0.1
0.077
0.101
C­
26
February
2003
Appendix
C
Table
4.
Comparison
Quantitation
Limits
for
the
Episode
6000
Data
Set
(
µ
g/
L
except
where
footnoted)

Analyte
Method
Procedure
EPA/
ACS
QL
Carbon
Tetrachloride
524.2
0.2
Carbontet+
1,1­
dcp
502.2
ELCD
0.2
Chloroacetonitrile
524.2
10
Chlorobenzene
502.2
ELCD
0.1
Chlorobenzene
502.2
PID
0.1
Chlorobenzene
524.2
0.1
Chloroethane
502.2
ELCD
0.5
Chloroethane
524.2
0.5
Chloroform
502.2
ELCD
0.2
Chloroform
524.2
0.2
Chloromethane
502.2
ELCD
0.2
Chloromethane
524.2
0.2
Chromium
1620
1
Chromium
200.8
0.2
Cis­
1,2­
dce+
2,2­
dcp
502.2
ELCD
0.05
Cis­
1,2­
dichloroethene
524.2
0.5
Cis­
1,3­
dichloropropene
502.2
ELCD
0.1
Cis­
1,3­
dichloropropene
502.2
PID
0.2
Cis­
1,3­
dichloropropene
524.2
0.2
Cobalt
1620
50
Cobalt
200.8
0.005
Copper
1620
20
Copper
200.8
0.1
Dibromochloromethane
502.2
ELCD
0.1
Dibromochloromethane
524.2
0.5
Dibromomethane
502.2
ELCD
0.1
Dibromomethane
524.2
0.5
Dichlorodifluoromethane
502.2
ELCD
0.1
Dichlorodifluoromethane
524.2
0.5
Diethyl
Ether
524.2
0.5
Ethyl
Methacrylate
524.2
0.5
Ethylbenzene
502.2
PID
0.1
Ethylbenzene
524.2
0.2
ISO/
IUPAC
LOQ
ASTM
SL­
IQE
0.127
0.140
0.173
0.069
4.169
3.310
0.092
1.766
0.504
0.119
0.108
0.059
0.037
5.826
0.185
0.255
2.217
0.025
0.138
0.121
0.709
1.734
0.181
0.141
0.993
1.259
0.331
1.028
0.097
0.039
0.154
0.144
0.090
0.415
0.254
0.017
1
0.116
0.141
20.916
40.837
undefined
3
undefined
4
27.513
47.509
0.142
1.825
0.106
1.252
0.149
0.288
0.257
1.395
0.400
0.460
5.759
1.091
0.289
0.480
0.563
0.404
0.139
0.183
0.341
0.157
0.123
0.077
Hardness
2
130.2
2
2.973
5.465
February
2003
C­
27
Assessment
of
Detection
and
Quantitation
Approaches
Table
4.
Comparison
Quantitation
Limits
for
the
Episode
6000
Data
Set
(
µ
g/
L
except
where
footnoted)

Analyte
Method
Procedure
EPA/
ACS
QL
ISO/
IUPAC
LOQ
Hexachlorobutadiene
502.2
ELCD
0.2
1.466
Hexachlorobutadiene
524.2
0.2
0.160
Hexachloroethane
524.2
0.2
0.232
Hexchlobutadiene+
naphthalene
502.2
PID
2
6.108
Iron
1620
200
1490.589
Isopropylbenzene
502.2
PID
0.1
0.337
Isopropylbenzene
524.2
0.1
0.056
Lead
1620
5
5.062
Lead
200.8
2
0.318
M+
p
Xylene
502.2
PID
0.2
0.652
M+
p
Xylene
524.2
0.1
0.042
Magnesium
1620
500
454.043
Manganese
1620
20
7.948
Manganese
200.8
0.1
0.133
Mercury
200.8
0.02
0.056
Methacrylonitrile
524.2
2
1.065
Methyl
Iodide
524.2
0.2
0.108
Methyl
Tert­
butyl
Ether
524.2
0.5
0.073
Methylacrylate
524.2
1
0.966
Methylene
Chloride
502.2
ELCD
1
undefined
3
Methylene
Chloride
524.2
0.2
0.354
Methylmethacrylate
524.2
1
0.381
Molybdenum
1620
10
9.752
Molybdenum
200.8
0.01
0.052
N­
butylbenzene
502.2
PID
0.1
0.429
N­
butylbenzene
524.2
0.1
0.077
N­
propylbenzene
502.2
PID
0.2
3.869
N­
propylbenzene
524.2
0.2
0.110
Naphthalene
524.2
0.2
0.184
Nickel
1620
100
66.486
Nickel
200.8
0.5
0.287
o­
xylene
524.2
0.2
0.062
o­
xylene+
styrene
502.2
PID
0.2
0.746
ASTM
SL­
IQE
0.243
0.228
0.167
1.542
996.565
0.129
25.592
5.698
0.685
0.222
24.651
267.199
15.264
0.245
0.039
19.062
0.083
0.122
0.727
6.033
0.433
20.773
7.597
0.608
0.745
0.067
0.186
29.878
0.108
67.206
0.183
0.040
0.181
P­
isoproptol+
1,4­
dcb
502.2
PID
0.2
0.956
0.456
C­
28
February
2003
Appendix
C
Table
4.
Comparison
Quantitation
Limits
for
the
Episode
6000
Data
Set
(
µ
g/
L
except
where
footnoted)

Analyte
Method
Procedure
EPA/
ACS
QL
Pentachloroethane
524.2
2
Sec­
butylbenzene
502.2
PID
0.2
Sec­
butylbenzene
524.2
0.1
Selenium
1620
2
Selenium
200.8
1
Silver
1620
20
Silver
200.8
0.02
Sodium
1620
200
Styrene
524.2
0.1
Tert­
butylbenzene
502.2
PID
0.1
Tert­
butylbenzene
524.2
0.1
Tetrachloroethene
502.2
ELCD
0.1
Tetrachloroethene
502.2
PID
0.2
Tetrachloroethene
524.2
0.2
Thallium
1620
2
Thallium
200.8
0.001
Thorium
200.8
0.002
Tin
1620
10
Titanium
1620
20
Toluene
502.2
PID
0.2
Toluene
524.2
0.2
Total
Phosphorus
2
365.2
0.02
Total
Suspended
Solids
2
160.2
5
Trans­
1,2­
dichloroethene
502.2
ELCD
0.2
Trans­
1,2­
dichloroethene
524.2
0.2
Trans­
1,3­
dichloropropene
502.2
ELCD
0.1
Trans­
1,3­
dichloropropene
502.2
PID
0.2
Trans­
1,3­
dichloropropene
524.2
0.5
Trans­
1,4­
dichloro­
2­
butene
524.2
2
Trichloroethene
502.2
ELCD
0.1
Trichloroethene
502.2
PID
0.1
Trichloroethene
524.2
0.2
Trichlorofluoromethane
502.2
ELCD
0.5
ISO/
IUPAC
LOQ
ASTM
SL­
IQE
0.086
0.551
0.377
0.157
0.063
0.047
3.859
5.235
0.805
1.045
16.734
25.842
0.011
0.056
251.546
337.755
0.054
0.041
0.391
0.203
0.063
0.073
1.226
0.122
2.084
0.750
0.377
30.554
3.748
2.799
0.002
0.003
0.005
0.004
9.237
9.406
20.807
14.236
0.409
0.194
0.028
0.046
0.024
0.030
5.011
6.729
1.060
0.191
0.140
0.153
0.073
0.729
0.205
0.175
0.121
0.218
1.801
30.108
0.081
3.169
0.260
0.401
0.283
0.167
0.085
4.662
Trichlorofluoromethane
524.2
0.5
0.279
42.490
February
2003
C­
29
Assessment
of
Detection
and
Quantitation
Approaches
Table
4.
Comparison
Quantitation
Limits
for
the
Episode
6000
Data
Set
(
µ
g/
L
except
where
footnoted)

Analyte
Method
Procedure
EPA/
ACS
QL
ISO/
IUPAC
LOQ
ASTM
SL­
IQE
Uranium
200.8
0.001
0.001
0.002
Vanadium
1620
20
21.586
24.338
Vanadium
200.8
2
2.627
1.933
Vinyl
Chloride
502.2
ELCD
1
0.270
8.234
Vinyl
Chloride
524.2
0.2
0.139
0.219
WAD
Cyanide
1677
2
0.852
1.624
Xylene
(
Total)
524.2
0.1
0.027
23.520
Yttrium
1620
5
6.571
8.962
Zinc
1620
10
9.575
10.452
Zinc
200.8
2
2.147
7.024
1
IQE
10%
undefined,
IQE
20%
reported
2
Results
reported
as
mg/
L
3
No
LOQ
could
be
calculated
due
to
a
square
root
of
a
negative
number
in
the
formula
4
IQE
10%,
IQE
20%
and
IQE
30%
all
negative
based
on
chosen
model
(
linear)
Note:
ELCD
or
PID
in
the
Procedure
column
indicates
the
photo­
ionization
detector
(
PID)
or
electrolytic
conductivity
detector
(
ELCD)
in
EPA
Method
502.2
Table
5.
Ratios
of
Quantitation
Limits
to
the
EPA/
ACS
QL
for
the
Episode
6000
Data
Set
Analyte
Method
Procedure
ISO
LOQ/
ML
SL­
IQE/
ML
1,1,1,2­
tetrachloroethane
502.2
ELCD
0.759
0.152
1,1,1,2­
tetrachloroethane
524.2
0.915
0.907
1,1,1­
trichloroethane
502.2
ELCD
0.445
8.298
1,1,1­
trichloroethane
524.2
0.203
0.479
1,1,2,2­
tce+
1,2,3­
tcp
502.2
ELCD
2.220
11.027
1,1,2,2­
tetrachloroethane
524.2
1.192
1.138
1,1,2­
trichloroethane
502.2
ELCD
2.886
0.603
1,1,2­
trichloroethane
524.2
0.424
0.579
1,1­
dichloroethane
502.2
ELCD
0.949
10.531
1,1­
dichloroethane
524.2
0.496
0.573
1,1­
dichloroethene
502.2
ELCD
0.960
37.963
1,1­
dichloroethene
524.2
0.795
0.644
1,1­
dichloropropanone
524.2
0.770
0.635
1,1­
dichloropropene
524.2
0.114
0.360
1,2,3­
trichlorobenzene
502.2
ELCD
8.751
4.257
C­
30
February
2003
Appendix
C
Table
5.
Ratios
of
Quantitation
Limits
to
the
EPA/
ACS
QL
for
the
Episode
6000
Data
Set
Analyte
Method
Procedure
ISO
LOQ/
ML
SL­
IQE/
ML
1,2,3­
trichlorobenzene
502.2
PID
9.092
1.239
1,2,3­
trichlorobenzene
524.2
0.959
1.080
1,2,3­
trichloropropane
524.2
0.013
0.566
1,2,4­
trichlorobenzene
502.2
ELCD
11.502
4.010
1,2,4­
trichlorobenzene
502.2
PID
6.853
2.197
1,2,4­
trichlorobenzene
524.2
1.157
0.703
1,2,4­
trimethylbenzene
502.2
PID
0.970
1.306
1,2,4­
trimethylbenzene
524.2
0.503
208.956
1,2­
dibromo­
3­
chloropropane
524.2
0.184
7.118
1,2­
dibromoethane
502.2
ELCD
0.311
1.185
1,2­
dibromoethane
524.2
1.119
0.834
1,2­
dichlorobenzene
502.2
ELCD
4.178
1.833
1,2­
dichlorobenzene
502.2
PID
1.393
3.455
1,2­
dichlorobenzene
524.2
1.006
0.848
1,2­
dichloroethane
502.2
ELCD
0.891
0.650
1,2­
dichloroethane
524.2
0.244
0.443
1,2­
dichloropropane
502.2
ELCD
11.378
1.023
1,2­
dichloropropane
524.2
0.296
0.393
1,3,5­
tmb+
4­
chlorotoluene
502.2
PID
6.373
0.946
1,3,5­
trimethylbenzene
524.2
0.436
237.442
1,3­
dichlorobenzene
502.2
ELCD
3.008
9.356
1,3­
dichlorobenzene
502.2
PID
4.201
2.326
1,3­
dichlorobenzene
524.2
0.800
0.760
1,3­
dichloropropane
502.2
ELCD
3.560
0.539
1,3­
dichloropropane
524.2
0.569
0.695
1,4­
dichlorobenzene
502.2
ELCD
5.714
1.010
1,4­
dichlorobenzene
524.2
0.686
0.784
1­
chlorobutane
524.2
0.823
299.428
2,2­
dichloropropane
524.2
0.057
3.801
2­
butanone
524.2
0.708
0.446
2­
chlorotoluene
502.2
ELCD
1.763
0.986
2­
chlorotoluene
502.2
PID
2.877
0.849
2­
chlorotoluene
524.2
0.463
0.533
2­
hexanone
524.2
0.067
0.044
2­
nitropropane
524.2
0.128
0.059
C­
31
February
2003
Assessment
of
Detection
and
Quantitation
Approaches
Table
5.
Ratios
of
Quantitation
Limits
to
the
EPA/
ACS
QL
for
the
Episode
6000
Data
Set
Analyte
Method
Procedure
ISO
LOQ/
ML
SL­
IQE/
ML
4­
chlorotoluene
502.2
ELCD
1.335
0.284
4­
chlorotoluene
524.2
0.373
238.097
4­
isopropyltoluene
524.2
0.428
0.163
4­
methyl­
2­
pentanone
524.2
0.413
0.357
Acetone
524.2
1.057
1.371
Acrylonitrile
524.2
0.363
5.611
Allyl
chloride
524.2
0.646
148.372
Aluminum
1620
0.762
4.641
Aluminum
200.8
ICP/
MS
0.188
0.594
Ammonia
as
nitrogen
350.3
0.733
0.709
Antimony
1620
0.957
1.910
Antimony
200.8
ICP/
MS
0.035
0.067
Arsenic
1620
0.737
0.619
Arsenic
200.8
ICP/
MS
0.720
0.798
Barium
1620
0.944
0.824
Barium
200.8
ICP/
MS
1.608
2.114
Benzene
502.2
PID
2.735
1.819
Benzene
524.2
1.509
0.877
Beryllium
1620
0.527
0.490
Beryllium
200.8
ICP/
MS
0.905
2.201
Boron
1620
0.460
0.511
Bromobenzene
502.2
ELCD
1.186
7.058
Bromobenzene
502.2
PID
35.338
2.007
Bromobenzene
524.2
0.833
0.699
Bromochloromethane
502.2
ELCD
0.900
15.977
Bromochloromethane
524.2
1.097
0.737
Bromodichloromethane
502.2
ELCD
1.814
8.484
Bromodichloromethane
524.2
0.676
0.640
Bromoform
502.2
ELCD
0.282
16.964
Bromoform
524.2
0.573
0.964
Bromomethane
502.2
ELCD
N/
A
16.351
Bromomethane
524.2
1.262
1.130
Cadmium
1620
0.692
0.820
Cadmium
200.8
ICP/
MS
2.311
3.148
Calcium
1620
1.865
1.000
February
2003C­
32
Appendix
C
Table
5.
Ratios
of
Quantitation
Limits
to
the
EPA/
ACS
QL
for
the
Episode
6000
Data
Set
Analyte
Method
Procedure
ISO
LOQ/
ML
SL­
IQE/
ML
Carbon
disulfide
524.2
0.768
1.013
Carbon
tetrachloride
524.2
0.635
0.700
Carbontet+
1,1­
dcp
502.2
ELCD
0.864
0.343
Chloroacetonitrile
524.2
0.417
0.331
Chlorobenzene
502.2
ELCD
0.921
17.658
Chlorobenzene
502.2
PID
5.040
1.190
Chlorobenzene
524.2
1.077
0.595
Chloroethane
502.2
ELCD
0.074
11.652
Chloroethane
524.2
0.369
0.510
Chloroform
502.2
ELCD
11.086
0.126
Chloroform
524.2
0.688
0.606
Chloromethane
502.2
ELCD
3.547
8.669
Chloromethane
524.2
0.906
0.703
Chromium
1620
0.993
1.259
Chromium
200.8
ICP/
MS
1.653
5.142
Cis­
1,2­
dce+
2,2­
dcp
502.2
ELCD
1.941
0.780
Cis­
1,2­
dichloroethene
524.2
0.307
0.288
Cis­
1,3­
dichloropropene
502.2
ELCD
0.902
4.151
Cis­
1,3­
dichloropropene
502.2
PID
1.271
0.083
Cis­
1,3­
dichloropropene
524.2
0.582
0.706
Cobalt
1620
0.418
0.817
Cobalt
200.8
ICP/
MS
N/
A
N/
A
Copper
1620
1.376
2.375
Copper
200.8
ICP/
MS
1.419
18.250
Dibromochloromethane
502.2
ELCD
1.059
12.515
Dibromochloromethane
524.2
0.299
0.575
Dibromomethane
502.2
ELCD
2.572
13.949
Dibromomethane
524.2
0.800
0.920
Dichlorodifluoromethane
502.2
ELCD
57.590
10.907
Dichlorodifluoromethane
524.2
0.579
0.959
Diethyl
ether
524.2
1.126
0.808
Ethyl
methacrylate
524.2
0.279
0.366
Ethylbenzene
502.2
PID
3.413
1.573
Ethylbenzene
524.2
0.613
0.387
Hardness
130.2
1.487
2.733
February
2003
C­
33
Assessment
of
Detection
and
Quantitation
Approaches
Table
5.
Ratios
of
Quantitation
Limits
to
the
EPA/
ACS
QL
for
the
Episode
6000
Data
Set
Analyte
Method
Procedure
ISO
LOQ/
ML
SL­
IQE/
ML
Hexachlorobutadiene
502.2
ELCD
7.332
1.215
Hexachlorobutadiene
524.2
0.799
1.142
Hexachloroethane
524.2
1.159
0.837
Hexchlobutadiene+
naphthalene
502.2
PID
3.054
0.771
Iron
1620
7.453
4.983
Isopropylbenzene
502.2
PID
3.372
1.290
Isopropylbenzene
524.2
0.563
255.921
Lead
1620
1.012
1.140
Lead
200.8
ICP/
MS
0.159
0.342
M+
p
xylene
502.2
PID
3.262
1.112
M+
p
xylene
524.2
0.419
246.513
Magnesium
1620
0.908
0.534
Manganese
1620
0.397
0.763
Manganese
200.8
ICP/
MS
1.326
2.451
Mercury
200.8
ICP/
MS
2.781
1.933
Methacrylonitrile
524.2
0.533
9.531
Methyl
iodide
524.2
0.538
0.417
Methyl
tert­
butyl
ether
524.2
0.146
0.245
C­
34
Methylacrylate
524.2
0.966
0.727
Methylene
chloride
502.2
ELCD
N/
A
6.033
Methylene
chloride
524.2
1.769
2.164
Methylmethacrylate
524.2
0.381
20.773
Molybdenum
1620
0.975
0.760
Molybdenum
200.8
ICP/
MS
5.181
60.817
N­
butylbenzene
502.2
PID
4.290
7.453
N­
butylbenzene
524.2
0.767
0.673
N­
propylbenzene
502.2
PID
19.343
0.931
N­
propylbenzene
524.2
0.552
149.392
Naphthalene
524.2
0.921
0.541
Nickel
1620
0.665
0.672
Nickel
200.8
ICP/
MS
0.574
0.365
O­
xylene
524.2
0.310
0.202
O­
xylene+
styrene
502.2
PID
3.731
0.905
P­
isoproptol+
1,4­
dcb
502.2
PID
4.778
2.281
Pentachloroethane
524.2
0.043
0.276
February
2003
Appendix
C
Table
5.
Ratios
of
Quantitation
Limits
to
the
EPA/
ACS
QL
for
the
Episode
6000
Data
Set
Analyte
Method
Procedure
ISO
LOQ/
ML
SL­
IQE/
ML
Sec­
butylbenzene
502.2
PID
1.885
0.784
Sec­
butylbenzene
524.2
0.628
0.475
Selenium
1620
1.929
2.617
Selenium
200.8
ICP/
MS
0.805
1.045
Silver
1620
0.837
1.292
Silver
200.8
ICP/
MS
0.543
2.800
Sodium
1620
1.258
1.689
Styrene
524.2
0.536
0.407
Tert­
butylbenzene
502.2
PID
3.911
2.027
Tert­
butylbenzene
524.2
0.634
0.735
Tetrachloroethene
502.2
ELCD
12.264
1.217
Tetrachloroethene
502.2
PID
10.419
3.749
Tetrachloroethene
524.2
1.886
152.769
Thallium
1620
1.874
1.399
Thallium
200.8
ICP/
MS
2.085
3.286
Thorium
200.8
ICP/
MS
2.648
2.198
Tin
1620
0.924
0.941
Titanium
1620
1.040
0.712
February
2003
Toluene
502.2
PID
2.045
0.971
Toluene
524.2
0.138
0.228
Total
phosphorus
365.2
1.188
1.499
Total
suspended
solids
160.2
1.002
1.346
Trans­
1,2­
dichloroethene
502.2
ELCD
5.298
0.953
Trans­
1,2­
dichloroethene
524.2
0.702
0.764
Trans­
1,3­
dichloropropene
502.2
ELCD
0.731
7.286
Trans­
1,3­
dichloropropene
502.2
PID
1.023
0.874
Trans­
1,3­
dichloropropene
524.2
0.241
0.436
Trans­
1,4­
dichloro­
2­
butene
524.2
0.900
15.054
Trichloroethene
502.2
ELCD
0.812
31.690
Trichloroethene
502.2
PID
2.601
4.010
Trichloroethene
524.2
1.417
0.837
Trichlorofluoromethane
502.2
ELCD
0.171
9.325
Trichlorofluoromethane
524.2
0.558
84.980
Uranium
200.8
ICP/
MS
0.721
1.853
Vanadium
1620
1.079
1.217
C­
35
Assessment
of
Detection
and
Quantitation
Approaches
Table
5.
Ratios
of
Quantitation
Limits
to
the
EPA/
ACS
QL
for
the
Episode
6000
Data
Set
ISO
Analyte
Method
Procedure
LOQ/
ML
SL­
IQE/
ML
Vanadium
200.8
ICP/
MS
1.314
0.966
Vinyl
chloride
502.2
ELCD
0.270
8.234
Vinyl
chloride
524.2
0.697
1.097
Wad
cyanide
1677
WADCN
0.426
0.812
Xylene
(
total)
524.2
0.266
235.197
Yttrium
1620
1.314
1.792
Zinc
1620
0.957
1.045
Zinc
200.8
ICP/
MS
1.073
3.512
Note:
ELCD
or
PID
in
the
Procedure
column
indicates
the
photo­
ionization
detector
(
PID)
or
electrolytic
conductivity
detector
(
ELCD)
in
EPA
Method
502.2
Summary
Statistics
for
Table
5
ISO
LOQ/
QL
SL­
IQE/
QL
Minimum
0.013
0.044
25th
percentile
0.547
0.672
Median
0.915
1.023
75th
percentile
1.792
3.512
Maximum
57.590
299.428
Number
of
analytes
Percent
of
analytes
p­
value
for
percent=
50
LOQ>
QL
84
43.08%
0.062
SL­
IQE>
QL
101
51.27%
0.776
C­
36
February
2003
­­­­­­
Appendix
C
Table
6.
Frequency
Comparisons
for
Lowest
and
Highest
Detection
and
Quantitation
Limits
for
the
Episode
6000
Data
Set
Quantitation
limits
Rank
1
(
lowest)
2
3
(
highest)
Detection
limits
Rank
EPA/
ACS
DL
ISO
CRV
ISO
MDV
ASTM
SL­
IDE
1
(
lowest)
30.3%
49.5%
17.7%
2.5%
2
34.3%
33.3%
16.2%
16.2%
3
30.8%
17.2%
33.3%
18.7%
4
(
highest)
4.5%
0%
32.8%
62.6%

EPA/
ACS
QL
50.5%
33.8%
14.1%
­
46.0%
38.4%
No
equivalent
ISO
LOQ
ASTM
SL­
IQE
­
25.8%
22.2%
­
26.8%
37.9%

Table
7.
Detection
and
Quantitation
Limits
for
EPA
Methods
1631
and
1638
as
Computed
by
EPA
and
by
EPRI
(
ng/
L)

Ambient
Element1
WQC
2
Antimony
Cadmium
Copper
Lead
Mercury
12
Nickel
Selenium
5000
Silver
14000
370
2400
540
8200
320
Thallium
Zinc
1700
32000
Detection
limits
Quantitation
limits
MDL
in
Method
IDE
computed
by
ML
in
Method
IQE
computed
by
EPA
EPRI
EPA
EPRI
9.7
140
110
20
270
270
25
150
150
100
540
380
87
780
770
200
3800
3000
15
140
160
50
420
370
0.2
0.5
0.43
0.5
0.55
1.6
330
220
130
1000
15000
330
450
760
600
1000
630
720
29
220
100
5500
7.9
27
20
20
87
50
140
1700
2100
500
21000
26100
1
Mercury
determined
by
EPA
Method
1631;
all
others
by
EPA
Method
1638
2
Lowest
ambient
water
quality
criterion
(
WQC)
in
the
National
Toxics
Rule
(
40
CFR
131.36)

February
2003
C­
37
Assessment
of
Detection
and
Quantitation
Approaches
Table
8.
Comparison
of
Single­
laboratory
IDEs
resulting
from
all
model
types
for
EPA
Methods
1631
and
1638
Analyte
IDE,
Based
on
Given
Model
Constant
Linear
Exponential
Hybrid
Antimony
­
72
1
140
99
Cadmium
120
150
140
Copper
960
780
690
Lead
140
140
140
Mercury
8.1
0.059
0.79
0.50
Nickel
­
37
1
220
110
Selenium
4300
680
760
500
Silver
670
220
undefined
2
Thallium
21
27
16
Zinc
1500
1700
1700
2400
1200
2600
380
6600
2400
220
9600
1
Negative
due
to
negative
intercept
estimate
in
precision
model.
2
IDE
did
not
converge
to
a
single
value
for
estimated
models.

Table
9.
Comparison
of
16­
point
and
5­
point
Single­
laboratory
IDEs
(
SL­
IDEs)
for
the
Episode
6000
Data
Set
SL­
IDE(
16)/
SL­
IDE
16
SL­
IDE
5
Analyte
Method
Procedure
SL­
IDE
(
16)
SL­
IDE
(
5)
SL­
IDE(
5)
Model
Model
1,1,1,2­
tetrachloroethane
502.2
ELCD
0.028
0.011
2.616
Exponential
Linear
1,1,1,2­
tetrachloroethane
524.2
0.206
0.160
1.287
Exponential
Exponential
1,1,1­
trichloroethane
502.2
ELCD
0.035
0.035
0.974
Exponential
Exponential
1,1,1­
trichloroethane
524.2
0.268
0.033
8.033
Exponential
Hybrid
1,1,2,2­
tce+
1,2,3­
tcp
502.2
ELCD
0.170
3.404
0.050
Exponential
Constant
1,1,2,2­
tetrachloroethane
524.2
0.377
0.505
0.746
Exponential
Exponential
1,1,2­
trichloroethane
502.2
ELCD
0.026
0.012
2.158
Exponential
Linear
1,1,2­
trichloroethane
524.2
0.284
0.218
1.300
Exponential
Exponential
1,1­
dichloroethane
502.2
ELCD
0.066
0.022
2.971
Exponential
Exponential
1,1­
dichloroethane
524.2
0.206
0.089
2.310
Exponential
Exponential
1,1­
dichloroethene
502.2
ELCD
0.193
0.068
2.834
Exponential
Exponential
1,1­
dichloroethene
524.2
0.278
0.077
3.607
Exponential
Hybrid
1,1­
dichloropropanone
524.2
6.032
8.566
0.704
Exponential
Exponential
1,1­
dichloropropene
524.2
0.247
0.038
6.493
Exponential
Constant
1
1,2,3­
trichlorobenzene
502.2
ELCD
0.122
0.161
0.755
Exponential
Constant
February
2003C­
38
Appendix
C
Table
9.
Comparison
of
16­
point
and
5­
point
Single­
laboratory
IDEs
(
SL­
IDEs)
for
the
Episode
6000
Data
Set
SL­
IDE(
16)/
SL­
IDE
16
SL­
IDE
5
Analyte
Method
Procedure
SL­
IDE
(
16)
SL­
IDE
(
5)
SL­
IDE(
5)
Model
Model
1,2,3­
trichlorobenzene
502.2
PID
0.114
0.060
1.891
Exponential
Exponential
1,2,3­
trichlorobenzene
524.2
0.259
0.139
1.854
Exponential
Exponential
1,2,3­
trichloropropane
524.2
1.206
0.230
5.241
Exponential
Constant
1
1,2,4­
trichlorobenzene
502.2
ELCD
0.077
0.096
0.798
Exponential
Constant
1,2,4­
trichlorobenzene
502.2
PID
0.124
0.070
1.774
Exponential
Exponential
1,2,4­
trichlorobenzene
524.2
0.208
0.108
1.916
Exponential
Exponential
1,2,4­
trimethylbenzene
502.2
PID
0.123
0.137
0.897
Exponential
Constant
1,2,4­
trimethylbenzene
524.2
0.129
0.054
2.380
Exponential
Exponential
1,2­
dibromo­
3­
chloropropane
524.2
1.619
0.414
3.912
Exponential
Hybrid
1,2­
dibromoethane
502.2
ELCD
0.143
0.023
6.138
Exponential
Linear
1,2­
dibromoethane
524.2
0.289
0.302
0.958
Exponential
Exponential
1,2­
dichlorobenzene
502.2
ELCD
0.053
0.053
1.007
Exponential
Linear
1,2­
dichlorobenzene
502.2
PID
0.147
0.067
2.197
Exponential
Exponential
1,2­
dichlorobenzene
524.2
0.112
0.065
1.727
Exponential
Exponential
1,2­
dichloroethane
502.2
ELCD
0.037
0.018
2.054
Exponential
Exponential
1,2­
dichloroethane
524.2
0.229
0.201
1.139
Exponential
Exponential
1,2­
dichloropropane
502.2
ELCD
0.037
0.083
0.440
Exponential
Constant
1,2­
dichloropropane
524.2
0.221
0.206
1.072
Exponential
Exponential
1,3,5­
tmb+
4­
chlorotoluene
502.2
PID
0.108
0.135
0.797
Exponential
Constant
1,3,5­
trimethylbenzene
524.2
0.117
0.045
2.612
Exponential
Exponential
1,3­
dichlorobenzene
502.2
ELCD
0.100
0.590
0.169
Exponential
Constant
1,3­
dichlorobenzene
502.2
PID
0.123
0.189
0.654
Exponential
Constant
1,3­
dichlorobenzene
524.2
0.126
0.040
3.123
Exponential
Exponential
1,3­
dichloropropane
502.2
ELCD
0.045
0.218
0.204
Exponential
Constant
1,3­
dichloropropane
524.2
0.170
0.112
1.517
Exponential
Exponential
1,4­
dichlorobenzene
502.2
ELCD
0.054
0.039
1.388
Exponential
Linear
1,4­
dichlorobenzene
524.2
0.110
0.047
2.333
Exponential
Exponential
1­
chlorobutane
524.2
0.200
0.058
3.451
Exponential
Linear
2,2­
dichloropropane
524.2
0.700
0.117
5.985
Exponential
Hybrid
2­
butanone
524.2
0.775
1.261
0.615
Exponential
Exponential
2­
chlorotoluene
502.2
ELCD
0.184
0.104
1.776
Exponential
Exponential
2­
chlorotoluene
502.2
PID
0.222
0.391
0.568
Exponential
Constant
2­
chlorotoluene
524.2
0.121
0.036
3.343
Exponential
Exponential
2­
hexanone
524.2
0.815
0.782
1.042
Exponential
Exponential
2­
nitropropane
524.2
0.965
8.974
0.108
Exponential
Constant
February
2003
C­
39
Assessment
of
Detection
and
Quantitation
Approaches
Table
9.
Comparison
of
16­
point
and
5­
point
Single­
laboratory
IDEs
(
SL­
IDEs)
for
the
Episode
6000
Data
Set
SL­
IDE(
16)/
SL­
IDE
16
SL­
IDE
5
Analyte
Method
Procedure
SL­
IDE
(
16)
SL­
IDE
(
5)
SL­
IDE(
5)
Model
Model
4­
chlorotoluene
502.2
ELCD
0.159
0.138
1.153
Exponential
Linear
4­
chlorotoluene
524.2
0.102
0.039
2.648
Exponential
Exponential
4­
isopropyltoluene
524.2
0.102
0.037
2.762
Exponential
Exponential
4­
methyl­
2­
pentanone
524.2
1.060
0.987
1.074
Exponential
Exponential
Acetone
524.2
2.025
28.956
0.070
Exponential
Constant
Acrylonitrile
524.2
1.197
0.982
1.219
Exponential
Exponential
Allyl
Chloride
524.2
0.203
0.070
2.915
Exponential
Hybrid
Aluminum
1620
198.565
70.438
2.819
Constant
Constant
Aluminum
200.8
12.004
21.862
0.549
Exponential
Constant
Ammonia
as
Nitrogen
350.3
0.013
0.038
0.336
Exponential
Constant
Antimony
1620
4.087
6.023
0.678
Constant
Linear
Antimony
200.8
0.018
0.293
0.062
Exponential
Constant
Arsenic
1620
1.463
2.175
0.672
Exponential
Constant
Arsenic
200.8
0.346
0.340
1.015
Exponential
Exponential
Barium
1620
1.762
1.558
1.131
Constant
Constant
Barium
200.8
0.079
0.071
1.120
Exponential
Constant
Benzene
502.2
PID
0.077
0.058
1.324
Exponential
Exponential
Benzene
524.2
0.115
0.030
3.907
Exponential
Exponential
Beryllium
1620
0.428
0.427
1.003
Exponential
Exponential
Beryllium
200.8
0.019
0.017
1.138
Exponential
Constant
Boron
1620
19.884
21.488
0.925
Exponential
Exponential
Bromobenzene
502.2
ELCD
0.729
0.343
2.122
Linear
Exponential
Bromobenzene
502.2
PID
0.048
0.025
1.947
Exponential
Exponential
Bromobenzene
524.2
0.175
0.156
1.125
Exponential
Exponential
Bromochloromethane
502.2
ELCD
0.462
0.029
15.797
Linear
Exponential
Bromochloromethane
524.2
0.309
0.396
0.780
Exponential
Exponential
Bromodichloromethane
502.2
ELCD
0.064
0.018
3.584
Exponential
Exponential
Bromodichloromethane
524.2
0.182
0.093
1.951
Exponential
Exponential
Bromoform
502.2
ELCD
1.450
0.023
62.020
Constant
Linear
Bromoform
524.2
0.350
0.247
1.417
Exponential
Exponential
Bromomethane
502.2
ELCD
6.993
0.731
9.569
Constant
Exponential
Bromomethane
524.2
0.238
0.148
1.610
Exponential
Linear
Cadmium
1620
0.184
0.200
0.922
Exponential
Exponential
Cadmium
200.8
0.011
0.015
0.735
Exponential
Constant
Calcium
1620
39.651
51.207
0.774
Linear
Constant
February
2003C­
40
Appendix
C
Table
9.
Comparison
of
16­
point
and
5­
point
Single­
laboratory
IDEs
(
SL­
IDEs)
for
the
Episode
6000
Data
Set
SL­
IDE(
16)/
SL­
IDE
16
SL­
IDE
5
Analyte
Method
Procedure
SL­
IDE
(
16)
SL­
IDE
(
5)
SL­
IDE(
5)
Model
Model
Carbon
Disulfide
524.2
0.203
0.083
2.440
Exponential
Linear
Carbon
Tetrachloride
524.2
0.258
0.166
1.549
Exponential
Linear
Carbontet+
1,1­
dcp
502.2
ELCD
0.062
0.049
1.274
Exponential
Exponential
Chloroacetonitrile
524.2
1.535
1.842
0.833
Exponential
Exponential
Chlorobenzene
502.2
ELCD
0.440
0.044
9.900
Linear
Exponential
Chlorobenzene
502.2
PID
0.062
0.058
1.083
Exponential
Exponential
Chlorobenzene
524.2
0.119
0.035
3.378
Exponential
Exponential
Chloroethane
502.2
ELCD
2.492
0.090
27.544
Constant
Linear
Chloroethane
524.2
0.336
0.239
1.403
Exponential
Exponential
Chloroform
502.2
ELCD
0.031
0.008
3.923
Exponential
Linear
Chloroform
524.2
0.203
0.111
1.829
Exponential
Exponential
Chloromethane
502.2
ELCD
0.204
0.499
0.409
Exponential
Constant
Chloromethane
524.2
0.215
0.148
1.456
Exponential
Exponential
Chromium
1620
0.478
0.728
0.657
Exponential
Constant
Chromium
200.8
0.393
0.473
0.830
Linear
Constant
Cis­
1,2­
dce+
2,2­
dcp
502.2
ELCD
0.043
0.027
1.575
Exponential
Exponential
Cis­
1,2­
dichloroethene
524.2
0.203
0.181
1.123
Exponential
Exponential
Cis­
1,3­
dichloropropene
502.2
ELCD
0.059
0.015
3.860
Exponential
Exponential
Cis­
1,3­
dichloropropene
502.2
PID
0.077
0.104
0.743
Exponential
Exponential
Cis­
1,3­
dichloropropene
524.2
0.158
0.103
1.536
Exponential
Exponential
Cobalt
1620
15.560
11.825
1.316
Exponential
Exponential
Cobalt
200.8
0.008
0.000
­
133.113
Exponential
Exponential
Copper
1620
20.328
15.251
1.333
Constant
Constant
Copper
200.8
0.770
0.873
0.882
Constant
Constant
Dibromochloromethane
502.2
ELCD
0.418
0.380
1.098
Linear
Constant
Dibromochloromethane
524.2
0.253
0.192
1.315
Exponential
Exponential
Dibromomethane
502.2
ELCD
0.441
0.286
1.543
Linear
Constant
Dibromomethane
524.2
0.342
0.347
0.985
Exponential
Exponential
Dichlorodifluoromethane
502.2
ELCD
0.087
1.175
0.074
Exponential
Constant
Dichlorodifluoromethane
524.2
0.420
0.265
1.584
Exponential
Exponential
Diethyl
Ether
524.2
0.340
0.314
1.082
Exponential
Exponential
Ethyl
Methacrylate
524.2
0.244
0.243
1.003
Exponential
Exponential
Ethylbenzene
502.2
PID
0.075
0.048
1.571
Exponential
Exponential
Ethylbenzene
524.2
0.167
0.111
1.504
Exponential
Exponential
Hardness
130.2
2.152
4.687
0.459
Exponential
Constant
February
2003
C­
41
Assessment
of
Detection
and
Quantitation
Approaches
Table
9.
Comparison
of
16­
point
and
5­
point
Single­
laboratory
IDEs
(
SL­
IDEs)
for
the
Episode
6000
Data
Set
SL­
IDE(
16)/
SL­
IDE
16
SL­
IDE
5
Analyte
Method
Procedure
SL­
IDE
(
16)
SL­
IDE
(
5)
SL­
IDE(
5)
Model
Model
Hexachlorobutadiene
502.2
ELCD
0.090
0.069
1.300
Exponential
Linear
Hexachlorobutadiene
524.2
0.263
0.208
1.265
Exponential
Exponential
Hexachloroethane
524.2
0.234
0.234
1.000
Exponential
Exponential
Hexchlobutadiene+
naphthalene
502.2
PID
0.598
0.567
1.055
Exponential
Constant
Iron
1620
345.686
1021.716
0.338
Linear
Constant
Isopropylbenzene
502.2
PID
0.059
0.038
1.551
Exponential
Exponential
Isopropylbenzene
524.2
0.113
0.036
3.137
Exponential
Exponential
Lead
1620
2.317
2.831
0.819
Exponential
Constant
Lead
200.8
0.197
2.771
0.071
Exponential
Constant
M+
p
Xylene
502.2
PID
0.116
0.114
1.014
Exponential
Constant
M+
p
Xylene
524.2
0.127
0.033
3.846
Exponential
Exponential
Magnesium
1620
99.662
176.736
0.564
Exponential
Constant
Manganese
1620
6.531
4.363
1.497
Constant
Constant
Manganese
200.8
0.106
0.074
1.419
Constant
Constant
Mercury
200.8
0.062
0.014
4.550
Exponential
Hybrid
Methacrylonitrile
524.2
0.643
0.529
1.216
Exponential
Hybrid
Methyl
Iodide
524.2
0.173
0.099
1.746
Exponential
Exponential
Methyl
Tert­
butyl
Ether
524.2
0.195
0.154
1.266
Exponential
Exponential
Methylacrylate
524.2
0.549
0.551
0.995
Exponential
Exponential
Methylene
Chloride
502.2
ELCD
2.727
­
1.325
­
2.057
Constant
Constant
Methylene
Chloride
524.2
0.276
0.159
1.737
Exponential
Exponential
Methylmethacrylate
524.2
0.484
0.366
1.322
Exponential
Linear
Molybdenum
1620
2.917
5.783
0.504
Exponential
Constant
Molybdenum
200.8
0.262
0.005
47.826
Constant
Constant
N­
butylbenzene
502.2
PID
0.139
0.049
2.819
Exponential
Linear
N­
butylbenzene
524.2
0.136
0.052
2.605
Exponential
Exponential
N­
propylbenzene
502.2
PID
0.089
0.100
0.889
Exponential
Constant
N­
propylbenzene
524.2
0.231
0.050
4.596
Exponential
Hybrid
Naphthalene
524.2
0.175
0.180
0.968
Exponential
Exponential
Nickel
1620
23.784
40.205
0.592
Exponential
Constant
Nickel
200.8
0.076
0.068
1.124
Exponential
Constant
o­
xylene
524.2
0.161
0.084
1.925
Exponential
Exponential
o­
xylene+
styrene
502.2
PID
0.111
0.145
0.769
Exponential
Constant
P­
isoproptol+
1,4­
dcb
502.2
PID
0.153
0.143
1.068
Exponential
Constant
Pentachloroethane
524.2
0.337
0.419
0.805
Exponential
Linear
C­
42
February
2003
Appendix
C
Table
9.
Comparison
of
16­
point
and
5­
point
Single­
laboratory
IDEs
(
SL­
IDEs)
for
the
Episode
6000
Data
Set
SL­
IDE(
16)/
SL­
IDE
16
SL­
IDE
5
Analyte
Method
Procedure
SL­
IDE
(
16)
SL­
IDE
(
5)
SL­
IDE(
5)
Model
Model
Sec­
butylbenzene
502.2
PID
0.079
0.053
1.504
Exponential
Exponential
Sec­
butylbenzene
524.2
0.132
0.038
3.422
Exponential
Exponential
Selenium
1620
1.915
1.757
1.090
Exponential
Exponential
Selenium
200.8
0.410
0.311
1.317
Exponential
Exponential
Silver
1620
10.219
11.118
0.919
Exponential
Constant
Silver
200.8
0.010
­
0.030
­
0.348
Exponential
Exponential
Sodium
1620
133.007
134.645
0.988
Exponential
Exponential
Styrene
524.2
0.119
0.045
2.676
Exponential
Exponential
Tert­
butylbenzene
502.2
PID
0.073
0.049
1.498
Exponential
Exponential
Tert­
butylbenzene
524.2
0.170
0.055
3.093
Exponential
Exponential
Tetrachloroethene
502.2
ELCD
0.051
0.045
1.119
Exponential
Exponential
Tetrachloroethene
502.2
PID
0.157
0.097
1.607
Exponential
Linear
Tetrachloroethene
524.2
0.379
0.526
0.721
Exponential
Linear
Thallium
1620
1.208
1.198
1.009
Exponential
Linear
Thallium
200.8
0.001
0.000
3.140
Exponential
Exponential
Thorium
200.8
0.003
0.000
7.428
Exponential
Constant
Tin
1620
1.200
4.383
0.274
Exponential
Exponential
Titanium
1620
5.238
19.982
0.262
Exponential
Constant
Toluene
502.2
PID
0.061
0.061
0.999
Exponential
Constant
Toluene
524.2
0.130
0.142
0.918
Exponential
Constant
1
Total
Phosphorus
365.2
0.013
0.011
1.219
Exponential
Exponential
Total
Suspended
Solids
160.2
2.877
2.131
1.350
Exponential
Exponential
Trans­
1,2­
dichloroethene
502.2
ELCD
0.065
0.061
1.069
Exponential
Linear
Trans­
1,2­
dichloroethene
524.2
0.255
0.072
3.531
Exponential
Hybrid
Trans­
1,3­
dichloropropene
502.2
ELCD
0.082
0.021
3.845
Exponential
Exponential
Trans­
1,3­
dichloropropene
502.2
PID
0.085
0.110
0.774
Exponential
Exponential
Trans­
1,3­
dichloropropene
524.2
0.204
0.127
1.613
Exponential
Exponential
Trans­
1,4­
dichloro­
2­
butene
524.2
1.182
1.205
0.981
Exponential
Exponential
Trichloroethene
502.2
ELCD
0.050
0.013
Trichloroethene
502.2
PID
0.096
0.080
Trichloroethene
524.2
0.288
0.329
Trichlorofluoromethane
502.2
ELCD
1.997
0.660
Trichlorofluoromethane
524.2
0.307
0.290
Uranium
200.8
0.001
0.000
Vanadium
1620
10.063
8.643
3.715
Exponential
Exponential
1.189
Exponential
Exponential
0.875
Exponential
Linear
3.025
Constant
Constant
1.059
Exponential
Exponential
4.743
Exponential
Exponential
1.164
Exponential
Exponential
February
2003
C­
43
Assessment
of
Detection
and
Quantitation
Approaches
Table
9.
Comparison
of
16­
point
and
5­
point
Single­
laboratory
IDEs
(
SL­
IDEs)
for
the
Episode
6000
Data
Set
SL­
IDE(
16)/
SL­
IDE
16
SL­
IDE
5
Analyte
Method
Procedure
SL­
IDE
(
16)
SL­
IDE
(
5)
SL­
IDE(
5)
Model
Model
Vanadium
200.8
0.845
0.987
0.856
Exponential
Linear
Vinyl
Chloride
502.2
ELCD
3.521
0.369
9.543
Constant
Linear
Vinyl
Chloride
524.2
0.295
0.180
1.641
Exponential
Linear
WAD
Cyanide
1677
0.672
1.243
0.541
Linear
Constant
Xylene
(
Total)
524.2
0.111
0.030
3.735
Exponential
Exponential
Yttrium
1620
3.119
13.404
0.233
Exponential
Constant
Zinc
1620
4.415
6.661
0.663
Exponential
Constant
Zinc
200.8
1.497
5.061
0.296
Exponential
Constant
Note:
ELCD
or
PID
in
the
Procedure
column
indicates
the
photo­
ionization
detector
(
PID)
or
electrolytic
conductivity
detector
(
ELCD)
in
EPA
Method
502.2
1
Original
model
picked
was
Hybrid,
but
failed
to
converge
Summary
Statistics
for
Table
9
IDE(
16)/
IDE(
5)
(
all
analytes)
IDE(
16)/
IDE(
5)
(
same
model
used)
IDE(
16)/
IDE(
5)
(
different
models
used)

Number
of
Analytes
198
108
90
Minimum:
­
133.113
­
133.113
0.050
25th
percentile:
0.876
1.072
0.564
Median:
1.270
1.419
0.919
75th
percentile:
2.328
2.310
2.122
Maximum:
62.020
47.826
62.020
Number
of
analytes
Percent
of
analytes
p­
value
(
for
percent=
50)

SL­
IDE
(
16)
>
SL­
IDE
(
5)
(
all
analytes)
133
67.17%
<
0.0001
SL­
IDE
(
16)
>
SL­
IDE
(
5)
(
same
model
used)
91
84.26%
<
00001
SL­
IDE
(
16)
>
SL­
IDE
(
5)
(
different
models
used)
43
48.31%
0.832
C­
44
February
2003
