ASTM D6620-00
(Practice)Standard Practice for Asbestos Detection Limit Based on Counts
Standard Practice for Asbestos Detection Limit Based on Counts
SCOPE
1.1 This practice presents the procedure for determining the detection limit (DL) for measurements of fibers or structures using microscopy methods.
1.2 This practice applies to samples of air that are analyzed either by phase contrast microscopy (PCM) or transmission electron microscopy (TEM), and samples of dust that are analyzed by TEM.
1.3 The microscopy methods entail counting asbestos structures and reporting the results as structures per cubic centimeter of air (str/cc) or fibers per cubic centimeter of air (f/cc) for air samples and structures per square centimeter of surface area (str/cm2) for dust samples.
General Information
Relations
Standards Content (Sample)
NOTICE: This standard has either been superseded and replaced by a new version or withdrawn.
Contact ASTM International (www.astm.org) for the latest information
Designation: D 6620 – 00
Standard Practice for
Asbestos Detection Limit Based on Counts
This standard is issued under the fixed designation D 6620; the number immediately following the designation indicates the year of
original adoption or, in the case of revision, the year of last revision. A number in parentheses indicates the year of last reapproval. A
superscript epsilon (e) indicates an editorial change since the last revision or reapproval.
1. Scope 3.1.1 average, n—the sum of a set of measurements
(counts) divided by the number of measurements in the set.
1.1 This practice presents the procedure for determining the
2 3
3.1.1.1 Discussion—The average is distinguished from the
detection limit (DL) for measurements of fibers or structures
mean. The average is calculated from data and serves as an
using microscopy methods.
estimate of the mean. The mean (also referred to as the
1.2 This practice applies to samples of air that are analyzed
population mean, expected value,or first moment) is a param-
either by phase contrast microscopy (PCM) or transmission
eter of the underlying statistical distribution of counts.
electron microscopy (TEM), and samples of dust that are
3.1.2 background, n—a statistical distribution of structures
analyzed by TEM.
introduced by (i) analyst counting errors and (ii) contamination
1.3 The microscopy methods entail counting asbestos struc-
on an unused filter or contamination as a consequence of the
tures and reporting the results as structures per cubic centime-
sample collection and sample preparation steps.
ter of air (str/cc) or fibers per cubic centimeter of air (f/cc) for
3.1.2.1 Discussion—This definition of background is spe-
airsamplesandstructurespersquarecentimeterofsurfacearea
cific to this practice. The only counting errors considered in
(str/cm ) for dust samples.
this definition of background are errors that result in an
2. Referenced Documents
over-count (that is, false positives).Analyst counting errors are
errors such as, determining the length of structures or fibers
2.1 ASTM Standards:
andwhether,basedonlength,theyshouldbecounted;counting
D 1356 Terminology Relating to Sampling and Analysis of
artifacts as fibers; determining the number of structures pro-
Atmospheres
truding from a matrix; and interpreting a cluster as one, two, or
D 5755 Test Method for Microvacuum Sampling and Indi-
more structures that should be counted only as zero or one
rect Analysis of Dust by Transmission Electron Micros-
structure. For purposes of developing the DL, assume that
copy for Asbestos Structure Number Concentrations
background contamination sources have been reduced to their
D 6281 Test Method for Airborne Asbestos Concentration
lowest achievable levels.
in Ambient and Indoor Atmospheres as Determined by
3.1.3 blank, n—a filter that has not been used to collect
Transmission Electron Microscopy Direct Transfer (TEM)
asbestos from the target environment.
D 6480 Test Method for Wipe Sampling of Surfaces, Indi-
3.1.3.1 Discussion—Blanks are used in this practice to
rect Preparation, andAnalysis ofAsbestos Structure Num-
determinethedegreeofasbestoscontaminationthatisreflected
ber Concentration by Transmission Electron Microscopy
in asbestos measurements. Contamination may be on the virgin
E 456 Terminology for Relating to Quality and Statistics
filter or introduced in handling the filter in the field or when
3. Terminology
preparing it for inspection with a microscope. The data
required to determine the degree of contamination consists,
3.1 Definitions of Terms Specific to This Standard:
therefore, of measurements of field blanks that have experi-
enced the full preparation process.
This practice is under the jurisdiction ofASTM Committee D22 onAir Quality
3.1.4 decision value, n—a numerical value used as a bound-
and is the direct responsibility of Subcommittee D22.07 on Sampling and Analysis
ary in a statistical test to decide between the null hypothesis
of Asbestos.
and the alternative hypothesis.
Current edition approved December 10, 2000. Published March 2001.
The DL also is referred to in the scientific literature as Limit of Detection 3.1.4.1 Discussion—In the present context, the decision
(LOD), Method Detection Limit (MDL), and other similar descriptive names.
value is a structure count that defines the boundary between
For purposes of general exposition, the term “structures” will be used in place
“below detection” (the null hypothesis) and “detection” (the
of “fibers or structures.” In the examples in Section 8, the specific term, “fiber” or
alternativehypothesis).Ifastructurecountwerelargerthanthe
“structure,” is used where appropriate.These terms are defined separately in Section
3.
decision value, then one would conclude that detection has
For referenced ASTM standards, visit the ASTM website, www.astm.org, or
been achieved (that is, the sample is from a distribution other
contact ASTM Customer Service at service@astm.org. For Annual Book of ASTM
thanthebackgrounddistribution).Ifthecountwerelessthanor
Standards volume information, refer to the standard’s Document Summary page on
equal to the decision value, the result would be reported as
the ASTM website.
Copyright © ASTM International, 100 Barr Harbor Drive, PO Box C700, West Conshohocken, PA 19428-2959, United States.
D6620–00
“below detection,” which means that the sample cannot be 3.1.13 structure, n—any of various discrete entities counted
differentiated from a sample that would have been collected by a particular method that specifies shape, length, width, and
from the background distribution. aspect ratio.
3.1.14 type I error, n—choosing, based on a statistical test,
3.1.5 detection limit—the mean of a structure count popu-
the alternative hypothesis over the null hypothesis when the
lation that is sufficiently large so a measurement from this
null hypothesis is, in fact, true; a false positive outcome of a
population would have a high probability (for example, 0.95 or
statistical test.
larger) of exceeding the decision value that determines detec-
3.1.14.1 Discussion—A type I error would occur if the
tion.
count for a sample exceeded the decision value, but the sample
3.1.5.1 Discussion—The DLis the value of a parameter, the
was, in fact, obtained from the background population. The
true mean of a structure count population in the statistical
analyst erroneously would be led by the statistical test to report
hypothesis testing problem, that underlies the DL concept.
a structure concentration (that is, choose the alternative hy-
Specifically, it is the true mean of the alternative hypothesis
pothesis of the statistical test), where the result should be
that ensures a sufficiently high power for the statistical test that
reported as “below the detection limit” (that is, the null
determines detection.
hypothesis of the statistical test is true).
3.1.6 count, n—the number of fibers or structures identified
3.1.15 type II error, n—choosing, based on a statistical test,
in a sample.
the null hypothesis over the alternative hypothesis when the
3.1.7 fiber, n—any of various discrete entities with essen-
alternative hypothesis is, in fact, true; a false negative outcome
tially parallel sides counted by a particular method that
of a statistical test.
specifies length, width, and aspect ratio.
3.1.15.1 Discussion—A type II error would occur if the
3.1.7.1 Discussion—The definitions of “fiber” and “struc-
count for a sample does not exceed the decision value, but the
ture” are similar because the measurement method employed
sample was, in fact, obtained from a population other than the
specifies the shape, length, width, and aspect ratio.
background population. The analyst would erroneously be led
3.1.8 mean, n—the mean value of the number of structures
by the statistical test to report a “below the detection limit”
in the population of air or dust sampled.
result (that is, choose the null hypothesis of the statistical test),
3.1.8.1 Discussion—The mean in this definition is intended where the result should be reported as a structure concentration
to be the population mean, expected value, or first moment of
(that is, the alternative hypothesis of the statistical test is true).
a statistical distribution. It is a theoretical parameter of the 3.1.16 type I error rate, n—the probability of a type I error
distribution that may be estimated by forming an average of
(also referred to as the significance level, a-level,or p-value of
measurements (refer to Terminology E 456 for definition of the statistical test).
population).
3.1.17 typeIIerrorrate,n—theprobabilityofatypeIIerror
(also referred to as the b-level of the statistical test).
3.1.9 power, n—the probability that a count exceeds the
3.1.18 l—lambda, the Greek letter used to represent the
decision value for a sample that was obtained from a popula-
population mean of a Poisson distribution.
tion other than the background population.
3.1.19 l —the population mean of the Poisson distribution
3.1.9.1 Discussion—Power is the probability of selecting, 0
of background counts.
based on a statistical test, the alternative hypothesis when it is
3.1.19.1 Discussion—l is the population mean of the
true. In the present context, this means the probability of 0
Poisson distribution under the null hypothesis in the statistical
making the correct decision to report a structure concentration
hypothesis testing problem that defines the DL.
forasamplethatwascollectedfromapopulationotherthanthe
3.1.20 l —the population mean of the Poisson distribution
background population. The power of the statistical test equals
under the alternative hypothesis in the statistical hypothesis
1 minus the type II error rate.
testing problem that defines the DL (DL = l ).
3.1.10 replicate, n—a second measurement is a replicate of
3.1.21 x —decision value for determining detection. If the
the initial measurement if the second measurement is obtained
countinameasurementisnotgreaterthan x ,themeasurement
from an identical sample and under identical conditions as the
is reported as “below detection.”
initial measurement.
3.1.22 X—a Poisson distributed random variable used to
3.1.10.1 Discussion—“Identical,” as applied to sample, can
denote the number of structures (fibers) counted in a sample.
mean“ same subsample preparation,” “separate preparation of
3.1.23 A—the area of the filter inspected to obtain a
a distinct subsample,” or a distinct sample obtained from the
structure count.
same population as the initial sample. For this practice,
3.1.24 P(X>x/l,A)—the Poisson probability of a structure
“identical” means distinct sample obtained from the same
countexceedingxstructures(fibers)whenthepopulationmean
population as the initial sample.
is equal to l and an area, A, of the filter is inspected.
3.1.11 sample, n—the segment of the filter that is inspected,
4. Significance and Use
and thereby, embodies the air or dust that was collected and the
subset of structures that were captured on the portion of the
4.1 The DL concept addresses potential measurement inter-
filter subjected to microscopic inspection (also, see Terminol-
pretation errors. It is used to control the likelihood of reporting
ogy D 1356).
apositivefindingofasbestoswhenthemeasuredasbestoslevel
3.1.12 sensitivity, n—the structure concentration corre- cannot clearly be differentiated from the background contami-
sponding to a count of one structure in the sample. nation level. Specifically, a measurement is reported as being
D6620–00
“below the DL” if the measured level is not statistically clarity for translation into operational terms; however, the DL
different than the background level. concept and operational implementation have been presented
4.2 The DL, along with other measurement characteristics
correctly in the scientific literature by a number of authors.
such as bias and precision, is used when selecting a measure-
These authors describe the DL as a theoretical value, specifi-
ment method for a particular application. The DL should be
cally the true mean concentration of a substance in a sampled
established either at the method development stage or prior to
medium. This true mean, the DL, must be large enough to
a specific application of the method. The method developer
ensure a high probability (for example, 0.95 or larger) of
subsequently would advertise the method as having a certain
concluding based on one or more measurements from a sample
DL.An analyst planning to collect and analyze samples would,
of the medium that the true concentration in the medium is, in
if alternative measurement methods were available, want to
fact, greater than zero or greater than an appropriately defined
select a measurement method with a DL that was appropriate
background level. The DL, therefore, is a parameter in the
for the intended application. The most important use of the
statistical decision that determines whether the concentration
DL, therefore, takes place at the planning stage of a study,
of a substance in a sample is consistent with the background
before samples are collected and analyzed.
level, which may be zero, or is greater than the background
5. Descriptive Terms and Procedures
level.
5.1 Introduction:
5.2.2 Determining whether the mean concentration of a
5.1.1 The DL is one of a number of characteristics used to
substance in a sample is consistent with the background
describe the expected performance of a measurement method.
concentration or is greater than the background concentration
The DL concept addresses certain potential measurement
is a statistical decision problem. Due to statistical variation,
interpretation errors. Specifically, a measurement is reported as
replicate measurements of a sample or measurements from
being “below the DL” if the measured level cannot be
replicate samples do not yield identical results; thus, a mea-
distinguished from zero or from the randomly varying back-
surement may exceed the true background mean level even if
groundcontaminationlevel.Stateddifferently,theDLprovides
the sample were collected from the background distribution.
protection against a false positive finding. When a measured
Differences in replicate results are characterized as statistical
value is less than an appropriately specified decision value, the
variation. Values of replicate measurements are described by a
analyst is instructed to disregard the measured value and report
probability distribution. The decision concerning whether or
the result only as “below the DL.”
not a measurement is consistent with the background concen-
5.1.2 TheDLconceptforasbestosmeasurements,whichare
tration fits the standard hypothesis testing framework in
based on microscopy, is simpler than the D
...
Questions, Comments and Discussion
Ask us and Technical Secretary will try to provide an answer. You can facilitate discussion about the standard in here.