ASTM D6620-06(2010)
(Practice)Standard Practice for Asbestos Detection Limit Based on Counts
Standard Practice for Asbestos Detection Limit Based on Counts
SIGNIFICANCE AND USE
The DL concept addresses potential measurement interpretation errors. It is used to control the likelihood of reporting a positive finding of asbestos when the measured asbestos level cannot clearly be differentiated from the background contamination level. Specifically, a measurement is reported as being “below the DL” if the measured level is not statistically different than the background level.
The DL, along with other measurement characteristics such as bias and precision, is used when selecting a measurement method for a particular application. The DL should be established either at the method development stage or prior to a specific application of the method. The method developer subsequently would advertise the method as having a certain DL. An analyst planning to collect and analyze samples would, if alternative measurement methods were available, want to select a measurement method with a DL that was appropriate for the intended application. The most important use of the DL, therefore, takes place at the planning stage of a study, before samples are collected and analyzed.
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.
1.4 The values stated in SI units are to be regarded as standard. No other units of measurement are included in this standard.
1.5 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety and health practices and determine the applicability of regulatory limitations prior to use.
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Designation: D6620 − 06 (Reapproved 2010)
Standard Practice for
Asbestos Detection Limit Based on Counts
This standard is issued under the fixed designation D6620; the number immediately following the designation indicates the year of
original adoption or, in the case of revision, the year of last revision.Anumber in parentheses indicates the year of last reapproval.A
superscript epsilon (´) indicates an editorial change since the last revision or reapproval.
1. Scope for Asbestos Structure Number Surface Loading
D6281Test Method forAirborneAsbestos Concentration in
1.1 This practice presents the procedure for determining the
2 3 Ambient and Indoor Atmospheres as Determined by
detection limit (DL) for measurements of fibers or structures
TransmissionElectronMicroscopyDirectTransfer(TEM)
using microscopy methods.
D6480TestMethodforWipeSamplingofSurfaces,Indirect
1.2 This practice applies to samples of air that are analyzed
Preparation, and Analysis for Asbestos Structure Number
either by phase contrast microscopy (PCM) or transmission
Surface Loading by Transmission Electron Microscopy
electron microscopy (TEM), and samples of dust that are
E456Terminology Relating to Quality and Statistics
analyzed by TEM.
3. Terminology
1.3 The microscopy methods entail counting asbestos struc-
3.1 Definitions of Terms Specific to This Standard:
tures and reporting the results as structures per cubic centime-
3.1.1 average,n—thesumofasetofmeasurements(counts)
ter of air (str/cc) or fibers per cubic centimeter of air (f/cc) for
divided by the number of measurements in the set.
airsamplesandstructurespersquarecentimeterofsurfacearea
3.1.1.1 Discussion—The average is distinguished from the
(str/cm ) for dust samples.
mean. The average is calculated from data and serves as an
1.4 The values stated in SI units are to be regarded as
estimate of the mean. The mean (also referred to as the
standard. No other units of measurement are included in this
population mean, expected value,or first moment) is a param-
standard.
eter of the underlying statistical distribution of counts.
1.5 This standard does not purport to address all of the
3.1.2 background, n—a statistical distribution of structures
safety concerns, if any, associated with its use. It is the
introducedby(i)analystcountingerrorsand(ii)contamination
responsibility of the user of this standard to establish appro-
on an unused filter or contamination as a consequence of the
priate safety and health practices and determine the applica-
sample collection and sample preparation steps.
bility of regulatory limitations prior to use.
3.1.2.1 Discussion—This definition of background is spe-
cific to this practice. The only counting errors considered in
2. Referenced Documents
this definition of background are errors that result in an
2.1 ASTM Standards:
over-count(thatis,falsepositives).Analystcountingerrorsare
D1356Terminology Relating to Sampling and Analysis of
errors such as, determining the length of structures or fibers
Atmospheres
andwhether,basedonlength,theyshouldbecounted;counting
D5755TestMethodforMicrovacuumSamplingandIndirect
artifacts as fibers; determining the number of structures pro-
Analysis of Dust by Transmission Electron Microscopy
trudingfromamatrix;andinterpretingaclusterasone,two,or
more structures that should be counted only as zero or one
structure. For purposes of developing the DL, assume that
ThispracticeisunderthejurisdictionofASTMCommitteeD22onAirQuality
background contamination sources have been reduced to their
and is the direct responsibility of Subcommittee D22.07 on Sampling andAnalysis
of Asbestos. lowest achievable levels.
Current edition approved Oct. 1, 2010. Published November 2010. Originally
3.1.3 blank, n—a filter that has not been used to collect
approved in 2000. Last previous edition approved 2006 as D6620–06. DOI:
asbestos from the target environment.
10.1520/D6620-06R10.
The DL also is referred to in the scientific literature as Limit of Detection
3.1.3.1 Discussion—Blanks are used in this practice to
(LOD), Method Detection Limit (MDL), and other similar descriptive names.
determinethedegreeofasbestoscontaminationthatisreflected
For purposes of general exposition, the term “structures” will be used in place
inasbestosmeasurements.Contaminationmaybeonthevirgin
of “fibers or structures.” In the examples in Section 8, the specific term, “fiber” or
filter or introduced in handling the filter in the field or when
“structure,”isusedwhereappropriate.ThesetermsaredefinedseparatelyinSection
3.
preparing it for inspection with a microscope. The data
For referenced ASTM standards, visit the ASTM website, www.astm.org, or
required to determine the degree of contamination consists,
contact ASTM Customer Service at service@astm.org. For Annual Book of ASTM
therefore, of measurements of field blanks that have experi-
Standards volume information, refer to the standard’s Document Summary page on
the ASTM website. enced the full preparation process.
Copyright © ASTM International, 100 Barr Harbor Drive, PO Box C700, West Conshohocken, PA 19428-2959. United States
D6620 − 06 (2010)
3.1.4 count, n—the number of fibers or structures identified a distinct subsample,” or a distinct sample obtained from the
in a sample. same population as the initial sample. For this practice,
“identical” means distinct sample obtained from the same
3.1.5 decision value, n—a numerical value used as a bound-
population as the initial sample.
ary in a statistical test to decide between the null hypothesis
and the alternative hypothesis. 3.1.11 sample, n—the segment of the filter that is inspected,
3.1.5.1 Discussion—In the present context, the decision andthereby,embodiestheairordustthatwascollectedandthe
subset of structures that were captured on the portion of the
value is a structure count that defines the boundary between
“below detection” (the null hypothesis) and “detection” (the filter subjected to microscopic inspection (also, see Terminol-
ogy D1356).
alternativehypothesis).Ifastructurecountwerelargerthanthe
decision value, then one would conclude that detection has
3.1.12 sensitivity, n—the structure concentration corre-
been achieved (that is, the sample is from a distribution other
sponding to a count of one structure in the sample.
thanthebackgrounddistribution).Ifthecountwerelessthanor
3.1.13 structure, n—any of various discrete entities counted
equal to the decision value, the result would be reported as
by a particular method that specifies shape, length, width, and
“below detection,” which means that the sample cannot be
aspect ratio.
differentiated from a sample that would have been collected
3.1.14 type I error, n—choosing, based on a statistical test,
from the background distribution.
the alternative hypothesis over the null hypothesis when the
3.1.6 detection limit—the mean of a structure count popu-
null hypothesis is, in fact, true; a false positive outcome of a
lation that is sufficiently large so a measurement from this
statistical test.
populationwouldhaveahighprobability(forexample,0.95or
3.1.14.1 Discussion—AtypeIerrorwouldoccurifthecount
larger) of exceeding the decision value that determines detec-
for a sample exceeded the decision value, but the sample was,
tion.
in fact, obtained from the background population. The analyst
3.1.6.1 Discussion—The DLis the value of a parameter, the
erroneously would be led by the statistical test to report a
true mean of a structure count population in the statistical
structure concentration (that is, choose the alternative hypoth-
hypothesis testing problem, that underlies the DL concept.
esis of the statistical test), where the result should be reported
Specifically, it is the true mean of the alternative hypothesis
as “below the detection limit” (that is, the null hypothesis of
thatensuresasufficientlyhighpowerforthestatisticaltestthat
the statistical test is true).
determines detection.
3.1.15 type II error, n—choosing, based on a statistical test,
3.1.7 fiber, n—any of various discrete entities with essen-
the null hypothesis over the alternative hypothesis when the
tially parallel sides counted by a particular method that
alternativehypothesisis,infact,true;afalsenegativeoutcome
specifies length, width, and aspect ratio.
of a statistical test.
3.1.7.1 Discussion—The definitions of “fiber” and “struc-
3.1.15.1 Discussion—A type II error would occur if the
ture” are similar because the measurement method employed
count for a sample does not exceed the decision value, but the
specifies the shape, length, width, and aspect ratio.
sample was, in fact, obtained from a population other than the
3.1.8 mean, n—the mean value of the number of structures
background population. The analyst would erroneously be led
in the population of air or dust sampled.
by the statistical test to report a “below the detection limit”
3.1.8.1 Discussion—The mean in this definition is intended
result (that is, choose the null hypothesis of the statistical test),
to be the population mean, expected value, or first moment of
wheretheresultshouldbereportedasastructureconcentration
a statistical distribution. It is a theoretical parameter of the
(that is, the alternative hypothesis of the statistical test is true).
distribution that may be estimated by forming an average of
3.1.16 type I error rate, n—the probability of a type I error
measurements (refer to Terminology E456 for definition of
(also referred to as the significance level,α-level,or p-value of
population).
the statistical test).
3.1.9 power, n—the probability that a count exceeds the
3.1.17 type II error rate, n—theprobabilityofatypeIIerror
decision value for a sample that was obtained from a popula-
(also referred to as the β-level of the statistical test).
tion other than the background population.
3.1.18 λ—lambda, the Greek letter used to represent the
3.1.9.1 Discussion—Power is the probability of selecting,
population mean of a Poisson distribution.
based on a statistical test, the alternative hypothesis when it is
3.1.19 λ —the population mean of the Poisson distribution
true. In the present context, this means the probability of 0
of background counts.
making the correct decision to report a structure concentration
3.1.19.1 Discussion—λ is the population mean of the
forasamplethatwascollectedfromapopulationotherthanthe 0
Poisson distribution under the null hypothesis in the statistical
background population.The power of the statistical test equals
hypothesis testing problem that defines the DL.
1 minus the type II error rate.
3.1.20 λ —the population mean of the Poisson distribution
3.1.10 replicate, n—a second measurement is a replicate of 1
under the alternative hypothesis in the statistical hypothesis
the initial measurement if the second measurement is obtained
testing problem that defines the DL (DL = λ ).
from an identical sample and under identical conditions as the 1
initial measurement. 3.1.21 x —decision value for determining detection. If the
3.1.10.1 Discussion—“Identical,” as applied to sample, can countinameasurementisnotgreaterthan x ,themeasurement
mean“ same subsample preparation,” “separate preparation of is reported as “below detection.”
D6620 − 06 (2010)
3.1.22 X—Poisson distributed random variable used to de- 5.1.3 The sources of false positives for asbestos counts are
note the number of structures (fibers) counted in a sample. (i) analyst errors (for example, determining the length of
structures or fibers and whether, based on length, they should
3.1.23 A—the area of the filter inspected to obtain a struc-
be counted; counting artifacts as fibers; determining the num-
ture count.
ber of structures protruding from a matrix; interpreting a
3.1.24 P(X>x/λ, A)—the Poisson probability of a structure
cluster as one, two, or more structures that should be counted
countexceedingxstructures(fibers)whenthepopulationmean
only as zero or one), and (ii) contamination (for example,
is equal to λ and an area, A, of the filter is inspected.
virgin filter contamination or contamination introduced during
sample collection or sample preparation). Collectively, these
4. Significance and Use
sources are referred to subsequently as “background.” For
4.1 The DLconcept addresses potential measurement inter-
purposes of developing the DL, assume that each background
pretationerrors.Itisusedtocontrolthelikelihoodofreporting
source has been reduced to its lowest achievable level.
apositivefindingofasbestoswhenthemeasuredasbestoslevel
5.2 DL—General Discussion:
cannot clearly be differentiated from the background contami-
5.2.1 DLs often have been misspecified and misinterpreted
nation level. Specifically, a measurement is reported as being
because the DL concept has not been defined with sufficient
“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
concludingbasedononeormoremeasurementsfromasample
DL.Ananalystplanningtocollectandanalyzesampleswould,
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
level.
5. Descriptive Terms and Procedures
5.2.2 Determining whether the mean concentration of a
5.1 Introduction:
substance in a sample is consistent with the background
5.1.1 The DL is one of a number of characteristics used to
concentration or is greater than the background concentration
describe the expected performance of a mea
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