# ASTM D6620-06 (Reapproved 2010)

Designation: D6620 − 06 (Reapproved 2010)Standard Practice forAsbestos Detection Limit Based on Counts1This standard is issued under the fixed designation D6620; the number immediately following the designation indicates the year oforiginal adoption or, in the case of revision, the year of last revision. A number in parentheses indicates the year of last reapproval. Asuperscript epsilon (´) indicates an editorial change since the last revision or reapproval.1. Scope1.1 This practice presents the procedure for determining thedetection limit (DL)2for measurements of fibers or structures3using microscopy methods.1.2 This practice applies to samples of air that are analyzedeither by phase contrast microscopy (PCM) or transmissionelectron microscopy (TEM), and samples of dust that areanalyzed by TEM.1.3 The microscopy methods entail counting asbestos struc-tures and reporting the results as structures per cubic centime-ter of air (str/cc) or fibers per cubic centimeter of air (f/cc) forair 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 asstandard. No other units of measurement are included in thisstandard.1.5 This standard does not purport to address all of thesafety concerns, if any, associated with its use. It is theresponsibility of the user of this standard to establish appro-priate safety and health practices and determine the applica-bility of regulatory limitations prior to use.2. Referenced Documents2.1 ASTM Standards:4D1356 Terminology Relating to Sampling and Analysis ofAtmospheresD5755 Test Method for Microvacuum Sampling and IndirectAnalysis of Dust by Transmission Electron Microscopyfor Asbestos Structure Number Surface LoadingD6281 Test Method for Airborne Asbestos Concentration inAmbient and Indoor Atmospheres as Determined byTransmission Electron Microscopy Direct Transfer (TEM)D6480 Test Method for Wipe Sampling of Surfaces, IndirectPreparation, and Analysis for Asbestos Structure NumberSurface Loading by Transmission Electron MicroscopyE456 Terminology Relating to Quality and Statistics3. Terminology3.1 Definitions of Terms Specific to This Standard:3.1.1 average, n—the sum of a set of measurements (counts)divided by the number of measurements in the set.3.1.1.1 Discussion—The average is distinguished from themean. The average is calculated from data and serves as anestimate of the mean. The mean (also referred to as thepopulation mean, expected value,orfirst moment) is a param-eter of the underlying statistical distribution of counts.3.1.2 background, n—a statistical distribution of structuresintroduced by (i) analyst counting errors and (ii) contaminationon an unused filter or contamination as a consequence of thesample collection and sample preparation steps.3.1.2.1 Discussion—This definition of background is spe-cific to this practice. The only counting errors considered inthis definition of background are errors that result in anover-count (that is, false positives).Analyst counting errors areerrors such as, determining the length of structures or fibersand whether, based on length, they should be counted; countingartifacts as fibers; determining the number of structures pro-truding from a matrix; and interpreting a cluster as one, two, ormore structures that should be counted only as zero or onestructure. For purposes of developing the DL, assume thatbackground contamination sources have been reduced to theirlowest achievable levels.3.1.3 blank, n—a filter that has not been used to collectasbestos from the target environment.3.1.3.1 Discussion—Blanks are used in this practice todetermine the degree of asbestos contamination that is reflectedin asbestos measurements. Contamination may be on the virginfilter or introduced in handling the filter in the field or whenpreparing it for inspection with a microscope. The datarequired to determine the degree of contamination consists,therefore, of measurements of field blanks that have experi-enced the full preparation process.1This practice is under the jurisdiction ofASTM Committee D22 on Air Qualityand is the direct responsibility of Subcommittee D22.07 on Sampling and Analysisof Asbestos.Current edition approved Oct. 1, 2010. Published November 2010. Originallyapproved in 2000. Last previous edition approved 2006 as D6620 – 06. DOI:10.1520/D6620-06R10.2The DL also is referred to in the scientific literature as Limit of Detection(LOD), Method Detection Limit (MDL), and other similar descriptive names.3For purposes of general exposition, the term “structures” will be used in placeof “fibers or structures.” In the examples in Section 8, the specific term, “fiber” or“structure,” is used where appropriate. These terms are defined separately in Section3.4For referenced ASTM standards, visit the ASTM website, www.astm.org, orcontact ASTM Customer Service at service@astm.org. For Annual Book of ASTMStandards volume information, refer to the standard’s Document Summary page onthe ASTM website.Copyright © ASTM International, 100 Barr Harbor Drive, PO Box C700, West Conshohocken, PA 19428-2959. United States13.1.4 count, n—the number of fibers or structures identifiedin a sample.3.1.5 decision value, n—a numerical value used as a bound-ary in a statistical test to decide between the null hypothesisand the alternative hypothesis.3.1.5.1 Discussion—In the present context, the decisionvalue is a structure count that defines the boundary between“below detection” (the null hypothesis) and “detection” (thealternative hypothesis). If a structure count were larger than thedecision value, then one would conclude that detection hasbeen achieved (that is, the sample is from a distribution otherthan the background distribution). If the count were less than orequal to the decision value, the result would be reported as“below detection,” which means that the sample cannot bedifferentiated from a sample that would have been collectedfrom the background distribution.3.1.6 detection limit—the mean of a structure count popu-lation that is sufficiently large so a measurement from thispopulation would have a high probability (for example, 0.95 orlarger) of exceeding the decision value that determines detec-tion.3.1.6.1 Discussion—The DL is the value of a parameter, thetrue mean of a structure count population in the statisticalhypothesis testing problem, that underlies the DL concept.Specifically, it is the true mean of the alternative hypothesisthat ensures a sufficiently high power for the statistical test thatdetermines detection.3.1.7 fiber, n—any of various discrete entities with essen-tially parallel sides counted by a particular method thatspecifies length, width, and aspect ratio.3.1.7.1 Discussion—The definitions of “fiber” and “struc-ture” are similar because the measurement method employedspecifies the shape, length, width, and aspect ratio.3.1.8 mean, n—the mean value of the number of structuresin the population of air or dust sampled.3.1.8.1 Discussion—The mean in this definition is intendedto be the population mean, expected value, or first moment ofa statistical distribution. It is a theoretical parameter of thedistribution that may be estimated by forming an average ofmeasurements (refer to Terminology E456 for definition ofpopulation).3.1.9 power, n—the probability that a count exceeds thedecision value for a sample that was obtained from a popula-tion other than the background population.3.1.9.1 Discussion—Power is the probability of selecting,based on a statistical test, the alternative hypothesis when it istrue. In the present context, this means the probability ofmaking the correct decision to report a structure concentrationfor a sample that was collected from a population other than thebackground population. The power of the statistical test equals1 minus the type II error rate.3.1.10 replicate, n—a second measurement is a replicate ofthe initial measurement if the second measurement is obtainedfrom an identical sample and under identical conditions as theinitial measurement.3.1.10.1 Discussion—“Identical,” as applied to sample, canmean“ same subsample preparation,” “separate preparation ofa distinct subsample,” or a distinct sample obtained from thesame population as the initial sample. For this practice,“identical” means distinct sample obtained from the samepopulation as the initial sample.3.1.11 sample, n—the segment of the filter that is inspected,and thereby, embodies the air or dust that was collected and thesubset of structures that were captured on the portion of thefilter subjected to microscopic inspection (also, see Terminol-ogy D1356).3.1.12 sensitivity, n—the structure concentration corre-sponding to a count of one structure in the sample.3.1.13 structure, n—any of various discrete entities countedby a particular method that specifies shape, length, width, andaspect ratio.3.1.14 type I error, n—choosing, based on a statistical test,the alternative hypothesis over the null hypothesis when thenull hypothesis is, in fact, true; a false positive outcome of astatistical test.3.1.14.1 Discussion—Atype I error would occur if the countfor a sample exceeded the decision value, but the sample was,in fact, obtained from the background population. The analysterroneously would be led by the statistical test to report astructure concentration (that is, choose the alternative hypoth-esis of the statistical test), where the result should be reportedas “below the detection limit” (that is, the null hypothesis ofthe statistical test is true).3.1.15 type II error, n—choosing, based on a statistical test,the null hypothesis over the alternative hypothesis when thealternative hypothesis is, in fact, true; a false negative outcomeof a statistical test.3.1.15.1 Discussion—A type II error would occur if thecount for a sample does not exceed the decision value, but thesample was, in fact, obtained from a population other than thebackground population. The analyst would erroneously be ledby the statistical test to report a “below the detection limit”result (that is, choose the null hypothesis of the statistical test),where the result should be reported as a structure concentration(that is, the alternative hypothesis of the statistical test is true).3.1.16 type I error rate, n—the probability of a type I error(also referred to as the significance level, α-level,orp-value ofthe statistical test).3.1.17 type II error rate, n—the probability of a type II error(also referred to as the β-level of the statistical test).3.1.18 λ—lambda, the Greek letter used to represent thepopulation mean of a Poisson distribution.3.1.19 λ0—the population mean of the Poisson distributionof background counts.3.1.19.1 Discussion—λ0is the population mean of thePoisson distribution under the null hypothesis in the statisticalhypothesis testing problem that defines the DL.3.1.20 λ1—the population mean of the Poisson distributionunder the alternative hypothesis in the statistical hypothesistesting problem that defines the DL (DL = λ1).3.1.21 x0—decision value for determining detection. If thecount in a measurement is not greater than x0, the measurementis reported as “below detection.”D6620 − 06 (2010)23.1.22 X—Poisson distributed random variable used to de-note the number of structures (fibers) counted in a sample.3.1.23 A—the area of the filter inspected to obtain a struc-ture count.3.1.24 P(Xx/λ, A)—the Poisson probability of a structurecount exceeding x structures (fibers) when the population meanis equal to λ and an area, A, of the filter is inspected.4. Significance and Use4.1 The DL concept addresses potential measurement inter-pretation errors. It is used to control the likelihood of reportinga positive finding of asbestos when the measured asbestos levelcannot clearly be differentiated from the background contami-nation level. Specifically, a measurement is reported as being“below the DL” if the measured level is not statisticallydifferent than the background level.4.2 The DL, along with other measurement characteristicssuch as bias and precision, is used when selecting a measure-ment method for a particular application. The DL should beestablished either at the method development stage or prior toa specific application of the method. The method developersubsequently would advertise the method as having a certainDL.An analyst planning to collect and analyze samples would,if alternative measurement methods were available, want toselect a measurement method with a DL that was appropriatefor the intended application.5The most important use of theDL, therefore, takes place at the planning stage of a study,before samples are collected and analyzed.5. Descriptive Terms and Procedures5.1 Introduction:5.1.1 The DL is one of a number of characteristics used todescribe the expected performance of a measurement method.6The DL concept addresses certain potential measurementinterpretation errors. Specifically, a measurement is reported asbeing “below the DL” if the measured level cannot bedistinguished from zero or from the randomly varying back-ground contamination level. Stated differently, the DLprovidesprotection against a false positive finding. When a measuredvalue is less than an appropriately specified decision value, theanalyst is instructed to disregard the measured value and reportthe result only as “below the DL.”5.1.2 The DLconcept for asbestos measurements, which arebased on microscopy, is simpler than the DL concept formeasurement methods that depend, for example, on spectros-copy. For asbestos, the measurement is derived from a directcount of discrete structures using a microscope. For spectros-copy methods, the measurement is indirect requiring a calibra-tion curve, and is subject to interferences and unspecifiedbackground signals that could be responsible for measurementvalues that are false positives.5.1.3 The sources of false positives for asbestos counts are(i) analyst errors (for example, determining the length ofstructures or fibers and whether, based on length, they shouldbe counted; counting artifacts as fibers; determining the num-ber of structures protruding from a matrix; interpreting acluster as one, two, or more structures that should be countedonly as zero or one), and (ii) contamination (for example,virgin filter contamination or contamination introduced duringsample collection or sample preparation). Collectively, thesesources are referred to subsequently as “background.” Forpurposes of developing the DL, assume that each backgroundsource has been reduced to its lowest achievable level.5.2 DL—General Discussion:5.2.1 DLs often have been misspecified and misinterpretedbecause the DL concept has not been defined with sufficientclarity for translation into operational terms; however, the DLconcept and operational implementation have been presentedcorrectly in the scientific literature by a number of authors.7These authors describe the DL as a theoretical value, specifi-cally the t