ASTM D6620-2006(2010) 1250 Standard Practice for Asbestos Detection Limit Based on Counts《基于计数测定石棉探测范围标准操作规程》.pdf

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1、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 revisi

2、on. 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 micro

3、scopy 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 stru

4、ctures 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 thiss

5、tandard.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. Refe

6、renced Documents2.1 ASTM Standards:4D1356 Terminology Relating to Sampling and Analysis ofAtmospheresD5755 Test Method for Microvacuum Sampling and Indi-rect Analysis of Dust by Transmission Electron Micros-copy for Asbestos Structure Number Surface LoadingD6281 Test Method for Airborne Asbestos Con

7、centration inAmbient and IndoorAtmospheres as Determined by Trans-mission Electron Microscopy Direct Transfer (TEM)D6480 Test Method for Wipe Sampling of Surfaces, Indi-rect Preparation, and Analysis for Asbestos StructureNumber Surface Loading by Transmission Electron Mi-croscopyE456 Terminology Re

8、lating to Quality and Statistics3. Terminology3.1 Definitions of Terms Specific to This Standard:3.1.1 average, nthe sum of a set of measurements(counts) divided by the number of measurements in the set.3.1.1.1 DiscussionThe average is distinguished from themean. The average is calculated from data

9、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, na statistical distribution of structuresintroduced by (i) analyst counting errors and (ii) co

10、ntaminationon an unused filter or contamination as a consequence of thesample collection and sample preparation steps.3.1.2.1 DiscussionThis definition of background is spe-cific to this practice. The only counting errors considered inthis definition of background are errors that result in anover-co

11、unt (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 on

12、e, 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, na filter that has not been used to collectasbestos from the target environmen

13、t.3.1.3.1 DiscussionBlanks 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 data1T

14、his practice is under the jurisdiction of ASTM 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 D6

15、620 - 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 e

16、xamples 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 serviceastm.org. For Annual Book of ASTMStandards volume

17、information, refer to the standards Document Summary page onthe ASTM website.1Copyright ASTM International, 100 Barr Harbor Drive, PO Box C700, West Conshohocken, PA 19428-2959, United States.required to determine the degree of contamination consists,therefore, of measurements of field blanks that h

18、ave experi-enced the full preparation process.3.1.4 count, nthe number of fibers or structures identifiedin a sample.3.1.5 decision value, na numerical value used as a bound-ary in a statistical test to decide between the null hypothesisand the alternative hypothesis.3.1.5.1 DiscussionIn the present

19、 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

20、 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 distributio

21、n.3.1.6 detection limitthe 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 DiscussionThe DL is the value of a parameter,

22、 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, nany of vario

23、us discrete entities with essen-tially parallel sides counted by a particular method thatspecifies length, width, and aspect ratio.3.1.7.1 DiscussionThe definitions of “fiber” and “struc-ture” are similar because the measurement method employedspecifies the shape, length, width, and aspect ratio.3.1

24、.8 mean, nthe mean value of the number of structuresin the population of air or dust sampled.3.1.8.1 DiscussionThe 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

25、estimated by forming an average ofmeasurements (refer to Terminology E456 for definition ofpopulation).3.1.9 power, nthe 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 DiscussionPower is the probabilit

26、y 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

27、of the statistical test equals1 minus the type II error rate.3.1.10 replicate, na 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 appl

28、ied 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

29、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, nthe structure concentration corre-sp

30、onding to a count of one structure in the sample.3.1.13 structure, nany of various discrete entities countedby a particular method that specifies shape, length, width, andaspect ratio.3.1.14 type I error, nchoosing, based on a statistical test,the alternative hypothesis over the null hypothesis when

31、 thenull hypothesis is, in fact, true; a false positive outcome of astatistical test.3.1.14.1 DiscussionA type I error would occur if thecount for a sample exceeded the decision value, but the samplewas, in fact, obtained from the background population. Theanalyst erroneously would be led by the sta

32、tistical test to reporta structure concentration (that is, choose the alternative hy-pothesis of the statistical test), where the result should bereported as “below the detection limit” (that is, the nullhypothesis of the statistical test is true).3.1.15 type II error, nchoosing, based on a statisti

33、cal 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 DiscussionA type II error would occur if thecount for a sample does not exceed the decision value, but thesample was, in fact, obtaine

34、d 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, t

35、he alternative hypothesis of the statistical test is true).3.1.16 type I error rate, nthe probability of a type I error(also referred to as the significance level, a-level,orp-value ofthe statistical test).3.1.17 type II error rate, nthe probability of a type II error(also referred to as the b-level

36、 of the statistical test).3.1.18 llambda, the Greek letter used to represent thepopulation mean of a Poisson distribution.3.1.19 l0the population mean of the Poisson distributionof background counts.3.1.19.1 Discussionl0is the population mean of thePoisson distribution under the null hypothesis in t

37、he statisticalhypothesis testing problem that defines the DL.3.1.20 l1the population mean of the Poisson distributionunder the alternative hypothesis in the statistical hypothesistesting problem that defines the DL (DL = l1).3.1.21 x0decision value for determining detection. If thecount in a measure

38、ment is not greater than x0, the measurementis reported as “below detection.”D6620 06 (2010)23.1.22 XPoisson distributed random variable used to de-note the number of structures (fibers) counted in a sample.3.1.23 Athe area of the filter inspected to obtain astructure count.3.1.24 P(Xx/l,A)the Poiss

39、on probability of a structurecount exceeding x structures (fibers) when the population meanis equal to l 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 pos

40、itive 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 oth

41、er 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 th

42、e 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 pl

43、anning 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 measurementinterpretat

44、ion 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 DL providesprotection against a false positive finding. When a measuredvalue is less

45、 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 DL concept for asbestos measurements, which arebased on microscopy, is simpler than the DL concept formeasurement methods that depend, for e

46、xample, 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 resp

47、onsible 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

48、 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, theseso

49、urces 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 DLGeneral 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