1、Designation: D 7390 07Standard Guide forEvaluating Asbestos in Dust on Surfaces by ComparisonBetween Two Environments1This standard is issued under the fixed designation D 7390; the number immediately following the designation indicates the year oforiginal adoption or, in the case of revision, the y
2、ear of last revision. A number in parentheses indicates the year of last reapproval. Asuperscript epsilon (e) indicates an editorial change since the last revision or reapproval.1. Scope1.1 There are multiple purposes for determining the loadingof asbestos in dust on surfaces. Each particular purpos
3、e mayrequire unique sampling strategies, analytical methods, andprocedures for data interpretation. Procedures are provided tofacilitate application of available methods for determiningasbestos surface loadings and/or asbestos loadings in surfacedust for comparison between two environments. At prese
4、nt,this guide addresses one application of the ASTM surface dustmethods. It is anticipated that additional areas will be added inthe future. It is not intended that the discussion of oneapplication should limit use of the methods in other areas.1.2 This standard does not purport to address all of th
5、esafety 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. For specificwarning statements, see 5.7.2. Referenced Documents2.1 AS
6、TM Standards:2D 5755 Test Method for Microvacuum Sampling and Indi-rect Analysis of Dust by Transmission Electron Micros-copy for Asbestos Structure Number Surface LoadingD 5756 Test Method for Microvacuum Sampling and Indi-rect Analysis of Dust by Transmission Electron Micros-copy for Asbestos Mass
7、 Surface LoadingD 6480 Test Method for Wipe Sampling of Surfaces, Indi-rect Preparation, and Analysis for Asbestos StructureNumber Surface Loading by Transmission Electron Mi-croscopyD 6620 Practice for Asbestos Detection Limit Based onCountsE 105 Practice for Probability Sampling Of MaterialsE 122
8、Practice for Calculating Sample Size to Estimate,With Specified Precision, the Average for a Characteristicof a Lot or ProcessE 456 Terminology Relating to Quality and StatisticsE 2356 Practice for Comprehensive Building Asbestos Sur-veys2.2 Other Document:Environmental Protection Agency, U.S. (EPA)
9、, (PinkBook) Asbestos in Buildings: Simplified SamplingScheme for Surfacing Materials, EPA 560/5/85/030A,U.S. Environmental Protection Agency, Washington, DC,198533. Terminology3.1 DefinitionsUnless otherwise noted all statistical termsare as defined in Terminology E 456.3.1.1 activity generated aer
10、osola dispersion of particlesin air that have become airborne due to physical disturbancessuch as human activity, sweeping, airflow, etc.3.1.2 background samplessamples taken from surfacesthat are considered to have concentrations of asbestos insurface dust that are representative of conditions that
11、 exist in anenvironment that is affected by only prevailing conditions andhas not experienced events, disturbances or activities unusualfor the environment.3.1.3 controlan area that is used as the basis for acomparison. This could be an area where the dust has beenpreviously characterized, an area t
12、hought to be suitable foroccupancy, an area that has not experienced a disturbance ofasbestos-containing materials, or that is for some other reasondeemed to be suitable as the basis for a comparison.3.1.4 control samplessamples collected for comparison tothe study samples. These differ from backgro
13、und samples inthat they are collected: either: in an area where the dust hasbeen previously characterized, or in an area that has notexperienced a disturbance of asbestos-containing materials, orin an area that is for some other reason deemed to be suitableas the basis for comparison.3.1.5 dustany m
14、aterial composed of particles in a sizerange of 0,(CHIINV(a/2,2(A2+1)/2),(CHIINV(a,2)/2),where the value in cell A2 is the observed count of structures.(b) To obtain the lower 1-a confidence limit:=IF(A20,(CHIINV(1-a/2,2A2)/2),0), where the value in cellA2 is the observed count of structures. Table
15、A1.1 provides anexample of the formulae in an Excel spreadsheet necessary tocalculate the lower and upper 95 % confidence limits.(2) The confidence limits associated with the significancelevel a is equal to 1-a. As such, Table A1.2 gives the a forvarious confidence limits.(3) The number of structure
16、s at the upper and lowerconfidence limit is multiplied by the sensitivity of the mea-surement to obtain the upper and lower 1-a confidence limitsfor asbestos structure loading based on one sample.A1.2.4 Interpretation of Estimate and Confidence Limits:A1.2.4.1 The value computed inA1.2.1 is an estim
17、ate of themean (expected value of the Poisson distribution) of asbestosstructure loading for the homogeneous area where the samplewas collected. The values calculated in A1.2.2 are confidencelimits for the mean (expected value of the Poisson distribution)of asbestos structure loading for the homogen
18、eous area wherethe sample was collected.A1.3 Asbestos Surface Loading Estimated from MultipleSamples Collected by Test Method D 5755:A1.3.1 The measurements for multiple samples, say nsamples, collected from a homogeneous area may be combinedto produce an estimate of asbestos surface loading for the
19、homogeneous area that is more precise than an estimate ofasbestos surface loading based on one sample. The individualmeasurements are averaged using a weighted average wherethe sensitivities of the individual samples determine theweights.A1.3.1.1 Given n measurements (Si, Xi, Wi):i=1,2,n, the struct
20、ure loadings are Yi = SiXi; the mass loadingsare Yi = SiWi . (Here, the mass, Wi, is the total massmeasured for the ith sample.) The “weights” in the weightedaverage are the reciprocals of the sensitivities (1/Si). Theweighted average has a numerator and a denominator. Thenumerator is the sum of “we
21、ight multiplied times measure-ment” for all measurements. The denominator is the sum of theweights used in the numerator. Therefore, for structure loading,the weighted average is (SXi)/S (1/Si); for mass loading, theweighted average is (SWi)/S (1/Si). Note when sensitivity isa constant, Si = S, the
22、answers are simple averages S(SXi/n) for structure loading; S(SWi/n) for mass load-ing.A1.3.2 Data for Multiple Samples:A1.3.2.1 STRi, Si:I=1,2,narethestructure countsand sensitivities of the n samples.A1.3.3 Estimate:STR/cm25 (STi#/(1/Si!# (A1.3)A1.3.3.1 Note that if the sensitivities for all measu
23、rementsare the same value, S, then the estimate is computed as theaverage structure count over the samples multiplied by S:STR/cm25 S (STi#/n! (A1.4)A1.3.4 Confidence Limits:A1.3.4.1 Upper and lower confidence limits are obtainedusing the formulas in A1.2.2 with B2 set equal to the totalnumber of st
24、ructures counted in the n samples, S STRi.A1.4 Compare Two Environments:A1.4.1 Compare Two Environments Using Confidence In-tervals:A1.4.1.1 Compute separate confidence limits based onsamples collected from Homogeneous Area 1 and Homoge-neous Area 2. Apply the following decision rule: If theconfiden
25、ce intervals based on these limits overlap, concludethat the asbestos structure loadings in the two homogeneousareas are the same; if the confidence intervals do not overlap,conclude that the asbestos structure loadings in the twohomogeneous areas are different. Overlap occurs when theupper confiden
26、ce limit of the interval with the smaller esti-mated mean is larger than the lower confidence limit of theinterval with the larger estimated mean.A1.4.2 Interpretation of Confidence Interval Test:A1.4.2.1 If 95 % confidence intervals are used to conductthe statistical test described inA1.4.1, the si
27、gnificance level forthe test is approximately 0.05. In general, if 100(1-a)%confidence intervals are used for the test described in A1.4.1,the significance level for the test is approximately a. Theconfidence interval test is an approximate test that yieldsreliable results where the overlap or separ
28、ation of the intervalsis large. For example, data where the confidence intervals havea small overlap indicating no statistically significant differencemay show a statistically significant difference if a more precisestatistical test were used. See for example “Testing the equalityof two Poisson mean
29、s using the rate ratio,” Hon Keung TonyNg and Man-Lai Tang, Statistics in Medicine, 24, 2005, pp.955-965.A1.4.3 Compare Two Environments Using Normal Distri-bution Approximation for Poisson Count Data:TABLE A1.1 Spreadsheet Formulae to Calculate Upper and Lower 95 % Confidence LimitsAB C1Number ofSt
30、ructures Counted95 % LCL (structures) 95 % UCL (structures)2 1 =(IF(A20,(CHIINV(0.975,2A2)/2),0) =(IF(A20,(CHIINV(0.025,2(A2+1)/2),(CHIINV(0.05,2)/2)TABLE A1.2Confidence Limit a90 % 0.1095 % 0.0599 % 0.01D7390078A1.4.3.1 One Sample from Each Environment:(1) The square root of a structure count has a
31、n approximateNormal distribution with mean equal to the square root of thecount mean and variance equal to 0.25. Let STR1and STR2bethe structure counts for two samples with sensitivities S1andS2respectively. The Z-value for testing the equality of theasbestos surface loadings for the two environment
32、s where thesamples were collected is:Z 5 ST1!1/2 ST2!1/2#/0.5S11 S2!1/2# (A1.5)(2) To test the null hypothesis of “no difference betweenmean asbestos surface loadings in the two environments”compare Z to test value 1.96 for a test with approximatesignificance level equal to 0.05; compare Z to 2.58 f
33、or a testwith approximate significance level equal to 0.01. Reject thenull hypothesis if Z is larger than the test value.A1.4.3.2 Multiple Samples from Each Environment:Z 5 ST1/cm2!1/2 ST2/cm2!1/2#/$0.51/(1/S1i!# 1 1/(1/S2i!#!1/2%(A1.6)where STRi/cm25 (STij#/(1/Sij!# i 5 1, 2; j 5 1, 2, ., ni(1) The
34、 subscripts “1” and “2” indicate measurements forsamples from the two different environments that are com-pared. (Refer to A1.3 for definitions of the notation.) Z is usedto test the null hypothesis of “no difference between meanasbestos surface loadings in the two environments” as de-scribed in A1.
35、3.1.A1.4.3.3 ExampleTest described in A1.4.3.2 applied toExample 2 in main body of the guide. (See Table A1.3.)(1) From Table 2 in 6.10 in the main body of the guide wehave:ST1/cm25 3508; ST2/cm25 2133 (A1.7)Sum of Sensitivity Weights S15 0.014821 and S25 0.024377(2) This makes the denominator in th
36、e Z ratio = 0.5(1/0.010205)+(1/0.02439)1/2= 5.2080.(3) Therefore:Z 5 59.23 46.19!/5.2080 5 2.5 (A1.8)(4) Since the statistical hypothesis being tested is atwo-sided hypothesis, mathematical notation for the p-value is21 F(Z), where F() is the standard normal distribution.Therefore the p-value is cal
37、culated with the formula:21FZ!# (A1.9)(5) The p-value can be calculated using spreadsheet func-tions. For example the following expression in MicrosoftsExcel spreadsheet program will calculate the p-value where Zis known:212NORMSDISTZ,0,1,TRUE! (A1.10)(6) The p-value for the Z in this example is 0.0
38、12 and asthis p-value is less than 0.05, as is described in 6.10.2.1 the twoareas are considered to be different. TableA1.4 gives Z and thep-value for various confidence intervals.A1.4.4 Additional details concerning statistical tests forPoisson data are provided in “Testing the Equality of TwoPoiss
39、on Means Using the Rate Ratio,” Hon Keung, Tony Ng,and Man-Lai Tang, Statistics in Medicine, 24, 2005, pp.955-965; and Statistical Rules of Thumb, Wiley, 2002.A1.5 Identification and Control of Sources of Variation:A1.5.1 Differences in collection efficiency which couldaffect comparisons are discuss
40、ed in Appendix X1.A1.6 Sample LocationsOne method of determining whereto sample using a random number table is described below.A1.6.1 The investigator wishes to collect samples from 20metal desks. The 20 metal desks are given number 01, 02,19, 20. Beginning in the middle of a random number table,the
41、 investigator separates the numbers into 2-digit values. Thefirst six pairs might be 88, 26. 14, 06, 72, and 96. Since thenumbers 14 and 06 correspond to the numbers assigned to thedesks, two of the desks have been chosen for sampling. Thisprocess continues until 5 different desks (or the number ofs
42、amples as determined below) have been selected.A1.6.2 This same process is repeated to select the locationon the top surface of each desk selected. An imaginary grid of9 equal areas is constructed on each desk top and numbered10-19. Again, from the random number table the investigatorselects 2-digit
43、 numbers until one pair of numbers matches oneof the grid numbers. If the 2-digit pairs are 66, 24, 42, and 12;then the grid corresponding to “12” is where the sample will becollected for that desk.A1.7 Sets of Samples:A1.7.1 One set of samples should be collected to character-ize the asbestos dust
44、loadings for each different type ofhomogeneous surface being tested. For example, if the sam-pling was being conducted following a cleaning the followingcould apply.A1.7.2 If workers followed the same cleaning procedure fora group of 10 desks, 20 filing cabinets and 12 bookcases allconstructed of me
45、tal then may be grouped together as “metalfurniture.” However, if 5 of the desks had leather tops, these 5would be sampled as a separate set, or could be combined withother leather surfaces.A1.7.3 If 40 desks were cleaned; 20 of which were wet-wiped, and 20 were HEPAvacuumed, these would be separate
46、dinto two groups of 20 desks for sampling since the cleaningmethods were significantly different.A1.8 Number of SamplesThe number of samples used toTABLE A1.3Number ofStructuresCounted inStudy SamplesSum ofSensitivitiesfor Study AreaMeasurementsNumber ofStructuresCounted inBackground SamplesSum ofSe
47、nsitivitiesfor BackgroundArea Measurements52 0.014821 52 0.024377Z = 2.5 p-value = 0.012TABLE A1.4Confidence Interval Z p-value99 % 2.56 #0.0195 % 1.96 #0.0590 % 1.64 #0.10D7390079test for a difference between the asbestos surface loading intwo environments determines the power of the statistical te
48、st.For a fixed number of samples, the power of the test, which isthe probability that a specified difference between the asbestossurface loadings will be detected by the test, varies with (1) themagnitude of the difference to be detected and (2) to someextent with the significance level of the stati
49、stical test. Todetermine the number of samples for a test, this relationshipwould be inverted. The significance level and power would bespecified as would the corresponding magnitude of differencethat should be detected by the test with appropriate probability(that is, power). These quantities, then, would be used todetermine the number of samples.A1.8.1 Base CaseRule of Thumb:A1.8.1.1 For this base case, the number of samples collectedfrom each environment will be the same, n, and the sensit
