Anal. Chem. 1985, 5 7 , 209-213
209
Accuracy of Transmission Electron Microscopy for the Analysis of Asbestos in Ambient Environments Eric B. Steel* and John A. Small National Bureau of Standards, Building 222, Room A121, Gaithersburg, Maryland 20899
Errors associated with the transmission electron microscopic (TEM) analysis of trace amounts of chrysotile asbestos In samples collected from ambient environments have been Investlgated. The microscope can be the source of order-ofmagnitude errors in the reported chrysotile concentration If the mechanical stage, image quality, and electron diffraction capablilties do not meet the demanding requirements of asbestos analysis. By use of a verified counting procedure, It was determined that most operators of a TEM have less than a 50% chance of finding and counting chrysotile fibers less than 1 pm in length. However, accuracies greater than 90% can be achieved on chrysotile fibers longer than 1 pm.
The accurate analysis of asbestos in the ambient environment has become an important issue due to the possible long-term health effects of low doses of asbestos. Environmental air and water samples generally have trace amounts (nanogram to picogram quantities) of asbestos in complex matrices of particulate matter collected onto membrane filters. The size distribution of the asbestos fibers in these environmental samples is generally much smaller and more finely divided than those found in asbestos-industry samples where light microscopy is commonly used ( I ) . Because the asbestos in environmental samples is often in the form of single fibrils or bundles of a few fibrils with widths on the order of tens of nanometers, the light microscope is not able to observe the mbestos. Of the available methods for the analysis of asbestos, the analytical electron microscope (AEM) method is currently the best technique (2). The AEM is essentially a combination transmission electron microscope and a scanning electron (transmission or secondary electron imaging) microscope. The AEM provides the capabilities of high-resolution and highcontrast imaging, observation of electron diffraction from individual fibers, and, by focusing the beam on individual asbestos fibers, chemical analysis using an energy dispersive X-ray spectrometer. The TEM imaging mode of the AEM is used to find the asbestos fibers in this study and the diffraction and X-ray spectrometry capabilities are used to identify the fibers. For nonoccupational types of samples no other method provides the sensitivity, resolution, particle identification and size information comparable to that available from an AEM. However, the accuracy of the analysis is determined by factors that are difficuk to control. These include the following: (1)There are many problems associated with sampling for trace quantities from what is likely to be a sporadic and/or unknown source, yielding asbestos concentrations that may vary widely with time and placement of sampling. (2) Particle loss or contamination in sample preparation. Asbestos is a ubiquitous mineral and clean room facilities for sample preparation are needed to reduce blank or background levels to the point where the trace amounts of asbestos discussed in this paper can be analyzed. In addition, many types of sample preparation procedures can alter the site distribution or cause actual fiber loss (3, 4). (3) The first step in asbestos analysis is essentially a visual identification based on the unique morphology of the asbestos
particles. Therefore, instrumental variables such as accelerating voltage, stage translation, speciment current, instrument age, ease of operation, etc. can dramatically affect the precision and accuracy of the technique. (4)Operator biases and variability can change measurably over both the long and the short term. Psychological factors, such as professional pressure to perform, physical factors, such as eye strain, as well as time constraints can measurably affect results. (5) Statistical problems are associated with doing what is essentially a bulk analysis using a microanalytical technique. Generally, very small portions of a total filter are analyzed and often fewer than 100 fibers are counted. These data are then projected to the whole filter surface through multiplication by factors of thousands to millions. The small sample areas and populations have the potential for large errors depending on the actual distribution of the fibers over the filter
(5, 6). The electron microscope was first used for determining asbestos concentrations in ambient environments approximately 10 years ago. The potential magnitude of the problems with the analytical and sampling methods (discussed above) were shown when an early round robin using split samples from the same filter and various sample preparation and analytical practices showed asbestos concentration variations of approximately 4 orders of magnitude (7). More recent round robins using the Environmental Protection Agency’s methodologies for air and water samples (8, 9) have shown interlaboratory variations in asbestos concentration that are generally within an order of magnitude (IO). NBS has prepared polycarbonate filter sections with light and medium loadings of chrysotile asbestos in a matrix of urban air particulate for use as reference materials for the electron micrscopic determination of asbestos contents in nonoccupational environments (11) (Standard Reference Material 1876, and a Chrysotile Asbestos Filter Research Material). Since the AEM is the best available method of analysis, it was used in the analysis of these filters. It was necessary to eliminate, control, or at least estimate the effect of the factors listed above so that accurate values for the asbestos content of the filters could be reported. This paper discusses some of the factors that were found to lead to significant analytical error and the methods that were used to measure and reduce these errors. One of the most useful techniques was a “verified counting method” where multiple operators would analyze the same area of filter. This method was helpful in determining both operator and machine related errors and was used to determine the best estimate of the concentration of chrysotile asbestos on the standard filters (11). The errors discussed in this paper apply to analysis of chrysotile asbestos, which is by far the most common type found commercially and environmentally in the U.S.Analysis of other types of asbestos, such as crocidolite or amosite, may have quite different types or magnitudes of errors. EXPERIMENTAL SECTION The filter materials are prepared by filtering suspensions containing small amounts of National Institutes of Environmental Health Sciences short fiber chrysotile (12) and St. Louis Urban
This article not subject to U S . Copyright. Published 1984 by the American Chemical Society
210
ANALYTICAL CHEMISTRY. VOL. 57. NO. I. JANUARY1985
F I p a 1. An slectromiaogaph of a R M of dwpatib h which the Cemral pMlon has been removed dving sample prepsrnh.
Air Particulate, NBS Standard Reference Material 1648. in distilled and filtered water onto 0.4 pm pore si% polycarbonate filters. The microscope specimens were prepared on indexed 200 mesh copper transmiasion electron microsmpe (TEM) following the EPA provisional method for analysis of asbestos in air (8). These samples yielded chrysotile concentrationsof approximately 30 fibers per 0.01 mm2. A more detailed description of sample preparation is given in Small et al. (11). Contamination during sample preparation wan not a significant faetor until after the filters were prepared. because the samples were only characterized for fiber number after preparation and no correlation with the mass of the doped chrysotile solution was attempted. After the fdters were prepared, c u e wan taken to keep the filters and prepared sections as free from contamination as possible. The specimenswere kept in covered containers in a clean room designed for asbestos sample preparation. Several times identid grid squares were analyzed with a time separation of up to 2 y w with no apparent deviation in asbestos concentration, showing neither contamination nor loss of asbeatos fibers on ow specimens. On many of the grids the Jaffe wick technique was supplemented or substituted with a chloroform condensation washing technique (8). Fiber loss due to preparation is more difficult to determine, but there was rare evidence for fiber loeses as shown in Figure 1. Figure 1shows a location on a prepared grid in which a portion of a fiber was either moved or washed away. Only two cases of this were observed during the course of a 4 year study involving over 100 grid square analyaes. However, if the whole small fiber were to wash away it would be extremely difficult to observe and verify, and this may occur with more frequeney than the partial fiber loss cited here. Other studies have shown that the polycarbonate method has the least fiber loss of any of the techniques tested thus far (3). RESULTS A N D DISCUSSION Counting P d u r e s . For the data presented on mimecope evaluation a t least two operatom (and generally four) analyzed each grid opening. The analysts all were trained extensively or had previously accrued more than 6 months of experience in electron microscopic analysis of asbestos. Seven in-house anal@ and two visiting analysts (seeverified counting section) were used for this study. Evaluation of Electron Microscopes. At the beginnii of the study it was realized that the instrument used could affect the analytical results, so eight different transmission electron microscopes (TEM) were evaluated for use in the analysis of chrysotile asbestos. The instruments were judged on the basis of image quality, electron diffraction quality, and reproducibility of good asbestos counting data. The "EMS varied in age from approximately 25 years to newly installed. All instrumentswere operated at 100kV acceleratingpotential The same specimens were analyzed by the same set of operators on each instrument.
The factors that were noted to have the most measurable effect on the asbestos count8 were 111 image quality (resolution, contrast, and brightness), [2] electron beam dose to the the specimen, and [3] mechanical stage operation. Resolution was judged by the ability to detect the hollow tubular structure of chrysotile, which is a key test in distinguishing chrysotile fibers from nonasbestos fibers. Image contrast and brightness can be controlled on each instrument by adjusting voltage, aperture sizes,Wehnelt adjustment and bias conditions. etc. But all the instruments were not equal in brightness performance even after optimizing these parameters. Some of the oldest instruments did not have sufficient resolution or brightness to clearly define the hollow tubular structure of chrysotile. Even instruments of the same approximate age, and the same manufacturer, but having different pole pi-, displayed quite different image quality. On the basis of image quality alone. three instruments were considered incapable of collecting accurate asbestos data. The electron beam dose to the specimen affects the diffraction data for chrysotile. Beam dose is the number of electrons which hit the sample and is a function of beam current a t the specimen and the length of time the beam is on the specimen. Often chrysotile will display beam damage by losing its crystallinity (13). There is a trade-off between having a bright (high current and beam dose) image for ease of visibility of the asbestos fibers and the generally low beam dose conditions needed to attain good diffraction data from chrysotile. If the TEM has an inefficient electron optic system, the specimen must be subjected to a large dose to obtain a useful image. The specimen current is again a function of some of the same parameters that determine image quality. But several instruments had to be operated a t such low image brightness levels to get reasonable diffraction that the image was too dim for general asbestos analysis. The time necessary to set up the proper diffraction conditions and the selected area aperture varied from a few seconds for some of the newer instruments to approximately half a minute for some of the older instruments. Since beam dose is a function of time, this set-up operation can effect the degree of beam damage to the specimen. Operating under adequate imaging conditions and working as quickly as possible, several T E M s had less than a 10% succe8s rate for obtaining observable diffraction patterns on chrysotile. The best machines had greater than a 90% s u m rate and many of the failures were due to fibers b e i closely associated with other objects which obscured the electron diffraction from the chrysotile. Four instruments were considered incapable of obtaining the combination of useful images and chrysotile diffraction data. The mechanical stage of the TEM is very important in asbestos analysis and is often overlooked as a source of error. Chrysotile concentration is analyzed as a function of area as measured on a TEM specimen support grid. This support grid is generally close to a 200 meah, yielding square holes with sides of approximately 100 pm. These squares are traversed very carefully at a magnification of approximately 20000X where the field of view in the TEM (approximately 5 pm on a side) is much smaller than the grid square. This means that approximately 2C-30 (depending on the amount of overlap used) traverses are needed to completely analyze one grid square. This assumes the traverses are straight and reproducible. On two of the TEMs tested, the stage traverses were not adequately reproducible. One instrument, in particular, wandered unpredictably up to 30 pm from a linear traverse. This caused fibers to be completely missed or recounted and yielded counts that had much higher variance and counts that were 50% lower than the best instruments. The TEM used for the operator error data in this paper has a stage which wanders less than 1pm during a 100 pm linear traverse and
ANALYTICAL CHEMISTRY, VOL. 57, NO. 1, JANUARY 1985
allows very consistent and reproducible traverses. Even for this instrument some wandering or backlash occurs when the direction of stage movement is reversed. This is remedied by continuing past the end of the traverse approximately 10 pm and then reversing directions so that by the time one is back in the area to be analyzed, the effect of the backlash is reduced to less than 1 pm. Of the eight instruments examined, five were considered incapable 9f accurate chrysotile asbestos analysis for one or more of the reasons listed above. Many of these shortcomings could have been improved through changes in the stages, pole pieces, general instrument maintenance, etc. However, the condition of these instruments were typical of the general conditions of TEMs found in many laboratories. Most were quite usable for more typical TEM studies, but not for asbestos analysis. The error associated with the instruments could be worse than approximately a factor of 2 when using morphology to determine concentration, but if electron diffraction were required, several instruments in this study would show results that were over an order of magnitude lower than the actual asbestos concentration. Evaluation of Operator Errors. In order to evaluate the accuracy of chrysotile analyses as a function of operator, each grid square was analyzed for asbestos by a t least four and as many as six operators and then the data were compared. Each operator logged the following data on each fiber in a grid square: comments on the hollow tubular morphology of the fiber (distinct, possible, not visible); whether the fiber was a bundle or single fibril; comments on the electron diffraction of the fiber (distinct, possible, none, chrysotile, amphibole, or other); whether the fiber was partially obscured by another particle or a grid bar; the length and width of the fiber; and the fiber type (using all the information from above to label each fiber as chrysotile, amphibole, other). Testing of operator variability was performed on the instrument that performed most reliably and accurately as discussed above. The average count of all operators was used as a basis for comparing each operator’s counts. “Operator count“ is defined as the number of chrysotile fibers found in the grid square being analyzed. The following observations were made. [11 The average deviation from the average chrysotile count was a function of the operator. That is, some operators’ counts were always close to the mean count while other operators’ counts were always much farther from the mean count. For example, our operator 4 showed a deviation from the mean that is 2.3 times greater than those of operators 1 or 2. [2] Some operators had a definite bias higher or lower than the average count, rather than being randomly distributed about the average. NBS operator 3 had the lowest count in over one-third of the analyses and operator 4 had the highest count in approximately half of the analyses. Operator 4 also had a large number of low counts to yield overall counts that were close to the average of the five operators. [3] In many cases the individual fiber data (Le., length, width, bundle-fibril,obscured or not) collected by one operator could not be successfully compared to another operator’s data. This was especially true of fibers shorter than 1pm. It was concluded from this that the operators were not counting the same fibers. [4] An operator’s counts can be adversely affected by professional pressure. When operators were told that their results were consistently too low (20% or more below the average),the next several counts showed much higher variation (up to a factor 2 higher than previously recorded for that operator) and were not as reliable as previous analyses. Similarly when an operator was told that he or she was taking much longer than other operators to count a grid, his or her
153-
m >,
211
212
ANALYTICAL CHEMISTRY, VOL. 57, NO. 1, JANUARY I985
Table I. Error Data as a Function of Operator and Time 1
2
operator 3 4 5
a
% fibers missed
14 330 range of % missed 5-36
13 330 5-21
14 330 4-40
6
7“
31 330 5-40
K
w m
fz
Year Two 11 360 range of % missed 0-33 % fibers missed
no. of fibers
11 9.4 360 322 0-25 5-30
29 318 5-40
23 201 5-36
% fibers missed
6.3 563 range of % missed 0-28
4.5 563 0-24
12 438 0-24
ij 40
20
0 0
Year Three
no. of fibers
I 1
Year One
no. of fibers
I2O
12 11 352 244 0-24 0-28
8.7 104 3-24
b
FIBER LENGTH ( p m l
120
“Operator 7 is a composite of two visiting operators’ counts. 100
rized. All other operators were used only part time for counting. Operators 3 and 4 had 1.5 years of experience, while operators 5 and 6 started 6 months previous to the period of analysis reported in Table I. From Table I it can be seen that an average operator missed approximately 10% of the asbestos fibers in the standards and that on any single grid square count an operator missed from 0 to approximately 30% of the fibers. Many operators showed improvement with time. Operators 1 and 2 improved over the 3-year period from missing approximately 13% of the fibers in the first year to an average of 5% fibers missed in the third year, and operator 5 improved from 23% to 12% missed in a 1-year period. Operator 3 showed only slight improvement, mainly noted in the range of fibers missed. Operator 4 stayed essentially the same throughout the study with approximately 30% of the fibers missed. On this basis it was determined that this operator did not have the necessary aptitude for asbestos analysis and was discontinued from the program. “Operator 7”, in Table I, consists of the composite counts of two visiting operators. The composite is used because each operator alone counted too few fibers to give meaningful statistics in comparison with the other operators listed; however, the composite data do show that operators from outside the NBS laboratory may be expected to get errors comparable to those of NBS personnel using the NBS microscope, counting methods, and specimen. Operators 1 and 2 showed the most dramatic improvement and accuracy. This is possibly due to their early analysis of the data (14) and subsequent effort at eliminating the known fiber size bias discussed below. Also, these operators were responsible for the the project and therefore had the greatest professional interest in the project. Figure 3a shows a histogram of the lengths of all the verified chrysotile fibers found and Figure 3b shows a histogram of the lengths of the chrysotile fibers missed by each of the operators in the third year data set in Table I. The data in Figure 3b have been weighted by multiplying by the number of operators missing each fiber. For example if three operators missed the same 0.2 pm length fiber, then it was entered three times in the histogram data set. Therefore the missed fibers are a weighted subset of the data in Figure 3a. These histograms show that the vast majority of the fibers missed are below 0.5 pm. Only six fibers (weighted to 9 by multiple misses) greater than 1pm in length were missed out of 269 fibers over 1 pm in length. Thus, only approximately 2% of the fibers over 1 pm in length were missed. Our data have consistently shown that below a fiber length of approximately
K
w
m t 3
z
40
20
0
2.0
4.0
FIBER
6.0
LENGTH
8.0
10.0
12.0
(pm)
Flgure 3. (a) Histogram of the lengths of all verified fibers analyzed by the operators listed under the third year in Table I. (b) Histogram of the lengths of all the fibers missed by the operators using the same data set as in Figure 3a. Each fiber length data entry was weighted by the number of operators missing the fiber.
0.5 pm, NBS operators (1-6 in Table I) have approximately a 50% chance or less of observing the fiber. Operators 1 and 2 have been able to drop this probability to approximately 25% by being very careful to guard against this known size bias, but we would not expect this to be typical among asbestos analysts. It should be noted that the verified counting method which incorporates the composite analyses of several operators is currently the most accurate technique for ambient asbestos counting. However, even this method has a small chance for missing fibers. During the 3 years of using the verified method we have found five chrysotile fibers that were not observed by anyone during the counting procedure and were only found by chance during the verification process. All these fibers were about 0.4 pm or less in length, and the chance of missing them is a function of the number of operators counting the specimen and the probability of each operator seeing the fiber. For instance with four operators each having a 50% change of seeing a fiber below 0.5 pm in length, there is still an -6% ((0.5)4) chance of missing the fiber. This means that the verified analysis technique gives data that approach as closely as currently possible the true asbestos count but still has some error in finding very short fibers. Fiber bundles are another potential source of error, due to the large number of ways a bundle can be broken into individual fibers for counting and recording purposes. The NBS standard solutions were mixed with an ultrasonic probe for 20 min at 100 W of power before filtration to decrease the occurrence of this type of fiber, but the complex bundles do
ANALYTICAL CHEMISTRY, VOL.
occur occasionally. With bundle fiber counting rules similar to those suggested by Yamate (15),the error associated with disagreements in the ways our operators counted the bundles averaged less than 1% of the total number of fibers observed and ranged from 0 to 20% on individual grid square counts. The magnitude of these bundle related errors may be sample dependent and should not be assumed to apply to all environmental samples. CONCLUSIONS Using data acquired during the research and certification of the NBS chrysotile standard filter materials, we have determined several major sources of error in the analysis of ambient-type samples by the TEM. The instrument alone can be the source of order-of-magnitude size errors in concentration if the mechanical stage, imaging and contrast, and diffraction capabilities are not up to the demanding requirements of asbestos analysis. Each instrument used for this type of analysis should first be tested by experienced personnel to see if it is capable of good analyses. The microscope should be tested specifically for the reproducibility and accuracy of the mechanical stage, whether it can easily resolve chrysotile’s hollow tubular morphology and attain greater than 90% success on electron diffraction of individual, short chrysotile fibrils of standard specimens. The NBS standard reference material may be useful in sorting out some of these instrumental problems as well as in the training and testing of operators. These results indicate that for chrysotile asbestos fibers above approximately 1.0 pm in length, a careful and experienced analyst using the TEM with the EPA provisional method can attain accuracies greater than 90%. The overall accuracy of the technique is then limited to the errors defined by the statistics of the distribution of fibers over the surface of the filter and problems associated with sampling. The results of this study call into question the value of attempting to analyze the very short chrysotile fibers, since the results are likely to be inaccurate and imprecise. ACKNOWLEDGMENT The authors wish to thank the following people for their help in the analysis of the filters: Patrick Sheridan, Barbara Thorne, Patricia Johnson, Robert Myklebust, and Sara Mathews of NBS, A1 Zermay of the United States Steel Corp., and Kim B. Shedd of the Bureau of Mines, U.S. Department of Interior. We also wish to thank Michael Beard of the
57, NO. 1, JANUARY 1985
213
Environmental Protection Agency for his support of the work in this paper. Registry No. Chrysotile, 12001-29-5. LITERATURE CITED Leidei, N. A.; Bayer, S. G.; Zumwaide, R. D.; Busch, K. A. “USPHS/ NIOSH Membrane Filter Method for Evaluating Airborne Asbestos Fibers”; U S . Department of Health, Education, and Welfare, National Institute for Occupational Safety and Health: Cincinnati, OH, 1979. Chatfieid, E. J. “Measurement of Asbestos Fibre Concentrations in Ambient Atmospheres”; Royal Commission on Matters of Health and Safety Arising from the Use of Asbestos in Ontario: Toronto, Ontario,
1983. Chatfieid, E. J.; Dillon, M. J. “Some Aspects of Specimen Preparation and Limitations of Precision in Particulate Analysis by SEM and TEM”; Johari, O., Ed.; SEM, Inc., AMF O’Hare: Chicago, IL, 1978; SEM/ 1978/1,pp 487-496. Cook, P. M.; Markiung, D. R. I n “Asbestos Standards: Materials and Analytical Methods”; Small, J., Steel, E., Eds.; US. Department of Commerce: Washington, DC, 1982;NBS Spec. Pubi. 619. Leigh, S.; et ai. I n “Asbestos Standards: Materials and Analytical Methods”; Small, J., Steel, E., Eds.; U S . Department of Commerce: Washington, DC, 1982;NBS Spec. Pubi. 619. Chatfieid, E. J. I n “Asbestos Standards: Materials and Analyticai Methods”; Small, J., Steel, E., Eds.; U.S.Department of Commerce: Washington, DC, 1982;NBS Spec. Pubi. 619. Montgomery County Asbestos Study, EPA Internal Report; U.S. Environmental Protection Agency, Envlronmentai Monitoring Systems Laboratory, Environmental Monitoring Division: Research Triangle Park, NC, 1977. Electron Microscope Measurement of Airborne Asbestos Concentrations: A Provisional Methodology Manual, EPA Report No. 600/2-77178;Environmental Sciences Research Laboratory, US. Environmental Protection Agency: Research Triangle Park, NC, Revised 1978. Anderson, C. H.; Long, J. M. Interim Method for Determining Asbestos National Technical Informatlon in Water; Report EPA 600/4-80-005; Service: Springfield, VA, 1980. Chopra, K. S.;Beaman, D.; Cook, P. I n “Asbestos Standards: Materials and Analytical Methods”; Small, J., Steel, E., Eds.; U.S. Department of Commerce: Washington, DC, 1982; NBS Spec. Pubi. 619. Small, J. A.; Steel, E. B.; Sheridan, P. Anal. Chem., preceding paper in this issue. Campbell, W. J.; Huggins, C. W.; Wylie, A. G. “Chemical and Physical Characterization of Amosite, Chrysotile, Crocidolite, and Nonfibrous Tremolite for Oral Ingestion Studies by the National Institute of Environmental Health Sciences”; U.S. Department of Interlor: Washlngton, DC, 1980;Bureau of Mines Publication RI-8452. Zussman, J.; Brindiey, G. W. Am. Mineral. 1957, 42, 133. Steel, E.; Small, J.; Sheridan, P. I n “Asbestos standards: Materials and Analytical Methods”; Small, J., Steel, E., Eds.; U S . Department of Commerce, Washington, DC, 1982;NBS Spec. Pubi. 619. Yamate, G.; Beard, M. E. I n “Asbestos Standards: Materials and Analytical Methods”; Small, J., Steel, E., Eds.; US. Department of Commerce, Washington, DC, 1982;NBS Spec. Publ. 619.
RECEIVED for review April 19, 1984. Resubmitted June 12, 1984. Accepted September 27,1984. The work presented in this paper was supported in part by the Environmental Monitoring and Support Laboratory of the U.S. Environmental Protection Agency.
