Document by0JEg9j0EN0Y6nN6wzY97BKD
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i
OUT OF NOTHING
Legal limits on
asbestos exposure are becoming
By Jeffrey A. Boggs
increasingly less.
I I H t is critical that decisions to re-
But how are valid air samplings
open removal sites to the un-
protected public are supported by statistically valid test data.
made when
Today a method for estimating lowlevel airborne asbestos fiber concen
the values
trations with statistical confidence, both prior to and following abatement
measured are near zero?
projects, has been developed. This "Poisson" distribution method has been tested and found the best statis
tical model for determining both
unexposed membrane filters (back
ground levels) and sample membrane
r
filters (exposed levels) of asbestos. The "limits of reliable detection"
for the USPHS/NIOSH methods
P&CAM 239 or 7400 are the limit of
qualitative detection (LOD) and the
limit ofquantitative detection (LOQ).
Standard calculating procedures
utilizing known variables--such as
microscope field area, filter effective
collecting area and sample air
volume--provide guidelines for deter
mining detection limits. The protocol
has been simplified for laboratory
analysis of low-level airborne fiber
concentrations by the presently
preferred NIOSH methods. Additional
formulae, which determine the re
quired air volume (Q) to "reliably
detect" the filter surfece fiber concen
tration standards (S) help laboratories
and hygienists specify appropriate
sampling strategies, a priori.
Thus, the proposed standard
methodology offers two significant
contributions for determining low-
level airborne asbestos fiber concen-
PLAINTIFF'S EXHIBIT AL-986
MAY/JUNE 1988 ASBESTOS ABATEMENT 23
trations: 1) provides point estimates based on the calculated, known "limit of detection" for any volume of air sampled, and 2) permits statistically valid "re-entry" decisions.
OSHA first regulated occupational exposures to asbestos (See Figure 2) in 1971 when it adopted a 12 f/cc limit. In June 1972, OSHA pro mulgated the present standard which is found at 29 CFR 1910.1001. This standard established an 8-hour TWA permissible exposure limit (PEL) of 5 f/cc (with a ceiling limit of 10 f/cc), and mandated further reduction in the PEL to 2 /cc effective July, 1976.
In 1975, OSHA again proposed to lower the PEL from 2.0 f/cc to 0.5 free and the ceiling limit from 10 f/cc to 5 free. This notice of proposed rulemaking was based on then-available evidence which OSHA believed had "accumulated to warrant the des ignation of asbestos as a human carcinogen."
In 1982, the State of Maryland
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24 ASBESTOS ABATEMENT MAY/JUNE 1988
promulgated asbestos regulations that required final air testing on any large project. Areas could not be opened to the public until airborne concentra tions were less than 0.1 f/cc. In November 1983, OSHA published an Emergency Temporary Standard (ETS) which mandated an immediate reduction in the PEL to 0.5 free.
In June 1985, the^SPA published "Guidance For ControHIhg AsbestosContaining Materials in Buildings". This text is generally regarded as the latest information on asbestos hazard evaluation. Appendix M of the docu ment recommends that if any phasecontrast microscope samples exceed 0.01 free, the abatement site should be recleaned.
The Veterans Administration lias specified that authorization for removal of barriers of small area asbestos removals will be authorized if the air sample is 0.005 free.
These current re-occupancy stan dards would suggest very low and zero fiber counts in post-abatement environments. The problem, there fore, is how to handle "zero" or "near zero" data values. In industrial hygiene work, zero value levels are generally undetectable. These levels do occur, however, and (here is no
the 1500 liter specification where 10 fibers must be counted in 100 fields. Our result, however, permits the "detection limit'' of 0.01 f/cc to be used when 1112 liters have been sampled and fewer than eight fibers are counted in 100 fields. Conclusions
We have shown how to compute the required volume Q to detect a given airborne fiber concentration. However, analytical laboratories do not usually control the volume sampled for individual analysis. As such, we have algebraically solved for the detection limit based on the volume of air sampled given as a con stant K. This computation uses the same features as the relationship for Q, i.e., the effective filter area times the LOQ, surface fiber concentration as known. However, this method solves for the concentration of air borne fibers/cc as a function of the volume sampled.
Here, we show for our own laboratory, that K equals 11.12
MAGNITUDE OF? ERRORS ENCOUNTEjffci WITH LOW FIBER CONCENTRATIONS:3
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CONDITIONS: 37M& DIA. FILTER T .006"SQ MM RELD-AREA^rs 960 LITERS 2 FIBERS IN 100 FIELDS
r
BY CAiicuuvnoiip . vXSs.
FIBERS/CG =
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fibers/cc divided by the dimension less value of the volume sampled. Somewhat obviously, if we divided K by the required volume Q to detect the previously shown re-occupancy limit, we solve for 0.01 fibers/cc.
Once analytical laboratories have derived a constant LOQ, they can derive the analytical detection limit based on the volume of air sampled when the fiber count LOQ is not ex ceeded. The results shown here (See Thble 6) for volumes varying from 100 to 5000 liters give corresponding detection limits of 0.12 to 0.002 fibers/cc.
We show here (See Thble 7) in the
two computations the type of error that results from calculating the air borne asbestos fiber concentration when the LOQ fiber count is not known. This is not a worst-case situa tion but rather, unfortunately, a con dition that arises quite often for samples submitted for re-occupancy.
In the upper calculation there were two fibers in 100 fields measured, a
value even lower than the LOD, for a sample volume of 960 liters. This is essentially an 8-hour TWA at 2 liters/min. Were the laboratory to release the result of 0.003 fibers/cc, the area would be improperly cleared for re-entry of the unprotected public when the limit of detection is actually 0.012 fibers/cc. This, again, is a moderate problem when compared to a fiber count of zero whose detection limit is still 0.012 fibers/cc--but without this LOQ relationship the analytical laboratory has no quantita tive estimate for the airborne fiber concentration. The value is not truly zero but rather the concentration was undetectable.
(About the Author: Jeffrey Boggs is on analytical consultant with Aerosol Monitoring & Analysis, Inc., Hunt Valley, Md. Also contributing to this article were M.J. Cirri and B.E. Lippy of the same laboratory, and N.A. Leidel of the federal Centerfor Disease Control, Atlanta, Ga.
38 ASBESTOS ABATEMENT MAY/JUNE 1988
Asbestos Abatement The Solution
EUROCLEAN has developed a unique, patented system for the safe, efficient removal of asbestos and the safe, efficient clean-up of asbestos removal equipment. The main component of the system is a combination cyclone and cleaning filter. The cyclone separates out the heavier dust particles into a replaceable, removable plastic bag.
The FlipStrip Filter
The FlipStrip filter, a five stage cleaning filter, is an easily removable cartridge that traps the finer dust particles. Air enters through the core of the tubular FlipStrip filter and sets hanging strips in motion that agglomerate the microscopic dust particles into larger particles that work down to the bottom of the cartridge. After four more stages of filtration, the air leaving the filter is virtually clean -- the outside of the filter remains clean at all times and the filter can be handled safely. The five stage filtration process of the FlipStrip filter also enhances filter capacity and efficiency.
Plastic Bag
Intended and designed for heavy industrial use, the EUROCLEAN system easily outperforms statutory requirements and meets maximum permissible hygienic levels.
Since the FlipStrip filter and the cyclone are internal components, they remain completely clean and dust-free on the outside. This means that the FlipStrip filter and the plastic bag can be changed at any time without risk of contamination and without the need to wear protective garments. In addition, the FlipStrip filter outlasts conventional micro filters by a factor of ten times.
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for a .006 mm2 field area. The value of S for Method 7400, where the microscope field area equals 0.00785 mm8, was computed to be 12 fibers/mm2.
Having computed the values for LOD and LOQ concentrations, look again at the cumulative observed and expected frequency distribution for re-occupancy sample fiber surface concentrations (See Figure 5). The vertical arrows indicate the LOD and LOQ fiber concentrations of 6 and 13 fibers/mm2, respectively. As can be seen, we have observed sample con centrations less than or equal to LOD at a frequency of 45 percent and less than or equal to LOQ at at frequency of 72 percent. It appears, therefore, we have chosen the appropriate dis tributional model and confidence limits under the condition of low-level airborne concentrations.
The relationship for the required air volume Q, in liters, to detect a given concentration level, such as a re
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occupancy standard, is computed by the effective collection area of the filter used, times the fiber surface concentration LOQ equals S, divided by a given concentration we wish to detect (See Table 5). In this example, we are using P&CAM 239, i.e., a 37mm-diameter filter and S equals 13 fibers/mm2, where we must be able
to detect the typical re-occupancy limit of 0.01 fibers/cc. The computed required voume of air, Q, is 1112 liters.
Those familiar with the EPA guid ance for the limit of reliable quantifi cation of 0.01 fibers/cc using P&CAM 239 method will recognize that this Q of 1112 liters is somewhat lower than
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to LOD (N) fibers in 100 fields, where the true average count (n) is then the LOQ fibers in 100 fields. The 95 per cent probability is given by one minus the sum of all event probabilities from 0 to (N-l) events.
Unfortunately, the procedure to solve for the LOQ (n) is a "trial and error" series of computations. A less burdensome evaluation can be made from the statistical tables of relative expected frequencies of the Poisson distribution. By successively sum ming the expected frequencies given in these tables for several LOQ (n) values by increasing LOQ (n) plus 2, plus 3, etc., one can quickly home in on the N-l value approximately equal to .05 the 95. percent prob ability.
In our example, the LOD-N-4 fibers in 100 fields, the LOQ (n) was found to be 7.8 fibers in 100 fibers. Thus there is a 95 percent probabil ity of counting less than or equal to LOD-4 fibers in a single 100-field count, where the true average count of LOQ is 7.8 fibers in 100 fields.
Now that we have solved for LOQ fibers in 100 fields at the 95 percent detection power, we can use the rela tionship shown to compute the average surface fiber concentration, S, that would yield a count of 7.8 fibers in 100 microscope fields (See Thble 4). Here, S is in fibers/mm2 and the count field area is in mm2.
In this example, using the LOQ equals 7.8 fibers in 100 fields and the microscope field area of .006 mm2, we solve for S equals 13 fibers/mm2. This is now our value for the limit of quan titative detection, LOQ. It is necessary to solve for the LOQ fibers in 100 fields from the LOD fiber count which is a function of the microscope field area.
The importance of using the LOD fiber count for an individual micro scope field area is inherent to the logarithmic nature of the cumulative expected frequencies of the Poisson distribution. For example, we have computed the LOD fiber count based on 6 fibers/mm2, the 95 percent detection power, LOQ: and S for com monly used microscope field areas. In the case for P&CAM 239 method us ing a Porton Reticle with a 0.003 mm* field area, S was computed to be 16 fibers/mm2 not twice the value of S
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Tables
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qualitative detection, LOD. From our data set (See Thble 1), in fact, the 95-99 percentile occured at the sur face concentration of 6 fibers/mm*. Such clumping is a result of the limited classes available from the counting of either whole or half fibers only.
The comparison of our data set with the results obtained by the NIOSH Division of Physical Science and Engineering shows good agree ment. There is no significant dif ference between the means of the two data sets. However, the proposed LOD of 6 fibers/mm2 is based on the tested Poisson model. The normally distributed mean plus three standard deviations (or 99th percentile) has been given by NIOSH as the esti mated LOD for Method 7400.
The fiber count LOD in fiber/100 fields (See Thble 2) is a function of the microscope field area for counting (mm2) and the 95th fractile value for the distribution of background fiber surface concentrations for unexposed filters, or the LOD in fibers/mm*.
For example, for our laboratory us ing a microscope with a count field area of 0.006 mm2, the fiber count LOD is four fibers in 100 fields. There are two conclusions which can result from the comparison of the fiber count LOD to a measured fiber count that exceeds the fiber count LOD: With regard to quality control, any filter lot from which representative filters have a measured fiber count greater than four fibers in 100 fields (LOD) should be discarded. Also, four fibers in a 100-field count is the minimum total count that must be ob tained from any exposed filter sam ple before concluding the exposed
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filter has a significantly greater sur face concentration of fibers than an unexposed filter. (This may not always be the case as shown earlier.)
We now have the tools necessary for estimating a sufficient surface fiber concentration to yield a specified power of counting at least the fiber count LOD of fibers in 100 fields, for a given set of measurement condi tions (See Table 3). First, we assume a distribution of many 100-field fiber counts is adequately described by the Poisson distribution. Next, we can solve for the 95th cumulative proba bility on counting less than or equal
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portion of the curve--comparable to the previously shown background fiber concentration distribution--sep arately from the higher concentration portion from 9 to 23 fibers/mm* For the purpose of Chi-Square testing for fit of the two curves we therefore chose to have just one degree of freedom.
Under these testing conditions the Chi-Square measured value was less than the critical value at 50 percent. Thus we now have two separate tests of significant agreement with the Poisson distributional model using both unexposed and exposed filter fiber concentrations. These results provide the proper statistical frame work from which we can evaluate the limits of qualitative detection (LOD) as well as the limits of quantitative detection (LOQ).
Limits of Detection We have chosen the 95th percen
tile of the observed, Poisson distributed, unexposed filter fiber concentration for the limit of
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30 ASBESTOS ABATEMENT MAY/JUNE 1988
A striking feature of the data is the large frequency of zero concentra tions, 33 percent of the total. Addi tionally, the clumping of 0-2 fibers/nun2 results in the observed relative frequency of nearly 60 percent.
These results indicate that back ground fibers concentrations might be adequately described by the Poisson distribution. The Poisson distribu tional model also seems appropriate based on the low mean value of 2.3 fibers/mm2 with a high coefficient of variation of 87 percent. The purpose of fitting a Poisson distribution to numbers of rare events is to test whether the events occur independ ently with respect to' each other. If they do, they will follow the Poisson distribution.
We have tested this observed dis tribution as well as the observed fre
quency distribution of re-occupancy sample fiber concentrations against the expected Poisson frequencies and evaluated the comparison by the ChiSquare test for goodness of fit. The plot of cumulative, relative observed and expected frequencies of fibers concentrations (f/mm2) from unex posed filters shows good agreement throughout the range of measured values (See Figure 3).
The shape of the Poisson expected frequency curve is completely defined by the mean of the observed values. The Chi-Square test value was less than the Chi-Square critical value at 10 percent with four degrees of freedom and by interpolation was ac tually less than the critical value at 30 percent. This significant agreement, therefore, supports our hypothesis that the observed fiber concentrations of unexposed filters are Poisson distributed.
Having adequately described the Poisson distribution of background fiber concentrations, we have ran domly selected 100 re-occupancy samples and plotted the observed fre quency distribution for fiber concen trations in fiber/mm2 (See Figure 4). Not too surprisingly, .as predicted from these presumed clean air en vironments, there is a relatively high frequency of low, 0-3 fibers/mm2, concentrations accounting for more than 20 percent of the distribution with more than 50 percent being less
than 8 fibers/mm2. The observed mean for this data set
was 8.8 fibers/mm* with a coefficient of variation of 76 percent. These sam ple concentrations are measured from filtered volumes of 1000-1500 liters and have not been corrected for background fiber concentrations. With such a high coefficient of varia
tion and a relatively low total fiber concentration, we felt this observed frequency distribution might also be Poisson distributed.
Again, we have plotted (See Figure 5) the observed and expected cumu lative frequencies of the fiber concen trations in fibers/mm2. We wished to evaluate the low-levl concentration
MAY/JUNE 1988 ASBESTOS ABATEMENT 29
Figure 2
single accepted way to handle them. One method is to obtain from the
analytical laboratory the least amount of the contaminant which the analy tical method can detect. This value is then used to determine the least detectable concentration in the amount of air sampled, and is then substituted for all zero values. By resolving the r roper distributional model, one can hen apply the ap propriate probability function, and thereby the detection power, to the analytical methods. Methods and Results
We have accumulated data over the past several years (See Figure 1) for fiber counts on unexposed filters as a routine quality control measure for background fiber surface concentra tions. The observed frequency distri bution of these fiber concentrations, shown as fibers per square millimeter, was obtained from phase-contrast microscope counts using the NIOSH analytical methods P&CAM 239. Some 100 separate factory lot num bers of 37mm-diameTer, celluloseester membrane filters have been analyzed with a microscope optical system using a Patterson-Globe graticule that has a calibrated field area of .0062 square millimeters.
Figure 3
28 ASBESTOS ABATEMENT MAY/JUNE 1988
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