characterization of the pattern and level of exposure.

		MR. KING:  This is Mr. King.  Just for point of clarification, I
believe that the analyses that both URS and Environomics did basically
were using the exposure assessment data that OSHA had prepared and not
separate data from individual industries.  They weren't challenging
OSHA's exposure data as reflected in the Preliminary Economic Analysis.
I just asked them to confirm; is that correct?

		MR. WAGGENER:  That is correct.  In the URS estimate, we used exactly
what OSHA had for the percentage of overexposed workers.

		MS. SEMINARIO:  So in some cases, for that particular item with
respect to the exposure distributions and numbers of workers, you relied
upon OSHA's data.  But when you looked at other areas, as far as a
number of workers that might be impacted by a particular control, you
developed your own estimates.  Is that correct?

		MR. WAGGENER:  Everyone's different, okay?  There's no simple answer
to that question, other than if we talked to individual plants and to
find out how many workers.  I'll give you a perfect example.  A perfect
example in my presentation, I talked about the enclosed cabs.  In our
interviews and in our surveys, that information would only be one person
per cab per shift; that was information that was gleaned from that
information, and we used that in our model.

		MR. KING:  Also, just one other clarification.  Although they were
using, starting with OSHA's exposure data, they did make adjustments in
doing the costing.  For example, I think Mr. Waggener referred to the
fact that because of the switch to the ISO/CEN sampling protocol, they
assumed that the number of workers who were going to be exposed above 50
would be higher than what OSHA had assumed because the greater dust
collection.

		MS. SEMINARIO:  Okay.  Thank you.  Just returning back to the survey,
I understand that these were sent out confidentially and returned
confidentially.  But if it would be possible to provide the results of
the survey with the identities masked, so that there's some sense of
what the underlying information that was used to make this assessment, I
think that would be very helpful.  You folks did an awful lot of work.
And so getting at that level of information, I think, would just be
helpful to all of us.

		One set of questions for -- going back to Mr. Sessions, you
indicated in your statement that it was your view that OSHA should
include in the cost of this standard the cost of coming into compliance
with the current 100 µg PEL.  Is that correct?

		MR. SESSIONS:  I'd like to put a bit of a distinction on that.  For
the purposes of economic impact assessment, I believe it's important to
consider the full costs, including both the cost to come into compliance
with the current PEL and the cost incrementally due to the reduced PEL.
For economic impact analysis in particular, it's important to calculate
the full costs.

		A second point that I made is that in attempting to calculate the
incremental costs of the reduction in the standard, I believe that OSHA
substantially missed the mark in what the Agency attempted to do.

		MS. SEMINARIO:  No, I understand that point.  But the cost of reaching
100, that's an obligation that exists now and has existed since 1971 in
general industry; is that correct?

		MR. SESSIONS:  Correct.

		MS. SEMINARIO:  And I think as was in your statement or a number of
the comments here, that there are perhaps 30 percent of -- I wasn't
clear if it was samples, establishment, workers that are above the
existing PEL.  So there's a substantial amount of noncompliance
currently, correct?

		MR. KING:  According to OSHA's IMIS data, that appears to be the case.

		MS. SEMINARIO:  And according to the exposure estimates that you used
in your economic analysis.

		MR. KING:  Well, those are just taken from OSHA.  Those are OSHA's
estimates.  We didn't make any estimates.

		MS. SEMINARIO:  Okay, so based upon that, there's a substantial amount
of noncompliance.  Is it your expectation that employers who are not now
complying and haven't complied for 40 years with the existing PEL, that
all of them will now comply with the current PEL?

		MR. KING:  That they will be able to?

		MS. SEMINARIO:  No, that they would, that they would in terms of the
actual economic analysis of compliance, not the theoretical, the actual
compliance.  If 30 percent are out of compliance now, would you assume
that all of them will comply with a new PEL?

		MR. KING:  No, I think the analysis that Mr. Waggener presented dealt
explicitly with that point.  He said, given the fact that after 40
years, a substantial of employees still seem to be exposed above the 100
µg/m3 PEL, he does not believe that everyone is going to be exposed
below this proposed 50 µg/m3 PEL.  Indeed, we assume they'll be more
people exposed above 50 µg/m3, if that is adopted as a standard, than
OSHA assumes.  OSHA, I believe, assumes only 10 percent would be exposed
above 50.

		JUDGE SOLOMON:  Two things.  First of all, Mr. King, you didn't
identify yourself again.  And, number two, why are you speaking for the
gentleman who is seated to your left?

		MR. MORRILL:  If I may, this is Mr. Morrill.  He is functioning as
sort of our quarterback for answering the questions.  And so, we'll work
through Neil, and then if there are other responses, then certainly we
can refer to others.

		MS. SEMINARIO:  But in costing out the -- your cost estimates on the
rule, we're costing out the proposal to get to 50 for all the workers in
general industry who are subject to the standard.  Is that correct?

		MR. WAGGENER:  What we -- excuse me, Your Honor, Mr. Waggener
speaking.  What we did was we determined for the people that were over
100, we also determined what it would take to get to 100, assuming the
world was perfect, okay.  And the reason they're not below 100 now is
because the world is not perfect.

		And I want to stop right there and say these people are not
necessarily out of compliance.  They -- for 40 years, they've been
trying to get into compliance, installing equipment, trying things in
different jobs, and they haven't been able to reach to 100.  So they --
most of those people, if not all, are in respirators to be able to
comply.

		And oftentimes, not always, but most of the time, there's some
agreement with OSHA on a local basis with inspectors and so forth,
either formally or informally, for that to occur.  And that's what's
been happening in the real world.

		MS. SEMINARIO:  So in the real world, there is no noncompliance.  It's
just that it's been infeasible for them to get to 100?

		MR. WAGGENER:  I didn't say no.

		MR. MORRILL:  Jack, if I could just jump in quickly.  Your Honor, I'm
just wondering, given the fact that OSHA also wants to ask a number of
questions, we want to make sure that we keep the questioners to --

		JUDGE SOLOMON:  You know, I'm a trial judge.  And if you did that in
my -- one of my trials, I'd probably refer you over to the Bar
Association.  So he was in the middle of making an answer, and you
stopped him, and you're not to do that, okay?

		So if you can answer, go ahead.

		MR. MORRILL:  I'm sorry, I'm -- I was just --

		JUDGE SOLOMON:  Let him answer the question.

		MR. MORRILL:  Okay.

		JUDGE SOLOMON:  He was just -- he was answering the question.

		MR. MORRILL:  I understand that, but we're trying to also manage the
time, given the instructions that you --

		JUDGE SOLOMON:  I've already ruled.

		MR. MORRILL:  Okay, thank you.

		JUDGE SOLOMON:  Okay, go ahead.

		MR. WAGGENER:  All right.  Yeah, thank you, Your Honor.  With regard
to the cost model, we put in what we believed would be controls to
better approximate the 100.  And then we put in controls we estimated it
would take to get to 50.

		It is a model, and you have to recognize it's a model.  And that's
what we did.

		MS. SEMINARIO:  Thank you very much.

		MR. WAGGENER:  Okay.

		JUDGE SOLOMON:  Who's next?  Mr. Comai?  State your name and spell
your last name.

		MR. COMAI:  I'm Andrew Comai.  Last name is C-o-m-a-i.  I had a
question for the industrial hygienist who worked -- who reported out on
the preparation of the samples.  I just wanted to know what was the OSHA
method used in these labs?  Were they all the same method?  What was the
number?

		MR. BAILEY:  The -- each of the labs was certified by AIHA to -- and
I would -- they're using NIOSH 7500, I would think.

		MR. COMAI:  7500.  So in that method, is there an acid wash procedure
that's available?

		MR. BAILEY:  Yes, it is an option.

		MR. COMAI:  It's an option.

		MR. BAILEY:  I do not know --

		MR. COMAI:  -- lab.  So you generated some samples in a -- you rigged
up some samples, I'm just going to say -- use the word "rigged" with
non-silica material?  Or you said kaolin and feldspar, was that --

		DR. LEE:  Rich Lee.  Yes, half the samples were pure silica and half
the samples were either 50/50 kaolin or 50/50 feldspar with silica.

		MR. COMAI:  So why didn't you report out the differences between the
pure and the obscured samples?  Was that --

		DR. LEE:  That data is in our report.

		MR. COMAI:  Okay.  It just wasn't up on the slide, so I wondered
what --

		DR. LEE:  Yeah, yeah, it just wasn't up on the slide.

		MR. COMAI:  Was there a difference?  Did that really generate some of
the randomness or chaos in the lab?

		MR. BAILEY:  This is Kelly Bailey.  I believe that the error
associated with what we saw in the -- all the variability we saw in the
samples, regardless if it was pure silica or not, would probably cloud
that difference.  So it was -- basically, there was not much difference
between --

		MR. COMAI:  So was it regardless of whether it was unpure or pure
silica.

		MR. BAILEY:  Yeah, I think that what was going on there was so large
that any kind of distinction like that would probably be masked.

		MR. COMAI:  You also did some size selection, so you took out larger
particles.  Why did you do that?

		DR. LEE:  Just to avoid size effects, so that we're attempting to
mimic the size that the cyclone is picking up.

		MR. COMAI:  So was there a lognormal distribution in the size you did?
 Did you have --

		MR. BAILEY:  In terms of the?

		MR. COMAI:  The log -- the particle size, was the particle size
distribution lognormal when you --

		DR. LEE:  Lee.  We did not measure particle sizes independently.  We
just did a sedimentation --

		JUDGE SOLOMON:  Just to clarify things.  That was Mr. Lee.

		DR. LEE:  I'm sorry, Rich Lee.

		MR. COMAI:  So you didn't do a size analysis of the raw material that
you were putting down on the sample filter paper?

		DR. LEE:  For the Min-U-Sil, there's a normal size distribution.  For
the others, we did a cut to respirable size.

		DR. LEE:  Cut using air?

		MR. COMAI:  No, cut using liquid sedimentation.

		DR. LEE:  Sedimentation, okay.

		MR. COMAI:  So did you ever control for -- with those labs, did they
report out on how many times they did an acid wash, if they got
something from -- something comes in the mail, we're not telling them
where it's from, they're having some trouble determining it, what's --
wouldn't you have to ask them, or they would report back?

		MR. BAILEY:  This is Kelly Bailey.  We did not inquire as to what they
did with respect to their treatment of the sample, whether they
acid-washed it or not.  It is basically like if they felt like they
needed to acid wash it to perform the analysis, then they would have.

		We were more interested in it the XRD analysis and also that -- how
the sample preparation, with respect to whether a muffle furnace was
used, a plasma asher was used, or THF was used.  And in the process of
doing this project, THF was found not to be usable, perhaps because of
the 0.8 micron pore size.

		MR. COMAI:  So when the lab felt like doing something, wouldn't --
that would depend on where the material came from.  So there's a
communication between the lab and the facility.  This is coming from a
foundry with -- or this is coming from a smelter.  These are the types
of contaminants.  This is how you should treat it.  This is how we've
treated it in the past.  None of that kind of discussion happened.  And
so, variability would increase if people -- if you're not telling
people where the sample comes from, it's -- they're guessing, in
essence, as to how they should treat that sample, how many times they
should wash it with acid.

		MR. BAILEY:  This is Kelly Bailey again.  I think that if a lab saw
the filter and had difficulty in getting the peaks that would indicate
calcite or something like that, then acid washing would be the
appropriate thing to do.

		MR. COMAI:  But you never controlled for that in your report.  You
don't know how many times they did it.

		MR. BAILEY:  No.  Many samples come in without a designation of where
they're from.

		JUDGE SOLOMON:  Do you have any more questions?

		MR. COMAI:  Yes, I do.

		JUDGE SOLOMON:  How many more questions?

		MR. COMAI:  Different topic, one question.

		JUDGE SOLOMON:  Okay.

		MR. COMAI:  The -- you mentioned the -- this is the economic
analysis where you have -- you mentioned the -- maybe an air
conditioner for a cab on a front loader that's loading dusty granite.
You assume that there's one person per control, and then each person has
their own control, and that was worked into your cost estimate?

		MR. WAGGENER:  To be specific, we assumed that there would be one
worker in that cab per shift.  And that -- if he was an overexposed
worker, that cab was controlling him.  If there were two shifts, then it
would be one person on each shift, so --

		MR. COMAI:  So sharing one front loader wasn't in your cost estimate?
Multiple people using the same cab --

		MR. WAGGENER:  Well, it was, but it was one person per shift.  So if
it was a two-shift operation, then it would be two people that were
being covered.

		MR. COMAI:  So is it when you do a control -- so a local exhaust
ventilation control, where -- do we estimate a separate control for
each person when, say, a larger shop floor exhaust ventilation system is
installed?  Do you again assume that each person has their own --  Each
person has their own --

		MR. WAGGENER:  No, no.  The example I gave was -- that's a very
specific example.  That's why we did the binomial distribution to
determine, in some cases, there may be four workers covered by one
control at a device, say a grinding operation.  At another facility,
there may be one person controlled by that.  It depends on the facility
size.

		MR. COMAI:  So what was the maximum number of people controlled --

		JUDGE SOLOMON:  Mr. Comai, I'm going to let you go, okay?  You're
over.

		Next, Mr. Frederick, come forward, please.

		MR. FREDERICK:  Thank you, Your Honor.  I'm Jim Frederick with the
United Steelworkers Union.  It's F-r-e-d-e-r-i-c-k.  A few questions for
the panel.  Did URS use only certified industrial hygienists cost for
the cost data in the estimate of performing their monitoring?

		MR. WAGGENER:  Oh, no.  We have numerous engineers involved that do
this.

		MR. FREDERICK:  Can you clarify?

		MR. WAGGENER:  I'm sorry, I misunderstood your question.

		MR. FREDERICK:  For the cost itself, did you utilize the cost of a CIH
to perform the actual air monitoring calibrating the pump, hanging it on
a worker, observing the sampling?

		MR. WAGGENER:  I don't remember the exact, but we did not use just a
CIH, which would be the most expensive person.

		MR. FREDERICK:  I'd like to try to go back to the data that was just
being talked about, about the controls per worker.  If I understood this
correctly in the presentation this afternoon, there were, at some points
in your cost calculations, calculated to be eight controls -- up to
eight controls per worker into the cost estimate.  So am I understanding
that correctly?

		MR. WAGGENER:  That was an example that I gave -- a real-world
example where a specific job in a specific industry may have eight unit
operations, and one guy on a shift is operating all of those.  So there
is one person per eight controls.  That was a rare instance.  And
actually that did not -- I should emphasize, that example was not in
our model.

		MR. FREDERICK:  Okay.

		MR. WAGGENER:  We never used anything of that nature.  And that was
one reason I said we felt like our model was conservatively low in terms
of the cost estimate.

		MR. FREDERICK:  Okay.  And then the cost estimate of controlling
exposure to silica, the United Steelworkers represent workers in small
businesses, medium-sized businesses, and large businesses.  Some of them
are member companies of ACC as well as many other employer
organizations.  Almost exclusively, our employers say to us that they
wish to provide a safe workplace for our members.

		And item that I did not understand, and again, I read this differently
in your written comments than I understood in the presentation this
afternoon, that small employers will spend more than medium employers on
controlling the same hazard.  And, again, I read that differently in
your written, but I understood it to be stated as I just did in your
presentation this afternoon.  Did I misunderstand it this afternoon?

		MR. WAGGENER:  I don't think I said that, but I'm not sure.

		JUDGE SOLOMON:  We have a transcript.

		MR. FREDERICK:  Okay, fair enough.  That's all I have.  Thank you.

		JUDGE SOLOMON:  Okay.  Now we have NIOSH revisited here.

		MR. HEARL:  Thank you, Your Honor.  I'm Frank Hearl, H-e-a-r-l, from
NIOSH, Washington, D.C.  I have questions for Dr. Morfeld.  I didn't
want to make you come all the way from Germany without getting a few
questions.

		DR. MORFELD:  I hope so.

		MR. HEARL:  I want to ask a few questions about the sampling for dust
in Germany.  How do you sample for respirable dust in Germany?

		DR. MORFELD:  As it is done now or historically?

		MR. HEARL:  How about let's go with the --

		DR. MORFELD:  What is done now at the moment.  We use gravimetric
sampling, usually personal-based.

		MR. HEARL:  Personal-based.  Okay, is it using a cyclone?

		DR. MORFELD:  Cyclone, yes.

		MR. HEARL:  What flow rate does that cyclone operate at?

		DR. MORFELD:  So I'm not sure at the moment because this is not my
field.

		MR. HEARL:  Okay.

		DR. MORFELD:  I'm doing the epidemiology, but I can give you the
references.

		MR. HEARL:  Great.  And, historically, how was the sampling done?

		DR. MORFELD:  So typically there were a couple of different
instruments from precipitation and colorimeter used in the older times.
And, therefore, in our studies we did for the porcelain workers and for
the uranium miners, we did comparisons between the new instruments and
the old instruments in the labs, and at working places so that we had
those conversion factors.

		MR. HEARL:  Right, so the old sampling, was it done on a task-based
basis instead of full-shift?

		DR. MORFELD:  It was done on full-shift during regular working shifts
and done additionally on the different conditions in the labs.

		MR. HEARL:  Okay.  Was there an adjustment that was made for unsampled
periods when they would collect those samples?

		DR. MORFELD:  Yes.

		MR. HEARL:  And was that -- did they assume that the concentration
was the same over the whole shift, or did they assume zero for the
unsampled period?

		DR. MORFELD:  So I -- in that case, I would refer to the two papers
by Darmin and Gouldner (ph.) who described this in detail.  I can give
you these details.

		MR. HEARL:  And so, the estimates that were -- that you referred to
for the threshold value in your calculations in the presentation, were
those concentrations being reported in terms of current German samples
or, I mean, what was the basis of those estimates?  I'll just leave it
at that.

		DR. MORFELD:  So all instruments that were used, so of course, we
incorporated also the old values.  We had measurements in the '50s when
transformed to gravimetric data in the porcelain industry in some
workers in the range from 1 to 2 mg/m3.  So we used also these data.

		MR. HEARL:  Right, and so it was just done with a variety of
conversion factors?

		DR. MORFELD:  Yes.

		MR. HEARL:  All right.  So, actually, I came across -- I was looking
to try to find out how the sampling was done just on my own and in the
audience.

		DR. MORFELD:  I can give you --

		MR. HEARL:  And there was a paper by Sun,  Chen, Yang and Bochmann --

		DR. MORFELD:  Right.

		MR. HEARL:  -- that from -- it was called "Quantitative Assessment
of Historical Silica Dust Exposures among a Cohort of Chinese Miners."

		DR. MORFELD:  This is Chinese miners --

		MR. HEARL:  Correct, same one, correct.  And then, that one -- I
think they had the conversion factor between the German-type sampling
and the U.S. sampling was 1.31 times the U.S. sampling would give you
the German for copper, 1.5 for iron, 1.8 for tungsten, and 2 for
pottery.  Does that sound correct?

		DR. MORFELD:  Yes.  They made these comparisons with the U.S. samples
and with the German samples.

		MR. HEARL:  Right.  Was that the historical German samplers or the
current?

		DR. MORFELD:  Historical and the current.

		MR. HEARL:  Historical and the current, okay.

		DR. MORFELD:  As far as I remember, yes, both.

		MR. HEARL:  Okay, great.  That's what I had.  Thank you.

		DR. PARK:  Robert Park, P-a-r-k, NIOSH Cincinnati.  Another question
for Dr. Morfeld.  I think there's a fundamental flaw in the analysis of
threshold for silica.  The profile likelihood procedure is fine.  It's
from Dr. Olm (ph.) in Germany.  I've done it myself on hexavalent
chromium.

		The problem is using the proportional hazard model, which makes a
fundamental assumption, which is that there's an estimable non-zero
baseline risk.  There is not for silica.  The baseline risk is zero.

		So this says "consequences."  It means that the nuisance parameters
are very unstable.  In this analysis, it means that the estimate for the
hazard ratio will have a high variance.  It means that it is a badly
fitting model.

		Now, one way to make it fit better is to redefine some of the silica
cases as non-silica, as not having silica exposure, for example, by
applying a threshold.  In your optimum model, 17 percent of silica cases
now have no exposure.

		JUDGE SOLOMON:  Is there a question there, Dr. Park?

		DR. PARK:  How can you justify that procedure?

		DR. MORFELD:  So the first is, the Cox models break down if you have
no cases in the reference categories.  So this was an analysis done with
the continuous exposures.  And similar as in other analyses with the
lung cancers, with the continuous exposures, the Cox model can run.  And
we check that carefully.

		So we did not have any conversion problems -- problems with
convergency of the Cox models.

		DR. PARK:  It could still be a bad model, right?

		DR. MORFELD:  No, not necessarily so.  It has been shown that in a lot
of instances, the Cox model is the limit of a Poisson model, if you use
the same.  And this is often applied because this can do estimate in
absolute risks, not in relative risks.  So if the distribution of the
cases is not too skewed in such a way that there are large areas of
exposure without any cases, then you are not running into trouble with
this model.

		The second question, I think the other was the question of precision.
We did include a couple of covariates and also have thrown out these
covariates to see whether our estimates differ a lot, whether the
variances differ, but this was not the case regarding the threshold
estimates.  So it was rather stable.

		And the third question, I think, was on this 17 percent of silica
cases set to zero exposure after applying the threshold value.  This is
true.  So the problem is, in estimating thresholds, that usually the
people think that a threshold should be lower, or at least as high as
the lowest exposure of a case in a study.

		This is not the case if you use a statistical procedure estimating the
threshold.  So it can be that some of the cases then are lying below
this estimated threshold.  Usually if you -- we have got some comments
in between and discussions whether it makes sense to look at the lowest
exposed case.  But usually you have to rely then only on the one case
with his data and not on the complete cohort data.

		So this is what we tried to do with this procedure, use everything,
and of course, not rely on a single case.  So it is possible that some
of these cases, if all the radiographs are rewrote again, it would
become non-cases, and other non-cases would become cases.  So all this
is unstable, of course.  And, therefore, we need a procedure to estimate
the threshold that takes all the data into account, and then of course,
you can end up with a result that, if you apply the threshold, some of
the cases are below the threshold.

		DR. PARK:  The same problem exists with Poisson regression, by the
way.  I have two papers that I'll be submitting to the post-hearing.

		One other question, have you done this same analysis for lung cancer,
and what did you find?

		DR. MORFELD:  So the lung cancer, no, we did not.  So the lung
cancer -- relative risk of lung cancer is not elevated in the study.
So --

		JUDGE SOLOMON:  Well, if you didn't do it, you don't have --

		DR. MORFELD:  So we didn't do it.

		JUDGE SOLOMON:  You did?

		DR. MORFELD:  We didn't.

		JUDGE SOLOMON:  Right, so you don't have to answer the follow-up
question because you didn't do it.  Okay, thank you very much,
Dr. Park.

		So Ms. Lindberg?

		MS. LINDBERG:  I'm going to let Bill Perry take over here.

		MR. PERRY:  Sorry.  Thank you.  We do have just a few questions for
this panel, Your Honor, if we may.  I believe first to go will be Janet
Carter.

		MS. CARTER:  Good afternoon, Dr. Morfeld.  I appreciate you coming
all the way from Germany to talk to us today.  I just have a few
questions.  Mine are going to be health-based.

		There's been considerable testimony over the past week regarding
poorly soluble particles and the concept of overload, and a threshold
effect for inflammation leading to tumor genesis and nonmalignant
respiratory diseases.

		The European Centre for Ecotoxicology and Toxicology of Chemicals
recently released a follow-up report to the International Life Science's
workshop report on poorly soluble particles and lung overload.  Both
reports define poorly soluble particles in their evaluation as including
non-asbestiform talc, titanium dioxide, diesel soot, coal dust, and
carbon black.

		Now, while the ISLI study didn't specifically include silica, the
ECETOC report specifically excluded crystalline silica due to its
phytotoxicity and reactive surface characteristics.  I was wondering if
you were of this European industry report?

		DR. MORFELD:  Yes, I know it.

		MS. CARTER:  Okay.  I appreciate that.  Do you have -- how do you
think it applies to what we're talking about today?

		DR. MORFELD:  So this ECETOC report mainly deals with the overload
question.  The question is whether the transitional toxicology that is
used to translate results from rat studies to humans are reliable or
not.  We have a big discussion on this.  You may know that the MAK
committee in Germany has released a document on this, how to calculate
from rat overload experiment limit values for general dusts.

		And the ECETOC report is a parallel approach to view whether the
overload results from the rats are really reliable and can be
transformed into the smallest negative in the results about this.  They
said they should not use it for classification and should not use it in
the limit value assessment.  It is a major outcome of it.

		MS. CARTER:  Yeah, it actually went further to say that they shouldn't
use it for risk assessment either.  And ECE actually talked about that
as well.

		Your testimony also discussed the concept of general dust causing
nonmalignant respiratory diseases.

		DR. MORFELD:  Right.

		MS. CARTER:  And you gave an example of carbon black, and I was
wondering if you thought it was appropriate to use carbon black as a
surrogate for crystalline silica for such diseases.

		DR. MORFELD:  No, this was not for crystalline silica.  It was one of
the dusts that we believe that it was -- in the old terminology, more
or less a nuisance dust.  So it's granular biopersistant, but of course,
carbon black is nanostructure, there may be something else going on.  So
there are other studies, there's titanium dioxide -- pigmentary
titanium dioxide and other use.

		So we see that all this dust has some impact on lung function, in
particular.  We see some impact on chronic bronchitis, so it is
difficult, in particular in those studies, that this diatomaceous earth
workers and others, that where we have mainly general dust measurements,
but only crude information about the crystalline silica content, then to
use only this crude information about crystalline silica content to
calculate crystalline silica concentrations and to relate these to the
nonmalignant respiratory diseases, and then forgetting about the main
information about the general dust.

		This is the point that I made.  And all these papers, we have talked
ECETOC particulates paper, or look at the MAK document.  What they are
saying is be careful.  The general dust itself is no nuisance dust.  It
causes lung function change.  It causes chronic bronchitis and things
like that.

		MS. CARTER:  Your testimony also talked about providing a reference
list that OSHA should look at.  One of them happened to be the IARC
monograph 2012.  The IARC monograph actually specifically talks about
three mechanisms.

		The primary mechanism could be an inflammatory response, but it
actually talked about two others which were derived from in vivo data.
And they felt they were substantiated by in vitro data.

		Have you looked at these alternative modes of action in consideration
of your evaluation for crystalline silica?

		DR. MORFELD:  Yes.  See, I attended that workshop, and I was also in
that meeting.  And there was a long debate about the direct genetic
effects.  And you see in the figure that we're drawn, that this is a
dotted line because it was not clear whether there was anything going
on, and they don't want to exclude that.  And if I remember correctly,
the line is dotted.  And this was a result of these discussions.

		And I'd just like to refer to this Borm paper, which I think is really
interesting because they try to make a quantitative comparison, not just
some qualitative things, quantitative comparison where the inflammation
and direct genetic effects appear on a similar level of dose.  So they
found out that there is a ratio of about 50 between them.  So
inflammation is always going on before there can be a genetic effect.
This was the general message.

		MS. CARTER:  Well, I'm glad you brought up the Borm study because that
particular study was actually extrapolating in vitro data to in vivo
data.  And those specific authors, actually two years prior, had
published a study saying that it's really not appropriate to do those
type of calculations.  So I was wondering what you thought about that,
about the limitations of those type of extrapolations from in vitro to
in vivo to symmetric calculations.

		DR. MORFELD:  Yes, I know the groups -- this is a group of Ken
Donaldson involved from Edinburgh.  They said they should be careful,
but there is a paper with Ken Donaldson and Overdurst (ph.) on it, and I
think Borm also, where they tried together with Tran (ph.) to calculate
coming back to the general dusting, whether the in vitro data and the in
vivo data in rats come to the same conclusion about those, that is a
minimum necessary to lead to inflammation.

		So I know that they are critical about this, but there are two
implications where they try to overcome this missing link between in
vitro and in vivo.  So it's not so that they are totally against this.

		MR. PERRY:  Just testing the microphone back here.  I think Steven
Schayer has a few questions.

		MR. SCHAYER:  Oh, yes.  So, Dr. Morfeld, I just have a couple of
quick questions for you.  So the first was just about the cohort and the
follow-up period in your study.  So I was just wondering, so were all of
the 17,644 employees followed up through 2005?  And if so, how often was
each worker assessed for silica during the follow-up period?

		DR. MORFELD:  Yes, they were followed up through that because it --
you see, if you go to the paper, it is a little bit more complicated
because in mortality, you can usually define an end date, up to -- that
the follow-up is preceded.  If you do it for morbidity study, you have
to take into account the last information you have about morbidity.

		So this must be sent at the endpoint of the last radiograph.  We did
so.  And all the person-years reported in, correctly sends it at the
last radiograph we had available.  So there are usually no radiographs
available, just for a few exceptions, but you can forget about it beyond
working at the companies.  Usually all these radiographs are taken
during being at work.  So -- but we sent it exactly, so it does not
that we expanded the person-years up to the end of the mortality
follow-up.

		I don't know whether you are alluding at that problem.

		MR. SCHAYER:  Okay, thank you.  The other question I have is a little
different.  And it was more on did you look at all at uncertainty in the
exposure assessment and the impact it might have had on your study?

		DR. MORFELD:  So we did not incorporate, as we said in the discussion
sector, and a formal uncertainty analysis on that.  So we used the data
as is and tried to find out the threshold value with confidence limit
based on this uncertainty that is then reflected in the confidence limit
of the exposure data.

		What could be done in future work is, of course, that you add
additional errors to the data as reported and documented in the study.
But the exposure assessments were done independently from any
information about the response.  So this is where we started from, and
so this is the very best first information we had.  I agree that this is
one step we can move forward.

		MR. SCHAYER:  Great, thank you.  One other question I had.  Did you
consider at all or look at an ILO category of 1/0 or greater?  I know
you looked 1/1, and we were wondering, you know, what effect you think
looking at 1/0 might have on the results of the power to detect a
threshold?

		DR. MORFELD:  So we are unable to do so because after explaining a
little bit about the process, we are running through to reread the
radiographs.  We have 120,000 radiographs that were originally read by
physicians responsible for the insurance company in Germany, doing all
this medical screening.  It is an insurance company of the employers, a
specific organization in Germany, we have so-called BGs, they are doing
this.

		So when we had all this data documented, we know from a lot of studies
we did before in coal mining and in other settings, and the UK has the
same information, that you do not simply pick up the information as it
is given in the documents because it can be very misleading.  So we try
to reread this.

		But imagine if you have 120,000 radiographs, who will reread this at
least two times?  So that is impossible to do.  So what we started is we
draw a random sample, and then try to find out whether we can rely on
the data as given or not.  And we find out if the data says it is
negative, you will never find a 1/1.  This is what the result of this
was.

		So we then went back and used all originally categorized 0/1, 1/0, and
higher, and reread all these radiographs independently by B readers.
So according to this procedure, this two-step procedure, we are unable
to identify the 1/0 as an endpoint in our study.  For this, we have to
reread all the radiographs.

		MR. SCHAYER:  Okay, great.  And my last question was just, and I don't
know if this is possible, but we were wondering if you'd be willing to
make any of the raw study data available for other people to take a look
at.

		DR. MORFELD:  In principle, yes.  I personally have no problem with
this, but this, of course, has to be discussed with the sponsor and all
others involved.  You know, we have a lot of trouble in epidemiology in
Germany and in Europe with data protection discussions.  They are really
complicated.  And it is not only on the owners of the data or from the
companies, but it is more or less for the data protection people.  You
have to be -- personally, I mean, I have no problems with this.  So if
there is a solution, yes.

		MR. SCHAYER:  Okay, thanks.  Yeah, maybe if you could look into that,
I know we'd like to see it.  But if not, that's okay, too.  Thank you.

		MR. PERRY:  Tiffany DeFoe.

		MS. DeFOE:  My questions are for Dr. Morfeld also.  Dr. Morfeld,
thank you for sharing your study with us.  It's very interesting.

		There are a couple of areas of information that aren't reflected very
completely, either in Dr. Mundt's paper that you based the analysis on
or in yours.  And I'm wondering if you might be willing to submit more
information on these in a post-hearing comment.

		One of them, Steve already touched on, would be a more complete
description of the follow-up for silicosis morbidity, how it was
generally conducted in the industries where it was conducted -- or in
the facilities, and the extent of it over all, a description of what it
looks like with the cohort, if that makes sense.

		And the other area of information that would really help us to have
more detail on is the annual exposure means that served as a surrogate
for concentration and urinalysis.  In particular, well, if I had my
wish, I would request for each individual in the cohort their case
status, their highest annual mean exposure in the work history, and
whether or not they were a worker who had probably prior exposure.

		And if that's too much to ask for, because I know that's a lot of
data, then simply for the cases, the highest annual mean exposure in
their work history and whether they were a worker with probably prior
exposure.

		DR. MORFELD:  So the first question was, if I remember correctly, on
the silicosis and the mobility follow-up.  So usually, in Germany,
according to law, the workers are invited to get radiographs after
silica dust exposure after every second year.  So were invited for a
radiograph, and these radiographs were read by physicians and stored and
documented.  So this was the basis of our analysis.

		So we had a radiograph on the average of about every second year for
every worker.  And so we followed up on the incidence of silicosis with
this process.  Yeah, so, this is the basis.

		Then, your second question, I think, was about the annual mean
concentrations, and that was estimated.  And do you want to know
whether -- how this relates to the shift values or whether there is
more uncertainty involved or what are you addressing?  Or do you want to
have numbers or --

		MS. DeFOE:  Yes, I'm actually asking for data for --

		DR. MORFELD:  Yes, so the -- I think most of the numbers are
published in the Bick et al. paper.  I don't know if you have that.  I
think I've got this in the docket.  It's published and, of course, if it
is possible, if you ask specific things, we can do additional analysis
to show this.  So yeah, I don't have a problem with this.

		But I think the major things are for the jobs, and the distributions
are published.

		MS. DeFOE:  Yes, Bick et al. did publish the information that they
calculated.  But the data that I'm asking for has to do with the annual
mean exposures by individual.

		DR. MORFELD:  Yeah.

		MS. DeFOE:  Because I think that this would help us get a better
handle on how -- on the implications of your analysis.

		DR. MORFELD:  Yeah, for the -- yeah, so what I published were the
cumulative exposures, yeah, and you want to have all -- annual
distribution of the annual exposure estimates.

		MS. DeFOE:  No, what I would like is for -- ideally for each
individual in the dataset.

		DR. MORFELD:  Yeah.

		MS. DeFOE:  Case status and their highest annual mean exposure.

		DR. MORFELD:  Yes, I can --

		MS. DeFOE:  And their work history.

		DR. MORFELD:  Yeah, this is not published, right.  I can do this.

		MS. DeFOE:  Thank you.  That'd be terrific.

		DR. MORFELD:  Yeah.

		MS. DeFOE:  Secondly, looking at Table 3 in your paper, just a moment,
this is where you were looking at the effects of different offset
parameter choices on your model.  And it seems -- the choice of offset
parameters seems to have a strong effect, certainly on the confidence
intervals around your threshold estimates.  And in one case, on the
threshold estimate itself, with -- apart from your main model, the
choice of offset parameters seems to lead to fairly wide confidence
intervals.

		And I'm wondering why does the choice of parameter have such a strong
effect on the model results?

		DR. MORFELD:  Yeah, so this is interesting because I've got this
question already a couple of times.  So the -- we used the log
transform of the data because some of the workers had exposures of zero.
 You can't directly apply the logarithm, so you have to put some offset
in.

		And you can go to textbooks of statistics that discuss what kind of
offset should be used.  And if you go to the book I cited there from
Broyston (ph.), you get the information that you should identify the
smallest unit of change of interest that is occurring in your exposure
data.  And this should be used as the offset.  We used this from the
textbook.  We did not estimate this offset.

		We followed that recommendation and put that in.  This is exactly the
.01, which leads to our main model we are working with.  But having seen
this in our group, we discussed, of course, that we then just relied on
this recommendation coming from the textbook.  And then did sensitivity
analysis with other epsilons, with other offsets.  This is where the
table comes from.  So it is not finding out which epsilon fit it best,
but just doing a sensitivity analysis.

		So we defined a priori what is our model according to the textbook and
then did the sensitivity analysis.  And the interesting finding is, if
we follow the recommendation, the AICs measuring the goodness of fit
were best.  So in all other cases, it gets worse in two directions.  One
is that the general fit of the model went down, measured in the AIC, and
the confidence interval got wider if we used an epsilon not following
the recommendation.

		You see, it did not -- perhaps there's a misunderstanding.  I tried
to make it clear in the paper.  We started with an a priori model
following the recommendation from the textbook, and later on, just
checked whether other epsilon values would lead to better fits against
the recommendation.  But this was not the case.  Therefore, we stayed
with this model as the best.

		JUDGE SOLOMON:  What page of the -- of his --

		MS. DeFOE:  That is one Page 1031.

		JUDGE SOLOMON:  Which is different pagination than what we --

		MS. DeFOE:  Of his article.

		DR. MORFELD:  This is all talking about the article and the table --
the article.

		MS. DeFOE:  And so you select -- you stuck with the original --

		DR. MORFELD:  Yeah, so if we -- so the interesting thing is we used a
priori the recommendation coming from the textbook, what kind of offset
we should choose.  We used this and did the calculation.  And then
sitting there and discussing, they just said okay.  This is just a
recommendation from the textbook.  Let's do a sensitivity analysis.

		So we put in other offsets.  And the finding was that we got the best
response measured in AIC as goodness of fit when we followed the
recommendation from the textbook.  So there was no indication that we
should change our a priori model.

		MS. DeFOE:  And did you elect to use a log transform on the exposure
data and to retain that particular offset parameter based on the AIC
value, based on model fit?

		DR. MORFELD:  No, we did not so.  So we did not decide on the offset
on the basis of goodness of fit.  We used it as a recommendation from
the statistical textbook.  And then, just did a sensitivity analysis,
whether this was a good recommendation with a view to our data, and it
came up, yes, it is because other offsets led to worse fits.  So,
therefore, we stick with the a priori model.

		MS. DeFOE:  Yes, thank you.  And the other part was about your choice
to log transform the data.  Did you choose that due to the model fit, or
was there another -- was there a different reason that you chose that?

		DR. MORFELD:  Yes, we also used the linear models.  We described this,
but the fit was so worse in comparison to the log models that we stick
with that.  There were a lot of recommendations going to that.  If you
go to Kyle Steenland, he always used the log because he found out that
the goodness of fit is far better if you take logs.

		MS. DeFOE:  Thank you so much.

		JUDGE SOLOMON:  Mr. Perry?

		MR. PERRY:  We'll play a little musical chairs here, if we may.  And
somebody take this before I get feedback.  Thank you.  Brian Albrecht
from our Salt Lake laboratory.

		MR. ALBRECHT:  Thank you.  The first question I have is for Paul
Scott.  In your written submissions to the docket and in your oral
testimony, you pointed out that OSHA had made a calculation error in
Table 4-B9, and thank you for catching that.

		And you also recalculated the means and the relative standard
deviations for sample loadings less than 70 µg.  Did you also
recalculate the means and RSDs, for example, for loadings greater than
70 µg?

		MR. SCOTT:  No, I did not.

		MR. ALBRECHT:  Okay.  I've got a few questions for Mr. Lee and
Mr. Bailey.  In your presentation today, you showed us some data where
there were six samples that R.J. Lee had analyzed with recoveries of 94
percent and an RSD of 9 percent.  But I've reviewed the docket
submission, and I don't know what the loadings were for those samples.
And --

		DR. LEE:  Those were the ones with the graphs?  I'm sorry, Rich Lee.

		MR. ALBRECHT:  Yes.

		DR. LEE:  The ones on the left, I think, if you look at the graph,
were 20 µg, and the ones on the right -- there were two graphs on each
slide.  The ones on the right were 40 µg.

		MR. ALBRECHT:  Oh, no, I'm sorry.  I'm referring to an earlier slide.
I believe it was the eighth slide, where it was just a general overall
accuracy and precision.

		DR. LEE:  If it was the original -- I think two samples at each of
20, 40, and 80.

		MR. ALBRECHT:  Oh, okay.  Then in the other data that was also
presented, and now I am talking about the slides that you had previously
thought, that there were four samples at 20 and there were four samples
at 40.  And I'm also looking in the docket submission for data for
these.  Could you supply to the docket in your post-hearing comments the
data for the preparation of these?

		DR. LEE:  I'm sorry, can you repeat that?

		MR. ALBRECHT:  In your presentation today, there are several sample
results that have come up, all of which were analyzed by R.J. Lee.  But
I don't see the preparation data for those samples anywhere in the R.J.
Lee submission.  So I'm curious to know if you could submit your
information on how those samples were prepared.

		DR. LEE:  Certainly.  They would've been prepared in the same way as I
described, but I can certainly --

		MR. ALBRECHT:  So they would've been prepared in the same way as the
other 100 --

		DR. LEE:  As the other 150.

		MR. ALBRECHT:  So if that is the case, then when did you choose to
compare to nominal values rather than actual values?

		DR. LEE:  Because the -- we had not yet received the actual -- the
code translating from actual to -- from nominal to actual.

		MR. ALBRECHT:  All right.  You discussed somewhat about how the
laboratories were selected to perform these analyses, and it was
laboratories were selected based on geographic region and capability to
use an XRD instrumentation.  Is that correct?

		MR. BAILEY:  That's partly correctly.  I mean, we also -- was an
AIHA-certified lab using the latest certification criteria of April
2010.  They had to use XRD.  They -- eventually found out we had to
have muffle furnace.

		MR. ALBRECHT:  Well -- and that's the point that I'd like to clarify.

		MR. BAILEY:  This is Kelly Bailey talking, by the way.

		MR. ALBRECHT:  Thank you, Kelly.  I'd like to clarify that, as well.
So some samples were sent to laboratories that did not use a muffle
furnace.

		MR. BAILEY:  From the original study, we did not expect that they
would have trouble dissolving the filter.  So we didn't really take into
account whether they had a muffle furnace or were using chemical.

		MR. ALBRECHT:  Okay.  And is there data for those samples and the
preparation of those samples, as well?

		MR. BAILEY:  They could not run a silica analysis because they could
not dissolve the filter.

		MR. ALBRECHT:  I understand that there's no result data, but is there
data for the preparation of those samples that were not included in the
result set?

		MR. BAILEY:  Oh, from R.J. Lee --

		MR. ALBRECHT:  Yes.

		MR. BAILEY:  -- the preparation -- yes, I believe there is.

		MR. ALBRECHT:  Could that be also submitted to the docket?

		MR. BAILEY:  Certainly, but there's no laboratory result.

		MR. ALBRECHT:  I understand that.

		MR. BAILEY:  Okay.

		MR. ALBRECHT:  With respect to the fact that these PVC filters were
not soluble with the chemical treatment THF, I'm confused as to how a
physical dimension like pore size would affect the solubility of a PVC
filter.  Can you speak to that?

		MR. BAILEY:  That is only speculation, and we do not know why they did
not dissolve.  But in both cases, the lab used THF.  Maybe perhaps
there's less activity when you have a small pore size.  They're probably
used to dissolving these 5 micron pore filters in, let's say just for an
example, 30 minutes, and this one may have to take an hour to do.  I
don't know the -- why they did not dissolve.

		MR. ALBRECHT:  Thank you.  When R.J. Lee performed analyses by XRD,
what preparation technique do they use to prepare their samples?  Do
they use THF dissolution?

		DR. LEE:  Rich Lee.  Thank you.

		MR. ALBRECHT:  Thank you.

		DR. LEE:  No, we do not.

		MR. ALBRECHT:  What method do you use?

		DR. LEE:  We use the plasma asher.

		MR. ALBRECHT:  All right.  Would R.J. Lee mind submitting manufacturer
and lot number information for these .8 micron, 37 mm PVC filters that
were used for these sample preparations?

		DR. LEE:  We would not.  I mean -- Rich Lee -- we'd be glad to.

		MR. ALBRECHT:  That would also be very helpful.  Thank you, Rich.

		The laboratories that did perform these analyses, do you know if they
wiped the walls of the cassette prior to performing the analysis on the
samples?

		MR. BAILEY:  This is Kelly Bailey.  No, we do not know the answer to
that.

		MR. ALBRECHT:  And is that a current practice at R.J. Lee?

		DR. LEE:  Rich Lee.  I'd have to check.

		MR. ALBRECHT:  All right.  Thank you.  Did the laboratories that
analyzed these samples report any kind of error that was associated with
their result?  I'm assuming because they are AIHA laboratories, they do
have to report.  AIHA accreditation does, I believe, require that there
is an error associated with the result.

		MR. BAILEY:  Kelly Bailey.  We did not see a laboratory result,
because these were blinded by us also, and so the only person who really
can answer that question is SOMA.

		MR. ALBRECHT:  Okay.  I'm coming near the conclusion here.  The other
idea that I'm really trying to wrap my mind around here is that the
alcohol suspensions used to spike these samples, you guys alluded to
perhaps that it was destructive to the filter, and that's why they
weighed less post-application of silica than before.

		Did you assume that this was a systematic process where they would
lose, you know, 50 µg with every application, or was it a random error?

		DR. LEE:  Rich Lee.  The data -- we did an independent set of
measurements on alcohol interaction with the filters alone, and it
appears that it's about 70 µg, and maybe varied from 50 to 100.

		MR. ALBRECHT:  Okay.

		DR. LEE:  Speaking very broadly.

		MR. ALBRECHT:  And then, my very last question, and then I'll turn it
over to Daniel, when -- well, two more, sorry.  They're quick.  When
applied silica or Min-U-Sil to the filters that also had, you know, one
of these interferences also applied, was that two applications of this
alcohol to the filter, or were both of those powders suspended in one
alcohol solution?

		DR. LEE:  They were both suspended in one.

		MR. ALBRECHT:  So it was just one application?

		DR. LEE:  I'm sorry, that was Rich Lee.

		MR. ALBRECHT:  Thank you.  And did R.J. Lee analyze any filters that
had been spiked with both Min-U-Sil and interference?

		DR. LEE:  I will have to check.

		MR. ALBRECHT:  Okay, thank you.

		MR. PERRY:  Daniel Johansen from our lab.

		MR. JOHANSEN:  One question I had about the Min-U-Sil.  Do you have
the lot number and -- for that, that you can submit, as well?

		DR. LEE:  Rich Lee.  I would believe so, but we'll have to check.  And
if we have it, we'll submit it.

		MR. JOHANSEN:  Okay.  Now, I notice that you did this as a blind
study.  And I know you guys are an AIHA-accredited laboratory.  Do you
guys treat your samples differently from the AIHA PAT Program than you
do your other samples that you analyze at your lab?

		DR. LEE:  I think the answer is we'd like to say "no."  But in point
of fact, they come in, and I think everybody's on their best behavior.

		MR. JOHANSEN:  So do you say that there's some bias maybe that's
associated with the --

		DR. LEE:  I can't say that.  But, you know, I think it's just human
nature.

		MR. JOHANSEN:  Okay.  Just to clarify, too, the Min-U-Sil is also
subjected to the sedimentation process.  Is that correct?

		DR. LEE:  Rich Lee again, and yes.

		MR. JOHANSEN:  Okay.  Out of curiosity, what instrument do you use to
analyze your samples?  And what is the maximum power that you use for
your generator?

		DR. LEE:  I mean, we use -- I'll have to check.  It's not -- it's
the derivative of Phillips, but -- Rich Lee again.  I'm just the owner.

		MR. JOHANSEN:  Okay.

		DR. LEE:  But I will provide that information.

		MR. JOHANSEN:  Okay.  I think that's all the questions that I have.

		JUDGE SOLOMON:  Mr. Perry?

		MR. PERRY:  Okay.  And we have Robert Bart.  I suspect he'll have more
than two or three.

		MR. BURT:  Good afternoon.  I wanted to start by asking some questions
about the cost model.  You mentioned binominal distribution model.  I
just want to be sure I understand what you did with that.

		For a real simple example, if somebody -- if some job category had
two people in it, and that's all there were, and 50 percent of those
were overexposed, then the model would say one person per facility is
overexposed.  I'm just -- is that what it would say, or would it say
something different?

		MR. WAGGENER:  Well, it's not that simple.  This is Jack Waggener
speaking.  It's not that simple.  I mean, every job was looked at
separately, from every industry.  And the curve -- I gave an example
curve there, but there could be 400 other curves that look completely
different.

		MR. BURT:  So I understand that.  I'm giving you one industry, one
firm size, two people, 50 percent overexposure.  I hate to ask someone
to calculate on stage, but that's a pretty simple calculation.  Would
you say that means one person per facility is overexposed in that
sector, in that job category?

		MR. WAGGENER:  It's getting late in the day.

		MR. SESSIONS:  Let me jump in.  Stuart Sessions.

		The binominal expansion would give the probability that any given
facility would have zero, one, or two overexposed workers, and would
calculate the fraction of the plants in the -- let's say we were
looking at very small plants, and there were hypothetically 500 of them.
 It would give the fraction of such plants that would have zero
overexposed workers in that job category, the fraction that would have
one.

		MR. BURT:  So you carried out the distribution across everyone.  So in
my 50 percent example, you'd have approximately 25 percent of the firms
with zero, 50 percent with 50 percent, and 25 percent with 100 percent.
Just carrying out a simple binomial, you would end up saying there were
people with no exposures, and there were people/places where everyone
was exposed.  Is that what you did?

		MR. WAGGENER:  Why don't we get back to you with a real example to
answer the question?

		JUDGE SOLOMON:  That's Mr. Waggener.

		MR. WAGGENER:  Yeah, I'm not trying to avoid your question, but you're
oversimplifying the binomial, yeah.

		MR. BURT:  No, I understand, but this is a very critical issue to what
the cost model produces.  I mean, this is the key to many things that
follow.

		You talk about -- well, I would also add that it's particularly
important to figure out what happens when there are fractional workers.
If the model produced an answer like .5 workers per facility, would you
say -- what would you do with that?

		MR. WAGGENER:  It only uses -- the binomial only uses whole workers.
It doesn't --

		MR. BURT:  So you didn't simply average?

		MR. WAGGENER:  No, no.

		MR. BURT:  Okay.

		MR. WAGGENER:  Only whole workers, yeah.

		MR. SESSIONS:  This is Stuart Sessions again.  The details of how it
works are in the spreadsheets that Jack --

		MR. BURT:  Oh, I'm sorry, I meant to say I want to thank you for
providing the spreadsheets, but we just haven't had time to get into
them during this hearing.

		MR. WAGGENER:  I understand.  And I just want to say, this is supposed
to be constructive criticism we're doing here, and I've done this
before.  And we'll be glad to work with you guys in any way to show you
what we did, how we did it, at any time.

		MR. BURT:  Okay.

		MR. WAGGENER:  Yeah, yeah.  And I'm not the statistician.

		MR. BURT:  You make a statement in your written testimony, "The
percentage of facilities in the first quartile of the graph would
receive one engineering control for each overexposed worker."  So that's
effective -- that sounds to me like it's applying an engineering
control that OSHA intended for four workers to each worker.  Is that
what the model would do?

		MR. WAGGENER:  It would -- for those -- there are very few of those,
but where that -- on that back end of the statistical curve, then that
could be the case.  Those workers are assumed to be spread out far
throughout in the facility, and we need --

		MR. BURT:  And then, if there are two workers, you would apply, once
again, the exposure controls OSHA might have said were appropriate for
four workers.  Is that correct?

		MR. WAGGENER:  We would on the other end.

		MR. BURT:  And the same with n4 would be four?

		MR. WAGGENER:  That's -- you're --

		MR. BURT:  So couldn't this be summarized as no matter how many people
are exposed, you always need all the controls?

		MR. WAGGENER:  No, that is not correct.

		MR. BURT:  Why not?

		MR. WAGGENER:  That's not what the model does.

		MR. BURT:  I'm just reading what you said it did.

		MR. WAGGENER:  I'm sorry?  I don't remember.  I don't know what -- I
don't remember saying that.

		MR. BURT:  I was quoting your own testimony --

		MR. WAGGENER:  Okay.

		MR. BURT:  -- that says if there's one more -- if 25 percent of the
workers are exposed, you get all the controls that OSHA prescribed.  If
half of them are exposed, you get all the controls OSHA --

		MR. WAGGENER:  I don't know what we're debating here.

		MR. KING:  Excuse me, this is Neil King.  I wonder if you could
provide the specific page reference.  Maybe this could be answered --

		MR. BURT:  Pardon me, Page 8 of the URS testimony, first paragraph.

		MR. WAGGENER:  The actual written testimony?

		MR. BURT:  Yes.

		MR. WAGGENER:  Okay.

		MR. BURT:  I was quoting.

		MR. WAGGENER:  I don't think I have that up here with me.

		MR. BURT:  You go on to say, and I'm still on Page 8 of the URS --

		MR. WAGGENER:  Where are you reading?

		MR. BURT:  Page 8 of the URS testimony.

		MR. WAGGENER:  Where are you--

		MR. BURT:  The original written testimony.

		MR. WAGGENER:  Yeah, I understand that, but where are we?

		MR. BURT:  The second paragraph.

		MR. WAGGENER:  We've got the wrong one.

		MR. BURT:  The first question was about the first paragraph.

		MR. KING:  You're talking about the -- excuse me, the written
testimony that was submitted earlier on?

		MR. BURT:  Yes.

		MR. KING:  Not today's written --

		MR. BURT:  Yeah.

		MR. WAGGENER:  You're talking about the top of the page?

		MR. BURT:  Yeah, I was --

		MR. WAGGENER:  Okay.

		MR. BURT:  -- just trying to sort through what it meant when you talk
about controls being applied.

		MR. WAGGENER:  Okay.

		JUDGE SOLOMON:  Give him a chance to read it.

		MR. WAGGENER:  Thank you, Your Honor.  Okay, that's what I believe is
correct.

		JUDGE SOLOMON:  Yeah, Mr. King is sitting right next to you.  Do you
need to read that into the record, Mr. King?

		MR. KING:  I -- let's see what the answer is and respond.  I --

		JUDGE SOLOMON:  This is an abbreviation.  Normally, what I would do is
I would ask you if you're familiar with that.  And then --

		MR. WAGGENER:  I'm familiar.

		JUDGE SOLOMON:  -- I would ask you did you write it and all that
stuff.  So I'm not -- I don't think we need to do that.  So you -- do
you know what he's talking about?

		MR. WAGGENER:  Reading this, I know what it is.

		JUDGE SOLOMON:  Go ahead, Mr. --

		MR. WAGGENER:  In the binominal distribution, which everyone looks
different, they're not the simple two-people distribution, we are
basically in the first core quartile or the quarter, the curves are
done, and we use one worker per control or one control per worker, okay?

		MR. BURT:  Um-hum.

		MR. WAGGENER:  In the second one, between 25 and 50 percent, we used
two workers per control, half of what OSHA did.  And for the 50 percent
and above, we believe that means you have 50 percent of the workers
exposed that you would need.  We used what OSHA said, which is four
workers per control, if that was what was used in the OSHA model.

		We keep talking about four, but there are a few where there six and
eight.

		MR. BURT:  Right, let's stick to the four then.

		MR. WAGGENER:  Yeah, right.

		MR. BURT:  So if there's only less than 25 percent of employees
exposed, and say that works out to one employee, you would have applied
the controls OSHA thought appropriate for four employees.  Is that
correct?

		MR. WAGGENER:  If there was more than -- if it's --

		MR. BURT:  If it's under 25.

		MR. WAGGENER:  -- from the top 50 percent, yeah, yeah.

		MR. BURT:  But even the one, you would still apply all the controls
OSHA thought was appropriate it seems?

		MR. WAGGENER:  I'm not following the conversation here.

		MR. BURT:  It says "would receive one engineering control."  Are those
the engineering controls OSHA recommended?

		MR. WAGGENER:  I -- you're going to have to read to me and show me
what you're talking about because I --

		JUDGE SOLOMON:  Maybe we should have -- let's get it into the record.
 Do you want to do that?

		MR. KING:  Well, he's now talking about a different hypothetical.  I
think Mr. Sessions may be able to enlighten on this one.

		MR. SESSIONS:  If I could.  Stuart Sessions.  Basically, we're talking
about -- instead of saying "number of controls," the package of
controls that OSHA posits as being appropriate to address an overexposed
worker in a particular industry in a particular job category.  So that
may be, you know, material handlers in structural clay.  It may be one
control.  It may be four, I don't know.  You know, it's the package.

		And the question is, how many times does that package need to be
applied for workers who find themselves in facilities when there is an
unknown number of such workers in the job category that are, in fact,
overexposed.  So let's say we're talking about very small facilities.
And on average, there are .5 overexposed workers in this job category in
each such very small facility.

		The decision rule -- I'm afraid I've lost you there, okay.

		JUDGE SOLOMON:  Maybe Mr. Burt will ask another question.

		MR. KING:  This is Mr. King.  Mr. Burt, was your question whether we
were assuming that the same package of controls that OSHA would be using
to protect four workers in a particular job category is the same package
of controls that, in some of these situations, we would be -- we would
say would be used to protect just one worker?  Is that what you're
asking?

		MR. BURT:  Yes.

		MR. KING:  Whether there's a different --

		MR. SESSIONS:  Yes.  The answer to that is "yes."  You know, if there
is a single overexposed worker in the facility, then in this step of the
analysis, we are agreeing that that worker needs the package of controls
that OSHA posits as appropriate for that job category.

		And the question is, how often, given the distribution of overexposed
workers among facilities, how often does that package of controls need
to be installed in situations where there's only one worker who needs
it?  And how often is it in situations where there are two workers?  And
how often are there four overexposed workers who, in fact, can all be
protected by that package of control?

		So, ultimately, the question is how often do you need the package of
controls, given the pattern of overexposed workers in different-sized
facilities?

		JUDGE SOLOMON:  Okay.  Just so we straight all this out, that was
Mr. Sessions, and his colloquy started with the word "yes."  Now,
before that, we had several speakers.  I don't remember what the actual
sequence was, so maybe you can straighten out the record.

		MR. KING:  Yeah, Mr. King was just trying to clarify the question as
being whether the same package of controls would be used for four
workers as for one worker, and then the answer from Mr. Sessions was
yes.

		MR. BURT:  Yes, your clarification was very helpful.  Thank you.

		MR. WAGGENER:  I'm sorry that I didn't follow it, sir.  Jack Waggener.

		MR. BURT:  Moving down to the next paragraph, another aspect of how
the model works.  "For the purpose of this cost model, URS has
determined that a majority of the workers, greater than 50 percent in
the job category, are exposed above the PEL.  It is rational to conclude
that the threshold has been exceeded and that the existing controls are
totally inadequate and must be replaced."

		I want to be sure I understand what that's saying.  Let's say you
encountered a situation in which there were four workers.  Two were
exposed at 35, two at 60.  You would scrap all of the controls and start
over again.  That's what it seems to be saying.

		JUDGE SOLOMON:  So, Mr. Waggener, are you familiar with that?

		MR. WAGGENER:  Yeah, actually, I just found it.  Yeah, yes, that they
would need to be replaced with a more adequate system, yeah.

		MR. KING:  Your Honor, can I just interject a second.  If there are no
more questions for Dr. Lee, for example, he has a train to catch.  I
wonder when he could go -- is that right?  Are you folks done with
Dr. Lee at this point, for example?

		MR. PERRY:  Yes, I believe so.  I think at this point we'll just be
asking questions about the cost and economic analysis.

		JUDGE SOLOMON:  Ms. Lindberg, are you going to have any questions for
him?

		MS. LINDBERG:  I just have one for Dr. Morfeld.

		JUDGE SOLOMON:  Okay.  Dr. -- or Mr. Lee, Mr. Bailey.

		MR. KING:  And, Your Honor, do we have an idea about how much longer
this will go this afternoon, or this evening at this point?

		JUDGE SOLOMON:  It's pretty much up to OSHA.  Mr. Stone is in the
back, held in abeyance, I assume.

		MR. BURT:  Sorry, this is my clock.  Okay.  We've had quite a bit of
discussion about assigning people to establishments and what kinds of
controls are needed.  And here, let me go back to the binominal model.

		Would it be -- you stated at one point, I think, that we start with
an exposure profile, rather than looking at individual establishments.
Would it be helpful to analyze the actual distribution and individual
establishments so that we were, instead of speculating about a binominal
or another model, we actually took a look at it?

		MR. WAGGENER:  Well, obviously, I mean -- excuse me, Jack Waggener --
the more time we have, obviously the more time we can do that kind of
thing.  And that would be something I would definitely encourage OSHA to
do.  And I've done that before with other rules when there's time and
there's very specific information, yeah.

		MR. BURT:  Turning to another aspect of it, you talked about the need
for professional cleaning.  And I think someone guessed, and I think
accurately, that OSHA may have inadvertently dropped that when we made a
couple of successive changes to the model.  And it -- as a result, it
might be necessary.

		I was curious about the parameters that were used for that.  For
example, you've got a 20,000-production area for a very small firm.  And
this is an operation that would typically have six to eight persons.
What's the basis for -- that seems to be pretty large.  I mean, that's
a football field up to the 40-yard -- a college football field up to
the 40-yard -- goal line to 40-yard line.

		Is there a basis for that, 20,000 square feet?

		MR. WAGGENER:  That, again, let's -- is that in -- are you reading
here now?

		MR. BURT:  Yes.

		MR. WAGGENER:  Okay.

		MR. BURT:  I'm sorry, I can -- Page 24, last paragraph.

		MR. WAGGENER:  Jack Waggener again.  Page 24.  From my experience in
seeing small facilities, that's not an unusual square footage for a
small facility in these industries.

		MR. BURT:  So these numbers are based on your experience?

		MR. WAGGENER:  Also, some of the surveys and discussions with the
industries that we talked to.

		MR. BURT:  Surveys as results we don't have access to?

		MR. WAGGENER:  I think we've answered that question and I --

		MR. BURT:  Thank you.

		MR. WAGGENER:  Yeah.

		MR. BURT:  We talked about you argue that we underestimated the costs
per -- of cfm, the first the capital costs.  I haven't had a chance to
pour over your testimony on that.  Will there be somewhere a worksheet
that shows what the basis for that much a higher number is?

		MR. WAGGENER:  I believe there is.

		MR. BURT:  Okay.

		MR. WAGGENER:  And it's -- the devil's in the details of all those
Excel sheets.

		MR. BURT:  Yeah.  And then did you -- you said that you applied the
25 percent factor OSHA used.  Did you separately try to be sure that
that was sensible, given the changes in the capital cost worksheet?

		MR. WAGGENER:  Yes.

		MR. BURT:  In other words, for example --

		Yes?

		MR. WAGGENER:  Yes, sir.

		MR. BURT:  Okay.  We'll want to take a look at that.  At one time, I
believe in the lead rule, OSHA argued that very small facilities might
have somewhat smaller capital costs because they would need less
ductwork.  Conversely larger facilities might have higher.

		Do you have any comment on that -- those possibilities?

		MR. WAGGENER:  We're going back -- excuse me, Jack Waggener -- we're
going back 40 years now, okay?

		MR. BURT:  I know.  But I'm saying the broad -- I'm saying it's
argued that now, let's just say, in your experience, do smaller
facilities have lower costs to install these things than larger ones?

		MR. WAGGENER:  Editorial-wise, there are no more small facilities in
the lead business because they went out of business.

		MR. BURT:  No, I mean, in this record --

		MR. WAGGENER:  Right.

		MR. BURT:  -- we're talking 17 persons is the average size of a
facility, as you yourself pointed out at one place.

		MR. WAGGENER:  Okay.  They're very small.  I think it was less than
eight people.

		MR. BURT:  Yeah.

		MR. WAGGENER:  Yeah.  And would you repeat the question?

		MR. BURT:  Just is there any -- people have argued that very small
facilities might have lower capital costs for cfm than very large ones.

		MR. WAGGENER:  I --

		MR. BURT:  There would be less ductwork in a very small facility is
one reason.

		MR. WAGGENER:  That's a possibility.

		MR. BURT:  You mentioned today that you had adjusted your costs in
some way to account for variability and exposure data.  What did that
involve?

		MR. WAGGENER:  We adjusted it for the ISO/CEN change.

		MR. BURT:  Um-hum.

		MR. KING:  Excuse me.  This is Mr. King.  Were you referring to the
initial exposure monitoring issue?

		MR. BURT:  I was referring to page 19 of your testimony today, where
it notes that additional monitoring will frequently give different
results.  Did you make an adjustment in your model for this, or you're
simply criticizing OSHA for failing to make such an adjustment?

		In other words, did you take account of this, or did you simply want
to point out that was something that should be accounted for?

		MR. WAGGENER:  To answer your question, I do not believe that we
actually made an adjustment.  And we're just pointing out the
conservatives -- that we were conservative in our estimates.
Jack Waggener.

		MR. BURT:  There has been some discussion of the costs of getting to
100.  Let's suppose -- I just want to pose a hypothetical.  Let's
suppose OSHA somehow figured out how to truly enforce the standard of
100, and in the next three years did so.

		Would you now say that we can exclude those costs from this record?

		MR. KING:  I'm not sure -- This is Mr. King.  Your hypothetical is if
you repropose this standard three years from now, at a time when no
employees are exposed above 100 µg/m3?  Are you say at what -- is that
what you're saying?  Would that be --

		MR. BURT:  I'm asking, would you say that, as a result, would the
economic impacts be less?

		MR. KING:  Would economic impacts be less if all exposures were below
100 µg/m3?

		MR. BURT:  Yes, we somehow succeed in enforcing the existing
standards.

		MR. SESSIONS:  This is Stuart Sessions.  I would say that the -- an
estimate -- any estimate of compliance costs is premised upon the
exposure distribution that one assumes that prompts the estimate.  And
if OSHA's exposure distribution were such that there's nobody exposed
above 100, then the costs that would be estimated for such a situation
would be quite a bit lower than the costs that are estimated for the
current situation.

		MR. BURT:  So are you saying that the economic feasibility of this
rule depends on the success of OSHA compliance, with the existing rule?

		MR. KING:  This is Mr. King.  I think what we're saying is the
economic impact of this proposed rule should be evaluated against the
current baseline of what exposures are today and how many employers
would therefore have to incur costs to install engineering controls, to
reduce those current exposures to a level of -- below 50.

		MR. BURT:  This is a question for Mr. King.  You've argued a few
times that, I believe, in your testimony that, to achieve 50, employers
would need to go to 25.  Well, it isn't.  The current data suggests that
to achieve 100, people are not going to 50.  They aren't even getting to
100.  How do you reconcile those two statements, those two?

		MR. KING:  I don't think there's anything to reconcile there.  I think
if people are currently having exposures above 100, that presumably
means that their -- on any single day when OSHA comes in to monitor,
that presumably means that their long-term average exposure in that
workplace is probably above something like 50 because on some days,
statistically they're going to be monitoring above 100, if that's the
situation.

		JUDGE SOLOMON:  Let me just say, that's pure argument.  We're not
supposed to take argumentative --

		MR. BURT:  Thank you, Your Honor.  One more question for
Mr. Waggener.  I think you mentioned testifying in the chromium
hearing.  What was the topic of your testimony at that time, if you do
recall?

		MR. WAGGENER:  It was with regard to costs, regard to technical
feasibility based on the NIOSH studies.  There were others.  I think it
was also on the measurability issue, also.

		MR. BURT:  Okay.  Thank you.  Let me turn to Mr. Sessions for a few
questions.  Now, I noticed you objected to our averaging profits across
both revenues for both facilities that did and didn't have profits.
That did lower the level of profits, didn't it -- lowered the estimated
profit rates, didn't it?

		MR. SESSIONS:  Yes.  This is Stuart Sessions.  Yes, averaging across
facilities that have profits, as well as facilities that do not have
profits, lowers the average profit rate.

		MR. BURT:  One troublesome issue that we wrestle with on these things
is OSHA is interested in firms that will be viable, not in marginal
firms that might disappear before this regulation.  In any case,
including all of the people with negative returns would seem to possibly
include -- I think it might include a good many marginal firms.  What
do you think?

		MR. SESSIONS:  This is Stuart Sessions.  One thing I can say from the
data is that there are clearly, as you look across the IRS data from
year to year, there are different numbers of firms each year that are in
the positive profits or the negative profits column.  And the IRS gives
breakdowns by asset class, also.

		And you see interesting things like, in one year, there is a big firm
that's reporting negative profits in a very big asset class.  In the
next year, that firm is not reporting negative profits because all the
data in that asset class is -- they're only profitable firms in the
next year.

		So, you know, I don't -- I understand perhaps that you're trying to,
you know, there is a reason in analysis to try to leave out what could
be called baseline closures, and that's appropriate.  But I don't think
that's what's going on in the IRS data, and particularly when you're
looking at it over, you know, 6 years, 10 years, 12 years, you know,
these are -- most of those firms are around for a good while.

		So, you know, my guidance -- my recommendation continues to be to
attempt to assess the ability of the entire industry to bear costs.

		MR. BURT:  In term -- if I could go back, if you object, I have no
problem with this, the other day you answered a question that small
firms have lower profits than large firms.  Am I remembering correctly?

		MR. SESSIONS:  This is Stuart Sessions.  I may have said that, in
general, to the extent I've looked at the data, for the most part, small
firms tend to have lower profit rates than larger firms.

		MR. BURT:  But would you find, say, the IRS breakdown by asset class a
reasonable way of addressing whether that's true from year to year?

		MR. SESSIONS:  Yes.  And, you know, there are issues about breaking
down the distribution the IRS gives you by asset class into, for
example, the SBA distinction based upon employee size and --

		MR. BURT:  Yes.

		MR. SESSIONS:  -- things like that.  That's all very tricky.  And,
you know, there are other data sources that are -- that will break
small versus large down in different ways.  The RMA data breaks it down
by sales, for example, and other data sources may provide different and
perhaps better, and additional, insights into this issue beyond what the
IRS can provide.

		MR. BURT:  The additional data sites -- sources you mentioned, RMA
and Dun and Bradstreet, are these random samples of firms?

		MR. SESSIONS:  This is Stuart Sessions.  No, they definitely are not.
And an additional data source that I may not have mentioned today but
that I put in my written comments is any number of industry-specific
benchmarking and sample survey sorts of efforts, benchmarking or best
practices assessment and that sort of thing.

		And my recommendation would be to try to sort of access all of the
relevant potential data sources for the industry in question, in order
to handle the sort of variety of different difficult issues that you've
got facing you, including, you know, the IRS data falls short on the
representativeness question, the three- or four- digit industry versus
six-digit.

		And some of the other data sources do better than that, but the other
data sources do have, as you point out, RMA in particular, those are
firms that are healthy enough to be looking for financing and then filed
their financial statements.  And so, there's some questions about the
representativeness of that data.

		And, in fact, I think back in 2003, OSHA did use the RMA data.  And I
don't know why OSHA switched from that to the IRS, but my counsel would
be to look at both and try to use some amalgamation of what you can
glean from each.

		MR. BURT:  That covers what I have for now for today.

		MR. MORRILL:  Your Honor, I have one quick question.  I'm wondering,
because Peter Morfeld's been sitting here for a while, and I know you
have one question for him.  I'm wondering if we could skip to that one
question and then --

		MR. PERRY:  Yes, absolutely we can.

		MS. LINDBERG:  Sorry to keep you waiting, Dr. Morfeld.  This is an
easy question, though.  You mentioned several studies in your
presentation today, and that OSHA's not sure it has in its -- in the
docket.  We're wondering if you would mind supplying them to the docket.
 It's the Borm et al. study from 2011, the Erin (ph.) et al. study from
2011 and the Solgul (ph.) et al. from 2012.

		MR. KING:  This is Mr. King.  Actually, we are planning to submit for
the record a whole slew of studies that were referenced in
Dr. Morfeld's testimony and comments but were not otherwise included in
the docket prior to that time.

		And these will be in hard copy because they will all -- they are
copyright protected, and we are very sensitive -- Dr. Morfeld and his
organization in particular, the University of Cologne, are very
sensitive about protecting the copyright features of these documents.

		MS. LINDBERG:  Sure, that's understood.  And that will include the
three studies I mentioned?

		DR. MORFELD:  Yes, of course.

		MS. LINDBERG:  Great.  Thank you.

		JUDGE SOLOMON:  You know, maybe I should -- I don't want to be a
buttinski here, and it's not really my province.  But when we had a
medical panel before, and I asked this question, and I'm going to ask it
now.  And that is, in the year 2000, the Department of Labor did
fact-finding with respect to pneumoconiosis.

		Silicosis is a subset of pneumoconiosis.  And in the fact-finding that
they made, they made a determination that smoking, for example, is
additive to pneumoconiosis.  And they also discussed something called
legal pneumoconiosis.  Is there -- I just want to ask whether there's
any comment, any literature or anything that we need to know about?

		DR. MORFELD:  So this is a longer discussion, whether smoking is
really increasing the risk of developing silicosis.  We try to adjust
for smoking in our analysis because we expected to see this argument
popping up.  But there was no big effect in our analysis, at least.

		But we used smoking as a covariable to control for this argument, yes.
 So they're -- in some studies, it appears to have an effect and others
not.  But you have to be careful because the argument is made that, in
particular, in those workers who have been shown to have developed
silicosis, the physician asked more precisely about the histories.

		So this can be a bias, or you get more precise and detailed smoking
information among the silicotics.

		JUDGE SOLOMON:  The only thing I would say is we have some other
physicians who have submitted their testimony and reports, so maybe you
want to take a look at that and respond to some of that.  Sorry that I
had to butt in.

		Okay, so the doctor can leave.  And let me just say for the record,
feeling dunk.

		MR. PERRY:  And thank you very much, Dr. Morfeld, for appearing
today, this afternoon, and spending the day with us all the way from
Germany.

		And now, I believe Robert Stone is ready with a few questions.

		MR. STONE:  The good news, this will be brief because my colleague,
Bob Burt, I think, addressed most of my questions.  However, in your
discussion of the distribution of controls, I thought it understood it.
Now, I'd like to run through it very quickly one time.  I promise it
will be very brief.

		As I understand it, you use our exposure profile, and you modified
based -- by 20 percent based on the ISO effect.  Is that right?  And
one -- if you get to 50 percent, you then apply the controls to all
workers in that job class that's at 50 percent.  Is that right so far?

		MR. WAGGENER:  I believe that's correct.

		MR. STONE:  Okay.  Now, my question where I'm now confused is are you
then -- let's say there would normally be one control for every four
workers.  Is that what you would apply to all the workers in the job
class depending on the number in each site?

		MR. WAGGENER:  If those higher of the two, yes, over the 50.

		MR. STONE:  Okay.  Then, there was the discussion about -- but you
may have to add or completely replace the current controls?  Or is that
also in effect -- or add more controls?  That was my last question on
this subject.

		MR. WAGGENER:  I think I'll have to get back to you on that one.  I
don't recall.

		MR. STONE:  Okay.

		MR. WAGGENER:  Yeah, yeah.

		MR. KING:  But -- and just to clarify the question -- so this is Mr.
King -- so that he'll know what to get back on, the question is, if for
a particular job category in an industry, the determination is made that
more than 50 percent of the workers are exposed above -- would be
exposed above the 50, the PEL, then would they assume that, for that job
category, controls have to be installed to protect all of the workers?

		MR. STONE:  That was part of the question.  And I think the answer to
that is "yes."

		MR. KING:  And then, the second part was --

are there -- are the controls basically replacement controls?  You're
going to have to basically -- I forgot what the term was, you're going
to have to basically start from scratch and put in new controls for
these workers?  And are you adding more controls than you otherwise
would?

		MR. WAGGENER:  Again, it is not that simple because every job has a
number of different controls that we approach.  And it's those details
that are in the spreadsheets that I talked about.  I'm not avoiding your
question; it's just not that simple.

		MR. STONE:  Okay.  But if -- let's say we're -- let's say we're 30
percent, and you have certain controls, would you typically have more
controls for the ones that are over, if you got to 50 percent of the
workers?

		MR. WAGGENER:  I didn't understand that.

		MR. STONE:  Okay.  You have a certain set of controls for the job.  If
you have 30 percent of the workers, you would use your -- you'd apply
your formula, and then you'd have them as to who gets controls.

		MR. WAGGENER:  Yeah.

		MR. STONE:  Would you -- if they got to 50 percent, would you
actually have them have more controls than the people who were at 30
percent?  That's what was throwing me off now.

		MR. WAGGENER:  We're saying, when we get to the last half on the
curve, in 400-and-something different examples, did it have all kind of
variances in it, and that we are using one -- four workers per control.

		MR. STONE:  Okay, but they're not more controls for the people -- for
the people who are getting controls at 50, they're not getting more
controls than the ones who are getting it at 30 percent overexposed, for
the workers that are getting their controls.

		MR. KING:  This is Mr. King.  Again, just on clarification, I think
what Mr. Waggener's model is doing is trying to figure out in how many
instances will we have to install the package of controls.  And he was
saying where -- for a particular job category, if they find more than
50 percent of the workers are overexposed, then you're basically saying
for that job category, they're going to need controls pretty much right
across the board because it's obvious that the controls in place for
that job category are not doing the job that they have to do.

		Now, if you're saying it's another situation where, instead of 50
percent, only 25 percent, let's say, are exposed above, you wouldn't
have to install as many packages of controls.  But the package of
controls you would install would essentially be the same one as you'd be
using when over 50 percent aren't.

		MR. STONE:  Oh, okay.  That's it.  Okay.  I'm good, thank you.

		Now, I have a few more questions actually for Mr. Waggener.  And
actually, it's really to clarify.  I think in your slides, you sort of
went out of your way to emphasize something, and I wanted to raise it.

		In two slides actually, in slide 9 and slide 11, I'll state what you
said in bold red -- in red on those slides at the bottom.  "Note:  OSHA
did not calculate very small and small facilities separately, but only
provided combined values.  URS recalculated these separately."

		And then, with an added bullet, "OSHA calculation obscured the
significant cost impact on very small facilities."  Is that -- that's
what you said in number 11 at the bottom of the page, slide 11?

		MR. WAGGENER:  That's correct.

		MR. STONE:  Okay.  Well, actually, I don't believe that is correct.
And let me just raise this for you to consider.

		OSHA separately divided throughout the PEA and in several places in
the preamble separate analyses and appendices for very small industries.
 I could point you to them if you wanted me.  But in addition, those are
completely just for very small.

		In addition, in several summary tables, we break out costs for all
facilities, all establishments, small establishments and very small
establishments.  Table 5.1, which begins the chapter, has that.  There's
an appendix to Chapter 5.  There's an appendix to Chapter 6, so there's
plenty of materials.

		We've carefully tried to break it out.  I think the confusion is that
you saw us presenting results for 1 to 500, not 20 to 500.  And we did
that because we have a legal obligation to the Reg Flex Act to consider
the effect on small entities, which is starting with one to everybody.

		But we thought we were very careful to try to break out the cost for
small.  And we tried to take separate -- I had separate unit costs for
very small entities in many cases.  You may not agree with how we dealt
with it, but we didn't disguise it, and we didn't obscure it in our
view.

		MR. WAGGENER:  I think I accept everything you just said.  I mean,
I've seen the PEA personally myself and numerous other people.  And it's
how it was all presented.  So maybe obscured is the wrong word, okay?

		MR. STONE:  Okay.  And partially, I wanted this on the transcript
because, you know, even though I don't see anyone from SBA here, they
might look at the transcript and decide that we were trying to hide
things from them.  We were not.

		The second item is also a point of clarification, if I can find it.
Okay, sorry.  Okay.  On slide 13, again, there are two places you sort
of emphasize this.  In one place, and this is -- I've heard this
actually throughout the hearings.  I've sort of not responded because we
can deal with it later.  But it's stated that OSHA basically estimates
the total number of overexposed workers nationwide, selected controls
assumed to be sufficient for four workers.

		And are you aware that we did not do that generally?

		MR. WAGGENER:  No, I'm not.

		MR. STONE:  Okay.  Well, we have 18 pages of tables in some detail,
describing the controls and the number of workers for -- per control.
It's actually in ERG (2007b), that's the reference.  It's a long title;
I'm not going to repeat it.

		And it's Table 3.3, Pages 3, let's see, 13 through 3 -- 30.  And
related to that in a later table, you specifically refer to an example.
And the example is in the enclosed cabs for front-end loaders, OSHA
assumed the capacity of four overexposed workers per cab.

		That's not accurate.  In that same table on Page 329, and the only
place I think we specify a front-end loader cabs, we have two workers.
And so -- and yeah, okay.  So I just don't know what the question was.
Was he aware of it?  So this is actually for asphalt pavement products.

		Anyway, now, my last question concerns when you got to ancillary
provisions, and let me see if I can get to the page for that.

		MR. BOXERMAN:  Your Honor, may I have ask that -- it's five after
6:00.

		JUDGE SOLOMON:  He's probably either the last questioner or the next
to the last questioner.

		MR. STONE:  I think this is going to be about it.

		MR. BOXERMAN:  He said this is his last question.  We've been very
cooperative.  It's long past the close date.  He's been sitting here for
five hours now and been testifying or questioned.  I think it's unfair
for OSHA to be continuing at this hour to continue to ask additional
questions.  And I would ask the chair for OSHA to reconsider whether
it's fair and reasonable and appropriate to continue questioning.

		We are obviously being cooperative.  We are here and present, but it's
way past where anybody else has been subject to this kind of
questioning.  I ask -- I request respectfully to stop.

		JUDGE SOLOMON:  Mr. Waggener, do you have any other --

		MR. WAGGENER:  Apparently not.  I'm fine, thank you.

		MR. PERRY:  If I may just ask one easy one, okay?  I just want to make
sure I understand that you used OSHA's exposure profile, and you made an
adjustment for the change from the existing curve for particle size
sampling criteria to the new ISO/CEN curve, which you say would average
about 20 percent greater dust mass being collected.

		So you kind of shoved everything up by 20 percent; is that correct?

		MR. WAGGENER:  It's Waggener, excuse me.  That is -- those details
are in the spreadsheet.  However, it does not shove it up -- it doesn't
give you 20 percent more employees.

		MR. PERRY:  No, I understand -- I think I understand that.

		MR. SESSIONS:  This is Stuart Sessions.  I can respond directly to
that.  The answer is we assumed in the exposure interval below 50, let's
say we're dealing with the ISO/CEN adjustment increasing the number of
workers exposed above 50, what we did was look at the number that OSHA
gave that were exposed between 25 and 50, and 20 percent increase to
41.2, I think gives 50.

		So we took 8.3 of the 25 and assumed a uniform distribution across the
lower exposure.

		MR. PERRY:  Okay, I understand.  Would you do something different if
most of those exposures -- if that exposure profile was drawn mostly
from exposure data using measurements that were taken with devices that
conform to the ISO/CEN curve, such as aluminum cyclone?

		MR. WAGGENER:  If it was done the proper way as ISO/CEN, we wouldn't
be adjusting it.  Yeah.

		MR. PERRY:  Okay.

		MR. WAGGENER:  I believe, and I stand to be corrected, that most of
the data or all the data in the PEA is not based on the ISO/CEN, I don't
think.

		MR. PERRY:  Okay.  Well, I mean, we'll look at that, but I believe
that is -- I believe we are done.  On behalf of the Agency, I really
thank Mr. Morrill.  I really thank the ACC and the Silica Panel for the
afternoon and early evening you spent with us.  You have been very
patient, and we appreciate that.  I think we learned a lot from you
today.  So thank you, and we'll look forward to your post-hearing
submissions.

		JUDGE SOLOMON:  Okay.  So if there's nothing else from anybody, the
time is 6:10, and the hearing is closed.

		(Whereupon, at 6:10 p.m., the hearing was continued, to resume the
next day, Thursday, March 27, 2014, at 9:30 a.m.)

C E R T I F I C A T E

	This is to certify that the attached proceedings in the matter of:

INFORMAL PUBLIC HEARINGS FOR THE PROPOSED RULE

ON OCCUPATIONAL EXPOSURE TO

RESPIRABLE CRYSTALLINE SILICA

March 26, 2014

Washington, D.C.

were held as herein appears, and that this is the original transcription
thereof for the files of the United States Department of Labor,
Occupational Safety & Health Administration.

				 							    					____________________________

				    	ED SCHWEITZER

				    	Official Reporter

_________________________

		Continued

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