22  underlined, I'm expecting you to summarize the group's

23  thoughts on these charge questions so that   and to get

24  that summary to Angela who is going to combine it so

25  that hopefully we can agree or agree not to agree on

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Page 210

1  what we want to send to, what message we want to send

2  to the Administrator.

3	But let's take a fifteen minute break.

4  What time is it?  2:30, so 2:45, come back and we'll

5  finish up Charge Questions 7 and 8 and discuss our, try

6  to summarize what the main issues are.

7  (WHEREUPON, there was a recess).

8	DR. HENDERSON: During the break I have

9  asked Karen Martin who is from the Air Office and

10  responsible for the next part of this review process,

11  that is pulling together the endpoint of the exposure

12  risk assessment document and then the   what is that

13  horrible acronym, ANPR.

14	And I thought it would be really helpful

15  if she just spent a few minutes reviewing where we are

16  in the process and the decisions that we need to make

17  today and the advice that the Air Office really needs

18  to help them in how they write their document.

19	And so I've asked Karen   where is

20  Karen?

21	DR. MARTIN: Okay.

22	DR. HENDERSON: Okay, you can use that

23  mike.  Go ahead.

24	DR. MARTIN: Since your conversation did

25  clearly stray into the, let's get to the end game of

Page 212

1  words?  How do we assess the importance of difference

2  choices for elements of the standard when there is no

3  clear cut one way that's the right way?

4	You know, different forms of a standard

5  matched up with different levels may get you the same

6  degree of health protection.

7	And all those considerations are part of

8  the broader policy assessment that we've historically

9  pulled together in the staff papers that we used to

10  produce.

11	And now that we have a new process that

12  isn't going to have a staff paper in it, you all are

13  going to have to wait a little bit longer before seeing

14  how the Agency will pull together the science in the

15  Integrative Science Assessment and the quantitative

16  results from exposure and risk assessments and these

17  broader policy considerations, how the Agency thinks

18  it's appropriate to pull those together to array a

19  range of standards that are appropriate to consider for

20  reaching final decisions here.

21	And I think it's important to recognize

22  that just as Mary was saying earlier, while the

23  Integrative Science Assessment can go a long way to

24  help informing those judgements, it can't and doesn't,

25  attempt to in the end, try to array the science

Page 211

1  what the standards ought to be, it seemed appropriate

2  just to take a step back and revisit the question about

3  the purpose of this document, the purpose of other

4  documents, and how we in the end pull this all

5  together.

6	And for some of you I'm sure we've been

7  through this before, but for others perhaps not and it

8  seemed worth saying a few words on this point.

9	The discussion of the Integrative

10  Science Assessment, I think we all recognize that

11  science and the interpretation of the science and

12  getting that interpretation clear and correct is

13  absolutely central and critical to reviewing the

14  standards.

15	But I think we also all know that it is

16  not definitive of the standard, it doesn't define a

17  standard in and of itself.

18	The science will never tell us alone

19  exactly what the standards ought to be, and that's why

20  we do other things.  That's why we do quantitative

21  exposure and risk assessments and why we do what we

22  generally refer to as a policy assessment, which is

23  bringing in broader policy considerations like what

24  does it mean to protect public health with an adequate

25  margin of safety?  How do we give meaning to those

Page 213

1  information in a way that creates the bottom line

2  answer to the question of what should the standard be.

3	And so I think that it's important that

4  we not try to get ahead of where we are.  Where we are

5  right is one, trying to get the science document, you

6  know, to strengthen it as much as it needs to be.  But

7  also in this early stage, to try to get advice from you

8  as to how we can take the next steps, which is to do

9  the quantitative exposure and risk assessment.

10	And that's of course going to be the

11  discussion that we have tomorrow.  But even tomorrow's

12  discussion isn't going to be about, and therefore what

13  is the right standard?  It's still going to be just one

14  of the building blocks that it takes to get there.

15	But in your discussion today in terms of

16  the information in the science assessment, to the

17  extent that you can help identify, even if you don't

18  have clear bottom line conclusions about the strength

19  of the evidence for different health effects, the where

20  you come out with regard to likely causality or in that

21  spectrum of conclusions or inferences that you might

22  reach, having some initial feedback from you will be

23  helpful because as you well know our next steps are

24  going to be to make judgements about how to structure

25  and conduct quantitative exposure and risk assessments.

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Page 214

1	We don't want to be about the business

2  of estimating risks for non-causal relationships.  And

3  yet we also realize that we have to start doing that

4  work before there are, you know, bottom line

5  conclusions from the final Integrative Science

6  Assessment.

7	So to the extent that you can share your

8  initial thinking at this point of information in the

9  first draft Integrative Science Assessment and

10  preliminary inferences you might draw from that that

11  would help us, both in the discussion tomorrow and in

12  the days following tomorrow when we need to go back and

13  start doing those assessments, that would be very

14  useful.

15	But I think we all, it would behoove us

16  all to be patient in terms of trying to jump ahead to

17  bottom line judgements about elements of the standard,

18  because in the end of course that's going to be

19  informed by, centrally by the science, but also by a

20  lot more information than just the science.

21	DR. HENDERSON: Does anybody have

22  questions for Karen?  Are there any questions?

23	DR. HATTIS: I imagine it still would be

24  helpful for you if we were to be able to come to

25  conclusions about what the relevant averaging time

Page 216

1  and 8.  I know we've already talked some about Charge

2  Question 7, but Ed Postlethwait, do you want to begin?

3	DR. POSTLETHWAIT: Sure.  Let me preface

4  my comments by saying that I actually struggled

5  somewhat with this because I thought that listening to

6  the discussions preceding this would be helpful for us

7  to try to focus in on a specific issue of identifying

8  susceptible populations.

9	One of the things I noticed in reading

10  specific, in Chapter 4 specifically, was that at least

11  the impression I derived was that many of the

12  identified populations were almost more intuitive

13  relative to being sort of quantifiable.

14	I mean we all think of kids, people with

15  asthma, preexisting cardiovascular disease, et cetera,

16  as being susceptible to whatever kind of environment

17  insult you want.  And so those were primarily the folks

18  that were identified in this.

19	What I thought was somewhat lacking in

20  here relative to the charge was whether or not we

21  needed to quantify the specific public health impacts.

22  And I mean, you know, the charge is to come to a

23  consensus on the appropriateness of the public health

24  impacts and characterizations of groups likely to be

25  susceptible.  But I mean is a public impact an NOI or

Page 215

1  would be for the causal processes.

2	DR. MARTIN: It would be, it's

3	DR. HATTIS: If there were some causal

4  process.

5	DR. MARTIN:   extremely useful to

6  understand what exposure durations are linked with what

7  health endpoints.

8	DR. HATTIS: Right.

9	DR. MARTIN: In the end of course the

10  averaging time for a standard might not necessarily be

11  exactly the same as any one of those averaging times.

12	DR. HATTIS: Sure.

13	DR. MARTIN: But, yeah.

14	DR. HENDERSON: Another thing that Karen

15  said was, you know, it's helpful to her and to the Air

16  Office, for us to discuss whether we, what we think

17  about for instance this cancer study.

18	Is that something that, you know, that

19  we think NO2 is causing cancer?  Which, you know, we've

20  already discussed that, but that's the sort of thing

21  that would be helpful for Karen.

22	Thank you so much, Karen.

23	Okay, so we don't really have to decide

24  everything today which is a relief you might say.

25	But let's go on to Charge Questions 7

Page 217

1  an NO, whatever?

2	And so again I thought that was

3  potentially up for discussion.

4	I liked the inclusion of the ATS

5  criteria for defining what a health effect was.  And I

6  really thought that it would be useful to put that

7  portion of the chapter up front to then be able to sort

8  of flow from there across the various groups and then

9  define back to them as has been done to some extent,

10  where they fall in that spectrum of those criteria.

11	There were a couple of   the table at

12  the end about what would be moderate, severe, et

13  cetera, the way it was presented I didn't find those

14  particularly useful because there was no specificity to

15  outcomes from either experimental or population based

16  studies.

17	There was an interesting component

18  written up front, it's on page 4-8, about the genetic

19  factors.  And I point this out, I'm actually going to

20  read from here because it's very clearly defined.  The

21  document reads, first the product of the candidate gene

22  must be specifically involved in the pathogenesis of

23  the adverse affect of interest, often a complex trade

24  with one of determinants.  Second, polymorphisms in the

25  gene must produce a functional change in either the

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Page 218

1  protein product or in another expression of the

2  protein.  Third, in epidemiological studies the issue

3  of confounding by other environmental exposures must be

4  carefully considered.

5	Those are pretty well defined criteria

6  that one subset of the aspect of this whole document

7  that I didn't see anything anywhere near as robust as

8  that applied to analysis of the other studies across

9  the document.

10	Now that may be a reflection of our

11  understanding of genetics and polymorphisms and

12  potential effects, but that was pretty hardcore biology

13  if you will, relative to let's take some measurements

14  and see what happens kind of thing.

15	And so whether you want to set the bar

16  at something like that or you want to remove that bar,

17  that's sort of not for me to say.

18	But the other thing I found about the

19  issue of susceptible populations was the   and this got

20  brought up early in the issue of dosimetry   was

21  whether or not the intrapulmonary distribution of NO2

22  relative to the anatomic site of disease should have

23  been included as part of the analysis.

24	And then I guess my last sort of general

25  comment was, as throughout the document there were no,

Page 220

1	I guess the main thing that I've focused

2  on or I noticed was the new lung growth studies that

3  have come out in the California Children's Health

4  Study.

5	And that was probably the, for me at

6  least was the biggest red flag that went up in terms of

7  protecting susceptible populations.

8	What's not present in the chapter

9  though, at least that I can dig out, was at what level

10  these kinds of effects can be seen, what was the

11  exposure history of these children?  And how did that

12  compare to the current standard?

13	But I think in terms of the risk

14  assessment document that's definitely I think a group

15  that should be focused on.  Asthmatics too, there's

16  been new information that has come out having to do

17  with hyperre   enhanced hyperreactivity by NO2 and

18  infection, more susceptibility to infection.

19	So I think that's also a group, a

20  subgroup to be focused on.  Probably in my way of

21  thinking though I would put more weight on the

22  children.

23	The elderly, I think the results on the

24  effect of age, elderly versus say middle aged or young

25  adults, that's kind of mixed and I'm not, it appears as

Page 219

1  there was no integration among the disease states,

2  measured outcomes, exposure and importantly, the

3  potential mechanisms of action that would relate NO2

4  exposure to why this group would be a susceptible

5  population.

6	It was pretty open ended.  And maybe

7  that information doesn't exist, but I think even

8  potential mechanisms would help strengthen it.

9	Other than that, you know, the

10  information, it was essentially presented before in

11  other aspects of the chapter and so I guess I'll

12  withhold any other comments until I hear the rest.

13	DR. HENDERSON: Okay.  Jim Ultman, are

14  you on?

15	DR. ULTMAN: Yes, can you hear me okay?

16	DR. HENDERSON: Yeah, but we always could

17  do better if you'd talk a little louder.

18	DR. ULTMAN: All right, I'll give it a

19  shot.  I agree with the comments that Ed made.  This is

20  a fairly qualitative chapter.  And it includes useful

21  information on asthmatic elderly and children as the

22  subgroups which I think have traditionally been the

23  ones that EPA has focused on with NO2 and for which

24  there is new information available since the last

25  review.

Page 221

1  if that's not a sub-population.  It really would

2  require much more emphasis.

3	So I think that the, basically the

4  information is here in terms of pointing out the new

5  information that's available to perform the risk

6  assessment.  But the same comment I made in one of the

7  other chapters was that there's not any real context

8  for this in terms of the current standard.

9	So I still can't tell whether the

10  effects that are being seen in children and asthmatics

11  are at or below or above the current standard.  So that

12  perspective is still missing from the chapter.  It

13  would be nice if that could be put in somewhere.  And

14  of course we also measure it.

15	We mentioned before, and Ed brought it

16  up again, the question of dosimetry and whether an

17  equivalent dose of NO2 in children at a given exposure

18  concentration would be the same as in adults.  And I

19  know there is some information that's come out on ozone

20  in that regard recently.  I'm not sure if there's

21  anything on NO2, but presumably the authors have looked

22  at the literature for that.  If they haven't they

23  should, you know, go back and see if they can put some

24  information in this particular chapter on the affect of

25  these, the differences in the sub-populations,

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Page 222

1  particularly the children because of their size, on the

2  affect of the dose that they're getting relative to an

3  adult.

4	And that's it.

5	DR. HENDERSON: Okay, thanks, Jim.  Are

6  there any other people who want to make comments.

7  There's Ed.

8	DR. AVOL: Yes, this is Ed Avol.  I've

9  thought a little bit about the susceptibility issue and

10  have a suggestion that may be worth considering for the

11  staff.

12	And that is the following.  Does it make

13  any sense, does this idea have some merit to consider

14  susceptibility in the context of the following

15  categories?

16	You might think about biological

17  susceptibility which would include the sorts of things

18  we've been talking about, either disease or age or

19  children or these sorts of things.

20	You might think about socioeconomic

21  susceptibility which would have things like a lower

22  SES, stress, violence.  I know there's been a little

23  bit of work in that area and some of which is reported

24  here.

25	And then you might think about

Page 224

1  susceptibility, biologic susceptibility if you will, to

2  NO and NOX.

3	And that the studies up to this point

4  are really a little bit like sort of looking under a

5  light post.  You know, we're taking those genes that we

6  think are going to be important without actually the

7  question about what genes should be important or taking

8  a much more systematic sort of evaluation of genetic

9  susceptibility and what it means in terms of the

10  criteria document and setting the standards.

11	I guess that gets more into the

12  recommendations that I was suggesting before.

13	DR. HENDERSON: Ed.

14	DR. AVOL: It's Ed Avol, just one more

15  comment in answer to Jim Ultman's question about the

16  levels of exposure in the Children's Health Study with

17  regard to NO2 and lung function and whether those are

18  above or below the standards.

19	In fact those are below the current

20  standard.

21	DR. HENDERSON: Okay, that's important to

22  know.  Yes, Terry.

23	DR. GORDON: I still want to bring my

24  earlier point and wonder what's the justification for

25  having a separate chapter?

Page 223

1  locational susceptibility which is also talked about

2  here to some extent.  And these are things like in-

3  vehicle exposures, living close to roadways.

4	And wether thinking about it in those

5  sort of terms helps to clarify and identify in some

6  logical framework, who and how large those susceptible

7  sub-populations might be.

8	DR. HENDERSON: Thank you, Ed.  And

9  Steve, I know you made comments on this chapter before.

10  Did you have anything you wanted to add?

11	DR. KLEEBERGER: No, not really.  I think

12  in terms of what Ed has just suggested I think is a

13  great idea.  I know I remember reading I think in this

14  document, attempts to sort of subdivide into perhaps

15  intrinsic and extrinsic or internal and external

16  factors of susceptibility.

17	But I think helping to categorize or in

18  some way compartmentalize the different ways we might

19  look at susceptibility might be an appropriate move.

20	The, I guess I would also like to make

21  a, maybe this is a plug, but a statement that in terms

22  of susceptibility and genetics, I think the section in

23  the document in Chapter 4 was actually very nicely

24  written and indicates there is great potential in terms

25  of genetics and genomics for helping us understand

Page 225

1	Are you going to leave out the children

2  or the aged from the earlier chapter on the health

3  effects and just include them here?  Or are you going

4  to repeat it?

5	I'm just not sure.

6	DR. HENDERSON: We can ask   well

7	DR. COTE: The actual intent of that was

8  to bring it out and highlight it as being more

9  important.  It doesn't exactly sound like that was a

10  successful strategy.  So we might consider integrating

11  it back into Chapter 3.

12	DR. GORDON: Well having it separate and

13  bringing it out sounds okay too.  It just would need

14  more of it.

15	DR. HENDERSON: Yeah, I interpreted it as

16  trying to emphasize.

17	DR. COTE: Is it worth a different

18  chapter to do it that way or does it achieve the

19  desired effect to have a separate chapter?

20	DR. POSTLETHWAIT: To follow Ed's

21  suggestion about the level of categorization, and I

22  think it is useful because it puts into context the

23  various aspects of the genesis of susceptibility,

24  whether it's geographic locale or underlying genetic

25  polymorphisms or whatever, that the broad spectrum of

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Page 226

1  sort of the 30,000 foot view in Chapter 3 won't

2  address.

3	So a tweak and tighten up and I think

4  actually it is useful as a standalone.

5	DR. KLEEBERGER: I do too.  I think

6  there's a danger if we include it.

7	I appreciate your point, I think it's a

8  difficult separation.  But if you don't separate it I

9  think you run the risk or the danger of having it

10  covered or embedded so far in that it's not going to

11  be, the point isn't going to be made that

12  susceptibility is an important issue to consider.

13	DR. GORDON: Overall I agree that it

14  should be separate showing special emphasis.  I guess

15  part of, I tend to think that susceptibility as I

16  assume you do, is physiologic or genetic.

17	And so I'm sort of surprised that

18  susceptible to me doesn't necessarily mean those who

19  live in traffic areas.  It's just one part of the

20  continuum or exposure.

21	And I guess that's the part that I

22  really thought was an odd choice for susceptibility.

23	DR. POSTLETHWAIT: It's a high exposure

24  category.

25	DR. HENDERSON: Yeah, it's higher

Page 228

1  and forth to figure out where I liked it and then

2  finally left it in 2.

3	DR. HENDERSON: Well some of that is, I

4  thought was the best causal data you had for NO2

5  because it was indoors and through a controlled study,

6  et cetera.

7	From my viewpoint it would beef up the

8  health chapter to have it in there, but we're talking

9  editorial things here.

10	George?

11	DR. THURSTON: Yeah, George Thurston.

12  Yeah, I think looking at it I like the idea of having a

13  separate chapter.  But I think also the point that Ed

14  was making was, at least as I took it, about the lung

15  function is you see the effects in the kids with

16  asthma.  You also see it in the kids not having asthma,

17  so we shouldn't forget those.

18	I think it's important when you're

19  talking susceptible populations to make sure people

20  don't suddenly think, oh, well then everybody else is

21  not susceptible, which would be wrong.

22	And so I think we have to make sure to

23  always sort of   I think maybe an introductory

24  discussion, well you know, a sentence or two or a

25  paragraph saying that everyone is affected, it's a

Page 227

1  exposure.

2	DR. ULTMAN: Yeah, I forgot to mention

3  when I was speaking, I agree with that, that section on

4  high exposure groups belongs in the exposure chapter,

5  not here.

6	It's really just a question of exposure,

7  not a question of

8	DR. POSTLETHWAIT: And Jim, would you say

9  that again and try to scream it into your cell phone.

10	DR. COTE: I think he's on the other

11  line.  I think what he said was that the high exposure

12  assessment belonged in the exposure chapter.

13	And it's kind of one of those

14  discussions, if that belongs in the exposure chapter,

15  then the health stuff may belong in the health chapter.

16	So it's six of one and a half dozen of

17  the other.

18	DR. HENDERSON: Yeah, there was some in

19  the Chapter 2 that was health.

20	DR. COTE: You know, I put that in

21  because I was, I thought the traffic related things

22  that were raised there, I was afraid if you waited

23  until the end of several chapters later that it at that

24  point wouldn't be clear.

25	I took that section and moved it back

Page 229

1  question of the degree to which those affects have

2  health implications.

3	I would say that a child who has asthma,

4  if they're getting the same lung function reduction as

5  a healthy child, it likely has more of a health

6  implication because they're starting out with reduced

7  lung function and then they're going to have an asthma

8  attack or, you know, on top of that.

9	So they have the same lung function

10  effect perhaps, but the health implications of those

11  effects are greater and I think that's true with many

12  susceptible populations, that they just can't cope with

13  the effect, as well with the effects that we all get.

14	So we don't want to forget that we're

15  sort of all in this together and these are just the

16  especially susceptible that we're focusing on.  And,

17  because you might be left with the impression that this

18  is a very small number of people that we're talking

19  about, you know.

20	And I don't know what the number is,

21  you're going to probably come up with some estimates.

22	DR. COTE: Well that was why I had

23  actually put that table in there about the number of

24	DR. THURSTON: Yeah.

25	DR. COTE:   asthmatics.

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Page 230

1	DR. THURSTON: Right.

2	DR. COTE: It's not that they're all

3  susceptible.  Were you speaking about air pollution in

4  general, George, or NOX specifically when you were

5	DR. THURSTON: Well I would say, you

6  know, probably air pollution in general but

7	DR. COTE: I just wanted to pin you down.

8	DR. THURSTON: But I think that it

9  applies across the board.  You know, the concept of

10  that the effects, you know, how we define susceptible

11  and especially, oh, I would say especially susceptible

12  populations, rather than just susceptible.

13	And a couple of other comments on it was

14  I liked to, I would think about using attributable

15  risks in the discussion, because if you just compare

16  relative risks, sometimes you can take different

17  populations and they can have fairly similar relative

18  risks, but one has such a much higher baseline that

19  you're talking about many more adverse health outcomes.

20	DR. COTE: Yes.

21	DR. THURSTON: If you have twice the

22  number of hospital admissions let's say in one group

23  versus another, and you have the same percentage

24  increase, that's many more per 100,000.

25	And so maybe it's worthwhile trying to

Page 232

1  Just not looking at them independently, but also

2  saying, you know, is there overlap and is that

3  population   and, you know, I think you'll end up with

4  saying that kids with asthma in inner cities are going

5  to be an extremely susceptible population when you're

6  done with that.

7	DR. HENDERSON: Okay, thank you, George.

8  I'd like to go on to the final charge question which is

9  the be all and end all.  I mean it really covers the

10  whole question and while we have two lead discussants,

11  everyone should chime in after they're through.

12	The question is, what are the panel's

13  views on the adequacy of this first external review

14  draft ISA to provide support for future risk exposure

15  and policy assessments?

16	In other words, is this document going

17  to help Karen Martin and her group go to the next

18  level?

19	And so I have asked Doug Crawford-Brown

20  to lead off.

21	DR. CRAWFORD-BROWN: Well there are a lot

22  of issues with this chapter.  I'll sort of summarize

23  them relatively quickly.

24	I was looking for the analogy here on

25  this and it's sort of like going into a car dealership

Page 231

1  work in that concept when you're looking at these

2  susceptible populations.  And, you know, ultimately

3  you're going to look at counts of effects and that

4  attributable or absolute attributable risk is a concept

5  that I think helps clarify.  Because you can look at

6  relative risks and say, gee, these aren't that, you

7  know, let's say, you know, if you have a certain

8  percentage death increase in older people which, older

9  adults which I prefer to, versus elderly, I'm getting

10  too close, I don't like that elderly term, but anyway

11  that's semantics, then if you look at it that way, you

12  know, you could say, well, you know, a 10% increase.

13  But there's a lot of older adults who are dying, and

14  that's a much bigger number than younger adults.

15	And then lastly, also, each of these is

16  looked at independently, these susceptible populations

17  as you go through.  You know, children, people with

18  asthma, people living in   and I alluded to this

19  earlier but I'll just repeat it, that I think you have

20  to look, what's the intersection of these?  Because I

21  do think there's a population that is a big chunk of

22  these especially susceptible people that have all of

23  these.

24	In other words they belong to more than

25  one category.  And I think that's worth looking at.

Page 233

1  to buy a car and the dealer gives you a pile of ore and

2  a bolt of cloth.  And I sort of felt, well, could you

3  assemble it a little?

4	It gets you a pretty good Deux Chevaux

5  by the way, but that's not anything you'll drive

6  outside of France.  And I say that as a former Deux

7  Chevaux owner.  A lover of Deux Chevaux.

8	I think I mean part of the issue that

9  gets raised here is sort of the working of the charge

10  which is, on this first external review draft, can this

11  first external review draft provide support for future

12  risk and so forth?

13	And, well, if you ask, can the whole

14  report provide the support?  That's a different

15  question than, does Chapter 5 take all of the material

16  from the earlier chapters, abstract it, summarize it

17  and make it ready for consumption as a vehicle?

18	And on that latter question I would say,

19  no, I don't think so right now.  I find a lot more in

20  the report as a whole than I find in Chapter 5.

21	And now I know that Karen is right about

22  the fact that we aren't drawing conclusions here about

23  specific risk estimates or what the form should be and

24  so forth, but it is an integrated assessment.  And I

25  don't know what the word integrated means outside of

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Page 234

1  specific questions that you're trying to address.

2	And it seems to me that those questions

3  are, eventually, not in this document but eventually

4  are, what is the incidence of disease in the population

5  of the United States at different levels?  What should

6  be the form?  What should be the level in the statute

7  and so on?

8	And I just don't think Chapter 5 gets

9  you there yet.  I think if you tore Chapter 5 loose

10  from the rest of the document you just couldn't use

11  what's in Chapter 5 to answer any questions that I

12  think lie at the heart of what we mean by an integrated

13  assessment.

14	Now, part of the problem arises from the

15  fact that I don't think Chapter 5, the bullets in

16  Chapter 5, are in fact that most relevant bullets that

17  you would get from the earlier chapters.  I'm not sure

18  if the people who wrote the earlier chapters got to be

19  the nominators for the bullets that go into Chapter 5.

20  Of if somebody who wrote Chapter 5 just went in and

21  decided what they thought, you know, Chapter 2's major

22  points were and so forth.

23	I didn't get a sense of the latter very

24  much.  I mean I got a sense more of the latter than of

25  the former here.

Page 236

1  concrete points?

2	DR. HATTIS: I tend to agree with that,

3  that essentially, you know, Chapter 5 and to some

4  extent the earlier chapters bring together like data

5  of, data of particular study types and give a survey of

6  them.

7	And they tend not to do an overall

8  uncertainty weighted inference from the data of

9  particular types.

10	And in particular what would be needed

11  for the next step is to make some inference of, you

12  know, not only is there likely a causal connection

13  here, but what do the data say about concentration

14  response relationships?

15	And I'm going to pick on one in

16  particular where, just so that no good deed goes

17  unpunished, is the data from the Von Strem study which

18  is a study of indoor exposures to NO2, measured on time

19  in one year olds or in babies within the first year of

20  life, usually between the second and fourth month of

21  life, and asking the parents repeatedly independent of

22  knowing what the exposure was, whether they had

23  persistent, how often they had persistent cough and

24  wheeze and a couple of other respiratory symptoms.

25	And basically then they went on to

Page 235

1	So you have the problem that I'm not

2  sure the bullets in Chapter 5 reflect the most

3  important parts of the earlier chapters.  And then I'm

4  not sure how you bring the bullets together in Chapter

5  5 to be able to address any of these questions that I

6  think ultimately someone using the chapter is going to

7  want to address.

8	Having said that I like the way in which

9  the sort of strength of evidence was at least discussed

10  in there.  I like the categorization scheme and that's

11  exactly the kind of integration that you would want to

12  see in something like this.  I'm not sure it was

13  applied very formally, I'm not sure how anybody who

14  made the judgement that it's suggestive or strongly

15  causal or something like this, made that judgement

16  because thee is no architecture of thought in here.

17  There's no, there's no sort of framework that's given.

18	But I think the main issue, and I'll let

19  Dale really touch on some more concrete points here, I

20  think the main issue has to do with the fact that

21  Chapter 5 doesn't point the reader towards any specific

22  questions that are going to eventually have to be

23  addressed by the risk assessment side and by our CASAC

24  at some point in time here.

25	So Dale, do you want to hit some more

Page 237

1  divide the group into four quartiles and the figure

2  2.7-3 shows a plot of these quartile data.  And I had a

3  very detailed suggestion to re-plot the data according

4  to basically the, as is usual the exposures of the

5  individual subjects were lognormal approximately.

6	And so that when you plot quartiles as

7  if they are equidistant from each other, you're

8  essentially plotting things on a log x axis, and that's

9  know to create distortions of a particular kind in ways

10  that tend to make you see thresholds when they aren't

11  there.  When even if you had a nice linear

12  relationship, it would appear to be an upward turning

13  curve.

14	You don't in fact see that in the

15  quartile, they're there, but I felt it would still be

16  more revealing to re-plot the data, estimating means

17  within, mean exposures within the quartiles and see

18  what the concentration response looks like from the

19  existing data which are pretty noisy.

20	And in my comments you'll see the plots

21  and essentially they look a little bit saturating in

22  their types, okay?  And these are indoor exposures.

23	This does not get rid of the problem of

24  possible confounding with other pollutants that are

25  all, that are correlated with indoor exposures to NO2,

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Page 238

1  but it does I think provide another piece of evidence

2  that goes together with the intervention study, which I

3  agree is some of the strongest kind of evidence.

4	But still, we have this problem of the

5  potential confounding with effects of other correlated

6  pollutants.

7	Anyhow, this type of plot still does

8  better at getting you an indication of concentration

9  response.  It still has its distortion in that they

10  only measured each person's, each one year old, or each

11  four month old's exposure once, okay?

12	And because they only measured it once

13  you're not quite sure that this is representative of

14  their long term average concentrations.  In fact the

15  people who you, who they, who they think are relatively

16  high in this highest quartile, probably tend to be, to

17  have average exposures less than that because of

18  regression to the mean effects.

19	Had they measured them ten times they

20  would have had, they would probably have had, tended to

21  have lower average exposures than the average that I

22  calculated from the, for the highest quartile.  And

23  conversely, the people who they think, or they

24  classified tentatively in the lowest quartile probably

25  tend to have higher average quartiles than you would

Page 240

1  of the data in some fair combined sense, but that's a,

2  you know, that meta-analytic type of exercise is

3  slightly different than this, although it should

4  probably benefit from the same kinds of considerations

5  because you don't want to bias your overall conclusions

6  by cherry picking as you said

7	DR. COTE: No me.

8	DR. HATTIS:    only the ones who happen

9  to be positive.  So essentially what you do need to go

10  to the next step is in fact to analyze well, you know,

11  any concentration response, you know, some of the

12  studies where you happen to have unusually good

13  information.  Not necessarily only the positive ones,

14  but unusually good information.

15	DR. HENDERSON: Thank you, Dale.  Do any

16  of you want to add to this discussion of Charge

17  Question 8, which I interpreted to include more than

18  Chapter 5, but any other general comments on how well

19  the document supports the future risk exposure and

20  policy assessment?

21	And I will ask   did someone raise their

22  hand?  Ah, Ellis, yes.

23	DR. COWLING: It seems to me that the

24  question that Doug raised, how were the authors of

25  Chapter 2 related to the authors of Chapter 5?

Page 239

1  expect just because, for the same kind of phenomenon

2  that if you have a baseball team and you look at their

3  batting aver   the distribution of their batting

4  averages after the first ten weeks of the season, you'd

5  find you have lots and lots of 400 hitters.

6	And by the end of the season you don't

7  have any 400 hitters because of the increased sample

8  size for the hitting performance.

9	And so in order to get a real feel for

10  what the indicated concentrations times time,

11  concentration versus effect incidence should be from

12  this, these data, what you would want to do is to take

13  into account this, the effect of measurement

14  uncertainty on the slope of the dose response

15  relationship.

16	So that would be the way I would try to

17  process the very best few data sets, okay, that you

18  have to try to get whatever insights they can provide

19  about concentration response.

20	DR. COTE: Just to be clear, what you're

21  suggesting is picking the best data sets we have and

22  looking at those in detail?

23	DR. HATTIS: Yeah, I mean because to some

24  extent you can have, you know, data sets that are, you

25  know, there is also a place for taking into account all

Page 241

1	I think that's a very important

2  procedural question and it seems to me it's ideal if

3  the author of any of the chapters was the principal

4  architect of the candidate as you called or the

5  nominator of the statements that would go in Chapter 5.

6	If you look at the question of how many

7  of the bulletized statements that are in Chapter 5 are

8  relevant to the question of whether we have a

9  satisfactory or unsatisfactory standard, there are only

10  6 out of those 47 that are directly relevant to the

11  question of the adequacy of the present standard.

12	So George made a suggestion earlier

13  today that there should be a scan of the content of

14  chapter, or whatever summary chapter we have to be sure

15  that there is an adequate emphasis on things that are

16  directly relevant to what should be done.

17	And I understand the caution about going

18  too far with that because you're to turn this thing up

19  to an Integrated Science Assessment, but rather into a

20  policy document.

21	So there needs to be an excellent

22  summary it seems to me of the information that is

23  essential for making judgements about whether the

24  general tenor of this document is favorable to the idea

25  the we ought to make some adjustment in the standard,

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Page 242

1  or not make an adjustment to the standard.

2	So, I would hope that very careful

3  attention would be given in the next integrated

4  assessment document that we see, to the very careful

5  formulation of summary statements from all of the

6  things that are covered in each of the chapters, and

7  that those become the candidates for the summary.

8	And I would agree with George Thurston's

9  recommendation that a scan of those statements of

10  findings, maybe preliminary statements of findings, are

11  evaluated in a coherent set of policy relevant

12  statements is being presented as the foundation for the

13  decision making process.

14	And on page 5 of my individual comments

15  you'll find an outline, a guideline for a series of

16  questions that were suggested by the Oversight Review

17  Board for the NAPAP Program, the National Acid

18  Precipitation Assessment Program.  And the group of

19  people that put those, that checklist series of

20  questions together is how to evaluate a statement that

21  tells the truth about some phenomenon that is relevant

22  to the decisions that are being made.

23	And I would encourage, and I said in my

24  statement I hope that you might look at those

25  guidelines for the formulation of those kinds of very

Page 244

1  our conclusions from the science if you can offer any

2  feedback to us.

3	DR. HENDERSON: So we could put it up

4  there.  Everyone should have a copy of the   it's

5  slides 15 and 16.

6	So that's a good idea, Mary.  We can

7  discuss these individually.

8	The key conclusions are for short term

9  and long term exposures.  These are the short term.

10  Respiratory morbidity is deemed likely causal.  Then

11  there's four points given under that which, rather than

12  me reading it, you can just read it off of there.

13	And I'd like to hear if anybody

14  considers this not likely causal.  I mean if you have

15  any problems with this conclusion.

16	DR. POSTLETHWAIT: Considering all the

17  uncertainties we've heard today, is everyone

18  comfortable with the likely causal related to NO2?

19	DR. AVOL: This is Ed Avol.  Again I

20  think we've talked about some of this through the day

21  that there's sort of been, I get the general sense that

22  there's consensus that there's been a, either, not a

23  transparent or an inconsistent determination of what

24  goes into the equally likely causal inconclusive

25  suggestion, and that if in the document if there was a

Page 243

1  carefully crafted statements of scientific findings

2  which could be used for policy purposes, and that that

3  be done in the next assessment, number two, external

4  review draft.

5	That's all that I wish to say.

6	DR. HENDERSON: Thank you, Ellis.  And of

7  course your comments as well as everyone's comments

8  will be attached to the letter that goes to the

9  Administrator.

10	I'd like to, before we go into the

11  summary section, ask the NCEA folk if you have any

12  questions or any more advice that you would like from

13  us that we have not given?

14	DR. ROSS: Well, as Karen said, I think

15  we'd like to invite you to also comment on even the

16  conclusions.  On slides 15 and 16 I summarized the real

17  brief points we had.

18	You know, you've been talking about some

19  of the evidence, but whether or not you agree with us

20  that the science, the evidence for respiratory

21  morbidity would be likely causal or such, where we have

22  suggestive, inconclusive or limited evidence for the

23  other health outcomes discussed on those two slides.

24	So we're inviting discussions of the

25  science too, how well we've pulled this together and

Page 245

1  clear tabulation or algorithm or something for how one

2  gets to this, then these might flow more smoothly.

3	It's not clear from what has been

4  presented that these are consistent with what's been

5  shown.

6	DR. CRAWFORD-BROWN: Yeah, I think that's

7  the direction I was going to say too, is that there's a

8  big difference between asking the CASAC what their

9  opinion is on these things, and asking the CASAC

10  whether this document makes the case for these things.

11	And I've really been assuming it's sort

12  of the latter issue.

13	When I look at Chapter 5 for example,

14  I'm not sure I would necessarily disagree with those

15  things.  I'm not sure that if I did a close reading of

16  the text of Chapter 5 the case is made coherently for

17  those particular claims right there.

18	DR. COTE: I guess what would be useful

19  is, you know, I think a number of things that need to

20  be changed in the document to clarify the case have

21  been identified, and that's been very useful.

22	But when we come back again, you know,

23  to the extent you have a sense of the underlying

24  scientific data, are we headed in the right direction

25  with these conclusions?

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Page 246

1	And the supporting evidence, I mean like

2  one of the things I heard is, even if everyone agreed

3  upon this, one would want to see another statement

4  about mode of action and the clinical and animal data.

5	So I think what Mary was more asking was

6  not so much did the document lay out the case, but

7  what's people's feeling about the science?

8	DR. HENDERSON: I will go out on a limb

9  and say, though I think it could be presented much

10  better, I don't have any problem with the likely causal

11  respiratory morbidity effects based mainly on the

12  Australian studies in the homes, indoors.

13	I mean that was a convincing study for

14  me.  But others should say what they think.

15	Yeah, George?

16	DR. THURSTON: This is George Thurston.

17  What I would say is that I would, that there is sort of

18  the rankings of these I would agree with.

19	In other words the case is strongest for

20  respiratory morbidity and so forth.  And I'm still, you

21  know, whether I would use exactly likely causal or not,

22  you know, could go up or down in terms of causality for

23  me once I see the revised report in terms of, you know,

24  looking at Hill's criteria and then looking at the

25  evidence for each across all the outcomes and the

Page 248

1	DR. THURSTON: And this is sort of a

2  basic question, this is George Thurston.

3	But, you know, is, let's, I mean if you

4  get right to the endpoint and say, well, if we control,

5  set a lower standard for NO2, will these health

6  benefits be achieved, is a slightly different question

7  than, will the reductions of NO2 themselves, and alone,

8  cause those benefits?

9	Because I believe that if we were to set

10  a more stringent, or set a short term standard, that if

11  you controlled NO2 you would also control co-

12  pollutants, there would be co-benefits associated with

13  this, such that, you know, the   do you see what I'm

14  getting at?

15	You know, the real question I think is,

16  if we control, if we set a more stringent standard,

17  will health benefits be accrued?

18	And, you know

19	DR. ULTMAN: George, I would defer to

20  the, you know, the affected industry to, especially the

21  automobile industry, but I don't know that that's

22  always going to be the case.  I mean especially the

23  ultra fine NO2 connection.  It's not clear to me that

24  if you go after NO2 in these latest control strategies,

25  that you're going to also by definition go after ultra

Page 247

1  information.

2	But I think that certainly the direction

3  of this and where you're putting the most reliance, I

4  agree with based on what I've seen.

5	DR. HENDERSON: Do other people wish to

6  commit or say anything?

7	DR. LARSON: This is Tim Larson.  I've

8  been putting in the qualifier about the surrogate

9  exposures for especially those indoor studies.

10	But I think what puts this in that

11  category are the clinical studies.  Even though the

12  symptoms are not, you know, necessarily the same as,

13  you don't get the same effect, clearly those are

14  several hour exposures and it's difficult to tease that

15  out.

16	If the clinical study shows no

17  inflammatory effects, hyperresponsive effects, then I

18  would probably lean on the other side, but I think I'm

19  persuaded that this is reasonable, given that, as well

20  as those indoor exposures as well the somewhat

21  confounded EPI work, the outdoor EPI work.

22	DR. HENDERSON: Anybody else have

23  comments?

24	DR. THURSTON: I have a question.

25	DR. HENDERSON: Okay.

Page 249

1  fine.

2	DR. THURSTON: Right.  Well, I mean but

3  couldn't that assessment, part of a, maybe I'm getting

4  into tomorrow.

5	DR. ULTMAN: Yeah.

6	DR. THURSTON: But couldn't you make that

7  assessment as part of it?  In other words

8	DR. ULTMAN: Sure, sure.

9	DR. THURSTON:   not just do a benefit

10  analysis, or impact analysis or whatever we want to

11  call it

12	DR. ULTMAN: Right.

13	DR. THURSTON:   looking only at NO2, but

14  saying, okay, if we could, if a standard were set here,

15  what changes would there be in NO2 and PM?

16	I would actually think that if you

17  included those two and then, you know, you could use

18  epidemiology where they've used PM and NO2 together, I,

19  you know, then I would, on just those two pollutants

20  then together they're, I don't like using individual

21	DR. ULTMAN: I would agree with you,

22  George.

23	DR. THURSTON:   things, but you know, if

24  you used them both together then the net impact is

25  correct.

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Page 250

1	So, you know, along, I'm thinking along

2  those lines.

3	DR. ULTMAN: It's better anyway.

4	DR. THURSTON: What?

5	DR. ULTMAN: It's better anyway, a meta-

6  analysis of proof.

7	DR. HENDERSON: Ted.

8	DR. RUSSELL: I would definitely with

9  what Tim is saying on that is, I'd be very cautious

10  about even thinking in that direction, by decreasing

11  the NO2 necessarily you are decreasing ultra fine

12  particulate and vice versa.

13	And that some of these control

14  strategies are the ones that are going to decrease

15  particulate but possibly increase NO2.

16	DR. COTE: The other thing is I'd rather

17  like just settle that we have the right words here

18  before we

19	DR. RUSSELL: Sorry, maybe we'll worry

20  about that tomorrow.

21	DR. COTE: I understand the need to

22  protect the public health of America though.

23	DR. RUSSELL: Well yeah.

24	DR. HENDERSON: Yeah, what's really being

25  asked is, is there a likely causal effect of NO2

Page 252

1  interpret the EPI studies and the Australian studies,

2  is there confounding or not?

3	When Samet spoke earlier he I think sort

4  of blew them away, saying that it was very little

5  relevance, didn't he?

6	DR. HENDERSON: No, I thought he liked

7  the Australian study.

8	DR. GORDON: Well someone spoke and said

9  that they thought this was a

10	DR. SAMET: This is Jon, I'm on actually.

11	DR. HENDERSON: Terry, there's Jon now.

12	DR. SAMET: Could I make one comment?  I

13  mean I think the Australian study I think is very

14  useful.  I think the dilemma and I think George's

15  question or comment speaks to this, is what inference

16  about NO2 based on the indoor may not be informative as

17  to what will happen with reduction of outdoor NO2

18  where, I mean, that's where the need for integration

19  comes.

20	Because, you know, obviously all the

21  chemistry, the transformation and what is happening

22  outdoors is substantially different from indoors.

23	So they are distinct questions.  One is,

24  are there health effects of NO2?  And the second, what

25  would follow from reduction of NO2 outdoors?  Perhaps

Page 251

1  exposure on respiratory morbidity?  And it may be based

2  on non-environmental studies like was mentioned, the

3  human clinical studies and the indoor studies.  And

4  we've based it on that because we can pin it down to

5  NO2 itself more readily than if we do outdoor studies.

6	So to me we oughtn't to get off into the

7  environmental thing right now because we're only

8  asking, is there a likely causal effect of NO2 on

9  respiratory morbidity?  And are there studies that

10  would suggest that?

11	Okay, Terry.

12	DR. GORDON: Well I'm not going to speak

13  necessarily for the other toxicologists, but I'm

14  confused, I haven't heard this group come to a

15  conclusion yet on exactly that issue, likely causal.

16	Is there confounding or not?  And I just

17  would like some guidance from the epidemiologists.

18  I've heard both sides, I heard skirting around and some

19  saying absolutely and some saying no.

20	And I feel like maybe are we ignoring

21  that by just saying likely?

22	DR. HENDERSON: I'm not really

23  understanding your question, Terry.  Because this is a

24  qualitative, this likely causal.

25	DR. GORDON: But it depends on how we

Page 253

1  the benefits would be greater than anticipated because

2  of PM reduction for example.

3	So they're distinctive questions.

4	DR. HENDERSON: Well

5	DR. SAMET: I think what's the use of the

6  NO2 study, the Australian study, was the fact that it

7  was NOX or NO2 largely that was being investigated.

8	DR. HENDERSON: I agree with you, Jon,

9  there's two questions being asked here and I think

10  today we just want to ask that first question.

11  Tomorrow we're going to address the other.

12	That's my opinion.  Is that what you

13  want, I mean

14	DR. COTE: We don't want to address the

15  issue of control strategy --

16	DR. HENDERSON: That's not the

17	DR. COTE:   here, today.

18	DR. HENDERSON:   purpose of the ISA.  If

19  we look at cardiovascular morbidity you say

20  inconclusive.  What do people think of that?  I don't

21  want to say what I think because it's   I want to hear

22  what you think.

23	DR. CRAWFORD-BROWN: If we're talking

24  about, you know, 10,000 parts per million then the

25  answer is, yes, yes, yes, yes.  And if we're talking

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Page 254

1  about, you know, 10 parts per billion, I don't

2  understand yet what the level of exposure is.  Are we

3  talking about current ambient levels?

4	DR. ROSS: Current ambient levels.  In

5  the Rogers studies they're generally using current

6  ambient levels.  Some of them were conducted perhaps in

7  the '80s when the levels might be higher.

8	But that was the actual purpose of

9  Tables 5.3 and 5.4, that listed, they listed levels

10  from the studies, some examples of distribution data

11  from the EPI studies.  And you can see that the levels

12  are in many cases quite low.

13		DR. CRAWFORD-BROWN: Okay.  I keep coming

14  back to the text though.

15	DR. ROSS: From the EPI studies.

16		DR. CRAWFORD-BROWN: What we have here is

17	DR. ROSS: Right.

18	DR. CRAWFORD-BROWN:   is respiratory

19  morbidity likely causal?  It doesn't say is respiratory

20  morbidity at current ambient levels?

21	Is that the question we're asking?

22	DR. COTE: Yes.

23		DR. CRAWFORD-BROWN: Okay, because in my

Page 256

1  everything out there.

2	DR. HENDERSON: Yeah.  Okay, George?

3	DR. THURSTON: Well I'm sorry, at the

4  risk of being a troublemaker.

5	DR. HENDERSON: Yeah.

6	DR. THURSTON: Let me just try one more

7  try, I mean I wasn't really getting into the regulatory

8  aspect.  I was sort of asking the question, are we, you

9  know, is the question, is NO2 alone causal?  Or is NO2

10  and everything that goes with it causal?

11	And I think you might come up with

12  different answers for those two.  And some people are

13  saying, well, it's confounding and it's negative.

14  Actually it's not negative, I mean it's actually, it

15  might explain the relationships.  You're saying when

16  you change NO2 you're changing other things along with

17  it and, you know, is NO2 and what the baggage it

18  carries with it, causal?  Or, do we have to stay with

19  only NO2?

20	DR. GORDON: That's what I was trying to

21  say.

22	DR. HENDERSON: Okay.

23	DR. COTE:  Do you want to speak to that,

24  Mary?

25	DR. HATTIS: Holding everything else

Page 255

1	DR. CRAWFORD-BROWN:   are much less

2  strong than

3	DR. COTE: I think that's actually in the

4  text.

5	DR. CRAWFORD-BROWN: It is in the text,

6  yeah.

7	DR. COTE: Yeah.  Yeah.  Yes, and that's

8  the rub.

9	DR. HENDERSON: Okay.  I'm looking   and

10  all cause mortality suggestive evidence, I don't,

11  anybody want to comment on that?

12	DR. WYZGA: You know, one of the things

13  is that   and I think we just need to look carefully, I

14  think that there are a lot of studies out there that's

15  looked at a lot of pollutants and they tended to

16  emphasize the results were positive and sort of NO2 is

17  a little footnote.  We looked at it and we didn't find

18  anything.

19	And I think we need to look carefully

20  and see if there are more of these studies because that

21  might inform our conclusion.

22	I don't know, I have no opinion until I

23  sort of

24	DR. HENDERSON: See this whole issue.

25	DR. WYZGA: Right.  Until we see

Page 257

1  constant

2	DR. THURSTON: But

3	DR. HATTIS:    if you reduced NO2, would

4  you then

5	DR. THURSTON: Well that's not the real

6  world, that's not what's going to happen.

7	DR. HATTIS: No, but that's being

8  optimistic.

9	DR. COTE: I think what I would say that

10  we're addressing are oxides of nitrogen which isn't

11  exactly NO2 but

12	DR. THURSTON: Well

13	DR. COTE:   oxides of nitrogen.

14	DR. THURSTON: Well I know we're using

15  NO2 as a standard.

16	DR. COTE: Yeah, an indicator.  But yes,

17  I don't think we mean NO2 and PM.  Is that your answer?

18	DR. ROSS: I mean it's fair to discuss

19  the reality as Jon Samet shows in page 37 of the

20  comment, Jon Samet lists things that were discussed

21  before for other pollutants like ozone and particulate

22  matter

23	DR. THURSTON: Right.

24	DR. ROSS:    is that in a mixture of air

25  pollutants you can have complicated interactions.

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Page 258

1	For this document we're really looking

2  at NO2 studies, but recognizing that you can have NO2

3  as a marker for an air pollution mixture as you're

4  saying.

5	DR. THURSTON: Yeah, you

6	DR. ROSS: Where if you lower the NO2

7	DR. THURSTON:   because

8	DR. ROSS:    you're

9	DR. THURSTON: I guess what I'm saying, I

10  think you might miss all the co-benefits that go with

11  it, you know.  And maybe we're not allowed to consider

12  those, but they're, you know, the fact that other

13  things go up and down with NO2 is, some, I don't know,

14  somehow it's being seen as a negative.

15	But actually it may, you know, mean that

16  we're underestimating the benefits of setting a

17  standard by just looking at that along and ignoring all

18  that goes with it.

19	And that's what epidemiology does for

20  you.  It tells you what everything that goes with it

21  and then I think the toxicology and the human studies,

22  they're great because they can tell you about

23  mechanisms and biological plausibility, but the

24  epidemiology gives you, you know, the plus as I see it

25  of telling you, you know, if it goes down, what will

Page 260

1  independent of every other variable out there.

2	I think the issue is, do we think that

3  NO2 itself is a significant contributor?  If we thought

4  that NO2 is nothing but a surrogate and it had no

5  impact at all at those levels and the whole thing was

6  being driven by particulates, then we shouldn't

7  regulate NO2.

8	But if you think there is an NO2

9  independent affect which in this document there's quite

10  a few things to suggest that there is a robust affect

11  that tracks with NO2, if you think that's correct, well

12  I think we should not, then we should recommend and let

13  that become a regulatory issue.

14	But the issue that there's a confounding

15  with other factors is inherent in the entire air

16  pollution field for everything we do.

17	DR. HENDERSON: I think you put that very

18  well, James.  That's what I'm thinking, I mean, do we

19  think that NO2 has no affect at all?  And I think the

20  evidence here says, you know, there are studies that

21  show that it, when it's closely controlled as possible,

22  that there are, that there is a morbidity effect in

23  terms of the respiratory symptoms.

24	That's what I'm basing my own   for the

25  long term exposures it gets, you know, when you look at

Page 259

1  the benefits be.

2	And it's not necessarily a negative that

3  you can put another pollutant in there and pick up some

4  of it and all of that anyway.

5	So I mean my question was really geared

6  to today, whether we can, we have to just limit

7  ourselves to NO2 alone of NO2 and what goes with it.

8  Tha'ts my question.  Maybe there's no answer, but

9	DR. HENDERSON: We all have to, I mean

10  because they're asking us for advice and so we need to

11  discuss with them, you know, hey we, they're saying we

12  came up with a suggestive evidence for all cause

13  mortality.  What do we think about that?

14	And you've been discussing it at length,

15  I mean you're saying, well, we should take into

16  consideration everything else.

17	DR. THURSTON: Right, I guess I'm just

18  trying to define the playing field or the, you know,

19  how, what I've got in order to answer that question.

20  You know, what's the latitude I should say of answering

21  that question?

22	DR. CRAPO: I'd like to try to respond to

23  that because I think that the, this is a, we've faced

24  this problem with every single pollutant we've met.

25  And in every case nothing has operated completely

Page 261

1  the conclusions it's suggestive, so is there anything

2  in here that you would object to?

3	I mean we want to see more information

4  as to how that was determined, et cetera or you know,

5  presented in a systematic way.  But lung cancer

6  incidence, I have a little bit of a problem with that.

7	DR. AVOL: This is Ed Avol.  I guess in

8  the scheme of things looking at this   well first of

9  all let me preface this by saying that I agree actually

10  with what George previously said which I don't

11  necessarily agree with the absolute words that were up

12  there, but I agree with the relative ranking from the

13  previous one.

14	In the same sense of looking at this, in

15  particular I think there's stronger evidence for

16  respiratory morbidity than there is for lung cancer

17  incidence, so I would not rank those sort of equally.

18	But I don't necessarily agree with the

19  actual words and that's what my comment previously was

20  about the transparency in the documentation and how you

21  get to this definition.

22	DR. HENDERSON: I don't, for instance

23  under lung cancer incidence, suggestive evidence that

24  the atmospheric reaction products of NO2 such as nitro

25  pH may be carcinogenic, that's a very true statement.

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Page 262

1  By gosh, how much of that is in the air?

2	It's such a small concentration.  I mean

3  in an occupational setting you might get enough, but is

4  that why you said suggestive?  I don't know, I don't

5  quite understand the reasoning on that.

6	DR. COTE: I think that's right, I think

7  it was plausible.  But the evidence for, you know, the

8  EPI evidence itself wasn't particularly strong or

9  convincing.

10	DR. HENDERSON: If the dosimetry were

11  right it would be absolutely true, you know, but it

12  just

13	DR. COTE: Yeah, no, I don't think we've

14  done that.

15	DR. HENDERSON: Yeah.

16	DR. COTE: I mean it's hard.

17	DR. HENDERSON: Does anybody else have

18  comments on these conclusions that would help them in

19  how they present their data?

20	DR. CRAPO: I think the lung cancer, I'd

21  call it limited, not suggestive, it's still weak.  The

22  correlation is with air pollution.

23	DR. HENDERSON: Yeah.

24	DR. CRAPO: And specifically with NO, so

25  it's got limited data to my thinking.

Page 264

1  including lung cancer is inconclusive.

2	SPEAKER: And most people die when they

3  get lung cancer.

4	DR. POSTLETHWAIT: Yeah, in a fairly

5  rapid or short period of time.

6	DR. COTE: Well I guess though that it's

7  the comparison of the incidence, the occurrence of lung

8  cancer in one, and then when you look at all cause

9  mortality, the evidence is not as strong.

10	So that's just a function of the way,

11  you know, it's kind of just a factual interpretation of

12  what those sets of data look like.

13	Do you know what I'm saying?  Is that

14  clear?

15	DR. POSTLETHWAIT: Sort of.

16	DR. COTE:  There were very few studies

17  that looked at lung cancer mortality.  This is

18  mortality lumped together that includes all cause

19	DR. WYZGA: Why don't you just take out,

20  including lung cancer.

21	DR. COTE: Yeah, good idea.

22	DR. HENDERSON: Yes, that would make it

23	DR. GORDON: Ila, George and I were

24  trying to look up where you have these definitions.  Is

25  limited above suggestive?

Page 263

1	DR. CRAPO:   Well the other thing too is

2  that --

3	DR. HATTIS: Because you have the nitro

4  aerobatics, it's likely that there is some, but

5	DR. CRAPO: If the concentration is high

6  enough, we don't know that.

7	DR. HATTIS: Well

8	DR. CRAPO: That's why it's

9	DR. HATTIS:    I don't.

10	DR. HENDERSON: There was a voice on the

11  phone that I could barely hear.  Who was that?

12	DR. POSTLETHWAIT: I think that was me.

13	DR. HENDERSON: Sorry, you have to

14	DR. POSTLETHWAIT: Sorry, Rogene, I'll

15  pull the string tighter so you can tell I'm in the

16  room.

17	In fact considering the five year

18  survival rates for lung cancer, to have incidences

19  suggestive in mortality is inconclusive, seems to be a

20  bit of a disconnect.

21	Boy, did that get dead silence, whoa.

22	DR. COTE: I wasn't sure I understood

23  what you said.

24	DR. AVOL: Well if you look there it says

25  lung cancer, it says suggestive, but mortality

Page 265

1	SPEAKER: Yeah, that's not in there.

2	DR. COTE: You know I was actually

3	DR. ROSS: Go ahead.

4	DR. COTE:   limited actually just means

5  very few studies available at all.

6	DR. GORDON: That seems like it would fit

7  the lung cancer incidence as well, limited.

8	DR. HENDERSON: I would say, yeah, I

9  would rather have limited evidence on lung cancer.

10	DR. ROSS: Well we don't mean to force

11  anybody into making spontaneous decisions with this.

12  But we would welcome any input, you know, from a

13  science perspective from those of you who have been

14  studying this for sometime.

15	DR. HENDERSON: And anybody who has not

16  turned in their written comments, please do so because

17  this is a very important task and we truly want to get

18  your ideas and your input.

19	DR. AVOL: So just to close the loop here

20  for staff, if in fact you're going to assign these

21  descriptors to these conclusions then you're going to

22  work backwards so that the respective chapters lead to

23  this conclusion?

24

25	DR. COTE: If we're lucky.

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Page 266

1	DR. HENDERSON: That was good.  I mean

2  you've heard the suggestions and I mean

3	DR. ROSS: Yes, thank you, that's very

4  helpful.

5	DR. HENDERSON:   a limited discussion.

6  I would like now to just, while we've got Jon Samet on

7  the phone, to just go through a summary of the issues

8  that we want to provide in the letter to the

9  Administrator.

10	And I need everybody's help in doing

11  this.  I jotted down things as we went along so I'm

12  going to read out what I have.

13	These are not formal sentences, these

14  are ideas or concepts that I would expect to come from

15  the summaries of the different discussion leaders.

16  Okay, I can do this.

17	So going through this, I heard it over

18  and over and over again the problem of the multi

19  pollutant confounders and is NO2 a surrogate for just

20  air pollution, that sort of thing.  I think that in the

21  letter to the Administrator we have to emphasize that

22  this is a problem and that a multi pollutant approach

23  is where we should be headed in the future.

24	Second, I heard a, the statement there

25  were a lack of negative studies reported, that there

Page 268

1  carefully.

2	Now those are just the notes I have.

3	Now tell me, what are the other major

4  issues that you'd like to see in that letter.

5	DR. CRAPO: I think that one thing I'd

6  add is that when you discuss dose response, we need to

7  know if there is any data that would let you consider

8  that the dose response relationship holds at ambient

9  levels and going downward.

10	I'm really concerned as to whether or

11  not, where the threshold is and whether the calculated

12  dose response relationships that we have are

13  schematically calculated using higher dose data.

14	And I'm not sure there is any answer but

15  we really, the critical question that needs to be

16  understand is, what is the dose response relationship

17  as you start approaching the ambient and going down

18  from there?

19	DR. COTE: Well I think what Mary said

20  about the studies in general are all reported below the

21  standard, all is not the right word, but predominantly

22  reported below the current standard.

23	DR. CRAPO: Yeah, so a real discussion of

24  that issue

25	DR. COTE: Okay.

Page 267

1  needed to be more complete reporting of the, all

2  studies, positive or negative.

3	I heard many, many, many pieces of

4  advice on better integration.  This is not a listing of

5  studies but to integrate the EPI, the clinical and the

6  toxicology studies better.

7	I heard that discussion of the

8  appropriate monitoring and the bottom line that I heard

9  was that the uncertainties associated with monitoring

10  should be discussed more completely.

11	I heard that thee needed to be a better

12  discussion of the plausibility of causality as well as

13  to summarize dose response data for those events that

14  were considered causal.

15	I heard that we needed more quantitative

16  information, though that's going to come a lot in the

17  next document.

18	I can't read my own handwriting here.

19  We need a clear distinction between short and long term

20  exposure health effects.  But I think we've probably

21  just discussed that at length.

22	And because I can't read my last one

23  oh, we need to condense Chapter 3.  A lot of people

24  said Chapter 3 is just too much like a mini CD and they

25  thought that that could be condensed and presented more

Page 269

1	DR. CRAPO:    though because I'm not

2  sure we can take that last table we talked about that

3  has the 20 parts per billion relationship scored from a

4  curve and think that that's what's really going to

5  occur from 15 to 10 let's say ppb.

6	And so I'm not sure we have much

7  information, but I'd like a discussion of that to

8  really   because the dose response relationship for us

9  is most important at the really low end.

10	DR. HENDERSON: Absolutely true, we

11  really need the

12	DR. POSTLETHWAIT: There's more work on

13  that and it may have been in here somewhere and I

14  missed it.

15	But are there any data available on what

16  a personal exposure looks like?  Because I think what

17  many of us struggle with in this plausibility issue is

18  we see causality being concluded from ppb exposure

19  concentrations which result from, you know, an area

20  monitor averaged over a long averaging time.  And it

21  doesn't include the spikes or anything.

22	It gets directly back to what James was

23  just talking about.  There could be exposures that are

24  far more robust than we appreciate.  And so having some

25  of that information in there I think would be very

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Page 270

1  helpful.

2	DR. HENDERSON: So you're saying you want

3  more of the personal exposure information?

4	DR. POSTLETHWAIT: Whatever data is

5  available, because rather than taking the average NO2

6  concentration over a week long

7	DR. HENDERSON: Sure.

8	DR. POSTLETHWAIT:    month long, year

9  long, whatever, compared to what people in the study

10  population are really exposed to could be very

11  different.

12	DR. HENDERSON: Oh, I'm sure they

13	DR. POSTLETHWAIT: And I'm sure they are

14  very different.

15	DR. HENDERSON: I understand, okay.  Ron.

16	DR. WYZGA: I think tied very much to

17  that is some indication that the levels we have are

18  those measured at monitors.  I think we need some

19  statement as to what the criteria are for siting a

20  monitor, and are they representative of all exposures.

21	I suspect they may not be representative

22  of exposures for example near roadways which may be

23  much higher for short periods of time.

24	And so I think that need, you know, need

25  be articulated.

Page 272

1	Okay, Ed.  We actually did that.

2	DR. AVOL: This is sort of a sidelight

3  question, but I think the criteria for placing a

4  monitor and the locations of the monitor, that is the

5  distribution to where they actually are might be

6  somewhat different.

7	DR. COTE: Right.

8	DR. HENDERSON: Right.

9	DR. AVOL: And I think what we want to

10  know is where the monitors actually are, not what the

11  rules are for where you're supposed to place them.

12	DR. COTE: Okay.  How about, you could do

13  both.

14	DR. HATTIS: Based upon where the

15  monitors actually are, what translation do you need

16  between the monitor levels on average and the actual

17  levels outdoors where people are exposed?

18	DR. HENDERSON: Yes.  Those are pieces of

19  information we would need.

20	Are there other issues that we want to

21  be sure in our letter to the

22	DR. WYZGA: I don't know if it's relevant

23  but someone mentioned, I know there are programs in

24  place that will reduce emissions of NOX.  Is it useful

25  to mention that?  Do we have some sense as to are

Page 271

1	DR. COTE: I that's what's available, you

2  know, that there are personal monitoring studies, so a

3  description of what those people were exposed to on a

4  shorter term average, the problem's going to be that,

5  you know, the EPI data is generally reported as just

6  the 24 hour averages.

7	So if you're looking at what peaks are

8  within that 24 hours that are significant, I don't

9  think that that data are available.

10	But we can go back and look at it

11  harder.

12	DR. HENDERSON: I also heard that you

13  wanted the criteria for the siting of the monitors.

14  That ought to be pretty easy to do.

15	DR. WYZGA: Would that show up in this

16  document?

17	DR. COTE: We could.

18	DR. HENDERSON: If we wanted it to, I

19  mean that's what we're giving them, the advice, we're

20  saying yes, we want it so

21	DR. COTE: I wrote that down.

22	DR. HENDERSON: Don't tell them to do

23  something we don't want them to do because we did that

24  once and we've done that before and they do it and so

25  then we complain.

Page 273

1  levels going to go down?  And if so, by much.  Is that

2  worth putting in this document or does that go

3  elsewhere?  I have no idea.

4	DR. HENDERSON: I don't know.  I think

5  it's an important piece of information.  I don't know

6  where we   I mean they are changing the engines so that

7  they put out less NOX as I understand it.

8	Is that something that goes, where would

9  that go?

10	DR. ROSS: It's hard to interpret the

11  health effects evidence based on predicted future

12  levels, given that the health studies are only based on

13  whatever we have now.

14	But sometimes in the ANPR or in the

15  policy making setting those kinds of considerations are

16  added in terms of what future outcomes will be.

17	DR. HATTIS: I think projections of

18  future levels are relevant to the next document rather

19  than this document.

20	DR. HENDERSON: Okay.  Well we'll keep

21  that in mind when we, as we're looking at that

22  tomorrow.

23	Okay, yes George?

24	DR. THURSTON: Well I thought in terms of

25  the letter, one of the issues that came up time and

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Page 274

1  time again was the framework, having at the beginning a

2  framework of evaluation that, you know, laid out what

3  were the criteria that were going to be used and how

4  would they be applied and then applied throughout.

5	And then come up with conclusions based

6  on those criteria.  I mean that's been done but it's,

7  you know, loosely and not in a, you know, comprehensive

8  and consistent way.

9	DR. SHEPHERD: This is Lianne Shepherd, I

10  wanted to interject a comment that's related to

11  George's comment.

12	And that is that there should be better

13  cross referencing between the Integrated Scientific

14  Assessment and the annexes.  And some of the

15  suggestions we're making might be more appropriately

16  put in great detail in the annex and then summarized in

17  the context of the criteria of how we're integrating

18  this information in the integrated document.

19	And that might be one of the ways of

20  addressing some of this feedback without lengthening

21  the scientific assessment too much.

22	DR. COTE: I have to say that I'm

23  committing to doing things like putting in the siting

24  criteria for monitors, I envision that going in the

25  annexes, and not the body of the document.

Page 276

1	And look for that, that way rather than

2  trying to look at, you know, that's where we have a lot

3  of studies, a lot of information.  And maybe that could

4  be, something could be squeezed out of the epidemiology

5  by looking as a function of concentration

6	DR. HENDERSON: To see if there's

7  evidence of a dose response.

8	DR. THURSTON: Yeah.

9	DR. HENDERSON: Yeah, no, I thought

10  that's what was done routinely but I'm not an

11  epidemiologist so I don't know.

12	DR. THURSTON: I don't think it's in

13  here, is it?

14	DR. HENDERSON: I don't know.

15	DR. THURSTON: I didn't see it in here.

16	DR. HENDERSON: No, I don't know, I don't

17  know.

18	SPEAKER: It's there for the animals.

19	DR. THURSTON: For the animals but not

20  for the EPI, so that might be a way to get at that

21  question anyway.

22	DR. HENDERSON: Yes, Ron.

23	DR. WYZGA: Also it was said that the

24  states collect the NO data.  I think to the extent that

25  someone could request that those data might be

Page 275

1	DR. HENDERSON: Okay.

2	DR. COTE: So I think that's a good

3  suggestion.

4   DR. SHEPHERD: But one of the things I think is missing

5	though right now is good cross referencing between the

6  annex and the

7	DR. COTE: Yeah, I think

8	DR. SHEPHERD:   scientific assessment so

9  that we can easily find that more detailed information

10  when necessary.

11	DR. COTE: That's a good comment, thank

12  you.

13	DR. HENDERSON: Okay, George?

14	DR. THURSTON: And then the other comment

15  I had was related to an earlier comment by Doctor Crapo

16  I think it was.

17	That we should look at the epidemiology

18  by concentration level.  I mean this tendency to look

19  at this outcome, that outcome, that outcome and then,

20  you know, if we were to try   I think it's worth a look

21  anyway to try and see if you look at a certain, if you

22  look at the concentrations in the studies and group

23  them into stratus and then see if there is a tendency

24  for effects to be a function of the   and I'm talking

25  epidemiology here, a function of the concentration.

Page 277

1  available, it might be useful in future studies to

2  consider those data as well.

3	My understanding is you said the data

4  are collected as part of the method for measuring NO2,

5  but the data are generally not reported.

6	SPEAKER: Right, not kept, not reported.

7	DR. HENDERSON: Oh, they don't report the

8  NO2 or they don't report the NO?

9	DR. WYZGA: They don't report the NO.

10	DR. HENDERSON: Oh, that's right, that's

11  right, we wanted the NO.

12	DR. WYZGA: So if   I think it would be

13  useful to have those data.

14	DR. HENDERSON: Okay, I got it.  I'd like

15  to remind people that those of you who are underlined

16  are responsible for summarizing your, the group's

17  response to the charge question that you're responsible

18  for, to get it to Angela.

19	So I am going to use this list to check

20  and be sure that they all come in, but I'm counting on

21  you all to address them.  I'm not writing up all these

22  things.  In other words, don't, I wouldn't be good at

23  doing it anyway, but

24	SPEAKER: That's by the end of the day.

25	DR. HENDERSON: That's by 10 o'clock

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1  tonight.  Now, we're going to eat at 6:00 and then

2  we're all going to rush home and sit down and watch the

3  World Series and while you're watching the World Series

4  I want you to script out your summaries.

5	But do it as a group, I mean take into

6  account everybody's comments, not just your own.  This

7  is the first time we've tried this, but hey, we never

8  had a World Series to hold you in your place for this

9  long.

10	So I hope that works out.

11	Okay, are there any other issues that

12  need to go in there?

13	DR. SHEPHERD: Yeah, this is Lianne

14  Shepherd.  There's another comment that I didn't think

15  to mention earlier today, and I think it's relevant

16  both to the exposure discussions and also to the EPI

17  discussions.

18	And often there are fairly generalized

19  comments made that really are only correct if you have

20  a particular epidemiological study design in mind.  And

21  somehow that needs to be attended to better in this

22  document.

23	For instance, there's comments about

24  there being exposure measurement error when the monitor

25  is, you know, near a local source or something like

Page 280

1  really.  But really, you know, you told me about this

2  before, I mean I   Ted was going to do more on the

3  monitoring and Ellis was going to do a little more on

4  multi pollutants.

5	DR. HENDERSON: Okay, I think what we'll

6  do, if you'll just, can you make a copy and pass them

7  out?

8	DR. SAMET: Yeah, I don't know, but

9  anyway I just had a few summary bullets.

10	DR. HENDERSON: Huh?

11	DR. SAMET: I just gave you a few summary

12  bullets trying to summarize the major points I had

13  written down.

14	DR. HENDERSON: Well we want to take

15  those into account, definitely.

16	DR. SAMET: But if somebody might, some

17  others who might have disagreed or heard it

18  differently, it would give them a chance to take a shot

19  at it.

20	DR. HENDERSON: How many points did you

21  have?

22	DR. SAMET: Just four.

23	DR. HENDERSON: Why don't you just read

24  them off?

25	DR. SAMET: The emissions of NO2 and

Page 279

1  that.  And that's particularly important to a timed

2  series study design.  That's just one example.

3	And so we need to be a little careful

4  about when generalizations are made.

5	DR. HENDERSON: Is there a specific

6  something we should include in the letter?  I mean I'm

7  thinking if you know of someone who is going to be

8  writing up the summary paragraph for the appropriate

9  charge question, maybe you could email them, you know,

10  a sentence or two addressing your concerns, Lianne.

11  I'm just

12	DR. SHEPHERD: Okay.

13	DR. HENDERSON: Okay.

14	DR. SHEPHERD: I'll do that.

15	DR. HENDERSON: Okay, very good.

16	DR. SAMET: Rogene, I sent Angela a set

17  of bullets, one sentence bullets on the summary of

18  Charge Question 3.  And if she wants to distribute

19  those to anyone else who wants to take a look at it

20  this evening, that's great.

21	DR. HENDERSON: Okay.  Do the people who

22  are working on Charge Question 3

23	DR. SAMET: The chapter

24	DR. HENDERSON: Oh, Chapter 3.

25	DR. SAMET: Charge Questions 1 to 3

Page 281

1  related species from both indoor and outdoor sources

2  needs to be discussed, both in general and specifically

3  in the context of the correlation of ambient NO2 levels

4  with other co-pollutants, including ultra fine

5  particles.

6	Two, the relationship between indoor and

7  outdoor levels of NO2 deserve more discussion,

8  particularly the relevance of the perimeter alpha

9  relating ambient levels to personal exposures.

10	Three, the spatial variability of NO2

11  within urban areas is very complex and there is

12  inadequate discussion of potential exposure

13  misclassification due to the affect of the siting of

14  monitors away from busy roads, the presence or absence

15  of street canyons, in vehicle exposures and the affect

16  of atmospheric dilution with height above ground.

17	And four, the inclusion of some of the

18  historical dosimetry information relevant to animal to

19  human extrapolations would be helpful in the subsequent

20  discussion of the animal toxicology.

21	DR. HENDERSON: Okay, I think most of

22  those we've got within

23	DR. SAMET: Yeah, I think you've got them

24  all.

25	DR. HENDERSON: Yeah, yeah.  Okay, thanks

US EPA CASAC PUBLIC MEETING 10/24/07 CCR#15676-1	Page 72

Page 282

1  a lot.  Any more discussion here of issues?

2	DR. COTE: I have one thing that I wanted

3  to say.  I think there's been a bit of a misperception.

4	Ron had identified a couple of negative

5  studies that had apparently been missed and certainly

6  as Jon was pointing out, you know, it's easier to miss

7  negative studies than positive studies because when you

8  do the lit search things don't pop up.

9	But in the annexes we have attempted to

10  report all studies so that I think it's not quite

11  accurate to say that there's a lack or reporting of the

12  negative studies.  We may have missed some positive and

13  negative studies.

14	So maybe the emphasis on publication

15  bias might be a more appropriate or clearer statement.

16	DR. HENDERSON: I think the main thing is

17  you want to give a balanced report that, you know, that

18  there have been both positive and negative and maybe

19  just refer to the references.

20	But we can put

21	DR. COTE: I just wanted to leave the

22  group with the awareness that it's not like we chose to

23  put in the positive studies.  We have made a real

24  attempt to put in positive and negative.

25	DR. HENDERSON: Okay.  Okay, are there

Page 284

1	DR. HENDERSON: That's the plan.

2	DR. COWLING: Okay.  So 10 o'clock is the

3  deadline for whatever a sentence or a two or a three

4  sentence statement.

5	DR. HENDERSON: That's right.

6	DR. COWLING: Okay.  And this will be a

7  placeholder I presume, rather than a submission but

8  we'll talk about it all in the morning.

9	DR. HENDERSON: It will be a placeholder

10  and in the morning what we're going to do is discuss,

11  and because of legal requirements we will publicly give

12  our okay to this list   or not okay, I mean since it's

13  a list I don't quite see why we would not be okay with

14  the list.  But it is legally required that we approve

15  what's going to go in the letter.

16	But then we will put, the letter will be

17  crafted, put together and sent out for everyone's

18  concurrence.  Just like we always have.

19	But that's why we're putting Angela to

20  so much work.

21	Okay, we do have a   there's a dinner

22  that you can, I mean you've already said if you're

23  going to attend that's at 6:00.  That's when we're

24  going to get picked up at 6:00.  I'm sure you know that

25  the World Series starts at 8:00 and we will

Page 283

1  any   yes, Ellis.

2	DR. COWLING: I have a logistical

3  question and this has to do with Angela's habits of

4  work.

5	My understanding is that you want a one

6  sentence placeholder or do you want a two or three

7  sentence paragraph?

8	DR. HENDERSON: Two or three sentences,

9  but not two or three pages.

10	DR. COWLING: No, no, okay.

11	DR. HENDERSON: Two or three sentences.

12	DR. COWLING: And you want those

13  delivered electronically to Angela's electronic

14  address.

15	DR. HENDERSON: That's right.

16	DR. COWLING: By 10 o'clock tonight.

17	DR. HENDERSON: Tonight.  She goes to bed

18  at 10:00, don't wait until after the game.

19	DR. COWLING: So how will Angela work?

20  If we send them to her by 10 o'clock, and she goes to

21  bed at 10:00

22	DR. HENDERSON: Oh, I'm just joking,

23  she's going to put them together and we'll have it all

24  printed out and in your chair in the morning.

25	DR. NUGENT: That's the plan.

Page 285

1	DR. CRAWFORD-BROWN: I'm informing you

2  that there is no World Series without my beloved

3  Yankees.

4	DR. HENDERSON: Oh, I'm so sorry.  I'm so

5  sorry.  Some people from Boston thought there was a

6  World Series tonight.

7	Okay, we will see you tonight or in the

8  morning as the case may be.

9	And I appreciate all your work to get

10  your information to Angela.

11	DR. NUGENT: Okay, I guess we're

12  adjourned until we meet at 8:30 for the public session.

13	Thank you.

14  (WHEREUPON, the PUBLIC MEETING was adjourned at 4:30

15  p.m.)

16

17

18

19

20

21

22

23

24

25

Page 286

1	CAPTION

2

3

4	The foregoing matter was taken on the date,

5  and at the time and place set out on the Title

6  page hereof.

7	It was requested that the matter be taken by

8  the reporter and that the same be reduced to

9  typewritten form.

10	Further, as relates to depositions, it was

11  agreed by and between counsel and the parties that

12  the reading and signing of the transcript, be and

13  the same is hereby waived.

14

15

16

17

18

19

20

21

22

23

24

25

Page 287

1	CERTIFICATE OF REPORTER

2  COMMONWEALTH OF VIRGINIA

3  AT LARGE:

4	I do hereby certify that the witness in the

5  foregoing transcript was taken on the date, and at

6  the time and place set out on the Title page

7  hereof by me after first being duly sworn to

8  testify the truth, the whole truth, and nothing

9  but the truth; and that the said matter was

10  recorded stenographically and mechanically by me

11  and then reduced to typewritten form under my

12  direction, and constitutes a true record of the

13  transcript as taken, all to the best of my skill

14  and ability.

15	I further certify that the inspection,

16  reading and signing of said deposition were waived

17  by counsel for the respective parties and by the

18  witness.

19	I certify that I am not a relative or

20  employee of either counsel, and that I am in no

21  way interested financially, directly or

22  indirectly, in this action.

23

24  MARK REIF, COURT REPORTER / NOTARY

25  SUBMITTED ON OCTOBER 24, 2007

0

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23 249:10, 10 250:1

analyze 176:1

196:1 197:25, 25

198:1 240:10

analyzed 66:14

115:17 196:11

anatomic 218:22 ammonia 63:1, 20, 21 ammonium 68:1, 1 among 117:22 194:1

206:1 219:1

amount 9:20 11:1

13:18 97:24 137:1

177:13

amounts 160:21 and/or 35:1 47:1 angela 2:15 4:18

5:1, 17 6:1, 16 8:1

18:17 29:22 30:1,

1, 11, 14 32:18

33:12 37:20 49:1

74:1 137:14, 20

138:13 140:1, 1

209:24 277:18

279:16 283:19

284:19 285:10

angela's 283:1, 13

animal 100:1, 13, 21

102:1 119:13 141:11

142:20 144:1

163:10, 12 164:1

166:1, 1, 11

182:1 183:10 185:23

187:21, 21 188:1,

1, 1 246:1

281:18, 20

animals 101:1, 11

106:23 156:20

163:20 188:1

276:18, 19

annex 14:20, 22

24:1, 25 52:25

70:1, 1, 18 76:1,

1, 1 80:1, 1, 1

81:1, 20 95:21

129:15 143:10, 11

274:16 275:1

annexes 13:1, 13, 25

14:16 19:14, 14, 17

20:1 45:19 92:1

95:22 274:14, 25

282:1

announcement 12:1

annual 20:12 24:23

25:1, 1 86:15

105:18 110:17

129:22 198:1

aods 191:1

anpr 12:17 199:18

210:13 273:14

answer 17:16 66:21

126:1 130:22 137:19

148:13 157:11

160:14 178:10, 12

186:13 197:13 199:1

200:24 204:14 213:1

224:15 234:11

253:25 257:17

259:1, 19 268:14

answered 117:13

answering 117:12

142:13 259:20

answers 49:12

89:12 256:12

anthroprogenic 45:1

anti-inflammatory

161:1

anticipated 253:1

anybody 49:23

77:24 78:1 143:15

171:24 214:21

235:13 244:13

247:22 255:11

262:17 265:11, 15

anyhow 238:1

anyone 172:15 279:19

anything 17:1 30:1

31:24 32:13 48:16

94:1 117:13 132:12,

18 135:1 141:23

164:22 169:14

172:16 174:18 218:1

221:21 223:10 233:1

247:1 255:18

261:1 269:21

anytime 160:1

anyway 17:1 79:12

88:24 92:14 99:19

170:1 177:24 231:10

250:1, 1 259:1

275:21 276:21

277:23 280:1

anywhere 75:25 218:1

api 37:22 38:1,

10, 10

apologize 16:23 17:1

148:23 152:25

apparent 36:1

apparently 42:19

282:1

appear 36:14 58:1

107:1 149:21 160:23

197:15 237:12

appeared 189:11 appears 35:20 220:25 appendix 97:1 appliances 44:18 application 34:25

35:13, 16 37:12

applied 218:1 235:13

274:1, 1

applies 61:22 175:25

230:1

apply 176:21

appreciate 5:16, 18,

21 29:1 44:1 92:1

122:21 226:1 269:24

285:1

appreciated 24:22 appreciation 57:1 approach 124:1, 1

179:20 200:16

266:22

approached 64:13

approaches 62:19

86:23

approaching 134:22

268:17

appropriate 23:1

50:24 64:21 65:1

69:1 84:1, 18

107:17 122:1

133:20, 21

134:13, 14 145:1

149:19 176:1

211:1 212:18, 19

223:19 267:1

279:1 282:15

appropriately 23:1

50:1 66:15 141:13

149:1 274:15

appropriateness

216:23

approve 284:14 approximately 237:1 arb 48:19, 25 architect 241:1 architecture 235:16 ards 188:16

area 66:1 73:15

75:17 77:16 98:1

119:1 154:11, 25

169:22 177:24 186:1

209:1 222:23 269:19

areas 25:1 44:1 82:1

89:1 93:21 109:19

114:11 116:1 129:21

132:10 226:19

281:11

aren't 14:1 75:1

106:1 110:25

128:1 129:21 153:21

231:1 233:22 237:10

argue 61:14 87:16

88:1 91:21 192:1

argued 192:1

arguing 91:11

argument 87:20 90:21

91:19 112:12 130:24

167:1 173:12

arguments 97:16

108:1

arises 234:14

aqs 77:1

arnold 16:1 75:22

76:1, 10, 25 77:1

136:1, 1, 1

arranged 4:1

array 60:1 212:18,

25

arriving 100:15 arrow 68:1, 1 aside 3:16 artery 96:1 article 168:22 articles 168:11 articulated

149:10, 17 201:1

270:25

articulates 12:10

artifacts 72:1 73:17

91:24

aspect 82:23 218:1

256:1

aspects 38:11 219:11

225:23

atherosclerosis

28:17

assemble 233:1

assess 51:21 118:1

212:1

assessed 36:1

55:12 177:20

assessing 33:20

52:18 82:25

assessment 2:10,

13 3:12, 19 5:25

6:1 9:1 11:13,

15, 16, 25 12:1, 1,

1, 1, 16, 17 13:1

14:1, 1, 1, 14

15:1, 1, 1, 13

19:1, 15, 23

22:24 45:1 86:23

88:1 107:1 116:23

128:1 198:24

199:16, 16, 20,

20 208:1 210:12

211:10, 22 212:1,

15, 23 213:1, 16

214:1, 1 220:14

221:1 227:12 233:24

234:13 235:23

240:20 241:19

242:1, 18 243:1

249:1, 1 274:14, 21

275:1

assessments 9:1,

1, 1 29:1 81:25

211:21 212:16

213:25 214:13

232:15

assign 265:20 assistant 199:1 assisted 17:18 20:25 associated 21:1

26:24 28:1 42:15

44:24 46:1 84:1

120:21 162:1 168:24

248:12 267:1

association 27:11

40:15 41:1 42:17

125:17 154:14

155:21 156:1 165:15

166:15 177:1 182:24

associations 26:18

27:13, 18 28:21

35:22 36:11 40:23

41:15 42:1 46:10,

17, 21 47:16, 18

70:1, 11 87:11 95:1

155:10 205:18,

21, 22, 23 206:1

assume 80:10

195:25 196:1, 23

197:1 226:16

assuming 42:23

177:15 245:11

assumption 118:1

asthma 28:1 113:20

127:1, 1, 17 134:17

152:16, 17 153:23

164:1 167:1

179:18 196:1, 1

216:15 228:16, 16

229:1, 1 231:18

232:1

asthmatic 47:1

184:18, 20 185:1

190:1 219:21

asthmatics 41:13

44:22 191:10 193:20

194:1, 1, 1

220:15 221:10

229:25

atlantic 73:1

atmosphere 52:1

96:19

atmospheric 14:18

16:11 19:18, 25

23:1, 10 24:1, 1

50:1 51:25 52:1

57:10, 17 64:13

66:19 78:1 85:1

98:21, 22 261:24

281:16

audibility 32:11

audience 17:10

106:17

august 15:11

ats 217:1

att 49:19 attached 243:1 attack 229:1

attainment 116:11

attempt 7:11

212:25 282:24

attempted 133:13

282:1

attempting 199:1 attempts 223:14 attend 284:23 attended 278:21 attention 37:14

44:1, 12 51:18

53:15 87:20 89:1

159:1 166:1 168:1

189:1 192:22 242:1

attributable 147:1

174:1 230:14 231:1,

1

attribute 41:1

196:20

attributed 41:20

42:1 165:14 169:1

attributes 37:1 attribution 115:13 av 18:1

available 3:13 17:12

22:1 23:19 27:1

28:16 43:1 46:12

60:1 62:1 77:1

82:13 106:15, 22

108:22 109:1

110:1 113:22, 24

117:10 128:1, 12,

13 136:14 144:22

171:1, 17 181:1

183:1 219:24

221:1 265:1

269:15 270:1 271:1,

1 277:1

aver 239:1

average 24:23

25:1, 1, 1 86:15,

18 88:25 105:17

110:17, 19 129:22

238:14, 17, 21, 21,

25 270:1 271:1

272:16

averaged 269:20

averages 109:13

239:1 271:1

averaging 59:16

121:14 130:1, 1, 1,

14 189:20 198:22

214:25 215:10, 11

269:20

australia 185:16

australian 103:1

114:10 129:11

246:12 252:1, 1, 13

253:1

author 142:10 241:1 author's 172:1 authors 42:17, 20,

23 45:25 47:1, 20

58:24 96:12

142:24 146:1

152:1 159:11

181:1 221:21

240:24, 25

automatically 141:1

automobile 43:10

44:1 248:21

aware 73:13 122:1, 1

128:19

awareness 63:13

282:22

away 5:1 7:23

86:16 109:18 130:24

131:1 154:18 155:1,

12 159:17 177:1, 1,

1 252:1 281:14

avol 113:12, 13

125:1, 1 129:1

161:14, 17, 18

184:1, 10 201:20,

23 202:1, 1

203:18 222:1, 1

224:14, 14

244:19, 19 261:1, 1

263:24 265:19

272:1, 1

awful 71:1 awfully 32:14 ax 129:16

axis 237:1

B

babies 236:19

backed 111:18, 19

background 66:1 81:1

82:14 89:18, 21

94:1 97:19 103:25

113:1 177:10 193:14

200:21

backwards 169:1

265:22

bad 94:16 100:12

192:1

baggage 256:17

balance 39:1 51:1

56:1 144:16

149:19 191:16

balanced 141:14

149:1 282:17

balmes 30:17, 17,

20, 24 31:1, 18,

21, 23 32:16

43:18 48:11, 11,

14, 20, 23 49:1

101:17, 20, 22,

22 123:1, 1, 1,

1, 10, 12 125:1

145:13, 17

148:21, 22 152:21

164:22 165:21, 21

183:14, 16, 16

baltimore 39:16

73:10

bandwagon 195:16 bar 218:15, 16 bare 82:1

barely 17:1 30:21

74:17 138:12 263:11

baseball 239:1

based 38:18 92:19

114:10 116:1 124:22

170:19 171:16

183:25 217:15

246:11 247:1 251:1,

1 252:16 272:14

273:11, 12 274:1

baseline 230:18

basic 21:12 22:23

123:13 248:1

basically 66:1

71:1 86:15 88:14

89:16 90:1 95:11

98:18, 19 99:23

102:15 130:1

154:1 168:20 204:20

221:1 236:25 237:1

basing 260:24

basis 25:19 42:16

48:1 60:1 61:18

85:1 91:11 108:1

209:1

battery 186:19 batting 239:1, 1 bear 15:1

bearing 34:1

bears 136:1

become 105:11 113:22

242:1 260:13

becomes 173:16 190:1

becoming 113:23 bed 283:17, 21 beef 228:1

begin 14:1 49:11

187:1 198:1, 15

216:1

beginning 4:12

13:1 19:15 34:14

99:1 105:18

112:14 164:1 177:23

180:1 181:1 274:1

begun 13:10 21:1

behalf 5:1 33:1,

13 37:22 38:10 43:1

behavior 82:24

behind 17:19

behoove 124:1 214:15

believe 44:1 49:1

75:20 118:24 127:25

129:25 162:21

171:20 207:20 248:1

belong 227:15 231:24 belonged 227:12 belongs 227:1, 14 beloved 12:1 285:1 benefit 198:1

240:1 249:1

benefits 147:20

248:1, 1, 17

253:1 258:16 259:1

berkeley 30:18

best 49:17 178:24

228:1 239:17, 21

better 17:15

30:24, 25 32:14

39:14 43:21 51:23

57:1 58:1, 21

59:1 83:15 91:1

93:1 102:1 109:1

116:21 119:1 144:16

151:13, 17 152:1

159:19 163:11 177:1

178:21 181:11

196:17, 17 199:1, 1

201:1 219:17

238:1 246:10 250:1,

1 267:1, 1, 11

274:12 278:21

beyond 131:1 207:1

bias 46:1 117:1

134:11 135:1, 21

168:1, 1 169:13

207:1 240:1 282:15

biased 135:1, 21

biases 134:10

bigger 135:22 231:14 biggest 24:16 220:1 billion 25:1, 1, 1

105:19 151:25

160:15 168:21 169:1

174:1, 15, 18

175:20 187:25 190:1

254:1 269:1

bio 44:25 45:1, 1 biochemistry 99:23 biologic 224:1 biological 45:11

130:14 160:1

161:1 182:21 190:11

222:16 258:23

biologically 107:1

182:24

biology 97:1, 11

160:1 218:12

birth 28:13

bit 10:1 18:16 29:18

50:16, 21 51:18

52:24 56:1 64:14

66:1 67:23, 23

68:12 79:1 83:11

86:1 91:1, 15 99:1,

24 100:22 102:20

103:19, 20 115:1

143:10 144:1 150:13

154:22 183:22 192:1

193:12 212:13

222:1, 23 224:1

237:21 261:1 263:20

282:1

black 187:12 blank 22:14 blanket 194:1

blew 252:1

block 95:11 blocks 213:14 blunt 46:23

board 2:17 8:1 230:1

242:17

body 13:25 59:25

96:1 104:25

119:12 181:22 182:1

190:12 206:1, 19

274:25

bolt 233:1

boston 39:16 285:1

bottom 12:18 19:13

140:23 204:20

205:16 213:1, 18

214:1, 17 267:1

boulanger 17:17

box 72:1

boxes 12:15 72:1 boy 89:25 263:21 branch 9:1, 1 break 3:13 73:24

75:1 77:1 210:1, 1

breakfast 140:11 breaking 137:12 breath 189:25 190:1,

25 191:12

brief 19:1 21:19

74:1 243:17

briefly 10:1 19:20

70:17 89:1 144:1

160:1

bring 12:22 14:1

15:22 24:1 99:1

143:1 165:23 201:22

208:1 224:23

225:1 235:1 236:1

bringing 53:12 55:23

161:13 165:22

204:16 211:23

225:13

brings 166:14

broad 12:10 85:12

204:1 225:25

broader 23:23 28:1

211:23 212:1, 17

brochoalveolar 150:1

broken 85:14

bronchoalveolar

150:1

brought 15:1 87:22

108:16 143:19 147:1

166:22 168:1 178:1,

19 179:19 181:21

191:1 193:14 202:16

204:1 205:1

218:20 221:15

brown 16:1, 1

build 17:1 96:19

104:24 159:19

building 89:10 192:1

213:14

buildings 88:13, 23 built 21:1 208:1 bulletized 241:1 bullets 57:17, 19

143:1 234:15, 16,

19 235:1, 1 279:17,

17 280:1, 12

bunch 39:22

burden 123:24 172:11

burned 31:16

buses 70:22, 25

71:25

business 15:1 114:19

214:1

busy 5:1 281:14 butterfield 6:11 buy 233:1

C

calculate 80:17

173:25

calculated 73:18

238:22 268:11, 13

calculation 70:19 calculations 95:21 california 8:1 27:23

31:14, 17, 19 44:22

113:17 129:1

154:1 220:1

calm 15:23

canada 91:1

canadian 42:22 91:1,

1

cancer 28:1, 1, 11

167:1 168:1, 14,

24, 25 169:10, 15

171:20 172:11,

12, 18 174:11, 13

175:14, 23 196:1

215:17, 19 261:1,

16, 23 262:20

263:18, 25 264:1,

1, 1, 17, 20 265:1,

1

cancers 169:11

candidate 217:21

241:1

candidates 242:1

canyon 88:15

canyons 89:18 281:15 capacity 2:19 6:15 capture 104:1 captures 99:1 136:25 capturing 82:1 86:17 car 232:25 233:1

carb 8:1 71:16

carbon 57:1 155:1

161:1 187:12

carbonate 191:1

carcinogenic 28:10

261:25

cardiopulmonary

40:11 42:11

cardiovascular

27:12, 14 28:15

35:1 97:1, 1 119:25

122:16 155:1 216:15

253:19

careful 159:1 194:12

242:1, 1 279:1

carefully 29:1 218:1

243:1 255:13, 19

268:1

carl 172:25

carrain 16:1 carried 46:1 179:1 carries 256:18

cart 107:11

cas 20:23, 25 21:1

casac 2:22 3:1, 1, 1

4:16 5:1, 1, 11,

16, 18 6:11, 16, 25

13:1 14:11 15:14

38:12 44:1, 10 46:1

106:21 131:17

135:17 140:10

183:24 235:23

245:1, 1

casac's 5:21

case 13:17 35:17, 20

44:17 48:1 58:11

59:1 71:1 79:11

87:17 101:14, 16

109:16 125:25

168:15 209:1, 1

245:10, 16, 20

246:1, 19 248:22

259:25 285:1

cases 35:1, 12 45:25

157:1, 1 191:1

254:12

catalytic 71:1

124:25

catalyzed 75:10 catchy 99:12 categories 178:17

179:1, 1 180:18

222:15

categorization

225:21 235:10

categorize 181:11

223:17

categorizing 194:13

category 180:19,

20 226:24 231:25

247:11

causal 26:18 27:1,

19 34:1, 14 35:18

36:1 147:12, 20

159:18 176:21

177:1, 1 183:1

215:1, 1 228:1

235:15 236:12

243:21 244:10,

14, 18, 24

246:10, 21 250:25

251:1, 15, 24

254:19 256:1, 10,

18 267:14

causality 160:14

213:20 246:22

267:12 269:18

causation 130:14

172:17

cause 27:16 44:13

45:12, 13 96:1

115:24 119:21,

21, 22 185:24 248:1

255:10 259:12

264:1, 18

causes 35:24

causing 38:17

40:1, 10 124:12

171:20 182:1

188:13, 23 215:19

caution 159:1 241:17 cautious 250:1 caveats 47:1 155:16 cd 39:1, 10 44:1

80:1 102:1 267:24

cea 10:22

cell 227:1 cellular 119:14 center 5:25 8:25

32:23

centerpiece 68:11

central 26:1 44:23

112:1, 1 114:24

144:17 177:15

211:13

centrally 214:19

certain 87:17 96:1

180:18 198:1

231:1 275:21

certainly 29:1

63:1 85:17 97:1

116:22 119:10

135:13, 25 158:1

184:17 186:20

192:21 247:1 282:1

certainty 47:24

179:1

cetera 52:13 57:1

69:23 101:1

113:20 161:10 191:1

198:22 216:15

217:13 228:1 261:1

chair 4:16, 17

6:25 175:1 283:24

challenge 80:1

challenging 15:22

160:22

chance 115:12

153:1 192:13 280:18

change 55:18 61:11

67:15 93:18 98:1

100:21 105:1

122:1 123:19 217:25

256:16

changed 59:11 61:15,

17 93:20 109:1

122:1 139:1 165:1

245:20

changes 11:1 18:25

38:15 58:24 65:21

97:14 119:22 185:18

249:15

changing 54:1

62:10 98:11 116:20,

25 256:16 273:1

chapter 14:17, 18

19:23, 24 20:1 22:1

23:1, 25 24:10,

24 25:24 29:12

33:17, 25 35:12,

17, 25 36:1 37:1

45:19, 20 50:15, 20

51:10, 12 53:1

57:12, 14, 17 60:1,

1, 10, 12, 16, 20

62:24 63:11 64:14

65:11 68:11 81:1

84:1 85:1, 1 89:1

90:16 94:1, 1,

10, 16 95:1, 18

97:21 98:19 99:18

100:1, 24 101:25

103:1, 12, 13

104:1, 1, 10

105:1 128:15

133:1 139:18 140:24

142:1, 1, 12, 13

143:1, 1, 10, 11,

15 144:1, 14, 14,

16 145:1, 1

150:21 159:25, 25

179:25 193:1, 1, 22

204:15 216:10 217:1

219:11, 20 220:1

221:12, 24 223:1,

23 224:25 225:1,

11, 18, 19 226:1

227:1, 12, 14,

15, 19 228:1, 13

232:22 233:15, 20

234:1, 1, 11, 15,

16, 19, 20, 21

235:1, 1, 1, 21

236:1 240:18, 25,

25 241:1, 1, 14, 14

245:13, 16

267:23, 24

279:23, 24

chapters 14:23

58:1 85:1 87:14

90:1, 1 92:1 161:24

162:11 170:15 203:1

221:1 227:23 233:16

234:17, 18 235:1

236:1 241:1 242:1

265:22

characteristics 34:1

characterization

136:18

characterizations

24:24 50:1 66:1

216:24

characterize 28:25

127:12 199:1 206:1

characterized

23:1, 1 26:13

36:13, 16 50:1 73:1

83:15

characterizes 137:1

charge 11:23 22:25

26:1 49:12, 25 50:1

64:1 75:17 77:15,

16, 17, 21 78:1,

1 80:25 85:1 93:1

103:1 114:1 126:1

137:20 139:16

140:17, 18 141:1, 1

142:13 145:24

146:23 148:14, 17

149:1 161:19 170:23

171:14 177:22 195:1

201:18 204:1

207:25, 25 209:23

210:1 215:25 216:1,

20, 22 232:1

233:1 240:16 277:17

279:1, 18, 22, 25

charged 142:24

170:23

charter 6:16

chartered 3:1, 1

4:16

chattanooga 172:25 check 277:19 checking 145:19 checklist 242:19 cheery 157:20 chemical 11:1, 11

62:15 80:1 118:15

chemicals 24:1

chemiluminescent

115:24

chemist 16:11

64:13 107:1

chemistry 14:18 23:1

24:1 50:1 52:10

53:25 57:10, 18

64:1 67:21, 21

69:20 78:1 98:21,

23 252:21

chemists 23:22 cherry 150:15 240:1 chevaux 233:1, 1, 1 chief 9:1

child 41:12 229:1, 1 childhood 153:23 children 29:13

47:1 127:1, 1, 17

128:1, 1, 13, 17

164:1, 16 179:18

184:18, 21, 22, 23,

25 185:19 219:21

220:11, 22

221:10, 17 222:1,

19 225:1 231:17

children's 27:22

129:1, 1, 1

151:10 184:19 220:1

224:16

chime 232:11

choice 59:14 61:1

117:23 118:1, 24

122:25 135:11

226:22

choices 212:1 choose 106:1 chooses 47:1

chose 59:22 282:22 chosen 59:21 136:13 christian 67:1 68:13

78:1 80:24 81:13

115:22 137:23

christopher 33:1 chronic 20:20 89:1 chunk 231:21 circulation 96:10 circulatory 96:1

97:1

circumstances 156:1

cite 54:19

cited 41:11

cites 40:13 41:24

cities 46:17 55:11

56:17 88:11 89:1,

16 105:16, 21

172:12 232:1

city 42:22 54:20

55:1, 10 71:12

72:1, 1, 18, 24

81:13 83:11, 11

88:17 127:17 207:10

civil 8:1 claim 113:13 claims 245:17 clarification

17:13 18:1 64:1

69:25 111:1 112:1

129:1 194:15

clarified 30:1 132:1

clarify 29:21

48:1, 21, 25 75:1

223:1 231:1 245:20

clarifying 29:24

classic 88:14, 19,

20 91:1

classified 238:24

clean 2:1, 1 4:21

67:23 68:12

clear 35:1 41:17

68:14 88:24

93:14, 18 130:16

146:15 147:18

150:20 151:20

158:20 161:20

194:25 195:1 202:21

211:12 212:1 213:18

227:24 239:20

245:1, 1 248:23

264:14 267:19

clearance 179:14

181:23 185:24

clearer 163:1 282:15

clearly 31:14

34:11 35:12 50:1

59:1 66:1 95:1

112:1 113:18 133:10

141:14 149:1, 12

155:20 162:1 165:19

184:1 190:11

201:1 210:25 217:20

247:13

clinical 8:1 16:1

17:22 20:1 33:23

34:19 36:12 37:1

41:1 90:25 107:22

120:1 142:19

144:1 156:18

163:12, 23, 24

166:1 246:1 247:11,

16 251:1 267:1

cmac 73:1 80:1, 1

close 29:20 109:19

114:1 129:22

166:1 190:12

206:1 223:1

231:10 245:15

265:19

closed 96:14

closely 52:1 162:1

168:12 178:1 260:21

closer 17:25 31:14

93:1 101:13 113:18

cloth 233:1 clue 191:13 cmsa 129:21

co 155:1, 1 161:1, 1

248:11

co-benefits 248:12

258:10

co-investigator

48:15

co-pollutant 160:25

co-pollutants 36:1

156:1, 15, 24

165:15 281:1

coarse 68:1 79:11 coauthor 150:13 coauthored 149:21 coefficients 133:1 coherence 34:1 36:1,

23 146:13 167:12

179:1, 12, 19

195:10 196:1, 1

203:1 204:12 205:17

206:1

coherent 34:16, 20

35:11 180:1 242:11

coherently 245:16

cohort 20:20 27:24

28:21

collaboratively

10:21

collate 138:14

colleagues 31:13

109:1

collect 276:24 collected 277:1 collection 58:1 columns 22:15 combine 141:1, 1

180:1 209:24

combined 240:1

combustion 45:1 87:1

91:1 92:1 120:19

124:1 125:17

162:1 172:17 173:1

comes 27:22 54:1

58:14 71:1 107:1

116:20 119:12

146:1, 11 159:1

176:13 205:10

207:18 252:19

comfortable 193:1

244:18

coming 54:1 71:24

113:16 124:1

129:1 168:1

176:18 254:13

commend 37:1 41:13

60:10, 20

comment 3:1, 23 7:22

8:10 14:12 32:18,

20, 22 49:1, 24

65:1 77:20 78:11

79:12, 14 80:1

91:15 101:23 103:15

104:1, 12 112:11

113:13 118:17 119:1

120:11 132:17 133:1

140:21 146:1 161:14

172:1 176:1 182:1

184:10 202:15, 16

218:25 221:1 224:15

243:15 252:12, 15

255:11 257:20

261:19 274:10, 11

275:11, 14, 15

278:14

commented 24:22 commenter 33:1 43:1 commenters 5:19 commenting 128:1

129:1

comments 3:1, 10,

18, 25 5:18, 20

7:13 26:16 29:1, 1,

1 33:1, 10, 13,

16 36:19 37:17,

22 38:13 43:1 44:1,

1 50:1, 19 58:17

59:25 61:1 63:25

64:1 67:1 68:17, 23

78:1 80:22 85:1

86:1 87:1, 1

91:1, 20 92:14

114:1 121:1 125:1

126:14, 16 143:1

145:11, 23, 25

146:1 147:1, 13

148:19, 21, 23

149:1, 11 152:23

157:10 158:15

161:19 166:19, 22

168:1 169:17 170:11

178:16, 20

192:14, 18 195:1

203:1, 1 204:1

207:21, 24 209:1,

14 216:1 219:12, 19

222:1 223:1

230:13 237:20

240:18 242:14

243:1, 1 247:23

262:18 265:16

278:1, 19, 23

commit 247:1

committee 2:1, 1 3:1

4:21 49:21 64:25

76:20 135:1 167:1

committing 274:23

common 44:14 147:1

152:1

communicated 50:1

141:14 149:1, 12

162:1

communication 61:1

144:20 150:21

151:20 161:20

community 9:14, 22

61:14 66:24 108:1

125:15

companies 38:11

compare 86:12

150:1 176:1

220:12 230:15

compared 47:17

73:1 102:1 133:1

270:1

comparing 72:1

comparison 56:18

89:20 133:1 264:1

compartmentalize

223:18

compelling 203:10 compiling 19:19 complain 271:25 complete 11:22 267:1 completed 15:12

18:21

completely 259:25

267:10

complex 23:15 94:1

217:23 281:11

compliance 4:1 93:21

complicated 66:1

67:24 69:19 89:11

125:20 159:1 257:25

compliment 201:13

component 173:10

217:17

components 14:12

45:1 84:1 87:1

149:1

composed 72:1 composition 39:23 compounds 23:24

24:14, 15 39:22

comprehensive

153:11, 12, 15

154:1 209:1 274:1

comprehensively

83:25 84:1, 17

concentrating 128:23

concentration 25:1

59:13 81:23 82:15

119:16 121:15

144:24 145:1

180:12, 21 181:12

221:18 236:13

237:18 238:1

239:11, 19 240:11

262:1 263:1 270:1

275:18, 25 276:1

concentrations 20:1,

18 24:23 25:1

37:1 38:16 39:12

44:24 52:13 56:14

79:15, 22 81:1, 1

82:10, 16 83:1

96:19 108:1

118:12 119:20

122:19 129:10

143:19 163:22

180:18 182:16

189:12 238:14

239:10 269:19

275:22

concentrator 182:14

concept 11:15 108:17

230:1 231:1, 1

concepts 266:14

concern 53:1, 16

65:1 67:10 131:1

149:10 163:19

188:22

concerned 107:20

131:1 146:21

147:1 149:20

150:13, 19 167:25

175:21 268:10

concerning 63:1

concerns 64:18

196:13, 24 207:1

279:10

concise 11:18

conclude 27:1

36:18 38:23 40:1, 1

47:12

concluded 39:11

90:1, 1 140:15

269:18

concludes 42:12 43:1

concluding 40:19

174:10

conclusion 26:1

35:18 36:15, 15

38:16, 20 79:1

95:19 168:1 170:1

186:14 197:1, 21

200:10 202:21

244:15 251:15

255:21 265:23

conclusions 15:1

22:1, 1, 1 26:17,

22 27:19 33:17 34:1

39:1, 15 42:20

47:1, 23 57:1,

11, 12 58:1 88:1

133:16 144:22

162:23 167:22

170:1, 19 171:1

174:1 193:13

195:1 196:1

197:19 213:18, 21

214:1, 25 233:22

240:1 243:16 244:1,

1 245:25 261:1

262:18 265:21 274:1

conclusive 27:15

concrete 167:21

170:19 171:1

175:1 235:19 236:1

concreted 170:1 concurrence 284:18 condensate 190:25 condense 7:1, 19

267:23

condensed 267:25 condensing 142:25 condition 94:1 conditions 94:24

96:16 97:13 101:10,

12

conduct 213:25 conducted 12:1 254:1 conference 139:1 confidence 27:10

174:1

configuration 88:11 confined 88:12 confirm 39:17 conflict 4:1 conformance 105:21 confound 90:18 confounded 35:1 39:1

165:15 187:13

247:21

confounder 120:13

confounders 44:20

91:13 266:19

confounding 42:23

44:15 46:1 54:21

55:1 57:1 84:1

90:1, 19 120:24

159:1 162:19 167:15

185:21 187:1, 1, 1,

19 196:13 203:20

218:1 237:24

238:1 251:16

252:1 256:13 260:14

confused 79:1 251:14 confusing 56:1 112:1 confusion 18:1 conjunction 44:14

72:10

connection 134:25,

25 161:1 236:12

248:23

connections 8:1 connotation 100:12 consensus 61:16

117:22 130:25

216:23 244:22

consent 18:20

consider 28:19

45:1 51:1 62:19

65:16 66:24

123:22 168:1

205:1 212:19 222:13

225:10 226:12

258:11 268:1 277:1

considerable 194:1

consideration 5:21

45:1, 11 134:21

259:16

considerations

211:23 212:1, 17

240:1 273:15

considered 23:22

34:23 42:1 47:11

61:1 62:10 124:1

163:19 183:13

193:10 200:22 207:1

218:1 267:14

considering 41:13

120:13 222:10

244:16 263:17

considers 108:1

140:25 244:14

consistency 26:17

34:1 36:1, 23

78:23, 25 146:14

167:11 195:10 203:1

204:12, 22 205:17

206:1

consistent 28:1,

22 34:16, 20

35:11 116:16

157:1 179:15 203:16

245:1 274:1

consistently 36:22 constant 257:1 constitutes 35:10 constraints 70:1 consult 73:24

consultation 2:12

6:1

consuming 135:24 consumption 233:17 contact 4:1 contains 10:24

11:1 60:1

content 241:13

context 45:16 93:12,

23, 25 102:1, 1, 20

108:10, 12 114:10

125:1 126:22 129:16

141:1 145:1, 1

155:11 160:1, 11

161:23 162:1

176:1 202:1 221:1

222:14 225:22

274:17 281:1

continue 107:16

125:1 126:1

continued 44:1

48:1 135:10

continues 6:25 continuum 226:20 contract 48:19 contradict 39:1 contradicts 39:1

40:20

contribute 25:22, 23

contributing 172:11,

17

contribution 177:17 contributions 147:1 contributor 260:1 contributors 24:17

162:13

control 44:12 53:1

75:12 125:11 248:1,

11, 16, 24 250:13

253:15

controlled 22:10

45:1 141:12 150:1

156:19 183:1

228:1 248:11 260:21

controlling 53:24 controls 53:19 convene 140:12 convened 2:1

convenient 146:16

convening 6:18 conversation 210:24 conversely 238:23 conversion 72:12 convert 168:19 converted 190:10 converting 34:1 convinced 203:11 convincing 40:1, 1

202:20 206:23

246:13 262:1

copd 41:1 196:1 cope 229:12 copies 157:15 copy 244:1 280:1 core 177:1 corporation 33:1 correct 65:1

75:21, 22 76:25

77:1 108:19

147:13 168:19

169:12, 18 183:18

196:24 197:1 211:12

249:25 260:11

278:19

correction 68:16

correlate 57:1

112:1, 1 173:21

correlated 38:24

39:1, 13, 14

40:25 168:15 176:15

177:1 187:1

237:25 238:1

correlates 56:25

correlation 25:19

39:17 115:1, 1

124:1 133:1

169:25 170:1, 1

175:15 262:22 281:1

correlations 36:1

37:1 65:21 85:19,

21 88:16 91:23,

23 110:1, 13, 18,

19 125:16 133:1

196:10

cote 5:24 8:15,

18, 22, 24 16:20,

22, 25 17:1, 1

18:25 30:1, 1 119:1

128:18 129:1

130:19, 22 131:1, 1

132:1, 25 194:15,

24 200:13 201:1

203:12 225:1, 17

227:10, 20

229:22, 25 230:1,

1, 20 239:20

240:1 245:18

250:16, 21

253:14, 17

254:22, 25 255:1, 1

256:23 257:1, 13,

16 262:1, 13, 16

263:22 264:1, 16,

21 265:1, 1, 25

268:19, 25 271:1,

17, 21 272:1, 12

274:22 275:1, 1, 11

282:1, 21

cough 196:1 236:23

count 97:23 counted 120:23 counterproductive

94:14

counting 45:17, 17

277:20

countries 169:23

country 61:19 63:22,

24 81:1 89:23 118:1

135:1 171:21

counts 80:19

120:15 231:1

couple 10:12 18:13

19:10 24:24 25:1

26:20 27:1 50:1

64:18 86:1 87:13

94:11 107:1

126:13 153:1, 24

161:19 189:25 204:1

217:11 230:13

236:24 282:1

course 40:20 63:1

92:23 122:20 130:13

134:10 145:1 146:22

159:15 174:12

178:25 190:21

213:10 214:18 215:1

221:14 243:1

court 4:1 cousins 206:1 cover 11:22

covered 10:1 70:16

113:1 226:10 242:1

covers 85:17 232:1

cowling 49:22

58:19 76:1, 1

117:21 118:14

121:1, 21 122:20

134:10 138:1 240:23

283:1, 10, 12,

16, 19 284:1, 1

cowling's 130:23 crafted 243:1 284:17 crapo 104:11, 13

167:1, 1 173:17

174:16 175:1

187:20, 25 188:1,

1, 12, 16 189:23

190:1 191:21, 25

195:14 199:24

200:23 201:11

202:12 259:22

262:20, 24 263:1,

1, 1 268:1, 23

269:1 275:15

crapo's 112:12

crawford-brown

232:19, 21 245:1

253:23 254:13,

16, 18, 23 255:1, 1

285:1

create 97:14

169:13 176:1 237:1

created 61:10 creates 213:1 creation 164:1 credibility 46:1 crisis 135:1, 1 criteria 7:1 9:10

11:17 19:1 21:1

35:10 39:1 63:1

65:25 69:17 86:1

92:1 122:13 148:1

149:12 150:1, 14

151:17, 18 153:1,

12 164:1, 10

165:1 178:25

179:1 182:23 205:25

208:17, 19 217:1,

10 218:1 224:10

246:24 270:19

271:13 272:1 274:1,

1, 17, 24

critical 15:1 83:1

94:16, 22 140:22

164:20 165:10 193:1

211:13 268:15

criticized 57:22

critique 7:15

49:14 64:1 171:25

cross 274:13 275:1

cubed 151:24 cubic 168:19 cumulative 56:16

curious 171:18 176:1

current 10:1 15:11

18:18 23:17 25:1

38:17 40:1, 10 48:1

53:17 54:17 57:22

69:1 93:13, 16, 17,

19 94:1 102:21

117:1 129:22, 24

130:1 145:1

164:13 208:11, 14

220:12 221:1, 11

224:19 254:1, 1, 1,

20 268:22

currently 8:24 13:25

56:18 83:10 89:1

123:16 183:22

curve 237:13 269:1

cut 212:1

cuts 150:21

D

daily 198:1

dale 114:1 115:20

129:13 144:23