US ENVIRONMENTAL PROTECTION AGENCY

SCIENCE ADVISORY BOARD (SAB) STAFF OFFICE

CLEAN AIR SCIENTIFIC ADVISORY COMMITTEE (CASAC)

OXIDES OF NITROGEN PRIMARY NAAQS REVIEW PANEL PUBLIC MEETING

MARRIOTT AT RESEARCH TRIANGLE PARK

4700 Guardian Drive

Durham, North Carolina 27703

OCTOBER 24, 2007

8:40 A.M.

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1	U.S. ENVIRONMENTAL PROTECTION AGENCY

2	CLEAN AIR SCIENTIFIC ADVISORY COMMITTEE

3	PUBLIC MEETING

4	October 24, 2007

5	DR. NUGENT: Good morning everyone, and

6  welcome to the Clean Air Scientific Advisory Committee,

7  Oxides of Nitrogen Primary Review Panel.

8	And today and tomorrow the panel is

9  convened to do a peer review of the first draft,

10  integrated science assessment of oxides of nitrogen.

11	And tomorrow the panel is going to be

12  reviewing, is going to be providing a consultation on a

13  draft Agency document on the NO2 health assessment

14  plan.

15	My name is Angela Nugent and I am the

16  Designated Federal Officer for this panel.  And I serve

17  in the EPA Science Advisory Board Staff Office.

18	I'd like to make a few remarks in my

19  capacity as Designated Federal Officer or DFO and then

20  introduce the first two speakers on the agenda for

21  their remarks.

22	So this panel, the CASAC Oxides of

23  Nitrogen Primary NAAQS Review Panel is a federal

24  advisory subcommittee and by EPA policy its meetings

25  and deliberations are held as public meetings, they're

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1  please contact me, either in person or by email by 8:00

2  a.m. tomorrow.

3	Let's see, I'd also like to note just as

4  a matter of record that the members of this panel are

5  in compliance with federal ethics and conflict of

6  interest laws that pertain to them.  So we're good to

7  go for this meeting.

8	The Agency has arranged for a recording

9  and a Court Reporter for this meeting.  So I ask every

10  member of the panel and every member of the Agency and

11  the public when they speak, to please identify

12  themselves by name at the beginning of their remarks.

13	Let's see, and I think that's it.

14	Let me now turn to Doctor Vanessa Vu who

15  is the Director of the SAB Staff Office, and then to

16  Doctor Rogene Henderson, Chair of the Chartered

CASAC

17  and Chair of this panel for their opening remarks.

18	DR. VU:   Thank you, Angela.  Can you

19  hear me?  Yes, that's good.  Good morning everyone.

20  I'd just like to also add my welcome to everyone to the

21  meeting of the Clean Scientific Advisory Committee, the

22  panel, the nitrogen oxide panel that will deliver

23  advice to the Administrator regarding the revision of

24  the NAAQS for the health effects, or the primary

25  standards of the NAAQS for nitrogen oxides.



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1  noticed in the Federal Register, all in written and

2  public comment are invited, minutes are kept and the

3  public is kept informed.

4	So the panel operates as part of CASAC

5  which is a chartered federal advisory committee that

6  the CASAC, chartered CASAC is empowered by law to

7  provide advice to the Administrator.

8	So far for this panel meeting there's

9  been three request for oral comments and I've just

10  received one set of written comments, that was the only

11  set received and it pertains to the NO2 health

12  assessment plan and I'll distribute that to you at the

13  break and make it available to the public for

14  tomorrow's discussion.

15	Let's see, as you can see on the agenda

16  there is time set aside this afternoon at the very end

17  of today's discussion for this panel to summarize the

18  major review comments and recommendations related to

19  the integrated science assessment.

20	So the plan is to distill down the

21  recommendations and advice of this panel at the end of

22  the day today.

23	There is a second public comment period

24  tomorrow morning and interested members of the public

25  who would like to provide additional public comments,

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1	On behalf of the Administrator I would

2  like to thank members of the CASAC and members of this

3  panel for your time and taking your time away from your

4  busy schedules to provide advice to the Administrator

5  regarding the subject matter that Angela had talked to

6  you about in her opening remarks.

7	I'd also like to take this opportunity

8  to thank, special thanks to two outgoing members of

9  CASAC, Doctor Frank Speizer and Mr. Rich Poirot for

10  their long, valuable service to the Agency in the past

11  six years as members of CASAC.

12	And I also take the opportunity to

13  welcome two new members, Doctor Donna Kenski and

Doctor

14  Jon Samet.  I know Doctor John Samet will be joining us

15  by the phone today, the next two days.  And thank you

16  both for being part of CASAC, I appreciate that.

17	As Angela indicated, this meeting is a

18  public meeting of CASAC.  We appreciate comments form

19  the public commenters and thanks in advance for those

20  who would like to submit comments for the panel and

21  CASAC's consideration.  I appreciate that.

22	I'd like to also take this opportunity

23  to thank the Agency representative for this morning.

24  You will hear from Doctor Ila Cote and Doctor Mary Ross

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1  are responsible for the preparation for the integrated

2  assessment.

3	And tomorrow you will hear from Mr.

4  Lydia Wegman and Doctor Karen Martin and her team from

5  the Air Office that will speak with you about the risk

6  and exposure methods document that you will give

7  consultation on that report.

8	Finally I'd like to thank Angela Nugent

9  for stepping in and serving as the DFO.

10	Some of you have been interacting with

11  Fred Butterfield who has been the CASAC DFO, and he

12  still is.  As you all know he now has a lot of work to

13  do given the fact that the Agency now is working on

14  many pollutants.  So you will still interact with Fred

15  in a different capacity, but Fred will still be part of

16  the charter of CASAC DFO and Angela will be part of

17  this particular review for the nitrogen oxide panel.

18	And in December you will be convening

19  again to delivery advice on sulphur dioxide and Holly

20  Stalworth, also a member of my staff, is going to be

21  supporting the DFO for the sulphur oxides issues.

22	With that I'd like to turn it over to

23  Doctor Rogene Henderson, and once again we would like

24  to thank, sincerely thank Doctor Rogene Henderson who

25  has been Chair for CASAC and continues on this year as

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1  clinical connections but also was very involved in

2  setting regulation, was a member of the CARB, the

3  California Air Resources Board.  A very good discusser.

4  We used to say he interacted, played well with others.

5  I mean he always got his point across, but in a very

6  civil fashion.

7	So I just want to take, you know, just

8  this moment to honor Henry, he meant a lot to me.

9	And now let's turn it over to Angela who

10  is going to lead the public comment period.

11	Oh, I'm so sorry, did I miss, I'm very

12  sorry, you have to keep me straight.  We're going to

13  turn it over to Ila who is going to give us a review of

14  the draft ISA.

15	DR. COTE: I was hoping I was going to

16  get out of this.

17	DR. HENDERSON: No Ila, never.

18	DR. COTE: (Inaudible).

19	DR. HENDERSON: We need you to be miked.

20  And the people on the phone really need you to be

21  miked.

22	DR. COTE: Let's do it again.  Can you

23  hear me now?

24	My name is Ila Cote, I'm currently the

25  Division Director for the National Center for



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1  well.

2	Thank you so much, Rogene.

3	DR. HENDERSON: Welcome.  It's good to

4  have you all here.  I think we are doing something

5  extremely important today.

6	As I have said to some of you, this is

7  the first ISA document after years and years of

8  suggestions to condense the criteria document into

9  something that's more focused on policy relevant

10  information for setting standards.

11	Now we're getting the first attempt at

12  doing that.

13	From all of the comments that I read I

14  think people have been extremely helpful in giving the

15  Agency a very detailed critique of this first ISA, and

16  I expect we'll have lively discussions.

17	But the product of what we do today will

18  be information to the Agency so that they can revise

19  the ISA, hopefully condense it some more and we will be

20  reviewing the next draft in several months.

21	But before we move on to the public

22  comment, I would like to pay honor to a member of this

23  panel, Henry Gong, who passed away very suddenly in the

24  last few months.  And, you know, Henry was a great

25  panel member.  He though well, he was, he had his

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1  Environmental Assessment at the Research Triangle Park

2  Division.

3	A primary mission for all of NCE is to

4  develop health assessments that are used in the

5  Agency's risk assessments.

6	RTP tends to focus on air pollutants and

7  Mary Ross, who you'll meet in a moment if you haven't

8  already, is the Branch Chief whose branch is

9  responsible for developing health assessments for the

10  criteria document.

11	I want to welcome everybody and thank

12  everybody for being here.

13	In particular I'd like to thank members

14  of the scientific community that have been so helpful

15  to us in the last few months.

16	As Rogene mentioned, you know, we have a

17  new process and a new product and largely a new staff

18  and largely new management and we just remodeled so we

19  all have new offices, so it's sort of a robust and

20  rampant amount of newness going around the office.

21	And so it's been very helpful to have

22  the guidance of the scientific community.  They're very

23  generous with their time, so I wanted to thank you all

24  for that.  Next slide.  That's not the right one.

25  Yeah, thank you.

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1	I briefly want to, I want to give you a

2  quick overview.  Many of you will have heard this

3  information before, but I just want to make sure

4  everybody's on the same page, including members of the

5  public that may not have been here before.

6	So what I'm going to, what I'm going to

7  talk about a bit is the NAAQS process, the current

8  NAQS, NAAQS, I love saying that, the draft IFA is going

9  to be covered by Mary in more detail.  Next slide.

10	So as Rogene had mentioned there had

11  been sort of a long interest in revising the NAAQS

12  process, so a couple of years ago Marcus Peacock who is

13  the Deputy Administrator for the EPA, asked that a work

14  group be formed and those people come up with a new

15  process, which they did.  And it is now the accepted

16  Agency process as of maybe last year.

17	So there are four steps in the new

18  process.  Planning, this whole, the whole start to

19  finish NAAQS process is guided by this plan that is

20  developed very early in the process.  It's done

21  collaboratively with the Air Office and ORD,

22  essentially OAQPS and CEA.

23	Some of the key features of the plan are

24  that it contains what is our draft policy relevant

25  questions or the final policy relevant questions so the

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1  will look like.

2	The next step is the risk and exposure

3  assessment which is conducted by the Air Office.  The

4  integrated science assessment essentially informs the

5  exposure and risk assessment.

6	The last step is also done by the Air

7  Office, policy assessment and rule making.  The much

8  beloved staff paper has disappeared and has now been

9  replaced with the announcement of the proposed rule

10  making that articulates sort of the broad Agency view

11  as opposed to the staff paper itself.  Next slide.  Go

12  to the next.  Okay, thanks.

13	This just points out in a little more

14  detail some key steps in the process.  You can see the

15  four boxes.  This identifies the integrated plan,

16  followed by the integrated science assessment, exposure

17  and risk assessment the draft ANPR.

18	The bottom half of this slide is

19  predominantly the rule making process.  So I'd like you

20  to focus on the top half of the slide.

21	We will have gone to a kickoff meeting,

22  what we're calling a kickoff meeting in which we bring

23  in scientists who are very knowledgeable about the

24  variety of topics of interest to us, have a workshop

25  about what the key policy relevant questions will be.



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1  plan is finalized.

2	One of the major changes that is

3  happening, rather than reviewing all of the science in

4  kind of an equal amount of detail, to really focus on

5  the science that will most make a difference or most

6  heavily impact our regulatory decision making.

7	The plan also contains a schedule for

8  that particular chemical.

9	As many of you know we've kind of jumped

10  into this process midstream with NAQS.  PM will be the

11  first chemical that goes through the start to finish

12  process so we're doing NAQS, then SOX, then PM.

13	The science assessment is what, is the

14  subject right now, we're here to talk about integrated

15  science assessment.  The concept was that the

16  integrated science assessment would replace the

17  criteria document and present information in a more

18  concise and essentially accessible kind of fashion.  It

19  was made more transparent with the key science that the

20  Agency was relying on.

21	At the same time while it was supposed

22  to be thorough and complete and cover everything,

23  that's kind of a difficult charge and so as with all

24  new processes, implementation has been in the details

25  about exactly what the integrated science assessment

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1  That gets incorporated into the plan.

2	CASAC has an opportunity as you know to

3  review the plan.

4	Then at the same time we're beginning,

5  we've done the literature search, we're starting to

6  pull all the information together here and which feeds

7  into what we're calling the science assessment

8  document, but we're simply calling the annexes now.

9	So at this stage we have a rough summary

10  of all the literature and we've begun to winnow through

11  that to identify the science that most specifically

12  addresses the policy relevant questions.

13	As this support document or the annexes

14  evolve, what we are moving toward is tabular form

15  summarizing studies so it gives the study and some

16  details for all the studies published since the last

17  review, which is the case of NAQS was in '93.

18	There was some amount of back and forth

19  about exactly what should be in and what should be out

20  and this rough draft kind of went to press before we

21  had that really nailed down, so as you read it you'll

22  notice there are some older studies that are included

23  that in the next version will essentially be summarized

24  in the, either will be included either by reference or

25  in the annexes that are currently in the main body of

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1  the document.

2	But in general I think it's a, there

3  aren't too many of those little faux pas.

4	So then the next step is the integrated

5  science assessment and we begin to really bring

6  together the summary of the information.

7	The risk and exposure assessment

8  essentially lags the integrated science assessment a

9  tad, but not much, and I'll show you the schedule in a

10  minute.

11	And again there's opportunity for CASAC

12  and public comment on both of those components.  Can I

13  have the next slide.

14	So in terms of the science assessment

15  itself, as I mentioned the first step is the

16  development of the annexes which are disciplinary

17  specific, so there's an EPI chapter and, you know, an

18  atmospheric chemistry chapter.  There was a workshop

19  held in February of '07 for peer review of the initial

20  draft of the annex material and a discussion on how to

21  focus the integration.

22	The IFA then draws from those annex

23  chapters to evaluate and simplify its evidence,

24  particular with the health outcome focus unless it's

25  one of the eco documents that generally has an eco

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1  always a steady and knowledgeable hand.

2	Jeff Arnold, Jeff, if you would raise

3  your hand back in the back.  Jim Brown, I don't know if

4  Jim Brown in the back who does our dosimetry and

5  clinical work.  Jeung Kim   I don't, oh, Jeumg's back,

6  I can see her, our epidemiologist as is Doctor Ellen

7  Carrain.  Tom Long and Tom Rubin are new to our

8  operations.  They walked in the door   all these new

9  hires have just walked in the door and started being

10  high performance.  That's great.  Herung Ming who's

11  here, another atmospheric chemist exposure scientist.

12  Joe Pinto, one of our senior scientists, again with

13  much, much experience.  And Paul Reinhart who's a

14  toxicologist for that.  Lori White who is also a

15  toxicologist is way in the back and William Wilson, an

16  exposure scientist of great, great knowledge.

17	So at this point I'm going to turn it

18  over to Mary Ross.  Can we have the next slide.

19	DR. HENDERSON: Can we leave it there.

20	DR. COTE: Which one does it

21	SPEAKER: Hello, hello.

22	DR. COTE: Oh, I'm sorry Dave, I really

23  apologize.

24	SPEAKER: Can you hear us?

25	DR. COTE: Yes, we can.



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1  focus on it.

2	One of the things that's really

3  important is to integrate across disciplines which is a

4  kind of tricky business.  But there's a lot of, a

5  variety of expertise that's brought to bear for the

6  publication of the integrated science assessment.

7	And then the last critical part are the

8  recommendations and conclusions that provide support

9  for the future risk assessment, exposure assessment and

10  policy analysis.  Could I have the next slide please.

11	This is the current schedule.  In August

12  we completed the first draft of the integrated science

13  assessment.  We're sitting right here in October with

14  the CASAC review.

15	You could see the schedules for the

16  remaining steps of the process, so all of us will

17  probably see each other frequently this year.  Next

18  slide.

19	I'd also like to introduce the NAQS team

20  and I want to particularly recognize Mary Ross and

21  Dennis Kotchmar.  I would say the process has, it has

22  been a challenging year and both Mary and Dennis bring

23  this calm presence to the whole process.  So Dennis,

24  would you raise your hand back there?  Doctor Dennis

25  Kotchmar who led the development of this document,

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1	SPEAKER: Because we can barely hear you.

2  Can you turn up the microphone?

3	DR. COTE: We'll be able to in a second.

4	DR. COTE: So anyway I'd like to turn

5  things over to Mary Ross.  Is there anything else I

6  skipped?  Dave, I apologize.  Okay, Mary.

7	DR. ROSS: Okay, I'm Mary Ross and I'd

8  actually like to build on that to say that we have some

9  of the experts who have helped us write the document

10  here in the audience with us too.

11	And purpose of introducing the team is

12  we have resources here available if points need

13  clarification or if for further elaboration on some of

14  the points or a discussion of how we could possibly

15  address things better, they will come up and join us or

16  be able to help answer questions.

17	Doctor Kathleen Boulanger and Jeanine

18  Gant are epidemiologists from Yale who assisted with

19  the document and they are behind Dennis.  And I know

20  Doctor Vic Hasselblad is with us, a statistician who

21  has helped us with understanding epidemiology and

22  Doctor Mark Frampton has helped us with the clinical

23  exposure studies.

24	SPEAKER: Hello, I don't hear a thing.

25	DR. ROSS: Okay, I'm moving closer to the

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1  mike.  Can you hear me now?

2	SPEAKER: Hardly.

3	DR. ROSS: The AV people are working on

4  that.

5	SPEAKER: Okay.

6	DR. ROSS: Okay.  And if I could step

7  back one more slide to the schedule, just a point of

8  clarification for any confusion there might be out

9  there.

10	When I put this set of slides together I

11  neglected to update the schedule to reflect the

12  negotiations we've had with the plaintiffs over the

13  last couple of months, so there's a version that was on

14  the web early and has been replaced I think with this

15  version.

16	The schedule is now a little bit shorter

17  than it was in the version that I first sent to Angela,

18  but these are the current dates that have been, that

19  are just about done.  There still is not a formal

20  consent decree schedule, but these are the dates.

21	So the final decision is to be completed

22  by the end of 2009 in this agreement.

23	So this is the schedule we'll be working

24  under unless something else develops.

25	DR. COTE: Unless it changes.

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1  of NAQS, the measurements and concentrations and

2  exposure issues that can help inform interpretation of

3  the health evidence.

4	The third chapter is, integration of

5  health evidence and there we've pulled from the annexes

6  for toxicology, clinical studies, exposure information

7  and epidemiology studies to try to pull it together in

8  a way that we think hopefully will be most relevant to

9  the policy.

10	The first order of division was by short

11  term exposure and long term exposure, generally

12  grouping the effects, right now we have an annual

13  standard for NAQS but there are a number of studies

14  that have looked at effects with shorter term exposure.

15  So the first discussion is on short term exposures

16  which ranges from the toxicology studies, it could be,

17  you know, a number of hours, a lot of epidemiology

18  studies use 24 hour or one hour of max concentrations.

19	And long term exposure as you know is in

20  the chronic toxicology studies or the sort of cohort

21  studies that have been done in epidemiology within

22  those, within short term exposure studies for example.

23	And I'm just going to point that Cas Ito

24  just walked in the door.  We've been introducing

25  members of the team.  Cas Ito assisted us with the



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1	DR. ROSS: Yeah, but it does seem to be

2  the way it's going to go.

3	So the next slide if you'll skip over to

4  the next one after that, just a brief overview of the

5  organization.

6	As part of the transition from the

7  criteria document to the integrated science assessment

8  we've really struggled with how to present the

9  information in the most policy relevant way.

10	And I'll just say a couple of words

11  about where we ended up and how we organized it in this

12  way.

13	At the bottom of that slide there are

14  the annexes and the annexes represent the work that you

15  do at the beginning of science assessment in any form

16  it takes, is gathering the information from the

17  different disciplines.  So the annexes are still

18  discipline specific, you know, atmospheric science,

19  toxicology, epidemiology and they involve compiling,

20  summarizing and briefly overviews and details of the

21  studies from the different disciplines.

22	And then in the integrated science

23  assessment we have a, our Chapter 2 is called, source

24  to dose.  And the purpose of that chapter is to pull

25  together information from atmospheric sciences, sources

Page 21

1  epidemiology studies.  Sorry, Cas.

2	Within each exposure window then we

3  looked at sort of the health outcome orientation so we

4  focused on respiratory morbidity first as the type of

5  health outcome that was most strongly associated with

6  NAQS in the past.

7	We've begun with what we knew before in

8  the 1993 criteria document for NO2 and for nitrogen

9  oxides and we've built on that to the extent we could.

10	We've then, you now, other morbidity and

11  mortality are discussed and then the health outcomes.

12	We discussed the basic evidence and then

13  we try to draw in what information we have about the

14  levels at which the effects were seen within the health

15  evidence discussion.

16	The way we tried to structure this is at

17  the end of a particular section, for example airways

18  inflammation or lung function, we tried to provide a

19  brief summary of the effects for that individual

20  outcome.  And then we prepared integration sections at

21  the end of a general group, like respiratory morbidity.

22	So there should be an integration

23  section where we tried to integrate the evidence from

24  the different outcomes related to respiratory

25  morbidity.  And that was the purpose of that structure.

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1	Chapter 4 includes just some overview of

2  the types of susceptible groups, the evidence we have

3  for susceptible groups and sort of the public health

4  impact information we have available.

5	The conclusions provide some overarching

6  conclusions about the conclusions that we have in this

7  draft, and we added some table at the end that include

8  the effects seen and the levels at which effects are

9  seen.  There's a table for toxicology studies, a table

10  for controlled human exposure studies.  And then for

11  epidemiology studies you don't only have a dose, but

12  what we presented is the studies with some points in

13  the air quality distribution there.

14	And I'll note that there are some blank

15  columns in the table of epidemiology studies that could

16  be, we could get data from the studies and prepare

17  things like 98th and 99th percentiles for the air

18  quality distribution within that study period.  That's

19  been useful for the program office in the past in terms

20  of evaluating the distribution across which health

21  effects were seen.

22	Now I'll skip through the last few, the

23  next set of slides just give you a basic overview of

24  what we did in this first draft assessment.

25	We grouped charge questions 1 to 3 here

Page 24

1  into any detail there.

2	The next slide just has a few key

3  highlights from the atmospheric science thing.  On

4  atmospheric chemistry we discussed the processes

5  involving NO2 and other oxides of nitrogen there.  It's

6  part of the photochemical production of ozone and PAN

7  as well as acidic and nitrogen oxides and nitro pH's

8  and there are a whole range of chemicals that we

9  discussed in some detail in the annex and then we bring

10  forward a few highlights in Chapter 2.

11	And the measurement that was discussed

12  in some length, we measure NO2 at the FRM, the Federal

13  Reference Method, but it's long been known that there

14  is interference of NO2 by other compounds called N0Z,

15  the short of mixture of non and NOX compounds.  And

16  nitric acid and PAN are probably the biggest

17  contributors to that.

18	We discussed measurements of N0Y which

19  is the overall oxides of nitrogen measurement that can

20  be done and it is a more precise measurement of the

21  overall mixture of oxides of nitrogen.  I know some of

22  you have commented on that and it's appreciated.

23	The annual average of concentrations,

24  there's a couple of characterizations or it in Chapter

25  2 and then more detailed discussion in the annex.  The



Page 23

1  on this page and the general questions we're seeking

2  input in, is how well have we characterized the

3  atmospheric chemistry and air quality information in

4  mostly Chapter 2 that can help inform the

5  interpretation of the health evidence, are the

6  properties of ambient oxides appropriately

7  characterized?  Many of you have specifically addressed

8  these questions which is much appropriate so I won't

9  read them all.

10	But they generally refer to atmospheric

11  sciences and exposure issues.

12	The next slide is just a figure that we

13  pulled, slide number 11, is a figure that we pulled

14  from the document that provides a general overview of

15  the fact that oxides of nitrogen is a complex mixture.

16  NO2 is the oxide of nitrogen for which the standard is

17  set, that's the indicator for this current standard

18  right now.  And it is the, when you look at the health

19  evidence, the vast majority of information is available

20  on NO2.

21	Within NAQS, the general NOX that is

22  measure that is considered by chemists, NO2 and N0 and

23  then you have this broader discussion of N0Y or N0Z

24  kind of compounds that are the other oxides of nitrogen

25  that we try to discuss in Chapter 2.  And I won't go

Page 25

1  annual average is about 15 parts per billion.  The

2  standard is 53 parts per billion annual average for the

3  current NAAQS.  So generally the levels are below the

4  NAAQS all over the United States.  You can have a few

5  peak concentrations in specific areas where a one hour

6  average concentration can exceed 100 parts per billion.

7	If we flip to the next slide just a

8  couple of highlights from exposure which we think is a

9  really key issue in this interpretation of health

10  evidence, is the relationship between ambient

11  measurements of NO2 or NOX or N0Y or whatever you're

12  measuring and the nitric oxides to which people are

13  exposed.

14	When we looked at studies that evaluated

15  the relationships between ambient NOX, NO2 and I must

16  say the studies were all on NO2 so I'll stop saying

17  NOX, so we looked at ambient levels of NO2 and personal

18  measurements of NO2.  Many of the studies actually

19  found the correlation on a day to day basis was pretty

20  good.  Some of them did not.

21	And we discussed a number of factors

22  that can contribute to that result, such as obviously

23  factors around the house that contribute too.  But a

24  number of those are discussed in Chapter 2.

25	Epidemiologic studies often use

US EPA CASAC PUBLIC MEETING 10/24/07 CCR#15676-1	Page 8

Page 26

1  measurements at central sites.  There are very rare

2  studies that use more localized measures.

3	Measurement error, this has actually

4  been discussed in more detail in ozone and particulate

5  matter and so we relied a lot on evaluations we've done

6  before.  But it found that measurement error often

7  results in underestimated risk estimates and increased

8  standard errors as a general conclusion.

9	And I'll skip ahead to charge questions

10  4 to 6 which are primarily about, primarily related to

11  the integration of the health evidence.  And without

12  reading them all, you know, we're interested in your

13  input on how well we've characterized the health

14  effects, how well we've pulled them together to

15  integrate them for the different health outcome

16  measures, and you know, your comments on our

17  conclusions about the strengths and consistency and the

18  causal nature of associations between NO2 and the

19  different health outcomes.

20	A couple of key slides, the next two

21  slides, the first one is on short term exposures and

22  these are just our key conclusions.  Respiratory

23  morbidity was the outcome that was most strongly

24  associated with NO2 in the last review and it remains

25  the health outcome for which there is the most

Page 28

1	The studies on respiratory morbidity

2  have given some suggested evidence but they're not

3  always consistent so we refer to that as suggestive

4  evidence for lung function growth in asthma prevalence

5  with long term exposure to NO2.

6	With lung cancer there is epidemiologic

7  evidence indicating that NO2 may be associated with

8  lung cancer.  In a broader perspective the NOX include

9  nitro pH's that are known to be, some of them are known

10  to be carcinogenic.  So it's possible but we don't have

11  a lot of evidence linking NOX with lung cancer

12  incidence.

13	There's a few studies on birth outcomes.

14  We refer to that as limited evidence.

15	Cardiovascular evidence, there are no

16  studies that we had available to us that looked at long

17  term exposure and things like atherosclerosis, things

18  that have been studied for PM.

19	And with mortality we consider that

20  inconclusive evidence.  Again a few of the prospective

21  cohort studies did indicate some associations with NO2

22  but it wasn't consistent across all the studies.

23	And the last two slides I'll quickly

24  wrap up, we asked, the last two questions are, how well

25  did we characterize the public health impact?  And your



Page 27

1  evidence.  And we conclude there's a likely causal

2  evidence.

3	There's a lot of new evidence from

4  epidemiologic studies, emergency department and

5  hospital admissions visits, that was not available

6  previously.

7	There also are new studies, a couple of

8  multi-city studies on symptoms and further indoor and

9  personal exposure studies related to NO2 in homes or in

10  schools.  These gave us a lot of confidence that there

11  was an association between NO2 and respiratory

12  morbidity.  Less evidence on cardiovascular morbidity,

13  a few epidemiologic studies have shown associations

14  with things like cardiovascular hospital admissions but

15  the evidence is a lot less conclusive.

16	And the same with all cause mortalities.

17  There's some evidence from epidemiologic studies that

18  generally shows positive associations, but it's

19  difficult to draw causal conclusions without a lot of

20  mechanistic evidence for that.

21	The next slide is about long term

22  exposure and this comes from things like the Children's

23  Health Study in California and the other, the related

24  similar studies to that and prospective cohort studies

25  of mortality.

Page 29

1  views on the adequacy of this draft to inform further

2  risk and exposure assessments.

3	And we certainly welcome comments on

4  that.  I'd say the team that we've had with us has

5  worked really hard to try to pull this information

6  together and we know we have some adjustments to make

7  and we really, we've seen some preliminary comments

8  that we've been reading carefully and we really

9  appreciate them and look forward to your comments.

10	And I have one more slide that's

11  actually sort of an add on.  It's the susceptible

12  groups that we identified in Chapter 4 and the existing

13  respiratory disease in children were identified as

14  susceptible groups in the last review.  There's some

15  very limited information on genetic susceptibility, I

16  think one study.  And also some discussion about high

17  exposure populations.  Not a lot of evidence directly

18  related to NO2 but a little bit of evidence is

19  discussed in there.

20	So with that I will close.  And if

21  there's any questions, we can clarify.  Or I don't

22  know, Angela is we have time.

23	DR. HENDERSON: I would ask the members

24  of the panel if they have any clarifying questions for

25  Ila and Mary.  We will be discussing this report all

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Page 30

1  day long, but is there anything about their

2  presentations that you would like to have clarified?

3	Okay, and you all

4	DR. COTE: Thank you.

5	DR. HENDERSON:   will be around, right?

6	DR. COTE: We will do that.

7	DR. HENDERSON: And then we're going to

8  Angela is nudging me here   I haven't forgotten,

9  Angela.

10	We forgot to take role of those who are

11  on the telephone, so I'll let Angela, you do that.

12	SPEAKER: Can you hear us?

13	DR. NUGENT: Good morning to those on the

14  phone.  I would ask that, this is Angela, I would ask

15  that the members of the panel who are on the line right

16  now identify themselves please.

17	DR. BALMES: this is John Balmes from

18  UCSF, UC Berkeley.  Can you hear me?

19	DR. HENDERSON: Yes, John.

20	DR. BALMES: Rogene, when you spoke we

21  could barely hear you.

22	DR. HENDERSON: Okay, thanks for telling

23  me that.

24	DR. BALMES: Now it's better.

25	DR. HENDERSON: Is that better?

Page 32

1	DR. LARSON: This is Tim Larson from

2  Seattle.

3	DR. NUGENT: Thank you, Tim.

4	DR. SHEPPARD: And this is Lianne

5  Sheppard, also from the University of Washington in

6  Seattle.

7	DR. NUGENT: Thank you all for being on

8  the line.  Any other panel members on the line?

9	Please let us know either by email or by

10  an interjection into the discussion if you have

11  problems with audibility and we'll work with the team

12  here to fix it.  So thank you.

13	DR. SHEPHERD: Well anything you can do

14  to make it better, it's awfully faint and difficult to

15  hear.  But we're hanging in there.

16	DR. BALMES: Well said.

17	DR. HENDERSON: Okay.  Now we will go to

18  the public comment period which is headed up by Angela.

19	DR. NUGENT: Thank you, Rogene.  This is

20  the first of our two public comment periods.  We've had

21  three individuals requesting the opportunity to provide

22  public comment and I would ask them to step up to the

23  mike at the center of the room.

24	Vanessa is offering you a seat at the

25  table so please join us.



Page 31

1	DR. BALMES: Yes.

2	DR. HENDERSON: I'm kind of eating the

3  microphone now.  Okay.

4	DR. NUGENT: Are there any other

5	DR. ULTMAN: This is Jim Ultman, Rogene,

6  how are you?

7	DR. NUGENT: Other than John, are there

8  any other panel members on the line right now?

9	DR. ULTMAN: This is Jim Ultman, can you

10  hear me?

11	DR. HENDERSON: Jim Ultman, very faintly.

12	DR. ULTMAN: Okay, well I'm having the

13  same problem as you.  I'm hearing my colleagues that

14  are in California very clearly but you are much closer

15  to me in Pennsylvania and I can hardly hear at all.

16	DR. HENDERSON: Are you burned up yet in

17  California?

18	DR. BALMES: Well actually the fires are

19  in Southern California.

20	DR. HENDERSON: Oh, okay.

21	DR. BALMES: So I'm fine up here.

22	DR. HENDERSON: You're northerners, okay.

23	DR. BALMES: So all our firefighters are

24  down south so if anything starts up here we're in

25  trouble.

Page 33

1	Our first commenter is Doctor

2  Christopher Long from Gradient Corporation and he is

3  presenting comments on behalf of the Utility Air

4  Regulatory Group and he provided some slides last

5  night.  And do you have this material with you?

6	DR. LONG: Not yet, I'm working on

7  preparing that right now.

8	DR. NUGENT: Okay.

9	DR. LONG: Yeah, I'd first like to thank

10  you for the opportunity to present comments on the NOX

11  ISA.

12	You know, as Angela mentioned I'm

13  presenting comments on behalf of the Utility Air

14  Regulatory Group.

15	Since my time is short I'd like to

16  immediately dive into our comments which primarily deal

17  with the Chapter 5 findings and conclusions section of

18  the ISA.

19	In this section EPA outlines a decision

20  paradigm for, you know, assessing and integrating the

21  overall weight of the scientific evidence within the

22  three lines of health effects evidence, namely

23  epidemiology, clinical toxicology and experimental

24  toxicology.  Next slide please.

25	In this chapter they proposed this

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Page 34

1  decision paradigm to draw conclusions regarding the

2  overall strength of the evidence and the extent to

3  which causal inference made be made.

4	And in doing this they identify several

5  essential characteristics of the scientific data

6  bearing on the health effects of the ambient NOX.

7  These include strength, consistency, coherence and

8  plausibility.  Next slide please.

9	I've taken the liberty of converting

10  EPA's textual description of its paradigm to a table

11  that clearly illustrates the required level of findings

12  within the three lines of evidence necessary to support

13  a given level of inference.

14	Beginning with the likely causal level

15  of inference EPA essentially requires that all three

16  lines of evidence be strong, consistent, coherent and

17  plausible.

18	To make a suggestive level of inference

19  either the epidemiology or the clinical toxicology must

20  be strong, consistent, coherent and plausible.  And in

21  suggestive the experimental evidence can be limited.

22	For the inconclusive level of inference

23  all three lines of evidence are generally considered to

24  be limited.  Next slide please.

25	In the application of its paradigm, you

Page 36

1  strength, consistency, coherence and plausibility of

2  these EPI data systematically assessed despite, you

3  know, observations in Chapter 5 that these studies

4  typically showed high correlations between a number of

5  co-pollutants and that there remains uncertainty as to

6  whether NO2 is the causal agent or is instead a marker

7  for the effects of another traffic related pollutant or

8  a mix of pollutants.

9	Another example of an apparent

10  inconsistency involves mortality in short term exposure

11  where the epidemiological associations are described as

12  suggestive, and later in this section both clinical and

13  experimental evidence are characterized as limited.

14	This would appear to support an overall

15  conclusion of inconclusive, but in the conclusion

16  section, mortality evidence is characterized as

17  suggestive.  Next slide please.

18	Just a few, just to conclude my

19  comments, a few recommendations for EPA.

20	Overall we feel that the ISA document

21  would be strengthened if the EPA evidence evaluation

22  paradigm was more consistently implemented.  That is,

23  strength, consistency, coherence and, you know,

24  plausibility or dose response require a more

25  quantitative definition.



Page 35

1  know, there are several examples where the evidence is

2  described as weak, inconsistent, with no clear pattern,

3  confounded and/or limited.  And generally EPA makes the

4  overall determination that the evidence in these cases

5  are inconclusive.

6	Examples include short term NO2

7  exposures and cardiovascular effects and long term NO2

8  exposures and mortality.

9	However, generally quantitative or even

10  methodical criteria as to what constitutes strong,

11  consistent, coherent and plausible evidence are not

12  clearly outlined in Chapter 5.  And in some cases the

13  text doesn't seem to reflect rigorous application of

14  this paradigm.  Next slide please.

15	Some example of what we've identified as

16  inconsistencies in the application of the paradigm can

17  be found in Chapter 5.  One of these involves the case,

18  the conclusion where a likely causal relationship

19  between short term NO2 exposures and adverse

20  respiratory effects is made.  In this case EPA appears

21  to heavily rely upon strong new epidemiological data of

22  associations between ambient NO2 and increased

23  emergency department visits and hospital admissions for

24  respiratory causes.

25	However, no where in Chapter 5 is the

Page 37

1	Often, you know, the positive attributes

2  of data are merely given as significant evidence,

3  numerous studies, new insights, robust effects and high

4  correlations.  You know, in addition the supportive or

5  non-supportive role of clinical and experimental

6  studies at the specific ambient concentrations in

7  question is not fully presented in Chapter 5.

8	So just to reiterate, you know, I'd like

9  to commend EPA for laying the groundwork for this

10  useful decision framework, paradigm, but I'd like to

11  strongly encourage EPA to more rigorously and

12  transparently follow through on the application of the

13  paradigm.

14	Thank you for your attention.

15	DR. HENDERSON: Thank you.  Are there any

16  questions.  Okay, well thank you very much for your

17  comments.

18	SPEAKER: We can't hear again.

19	DR. NUGENT: We'll try harder.  This is

20  Angela introducing the next public speaker, Doctor Will

21  Ellison from the American Petroleum Institute and he's

22  presenting comments on behalf of API.

23	MR. FELDMAN: Good morning everyone.

24  Those of you who know me know I'm not Will.  Will has

25  effectively delegated upwards and I got to come to the

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Page 38

1  meeting.

2	This is Howard Feldman from API and I do

3  have some handouts, but not to those of you on the

4  phone though.

5	Okay, as they're going around let me

6  just, let me get started here.  And I don't have

7  slides, I'm sorry, so we can just hold off on those for

8  the moment.

9	Good morning, I'm Howard Feldman, I'm

10  here on behalf of API.  API represents almost 400

11  member companies in all aspects of the oil and gas

12  industry and thank you very much, CASAC, for taking

13  these comments on the ISA.

14	A preliminary review indicates that

15  there need to be significant changes made to the draft

16  ISA.  The ISA conclusion that NO2 concentrations below

17  the current standard are causing health effects is

18  based primarily on observational EPI.

19	The inherent limitations of these

20  studies do not permit such a conclusion and the reasons

21  for our views will be stated below.

22	First, we recommend that the draft ISA

23  be revised to conclude that ambient NO2 levels are

24  poorly correlated with personal NO2.  I just heard Mary

25  saying some yes, some no, but we think that they are

Page 40

1  to conclude that there is inconclusive evidence rather

2  than stronger suggestive evidence, that ambient NO2

3  levels below the current standard are causing decreased

4  lung function, respiratory symptoms and increased

5  emergency department visits or hospital admissions.

6	We also recommend that the draft ISA be

7  revised to conclude that the multi-city and mechanistic

8  studies providing no convincing evidence, provide no

9  convincing evidence, rather than suggestive evidence

10  that current ambient NO2 levels are causing acute

11  cardiopulmonary mortality.

12	First, I want to go into four of these,

13  pulmonary function, the ISA cites a number of

14  observational studies as evidence of acute effects.  No

15  association of peak exploratory flow rate, PEFR, with

16  NO2 exposure reported in nine of the nine studies using

17  self-reported PEFR measurements.

18	The ISA discounts these negative

19  results, concluding the PEFR data are notoriously

20  unreliable.  And of course this contradicts the use of

21  the PEFR studies in the ozone we're making.

22	In two of the three NO2 studies

23  performed using spirometry, small associations were

24  reported using single pollutant models.  Since similar

25  responses were observed for other highly correlated air



Page 39

1  poorly correlated with the ambient monitors and also

2  that observational studies reporting effects of NO2 are

3  confounded with ambient PM.

4	These ISA conclusions contradict those

5  in the final PM criteria document, so we're trying to

6  balance, what are we seeing in one CD and then we're

7  seeing something else here.  How does that all come

8  together?

9	This contradicts what was in the final

10  PM CD and staff paper.

11	In the PM review EPA concluded that the

12  monitored gaseous ambient concentrations, including

NO2

13  were poorly correlated with personal gaseous exposures

14  and better correlated with the personal PM.

15	Nor are these conclusions supported by

16  results from recent studies in Baltimore, Boston,

17  Steubenville, that confirm the poor correlation of

18  ambient and personal NO2 exposures.

19	Furthermore the ISA acknowledges that

20  the Federal Reference Method for NO2 fails to provide

21  reliable measures of NO2, but rather of N0I which is a

22  whole bunch of compounds that varies in response to

23  composition of the ambient mixture and humidity.

24	Okay, second, I'm going to give you four

25  reasons why we recommend that the draft ISA be revised

Page 41

1  pollutants, it's not possible to attribute these

2  effects to NO2 alone.

3	In the third study no association was

4  found using spirometry.  So as the ISA proceeds, the

5  ISA then proceeds to go on and to discount results from

6  the human clinical studies, including studies of

7  potentially susceptible groups such as the elderly and

8  those with COPD which fail to report pulmonary function

9  effects at ambient NO2.

10	Moving on to the respiratory symptoms,

11  Schildkraut, et al in 2006 is cited by the ISA as

12  strong evidence of respiratory symptoms in child

13  asthmatics.  We commend EPA for considering this study

14  which was ignored during the ozone review, possibly

15  because they reported no positive associations for

16  ozone.  However Schildkraut, et al does not provide

17  clear, much less strong evidence for independent effect

18  of NO2.

19	In three of the four results the risks

20  attributed to NO2 were not statistically significant

21  when PM 10 was included in the multi-pollutant

22  analysis.

23	Moving on to emergency department

24  visits.  The ISA cites selected observational studies

25  as evidence of independent effects of NO2.  However the

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Page 42

1  results of these studies are mixed, with some reporting

2  positive statistical significance and others not.

3	In many of the studies reporting

4  positive associations, only single pollutant models

5  were used.  And many studies considered positive, only

6  one of the multi-pollutant results presented was

7  statistically significant.  And NO2 risks were not

8  generally robust to the inclusion of other pollutants.

9  Rather, in many of these studies the risks attributed

10  to NO2 were markedly reduced in multi-pollutant models.

11	Moving on to acute cardiopulmonary

12  mortality, the ISA concludes that multi-city studies,

13  particularly n-maps provides the most useful

14  information for determining whether ambient NO2 is

15  associated with acute mortality.  Although this study

16  provided the primary basis of early mortality effects

17  for PM and ozone, the authors reported no association

18  between NO2 and total mortality.

19	The ISA apparently revised its

20  conclusions to the n-maps authors without performing

21  published or reviewable independent re-analysis.  The

22  ISA also reinterprets the Canadian eight city study,

23  assuming little PM confounding, although the authors

24  report that the inclusion of PM 2.5 markedly reduced

25  estimates of NO2 risk, particularly when everyday PM

Page 44

1  providing comments for the Alliance of Automobile

2  Manufacturers.

3	We will be providing detailed written

4  comments next week to the Agency and CASAC.

5	We appreciate the Agency's efforts to

6  enhance the review process with the ISA as a

7  replacement for the CD.

8	We believe the following areas can be

9  improved through the continued attention of staff and

10  CASAC.

11	First, the ISA primarily focuses on EPI

12  studies, gives only limited attention to control

13  studies that can establish cause and effect.  Since NO2

14  occurs in conjunction with other common air pollutants,

15  issues like confounding of surrogacy plague the

16  interpretation of the EPI literature.

17	Even in the case of indoor NO2 sources

18  such as gas stoves or unvented appliances, it is now

19  know that other gases and particles that are perpetual

20  confounders are also emitted by these sources.

21	Furthermore, in a recent detailed study

22  of asthmatics in Fresno, California Tegger, et al found

23  that both central monitoring site NO2 and personal

24  exposures to NO2 were associated in concentrations of

25  several bio aerosols, endotoxin, sporia mold and



Page 43

1  data were available.

2	So that concludes my remarks.  We will

3  be submitting comments into the docket.

4	DR. HENDERSON: Thank you, Howard.  Are

5  there questions from the panel?  Okay, thank you.

6	MR. FELDMAN: Thank you.

7	DR. NUGENT: Our third and last oral

8  public commenter is Mr. John Hice from the Air

9  Improvement Resource, Incorporated, speaking on behalf

10  of the Alliance of Automobile Manufacturers.  And I was

11  expecting him to be on the phone.  Are you there?

12	DR. HICE: Yes I am.

13	DR. NUGENT: Hello, are you there on the

14  line, Mr. Heuse?

15	DR. HICE: Yes I am.

16	DR. HENDERSON: You're going to have to

17  speak up a whole lot louder.

18	DR. BALMES: Now you know what we've been

19  experiencing.

20	DR. HICE: Can you hear me now?

21	DR. NUGENT: Better.

22	DR. HICE: Can you hear me now?

23	DR. NUGENT: You're on.

24	DR. HICE: Okay, then I'll start.  My

25  name is John Hice with AIR and as indicated I'm

Page 45

1  agricultural fungi.

2	Thus NO2 not only is a marker for

3  combustion, but also for bio aerosol components.

4	Tegger, et al indicate that their

5  analyses highlight the importance of the consideration

6  of effects of bio aerosols in the assessment of health

7  effects and related anthroprogenic leads.

8	Second, the ISA must consider dose

9  plausibility when integrating the results of controlled

10  studies with the results of observational studies.

11  Biological plausibility involves consideration of both

12  the kinds of effects the agent can cause as well as the

13  dose required to cause the effect.

14	Third, the ISA focuses on similar model

15  results rather than evaluating the results in the

16  context of a full suite of air pollutants.  This can

17  lead to double counting or triple counting of health

18  effects as different pollutants are reviewed.

19	The tables in Chapter 6 of the annexes

20  and most of the discussion in Chapter 3 focus on single

21  pollutant NO2 results and the multi-pollutant analyses

22  that include NO2.

23	Although many of the studies evaluated a

24  suite of pollutants support results for many more

25  outcomes.  In most cases the authors implicate air

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Page 46

1  pollution in general rather than NO2 in particular as

2  being associated with a given health endpoint.

3	Fourth, to ensure scientific credibility

4  ISA must address the issues of publication bias, model

5  selection and uncertain confounding that hinder the

6  interpretation of air pollution EPI studies.

7	CASAC has pointed out in the ozone

8  review where systematic analyses have been carried out

9  as n-maps by Steeb, et al and also I'd add Ito 2003,

10  similar patterns of associations are reported for many

11  pollutants.  This includes the warm season effect.

12  While there are many more studies than available in the

13  prior review for NO2, there's reported to be a wide

14  range of results from positive and negative in

15  systematic analyses.

16	The full range of mortality and

17  associations in the individual cities is not 0.5% to

18  3.6% as over the United States, but it's something like

19  -3, 2.5%.

20	So those are the many issues related to

21  interpreting such wide ranges of associations,

22  especially the knowledge of time space studies as a

23  blunt tool have limited utility in establishing air

24  quality standards.

25	Fifth, the ISA must not omit key

Page 48

1  of the adequacy of the current standard the ISA should

2  clarify the extent of new information since the

3  previous review in each case.

4	We identify the ISA as the basis for

5  scientifically sound air quality policy.  Therefore we

6  strongly urge continued development of that in

7  accordance with our panelists.

8	Thank you.

9	DR. HENDERSON: Are there any questions

10  from the panel for Doctor Hice?

11	DR. BALMES: This is John Balmes.  Yes, I

12  do have a question.

13	DR. HICE: Yes.

14	DR. BALMES: You quoted the Tegger, et al

15  Fresno study.  I'm a co-investigator of that study and

16  I don't think we've published anything as you've

17  described.  There must have been a presentation.

18	DR. HICE: It's the final report for the

19  ARB contract 99322.

20	DR. BALMES: Okay.  Yes, thank you, I

21  just wanted to clarify.

22	DR. HICE: On page 5.6.

23	DR. BALMES: Yeah, no, so it's not

24  that's been, it's not a peer reviewed published paper.

25  It's been peer reviewed only by ARB.  Just to clarify,



Page 47

1  information and/or key caveats when summarizing and

2  drawing conclusions.  For example, the Mortimer, et al

3  2002 study that was used in the ozone review, there is

4  evidence of respiratory effects in asthmatic children.

5  And now the ISA chooses evidence for NO2 effects.  The

6  authors of the study implicate summertime air

7  pollution, not NO2 itself.

8	ISA also uses the Schildkraut 2006 study

9  as evidence of respiratory effects of NO2.  However

10  that study showed no effect of ozone and that finding

11  was not considered by the Agency's proposed ozone rule.

12	In addition, Schildkraut, et al conclude

13  their findings may represent particulate matter

14  effects.

15	ISA also relies on Schwartz, et al '94,

16  but that study discounts any NO2 associations with

17  symptoms compared to other pollutants.

18	And for air pollution associations with

19  respiratory admissions after emergency department

20  visits, there are similar examples where many authors

21  note the inconsistent results.

22	And as a result of these five issues the

23  ISA conclusions overstate the evidence for NO2 health

24  effects and the certainty of those effects.

25	Finally, in order to aid in the judging

Page 49

1  it's not a regular

2	DR. HICE: Good, good.

3	DR. BALMES:   publication.

4	DR. HICE: Yes.

5	DR. HENDERSON: Okay, thank you.  Are

6  there any other questions?  If not, we thank you very

7  much for your presentation and that ends our public

8  comment period I believe.  Is that right, Angela?

9	DR. NUGENT: Yes.

10	DR. HENDERSON: Okay.  Next we'll turn to

11  the very important part of our meeting where we begin

12  to discuss the answers to these charge questions.

13	I want to reemphasize that the purpose

14  of our critique is to improve this ISA.  This is a very

15  important process we're going through because this is

16  the very first ISA and we want to work with the Agency

17  to develop an ISA that is the very best possible.

18	So, we are   and I remind the people

19  whose names are underlined, that att eh end of our

20  discussion I would like for you to summarize in writing

21  the findings of the committee.

22	So, Ted Russell and Ellis Cowling are

23  responsible for leading the discussion.  Anybody can

24  comment on this, they're just going to be the lead off

25  people for Charge Question Number 1 which is   it's on

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Page 50

1  the, the first three questions as Mary said, the first

2  three charge questions are really quality, but it's to

3  what extent are the atmospheric chemistry and air

4  quality characterizations clearly communicated,

5  appropriately characterized, and relevant to the review

6  of the primary NOX NAQS?

7	DR. RUSSELL: Again this is Ted Russell

8  for those on the phone and elsewhere.

9	First a couple of comments.  Having a

10  greatly trimmed down report was great.  I really like

11  the idea that we're getting much faster to what is

12  relevant to the task at hand which is reviewing a

13  standard.

14	But that being said, I think there are a

15  number of things with this chapter, and also again in

16  the summary, that needs some work, if not quite a bit

17  of work.

18	Just going through it, the first thing

19  was is that, and I write this in my comments, is I

20  still find the chapter somewhat scattered and I think

21  it could use a little bit more structure.  And it goes

22  back to a much more traditional structure showing,

23  specifically having a section on sources because one

24  doesn't I think, get an appropriate view of what the

25  sources are that are most important at this, in this

Page 52

1  outdoor and indoor atmospheric and indoor together

2  again because they're so closely linked.

3	I found that the one section later on

4  about indoor exposures and processing sort of just

5  didn't work where it was.  But again that's my personal

6  take on it and I think it would have been much stronger

7  if one puts it where you're talking about what's

8  happening in the atmosphere and then what's happening

9  indoor at the same time.

10	Similar chemistry going on, it tends to

11  repeat things now between the two.

12	And I then go on to measurement methods

13  with ambient indoor concentrations, et cetera.  And

14  after that I leave the exposure sections to someone

15  else.

16	It's not radically different but I think

17  it would add some structure and really focus on what is

18  going to be important in terms of assessing exposure,

19  and to what sources.

20	The whole, and again, any more

21  information that could be provided on the fraction of

22  ambient NOX that one gets indoors would be good.

23	In their discussion, in the discussion

24  of sources I thought it was again a bit short and light

25  on detail.  I also thought the annex was somewhat light



Page 51

1  day and time.  And consider the balance between outdoor

2  and indoor sources as well as sources that are local

3  versus those that are more distant, those that are at

4  ground level, those that are at more elevated sources.

5	You know, I think that that has to be

6  presented right up front just so people can get an idea

7  of what are the sources of oxides of nitrogen that are

8  most important to them and most important to exposure.

9	You sort of get hints of this in the

10  chapter as you go along, but I don't think it's really

11  presented in a way up front that puts the rest of the

12  chapter in perspective.

13	And I think as part of this they do talk

14  later about how much time people spend indoors and

15  outdoors.  I think that that has to be up front just so

16  one can get a feel.

17	I thought it would also be very good if

18  a bit more attention was given to quantifying the

19  fraction of NOX indoors that would be from an outdoor

20  or ambient source.  Just again so that the reader when

21  they try to assess what are the important processes

22  that are going to impact their exposure, they have

23  that, a much better feel right up front.

24	So go from sources and then you can talk

25  about atmospheric processing.  And I'd do this, indoor,

Page 53

1  on detail, but not   going back over it again, probably

2  not as much as thought the first time.

3	I really think there should be again a

4  table of source emissions with emission estimates to

5  put it all in perspective.

6	One thing that is really not present in

7  this chapter is looking a the fraction of NOX that's

8  NO2 or other sources where there is a large push or a

9  concern in Europe that some of the new control devices

10  are moving more of the NOX to NO2, thus potentially

11  increasing exposure to NO2.

12	Even though you might be bringing NOX

13  down you could actually be increasing NO2 exposure.  So

14  just looking at the inventory alone for NOX without

15  some attention to the speciation could be misleading if

16  your concern is primarily NO2 exposure.

17	I would also put not just a current

18  inventory but looking forward to the future, just

19  because we have a number of NOX controls going in right

20  now.  But I think it's important to show what future

21  exposures are going to be, given that the standard is

22  going to have a future effect.  And if you're shifting

23  it from one source to another, that has implications on

24  how you might want to go about controlling things.

25	And I thought the section on chemistry

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Page 54

1  was sufficient and about the right length.  And I would

2  put more emphasis that NOX comes out primarily and N0

3  and is then transformed to NO2 by ozone and other

4  oxygen species.  This has impact on near source

5  exposures, particularly if you are going to start

6  changing the speciation of N0 coming out from the

7  source, from the source itself.

8	And then also talk more about how the

9  transport and rate at which re-speciation of NOX takes

10  place, both first from N0 to NO2, then nitric acid PAN

11  and the differences between nighttime and daytime I

12  think would be important when you're looking at

13  exposures.

14	The section on measurement techniques

15  and measurement uncertainty I though came across as

16  very non-quantitative.  But it seemed to infer that the

17  current measurements are woefully inadequate and

18  provide tremendous uncertainty.

19	And they cite, actually in a different

20  part, the Mexico City results to say that there is

21  significant uncertainty and confounding right now.  And

22  it's, it is well known that the NOX monitors, there is

23  significant interference form species like nitric acid

24  and peroxyacetyl nitrate.

25	But at the same time that there's

Page 56

1  sort of, it pops around in the various sections back

2  and forth.

3	As I said, the ambient measurement

4  section should include indoor measurements as well,

5  just to put that in perspective.

6	And one of the things I found a little

7  bit confusing throughout this was sometimes it seems as

8  though there is a quick focus on NO2 without looking at

9  the other species and I thought some more balance would

10  be useful there.

11	One thing that I think would be very

12  good is just to put it in perspective, have a figure

13  with observed   actually I say in my notes NO2, but

14  actually NOX and NO2 concentrations of all the monitors

15  throughout the U.S.  And something like a probability

16  density function or a cumulative density function, just

17  so you get an idea of where the various cities

18  currently reside in comparison to the NAQS.

19	And if one is looking to have the

20  potential of a short term standard, that should also be

21  given, not just in terms of the long term standard, but

22  also show the distribution in terms of the short term,

23  potential short term standards.

24	And the other thing that this section

25  really needs is to show how NOX correlates with related



Page 55

1  limitations to how much that can be confounding just

2  because of how much PAN and nitric acid you have at any

3  one time and in particular, in many of the monitors

4  it's not going to have a very big affect at all, just

5  because of their location.

6	So I thought it would be very good if

7  one could be more quantitative, and instead of relying

8  on results from an extraordinarily different city to

9  suggest how uncertain the measurements might be, if one

10  actually took typical measurements from a U.S. city or

11  cities where they have done these sorts of measurements

12  and assessed what the interference is, and discuss them

13  in that rite.

14	It would be good to have a pure NO2

15  monitor and that actually gets to something in the,

16  later on in the summary.

17	The question has to be is, how much

18  would that change what we're doing right now?

19	So, and also, let's see, also in this

20  section when you're talking about measurements it

21  should ask, it should look at how indoor measurements

22  and personal exposure monitoring is also done.  I guess

23  it's again bringing a discussion that is later more up

24  front, just so you get an overall sense of how the

25  various monitoring is done, because again right now you

Page 57

1  species.  There's a number of locations where you can

2  get, actually throughout the U.S., how N0 and NO2

3  correlate with related species such as PM 2.5, primary,

4  or not primary but elemental carbon, sulphate, nitrate,

5  et cetera, that have potential health effects.

6	And I think it's important to put that

7  up front just so one can get a better appreciation for

8  the confounding that will come later.

9	Looking at the findings and conclusions

10  and how it relates to the atmospheric chemistry, I was

11  actually taken aback when I read the conclusions, the

12  findings and conclusions chapter, because it doesn't

13  seem to actually pick up what was said in the, at least

14  what I was taking as the main points in the, in Chapter

15  2.  And in particular it seemed to overemphasize the

16  monitoring issues.  There was something, most of the

17  bullets that came from Chapter 2, the atmospheric

18  chemistry part, really have to do with monitoring.

19  There were multiple bullets there and it didn't seem to

20  make sense, given what the discussions were.

21	They were saying that maybe we should

22  monitor N0I, but then they criticized that the current

23  measurement sort of was an N0I measurement.  I

24  personally would say that let's at least measure what

25  we think we're trying to measure.

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Page 58

1	So it would be better to get an NO2

2  measurement device as opposed to something that

3  measures a collection of things and then we don't know

4  what the species are.  But that's just a personal view

5  in terms of I like to know what I'm looking at.

6	So I would take and re-look at the

7  conclusions section and see what are the truly

8  important pieces from the prior chapters and not try to

9  come up with, I would say in some ways what appear to

10  be personal sort of issues or whatever that   and in

11  this case the monitoring seemed to be a real focus at

12  that point, but I don't think was, when at the end of

13  the day it's going to be as big of an issue when it

14  comes reviewing the standard.

15	Thank you.

16	DR. HENDERSON: Thank you very much, Ted.

17  Ellis, would you like to add your comments and then

18  we'll open it up for everybody?

19	DR. COWLING: Okay.  Let me ask that

20  everybody who is on the phone who can't here me, speak

21  up because we can try to do better.

22	And obviously we are all engaged in a

23  new set of processes with a new set of actors.  A new

24  set of authors, a substantially new   some changes in

25  the statutory membership and we have an entirely new

Page 60

1  evidence available for NO2 than for the other oxides of

2  nitrogen and if that was, in 1971, the primary basis

3  for the selection of NO2 as the indicator for this

4  large array of very diverse oxides of nitrogen, we

5  ought to say that someplace in this document.

6	And it seems to me that we ought to

7  focus on the elements that make up the standard.

8	Chapter 2 contains no reference to the

9  existing standard.  Now Chapter 5 does, and I must say

10  I commend the organization of Chapter 5.  And Ted

11  mentioned this as well, the summary that are, there are

12  nine summary statements derived from Chapter 2 but all

13  nine of those relate to the method by which oxides of

14  nitrogen are measured.

15	It does not deal with the questions of

16  indoor or outdoor exposures and other parts of Chapter

17  2 are not very well summarized by those nine

18  statements.

19	Now there are 37 statements in the whole

20  of Chapter 5 and I commend the effort that is being

21  made to summarize the distilled essence, the distilled

22  essence of the new insights that have been developed

23  since the last review that are relevant to the question

24  of whether the present standard is quite adequate or

25  whether the evidence should suggest that some



Page 59

1  process.  And we are engaged in something that we

2  think, we all have hope can be made more efficient and

3  I support Ted's motion that a document, well a more

4  modest document maybe would be a better way to describe

5  it.

6	A more modest document, clearly focused

7  on issues that are pertinent to the need for

8  reexamination of the standard.

9	The standard in the case of oxides of

10  nitrogen was established in 1971.  It has never been

11  changed in the 36 years since 1971.

12	The standard has four parts.  It

13  requires a definition of a letter or air concentration.

14  It requires a definition of the indicator of choice.

15  It requires a statistical form.  And it requires an

16  averaging time.

17	There's only one place in the ISA where

18  all four of those are discussed and that is in the

19  preface.

20	Another important point is that the

21  indicator chosen in 1971 was NO2.  There is no

22  description in the ISA of why EPA chose NO2 when the

23  standard is the oxides of nitrogen.

24	Now Mary mentions earlier in her

25  comments this morning, that there is a larger body of

Page 61

1  alternative standards should be considered.

2	So this is the first ISA.  Everyone

3  speaks of it with great hope for its success and I join

4  with Ted and others on this panel in my hope that it

5  can be made a very much more efficient communication

6  device to provide the foundation for a wise choice.

7	Now, I said in my individual comments

8  that it must have been very wise on the part of the

9  Administrator and the staff of EPA in 1971 to have

10  created this standard that has never required any

11  change in 36 years of additional scientific and public

12  debate about oxides of nitrogen.

13	Now I think there are some in the health

14  community that would argue that, well, it should have

15  been changed.  Well, we'll see at the end of this day

16  whether there is a consensus view about whether the

17  standard is, as written in 1971 and never changed, a

18  suitable basis for exploration of how to manage the

19  oxides of nitrogen exposure in this country.

20	It's important to remember that this is

21  a national ambient air quality standard that we're

22  discussing as it applies to the nation as a whole and

23  it would be worthwhile though, and I was disappointed

24  not to find a map that would show geographical

25  variability.

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Page 62

1	I think it would be very helpful also to

2  have a graph that would show trends in oxides of

3  nitrogen exposure over time, at least as well as it can

4  be inferred from the available evidence, and that it

5  would be not just for NO2, but for each of the oxides

6  of nitrogen for which there is some substantial

7  evidence of health effects.

8	I was very pleased to find in this, in

9  the preface, a history of all the revisions that have

10  been considered in not changing the nitrogen, the

11  oxides of nitrogen standard.  And there are places in

12  the document where it's called the NO2 standard.

13	Well yes, it is the, that is the

14  indicator but that's not the whole.  It's just like

15  ozone is not ozone, it's ozone and other "chemical

16  oxidants" so it's well worth our while in understanding

17  what it is that we're seeking to measure and what it is

18  that has health effects and what it is that we should

19  consider by way of managerial approaches in order to

20  decrease the health effects.

21	And finally, I'm an ecologist and I

22  worry more about welfare effects than I do about health

23  effects in my personal life, that is, in my

24  professional life.  This chapter deals with oxides of

25  nitrogen and it deals with health effects.  We will

Page 64

1  discussion about these matters.

2	Thank you.

3	DR. HENDERSON: Thank you, Ellis.  Now

4  are there other people who have comments on this first

5  charge question, the chemistry question?

6	I would like to ask if Ila and Mary have

7  any response to the critique or any questions for

8  clarification.

9	DR. WYZGA: I had my hand up.

10	DR. HENDERSON: Oh, I'm sorry, didn't see

11  you, Ron, go ahead.

12	DR. WYZGA: Let me say that I'm not an

13  atmospheric chemist and I sort of approached this

14  chapter in a little bit of a naive sense and tried to

15  learn as much as I could.

16	And I have to say that I agree

17  wholeheartedly with what Ted and Ellis said.

18	I guess I had a couple of concerns and

19  one is, there is a lot of discussion about the

20  measurement method.  And I'm not sure who makes the

21  decisions about what is the appropriate measurement

22  method.

23	And I guess one question I have for the

24  staff, is any discussion or recommendation from this

25  committee useful in terms of suggesting what an



Page 63

1  have, and Ted will be leading us in a discussion about

2  the welfare effects.

3	But I would hope that we could at

4  sometime in the course of this discussion, in spite of

5  the fact that this criteria of pollutant is called

6  oxides of nitrogen, and reduced forms of nitrogen

7  certainly are going to be concerning also.

8	But we don't have a standard for

9  ammonia, we don't have a standard for reduced forms of

10  nitrogen and I was in fact delighted to see that there

11  is at least one place in the introductory chapter where

12  reduced forms are mentioned.

13	And I would like to encourage awareness

14  on the part of our panel that there is serious debate

15  about whether a standard for nitrogen that emphasizes

16  only oxides of nitrogen is adequate to protect public

17  welfare.

18	And I'll be interested to see if there

19  is any discussion today about the health effects of

20  reduced forms of nitrogen, particularly ammonia.  And I

21  would also mention that the total ammonia emissions of

22  this country, and of the world as a whole are larger

23  than the total emissions of oxides of nitrogen, either

24  in this country or in the world as a whole.

25	I look forward to comments and

Page 65

1  appropriate measurement method should be for whatever

2  we're going to measure?

3	And I think Ellis' comment about what

4  the correct index is, is of some concern.

5	And when I read the health information,

6  particularly the toxicology, I noticed that there seems

7  to be some evidence for some independent health effects

8  of N0 as opposed to NO2.

9	And for that reason I would to see to

10  the extent that it's possible, more discussion in

11  Chapter 2 of the split between N0 and NO2.  What is it?

12  What is the reaction rate that determines it?  If

13  things like ozone influence it as you said, is it

14  different in the summer and in the winter?

15	And to the extent that we have such

16  measurements in the future we could consider them in

17  epidemiology studies for example to see whether or not

18  something may indeed be going on with N0.

19	The other thing that I think would be

20  useful is that a lot of the discussion in terms of

21  looking at correlations and measurements and changes

22  over time, are really dependent on where monitors are

23  placed.

24	And it would useful to have some

25  discussion of the criteria for monitor placement.

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1	I think, and we're probably getting into

2  the next question a little bit, I felt that, I got a

3  feeling that many of the characterizations of the

4  spatial homogeneity of NO2 is pretty complicated

5  because you basically have some relatively large

6  background levels in an urban area, but also you have

7  point sources.

8	You know, clearly, you know, people talk

9  about this A-frame effect near roadways.  And so you

10  have, so depending on where your monitoring station is

11  located, it can reflect very different things.

12	And I think it's important to sort of

13  get some understanding of what these monitoring data

14  really represent so that they can be analyzed

15  appropriately.

16	And I would also ask when we're, you

17  know, looking at some of these near term sources, how

18  important is N0 as opposed to NO2.  So I would urge to

19  the extent   and let me say that I'm not an atmospheric

20  scientists and maybe we just don't know enough to

21  answer these questions   but at least I'd like to see

22  them raised.  And that's something that hopefully if

23  they're not, haven't been addressed to date, that the

24  research community would consider them in the future.

25	DR. HENDERSON: Thank you, Ron.  Yes, go

Page 68

1  be revised in that figure.  You have an arrow going

2  from ammonium to nitrate.  What you should have is an

3  arrow taking ammonium and nitrate together to go to a

4  nitrate.

5	You also may want to add coarse nitrate

6  formation.

7	And one thing which is mentioned in the

8  text but is not reflected in the figure is the

9  formation of organic PM nitrate.

10	Just a point, but since the figure is

11  really a centerpiece of that chapter I think we need to

12  clean that a little bit.

13	DR. HENDERSON: Thank you, Christian.

14  Was that clear, Mary, do you get what he's

15	DR. ROSS: Yes.

16	DR. HENDERSON:   his correction, he's

17  got those in his written comments as I recall.

18	DR. ROSS: Yes, that's helpful.  And I

19  think that the advice we've received has been very

20  helpful, but the team that worked on this, Joe and Mung

21  and Tom   I don't know we have any questions that we'd

22  like to address to the panel right now, I find the

23  comments generally quite helpful.

24	Joe, would you like to

25	DR. PINTO: We were looking for from this



Page 67

1  ahead, Christian.

2	DR. SEIGNEUR: Okay, yes, I'll just make

3  two comments.  The first one is further to a point that

4  Ted made earlier which is that the ratio of NO2 to NOX

5  in the emissions is much more at issue than the

6  restructures.

7	At some point it says that NO2 is 5% to

8  10% of NOX which definitely is not true.  Some

9  PowerPoints may show 5% of NO2 as to NOX.  And as

Ted

10  mentioned, in Europe a major concern today is that NO2

11  from diesel trucks is going to be much more than 10%,

12  it could be 40%, 70%.

13	And I think this ISA should reflect the

14  fact that this NO2/NOX ratio is unknown and is likely

15  to change in the future.  I think that's going to be

16  particularly important when you look at exposure of

17  people living near roadways.

18	The second point is a figure which I

19  find is very useful in the document and Mary showed

20  that figure earlier which is that summary of the NOX

21  chemistry, NOX/N0I chemistry.

22	I think there is a need to actually

23  clean up the figure a little bit, some parts are a bit

24  too complicated with points which are not very

25  important.  And also the treatment of PM nitrate should

Page 69

1  panel, what should be the appropriate monitoring

2  effect.  And what are the implications for, you know,

3  epidemiologic studies.

4	SPEAKER: Okay, a few points.  As I say,

5  I don't know where to start.

6	You know, it's ironic in that, you know,

7  with the current monitoring technique, you know, the

8  one species which we can measure very well is N0,

9  nitric oxide.  Unfortunately none of the states report

10  N0.

11	So it's not like we can do any   we

12  would have loved to have done analyses with N0, NOX

and

13  NO2   we just can't, okay?  Because that data isn't

14  reported.

15	A few minor points.  Let's see, yeah, it

16  would be useful to include something, you know, about

17  monitor location or criteria, thanks Ron.

18	Yes, spatial homogeneity I mean is very

19  complicated for NO2, especially since there's a lot of

20  chemistry going on.  And unfortunately there's not much

21  known about, you know, the neighborhood point sources,

22  you know, the pizza parlors, you know, you know, et

23  cetera.  Wish we had that data.

24	Let's see, and Ted, okay, a few points

25  just for clarification.

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Page 70

1	With regard for associations between NO2

2  and other species we have six tables in the back, those

3  are Tables 2.5 to 2.

4	DR. RUSSELL: I was looking for something

5  a little more

6	SPEAKER: Yeah, that you'll find in the

7  annex.  I mean, you know, you know, you know, we

8  haven't, we have, you know, rather serious space

9  constraints on us, so you'll find that in annex 3,

10  okay?  And there are long discussions in there, you

11  know, about associations.

12	We have summary tables for it up front,

13  okay?  So there's six or seven summary tables.

14	Also with regard to this question about

15  the   for the fraction of a person's total exposure

16  which is due to exposure to ambient, that's covered

17  briefly on page 2-29.  But again I mean, you know,

18  there are rather lengthy sections in annex 3 that deal

19  with, you know, the calculation of, you know, you know,

20  of that quantity.

21	Okay, what else did I want to talk

22  yeah, the issue about the buses.  Yeah, no, no, no,

23  this is something which is very, could potentially be

24  very important.  It's shown to be very important in

25  London, okay, where you take buses, you know, that are

Page 72

1  City and the artifacts and the measurements, okay, and

2  the NOX boxes for instance, okay?

3	Yeah, what, I mean how would I put it to

4  you?  I mean it's not like those measurements in Mexico

5  City, I mean were measurements of, you know, some of

6  the things which you don't know, you know, what it's

7  composed of, okay.  And you're comparing that to the,

8  you know, to the NOX box, no.

9	What you have there are measurements of

10  individual interference, okay?  And in conjunction with

11  laboratory studies, okay, which look at, you know, the

12  efficiency of conversion, you know, of those species.

13  You know, you make an estimate.

14	So what I had done was actually a few

15  issues here in which I'm involved, okay.  So what I had

16  done was we looked at, you know, the levels of the

17  potential interference, that's the PAN, that's the

18  nitric acid in, you know, in Mexico City and indeed, at

19  the time of the measurements, you know, they were

20  fairly typical of what you see in the U.S., okay.

21  However I didn't stop, you don't want to stop there,

22  okay?

23	I mean it's not like, you know, you're

24  looking at hydrocarbons in Mexico, Mexico City for

25  instance.  Yeah, there I mean, you know, you have this



Page 71

1  fueled by ordinary diesel engines and then you fit this

2  catalytic trap on them, you know, to remove PM, okay?

3  You know, to oxidize PM, basically you're doing that by

4  oxidizing the N0 and NO2 and you have the NO2 oxidized

5  to PM, okay?

6	Unfortunately what happens there is that

7  you wind up making an awful lot of NO2, especially at

8  the ratios I think of what, 30% to 60% of NOX comes out

9  as NO2, you know, in that case.  Okay, this is

10  something, I mean I think there's only one study I know

11  about in the U.S.  It was a study done in New York

12  City, it was a paper by Shorter, dealing with that

13  issue.

14	And yes, and then found similar results.

15  However, there are programs, you know, by EPA, involved

16  the EPA, CARB and other groups, okay, which are, you

17  know, addressing this issue and, you know, thinking of

18  ways, you know, to work around, you know that problem.

19	Nothing has come out yet, it's very

20  transient and that's why I haven't included it, okay?

21  That's simply that and waiting for, you know, the

22  program officers to come out with, you know, their

23  reports.

24	Ted, coming back to your question on

25  let's see, you also mentioned the buses, yeah, Mexico

Page 73

1  very, very poorly characterized mix.  I mean here

2  you're just looking at a few species.

3	Okay, also what I've done is I've taken

4  CMAC results, okay, for the Middle Atlantic, okay?  And

5  I looked at the ratios, okay, of the NO2 to the more

6  oxidized products and then compared those, okay?  You

7  know, I mean to those measurements.

8	And, yeah, I mean what you find is that,

9  yeah, you know, the ratios are highly variable.  NO2

10  for, you know, so for instance in downtown Baltimore,

11  yeah, I mean we think that maybe you're under

12  overestimating, you know, true NO2 by 20%.

13	However, I guess as you're well aware,

14  that if you go out, you know, to a relatively

15  unpolluted area, okay, where all the NOX has been

16  oxidized, okay, that here you have the potential from

17  which the larger artifacts are being formed.  And those

18  I calculated.

19	Also, I have a paper in preparation

20	DR. HENDERSON: I wonder if you could

21  wind this up because I think we

22	SPEAKER: Okay, several, several

23	DR. HENDERSON: I mean one possibility is

24  that you consult with Ted during the break which we're

25  going to have to have very quickly here.  Is that okay

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Page 74

1  with you, Ted.

2	DR. RUSSELL: Yes.

3	DR. HENDERSON: Because I think you all

4  could talk.  I hear very loudly that the Agency would

5  like advice on how to do the monitoring.  Is that

6  something that we are able to give advice on?

7	DR. LARSON: Rogene, this is Tim Larson.

8  Just one brief point and I think the question is

9	DR. NUGENT: Excuse me, this is Angela

10  Nugent, the DFO, who is speaking please?

11	DR. LARSON: This is Tim Larson, can you

12  hear me?

13	DR. NUGENT: Tim, could you speak more

14  directly into your phone, we're having trouble.

15	DR. LARSON: All right, can you hear me?

16  Hello?

17	DR. NUGENT: Barely.

18	DR. LARSON: Well, I'm almost yelling.

19	DR. NUGENT: Okay.

20	DR. LARSON: I just had a question.  To

21  what extent is the Agency already measuring N0I at the

22  monitoring sites, versus NOX?

23	It seems to be an unstated issue that,

24  you know, the recommendation is you should do this, but

25  I think there are sites where this is already going on.

Page 76

1	DR. COWLING: Could we get a map, excuse

2  me, a map of where these monitors are that are in

3  existence now and where those that also measure N0I are

4  located?

5	DR. ARNOLD: Yes, we can provide that.

6	SPEAKER: You'll find a map of the

7  measurements of NO2, Ellis, in annex 3.

8	DR. COWLING: In annex 3.

9	SPEAKER: And annex 2.3, okay.

10	DR. ARNOLD: These are not the standard

11  monitors.

12	DR. THURSTON: This is George Thurston

13  and can I ask a quick question related to this, which

14  is having dealt with, you know, the NOX machines they

15  give you N0 and NO2, the data are there, they're just

16  not reported.

17	Is that something that could be, you

18  know, a recommendation that could come out of this?

19  That they would report N0, and would that be, you know,

20  I don't know, would the committee think that's a good

21  idea if we could do it?

22	DR. HENDERSON: Everyone's saying no.  I

23  think you get, what, N0 and NOX and then you get the

24  NO2 by subtraction?

25	DR. ARNOLD: That's correct, but



Page 75

1	DR. HENDERSON: Yes, go ahead and tell us

2  and then we'll take a break.

3	DR. HOYER: My name is Marion Hoyer from

4  the U.S. EPA's Office of Transportation and Air

5  Quality.

6	And I want to just clarify something so

7  we aren't left with misperceptions about what's

8  happening in the diesel world.  Retrofitted diesel

9  engines do emit more NO2 because of these heavily

10  catalyzed traps.  However, the Agency has finalized

11  rules that go into effect in 2010 for new engines that

12  will control those NO2 emission.

13	So when we're talking about this as an

14  issue in the U.S. it's going to be more an issue

15  related to the retrofitted trucks.

16	DR. HENDERSON: Thank you very much.  The

17  next two charge questions are in the same area.

18	DR. ROSS: Doctor Larson asked a question

19  about whether N0I is measured at some monitors and I

20  believe there are some monitors that can measure N0I

21  but   correct Jeff?

22	DR. ARNOLD: That's correct.

23  Measurements between measured NO2 as in the Federal

24  Reference Method and total N0I are not systematically

25  done anywhere in the network.

Page 77

1	DR. THURSTON: All right, either way.

2	DR. ARNOLD: But he's correct that the N0

3  number is available, it's not reported to AQS so we

4  would welcome recommendations that would help us

5  understand what that measurement could help us with.

6	DR. HENDERSON: I think we should give

7  some thought to monitoring during the break and I would

8  ask that you only take fifteen minutes if possible.

9	So be back by 10:30 if you can.

10  (WHEREUPON, there was a recess).

11	DR. HENDERSON: If everybody could take

12  their seat, we'll get started.

13	I tell you, we are into some very

14  important discussions and I'll tell you my game plan.

15	The next two charge questions are very

16  similar, I mean they're in the same area as Charge

17  Question 1.  And I would like to finish those charge

18  questions, 1, 2 and 3 before lunch.

19	I'm wondering if it wouldn't be good to

20  comment on the other two questions and then have a

21  general discussion of all three charge questions, or at

22  least finish up.

23	But I want to know if that would, if

24  anybody sees any problems with that.  I know we need to

25  finish the discussion on monitoring, but it seems to me

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Page 78

1  it would be wise to have the lead discussants on Charge

2  Questions 2 and 3 give their summaries.

3	And then we can discuss the whole

4  atmospheric chemistry, all three questions.  Anybody

5  object to that?

6	Okay, then I would like to start off

7  with Christian if you would on Charge Question 2.

8	DR. SEIGNEUR: Okay, I will do that.  I

9  will make only three major comments, I won't go into

10  any details.

11	And the first comment I have relates to

12  discussions which started earlier on the measurement

13  method, N0I versus the M0X, NO2 measurement method.

14	One related to exposure, my view is that

15  if all the health effects, the epidemiological studies

16  have been derived from measurements using the method

17  which measures NO2 by the difference between NOX and

18  N0, I think it will be dangerous at this point to

19  switch measurement techniques if we come up with

20  national air quality standards, they are from a given

21  technique.  And then use another measurement technique

22  which will give different results possibly, because

23  then there will not be consistency between the standard

24  and measurement that we'd use to define it.  And I

25  think that consistency will potentially be very

Page 80

1  So I would recommend to have a much more in depth

2  discussion of that issue of near roadway exposure.

3	And the last comment I have is actually

4  in an annex of the report which is on the CD, annex

5  2.7.1 of chemical transport models.  And this annex

6  addressed CMAC, which is a fine model.  The challenge

7  there though is that NO2 being mostly an issue near

8  sources, CMAC because of its spatial resolution which

9  is several kilometers, is not going to be the major

10  tool that EPA will be using I assume to look at

11  population exposure.

12	Actually in the report that we'll

13  discuss tomorrow, the methods document, EPA talks about

14  another model or mode, which is to address near source

15  exposure.

16	So I would recommend that in the ISA the

17  models which will be used by EPA to calculate

18  population exposure be presented and discussed in terms

19  of their present counts.

20	That's all I have.

21	DR. HENDERSON: Thank you.  Donna, do you

22  have your comments ready?

23	DR. KENSKI: Yes, and this is sort of

24  adding on to what Christian had to say.

25	To address the charge question I guess



Page 79

1  important.

2	Also, in the ISA I was a little bit

3  confused in the measurement section, which is Section

4  2.3 because by reading it I didn't see a conclusion at

5  the end, I just saw a lot of information being

6  presented on different measurement techniques.  And at

7  the end I was wondering why are we talking about N0I

8  measurement techniques when all the discussion in the

9  health effects section is on NO2.  I don't see how you

10  could define an NO2 standard if you're measuring N0I

11  and that's more coarse too, which is not the case.

12	Anyway, so that was the major comment I

13  have on Section 2.3 I think.

14	The other comment I want to make is on

15  the spatial variability of NOX and NO2 concentrations.

16  I didn't see a lot of discussion in the ISA about the

17  strong gradients that you can see near roadways which

18  obviously are going to be a major issue when dealing

19  with exposure, population exposure, either people on

20  the roadways or people living or going to school next

21  to a roadway, because those people will be exposed to

22  much higher concentrations of NO2 than the rest of the

23  population.

24	There is some discussion of spatial

25  gradients but they are at much large spatial scales.

Page 81

1  is, are properties of oxides of nitrogen, you know,

2  adequately addressed?  Including the background

3  concentrations and spatial and temporal distributions.

4	I found that that was not adequate

5  actually to satisfy me.  And a lot of the detail I

6  would like to see was in the annex, but I think it

7  should be pulled into this chapter.  In particular, you

8  know, at the very least we needed a map of spatial

9  concentrations across the country.

10	And also, you know, along those lines of

11  spatial distributions it's also important to look at,

12  you know, to have some visual representation of the

13  spatial gradients within a city.  And as Christian

14  said, you know, those very small scale gradients from

15  roadways are going to be very important in determining

16  exposure.

17	So I think it's imperative to have, you

18  know, a great deal more information on that in this

19  section and not relegate that information, much of

20  which does exist in the annex, not, you know, to pull

21  that into this section.

22	And not only do we need the spatial

23  concentration patterns but I think it's also important

24  to have a map of the monitors because I think people

25  making exposure assessments need to, and the health

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Page 82

1  people, need to understand the very sparse nature of

2  our existing NOX network in the United States.

3	It's really a bare minimum, and to think

4  that it perhaps is adequately capturing the highest

5  exposures that people could be exposed to I think is

6  really a stretch.  You know, when you talk about most

7  of our major urban areas have, you know, three, four,

8  five monitors, I don't think that that's probably

9  adequate to, you know, if we're talking about short

10  term exposures to peak concentrations which are going

11  to occur on a very small scale.

12	So I think it's important to have that

13  map of monitors available.

14	I thought the policy relevant background

15  concentration was fine.  I thought they adequately

16  established that those concentrations are very small.

17	And okay, also we talked about spatial

18  patterns but I think temporal, this section could

19  include a great deal more information about temporal

20  variation as well.  It just sort of touched on it but

21  here again, you know, and there were temporal,

22  information on temporal distributions in other sections

23  of the report.  But that's another aspect of, you know,

24  sort of general NOX behavior that needs to be here.

25	Again, you know, to help in assessing

Page 84

1  the, you know, confounding by various species, not just

2  the, you know, the components of N0I but PM 2.5 and

3  ultra fines and all the other associated species.

4	You know, it's touched on in many, many

5  different places but it's never addressed really

6  comprehensively.  So I guess I'd like to see a section

7  and it seemed most appropriate in this particular

8  chapter but I think that could be, I don't know, you

9  know, put in here and tackled up front before we get to

10  the health studies.

11	And finally I guess I think there was

12  some data about   given that traffic exposures are,

13  seem to be very, you know, very important, I think

14  that, those exposures should be addressed in this

15  section as well, rather than   it's really not until

16  you get to the section on susceptible populations that

17  that's talked about comprehensively in the document.

18  It's probably more appropriate for this, you know, in

19  talking about sources, that those, you know, vehicles

20  exposure could be addressed here.

21	DR. HENDERSON: Thank you, Donna.  Could

22  the people on the phone hear Donna?

23	SPEAKER: Yes.

24	SPEAKER: Yes.

25	DR. HENDERSON: Good.  Okay, because the



Page 83

1  when, you know, when are those high concentrations

2  occurring.

3	And along with that I guess I'd like to

4  see not just that spatial and temporal distribution of

5  NOX but   and the affect of monitor siting, that's, you

6  know, goes along with having so few monitors and, and

7  with these sort of intense spatial gradients that the

8  effect of monitor siting is going to be critical.

9	So there should be some summary of how

10  the monitors are currently sited.  And that varies

11  quite a bit from city to city.

12	This whole idea of NOX versus N0I

13  versus, you know, N0Z and when do we, and N0 and what

14  do we need to really measure, I guess I'd like to see

15  that, those various species better characterized in

16  terms of their, and to the extent possible, in terms of

17  their temporal distribution.

18	So when, you know, when NOX goes up,

19  when NOX is peaking, what does that mean in terms of

N0

20  and what does that mean in terms of PAN and nitric

21  acid?

22	So are those, because, I think that

23  might be useful information and sort of leads into

24  another issue that I think needs to be addressed more

25  comprehensively in the document as a whole, which is

Page 85

1  Charge Question 3 is related to Chapter 2 and that it

2  asks, does the information in Chapter 2 provide a

3  sufficient atmospheric science and exposure basis for

4  the evaluation of human health effects presented in the

5  later chapters?

6	Since it's related I'm going to ask Tim

7  Larson on the phone to go ahead with his comments.

8	DR. LARSON: Yes, can you hear me?

9	DR. HENDERSON: Yeah, speak up, just

10  shout as much as you can.

11	DR. LARSON: Okay, I'll try.  Yeah, this

12  is a fairly broad question that I'm sure everybody will

13  have a lot to say about.

14	I think it, you know, it's broken down

15  into the topics we've already discussed for the most

16  part.  And the document, you know, has its strengths

17  and weaknesses, but it covers certainly the issues of

18  what is it we're actually measuring with our monitors,

19  what are the correlations between personal exposure and

20  ambient exposure to and what are the things that

21  determine the strength of those correlations?

22	What are the other measured pollutants

23  that, and how do they, you know, that come along with

24  NO2 at the various monitoring sites for use in multi-

25  pollutant models subsequently?

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Page 86

1	And I think Ted pointed out a good point

2  about sources which are really kind of lacking, which I

3  think would help in a number of ways to address this

4  issue as well.

5	I come down to a couple of points and I

6  agree on my comments, I also mentioned the fact that

7  the siting criteria for NO2 monitors needs to be

8  discussed a little bit.

9	It would be nice to see, because the

10  information is there, you know, how far from major

11  roads for instance are these monitors and how does that

12  compare with where people live?  It might be an

13  interesting perspective.

14	I think that the siting of those

15  monitors was basically predicated on an annual average

16  standard with the hope that even though they were away

17  from roads they were capturing a spatial field because

18  they had a long term average.

19	But in fact as well all know, you know,

20  roads don't move around in time and so people who live

21  nearer to those sources are going to get systematically

22  higher exposures.  And I think that's discussed,

23  especially in the approaches to the health assessment

24  later on.

25	One issue which isn't really discussed

Page 88

1  elaboration, you know, we can argue about the

2  conclusions of it, but at least we should discuss it as

3  relevant to this question, would be sort of this

4  spatial distribution issue and the surrogacy issue.

5	One of the spatial distribution points

6  which I'll repeat again when we do the health

7  assessment, is that proximity to a road is only really

8  one dimension of the spatial distribution problem.

9	And another one, which there's been a

10  lot more work done in Europe because of the

11  configuration geometries of the cities, has to do with

12  the confined roadways and streets.  And you get a

13  spatially stationary feel determined by the buildings,

14  basically this sort of classic street, so called street

15  canyon effects.

16	And those correlations over space, we've

17  been doing some studies in New York City and other

18  places, have little to do actually with proximity, the

19  classic sort of proximity to a roadway, that has to do

20  with the sort of classic gradients that are in the

21  literature.

22	Those fields are stationary in the sense

23  that the buildings don't move as well as the roads.

24	And so it's not clear to me anyway at

25  this point, that the   even in a long term average the



Page 87

1  as much, and other people mentioned this, is this sort

2  of surrogacy issue having to do with NO2 being a

3  surrogate or NOX being a surrogate for other traffic

4  related pollutants or combustion related pollutants

5  more generally.

6	And I think George pointed this out in

7  his comments, written comments, that especially some of

8  the components of PM which people have just been

9  looking at, that EPA had been looking at quite a lot,

10  have a similar kinds of health endpoint outcomes and

11  associations.

12	So I think that   and there's various

13  sentences in this document in the first couple of

14  chapters mentioning that, but there's not a lot of

15  elaboration on the point.

16	I mean one could argue a theoretical

17  case that NO2 is merely a surrogate for certain ultra

18  fine particles.  And that may not be true but, you

19  know, there's, I mean I there's a plausibility to that

20  argument and I think it deserves some attention because

21  I think there is information that might be, be able to

22  brought into this discussion that could shed light on

23  whether that's true or not.

24	So my two major, I think, two points I

25  think are sort of the way the discussion needs

Page 89

1  currently sited monitors reflect that longer term or

2  chronic exposure distribution within the cities.

3	And it's mentioned also I think briefly

4  in the chapter about the vertical distributions.  A lot

5  of attention was paid to sort of the height of the

6  inlet monitors.  But really, more importantly with

7  people living in dense areas, you know, what's the

8  vertical distribution relative to where you live and

9  what floor you live on or where the inlet to the

10  building is?

11	These are very complicated issues and

12  I'm not saying that we have all the answers but I think

13  it deserves some discussion and we really don't have

14  any of that.

15	One possible way to do this is, a number

16  of European cities have basically as you know, their

17  NO2 monitors are really sited next to the roads or in

18  the canyons they do have sort of urban background sites

19  that are additionally required.  And that might be an

20  interesting comparison to see, because those urban

21  background sites are much more similar in spirit to

22  our, you know, NOX, NO2 monitoring sites in this

23  country.

24	Finally the issue of surrogacy, I think

25  boy, that's a tough one.  I think it's generally

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Page 90

1  concluded and fairly concluded later on, although not a

2  lot of discussion of it in the earlier chapters, that

3  there can be surrogate confounding in the, for traffic

4  related pollutants for the NO2 interpretations.

5	But you know, one thing that, there's a,

6  reading the thread of the later chapters there's some

7  emphasis on some of the indoor intervention studies,

8  the Palato studies in which basically the unvented gas

9  heaters were removed from homes and the difference in

10  the, the improvement in health was noted.

11	And that's sort of a qualitatively

12  different and more powerful study design and a natural

13  experiment.

14	And so there's an opportunity there it

15  seems which   it must, you know, I don't know the role

16  of in the first chapter or two, but there's an

17  opportunity to explore whether or not the same

18  surrogacy issues confound that type of study as are

19  potentially confounding the outdoor measurements.

20	Because it's an important study in the

21  sense that it, the argument is that the NO2 levels were

22  high and they went down independent of these other

23  pollutants and it's the real life exposure to NO2,

24  albeit in a longer term, that we can't get in the

25  clinical environment.  And it, you know, points the

Page 92

1  importance of various source, other combustion sources.

2	But I think at least those two, the

3  spatial variability issue and the surrogacy issue

4  deserve a little more expansion, either in these

5  chapters or refer to the annexes and give it more space

6  there.  I realize people are pressed for space and I

7  appreciate that.  I think this is a, you know, I'm an

8  old guy and I used to read these giant tomes of the

9  criteria documents and when I was doing it in the past

10  my kids were at such an age that I used them to put on

11  their highchairs so they could sit at the table.

12	And so at least we've gotten to the

13  point where that's no longer useful.

14	Anyway, those are my comments.

15	DR. HENDERSON: Thank you very much, Tim.

16  You're not the only one who's used it for the highchair

17  or for the doorstop or whatever.  But it's also gotten

18  some students through graduate school, I've heard that

19  they've based their thesis on it.

20	DR. LARSON: That's true.

21	DR. HENDERSON: Well let's finally hear

22  from Jim Ultman, the final one that's on this list.

23  But of course we'll have many more speak.  Jim.

24	DR. ULTMAN: Is the volume okay?

25	DR. HENDERSON: Can you get a little



Page 91

1  finger at NO2.

2	And it may be right, I'd just like to be

3  able to see a bit better support for that.

4	There are the Canadian studies I

5  mentioned in my comments by Vick, et al recently in

6  2007, the Canadian survey, it's admittedly limited to

7  eastern Canada where they were looking at ultra fine

8  source indoors.  And I think in a different set of

9  sources than the classic NO2 combustion sources

10  indoors.

11	So there may be some basis for arguing

12  that, you know, inside homes there are independent

13  sources of these potential confounders.

14	And again I think it goes back to Ted's

15  initial comment about talking a little bit about

16  sources.  I think it would help the framework of this

17  discussion because when you come down to it, those

18  indoor sources are really one of the strengths of the

19  argument for saying that NO2 actually is doing this.

20	And I think that's   so my comments in

21  general are, we can all argue about the finer points of

22  these various issues, the ambient versus personal

23  correlations, the correlations with other pollutants,

24  the measurements, artifacts of the instruments, the

25  spatial variability and the indoor relatives, the

Page 93

1  closer to your mike, or to your phone?

2	DR. ULTMAN: I can try.  Let me switch on

3  the handset.  Is that a little better?

4	DR. HENDERSON: Yeah, that's good.

5	DR. ULTMAN: Okay, good, good.  Okay.

6  Some other people have already stolen my thunder, but

7  I'll press on.

8	The first point I have is kind of

9  general and I think it impacts on the Charge Question 3

10  as well as just the document in general.

11	And that is that I think that there's a

12  lack of context in this document as to the, how the

13  information is presented relates to the current

14  standard.  You know, it's not, it's not entirely clear,

15  you know, whether a study is showing effects because

16  it's, you know, under the current standard or because

17  it's over the current standard.

18	So it's not clear if we were to change

19  the current standard for example, whether it would have

20  changed those studies or not.  Maybe not because maybe

21  those areas were out of compliance.

22	So I think that the, I think that the

23  document needs to put more context and I think Ellis

24  stated that very eloquently previously.

25	More context with respect to the

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Page 94

1  exposure condition relative to the current standard.

2	Okay, now more specifically in Chapter 2

3  there are a set of equations that are given which

4  quantify personal exposure.  And even though my

5  background is in engineering, I don't get anything out

6  of the equation.  They're algebraic equations, they're

7  very complex.  They are referred to later on in the

8  chapter.  I think these are equations 2.1 to 2.5.

9	So they're referred to once or twice

10  later in the chapter, but even when they're referred to

11  there's only a couple of parameters that are referred

12  to and then you have to kind of dig out their meaning

13  on your own from the equations.  And it gets to be I

14  think counterproductive.

15	So I think that the information is, it's

16  bad, it's really critical in that chapter that the

17  information people understand let's say how in a

18  physical sense, you know, the various micro

19  environments and people's activities and movements

20  between micro environments, how that affects their

21  personal exposures.

22	And it's also critical to understand how

23  the various micro environments themselves interplay

24  with each other to affect the ambient conditions in the

25  different environments.  You know, things like

Page 96

1  It's a mediator, it's a very important mediator, a

2  signal transducer which affects things like smooth

3  muscle tension in the circulatory system.

4	In fact I think most of, some of you or

5  maybe most of you realize that in order to treat

6  certain lung diseases, NO, at least experimentally has

7  been administered thinking that it will, exogenous NO

8  will make up for deficiencies in the body and will

9  cause pulmonary artery relaxation and improve

10  circulation.  So it's even used as a therapeutic tool.

11	So I thought it was interesting that the

12  authors of the document actually did an analysis of how

13  much the environmental level of NO would be increased

14  if there were a group of people in a closed space, in a

15  room where the ventilation, you know, was at some, in

16  different conditions.  And what they found was that,

17  you know, if there was a low enough ventilation and if

18  you pack in the elevator enough, that you could

19  actually build up NO concentrations in the atmosphere.

20	So I thought that was very interesting.

21	But I think it was even more relevant as

22  the reverse question.  And that is, if there is NO

23  present in the environment, what affect will it have on

24  physiological functions?

25	And this plays out into the



Page 95

1  infiltration of outdoor air into indoor environments

2  for example.

3	So there's a lot of physical

4  associations here which are really not clearly

5  explained.  And so you have to get it by implication in

6  the chapter, and I find it very hard to dig out.

7	Some of this can be, I think can be

8  solved by organization.  But I think that the most

9  important and the most useful thing I would say that

10  could be done, was to have one or two figures instead

11  of equations, which you know, basically block diagrams

12  which introduce the factors which influence personal

13  exposure and show how they interplay with each other as

14  people move around and as they involve different kinds

15  of activity and how the various micro environments

16  themselves interplay with each other.

17	So I think that would be a big help in

18  terms of understand the chapter and it might also help

19  in terms of formulating a conclusion in the document.

20	I found it very interesting on page 221,

21  that there were some calculations made in the annex,

22  the annexes, to see what the effect of expired NO from

23  people would be on the surrounding environment.

24	In other words, endogenous NO, NO is

25  produced endogenously and it has a physiological role.

Page 97

1  cardiovascular effect I think of NOI.  You know, they

2  will have a cardiovascular effect if there's sufficient

3  NO present.  That we know from some of these

4  therapeutic studies, particularly on, I should say not

5  particularly, but probably only on people that have

6  some preexisting disease, circulatory disease.

7	At any rate, the biology of these

8  processes I don't think are explained in the appendix.

9  They're certainly not explained in the document itself.

10	So I think there needs to be some

11  explanation of the biology of NO.  And possibly some

12  exploration of the studies that are quoted to see if

13  there's any conditions where the NO might rise to a

14  level which would create some physiological changes.

15  And that would help I think with some of the

16  plausibility arguments later on in the document.

17	Okay, so that's that point.

18	Okay, the dosimetry section which is

19  really my background, I don't really have a lot to say

20  about it.  Although I found it peculiar that the title

21  of this chapter   let's see if I can dig out the exact

22  it was called, Source to Tissue Dose, was the title.

23	So if you count words, dose occupies 25%

24  of the title and yet if you look at the amount that's

25  allocated to dose, there's only two pages in the

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Page 98

1  document.

2	So I think I either have to advocate

3  for, you know, for fairness and we ought to expand the

4  section on dose, or we ought to recognize the fact that

5  there really been much new work in the dosimetry area

6  since the last review and we should change the title to

7  something else.

8	But I think it's inappropriate to have

9  the word dose in the title and have so little really

10  devoted to dose.

11	So I would recommend changing the title.

12	DR. HENDERSON: Jim, do you have a

13  specific alternative?

14	DR. ULTMAN: Well it could be, I guess it

15  could be, Human Exposure or something like, Human

16  Exposure to, you know, to Nitric Oxide, something like

17  that.

18	I mean it's basically, I think it's

19  basically an exposure chapter.

20	DR. HENDERSON: Okay, I was thinking

21  maybe, Atmospheric Chemistry.

22	DR. ULTMAN: Oh, the other's Atmospheric

23  Chemistry.

24	DR. HENDERSON: In Human Exposure.

25	DR. RUSSELL: If I might, that's a page

Page 100

1	But there's nothing really in the

2  chapter about the distribution of dose and there's

3  nothing about animal to human extrapolation.

4	And these, it's understandable because

5  nothing much new has been done.

6	Nevertheless, when you look at the rest

7  of the document there's really nothing about, it

8  doesn't, nothing else in the document ties into does, I

9  mean there's this one little section.

10	And I think part of the reason for this

11  was the mentality that, or the philosophy, I mean

12  mentality has a bad connotation   with the philosophy

13  that animal experiments speak only to the toxicology of

14  the substance or the plausibility of particular

15  mechanisms.  But they don't really help you in arriving

16  at a standard.

17	I think that's why it was omitted,

18  because it really doesn't seem to have any practical

19  purpose.

20	And I think if you start thinking in

21  terms of animal to human extrapolation it might change

22  the philosophy a little bit.  So that if there was some

23  of that material, the older material, that was put into

24  the dosimetry chapter, there were some things that Fred

25  Miller had done in the past looking at extrapolation



Page 99

1  and a half more than it has on sources.  And actually I

2  like the title that   this is Ted Russell by the way

3	DR. ULTMAN: Yeah.

4	DR. RUSSELL:   if it goes, it was for

5  the beginning and the end and so it captures everything

6  that's not mentioned is in the middle.

7	DR. HENDERSON: Yeah.

8	DR. ULTMAN: Okay, well I just, I bring

9  it up because it just seems, it seems a little bit

10  strange.

11	DR. HENDERSON: I thought it was pretty

12  catchy myself but

13	DR. ULTMAN: Yeah.

14	DR. HENDERSON:   I don't know if I like

15  it as well as Jim.

16	DR. ULTMAN: You're going to have

17  deflated expectations when people read the title and

18  then go on to read the chapter.

19	But anyway, but I, something else though

20  may be more substantial that maybe could be added to

21  that section.  Because it only, because so little has

22  been done since the last review, I mean what's in the

23  section now is basically some of the biochemistry

24  that's been done recently and a little bit about

25  uptake, you know, kind of global uptake.

Page 101

1  between laboratory animals and humans, both, well

2  primarily from a modeling, from a modeling point of

3  view.

4	And that kind of material then starts

5  stimulating your imagine in terms of, well, maybe some

6  of these studies, even the newer ones that looked at

7  the effect of exposure on hyperreactivity of the

8  airwave or the effect of exposure on the immune system,

9  et cetera, maybe some of those studies could be

10  extrapolated, the exposure conditions that were used in

11  the animals could be extrapolated to humans.  And, you

12  know, it might turn out that those conditions are

13  closer to realistic human exposures than we think.

14	Now I don't know that that's the case

15  and, you know, it's pretty likely that it might not be

16  the case, but

17	DR. BALMES: Jim

18	DR. ULTMAN:   by putting that material

19  in it really helps as I said, look in that direction.

20	DR. BALMES: Jim?

21	DR. ULTMAN: Yeah.

22	DR. BALMES: This is John Balmes.  Sorry

23  to interrupt but I wanted to make a comment directly

24  pertinent to that last point.

25	In several places in Chapter 3 it would

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Page 102

1  be very helpful to have that kind of context about how

2  the animal doses compared to human doses.  You know, we

3  had that for ozone with the ozone CD.

4	And even if we don't feel we have good

5  enough data to be able to extrapolate, just to put it

6  into context, some of the toxicology sections would

7  read better because it's really hard to figure out, you

8  know, what a five part per million dose is to a rat,

9  you know, versus a human.

10	So I think that's an important point.  I

11  just wanted to echo it.

12	DR. ULTMAN: Okay, thank you.  Well that

13  was about it.  I think otherwise I think that, you

14  know, other people have already mentioned some very

15  useful things.  And I think that basically the

16  material, a lot of the material except for this source

17  material I think and some of the things we've been

18  saying about the dosimetry, a lot of the materials

19  there, it could do possibly with some reorganization,

20  as I said, putting things in context a little bit with

21  the current standard.

22	But I think the material needs to be

23  there.

24	DR. HENDERSON: Okay, thank you, Jim.

25  We'll all be up for more discussion of all three of the

Page 104

1	So it was kind of an interesting

2  exposure scenario.  And I think, you know, for that

3  point of view it was, it's useful to be in Chapter 2,

4  but because mostly it's about the health effects, it

5  also seems like it should be in Chapter 3.

6	So I was kind of torn.  I mean I have a

7  comment that said it might be moved.  But I don't know

8  if it's possible to somehow split it up to minimize

9  redundancy but capture some of the exposure scenario in

10  Chapter 2.

11	DR. HENDERSON: Okay, now James Crapo has

12  a comment.

13	DR. CRAPO: One of the issues that I

14  think is going to come up as we go more into health

15  effects is the issue of what kind of a standard we

16  ought to have.

17	I remember when we talked about it

18  earlier some time ago, we had a very detailed

19  discussion of the short term or the 24 hour standard, a

20  long term standard at peak levels and how they

21  interface with it.

22	And that's really not been very

23  effectively addressed in the NO2 document or the

24  literature.  All of this is starting to build a fairly

25  good body of literature that suggests that the short



Page 103

1  first charge questions.

2	I would just like to note, in my reading

3  of Chapter 2, that there's a great health effects

4  section at the very end of it on this Australian study

5  that looks at the indoor air where

6	DR. ULTMAN: Yeah.

7	DR. HENDERSON:   it's mainly NO2 that

8  they were looking at.  And I thought it was a great

9  description of health effects, but I wasn't quite sure

10  why it was

11	DR. ULTMAN: Yeah.

12	DR. HENDERSON:   in Chapter 2 and not

13  Chapter 3.

14	DR. ULTMAN: Yeah, I had the same

15  comment, Rogene.

16	DR. HENDERSON: Okay.

17	DR. ULTMAN: It seemed out of place.  My

18  feeling was that there was a little of a, there was a

19  little bit both there because the kinds of exposure

20  they were getting were a little bit out of the ordinary

21  and very useful, because they were getting, the idea is

22  they were getting these exposures, you know, they were

23  getting the indoor exposures that were, for short

24  periods, relatively short periods of time overlaid on

25  their other expose   you know, on kind of a background.

Page 105

1  term effects are strong and that there are likely peak

2  effects as well.

3	And while we're on the exposure chapter

4  we're going to talk about that because I think

5  ultimately we're going to talk about whether the

6  standard or the recommended change in the standard,

7  what type of a standard it ought to be, what the form

8  ought to be.

9	And as we have this discussion of form

10  here and the data that would underlie that, which I

11  think is going to become a profound question at the end

12  of the day.

13	So I think from the point of view of

14  exposure we ought to see the data expressed in a form

15  that tells me more about the excursions and the

16  shortened effect, the difference between cities in

17  terms of the   for example if you have an average

18  annual level which we talked about at the beginning

19  which is about fifteen parts per billion, if you

20  lowered the national standard to that level, how many

21  cities would be out of conformance with it and what

22  would be the peaks and would that have an effect on all

23  the adverse health effects we're starting to see?

24	I'm sitting her wondering if the

25  exposure data is going to really support us looking at

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Page 106

1  the form of the standards.

2	DR. HENDERSON: And that's the kind of

3  information we need for this to tell us, to support the

4  standard setting process.

5	I'd like to   did the Air Office want to

6  say something?

7	DR. ROSS:    One of the things we really

8  aren't directly in the ISA trying to choose a standard

9  or a form.  The form is actually less influenced by

10  science.  It's sort of a hybrid of science and policy.

11	What we're trying to is develop the

12  evidence that can inform, like what are the effects of

13  exposure to short term exposures and what are these

14  exposure, 24 hour, a one hour peak, what information is

15  available that we can summarize for the Program Office.

16	I'm not sure, I think we're getting some

17  helpful feedback from people in the audience.  I think

18  some of the recommendations, some of reasons we didn't

19  some of the things that are discussed is it was just

20  lack of data.

21	So we would welcome any input from CASAC

22  about data that are available to further expand on

23  these issues like extrapolation from animals to humans

24  for example.

25	Just a follow up statement is that much

Page 108

1  concentrations of oxygen for literally weeks and weeks

2  and weeks at a time.

3	Now, the pediatric community considers

4  that to be "safe".  One can make arguments about that

5  but you're still talking 5 parts per million.

6	What are the environmental NO exposures

7  relative to what it requires on a therapeutic basis to

8  induce peripheral vasodilation?

9

10	So I think some context along those lines

11  if you're going to go down that road I think that that

12  context needs to be included in terms of this dose

13  issue.

14	DR. GORDON: Oh, I agree, it's just we're

15  including some NO2 studies that are private and the

16  relative NO to NO2 emissions could be brought into play

17  in your concept.  I agree.

18	DR. HENDERSON: When you monitor, you

19  monitor both NO2 and NO, correct?

20	DR. PINTO: Yeah, but the NO isn't

21  deposited into the air quality system, you know, that's

22  been available to the public.  That's the problem.

23	DR. GORDON: The data was required in the

24  report.

25	DR. HENDERSON: Well that could be



Page 107

1  of the exposure analysis that we're talking about, you

2  probably will see that it'll be in the risk and

3  exposure assessment that comes from the Air Office.

4	DR. HENDERSON: Okay.  Go ahead, Terry.

5	DR. GORDON: Yeah, even though I'm a non-

6  chemist I wanted to emphasize a couple of points that

7  were stated earlier.

8	Given that NO is so biologically potent

9  and given the fact that all the health effects appear

10  to be on NO2 and that's what's discussed, I'm just

11  wondering if it's the cart or the horse, and that maybe

12  we should really and seriously encourage the EPA to

13  include NO and other temporal species in the routine

14  monitoring.

15	Otherwise we're going to drive it and

16  continue to drive it to NO2 which may or not be

17  appropriate, but we don't know until we have more data

18  NO in particular.

19	DR. HENDERSON: Okay, Ed.

20	DR. POSTLETHWAIT: I'm a little concerned

21  about the use of the word potent.

22	In most clinical situations

23  therapeutically delivered NO is administered in the

24  range of 5 to 10 parts per million and it's given to

25  premature infants on respirators with high

Page 109

1  changed, right, if it was deemed necessary.  I'm just

2  saying, could it be made available?

3	DR. PINTO: I don't know, what's the

4  regulation for it?  Mary, do you have that?

5	DR. ROSS: We're not the right people to

6  speak to the monitoring network.  Out colleagues in

7  OAQPS I'm sure could find out.

8	DR. PINTO: It might be a better question

9  for tomorrow.  Seriously.

10	DR. HENDERSON: Okay.

11	DR. LARSON:  Back to the point about the

12  relationship between the short term and the long term

13  averages.  This is Tim Larson again.

14	I think you would find that that might

15  be different depending on proximity to source, in this

16  case the most ubiquitous sources being near major

17  roads.  And as you know some of those monitors are

18  sited as far away from major roads as possible, but

19  still fairly close in these urban areas.

20	So if you're going to be looking at that

21  later on, you probably already have, but it's useful to

22  try to qualitatively separate out those monitors in

23  that regard because they get very different temporal

24  patterns.

25	DR. WYZGA: I think one simple thing

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Page 110

1	SPEAKER: We can't hear you.

2	DR. WYZGA: Oh, I think one simple thing

3  that can be done to reorganize some of the material in

4  the tables to the extent it's available, is that what I

5  think in terms of trying to sort out the epidemiology,

6  I think that the big issue is the whole issue of

7  surrogacy and so it's very important to look at

8  correlations between NO2 and some of the other

9  pollutants.

10	And it's going to be very dependent upon

11  where the monitor is.  I suspect that if the monitor is

12  sort of source neutral, you're going to get a different

13  set of correlations than if your monitor is near a

14  roadway.

15	And to the extent that that can be

16  separated out I think would be useful.  And I think

17  also temporally too.  I think that annual average

18  correlations could be very different from some of the

19  peak average, peak correlations.

20	So to the extent that we can separate

21  these out I think it would be particularly informative

22  and help us in understanding the epidemiology studies.

23	Because one of the problems we face

24  about it is we don't know who is responding.  Is it the

25  people who are near the roadways or people who aren't?

Page 112

1  and clarification, because I think, you know, it gets

2  confusing when people start seeing that the personal

3  exposures may not correlate with the central site.

4	But what we're looking at is, does the

5  central site correlate with people's personal exposure

6  to out   you know, to NO2 or not, I should say, of

7  outdoor origins.

8	So I don't know if I said that clearly

9  enough, but I think we need to make those distinctions

10  in the document to make it more useful.

11	And then a second comment.  Really I

12  wanted to pick up on Doctor Crapo's argument just in

13  general I think, that throughout the document, starting

14  right at the beginning, the thought has to be, well,

15  how is this useful, you know, what is presented?  How

16  will this be needed for the standard setting process?

17	And a lot of the information is very

18  interesting, but it might not be what is needed at the

19  end.

20	So, you know, throughout the document I

21  get the feel that each   and you know, I'm sure it's

22  true   each section was written independently but I

23  think we need to do another iteration where everybody

24  says, okay, this is what we really need, this is the

25  endpoint we've got to get to and you need to give me



Page 111

1  We just don't know from a lot of these studies.

2	So it's useful to have both in mind.

3	DR. HENDERSON: Oh, George, do you have

4  something?

5	DR. THURSTON: I'd like to take a moment

6  just to talk about the question of indoor and outdoor

7  exposure and I think that we need clarification in the

8  document about the exposure, the personal exposures to

9  outdoor NO2, because EPA is regulating outdoor NO2.

10  It's not going to regulate indoor NO2.

11	I think indoor NO2 is important vis-a-

12  vis, especially vis-a-vis studies that have been done

13  of it.  I think the point was made earlier that some of

14  the most instructive studies about the effects of NO2

15  have been indoor studies.

16	But in terms of the epidemiology and

17  standard setting processes that I think are largely

18  relying on epidemiology, backed up by the other, or not

19  backed up, you know, by the other disciplines, you

20  really need to differentiate the exposures and

21  distinguish in the discussion between NO2 of outdoor

22  origins, personal exposures to NO2 of outdoor origins

23  versus personal exposures to NO2 of indoor origins.

24	And I think that was done in the PM

25  document and I think it was a very helpful discussion

Page 113

1  the information that's most relevant to this end, you

2  know, the endpoint of the process that we're involved

3  in.  And make it most directly relevant, you know, the

4  things like the exposures, who is getting them and what

5  are the various levels of exposures, source of

6  background.  I know that example, that'll be covered

7  later in the next document.

8	But I think throughout that theme has to

9  be there.  How is this useful to the end goal?

10	DR. HENDERSON: Okay.  Thank you.  And Ed

11  has been wanting to talk and I haven't seen him, so Ed.

12	DR. AVOL: Yeah, thank you, this is Ed

13  Avol.  Just one comment on Ron Wyzga's sort of claim

14  that we don't know who is responsive in terms of NO2

15  and whether it has to do with roadways.  I mean there

16  are studies coming out and in fact the studies in

17  Southern California for example, have shown pretty

18  clearly that it's the kids that are closer to the

19  roadways that we see increased incidence of a number of

20  things, symptoms, low lung function, asthma, et cetera.

21	So I think that information is starting

22  to become available.  So it's not quite   I agree the

23  jury is still out, but there is information becoming

24  available.

25	DR. HENDERSON: Thanks Ed.  Now, are

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Page 114

1  there other comments regarding the first three charge

2  questions?  I haven't heard   oh Dale, hi.

3	DR. HATTIS: Hi, hello.  Yeah, I think

4  the vertical gradient in NO2 exposures and therefore

5  being where you have exposure to the higher up are less

6  than the exposures at ground level, and that people

7  have to be located more close to the ground level than

8  the monitors do, I think that's a terrific problem for

9  the interpretation of the epidemiological data in the

10  context of this Australian study which is based upon

11  actually personal measurements, or at least areas,

12  measurements indoors.

13	So in order to translate between these

14  two we have to have an idea of how, of what that

15  vertical gradient is, how often, and how many monitors

16  are located how high.

17	So, you know, the interpretation of the

18  EPI studies in particular is going to be greatly

19  modified by what your analysis is of that business and

20  the distribution of those differences in the people

21  that have been studied.  And I think that reinforces a

22  point that I think you were making, Donna.

23	And so I think that that's really the

24  central issue for the interpretation of how distorted

25  the epidemiological studies are, because you have both

Page 116

1	Did I hear you right?

2	DR. SEIGNEUR: Yes.  Well, maybe I can

3  take a quick example or an extreme example.  Let's say

4  that the existing technique will estimate by a factor

5  of two, then you do an epidemiological study to really

6  understand that based on that measurement technique.

7	Then if you introduce a new technique,

8  which then would give you values which would be higher

9  for what you had before, you may have areas which would

10  be in non-attainment with the old technique which

11  suddenly would turn into attainment.

12	The EPI study would tell you that you

13  would have problems, you know, on the health effects

14  analysis.

15	So I think it's important to be

16  consistent between the EPI studies and the measurement

17  techniques.

18	DR. HENDERSON: Yes, Ted.

19	DR. RUSSELL: If I might, I think it

20  comes down to more not necessarily changing the

21  measurement, but understanding it better.

22	And my advice certainly would be to

23  provide a more thorough assessment of what the

24  uncertainties are with the various measurement metrics

25  of NO2.  Not necessarily saying go and start changing



Page 115

1  systematic error from the differences, the overall

2  differences between the outdoor related exposures to

3  the people relative to the monitoring measurements.

4	And likely quite a bit of random error

5  introduced by the fact that there's some correlation

6  but by far, a far from perfect correlation between

7  what's being measured in the monitors and what's being

8  experienced at least for the outdoor exposure, related

9  exposure of the people.

10	So I think that, you know, that is,

11  because of that difference, the different pollutants in

12  particular, you have a really good chance of

13  distorting, you know, the attribution of effects

14  between pollutants of different kinds.

15	So I think in order to do an

16  quantitative analysis you at least have to have that

17  feature pretty thoroughly quantitatively analyzed, even

18  though the data may well be very sparse to do such an

19  analysis at the moment.

20	DR. HENDERSON: Thank you, Dale.  I would

21  like to hear someone summarize what our advice is on

22  monitoring.  I think I heard you say, Christian, that

23  since the past monitoring has been with this

24  chemiluminescent technique, that to switch would cause

25  problems.

Page 117

1  our measurement method, though it would be nice if we

2  had one that was truly specific to NO2 in the long run,

3  but right now saying, this is the current measurement

4  technology, this is the level of NO2 we usually get, at

5  which time and which season, and this is the likely

6  level of interference and bias that we have in it.

7	Not necessarily throw out the whole

8  thing but really understand what it's trying to tell us

9  at this point.  And I think that information is

10  available.

11	DR. HENDERSON: That sounds like very

12  wise advice.  Are we answering the questions that you

13  wanted to have answered and is there anything we

14  haven't discussed that you were hoping we would

15  discuss?

16	DR. ROSS: Yeah, I think it's been very

17  helpful and it should help us improve on the document

18  for the second draft.

19	DR. HENDERSON: Okay, I'm sorry, go

20  ahead, Ellis.

21	DR. COWLING: I wanted to be sure, is

22  there a consensus among this group that NO2 is the

23  indicator of choice for oxides of nitrogen?

24	We're talking about alternative methods

25  of getting to NO2, but that involves the original

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Page 118

1  assumption that the wisest choice, the most adequate

2  way for this country to understand exposure to oxides

3  of nitrogen, is to get accurate measurements of NO2.

4	DR. RUSSELL: If I might?

5	DR. HENDERSON: Yes, go ahead.

6	DR. RUSSELL: Actually Ellis, I think

7  your question is not as looking at exposure to oxides

8  of nitrogen, but looking at the relevant health

9  effects.  That's what we're trying to assess.

10	So I think that has to come from the

11  people who can tell us which oxides of nitrogen is

12  likely to be given the ambient concentrations one's

13  exposed to.

14	DR. COWLING: No, this isn't just a

15  chemical question.  It is fundamentally a public health

16  question.

17	And I accept your comment, but we have a

18  number of people who are very skilled in health

19  research here.

20	Do you who are skilled in understanding

21  what America ought to do about management of oxides of

22  nitrogen, do you who understand the health effects as

23  thoroughly as possible, just as Ted is suggesting, do

24  you believe that NO2 is the indicator of choice to

25  protect people from oxides of nitrogen?

Page 120

1  NO is a pulmonary vasodilator, it's a pulmonary

2  vasodilator in healthy people as well as sick people,

3  it's just a, it's a smooth muscle relaxant.  Just that

4  it doesn't seem to have any adverse effects when you

5  inhale it over the short term.  But that really hasn't

6  been examined in clinical studies or in long term

7  studies, neither NO2 or NO.

8	But in terms of its irritant

9  inflammatory effects, NO2 has a much stronger action

10  than NO.

11	And I would make the comment that I

12  think the more important thing to be monitoring or

13  considering as a confounder, and this has been

14  mentioned previously, is not NO per se but its particle

15  member, or ultra fine particle counts, because I think

16  many of the indoor studies which look at effects of

17  NO2, the things that produce NO2 indoors are the things

18  that produce ultra fine particles as well, including

19  natural gas combustion.

20	And it's very possible that many of the

21  symptom effects that have been associated with NO2 in

22  indoor studies are in fact studies of particle exposure

23  where it wasn't counted.

24	So I think looking for confounding with

25  PM 2.5 really does not address the issue of whether



Page 119

1	DR. COTE: One of the   I'm about to step

2  into quicksand because this is not my area of expertise

3  at all, but there was a lot of discussion in house that

4  in fact what is really monitored is NOX and what people

5  are really exposed to are NOX and that, you know, we

6  might be better served by simply it that as opposed to

7  NO2.

8	DR. FRAMES: Can I make a comment?  Mark

9  Frames, I'm from the University of Rochester.

10	I mean my understanding certainly of NO2

11  is the regulated pollutant in the NAQS and not NO.  And

12  I think most of that comes from a fairly extensive body

13  of literature, both in vitro and in animal studies and

14  some studies in humans of sort of direct cellular

15  effects but also respiratory and irritant effects of

16  NO2 are much stronger than NO at a given concentration.

17	For example I think Ed made the point

18  that, you know, we're using NO therapeutically at

19  ranges of 5 to 8 and sometimes higher ppm and those

20  kinds of concentrations of NO2 are definitely

21  irritating and cause symptoms and cause lung function

22  changes in some people and cause inflammatory effects

23  as well.  And NO does not.

24	The thing that hasn't been examined are

25  the cardiovascular effects and this was mentioned.  And

Page 121

1  what we're seeing with NO2 effects is in fact ultra

2  fine particle effects.

3	DR. COWLING: Can we infer from your

4  comments that you think   well, let's ask the question

5  directly.  If you were Administrator of EPA, would you

6  endorse the idea that has been with us for 36 years,

7  that the most useful indicator of exposure to oxides of

8  nitrogen is in fact NO2?  And do you think that the

9  present system that we've devised is reasonable?

10	After all, that's why we're here, is to

11  examine the scientific evidence for a decision about

12  whether to keep the standard we've had for all these

13  years, or to alter it in some way.  And I mentioned

14  these four important indicators, the averaging time,

15  the concentration, and what's the fourth one, I can't

16  remember   form, right.

17	If you were Administrator, what would

18  you recommend?

19	DR. FRAMES: You're all fortunate that

20  I'm not the Administrator.

21	DR. COWLING: I know.

22	DR. FRAMES: And I am too I think.

23	DR. ULTMAN: I don't know about that

24  actually.

25	DR. FRAMES: I'm sorry?

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1	DR. ULTMAN: I don't know about that, I

2  think I'd rather have you.

3	DR. FRAMES: Thanks, but I'm not ready to

4  pronounce my opinion on whether the standard ought to

5  be changed.

6	But your questions about whether NO2 is

7  the appropriate indicator, I'm not aware, at least from

8  the evidence that I'm aware of, I don't think we have

9  evidence to change whether NO2 versus NO is the

10  indicator.

11	I don't have, I don't see any evidence

12  that pushes us to say NO ought to be one of the

13  regulated criteria of pollutants.

14	On the other hand, you know, how do we

15  know unless we have data to look at?  And if there's

16  going to be some additional studies of cardiovascular

17  effects in the future, particularly epidemiology and

18  panel studies, it would be very helpful to have NO

19  concentrations in order to gather that information.

20	DR. COWLING: NO of course is only one of

21  the many different oxides of nitrogen and I appreciate

22  what you've just said, and you're demurring from taking

23  the responsibility if you were Administrator.

24	But I think this question, what is the

25  indicator of choice and how should we measure whatever

Page 124

1  the health effects.

2	And I think again the issue that kept

3  coming up in my mind as I read the document, is the

4  fact that there is often good correlation with other

5  pollutants related to combustion sources.  And I think

6  it would behoove us, even we don't have a specific way

7  to, a specific recommendation about a new approach, to

8  say that a new approach needs to be considered, because

9  I really think that we somehow spend a lot of time,

10  waste a lot of time, trying to pin health effects down

11  to a specific group when it's really the pollutant

12  mixture causing the health effects.

13	And so that regulating the pollutant mix

14  should be a goal for the future.

15	DR. HENDERSON: Thank you, John, I think

16  that's a goal of many, many people.  Ed?

17	DR. POSTLETHWAIT: It's Ed Postlethwait.

18  I think there's been various speakers that have touched

19  on this, but we have to remember that as Mark pointed

20  out, the standard is for NO2 yet what we're measuring

21  really is non-NO/NOX.

22	And so the exposure estimates based on

23  that for NO2 are probably only going to overestimate

24  the exposure, not underestimate the exposure.

25	So as long as the catalytic reductants



Page 123

1  it is that we will measure in order to administer a

2  standard for the nation, that is a fundamental issue

3  that we ought to try to wrestle with.

4	DR. BALMES: This is John Balmes.  May I

5  say something?

6	DR. HENDERSON: John Balmes, are you, is

7  that you on the

8	DR. BALMES: Yes.

9	DR. HENDERSON: Okay.

10	DR. BALMES: Can you hear me?

11	DR. HENDERSON: Yeah.

12	DR. BALMES: So I'm glad that Ellis

13  raised the basic question, not so much because I want

14  to get into a discussion about NO2 versus other ways to

15  measure oxides of nitrogen per se, but to get the

16  larger issue of the fact that we currently are

17  regulating pollutant at a time.

18	I don't have a ready suggestion about

19  how to change that, but I do recall from the ozone

20  discussion and it's actually even in our letter to the

21  Administrator, we've written a letter, that we can, the

22  Agency should consider ways to deal with oxidant

23  pollutants in total and not pollutant by pollutant,

24  because it's really probably the burden of oxidant

25  pollutants that are responsible for at least some of

Page 125

1  continue to be used, you're actually measuring by and

2  large the entire population of NOX.  You're just not

3  getting recordings of NO reported.

4	DR. AVOL: This is Ed Avol.  I think

5  there are two other issues echoing this part of John

6  Balmes' comments about the mix.

7	And that is that you remember at the

8  earlier workshop there was a lot of discussion about

9  whether NO2 standard setting was useful in the context

10  of separating it from particulate NOX or nitrates and

11  going at the health effects and even control

12  strategies.

13	And so in terms of thinking about the

14  mix it's not the NO2.  It may or may not be the NO2 and

15  in fact from the community of epidemiology, you know,

16  many times that's what's pointed out, the correlations

17  and the association of the combustion exhaust involves

18  both particles and the gases, so it's often difficult

19  to separate those out.

20	So it really is a more complicated issue

21  that even just talking about NO/NO2.

22	From the epidemiological sense I would

23  also, or the standpoint, I would also point out that in

24  terms of understanding public health and looking at

25  trends in public health, it may or may not be the case

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1  that we want to go forward with NO, or pick up NO and

2  continue with NO2.  I think if we do go forward with

3  NO, we don't, because of the fact that it hasn't been

4  reported all these years, we don't know much about NO

5  nationally.

6	DR. HENDERSON: That's true.  Perhaps,

7  you know, this idea of the multi pollutant is something

8  we may want to address in our letter because it's such

9  an important point.  It's not an answer to a charge

10  question but it's a very important point.

11	So I have noted that we've mentioned

12  that.  George?

13	DR. THURSTON: Well, a couple of

14  comments.  George Thurston.

15	One is I think a start for that would be

16  something that I've mentioned in my written comments

17  and something I mentioned at our last meeting, and

18  other people have alluded to, and that is to start with

19  the interaction of NOX and PM and particulate matter.

20	And start with that, you know, I think

21  that would be a big step forward and it's doable within

22  the context of this document.

23	Parts of it are already in the document

24  here and there, but it's just a matter of organizing it

25  and trying to see that as a theme throughout the

Page 128

1  published studies of exposure.  There aren't any

2  studies that have used children in exposure studies.

3  There are panels for other specific groups that I think

4  we've discussed.

5	One of the things I will mention though

6  is tomorrow we'll be discussing the exposure assessment

7  and we'll be some models and available data to try to

8  estimate exposure to children and other groups like

9  that possibly.  There's data that we'll be commenting

10  on tomorrow.

11	So we can look at what studies and what

12  data are available and I'm not sure that there were any

13  data available on children.

14	DR. KIM: When you use the specific term,

15  susceptible population, in Chapter 2, but if you look

16  at table, especially Table 2.5 or a, a lot of studies

17  are focused on the children and senior groups.

18	DR. COTE: The other thing I'm sure

19  everybody is aware of is HEI has this large effort

20  ongoing that they are hopeful they can share with us

21  before the final draft that's focused more on roadways

22  and transportation issues.

23	DR. HENDERSON: You're concentrating on

24  the exposures near roadways, is that what you're

25  saying?



Page 127

1  document.

2	There was one other thing.  Oh, and that

3  was with the exposures.  Is there a place here to look

4  at the exposures of susceptible populations?  As we get

5  to the end of the document we're focusing on

6  susceptible populations, people with asthma, children,

7  people who live near traffic, actually those are all

8  three pretty much the same people, because a lot of

9  children with asthma live near traffic in the United

10  States.

11	So what are their exposures and how are

12  they   you know, we can characterize exposures

13  throughout the United States in the general population,

14  but this is a very large group of people that will end

15  up I think being a focus of the evaluation at the

16  endpoint, protecting public health.  Are we protecting

17  the health of children with asthma in inner city

18  locations?

19	And so I think we might want to have

20  information about their exposures in the exposure

21  section or just in general exposures of susceptible

22  populations to outdoor air pollutants, outdoor NOX.

23	DR. HENDERSON: Okay.  Can I ask, Mary,

24  do we have data to do this?

25	DR. ROSS: Well I believe there are no

Page 129

1	DR. COTE: I think that's right.

2	DR. HENDERSON: Yes, I think so.  Ed?

3	DR. AVOL: I'd just ask for one

4  clarification from Mary coming from the children's

5  health study in California.

6	Did you say there are no children's

7  studies?

8	DR. ROSS: There are children's studies.

9  But I was commenting on the personal exposures and

10  ambient concentrations.

11	DR. HENDERSON: The Australian studies

12  have too.  I thought those were very impressive.

13	Are thee other questions?  Yeah, Dale?

14	DR. HATTIS: Yeah, I've been taking a

15  quick look at the data that are in one of the annex

16  tables, AX 3.1, and I think in the context of looking

17  at the relationship of the existing data to the

18  standard, I think there are some facts in that table

19  that are helpful.

20	First is that, off all of the monitors

21  in CMSA in urban areas there aren't any that get even

22  close to the current .053 annual average, okay?  That I

23  think might be a fact that's more prominent.  So if in

24  fact you think that the current epidemiological studies

25  are detecting effects, then you must believe there are

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1  effects below the current standard, okay?

2	The second is that, you know, one of the

3  things that I've been doing just sort of on the side

4  here is to try to look at the difference in the

5  variations between averaging times.  And so I've got a

6  figure that does that but maybe this isn't the right

7  time to show you that.  But basically the shorter

8  averaging times that you expect have more variability

9  than the longer averaging times.

10	And we can know how much that is and

11  that seems to me one of the things that could go into

12  the decision as to how to structure the standard.  But

13  of course, even more important is, okay, what is the

14  averaging for the actual causation of the biological

15  effects.

16	And I don't have a clear idea of the

17  existing discussions of the health effects yet, what

18  that is.

19	DR. COTE: Rogene, I have two quick

20  questions.

21	DR. HENDERSON: Okay.

22	DR. COTE: I thought I heard in answer to

23  Doctor Cowling's question, that there wasn't a

24  substantial argument for moving away from NO2 as an

25  indicator.  I think that's what I heard as a consensus.

Page 132

1  favorable things about doing uncertainty analysis.

2	DR. COTE: Yeah, I think that's   okay,

3  Mary has clarified that that was really meta-analysis

4  rather than uncertainty analysis.

5	DR. ULTMAN: Those are two different

6  things.

7	DR. HENDERSON: No, I think uncertainty

8  analysis is favorably

9	DR. ULTMAN: Is Lianne on the phone,

10  because that's one of her areas of special expertise?

11	DR. SHEPHERD: Yeah, I am on the phone.

12  I don't know that I have anything to add to that now.

13  It'll probably come up a lot more tomorrow.

14	DR. HENDERSON: Okay, is that Lianne?

15	DR. SHEPHERD: Yes.

16	DR. HENDERSON: Okay, I thought we needed

17  a comment.

18	DR. SHEPHERD: I don't have anything to

19  add right now.

20	DR. HENDERSON: Okay, she said she --

21	DR. ULTMAN: More later.

22	DR. HENDERSON:   would have more later,

23  yeah.

24	DR. SHEPHERD: Right.

25	DR. COTE: Okay, that was all that I



Page 131

1	DR. HENDERSON: I thought I heard that

2  there is not now good evidence to move away from NO2,

3  though there is concern about the multi pollutant

4  effects and how you handle that, which probably goes

5  way beyond the scope of this panel.

6	DR. COTE: We're concerned about that

7  too.  We've been discussing that a lot.

8	DR. HENDERSON: Yeah.

9	DR. COTE: I don't want to get into a

10  long discussion but the second question I had, I just

11  wanted a little feedback on is, you know, a number of

12  people have said, have mentioned looking at the

13  uncertainties around a number of these factors.

14	And my questions is there's, you know,

15  I'm sort of of the school of uncertainty analysis, but

16  there is a deep seated feeling in the organization that

17  CASAC in the past has not particularly looked favorable

18  on uncertainty analysis.

19	Now maybe that has more to do with how

20  the uncertainty analysis was done versus a general

21  dislike of it.  But maybe Mary can shed a little more

22  light on that.

23	Meta-analysis, Mary says it was meta-

24  analysis, not

25	DR. HENDERSON: I think I've heard very

Page 133

1  wanted to know.

2	DR. SHEPHERD: I do have a comment though

3  about

4	DR. HENDERSON: Okay.

5	DR. SHEPHERD:   Chapter 2 with respect

6  to this comparison and discussion of correlation

7  coefficients.

8	I just couldn't make sense out of it,

9  there are so many different correlations being compared

10  and they weren't clearly defined and there were so many

11  factors that would make them different, like seasonal

12  restriction and so on.

13	And that was tried, attempted to be

14  addressed, but that whole piece needs to be reworked

15  because I didn't think that we could draw any

16  conclusions from the data as presented.

17	DR. HENDERSON: Thank you, Lianne.  Ron?

18	DR. WYZGA: Just one thing.  I think this

19  is in response to the issue about what's the

20  appropriate indexing method, you know, NO2 is thought

21  to be appropriate.

22	But I would still urge that to the

23  extent the Agency can update the report NO data, it

24  would be particularly for people with a deeper

25  analysis.

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Page 134

1	So I think that's something we don't

2  want to let go of.

3	DR. HENDERSON: Okay, thanks, Ron.  Ted,

4  you look like you're about to say something.

5	DR. RUSSELL: Yes.  I was going to ask

6  Ellis, I actually got the feeling you were pushing

7  maybe the Agency looking at something like the nitric

8  acid or something like that.  And I'm not sure if

9  that's

10	DR. COWLING: No, I have biases of course

11  over the two, but I have no special bias towards the

12  nitric acid simply raising the question, what is the

13  appropriate measurement technique and what is the

14  appropriate monitoring design and what is it, as you

15  pointed out yourself, what is it that worries the

16  health people in terms of their experience in dealing

17  with humans that suffer from asthma and all the other

18  difficulties that observed?

19	The Academy of Sciences has urged that,

20  in its most recent management of air quality in the

21  United States report, urged consideration of multiple

22  pollutant, multi effects ways of approaching the air

23  quality management.

24	And this discussion about what about the

25  connection with ozone, what about the connection with

Page 136

1  pollutant at a time.  So I think we will eventually go

2  to the multi pollutant system.

3	DR. ARNOLD: I just want to say just one

4  thing, this is Jeff Arnold.

5	DR. HENDERSON: Can you speak into the

6  mike so we can hear you?

7	DR. ARNOLD: I just want to say that one

8  of things we are trying to do with the discussion about

9  the monitoring of NO2 in itself, and this bears

10  directly on both of Ellis' points, is that we were

11  talking generally about the uncertainty in the NO2

12  measurement and whether or not NO2 is the indicator

13  chosen to go forward, because we thought it was

14  important to have that information available to people

15  who are working on health effects.

16	The other side of this whole thing, we

17  were talking about the more general measurement in

18  trying to get to a characterization of the mix is the

19  reason that we were looking at and talking about the

20  measurement of NOI together because it's a fairly

21  simple transformation to make mechanically.  And some

22  measurements are actually in place in the network now

23  and we can understand what those relationships look

24  like.

25	And that NOI then captures more of the



Page 135

1  PM, emphasizes exactly why that committee strongly

2  urged, and why Europe is in the process of accepting

3  that recommendation.

4	We have a bias in this country to doing

5  one thing at a time and we're biased also to not do

6  anything until there's a crisis.

7	I presume they were interested in the

8  crisis in 1971 relating to oxides of nitrogen and that

9  that's where we got the standard that we now have and

10  have continued to use for 36 years.

11	So we should take a wiser choice, a

12  wiser, make a wiser series of recommendations.  And

13  certainly as Rogene said a few moments ago, we'll

14  probably have to deal with that multiple pollutant, but

15  Amen.

16	So I'm asking in the most general way,

17  what is it that CASAC ought to recommend to the

18  Administrator with regards to management of oxides of

19  nitrogen?  And if that means what they ought to do

20  about ozone and PM at the same time   by all means.

21	That is a bias, I am biased toward the

22  notion that managing air quality is a much bigger job

23  than managing one pollutant at a time.

24	DR. HENDERSON: Well as far as consuming

25  time it certainly takes more time to do it one

Page 137

1  actual oxides of nitrogen mix than we do with the NO2

2  measurement which has got an unknown and varying amount

3  of interference.  It varies both spatially and

4  temporally at all the measurements that are in there.

5	And so as part of the point of getting

6  to a multi pollutant strategy, which I'm not

7  recommending that we try to do at this point in this

8  meeting, but that was part of the idea of looking at

9  NOI because it characterizes more of the oxides of

10  nitrogen.

11	DR. HENDERSON: Thank you.  Now, we're

12  going to be breaking for lunch.

13	Before we do as we discussed earlier, we

14  have a little new process at the end, so Angela is

15  going to try to summarize what we want to say to the

16  Administrator, the key points.

17	And so those of you who have, your name

18  is underlined, I'm hoping that you will be able to get

19  a written summary of our, the panel's answer to those

20  charge questions to Angela by email.

21	There's two important things, monitoring

22  Ted, will you put that in, and you had I think a good

23  summary of   you and Christian together, be sure that

24  monitoring is in there.

25	And then Ellis, could you write up a

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Page 138

1  little sentence on that we need to start addressing

2  multi pollutants?

3	DR. COWLING: I would be happy to.

4	DR. HENDERSON: Thank you.  And send

5  these snippets to   Tim Larson, are you on the phone?

6	DR. LARSON: Yeah.

7	DR. HENDERSON: You may not realize

8  you're supposed to be writing something up.

9	DR. LARSON: Yes.  So you'd like me to,

10  would you like me to try to summarize some of these

11  points about the sufficiency for evaluation?

12	DR. HENDERSON: Okay, I could barely hear

13  you but if you would send us that email, to Angela,

14  she's going to collate them.

15	DR. LARSON: Okay, can you hear me?

16	DR. HENDERSON: Yeah, when you speak up I

17  can hear you.

18	DR. LARSON: Okay, I don't know what the

19  phone is but I'm sort of yelling into it.

20	DR. NUGENT: Rogene is asking for this by

21  tonight.

22	DR. HENDERSON: Oh yeah, this is not in

23  the future, this is today.  Today.

24	DR. NUGENT: Today.

25	DR. HENDERSON: And tomorrow morning

Page 140

1  letter to be 50 pages long, but you know.

2	DR. THURSTON: And Angela said she wanted

3  it at the latest by 10:00 p.m. eastern time, is that

4  daylight I guess, we're still on daylight, right?

5	DR. HENDERSON: And I really thank Angela

6  for being willing to pull this all together for us.

7	Okay, let's have lunch.  The restaurant

8  is what are we going to do?

9	SPEAKER: Vanessa knows.

10	DR. VU: Lunch for CASAC members is where

11  you meet for breakfast, the Raleigh Room.

12	DR. HENDERSON: So we will convene at

13  1:00 and there are people here who are going to be on

14  the phone, so let's be back.

15  (WHEREUPON, the morning session was concluded at

12:03

16  p.m.)

17	DR. HENDERSON: The next three charge

18  questions are all related to health, the Charge

19  Questions 4, 5 and 6.

20	So I think, and we have many health

21  experts here to comment on this.  This is a very

22  important section, quite critical and I hope everybody

23  has read the bottom line that was on the last paragraph

24  of Chapter 5, because it tells you that the Agency

25  considers that there's sufficient evidence to, that the



Page 139

1  we're going to pass this around and we're going to

2  decide whether this is something that we can agree on

3  as far as the letter to the Administrator and how we

4  think this document needs to be changed to improve it

5  or whether we can't.

6	If we can't we have a conference call

7  later on.

8	DR. LARSON: Rogene, what would you like

9  me to emphasize and what part of the discussion?

10	DR. HENDERSON: What did you say?

11	DR. RUSSELL: What would you like him to

12  emphasize.

13	DR. HENDERSON: Oh.

14	DR. LARSON: What part of the discussion

15  do you want me to try to summarize?

16	DR. HENDERSON: Well, Charge Question 3

17  but that's, I know what you mean, that's kind of, it

18  involves everything under, in Chapter 3.

19	The indoor/outdoor or maybe NO as the

20  surrogate for, I mean NOX, NO2 as the surrogate for

21  nitrogen oxide.  That's something we want to have in

22  there.

23	DR. LARSON: Okay, okay.

24	DR. HENDERSON: Just a paragraph, short,

25  short and sweet because the letter, we don't want the

Page 141

1  standard should be strengthened as I understand what's

2  written up there.

3	But we need to put this in context as we

4  go through these different charge questions.

5	We'll see how it goes, we may want to

6  combine some of these discussions.  I think they will

7  combine themselves almost automatically but we'll start

8  out with Charge Question 4, which is really at the

9  heart of the whole thing.

10	To what extent is the discussion and

11  integration of evidence when the animal toxicology in

12  controlled exposure human experimental studies and

13  epidemiologic studies technically sound, appropriately

14  balanced and clearly communicated?

15	So that's going to be headed by Terry

16  Gordon.

17	The man who is writing down what we are

18  saying would like for us to identify ourselves before

19  we start talking, and particularly those who are on the

20  telephone.  So if you don't mind doing that, that would

21  be helpful.

22	And Terry Gordon is speaking first.

23	SPEAKER: Rogene, I can't hear anything.

24	DR. HENDERSON: Well nobody's talking

25  right now.  That's good.

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Page 142

1	SPEAKER: That's good, okay.

2	DR. HENDERSON: We have to speak up into

3  the mike.

4	SPEAKER: Okay, all right.

5	DR. GORDON: There's a great deal of good

6  work here in this Chapter 3 and 4 and I feel that the

7  health relevant studies have been presented.  This is

8  really loud to me.

9	Obviously this long, long chapter was a

10  multi author effort and the inconsistencies in

11  integration across the different sections is what I

12  feel is the main problem with this chapter, this

13  Chapter 3, in terms of answering the Charge Question

14  number 4.

15	So the proper degree of integration and

16  study discussion in terms of relevance to our task of

17  reviewing the science of NOX health effects, it's

18  presented in a few places, mostly in the descriptions

19  of the clinical studies.  But adequate integration is

20  most absent in the animal tox descriptions and

21  sometimes I feel the EPI studies were not integrated,

22  they just tend to wander.

23	So part of me was thinking that a single

24  or maybe two at the most authors should be charged with

25  the next step of condensing and integrating this

Page 144

1  might be easier to give a full interpretation and

2  integration of the EPI studies and then mention briefly

3  in each one of those sections afterwards, how the

4  clinical and animal tox data supports or refutes the

5  EPI data, rather than how it is now.  It's a little bit

6  separate.

7	Then, and this is just out in left

8  field, I was wondering is Chapter 4 necessary, the

9  susceptible sub-populations, even though it's something

10  I actually do research on a lot.  It seems it's partly

11  duplicative of what's going on in 3.

12	Why would you pull out the most

13  sensitive sub-population effects into a separate

14  chapter?  Shouldn't that be in the Chapter 3?

15	And in summary I think is like a key if

16  not the key chapter and it's needs better balance

17  between providing the details of the central studies

18  and the overall integration with health effects.

19	And as Ellis said this morning, it needs

20  to be made a much more efficient communication device.

21  And it's most important to have an integrated analysis

22  that draws the key conclusions from the available data

23  sets, and I stole this from Dale, and include the

24  magnitude of the concentration response for the

25  different health endpoints.



Page 143

1  chapter.

2	And for example there are several

3  redundancies in these studies, things repeated two

4  pages later.

5	So in general I just have four short

6  bullets and I feel it's important

7  that only the key studies that support or refute the

8  NAQS should be included.  And unlike Chapter 2

comments

9  we heard earlier where they wanted to bring some of the

10  annex information into Chapter 2, I think a good bit of

11  information in Chapter 3 should go back to the annex,

12  and more integration and discussion devoted to the key

13  health relevant studies.

14	And then because it's such a large

15  chapter, and I don't know if anybody is going to

16  suggest splitting it up, it seems it should have a

17  summary at the end of each section that discusses the

18  relevance of that section as it relates to adverse

19  effects with concentrations, something that was brought

20  up before and something that's missing.

21	And in this latter point it's key across

22  all the study types, especially the EPI studies which I

23  think are driving the NAQS review.

24	And therefore if the EPI studies, if

25  it's decided the EPI studies drive the NAQS, I think it

Page 145

1	And that's probably the key to this

2  whole chapter and it's only there as I said in a few

3  places.

4	And to reemphasize what Jim Ultman said

5  earlier, that the exposure concentration in studies,

6  the EPI ones of course, should be put in context

7  throughout during the summary at the end of the chapter

8  in the context of the current standard with respect to

9  reviewing is it appropriate or not.

10	DR. HENDERSON: Thank you, Terry.  John,

11  are you ready to give your comments?

12	DR. SAMET: Yes, it's Jon Samet or John

13  Balmes?

14	DR. HENDERSON: Oh, I'm sorry, it's Jon

15  Samet

16	DR. SAMET: Okay.

17	DR. HENDERSON:   and not John Balmes,

18  I'm sorry.

19	DR. SAMET: Just checking.

20	DR. HENDERSON: I was thinking J-O-N, but

21  you can't tell the difference.

22	DR. SAMET: Yes, so I wrote fairly

23  lengthy general comments that I think speak largely to

24  this charge question.

25	So my general comments were that I did

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Page 146

1  not see this document succeeding in meeting what it was

2  called, integrated.  And that this problem really

3  reflects sort of a failure of process which I think

4  sort of comes through in the last comment and some of

5  the other comments.

6	There are models for doing systematic,

7  integrated reviews and I don't really feel that this

8  document looked to those models, the authors looked to

9  those models, the Agency looked to those models in

10  setting out on a process.

11	And then I think that comes through

12  because the methodology is rather opaque for me in sort

13  of achieving the integration.  Terms like coherence,

14  plausibility, consistency pop up but they're not really

15  clear as to the intent of those terms as they're

16  reviewed.  They're sort of convenient to use.  The word

17  is integration is used without integration taking

18  place.

19	So I will say that as a general model

20  for how to proceed to do integrated summaries, I'm

21  concerned about this as a starting point.

22	And then that reflects back of course on

23  question 4, on Charge Question 4 because that is the

24  one where the integration is supposed to come in.  And

25  I just don't see that the methodology was set out.  I

Page 148

1	So I saw problems and the problems don't

2  relate to necessarily these were picked out in how they

3  were represented, but really whether they were

4  integrated or not.  And as I say right now my view is

5  that the integration and synthesis that was needed here

6  has not been accomplished.

7	And so much of this sort of reads   I'm

8  sorry to say this   but sort of like a mini criteria

9  document with sort of recitations of studies with, you

10  know, paragraphs starting of with, you know, Schwatz,

11  et al shows and so on, so that it's, I just don't think

12  the model's integration has been met.

13	So that means that the answer for the

14  charge question is that this has not yet been done

15  adequately.

16	DR. HENDERSON: Okay Jon, was that all

17  you had for this charge question?

18	DR. SAMET: Yeah, and I think again I've

19  laid out a lot of general thoughts in my comments.

20	DR. HENDERSON: Yes, you sent extensive

21  comments.  Well now let's go to John Balmes.

22	DR. BALMES: Okay.  So first of all I

23  apologize for not submitting written comments yet.

24  I've been working on a grant and that's had to take

25  priority.  But I will submit those by the end of



Page 147

1  mean there's sort of these little mini reviews of that,

2  the mini reviews of some tox that might be viewed as

3  relevant.  But it's not really brought together.

4	I was concerned, and I think I saw some

5  of this in George Thurston's comments as well about

6  sort of the underlying framework and ideas.  And I

7  think the interpretation of effects attributable to NO2

8  and NOX is very difficult because of the links back to

9  common sources of other pollutants, the contributions

10  of NOX and PM, the role in ozone generation.

11	And these sort of simple underlying

12  causal models that seem to play throughout the document

13  may not be correct.  And again in my comments I sort of

14  outlined some of the different models and there's some

15  little figures there that are the kind of thinking that

16  I think ought to come up front in the document.

17	Because again, the document has to make

18  clear that NO2 is the right indicator itself, that

19  reduction of NO2 could be reasonably expected to have

20  benefits, which is the causal model and potentially

21  some of the other models.

22	But again if we're working to lower PM,

23  and that is one way that NOX is in fact mediated, we're

24  sort of going after the same sources twice obviously

25  and I think that that could be acknowledged.

Page 149

1  tomorrow.

2	I didn't hear the start of Terry's

3  comments but I heard the end and I heard of Jon's.

4	And, you know, the question for charge 4

5  has four, excuse me, three specific components, is the

6  discussion integration of the evidence from different

7  types of studies technically sound, appropriately

8  balanced and clearly communicated?

9	So on the technically sound part I would

10  say that my major concern was just articulated by Jon

11  and also George Thurston in his written comments, that

12  I think there need to be clearly communicated criteria

13  about how steady the epidemiologic studies in

14  particular were selected.  And then how the results are

15  evaluated.

16	I thought Jon and George both

17  articulated that well.  So that's on the technically

18  sound thing.

19	With regard to appropriate balance, I

20  guess I was a little concerned that two negative

21  studies that I've coauthored didn't appear in the

22  discussion.  And I think while neither one of these

23  studies is earthshattering, given the relative dearth

24  of information with regard to nitric acid vapor, our

25  1993 study which I think is one of the very few studies

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Page 150

1  to compare filtered air and nitric acid vapor, the

2  controlled human exposure study, the fact that's not

3  even mentioned, and it has been published since the

4  last criteria document, should be mentioned.

5	Again it's a negative study.  There's

6  also a study that was published in 2005 by my group

7  which was a negative study about NO2's affect on

8  allergic inflammation using induced sputum rather than

9  bronchoalveolar lavage.  There's a brochoalveolar

10  lavage study mentioned.

11	I only point out these two studies

12  because those are ones I knew about because I'm the

13  coauthor.  I am a little bit concerned that even though

14  we need a shorter document than the old criteria

15  document, that there may have been some cherry picking

16  in terms of studies to the exclu   you know, which, to

17  the exclusion of some relevant information.

18	I don't know that for a fact but I'm

19  concerned about it.

20	And, you know, in terms of the clear

21  communication, I don't think it cuts it.  The chapter

22  is repetitive about mechanisms for sure.  I don't think

23  the mechanistic information is well integrated with the

24  epidemiologic information.

25	You know, an example would be when the

Page 152

1  they're taking, that the authors are taking what the

2  original studies probably used, but it would be nice to

3  have a common metric when you're going back and forth

4  between studies.

5	And I also think that the tables and

6  figures, which I like, at times need better labels or

7  legends because they really should sort of stand on

8  their own so you don't have to go back into the text

9  and figure out what's there.

10	So those are two picky things.

11	I guess one more, sorry, there is a

12  section on the effects of NO2 on allergic responses in

13  synthesized individuals which I think is an important

14  set of, it's an important section, but that important

15  section in my mind doesn't make it into the integration

16  with a focus on asthma.  And I think it should because

17  that may be an important way by which asthma is

18  exacerbated by NO2.

19	That's all I have to say --

20	DR. HENDERSON: Thanks, John.

21	DR. BALMES:   at this point.

22	DR. HENDERSON: Thank you very much,

23  those are very helpful comments.  And Ron?

24	DR. WYZGA: Let me first of all

25  apologize, I've been in the office two days in the past



Page 151

1  long term exposure and morbidity sort of integrated

2  summary of that piece is done, the first paragraph is

3  about, it mentions respiratory illness and growth of

4  lung function, and then there's like three or four

5  paragraphs about respiratory illness, potential

6  mechanisms by which respiratory illness in kids might

7  be increase by NO2 exposure.

8	And then there's a little, there's very

9  little about possible mechanisms for the observed

10  effect on growth of lung function from the Children's

11  Health Study.

12	And I just think you could do a much

13  better job of integrating the toxicologic information

14  with the, in support of various epidemiologic results.

15	So I would have to agree with Jon that

16  the 150 pages or whatever it is that are there are,

17  while better than a criteria document, it's kind of a

18  mini criteria document, it's not really an integrative

19  summary that I think can inform policy makers with

20  clear communication.

21	And the one final sort of picky thing

22  that I think would make it easier for   or two things

23  in terms of policy makers reading this.  It goes back

24  and forth between micrograms per meter cubed and parts

25  per billion and parts per million.  I realize that

Page 153

1  six weeks due to personal and professional activities.

2  So I have not had a chance, had access to all of my

3  files and all of my data, but I depended very heavily

4  on what I know and sort of grabbing a couple of things

5  when I was in the office.

6	And it's difficult, we don't want a

7  criteria document but we really want to include what's

8  relevant and it's sort of hard to decided what the

9  dividing line is.

10	But the first issue I asked myself is,

11  what's here, is it comprehensive?  And the idea is we

12  don't to be as comprehensive as a criteria document,

13  but where do we stop?  I don't know.

14	But I'll say that I was very

15  disappointed that it's not comprehensive.  Thinking

16  about studies that I've been involved in, there are

17  some very key studies that have been published that are

18  not listed.

19	They were negative studies that looked

20  at a whole range of pollutants, including NO2, the

21  findings were negative and the studies aren't referred

22  to at all, including one looking at physician visits

23  for childhood asthma.

24	I grabbed a couple of papers as I was

25  leaving the office that had NO2 in them and I looked at

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Page 154

1  them on the airplane.  They weren't referenced either.

2  And one of the studies was a study in Southern

3  California that looked at VOCs and NO2 and basically

4  when the two are looked at together they show nothing

5  for NO2 and it's very hard to discern on both of them.

6	So I felt that it wasn't comprehensive.

7	And the second thing is, again thinking

8  about the studies that I know well, I didn't feel that

9  they were accurately reported and there were just parts

10  of them reported.

11	An example, as part of the area study,

12  Peel, et al looked very extensively at respiratory

13  endpoints.  And when they looked, she looked at single

14  pollutant models she found association with NO2 and

15  respiratory, hospital admissions for respiratory

16  diseases.

17	When she looked at multi pollutant

18  models she found that NO2 went away and the ozone

19  seemed to dominate everything.

20	Now, there are problems with multi

21  pollutant models and you have to wave your hands a

22  little bit and explain them, but I felt at least the

23  document should have presented the multi pollutant

24  results and not only the single pollutant results.

25	The same is true of the area study by

Page 156

1	And for that reason I think that multi

2  pollutant studies are particularly important.  How

3  robust is that association if you look at other

4  pollutants?

5	And I think this document needs to look

6  at it more systematically and sort of talk about what

7  are the co-pollutants under different circumstances?

8  If you're near a roadway in general.

9

10

11

12

13

14	And I think more weight should be given

15  to those studies that tend to look at co-pollutants

16  rather than studies that look at a single pollutant.

17  And this is why I think it's also important to tie it

18  in with the clinical studies and the toxicology studies

19  because in the controlled exposures we know exactly

20  what people and animals were exposed to and tie them

21  together.

22	So I would ask that one go back and see,

23  are you missing other important studies?  Are you

24  treating them fairly when they deal with co-pollutants?

25  Are you emphasizing that?  And then ask yourself other



Page 155

1  Metzger which looked at cardiovascular disease and

2  admissions.  You know, NO2 is reported in an earlier

3  data set, NO2 was reported and then they spoke about

4  results of NO2 and CO together where NO2 was still

5  important.  But in a later data period where we had

6  much more extensive data, NO2 went away, EC and carbon

7  particles were much more important as was CO.

8	Again, these results were not reported.

9  I was involved in a long term study with mortality with

10  Lipford where we found associations with NO2.  And

11  again when we looked a multi pollutant context it was

12  dominated by ozone and it went away.

13	And the study that's in here reports the

14  single pollutant results and does not report some of

15  these multi pollutant results.

16	Now there are caveats in dealing with

17  them and I think they can be handled and discussion,

18  but I think it's fair to get them.

19	I think the major problem we have to ask

20  ourselves with NO2 is clearly in single pollutant

21  models we see a lot of evidence of association with

22  health effects.  And the really big question is, is NO2

23  serving as a surrogate for something?  And that's

24  something we really have to, you know, dig into and

25  think about it.

Page 157

1  questions too.

2	In looking at some studies, in looking

3  at results, you know, people looked at different lags

4  and I found, you know, it wasn't always consistent.  In

5  some cases it was a very short lag that's important.

6  In other cases the lag was several days out.

7	Is that meaningful or not?  I don't know

8  but I think it's something that needs to be

9  entertained.

10	Those are my major comments and I'm

11  happy to answer further questions and I'll send you

12  those specific references as soon as I get back to the

13  office.

14	DR. HENDERSON: Thank was my first thing,

15  I wanted to be sure that we will have those copies of

16  the reports you're talking about.

17	Can you off the top of your head say why

18  some of these negative studies were not included?

19	DR. ROSS: Well I've been looking in the

20  document because cheery picking is obviously something

21  we take very seriously.  And all I can say is we did a

22  systematic literature search using source terms that we

23  worked out with the librarian and worked over.  And I

24  think we tried to gather information.

25	For Peel and Metzger I'm looking at the

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Page 158

1  multi pollutant figure we put together and as I recall

2  the results were in figures and not quantitative

3  results that we could pull into to a figure ourselves.

4	So I think we tried to look at those

5  studies as much as we can.

6	I don't have any reason, I don't know

7  all the specific studies people are mentioning, but we

8  certainly tried to include as many as we can and we

9  welcome any   we will look very seriously and do

10  another literature search and make sure we didn't miss

11  something.

12	But please, you know, submit references

13  that you think we missed.

14	DR. SAMET: Rogene, this is Jon.  Can I

15  make two follow up comments?

16	DR. HENDERSON: Sure.

17	DR. SAMET: Yeah, just one on the

18  literature search strategy, I think it has to be more

19  transparent than it is.  And I think, I'm sympathetic

20  to trying to have a list, but when it's not clear and

21  replicable how studies are being selected you'll always

22  be subject to enquiries like, why wasn't whatever study

23  included?

24	And I think that that's a problem with

25  the document.

Page 160

1  was very briefly mentioned about endogenous NO

2  production, I thought in terms of trying to put the

3  experimental results, both in toxicology and

4  epidemiology into a biological plausibility context,

5  that the endogenous production of reactive nitrogen

6  species was pretty absent from the discussion.

7	In the field of free radical biology

8  it's been recognized now for many years, that NO2 is

9  produced endogenously anytime you have an inflammatory

10  response.

11	How you put that into context relative

12  to the low ppb NO2 inhalation exposures we're talking

13  about, especially in the epidemiology studies, I don't

14  have an answer to.  But to equate causality to

15  something that is 10, 20 parts per billion relative to

16  the exact same molecule that's produced from a

17  peroxidase reaction and uses nitrite and hydrogen

18  peroxide, I think somewhere in this document that whole

19  issue has to be addressed.

20	Now as I said, putting that in terms of

21  quantifiable amounts of NO2 is an extraordinarily

22  challenging thing to do.  But I think on a relative

23  term at least, that should appear.

24	Likewise when in the document when we're

25  talking about some of the co-pollutant stuff, nothing



Page 159

1	I just want to have a caution, and this

2  comes in light of the little figure, that

3  interpretation of the multi variant models here is very

4  complicated, because of the possibility of direct

5  pathways, indirect pathways and confounding.

6	And I think that this issue needs very

7  careful intellectual attention up front.  And how you

8  do interpret these models and when effects come and go

9  depending on what variables are included, the

10  interpretations are not so simple as either the

11  document portrays them or very often how authors

12  interpret them.

13	So I would urge some real thinking about

14  how to interpret these multi pollutant models.  And of

15  course if in fact NOX is acting through other

16  pollutants and you put those pollutants in a model and

17  the NO2 goes away, that does not mean it's not having a

18  causal effect.  Just as one example.

19	So I think you need to build a better

20  framework up front for interpreting the evidence you're

21  going to present.

22	DR. HENDERSON: Thank you, Jon.  Yeah,

23  Ed?

24	DR. POSTLETHWAIT: Yeah, this is Ed

25  Postlethwait.  In Chapter 3 and Chapter 4, although it

Page 161

1  was said about the endogenous production of carbon

2  monoxide and CO now is recognized as a second, and in

3  fact it's being used in preclinical trials.  And so

4  they're delivering CO to people that ten years ago we

5  would have thought was just nuts to do.  And now it's

6  shown to have some anti-inflammatory and other types of

7  efficacies.

8	And so the connection between the known

9  mechanisms of action and biological plausibility, et

10  cetera and the outcomes that were reported in the

11  document, I think could really be tightened up.

12	DR. HENDERSON: Okay.  Ed, those are some

13  important points and I thank you for bringing it up.

14	Ed Avol has a comment and then I want

15  Kent Pinkerton to come in because Kent at one time was

16  not going to be here and so he inadvertently got left

17  off this list, so he's going to speak after Ed Avol.

18	DR. AVOL: Thank you.  So I just have a

19  couple of comments to get at the charge question

20  related to clear communication.

21	And it seemed to me the heart of the

22  issue in this document is the understanding and

23  relating in terms of the public health context.  And

24  there are threads throughout the different chapters,

25  this one included, that get at how we interpret what we

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Page 162

1  do.

2	But clearly because NO2 and NOX is so

3  closely associated with combustion exhaust and other

4  pollutants, for example ultra fine particles that Mark

5  Frampton measured and mentioned earlier.

6	I think we need to sort of think about

7  how this is communicated and the context really in

8  which it's reported throughout the document.  So it

9  goes back to what Ted Russell had said earlier about

10  sources, because I think if there is an overriding

11  writer that sort of integrated many of the chapters

12  because there were many different writers and

13  contributors to this document, understandably, but

14  there's sort of a theme that underlies all of these

15  facets that goes from the sources and the fact that we

16  need to identify it, its multi pollutant nature I guess

17  and then look at the pollutants and health effects and

18  understand that in fact we have these potentially

19  confounding issues that might be able to be uncoupled

20  by multi pollutant models by some of these studies and

21  to what extent we believe that the studies have

22  successfully demonstrated that.

23	And then finally to conclusions later on

24  that say, that talk about this rather than just a

25  sentence here or there that sort of says, allows it as

Page 164

1  higher than the epidemiological studies that are

2  beginning to show effects, especially in children with

3  asthma.

4	And so I think that kind of integration

5  and interpretation of how do we use the animal tox

6  studies, if at all in the creation of the next

7  rendition of this criteria document.  Is there a place

8  for that in the document?

9	I think it's also really important,

10  since this criteria that has been established for NOX

11  is on the order of 36 years that I thought I heard

12  earlier today, you know, where do we go with that?

13  Because it seems as though with the current standard as

14  it is, there is very rare exceedances of the standard

15  as it exists today.  Yet how do we take into account

16  that there are health effects in children exposed to

17  incremental levels that are on the range of 10 to 20

18  ppb levels?

19	So those are things that I think are

20  really critical for the integration for this document.

21	And really, before Ron mentioned

22  anything and as well as John Balmes, I thought the

23  review of the literature seemed to be really good and

24  that it was, you know, with new literature and things

25  that are there, but again it sounds like it would be



Page 163

1  a possibility.  I think that would help the overall

2  document and make it clearer to the user of this

3  document as to what it means and how the document

4  itself is integrated.

5	DR. HENDERSON: Thank you, Ed.  And now

6  Kent, it's your turn.

7	DR. PINKERTON: Thank you.  What I'm

8  about to say will echo much of what has already been

9  stated.

10	But as an animal toxicologist I think

11  that it's very important to me to better understand how

12  we integrate animal toxicology to human clinical

13  experimental studies as well as epidemiological

14  studies.

15	And I think that with the document,

16  although it's really been a great effort to pull

17  together a lot of the literature and perhaps there are

18  other sources of literature that still need to be

19  considered, but a concern is the fact that in order to

20  produce toxic effects in animals we're usually dealing

21  with an order, the two orders of magnitude, higher

22  concentrations of nitrogen dioxide than we need to use

23  in the human clinical studies.

24	And then even with the human clinical

25  studies they tend to be usually an order of magnitude

Page 165

1  good to take advantage of the things that we're

2  learning today about other literature, other studies

3  that may be pertinent to helping us with this criteria

4  document.

5	And finally I would like to think that,

6  you know, there really is a lot of pressing issues here

7  from the perspective of whether this document needs to

8  be changed or not in terms of a new standard.

9	And so again these discussions and the

10  way you put together the document will be critical.

11	And I would just like to also emphasize

12  the fact that it is very important because it seems to

13  be a recurring theme throughout the document, that the

14  health effect that are attributed to NO2 may always be

15  confounded by the association of other co-pollutants or

16  it may be that NO2 is just serving as a surrogate for

17  other pollutants.

18	So again that's another point again that

19  I would emphasize that needs to be really clearly

20  defined in this document.

21	DR. BALMES: This is John Balmes again.

22  I wanted to thank Kent for bringing up a point that I

23  had meant to bring up but I forgot to and that's a key

24  point.

25	With regard to ozone we have good

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1  experimental data, both from clinical human studies and

2  animal toxicologic studies to support inflammatory

3  effects at levels at least close to ambient.  But we

4  don't have that with NO2.

5	So that it makes the integration of the

6  epidemiologic literature with the toxicologic

7  literature, both human and animal, you know, very

8  important.

9	And I think that insufficient attention

10  has been paid to that as Kent pointed out.  I think

11  there has to be an acknowledgment that both the animal

12  and human studies that show acute effects are at higher

13  levels than ambient.

14	So that sort of brings up again the

15  issue of how NO2 is acting to, in its association in

16  the epidemiologic studies with health effects.  Is it

17  direct NO2 effect or not?  Or is NO2 a surrogate?  You

18  know, the various models that Jon Samet included in his

19  written comments.

20	But I'm repeating Kent because I want to

21  underscore, think that's very important and I think one

22  of the public comments this morning already brought up

23  the relative lack of support from the toxicologic

24  studies for the epidemiologic evidence.  And so I think

25  we have to sort of, I think the Agency needs to deal

Page 168

1  these comments that are brought up that indicate that

2  we may not have been thorough in picking up all the

3  negative studies.  And so if there's a positive, it's

4  not a publication bias but a positive bias for finding

5  the positive studies is in there, so it's also very

6  important for us consider in coming to that conclusion.

7	And then I wanted in particular to draw

8  your attention to a section that hasn't been talked

9  about yet, it's on page 3-126 on cancer incidence.

10  I've been puzzling over this since I read this section

11  since I really hadn't watched these two articles real

12  closely when they came out.

13	But one from Sweden and one from Norway

14  in which they looked at incidence of cancer and

15  correlated it with air pollution.  In this case it's

16  translated all the way down to NO2 being the driving

17  agent to it.

18	But they, because they actually, if this

19  is correct and I convert the micrograms per cubic

20  meter, basically divide it by two to get parts per

21  billion, you're talking about exposure levels that they

22  say is, by Nyberg's article in 2000, exposure a the

23  98th percentile to an ambient level of NO2 was

24  associated with a odds ratio of 1.44 for cancer, for

25  lung cancer.  And the other study came up with an



Page 167

1  with that head on.

2	DR. HENDERSON: James Crapo.

3	DR. CRAPO: I'd like to sort of partially

4  weigh in, I think the major issue that we need to

5  provide advice on as a committee, and that is if you

6  read this document the way it's written right now

7  there's a very persuasive argument that there's a

8  profound effect of NOX exposures on many tests of

9  mortality, ER admissions or asthma admissions, cancer,

10  lung growth and development and, you know, a lot of

11  studies that support it with a lot of consistency and

12  coherence.

13	But I think we need to give advice and

14  I'm not sure what the advice ought to be as to whether

15  or not in fact we're looking at a confounding issue and

16  it's surrogate for something else that's doing this or

17  whether the NO2 is doing it directly.

18	And so we need to have some real depth

19  in our knowledge to put those two things together that

20  Kent and John have just talked about.

21	But I think we need to be very concrete

22  in our recommendations to the Agency about conclusions

23  that can be drawn from this and the power that relates

24  to it.

25	It's, I'm a little concerned by some of

Page 169

1  incidence of 1.36.

2	So you're talking about a possibility

3  if you then extrapolate this backwards, if you were

4  able to reduce the, you know, if you attributed this

5  all to NO2 and then reduced it by 20 parts per billion

6  I guess is what they're standardizing this to, it's

7  kind of hard to reduce from 15 to, by 20, but

8  nevertheless it raises the point that if you could make

9  a profound decrease in NO2 you could have a profound

10  impact on the incidence of lung cancer, and on other

11  cancers as well which is also part of the study.

12	My instincts are this is not correct.

13  It's probably a substantial bias in it to create such a

14  profound effect because I've not seen anything that

15  could reduce lung cancer by that kind of a magnitude.

16	And I wonder if this kind of   well, I'd

17  like other people's comments on this data.  But if this

18  were correct it would mandate that we have to do

19  something abut the NO2 levels.

20	But my interpretation of this is that

21  it's probably a surrogate for air pollutants and I'm

22  not sure what the pollutant is in that area.  Although

23  these are two good countries where you should expect

24  good epidemiology and good data.

25	But the only correlation is to where the

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1  people live and to a correlation of air pollutants.

2	Anyway, this kind of correlation is

3  what's, what we're talking about throughout the whole

4  study.  And we need to come to this conclusion

5  concreted, before we can start making conclusions about

6  the overall study and where it ought to go and what

7  ought to happen with it when it goes up to the

8  Administrator for a decision.

9	DR. HENDERSON: Yeah, go ahead Steve.

10	DR. KLEEBERGER: This is Steve

11  Kleeberger.  I'd like to follow up on James' comments,

12  I think those were outstanding.  And actually I was

13  going to save this for when it was time for me to speak

14  but I think I'll start now.

15	What I got from reading Chapters 3 and 4

16  is that while there are a number of interesting

17  observations, there are very few that substantiate

18  initial observations and that it's very difficult to

19  make any concrete conclusions based on the very few

20  studies addressing questions related to susceptibility

21  for instance.

22	And it made me think about what our

23  charge is here.  And that is, are we charged only with

24  evaluating what is there in order to make

25  recommendations?  Or can we as a group also make

Page 172

1	DR. SAMET: Oh Rogene, this is Jon, let

2  me comment.

3	DR. HENDERSON: Yeah.

4	DR. SAMET: The Nyberg study I know well

5  and I mean I think the author's intent on that study

6  was that the NO, the model of the NO variable, the NO2

7  variable was a surrogate for air pollution as I think

8  perhaps James suggested.

9	And there are many epidemiological

10  studies that point to air pollution in general as

11  contributing to the burden of lung cancer, the Six

12  Cities Study and the American Cancer Society's study

13  most notably.

14	So I don't think this is new news, I

15  don't think anyone though has felt that there's a way

16  to do anything other than to point toward the general

17  combustion mix as contributing to the causation of

18  cancer.

19	And again I, you know, I think in

20  looking at the evolution of the epidemiological

21  literature on NO2, if you look back, a long time ago

22  there was emphasis given to just a very few outdoor

23  studies where there was the thought that there was a

24  pure NO2 exposure that was higher for some people.

25  That was the same as the Chattanooga study that Carl



Page 171

1  recommendations for future studies to address these

2  kinds of questions, these gaps in the literature if you

3  will, that will help us or inform us in actually making

4  some concrete conclusions about the literature that's

5  already there?

6	DR. HENDERSON: Well I think we should

7  feel free to make recommendations for future studies to

8  fill data gaps.  However, the regulation has to be set

9  of what's available now.

10	But I'm trying to think of an example

11  where we've recommended future studies, but there's

12  nothing wrong with making recommendations for future

13  studies.

14	Our main charge is to say, is this

15  document, is the science in this document sound enough

16  to be used in the standard setting process based on

17  what's available now?

18	I am very curious about these studies

19  too but I'm kind of like James, intuitively, gosh, I

20  can't believe that NO2 is causing that much cancer

21  around the country.

22	But I don't know, John Samet, did you

23  look at the, are you familiar with those studies?  He's

24  probably muted.  Has anybody read those studies that

25  could critique them and will add

Page 173

1  Shie did back in the '70s.

2	And then there was the emphasis on the

3  indoor studies because that was NO2 independent of the

4  rest of the outdoor combustion mixture.

5	And I think what is new in this review,

6  and again I think this goes back to the problems I

7  highlighted of interpretation, is that people are now

8  turning to times series studies or some other studies

9  where multi variable models have been used to try and

10  tease out NO2 as a mixture component.

11	And to me the heart of the interpretive

12  argument lies in how well you can, how well you can do

13  that.  And I think again, just to reiterate, this is

14  something the document needs to deal with.

15	And this is where the integration with

16  the toxicology becomes so important in my mind.

17	DR. CRAPO: But can I add further on

18  that.  Jon, if you look at the Table 3.   no 5.5-3 at

19  the very end of Section 5, it is the table in which I

20  thought that they really made a strong and I think a

21  laudable effort to try to correlate, put it all

22  together and come up with an integration of the various

23  risks.

24	And what they do on the right side of

25  that table is calculate the standardized excess risk at

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Page 174

1  the 95% confidence interval for various functions,

2  which go through a whole lot of different functions

3  over this whole table.

4	And it's defined, that function is

5  defined as I think an excess risk attributable to NO2

6  at a, in 20 parts per billion increments.

7	Another question on this table, but I'm

8  wondering if in fact we've gone too far with this table

9  and started to draw conclusions where we're actually

10  concluding here that a 20   because when they say

11  standardized risk, and if you look at the lung cancer

12  one, which is on page   and of course they're all like

13  this, but the lung cancer one is on

14	DR. ROSS: James, can I speak to that

15  point about the 20 parts per billion?

16	DR. CRAPO: Sure, go ahead.

17	DR. ROSS: It's not actually intended to

18  say anything about 20 parts per billion.  What you get

19  from the epidemiology study is a relative risk, it's

20  essentially a slope and what we're doing is

21  standardizing it, because the studies presented for

22  different increments in NO2 and what we've done is

23  standardize to an increment that's sort of high to low

24  range in the ambient air.

25	But it's, that's the way that you could,

Page 176

1  throughout this table or through many of the other

2  problems and it's part of the problem we're talking

3  about.

4	So I particularly wanted Jon's comment

5  about this table.  If this is an appropriate to analyze

6  it?  Does it compare to all these variable studies?

7  Because I like the idea, I'm curious if I can really

8  use it in this context to create an integration across

9  all these very different study designs.

10	DR. SAMET: Well to me the major issue is

11  whether you trust the model and I mean that's really

12  the key to this.

13	And I think that comes in light of what

14  the models can tell you in the sense of how these

15  variables may be correlated and what the potential

16  paths for NO2 to have effects are.

17	So you could estimate these effects but

18  these may be coming under the wrong model and I think

19  that's where the decision has to made about what are

20  the right model or models.  And these are sort of, I

21  mean in a sense these tables apply to causal

22  interpretation.

23	DR. HATTIS: This is Dale Hattis.  Notice

24  that there are distortions that are likely in both

25  directions.



Page 175

1  it's just intended so that if we put them in figures

2  you could see them on a sort of a same scale.

3	DR. CRAPO: Right, I understand that.

4  And I'm feeling ambivalent about what I'm saying

5  because for the last several years I've been sitting in

6  this chair saying, be concrete, give me, take hard

7  stands, interpret this data, put your neck out and

8  we'll, so we can talk about it.  And you've done it,

9  and I'm really proud of you for that, and I like it.

10	But now I'm wondering if we've stretched

11  the statement on NO2 to the point where it's saying

12  something that we probably can't say.  Because when I

13  start translating this down to an absolute risk, in

14  fact I, the lung cancer example is one where I agree

15  with Jon, I think it's related, it's a correlation with

16  air pollution and we don't know what it is, it's a

17  surrogate.

18	And I have real doubts that you can

19  express this as an odds ratio or as a standardized risk

20  relative to parts per billion of NO2.

21	And I'm, so I'm concerned as to whether

22  we can do this for many of these studies.  And the lung

23  cancer is an example that I think is pretty obvious

24  that we probably can't do it.

25	But maybe that same logic applies

Page 177

1	Just because it goes away, the core of

2  the association might go away if you put it in a multi

3  pollutant model, if the NO2 is poorly measured and some

4  other thing is better measured and correlated with

5  whatever the causal agent is, then, you know, the

6  causal agent still could be NO2 and have this affect of

7  going away with the, in the multi pollutant model

8  analysis.

9	So that's partly why you need to do what

10  was suggested earlier, is to have a background

11  intellectual discussion of, okay, what are the

12  distortions?  How quantitatively important could they

13  be with the amount of distortion of the measurements

14  that we know happens for NO2 from the verticality

15  problem and the other problems of assuming that central

16  state monitors are well predictive of the outdoor

17  contribution to personal exposures?

18	So I think that's   sort of we know

19  there are distortions in both directions that need to

20  be to some extent fairly assessed.

21	DR. HENDERSON: Okay, I think we'll let

22  George Thurston talk about Charge Question 5, it's also

23  a health question.  And maybe we're beginning to get

24  into that area a little anyway.

25	DR. THURSTON: Okay, yeah.  The question

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1  is, to what extent does the integration of the health

2  evidence focus on the most policy relevant studies or

3  health findings?

4	And I find when I look at what I wrote

5  down here, a lot of it overlaps with what we've just

6  discussed because I do think these are related

7  questions, very closely.

8	I mean one of the first points is one

9  that Jon Samet brought up.  Well first of all, I guess

10  the answer to the question that I come up with is that,

11  yes, but not well enough.  Okay, so, you know, the

12  obvious answer, right?

13	But the need for a framework of the

14  document, and I'd just reiterate that.  It's been said

15  before, I wrote something along those lines in my

16  written comments, but page 5-7 talks about the strength

17  of evidence categories, good, the, you know, those are

18  good.  But we need a foundation for that.

19	And that was also brought up in some of

20  the public comments before we started, you know, that

21  we need to better say what the meaning of these are and

22  their foundation.

23	And we need to set that out at the front

24  of the document.  And I think the best way to do this

25  of course is to start with A.B. Hill's criteria and

Page 180

1  move that in, you know, combine them.  But again, the

2  susceptibility question is one that should be thought

3  of all the way through the document and from the

4  beginning to end.

5	Who is most exposed and what are the

6  effects that might make people susceptible?  And then

7  what do the studies indicate who are the susceptible

8  people?  And do we see a coherent picture?

9	We need to look at the results, you

10  know, in terms of the policy relevant studies and using

11  it for policy.  We need to look at the results as a

12  function of concentration to be more useful for

13  standard setting.

14	I mean we have this long table and

15  there's a lot of missing information unfortunately, and

16  maybe there are ways to fill this in in terms of   and

17  then rank them and put them in groups, you know, across

18  outcomes in certain categories of concentrations.

19	You know, instead of doing one category,

20  then the next category by health outcome, maybe we

21  could group them by concentration and of exposures and

22  then look across there.

23	Now, you know, the 98th percentile, the

24  99th percentile is, you know, sometimes we've got the

25  maximum, we've got the mean, we have the standard



Page 179

1  figure them into these categories, the strength of

2  evidence categories and say what we expect for the

3  various levels of certainty.

4	So that really is something that needs

5  to be done up front and then carried throughout the

6  document, that each time someone writes a section of

7  evaluates a section they'll say, okay, how does this

8  fit into those criteria and, you know, the coherence

9  questions and so on?

10	And we need to look across disciplined

11  evidence, something we've been discussing about

12  coherence.  You know, are the effects, when we look at

13  the toxicology studies and the exposure studies, are

14  the effects on clearance and immune function that are

15  documented, are they consistent with the epidemiology?

16	And I think that there is some evidence

17  that it is.  In other words, who are we seeing

18  affected?  The children with asthma.  So there is a

19  coherence and I think that needs to be brought out and

20  there needs to be a thematic approach to that where

21  each section is not standing alone, but looking across

22  the document.

23	And, you know, another point was the

24  susceptibility section that's not well linked to the

25  previous chapter.  So someone mentioned maybe we should

Page 181

1  deviation, I think they could probably estimate what

2  these things are from the data or we could go to the

3  original authors and ask them if they have that

4  information.  Or a lot of these studies use ambient

5  data, most of them.

6	And so that data, you know, are

7  available so that you could look at the start at the

8  beginning of the study and look at the NOX data and

9  come up with those numbers.

10	So that could be done to fill that in

11  more so we could better categorize these studies by

12  concentration range, which I think would be more useful

13  for standard setting.

14	So, you know, as we've said before, we

15  need to focus the results on results for the especially

16  susceptible populations and try and work on that,

17  because ultimately those are the groups that you're

18  trying to protect.

19	I mentioned before about the PM and NOX

20  interactions so I won't go into that again and others

21  have brought this up, that NOX may be acting by making,

22  you know, by knocking down the defense of the body,

23  let's say clearance of particles and then enhancing

24  particle effects, so there may be a pathway that way.

25	So that needs to be discussed, how these

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Page 182

1  pollutants might be interacting in the body and causing

2  greater effects than they would if there was only one

3  of them.

4	And just sort of lastly to comment,

5  since I've got the microphone, the discussion about the

6  lack of animal and human exposure, exposures at ambient

7  levels like we have for ozone, well I think it's

8  wonderful we have those studies for ozone, that they've

9  been able to be done and we have them.

10	But I don't think that's absolutely

11  required.  And for example we don't have them for PM,

12  ambient exposures where we can replicate health

13  outcomes in human exposure studies.  You know, there's

14  near ambient and there's, you know, the concentrator

15  studies and that kind of thing, but we don't have the

16  direct at ambient concentrations for PM.

17	So I don't think we should set a higher

18  standard for this than we do for PM and other

19  pollutants.

20	I do think that they're very important,

21  those studies, to learn about the biological

22  plausibility.  And again, if you're doing A.B. Hill's

23  criteria you're going to look and say, okay, we've got

24  this association in epidemiology.  Is it biologically

25  plausible?  Then we turn to the studies we have

Page 184

1  primarily epidemiologic data, that that's wrong to do.

2  That's for us to discuss.

3	But I do think the acknowledgment that

4  the study, the toxicologic studies are at levels higher

5  than ambient needs to be in the document sort of more

6  clearly.

7	That's two different things.

8	DR. HENDERSON: Ed Avol has something to

9  say.

10	DR. AVOL: Just to follow up on a comment

11  that George made with regard to susceptible sub-

12  populations.

13	I mean I think it's important for the

14  document to look at and identify susceptible

15  populations and that's fine.  But I think we don't want

16  to lose sight of the fact that there's, there are

17  ranges of susceptibility.  I mean there are certainly

18  asthmatic children that we're interested in, but for

19  example in lung growth function from the Children's

20  Health Study we don't have any evidence that asthmatic

21  children are losing function any faster than healthy

22  children.

23	In fact healthy children are losing

24  function, have depressed function as well.  And so I

25  think in that sense children are a susceptible



Page 183

1  available.

2	And I think some of the most important

3  studies that were noted in here in that regard, not in

4  terms of setting the standard, but in terms of deciding

5  whether this is a causal relationship, are the

6  intervention study that was mentioned, the indoor

7  studies are very, I thought informative of that

8  question.

9	So we don't have the controlled studies

10  and animal studies that everybody loves.  We do have

11  those indoor studies and an intervention study that

12  wass mentioned.  So I think that's very powerful

13  evidence that needs to be considered.

14	DR. BALMES: So George?

15	DR. THURSTON: Yes.

16	DR. BALMES: It's John Balmes again.  I

17  agree with you that we don't have to have a toxicologic

18  study supporting the EPI findings, but you're correct

19  about PM.

20	But I just think we should acknowledge

21  that up front.  You know, I think it's sort of a little

22  bit obfuscated in the document the way it currently is.

23	So I want' trying to say that before the

24  Agency or before CASAC recommends to the Agency that we

25  have a different standard for NO2 that's based on

Page 185

1  population.

2	Similarly there is some talk in the

3  document about genetic susceptibility and if you look

4  at the penetration of GSTM presence or absence in the

5  population, I mean there are significant numbers of

6  people, which may be a different way of saying the same

7  things with regard to normal or healthy or asthmatic

8  sub-populations, there are large portions that are at

9  increased risk.

10	And so I think that's the issue that

11  needs some gradation or some description and discussion

12  needs to come across in there as well.

13	DR. HENDERSON: I would like to say I

14  agree with you, George, that the EPI studies that were

15  most impressive for me were those intervention studies

16  in Australia as I recall, where they did them indoors

17  and they had, you know, the stoves were taken in and

18  out and he saw changes in the health effects in the

19  children as I recall.

20	Those were very impressive because you

21  have less confounding by the other air pollutants.

22	But I have a question for you.  What is

23  the level in animal studies of, the level of NO2 that's

24  required to cause problems with particle clearance?  I

25  can't remember, I'm asking because I can't remember

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Page 186

1  what those were.

2	DR. THURSTON: Well that's not my area of

3  research.  Terry Gordon, can we put you on the spot

4  here?

5	DR. GORDON: Yeah, Steve, I'll put you on

6  the spot.

7	DR. THURSTON: Yeah, this is his

8  question.

9	DR. KLEEBERGER: You know, I think this

10  gets back to part of the problems with what's out

11  there, is these kinds of studies have not been

12  addressed, or these kinds of questions have not been

13  addressed systematically well enough to answer, or come

14  to a conclusion about that.

15	DR. HENDERSON: Okay.

16	DR. KLEEBERGER: I mean if you would ask

17  me that question in mice, I would say well you need to

18  set up a strain screen, so you start looking across of

19  battery of inbred strains in mice until you actually

20  find that there are, and you almost certainly will find

21  that there are differences across a particular species.

22	DR. LARSON: Rogene, this is Tim Larson

23  again.  Can you hear me?

24	DR. KLEEBERGER: Yep, yep.

25	DR. HENDERSON: Yep.

Page 188

1	DR. KLEEBERGER: Yes.

2	DR. CRAPO: So you're dealing within

3  almost two, three orders of magnitude at higher levels

4  to get acute animal effects that we can measure in

5  small numbers of animals.

6	DR. KLEEBERGER: If there's a generic

7  animal.

8	DR. CRAPO: Yeah, but I mean if it's a

9  generic animal but various ones are reported at 1, 2,

10  3, 4, 5, 10

11	DR. KLEEBERGER: Right.

12	DR. CRAPO:    at 15 parts per million

13  you are causing acute severe injury in an hour of

14  exposure

15	DR. HENDERSON: Oh.

16	DR. CRAPO:    with ARDS following that.

17  But then you, but if you get down to one part per

18  million you're starting to lose all your effects that

19  you can measure acutely.

20	That's what I've read.

21	DR. HENDERSON: That's what my memory

22  tells me and so I think that lessens our concern about

23  ambient levels of NO2 causing

24	DR. GORDON: But this is ignoring all

25  short term, one hour max values which



Page 187

1	DR. LARSON: I had a question about your

2  statement that there was less confounding in the indoor

3  studies.

4	I thought a lot about that and when you

5  really get down to the question of what's confounding

6  about the outdoor studies, you know, the other

7  pollutants may have a, I mean may have confounding

8  effects, but they're not that strongly correlated with

9  NO2 to begin with.

10	Other pollutants which we don't measure

11  outdoors, perhaps are.  And the question really is, are

12  those other pollutants, the black carbon, the ultra

13  fines, are they similarly confounded indoors?

14	I mean I think we might be able to

15  address the question.  We don't discuss it in the

16  document, but I agree that's an important set of

17  studies that seem to be key to isolating the NO2

18  effects in epidemiology.  But we're not addressing that

19  particular question of confounding.

20	DR. CRAPO: I think in terms of the

21  animal studies, my memory is that the animal effects

22  require, for all the various effects require parts per

23  million.

24	DR. HENDERSON: That's right.

25	DR. CRAPO: And not parts per billion.

Page 189

1	DR. HENDERSON: Oh sure.

2	DR. GORDON:   can get up to 100

3	DR. HENDERSON: That's right, yeah.

4	DR. GORDON:   or more ppb in talking

5  about those where the verticality issue or whatever the

6  word is, you know, it could be even higher than 100.

7	DR. HENDERSON: That's right, it could be

8  higher.  If somebody   yeah, Mary, what

9	DR. ROSS: Could I draw your attention to

10  the table on page 5-18, it's a table of toxicology

11  where we tried to draw what appeared to be the lowest

12  concentrations at which some effects were seen.  And

13  they're in the order of .2 to .8 parts per million.

14	So I just welcome any feedback you have

15  on that.  It's table 5.5-2.  And similarly the page

16  before, 5-17 is a human health studies.

17	DR. HATTIS:  I didn't hear that last

18	DR. GORDON: Another variable that's

19  important here is the duration of the exposure.  Some

20  things can have effects over a longer averaging time

21  than others, depending upon the details of the

22  mechanisms.

23	DR. CRAPO: One more number when we are

24  thinking about those, I looked it up online to find a

25  couple of papers to get, the exhaled breath NO for all

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Page 190

1  us normals today, is usually about, a means of about 6

2  to 7 parts per billion.

3	DR. HATTIS: Of NO2?

4	DR. CRAPO: Of NO, NO, in an asthmatic

5  the exhaled breath NO was about 30.

6	So you're saying that the   I'm not sure

7  that NO is a good surrogate for NO2 because NO is a, in

8  my mind a very good molecule except when it interacts

9  with an oxidant like ozone or a super oxide and becomes

10  converted to another species.

11	But clearly you have biological

12  productions of NO in your body that are very close to

13  ambient, airborne levels.

14	DR. HENDERSON: Yeah.  Thank you for

15  looking that up.  And someone was saying today, was it

16  you, George, that the peroxide   who was saying that

17  this could go to NO2?

18	DR. LARSON: You have to scrub the

19  outdoor air before you exhale just to get a legitimate

20  reading.

21	DR. POSTLETHWAIT: Of course the problem

22  with NO2 is it's so reactive once formed endogenously.

23  You're likelihood of finding it in expired air is

24  almost zero to none.

25	But in expired breath condensate they do

Page 192

1  nitrated proteins in the lungs of people with

2  inflammation.

3	DR. POSTLETHWAIT: Absolutely.

4	DR. HENDERSON: Well you can argue that

5  two ways and I've heard it argued both ways.

6	If there's an endogenous source, some

7  people will say, well, a little bit more won't hurt.

8  And others will say, oh, but it does, it's building on

9  an already, you know, bad situation.

10	And so you have to think of it both ways

11  I think.

12	James, you   oh no, Steve Kleeberger,

13  you haven't had a chance.  Steve, do you have some

14  comments you'd like to make?

15	DR. KLEEBERGER: I was just actually

16  doing a pub med search on something here, but hand on a

17  second.

18	So I will echo comments from George in

19  that I think the integration in terms of reflecting

20  health effects is there, but it's probably not very

21  good at this point.  And certainly greater, at least in

22  reading the document, I think greater attention made to

23  efforts regarding the integration are going to be

24  necessary and helpful.

25	I focused mostly on the susceptibility



Page 191

1  find nitrite which is the first, one electron reduction

2  product of NO2.  And in all the studies in AODS and

3  inflammation, et cetera, when you find proteins being

4  nitrated, NO2 is the nitrating species.

5	And so as James brought up, any of these

6  issues with NO reacting with super oxide, the ultimate

7  oxidant that's formed is NO2.  In some cases there's

8  also a thing called a carbonate radical that's also

9  formed.

10	And so you wonder in asthmatics with

11  underlying inflammation if they've got 30 ppb of NO in

12  expired breath, you know, and they've got resident

13  pnn's with peroxidase activity, I have no clue how much

14  NO2 they're making.

15	But if they inhale a little NO2 on top

16  of that, is it really going to tip the balance into

17  sort of a new realm of health effect, or would it be

18  sort of like a smoker who is exposing himself to a ton

19  of NO2 and give him a few ppb and expect to see

20  something?

21	DR. CRAPO: I don't know that, but I've

22  heard that these patients all have enhanced labeling of

23  their lungs of nitrotyrosine

24	DR. POSTLETHWAIT: Right.

25	DR. CRAPO:    so there's a lot of

Page 193

1  of the chapter, Chapter 4, largely because that's what

2  I'm most comfortable with.

3	And my feeling is that the document I

4  think actually discussed the existing literature, but

5  as I had mentioned earlier I think what is a critical

6  issue is the darth (sic) of, or the dearth of

7  information to help us make any meaningful sense of the

8  data that are actually out there in terms of

9  reproducibility and systematically looking at specific

10  susceptibility facts that could be considered in terms

11  of our recommendations.

12	And so it made it a little bit difficult

13  for me to make any real conclusions about the effects

14  of genetic background for instance as Ed brought up,

15  and gender which I don't think was addressed, and

16  preexisting disease.

17	One point that I also wanted to raise

18  about the document per se is that, I think it was on

19  page 4-12 where there was an estimation of the number

20  of asthmatics and the number of   I forget what the

21  other population was   oh, heart disease, I'm not sure

22  how meaningful that particular section of Chapter 4 is.

23  And I'm not entirely sure what it relates to.

24	In fact what they're saying is that, you

25  know, we have a large and growing population of

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Page 194

1  asthmatics, we have a large and growing population of

2  individuals with heart disease, but that doesn't

3  necessarily mean that these people are all going to be

4  susceptible to the effects of air pollution, let alone

5  NO or NO2.

6	In fact there is considerable

7  variability among asthmatics in terms of their response

8  to air pollutants like ozone.  And to make a blanket

9  statement that asthmatics as a whole are going to be

10  susceptible or more susceptible than a healthy

11  individual is probably not true.

12	And so I think we have to be careful in

13  terms of describing or categorizing individuals with

14  preexisting disease as extraordinarily susceptible.

15	DR. COTE: Just a point of clarification

16  on the table.  The implication wasn't that all those

17  people would be affected.  It was just trying to get a

18  handle on the potential at risk population.

19	If you're following up on what George

20  was saying, I think that these kind of disease states

21  would put people at some potential increased risk.

22	DR. KLEEBERGER: Well they could, they

23  could be.  But I'm just saying it has to be

24	DR. COTE: I think the language that

25  needs to be clear.

Page 196

1  to start, let's assume that I accept the fundamental

2  conclusions here, because I do see a lot of coherence

3  of findings when you analyze them in the way that

4  they're done, a lot of coherence from human

5  epidemiology studies, field studies or multiple groups

6  all around the world looking at multiple endpoint,

7  hospital admissions, ER admissions, asthma, COPD,

8  exacerbations of a cough, of other asthma symptoms, of

9  decreased lung growth and development and cancer as

10  we've mentioned, all with powerful correlations in the

11  form in which they're analyzed today.

12	And I've already said that I have

13  concerns that we have a confounding issue going on and

14  we might be, I don't know whether to lower the PM level

15  or lower the NOX level.

16	But I think we're talking about a very

17  real effect.  Better epidemiology and better analyses

18  of all these various groups are finding that there is a

19  profound effect.  And I'm on the fence as to whether I

20  attribute this to NOX or not, I want to put that on the

21  table.  Maybe by the end of this two days I'll have a

22  strong opinion on that one.

23	The, but if we assume that this is

24  correct, then I have several concerns about the

25  document that I think need to be done, because my



Page 195

1	DR. KLEEBERGER:   more clear, yeah,

2  yeah.  And I have a number of other minor comments but

3  I can, I'll have that in my written, it's in my written

4  document.

5	DR. HENDERSON: Okay.  Thank you.  Let's

6  look at Charge Question 6, which is really what we've

7  been discussing.

8	What are the views of the panel on the

9  conclusions drawn in the draft ISA regarding the

10  strength, consistency, coherence and plausibility of

11  NO2 related health effects?

12	And I had asked James to talk about

13  that.

14	DR. CRAPO: Yeah, and I've already said a

15  lot of what I think on this and I'm trying to   I'm

16  really on the fence, do I really go on the bandwagon to

17  lower the NOX level dramatically?  Or do we say this

18  needs to be revised in terms of what we've said?

19	But the way this document's written it

20  scientifically mandates that  we do everything we can

21  to lower the NO levels and the NOX levels in the United

22  States.

23	And so I'm on the fence trying to have

24  my own recommendation on that on which way to go.

25	But let's assume that I accept, I want

Page 197

1  question would be, how should I lower the standard?

2  And how should I affect the standard?  What should the

3  form of the standard be?

4	And I find that the document doesn't

5  inform me adequately to start to make the next

6  decision.

7	If I assume that the conclusion is

8  correct, then I want to know, I want to have a dose

9  response that tells me about what's going on at the

10  ambient level when I know that I can't drop the levels

11  20 ppb since I'm starting out at 15, and it looks to me

12  like we really, we don't have a very good discussion of

13  the threshold.  And again I think your answer is going

14  to be, we don't have good data on threshold and we

15  can't, we can detect effects that appear to be going

16  towards zero.

17	But we really need a discussion of that

18  because if you, as soon as you accept any of the

19  fundamental conclusions of this document, the one that

20  you mentioned, the last sentences on page, on Section

21  5, of our conclusion that if it stands will man   to

22  me, would mandate action on it.

23	So I think I'd to see the document

24  worked again about to tell me how to do that action and

25  I'd like to analyze the threshold, I'd like to analyze

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Page 198

1  the lower limits to it, I'd like to look at the peak

2  effects and I'd like to have some data that helps me to

3  analyze that.

4	I mean can I get the benefit by just

5  decreasing the peaks and excursions?  And should it be

6  a   and then I need to begin to ask whether it should

7  be a daily standard or an annual standard and should it

8  have a certain number of excursions in it and does it

9  make a difference on what those are?

10	So those are all the kinds of questions

11  that were discussed in detail on ozone and PM that are

12  not here.

13	And I think that's the   in fact that

14  needs to be looked, even if we decide that this is a

15  surrogate for something else.  We need to begin to

16  understand that set of data to go with it.

17	The   and I think I've said everything

18  else already.

19	DR. HENDERSON: Okay.  I'm wondering,

20  when can expect, I mean several people have mentioned

21  that we're missing any discussion of the form and

22  averaging time, et cetera.

23	Is that something that will come

24  tomorrow in the exposure risk assessment document?  Or

25  are we expecting too much of the ISA?

Page 200

1  let me accept this data, what should I do with it now?

2	And I discovered that I really couldn't,

3  I couldn't find the information I needed to sit here

4  and say, I'd recommend you drop it to .1, or no, 10

5  ppb, and these are the reasons why.

6	And I would need a scientific reason for

7  doing that and I couldn't find it.  I also asked myself

8  if there's any evidence of a lower threshold and I   so

9  those are the kinds of things that I don't think you

10  ought to make the conclusion, but I would like to see

11  the data organized so it could tell me there is or

12  there is not data to help me make that decision.

13	DR. COTE: Maybe this section needs to be

14  expanded, but I think there's only a few studies that

15  specifically tried to look for a threshold.  You know,

16  that's generally not a very successful kind of approach

17  with EPI.

18	So I think you would have to rely on

19  something like modeling.  You know, the LOTUS

20  extrapolation modeling, my understanding is if you're

21  adding to some sort of background process it's

22  generally considered to be linear.

23	DR. CRAPO: Well I wouldn't be surprised

24  if your answer was, we looked at all these factors and

25  we can't do it.  I would accept that, but I want to



Page 199

1	DR. ROSS: The science assistant has

2  never been in the past intended to answer those

3  questions, to say this is what the form should be.

4	We are attempting to organize the

5  information about short term exposures and long term

6  exposures, that then could be interpreted by others

7  and, you know, and we look at ways we could do that

8  better.  To better characterize the 24 hour, one hour

9  and the tox studies with all kinds of exposure levels.

10	But we'll try to organize that as well

11  as we can.  And we'll discuss the levels at which

12  effects are seen and to the extent possible in our EPI

13  studies it's often a range of air   at the distribution

14  of air quality and not a level.

15	But we have not, we were not striving

16  for the integrated assessment, science assessment to

17  have a specific recommendation.  That is usually

18  targeted for the ANPR, the Advance Notice of Proposed

19  Rule Making, where the Agency would be looking at the

20  science assessment and the risk and exposure assessment

21  and then making those recommendations.

22	But we would like to organize the

23  information in a way that can inform those decisions.

24	DR. CRAPO: Yeah, that's what I was

25  looking for because I was sitting here saying, well,

Page 201

1  hear you tried.

2	DR. COTE: Okay.  Yeah, in fact I think

3  we went through that thought process in house but we

4  probably haven't articulated it in the document as

5  clearly as we need to.

6	If it makes you feel any better, we had

7  those same discussions about, is it yes, is it no, is

8  it yes, is it no?  And decided because it was easier

9  for you to respond to that we would present the

10  information kind of going out on a limb, but I guess

11	DR. CRAPO: And I want to, I really like

12  the way you've presented it because you reached out and

13  took a position and that's, I compliment you, this is a

14  very much more productive discussion than the kinds we

15  were having before where we were struggling with what

16  to do with the data.

17	DR. HENDERSON: So that's good.  Now Ed,

18  you were on the same charge question.  Did you have

19  something to add?

20	DR. AVOL: Yeah, I do but Jon Samet is --

21	DR. HENDERSON: Well I was letting him, I

22  was going to bring him in at the end --

23	DR. AVOL: Okay.

24	DR. HENDERSON:   so he could give the

25  final word.

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Page 202

1	DR. AVOL: Okay, that's fine.

2	DR. HENDERSON: So Jon, prepare yourself,

3  after Ed it's

4	DR. SAMET: Yes, okay.

5	DR. HENDERSON:   your turn.

6	DR. SAMET: Okay.

7	DR. AVOL: Okay, that's fine.  Well I

8  also, I mean I think a lot of this we've already talked

9  about in the context of the earlier discussion and

10  questions.

11	Looking at this I did sort of get the

12  sense as Jim Crapo did, that sure, this preponderance

13  of evidence is there that sort of makes you lean in one

14  direction.

15	But I think it is a fair comment that

16  was brought up earlier this morning in public comment,

17  that we need to, in the document we need to be sort of

18  more an objective discussion and layout of what the

19  decision tree is for getting to why something is

20  convincing or suggestive or not.  So that by the time

21  you get to the conclusion section there's a clear and

22  transparent process and it doesn't just sort of come at

23  you from nowhere.

24	I mean I think if we were to do that,

25  some of these, there may well be some readjustment of

Page 204

1  not brought out in broad discussion here but it really

2  is a big issue in terms of being able to tease out and

3  uncouple how important is, or will the public's health

4  be protected by a NOX reduction as opposed to

5  identifying it and relating it to something else.

6	DR. HENDERSON: Thank you, Ed.  Jon

7  Samet.

8	DR. SAMET: Yeah, I'll make a couple of

9  comments.  So I guess I'll interpret this charge

10  question in two ways.

11	So one is, does the draft ISA

12  established strength, consistency, coherence and

13  plausibility as a document?

14	And there I think my answer is, no.  And

15  I will say that just looking at Chapter 5 which should

16  be really, I think where that final bringing it

17  together should be accomplished and I think it's just

18  really weak in doing so.

19	And, you know, just for example at the

20  bottom of page 5-15 there is a sentence that basically

21  says, integrating across all the data, there is

22  plausibility, consistency and so on.  But it's not, the

23  document is not really   does the job let's the way

24  that a Surgeon General's report or other kinds of

25  public health related reviews would do.



Page 203

1  the words that have been used in some of the earlier

2  chapters.

3	I think I gave a number of specific

4  comments about form and substance in the written

5  comments so I won't go through those now.  You can read

6  those.

7	I think again though in terms of the

8  strength, consistency, coherence and plausibility, I

9  think the information is there and   the information is

10  there but it hasn't, it hasn't been so compelling that

11  I'm convinced that all those four pieces are there yet.

12	DR. COTE: I think some definitions would

13  be very useful.  We actually went through   I have on

14  my desk a sheet of paper that has the Rosetta Stones

15  and all of that and we tried to, we tried to read the

16  document to make sure it was consistent, but we can be

17  more explicit about

18	DR. AVOL: Okay.  That would help.  And

19  again I think, you know, a big issue throughout all

20  this is this notion of multi pollutants and confounding

21  the inter-correlation and the relationship of NOX with

22  other species, particularly, or especially

23  particulates.

24	And so I think it's something that, it's

25  sort of the elephant in the room that we sort of, it's

Page 205

1	So I mean I think as a document I don't

2  think that those four features of the evidence are

3  established.  And that is regardless of what the

4  evidence shows.  As a document itself this is a failing

5  of the way the information is brought together and

6  discussed.

7	And again I would urge the office to

8  consider the kinds of discussions that are in other

9  models.

10	So then it comes back to the question

11  of, you know, what do I or we think the evidence shows?

12  And I think when I look at it I go through some of the

13  same sort of agonizing that you've heard already from

14  James and others.

15	And I think that I don't have a personal

16  bottom line yet on whether the sort of strength,

17  consistency, coherence and plausibility are met.  I

18  think if strength means strength of associations and

19  that's the usual way that word is used, I would not

20  really expect there to be particularly strong

21  associations at ambient or near ambient levels.  I

22  would actually look to rather weak associations as far

23  more plausible than strong associations.

24	So I'm not strength, what is even meant

25  by the strength criteria here.  I would not

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Page 206

1  characterize the epidemiological associations as strong

2  either for NOX or for PM for that matter.  They're

3  statistically significant and they're plausible.

4	And there is consistency in let's say

5  among studies.

6	Coherence and plausibility are pretty

7  close cousins so I'm not sure exactly what the

8  distinction is.

9	And so when you look at the body of

10  evidence, and again how the discussion should line up

11  is, in terms of plausibility, what do we have from the

12  toxicologic studies?  And I think here the dose

13  question just has to come in.  And again most of the

14  toxicology is showing effects at exposures, you know,

15  at the some hundreds of ppb and up.

16	There is the question of I think what is

17  the signal from the indoor studies where there's not

18  NO2 as present in a different mixture from what you see

19  outdoors, so I think that's a very useful body of

20  evidence.

21	And I think again there, there is some

22  indication of effects in some of the studies, but not

23  all and I think there is I think more convincing

24  evidence in the experimental study.

25	And then the outdoor work is just very,

Page 208

1  and 6, about any of them that we haven't discussed that

2  people want to bring up?

3	If not I   well I see one, Donna.

4	DR. KENSKI: Well this is not exactly a

5  question but an observation I guess, and it's built on

6  what Steven had to say about, you know, suggestions

7  for, you know, studies that we need to see.

8	But what would be helpful I think in

9  this document is some kind of sort of assessment of

10  what we're missing.  You know, sort of limitations of

11  the current data would be really helpful.

12	DR. HENDERSON: It sounds like a good

13  idea.  Mary, do you usually do that, have limitations?

14  I think you have in the past had limitations of current

15  data.

16	DR. ROSS: We have often followed a

17  criteria document with a research needs document, which

18  was a formal process involving a workshop that followed

19  the production of a criteria document.

20	So research needs to be identified in a

21  process through meetings like this and then it would be

22  a separate document.

23	We haven't always had, we, I don't think

24  we've usually had separate sections on research needs.

25  At times in a particular issue a limitation will be



Page 207

1  very difficult to interpret.  And I think, and this is

2  a major problem beyond these sort of technical concerns

3  I've raised about model interpretation, I think the

4  issue of publication bias has to be considered here

5  because there are, for example in the time series

6  studies there have just been so many done.

7	And I think there's been such an

8  emphasis on PM in '03 that we've only seen perhaps a

9  tendency to report the more positive effects for NO2,

10  and not all.  And that's where the multi city studies,

11  which are emphasized are most important.

12	So I think there's two issues that need

13  to get sorted out.

14	One is the document's handling of these

15  points where I think it's failed right now.

16	And then there's, actually what does the

17  evidence, what does the evidence show?

18	And I think strength probably comes off

19  the table in interpreting the epidemiological studies I

20  believe.

21	So those are my comments.

22	DR. HENDERSON: Thank you, Jon, and thank

23  you for calling in.

24	Are there other comments now about the

25  health charge questions, that's Charge Questions 4, 5

Page 209

1  it wasn't a comprehensive search for a research needs

2  but it might be identified on a case by case basis in a

3  specific area.

4	DR. KENSKI: So is that something we

5  should make reference to in our comments so that you

6  could, you know, incorporate that?

7	DR. HENDERSON:   I think you need to

8  talk into your mike, Donna

9	MR. DOLAN: Oh.

10	DR. HENDERSON:   because I couldn't hear

11  what you were saying.

12	DR. KENSKI: Oh, sorry, I was just

13  saying, is that something we should incorporate in our

14  comments then?

15	DR. HENDERSON: Sure, we could

16	DR. KENSKI: Rather than asking you to do

17  it.

18	DR. HENDERSON:   we can incorporate

19  those ideas in our letter.

20	I suggest if there are no more

21  questions, I want to remind people that if your name is

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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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

US EPA CASAC PUBLIC MEETING 10/24/07 CCR#15676-1	Page 71

Page 278

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

0.5% 46:17

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04 104:1 204:1

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22 22:1 122:1 222:1

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23 23:1 123:1 223:1

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25% 97:23

26 26:1 126:1 226:1

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29 29:1 129:1 229:1

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3.6% 46:18

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30% 71:1

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32 32:1 132:1 232:1

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35 35:1 135:1 235:1

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54 54:1 154:1 254:1

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5% 67:1, 1

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 	6

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194:1, 1 199:13, 14

210:1, 17 215:15

230:1, 1 257:24

258:1 260:15 262:1,

22 266:20

airborne 190:13

airplane 154:1

airwave 101:1

airways 21:17

al 41:11, 16 44:22

45:1 46:1 47:1, 12,

15 48:14 91:1

148:11 154:12

albeit 90:24 algebraic 94:1 algorithm 245:1 allergic 150:1

152:12

alliance 43:10 44:1 allocated 97:25 allowed 258:11 allows 162:25 alluded
126:18

231:18

am 2:15 43:12, 15

121:22 132:11

135:21 150:13

171:18 277:19

ambient 23:1

25:10, 15, 17

34:1 35:22 37:1

38:23 39:1, 1,

12, 18, 23 40:1, 10

41:1 42:14 51:20

52:13, 22 56:1

61:21 70:16 85:20

91:22 94:24

118:12 129:10

166:1, 13 168:23

174:24 181:1 182:1,

12, 14, 16 184:1

188:23 190:13

197:10 205:21, 21

254:1, 1, 1, 20

268:1, 17 281:1, 1

ambivalent 175:1

alone 41:1 53:14

179:21 194:1 211:18

248:1 256:1 259:1

amen 135:15

america 118:21

250:22

american 37:21

172:12

alpha 281:1



already 9:1 74:21,

25 85:15 93:1

102:14 109:21

126:23 163:1 166:22

171:1 192:1

195:14 196:12

198:18 202:1 205:13

215:20 216:1 284:22

alter 121:13

alternative 61:1

98:13 117:24

analogy 232:24

analyses 45:1, 21

46:1, 15 69:12

196:17

analysis 15:10 41:22

96:12 107:1

114:19 115:16, 19

116:14 131:15,

18, 20, 24 132:1,

1, 1 133:25

144:21 177:1 218:1,

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

176:23 235:19, 25

240:15

danger 226:1, 1 dangerous 78:18 darth 193:1

data 22:16 34:1

35:21 36:1 37:1

40:19 43:1 66:13

69:13, 23 76:15

84:12 102:1 105:10,

14, 25 106:20, 22

107:17 108:23 114:1

115:18 122:15

127:24 128:1, 1,

12, 13 129:15, 17

133:16, 23 144:1,

1, 22 153:1

155:1, 1, 1 166:1

169:17, 24 171:1

175:1 181:1, 1,

1, 1 184:1 193:1

197:14 198:1, 16

200:1, 11, 12

201:16 204:21

208:11, 15 228:1

236:1, 1, 1, 13, 17

237:1, 1, 16, 19

239:12, 17, 21,

24 240:1 245:24

246:1 254:10

262:19, 25 264:12

267:13 268:1, 13

269:15 270:1 271:1,

1 276:24, 25 277:1,

1, 1, 13

date 66:23

dates 18:18, 20

dave 16:22 17:1

day 3:22 25:19, 19

30:1 51:1 58:13

61:15 105:12 244:20

277:24

daylight 140:1, 1

days 5:15 152:25

157:1 196:21 214:12

daytime 54:11 dead 263:21 deadline 284:1 deal 33:16 60:15

70:18 81:18 82:19

123:22 135:14 142:1

156:24 166:25

173:14

dealer 233:1

dealership 232:25

dealing 71:12

79:18 134:16 155:16

163:20 188:1

deals 62:24, 25

dealt 76:14

dearth 149:23 193:1

death 231:1

debate 61:12 63:14 december 6:18 decide 139:1

198:14 215:23

decided 143:25 153:1

201:1 234:21

deciding 183:1

decision 11:1

18:21 33:19 34:1

37:10 121:11 130:12

170:1 176:19

197:1 200:12 202:19

242:13

decisions 64:21

199:23 210:16

212:20 242:22

265:11

decrease 62:20 169:1

250:14

decreased 40:1 196:1

decreasing 198:1

250:10, 11

decree 18:20

deed 236:16

deemed 109:1 244:10

deep 131:16 deeper 133:24 defense 181:22 defer 248:19

deficiencies 96:1

define 78:24 79:10

211:16 217:1 230:10

259:18

defined 133:10

165:20 174:1, 1

217:20 218:1

defining 217:1

definitely 67:1

119:20 220:14 250:1

280:15



definition 36:25

59:13, 14 248:25

261:21

definitions 203:12

264:24

definitive 211:16 deflated 99:17 degree 142:15

212:1 229:1

delegated 37:25 deliberations 2:25 delighted 63:10 deliver 4:22
delivered 107:23

283:13

delivering 161:1 delivery 6:19 demonstrated 162:22 demurring 122:22
dennis 15:21, 22,

23, 24 17:19

dense 89:1

density 56:16, 16

department 27:1

35:23 40:1 41:23

47:19

depended 153:1

dependent 65:22

110:10

depending 66:10

109:15 159:1 189:21

depends 251:25 deposited 108:21 depressed 184:24 depth 80:1 167:18
deputy 10:13 derived 60:12

78:16 216:11

describe 59:1

described 35:1 36:11

48:17

describing 194:13

description 34:10

59:22 103:1

185:11 271:1

descriptions 142:18,

20

descriptors 265:21

deserve 92:1 281:1

deserves 87:20 89:13

design 90:12

134:14 278:20 279:1

designated 2:16, 19 designs 176:1 desired 225:19

desk 203:14 despite 36:1 detail 10:1 11:1

12:14 24:1, 1

26:1 52:25 53:1

81:1 198:11

239:22 274:16

detailed 7:15

24:25 44:1, 21

104:18 237:1 275:1

details 11:24

13:16 19:20 78:10

144:17 189:21

detect 197:15 detecting 129:25 determinants 217:24 determination 35:1

244:23

determine 85:21

determined 88:13

261:1

determines 65:12

determining 42:14

81:15

deux 233:1, 1, 1

develop 9:1 49:17

106:11

developed 10:20

60:22

developing 9:1

development 14:16

15:25 48:1 167:10

196:1

develops 18:24 deviation 181:1 device 58:1 61:1

144:20

devices 53:1

devised 121:1

devoted 98:10 143:12

dfo 2:19 6:1, 11,

16, 21 74:10

diagrams 95:11

die 264:1

diesel 67:11 71:1

75:1, 1

difference 11:1

78:17 90:1 105:16

115:11 130:1 145:21

198:1 212:1 245:1

differences 54:11

114:20 115:1, 1

186:21 221:25

different 6:15

19:17, 21 21:24

26:15, 19 45:18

52:16 54:19 55:1

65:14 66:11 78:22

79:1 84:1 90:12

91:1 94:25 95:14

96:16 109:15, 23

110:12, 18

115:11, 14 122:21

132:1 133:1, 11

141:1 142:11 144:25

147:14 149:1

156:1 157:1

161:24 162:12

174:1, 22 176:1

183:25 184:1

185:1 206:18 212:1,

1 213:19 223:18

225:17 230:16

233:14 234:1

240:1 248:1

252:22 256:12

266:15 270:11, 14

272:1

differentiate 111:20 differently 280:18 difficult 11:23

27:19 32:14

125:18 147:1

153:1 170:18 193:12

207:1 226:1 247:14

difficulties 134:18

dig 94:12 95:1 97:21

155:24 220:1

dilemma 252:14

dilution 281:16



dimension 88:1

dinner 284:21 dioxide 6:19 163:22 direct 119:14

159:1 166:17 182:16

direction 101:19

202:14 245:1, 24

247:1 250:10

directions 176:25

177:19

directly 29:17 74:14

101:23 106:1

113:1 121:1

136:10 167:17

241:10, 16 269:22

director 4:15 8:25 disagree 245:14 disagreed 280:17 disappeared 12:1
disappointed 61:23

153:15

discern 154:1 disciplinary 14:16 discipline 19:18 disciplined 179:10
disciplines 15:1

19:17, 21 111:19

disconnect 263:20 discount 41:1 discounts 40:18

47:16

discovered 200:1

discuss 23:25

49:12 55:12 78:1

80:13 88:1 117:15

184:1 187:15 199:11

210:1 215:16

244:1 257:18 259:11

268:1 284:10

discussants 78:1

232:10

discussed 21:11,

12 24:1, 1, 11,

18 25:21, 24 26:1

29:19 59:18 80:18

85:15 86:1, 22,

25 106:19 107:10

117:14 128:1 137:13

178:1 181:25

193:1 198:11

205:1 208:1

215:20 235:1 243:23

257:20 267:10, 21

281:1

discusser 8:1 discusses 143:17 discussing 29:25

61:22 128:1 131:1

179:11 195:1 259:14

discussion 3:14,

17 14:20 17:14

20:15 21:15 23:23

24:25 29:16 32:10

45:20 49:20, 23

52:23, 23 55:23

63:1, 1, 19 64:1,

19, 24 65:10, 20,

25 77:21, 25

79:1, 16, 24 80:1

87:22, 25 89:13

90:1 91:17 102:25

104:19 105:1

111:21, 25 119:1

123:14, 20 125:1

131:10 133:1 134:24

136:1 139:1, 14

141:10 142:16

143:12 149:1, 22

155:17 160:1 177:11

182:1 185:11

197:12, 17 198:21

201:14 202:1, 18

204:1 206:10

211:1 213:11, 12,

15 214:11 217:1

228:24 230:15

240:16 266:1, 15

267:1, 12 268:23

269:1 281:1, 12, 20

282:1

discussions 7:16

57:20 70:10 77:14

78:12 130:17

141:1 165:1 201:1

205:1 216:1

227:14 243:24

278:16, 17

disease 29:13

97:1, 1 155:1

193:16, 21 194:1,

14, 20 216:15

218:22 219:1 222:18

234:1

diseases 96:1 154:16 dislike 131:21 distant 51:1

distill 3:20 distilled 60:21, 21 distinct 252:23 distinction 206:1

267:19

distinctions 112:1 distinctive 253:1 distinguish 111:21 distorted 114:24
distorting 115:13 distortion 177:13

238:1

distortions 176:24

177:12, 19 237:1

distribute 3:12

279:18

distribution

22:13, 18, 20 56:22

83:1, 17 88:1, 1, 1

89:1, 1 100:1

114:20 199:13

218:21 239:1 254:10

272:1

distributions

81:1, 11 82:22 89:1

dive 33:16

diverse 60:1

divide 168:20 237:1 dividing 153:1 division 8:25 9:1

20:10

doable 126:21

docket 43:1

doctor 4:14, 16 5:1,

13, 13, 14, 24,

24 6:1, 23, 24

15:24 16:1 17:17,

20, 22 33:1 37:20

48:10 75:18



112:12 130:23

275:15

document 2:13 6:1

7:1, 1 9:10 11:17

13:1, 13 14:1 15:25

17:1, 19 19:1

21:1 23:14 36:20

39:1 59:1, 1, 1

60:1 62:12 67:19

80:13 83:25 84:17

85:16 87:13

93:10, 12, 23 95:19

96:12 97:1, 16 98:1

100:1, 1 104:23

111:1, 25 112:10,

13, 20 113:1 117:17

124:1 126:22, 23

127:1, 1 139:1

146:1, 1 147:12,

16, 17 148:1 150:1,

14, 15 151:17, 18

153:1, 12 154:23

156:1 157:20 158:25

159:11 160:18, 24

161:11, 22 162:1,

13 163:1, 1, 1,

15 164:1, 1, 20

165:1, 1, 10, 13,

20 167:1 171:15, 15

173:14 178:14, 24

179:1, 22 180:1

183:22 184:1, 14

185:1 187:16 192:22

193:1, 18 195:1

196:25 197:1, 19,

23 198:24 201:1

202:17 203:16

204:13, 23 205:1, 1

208:1, 17, 17,

19, 22 210:12, 18

211:1 213:1

217:21 218:1, 1, 25

220:14 223:14, 23

224:10 232:16

234:1, 10 240:19

241:20, 24 242:1

244:25 245:10, 20

246:1 258:1 260:1

267:17 271:16

273:1, 18, 19

274:18, 25 278:22

document's 195:19

207:14

documentation 261:20 documented 179:15 documents 14:25 92:1

211:1

dolan 209:1 dominate 154:19 dominated 155:12

done 10:20 12:1 13:1

18:19 20:21 24:20

26:1 55:11, 22,

25 69:12 71:11

72:14, 16 73:1

75:25 88:10 95:10

99:22, 24 100:1, 25

110:1 111:12, 24

131:20 148:14 151:1

174:22 175:1

179:1 181:10

182:1 196:1, 25

207:1 217:1 232:1

241:16 243:1 262:14

271:24 274:1 276:10

donna 5:13 80:21

84:21, 22 114:22

208:1 209:1

door 16:1, 1 20:24

doorstop 92:17

dose 19:24 22:11

36:24 45:1, 13

97:22, 23, 25 98:1,

1, 10 100:1 102:1

108:12 197:1 206:12

221:17 222:1 239:14

267:13 268:1, 1,

12, 13, 16 269:1

276:1

doses 102:1, 1

dosimetry 16:1 97:18

98:1 100:24

102:18 218:20

221:16 262:10

281:18

double 45:17

doubts 175:18

doug 232:19 240:24

downtown 73:10

downward 268:1

dozen 227:16

dr 2:1 4:18 7:1

8:15, 17, 18, 19,

22 16:19, 20, 22,

25 17:1, 1, 1, 25

18:1, 1, 25 19:1

29:23 30:1, 1, 1,

1, 13, 17, 19,

20, 22, 24, 25

31:1, 1, 1, 1, 1,

1, 11, 12, 16,

18, 20, 21, 22,

23 32:1, 1, 1, 1,

13, 16, 17, 19

33:1, 1, 1 37:15,

19 43:1, 1, 12, 13,

15, 16, 18, 20, 21,

22, 23, 24 48:1,

11, 13, 14, 18, 20,

22, 23 49:1, 1,

1, 1, 1, 10 50:1

58:16, 19 64:1,

1, 10, 12 66:25

67:1 68:13, 15, 16,

18, 25 70:1

73:20, 23 74:1,

1, 1, 1, 11, 13,

15, 17, 18, 19,

20 75:1, 1, 16, 18,

22 76:1, 1, 1,

10, 12, 22, 25

77:1, 1, 1, 11 78:1

80:21, 23 84:21, 25

85:1, 1, 11

92:15, 20, 21,

24, 25 93:1, 1, 1

98:12, 14, 20,

22, 24, 25 99:1, 1,

1, 1, 11, 13, 14,

16 101:17, 18,

20, 21, 22

102:12, 24 103:1,

1, 11, 12, 14,

16, 17 104:11, 13

106:1, 1 107:1,

1, 19, 20 108:14,

18, 20, 23, 25



109:1, 1, 1, 10,

11, 25 110:1 111:1,

1 113:10, 12, 25

114:1 115:20 116:1,

18, 19 117:11,

16, 19, 21 118:1,

1, 1, 14 119:1, 1

121:1, 19, 21,

22, 23, 25 122:1,

1, 20 123:1, 1,

1, 1, 10, 11, 12

124:15, 17 125:1

126:1, 13 127:23,

25 128:14, 18, 23

129:1, 1, 1, 1, 11,

14 130:19, 21, 22

131:1, 1, 1, 1,

25 132:1, 1, 1,

1, 11, 14, 15,

16, 18, 20, 21, 22,

24, 25 133:1, 1, 1,

17, 18 134:1, 1, 10

135:24 136:1, 1,

1 137:11 138:1,

1, 1, 1, 1, 12, 15,

16, 18, 20, 22, 24,

25 139:1, 10, 11,

13, 14, 16, 23,

24 140:1, 1, 10,

12, 17 141:24

142:1, 1 145:10,

12, 14, 16, 17, 19,

20, 22 148:16,

18, 20, 22

152:20, 21, 22,

24 157:14, 19

158:14, 16, 17

159:22, 24

161:12, 18 163:1, 1

165:21 167:1, 1

170:1, 10 171:1

172:1, 1, 1

173:17 174:14,

16, 17 175:1

176:10, 23

177:21, 25

183:14, 15, 16

184:1, 10 185:13

186:1, 1, 1, 1, 15,

16, 22, 24, 25

187:1, 20, 24, 25

188:1, 1, 1, 1, 11,

12, 15, 16, 21,

24 189:1, 1, 1,

1, 1, 1, 17, 18, 23

190:1, 1, 14, 18,

21 191:21, 24, 25

192:1, 1, 15

194:15, 22, 24

195:1, 1, 14 198:19

199:1, 24 200:13,

23 201:1, 11, 17,

20, 21, 23, 24

202:1, 1, 1, 1,

1, 1 203:12, 18

204:1, 1 207:22

208:1, 12, 16

209:1, 1, 10, 12,

15, 16, 18 210:1,

21, 22, 24

214:21, 23 215:1,

1, 1, 1, 1, 12, 13,

14 216:1 219:13,

15, 16, 18 222:1, 1

223:1, 11 224:13,

14, 21, 23 225:1,

1, 12, 15, 17, 20

226:1, 13, 23, 25

227:1, 1, 10, 18,

20 228:1, 11

229:22, 24, 25

230:1, 1, 1, 1,

1, 20, 21 232:1, 21

236:1 239:20, 23

240:1, 1, 15, 23

243:1, 14 244:1,

16, 19 245:1, 18

246:1, 16 247:1, 1,

22, 24, 25 248:1,

19 249:1, 1, 1,

1, 1, 12, 13, 21,

23 250:1, 1, 1,

1, 1, 16, 19, 21,

23, 24 251:12,

22, 25 252:1, 1,

10, 11, 12 253:1,

1, 1, 14, 16, 17,

18, 23 254:1, 13,

15, 16, 17, 18, 22,

23, 25 255:1, 1, 1,

1, 1, 12, 24, 25

256:1, 1, 1, 1, 20,

22, 23, 25 257:1,

1, 1, 1, 1, 12, 13,

14, 16, 18, 23,

24 258:1, 1, 1,

1, 1 259:1, 17,

22 260:17 261:1, 22

262:1, 10, 13,

15, 16, 17, 20, 23,

24 263:1, 1, 1,

1, 1, 1, 10, 12,

13, 14, 22, 24

264:1, 1, 15, 16,

19, 21, 22, 23

265:1, 1, 1, 1,

1, 10, 15, 19, 25

266:1, 1, 1

268:1, 19, 23, 25

269:1, 10, 12

270:1, 1, 1, 1, 12,

13, 15, 16 271:1,

12, 15, 17, 18, 21,

22 272:1, 1, 1,

1, 12, 14, 18, 22

273:1, 10, 17,

20, 24 274:1, 22

275:1, 1, 1, 1,

1, 11, 13, 14

276:1, 1, 1, 12,

14, 15, 16, 19, 22,

23 277:1, 1, 10,

12, 14, 25 278:13

279:1, 12, 13,

14, 15, 16, 21, 23,

24, 25 280:1, 1,

10, 11, 14, 16, 20,

22, 23, 25

281:21, 23, 25

282:1, 16, 21, 25

283:1, 1, 10, 11,

12, 15, 16, 17, 19,

22, 25 284:1, 1, 1,

1, 1 285:1, 1, 11

draft 2:1, 13 7:20

8:14 10:1, 24 12:17

13:20 14:20 15:12

22:1, 24 29:1

38:15, 22 39:25

40:1 117:18



128:21 195:1 204:11

214:1 232:14

233:10, 11 243:1

dramatically 195:17

draw 21:13 27:19

34:1 133:15 168:1

174:1 189:1, 11

214:10

drawing 47:1 233:22 drawn 167:23 195:1 draws 14:22 144:22 drive 107:15,
16

143:25 233:1

driven 260:1

driving 143:23

168:16

drop 197:10 200:1

due 70:16 153:1

281:13

duplicative 144:11 duration 189:19 durations 215:1 during 41:14 73:24

77:1 145:1 210:1

dying 231:13

E

earlier 59:24

67:1, 20 78:12 90:1

104:18 107:1 111:13

125:1 137:13

143:1 145:1 155:1

162:1, 1 164:12

177:10 193:1 202:1,

16 203:1 212:22

224:24 225:1 231:19

233:16 234:17, 18

235:1 236:1

241:12 252:1 275:15

278:15

early 10:20 18:14

42:16 213:1 218:20

earthshattering

149:23

easier 144:1

151:22 201:1 282:1

easily 275:1

eastern 91:1 140:1

easy 271:14

eat 278:1 eating 31:1 ec 155:1

echo 102:11 163:1

192:18

echoing 125:1

ed 107:19 113:10,

11, 12, 25 119:17

124:16, 17 125:1

129:1 159:23, 24

161:12, 14, 17

163:1 184:1

193:14 201:17 202:1

204:1 216:1

219:19 221:15

222:1, 1 223:1,

12 224:13, 14

228:13 244:19 261:1

272:1

ed's 225:20

eco 14:25, 25 ecologist 62:21 editorial 228:1 effect 41:17 44:13

45:13 46:11 47:10

53:22 66:1 69:1

75:11 83:1 95:22

97:1, 1 101:1, 1

105:16, 22 151:10

159:18 165:14

166:17 167:1 169:14

191:17 196:17, 19

217:1 220:24 225:19

229:10, 13

239:11, 13 247:13

250:25 251:1 260:22

effectively 37:25

104:23

effects 4:24

20:12, 14 21:14, 19

22:1, 1, 21 26:14

33:22 34:1 35:1, 20

36:1 37:1 38:17

39:1 40:14 41:1, 1,

25 42:16 45:1, 1,

12, 18 47:1, 1,

1, 14, 24, 24

57:1 62:1, 18,

20, 22, 23, 25

63:1, 19 65:1 78:15

79:1 85:1 88:15

93:15 103:1, 1

104:1, 15 105:1, 1,

23 106:12 107:1

111:14 115:13

116:13 118:1, 22

119:15, 15, 22,

25 120:1, 1, 16, 21

121:1, 1 122:17

124:1, 10, 12

125:11 129:25

130:1, 15, 17 131:1

134:22 136:15

142:17 143:19

144:13, 18 147:1

152:12 155:22 159:1

162:17 163:20

164:1, 16 166:1,

12, 16 176:16, 17

179:12, 14 180:1

181:24 182:1 185:18

187:1, 18, 21, 22

188:1, 18 189:12,

20 192:20 193:13

194:1 195:11 197:15

198:1 199:12

206:14, 22 207:1

213:19 218:12

220:10 221:10 225:1

228:15 229:11, 13

230:10 231:1 238:1,

18 246:11 247:17,

17 252:24 267:20

273:11 275:24

efficacies 161:1 efficiency 72:12 efficient 59:1

61:1 144:20

effort 60:20

128:19 142:10

163:16 173:21

efforts 44:1 192:23

eh 49:19

eight 42:22

either 4:1 13:24, 24

32:1 34:19 63:23

77:1 79:19 92:1



98:1 154:1 159:10

206:1 217:15, 25

222:18 244:22

elaboration 17:13

87:15 88:1

elderly 41:1

219:21 220:23, 24

231:1, 10

electron 191:1 electronic 283:13 electronically

283:13

elemental 57:1

elements 60:1

212:1 214:17

elephant 203:25 elevated 51:1 elevator 96:18 ellen 16:1

ellis 49:22 58:17

64:1, 17 65:1

76:1 93:23 117:20

118:1 123:12

134:1 136:10 137:25

144:19 240:22 243:1

280:1 283:1

ellison 37:21

email 4:1 32:1

137:20 138:13 279:1

embedded 226:10 eloquently 93:24 emergency 27:1 35:23

40:1 41:23 47:19

emission 53:1 75:12

emissions 53:1

63:21, 23 67:1

108:16 272:24

280:25

emit 75:1

emitted 44:20

else 17:1 18:24 39:1

52:15 70:21 98:1

99:19 100:1

167:16 198:15, 18

204:1 228:20 247:22

256:25 259:16

262:17 279:19

elsewhere 50:1 273:1

encourage 37:11

63:13 107:12 242:23

endogenous 95:24

160:1, 1 161:1

192:1

endogenously 95:25

160:1 190:22

endorse 121:1 endotoxin 44:25 endpoint 46:1

87:10 112:25

113:1 127:16

196:1 210:11 248:1

endpoints 144:25

154:13 215:1

emphasis 54:1 90:1

172:22 173:1

207:1 221:1

226:14 241:15

282:14

emphasize 107:1

139:1, 12 165:11,

19 225:16 255:16

266:21

emphasized 207:11

emphasizes 63:15

135:1

emphasizing 156:25 empowered 3:1 engaged 58:22 59:1 engineering 94:1
engines 71:1 75:1,

11 273:1

enhance 44:1

enhanced 191:22

220:17

enhancing 181:23 enquiries 158:22 ensure 46:1 entertained 157:1 entire
125:1 260:15 entirely 58:25 93:14

193:23

epa 2:17, 24 10:13

33:19 34:15 35:1,

20 36:19, 21

37:1, 11 39:11

41:13 59:22 61:1

71:15, 16 80:10,

13, 17 87:1

107:12 111:1

121:1 219:23

epa's 34:10 75:1

environment 5:25

90:25 95:23 96:23

216:16

environmental 2:1

9:1 96:13 108:1

218:1 251:1

environments

94:19, 20, 23, 25

95:1, 15

envision 274:24

epi 14:17 36:1 38:18

44:11, 16 46:1

114:18 116:12, 16

142:21 143:22,

24, 25 144:1, 1

145:1 183:18 185:14

199:12 200:17

247:21, 21 252:1

254:11, 15 262:1

267:1 271:1

276:20 278:16

epidemiologic

25:25 27:1, 13,

17 28:1 69:1 141:13

149:13 150:24

151:14 166:1, 16,

24 184:1

epidemiological

35:21 36:11 78:15

114:1, 25 116:1

125:22 129:24

163:13 164:1 172:1,

20 206:1 207:19

218:1 278:20

epidemiologist

16:1 276:11

epidemiologists

17:18 251:17

epidemiology 17:21

19:19 20:1, 17,

21 21:1 22:11, 15

33:23 34:19 65:17

110:1, 22 111:16,

18 122:17 125:15



160:1, 13 169:24

174:19 179:15

182:24 187:18

196:1, 17 249:18

258:19, 24

275:17, 25 276:1

er 167:1 196:1 equal 11:1 equally 244:24

261:17

equate 160:14 equation 94:1 equations 94:1, 1,

1, 13 95:11

equidistant 237:1 equivalent 221:17 error 26:1, 1 115:1,

1 278:24

errors 26:1

et 41:11, 16 44:22

45:1 46:1 47:1, 12,

15 48:14 52:13 57:1

69:22 91:1 101:1

113:20 148:11

154:12 161:1

191:1 198:22 216:15

217:12 228:1 261:1

especially 46:22

69:19 71:1 86:23

87:1 111:12

128:16 143:22

160:13 164:1 181:15

203:22 229:16

230:11, 11 231:22

247:1 248:20, 22

ethics 4:1

essence 60:21, 22

essential 34:1

241:23

essentially 10:22

11:18 12:1 13:23

14:1 34:15 174:20

219:10 236:1 237:1,

21 240:1

establish 44:13

established 59:10

82:16 164:10 204:12

205:1

establishing 46:23

estimate 72:13 116:1

128:1 176:17 181:1

estimates 26:1 42:25

53:1 124:22

229:21 233:23

estimating 214:1

237:16

estimation 193:19

evaluate 14:23

242:20

evaluated 25:14

45:23 149:15 242:11

evaluates 179:1

evaluating 22:20

45:15 170:24

evaluation 36:21

85:1 127:15

138:11 224:1 274:1

evaluations 26:1 evening 279:20 events 267:13 eventually 136:1

234:1, 1 235:22

everybody 9:11, 12

58:18, 20 77:11

85:12 112:23 128:19

140:22 183:10

228:20

everybody's 10:1

266:10 278:1

everyday 42:25

everyone 2:1 4:19,

20 37:23 61:1

228:25 232:11

244:1, 17 246:1

everyone's 76:22

243:1 284:17

everything 11:22

99:1 139:18

154:19 195:20

198:17 215:24

256:1, 10, 25

258:20 259:16

260:16

europe 53:1 67:10

88:10 135:1

european 89:16

evidence 14:23 20:1,

1 21:12, 15, 23

22:1 23:1, 19 25:10

26:11 27:1, 1, 1,

12, 15, 17, 20

28:1, 1, 1, 11, 14,

15, 20 29:17, 18

33:21, 22 34:1, 12,

16, 21, 23 35:1, 1,

11 36:13, 16, 21

37:1 40:1, 1, 1, 1,

1, 14 41:12, 17, 25

47:1, 1, 1, 23

60:1, 25 62:1, 1

65:1 106:12

121:11 122:1, 1, 11

131:1 140:25 141:11

149:1 155:21 159:20

166:24 178:1, 17

179:1, 11, 16

183:13 184:20 200:1

202:13 205:1, 1, 11

206:10, 20, 24

207:17, 17 213:19

235:1 238:1, 1

243:19, 20, 22

246:1, 25 255:10

259:12 260:20

261:15, 23 262:1, 1

264:1 265:1

273:11 276:1

evolution 172:20 evolve 13:14 exacerbated 152:18 exacerbations 196:1
exact 97:21 160:16 exactly 11:25

13:19 135:1

156:19 206:1

208:1 211:19 215:11

225:1 235:11 246:21

251:15 257:11

examine 121:11

examined 119:24

120:1

example 20:22

21:17 35:15 36:1

47:1 65:17 93:19

95:1 105:17



106:24 113:1, 17

116:1, 1 119:17

143:1 150:25 154:11

159:18 162:1 171:10

175:14, 23 182:11

184:19 204:19 207:1

245:13 253:1 270:22

279:1

examples 35:1, 1

47:20 254:10

exceed 25:1 exceedances 164:14 excellent 241:21 except 102:16 190:1
excess 173:25 174:1 exclu 150:16 exclusion 150:17 excursions 105:15

198:1, 1

excuse 74:1 76:1

149:1

exercise 240:1

exhale 190:19

exhaled 189:25 190:1 exhaust 125:17 162:1 exist 81:20 219:1 existence
76:1 existing 29:12

60:1 82:1 116:1

129:17 130:17 193:1

237:19

exists 164:15 exogenous 96:1 expand 98:1 106:22 expanded 200:14
expansion 92:1 expect 7:16 130:1

169:23 179:1 191:19

198:20 205:20 239:1

266:14

expectations 99:17 expected 147:19 expecting 43:11

198:25 209:22

experience 16:13

134:16

experienced 115:1

experiencing 43:19

experiment 90:13

experimental 33:23

34:21 36:13 37:1

141:12 160:1 163:13

166:1 206:24 217:15

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93:1 153:14

157:11 170:14 186:1

195:1 196:21 204:1,

1 219:11, 18 231:19

232:22 235:18

263:14 279:14

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10:1, 1 16:17, 22

17:1, 25 20:23

31:1, 12, 13, 21

33:1, 12 37:24

38:1, 1, 1 39:24

43:25 48:15 58:1

62:21 64:10, 12, 20

66:19 72:15 74:18



77:19 85:1, 12

89:12 92:1 105:24

106:16 107:1, 10,

20 109:1, 1

112:21 117:19

119:1, 1 121:20, 25

122:1, 1, 1

123:12 128:12, 18

131:15 134:1 135:16

137:1, 18 138:19

145:14, 18 146:20

148:1 150:12, 18

157:10, 25 158:19

163:1 166:20

167:14, 25 169:21

171:10, 19 174:1

175:1, 1, 1, 10,

21, 21 176:1 185:25

190:1 193:1, 21, 23

194:23 195:15,

15, 23 196:19

197:11 198:19

203:11 205:24 206:1

209:22 211:1 217:19

220:25 221:20 225:1

226:17 231:1 234:17

235:1, 1, 12, 13

236:15 245:14, 15

246:20 247:18

248:13 249:1

250:1 251:12, 13,

22 252:10 255:1

256:1 258:1

259:17 260:18, 24

263:15 264:13

266:11 268:10, 14

269:1, 1 270:12, 13

274:22 275:24

276:10 277:20, 21

279:1, 11 283:22

284:24 285:1, 1, 1

i've 3:1 34:1

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126:16 129:14

130:1, 1 131:25

148:18, 24 149:21

152:25 153:16

157:19 168:10

169:14 175:1

182:1 188:20 191:21

192:1 195:14 196:12

198:17 207:1 210:19

220:1 222:1

245:11 247:1, 1

251:18 259:19

idea 50:11 51:1

56:17 76:21 83:12

103:21 114:14 121:1

126:1 130:16

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176:1 208:13 222:13

223:13 228:12

241:24 244:1 264:21

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ideal 241:1

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265:18 266:14

identified 29:12, 13

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identifies 12:15

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158:1 222:17

225:1 226:1

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included 13:22, 24

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41:1 81:1 108:15

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217:1 281:17

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34:22 35:1 36:15

40:1 243:22

244:24 253:20

263:19 264:1

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35:16 142:10

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47:21 244:23

incorporate 209:1,

13, 18

incorporated 13:1

43:1

increase 151:1

230:24 231:1, 12

250:15

increased 26:1 35:22

40:1 96:13 113:19

185:1 194:21 239:1

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59:14, 21 60:1

62:14 117:23 118:24

121:1 122:1, 10, 25

130:25 136:12

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46:17 61:1 72:10

194:11 237:1 242:14

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51:1, 25 52:1, 1,

1, 1, 13 55:21 56:1

60:16 90:1 91:18,

25 95:1 103:1, 23

111:1, 10, 11,

15, 23 120:16, 22

173:1 183:1, 11

187:1 206:17 236:18

237:22, 25 247:1,

20 251:1 252:16

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139:19

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52:22 91:1, 10

114:12 120:17

185:16 187:13 228:1

246:12 252:22

induce 108:1 induced 150:1 industry 38:12

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infants 107:25 infection 220:18, 18 infer 54:16 121:1 inference 34:1,

13, 15, 18, 22

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inferences 213:21

214:10

inferred 62:1 infiltration 95:1 inflammation 21:18

150:1 191:1, 11

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119:22 120:1

160:1 166:1 247:17

influence 65:13

95:12

influenced 106:1

inform 20:1 23:1

29:1 106:12

151:19 171:1

197:1 199:23 255:21

information 7:10, 18

10:1 11:17 13:1

14:1 19:1, 16, 25

20:1 21:13 22:1

23:1, 19 29:1, 15

42:14 47:1 48:1

52:21 65:1 79:1

81:18, 19 82:19, 22

83:23 85:1 86:10

87:21 93:13

94:15, 17 106:1, 14

112:17 113:1, 21,

23 117:1 122:19

127:20 136:14

143:10, 11 149:24

150:17, 23, 24

151:13 157:24

180:15 181:1

193:1 199:1, 23

200:1 201:10 203:1,

1 205:1 213:1, 16

214:1, 20 219:1,

10, 21, 24 220:16

221:1, 1, 19, 24

240:13, 14 241:22

247:1 261:1

267:16 269:1, 25

270:1 272:19

273:1 274:18

275:1 276:1

281:18 285:10

informative 110:21

183:1 252:16

informed 3:1 214:19

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impact 11:1 22:1

28:25 51:22 54:1

169:10 216:25

249:10, 24 260:1

impacts 93:1 216:21,

24

imperative 81:17 implementation 11:24 implemented 36:22 implicate 45:25
47:1 implication 95:1

194:16 229:1

implications 53:23

69:1 229:1, 10

importance 45:1 92:1

212:1

important 7:1 15:1

49:11, 15 50:25

51:1, 1, 21 52:18

53:20 54:12 57:1

58:1 59:20 61:20

66:12, 18 67:16, 25

70:24, 24 77:14

79:1 81:11, 15,

23 82:12 84:13

90:20 95:1 96:1

102:10 110:1 111:11

116:15 120:12



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130:13 136:14

137:21 140:22 143:1

144:21 152:13,

14, 14, 17 155:1, 1

156:1, 17, 23 157:1

161:13 163:11 164:1

165:12 166:1, 21

168:1 173:16 177:12

182:20 183:1 184:13

187:16 189:19 204:1

207:11 212:21 213:1

224:1, 1, 21

225:1 226:12 228:18

235:1 241:1

265:17 269:1

273:1 279:1

importantly 89:1

219:1

impression 216:11

229:17

impressive 129:12

185:15, 20

improve 49:14 96:1

117:17 139:1

improved 44:1

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90:10

inhalation 160:12 inhale 120:1 191:15 inherent 38:19

260:15

initial 14:19

91:15 170:18 213:22

214:1

injury 188:13

inlet 89:1, 1

inner 127:17 232:1

input 23:1 26:13

106:21 265:12, 18

inside 91:12

insights 37:1

60:22 239:18

instance 72:1, 25

73:10 86:11

170:21 193:14

215:17 261:22

278:23

instead 36:1 55:1

95:10 180:19

instincts 169:12 institute 37:21 instructive 111:14 instruments 91:24
insufficient 166:1 insult 216:17 integrate 15:1 21:23

26:15 163:12 267:1

integrated 2:10 3:19

6:1 11:14, 16, 25

12:1, 15, 16

14:1, 1 15:1, 12

19:1, 22 142:21

144:21 146:1, 1, 20

148:1 150:23

151:1 162:11

163:1 199:16

233:24, 25 234:12

241:19 242:1

274:13, 18

integrating 33:20

45:1 142:25

151:13 204:21

225:10 274:17

integration 14:21

20:1 21:20, 22

26:11 141:11

142:11, 15, 19

143:12 144:1, 18

146:13, 17, 17,

24 148:1, 12

149:1 152:15 164:1,

20 166:1 173:15, 22

176:1 178:1 192:19,

23 219:1 235:11

252:18 267:1

integrative 151:18

211:1 212:15, 23

214:1, 1

intellectual 159:1

177:11

intended 174:17

175:1 199:1

intense 83:1

intent 146:15

172:1 225:1

inter-correlation

203:21

interact 6:14 interacted 8:1 interacting 6:10

182:1

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interactions

181:20 257:25

interacts 190:1

interest 4:1 10:11

12:24 217:23

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26:12 63:18 135:1

184:18

interesting 86:13

89:20 95:20

96:11, 20 104:1

112:18 170:16

217:17

interface 104:21

interference 24:14

54:23 55:12

72:10, 17 117:1

137:1

interject 274:10 interjection 32:10 internal 223:15 interplay 94:23

95:13, 16

interpret 159:1, 12,

14 161:25 175:1

204:1 207:1 252:1

273:10

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20:1 23:1 25:1

44:16 46:1 114:1,

17, 24 144:1

147:1 159:1 164:1

169:20 173:1 176:22

207:1 211:11, 12

264:11

interpretations 90:1

159:10

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225:15 240:17

interpreting 46:21

159:20 207:19

interpretive 173:11



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intersection 231:20 interval 174:1 intervention 90:1

183:1, 11 185:15

238:1

intrapulmonary

218:21

intrinsic 223:15

introduce 2:20 15:19

95:12 116:1

introduced 115:1

introducing 17:11

20:24 37:20

introductory 63:11

228:23

intuitive 216:12 intuitively 171:19 inventory 53:14, 18 investigated
253:1 invite 243:15 invited 3:1

inviting 243:24 involve 19:19 95:14 involved 8:1 71:15

72:15 113:1

153:16 155:1 217:22

involves 35:17 36:10

45:11 117:25 125:17

139:18

involving 24:1

208:18

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33:11, 18 36:20

38:13, 16, 16, 22

39:1, 19, 25

40:1, 13, 18

41:1, 1, 11, 24

42:12, 19, 22 44:1,

11 45:1, 14 46:1,

25 47:1, 1, 15,

23 48:1, 1 49:14,

16, 17 59:17, 22

61:1 67:13 79:1, 16

80:16 106:1 195:1

198:25 204:11

232:14 253:18

ironic 69:1

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120:1

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10:20 14:1, 24 19:1

24:1, 13, 22

27:18 28:10 29:11

30:24 32:14 41:1

46:18 48:18, 23,

24, 25 49:1, 25

50:1 51:10 52:16

53:20 54:22 55:1,

23 57:1 58:13 61:20

62:12, 14, 15, 16

65:10 66:12 69:1,

11 70:24 71:19

72:1, 1, 23 75:14

77:1 81:11, 17,

23 82:1, 12 84:1,

1, 15, 18 85:1,

14 88:24 89:1, 25

90:20, 23 91:1

92:17 93:14, 14,

16, 17, 18 94:15,

16, 22 96:1, 1,

10 98:1, 18, 18

100:1 101:15

102:1 103:1

104:1, 1, 1

106:10 107:11, 24

108:14 109:21

110:1, 1, 10 111:1,

10 112:21 113:18,

22 116:15 117:1, 16

120:1, 1, 1, 20

123:20, 24

124:11, 17

125:14, 18 126:1,

1, 10, 21, 24

136:20 142:17

143:1, 14, 21, 25

144:1, 1, 10, 16,

21 145:1, 12, 14

147:1 148:11

150:1 151:17, 18

152:14 153:1, 1, 15

154:1 155:18 156:17

157:1 158:20 159:17

160:1 161:1, 1

162:1 163:1, 11, 16

164:1 167:1, 16, 25

168:1, 1, 1, 15

169:1, 13, 21

170:18 174:1, 17,

19, 25 175:1, 11,

15, 15, 16 176:1

177:22 178:14 182:1

183:16, 21 184:13

188:1 189:10, 15

190:22 192:1, 20

195:1 199:13 200:21

202:1 203:24, 24,

25 204:17, 22

207:15 208:1

212:18, 21 213:1,

13 215:1, 15

217:18, 20 224:14

225:24 226:1, 10,

19, 23, 25 227:1,

13, 16 228:18, 25

230:1, 25 232:25

235:14 241:1

244:1 245:1, 11

247:14 248:23

250:1, 1 253:21

256:13, 13, 14,

14 257:18 258:14

259:1 260:21

261:1 262:1, 16,

21, 25 263:1, 1

264:1, 11 272:22

273:1, 10 274:1

275:20 276:12, 18

278:15 282:1, 10,

22 284:12

isn't 69:13 86:25

108:20 118:14 130:1

212:12 213:12

226:11 257:10

isolating 187:17 iteration 112:23 issue 25:1 58:13

67:1 70:22 71:13,

17 74:23 75:14,

14 79:18 80:1, 1

83:24 86:1, 25 87:1

88:1, 1 89:24 92:1,



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110:1, 1 114:24

120:25 123:1, 16

124:1 125:20 133:19

153:10 159:1 160:19

161:22 166:15

167:1, 15 176:10

185:10 189:1

193:1 196:13 203:19

204:1 207:1

208:25 216:1 218:1,

19, 20 222:1 226:12

233:1 235:18, 20

245:12 251:15

253:15 255:24

260:1, 13, 14

268:24 269:17

issues 6:21 20:1

23:11 44:15 46:1,

20 47:22 57:16

58:10 59:1 72:15

85:17 89:11 90:18

91:22 104:13 106:23

125:1 128:22 162:19

165:1 191:1

207:12 210:1 232:22

266:1 268:1

272:20 273:25

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j-o-n 145:20

james 104:11 167:1

170:11 171:19 172:1

174:14 191:1 192:12

195:12 205:14

260:18 269:22

jeanine 17:17

jeff 16:1, 1 75:21

136:1

jeumg's 16:1

jeung 16:1

jim 16:1, 1 31:1, 1,

11 92:22, 23

98:12 99:15 101:17,

20 102:24 145:1

202:12 219:13 222:1

224:15 227:1

job 135:22 151:13

204:23

joe 16:12 68:20, 24

john 5:14 30:17,

19 31:1 43:1, 25

48:11 101:22 123:1,

1 124:15 125:1

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148:21 152:20

164:22 165:21

167:20 171:22

183:16

join 17:15 32:25

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14 148:16 149:10,

16 151:15 158:14

159:22 166:18 172:1

173:18 175:15 178:1

201:20 202:1

204:1 207:22

252:10, 11 253:1

257:19, 20 266:1

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jon's 149:1 176:1 jotted 266:11 judgement 235:14, 15

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judgements 212:24

213:24 214:17

241:23

judging 47:25 jump 214:16 jumped 11:1 jury 113:23

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karen 6:1 210:1, 19,

20 214:22 215:14,

21, 22 232:17

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208:1 209:1, 12, 16

kent 161:15, 15

163:1 165:22

166:10, 20 167:20

key 10:23 11:19

12:14, 25 24:1 25:1

26:20, 22 46:25

47:1 137:16

143:1, 12, 21

144:15, 16, 22

145:1 153:17 165:23

176:12 187:17 244:1

kickoff 12:21, 22

kids 92:10 113:18

151:1 216:14

228:15, 16 232:1

kilometers 80:1 kim 16:1 128:14 kinds 45:12 87:10

95:14 103:19 115:14

119:20 171:1

186:11, 12 198:10

199:1 200:1

201:14 204:24 205:1

220:10 240:1 242:25

273:15

kleeberger 170:10,

11 186:1, 16, 24

188:1, 1, 11

192:12, 15 194:22

195:1 223:11 226:1

knew 21:1 150:12 knocking 181:22 knowledge 16:16

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12:23 16:1

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1 54:22 69:21 161:1

kotchmar 15:21, 25

L

labeling 191:22 labels 152:1 laboratory 72:11

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166:23 182:1 266:25

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lags 14:1 157:1 laid 148:19 274:1 language 194:24

large 53:1 60:1 66:1

79:25 125:1

127:14 128:19

143:14 185:1 193:25

194:1 223:1

largely 9:17, 18

111:17 145:23 193:1

253:1

larger 59:25 63:22

73:17 123:16

larson 32:1, 1 74:1,

1, 11, 11, 15,

18, 20 75:18

85:1, 1, 11 92:20

109:11, 13 138:1,

1, 1, 15, 18 139:1,

14, 23 186:22, 22

187:1 190:18 247:1,

1

last 7:24 9:15 10:16

12:1 13:16 15:1

18:13 22:22 26:24

28:23, 24 29:14

33:1 43:1 60:23

80:1 98:1 99:22

101:24 126:17

140:23 146:1

150:1 175:1

189:17 197:20

218:24 219:24

267:22 269:1

lastly 182:1 231:15

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52:1 55:16, 23 57:1

85:1 86:24 90:1,

1 94:1, 10 97:16

109:21 113:1

132:21, 22 139:1

143:1 155:1

162:23 227:23

latest 140:1 248:24 latitude 259:20 latter 143:21 233:18

234:23, 24 245:12

laudable 173:21

lavage 150:1, 10

law 3:1 laws 4:1 lay 246:1

laying 37:1 layout 202:18 lead 8:10 45:17

49:24 78:1

232:10, 20 265:22

leaders 266:15 leading 49:23 63:1 leads 45:1 83:23 lean 202:13 247:18
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63:11 66:21 77:22

81:1 88:1 92:1,

12 96:1 114:11

115:1, 16 122:1

123:25 154:22

160:23 166:1 192:21

216:10 220:1, 1

228:14 235:1

leave 16:19 52:14

225:1 282:21

leaving 153:25

led 15:25

legal 284:11 legally 284:14 legends 152:1 legitimate 190:19 length 24:12
54:1

259:14 267:21

lengthening 274:20 lengthy 70:18 145:23 less 27:12, 15 41:17

106:1 114:1

185:21 187:1 238:17

255:1 273:1

lessens 188:22

let's 3:15 4:1, 13

8:1, 22 55:19 57:24

69:15, 24 71:25

92:21 94:17 97:21

116:1 121:1

140:1, 14 148:21

181:23 195:1, 25

196:1 204:23

206:1 210:1, 25

215:25 218:13

230:22 231:1

248:1 269:1

letter 59:13 123:20,

21 126:1 139:1,

25 140:1 209:19

243:1 266:1, 21

268:1 272:21 273:25

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letting 201:21

level 34:11, 13, 14,

18, 22 51:1 96:13

97:14 105:18, 20

114:1, 1 117:1, 1

168:23 185:23, 23

195:17 196:14, 15

197:10 199:14 220:1

225:21 232:18 234:1

254:1 275:18

levels 21:14 22:1

25:1, 17 38:23

40:1, 10 66:1 72:16

90:21 104:20

113:1 164:17, 18

166:1, 13 168:21

169:19 179:1

182:1 184:1

188:1, 23 190:13

195:21, 21 197:10

199:1, 11 205:21

212:1 224:16

234:1 254:1, 1,

1, 1, 1, 11, 20

260:1 268:1

270:17 272:16, 17

273:1, 12, 18

281:1, 1, 1

lianne 32:1 132:1,

14 133:17 274:1

278:13 279:10

liberty 34:1 librarian 157:23 lie 234:12

lies 173:12

life 62:23, 24 90:23

236:20, 21

light 52:24, 25



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159:1 176:13 224:1

likelihood 190:23

likely 27:1 34:14

35:18 67:14

101:15 105:1

115:1 117:1

118:12 176:24

213:20 216:24 229:1

236:12 243:21

244:10, 14, 18,

24 246:10, 21

250:25 251:1, 15,

21, 24 254:19 263:1

likewise 160:24 limb 201:10 246:1 limit 259:1 limitation 208:25
limitations 38:19

55:1 208:10, 13, 14

limited 28:14

29:15 34:21, 24

35:1 36:13 44:12

46:23 91:1 243:22

262:21, 25 264:25

265:1, 1, 1 266:1

limits 198:1

line 30:15 31:1

32:1, 1 43:14

140:23 153:1 205:16

206:10 213:1, 18

214:1, 17 227:11

267:1

linear 200:22 237:11

lines 33:22 34:12,

16, 23 81:10 108:10

178:15 250:1

linked 52:1 179:24

215:1

linking 28:11 links 147:1 lipford 155:10 list 92:22 158:20

161:17 277:19

284:12, 13, 14

listed 153:18 254:1,

1

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lit 282:1 literally 108:1 literature 13:1,

10 44:16 88:21

104:24, 25 119:13

157:22 158:10, 18

163:17, 18

164:23, 24 165:1

166:1, 1 171:1, 1

172:21 193:1 221:22

little 12:13 14:1

18:16 29:18 42:23

50:21 56:1 64:14

66:1 67:23 68:12

70:1 79:1 86:1

88:18 91:15 92:1,

25 93:1 98:1

99:1, 21, 24 100:1,

22 102:20 103:18,

19, 20 107:20

131:11, 21 137:14

138:1 144:1

147:1, 15 149:20

150:13 151:1, 1

154:22 159:1 167:25

177:24 183:21

191:15 192:1 193:12

212:13 219:17

222:1, 22 224:1

233:1 237:21

252:1 255:17

261:1 279:1 280:1

live 86:12, 20 89:1,

1 127:1, 1 170:1

226:19

lively 7:16

living 67:17 79:20

89:1 223:1 231:18

local 51:1 278:25 locale 225:24 localized 26:1 located 66:11 76:1

114:1, 16

location 55:1 69:17 locational 223:1 locations 57:1

127:18 272:1

log 237:1

logic 175:25 logical 223:1 logistical 283:1 lognormal 237:1 london 70:25

long 5:10 10:11 16:1

20:11, 19 24:13

27:21 28:1, 16 30:1

33:1, 1, 1 35:1

56:21 70:10 86:18

88:25 104:20 109:12

117:1 120:1

124:25 131:10 140:1

142:1, 1 151:1

155:1 172:21 180:14

199:1 212:23 238:14

244:1 260:25 267:19

269:20 270:1, 1,

1 278:1

longer 89:1 90:24

92:13 130:1

189:20 212:13

loop 265:19 loose 234:1 loosely 274:1 lori 16:14

lose 184:16 188:18 losing 184:21, 23 lot 6:12 8:1 15:1

20:17 26:1 27:1,

10, 15, 19 28:11

29:17 43:17 64:19

65:20 69:19 71:1

79:1, 16 81:1 85:13

87:1, 14 88:10 89:1

90:1 95:1 97:19

102:16, 18 111:1

112:17 119:1 124:1,

10 125:1 127:1

128:16 131:1 132:13

144:10 148:19

155:21 163:17 165:1

167:10, 11 174:1

178:1 180:15

181:1 187:1

191:25 195:15

196:1, 1 202:1

214:20 231:13



232:21 233:19

255:14, 15

267:16, 23 276:1, 1

282:1

lots 239:1, 1 lotus 200:19 loud 142:1

louder 43:17 219:17

loudly 74:1 love 10:1 loved 69:12 lover 233:1 loves 183:10

low 96:17 113:20

160:12 174:23

254:12 269:1

lower 147:22 195:17,

21 196:14, 15 197:1

198:1 200:1

222:21 238:21 248:1

258:1

lowered 105:20

lowest 189:11 238:24

lucky 265:25

lumped 264:18

lunch 77:18 137:12

140:1, 10

lung 21:18 28:1,

1, 1, 11 40:1

96:1 113:20

119:21 151:1, 10

167:10 168:25

169:10, 15 172:11

174:11, 13

175:14, 22 184:19

196:1 220:1

224:17 228:14

229:1, 1, 1

261:1, 16, 23

262:20 263:18, 25

264:1, 1, 1, 17, 20

265:1, 1

lungs 191:23 192:1

lydia 6:1

M

machines 76:14

magnitude 144:24

163:21, 25 169:15

188:1

main 13:25 57:14

142:12 171:14 210:1

220:1 235:18, 20

282:16

mainly 103:1 246:11

major 3:18 11:1

67:10 78:1 79:12,

18 80:1 82:1

86:10 87:24 109:16,

18 149:10 155:19

157:10 167:1 176:10

207:1 234:21

268:1 280:12

majority 23:19 makers 151:19, 23 man 141:17 197:21 manage 61:18
management 9:18

118:21 134:20, 23

135:18

managerial 62:19 managing 135:22, 23 mandate 169:18

197:22

mandates 195:20

manufacturers

43:10 44:1

map 61:24 76:1, 1, 1

81:1, 24 82:13

marcus 10:12 margin 211:25 marion 75:1

mark 17:22 119:1

124:19 162:1

markedly 42:10, 24

marker 36:1 45:1

258:1

martin 6:1 210:1,

21, 24 215:1, 1, 1,

13 232:17

mary 5:24 9:1 10:1

15:20, 22 16:18

17:1, 1, 1 29:25

38:24 50:1 59:24

64:1 67:19 68:14

109:1 127:23

129:1 131:21, 23

132:1 189:1

208:13 212:22 244:1

246:1 256:24 268:19

matched 212:1

material 14:20

33:1 100:23, 23

101:1, 18 102:16,

16, 17, 22 110:1

233:15

materials 102:18

matter 4:1 5:1

26:1 47:13

126:19, 24 206:1

257:22

matters 64:1

m0x 78:13

max 20:18 188:25 maximum 180:25 may 10:1 28:1

47:13 65:18 67:1

68:1 87:18 91:1, 11

99:20 107:16

112:1 115:18

116:1 123:1 125:14,

14, 25, 25 126:1

138:1 141:1

147:13 150:15

152:17 165:1, 14,

16 168:1 176:15, 18

181:21, 24 185:1

187:1, 1 202:25

212:1 218:10 222:10

227:15 251:1 252:16

258:15 261:25

269:13 270:21, 22

282:12 285:1

maybe 10:16 57:21

59:1 66:20 73:11

93:20, 20 96:1

98:21 99:20

101:1, 1 107:11

116:1 130:1 131:19,

21 134:1 139:19

142:24 175:25

177:23 179:25

180:16, 20 196:21

200:13 219:1 223:21

228:23 230:25



242:10 249:1 250:19

251:20 258:11 259:1

276:1 279:1 282:14,

18

mean 8:1 69:18 70:1,

17 71:10 72:1, 1,

1, 23, 25 73:1,

1, 1, 11, 23

77:16 83:19, 20

87:16, 19 98:18

99:22 100:1, 11

104:1 113:15 119:10

139:17, 20 147:1

159:17 172:1

176:11, 21 178:1

180:14, 25

184:13, 17 185:1

186:16 187:1, 14

188:1 194:1

198:1, 20 202:1, 24

205:1 211:24

216:14, 22, 25

226:18 232:1

233:1 234:12, 24

237:17 238:18

239:23 244:14

246:1, 13 248:1, 22

249:1 252:13, 18

253:13 256:1, 14

257:17, 18 258:15

259:1, 1, 15 260:18

261:1 262:1, 16

265:10 266:1, 1

271:19 273:1

274:1 275:18

278:1 279:1 280:1

284:12, 22

meaning 94:12 178:21

211:25

meaningful 157:1

193:1, 22

means 135:19, 20

148:13 163:1

190:1 205:18

224:1 233:25 237:16

265:1

meant 8:1 165:23

205:24

measure 23:22

24:12 57:24, 25

62:17 65:1 69:1

75:20 76:1 83:14

122:25 123:1, 15

187:10 188:1, 19

221:14

measured 60:14

75:19, 23 85:22

115:1 162:1

177:1, 1 219:1

236:18 238:10,

12, 19 270:18

measurement 24:11,

19, 20 26:1, 1

52:12 54:14, 15

56:1 57:23, 23 58:1

64:20, 21 65:1 77:1

78:12, 13, 19,

21, 24 79:1, 1, 1

116:1, 16, 21, 24

117:1, 1 134:13

136:12, 17, 20

137:1 239:13 278:24

measurements 20:1

24:18 25:11, 18

26:1 40:17 54:17

55:1, 10, 11, 20,

21 56:1 65:16, 21

72:1, 1, 1, 1, 19

73:1 75:23 76:1

78:16 90:19 91:24

114:11, 12 115:1

118:1 136:22

137:1 177:13 218:13

measures 26:1, 16

39:21 58:1 78:17

measuring 25:12

74:21 79:10 85:18

124:20 125:1 277:1

mechanically 136:21

mechanisms 100:15

150:22 151:1, 1

161:1 189:22 219:1,

1 258:23

mechanistic 27:20

40:1 150:23

med 192:16 mediated 147:23 mediator 96:1, 1

meet 9:1 140:11

285:12

meeting 2:1 3:1 4:1,

1, 21 5:17, 18

12:21, 22 38:1

49:11 126:17

137:1 146:1 285:14

meetings 2:24, 25

208:21

member 4:10, 10 6:20

7:22, 25 8:1

38:11 120:15

members 3:24 4:1

5:1, 1, 1, 11, 13

9:13 10:1 20:25

29:23 30:15 31:1

32:1 140:10

membership 58:25 memory 187:21 188:21 mentality 100:11, 12 mention 63:21

128:1 144:1 227:1

272:25 278:15

mentioned 9:16 10:10

14:15 33:12 60:11

63:12 67:10 68:1

71:25 86:1 87:1

89:1 91:1 99:1

102:14 119:25

120:14 121:13

126:11, 16, 17

131:12 150:1, 1, 10

160:1 162:1

164:21 179:25

181:19 183:1, 12

193:1 196:10 197:20

198:20 221:15 251:1

272:23

mentioning 87:14

158:1

mentions 59:24 151:1 merely 37:1 87:17 merit 222:13

message 210:1

met 148:12 205:17

259:24

meta 131:23 250:1

meta-analysis 131:23



132:1

meta-analytic 240:1 meter 151:24 168:20 method 24:13 39:20

60:13 64:20, 22

65:1 75:24 78:13,

13, 16 117:1 133:20

277:1

methodical 35:10

methodology

146:12, 25

methods 6:1 52:12

80:13 117:24

metric 152:1

metrics 116:24 metzger 155:1 157:25 mexico 54:20 71:25

72:1, 18, 24, 24

mice 186:17, 19

micro 94:18, 20,

23 95:15

micrograms 151:24

168:19

microphone 17:1 31:1

182:1

middle 73:1 99:1

220:24

midstream 11:10

mike 18:1 32:23 93:1

136:1 142:1 209:1

210:23

miked 8:19, 21

miller 100:25

million 102:1 107:24

108:1 151:25 187:23

188:12, 18 189:13

253:24

mind 111:1 124:1

141:20 152:15

173:16 190:1 273:21

278:20

ming 16:10

mini 147:1, 1

148:1 151:18 267:24

minimize 104:1

minimum 82:1

minor 69:15 195:1

minute 14:10 210:1

minutes 3:1 77:1

210:15

misclassification

281:13

misleading 53:15 misperception 282:1 misperceptions 75:1 miss 8:11
158:10

258:10 282:1

missed 158:13 269:14

282:1, 12

missing 143:20

156:23 180:15

198:21 208:10

221:12 275:1

mission 9:1

mix 36:1 73:1 124:13

125:1, 14 136:18

137:1 172:17

mixed 42:1 220:25

mixture 23:15 24:15,

21 39:23 124:12

173:1, 10 206:18

257:24 258:1

mode 80:14 246:1

model 45:14 46:1

80:1, 14 146:19

147:20 159:16 172:1

176:11, 18, 20

177:1, 1 207:1

model's 148:12

modeling 101:1, 1

200:19, 20

models 40:24 42:1,

10 80:1, 17 85:25

128:1 146:1, 1,

1, 1 147:12, 14, 21

154:14, 18, 21

155:21 159:1, 1, 14

162:20 166:18 173:1

176:14, 20 205:1

moderate 217:12 modest 59:1, 1 modified 114:19 mold 44:25 molecule
160:16

190:1

moment 8:1 9:1

38:1 111:1 115:19

moments 135:13

monitor 55:15

57:22 65:25 69:17

83:1, 1 108:18,

19 110:11, 11, 13

269:20 270:20

272:1, 1, 16 278:24

monitored 39:12

119:1

monitoring 44:23

55:22, 25 57:16, 18

58:11 66:10, 13

69:1, 1 74:1, 22

77:1, 25 85:24

89:22 107:14

109:1 115:1, 22, 23

120:12 134:14 136:1

137:21, 24 267:1, 1

271:1 280:1

monitors 39:1

54:22 55:1 56:14

65:22 75:19, 20

76:1, 11 81:24

82:1, 13 83:1, 10

85:18 86:1, 11,

15 89:1, 1, 17

109:17, 22 114:1,

15 115:1 129:20

177:16 270:18

271:13 272:10, 15

274:24 281:14

monoxide 161:1

month 236:20

238:11 270:1

months 7:20, 24 9:15

18:13

morbidity 21:1,

10, 21, 25 26:23

27:12, 12 28:1

151:1 243:21 244:10

246:11, 20 251:1, 1

253:19 254:19, 20

260:22 261:16

morning 2:1 3:24

4:19 5:23 30:13

37:23 38:1 59:25

138:25 140:15

144:19 166:22



202:16 283:24

284:1, 10 285:1

mortalities 27:16

mortality 21:11

27:25 28:19 35:1

36:10, 16 40:11

42:12, 15, 16, 18

46:16 155:1 167:1

255:10 259:13

263:19, 25 264:1,

17, 18

mortimer 47:1

mostly 23:1 80:1

104:1 142:18 192:25

motion 59:1

move 7:21 86:20

88:23 95:14 131:1

180:1 223:19

moved 104:1 227:25 movements 94:19 moving 13:14 17:25

41:10, 23 42:11

53:10 130:24

multi 85:24 126:1

131:1 134:22

136:1 137:1 138:1

142:10 154:17,

20, 23 155:11, 15

156:1 158:1

159:1, 14 162:16,

20 173:1 177:1, 1

203:20 207:10

266:18, 22 280:1

multi-city 27:1 40:1

42:12

multi-pollutant

41:21 42:1, 10

45:21

multiple 57:19

134:21 135:14

196:1, 1

mung 68:20

muscle 96:1 120:1 muted 171:24 myself 99:12

153:10 200:1

57:1 65:1, 11, 18

66:18 69:1, 10,

12 71:1 76:15,

19, 23 77:1 78:18

83:13, 19

naaqs 2:23 4:24,

25 10:1, 1, 11,

19 25:1, 1

n0i 39:21 57:22,

23 74:21 75:19, 20,

24 76:1 78:13 79:1,

10 83:12 84:1

nailed 13:21

naive 64:14

n-maps 42:13, 20

46:1

namely 33:22

napap 242:17

naqs 10:1 11:10,

12 13:17 15:19

20:1, 13 21:1 23:21

50:1 56:18 119:11

143:1, 23, 25

nation 61:22 123:1

national 5:25 8:25

61:21 78:20

105:20 242:17

nationally 126:1 natural 90:12 120:19 nature 26:18 82:1

162:16

nce 9:1

ncea 243:11

n0y 23:23 24:18

25:11

n0z 23:23 24:14

83:13

nearer 86:21

necessarily

116:20, 25 117:1

148:1 194:1

215:10 226:18

240:13 245:14

247:12 250:11

251:13 259:1

261:11, 18

192:24 275:10

neck 175:1

negative 40:18 46:14

149:20 150:1, 1

153:19, 21 157:18

168:1 256:13, 14

258:14 259:1 266:25

267:1 282:1, 1, 12,

13, 18, 24

neglected 18:11 negotiations 18:12 neighborhood 69:21 neither 120:1
149:22 net 249:24

network 75:25 82:1

109:1 136:22

neutral 110:12

nevertheless 100:1

169:1

newer 101:1 newness 9:20 news 172:14

nice 86:1 117:1

152:1 221:13 237:11

nicely 223:23 night 33:1 nighttime 54:11 nine 40:16, 16

60:12, 13, 17

nitrate 54:24 57:1

67:25 68:1, 1, 1,

1, 1

nitrated 191:1 192:1 nitrates 125:10 nitrating 191:1 nitric 24:16 25:12

54:10, 23 55:1 69:1

72:18 83:20 98:16

134:1, 12 149:24

150:1

nitrite 160:17 191:1

nitro 24:1 28:1

261:24 263:1

nitrogen 2:1, 10, 23

4:22, 25 6:17



 		necessary 34:12

21:1 23:15, 16,

N

n0 23:22 54:1, 1, 10

109:1 144:1

24 24:1, 1, 19,

21 51:1 59:10, 23



60:1, 1, 14

61:12, 19 62:1,

1, 10, 11, 25 63:1,

1, 10, 15, 16,

20, 23 81:1

117:23 118:1, 1,

11, 22, 25 121:1

122:21 123:15

135:1, 19 137:1, 10

139:21 160:1 163:22

257:10, 13

nitrotyrosine 191:23

no/no2 125:21

no2 2:13 3:11 21:1

23:16, 20, 22 24:1,

12, 14 25:11, 15,

16, 17, 18 26:18,

24 27:1, 11 28:1,

1, 21 29:18 35:1,

1, 19, 22 36:1

38:16, 23, 24 39:1,

12, 18, 20, 21

40:1, 10, 16, 22

41:1, 1, 18, 20, 25

42:1, 10, 14, 18,

25 44:13, 17, 23,

24 45:1, 21, 22

46:1, 13 47:1, 1,

1, 16, 23 53:1, 10,

11, 13, 16 54:1, 10

55:14 56:1, 13,

14 57:1 58:1 59:21,

22 60:1, 1 62:1, 12

65:1, 11 66:1, 18

67:1, 1, 1, 10

69:13, 19 70:1

71:1, 1, 1, 1 73:1,

1, 12 75:1, 12,

23 76:1, 15, 24

78:13, 17 79:1, 10,

15, 22 80:1 85:24

86:1 87:1, 17

89:17, 22 90:1, 21,

23 91:1, 1, 19

103:1 104:23

107:10, 16

108:15, 16, 19

110:1 111:1, 1, 10,

11, 14, 21, 22,

23 112:1 113:14

114:1 116:25 117:1,

1, 22, 25 118:1, 24

119:1, 10, 16, 20

120:1, 1, 17, 17,

21 121:1, 1

122:1, 1 123:14

124:20, 23 125:1,

14, 14 126:1 130:24

131:1 133:20 136:1,

11, 12 137:1 139:20

147:1, 18, 19 151:1

152:12, 18

153:20, 25 154:1,

1, 14, 18 155:1, 1,

1, 1, 1, 10, 20, 22

159:17 160:1, 12,

21 162:1 165:14, 16

166:1, 15, 17, 17

167:17 168:16, 23

169:1, 1, 19 171:20

172:1, 21, 24

173:1, 10 174:1, 22

175:11, 20 176:16

177:1, 1, 14 183:25

185:23 187:1, 17

188:23 190:1, 1,

17, 22 191:1, 1, 1,

14, 15, 19 194:1

195:11 206:18 207:1

215:19 218:21

219:1, 23 220:17

221:17, 21 224:17

228:1 236:18 237:25

244:18 248:1, 1,

11, 23, 24

249:13, 15, 18

250:11, 15, 25

251:1, 1 252:16,

17, 24, 25 253:1, 1

255:16 256:1, 1,

16, 17, 19 257:1,

11, 15, 17 258:1,

1, 1, 13 259:1, 1

260:1, 1, 1, 1, 11,

19 261:24 266:19

270:1 277:1, 1

280:25 281:1, 1, 10

no2's 150:1

no2/nox 67:14

nobody's 141:24

noi 97:1 136:20,

25 137:1 216:25

noisy 237:19 nominator 241:1 nominators 234:19 non 24:15 107:1
non-attainment

116:10

non-causal 214:1

non-environmental

251:1

non-no/nox 124:21

non-quantitative

54:16

non-supportive 37:1

none 69:1 190:24

nor 39:15 normal 185:1 normals 190:1

northerners 31:22 norway 168:13 notably 172:13

note 4:1 22:14 47:21

103:1

noted 90:10 126:11

183:1

notes 56:13 268:1

nothing 71:19 100:1,

1, 1, 1, 1 154:1

160:25 171:12

259:25 260:1

notice 13:22

176:23 199:18

noticed 3:1 65:1

216:1 220:1

notion 135:22 203:20 notoriously 40:19 nowhere 202:23

nox 23:21 24:15

25:11, 15, 17 28:1,

11 33:10 34:1

50:1 51:19 52:22

53:1, 10, 12, 14,

19 54:1, 1, 22

56:14, 25 67:1,

1, 1, 20 69:12 71:1



72:1, 1 73:15 74:22

76:14, 23 78:17

79:15 82:1, 24

83:1, 12, 18, 19

87:1 89:22 119:1, 1

125:1, 10 126:19

127:22 139:20

142:17 147:1, 10,

23 159:15 162:1

164:10 167:1 181:1,

19, 21 195:17, 21

196:15, 20 203:21

204:1 206:1 224:1

230:1 253:1

272:24 273:1

nox/n0i 67:21

nudging 30:1

nugent 2:1, 15 6:1

30:13 31:1, 1 32:1,

1, 19 33:1 37:19

43:1, 13, 21, 23

49:1 74:1, 10,

13, 17, 19

138:20, 24 283:25

285:11

numerous 37:1 nuts 161:1 nyberg 172:1 nyberg's 168:22

O

o'clock 277:25

283:16, 20 284:1

obfuscated 183:22 oaqps 10:22 109:1 object 78:1 261:1 objective 202:18
occupational 262:1 occupies 97:23 occur 82:11 269:1 occurrence 264:1
occurring 83:1 occurs 44:14 observation 208:1 observational

38:18 39:1 40:14

41:24 45:10

observations 36:1

170:17, 18

obvious 175:23

178:12

obviously 25:22

58:22 79:18 142:1

147:24 157:20

252:20

odd 226:22

odds 168:24 175:19 october 2:1 15:13 offer 244:1 offering 32:24

office 2:17 4:15 6:1

9:20 10:21 12:1,

1 22:19 75:1 106:1,

15 107:1 152:25

153:1, 25 157:13

205:1 210:1, 17

215:16

officer 2:16, 19 officers 71:22 offices 9:19

oh 8:11 16:1, 22

31:20 64:10 98:22

108:14 110:1

111:1 114:1 127:1

138:22 139:13

145:14 172:1 188:15

189:1 192:1, 12

193:21 209:1, 12

228:20 230:11

267:23 270:12

277:1, 10 279:24

283:22 285:1

oil 38:11

okay 12:12 17:1,

1, 25 18:1, 1 30:1,

22 31:1, 12, 20, 22

32:17 33:1 37:16

38:1 39:24 43:1, 24

48:20 49:1, 10

58:19 67:1 69:1,

13, 24 70:10, 13,

21, 25 71:1, 1,

1, 16, 20 72:1,

1, 1, 10, 11, 15,

20, 22 73:1, 1,

1, 1, 1, 15, 16,

22, 25 74:19 76:1

78:1, 1 82:17 84:25

85:11 92:24 93:1, 1

94:1 97:17, 18

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266:20

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22 181:16 184:12,

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14:12 22:1 28:25

32:18, 20, 22 37:20

43:1 49:1 61:11

63:16 108:22 118:15

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134:20, 23 135:22

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213:1, 25 267:15

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238:16, 22, 24

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1, 17 238:25

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60:23 64:1, 1, 23

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74:1, 20 75:18

76:13 77:17 78:1

80:25 85:1, 12 88:1

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109:1 111:1

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126:10 130:23

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109:1 136:1

138:16 142:1 145:23

161:17 170:13

174:14 251:12

256:23

speaker 16:21, 24

17:1, 24 18:1, 1

30:12 37:18, 20

69:1 70:1 73:22

76:1, 1 84:23, 24

110:1 140:1

141:23 142:1, 1

264:1 265:1

276:18 277:1, 24

speakers 2:20 124:18

speaking 43:1

74:10 141:22

227:1 230:1

speaks 61:1 252:15

special 5:1 132:10

134:11 226:14

speciation 53:15

54:1

species 54:1, 23

56:1 57:1, 1 58:1

69:1 70:1 72:12

73:1 83:15 84:1,

1 107:13 160:1

186:21 190:10 191:1

203:22 281:1

specific 14:17 19:18

25:1 37:1 98:13

117:1 124:1, 1,

11 128:1, 14

149:1 157:12

158:1 193:1

199:17 203:1

209:1 216:1, 10, 21

233:23 234:1 235:21

279:1

specifically 13:11

23:1 50:23 94:1

200:15 216:10

217:22 230:1 262:24

281:1

specificity 217:14

spectrum 213:21

217:10 225:25

speizer 5:1

spend 51:14 124:1

spent 210:15

sorry 8:11, 12 16:22

21:1 38:1 64:10

101:22 117:19

121:25 145:14, 18

148:1 152:11 209:12

250:19 256:1

263:13, 14 285:1, 1

sort 9:19 10:11

12:10 20:20 21:1

22:1 29:11 51:1

52:1 56:1 57:23

58:10 64:13 66:12

80:23 82:20, 24

83:1, 23 87:1, 25

88:1, 14, 19, 20

89:1, 18 90:11

106:10 110:1, 12

113:13 119:14 130:1

131:15 138:19

146:1, 1, 12, 16

147:1, 1, 11, 13,

24 148:1, 1, 1

151:1, 21 152:1

153:1, 1 156:1

162:1, 11, 14, 25

166:14, 25 167:1

174:23 175:1 176:20

177:18 182:1 183:21

184:1 191:17, 18

200:21 202:11,

13, 17, 22

203:25, 25

205:13, 16 207:1

208:1, 10 215:20

216:13 217:1

218:17, 24 223:1,

14 224:1, 1

226:1, 17 228:23

229:15 232:22, 25

233:1, 1 235:1,

17 244:21 245:11

246:17 248:1

252:1 255:16, 23

256:1 261:17 264:15

266:20 272:1

sorted 207:13

sorts 55:11

222:17, 19

spikes 269:21 spirit 89:21 spirometry 40:23

41:1

spite 63:1

sound 48:1 141:13

149:1, 1, 18 171:15

225:1

sounds 117:11 164:25

208:12 225:13

source 19:23 51:20

53:1, 23 54:1, 1, 1

80:14 91:1 92:1

97:22 102:16 109:15

110:12 113:1 157:22

192:1 278:25

sources 19:25 44:17,

20 50:23, 25

51:1, 1, 1, 1, 24

52:19, 24 53:1

66:1, 17 69:21 80:1

84:19 86:1, 21

91:1, 1, 13, 16, 18

92:1 99:1 109:16

124:1 147:1, 24

162:10, 15 163:18

281:1

south 31:24

southern 31:19

113:17 154:1

split 65:11 104:1 splitting 143:16 sox 11:12

spoke 30:20 155:1

252:1, 1

spontaneous 265:11

sporia 44:25 spot 186:1, 1 sputum 150:1 squeezed 276:1

staff 2:17 4:15 6:20



9:17 12:1, 11 39:10

44:1 61:1 64:24

212:1, 12 222:11

265:20

stage 13:1 213:1 stalworth 6:20 stand 152:1 standalone 226:1 standard
20:13

23:16, 17 25:1 26:1

38:17 40:1 48:1

50:13 53:21

56:20, 21 58:14

59:1, 1, 12, 23

60:1, 1, 24

61:10, 17, 21

62:11, 12 63:1,

1, 15 76:10 78:23

79:10 86:16

93:14, 16, 17, 19

94:1 100:16

102:21 104:15,

19, 20 105:1, 1, 1,

20 106:1, 1

111:17 112:16

121:12 122:1

123:1 124:20

125:1 129:18 130:1,

12 135:1 141:1

145:1 164:13, 14

165:1 171:16

180:13, 25 181:13

182:18 183:1, 25

197:1, 1, 1

198:1, 1 211:16, 17

212:1, 1 213:1,

13 214:17 215:10

220:12 221:1, 11

224:20 241:1, 11,

25 242:1 248:1, 10,

16 249:14 257:15

258:17 268:21, 22

standardize 174:23

standardized

173:25 174:11

175:19

standardizing

169:1 174:21

standards 4:25

7:10 46:24 56:23

61:1 78:20 106:1

211:1, 14, 19

212:19 224:10, 18

standing 179:21 standpoint 125:23 stands 175:1 197:21 start 10:18 11:11

43:24 54:1 69:1

78:1 100:20 112:1

116:25 126:15,

18, 20 138:1 141:1,

19 149:1 170:1,

14 175:13 178:25

181:1 186:18

196:1 197:1

214:1, 13 268:17

started 16:1 38:1

77:12 78:12 174:1

178:20

starting 13:1 104:24

105:23 112:13

113:21 146:21

148:10 188:18

197:11 229:1

starts 31:24 101:1

284:25

state 177:16

stated 38:21 93:24

107:1 163:1

statement 106:25

175:11 187:1

194:1 223:21

242:20, 24 246:1

261:25 266:24

270:19 282:15 284:1

statements 60:12,

18, 19 241:1, 1

242:1, 1, 10, 12

243:1

states 25:1 46:18

69:1 82:1 127:10,

13 134:21 194:20

195:22 219:1

234:1 276:24

station 66:10 stationary 88:13, 22 statistical 42:1

59:15

statistically

41:20 42:1 206:1

statistician 17:20 statute 234:1 statutory 58:25 stay 256:18

steady 16:1 149:13

steeb 46:1

step 12:1, 1 14:1,

15 18:1 32:22 119:1

126:21 142:25 211:1

236:11 240:10

stepping 6:1

steps 10:17 12:14

15:16 213:1, 23

steubenville 39:17

steve 170:1, 10

186:1 192:12, 13

223:1

steven 208:1 stimulating 101:1 sub 184:11

sub-population

144:13 221:1

sub-populations

144:1 185:1

221:25 223:1

subcommittee 2:24 subdivide 223:14 subgroup 220:20 subgroups 219:22
subject 5:1 11:14

158:22

subjects 237:1 submission 284:1 submit 5:20 148:25

158:12

submitting 43:1

148:23

subsequent 281:19 subsequently 85:25 subset 218:1 substance 100:14

203:1

substantial 62:1

99:20 130:24 169:13

substantially

58:24 252:22



substantiate 170:17

subtraction 76:24 succeeding 146:1 success 61:1 successful 200:16

225:10

successfully 162:22

stole 144:23 stolen 93:1 stones 203:14

stop 25:16 72:21, 21

153:13

stoves 44:18 185:17

suddenly 7:23 116:11

228:20

suffer 134:17 sufficiency 138:11 sufficient 54:1 85:1

97:1 140:25

straight 8:12 strain 186:18 strains 186:19 strange 99:10 strategies
125:12

248:24 250:14

strategy 137:1

158:18 225:10

253:15

stratus 275:23 stray 210:25 street 88:14, 14

281:15

streets 88:12 strem 236:17 strength 34:1, 1

36:1, 23 85:21

178:16 179:1 195:10

203:1 204:12

205:16, 18, 18, 24,

25 207:18 213:18

235:1

strengthen 213:1

219:1

strengthened 36:21

141:1

strengths 26:17

85:16 91:18

stress 222:22

stretch 82:1

stretched 175:10 string 263:15 stringent 248:10, 16 striving 199:15
strong 34:16, 20

35:10, 21 41:12, 17

79:17 105:1

173:20 196:22

205:20, 23 206:1

255:1 262:1 264:1

stronger 40:1 52:1

119:16 120:1 261:15

strongest 238:1

246:19

strongly 21:1

26:23 37:11 48:1

135:1 187:1 235:14

structure 21:16,

25 50:21, 22

52:17 130:12 213:24

struggle 269:17 struggled 19:1 216:1 struggling 201:15 suggest 55:1
60:25

143:16 209:20

251:10 260:10

suggested 28:1 172:1

177:10 223:12

242:16

suggesting 64:25

118:23 224:12

239:21

suggestion 123:18

222:10 225:21 237:1

241:12 244:25 275:1

suggestions 7:1

208:1 266:1 274:15

suggestive 28:1

34:18, 21 36:12, 17

40:1, 1 202:20

235:14 243:22

255:10 259:12

261:1, 23 262:1, 21

263:19, 25 264:25

suggests 104:25 suitable 61:18 suite 45:16, 24

students 92:18

studied 28:18 114:21

studies 13:15, 16,

22 17:23 19:21

20:1, 1, 13, 16,

18, 20, 21, 22 21:1

22:1, 10, 11, 12,

15, 16 25:14, 16,

18, 25 26:1 27:1,

1, 1, 1, 13, 17,

24, 24 28:1, 13,

16, 21, 22 36:1

37:1, 1 38:20 39:1,

16 40:1, 14, 16,

21, 22 41:1, 1,

24 42:1, 1, 1, 1,

12 44:12, 13 45:10,

10, 23 46:1, 12, 22

65:17 69:1 72:11

78:15 84:10 88:17

90:1, 1 91:1

93:20 97:1, 12

101:1, 1 108:15

110:22 111:1, 12,

14, 15 113:16, 16

114:18, 25 116:16

119:13, 14 120:1,

1, 16, 22, 22

122:16, 18 128:1,

1, 1, 11, 16 129:1,

1, 11, 24 141:12,

13 142:1, 19, 21

143:1, 1, 13, 22,

24, 25 144:1, 17

145:1 148:1

149:1, 13, 21,

23, 25 150:11, 16

152:1, 1 153:16,

17, 19, 21 154:1, 1

156:1, 15, 16,

18, 18, 23 157:1,

18 158:1, 1, 21

160:13 162:20, 21

163:13, 14, 23,

25 164:1, 1 165:1

166:1, 1, 12, 16,

24 167:11 168:1,

1 170:20 171:1,

1, 11, 13, 18,



23, 24 172:10, 23

173:1, 1, 1

174:21 175:22 176:1

178:1 179:13, 13

180:1, 10 181:1, 11

182:1, 13, 15,

21, 25 183:1, 1, 1,

10, 11 184:1

185:14, 15, 23

186:11 187:1, 1,

17, 21 189:16 191:1

196:1, 1 199:1,

13 200:14 206:1,

12, 17, 22 207:1,

10, 19 208:1 217:16

218:1, 1 220:1

224:1 240:12 246:12

247:1, 11 251:1, 1,

1, 1, 1 252:1, 1

254:1, 10, 11, 15

255:14, 20 258:1,

21 260:20 264:16

265:1 266:25 267:1,

1, 1 268:20 271:1

273:12 275:22 276:1

277:1 282:1, 1,

1, 10, 12, 13, 23

studying 265:14 stuff 160:25 227:15 sulphate 57:1 sulphur 6:19, 21
summaries 78:1

146:20 266:15 278:1

summarize 3:17 49:20

60:21 106:15 115:21

137:15 138:10

139:15 209:22 210:1

232:22 233:16

267:13 280:12

summarized 13:23

60:17 243:16 274:16

summarizing 13:15

19:20 47:1 277:16

summary 13:1 14:1

21:19 50:16 55:16

60:11, 12 67:20

70:12, 13 83:1

137:19, 23 143:17

144:15 145:1 151:1,

19 209:24 241:14,

22 242:1, 1

243:11 266:1 279:1,

17 280:1, 11

summer 65:14 summertime 47:1 super 190:1 191:1 support 13:13 15:1

34:12 36:14 45:24

59:1 91:1 105:25

106:1 143:1

151:14 166:1, 23

167:11 232:14

233:11, 14

supported 39:15

supporting 6:21

183:18 246:1

supportive 37:1

supports 144:1

240:19

supposed 11:21 138:1

146:24 272:11

sure 10:1 64:20

85:12 103:1

106:16 109:1 112:21

117:21 128:12, 18

134:1 137:23 150:22

157:15 158:10, 16

167:14 169:22

174:16 189:1

190:1 193:21, 23

202:12 203:16 206:1

209:15 211:1 215:12

216:1 221:20

225:1 228:19, 22

234:17 235:1, 1,

12, 13 238:13

241:14 245:14, 15

249:1, 1 263:22

268:14 269:1, 1

270:1, 12, 13

272:21 277:20

284:24

surgeon 204:24

surprised 200:23

226:17

surrogacy 44:15 87:1

88:1 89:24 90:18

92:1 110:1

surrogate 87:1, 1,

17 90:1 139:20,

20 155:23 165:16

166:17 167:16

169:21 172:1 175:17

190:1 198:15

247:1 260:1 266:19

surrounding 95:23 survey 91:1 236:1 survival 263:18 susceptibility 29:15

170:20 179:24 180:1

184:17 185:1 192:25

193:10 220:18

222:1, 14, 17, 21

223:1, 16, 19, 22

224:1, 1, 1

225:23 226:12,

15, 22

susceptible 22:1,

1 29:11, 14 41:1

84:16 127:1, 1,

21 128:15 144:1

180:1, 1 181:16

184:11, 14, 25

194:1, 10, 10, 14

216:1, 16, 25

218:19 219:1

220:1 223:1

226:18 228:19, 21

229:12, 16 230:1,

10, 11, 12 231:1,

16, 22 232:1

suspect 110:11

270:21

sweden 168:13 sweet 139:25 switch 78:19 93:1

115:24

sympathetic 158:19 symptom 120:21 symptoms 27:1 40:1

41:10, 12 47:17

113:20 119:21 196:1

236:24 247:12

260:23

synthesis 148:1 synthesized 152:13 system 96:1 101:1



108:21 121:1 136:1

systematic 46:1,

15 115:1 146:1

157:22 224:1 261:1

systematically

36:1 75:24 86:21

156:1 186:13 193:1

T

table 22:1, 1, 1, 15

32:25 34:10 53:1

92:11 128:16, 16

129:18 173:18,

19, 25 174:1, 1,

1 176:1, 1 180:14

189:10, 10, 15

194:16 196:21

207:19 217:11

229:23 269:1

tables 45:19 70:1,

1, 12, 13 110:1

129:16 152:1 176:21

254:1

tabular 13:14 tabulation 245:1 tackled 84:1

tad 14:1

taking 5:1 38:12

57:14 68:1 122:22

129:14 146:17

152:1, 1 224:1, 1

239:25 270:1

talk 10:1 11:14

51:13, 24 54:1 66:1

70:21 74:1 82:1

105:1, 1 111:1

113:11 156:1 162:24

175:1 177:22

185:1 195:12

209:1 219:17 284:1

talked 5:1 82:17

84:17 104:17 105:18

167:20 168:1

202:1 216:1 223:1

244:20 269:1

talking 52:1 55:20

75:13 79:1 82:1

84:19 91:15 107:1

108:1 117:24 125:21

136:11, 17, 19

141:19, 24 157:16

160:12, 25 168:21

169:1 170:1 176:1

189:1 196:16 222:18

228:1, 19 229:18

230:19 243:18

253:23, 25 254:1

269:23 275:24

talks 80:13 178:16 targeted 199:18 task 50:12 142:16

265:17

team 6:1 15:19 17:11

20:25 29:1 32:11

68:20 239:1

tease 173:10 204:1

247:14

technical 207:1

technically 141:13

149:1, 1, 17

technique 69:1

78:21, 21 115:24

116:1, 1, 1, 10

134:13

techniques 54:14

78:19 79:1, 1

116:17

technology 117:1

ted 49:22 50:1 58:16

60:10 61:1 63:1

64:17 67:1, 1 69:24

71:24 73:24 74:1

86:1 99:1 116:18

118:23 134:1 137:22

162:1 250:1 280:1

ted's 59:1 91:14

tegger 44:22 45:1

48:14

telephone 30:11

141:20

temporal 81:1 82:18,

19, 21, 22 83:1, 17

107:13 109:23

temporally 110:17

137:1

ten 161:1 238:19

239:1

tend 142:22 156:15

163:25 226:15

236:1, 1 237:10

238:16, 25

tended 238:20 255:15

tendency 207:1

275:18, 23

tends 9:1 52:10 tenor 241:24 tension 96:1 tentatively 238:24 term 20:11,
11,

14, 15, 19, 22

26:21 27:21 28:1,

17 35:1, 1, 19

36:10 56:20, 21,

22, 23 66:17

82:10 86:18 88:25

89:1 90:24

104:19, 20 105:1

106:13 109:12, 12

120:1, 1 128:14

151:1 155:1

160:23 188:25

199:1, 1 231:10

238:14 244:1, 1,

1 248:10 260:25

267:19 271:1

terms 14:14 22:19

52:18 56:21, 22

58:1 64:25 65:20

80:18 83:16, 16,

19, 20 95:18, 19

100:21 101:1 105:17

108:12 110:1 111:16

113:14 120:1

125:13, 24 134:16

142:13, 16

146:13, 15

150:16, 20 151:23

157:22 160:1, 20

161:23 165:1

180:10, 16 183:1, 1

187:20 192:19

193:1, 10 194:1, 13

195:18 203:1

204:1 206:11 213:15

214:16 220:1, 13

221:1, 1 223:1, 12,



21, 24 224:1

246:22, 23 260:23

273:16, 24

terrific 114:1

terry 107:1

141:15, 22 145:10

186:1 224:22

251:11, 23 252:11

terry's 149:1

tests 167:1

text 35:13 68:1

152:1 245:16 254:14

255:1, 1

textual 34:10

tha'ts 259:1

thank 4:18 5:1, 1,

15, 23 6:1, 24,

24 7:1 9:11, 13,

23, 25 30:1 32:1,

1, 12, 19 33:1

37:14, 15, 16 38:12

43:1, 1, 1 48:1, 20

49:1, 1 58:15, 16

64:1, 1 66:25 68:13

75:16 80:21 84:21

92:15 102:12, 24

113:10, 12 115:20

124:15 133:17

137:11 138:1

140:1 145:10 152:22

157:14 159:22

161:13, 18 163:1, 1

165:22 190:14 195:1

204:1 207:22, 22

215:22 223:1

232:1 240:15

243:1 266:1

275:11 285:13

thanks 5:1, 19 12:12

30:22 69:17

113:25 122:1

134:1 152:20

222:1 281:25

that'll 113:1

that's 4:13, 19

7:1 9:24 11:23

15:1, 1 16:10 22:18

23:17 29:10 48:24

52:1 53:1 58:1

62:14 66:22 67:15

68:18 70:16

71:20, 21 72:17, 17

75:22 76:20, 25

79:11 80:20 82:1,

23 83:1 84:17 86:22

87:23 89:25 90:11

91:20 92:13, 20, 22

93:1 97:17, 24

98:25 99:1, 24

100:17 101:14

102:10 104:22 106:1

107:10 108:21, 22

113:1 114:1, 23

118:1 121:10 124:16

125:16 126:1 128:21

129:1, 23 130:25

132:1, 10 134:1,

1 135:1 139:17, 17,

21 141:15, 25 142:1

143:20 145:1 148:24

149:17 150:1 152:19

155:13, 23 157:1

158:24 160:16

165:18, 23 166:21

167:16 171:1

174:23, 25

176:11, 19 177:1,

18 179:24 182:10

183:12, 25 184:1,

1, 1, 15 185:10, 23

186:1 187:16, 24

188:20, 21 189:1,

1, 18 191:1, 1

193:1 198:13 199:24

200:16 201:13, 17

202:1, 1 205:19

206:19 207:10, 25

211:19, 20 212:1

213:10 214:18

215:20 218:17

220:14, 19, 25

221:1, 1, 19

222:1 224:21 226:21

229:11 230:24

231:11, 14, 25

233:1, 14 235:10,

17 237:1 240:1

241:1 243:1 244:1

245:1, 21 248:21

252:18 253:12, 16

254:25 255:1, 1, 14

256:20 257:1, 1,

1 258:19 260:11,

18, 24 261:19, 25

262:1 263:1

264:10 265:1

266:1 267:16

269:1 271:1, 19

274:1, 10 275:1, 11

276:1, 10 277:10,

10, 24, 25 279:1,

1, 20 283:15, 25

284:1, 1, 19, 23,

23

thee 129:13 235:16

267:11

thematic 179:20

theme 113:1 126:25

162:14 165:13

themselves 4:12

30:16 94:23 95:16

141:1 248:1

theoretical 87:16

therapeutic 96:10

97:1 108:1

therapeutically

107:23 119:18

there's 3:1 14:11,

17 15:1 18:13

22:1 24:24 27:1, 1,

17 28:13 29:14,

21 46:13 54:25 57:1

59:17 69:19, 20

70:13 71:10

87:12, 14, 19, 19

88:1 90:1, 1, 14,

16 93:11 94:11 95:1

97:1, 13, 25 100:1,

1, 1, 1 103:1 115:1

122:15 124:18 128:1

131:14 135:1 137:21

140:25 142:1 147:1,

14 150:1, 1

151:1, 1, 1

162:14 167:1, 1

168:1 171:11 172:15

180:15 182:13, 14

184:16 188:1 191:1,



25 192:1 200:1,

14 202:21 206:17

207:1, 12, 16

220:15 221:1, 20

222:1, 22 226:1

231:13, 21

235:17, 17

244:11, 21, 22,

22 245:1 252:11

253:1 259:1

260:1, 14 261:15

269:12 276:1

278:14, 23 282:1,

11 284:21

therefore 48:1 114:1

143:24 213:12

thesis 92:19 they'll 179:1 they're 2:25 9:22

28:1 38:1 49:24

52:1 66:23 76:15

77:16 94:1, 1, 1,

10 97:1 146:14, 15,

16 152:1 161:1

169:1 174:12 182:20

187:1 189:13 191:14

193:24 196:1, 11

206:1, 1 222:1

229:1, 1, 1 230:1

232:11 237:15

249:20 253:1

254:1 258:12, 22

259:10, 11

they've 92:19

182:1 191:11, 12

249:18

third 20:1 41:1 43:1

45:14 218:1

thorough 11:22

116:23 168:1

thoroughly 115:17

118:23

thoughts 148:19

209:23

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