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 U.S. ENVIRONMENTAL PROTECTION AGENCY

 + + + + +

 CLEAN AIR SCIENTIFIC ADVISORY COMMITTEE

 CARBON MONOXIDE NAAQS REVIEW PANEL

 + + + + +

 PUBLIC MEETING

 + + + + +

 MONDAY, MARCH 22, 2010

 + + + + +

 The meeting convened, in Salon

ABC of the Marriott Research Triangle Park,

4700 Guardian Drive, Durham, NC, at

8:30 a.m., Joseph Brain, Chair, presiding.

CASAC MEMBERS PRESENT:

JOSEPH BRAIN, Chair

PANEL MEMBERS PRESENT:

PAUL BLANC

THOMAS DAHMS

RUSSELL DICKERSON*

MILAN HAZUCHA

JOEL KAUFMAN*

MICHAEL KLEINMAN

FRANCINE LADEN

ARTHUR PENN

BEATE RITZ*

PAUL ROBERTS

STEPHEN THOM
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SCIENCE ADVISORY BOARD STAFF:

KYNDALL BARRY, Designated Federal Officer

ANTHONY MACIOROWSKI, Deputy Director

*Participating via telephone
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C-O-N-T-E-N-T-S

Call to Order and Opening Remarks 9

 Kyndall Barry

 Designated Federal Official

Opening Remarks 12

 Dr. Anthony Maciorowski

 SAB Office Deputy Director

Opening Remarks 12

 Dr. Joe Brain 

 Chair

Comments 16

 Lydia Wegman

 Director, Health and Environmental

 Impacts Division

 Environmental Protection Agency

 Questions and Answers 22

Presentation on Risk and 26

Exposure Assessment

 Dr. Deidre Murphy 26

 Dr. Stephen Graham 28

Public Comment 112

 John Heuss 112

 Air Improvement Resource, Inc.

REA Charge Questions 119

 Charge Question 1 119

 Dr. Francine Laden 120

 Dr. Arthur Penn 122

 Discussion 123
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C-O-N-T-E-N-T-S (CONTINUED)

 Agency Clarification 153

 Dr. Deidre Murphy 153

 Panel's Response 155

 Charge Question 2 163

 Dr. Russell Dickerson 163

 Dr. Paul Roberts 166

 Agency Clarification 165

 Dr. Stephen Graham 165

 Charge Question 3 167

 Dr. Milan Hazucha 167, 176

 Dr. Stephen Thom 171

 Discussion 178

 Agency Clarification 172

 Dr. Stephen Graham 172

 Ted Johnson 172, 173

 Dr. Deidre Murphy 175
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C-O-N-T-E-N-T-S (CONTINUED)

 Charge Question 4 178

 Dr. Milan Hazucha 178

 Discussion 183

 Agency Clarification 181

 Dr. Stephen Graham 181, 187

 Dr. Deidre Murphy 182

 Ted Johnson 189, 197

 Charge Question 5 205

 Dr. Paul Blanc 205

 Dr. Tom Dahms 207

 Discussion 211

 Agency Clarification 210

 Dr. Stephen Graham 210

 Charge Question 6 211

 Dr. Paul Blanc 211

 Discussion 222

 Agency Clarification 214

 Dr. Stephen Graham 214

 Dr. Deidre Murphy 218

 Ted Johnson 221
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C-O-N-T-E-N-T-S (CONTINUED)

 Charge Question 7 238

 Dr. Paul Blanc 238

 Discussion 243

 Charge Question 8 255

 Dr. Paul Roberts 255

 Discussion 257

 Agency Clarification 257

 Dr. Stephen Graham 257

Policy Assessment 275

 Dr. Deidre Murphy 275, 300, 304

 Dr. Ines Pagan 278, 296, 301

 Dr. Meredith Lassiter 302

 Discussion 279, 306

Policy Assessment Charge Questions 328

 Charge Question 1 329

 Dr. Arthur Penn 329

 Discussion 331
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C-O-N-T-E-N-T-S (CONTINUED)

 Charge Question 2 334

 Dr. Thomas Dahms 334

 Dr. Francine Laden 341

 Dr. Milan Hazucha 342

 Discussion 336

 Charge Question 3 375

 Dr. Thomas Dahms 375

 Dr. Milan Hazucha 378

 Discussion 376

 Charge Question 4 380

 Dr. Joel Kaufman 380

 Dr. Stephen Thom 382

 Dr. Milan Hazucha 382

 Dr. Paul Blanc 384

 Discussion 385

 Charge Question 5 402

 Dr. Thomas Dahms 402, 405

 Agency Clarification 403

 Discussion 406
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C-O-N-T-E-N-T-S (CONTINUED)

 Charge Question 6 420

 Dr. Stephen Thom 420

 Discussion 424
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1 P-R-O-C-E-E-D-I-N-G-S

2 (8:29 a.m.)

3 MS. BARRY: I would like to go

4 ahead and bring everyone to their seats, so we

5 can go ahead and get started with our meeting

6 today.

7 I am Kyndall Barry, the Designated

8 Federal Officer for the Clean Air Scientific

9 Advisory Committee Carbon Monoxide Review

10 Panel.

11 I would like to open this public

12 meeting with a short statement.

13 The CASAC was established under

14 the Clean Air Act as an independent scientific

15 advisory committee to provide advice,

16 information, and recommendations on the

17 scientific and technical aspects of air

18 quality criteria and the NAAQS.

19 The Carbon Monoxide Review Panel

20 is convened under the auspices of the CASAC. 

21 The Panel is meeting to peer review EPA OAR's

22 Risk and Exposure Assessment for Review of the
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1 CO Primary NAAQS Second External Review Draft,

2 and the Policy Assessment for the Review of

3 the Carbon Monoxide NAAQS First External

4 Review Draft.

5 Consistent with the requirements

6 of the Federal Advisory Committee Act, or

7 FACA, and with EPA policy, the deliberations

8 of the Panel are conducted in public at

9 meetings for which advanced public notice is

10 given. FACA also requires that, as DFO, I

11 maintain records of deliberations of the

12 Panel, make publicly available the meeting

13 summaries, and provide opportunities for

14 public comment.

15 During the public comment period

16 scheduled to begin at 9:30 today, we will hear 

17 comments prepared on behalf of the Alliance of

18 Automobile Manufacturers by Mr. John Heuss.

19 The minutes of this meeting are

20 being taken to summarize discussions and

21 action items, in accordance with the

22 requirements under FACA. These minutes will
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1 be certified by the Panel Chair, Dr. Joe

2 Brain. The Panel's draft reports on the peer

3 reviews of the REA and the PA will be

4 forwarded to the chartered CASAC for their

5 consideration and approval at a public

6 teleconference call scheduled for April 19th.

7 I would like to note that the

8 members of this Panel are in compliance with

9 the federal ethics and conflict-of-interest

10 laws that pertain to them. The SAB Staff

11 Office Director, who is the EPA Deputy Ethics

12 Official, has determined that there are no

13 conflicts of interest or appearance of lack of

14 impartiality issues for this review. 

15 Therefore, waivers were not needed or

16 considered for any of the panelists.

17 Thank you for your attention and

18 participation at this meeting.

19 It is now my pleasure to introduce

20 Dr. Anthony Maciorowski, the SAB Office Deputy

21 Director, and Dr. Joe Brain, the Panel Chair,

22 for their opening remarks.
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1 Thank you.

2 DR. MACIOROWSKI: Thanks, Kyndall.

3 My remarks will be very short. We

4 have been here a number of times.

5 Again, I just want to thank Dr.

6 Brain and the members of the Panel for

7 undertaking this important work for the

8 Science Advisory Board and for the agency as

9 a whole. Again, thanks to Lydia and Karen and

10 all the folks from OAQPS who are here to

11 present their findings.

12 So, Dr. Brain.

13 CHAIR BRAIN: I think I can also

14 be brief.

15 Thank you for coming.

16 I think we accomplished a lot at

17 our last meeting. I received a letter from

18 the Administrator thanking us for our work.

19 I also note that, really, out of

20 our first meeting came a new format for

21 communicating to the Administrator. It used

22 to be there was this letter that was 20 pages
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1 long. I think at discussions here we said,

2 why don't we break that into two pieces? Why

3 don't we have a one- or two-page letter to the

4 Administrator that really succinctly gives a

5 macroscopic view of the document and our

6 opinions about it, and then we'l have the

7 answers to the charge questions?

8 So, at subsequent PM meetings, the

9 format that we created has really been

10 adopted, and I think is now becoming kind of

11 standard for the way CASAC operates. I think

12 it works well.

13 So, again, that is our goal today,

14 is to produce a high-level letter about each

15 of the documents in a format that the

16 Administrator can read and understand. That

17 is followed by a consensus view of our answers

18 to the charge questions, which is, then,

19 followed by individual comments where you can

20 be as detailed and specific, and perhaps even

21 disagree, if you wish, with the consensus

22 view.
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1 So, I think we all sort of know

2 what we have to produce. It is a historic

3 day, isn't it? You can remember what you were

4 thinking about CO the morning after the

5 healthcare vote passed in the House. We'll

6 see how we interpret that event in the years

7 ahead. That will be really interesting.

8 So, CO, again, we were having kind

9 of an interesting conversation at breakfast

10 about some of the unusual aspects of CO. It

11 stands out as a pollutant where great progress

12 has been made. It stands out as a pollutant

13 where it is increasingly difficult, or perhaps

14 impossible, some would say, to carry out CO

15 epidemiology studies in the United States. 

16 So, that creates some special problems.

17 At the same time, there are new

18 things. On the way down in the plane, the

19 latest ATS Journal -- did anyone else see

20 this? There's an article in the one that

21 arrived on my desk a few days ago, "Carbon

22 Monoxide Pollution Promotes Cardiac Remodeling
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1 in Ventricular Arrhythmia in Healthy Rats". 

2 So, it clearly has some regulatory

3 significance. Too late to include in this

4 round, but an interesting paper with some

5 interesting mechanistic data and

6 interpretations of the role of CO.

7 Then, there are other directions. 

8 You know, the whole possibility that CO has

9 something to do with climate changes are some

10 new elements that we haven't really thought

11 about very much, which came up last time.

12 But thank you all for coming. I

13 don't know about you, but it is a busy time of

14 year between academia and the rhythms of

15 family life, let alone all the things we have

16 to do for this Committee and for our jobs.

17 So, let's get started. Let's now

18 turn to Lydia, who will kind of bring us up19 to-date on where we are and her vision of

20 where we are in the overall process, and what

21 we have to do to complete our task and give

22 the Administrator as much direction and
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1 information as possible.

2 MS. WEGMAN: Thank you, Joe.

3 Welcome to everybody. Thank you

4 all for coming and for the time you have spent

5 reviewing our documents and offering us

6 comments on them, both in writing and, then,

7 today and tomorrow in person. We very much

8 appreciate the time you have all taken. I

9 know you are all very busy, as Joe says, and

10 the effort you make on our behalf, and on

11 behalf of the American public, is very much

12 appreciated.

13 I want to just go over process a

14 little bit and sort of remind you what the

15 process is for this overall review and where

16 we are in that process.

17 So, you have all seen this slide

18 before, but let's just take a quick look. You

19 have reviewed the Integrated Science

20 Assessment and commented on it. You are now

21 reviewing the Second Draft of the Risk and

22 Exposure Assessment and, also, the Draft
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1 Policy Assessment.

2 As you all know, we are only going

3 to have one draft of the Policy Assessment

4 because of the very tight schedule we have for

5 this review. I will put the schedule up when

6 we get done with this slide. But this review

7 stage is critical, as all of the stages have

8 been.

9 Just going on now to say a little

10 bit more about this process, again, as you

11 probably remember, the Integrated Science

12 Assessment is a synthesis of the policy13 relevant science and is designed to inform the

14 Risk and Exposure Assessment and the evidence15 based considerations for the Policy

16 Assessment.

17 The Risk and Exposure Assessment

18 characterizes the nature, magnitude, and

19 uncertainties of the population estimates of

20 exposure, dose, and risk for the selected

21 health endpoints, and we look at recent air

22 quality conditions, the simulation of just
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1 meeting the current standard, which, as Joe

2 notes, is being met, and the simulation of

3 potential alternative standards under

4 consideration. So, this is designed to inform

5 the Policy Assessment and to help understand

6 the risks associated with exposure to the

7 pollutant.

8 Now we get to the role of the

9 Policy Assessment. This is a critical step

10 that helps us move forward to issuing a

11 proposal. What the Policy Assessment does is

12 link the consideration of the scientific

13 evidence and the risk and exposure-based

14 information, and presents options for

15 consideration.

16 I want to emphasize here that the

17 purpose of the Policy Assessment is to present

18 a range of options. It is to present a range

19 of options concerning the adequacy of the

20 standard and, if we think the current standard

21 is not adequate or may not be adequate, then

22 to look at consideration of alternative
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1 standards that would be appropriate for

2 consideration. This is a pretty big issue in

3 the case of CO.

4 The purpose of this Policy

5 Assessment was to present a range of options

6 to you, one being the possibility of the

7 current standard is, indeed, adequate. But

8 the second being that the current standard is

9 not adequate. And if it is not adequate, what

10 range of options should we be considering?

11 We try to present as broad an

12 array of options as we think is appropriate,

13 in light of the evidence that is presented in

14 the Integrated Science Assessment and the

15 results of the Risk and Exposure Assessment. 

16 We don't want to narrow our options too

17 drastically in this Policy Assessment because

18 our goal is to get your views on what range of

19 options is appropriate. So, we present what

20 we think is reasonable, as reasonable and as

21 broad as we can. So, I just want to make sure

22 that that is understood.
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1 It is not our purpose in this

2 Draft Policy Assessment to narrow our options,

3 but, again, to present as broad a range as we

4 think is reasonably supportable. We, then,

5 get your advice and, with that advice, we will

6 create a Final Policy Assessment.

7 That document will be considered

8 by the Administrator, along with your advice,

9 in deciding what to propose. I should note we

10 typically do propose a range of options,

11 especially when there is a lack of clarity as

12 to what the right path is. So, this is one

13 step along the way to a proposal. It's the

14 Administrator's judgment as to what to

15 propose. It is the quintessential science

16 policy judgment.

17 So, I just want to make sure you

18 all understand that the breadth of options in

19 the Policy Assessment is designed to allow you

20 to give us advice on whether we've got the

21 right range, whether we should narrow it,

22 whether we should broaden it, as we move
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1 forward to give advice to the Administrator,

2 and as you give your advice to the

3 Administrator.

4 Just to go over quickly the

5 schedule, you can see here we have already,

6 thanks to your help and the work of all the

7 folks here today, completed a good deal of

8 this review, but we have some very central

9 steps to continue forward on.

10 So, we are having the review, as I

11 said, of the Second Draft Risk and Exposure

12 Assessment and the Draft Policy Assessment. 

13 The Risk and Exposure Assessment will be

14 issued in its final form on May 28th. That is

15 a court-ordered deadline, so we will

16 definitely make May 28th.

17 We expect to complete the Policy

18 Assessment by early summer of this year, and

19 then move forward quite rapidly to a proposal

20 on October 28th of this year, and a final rule

21 on May 13th of 2011. So, we are moving

22 forward here on the home stretch to try to get
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1 all these critical documents that are needed

2 for the Administrator's consideration before 

3 a proposal done on time.

4 Does anyone have any questions?

5 CHAIR BRAIN: I have a question. 

6 You said several times about the goal is for

7 the EPA in this policy document to give advice

8 to the Administrator and, quote, "your

9 advice", meaning us.

10 MS. WEGMAN: Yes.

11 CHAIR BRAIN: I guess I'm new

12 enough, I still don't quite understand the

13 nature of our advice. Is it to say, "Yes,

14 this is a reasonable suite of alternatives and

15 they are adequately explained?" Or, do we

16 actually have the option of saying, you know,

17 "We really like option B; it makes more sense

18 to us?"

19 Could you elaborate by what is

20 appropriate and what you expect from us in

21 terms of our advice?

22 MS. WEGMAN: Yes, I can. This is
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1 truly a choice that you make as the scientists

2 who are reviewing this evidence and Risk and

3 Exposure Assessment. If you feel that there

4 is one option or a very narrow range of

5 options that the Administrator should

6 consider, it is certainly your role to tell us

7 that. If you think a broader range of options

8 can be supported, or should be considered by

9 the Administrator, you should tell us that. 

10 It is really your judgment, and that is what

11 is most important to us, your judgment on the

12 science and the Risk and Exposure Assessment. 

13 But if you feel one or a very narrow range is

14 appropriate, you certainly can and should tell

15 us that.

16 We have presented a pretty broad

17 range of options in the Policy Assessment,

18 based on our read of the evidence and what we

19 think could be supported. If your view is

20 that the range we have presented is too broad,

21 and that some element of it is, in fact, not

22 well-supported, it is very important for us to
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1 know that.

2 CHAIR BRAIN: Thank you. So, it

3 sounds like the answer is it's really both of

4 those things, to comment on the suite of

5 options, but, also, if we care to, to express

6 our preference for a particular option or

7 options. Right?

8 MS. WEGMAN: Yes. That would be

9 my view.

10 I don't know, Tony, do you have

11 anything else you want to offer?

12 DR. MACIOROWSKI: No, I think

13 that's fine. I think the key here is making

14 sure that you are commenting on the scientific

15 evidence that supports it. That is kind of a

16 nuance sometimes for people who don't -- it is

17 important that the Panel puts its emphasis on

18 the science support for its decisions,

19 whatever that happens to be.

20 I only raise that because those of

21 us who work at government circles have a very

22 clear sense of what science policy and science
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1 is, but sometimes that is not clear to a lot

2 of people.

3 But this is a science advisory

4 committee, and its role is the science support

5 for these options or this option. Within that

6 context, it is perfectly fine to go there.

7 CHAIR BRAIN: This is perhaps,

8 also, adjacent to just one other comment that

9 I will make that came up at the PM meeting

10 that was in this room about two weeks ago. 

11 That was the issue of the charge questions,

12 you know, are really quite elaborate and

13 detailed. I think we all work hard on

14 providing good answers. But a few members

15 said we also need to take a step back, and the

16 existence of the charge question should not

17 prohibit us from making other comments.

18 So, we are not confined to the

19 charge questions. We do want to complete them

20 and we want to provide adequate answers, but

21 there may be other issues that are not covered

22 by the charge questions. There may be other
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1 advice that we want to give. This is also the

2 opportunity to do that as well, whether that

3 advice is a response to a charge question or

4 not.

5 MS. WEGMAN: Yes, that is quite

6 true, yes.

7 CHAIR BRAIN: Okay. Any other

8 questions that anyone else has for Lydia about

9 the background and the schedule?

10 (No response.)

11 It is really quite exciting. So,

12 before the year is out --

13 MS. WEGMAN: It is. It is moving

14 forward very rapidly from our perspective

15 Again, thank you very much for

16 your time and your advice today and tomorrow.

17 I am just going to turn this over

18 now to Dr. Deidre Murphy and Dr. Stephen

19 Graham, who will make the presentation on the

20 Risk and Exposure Assessment.

21 DR. MURPHY: Okay. So, I'm just

22 going to take a couple of minutes at the top
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1 to introduce the team, first of all, to remind

2 you all of who we are.

3 I'm Dr. Deidre Murphy. This is

4 Dr. Stephen Graham, who is the lead for the

5 Risk and Exposure Analysis. We have Dr. Ines

6 Pagan, who is the lead for the Policy

7 Assessment. You will hear more from her in

8 the afternoon. Dr. Pradeep Rajan, who is our

9 epidemiologist on the team, and Dr. Meredith

10 Lassiter, who is sitting in the back, who is

11 our eco person on the secondary standards. 

12 She is the lead on that portion of the Policy

13 Assessment. Dr. Dave McKee, I'm not sure if

14 he is here, but he is a voice of experience. 

15 He's been involved on numerous CO reviews in

16 the past. And you know Lydia and Dr. Karen

17 Martin, who is our group leader.

18 With the next slide, you have seen

19 these words before. Lydia took a moment to

20 discuss differences among the different

21 documents that we create as part of the

22 review.
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1 I will just take a moment, before

2 we launch into the details of this scientific

3 analysis that is the REA, to again delineate

4 some of the differences between the two

5 documents you have in front of you, the REA

6 being a quantitative assessment that is

7 focused on methods, key results, and

8 uncertainties associated with estimating

9 population exposure and dose for a selected

10 set of endpoints and populations.

11 The Policy Assessment, as Lydia

12 emphasized, is our staff analysis of policy

13 options that can reasonably be supported by

14 both the evidence and the quantitative

15 analyses, based on an integration and

16 interpretation of the information in the ISA

17 document and in the REA document.

18 So, with that, I am going to turn

19 it over to Dr. Graham.

20 DR. GRAHAM: Thank you, Deidre.

21 In response to the first draft

22 review, the CASAC Committee provided a number
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1 of comments. Hopefully, we have addressed

2 those in a reasonable manner. I will go

3 through some of the modifications that we made

4 to this particular approach used in the second

5 draft here. I will provide, also, an example

6 of how we use these REA results in the context

7 of the Policy Assessment.

8 Then, I will run through some

9 results, some of which you should be familiar

10 with; they are already in the document. But

11 there were a few additional analyses that I

12 did have some time to collect the necessary

13 data and present those here. You have those

14 slides in front of you as well.

15 Those include information on the

16 COHb estimates. It includes both estimates of

17 single maximum end-of-hour COHb dose levels,

18 as well as multiple days in a year where an

19 individual might experience a maximum end-of20 hour COHb level at or above a given benchmark

21 level, as well as the influence of

22 endogenous CO production on an individual's
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1 maximum end-of-hour COHb dose levels.

2 Then, I will go through some

3 micro-environmental contributions to exposure. 

4 That is something that wasn't included in the

5 document. That is entirely new. But we will

6 include these in the final assessment when we

7 complete that in May and, of course, the

8 uncertainty characterization.

9 So, as I mentioned earlier, in

10 response to the comments that were made, we

11 did make a number of expansions, including the

12 modeling domains themselves. The same two

13 study areas were assessed, but we actually

14 included a number of additional monitors in

15 each location. By using the additional

16 monitors, we have also expanded the number of

17 persons that actually were simulated.

18 There was an increase in the

19 number of micro-environments. Originally, in

20 the first draft it was two. In this

21 assessment, we modeled eight.

22 The at-risk population was also
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1 expanded to not only include the COHb

2 population, but also those that might be

3 undiagnosed.

4 And we included additional air

5 quality scenarios in the first draft we looked

6 at, just in the current standard as well as

7 as-is air quality. In this one, we included

8 three alternatives standards, and I will get

9 to that in a moment.

10 We also implemented the mass

11 balance model for all of the indoor micro12 environments and implemented the commuting

13 algorithm as well as mapping of micro14 environments, which allows for individuals to

15 experience alternative air quality

16 concentrations due to their geographic

17 location within the modeling domain.

18 As a result, this assessment

19 presents an improved representation of the

20 variability in the estimated micro21 environmental concentrations as well as

22 spatial variability in the outdoor
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1 concentrations, because we also implemented an

2 algorithm that adjusts for ambient monitoring

3 concentrations at each of the simulated

4 individual's outdoor concentrations.

5 This slide just presents an

6 overview of the approach, the general

7 approach. Again, we used APEX to simulate

8 population exposures and COHb dose levels. 

9 The study areas were Denver and Los Angeles.

10 As you can see here by these

11 graphs, the blocks are essentially Census12 tracked information. The population density

13 are shaded by the colors. You can see in each

14 location we have essentially captured the

15 urban core of each of these modeling domains.

16 The smaller circles are the air

17 quality radii, or shall I say the radii

18 surrounding the monitor location. Within

19 those radii is where we pulled out the Census

20 tracks for the simulated population.

21 As noted here, Denver had four

22 monitors included in its study area, and Los
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1 Angeles had 10. I just want to note that,

2 also, CO from indoor sources was not modeled

3 in this assessment, even though we understand

4 that it is a contributor to an individual's CO

5 exposure. We are focusing on ambient

6 exposures in this assessment.

7 The simulated population, as I

8 mentioned earlier, was the individuals within

9 10 kilometers of each of these ambient monitor

10 locations within the domains. We included the

11 diagnosed and undiagnosed CHD population. 

12 That is how I will refer to them, and how they

13 are referred to in the document is just the

14 CHD population.

15 The air quality scenarios, as I

16 mentioned, air quality as-is, that is

17 unadjusted 2006 air quality. We also looked

18 at concentrations just meeting the current

19 standard. In this assessment, we looked at

20 historical air quality from 1995 for Denver

21 and 1997 for Los Angeles because that is a

22 time where we actually saw concentrations that
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1 were either close to or very close to just

2 meeting the current standard, the current

3 eight-hour standard, which is 9 ppm or, with

4 a rounding convention, it is 9.4 ppm.

5 Three alternatives were selected

6 for the simulation. We had second-highest

7 eight-hour average, which is the form of the

8 current standard, the current eight-hour

9 standard. We looked at a lower level of 5

10 ppm, and with a rounding convention, that is

11 5.4.

12 We also looked at percentile forms

13 of the standard, one, an eight-hour percentile

14 form, and the other a one-hour percentile

15 form. It is 99th percentile. The eight-hour

16 was 5.0, and the one-hour was 8.0. So,

17 essentially, we adjust air quality to meet

18 that particular metric. Then, that was using

19 that historical air quality. So, we had 2006

20 air quality and 1995 and 1997 air quality used

21 in each of these assessments.

22 And the output, in general, were
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1 the number and percent of individuals exposed

2 at selected levels, as well as these COHb dose

3 benchmark levels.

4 This slide presents how we make

5 this connection between the information that

6 is generated in the REA with its application

7 in the Policy Assessment. Just sort of going

8 through this quickly, for the as-is, as an

9 example, there can be a number of metrics that

10 we can extract from that.

11 So, for example, as-is air quality

12 in Denver, given an eight-hour averaging time,

13 the second-highest concentration is 3.1 ppm,

14 and the 99th percentile daily max for an

15 eight-hour is 2.8. So, we can actually

16 extract out different information using the

17 same air quality data.

18 But at the same time, we can also

19 see that, considering the actual form and the

20 averaging time for the standard, we generate

21 different exposure and dose results for the

22 air quality scenarios, but then have this
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1 related to the different levels within each of

2 these averaging times and forms. You will see

3 some of that later on in the Policy Assessment

4 slides, which I guess you already have a copy

5 of.

6 Is that reasonable? Okay. Are

7 there any questions about this slide? Because

8 I know it is new.

9 The whole point of it is we

10 generate these multiple air quality scenarios. 

11 The results are extracted from it, and then we

12 can relate it to different levels of these

13 different standards. So, we have an idea of

14 what is happening with respect to different

15 levels of a given standard, as far as how many

16 persons might be exposed or how many persons

17 might be at or above a given COHb level.

18 Okay. This is a different

19 presentation than what was presented in the

20 document, but it is essentially based on the

21 tables, the tabular format. I have combined

22 all of the results for the five standard
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1 scenarios.

2 Essentially, you can see on the

3 X-axis we have the maximum end-of-hour COHb

4 dose level. That is actually daily dose

5 level, the maximum end-of-hour for the day. 

6 And on the Y-axis we have the percent of the

7 at-risk population, the CHD population, at or

8 above the given benchmark level.

9 As you can see, there is a

10 significant amount of variability with respect

11 to the percent of persons at a given dose

12 level, given the benchmark that is considered,

13 as well as the air quality scenario. The

14 current standard, obviously, having the

15 highest concentrations with respect to the

16 other air quality scenarios, is going to have

17 the greatest number of persons exposed at or

18 above any given level. That is given by the

19 solid line. And the other alternatives, of

20 course, since they have a lower metric or

21 target design value, they are going to have a

22 lower percent of persons at or above the given
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1 dose levels.

2 That was Denver. This is the

3 results presented for Los Angeles, the same

4 results for all of the five air quality

5 scenarios. As you can see, for most of the

6 benchmarks, the percent of the population at

7 or above a given COHb level is pretty much

8 less than 1 percent for at least the as-is and

9 the alternative air quality scenarios. That

10 is for most of the benchmark levels, if I

11 didn't say that already.

12 CHAIR BRAIN: All the lines have a

13 clear definition, but can you say a little bit

14 more about the as-is air quality, and what is

15 that really?

16 DR. GRAHAM: Yes. As-is air

17 quality was just using the 2006 ambient data

18 for the monitors that were within each of the

19 locations as an input to the model. That was

20 unadjusted. So, that is what we refer to as

21 as-is.

22 CHAIR BRAIN: 2006 and what --
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1 DR. GRAHAM: Yes, it was 2006. 

2 The alternative scenarios used air quality

3 that was adjusted to meet a given target, and

4 the data that were used were the 1995 for

5 Denver and the 1997 for Los Angeles. That is

6 for each of those alternatives, as well as

7 just meeting the current eight-hour standard.

8 CHAIR BRAIN: So, again, it really

9 emphasizes the extent to which we are

10 meeting/beating the current air quality

11 standards?

12 DR. GRAHAM: Right. Right. 

13 Absolutely. In other words, the air quality

14 is a significant driver to a person's maximum

15 end-of-hour COHb level, yes, in the absence of

16 indoor sources.

17 Okay. The next slide has similar

18 results. But, as I mentioned earlier, we are

19 looking at the multiple occurrences. This is

20 not within a given day.

21 The output from the model, the

22 standard output is maximum end-of-hour per
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1 day. I apologize for not having that on this

2 particular slide.

3 Because we are simulating these

4 individuals across an entire year, we are able

5 to collect the data for that entire year, so

6 there can be multiple days where an individual

7 experiences a dose level at or above the

8 selected benchmark.

9 The backdrop here for this

10 particular figure shows the data that you saw

11 earlier on those previous slides. That is,

12 how many occurrences? At least one. How many

13 times? At least one.

14 I'm sorry. The percent of persons

15 that had at least one exposure or COHb dose at

16 or above the given level, that is what is show

17 in the back here. Along this Z-axis, that is

18 where they either had more than one -- so, for

19 example, the next level is the percent of

20 persons that had at least two or more, and it

21 follow the next level would be the percent of

22 persons that had at least three or more.
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1 As I mentioned, or maybe I didn't,

2 this is the as-is air quality. So, you see,

3 there's very few persons, considering the as4 is air quality, that experience a COHb dose

5 level at or above these selected benchmarks,

6 ranging from 1.5 to 2.0. I just want to

7 mention we only talk about the 1.5 and 2.0

8 being benchmarks, but we have data for the

9 values in between.

10 DR. BLANC: Can I just clarify?

11 DR. GRAHAM: Yes.

12 DR. BLANC: In all of these, where

13 you say, "percent of the CHD population,"

14 because you actually estimated the CHD

15 population as a straight percentage of the

16 population, which wasn't modeled to be varying

17 in any kind of way, except randomly, to

18 exposure, isn't that correct? Isn't this also

19 just the percent of the population?

20 DR. GRAHAM: No. We identify in

21 the simulation, we actually do the simulation

22 for the entire modeling domain. Then, we
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1 identify individuals as having the disease

2 based on the disease frequency, the disease

3 prevalence rates.

4 DR. BLANC: But it is just a

5 proportion.

6 CHAIR BRAIN: Can you speak into

7 the microphone?

8 DR. BLANC: I'm sorry.

9 It is just a proportion, isn't it

10 random? You are not presuming that people

11 with CHD actually have -- or maybe I didn't

12 understand. Are you assuming, when you do

13 these percentages of the population with CHD,

14 that it varies in some way other than randomly

15 in terms of the percent of the population?

16 DR. GRAHAM: Yes.

17 DR. BLANC: What is the

18 presumption then?

19 DR. GRAHAM: We actually use both

20 age and gender statistics. So, there is a

21 different prevalence rate associated with

22 individuals between -- I don't have the
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1 breakout in front of me -- but it is 18 to --

2 DR. BLANC: No, I understand that. 

3 Then, what I don't understand is, then, are

4 you assuming in your modeling -- does the

5 percent -- what would be the percent of

6 people, of the whole population? Does it

7 differ much in these percentage calculations? 

8 That is what I can't tell. It is not

9 transparent.

10 Let me say it a different way. If

11 you say 1.5 percent of the population with --

12 I'm sorry. If you say that -- which is it?

13 That is the percent of the population.

14 So, if you say that .4 percent of

15 the population with CHD has two excursions or

16 more at a particular level, would the percent

17 of the population, of the whole population, be

18 much different that varies?

19 DR. MURPHY: It could be. So, let

20 me clarify the why, which is what you are

21 struggling with, if I understand correctly.

22 In the simulations, the prevalence
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1 rate for the disease is, as Stephen mentioned,

2 broken by gender and --

3 DR. BLANC: I understand that. 

4 Right.

5 DR. MURPHY: -- age, which, then,

6 is used in defining our population to be

7 simulated. Once we have defined that

8 population to be simulated by gender and age,

9 that influences various variables about those

10 people, which influences their exposures and

11 which influenced their endogenous COHb rates

12 because it influences their age and gender,

13 which can influence physiological

14 characteristics such as body weight and size

15 and which can influence their activities,

16 which can, therefore, have something to do

17 with what exposures they have, whether they

18 spend time in cars, et cetera, or indoors.

19 So, there are variables associated

20 with the defined simulated population versus

21 the general population that influence COHb

22 levels which differ.
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1 Now do they, is your question? I

2 think we may have analyses -- I am not sure if

3 we have pulled them together -- on a general

4 population versus the subset, which is the

5 simulated at-risk. And to know whether they

6 actually do give us a different answer, I

7 don't know the answer to that, but they could

8 because there are variables which will

9 influence their COHb.

10 DR. GRAHAM: Right. In other

11 words, the population distribution of age and

12 gender for the CHD population is going to be

13 different than the actual population that

14 resides in the defined modeling domain.

15 DR. DAHMS: But the question is,

16 is the CHAD data for the CHD population from

17 their age and gender cohorts?

18 DR. GRAHAM: Are you asking about,

19 is an individual, a CHD person different from

20 a regular person in their activities?

21 DR. DAHMS: Yes.

22 DR. GRAHAM: Well, there was an
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1 analysis done in one of the appendices that

2 compared the data where we had information on

3 individuals that were characterized as having

4 a heart condition versus those that were

5 characterized as being normal.

6 While there were some differences

7 that were statistically significant,

8 essentially, they weren't of great practical

9 significance to suggest that there would be

10 great difference in the activity patterns of

11 those individuals. That is why we utilized,

12 as far as representing the simulated

13 population, we utilized all the CHAD data that

14 we had available to us. We felt that was

15 better than essentially using the limited,

16 extremely limited, number of diaries where we

17 had that information characterized.

18 DR. HAZUCHA: Yes. I find this

19 plot quite illustrative, but I would suggest,

20 if you can add another level for COHb, and it

21 will be 1.4 percent, simply because 9 ppm CO 

22 works out in 1.4 percent COHb level. So, if
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1 you have that level as well in the plot, it

2 will give us some comparison.

3 DR. GRAHAM: Thank you.

4 Are there any further questions? 

5 Or maybe we can discuss that as we get into

6 the meat of this discussion maybe? Okay,

7 great.

8 I almost forgot we were having

9 this presentation. I was thinking for a

10 minute I was the voice of experience. How do

11 I get to achieve that?

12 Anyhow, in comparison to that

13 previous graph, remember, that was using the

14 as-is air quality. And again, if you look at

15 the back of the graph, that is essentially

16 what was presented earlier, when we showed the

17 results for all of the air quality scenarios

18 where an individual experienced at least one

19 COHb, maximum end-of-hour COHb level at or

20 above the given benchmarks.

21 So, as you come forward in the

22 plot, you can see that, with increasing number
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1 of days where you had these occurrences at or

2 above the COHb levels, you have fewer and

3 fewer persons. Most persons, considering just

4 meeting the current standard, most persons do

5 experience -- I don't want to say "only one"

6 -- were estimated to experience one. Again,

7 like I said, fewer or more experienced two or

8 more, and so on, as the graph progresses

9 towards the front.

10 And I also want to make a note,

11 again, when we compare just meeting the

12 current standard, the results there versus the

13 results for as-is air quality, there's a

14 difference in the Y-axis here.

15 What we have here is based on the

16 data that are presented in a tabular format as

17 well in the document, but here as a graphical

18 presentation. I have constructed cumulative

19 density functions here.

20 On the Y-axis we have the

21 percentage of simulated at-risk population at

22 or above -- I'm sorry -- at the COHb level
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1 given. This is based on bins of .25 percent

2 COHb increments, and it progresses all the way

3 up to 4.0.

4 The first dashed line is the

5 endogenous-only. We simulated the population

6 in each of the locations. So, this is Denver. 

7 We simulated the entire population, as we did

8 in the presence of ambient exposure. We just

9 zeroed out the ambient concentrations.

10 So, essentially, what we end up

11 with is the maximum end-of-hour dose levels in

12 the absence of ambient concentration. So,

13 that is, it represents that as a result of the

14 endogenous CO production rate.

15 That is what is depicted here. 

16 You can see the bulk of the population in this

17 first dashed line, the bulk of the population

18 experiences, I think the geometric mean was

19 about .22, and this is the maximum end-of20 hour, but there are a number of persons that

21 experience higher levels, as we might expect

22 and has been shown in some of the literature.
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1 But in the presence of the

2 ambient, of course, since it is an additive,

3 we actually see a higher percent of persons

4 that experience maximum end-of-hour COHb dose

5 levels that are above a given dose level.

6 This first one is ambient plus

7 endogenous exposure. That is the first

8 thinner line. Then, the second line

9 represents the distribution of maximum end-of10 hour COHb dose levels for persons that have,

11 for their endogenous CO production, the

12 contribution from that, as well as the

13 contribution from ambient exposure, ambient

14 that just meets the current standard.

15 The take-home message is that most

16 persons, approximately 95 percent, have that

17 maximum end-of-hour contribution from

18 endogenous of less than 1 percent, but there

19 are a number of individuals that were

20 simulated that did have some COHb contribution

21 from endogenous levels above 1 percent, and

22 that ambient exposure actually contributes a
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1 significant amount to individuals in

2 combination to the endogenous productions,

3 contributes to a significant amount of that

4 COHb, the maximum end-of-hour COHb level dose.

5 DR. BLANC: Can I just ask for

6 clarification --

7 DR. GRAHAM: Yes.

8 DR. BLANC: -- on the simulation

9 of the endogenous CO?

10 DR. GRAHAM: Yes.

11 DR. BLANC: At one point in the

12 document, it seemed to indicate that it was

13 simulated based on 59 individuals with 800,000

14 hours of activity.

15 DR. GRAHAM: Right.

16 DR. BLANC: Did I misunderstand

17 that?

18 DR. GRAHAM: No. This data is

19 based on a 50,000-person simulation and the

20 CHD population extracted from that. So, this

21 is the CHD population that was simulated in

22 each, the full simulated population that was
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1 simulated in each area for the endogenous and

2 comparable to the ambient simulation as well

3 as the current standard.

4 There was an additional analysis

5 that I will get to in a graph that follows

6 that was focused on, it was actually 92

7 individuals. Because of the way that

8 simulation was performed, I will tell you why

9 we did 92 individuals.

10 DR. BLANC: Okay.

11 DR. GRAHAM: But this is the

12 entire population. So, it is synonymous or

13 corresponds to, the endogenous one corresponds

14 to the ambient and just meeting the current

15 standard runs.

16 And these are the results for Los

17 Angeles. You can see there are negligible

18 differences between the endogenous

19 contribution as well as there are, of course,

20 differences. As we saw with the as-is air

21 quality and just meeting the current standard,

22 the Los Angeles, the results for Los Angeles
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1 were lower than that of the Denver as far as

2 the percent of persons at or above the

3 benchmark levels.

4 DR. DAHMS: Excuse me.

5 DR. GRAHAM: Yes.

6 DR. DAHMS: Could I ask for a

7 clarification?

8 DR. GRAHAM: Certainly.

9 DR. DAHMS: The endogenous-only,

10 that is non-parametric, correct? That

11 display, is that how you would characterize

12 that? Is there a median value for that?

13 DR. GRAHAM: Well, we can

14 calculate the median, but this is, I would

15 say, non-parametric because it is binned --

16 DR. DAHMS: Because it looks like

17 the as-is and the current get to be more

18 parametric.

19 DR. GRAHAM: I'm not sure I follow

20 the questioning, but, as I said, these are

21 based on binning between these, you know,

22 whether a person was at or above a COHb level
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1 between zero and .25. So, the percent of the

2 total population at that given level. So, it

3 is essentially, you know --

4 DR. DAHMS: I am just trying to

5 understand what changed the skewedness of the

6 data.

7 DR. GRAHAM: As far as that

8 between Los Angeles and Denver?

9 DR. DAHMS: No, no. They're both

10 the same. Whether it is Denver or Los

11 Angeles, they're both the --

12 DR. GRAHAM: Oh, oh.

13 DR. DAHMS: The descriptive graphs

14 look the same. It looks like the endogenous15 only has less of a tail towards the low end,

16 but then, as you add the as-is and the current

17 standard, all of a sudden, you wind up with

18 more of a symmetrical distribution.

19 DR. GRAHAM: Right. I don't know

20 if I could answer that question at this point,

21 but I can take a closer look at it.

22 DR. BLANC: You know, my guess is
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1 it has to do with the fact that the two are

2 randomly associated with each other. This

3 does not presume that there's any systematic

4 relationship between what your endogenous

5 level is and what your ambient air exposure

6 level is. That may tend to smooth it in this

7 way, when you add them together, and that if

8 you looked at the ambient, absent the

9 endogenous, it may look more skewed, more of

10 a tail, also.

11 I'm just guessing, but I --

12 DR. GRAHAM: Thank you, Dr. Blanc. 

13 I apologize for not recognizing that as being

14 the answer because that is, in fact, the

15 answer.

16 We shouldn't assume that there is

17 a correlation between an individual's

18 endogenous level and their ambient exposure. 

19 They are not correlated. In fact, I have a

20 small discussion in the document about that. 

21 Just because an individual has a high

22 endogenous rate, I mean their exposure is not
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1 necessarily related to that. That would be

2 the result that affects this.

3 CHAIR BRAIN: I have a qualitative

4 confusion. As I look at that, you know,

5 there's not very much difference between the

6 as-is and the current standard. And yet, in

7 an earlier graph for Los Angeles, I remember

8 these lines sort of coming down; there seemed

9 to be a rather dramatic difference between the

10 as-is and the current standard.

11 So, I am having, you know, that

12 came as a surprise, having seen that, that

13 they, then, are so close together.

14 DR. GRAHAM: Right.

15 CHAIR BRAIN: Why am I confused?

16 DR. GRAHAM: Well, I'll tell you

17 why or perhaps I can help confuse you further.

18 (Laughter.)

19 But if we look at this graph, it

20 might be deceiving in that, at the very lowest

21 benchmark that is exhibited here, we see a

22 great difference between just meeting the
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1 current standard --

2 CHAIR BRAIN: Right.

3 DR. GRAHAM: -- but not a whole lot

4 of difference at a higher benchmark level. I

5 mean, essentially, you are less than 1 percent

6 for all of them. I mean it is just a fraction

7 of a percent for the as-is and just meeting

8 the current standard.

9 When we go to those other graphs,

10 I mean you see there, with the 1.5 percent,

11 that is where you are seeing that greatest

12 difference right here. But, of course, you

13 are not going to see much difference between

14 the distribution at the higher benchmark

15 levels. So, that is where you are seeing that

16 difference. It's the same data.

17 Okay. This is the case where,

18 because of the fact that the ambient exposure

19 isn't correlated with any individual's

20 endogenous production, we were interested in,

21 okay, well, we are calculating the maximum

22 end-of-hour COHb dose levels. How much of
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1 that is from an individual's endogenous

2 production rate? It is only a natural

3 question. I believe it was raised at the

4 meeting on the first draft. We said, okay,

5 well, we can actually use the model to answer

6 that question.

7 The earlier graphs, again, showed

8 the maximum end-of-hour, but it wasn't

9 necessarily the relationship between that

10 given hourly concentration. So, we performed

11 a limited simulation where 92 individuals were

12 simulated, because to generate the output, we

13 would have to actually estimate, for output,

14 every single hour for the entire year for all

15 the individuals.

16 It creates a fairly large dataset

17 that requires, again, additional analysis and

18 manipulation. So, there's time and

19 computational resources involved there. So,

20 we had to limit the population to a few

21 individuals.

22 So, we ran the model, generated
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1 the output, the hourly output, every single

2 hour, and said, okay, well, what's the maximum

3 end-of-hour for each of these individuals,

4 just as we did in the earlier analyses. Okay. 

5 Now, at that hour, where we see that maximum

6 COHb level, what is the contribution from

7 endogenous CO production? Okay. Take the

8 difference between the two. Then, we have the

9 total COHb, which is endogenous plus ambient

10 at that given hour for every single individual

11 that was simulated.

12 We've got the ambient

13 concentration or ambient contribution, as well

14 as the endogenous contribution. And that is

15 what is plotted here.

16 The total, which is on the Y-axis,

17 versus the ambient, which is on the X-axis,

18 and you can see, for most of the individuals,

19 and this is, again, 92 individuals, for most

20 of them, the relationship is fairly linear. 

21 That is, the maximum end-of-hour COHb is

22 essentially driven by ambient exposure. But
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1 for a few individuals, as you see here, they

2 have a different endogenous contribution that

3 makes up a greater portion of their total

4 maximum end-of-hour COHb level.

5 But it is as we might expect. If

6 we saw everybody that was on a straight line,

7 then we would be pretty concerned. You can

8 see, of course, that there is variability in

9 that amount of the total contribution as far

10 as the percent.

11 Are there any questions about

12 this?

13 DR. HAZUCHA: Yes. What are those

14 four outliers there? Can you identify it any

15 way? Were they from any at-risk population,

16 let's say anemics or CHD, or it's impossible

17 to do it, the ones which have higher

18 endogenous production of CO?

19 DR. GRAHAM: Right. No, there is

20 a way to do it, but I apologize for not having

21 done that at this point. But these points are

22 actual simulated individuals. There may be
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1 characteristics associated with why they

2 actually have that greater endogenous

3 contribution.

4 But, again, we also have to keep

5 in mind that it is just this single hour. The

6 endogenous contribution likely varies for an

7 individual across that entire simulation

8 period. We will, hopefully, have the time to

9 take a look at that and try to identify some

10 of these characteristics of what might be

11 influencing those influential or points

12 outside that regression.

13 DR. BLANC: But I think the

14 question goes to the heart of what is in your

15 predictive model for endogenous CO, which is

16 in a part of the document, but mostly the

17 appendix deals with it more, I think. It was

18 not entirely transparent, but it didn't seem

19 to me that the model actually took into

20 account disease states that would be outside

21 of a distribution, even a skewed distribution.

22 In other words, I don't think the
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1 model presumes a bimodal distribution with

2 subpopulations which actually had quite

3 elevated endogenous production, because, in

4 fact, your 99th percentile values were

5 considerably below 2 percent

6 carboxyhemoglobin. It was like 1 -- wasn't

7 your upper limit, your extreme limit was 1.4

8 or something or 1.8 or 1.6? I don't remember

9 the --

10 DR. GRAHAM: Right. I think in

11 Los Angeles it might have gone up to 1.6 or

12 1.7.

13 DR. BLANC: Yes. For endogenous?

14 DR. GRAHAM: For endogenous,

15 right.

16 DR. BLANC: But that is, clearly,

17 not consistent with real population data,

18 where there are subpopulations such as people

19 with sickle cell disease. So, how does your

20 model take those conditions into account? I

21 assume it doesn't.

22 DR. GRAHAM: Right. You are
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1 correct in that regard. What we have for

2 endogenous production rate, I looked at some

3 of the comments, and I believe there were

4 comments and questions about one of the tables

5 there where we actually have the CO production

6 rates.

7 I haven't gone through all the

8 papers that were used there, but we know that

9 for a lot of this data there isn't a wealth of

10 data that are available. For a lot of the

11 data, the production rates may, in fact, be

12 for healthy individuals versus not as many for

13 a CHD population. It is an area that was

14 identified in the uncertainty characterization

15 of an area that we still have some improvement

16 to make.

17 If you are suggesting that there

18 are data for a CHD population that can

19 address, say, CO endogenous production rate,

20 then, by all means, we should implement that. 

21 But the other thing that we need to recognize

22 is, how is that -- say there is data from a
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1 limited study where they measured endogenous

2 CO in 20, 100, or so persons. How

3 representative of that population, how do you

4 extrapolate that to the absolute CHD

5 population? I mean that is another

6 uncertainty that gets introduced.

7 In other words, you have it from a

8 limited study group. Is that really

9 representative of the entire CHD population?

10 So, we will have to, again, take

11 that into consideration.

12 DR. BLANC: Well, I guess we can

13 come back to this more in our discussion.

14 DR. GRAHAM: Yes.

15 DR. BLANC: But I think that the

16 first step would be making clearer the

17 presumptions of the endogenous model because

18 I think the endogenous model doesn't reflect

19 a human population. It just doesn't. It's a

20 healthy population of some sort.

21 It is not clear to me all your

22 parameters, but it is parameters which do not
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1 take into account that there are

2 subpopulations that we certainly know from

3 clinical literature whose endogenous CO2, I'm

4 sorry, CO rates are considerably --

5 DR. GRAHAM: Right.

6 DR. BLANC: Like double what you

7 are saying is your upper maximum of normal. 

8 So, something is wrong with the presumption. 

9 It is like you are burying your head in the

10 sand. You are saying, well, we don't have

11 these data, so we are going to assume that

12 this narrow projection that we have is the

13 population, when we know that there are

14 subpopulations which don't behave in that way. 

15 So, there has to be some way of taking that

16 into account in your model.

17 DR. GRAHAM: Right. And like I

18 said, if there is data available, then, if you

19 could assist us in identifying that data, it

20 could be put in the appropriate location, and

21 the simulation can be reperformed. But it

22 doesn't necessarily change the contribution of
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1 ambient on top of that endogenous.

2 So, in a sense, what was done

3 there can, like, for example, you are

4 suggesting that the distribution is altered

5 for endogenous.

6 DR. BLANC: Which is going to

7 shift your --

8 DR. GRAHAM: Right, the entire --

9 right, absolutely.

10 DR. BLANC: Yes.

11 DR. GRAHAM: So, that's fine. But

12 we would need to have that data identified.

13 CHAIR BRAIN: But I guess we do

14 know what percentage of the population has

15 sickle cell or thalassemia. I mean that is

16 what you are thinking, situations like that?

17 DR. BLANC: Yes, and I think there

18 is reason to presume that the population with

19 sickle cell is not normally distributed in Los

20 Angeles, but, in fact, lives in areas of Los

21 Angeles that probably are closer to major

22 roadways and have more ambient pollution
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1 effects.

2 So, the distribution you show

3 here, where it is somewhat random, more or

4 less, between endogenous production and

5 ambient exposure, that presumption, in fact,

6 may not be correct in Los Angeles.

7 DR. MURPHY: Just if I could

8 clarify? So, what we would need, it seems,

9 would be prevalence rate of, for example,

10 sickle cell anemia patients among the CHD

11 population, since we are simulating the CHD

12 population here? And that's what Stephen was

13 responding to, that we would need information

14 on the CHD population and the variability of

15 the different variables influencing COHb.

16 And you all are saying, well, we

17 know something about sickle cell. And that

18 would certainly be informative, but we would

19 need that link, the representation of sickle

20 cell anemia within the CHD population, for

21 example.

22 DR. GRAHAM: Well, if that is what
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1 you are talking about with respect to the CHD

2 population, or is it exclusive of that CHD

3 population? Because, then, that would be a

4 different population that would be simulated. 

5 What is the benchmark level of interest for

6 those individuals? Do we have health

7 information on those?

8 DR. BLANC: I think we can come

9 back to some of it, but there's certain

10 presumptions that one could make, at least in

11 terms of modeling certain scenarios. I mean

12 I think this will come back in the discussion,

13 but there's so much effort that you put into

14 simulating a whole variety of different

15 exposure characteristics, but there's very

16 little on the other side of the at-risk

17 population. That is very disconcerting.

18 DR. GRAHAM: Right. But, again,

19 if we can identify the data that we can use --

20 DR. BLANC: But sometimes it can

21 be driven by presumptions of data, in the same

22 way that one makes other presumptions. I
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1 mean, if you want to be public health

2 protective, because you are making a

3 presumption. The way you do it, you are

4 making a presumption that no one has anemia in

5 the population.

6 DR. GRAHAM: Right.

7 DR. BLANC: I mean presumptions

8 that no one has anemia and is closer to a

9 freeway.

10 DR. GRAHAM: Uh-hum.

11 DR. BLANC: So, you are making

12 presumptions.

13 DR. GRAHAM: Absolutely.

14 DR. BLANC: I'm just concerned

15 that all of the presumptions that are made in

16 that direction are not public health17 protective.

18 DR. GRAHAM: Right. I can agree

19 with that.

20 DR. KAUFMAN:KAUFMAN: Can I ask a

21 different question? Hello.

22 MS. BARRY: Sure. Go ahead. Is
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1 this Joel?

2 DR. KAUFMAN: Yes.

3 MS. BARRY: Thanks. Okay.

4 DR. KAUFMAN: Joel Kaufman.

5 I'm very pleased to see this data

6 developed that actually shows the contribution

7 of the ambient because I think, obviously,

8 that is the kernel that is missing in trying

9 to disentangle the ambient stuff.

10 I want to make sure I am

11 understanding what we are seeing in the

12 figure. Leaving aside the handful of outliers

13 on there, it appears to me -- and I want to

14 hear if I'm seeing this correctly -- that you

15 can essentially model this as a one-to-one,

16 linear, additive relationship here between the

17 ambient plus the total COHb level, whereby

18 almost all, but somewhere between .2 and .4 of

19 the total COHb can be attributed, as it were,

20 to the ambient exposure for all but a handful

21 of outliers. Am I reading this correctly?

22 DR. GRAHAM: Yes, that is correct. 
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1 And if you looked at the earlier graph that

2 showed for the population, for most persons,

3 their maximum end-of-hour COHb level, and that

4 is not just the entire contribution -- again,

5 that is the maximum end-of-hour COHb -- is

6 about .2 to .25, I think.

7 DR. KAUFMAN: It sort of begs this

8 question that you can't model deep down into

9 the total COHb level because there's confusion

10 with that endogenous level. In actuality, if

11 you chose, instead, to do your modeling based

12 on ambient attributable COHb elevation, you

13 could do that, it seems like from this figure,

14 even though it is computationally a more

15 challenging simulation.

16 DR. GRAHAM: That is correct.

17 DR. KAUFMAN: Okay. But you have

18 chosen, as a whole, the team has chosen not to

19 go down that road, is that right? Because all

20 of the document is around total COHb, except

21 for this small number of displays.

22 DR. GRAHAM: Right. That is
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1 correct. That is traditionally what we had

2 done.

3 DR. KAUFMAN: Thank you.

4 DR. HAZUCHA: If I can make

5 another comment and a question as well, as I

6 am looking at it, and you will, let's say,

7 draw an additional line, it will cross the

8 Y-axis, what, approximately at .2 percent

9 COHb?

10 DR. GRAHAM: Right.

11 DR. HAZUCHA: And that intercept,

12 basically, will give you endogenous

13 production, average endogenous production

14 without any effect of ambient air. However,

15 .2, it's low, very low end of normal

16 distribution of endogenous COHb. Generally,

17 the average is about .6. So, I would expect,

18 really, that slope slightly different than

19 what one can draw from this data.

20 DR. GRAHAM: Right. I mean I

21 guess the thing we should recognize is that

22 this is based on a population simulation. 
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1 Much of what you might be referring to is

2 based on limited studies, and I don't know the

3 number that you may be talking about, but it

4 is based on limited studies of a limited

5 number of individuals. I'm not sure of how

6 representative of the simulated population,

7 you know, as far as comparing that data versus

8 this data, I am not sure how well they

9 compare. But it is something that we should

10 take a closer look at.

11 DR. HAZUCHA: Well, just looking

12 at your distributions, for example,

13 distribution plots for endogenous COHb, the

14 mean value, mean and mode, actually, will be

15 very close, both around .5, .6 COHb level.

16 DR. GRAHAM: Right. You're

17 talking about endogenous?

18 DR. DAHMS: The mean

19 carboxyhemoglobin that he showed up here, that

20 bin is between .25 and .50.

21 DR. GRAHAM: Right.

22 DR. DAHMS: And the mean is in the
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1 middle of that.

2 DR. GRAHAM: Right.

3 DR. DAHMS: So, the median value

4 or the mode is probably going to be around .4.

5 DR. GRAHAM: Right.

6 CHAIR BRAIN: So, you are saying

7 it is fairly consistent with the earlier graph

8 then? Or not?

9 DR. DAHMS: Yes. Well, we are

10 probably talking apples and oranges, but --

11 DR. GRAHAM: Right, right. Keep

12 in mind, also, that earlier graph, that

13 distribution is the maximum. That would be

14 the maximum end-of-hour COHb level, rather

15 than just some average of COHb levels,

16 endogenous.

17 DR. DAHMS: But the endogenous is

18 constant.

19 DR. GRAHAM: This is for the

20 operation on an individual.

21 DR. THOM:THOM: But the population

22 is constant.
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1 DR. DAHMS: For whatever it is, it

2 is a constant number throughout your --

3 DR. GRAHAM: Wouldn't there be

4 variability in the population distribution of

5 endogenous contribution to COHb level?

6 DR. THOM: It is not important to

7 this discussion.

8 DR. GRAHAM: Oh.

9 DR. THOM: The issue is, it is how

10 you are defining your parameter, the end-of11 hour. The point is, if one has an endogenous

12 rate of carbon monoxide production, yes,

13 there's a diurnal variability that is quite

14 narrow.

15 DR. GRAHAM: Right.

16 DR. THOM: But it doesn't matter

17 if it is 6:00 a.m. or 7:00 a.m. or 8:00 a.m. 

18 The end-of-hour is sort of a trivial way of

19 defining it. It is just because it is

20 endogenous, that's all.

21 DR. GRAHAM: Okay.

22 DR. BLANC: Well, I mean maybe the
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1 confusion in the readers comes about, if you

2 go to Section 6.4 of the document, I guess

3 that is where you are starting in on this

4 simulation with the roughly 100 individuals.

5 DR. GRAHAM: Right.

6 DR. BLANC: So, in your simulation

7 with 100 individuals, your 50th percentile

8 endogenous CO value is .22 percent, if you go

9 to page 6-20, Section 6 --

10 DR. GRAHAM: Uh-hum.

11 DR. BLANC: So, I think the

12 question was --

13 DR. GRAHAM: Right.

14 DR. BLANC: -- that median value

15 of .22, if that's what you got from your

16 simulation, which is consistent with your

17 intercept here, isn't that consistent with

18 other data? But that is a simulation that has

19 only 100 people in it, albeit it has lots and

20 lots of scenarios of hours, right? I mean it

21 is lots of --

22 DR. GRAHAM: Right, 8,706.
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1 DR. BLANC: But the point that was

2 just made is those hours aren't going to

3 matter much for the endogenous part. They are

4 only going to matter for the other part,

5 right?

6 DR. GRAHAM: Right. Okay.

7 DR. BLANC: So, you have a very

8 seemingly tight distribution of endogenous CO

9 because what drives the variability of CO is

10 not hour-to-hour variation within person. It

11 is between-people variability, which can't be

12 captured when you use 100 people. By force,

13 you are going to have a very narrow

14 distribution of the endogenous CO.

15 DR. GRAHAM: Uh-hum.

16 DR. BLANC: So, somewhere earlier

17 on in the document, and I missed this when I

18 read it, there must be what you are assuming

19 in your population, when you did the whole

20 population simulation, what your median

21 endogenous CO value is.

22 DR. GRAHAM: Yes. As far as the
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1 standard output for that 50,000-person

2 simulation, that isn't a standard output from

3 the model. We wouldn't be able to generate

4 the median value or the mean value for the

5 COHb. We are just selecting at those

6 particular benchmark levels the percent of the

7 population that actually had --

8 DR. BLANC: So, you are assigning

9 it? Or the model presumes it?

10 DR. GRAHAM: Well, we generate it,

11 but as far as output, the output is in summary

12 form for the 50,000-person simulation. So, we

13 are doing the hour, minute-by minute, an

14 individual experiences an exposure. We output

15 the hourly COHb level, but it isn't put in

16 that output file. We just summarize the data.

17 DR. BLANC: Well, do you have some

18 way of double-checking whether your model is

19 working insofar as the endogenous CO is

20 concerned in your big model, not the 96-person

21 simulation? So, that you are convinced that

22 your endogenous numbers are consistent with
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1 what you would expect biologically?

2 In other words, the graphs, two

3 graphs ago when you showed this thing --

4 DR. GRAHAM: Right.

5 DR. BLANC: -- well, we should be

6 able to look at it and see what the median --

7 what's the median on that one? Can you go

8 back two graphs?

9 So, the peak, the mode is --

10 DR. GRAHAM: .4.

11 DR. BLANC: -- .4 in that. I see. 

12 Okay. So, it is probably something like .4.

13 DR. GRAHAM: But, again, this is

14 the maximum end-of-hour, not for all --

15 DR. BLANC: Well, the maximum end16 of-hour for endogenous is going to be --

17 DR. GRAHAM: I've been corrected. 

18 Right.

19 DR. BLANC: Right. It is going to

20 be not very, very much, right?

21 So, does that distribution, Dr.

22 Hazucha, look more like what you would expect?
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1 DR. HAZUCHA: Well, it would. 

2 Because if you look at .2, it is on your

3 lefthand. That would be about .2. So, I

4 expect that it will be close to .4, let's say,

5 or .5.

6 CHAIR BRAIN: I just have a

7 process question. What fraction of all these

8 graphs are in the REA itself?

9 DR. GRAHAM: Most of the graphs

10 are not in the REA. These were additional

11 analyses that were performed. Some of the

12 data are based on tables that are presented in

13 the REA.

14 CHAIR BRAIN: And what is your

15 intention, that they should be folded into a

16 future --

17 DR. GRAHAM: Yes.

18 CHAIR BRAIN: Into the final?

19 DR. GRAHAM: Absolutely.

20 CHAIR BRAIN: So, these are

21 potential graphs that you are likely to add?

22 DR. GRAHAM: Absolutely.
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1 CHAIR BRAIN: So, this discussion

2 is fruitful and appropriate?

3 DR. GRAHAM: Yes. And I think

4 part of the reason why we included it here was

5 for that, so that you could see the data in a

6 new light, in a sense, and hopefully, you can

7 comment on it and help us present the data

8 favorably in the final document.

9 Okay, are we ready to move on?

10 I think this is a good example of

11 there's no particular charge -- well, it

12 overlaps with some specific charge questions.

13 But it seems to me the people involved in this

14 discussion should write something, you know,

15 give us your evaluation, your critique of the

16 problems and potential of these graphs, what's

17 good about them, what's bad about them,

18 because it sounds like they really would be

19 folded into the next --

20 DR. BLANC: Well, then, let me ask

21 you a question, if that is going to be the

22 case. So, if you go back to the graph that
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1 adds them together, back. Yes, this one. And

2 we have a parallel one for Denver.

3 You have a table in the document

4 which was from an earlier analysis, not your

5 current analysis, but your provided analysis

6 that had been done --

7 DR. GRAHAM: The 2000 assessment?

8 DR. BLANC: The 2000 assessment. 

9 In that analysis, there was a table which

10 included the contribution of indoor exposure

11 that wasn't from ambient sources.

12 DR. GRAHAM: Right.

13 DR. BLANC: How hard would it be

14 to provide in this figure what happens when

15 you finally add that in, and what the curve

16 looks like?

17 DR. GRAHAM: Well, by adding that

18 in, I mean that was -- what was done in the

19 2000 assessment, while there are similarities

20 between what was done then and now, it is not

21 necessarily something that we could just

22 easily add.
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1 DR. BLANC: Well, how about

2 generating your own estimate of what the

3 contribution from the indoor environment would

4 be?

5 DR. GRAHAM: Again, much like

6 making adjustments to the physiological

7 parameters that are used in updating those, we

8 would need to have updates to some of those

9 parameters that are used for the indoor source

10 model. It would be, I think, a significant

11 effort. And given the time that we have, to

12 the end of May, I think it is best to just use

13 that data that has already been generated and

14 use a quantitative approach to say, okay,

15 well, based on indoor sources, we see that

16 there is a contribution of "X".

17 DR. BLANC: Well, all right, let

18 me ask the question in a different way then. 

19 Is there some way in which you could do a

20 visual display of those data that would

21 parallel, basically, what you are showing

22 here, which is a useful visualization of how
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1 these things add together? Because that is

2 the piece that is completely lacking in the

3 current document.

4 DR. GRAHAM: Yes, that is great. 

5 I think it is a good idea, but I think in the

6 2000 assessment, the endogenous, there was no

7 estimation of the endogenous contribution.

8 DR. BLANC: I understand that. 

9 So, what would be the downside, bearing in

10 mind the limitations of the data, to simply

11 presuming that the values that were done for

12 the 2000 still applied as a kind of -- you

13 know, it's not any worse than that now.

14 DR. GRAHAM: Right. It is an

15 estimate. But it would have to be fully

16 characterized and qualified.

17 DR. BLANC: Well, okay, but would

18 that be possible to have some illustration

19 that would show that?

20 DR. GRAHAM: Yes, sure.

21 DR. MURPHY: Just if I understand,

22 I want to clarify if we understand. So, you
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1 are just suggesting we have these tables that

2 show the 2000 results? With indoor sources,

3 without indoor sources, you could present

4 those graphically?

5 DR. GRAHAM: And add to it

6 endogenous.

7 DR. MURPHY: But we don't have --

8 DR. BLANC: Well, but do you

9 understand my frustration? There are three

10 main sources of exposure for people --

11 DR. MURPHY: Certainly.

12 DR. BLANC: -- who are not active

13 smokers. There's endogenous. There's air

14 pollution, and there's indoor sources that

15 don't derive from the ambient air. And

16 there's nowhere in this document where all

17 three things are combined. Therefore, the

18 implication of the document is that it doesn't

19 exist. That's the implication.

20 So, from a public health21 protective point of view, what we really care

22 about is, what is an actual human being's
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1 carboxyhemoglobin likely to be, taking their

2 real-world exposures into account? In one

3 place, you have the ambient plus the indoor,

4 but that is from 2000. Somewhere else, you

5 have the endogenous plus the ambient. But

6 nowhere are all three together.

7 But isn't that what we really care

8 about, at a certain level?

9 DR. MURPHY: Right.

10 DR. KAUFMAN: Can I say something

11 here, Paul? Joel, again here.

12 That would be one approach, I

13 agree, and the other approach, which is to

14 really focus like those human controlled

15 exposure studies that we are focused so much

16 on did, was to focus exclusively on the

17 additional impact of the ambient. Right? 

18 Because that is really what the Allred study

19 is about. It is saying we have given them

20 enough CO to add 2 percent carboxyhemoglobin

21 to them. So, they are sort of ignoring what

22 it was in the beginning, but saying this is
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1 what it is going to be at the end. Right?

2 I mean both of those are, that is

3 very artificial, but that is what this has

4 done. But this is the first time we have seen

5 it in this REA, is this figure we have just

6 looked at, where they have subtracted the two

7 things out and modeled, actually, the ambient

8 contribution.

9 It seems like we are not seeing

10 either of the things that we need to see. One

11 is the realistic real-world view of all of the

12 components together, and where that ends up

13 somebody's COHb being, or what we have just

14 begun to see, the actual exclusive ambient

15 contribution.

16 Am I seeing something different

17 than you are, Paul?

18 DR. BLANC: No. I mean, either

19 way, you would get to the same place. The

20 problem is that, as we go forward in the day

21 and we get to the policy considerations, they

22 are driven by making the assumption that no
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1 one has any indoor exposure.

2 DR. KAUFMAN: Right, and that they

3 don't smoke. Right?

4 DR. BLANC: Well, let's leave the

5 smoking aside for right now. But the

6 rationale, I think it is great that there is

7 attention to endogenous production, there has

8 to be, but I think it is great that there is. 

9 Then, I think that the modeling is too

10 conservative, but that is almost a nuance.

11 But without the other piece, it is

12 just not realistic. I think that what was a

13 real problem is when you try to look at, well,

14 what are population distributions for

15 carboxyhemoglobin levels in non-smokers. Of

16 course, they are quite a bit higher than the

17 endogenous value. That is because, if you

18 look at the population, you are including what

19 they are getting from ambient air population,

20 and you are including what they get from

21 indoor air.

22 The data from 2000 were very
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1 convincing that there is a hefty contribution

2 from indoor air, which, again, may not be

3 distributed randomly in relation to what you

4 get from ambient air, and probably isn't

5 distributed randomly, in fact,

6 DR. GRAHAM: Right, and when you

7 refer to indoor air, you mean in the presence

8 of indoor sources?

9 DR. BLANC: Right.

10 DR. GRAHAM: Because we are

11 modeling indoor air.

12 DR. BLANC: No, no. Yes, that's

13 right. I mean the indoor air that is not

14 coming from the outdoors, right.

15 CHAIR BRAIN: Let's figure out how

16 to proceed. I think this is a really useful

17 and important conversation. I guess my

18 question is, do these questions and answers,

19 is it embedded in the charge questions? Or do

20 we need a separate little piece?

21 It sort of sounds like we need a

22 separate piece, and it sounds like Paul and
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1 Tom and Milan and Joel -- because I think

2 these are potentially useful figures, and they

3 are very educational and understandable. So,

4 I think this is important. How should we deal

5 with it? Can we ask the four of you to put

6 some of this down on paper?

7 DR. HAZUCHA: Well, some of these

8 figures are really in the document, not all of

9 them. It would be maybe helpful to have

10 additional figures in the document here.

11 CHAIR BRAIN: Well, I think you

12 are saying that it is probably their intention

13 that some of these figures will be folded into

14 the next --

15 DR. HAZUCHA: So, we can comment

16 probably, once it is in the document, we can

17 comment on the individual --

18 CHAIR BRAIN: Well, I think now is

19 the time, now is the good time to say

20 something about it.

21 So, could we ask the four of you

22 to --
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1 DR. DAHMS: Are all the figures in

2 this packet that you're showing?

3 DR. GRAHAM: Right.

4 DR. DAHMS: So, we have a copy?

5 DR. GRAHAM: Uh-hum, yes.

6 DR. DAHMS: So, if we treat this

7 as an appendix to the document, we can, then,

8 make comment on it? Correct?

9 DR. MURPHY: You can make comment,

10 however you want to treat it, you can make

11 comment on these figures. Because we are

12 presenting them to you to ask for your advice

13 on these figures, with our intent of putting

14 these figures, or some variation on them,

15 based on your advice, into the final document.

16 DR. DAHMS: Okay.

17 DR. GRAHAM: Right. The intent of

18 the figures is, of course, to provide you

19 supplemental information on how the model is

20 performing and what exactly do the results

21 mean. It was in response to your comments on

22 the first draft.
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1 Of course, given all the

2 modifications that were done and additional

3 scenarios, and so on, that were done for this

4 analysis, there was only a limited amount of

5 time to get all of that done, and then include

6 these additional figures. So, they didn't

7 make it into that document. The intent is to

8 have them in the final document. I wanted you

9 to have them, so you can comment on them here.

10 CHAIR BRAIN: Because I think we

11 have come up with a lot of -- you know, I hear

12 issues of internal consistency. I hear issues

13 of, what about susceptible individuals, about

14 indoor air? So, I think there are a number of

15 topics.

16 Paul, perhaps can we ask you to

17 pull them together, if others give you some --

18 DR. BLANC: Well, I think that we

19 should re-ask this question once we discuss

20 the charge questions.

21 CHAIR BRAIN: Okay.

22 DR. BLANC: Because, actually, a
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1 lot of my comments, although I will have to

2 correct some of them because I was really --

3 actually, I'm still confused about how you

4 model the endogenous between the two things. 

5 I think I understand better about why there

6 were 96 individuals in that. I mean I always

7 understood about that, but now I understand

8 that, in addition to that, on your big

9 simulation everybody also had some kind of not

10 simulated, or maybe simulated, CO level also,

11 based on your model of CO. So, that's why the

12 difference.

13 I mean, so those are two different

14 simulations, and I understand that better now. 

15 I somehow didn't understand it, reading the

16 document.

17 DR. GRAHAM: Well, the only

18 difference is not in the actual simulation

19 that was performed. It is just the number of

20 individuals that were extracted from the model

21 and the type of data that were extracted.

22 For the limited analysis, it was
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1 just 100 individuals --

2 DR. BLANC: Right.

3 DR. GRAHAM: -- or 92 individuals

4 that were randomly sampled from that

5 population.

6 DR. BLANC: Right, right.

7 DR. GRAHAM: We had to restrict it

8 to a smaller sample.

9 DR. BLANC: Right, right.

10 DR. GRAHAM: But everything that

11 was done for that simulation was the same that

12 was done in the other simulations. How we

13 estimate the endogenous contribution, how we

14 estimate the ambient, everything else was the

15 same.

16 DR. BLANC: Right.

17 CHAIR BRAIN: So, let's press on. 

18 I mean I think the good news is a lot of this

19 is territory that is covered in some of the

20 charge questions.

21 Let's decide, No. 1, that we will

22 make some comment on these graphs, referring
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1 to this document. So, Tom and Milan and Joel,

2 and everyone else, and Stephen, who had

3 comments about this, and maybe we will ask

4 you, Paul, to pull them together. But let's

5 also do what you have suggested, is revisit it

6 and see how much of this discussion belongs in

7 a comment on these figures, and how much will

8 come up in charge questions.

9 But I think it is clear that this

10 is a potentially important part of the new

11 document that will be next and that we should

12 comment on it, because I think it has been a

13 very useful discussion.

14 Good. Are we nearing the end of

15 the discussion? Do you want to finish it up? 

16 Then, we will take our public comment and get

17 going.

18 DR. GRAHAM: Yes. Right. But I

19 hate to say this is another new figure.

20 (Laughter.)

21 Again, we are interested in

22 understanding where these exposures occur. 
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1 So, as part of the output from the model, we

2 can generate the percent of individuals where

3 they experience a given exposure, what micro4 environment.

5 What I have done is taken the

6 eight micro-environments and aggregated them

7 to five. So, it would make it an easier

8 presentation. And I aggregated them based on

9 the factors that were used to estimate the

10 micro-environmental concentrations.

11 That is what is depicted here in

12 these bar graphs. They all sum to 100 percent

13 for each of the exposure concentration levels.

14 We have got inside vehicles as its

15 own, it was its own micro-environment. It

16 wasn't aggregated with others.

17 We have outdoors, low and high,

18 and indoors, low and high. Those low and high

19 categories are based on the factors that were

20 used, basically.

21 And outdoors means the person

22 experienced the concentration, the exposure
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1 concentration, outside, and indoors means they

2 were inside some micro-environment.

3 And again, along the Y-axis we

4 have the percent of the total time that the

5 population was at or above the given exposure

6 concentrations that are listed here,

7 increasing in concentration across the X-axis.

8 For the first condition, that is

9 essentially all of the persons, the time spent

10 in each of these particular micro11 environments. Of course, we tend to have this

12 spend a lot of time indoors, and that is what

13 is given by this white bar, indoors, low

14 concentration micro-environment.

15 And about 5 or so percent, inside

16 vehicles and outdoors, which is consistent

17 with this particular population. And again,

18 this is the entire simulated population, all

19 adults.

20 Then, as we go along this x-axis,

21 it is the percent of the population that

22 experienced a concentration exposure, a
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1 concentration, in this first instance, it is

2 at or above 3 ppm. You can see quickly a

3 distinct difference between where people

4 actually spend time in the simulation,

5 assuming that there was no exposure.

6 Most persons experienced

7 concentrations at or above 3 ppm inside

8 vehicles. This influence from inside vehicles

9 increases with increasing concentrations. 

10 That is, the bulk of those high-end exposures

11 are associated with in-vehicle exposures.

12 Now there is still a small amount,

13 but relevant amount, of exposure occurring in

14 outdoor or micro-environments, both low- and

15 high-concentration micro-environments, but

16 certainly less than that of the contribution

17 from inside vehicles.

18 This is considering as-is air

19 quality. When we look at the air quality just

20 meeting the current standard in Denver, they

21 are fairly similar, but you could see that, at

22 some of the higher concentrations, you see a
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1 greater contribution from non-indoor sources

2 occurring inside indoor micro-environments.

3 Well, before I go, actually, were

4 there any questions about those particular

5 figures?

6 DR. DAHMS: Are any of these

7 things based on reality?

8 (Laughter.)

9 I mean the high exposures in the

10 cars, are those people that look to be 100

11 percent of the time in cars, are they sleeping

12 in their cars? What are they doing? I don't

13 understand that.

14 DR. GRAHAM: Right. Let me just

15 explain that.

16 CHAIR BRAIN: This doesn't add up

17 to 24 hours. I mean look at the --

18 DR. GRAHAM: Right. No, no.

19 CHAIR BRAIN: It's the vertical

20 axis here.

21 DR. GRAHAM: Right. So, you have

22 a simulation. An individual experiences a
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1 given concentration. This is a collection of

2 that data where they experience -- we draw the

3 line in the sand, like, say, for

4 concentrations at or above 20 ppm, where did

5 they occur? Okay, well, out of the total time

6 that people had concentrations at or above 20

7 ppm, the bulk of it was associated with inside

8 vehicles. It doesn't mean that, oh, well,

9 they spent 90 percent of their time in cars. 

10 No, it's 90 percent of the time that they were

11 in cars at or above 20 ppm.

12 CHAIR BRAIN: In fact, toward the

13 right, I mean the total time might add up to

14 40 minutes, not 24 hours.

15 DR. GRAHAM: Right. Right. And

16 that is probably something that should be

17 included --

18 CHAIR BRAIN: This is only the

19 time that they are exposed above the levels.

20 DR. GRAHAM: Absolutely.

21 DR. DAHMS: Because in terms of

22 trying to understand dose, what makes sense to
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1 me is actual time at a concentration, and not

2 percentage of time. I guess that is where my

3 problem is.

4 DR. GRAHAM: Of course, yes. The

5 dose is going to be related to the time, the

6 duration associated with that exposure level. 

7 But this is telling us, well, where are these

8 high-end exposures occurring? It is not

9 directly linked to, okay, is that linked to

10 the maximum end-of-hour COHb dose level? That

11 is not the intent of the presentation. It is

12 to show where these exposures are occurring

13 and at what level.

14 DR. BLANC: This might be more

15 informative if it also included, you know, 2

16 ppm and 1 ppm, because, basically, what you do

17 is you go from the all to these very high

18 concentrations where it is almost all blacked

19 out because it has to be, by definition,

20 dominantly from vehicular exposure. So, I

21 don't know whether you would see more of a mix

22 at the 2 ppm and 1 ppm, but it might be more
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1 informative. I don't know.

2 CHAIR BRAIN: Yes, I mean that's

3 where most of the population is. We are

4 looking at this extreme case, and on the right

5 we are looking at, what, people with leaky

6 mufflers and things, and holes in the

7 floorboard?

8 (Laughter.)

9 DR. GRAHAM: Well, we know that on

10 road, and associated with on-road exposure

11 concentrations, inside vehicles those

12 concentrations are, of course, going to be

13 higher than ambient contribution. When we

14 factor in infiltration inside indoor micro15 environments, using a mass balanced model,

16 obviously, those are going to be, in general,

17 less than the ambient exposure. So, you

18 wouldn't expect to see a large proportion of

19 the population experiencing concentrations

20 above ambient levels. When you consider as-is

21 air quality, that is why you see very few

22 people at or above 3 ppm because as-is air
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1 quality there's very few points that are above

2 3 ppm.

3 CHAIR BRAIN: Yes, that would be

4 useful to know, what percentage because, I

5 mean, as we move right, we are dealing with

6 tiny fractions, right?

7 DR. GRAHAM: Right. Like you

8 said, this is percent of total of time at or

9 above that concentration. So, there's varying

10 minutes as you move across that X-axis, and

11 that is something that should be included as

12 far as the total minutes that the entire

13 population spent at or above those

14 concentrations. I can include that.

15 DR. HAZUCHA: Would it be possible

16 to develop such histograms for subpopulations

17 that are called CHD subpopulation? They have

18 all been indoors. They usually spend more

19 time indoors.

20 I understand that these are for

21 all individuals, including CHD. Is that

22 correct or --
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1 DR. GRAHAM: This is all persons. 

2 I think that is the way that this data are

3 output. I think to get that data for the CHD

4 population, it would require more than we have

5 time to do --

6 DR. HAZUCHA: Okay.

7 DR. GRAHAM: -- with the recoding

8 of the model.

9 DR. BLANC: Can you also, while

10 you are here, explain something technical

11 about the exposure scenarios? You had a

12 useful table that presented exposure levels at

13 the various, at all eight, or whatever the

14 scenarios. There were several scenarios of

15 indoor --

16 DR. MURPHY: In the slides?

17 DR. BLANC: No, in your --

18 DR. DICKERSON: DICKERSON: Is this

19 connection working?

20 DR. BLANC: In your document

21 somewhere, there was an explanation. I don't

22 know the page number.
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1 MS. BARRY: Yes. Is there someone

2 on the line who is having technical

3 difficulty?

4 DR. DICKERSON: Hi, Kyndall. This

5 is Russ.

6 MS. BARRY: Hi, Russ.

7 DR. DICKERSON: I just wanted to

8 let you know I'm here.

9 MS. BARRY: Thank you.

10 CHAIR BRAIN: Thanks, Russ.

11 In any event, we are in the middle

12 of discussing the new material and some new

13 graphs that we are looking at. We are nearing

14 the end of that.

15 DR. BLANC: Yes, 5-24, it is table

16 5-16 and has the eight scenarios of exposure,

17 and it gives the geometric mean. And then you

18 give some examples of what you include in the

19 micro-environment.

20 So, in one of the indoor

21 environments which is the sort of low indoor

22 environment, which includes healthcare
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1 facilities and schools and churches and then

2 manufacturing facilities, and then you have

3 examples of service station and auto repair,

4 which is the highest.

5 So, in the auto repair, for

6 example, that is high because an auto repair

7 would have more ambient air pollution coming

8 into it from -- it is not treating the cars

9 that are being worked on in the auto repair

10 station as a point source? Conceptually, I

11 just want to understand conceptually since --

12 DR. GRAHAM: Right. Yes, we can

13 go into this in greater detail later, but it

14 is based on the relationship between what is

15 measured at an ambient monitor or an outdoor

16 location, rather -- forgive me -- and what

17 occurs inside. So, it is, essentially, a

18 micro-environmental factor that is used to

19 adjust the outdoor concentration that is

20 estimated from the ambient concentration in

21 each of these micro-environments.

22 DR. BLANC: But it wouldn't be
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1 because an automobile was running in the

2 garage?

3 DR. GRAHAM: No, but it was based

4 on measurement data that they had

5 concentrations where they measured inside

6 these particular micro-environments, and they

7 had concentrations on the outdoor

8 concentration, and they developed this factor

9 based on that.

10 DR. BLANC: Right. But if I had a

11 heater running in the garage, that wouldn't be

12 counted because you don't count indoor sources

13 of air? You wouldn't count an indoor source? 

14 I'm just trying to understand conceptually

15 because this seems to be a bit of a

16 contradiction.

17 DR. GRAHAM: Absolutely.

18 DR. BLANC: So, if it is a

19 vehicle, if it is running indoors, you would

20 count it, but if it was a heater running

21 indoors, you wouldn't count it because that is

22 not an ambient --
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1 DR. GRAHAM: It would be accounted

2 for if it were part of that study, and it

3 would be built into that factor. If you see

4 there's a geometric mean and a distribution,

5 that is there's variability in the

6 relationship between that concentration that

7 was measured inside versus that outside. And

8 it could be due to a particular source,

9 whether it was the motor vehicle or a heater

10 that was present. CHAIR BRAIN: Let's move

11 on and take us through the last two slides,

12 pages 17 and 18. Then, we will return to

13 these issues as needed when we get to the

14 charge questions.

15 DR. GRAHAM: Right. Thank you.

16 So, as was done in the earlier

17 assessment, we used a qualitative assessment

18 approach to characterize the uncertainty. The

19 first step, of course, was to identify sources

20 of uncertainty that may influence the exposure

21 in the dose estimates. Then, we qualitatively

22 ranked the magnitude in direction, that is,
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1 how much it might affect, and why would it be

2 over- or underestimating as far as the impact. 

3 Would it overestimate or underestimate the

4 exposure dose? And, of course, an assessment

5 of the state of the knowledge of that data

6 that we used.

7 So, we identified 14 sources. 

8 There were a number of sources that under

9 certain conditions would exhibit bidirectional

10 influence. That is, there were certain

11 sources that could influence it up or down, as

12 far as the exposure estimates. A few were

13 identified; namely, two were identified as

14 specifically this would contribute to perhaps

15 an underestimate or an overestimate.

16 And the magnitude, of course, also

17 varied depending on the conditions associated

18 with that particular source, and the majority

19 were low, identified as having a low magnitude

20 of influence, but there were several that had

21 between low- and medium-level influence.

22 The knowledge database, we
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1 recognize that there is limited data that are

2 available for a lot of the data that were used

3 in the model, and, also, in performing

4 evaluations, ranging from low to medium as

5 well.

6 In conclusion, we recognize that,

7 given the time that we had to perform this,

8 that this is some of the best estimates of CO

9 exposure for the simulated population that we

10 are trying to represent here, and there were

11 a few that we identified, based on this

12 characterization, that could have potential

13 for improving the characterization.

14 Those are listed here, including

15 the spatial and temporal representation of the

16 ambient and outdoor concentrations, the use of

17 the historical data, which, again, in using

18 the historical data, there may be many

19 approaches that we could use, as I identified

20 in the earlier assessment, but it is very

21 difficult to actually predict what a future

22 hypothetical scenario might be, even though we
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1 can characterize it based on what we know

2 about the current situation, given current and

3 historical air quality.

4 In addition, these others, you

5 know representation of the activity pattern

6 database, and there was some discussion about

7 that in one of the appendices as far as the

8 comparability with normal, so-called normal,

9 individuals and those with CHD, and the

10 representativeness of the longitudinal profile

11 approach that we have here to string together

12 these hourly, or I'm sorry, daily diaries. 

13 The micro-environmental algorithm in the input

14 data that we used, as well as the earlier15 discussed physiological factors that we used

16 to represent the at-risk population.

17 So, with that, I leave it to the

18 Committee to further comment on the document

19 as well as the slides that I provided,

20 including the modifications that were made for

21 this assessment, in response to the questions

22 and comments on the earlier draft, and some of
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1 these additional air quality scenarios that we

2 considered, as well as the new data that were

3 presented at this meeting.

4 Thank you.

5 CHAIR BRAIN: Great. Thank you.

6 Let's now proceed to the public

7 comment.

8 MS. BARRY: Mr. Heuss, are you on

9 the line?

10 MR. HEUSS: Yes, I am.

11 MS. BARRY: Okay. We will now

12 give you your five-minute opportunity to speak

13 with the CO Panel. Your time begins now. 

14 Thank you.

15 MR. HEUSS: Thank you.

16 I am John Heuss with Air

17 Improvement Resource, Incorporated.

18 The second Draft REA is a distinct

19 improvement over the first. By taking into

20 account the spatial variation in CO and

21 several micro-environments, the distribution

22 of COHb exposures is now much more realistic. 
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1 But no comparison is provided to show the

2 substantial reduction in estimated risk.

3 EPA should include a direct

4 comparison for CASAC. For example, comparing

5 tables 6-11 and 6-12 in the second draft with

6 tables 6-22 and 6-23 in the first draft, you

7 can see that CO levels that just meet the

8 current standard, at that level, the

9 percentage of persons with maximum COHb levels

10 at or above 2 percent was reduced by over a

11 factor of ten, for example, from 6.6 percent

12 to 0.5 percent in Los Angeles. We commend EPA

13 for using more realistic assumptions.

14 In addition to the distribution of

15 maximum levels, we applaud the inclusion of

16 the data on person-days. These data are

17 extremely important in evaluating the day-by18 day risk and putting it into a public health

19 perspective. For example, in LA, just meeting

20 the current standard results in only 0.002

21 percent of the person-days in the population

22 of adults with COHb levels at or above 2
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1 percent. In fact, less than .1 percent of

2 person-days are above 1.5 percent. This

3 demonstrates that the current standard is

4 highly protective.

5 Since as-is CO concentrations are

6 now lower than the standard, the risk from

7 current ambient CO is even lower, and that is

8 documented in the REA. In addition, the

9 second draft risk estimates are quite similar

10 to the risk estimates from 2000 for Los

11 Angeles, but somewhat higher for Denver. 

12 Thus, the estimates of risk for a given level

13 of ambient CO have not materially changed

14 since the standard was last reviewed.

15 However, we believe the upper tail

16 of the COHb distribution estimated for Denver

17 in the second draft is too high because one of

18 the four sites is a micro-scale site, located

19 on a traffic island at the intersection of

20 major arterial roads. In both Denver and Los

21 Angeles, we are concerned that the methodology

22 for estimating in-vehicle exposures
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1 overestimates the actual in-vehicle

2 concentrations under adverse meteorology.

3 Since day-to-day emissions are

4 relatively constant, the wide distribution of

5 ambient CO arises due to the differences in

6 dispersion that are driven by variations in

7 meteorology. High ground-level concentrations

8 result from low wind speeds and limited

9 vertical dispersion. However, as Chock

10 documented in detail in 1977, the

11 concentration fields around roadways are also

12 influenced by the mechanical mixing and

13 turbulence generated by the traffic that

14 effectively limits the buildup of CO and other

15 pollutants under adverse ambient meteorology.

16 There is no data indicating that the

17 in-vehicle concentrations in the U.S. now

18 approach the upper end of the ranges used in

19 the model. As you just saw in slide 16, there

20 are times when the model says it is greater

21 than 60 parts per million. There is no data

22 that demonstrates this. Rather than use some
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1 multiplicative method, as EPA does now, we

2 think these data should be in terms of an

3 increment of mass units for in-vehicle.

4 Turning now to the Policy

5 Assessment, we agree that great weight should

6 be placed on the control studies. We urge the

7 staff to add information on the percent-days

8 of COHb from the REA to the various benchmarks

9 in tables 2.5, 2.6, and 2.7. Again, the

10 distribution of person-days of COHb is a more

11 appropriate metric to evaluate the overall

12 public health risk than just the maximum COHb

13 in the air.

14 In November of 2009, we provided

15 comments detailing reasons why the

16 epidemiology summarized in the ISA should be

17 given little weight. First, the pattern of

18 acute associations reported for CO is

19 remarkably similar to that from all the

20 criteria pollutants.

21 Second, multi-city studies report a

22 biologically-implausible wide range in
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1 individual-city associations from strongly

2 positive to strongly negative for each

3 pollutant. With 25 to 40 percent of the

4 associations in various multi-city studies

5 being negative, it is impossible to

6 characterize that data as consistent.

7 Third, with such stochastic

8 variation, relying on any one individual study

9 or a small cluster of studies in a given city

10 is unreliable.

11 Fourth, there is now greater

12 appreciation that model selection uncertainty,

13 publication bias, and issues of surrogacy or

14 confounding limit the interpretation of the

15 published associations as true effects.

16 The arguments in the PA for a more

17 stringent standard at one point rely on

18 cardiovascular hospital admission associations

19 reported in three Atlanta studies. In the one

20 study that reports a significant positive

21 association with CO, the authors do not

22 ascribe that to an effective CO per se, but,
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1 rather, raise the same issues of CO acting as

2 an indicator that are acknowledged in the PA.

3 MS. BARRY: Mr. Heuss?

4 MR. HEUSS: Yes?

5 MS. BARRY: That is five minutes.

6 MR. HEUSS: Thank you. I would just

7 indicate that, based on these considerations

8 and the improved estimates they provide for

9 COHb, we believe the current eight-hour

10 standard is protective.

11 Thank you.

12 MS. BARRY: Thank you.

13 CHAIR BRAIN: Thank you. And if you

14 do want to send us your remarks in writing, we

15 will be glad to add them to the record.

16 MR. HEUSS: Thank you.

17 CHAIR BRAIN: Let's now turn to the

18 REA charge questions. So, everyone should

19 have brought with them, this is the letter

20 dated February 24th, 2010, from Lydia Wegman

21 to Kyndall. So, this will be the sort of

22 guide, and it will also be up there as well.
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1 So, let's now begin with Francine,

2 who will take us through Charge Question 1.

3 DR. BLANC: Can we have a five4 minute break? We have been going since 8:30. 

5 It's 10:30.

6 MS. BARRY: It is scheduled for

7 10:45.

8 DR. BLANC: Well, it is scheduled

9 for 10:45? All right.

10 CHAIR BRAIN: Why don't we at least

11 get one done, and then we will take a break? 

12 But if anybody needs to take an individual

13 break, feel free.

14 DR. LADEN: And from the preliminary

15 comments I have seen, this shouldn't take that

16 long.

17 Okay. So, really briefly, the

18 question was: "Does the Panel find the

19 summary of CO exposure and discussion of

20 ambient CO sources, exposure dose, health

21 effects, and risk characterization approach to

22 be technically-sound, clearly-communicated,
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1 and appropriately-characterized?" This is

2 about Chapter 2.

3 I found this chapter very well4 organized and technically-sound. I thought

5 that EPA did appropriately characterize what

6 they did do. I thought it was also important

7 that they discussed what they did not do. I

8 thought that was well-defended.

9 In terms of there were a little

10 couple of statements in there about, you know,

11 why is it that they are focusing on COHb

12 levels as opposed to the ambient CO

13 measurements, I thought that that was

14 important to describe. And for a lay-reader

15 who is coming into this cold like, why is it

16 that all the analyses are focused on the COHb

17 levels, I thought that was important and well18 done.

19 One concern I had, it is just the

20 fact that most of the Allred data is old. So,

21 there is nothing we can do about that. I just

22 wanted some statement that we are, that EPA is
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1 confident that the current situations can be

2 extrapolated appropriately from what was

3 observed in the past, and just acknowledgment

4 that the data is old, and that this is the

5 best that we have. I don't think it is a

6 problem. I just think it is a statement of

7 acknowledging that uncertainty.

8 I thought that the chapter was

9 clearly-communicated. Just, in general, in

10 terms of reading it, I thought there was some

11 editing that, you know, this is really minor

12 editing that needed to be done. There were

13 some very long sentences. There were a few

14 sentences where there were not complete

15 sentences. And I understand the speed of the

16 time, and I thought that just, particularly

17 when I was reading this chapter and other

18 chapters, I think there was more of it already

19 written previously, that this one just needed

20 a little bit of editing.

21 But that was all I had.

22 CHAIR BRAIN: Arthur, you also
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1 looked at this. Any comments that you want to

2 add?

3 DR. PENN: I had, as I recall,

4 almost no comments on that. Paul had a bunch. 

5 Yes, I thought, overall, that that particular

6 chapter, everything seemed to be well-done and

7 seemed technically-sound. Stylistically,

8 there were some changes that should be made,

9 but that's trivial.

10 CHAIR BRAIN: Anyone else on the

11 Panel want to response to Charge Question 1?

12 (No response.)

13 So, just to make sure we are all

14 oriented, this is --

15 DR. RITZ: Hello this is Beate.

16 CHAIR BRAIN: Yes?

17 DR. RITZ: Yes, I would like to say

18 something. I actually thought that some of

19 the wording could really be improved with

20 respect to the non-COHb potential mechanism. 

21 I totally understand and agree with the choice

22 of the REA using the COHb levels, but in the
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1 wording of why that is happening, it puts a

2 lot of disregard onto other biologic

3 mechanisms and the Epi results. It is not

4 always very clear to me that they are really

5 addressing these are controlled studies and

6 these are the reasons why we are doing it.

7 But the reasons are because we have

8 experimental data for the short-term effects,

9 but we are really not doing a risk assessment

10 for a lot of other types of effects that could

11 be happening at other levels and through other

12 mechanisms.

13 I think there's a convolution that

14 needs to be taken care of.

15 CHAIR BRAIN: Thank you.

16 So, Francine, you are going to pull

17 this together. Is that clear you to?

18 DR. LADEN: Yes. I think it is

19 along the lines of what I was commenting

20 about, about how it is important to have that

21 discussion in there about why the reliance on

22 COHb. As far as I understand what you are
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1 saying, Beate, it is that it needs to be

2 clarified more and maybe expanded a little

3 bit.

4 DR. RITZ: Yes, exactly. I mean

5 right now, to me, it is not clear that a lot

6 of the sentences refer to effects that are due

7 to COHb, and that we actually also have other

8 in-human health effects that may not go

9 through the same mechanism.

10 So, we are kind of making several

11 leaps of faith that what we are doing with the

12 REA is actually addressing most of the bulk of

13 the health effects, but it might not.

14 CHAIR BRAIN: Thank you.

15 Yes, just is there anyone that is

16 missing this letter? I guess, if you need it,

17 raise your hand, and Kyndall can provide you

18 with a copy.

19 But the other thing that I want to

20 point out, which I should have done even

21 before, is the letter actually begins with a

22 detailed list of responses to our previous
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1 comments. So, I think that is very helpful

2 and very much appreciated, and really saves us

3 a lot of time in having you summarize for us

4 what you have done. So, thank you.

5 So, we are now looking at page 1. 

6 Since that went so quickly, let's, actually --

7 yes, Milan?

8 DR. HAZUCHA: Yes, I have a couple

9 of questions --

10 CHAIR BRAIN: Please.

11 DR. HAZUCHA: -- yes, to Charge

12 Question 1.

13 The sources of endogenous carbon

14 monoxide, it is mentioned only hemoglobin as

15 source, metabolism of hemoglobin. Maybe we

16 should mention that there are other sources as

17 well. For example, medication will increase

18 endogenous production or inhalation of

19 dihalomethanes will increase endogenous CO. 

20 So, I think it should be included.

21 Then, on one of the pages, and I

22 guess it is page 2-8, the users of
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1 recreational drugs are considered to be an at2 risk population, if I read it correctly. Now,

3 certainly, they are at risk, but not from

4 ambient carbon monoxide. So, I guess that

5 needs to be clarified, if I understood it

6 correctly. Page 2-8, line 19, I believe.

7 Now, in discussion of Allred

8 studies, the results are presented as percent

9 of change. I guess it is 4.2 percent

10 decreasing time to angina. It would be really

11 very helpful for better understanding where

12 the changes are if, in addition to just

13 relative percentage changes, we also had the

14 true units, like seconds, here. So, we will

15 have the 4.2 percent is comparable, actually,

16 to 22 seconds decrease from close to 9

17 minutes. So, that way, we will get a better

18 perception of what the change is. 4.2

19 percent, it is sort of a number which is

20 difficult to compare to something.

21 In addition, I am glad to have at

22 least some comments there about time to
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1 angina, when it was reduced, was the

2 subsequent times to angina reduced as well? 

3 What was actually the sequelae to initial

4 exposure to carbon monoxide? Was, let's say,

5 in subsequent weeks or months the change was

6 still there or was the frequency of attacks

7 increased, and so on? Maybe there are no

8 data, but if there are no data, then maybe we

9 should say so, that we really don't know

10 without a sequelae of these exposures to

11 carbon monoxide.

12 CHAIR BRAIN: So, you are asking

13 about long-term consequences of these acute --

14 DR. HAZUCHA: Long-term, yes.

15 CHAIR BRAIN: -- exposures, like in

16 the Allred study?

17 DR. HAZUCHA: Yes. Yes.

18 CHAIR BRAIN: Then, I guess we have

19 no idea, do we?

20 DR. HAZUCHA: Well, maybe we should

21 say so, if we have no idea.

22 CHAIR BRAIN: Tom, do you want to
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1 comment on that?

2 DR. DAHMS: Well, this has been a

3 topic of discussion at dinner last night with

4 a bunch of us. It has gone on since these

5 studies were carried out.

6 It is a concern of mine for sure,

7 and probably a lot of us, that this is an

8 adverse health effect. I think that is pretty

9 clear.

10 CHAIR BRAIN: What do you mean by

11 "this is"? The shortening to the time of

12 onset --

13 DR. DAHMS: The shortening of

14 anything that looks like an increase in

15 severity of disease that would logically

16 follow what would happen. Someone with

17 progressive coronary artery disease is going

18 to able to work less and less. Therefore, it

19 is, by transfer of that concept, that this

20 would be looked at as an adverse health

21 effect.

22 CHAIR BRAIN: Myocardial ischemia is
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1 not a good idea?

2 DR. DAHMS: Right. And increasing

3 severity of this is likewise.

4 But whether it has any consequence,

5 I look at the epidemiologic data as one way

6 and one part of the epidemiologic data is

7 getting an answer to that. If there is an

8 increase in cardiovascular admissions to the

9 hospital or ER visits, and I think that is the

10 way I interpret what is in these documents as

11 being, when they say the epidemiologic data is

12 -- I don't know whether substantiates is

13 consistent with whatever these findings. I

14 think that is, without stating it, I think

15 that was my interpretation.

16 I don't know what anybody else's

17 interpretation of those data are, but that is

18 the only way you are going to get an answer to

19 that, Milan. It is only one answer.

20 DR. HAZUCHA: Yes. Well, still, I

21 would like to see a comment that we really do

22 not have data because it will tell us for the
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1 future maybe some additional studies need to

2 be done.

3 CHAIR BRAIN: I guess I am still

4 unclear as to exactly what you are saying. I

5 mean, clearly, susceptibility to increased

6 levels of CO is a bad idea, and myocardial

7 ischemia is a bad idea.

8 But are you also asking whether CO

9 exposure causes a progression of the lesion? 

10 Or I don't quite understand what you are

11 saying.

12 DR. HAZUCHA: What I was asking was

13 this single exposure to carbon monoxide

14 decreased time to angina --

15 CHAIR BRAIN: right.

16 DR. HAZUCHA: -- by 22 seconds out

17 of 9 minutes.

18 CHAIR BRAIN: Right.

19 DR. HAZUCHA: Are there any

20 consequences? Let's say next time, and these

21 people have attacks, some of them --

22 CHAIR BRAIN: Or does that suggest
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1 that you are more susceptible to an

2 arrhythmia?

3 DR. HAZUCHA: Are they susceptible

4 to anything else?

5 CHAIR BRAIN: And I think most

6 people would say yes.

7 DR. HAZUCHA: Are they susceptible

8 to increased frequency of these attacks, and

9 so on, because of that previous exposure to

10 carbon monoxide?

11 CHAIR BRAIN: Well, when you add

12 that, then that seems to go in a different

13 direction.

14 DR. HAZUCHA: Not necessarily.

15 CHAIR BRAIN: Because it seems to me

16 you are, then, saying, does CO cause, you

17 know, heightened --

18 DR. HAZUCHA: Yes, does CO cause an

19 increased frequency, let's say?

20 DR. DAHMS: It gets back to the

21 modeling. So, what number of exposures --

22 let's say that 2 percent was significant in
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1 some way. How many of those exposures do you

2 have to have in a year's time to precipitate

3 some kind of more severe event?

4 I mean, if you are going to limit

5 your exercise performance, and you want to

6 walk to a candy dish, and you've got CO, you

7 are going to walk to the closest one rather

8 than the next one over there. That is what

9 that means, right? You are going to do less

10 work.

11 CHAIR BRAIN: But you are hinting at

12 a cumulative effect of repeated CO exposures.

13 DR. DAHMS: Well, I don't know.

14 CHAIR BRAIN: Well, I don't think we

15 have any evidence for that, do we?

16 DR. DAHMS: We don't.

17 CHAIR BRAIN: No.

18 DR. DAHMS: Milan is right; we have

19 no evidence that --

20 CHAIR BRAIN: We are talking about

21 persistent susceptibility, but not a

22 cumulative effect.
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1 DR. DAHMS: And I don't know what

2 the history of this has been in terms of any

3 kind of a negative adverse health effect is

4 sufficient for the Administrator to --

5 DR. BLANC: I mean, coming back to

6 Beate's comment on the telephone, I think this

7 is the critical flaw in emphasis, which is

8 this is the path you go down if you

9 overemphasize the controlled human exposure

10 study and put blinders onto the convincing

11 epidemiologic data. To do that, I think is a

12 big mistake. I don't want to put words in Dr.

13 Ritz's mouth, but I think that is what she was

14 trying to get at.

15 I think there is a problem --

16 DR. RITZ: Yes, that is exactly what

17 I meant.

18 DR. BLANC: I think there is,

19 actually, a fatal flaw in Chapter 1. I think

20 it will come up in that later discussion. 

21 Since Chapter 1 is kind of a summary, I don't

22 know if the way to go about it is to deal with
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1 it here, but it has to do, in fact, with who

2 is the population at risk.

3 Chapter 1 sets up the rest of the

4 document to narrowly define coronary artery

5 disease and disregard all other cardiac

6 disease as a susceptible population by using

7 language such as other types of cardiovascular

8 disease may also potentially contribute to

9 increased susceptible.

10 I think we went through this with

11 the ISA. We concluded that the data were

12 conclusive that there was a causative

13 relationship between CO exposure and adverse

14 health events in the population with cardiac

15 disease, more broadly defined than coronary

16 artery disease because the epidemiologic data

17 were consistent with congestive failure and

18 with more broadly-defined disease as such.

19 So, the last paragraph on 2-7

20 through the second paragraph on 2-8 I think

21 are completely off-target, and this, of

22 course, is carried through the rest of the
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1 document, which allows the document to have a

2 fairly narrowly-defined population at risk,

3 which, then, gives them very low numbers for

4 the number of people who are overexposed in

5 all of the modeling. I think it is

6 inconsistent with the ISA, and it is why we

7 had so much emphasis and discussion on the

8 endpoints in that document.

9 So, I am not satisfied, actually,

10 with the introductory chapter, for that

11 reason. I mean I talk about it in my charge

12 question because it is where it is dealt with

13 not as an introduction, but more

14 substantively.

15 DR. DAHMS: But it was my

16 understanding that the level of causality was

17 lower, was judged to be lower, and I don't

18 remember the specific words that are used to

19 rank those levels of causality.

20 DR. BLANC: Not by us, is my

21 recollection.

22 DR. KLEINMAN: I think the document
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1 says it is suggestive of a causal effect on

2 morbidity, which is lower than what is likely

3 to be --

4 DR. DAHMS: Which is likely to be

5 suggestive --

6 DR. JOHNS: Likely to be causal. 

7 So, that is the second --

8 DR. DAHMS: Likely to be causal,

9 okay.

10 DR. PENN: Yes, but if you look at

11 the actual reports dealing with congestive

12 heart failure and stroke, and we talked about

13 this in the ISA, the numbers really are better

14 than the conclusions that are drawn here. 

15 They talked about two out of five represent

16 possible changes. It is really four of the

17 five studies that they talked about.

18 In my writeup, I had another

19 extended thing on it. If you look at, for

20 congestive heart failure, stroke, and for

21 coronary artery disease, I think it was

22 figures 5.2 through 5.4 in the ISA, the x-axis
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1 changed dramatically. So, that for coronary

2 artery disease, where I think there were 31

3 studies that were listed, 27 of them showed

4 relative risk increases of less. The relative

5 risk went from 1 to 1.04; whereas, for

6 congestive heart failure and for stroke, they

7 went up over 1.75. In one case, they went up

8 to almost to 3.

9 So, the sense that you get from

10 looking at the data is that things weren't

11 balanced equally. So, if all of the data were

12 presented for each of the three sets, if for

13 the three sets of data all of the graphs were

14 presented with the same axes, I think you

15 would see that the epidemiology data really

16 speak very strongly to the fact that there are

17 causal relationships between CO exposure and

18 stroke, and ischemic stroke, and CO exposure

19 and congestive heart failure, that tend to be

20 really minimized in this writeup.

21 DR. KLEINMAN: But I think the point

22 that they make in the document is that there
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1 are other factors that make it more difficult

2 to pinpoint CO. There are other confounding

3 things, other things that are associated with

4 CO that make it difficult to use the

5 epidemiology to have a dose/response

6 relationship. Therefore, the controlled human

7 exposure work, where all you have is CO, they

8 have a nice, clean dose response curve that

9 they, then, apply to their models.

10 So, I think we have to separate the

11 concept of the short-term exposures being used

12 as a way or a tool to develop a dose/response

13 relationship that we can, then, use to set a 

14 standard, as opposed to the epidemiology,

15 which gives very good evidence that there is

16 something going on that is associated with CO,

17 but can you really put the number, you know,

18 the CO number that would be related to that

19 effect? That may be more difficult. But I

20 think that it is clear that there is a long21 term consequence of chronic CO exposure, based

22 on the epidemiology.
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1 CHAIR BRAIN: So, I think this is

2 really important. I think it is clear from

3 our discussion of the ISA that everybody

4 wanted to broaden the definition of

5 susceptibility beyond angina, and that all

6 these other underlying cardiovascular

7 conditions were really important.

8 I guess this now really becomes more

9 critical when we move to the REA, where we

10 want to make some quantitative risk

11 assessments, which are all saying, is that

12 concern and the data that generates that

13 concern, good enough that it should really be

14 part of the REA?

15 What's your summary sort of,

16 Francine? Is it included adequately in

17 this --

18 DR. LADEN: I think that the way

19 Michael put it is really important. I mean

20 I'm not trying to discount the epidemiology at

21 all. I think it is very crucial to show the

22 importance of doing this, and trying to figure
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1 out what the risks are for the susceptible

2 populations, but I think there's a lot of

3 limitations for what we can do with the

4 epidemiology in figuring out a number to use

5 in the Risk Assessment because of the

6 confounders and the interpollutant

7 concentrations.

8 What I just want to say is that I

9 think that, given all that, I'm not saying it

10 is impossible, but the decision was made to

11 use the COHb data and the controlled

12 experiments to use for the REA. So, I think

13 expanding the discussion of that decision, and

14 of what the epidemiology can mean in terms of

15 putting it in context and the importance of

16 the chronic exposures, and what is in

17 persistence, it shouldn't be ignored, but I

18 don't think -- so, I think that those

19 limitations need to be acknowledged, but I

20 think that it still makes sense what it was

21 that was done.

22 CHAIR BRAIN: I guess I am also
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1 hearing that this topic, this concern, really

2 ought to achieve its full flower in the Policy

3 Assessment, right?

4 DR. BLANC: But, Joe, the Policy

5 Assessment is driven by the tables which show

6 how many people are being exposed. And in

7 fact, to define the population at risk more

8 broadly has nothing to do with whether or not

9 they used the ppm exposure response data from

10 the human exposures.

11 What it has to do with is, how do

12 you define population at risk? Everybody

13 agrees that the data from the human exposure

14 is convincing, that there's a physiologic

15 response. Because the experiment was done in

16 patients with ischemic heart disease with an

17 ischemia outcome is one thing, but to say that

18 that has no bearance at all or no connection

19 to epidemiologic data, which convincingly

20 shows that you see the effect not only in

21 people with narrowly-defined ischemic heart

22 disease, but, also, with hospitalizations and
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1 morbidity in other more broadly-defined at2 risk cardiovascular disease is not to, then,

3 say, but there must be some different

4 biological mechanism.

5 I think it is the presumption, the

6 public health protective reasonable

7 presumption is that it is a continuum, and the

8 word "continuum" was used in the document.

9 So, the question is, what is the --

10 it has nothing to do really with -- no one

11 here is suggesting throw out the

12 carboxyhemoglobin-driven exposure methods that

13 are used. The only question is, what is your

14 number that you are going to use for the

15 percent of the population which is at risk?

16 I am going to come back to this in

17 my own comments, but they spent all of this

18 energy on very sophisticated modeling, which

19 is great in terms of exposure, and then, take

20 very simplistic, very crude, and very, I

21 think, overly-narrowly-defined scenarios for

22 what the population at risk is.
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1 Now you can do more than one

2 scenario, the same way that they say, what is

3 it at the current standard? What would it be

4 "as is?" What is it with the 99th percentile? 

5 There are easy ways of doing the estimates

6 that they do of how many people are exposed. 

7 Under one presumption, let's presume we define

8 it narrowly as coronary artery disease only,

9 and let's use National Health Interview Survey

10 self-report as the way we derive that, versus

11 more broadly-defined cardiac disease. That is

12 all I am saying.

13 CHAIR BRAIN: I think that makes a

14 lot of sense, right, and particularly in terms

15 of the pathogenesis. I mean, if you are

16 talking congestive heart failure or

17 susceptibility to arrhythmia, I mean there's

18 no reason not to think that the same

19 mechanisms of oxygen delivery apply -- I mean

20 stroke is maybe a different matter. I don't

21 quite see the same link of susceptibility to

22 stroke.
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1 DR. BLANC: Dr. Ritz, are you still

2 on the phone?

3 DR. RITZ: Yes.

4 DR. BLANC: I mean, maybe, since 

5 you were a secondary on this charge question,

6 and I certainly wasn't, I mean, if you think

7 this is consistent with what you were trying

8 to say, maybe you could --

9 DR. RITZ: It is consistent with

10 part of what I was saying. It is consistent

11 with, well, we are using certain models in

12 chambers studies of diseases because that is

13 ethical to do and possible. We are not

14 looking at other types of diseases because it

15 is just not possible. We are not going to put

16 pregnant women into those chambers, right?

17 So, I think that gets lost in that

18 document. I think the non-COHb-related

19 mechanisms are what has more recently been

20 discussed in the newer literature. That comes

21 back to Francine Laden's comment that all of

22 the COHb literature is fairly old. But that
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1 is okay because it is valid, certainly.

2 But we have some things that maybe

3 there's actually additional biological

4 mechanisms to be taken care of. Maybe the

5 COHb threshold or levels that we are dealing

6 with are also not very accurate. We are just

7 guessing that that's the relevant number that

8 we should use for a risk assessment.

9 So, we are making a lot of

10 assumptions that do not include either a

11 larger susceptible population or maybe even a

12 lower threshold for biologic mechanisms that

13 are not related to COHb.

14 DR. KLEINMAN: I guess when we come

15 to the Policy Assessment, I think a lot more

16 is said about those factors because that

17 really provides the rationale for the

18 alternative standards that are brought up.

19 DR. RITZ: I agree.

20 DR. KLEINMAN: So, there may be some

21 way of taking some of the information,

22 especially the way it has been interpreted in
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1 the policy analysis, and moving some of that

2 or duplicating some of that in the Risk

3 Assessment as a defined paragraph or something

4 that would give it a little bit more structure

5 and attend to this.

6 CHAIR BRAIN: Okay. Well, I think

7 this is going to come up repeatedly. I think

8 we are going to return to this first chapter. 

9 It seems to me this is also kind of at the

10 level where our view on this topic belongs in

11 the two-page letter to the Administrator.

12 So, why don't we move on, unless

13 anybody has a specific comment?

14 Milan, you have something you want

15 to --

16 DR. HAZUCHA: Yes, I have a specific

17 comment, actually. Many of you found, we

18 already saw this Special Report No. 17

19 published in January, 400 pages, by a special

20 panel of experts. It is entitled, "Traffic21 Related Air Pollution: a Critical Reading of

22 the Literature on Emissions, Exposure, and
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1 Health Effects".

2 What is surprising in this document

3 is that carbon monoxide is considered simply

4 as a surrogate for traffic-related air

5 pollution, primarily for PM. Basically, there

6 is barely any discussion on the health effects

7 of carbon monoxide.

8 I am sort of inclined to believe,

9 and I recall the data from epidemiologic

10 studies, ISA, which we discussed earlier, that

11 the concentrations of carbon monoxide which

12 are presented in these studies will,

13 essentially, result in normal, almost normal

14 range of carboxyhemoglobin levels in blood.

15 So, it appears like that, indeed,

16 carbon monoxide here is more like a surrogate

17 for other pollutants than actually the

18 effective agent itself.

19 CHAIR BRAIN: So, how does that --

20 so, you are accepting the conclusions of this

21 HEI summary? And you are saying -- or how

22 does that affect what we say about the --
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1 DR. HAZUCHA: Basically, yes, that

2 carbon monoxide, despite the data presented

3 that there is an increased risk associated

4 with carbon monoxide, that probably just

5 reflects sort of a different pollutant, most

6 likely PM or other pollutants and nitrogen

7 dioxide or a combination of those, but not

8 necessarily just carbon monoxide itself

9 because it acts as a surrogate.

10 DR. BLANC: But the epidemiologic

11 literature argued against that because the ISA

12 takes into quite heavy consideration the

13 studies which adjusted for co-pollutants and

14 didn't adjust for co-pollutants. So, in fact, 

15 the data were surprisingly convincing,

16 adjusting or taking into account the measured

17 co-pollutants and arguing against that

18 interpretation. In fact, studies which did

19 not measure co-pollutants were basically

20 thrown out of the mix or taken out of the mix.

21 CHAIR BRAIN: I guess the other

22 comment, Milan, is you are really discussing
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1 in that report, the study discusses the as-is

2 levels. You know, what are the current levels

3 of CO? But the report we are talking about is

4 focusing on the CO standard and what do we

5 know about health effects at that level and

6 around it. Just because we are now way below

7 that doesn't mitigate our responsibility for

8 trying to make an accurate assessment of what

9 might be happening at the CO standard, right,

10 and alternative standards?

11 DR. HAZUCHA: Yes, we certainly

12 should consider it, but, as I said, I am more

13 suspect, after reading this report here, I am

14 more suspect that it is not the effect of CO;

15 it is the effect of other pollutants which we

16 see.

17 CHAIR BRAIN: But most of those

18 studies are at lower levels of CO than the

19 current standard.

20 DR. HAZUCHA: Yes.

21 CHAIR BRAIN: Tom?

22 DR. DAHMS: Some guidance from Dr.
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1 Ritz, we have talked about asking to have

2 additional numbers of at-risk people from

3 cardiovascular disease. Would you add

4 pregnant women to the at-risk pool?

5 CHAIR BRAIN: Or their fetuses?

6 DR. RITZ: What's the question?

7 DR. DAHMS: Well, we are trying to

8 figure out, I am trying to figure out, if you

9 were going to ask the EPA to increase the

10 number of people potentially at risk for CO

11 exposure, would you add fetuses to that list?

12 DR. RITZ: Yes, I would.

13 CHAIR BRAIN: Okay. I think, why

14 don't we take a break? Russell, you will be

15 here after the break? You are available? You

16 are the lead discussant for the next charge

17 question.

18 DR. DICKERSON: Okay. Did I

19 successfully unmute?

20 CHAIR BRAIN: Yes. Yes, thank you. 

21 Yes, we heard you.

22 So, it is now about almost five of
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1 11:00. Let's return at 10 after 11:00, and we

2 will begin with Charge Question 2.

3 Kyndall has a comment. What?

4 MS. BARRY: My watch shows 10:50.

5 CHAIR BRAIN: Well, somewhere in

6 between.

7 MS. BARRY: Okay. So 10 minutes?

8 CHAIR BRAIN: Yes. Let's be back

9 between five and ten after, and we will resume

10 with Russell.

11 (Whereupon, the foregoing matter

12 went off the record at 10:52 a.m. and went

13 back on the record at 11:08 a.m.)

14 CHAIR BRAIN: So, let's reconvene.

15 Hi, Russell. Are you there?

16 DR. DICKERSON: I am. Can you hear

17 me?

18 CHAIR BRAIN: Oh, good.

19 Before we turn to you, we are going

20 to do one other thing first. That is simply

21 to turn to the agency representatives and ask

22 them for feedback or for points that they want
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1 clarified.

2 I think we are all a little confused

3 and hope that clarity will emerge as we deal

4 with some of these issues, as we march

5 forward.

6 But, please, tell us other comments

7 or questions that you might have.

8 DR. MURPHY: Sure, sure. I think we

9 all together are finding clarity.

10 But what we wanted to just touch on

11 in terms a clarifying question and comment is,

12 with regard to some of the discussion here, I

13 think the panel is doing some things which we

14 had to do as well, tease out how we use the

15 different types of evidence that are available

16 to us in this review, and how those puzzle

17 pieces can be fit together to be considered in

18 considering a review of the standard.

19 In terms of the REA, as we talked

20 about earlier, that is a piece where we do a

21 quantitative analysis based on the evidence

22 that allows us to do a quantitative analysis. 
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1 Then, we bring that into the Policy Assessment

2 to meet up with all the other types of

3 evidence that doesn't fit so well into the

4 quantitative analysis, and try to consider all

5 of that together in the policy assessment.

6 With regard to the quantitative

7 assessment, which is some of the discussion

8 here talked about in Chapter 2 giving a little

9 more discussion to some of the evidence in

10 terms of broadly characterizing what it can

11 tell us, but some of the rest of the

12 discussion had to do with identifying a

13 population to be simulated in the REA.

14 What we had selected for simulation

15 was the CHD population, based on the fact that

16 the clinical studies showing COHb response

17 relationships was focused on individuals with

18 coronary heart disease and the responses that

19 they got at the different COHb levels.

20 There seemed to be some discussion

21 here about considering a larger or additional

22 populations. We just wanted to understand how
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1 we might do that, given that the quantitative

2 relationships that we have are for coronary

3 heart disease patients, and what we are

4 looking at in the quantitative analysis here

5 is relating our simulated COHb to potential

6 health benchmarks drawn from those studies.

7 So, we would be interested in the

8 Panel's comments on that.

9 CHAIR BRAIN: Paul?

10 DR. BLANC: I think the answer is

11 straightforward. I think that, in the same

12 way that the actual experimental study was

13 done with people defined with coronary artery

14 disease in a very specific, narrow way, and,

15 obviously, you haven't limited yourself in

16 terms of estimating the population at risk to

17 be simply defined literally that way because

18 you couldn't. I think in the same way, at

19 least some model should be estimated where you

20 simply extrapolate the parallel risk, whatever

21 the risk is for ischemic heart disease. In

22 fact, that risk can be applied at the same
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1 level to cardiac disease more broadly defined.

2 So, the proportion of the population

3 who are at risk, you have all the same

4 assumptions, but you define not as 13 percent

5 of the population based on the NHIS definition

6 of self-reported coronary artery disease, but

7 you take a broader proportion of the

8 population who have cardiac disease broadly

9 defined. If you want to use the other NHIS

10 column, which is, as you know, coronary artery

11 disease, all cardiac disease, you could use

12 that as your upper-end limit.

13 But there is no biological reason to

14 presume, which is what you are doing, that

15 because the Allred experiment was done in

16 coronary artery disease, that, in fact, the

17 same adverse health effects at the same levels

18 wouldn't occur in the more broadly-defined

19 population because the epidemiologic data

20 support expanding that effect. Biologically,

21 it makes sense. Epidemiologically, the data

22 are convincing.
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1 DR. MURPHY: Well, the strongest

2 data among the epidemiological data was for

3 the ischemic heart disease.

4 DR. BLANC: No, that is not correct. 

5 That is not the strongest data. I think that

6 was a mischaracterization.

7 In fact, it depends on what you

8 define as strong. That was the point I think

9 Dr. Penn was trying to make. If you are

10 talking about relative risk, maybe that wasn't

11 the strongest effect. It is just that you had

12 more studies that you could -- in fact, I even

13 don't know if consistency is the right word;

14 you could say that one was more consistent

15 than the other.

16 So, no, I don't think --

17 CHAIR BRAIN: But I hear Paul also

18 saying, even if that data was lacking, why not

19 simply say, why not give those caveats? You

20 know, there's not adequate epidemiology. But

21 if we broaden the category of cardiovascular

22 disease to include X, Y, and Z, then this
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1 number may be four times greater.

2 DR. MURPHY: So, what we need to

3 understand is, is the Panel suggesting that

4 ischemia would result as similar COHb levels

5 for a population that goes beyond the coronary

6 heart disease patients? That is what this

7 presumption, so to speak, would be doing,

8 applying the dose/response relationships that

9 we have from the coronary heart disease

10 patients.

11 What we tried to do is, rather,

12 focus in the REA on the population for which

13 we had those dose/response relationships, and

14 then, in the Policy Assessment, recognize that

15 there's a larger population potentially at

16 risk, which we very clearly provide sizes

17 estimates for that larger population, as Dr.

18 Blanc has suggested, to raise that as

19 something which is an important consideration

20 for the Policy Assessment because we have a

21 variety of populations with oxygen22 availability issues with potential
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1 susceptibility to the increased CO. So, that

2 is the way we have covered this, if you will,

3 in the review.

4 But I am interested in the question

5 on my first, which is, do we expect to see

6 ischemia?

7 CHAIR BRAIN: I guess, in part, you

8 are dealing with a fear that some people that

9 have that, if it is missing in the REA, it is

10 not going to appear in the PA. I guess you

11 are saying that is not true.

12 DR. MURPHY: It's not true.

13 CHAIR BRAIN: So, I guess that is

14 one of the issues for CASAC, is: do you want

15 to add that concern about other populations in

16 the REA, or are you content with it?

17 DR. BLANC: I'm not content, and I

18 think it is a different question. I think Dr.

19 Ritz's point about pregnant women, where we

20 don't actually know the mechanism, and I think

21 that would be a very big leap to say it is

22 going to be a mechanism of ischemia. So,
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1 therefore, I think that is an example of

2 something where you would talk about it in a

3 different context.

4 But in terms of your modeling, in

5 fact, I think the presumption would have to be

6 that, in fact, the mechanism would be ischemia

7 or ischemic-related in those people with, for

8 example, congestive heart failure.

9 I think that is why I wouldn't

10 include the cerebrovascular accident group

11 because I think, then, you are getting, yet,

12 one more step, and the epidemiologic data are

13 slightly less robust. But I think when you

14 are talking about hospital admissions as the

15 endpoint convincingly, and the epidemiological

16 issues are for the population with congestive

17 failure, it ultimately is ischemia or

18 downstream from ischemia, one way or the

19 other. I think that is a reasonable

20 assumption for one model.

21 Am I saying you shouldn't model your

22 narrower at-risk population? No, I'm just
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1 saying, in the same way that you have a

2 scenario, okay, here is if the standard were

3 at the maximum, here is at the standard "as

4 is" the number of people, I want to see if you

5 had a more realistic number of people with

6 cardiac disease as a susceptible population,

7 what is your input? Yes, I do think it is a

8 reasonable extrapolation from the controlled

9 human exposure data that you have.

10 I really do think that you are in a

11 situation where we are saying A equals B, and

12 B clearly equals C; then, we should have some

13 model which assumes that A equals C. It is

14 just a critical piece that is missing.

15 It is not the same as saying, okay,

16 also, model for pregnant people or model for

17 some of these other things, where, yes, that

18 should be discussed as something that we are

19 not modeling at all or not including, but it

20 is still an important thing to think about.

21 DR. PENN: I think you will have to

22 at least have some language change because
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1 there is some place -- I think it is in the PA

2 -- that says very clearly that the most

3 susceptible population are people with

4 coronary artery disease. Maybe it would be

5 easier at some level to say the clinical

6 studies clearly indicate that the coronary

7 artery disease population is very susceptible

8 to these changes in ambient CO. However, the

9 epidemiologic data strongly suggests that

10 there are other groups that are at least as

11 susceptible, if not more so, to CO exposures.

12 But the blanket statement that the

13 coronary artery disease is the most

14 susceptible is really unfair because those are

15 the only people where there has been a

16 clinical study. So, you can't make the

17 extension to --

18 CHAIR BRAIN: And, in fact, the

19 people who really meet the Allred criteria are

20 increasingly rare because people with

21 reproducible angina are treated, right? I

22 mean the subjects they studied have
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1 reproducible angina, and they are getting hard

2 to find.

3 DR. DAHMS: But I still think for a

4 lot of people, all of the people stayed on

5 their medications.

6 CHAIR BRAIN: Yes, but now they are

7 more likely to have stents or coronary -- I

8 think this is not finished, but I think we

9 should move on and let's see what develops

10 with the charge questions.

11 I think we also need to look and see

12 what we find in the Policy Assessment, but I

13 think it is a big, you know, it is the

14 elephant in the room for the whole Panel that

15 we have.

16 So, let's hear from Russell. 

17 Russell, you're still there? Tell us about

18 Charge Question 2.

19 DR. DICKERSON: Okay. Charge

20 Question 2 concerns air quality

21 considerations, Chapter 3 and 5. I think Paul

22 Roberts has some comments, too.
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1 The question is: Does the Panel

2 find the consideration of current ambient

3 carbon monoxide monitoring data, et cetera, et

4 cetera, approximately characterized?

5 I think the broad answer to that is,

6 yes, we are looking at a big improvement in

7 air quality considerations in Chapters 3 and

8 5. Measurements were poor, but are getting

9 better. This is adequately handled.

10 The NCOR assemblage of monitoring

11 sites is not characterized. That is an

12 important improvement that EPA put in to

13 adhere.

14 There are still too few quality

15 measurements. I think they are extrapolated

16 to exposure as best as can be done, given

17 their limitations. So, what more can you do?

18 One thing that may be missing is

19 that there is substantial evidence in the

20 reviewed literature that the emissions

21 estimates from emissions models such as Mobile

22 6 may be in substantial error by as much as a
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1 factor of two. This limits the usefulness of

2 chemical transport models for exposure

3 assessment.

4 Those questions about the emissions

5 models need to be addressed before bottom-up

6 chemical transport models can become more

7 useful on a scale too fine to monitor.

8 That, basically, is all I have to

9 say on the REA.

10 CHAIR BRAIN: Thank you.

11 Paul?

12 Yes, first, a quick question or

13 response from the agency.

14 DR. GRAHAM: I just want to comment

15 briefly on the comment on emissions. While I

16 don't disagree that there needs to be

17 improvement in emissions estimates, in this

18 assessment we didn't use any sort of air

19 quality modeling that would require emissions

20 estimates to estimate the concentrations. All

21 the concentrations that we used were based on

22 ambient monitor measurements.
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1 DR. DICKERSON: Yes, but that is the

2 point, that, in fact, the ambient measurements

3 are substantially more accurate than the

4 emission. That is not a particularly good

5 situation.

6 It is worthy of comment. I'm not

7 saying that it doesn't detract from your

8 calculations of exposure assessment, but it is

9 a tool that could be used, should be used, and

10 at the moment can't be used.

11 CHAIR BRAIN: Paul?

12 DR. ROBERTS: Yes, I have fairly

13 brief comments here.

14 I agree with Russ in that Chapter 3

15 especially has a better description of what is

16 going on. You know, it does describe the poor

17 representation near roadway concentrations

18 with these particular monitors. I think that

19 is really good because none of these, even

20 though, as was mentioned, one of them is a

21 micro-scale monitor, it really doesn't

22 represent near roadway. So, that is all good,
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1 and I think those are improvements.

2 So, I think I will let that stand. 

3 I think this chapter is good.

4 CHAIR BRAIN: Anyone else want to

5 comment on Charge Question 2 or any other

6 questions or comments from the EPA?

7 (No response.)

8 Okay. Let's now turn to Charge

9 Questions 3 and 4, and Milan will lead us

10 through that.

11 Does it make sense to deal with 3

12 and then 4? Or how would you want to parse

13 your comments, Milan?

14 DR. HAZUCHA: Yes, we can start with

15 Charge Question 3 and then, once we are

16 finished with that, we can go with Charge

17 Question 4.

18 CHAIR BRAIN: Very good.

19 DR. HAZUCHA: Anyhow, some of the

20 questions and comments were already discussed

21 briefly from Charge Question 2.

22 Because for this Charge Question 3,
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1 we have actually three chapters, and they all

2 deal in one way or another with APEX modeling.

3 Unfortunately, I do not have all the

4 comments here. I just got some comments from

5 Tom, but Beate and Joel, they will have to

6 comment themselves.

7 Generally, the chapters accurately

8 reflect the currently-available information. 

9 They are clearly communicated. They are well10 organized, appropriately-balanced, and so on. 

11 However, after this praise, there is always

12 however. We would like to make some comments

13 to include on some section or clarify some of

14 the sections.

15 I found a bulleted list of modified

16 or expanded sections very helpful, actually,

17 because, then you know exactly what was

18 changed, particularly the major changes. 

19 Similarly, the flowcharts showing the input

20 points and flow data was helpful as well.

21 Now the subquestion A deals with

22 number of monitors. It may be actually quite
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1 helpful to have for exposure assessment more

2 monitors. I am not sure because this is not

3 discussed in comparison to previous REA, where

4 there were fewer monitors than we have now in

5 the second draft.

6 There is a number in each, whether

7 it is Denver or LA, we have a number of air

8 districts, methodological zones, and for LA

9 study areas as well, where there is a

10 considerable overlap. For exposure, it is

11 dealt with algorithms, and so on, for

12 adjustments.

13 But what about other input besides

14 exposure data input? For example, how you

15 dealt with input with individuals, where you

16 have overlapping areas? And particularly for

17 LA, where practically the two areas are almost

18 90 percent overlapped, have you simply

19 evaluated first one area and then the second

20 area, or somehow merged both areas together,

21 ultimately? How was it dealt with? That is

22 unclear from the document.
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1 Also, then, the section dealing with

2 some of the APEX modules, the demographic

3 variables I believe should include

4 socioeconomic status and race. It is

5 particularly important for a COHb module,

6 where race may have an impact, like for

7 example, blacks, it is well-known that they

8 have lower concentration of hemoglobin than

9 whites, and it will affect COHb levels. Or,

10 for example, for individuals with diseases

11 like COPD, diffusion will be substantially

12 lower in healthy individuals. And it doesn't

13 come up clear from the description here how

14 that was handled in the APEX model.

15 I found the tables, and we already

16 discussed briefly some of the tables and some

17 of the parts, very valuable, actually, very

18 elucidating. Because you can really see

19 clearly how, when the concentration changes or

20 the percentage of individuals, to what degree

21 they will be affected.

22 The plots and tabulation of
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1 endogenous COHb, and again, we discussed it

2 considerably, was also very helpful. So, if

3 we have now additional plots as an appendix,

4 then that will be really great.

5 Those are basically my comments for

6 Sub-Charge Question A. I guess Thom has a

7 comment or two.

8 DR. THOM: Me?

9 DR. HAZUCHA: Yes. Right here.

10 DR. THOM: Okay. So, my only, it is

11 a question. Perhaps it is because I don't

12 understand a lot of the modeling issues.

13 But discussed in the REA was the

14 fact that, with the APEX modeling, because of

15 the sensitivity of the monitors, and the fact

16 that they re-zero themselves, there is a

17 drift. And the model can't, and I don't

18 understand why, take a zero or a negative

19 number into consideration. I can understand

20 a negative number, but zero would seem to make

21 sense.

22 But, nonetheless, according to the
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1 REA, it says that for your modeling

2 calculations, because of the zeroes and the

3 negative numbers, you added .5 parts per

4 million to all of the measurements in order to

5 come up with your estimates. Or did I not

6 understand what was written in the REA?

7 DR. GRAHAM: Yes, I'm not sure what

8 you are referring to because my understanding

9 -- well, I don't want to say my understanding;

10 I did generate the air quality data. 

11 Substituting for missing values where there

12 weren't any hourly measurements, and if there

13 were -- I don't believe there were too many

14 negative values, but I don't think .5 was

15 added to --

16 MR. JOHNSON: I think that might

17 have been a different part of the assessment,

18 when we were calibrating one of the

19 algorithms, and we needed to adjust some of

20 the data. But I think the actual monitoring

21 data that was used, we did not add .5 to it.

22 DR. ROBERTS: It is on page 4-22 of
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1 the REA.

2 DR. THOM: I'm sorry, what page,

3 Steve?

4 DR. ROBERTS: Page 4-22.

5 DR. GRAHAM: Before we go any

6 further, this is Ted Johnson with TRJ

7 Environmental. He provided substantial

8 technical expertise in the APEX modeling.

9 MR. JOHNSON: And the part that you

10 are talking about was the development of an

11 algorithm that was used to take the values

12 that were measured at monitors and estimate

13 what the concentrations were at outdoor

14 locations near various micro-environments. It

15 was an analysis done back in 2000.

16 This was used to calibrate an

17 algorithm, but the monitoring data which is

18 used as the input for Denver and Los Angeles,

19 we just used the data that came from the

20 monitor, and we occasionally filled in missing

21 values, but we did not add .5 to the

22 concentrations.
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1 DR. THOM: So, what is being spoken

2 about on this page?

3 MR. JOHNSON: When we have a monitor

4 value, we have a separate algorithm which

5 takes the value at the monitor and uses that

6 to estimate what an outdoor concentration

7 would be outside, say, somebody's home. That

8 particular algorithm is a probabilistic

9 algorithm. The statistical analysis that

10 developed that algorithm required that we get

11 rid of negative values.

12 DR. THOM: So, you are telling me

13 that that's not what is being used today?

14 MR. JOHNSON: Well, there's a two15 stage process going on. We start with the

16 fixed-site monitors in the city. That tells

17 us what the concentrations are at the monitor

18 locations. We, then, have a process which

19 takes those concentrations and converts them

20 to concentrations that are outside various

21 micro-environments, like schools, for

22 instance.
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1 That transfer equation is based on

2 the analysis of data. To analyze that data,

3 to come up with that equation, required that

4 we not use negative values.

5 DR. GRAHAM: So, it is essentially

6 using that to derive a relationship. Then,

7 that relationship is used for the air quality

8 that was input into the current assessment.

9 DR. ROBERTS: Using real data, not

10 the adjusted --

11 MR. JOHNSON: These are real

12 numbers.

13 DR. GRAHAM: Right.

14 DR. THOM: So, why is it in the REA?

15 DR. GRAHAM: Because that was used

16 to derive the actual relationship, the factors

17 that are used for estimating the outdoor

18 concentrations and the micro-environmental

19 concentrations in this assessment.

20 MR. JOHNSON: The relationship had

21 to be based on an analysis of data. This is

22 telling you the data that was used for that
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1 relationship. Okay?

2 DR. THOM: No, but okay.

3 DR. MURPHY: Let me try, as someone

4 a little further away. Maybe I could be

5 closer to what your confusion is.

6 CHAIR BRAIN: Well, I think we

7 understand the confusion. I think we just

8 want the document changed, so that it explains

9 -- SO it is less confusing.

10 DR. MURPHY: We could certainly try

11 to address that in the document, if you would

12 like to move on.

13 CHAIR BRAIN: Milan, why don't you

14 polish off a, b, and c? Then, we will also

15 move on to others. Joel and Beate may have

16 something to say --

17 DR. HAZUCHA: Okay, sure.

18 CHAIR BRAIN: -- rather than

19 breaking it up too much. But, yes, why don't

20 you complete?

21 DR. HAZUCHA: Okay, very good.

22 For b, it is micro-environments,
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1 yes, they are micro-environments. Initially,

2 in the 2000 document there were 15

3 environments, micro-environments, considered. 

4 Now in REA 1, there were two, and now it is

5 expanded to eight.

6 I would like to see somewhere sort

7 of a statement or two. It doesn't make really

8 a difference whether you use fifteen or two or

9 eight, or it is just simply an easily-changed

10 number and it doesn't have any impact on the

11 APEX modeling. Why, for example, how eight is

12 better than two, or these two represented

13 those fifteen reduced to indoor and outdoor. 

14 So, that is one of the comments I have for b.

15 Certainly, I believe that, if you

16 have actually more of these micro17 environments, it probably will enhance the

18 decisionmaking, ensure the estimates, and then

19 decisionmaking.

20 I found the key observations

21 actually in every chapter very helpful because

22 it, basically, summarizes what was done and
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1 what happened. They reflect, indeed, truly

2 what was discussed in those sections.

3 So, those are comments for b. And,

4 for c, since it was really these questions are

5 rather narrow questions, indeed, I consider

6 the selection of most bonds appropriate for

7 indoor estimation.

8 CHAIR BRAIN: Sounds good.

9 Joel, are you with us? Dr. Kaufman?

10 DR. KAUFMAN: Yes, I'm here.

11 CHAIR BRAIN: Oh, good, yes. Do you

12 want to comment on --

13 DR. KAUFMAN: I actually have no

14 additional comments on Question 3.

15 CHAIR BRAIN: Okay. Beate, how

16 about you?

17 (No response.)

18 DR. THOM: Nothing further.

19 CHAIR BRAIN: Steve, nothing else? 

20 Okay.

21 Why don't you proceed to Charge

22 Question 4, Milan?
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1 DR. HAZUCHA: Okay. Well, for the

2 Charge Question 4, again, the same goes as for

3 Charge Question 3, that it is really well4 written. However, again, the APEX model, it

5 is certainly better than the older versions

6 because it is shown much better some of the

7 inputs.

8 I am still unclear, since, as we

9 discussed so many times about this Coburn10 Foster-Kane equation on the COHb models, why,

11 for example, in the document it is mentioned

12 Bruce and Bruce module, which is really simple

13 enough. I still haven't seen anywhere even in

14 this document an attempt made to explore other

15 predictive COHb models.

16 Probably, just again, one or two

17 sentences: yes, we tried it, and it doesn't

18 add anything to CFKE, which is not a robust

19 equation, well-validated and used over

20 decades. But Bruce and Bruce, and others,

21 they all claim, oh, our model is much better

22 than CFKE. So, if they claim it is much
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1 better, there must be something to it. They,

2 of course, go through details, why it is

3 better than CFKE.

4 So, it might and it might not be

5 true, but it might be worth it to examine it

6 again. You might have done it, but I don't

7 see anything about it over here.

8 Now, regardless of the mathematical

9 model used for COHb prediction, one of the

10 modules which is very sensitive, of course, is

11 the COHb module and the input estimates to the

12 module. I already mentioned hemoglobin, for

13 example, or diffusion capacity. There are

14 data, there are predictive formula, for

15 example, for diffusion capacity which can be

16 used. So, you have a range of data that are

17 depending on age, for example, and gender.

18 For others, that is true, like, for

19 example, capillary concentration of CO2. 

20 Unfortunately, we do not have data, so we

21 cannot do anything about it. But if you can,

22 it will really add to the model to make it
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1 more better-tuned.

2 In Appendix A, you actually agree

3 and say the current physiology data file is

4 obsolete, and it may even have incorrect data

5 for some variables. So, my question is, are

6 you going to overhaul this physiologic model,

7 and when are you going to overhaul it?

8 DR. GRAHAM: Well, if I can respond,

9 I guess I will first talk about the model

10 itself, the CFKE versus Bruce and Bruce, and

11 maybe other models that individuals may have

12 suggested are improved.

13 The ISA states that, I think in a

14 conclusion statement, based on the evaluations

15 and comparisons that were done by several

16 authors, that the CFK model is the most

17 widely-used as well as the most validated

18 model to date. To actually incorporate

19 additional algorithms or what other

20 researchers might suggest in recent

21 investigations, that would require significant

22 model development activities, something that
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1 we certainly don't have available to us on the

2 short-term, but it doesn't not necessarily

3 mean that on a longer-term plan regarding CO

4 and estimating COHb dose levels, that it is

5 something that could be undertaken in the

6 future, but that would certainly be a long7 term plan.

8 DR. HAZUCHA: And the physiology

9 module?

10 DR. MURPHY: Yes, I'm sorry. I'm

11 not sure if you looked at Appendix B, but

12 there is a table in Appendix B that makes

13 clear -- it is titled, B-2, which begins on

14 B-11, Principal Parameters Included in the

15 Profile. It talks about how they were

16 estimated.

17 For example, if I am following

18 correctly what your comment was on diffusion

19 rate, you talked about an equation. There is

20 an equation used by the model to estimate

21 diffusion rate. That is described on B-13. 

22 So, gender, age, and height specific.
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1 DR. HAZUCHA: Well, that's what I

2 got, but what about diseases, for example,

3 coronary heart disease, for which we may not

4 have data, but we certainly have for COPD

5 patients data?

6 Yes, I read all what you said. It

7 is adjusted, but for COPD, for example, I

8 don't see any comment there to that effect.

9 DR. MURPHY: And obviously, if our

10 focus was the COPD population, then that would

11 be more of an issue than for the CHD

12 population. Presumably, you are talking about

13 the subset of the CHD population that may have

14 COPD, that perhaps we are missing that in our

15 characterization. That certainly would be

16 something to describe any uncertainty to the

17 extent we are missing that.

18 CHAIR BRAIN: But to take a common

19 problem that people with COPD or emphysema or

20 fibrosis have, you know, they have a

21 diminished diffusing capacity. So, to what

22 extent is that in the model, if you have a
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1 lower-than-normal DLCO? Again, we have some

2 data on what fraction of the population have

3 problems in oxygen diffusing across the

4 air/blood barrier. Is that part of it?

5 DR. GRAHAM: Right, and, of course,

6 as you stated, that may be extremely limited

7 as far as its utility currently in the model. 

8 But if CASAC has recommendations or can

9 identify particular studies that have that

10 type of data that we could use as an input,

11 that would certainly be helpful.

12 CHAIR BRAIN: So, it is not

13 currently part, people with diminished

14 diffusing capacity, that is not currently a

15 susceptible population that is considered in

16 the model.

17 DR. GRAHAM: Right.

18 CHAIR BRAIN: Is that right? Yes.

19 DR. HAZUCHA: What about race and

20 socioeconomic status? Is that in the model? 

21 Because I'm not sure. I might have missed

22 something, but I don't see that.
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1 DR. GRAHAM: We could have that as

2 an output, based on the U.S. Census data,

3 because that is where we are deriving the data

4 to formulate this simulated population. But

5 what you are suggesting is, do we also have

6 the physiological variables to represent those

7 populations? We don't have that input data in

8 the model currently. But if you can identify

9 particular studies that might have that

10 information, then that would be helpful.

11 CHAIR BRAIN: Okay, let's move on to

12 other discussants.

13 DR. DAHMS: I have one

14 clarification.

15 CHAIR BRAIN: Yes, Tom?

16 DR. DAHMS: In that table B-2, when

17 you talk about ventilation rate, are you

18 talking about alveolar ventilation rate?

19 DR. THOM: Which page?

20 DR. DAHMS: B-2, page B-11, you list

21 algorithms. In the appendix.

22 CHAIR BRAIN: It's alveolar
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1 ventilation, not minute ventilation, not total

2 ventilation?

3 MR. JOHNSON: No.

4 CHAIR BRAIN: Dr. Kaufman, do you

5 have anything to add in relation to Question

6 4? Dr. Kaufman?

7 DR. KAUFMAN: I don't have anything

8 to add.

9 CHAIR BRAIN: Okay. Dr. Ritz, are

10 you there?

11 DR. RITZ: Yes, I'm here.

12 CHAIR BRAIN: Oh, good, yes. Do you

13 have any comments, actually, on Charge

14 Questions 3 or 4?

15 DR. RITZ: Yes, actually, I have a

16 general comment, which refers to taking care

17 of the spatial heterogeneity issue. I just

18 want to remind everybody, we have already

19 discussed it earlier, that we really do not

20 measure spatial heterogeneity by using these

21 ambient monitors correctly. We are all aware

22 of it.
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1 So, the APEX model, actually, makes

2 a lot of assumptions about now addressing

3 spatial heterogeneity, when it really isn't by

4 using more monitoring data, that it is not

5 really representative of the high-exposure

6 scenarios that we know near freeways and on

7 freeways, et cetera, et cetera.

8 DR. GRAHAM: Can I just comment?

9 DR. RITZ: So, the question was,

10 does it adequately reflect safer

11 heterogeneity? I don't think so.

12 CHAIR BRAIN: So, the EPA has a

13 response for you. Then, we will come back and

14 see if you have other comments.

15 Yes, we will hear from staff.

16 DR. GRAHAM: Yes. Well, actually,

17 there are a number of adjustments that are

18 made for estimating outdoor concentrations for

19 the individuals that are simulated, in

20 addition to not just the outdoor

21 concentrations, but the micro-environmental

22 concentrations have adjustments associated
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1 with them.

2 Like, for example, in one of the

3 tables, table 4-5, it contains a listing of

4 all the factors that are used to address, or

5 shall I say, to apply to the outdoor ambient

6 concentration that is estimated, and they are

7 a distribution. It is not just a single

8 number that is used.

9 So, for example, the in-vehicle, the

10 geometric mean was approximately 3, and that

11 value ranged from about 1.5 to upwards to 6. 

12 So, in other words, while an individual was

13 inside a motor vehicle, they could experience

14 concentrations as high as six times the

15 ambient -- I'm sorry -- the outdoor

16 concentration, but, on average, the geometric

17 mean of that would be three times that. So,

18 we are adjusting for high-concentration micro19 environments.

20 DR. RITZ: Well, yes, I am very

21 aware of that table and your adjustment

22 factor. But when you use a monitoring station
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1 that is not reflective really of -- well, it

2 has a very low background measure. Some of

3 them are actually below the detection limits. 

4 Any factor you are adding doesn't really add

5 anything. Do you see what I'm saying?

6 As soon as you get close to the

7 detection limit, this may not work at all. I

8 don't know how many monitors had that kind of

9 situation.

10 MR. JOHNSON: This is Ted Johnson.

11 In addition to the micro12 environments, we also have another factor

13 which adjusts the monitor values up and down. 

14 That factor also was based on a study of

15 spatial variation of actual outdoor

16 concentrations versus the concentrations

17 measured at nearby monitors.

18 So, it will also produce values that

19 are both higher and lower than the fixed-site

20 monitors that we are using. So, I think that,

21 plus the micro-environmental multipliers,

22 provides actually a very high degree of
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1 variability.

2 We have also taken the overall model

3 that does all these calculations, and we have

4 compared it to a personal monitoring study

5 that was done in Denver, Colorado, where we

6 had a thousand people carrying personal

7 monitors around. We got a good, we got

8 similar characteristics, spatial

9 characteristics, from what the model was

10 producing to what was actually measured by

11 these personal monitors. So, in a sense, that

12 was a partial validation of this approach.

13 Yes, this was done in the past.

14 DR. ROBERTS: I had a question here. 

15 I don't see a lot in your numbers that the

16 adjustments can be higher than the monitor

17 site. All I see is the lower-than.

18 MR. JOHNSON: Well, the micro19 environment, the geometric means, which would

20 be a middle point in the multiplier,

21 distribution multipliers, most of those values

22 are greater than one.
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1 DR. ROBERTS: Okay. Yes, I

2 understand on 4-5 that is the case. I thought

3 you were mentioning that like the Wilson4 Colome had higher-than, and I think it only

5 has lower-than, unless maybe I misunderstood

6 your comment.

7 MR. JOHNSON: Well, there's actually

8 a distribution of multipliers. It may be that

9 more of them are lower, but there are still

10 some multipliers that are greater than one in

11 the distribution.

12 CHAIR BRAIN: Back to Dr. Ritz, any

13 other comments you want to make?

14 DR. RITZ: Yes, I still don't

15 understand how measurements near the detection

16 limit or under the detection limit at the

17 monitors would give you any results. Do you

18 replace it with a detection limit? Or what

19 did you do there?

20 DR. GRAHAM: Are you referring to

21 the ambient concentration, as to whether or

22 not zero estimates were replaced with some
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1 sort of detection limit?

2 DR. RITZ: Right.

3 MR. JOHNSON: Is your point that, if

4 a monitor measured zero, that with all these

5 multipliers, we would still get zero because

6 they would all be multiplying an initial value

7 of zero?

8 CHAIR BRAIN: I don't think it was a

9 point. It was a question. What do you do

10 with zero? How are they handled.

11 DR. GRAHAM: Zero was retained as

12 zero. If it were reported as a level below

13 the detection limit, then that data were used

14 "as is."

15 CHAIR BRAIN: Which could be a zero,

16 or it is the detection limit?

17 DR. GRAHAM: If a zero was reported,

18 it was used a zero. Yes, it was used as zero.

19 DR. MURPHY: Just to clarify, there

20 are reported values below the detection limit. 

21 So, often, in the data you will have a

22 reported value that it just happens to fall
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1 below the method detection calculated by that

2 lab. But the reported value would have been

3 used, as well as zeroes, I think is what they

4 are saying.

5 CHAIR BRAIN: Does that answer your

6 question, Dr. Ritz?

7 DR. RITZ: Yes.

8 CHAIR BRAIN: Okay. Anything else

9 that you want to add to Questions 3 and 4?

10 DR. RITZ: No, that's it.

11 CHAIR BRAIN: Okay. Before turning

12 to Dr. Thom, Paul, you had a question?

13 DR. ROBERTS: Well, on the new

14 detection limit, I am concerned about that a

15 little bit when -- and I don't know the exact

16 details on these monitors, but some agencies

17 with older monitors only report whole

18 increment ppm concentrations. So, they might

19 only report zero or one, for example. I am

20 not sure how that is used.

21 But if you look at the distributions

22 of the data, like on 3-3, figures 3-3 and 3-2,
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1 et cetera, which are on pages 3-9 and 3-10, it

2 doesn't look like there's a significant amount

3 of data down at the zero level. So,

4 hopefully, the question Dr. Ritz is asking is

5 not too important, I think.

6 DR. GRAHAM: Right, and I was going

7 to point to that as well as some of the data

8 that are in tabular format, that

9 concentrations that are, say, at or below a

10 so-called detection limit of approximately 1

11 ppm aren't necessarily highly prevalent, but

12 they are not necessarily the most important

13 driver to maximum end-of-hour COHb level. 

14 Most of those are going to be driven by the

15 upper percentiles of the distribution of the

16 air quality data, most, if not all.

17 CHAIR BRAIN: Dr. Thom, anything

18 else you want to add?

19 DR. THOM: I have nothing else.

20 DR. ROBERTS: I have some.

21 CHAIR BRAIN: Yes, anything else on

22 Question 4?
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1 DR. ROBERTS: Well, a few of my

2 questions may be on 5, comments may be on

3 Charge Question 5, too. I think it is a

4 little together.

5 But I do think the expansion of the

6 modeling domain with more monitors, the

7 spatial distribution, the more micro8 environments, all of that does have a really

9 positive effect at the end I'm concerned

10 about, which is the near-roadway exposure

11 part.

12 I think those are really positive

13 improvements here in this version of the REA

14 versus the second. Even with the limitation

15 that Dr. Ritz talks about with adding the more

16 monitors, the spatial coverage from that

17 doesn't produce the better representation of

18 the near-roadway, but I think the micro19 environmental addition does do that. I think

20 those are real positives here.

21 But I do have a question or a

22 comment. There's one part I don't understand,
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1 and I have put it in my written comments. 

2 There's a couple of equations, 4-11 and 4-22,

3 which are essentially the same equation,

4 basically reduce the ambient concentration to

5 other outdoor locations. Okay?

6 And I don't really see the

7 justification for this power of .621. I think

8 that is pretty weak. In one place, it says,

9 well, that is the way to make pNEM and APEX

10 agree. I don't see any physical rationale

11 there.

12 In another place, it talks about the

13 Wilson-Colome work as sort of confirming that. 

14 The problem I have with that is that I'm

15 pretty sure that most of that work was homes

16 and not near roadway or other kinds of

17 locations.

18 In the end, to me, what is

19 bothersome is that the kinds of factors, in

20 particular, for the high exposure part, the

21 near-roadway/in-vehicle kinds of factors that

22 are in table 4-5 should represent from a
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1 monitor to this exposure location, micro2 environment, but, in fact, that monitor is

3 being reduced almost by a factor of two in

4 some cases by this .621 factor. I don't

5 really understand. That sort of defeats the

6 purpose of having -- you know these multiple

7 predictors of factors have been developed with

8 the real ambient data and not some reduced

9 ambient data.

10 So, maybe you guys can point out

11 where I am missing something.

12 MR. JOHNSON: This equation was

13 developed by fitting data to the Colome study. 

14 The .621 factor was not added as an

15 afterthought. It actually improved the fit of

16 the model to the data.

17 The fit was done by statisticians

18 with ICF, and I assisted with the analysis. 

19 But besides the exponential value of .621,

20 these various terms had their own

21 distributions. It is the product of all these

22 terms together which determines what the
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1 multiplier is, not just the .621 factor.

2 When you look at the distribution of

3 the product of all these terms, including the

4 one with the .621 factor, you do get a

5 distribution of multipliers which is

6 consistent with the relationships that were

7 found in the Colome study between outdoor

8 locations and fixed-site monitor

9 concentrations.

10 Also, the Colome study, though it

11 was mostly residential, included many

12 residential areas that were close to roadways. 

13 So, it is a diversity of different outdoor

14 locations.

15 The extra exposure that you would

16 get if you were walking down a sidewalk or

17 something is reflected with the micro18 environment factor. You could think of this

19 as providing more of the distribution of a

20 more general ambient outdoor location. Then,

21 the micro-environment factor would provide an

22 extra degree of exposure if you were next to
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1 a roadway.

2 The main reason for having this type

3 of equation in the model is it provides for

4 all the micro-environments an estimate of what

5 the outdoor concentration is. For the indoor

6 micro-environments, it gives us an outdoor

7 concentration that the mass balance model can

8 work on.

9 For outdoor locations, it gives us a

10 value that you could consider a proximity

11 factor would be added to. The proximity

12 factor would be the fact that somebody is

13 staying right next to a roadway, which would

14 increase their exposure more.

15 It is not a perfect solution, but it

16 does have the advantage of providing a very

17 good fit to one of the most extensive datasets

18 of data representing a wide variety of

19 locations, all of which were paired with

20 nearby fixed-site monitor concentrations. 

21 That type of study is actually very rare in

22 the literature.
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1 Also, this equation and everything

2 was developed for the 2000 pNEM CO analysis. 

3 This long discussion that is in the REA is

4 explaining the fact that we are still using

5 the same relationship, but in order to make it

6 work with APEX, we have to implement it in a

7 slightly different way. This is an

8 explanation of the changes in the

9 implementation, but the mathematical

10 characteristics of the equation are still the

11 same as they were in the 2000 pNEM assessment. 

12 The .621 is not something that was added after

13 the fact.

14 DR. ROBERTS: Well, I understand

15 what you are saying, but the net result,

16 though, is that, yes, the table 4-5 has

17 distributions. By the way, I think that is a

18 big improvement, too, if I didn't mention it

19 earlier, over the earlier REA. The

20 distributions are good.

21 But take the top end of the in22 vehicle, for instance, the factor of six. The
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1 factor actually is only three because of this

2 .621. That does not agree with the ambient

3 data that was in the ISA, as far as I

4 understand.

5 I mean I haven't gone back and

6 looked at Wilson and Colome, but, as I

7 remember when that study was being done, we,

8 as a community, were not focused on near9 roadway. I didn't really remember that a

10 significant number of those were near-roadway

11 homes. I don't think they were, but I could

12 be wrong. I just don't remember. But we, as

13 a community, certainly weren't focused on

14 that. So, that comparison is sort of weak,

15 from my view, as justification of this.

16 But the net result, from my view, if

17 I calculate what the ratio-to-ambient is for

18 these higher-exposure micro-environments, it

19 is a factor of two less than this because of

20 that factor. That is not what the literature

21 says on those ratios. That is not what the

22 ISA said.
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1 MR. JOHNSON: Well, we are getting

2 concentrations from APEX that are greater than

3 30 parts per million. In fact, I believe they

4 go as high as 40 for the current standard.

5 Are you suggesting that they should

6 be much higher than that?

7 DR. ROBERTS: Well, I didn't do

8 exact concentrations. All I was doing was

9 ratios based on outdoor concentration to the

10 .621 factor times these ratios. Okay? That

11 net ratio is only three, instead of six. My

12 reading of the ISA literature was that that

13 number was five and six, not three. Even

14 though 30 seems pretty high, it seems

15 reasonable, but that is not what this factor

16 would say.

17 DR. GRAHAM: Right, and I think we

18 need to think about it from a practical

19 consideration. As Ted pointed out, we are

20 estimating concentrations, say, inside

21 vehicles because that is largely the driver of

22 the higher concentrations. We are estimating
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1 concentrations as high as 30 or 40 ppm, which

2 is a reasonable estimation, given air quality

3 just meeting the current standard.

4 We have to recognize that the data

5 that are reported in a lot of these studies,

6 they provide some relationship between the

7 concentration and the vehicle versus the

8 ambient monitor. We are also not provided,

9 well, what was that concentration? Was it a

10 low concentration at the ambient monitor or

11 was it a high concentration at the ambient

12 monitor?

13 Because a lot of times we will see

14 there's a relationship between the two; that

15 is, you will have smaller ratios between high

16 concentration, ambient concentrations and in17 vehicle versus the opposite of that is that,

18 from a very low concentration, you will have

19 a high ratio because of concentrations that

20 are measured at the in-vehicle site.

21 So, this, in effect, adjusts for

22 that. That is, we won't apply high ratios to
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1 high concentrations because, then, the next

2 thing you know, there will be individuals that

3 have exposures that are outside of what has

4 been observed previously.

5 DR. ROBERTS: Right. Well, the

6 distribution I think helps take care of that. 

7 I think that is good. Okay.

8 CHAIR BRAIN: Okay. Are we ready to

9 move on to Charge Questions 5 and 7? So,

10 let's hear from --

11 DR. BLANC: Can I just ask --

12 CHAIR BRAIN: Yes.

13 DR. BLANC: After hearing all of

14 that, so it is still a doubt that you have

15 that the system that was used may selectively

16 or systematically underestimate near-roadway

17 exposure? Because that, for a different

18 reason, was Dr. Ritz's concern, but for a

19 completely different reason.

20 DR. ROBERTS: Right, yes.

21 CHAIR BRAIN: So, that concern

22 persists?
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1 DR. BLANC: So, I think that when,

2 at a minimum, when we come back to whoever is

3 doing the chapter with the estimates of

4 uncertainty and direction of estimation, that

5 needs to be emphasized there, if it is not

6 already reflected.

7 CHAIR BRAIN: That sounds like a

8 good summary comment.

9 Okay. Yes, why don't we turn to

10 you, Paul, and also to Francine and Tom Dahms'

11 questions to 7?

12 DR. BLANC: So, 5, 6, and 7, so it

13 is a big hunk of a thing. Can we do it one at

14 a time?

15 CHAIR BRAIN: How would you like to? 

16 What is the most appropriate way? Do any of

17 the three fit together?

18 DR. BLANC: Well, I mean I would

19 just do 5, and have everybody do their spiel. 

20 Is that okay?

21 CHAIR BRAIN: Okay.

22 DR. BLANC: Because 5 overlaps a lot
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1 with what we have just been talking about.

2 CHAIR BRAIN: Yes.

3 DR. BLANC: As I understood it, it

4 was really talking, again, about the modeling

5 approach and was it technically sound.

6 Again, I think it comes back to the

7 comments that were already made that the model

8 certainly has increased its number of inputs

9 and has been, in that sense, extremely

10 responsive to the feedback that was given at

11 the first review, and especially because there

12 was a lot of hesitancy, I think, because of

13 the person-hours of work that it would take to

14 do these changes. I think it was extremely

15 responsive.

16 I think that the challenge is really

17 the technical nature of the modeling and how

18 can you communicate that in ways which are

19 interpretable to non-modelers. If I had some

20 solution to that, I would give it to you.

21 But, as you can see, I mean I just

22 heard a 15-minute discussion, and at the end
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1 of it I wasn't sure whether Paul's question

2 had been answered or not. You may feel you

3 did answer it, but he still doesn't feel that

4 you did -- not answer it, but, you know, allay

5 his concern.

6 So, that is my answer to No. 5. 

7 Yes, I think it is within the limitations of

8 being able to explain that it certainly seems

9 that they have used a lot more data to drive

10 it.

11 CHAIR BRAIN: Tom, do you want to

12 chime in?

13 DR. DAHMS: My concern is with

14 scratching for some sort of validation in the

15 model, no matter how weak, how limp, how

16 brief, whatever. Because, over the years,

17 things get changed.

18 I am familiar with how much

19 validation went into the CFK thing over the

20 past 30 years, but I'm still looking for some

21 way of showing that, because, basically, my

22 concern is, if we are using the dose metric of
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1 COHb, how reliable is the model? Is the

2 distribution of values too great, so we wind

3 up overestimating the number of people at

4 risk?

5 So, I kept scratching around for

6 some kind of way of validating this thing

7 where people have actually measured blood

8 levels of COHb. You know, it is just the

9 unease, the real uncertainty of the values

10 generated by the model.

11 You know, we have heard a lot about

12 that all morning. I think that everybody is

13 anxious about that. I don't know how to

14 alleviate those concerns.

15 I know it is trivial, but I thought

16 that maybe where you have all the coronary

17 artery disease patients in Sheps, Kleinman and

18 Allred, you have exposure data from pretty

19 well-calibrated monitors, even though the

20 levels are higher than what you've got, than

21 what you're using here, is there a way of

22 plugging it in to see if the numbers even are
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1 in the ballpark?

2 What's the range of data that you

3 get out of these people with coronary artery

4 disease? I don't know if there has been any

5 attempts to use this whole APEX model. I mean

6 you've even got an activity pattern for these

7 people and ages, and everything else, pretty

8 well laid out.

9 I don't know. Has anybody ever

10 attempted to do this?

11 CHAIR BRAIN: So, you are talking

12 about real measurements of COHb in people

13 when --

14 DR. DAHMS: Yes, to validate.

15 CHAIR BRAIN: -- you have both

16 exposure and blood values?

17 DR. DAHMS: Yes.

18 CHAIR BRAIN: And there's little of

19 that or none of it is here?

20 DR. DAHMS: No. And I understand

21 what the modeling is, that the range of values

22 you are getting are for thousands of people
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1 over an entire year. So the splay is going to

2 be much greater than what you get.

3 DR. GRAHAM: Right. I agree that

4 there can always be more evaluation that

5 improves our confidence or reduces our so6 called uncertainty about what's being

7 generated.

8 In earlier NAAQS reviews, we have

9 done some -- and again, we have to look at it

10 as we don't have the end-of-hour COHb levels

11 for the population. It just doesn't exist. 

12 So, I don't even want to call it a gold

13 standard, but that would be some way where we

14 could evaluate the model performance with some

15 measured data.

16 But we do have pieces. One of the

17 pieces is, yes, the CFK module. We know that

18 that has been extensively evaluated, as well

19 as validated, based on real measurement data.

20 We know that there is, again, other

21 pollutants that APEX has been used to model,

22 and those have been compared to personal
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1 exposure or measurement data for ozone and,

2 recently, for nitrogen dioxide.

3 The model is generating reasonable

4 estimates of individuals' exposures. We know

5 that CFK module is estimating dose reasonably. 

6 Therefore, we can feel a little bit better

7 about the estimates, in the absence of the

8 actual measurement data that, yes, it is

9 likely that we are estimating COHb dose levels

10 reasonably.

11 But, again, more can be done to try

12 to evaluate these pieces that exist in the

13 model. I will include additional discussion

14 about what has been done in the past.

15 CHAIR BRAIN: Francine, anything you

16 want to say about Question 5?

17 DR. LADEN: I don't have anything to

18 add. I think we covered it.

19 CHAIR BRAIN: Good. In fact, Tom,

20 it sounds like a lot of what you had to say

21 deals with Question 6. So, back to Paul.

22 DR. BLANC: So, as opposed to my
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1 sort of generic models that are for the

2 previous question, here is where I start to

3 have a lot of issues. I alluded to many of

4 them this morning in the questions that I was

5 asking.

6 So, as I tried to take a step back

7 and think about it, there are four

8 contributors to somebody's carboxyhemoglobin

9 level in general. One we are not going to

10 deal with at all, which would be active

11 smoking. A second is endogenous production. 

12 A third is indoor point sources that are

13 independent of outdoor ambient pollution

14 coming indoors. And the fourth is ambient

15 pollution.

16 So, I had to step back and think

17 about that because that really confuses the

18 picture when you start thinking about what is

19 the carboxyhemoglobin distribution in a normal

20 population, in a normal, non-smoking

21 population. Because, obviously, in a normal,

22 non-smoking population, it comes from three of
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1 those four because they are not active

2 cigarette smokers.

3 So, that is not actually said

4 explicitly in the document. I don't know

5 whether it would help solve confusion or not,

6 but it was helpful for me to think it through.

7 Because the document insofar as the

8 indoor contribution is focused on the outdoor

9 contribution to the indoor contribution, it

10 gets confusing. It might be helpful, again,

11 for you in some of your exposure scenarios to 

12 be explicit about what would be contributing

13 to the indoor from the outdoor, as you are

14 saying, because I don't think you actually are

15 consistent.

16 Because an automobile that is

17 running in a garage isn't exactly an ambient

18 source, but that is why your garages come out

19 having higher levels. But your manufacturing

20 facilities, which are the same as churches and

21 hospitals, obviously, there's no possible

22 scenario that there is a forklift in any of
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1 those manufacturing facilities, let alone a

2 manufacturing process that would produce CO

3 some other way.

4 Now, if it produces CO some other

5 way, it wouldn't be consistent with your

6 definition. But I don't see why a forklift is

7 different than an automobile, just as an

8 example. It may have to do with the sample on

9 which you drew those.

10 But in Chapter 6, well into the

11 chapter, suddenly, you start talking about

12 internal sources of carbon monoxide and

13 carboxyhemoglobin, using the 2000 data.

14 So, first of all, I have a question. 

15 Is the word internal, as it is used there,

16 meant to be only indoor, non-ambient, or does

17 it mean indoor, non-ambient plus endogenous? 

18 As it was used in the 2000 report, what was

19 that? Was that just indoor, non-ambient?

20 DR. GRAHAM: I think what's referred

21 to in Chapter 6, when it says, internal, I

22 think they are talking about the indoor
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1 sources that were modeled.

2 DR. BLANC: Internal sources?

3 DR. GRAHAM: Right, yes. So, it was

4 gas stoves and --

5 DR. BLANC: So, it was not

6 endogenous? Not endogenous, internal, but

7 not --

8 DR. GRAHAM: Yes, yes, and I

9 apologize for that language.

10 DR. BLANC: Okay. I would

11 definitely go back and clean up that language.

12 DR. GRAHAM: I think that is how

13 they termed it back then, and maybe that is

14 why it was called --

15 DR. BLANC: So, I would rename it

16 for your document, please.

17 DR. GRAHAM: Yes. Yes.

18 DR. BLANC: And say indoor, not

19 ambient.

20 DR. GRAHAM: Right.

21 DR. MURPHY: It is just additional

22 indoor.
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1 DR. BLANC: Additional to the

2 ambient to the indoor.

3 So, you can see why --

4 DR. GRAHAM: Yes.

5 DR. BLANC: Okay. So, your data,

6 though, are very convincing that this is an

7 important driver to somebody's

8 carboxyhemoglobin level, which is why, in

9 part, when I think one of the reviewers said,

10 well, wait a second, if we look at the

11 baseline pre-exposure data in Allred, they

12 have carboxyhemoglobin levels that are above

13 what you are saying people's carboxyhemoglobin

14 levels are from endogenous production.

15 But, of course, that is because

16 those people's levels aren't just endogenous;

17 they are also from their own airborne and

18 their own indoor air exposure, wherever they

19 are coming from.

20 And it is clear from what you show

21 that, when you add this indoor air pollution,

22 that 5 percent of the population hits a 3
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1 percent carboxyhemoglobin level, and 2 percent

2 hits a 4 percent, roughly, slightly higher and

3 lower. Yet, then, that is sort of completely

4 abandoned.

5 That is why I said earlier today

6 that I think it would be critical to see the

7 curve of what happens when you add all three

8 together. Because you have one presentation

9 which is the indoor plus the outdoor, and you

10 have one which is the endogenous plus the

11 outdoor, but you don't have anywhere all

12 three.

13 Although your stated rationale --

14 and I forget where it was in the document --

15 is, well, you know, this is about ambient

16 pollution, we can't control by our standard

17 indoor air pollution, but you can't control by

18 your standard endogenous production, either,

19 but you do take it into account.

20 I wonder if there isn't some other

21 standard process that you have gone through

22 where the issue of multiple sources of
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1 exposure have to be dealt with as explicitly. 

2 For example, the last time you redid an

3 ambient lead standard, didn't you have to take

4 into account sources of lead that weren't from

5 ambient air pollution?

6 DR. MURPHY: Yes. Yes, I worked on

7 that standard.

8 And, yes, the reason we did was

9 because of the non-linear relationship in the

10 blood biokinetic modeling. So, that we

11 needed to pull together all of the exposure,

12 and then take back out to figure out how much

13 was ambient. Because in setting the standard,

14 we focused on the amount of air-related blood

15 lead that was contributed by the air, be it

16 multiple pathways of exposure, but, still, the

17 focus in lead was on the ambient air-related 

18 lead, although we did in the assessment need

19 to consider all the different sources because

20 we had a non-linear relationship going on in

21 the blood lead model that was used.

22 There was a comment made this
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1 morning which I thought was useful. What we

2 are looking for here is a link back to the

3 Allred data. Obviously, they had an

4 experimental exposure that upped their COHb. 

5 So, it is that change that saw the response

6 that we saw in that study. So, that is sort

7 of a parallel to what we are looking at here

8 in terms of the ambient concentration.

9 DR. BLANC: But, in order to do

10 that, if the issue is biologically -- you are

11 taking an approach where, in your tabular

12 presentations, you are saying how many people

13 are pushed over 2 percent carboxyhemoglobin

14 and how many people are pushed over 3 percent.

15 Well, if the issue is being pushed

16 up to that level, then you have to think about

17 where people are starting from. You have done

18 that appropriately because you think about the

19 endogenous level. So, clearly, you are going

20 in that direction.

21 By the same logic, it also matters

22 what people's contribution from their indoor
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1 air is because they are going to be pushed

2 even higher. So, in fact, the percent of the

3 at-risk population which reaches 3 percent for

4 carboxyhemoglobin isn't what you are

5 estimating it is. It is going to be higher

6 because those people don't just have their

7 endogenous production; they have their indoor

8 exposure as well.

9 DR. MURPHY: But it seems to me it

10 would depend on the relationship between the

11 ambient contribution and the indoor

12 contribution. In some ways, the ambient may

13 not really change a person's COHb if they have

14 a larger indoor contribution to their COHb.

15 DR. BLANC: Well, I don't see why

16 that would be true, and that wasn't what your

17 estimation from the 2000 data showed. You

18 added them together linearly. You wouldn't

19 assume that you would have less of a response

20 to ambient superimposed carbon monoxide

21 because you have already been exposed

22 internally.
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1 DR. MURPHY: It would depend on the

2 magnitude of the indoor contributions, and

3 that is an uncertainty we have in this

4 assessment; that's true.

5 DR. BLANC: Yes.

6 CHAIR BRAIN: So, if it is higher

7 indoors and you go outdoors, then it will go

8 down, not up, right?

9 DR. BLANC: Yes. Yes, but, overall,

10 your value will be higher, right? And since

11 you showed in your model that for most people

12 90 percent of their exposure is coming from

13 their times indoors, right?

14 DR. MURPHY: Right.

15 DR. BLANC: Well, I mean in the all

16 column. People spend most of their time --

17 MR. JOHNSON: But it is unlikely

18 that you have a really high ambient exposure

19 indoors. So, the really high COHb would

20 probably not be affected.

21 Another point here is these numbers

22 are for 2000. Some of these indoor sources
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1 have actually come down since then. That

2 doesn't mean we should ignore them, but the

3 effect will probably be less than what is

4 shown.

5 DR. BLANC: Well, okay, it will be

6 less, but I think it is going to add overall

7 a part per million to everybody, which means

8 that the percentage of people, if you

9 estimate, however you do the at-risk

10 population, the number of people who exceed

11 each threshold would be substantively more,

12 substantially more.

13 DR. MURPHY: Their total exposure is

14 not necessarily from ambient, that's right.

15 DR. BLANC: That's right, but that's

16 what matters, is who gets pushed over because

17 of the ambient up into this higher category

18 biologically and clinically and

19 epidemiologically.

20 DR. KAUFMAN: Paul, this is Joel

21 again.

22 I guess I don't read the Allred data
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1 that way. I mean I read that data as being

2 increments up having an effect, not reaching

3 a certain COHb concentration being important. 

4 It is important, obviously, but that is not

5 the way that data is laid out.

6 DR. BLANC: Well, it is a linear

7 response, in fact. So, I would disagree with

8 your interpretation. In fact, those data

9 suggested that there is a linear dose

10 response, and the higher you go, the worse

11 your effect is.

12 CHAIR BRAIN: Tom, do you want to

13 comment on that? You are one of the key

14 authors.

15 DR. DAHMS: You are probably both

16 right.

17 Because the way in which the

18 analysis was done was to compare the decrement

19 from a pre- and post-test versus one with two

20 different levels of exposure in that study. 

21 So, in that sense, it is incremental.

22 However, when you do the analysis of
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1 a dose response, you do get a clear dose

2 response curve that suggests that it is

3 related to the absolute level of the

4 increment. So, it is linear, yes.

5 DR. KAUFMAN: I mean I put my weight

6 on the incremented being what is informative

7 and also would be extremely informative to

8 see, as the actual outcome in the modeling in

9 the REA and the Policy Assessment because this

10 was a clinical trial that was designed in a

11 way to increase people a certain amount. So,

12 that is really the inference that is designed

13 to be taken out of that study.

14 I always think, when you analyze

15 that kind of data, your first approach should

16 be to take what was the design element of the

17 study, sort of just as you would in a clinical

18 trial, with an intent-to-treat kind of thing,

19 rather than trying to model it in a different

20 way post-hoc.

21 So, that is why, for me, I mean I

22 wasn't on the group to answer Question 6, but,
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1 to me, the piece that I liked seeing this

2 morning, and that I think needs to be pulled

3 out even more and emphasized as this process

4 moves forward, and it doesn't sound like we

5 are going to have another crack at it, is

6 really to develop the part where we talk about

7 attributable to ambient exposure, rather than

8 so much on the endpoint of what is the total

9 carboxyhemoglobin level.

10 Because people come in with all

11 kinds of background levels from all kinds of

12 reasons, as we have been discussing, including

13 smoking. If you are adding some amount of

14 carboxyhemoglobin on top of whatever their

15 background is, I think there is reason to

16 believe, from what we have heard, that it

17 pushes them further. That is what has been

18 informed by the study that we are really

19 basing the whole risk assessment on.

20 DR. BLANC: Well, but, Joel, I think

21 that completely ignores the epidemiological

22 literature. If we only had Allred and no
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1 epidemiological literature, I might be

2 inclined to -- but I don't think that that is

3 a public health protective interpretation of

4 the Allred data.

5 DR. KAUFMAN: I disagree. I think

6 the way that I am interpreting it is

7 completely public health protective and

8 provides public health protection across the

9 entire range of background carboxyhemoglobin

10 level that people come in, rather than

11 discounting people who come in with high

12 levels, which I think your approach does.

13 Further, I think the epidemiological

14 data is actually surprisingly weak, for the

15 reasons that are discussed extremely well, I

16 thought, in the Policy Assessment and the REA.

17 So, I think where we are right now,

18 we may be better off in five years, but where

19 we are right now is, unfortunately, this

20 process is appropriately based on the Allred

21 study. That is where we are going to have to

22 be. I think public health protection says
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1 that you start with wherever somebody's

2 carboxyhemoglobin level is and talk about the

3 increment and trying to reduce the amount of

4 increment caused by the ambient contribution

5 to their carboxyhemoglobin level.

6 That is where I think this piece

7 actually needs to be firmed-up. And they have

8 taken initial steps towards that, but haven't

9 gone far enough yet.

10 CHAIR BRAIN: Francine, while Paul

11 is thinking about that, do you want to add

12 anything to Charge Question 6?

13 DR. LADEN: I don't have anything to

14 add to that, except I would actually agree

15 with what Joel has just said. I think that

16 the increment is what is really important here

17 and what we have got the data to be able to

18 look at.

19 DR. BLANC: But if that were true,

20 then we wouldn't be talking about an at-risk

21 population. You would say the population is

22 the entire population that is exposed, Joel. 
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1 So, I don't think you can have your cake and

2 eat it, too.

3 If we are going to say only people

4 with coronary disease are at risk, then, in

5 fact, those are the people that are being

6 thrown over a threshold. If you are saying

7 everybody is at risk, then, the epidemiologic

8 data don't suggest that.

9 So, you haven't convinced me. Maybe

10 it is partly the language that we are using is

11 we are talking apples and oranges. I don't

12 know.

13 But, to me, why I am harping on the

14 indoor air pollution is because, if you are

15 going to make a calculation with the added

16 increment of ambient pollution, how many

17 people have now gone into the danger zone

18 because they are using a cutoff of, for better

19 or for worse, 2 parts per million, then I

20 think it is reasonable to think about. 

21 Because your argument would say, then, cut out

22 the endogenous production, too, and forget
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1 about that.

2 For the second half of my comments

3 on the CO, I would just reiterate what I said

4 this morning, which is that the model isn't so

5 transparent of how the endogenous was done. 

6 But from what I can understand from it, it

7 doesn't include parameters that presume

8 outlying subpopulations.

9 We are told that there aren't

10 numeric ways of really doing that, but it

11 comes back more to the question of when you,

12 then, go back and see, are the numbers that

13 are being generated here reasonable, we know

14 that there have to be people by endogenous

15 production who are higher than the maximum

16 numbers that are coming out here. So, that is

17 a little tricky.

18 I do think that, whatever you stick

19 with, it could be more transparent. In the

20 appendix is where that stuff is supposed to

21 be, but you can't actually tell -- from the

22 appendix, there is a reference list, but you
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1 can't tell, and it says somewhere something

2 like eight different studies were used to

3 inform. But there is no way of knowing which

4 eight those were.

5 DR. GRAHAM: Yes, they are

6 summarized in the table.

7 DR. BLANC: Yes, but the table is

8 not labeled.

9 DR. GRAHAM: B-3.

10 CHAIR BRAIN: Okay. Anything else

11 on Question 6? We sort of wandered around

12 into multiple issues.

13 DR. DAHMS: Well, I've got

14 something.

15 CHAIR BRAIN: Yes.

16 DR. DAHMS: My concern with the

17 endogenous levels, now in the past I went

18 looking for this through all the documents

19 from '79 on, trying to find a description of

20 baseline levels of carboxyhemoglobin. Now one

21 of the issues that you bring up with the

22 endogenous rates not having an influence on
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1 anything doesn't make any physiologic sense to

2 me. That is what I am really having a hard

3 time with.

4 Because if we are all exhaling 2

5 parts per million, that means we have to have

6 a gradient of 2 parts per million to get rid

7 of what we are producing every minute of every

8 day. If you add one part per million

9 inspired, that means you've got to raise your

10 expired to 3 parts per million to get rid of

11 our endogenous production. So, it is just

12 going to keep raising it up.

13 So, I'm really having a hard time

14 understanding why the endogenous rate does not

15 influence the eventual dose of

16 carboxyhemoglobin, which is related to the

17 parts per million of carbon monoxide.

18 It gets back to exactly what Paul is

19 talking about. If you have got 3 parts per

20 million in your kitchen and you need three to

21 get rid of your endogenous, you are going to

22 wind up with 5 parts per million being
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1 exhaled.

2 CHAIR BRAIN: So, the alveolar PCO

3 will be higher, and so the carboxyhemoglobin

4 will be higher.

5 DR. DAHMS: Correct. And I can't

6 figure out why that is not the case.

7 DR. HAZUCHA: Well, let me comment

8 here. It is true and maybe not so true.

9 The COHb level depends on the

10 maximum level of carbon monoxide you inhale. 

11 If you have in the environment 5 ppm, and your

12 COHb production is 2 ppm, you will be taking

13 in carbon monoxide. If you are in absolutely

14 pure air, you will be exhaling carbon

15 monoxide.

16 If you are outside and there is 5

17 ppm exposure, and you came from inside where

18 there was 9 ppm, you will be exhaling carbon

19 monoxide outside. If it is reverse, we have

20 a higher concentration outside and lower

21 concentration indoors, then probably you will

22 be taking in. If there is carbon monoxide
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1 seeping inside indoors, then you will be

2 taking up carbon monoxide.

3 So, it is not additive effect. It

4 is not 2 ppm and 5 ppm, and so on. It is the

5 highest concentration which you are inhaling

6 which will be driving carbon monoxide level.

7 CHAIR BRAIN: I mean what I find

8 helpful about that, Milan, is it is sort of

9 the steady-state. Once you have equilibrated

10 with this 3 parts per million --

11 DR. HAZUCHA: Yes.

12 CHAIR BRAIN: -- then there is no

13 additional.

14 DR. HAZUCHA: There is no minimum

15 exchange.

16 CHAIR BRAIN: You don't have to get

17 rid of it anymore. You have reached that new

18 equilibrium level. Now you simply --

19 DR. DAHMS: But, then, you reach

20 maximum levels in your body, and that doesn't

21 happen. Your endogenous rate continues. You

22 can't stop it.
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1 CHAIR BRAIN: You are now no longer

2 taking up the 3 ppm of CO. You are

3 exhaling --

4 DR. DAHMS: You've got to maintain

5 that gradient to get rid of --

6 CHAIR BRAIN: But, then, you have to

7 add the 2. You are adding your own 2 ppm to

8 that.

9 DR. DAHMS: Yes. You are raising

10 your own body burden.

11 DR. HAZUCHA: You will be increasing

12 body burden, but you won't be adding. You

13 will have, indeed, steady production, let's

14 say, of endogenous carbon monoxide. And it

15 will be always produced, but if the outside

16 level is higher, you will be constantly taking

17 in until it is reached --

18 DR. DAHMS: But we will be masking

19 that.

20 DR. HAZUCHA: Yes, you will be

21 masking that.

22 DR. DAHMS: No, you will never reach
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1 an equilibrium because you are always going to

2 get rid of it.

3 CHAIR BRAIN: But now you are

4 equilibrating at this new level of five

5 instead of two.

6 DR. BLANC: So, just a final

7 question because I actually hadn't -- it is

8 helpful to see the table B-3. I guess it

9 wasn't right where the other statement was

10 made. But what are the units in this table?

11 DR. GRAHAM: Yes, I know. I

12 apologize for that not being there. It's mLs

13 per hour. If you look in table B-2, that

14 actually has the -- it is on page -- oh, I'm

15 sorry -- B-14. That confirms that and

16 provides the distributions of the endogenous

17 CO production rate that were used for males

18 and females, and females for -- stratified by

19 two.

20 DR. BLANC: So, these would be the

21 number of subjects?

22 DR. GRAHAM: Yes.
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1 DR. BLANC: Each of these? Does

2 that mean you probably could explain, label

3 the table --

4 DR. GRAHAM: Right. And again, I

5 apologize. And of course, none of the

6 subjects are identified as far as females and

7 males. I will try to get that in there as

8 well.

9 CHAIR BRAIN: Let's break for lunch. 

10 We will return and do 7.

11 I guess just a final question. I

12 found this exchange with Milan and Tom

13 helpful. Is that consistent with what the

14 document is saying or does something need to

15 be altered to reflect your understanding?

16 DR. DAHMS: It's a concern.

17 CHAIR BRAIN: Yes.

18 DR. DAHMS: This goes back to the

19 concern about the validity of the modeling,

20 and it is an uncertainty. I don't know that

21 it can be resolved. But somehow, when we get

22 to those uncertainties, we have to flesh it
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1 out a little bit.

2 CHAIR BRAIN: Well, maybe you can

3 confer. I mean I guess it is not quite clear

4 to me what we are telling the EPA, given your

5 understanding of the situation. But maybe we

6 can start with that when we come back.

7 Let's break for lunch, and we will

8 reconvene at 1:30. Maybe a few extra minutes. 

9 So, we will break for lunch and we will

10 reconvene at 1:30.

11 (Whereupon, the foregoing matter

12 went off the record for lunch at 12:36 p.m.

13 and went back on the record at 1:30 p.m.)

14

15

16

17

18

19

20

21

22
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1 A-F-T-E-R-N-O-O-N S-E-S-S-I-O-N

2 1:30 p.m.

3 MS. BARRY: Okay. It is straight-up

4 1:30. I would like us to go ahead and

5 reconvene.

6 CHAIR BRAIN: All right, I think we

7 are now up to Charge Question 7. So, we will

8 turn back to Paul to get us started on that.

9 DR. BLANC: Okay. Let's see,

10 Question 7 is the one that really addresses,

11 as I interpreted it, addresses the issue of,

12 what's the population at risk? Because that

13 has to do with the public health implications,

14 from my point of view, all other things being

15 equal.

16 Just to briefly reiterate, I think

17 that they are to be commended on the effort

18 that went into all of the parameters on

19 modeling exposure. You know, even if there

20 are suggestions on how they could bring into

21 that the estimate of indoor non-ambient source

22 exposure, and even if perhaps the distribution
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1 isn't wide enough on the endogenous component,

2 and even if there are some questions about the

3 near-roadway, some degree of potential

4 systematic underestimation of near-roadway

5 exposure, but I think all of that is kind of

6 dwarfed by this issue of who the population at

7 risk is.

8 It is not that I would suggest that

9 there be no estimation, roughly, using the

10 approach that they did of one definition of

11 the population at risk for adverse cardiac

12 events being persons believed to have coronary

13 artery disease narrowly-defined. I appreciate

14 the effort, also, of trying to estimate

15 undiagnosed coronary artery disease. But I

16 think that there needs to also be an upper-end

17 estimate provided in parallel, which is

18 exposure to people with cardiac disease

19 defined more broadly.

20 I think in terms of the estimates

21 that are there, probably the document would

22 help itself by pointing out that, although
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1 estimates based not on a National Health

2 Interview Survey, but based on the National

3 Behavioral Risk estimate survey, and based on

4 the NHANES, are slightly different, they are

5 not outrageously different, just for

6 consistency's point of view.

7 I think that this ratio that they

8 derive from the heart disease facts and

9 figures from the brochure of the American

10 Heart Association is probably a weak source

11 for an estimate of undiagnosed ischaemic heart

12 disease, unless that document itself provides

13 some coherent source of that estimate.

14 So, that would be another --

15 because, obviously, if it is double the amount

16 and not 40 percent more, it would change it

17 considerably. The problem with that number,

18 also, is I think anybody looking at it would

19 presume that the proportion is different for

20 women than for men, as women are recognized to

21 be underdiagnosed and undertreated for heart

22 disease. So, on face value, whatever the
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1 number is, there should be a sex differential.

2 So, those are my main comments in

3 terms of Question No. 7.

4 CHAIR BRAIN: Okay. Tom?

5 DR. BLANC: Just to put a number by

6 it, by the way, I mean the National Health

7 Interview Survey number is approximately three

8 times as large, if you say heart disease

9 generally. I think that is about the range. 

10 It is quite a bit larger.

11 CHAIR BRAIN: So, one possibility is

12 not to substitute that larger number, but to

13 add it and say, if you would also include

14 these other --

15 DR. BLANC: Yes. I mean the same

16 way that you model, if we are just at the

17 standard, if we are at the 99th percent, so I

18 think it is worth seeing, what are we talking

19 about, if we are not talking about this

20 definition of disease? And I think that the

21 biological plausibility is there.

22 CHAIR BRAIN: All right. Tom?
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1 DR. GRAHAM: May I just ask a

2 question? Just so I'm clear on this, I think

3 you referred to NHIS, which is where we

4 derived the original dataset. You are

5 suggesting there's additional information on

6 coronary disease as a whole?

7 DR. BLANC: Well, you took the

8 coronary disease column, and then there's all

9 heart disease.

10 DR. GRAHAM: Right. All heart

11 disease. I'm sorry.

12 DR. BLANC: Yes, right there.

13 DR. GRAHAM: Right.

14 DR. BLANC: If you could be

15 consistent --

16 DR. GRAHAM: Right, and use the same

17 approach that we did to stratify it by age and

18 gender.

19 DR. BLANC: Yes, yes.

20 DR. GRAHAM: Okay.

21 CHAIR BRAIN: Tom?

22 DR. DAHMS: I have just one concern. 
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1 I may have missed it someplace in the text of

2 this. But the number of people, person-hours,

3 everything else at risk, has been listed for

4 LA and Denver in detail. How are we to

5 connect this to the whole country, because you

6 are using whole country data for heart

7 disease? So, I was having trouble going to

8 the whole U.S. population when you take the

9 number of people with coronary artery disease,

10 or however you want to define it for the whole

11 country. I don't know how to go from the

12 exposure data from these two cities to the

13 whole country. How do we do that?

14 DR. GRAHAM: Right, and that is an

15 important question. I mean these two case

16 studies represent two specific locations in

17 the United States. As you can see by the

18 results, we have two different sets of results

19 that are different. Or shall I say I said

20 that already?

21 How that relates to other locations,

22 in the past what we have done, like for NO2,
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1 we had information on what may be influencing

2 these concentrations, and then, comparing that

3 within these locations to other select

4 locations across the United States to get a

5 feel for, well, where does Los Angeles fit

6 with respect to air quality data? Where does

7 Los Angeles fit with respect to time spent

8 inside vehicles, since we see that that is

9 important in determining high-end exposures? 

10 So, that type of information could be included

11 in this final discussion, as far as the

12 representation of these two locations.

13 DR. BLANC: I think he was asking,

14 rather, did you, beyond an age/gender

15 adjustment, were there other adjustments for

16 region of the United States or for race in

17 terms of heart disease?

18 I thought that is what you were

19 asking.

20 DR. DAHMS: I was really trying

21 to --

22 DR. BLANC: You just did a
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1 gender/age adjustment, but not adjusting on --

2 you assumed the national rates were --

3 DR. MURPHY: Yes, just to clarify,

4 is that what you were asking? It sounded

5 different.

6 I mean there are two things. One,

7 we took the national estimates of prevalence

8 of the disease that we had stratified by

9 gender and age, and then applied that to the

10 two study populations.

11 But you seem to be asking a question

12 from the other perspective, of taking the

13 results from the two study areas and saying,

14 what do they mean with regard to the rest of

15 the country? That is what we --

16 DR. DAHMS: That was the question I

17 was really asking. How in the world do we

18 apply this? Because it is not the Denver/LA

19 EPA. It is the U.S. EPA.

20 DR. MURPHY: Right, and what Stephen

21 said is, well, they provide us information,

22 and we need to, then, look at that and put
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1 them in context, to the extent we can. It is

2 not unusual for the different pollutants we do

3 different things. It is unusual for us to do

4 a national risk assessment. Usually, we do

5 case study risk assessments for different

6 areas where we have the best data, for

7 example, or we have a particular interest.

8 Then, we try to look at those

9 results and put them in the context of other

10 information we have nationally to help inform

11 the Administrator's decisions about what

12 significance they are going to ascribe to

13 those data.

14 In this case, for example, the

15 differences that we see between the study

16 areas, that will be important to consider as

17 well, how prevalent are such differences in

18 other cities across the country.

19 DR. DAHMS: I guess it just gets to

20 the whole idea, and I don't know whose task it

21 is in this whole chain of command to decide

22 what's an acceptable number of people to be at
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1 risk. Is that totally the Administrator's

2 decision? When do we get anxious about there

3 being too many people, too many days at risk

4 in the country?

5 DR. MURPHY: Right, and that is what

6 Lydia was referring to this morning, is

7 clearly a public health policy-based judgment. 

8 That is a judgment made by the Administrator

9 in deciding in the end on what the standard

10 ought to be. There are a lot of things that

11 need to be weighed.

12 Our job, in terms of writing the

13 assessment, the staff's job in terms of

14 writing what used to be the staff paper, and

15 is now the Policy Assessment, is to try to

16 pull together all the appropriate options that

17 are reasonably supported by the scientific

18 data and the analyses that we have done, and

19 that could be described to the Administrator,

20 so that they can understand what the weights

21 are scientifically behind the information that

22 we have, and they can understand what the
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1 science policy judgments are that need to be

2 made. Then, there will need to be decisions

3 made.

4 We do it with every standard that we

5 set. Lead was mentioned earlier. Lead had

6 its own host of public health policy decisions

7 to be made in terms of IQ results, et cetera.

8 So, it is something that the agency

9 struggles with. It is, in the end, the

10 Administrator's decision. But, as Lydia

11 mentioned, it is also an area where we are

12 interested in the Panel's views in terms of

13 how well we have characterized what the

14 evidence and the science support in terms of

15 the range of public policy options.

16 CHAIR BRAIN: Thank you. Tom, other

17 comments?

18 DR. DAHMS: No.

19 CHAIR BRAIN: Francine?

20 DR. ROBERTS: I just had an

21 observation there. Would it help -- and I

22 didn't see this -- would it help to actually
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1 translate the numbers of people from LA and

2 Denver to a national, to have a national table

3 somehow that says this results in X number of

4 people in different exposure or COHb

5 categories?

6 Because that is part of it. I guess

7 it is percentage.

8 DR. DAHMS: But we don't have

9 exposure data for the rest of the cities.

10 DR. ROBERTS: No. You have to

11 explain that you are using this to represent

12 the rest and how well that does.

13 CHAIR BRAIN: But they don't

14 represent very well the rest of the country.

15 Francine?

16 DR. LADEN: Okay I don't really

17 have very much to add. I just wanted to say

18 that, I mean, I think this is an interesting

19 challenge because the CO levels have decreased

20 so significantly over what the standards are,

21 and how to express that, you know, what the

22 public health risk is, I think is important. 
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1 It is, obviously, very important, and I think

2 an interesting challenge.

3 In terms of just a little comment

4 that Paul had brought up about the undiagnosed

5 rates between males and females, I had

6 mentioned that in my response to Question 5. 

7 I think that is an important question. I

8 don't think we can assume that they are the

9 same.

10 It seemed like those rates, the

11 undiagnosed rates, were from 1990. I am not

12 sure that they would still, if we really think

13 that they are the same now. So, just how does

14 that relate to what today's reality is, I

15 don't know.

16 CHAIR BRAIN: Yes, it is an

17 interesting question. To what extent do we

18 address and summarize where we are today? And

19 what are the current levels? I suppose the

20 decision is more about the standard and what

21 we will expect as different alternatives to

22 the standard.
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1 DR. ROBERTS: The standard would be

2 easier to meet if --

3 DR. LADEN: Exactly. It should be

4 easier.

5 DR. BLANC: Can I just ask one

6 follow-up question just to clarify?

7 I think it is the case that the

8 activity diary data that went into the

9 modeling was area-specific.

10 DR. GRAHAM: No, and the answer, the

11 reason for that is, of course, there is a

12 limited number of diaries that are used. I

13 mean the maximum is about 35,000. That

14 includes individuals of all ages. We reduce

15 that automatically by just simulating all

16 adults 18 and over. So, there's a smaller

17 number of diaries that are available.

18 Not all the diaries have location19 specific information. You will find that with

20 a lot of these diaries, that there may be some

21 lapses in the data provided for age or gender. 

22 So, there's a limited number of diaries that
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1 can be used.

2 So, if we were to use, say, diaries

3 that came specifically from, say, California,

4 we would have an extremely limited pool of

5 data available to do this simulation for the

6 entire population. So, it may not necessarily

7 be representative, based on those limited

8 diaries.

9 However, we know that there are

10 activities that people perform in locations

11 that they visit that are influenced by certain

12 attributes like temperature. That is actually

13 used as a variable to sample for.

14 So, we know that in, say, Los

15 Angeles the maximum or the mean temperature

16 was 55. Well, then, we draw from diaries that

17 actually have a temperature that corresponds

18 to, say, between 50 and 60, so that we can

19 reproduce the activities that people might

20 perform, given the general temperature, which

21 is more of an influential variable likely

22 than, say, a specific location. So, in a
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1 sense, the diary simulation for the population

2 in each area is representative but not from by

3 that person.

4 DR. BLANC: Right.

5 DR. GRAHAM: We also stratify by

6 other variables like, say, day of week. We

7 know that our activities during the week as

8 adults are generally driven by our workplaces

9 and time spent indoors. But on the weekends,

10 it might be something different. So, we

11 stratify the diaries that way.

12 DR. BLANC: The reason I asked the

13 question is because you made the comment that

14 is quite correct that exposure is -- and you

15 showed us day to that effect, too -- that

16 exposure is driven by commuting time, and

17 commuting time in Los Angeles is certainly on

18 the higher end. I don't know the Denver

19 patterns as well.

20 DR. GRAHAM: Right. Well, in one of

21 the appendices there is a comparison of the

22 CHAD as a whole for the population age 18 and
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1 above, I think stratified by various age

2 groups. In there, we compare that

3 distribution of drive times, in-vehicle drive

4 times, with that that we have got from the --

5 it's Appendix E. We compare that with the

6 distributions obtained from the Census as far

7 as time spent and the percent of vehicles

8 spent -- I'm sorry -- the percent of --

9 DR. BLANC: Nationally or for the

10 two locations?

11 DR. GRAHAM: For the two locations,

12 Denver County and Los Angeles County.

13 DR. BLANC: And did it come out

14 okay?

15 DR. GRAHAM: Yes, they looked very

16 comparable. I mean, of course, there is going

17 to be some locations or shall I say some

18 differences in some of the time for some of

19 them, but if you look at the numbers, they are

20 very comparable.

21 CHAIR BRAIN: All right. Any other

22 comments on 7?
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1 Let's go on, then, to the last

2 Charge question. That's Number 8, and Paul

3 Roberts will lead us on that.

4 DR. ROBERTS: So, this has to do

5 with the views of the Panel on the adequacy of

6 the assessment of uncertainty and variability,

7 and how they have been identified and what

8 their implications are, and to what extent it

9 is adequately described. So, this is the same

10 approach that was in the previous draft table

11 with qualitative low, medium, and high in

12 direction.

13 I think this is pretty good. I

14 still repeat my comments from the previous

15 one, which I would much rather see some

16 sensitivity runs on the ones of most concern. 

17 I realize the time schedule, but I still think

18 that is a better approach in general.

19 I guess I am still getting used to

20 this new system, but I would still like, even

21 though I guess it has been said that the

22 summary of this is in the PA, I would still
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1 like some summary in here of what this means

2 in this document before someone goes on to

3 read the Policy Assessment. But maybe that is

4 just me.

5 I guess, let's see, one other -- I

6 think, in general, the improvements from the

7 first draft to the second draft have, like in

8 terms of the micro-environments, for example,

9 et cetera, those have reduced the impact of

10 those parameters on the overall results, and

11 that is reflected here. I think that is good.

12 You know, there are still some

13 uncertainties here. I think the significant

14 improvements, though, have resulted in better

15 representing the tail of the distribution that

16 we are most concerned about, again, the near17 roadway and in-vehicle exposures. So, I think

18 that is good.

19 I could quibble about a couple of

20 small words, but I can put those in my

21 detailed comments. I am talking mainly about,

22 I guess, it is the first 10 or so here. 
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1 Others can comment on the last three or four

2 that are more related to the rest of the

3 panel's comments.

4 CHAIR BRAIN: Thank you.

5 Joel, Dr. Kaufman, are you with us?

6 DR. KAUFMAN: I am.

7 CHAIR BRAIN: Oh, thank you.

8 DR. KAUFMAN: But I don't have

9 anything to add here.

10 CHAIR BRAIN: Okay. Very good. 

11 Anyone else want to comment on Charge Question

12 8? Milan?

13 DR. HAZUCHA: I have, actually, two

14 questions.

15 One is the activity pattern is over

16 30 years old. Nowadays, our activity pattern,

17 we are much more sedentary. We spend more

18 time in vehicles.

19 Is there any way that you can update

20 the activity pattern?

21 DR. GRAHAM: Well, I think there is

22 a table, if somebody could help me out here as
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1 far as the activity patterns that were used. 

2 I think it is in Chapter 5.

3 Some of the data actually do come

4 from more recent studies that were conducted

5 internally, as well as I think some external

6 studies funded by the EPA, and includes a

7 number -- I think we have increased that

8 dataset that we originally used back in 2000,

9 we have increased it by 15,000 person-days.

10 While your comments are reasonable

11 in suggesting that persons' activities have

12 changed over time, we may spend more time

13 indoors or it is possible that we are more

14 sedentary, as you suggest. But there's no way

15 for us to actually compare, say, data now to

16 the prior data that were available because of

17 a lot of the differences in the surveys

18 themselves. There may be different micro19 environments that were identified or missing

20 information regarding activities performed or

21 different descriptions of activities.

22 So, in a sense, if you were to
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1 compare a given parameter, like, say, time

2 spent outdoors with the more recent data to

3 the earlier data of time spent outdoors, you

4 might end up with a significant effect, but it

5 is more related to the study rather than the

6 actual differences in persons' behaviors. So,

7 it is a very difficult thing for us to

8 actually -- if there were significant or

9 statistically-significant effects, is it

10 because of that or is it because we are doing

11 a better job of characterizing where people

12 are and what they are doing?

13 But there are recent data.

14 DR. HAZUCHA: Yes, okay.

15 The other question which I have is,

16 this APEX model has built in internal, what I

17 would call, consistency checks between input

18 variables. Like, for example, and I guess we

19 already discussed it briefly in the morning,

20 if you, for example, select in the model

21 somebody with CHD, and then there is randomly

22 assigned an activity level. That individual
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1 may not, for example, perform beyond a

2 moderate level. He or she may have

3 difficulties even with upper level of a

4 moderate exercise level.

5 So, are there any internal checks

6 that, if you select a CHD patient, heavy

7 exercise is out? Or if you select some other

8 patient or other individual, something else is

9 out?

10 DR. GRAHAM: But for the CHD

11 population, that is not something that we

12 would correct for at this time. Right now,

13 what we have is an algorithm that directly

14 applies to what is called excess post-oxygen

15 consumption that is over a period of time,

16 like you suggest. No, I'm sorry. Let me talk

17 about something else.

18 It is the METS distribution, right. 

19 There is actually a control on the METS

20 distribution itself that, again, a person

21 couldn't necessarily keep performing activity

22 after activity at a strenuous level. So, we
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1 do have an algorithm that controls for that. 

2 But, again, that is based on the general

3 population. It isn't necessarily driven for

4 the CHD population.

5 CHAIR BRAIN: Other comments about

6 this charge question or any other one?

7 DR. BLANC: Well, I have a question

8 for Paul.

9 We had talked earlier about the

10 systematic possible effect of underestimating

11 near-road exposure. So, where on the grid of

12 this table of uncertainty on exposure and dose

13 estimates would that be? And is the direction

14 of the influence of uncertainty appropriately

15 characterized?

16 DR. ROBERTS: You know, I guess it

17 is the micro-environmental algorithm and input

18 data. It is a medium-medium.

19 DR. BLANC: So, it's not under

20 spatial temporal representation?

21 DR. ROBERTS: Well, I don't know. I

22 wouldn't put it there. I guess I would put it
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1 under how the algorithm is actually working. 

2 I don't know. I had trouble figuring that out

3 earlier.

4 DR. BLANC: And is that the one that

5 says, direction unknown?

6 DR. ROBERTS: Yes.

7 DR. BLANC: But, basically, I think

8 it needs to be made clear that if the

9 direction is, in fact, not unknown, but more

10 likely to be underestimation, at least in

11 terms of that issue, it should be stated, if

12 I understood the critique correctly.

13 DR. ROBERTS: If that is the right

14 category. Maybe somebody else can tell me

15 where -- I'm not sure where else that comes.

16 DR. BLANC: Because one thing I

17 would say is that, at least in the current

18 formulation where it says, CHD prevalence, I

19 would say that the direction is probably --

20 well, first of all, the magnitude of the

21 uncertainty is high because it is a major

22 final driver in the number of people exposed.
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1 I think that our knowledge base

2 uncertainty isn't medium. It is probably low. 

3 It is just how you use the data. Let us say

4 we have epidemiologic data on prevalence. It

5 just depends on what you are defining as

6 disease.

7 And the direction is that the more

8 narrowly you define disease, the more likely

9 you are to underestimate the population at

10 risk.

11 I wouldn't agree with the

12 characterization of the uncertainty issues as

13 stated here.

14 DR. GRAHAM: I just want to comment

15 on the in-vehicle micro-environment, as far as

16 the exposure concentrations being over- or

17 underestimated. I do have some discussion

18 about that, not about the over- or

19 underestimation, but there was a limited

20 comparison that I could do to literature data

21 that were available. It is on page 6-5.

22 This has to do with the scenario
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1 where we estimated people's exposure with just

2 meeting the current air quality, that

3 particular scenario, and again, which used the

4 1995 data. At that same time, not that same

5 exact time, but I think it was 1997, where

6 they collected some measurements for in7 vehicle concentrations. Those are presented

8 there as well.

9 You can see that our upper end is

10 actually above that which was measured in this

11 particular study. I think they measured less

12 than 10 for a two-hour average concentration,

13 which, of course, is different from the

14 averaging that we are reporting here for

15 hourly concentrations.

16 But it gives you a feel or a sense

17 of where we are with respect to hour

18 estimation. We have concentrations maximums

19 going upwards to, I think it is 30 or, yes,

20 upwards to 60 ppm.

21 Then, there was this other study

22 available as well -- where they actually had
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1 more individuals, a greater number of

2 commuters where they estimated in-vehicle

3 exposures. Those went upwards to 46, I think,

4 yes, 46 ppm.

5 So, again, I know it is a limited

6 comparison, but it should give you some

7 perspective on the relationship between our

8 upper end and some of the upper ends that have

9 been reported in the literature.

10 CHAIR BRAIN: All right. Any other

11 comments from the agency or from anyone else

12 on the panel on the REA?

13 (No response.)

14 CHAIR BRAIN: Well, let me just very

15 quickly sort of tell you where we are going

16 and how we are going to get there. Again,

17 this is a familiar process. It is what we did

18 the last time as well.

19 So, we are hoping, more than hoping,

20 we are expecting that the topic leaders for

21 each of the charge questions will put together

22 what they feel is a reasonable consensus
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1 statement. So, again, your job is to put

2 together something that really sort of almost

3 everyone can sign on. If there are more

4 detailed comments, put them in your own

5 individual comments. If you feel they are

6 really idiosyncratic and not widely shared,

7 then, again, put them in your own individual

8 comments.

9 What we are going to do is, if you

10 send those to Kyndall probably anytime until

11 nine o'clock or something like that, she will

12 put them together after the charge questions,

13 and we will have a first draft of our letter

14 to the Administrator.

15 She will print that out, and we will

16 look at it tomorrow, which I think is really

17 important because there is some difference of

18 agreement and there's some tough problems that

19 it wasn't exactly clear how we were going to

20 frame our answer. But if we can put together

21 our best shot, then tomorrow morning we will

22 find some time to look at that, and not to
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1 wordsmith it, but really for everyone to say,

2 yes, this is generally what I can sign my name

3 to.

4 It will also be an opportunity for

5 the agency to look at it and say this doesn't

6 make sense; I don't understand where you are

7 going with this. So, tomorrow is really an

8 ideal time to get some feedback on the general

9 direction of those comments.

10 Then, you will have an extra couple

11 of days -- maybe we will announce that

12 tomorrow, but probably through the end of this

13 week or something -- to improve those. Then,

14 next week we will go to work and do some

15 additional wordsmithing and try to make it

16 more coherent and integrated and see if

17 there's any conflicts between one question

18 saying one thing and another question saying

19 something else.

20 We will, then, send that to you for

21 you to look at and give you a little time to

22 look at. Then, when we have done our best
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1 collectively, then we will send it on to the

2 CASAC Committee, and there will be a

3 teleconference, which you already know about,

4 April 19th.

5 So, yes, in fact, working backwards,

6 in order to have a legal teleconference on

7 April 19th, it needs to be posted, what, a

8 week before that? Something like that. Plus,

9 we want to give CASAC time to look at it,

10 which I think is particularly important since

11 CASAC is not adequately represented or is not

12 widely represented at this meeting.

13 So, then, CASAC will look at it. 

14 They will make a few more edits. Then, it

15 will go off to the Administrator. So, that is

16 the general process.

17 The other thing, as you are

18 preparing your best draft for tomorrow, if you

19 think there are things that should be part of

20 this two-page highlights letter to the

21 Administrator, let us know. I will be looking

22 at that, and I've got a few notes already of
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1 things that I think are big issues that we

2 want to bring simply to her.

3 DR. BLANC: I'm sorry, Joe, now I am

4 confused. You are saying there are going to

5 be three documents, a highlights letter, 

6 bullets, and then our own detailed comments?

7 CHAIR BRAIN: Yes. So, the first

8 letter is a two max, you know, about a two9 page letter to the Administrator saying

10 general comments. We like it. We don't like

11 it. Here's some big problems you need to

12 really think about or major comments.

13 Then, that is followed by the first

14 attachment would, then, be the Panel consensus

15 on the answers to all the charge questions, as

16 well as other major topics. Again, we don't

17 need to be confined by the charge questions.

18 For example, it came up this morning

19 that we have some comments on the new graphs

20 that were presented to us. So, if that

21 doesn't intersect adequately with a charge

22 question, that can be a completely new topic.
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1 Or you may have some other comment that you

2 think came up. So, we need not be constricted

3 by that.

4 But, yes, so there is the two-page

5 letter. Then, comes Attachment A. Well,

6 then, there's the members of the Panel. Then,

7 comes the Attachment A, which are the answers

8 to all the charge questions with an adequate

9 amount of detail. That is usually 10-15 pages

10 or something. Then, comes everybody's

11 individual comments.

12 MS. BARRY: Did that answer your

13 question?

14 DR. BLANC: Yes, I just didn't

15 remember that last part as being what happened

16 last time.

17 CHAIR BRAIN: Yes. And you should

18 have, on the website are the letters that went

19 forward from the Committee last time.

20 DR. BLANC: I just remember the

21 integrated comments. I don't remember a bunch

22 of additional comments.
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1 MS. BARRY: The members always have

2 an opportunity following the meetings to

3 revise your individual review comments. So,

4 you will have an opportunity. We always

5 append any revised comments to the letter

6 because a lot of times the agency has

7 requested specific references that have been

8 discussed. So, that is generally an

9 opportunity for you all to identify other

10 references that may be useful.

11 So, we have the cover letter. We

12 have the consensus responses to the charge. 

13 Then, there's always opportunity for a

14 compendium of individual review comments to

15 also be attached to make this final report

16 that goes to the Administrator.

17 CHAIR BRAIN: In the case of the

18 REA, you might find it useful to look at the

19 final document that did go from CASAC to the

20 Administrator, which was our report, because,

21 again, it will remind you of some of the

22 issues that we addressed last time. One of
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1 the questions is, were all those concerns

2 addressed as best as they could or not? But

3 that will also sort of let you see what the

4 final document looked like. That is available

5 on the website.

6 Or, if you need a hard copy -- in

7 fact, is it trivial for you to send that as an

8 attachment to everybody?

9 MS. BARRY: The previous letter?

10 CHAIR BRAIN: Yes.

11 MS. BARRY: No, that's easy.

12 CHAIR BRAIN: So, why don't you send

13 out the previous letter for the REA? That

14 will both serve as a draft as well as some

15 context and background for this letter. 

16 Again, one would hope that the two letters are

17 somewhat coherent.

18 So, does that all make sense? So,

19 give it your best shot.

20 Yes, we are now going to make as

21 much progress as we can with the Policy

22 Assessment. We will do the same to the extent
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1 that topic leaders can produce a consensus

2 report, even though we won't complete the

3 discussion today. Again, we can ask Kyndall

4 to pull those together, and at the end of our

5 meeting tomorrow we can at least look at the

6 answers to the charge questions that we have

7 addressed today.

8 Again, the major question is for you

9 to all have a chance to say, yes, that is my

10 recollection of our discussion; that

11 represents a consensus statement. Or, if

12 there is something that still needs to be

13 resolved, this will be an ideal time to

14 resolve it.

15 Then, Kyndall, there is also dinner

16 is going to be at 7:30 with people leaving at

17 7:15, and the destination is --

18 MS. BARRY: We'll work on that. If

19 you guys are not opposed to trying some

20 Mexican food -- notice the air quotes -- if

21 there are any objections, let me know and we

22 will pick somewhere else.
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1 CHAIR BRAIN: So, the plan for

2 those, do they need to let you know if they

3 are able to come or not?

4 MS. BARRY: Well, I have got a hint.

5 CHAIR BRAIN: Okay. So, meet in the

6 lobby at 7:15, dinner at 7:30, back at 9:00 or

7 9:30 or something probably.

8 So, any other questions about that? 

9 We are surprisingly on time. As is true, some

10 areas took longer than anticipated, but,

11 fortunately, that was compensated by others

12 that were less complicated.

13 So, let's now turn to the next step

14 in the process. So, after the ISA comes the

15 REA. Then, comes the PA. So, we are getting

16 closer to a real decision. So, let's hear all

17 about the PA. You will hear a little bit more

18 about the philosophy and how it will be used

19 by the Administrator. Then, we will hear

20 about the document itself. Then, we will move

21 to the charge questions.

22 So, we will turn it over to EPA
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1 staff.

2 DR. MURPHY: Sure. While he is

3 getting the slides up, I will remind you all

4 of the team. We have changed faces here at

5 the table. Again, Deidre Murphy here as the

6 team lead, and we have Dr. Inez Pagan, who is

7 the lead on the Policy Assessment document,

8 particularly for the health aspects. Then, we

9 have Dr. Meredith Lassiter, who is the lead on

10 the secondary standard, the ecological

11 aspects, and Dr. Pradeep Rajan, who is the

12 epidemiologist on the team.

13 So, the team we just introduced. 

14 The overview, we are going to go through the

15 Policy Assessment, touching on the purpose and

16 description, as we did this morning as well. 

17 Then, just reminding you all on what's in the

18 document in terms of the considerations raised

19 for primary standards and consideration of the

20 secondary standard, and then, briefly, an

21 overview of the subject areas for the CASAC

22 charge.
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1 Just a reminder, as we did this

2 morning of the role of the Policy Assessment 

3 and the purpose, it is a staff analysis of key

4 science policy issues. It is created to

5 facilitate the Administrator's judgment and

6 review of the CO NAAQS, so that we create this

7 document, and then we go into briefings with

8 the Administrator to help identify what should

9 go into the proposal notice, as Lydia

10 mentioned this morning.

11 This is the step preceding

12 development of a proposal notice. So, this

13 document is intended to interpret and

14 integrate information from both the ISA and

15 the REA. As we said before, often, we have a

16 lot of evidence presented in the integrated

17 science assessment, some of which will be used

18 to design and frame the quantitative analysis

19 that is in the REA document, and some of which

20 doesn't quite fit into that box, if you will,

21 but it comes back into the conversation, comes

22 back into our consideration in this document.
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1 So, that we try to consider all of

2 the evidence and any of the quantitative

3 analyses that we have performed. So, by

4 default, then the Policy Assessment will

5 include consideration of ISA evidence and our

6 quality analyses perhaps that are beyond the

7 focus of the quantitative REA.

8 Also, as was mentioned this morning,

9 the document facilitates our getting your

10 advice on the adequacy of the current

11 standards and on any appropriate alternative

12 standards. That, also, Lydia tried to explain

13 this morning.

14 As I mentioned, this precedes the

15 rulemaking phase, which, as you will recall,

16 we have a court-ordered date for a proposal

17 notice to go out in October of this year. So,

18 we are keeping to a very rapid pace.

19 With that, I will turn it over to

20 Dr. Pagan to continue on.

21 DR. PAGAN: So, we have a very brief

22 presentation.
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1 In the Policy Assessment, we have

2 framed our discussions around policy-relevant

3 questions with regard to the adequacy of the

4 current standard and the alternative

5 standards. The overarching question with

6 regard to the adequacy of the current standard

7 addresses whether the current available

8 scientific evidence and exposure and risk9 based information, as reflected in the ISA and

10 in the Risk and Exposure Assessment, supports

11 or calls into question the adequacy of

12 protection afforded by the current CO

13 standards.

14 With regard to the alternative

15 standards, that same information is used to

16 support consideration of alternative standards

17 to the current CO, and the focus would be to

18 provide increased protection to ambient CO

19 exposures.

20 The discussions included that the

21 evidence-based considerations indicate since

22 the last review that ischemia-related effects
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1 is the most sensitive endpoint. Hypoxia due

2 to increases in COHb levels is the best

3 characterized mechanism of CO-induced effects.

4 Cardiovascular diseases and other

5 diseases that have limited oxygen availability

6 are potential susceptibilities.

7 DR. BLANC: And what does,

8 potential, mean to you?

9 (Laughter.)

10 DR. PAGAN: Well --

11 DR. BLANC: Don't you see potential

12 as an extremely weak adjective in that

13 sentence?

14 DR. PAGAN: At their potential, we

15 can speculate on --

16 DR. BLANC: But it is not

17 speculation. Didn't the ISA have a very

18 different take on that?

19 DR. MURPHY: No, the ISA had a very

20 similar take on it. It used the words,

21 potentially susceptible. We drew from the ISA

22 in the language that we used in the Policy
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1 Assessment, and it used the words, potentially

2 susceptible.

3 DR. PAGAN: I think we have

4 characterized what the ISA has put together,

5 was summarized on this.

6 And as we were discussing before,

7 the coronary artery disease continues to be

8 the best characterized susceptibility.

9 Clinical studies and estimates of

10 COHb levels associated with ambient CO

11 exposure play a key role in our conclusions on

12 ambient CO levels associated with health

13 effects.

14 Since the last review, we have an

15 expanded epidemiological database and

16 specifically very strong in supporting

17 ischemic outcomes, and it is in coherence with

18 the clinical evidence.

19 Previously, we still have some of

20 the identified uncertainties from previous

21 reviews remaining. Those are the key, most

22 important, the clinical significance of
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1 ischemia-related changes that are observed at

2 the lowest levels tested in the controlled

3 human exposure studies; the CO and the COHb

4 levels at which potentially-susceptible

5 populations may be affected and the exact

6 nature of those effects. Of course, the

7 expanded body of epi data includes its own set

8 of uncertainties.

9 CHAIR BRAIN: I just have one

10 question. On that first, the word ischemia or

11 ischemia-related or ischemic outcomes appears

12 three times. I mean, aren't we really talking

13 about diminished oxygen delivery? And, yes,

14 when you have ischemia, that sort of sets the

15 stage for further decreases in oxygen delivery

16 being important.

17 But, I mean, in none of these

18 situations -- I mean ischemia is not an

19 outcome. We don't measure ischemia. So, I

20 think hypoxemia is a much better word

21 throughout.

22 Tom agrees, yes?
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1 DR. PAGAN: Yes, and the

2 epidemiological database has been

3 characterized as ischemic or ischemia-related

4 outcomes in the ISA, but --

5 CHAIR BRAIN: Well, maybe we need to

6 go back. I find it misleading. Am I the only

7 one? No.

8 Yes?

9 DR. THOM: If it is in your

10 epidemiologic data, it is the wrong word.

11 CHAIR BRAIN: Yes, it is really

12 hypoxemia or hypoxic-related effects.

13 DR. THOM: Yes.

14 CHAIR BRAIN: It is lack of oxygen

15 delivery. I mean in no case, nobody is

16 measuring changes in blood flow.

17 DR. MURPHY: If I could just make

18 sure we understand the point, in terms of the

19 outcomes in the epi database, it is IHD,

20 ischemic heart disease, is the outcome that --

21 CHAIR BRAIN: It is not the outcome. 

22 It is the susceptible population.
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1 DR. MURPHY: In the epidemiological

2 study?

3 DR. BLANC: Yes, I can see the

4 problem here. No, you're quite correct, in

5 the epidemiologic literature what the

6 endpoints are are hospital admissions for

7 ischemic heart disease or acute MI.

8 CHAIR BRAIN: Okay.

9 DR. BLANC: Or due to compensation

10 of CHF. So, I think the wording problem is

11 mixing up probable mechanism with what the

12 endpoints are. Of course, the endpoint in the

13 main study that is used for the dose response

14 is EKG changes which are consistent with

15 ischemia, but it is not hypoxemia. The

16 carboxyhemoglobin level is the exposure side,

17 but the endpoint -- it is both in a sense.

18 So, you know, I see why the problem

19 is arising, but it is partly because in some

20 sense this is cast too narrowly and in others

21 maybe too broadly. But I don't see an easy

22 solution to it.
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1 CHAIR BRAIN: Well, maybe in the

2 very first bullet, if we changed it to

3 cardiovascular-related effects encompass the

4 most sensitive endpoints.

5 DR. BLANC: I certainly support

6 that.

7 CHAIR BRAIN: Right.

8 DR. BLANC: But that is part of the

9 whole problem. I am trying, while I am doing

10 this, to look through because I think, again,

11 the way this is constructed, it discounts

12 everything else except for the narrowly-cast

13 Allred endpoint. I think that fails to

14 integrate the epidemiologic literature with

15 biological controlled exposure literature, and

16 I think that is a major shortcoming, the major

17 shortcoming of this document.

18 I just think there is no way around

19 that. I think back-peddling and saying, well,

20 and there is also the possibility that it

21 might, on the other hand, have some

22 relationship to other cardiovascular
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1 endpoints, that is not what the epi literature

2 said. And even if they used the word

3 potential, they didn't use it in the same

4 implication that it has in the bullets here.

5 DR. MURPHY: If I could just clarify

6 the bullets for a minute, to make sure we are

7 all on the same page, I appreciate your

8 comments.

9 The first large set of bullets is

10 with regard to evidence available since the

11 last review and how it continues to indicate

12 things. So, things that were true or

13 concluded at the time of the last review,

14 whether or not the current evidence still

15 relates or supports that. Ischemia-related

16 effects may not be the appropriate phrase. We

17 certainly recognize that point.

18 We recognize here that hypoxia is

19 identified as the best characterized

20 mechanism. The current ISA continues to

21 support that.

22 In terms of susceptibilities, the
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1 current ISA continues to support that

2 cardiovascular and other diseases with reduced

3 oxygen availability are the key potential

4 susceptibilities and that CHD continues to be

5 the best characterized one, predominantly

6 because we do have the controlled studies on

7 that.

8 Then, lastly, under this as a sub9 bullet, that the clinical studies, and in

10 combination with estimates of COHb levels

11 associated with ambient, continue to play a

12 key role in helping us draw conclusions on

13 ambient CO levels that might be associated

14 with health effects.

15 Then, moving on to the next large

16 bullet, since the last review, what has

17 changed, one thing that has changed is we have

18 an expanded epidemiological database

19 supporting ischemic outcomes, and that that

20 database is coherent with the clinical

21 studies. That fits together very well. That

22 was discussed this morning, I believe, in
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1 various Panel members' comments.

2 Then, lastly, we just go through

3 some of the previously-identified

4 uncertainties which still remain. Some of

5 them have been reviewed. Some still remain.

6 And then, along with the epi

7 evidence, we have its own complications for

8 interpretation.

9 CHAIR BRAIN: But I still have

10 problems with that third bullet from the

11 bottom, you know, ischemia-related changes

12 observed at low doses of CO. I mean they are

13 not -- well, maybe they are related to

14 ischemia, but it seems to me they are more

15 related to oxygen delivery. Ischemia sort of

16 sets the stage for their susceptibility.

17 DR. PAGAN: The clinical studies are

18 described as myocardial ischemia indicators,

19 which are the reduced time to onset of angina

20 or reduced time to onset of the ECG ST

21 segment.

22 CHAIR BRAIN: Well, ischemia is one
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1 contributor, but it is not the only one. No

2 one thinks, do they, that CO is affecting

3 arterial diameter and affecting blood supply

4 to the myocardium? No, I haven't heard that

5 theory. Or is that a theory?

6 DR. THOM: There's some data, but it

7 is not a lot. It is not worth going into,

8 Joe.

9 DR. DAHMS: And it's not when you

10 get diseased vessels that can't dilate. So,

11 the whole point is that it is a combination of

12 factors.

13 CHAIR BRAIN: Right.

14 DR. DAHMS: It is not just that you

15 are going to get a relative ischemia.

16 CHAIR BRAIN: Right.

17 DR. DAHMS: You are also going to

18 get --

19 CHAIR BRAIN: The consequences of

20 ischemia are augmented by CO. We are not

21 claiming that CO causes --

22 DR. DAHMS: Otherwise, if you don't
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1 use reduced oxygen delivery, then you have to

2 talk about relative ischemia and reduced

3 oxygen supply.

4 CHAIR BRAIN: So, it is okay as it

5 is? Or what --

6 DR. DAHMS: No.

7 CHAIR BRAIN: No?

8 DR. DAHMS: I think it ought to be

9 changed, but --

10 DR. PAGAN: Do you have any

11 suggestions?

12 CHAIR BRAIN: Clinical significance

13 of CO aggravating ischemia, or something like

14 that. Isn't that what we are -- or

15 interacting with ischemia?

16 DR. MURPHY: Your point being that

17 the CO is not causing the ischemia; it is

18 exacerbating it?

19 CHAIR BRAIN: Yes, and in no case

20 are you measuring ischemia. You are measuring

21 angina or --

22 DR. PENN: Why not CO-aggravated
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1 changes?

2 CHAIR BRAIN: Yes.

3 DR. KAUFMAN: I guess I would

4 interpret ST segment changes as ischemia, not

5 just hypoxemia.

6 CHAIR BRAIN: Say that again?

7 DR. KAUFMAN: If I remember

8 correctly, one of the outcomes in the studies

9 is ST segment changes, which is a measure of

10 ischemia, not just hypoxemia.

11 DR. DAHMS: But in the controlled

12 studies, it is both.

13 DR. KLEINMAN: Well, what we have is

14 a chemical hypoxia, chemically-induced

15 hypoxia, that leads to reduced supply of

16 oxygen to the heart, which is ischemia.

17 CHAIR BRAIN: No.

18 DR. KLEINMAN: Isn't it?

19 CHAIR BRAIN: Which is angina.

20 DR. KLEINMAN: Well, angina is a

21 system of ischemia.

22 DR. KAUFMAN: Depression is,
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1 although some might quibble, is considered a

2 sine qua non of ischemia, and as opposed to ST

3 segment elevation, which is infarction. So,

4 if that is what is observed as an outcome in

5 a study, then that is ischemia.

6 DR. DAHMS: Yes, but carbon monoxide

7 enhanced that, brought it on sooner, and

8 therefore, there's an underlying ischemia when

9 you are undergoing exercise that is enhanced

10 by the carbon monoxide.

11 So, you are trying to convey all the

12 things in a few words, and it may not be

13 possible.

14 DR. KAUFMAN: Well, I mean, you

15 know, if you follow the concentration/response

16 relationship, we know that at rest a person

17 can have a myocardial infarction with

18 underlying ischemia as a result of just carbon

19 monoxide exposure. It happens all the time. 

20 Carbon monoxide does that.

21 So, the question is, does it also --

22 I don't think it is a big stretch to say at
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1 the lower concentrations ischemia is also an

2 outcome, not just a bystander, I guess.

3 CHAIR BRAIN: But if we take what

4 you said, do you really think that CO acts for

5 any of these outcomes by reducing blood flow

6 to the myocardium? That if you monitored

7 blood flow through the coronary vessels with

8 microspheres or --

9 DR. KAUFMAN: Well, the ischemia

10 does not require a decrease in blood flow. It

11 requires decreased oxygen delivery to the

12 myocardium to decrease --

13 CHAIR BRAIN: That is not the Latin

14 root of the word. Ischemia has to --

15 DR. KAUFMAN: But that is the way it

16 is used --

17 CHAIR BRAIN: That may be true.

18 DR. KAUFMAN: I mean if you read a

19 cardiology textbook, they don't talk about the

20 Latin roots; they talk about --

21 CHAIR BRAIN: No, but ischemia

22 implies a particular mechanism.
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1 DR. KAUFMAN: Cardio ischemia, that

2 is what it is.

3 CHAIR BRAIN: You know, there's

4 hyperaemia, unusually high blood flow, and

5 then there's -- you know, it is relating to

6 blood flow, and we are talking about something

7 more complex, where blood flow is a critical

8 component and often the major cause, but it is

9 a different --

10 DR. BLANC: So, Joe, can I just try

11 to cut through this knot?

12 CHAIR BRAIN: Yes.

13 DR. BLANC: As I understand it,

14 where you are really taking exception is in

15 the use of ischemic outcomes more than

16 anywhere else in the bullet that says ischemic

17 outcomes.

18 CHAIR BRAIN: Outcomes usually

19 associated with ischemia or something like

20 that.

21 DR. BLANC: Well, I think really, to

22 be consistent with the ISA, what that phrase
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1 there should be is adverse cardiovascular

2 outcomes because that is what, since the last

3 review, the epidemiologic database supporting

4 adverse cardiovascular outcomes has expanded

5 and is coherent with the clinical evidence. 

6 That is what the section summarizes, the

7 summary comments on the section there say. 

8 So, that would, I think, solve it for

9 everybody.

10 DR. HAZUCHA: Well, they refer to

11 controlled human exposure studies. I believe

12 that it is reference to Allred studies. Right

13 here, and they repeat it again and again, it

14 is myocardial ischemia. Myocardial ischemia,

15 these findings show that myocardial ischemia,

16 and so on, as measured by ECG changes and

17 angina, and so on.

18 So, repeated as you go through the

19 document, it is myocardial ischemia.

20 DR. BLANC: I'm not talking about

21 Allred here. I'm talking about --

22 DR. HAZUCHA: So, we are talking
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1 about what study?

2 DR. BLANC: About the epidemiologic

3 database. Their sentence, Since the last

4 review, epidemiological database supporting

5 ischemic outcomes is expanded. It's really

6 the epidemiological database supporting

7 adverse cardiovascular outcome is expanded,

8 because that is what we reviewed and that is

9 what the summary comments are on.

10 CHAIR BRAIN: It seems to me that

11 kills two birds with one stone. It both

12 enlarges it a little bit and it clarifies the

13 messy language. Then, in detail, you can

14 parse it.

15 DR. BLANC: And the final sentence

16 of that whole section is, A causal

17 relationship is likely to exist between

18 relevant short-term exposures to CO and

19 cardiovascular morbidity.

20 So, you should be able to live with

21 that, with adverse cardiovascular.

22 DR. MURPHY: Hopefully, you all will
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1 give the same focus to the words in the

2 document as our slide. And we may have said

3 it better in the document.

4 CHAIR BRAIN: Okay, yes, let's press

5 on. I think this has been helpful. Please.

6 DR. PAGAN: Okay. So, you have

7 heard this morning on the risk, a lot about

8 the risk-based considerations.

9 The current and the potential

10 alternative lower standards provided by this

11 analysis have differing maximum COHb levels on 

12 the simulated at-risk populations.

13 For the scenario of just meeting the

14 eight-hour controlling standards, less than

15 four percent of either of the study

16 populations would experience maximum COHb

17 levels at or above two percent. On the other

18 hand, more than 80 percent of both of the

19 study populations are estimated to have

20 maximum COHb levels below 1.5 percent.

21 Just meeting the alternative eight22 hour standard of approximately three ppm would
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1 result in more than 99 percent of both study

2 populations with maximum COHb levels below 1.5

3 percent.

4 Similar to the evidence-based

5 information, with regards to the risk-based

6 considerations, some uncertainties previously

7 identified have been reduced and some still

8 remain.

9 Public health implications of the

10 exposure and dose estimate will be affected by

11 our interpretation of the clinical

12 significance of the responses observed at the

13 lowest COHb levels in the controlled studies,

14 the clinical studies. That is the weight that

15 we give to the different benchmarks and

16 judgments regarding the potential significance

17 of those estimated COHb levels, what would

18 that signify for other potentially-susceptible

19 populations?

20 So, here, in making interpretations

21 with regards to the current and alternative

22 standards, we integrate the information, the
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1 evidence and the exposure risk information, as

2 it relates to the level and form of a

3 standard. On top of that, we overlay some

4 public health policy considerations.

5 For the eight-hour standards, those

6 would be, as we had said before, the nature

7 and severity of the effects that we are

8 considering. What are the appropriate COHb

9 benchmarks to focus on? And what is an

10 adequate margin of safety for the at-risk

11 population?

12 And those same considerations would

13 apply for the one-hour standard, in addition

14 to the peak levels that this one-hour standard

15 is protecting against, and how frequently we

16 would have peaks of CO, ambient CO.

17 So, this integration is illustrated

18 in this graph. On the X-axis, we have the

19 level for the second-highest eight-hour

20 average, which is the current form, and on the

21 Y-axis we have the percentage simulated at22 risk population. We have highlighted on the
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1 X-axis where the current standard lays, which

2 is 9.4 ppm.

3 This is all related to specific

4 benchmarks. We have highlighted three

5 benchmarks here: the 1.5, which is labeled in

6 black; two percent COHb, labeled in green, and

7 2.5 COHb, labeled in orange. The solid

8 symbols represent the LA area, and the open

9 symbols represent Denver.

10 As you can see, more than 90

11 percent, with all of these benchmarks, except

12 for the one in Denver, the black open in

13 Denver, more than 90 percent of the population

14 would experience maximum COHb levels below

15 these benchmarks.

16 And this is a slide, the same

17 graphical presentation. However, we present

18 here on the X-axis, this is the level for the

19 99 percentile daily max eight-hour average,

20 which this is an alternative form than the

21 eight-hour second max --

22 DR. MURPHY: I was just going to
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1 take a moment to make sure you all understood

2 these slides because these figures are not in

3 the document, similar to some of the figures

4 we saw this morning that Dr. Graham presented. 

5 This is just another way to present the data

6 that are in the tables in the Policy

7 Assessment. This is just presenting them

8 graphically.

9 So, I wanted to make sure, if there

10 were any questions, you could ask them and we

11 could make sure you understood.

12 It is just showing -- using how you

13 can look at these data. Dr. Graham mentioned

14 this morning that the five scenarios that were

15 run actually give you information about a lot

16 of different combinations of averaging time,

17 form, and level, which might go to a potential

18 alternative standard.

19 This just illustrates different ways 

20 you can look at it for two different forms for

21 the standard, with the level varying across

22 the bottom. Both of these figures are with
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1 regard to the eight-hour standard.

2 DR. PAGAN: Any questions with

3 regards to those figures?

4 So, in summary, the adequacy of the

5 current standards may or may not be just

6 adequate, depending on judgments regarding the

7 nature and the severity of the effects that we

8 are considering at the lowest COHb levels

9 tested, the weight that we place on the

10 different benchmarks, the weight that we place

11 on the epidemiological studies, and an

12 adequate margin of safety for the at-risk

13 population.

14 With regards to the alternative

15 standards, for the eight-hour standard it may

16 be appropriate to consider a range from nine

17 to three ppm with the lower end depending on

18 the same judgments as above. In conjunction

19 with considering revising the level, it may be

20 appropriate to consider an alternative form,

21 such as the 99th percentile or fourth highest

22 daily max, average across three years.
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1 And for the one-hour standard, it

2 would be appropriate to consider a range of

3 policy options that include retaining,

4 revising, or revoking. This would be

5 depending on the role that this standard has

6 relative to the eight-hour standard.

7 DR. MURPHY: So, now we are just

8 going to switch to Dr. Lassiter for the

9 secondary standards slide.

10 DR. LASSITER: All right. To

11 address our overarching question in regards to

12 the secondary standards, does the currently13 available information provide support for

14 considering the establishment of a secondary

15 standard for CO? We considered both the

16 climate effects and the non-climate effects of

17 CO, including effects on vegetation and

18 ecosystems.

19 So, there is no evidence of pseudo20 effects on non-climate-related endpoints. For

21 the effects of CO on climate, there are both

22 indirect and direct effects. The direct
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1 effects are weak and highly variable. The

2 primary effects of CO on climate are the

3 indirect effects, which is mediated through

4 methane and through ozone formation.

5 So, we found there's insufficient

6 information at this time to interpret how

7 these ambient levels of CO, which are

8 spatially variable and localized, and depend

9 on the other atmospheric chemistry, the

10 atmospheric chemistry in local areas. So,

11 there's not enough information right now to

12 assess how these differences would affect

13 climate changes at the local and regional

14 level.

15 DR. MURPHY: And the last slide is

16 just providing an overview of the areas of the

17 charge for the CASAC review on these Panels. 

18 The questions cover the background with regard

19 to our characterization of the air quality

20 information. We have questions with regard to

21 the organization. This is one of the first

22 Policy Assessments. We previously had staff
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1 papers, and, then, for one, I guess just one

2 review or two, we had an Advanced Notice of

3 Proposed Rulemaking. Now we have a Policy

4 Assessment.

5 So, we have a question with regard

6 to the organization, have we teed-up the

7 policy-relevant questions appropriately,

8 provided the appropriate level of detail in

9 discussing them?

10 Then, specifically, with regard to

11 the primary standards, we discussed the issue

12 of adequacy of protection provided by the

13 current standards and tried to bring forward

14 what are thought to be the appropriate

15 considerations that inform that question. 

16 That goes at characterization and integration

17 of the health effects evidence, including

18 differences from the last review;

19 characterization of the quantitative exposure

20 dose estimates, as well as important

21 uncertainties, particularly those significant

22 to drawing conclusions regarding adequacy of
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1 the standard.

2 We ask about your reviews on the

3 considerations that we have brought forward to

4 inform our initial conclusions, and, more

5 broadly, as we described this morning, we are

6 interested in the Panel views on the adequacy

7 of the current standards and the extent to

8 which the current document is consistent with

9 them.

10 Then, with regard to potential

11 alternative standards, we ask with regard to,

12 have we teed-up the appropriate considerations

13 that inform a characterization of the options

14 that are appropriate for the Administrator to

15 consider and that are well-supported by the

16 information? Have we provided the rationale

17 to justify the range of policy options

18 presented? And again, more broadly, what are

19 the Panel views on the range of alternatives

20 that are appropriate to consider?

21 Then, lastly, with regard to

22 consideration of the secondary standard, we
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1 ask questions regarding our characterization

2 of the current evidence, including

3 specifically the climate-related effects of

4 CO.

5 CHAIR BRAIN: Thank you.

6 Yes, a question?

7 DR. DAHMS: I would just like to

8 clarify something and admit my total

9 ignorance. When you go back to the

10 alternative standards, you talk about picking

11 the fourth highest. Could you inform me of

12 the statistical basis of the rationale for

13 picking that number?

14 DR. MURPHY: Right. So, the current

15 form of the standard, the standard is 9 ppm,

16 not to be exceeded more than once per year,

17 and the rounding convention is such that it is

18 one figure. So, a 9.4 as a second maximum in

19 the year meets the current standard. So, that

20 is what we call a design value.

21 DR. DAHMS: So, you can exceed the 9

22 once and be in compliance?
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1 DR. MURPHY: Yes.

2 DR. DAHMS: And the second time

3 you're out of compliance?

4 DR. MURPHY: Right. So, if we have

5 an area where the second highest eight-hour

6 average CO concentration is above 9.4, then we

7 have an area that is out of attainment and

8 controls need to be brought to bear, a state

9 implementation plan developed, et cetera.

10 DR. DAHMS: And so, when you are

11 talking about the fourth, then you are talking

12 about going to the fourth incident?

13 DR. MURPHY: Right. And really, in

14 more recent standards that we have developed,

15 we tend to move away from the more

16 deterministic not-to-be-exceeded or to-be17 exceeded-only-once. It is a less-stable form

18 of the standard to use because you may end

19 with areas that go in and out of attainment,

20 just because of meteorological differences

21 year to year.

22 So, in terms of implementing the
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1 standard, you want to put a control program in

2 place and keep people in that control program

3 longer-term. So, more recently, we tend to

4 use forms of the standard that are more

5 stable, we would say, such as 98th or 99th

6 percentile daily maximum, averaged over the

7 last three years. So, the 99th percentile,

8 when you have hourly measurements over a year,

9 will correspond to the fourth highest value.

10 So, often, it is a question of, do

11 we want to call the form the 99th percentile

12 or is it more easily understood by the public

13 to call it the fourth highest value? So, that

14 is why, in the discussion in the document, we

15 say one or the other, so people understand

16 they are the same, when you have a full

17 dataset of hourly values, and the decision on

18 which it will be will be up to the

19 Administrator. Some of what is taken into

20 account is what is more easily understood.

21 But in terms of the form, that type

22 of form, which is a more stable form, is
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1 thought to be a better form in terms of

2 stability for control programs, which is

3 really what we are after in the end.

4 DR. DAHMS: So, that is not so much

5 an acute public health warning thing as it is

6 an attainment issue, right?

7 DR. MURPHY: Well, we set the

8 standard to keep the air quality where we want

9 it to be. So, there are different ways to do

10 that.

11 I am not sure how to answer the

12 question because there is not a clear answer

13 really. But one thing I would mention is you

14 can see that there's a correspondence between

15 an air quality dataset that has a second

16 maximum and a fourth maximum. So, when you

17 look at those different X-axes for the two

18 figures, you can see the same data plotted

19 there; they will just be shifted down for the

20 fourth highest because it will correspond to

21 a lower level.

22 That is perhaps a little off your
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1 question, but --

2 DR. DAHMS: Well, no, I'm just

3 thinking about the practicality of living in

4 LA and when it is really a bad day for health

5 for people with cardiovascular disease. Now,

6 let's see, this is the fourth time, so it's

7 bad, but the first time that it hits 9, it's

8 not so bad?

9 DR. MURPHY: Now you are talking in

10 terms of the public communication about, you

11 know, people's behaviors.

12 DR. DAHMS: Sure.

13 CHAIR BRAIN: And she is talking

14 about long-term planning.

15 DR. DAHMS: Oh, I know. That is

16 what I am talking about, attainment versus

17 public health.

18 CHAIR BRAIN: Right, which are

19 different.

20 DR. MURPHY: Communication. And

21 that is certainly a good point, and we have,

22 obviously, the agency has a whole program with
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1 the air quality indicator, the AQI, the Air

2 Quality Index, where we try to inform people. 

3 For example, on ozone, when we have high ozone

4 days, what are the populations that need to

5 take action? And we do that when the days are

6 just below the standard.

7 Now we haven't talked at all about

8 an Air Quality Index for CO. That would be a

9 whole other conversation. But the things you

10 are raising are things that would be pertinent

11 to that conversation.

12 DR. BLANC: So, can I clarify? 

13 There's a difference a little bit in the slide

14 I guess before this one. I'm not sure. And

15 the document, the draft document, seems to say

16 unequivocally, that whatever it may be, the

17 standard should at least be as tough as it is

18 currently. I thought on the slide it sort of

19 said, well, the policy considerations are it

20 could be as restrictive as it is or it could

21 be less restrictive or it could be more

22 restrictive.
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1 But you have already, your

2 recommendation, at a minimum in the draft, is

3 that it should at least be what it is

4 currently, right?

5 DR. MURPHY: Right. We have not

6 recommended that it should be relaxed.

7 DR. BLANC: But in that slide I was

8 confused by it because of the way it was

9 worded. I might have just read it too

10 quickly.

11 DR. MURPHY: Oh, you mean the phrase

12 "may or may not be judged adequate"?

13 DR. BLANC: Yes.

14 DR. MURPHY: The point being, if it

15 is not judged adequate, it needs to be more

16 stringent. That would be the way we would

17 view that phrase.

18 DR. BLANC: Oh, I see. Okay.

19 DR. MURPHY: Yes, yes. So, it may

20 be adequate; it may not need to be more

21 stringent, which is why our range that we say

22 is appropriate --
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1 DR. BLANC: Okay.

2 DR. MURPHY: -- extends to that

3 value.

4 DR. BLANC: Okay.

5 DR. MURPHY: Yes.

6 DR. BLANC: But the opposite is

7 true? At a minimum, you are saying it has to

8 be, what you are saying here is what you are

9 saying there? It is just worded differently? 

10 Okay.

11 DR. ROBERTS: Joe, I have one

12 question.

13 CHAIR BRAIN: Yes.

14 DR. ROBERTS: It seemed a little

15 off-base, but maybe not. In considering

16 alternative standards, can you tell us what

17 the thought process was for the NO2 near

18 roadway, in particular? I mean you haven't

19 mentioned anything like that here. The

20 alternative standards you have suggested are

21 all of the same -- well, not exactly the same

22 form, but the same approach, rather than
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1 that's a completely different approach to

2 trying to address the tail of this

3 distribution? Is that something that could be

4 considered here or should? Or how is that not

5 been thought about?

6 DR. MURPHY: I'm not completely

7 familiar with the NO2 review issues. I do

8 know that they did consider different forms,

9 and going from a more deterministic to a

10 percentile-based form. Some of the

11 considerations that are raised in the policy

12 chapter of the NO2 REA are consistent with the

13 ones we raised here in terms of judgments you

14 might make on selection of a form, that there

15 is greater stability in going to a 99th

16 percentile or a 98th. I can't remember which

17 they ended up going to, 99th or 98th.

18 DR. ROBERTS: Yes, 98. But that is

19 a near-roadway, I mean there's a near-roadway

20 standard now.

21 DR. MURPHY: Yes. Yes.

22 DR. ROBERTS: That is the part I am
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1 asking about really, not the form. Doesn't

2 that address the same kind of thing as we have

3 here, which is here's a tail that is driven by

4 the highest exposures?

5 DR. MURPHY: Well, I think one

6 difference is the dataset. My understanding

7 is they do not have monitors near roads;

8 whereas, CO monitors, while they are not all

9 near roads, many of them are because that is

10 the focus for CO, the main, the source for CO,

11 if you will. The main source is roadways.

12 So, in designing the monitoring

13 network, the first push was to put them near

14 roads. Now we currently don't have as many

15 near roads as we would like.

16 But in NO2, I thought they did not

17 have the near-roadway monitors per se.

18 DR. ROBERTS: Right.

19 DR. MURPHY: So, they ended up in a

20 different world for their --

21 DR. ROBERTS: Right, there are none. 

22 But, in hindsight now, I would judge that the
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1 CO network isn't much better. Okay? I mean

2 the new monitoring approach for NO2 is 50

3 meters, and none of these CO monitors -- you

4 know, there's one micro-site on the sidewalk

5 in Las Vegas and a couple of others like that

6 for CO, and that's it. So, the network isn't

7 really any better.

8 DR. MURPHY: Right. And one point

9 you are raising is that, as part of the

10 proposal notice, as we go forward, we will

11 consider all aspects of the standard. One

12 aspect of the standard is the design for the

13 monitoring network.

14 So, I suspect that in developing the

15 proposal our monitoring group will be looking

16 closely at the existing network and how it

17 needs to be tweaked because it has been a

18 while since we did a review of the CO

19 standard. And therefore, those monitors are

20 not any more where they perhaps would be most

21 appropriate to be.

22 My understanding in talking to some
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1 of the monitoring group is that they are

2 looking to how they are doing the design of

3 the network for NOx and thinking maybe there's

4 some similarities that could be done for

5 reemphasizing the network for CO in similar

6 ways. That goes to monitor placement, but

7 that is another aspect of the proposal that

8 will go forward. It doesn't affect the

9 standard per se in terms of quantitatively,

10 but it affects how we monitor for the

11 standard.

12 DR. ROBERTS: Now, I agree, I have

13 heard from the staff the idea that they are

14 going to put out an NO2 network with the idea

15 that they might add CO or other pollutants to

16 that same network.

17 But it seems to me for this Panel,

18 our consideration is, should we consider a

19 near-road standard, form of the standard? I

20 don't know. That is what I am asking about

21 because you haven't brought it up at all. 

22 Yet, it seems, like NO2, it could protect
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1 against the -- but am I way off? I don't

2 know.

3 DR. MURPHY: So, are you suggesting

4 that there be two types of standards? I mean

5 we were suggesting there be a standard which

6 protects all ambient air, be it near-road or

7 not-near-road, and that we need, of course, to

8 place monitors to appropriately judge

9 attainment of that standard.

10 But I am not sure I am seeing what

11 you are thinking --

12 DR. ROBERTS: Right. Well, I guess

13 I am saying we could, I guess, I am wondering

14 whether we should be considering this. We

15 could pick a near-roadway standard to protect

16 against this distribution or we could pick a

17 more stringent, you know, sort of everywhere

18 standard. In either case, we are trying to

19 address the same part of the distribution,

20 which is those people who spend time commuting

21 or near roadways. Couldn't there be both

22 considered?
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1 DR. MURPHY: Part of my handicap is

2 I don't understand exactly why the NO2

3 standard was constructed the way it was.

4 In this review, it certainly makes

5 sense, what's being considered, in terms of a

6 standard that would apply wherever there is

7 ambient air. I mean that is a usual way to do

8 it. There were nuances to the data, the

9 evidence associated with NO2, that led them to

10 what they have ultimately decided on, but I

11 don't know that all those nuances apply in the

12 CO situation. They haven't been raised

13 before.

14 DR. ROBERTS: You're probably right,

15 in that the recent epi studies have done near16 roadway mapping and imply that NO2 is having

17 more effect in that, and that is not done

18 here. But I don't see that the fundamental

19 logic really should be different. I don't

20 know.

21 Do other people have this concern?

22 DR. PENN: Well, for the PM, have
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1 they talked about near-roadway mapping also? 

2 Because there have certainly been recent

3 studies with PM trying to associate PM

4 exposure with increased admissions for asthma

5 for kids and for things like that from a

6 couple of places.

7 CHAIR BRAIN: There was some

8 discussion like that, but it never bore fruit

9 in terms of affecting the possible standards.

10 Tom?

11 DR. DAHMS: Yes, I have a question.

12 If you go to the 99th percentile and

13 levels keep dropping, that means the standard

14 keeps dropping.

15 DR. MURPHY: No, no, no, no, no. 

16 Sorry. No.

17 In judging attainment with the

18 standard, you would take the 99th percentile

19 of a year's worth of data at a particular

20 site. You wouldn't change the standard. The

21 standard would be whatever the number is. If

22 it remains 9, it will be 9. Then, you look at
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1 your dataset over the year and say, did you

2 exceed 9, or how many times?

3 DR. DAHMS: Oh, okay.

4 DR. MURPHY: Or what is the

5 distribution and what is the 99th percentile?

6 DR. THOM: But just because ambient

7 CO concentrations are dropping, by switching

8 to the 99th percentile, in effect, you would

9 be making the national standard substantially

10 lower than 9 parts per million for eight-hour

11 exposure. Right?

12 DR. MURPHY: Well, yes. That is why

13 I think we teed it up in the conclusion

14 section, that we would consider a change to

15 the form, if there was to be considered a

16 change to the standard. If we were going to

17 retain the current standard, we wouldn't just

18 change the form.

19 But you're right, there's a

20 relationship between levels. The level is

21 different for a different form, obviously. 

22 That is actually what those two figures were
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1 intended to -- one thing they illustrate is

2 that you move the curves along the X-axis

3 because you are changing the level for that

4 form.

5 DR. THOM: Okay.

6 And then, to Paul, I guess I am

7 confused, maybe because I am just ignorant. 

8 But carbon monoxide is equally as poisonous or

9 injurious to a person, whether they are on a

10 roadway or in a house. I guess I don't get

11 the logic of why you would have a standard

12 next to the road versus someplace else.

13 DR. ROBERTS: Well, I'm not sure I

14 know, Steve. Okay? But I was trying to

15 figure, if you look at some of the plots we

16 were shown this morning that were new, 95

17 percent of the exposures at the high

18 concentration are driven by the near-roadway.

19 CHAIR BRAIN: So, why doesn't that

20 affect where you put the monitors?

21 DR. ROBERTS: Right, and I guess we

22 are ignoring in-home other sources. Okay? If
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1 we weren't ignoring that, then, yes, the

2 question is completely different.

3 But if those figures are showing

4 almost all the exposure at the levels above

5 the current standard, well, at the individual

6 hours that are above the current standard --

7 I mean they accumulate to be less-than -- our

8 near-roadway, then should we be focusing on

9 near-roadway? That is sort of what I am

10 asking.

11 CHAIR BRAIN: And if so, how do we

12 focus? I mean, is it by modeling, by

13 monitors?

14 DR. ROBERTS: Yes.

15 CHAIR BRAIN: I mean you could have

16 modeling that would emphasize those higher

17 levels.

18 DR. ROBERTS: And you know, one of

19 the uncertainties in the exposure modeling is

20 taking this central site, which doesn't

21 represent those high concentrations, and

22 translating it over, because that is where the
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1 big exposures are.

2 So, I am asking, should we be

3 considering something else? I don't know. Is

4 it we can ask about a network that is more

5 focused on the highest exposure locations, but

6 not change the standard?

7 DR. MURPHY: Yes, I'm not sure what

8 you gain by -- you're suggesting there be a

9 different type of standard, and I'm struggling

10 to understand what you would gain by that than

11 what we have teed-up here, which is just

12 whether or not the current standard is

13 appropriate or needs to be lower. But it

14 would be applied to all ambient air,

15 regardless of where that is.

16 Obviously, the network needs to be

17 appropriate. With every review of every

18 standard, we look again at the network and

19 say, how's the network doing in terms of is it

20 monitoring in places with a likelihood of

21 exceeding the standard? That is the judgment? 

22 That is what the network of monitors should be
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1 doing?

2 To the extent it is not doing that,

3 it needs to be revamped. That is part of what

4 the review helps us do, is focus again on,

5 how's that network doing? Does it need to be

6 revamped?

7 And my understanding, based on

8 talking to the monitoring group, is that they

9 are already starting to look at that to see if

10 there is tightening to the distribution of

11 monitors to make sure they are appropriately

12 placed to find any exceedances that there

13 might be. That is their objective, the

14 monitors.

15 DR. ROBERTS: That's good. Maybe

16 that is the direction. Because, certainly,

17 well, I know agencies don't want to move their

18 monitors to a place that will measure a higher

19 concentration. Okay? So, there is a

20 reluctance to even consider that.

21 DR. MURPHY: That is why we have

22 regulations that require it.
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1 DR. ROBERTS: Yes.

2 CHAIR BRAIN: And, Paul, it would be

3 good if you made that clear in your

4 recommendations, even if it was a separate

5 part. You know, we talked about that before. 

6 Say something about the adequacy of the

7 network, what would an ideal network look

8 like. That would really capture your

9 concerns.

10 DR. ROBERTS: Yes, I think so.

11 CHAIR BRAIN: I think that is

12 important.

13 DR. GRAHAM: Dr. Brain, I just

14 wanted to add one thing. The current exposure

15 assessment, just as a reminder, that is linked

16 to the existing monitoring network that is in

17 those locations. So, if you are going to

18 control at the monitor, then that has going to

19 be linked to the exposures and the dose, and

20 so on.

21 CHAIR BRAIN: Okay, thank you. That

22 got us started on a lot of key issues.
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1 So, everyone should have a copy of

2 the letter from Lydia Wegman dated March 2nd. 

3 So, that includes the charge questions that we

4 will now be dealing with. So, if you don't

5 have a copy, ask Kyndall.

6 And looking at the schedule, we are

7 a little bit past the break. So, maybe we

8 should take a break for 15 minutes and return

9 a little before quarter after 3:00. We will,

10 then, begin with Arthur, who will get us

11 started on Charge Question 1. Okay?

12 So, let's take a break and let's

13 reconvene a little bit before 3:15.

14 (Whereupon, the foregoing matter

15 went off the record at 2:57 p.m. and went back

16 on the record at 3:14 p.m.)

17 CHAIR BRAIN: It would be very

18 helpful if those of you who have new comments

19 or haven't sent your comments for the REA, if

20 you could send them to the topic leader, the

21 person whose name is underlined, that would be

22 very helpful.
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1 And if you need to, when we adjourn

2 this afternoon, it is often helpful for people

3 to meet. So, if you are unclear about what

4 the consensus is or some point of

5 clarification, don't hesitate to get together. 

6 But if everyone who wants to update their

7 comments, revise it, with an eye toward what

8 the consensus should be, please send that

9 along by email.

10 So, let's now with begin Charge

11 Question 1. Arthur is going to started on

12 this.

13 DR. PENN: I found this one pretty

14 easy. Apparently, a couple of other comments

15 I have seen also thought it was pretty easy. 

16 I have just one exception.

17 A brief chapter, I thought they did

18 a very good job, a limited number of pages,

19 good introduction and background for this

20 Policy Assessment, a brief review going back

21 to the Clean Air Act and establishment of the

22 air quality standards and margins of safety
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1 and reviews and new monitors and low dose

2 levels and the NCOR network, and all that

3 stuff.

4 I thought in 12 pages everything was

5 summarized pretty well. I went through a

6 couple of the references, and they seemed like

7 they are very descriptive.

8 The one item that I take issue with

9 is on page 1-1. I think it could benefit from

10 some clarification and possibly a change of

11 location.

12 On lines 22 through 25, on page 1-1,

13 it emphasizes that the focus of the Policy

14 Assessment is on four basic elements of the

15 air quality standards: indicator, averaging

16 time, form, and level. None of those items is

17 explicitly defined in the first 46 pages of

18 the Policy Assessment.

19 Indicator and averaging time are

20 both noted on page 2-47, and they are clearly

21 defined. Level, I had a real problem with,

22 despite the footnote on page 1-1. I couldn't
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1 begin to figure out what it meant.

2 When I went back last night after

3 watching all the basketball games and the

4 votes and everything, I found, I think it was,

5 page 2-52, there was a table that was

6 presented this morning that showed that form

7 could be the 99th percentile, but it could

8 also be the second or third exceedance, or I

9 forget what the other characterization was.

10 But the explanation for form on page

11 1-1 and the footnote is, to me, inadequate

12 because it says, it defines the air quality

13 statistic without saying what it is. That is

14 to be compared to the level of the standard. 

15 So, I thought that that was not really

16 descriptive.

17 Concentration-based form without

18 explaining what form is, also, is apparently

19 an area of focus, and that is not defined. It

20 is clear on another page that form sometimes

21 equals percentile.

22 So, my question is, could all of
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1 those four things be explained as a footnote

2 of page 1-1? So, that everybody can, then,

3 follow that through, and maybe that they can

4 be explained a little bit more clearly.

5 CHAIR BRAIN: Yes, I guess I also,

6 early on, would like to point out, it seems to

7 me that there's sort of no charge question

8 that deals with the overall sort of size and

9 scope of the Policy Assessment. But I would

10 like to hear at some point, perhaps at the

11 end, you know, thinking of its destination and

12 how it will be used by the Administrator, is

13 it too short, too long? What is your sort of

14 overall assessment of too documented, not

15 documented enough, sort of some of those

16 general overarching questions?

17 Dr. Thom?

18 DR. THOM: I have nothing to add to

19 what Arthur said.

20 CHAIR BRAIN: Okay. Anybody else

21 want to talk about it?

22 DR. THOM: Is Larry on?
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1 CHAIR BRAIN: I think Larry is not

2 on the phone, wasn't able to join us today.

3 Okay. Any questions or comments

4 from the agency?

5 (No response.)

6 No?

7 DR. PENN: Could I just ask, where

8 does the term "form" come from? Because it

9 seems to be so out of keeping with all the

10 other labels and titles, and things like that. 

11 I mean, is it percentile? Why don't you say

12 percentile?

13 DR. MURPHY: Oh, no, because it

14 doesn't have to be percentile.

15 DR. PENN: But what is it? You look

16 at all these statistics and you say, well,

17 what is that statistic, and you say, well,

18 that's the form.

19 DR. MURPHY: It depends on the

20 standard. So, for example, I don't mean to be

21 facile in answer. But, for example, for lead,

22 it is a not-to-be-exceeded form. In the case
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1 of CO, it is may be exceeded once. That is

2 the form. In the case of PM, it is 98th

3 percentile. In the case of NOx, I believe it

4 is 98th percentile now. It was something

5 different previously.

6 So, the form is a statistic. It is

7 a statistic that we look at our air quality

8 dataset, we apply the averaging time, and then

9 we derive that statistic and compare it to

10 that level of the standard.

11 DR. PENN: And I think that should

12 be said.

13 DR. MURPHY: We need to say it more

14 clearly for you, yes, definitely.

15 CHAIR BRAIN: Thank you. Yes, that

16 was helpful.

17 All right, number 2, I guess 2 and

18 3. I don't know, how do you want to handle

19 those, Tom, do both at once or one at a time? 

20 What works for you?

21 DR. DAHMS: One at a time.

22 CHAIR BRAIN: One at a time, okay,
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1 number 2.

2 DR. DAHMS: All right, everyone can

3 read what's up on the screen. A lot of what

4 I am going to say you have heard before, you

5 have heard earlier today.

6 Basically, I think it lays things

7 out fairly well, but the biggest thing is not

8 dealing with the epidemiology data. To me,

9 they are rather crucial for explaining -- you

10 know, this falls under 8. "Does the Panel

11 find the questions posed appropriately reflect

12 the policy-relevant questions in this review?"

13 Without the epidemiology data

14 supporting the controlled human exposure data,

15 I would just strongly state it to be the fact

16 that it presents a real problem to me.

17 When you get into the details about

18 raising some of the concerns about the

19 controlled human subject stuff, especially the

20 Allred study, the ST segment information is

21 pulled out of there and questioned. You have

22 to understand the design of that study is that
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1 in all these studies, if you look at time to

2 angina, that is a subjective endpoint.

3 You are asking the patient to tell

4 you when their angina came on, and that can be

5 pretty variable. One person may have a little

6 bit of angina, but not really raise their hand

7 until it is severe enough that they would

8 stop. That is a very subjective endpoint.

9 So, only in concert with that, you

10 have the ST segment change that confirmed that

11 time to angina. So, to pull them apart is not

12 really legitimate, from looking at those

13 studies.

14 There is a statement on that where

15 the ST segment, the interpretation of the ST

16 segment changes is a matter of concern or

17 there's various opinions about what that

18 means. That means, to me, that you are trying

19 to pull that out, and that is the way it read. 

20 So, that needs to be fixed. Otherwise, you

21 have to have ST segment changes have to be

22 valid; otherwise, how could you ever determine
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1 silent ischemia? So, that was on page 2-32,

2 I think that all that was going on.

3 CHAIR BRAIN: And there's an

4 extensive literature showing ST segment

5 depression does correlate with increased

6 susceptibility to arrhythmias and all kinds of

7 things.

8 DR. DAHMS: Yes. Then, part of the

9 problem you run into, I think, with putting

10 the epidemiology data in is all we have talked

11 about this morning, is, then, what mechanism

12 do you propose? Is it, as Paul brought up

13 earlier, a continuum of the reduce in oxygen

14 availability? That is one possibility, that

15 you get very low levels of exposure and you

16 just have a much higher N, so you are going to

17 see the effect.

18 But it gets back to this whole --

19 again, I think there must have been some

20 statements in there that, you know, well, it

21 is consistent. I can give you the written, in

22 here, the citations where you state in the
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1 document that CO effects are without

2 threshold. There's, I don't know, half a

3 dozen of them in this section alone.

4 If you accept that, then there's got

5 to be some verbalization, a description of how

6 you assume the epidemiologic effects are

7 occurring. There has to be some mechanism

8 brought forward, you know. I suggested

9 another way of approaching this, but it seems

10 to be talking about partial pressure of CO is

11 just introducing something that is too foreign

12 to this document at this point. I mean it has

13 not come up in the REA or anywhere else before

14 this. So, to introduce it now is probably too

15 late.

16 We talked earlier on about the

17 uncertainties with dealing with CO exposure

18 because of not knowing what the real

19 relationships are between CO exposure in

20 people with coronary artery disease and long21 term prognosis. It's got to be an

22 uncertainty.
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1 But it gets back to this very first

2 point of, what is an acceptable risk? I guess

3 all of us have to come up with our own opinion

4 of this. Because if we don't have some,

5 there's no guidance given in this document. 

6 There is probably no guidance given in any EPA

7 document as to what an acceptable risk is,

8 right? It is up to every one of the Panel

9 members to decide what is an acceptable risk. 

10 If the current risk is too great, then we

11 would push for a lower standard.

12 Is that how this whole process

13 functions through CASAC? Is that what it is,

14 Joe?

15 CHAIR BRAIN: What --

16 DR. DAHMS: So, in other words, you

17 know, we all have our own internal standard of

18 what an acceptable risk is.

19 CHAIR BRAIN: Right.

20 DR. DAHMS: So, if we feel the

21 numbers are showing that the risk too high,

22 then we have to push for a lower standard,
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1 justify a lower standard.

2 So, is it a consensus of this group,

3 written, I mean either in writing or just by

4 action, that we make those decisions?

5 CHAIR BRAIN: I think that is what

6 we are looking for, is, yes, we should give

7 advice as to whether we think it is acceptable

8 or not. That opinion will, then, be passed on

9 to the Administrator.

10 MS. BARRY: The CASAC will make a

11 recommendation.

12 CHAIR BRAIN: We don't set the

13 standard.

14 MS. BARRY: Based on the state of

15 the science, the agency can decide what level

16 is acceptable for protection, but your job, as

17 independent scientists, is to just speak to

18 the evidence, and perhaps if there is a range

19 that is more acceptable or more protective,

20 that can be done in this venue.

21 DR. MURPHY: Right. And another

22 way, I would add, to think about it is, I
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1 mean, we would suggest you look at the

2 considerations that we teed-up and think

3 about, did we hit the appropriate

4 considerations or did we miss some? Or did we

5 characterize some inappropriately? And have

6 we recognized there seemed to be a variety of

7 public health policy judgments that need to be

8 made in drawing a conclusion as well, in terms

9 of the adequacy of the standard? Have we

10 characterized them appropriately? Is there

11 any science that would inform these public

12 health policy judgments that hasn't been teed13 up that needs to be? That sort of thing, I

14 think, is another way to look at it.

15 But, as Kyndall is saying, it is

16 tied to the science. What is well-supported

17 by the evidence and the quantitative analyses

18 that we have?

19 CHAIR BRAIN: Okay.

20 DR. DAHMS: That's all I have to say

21 on Charge Question 2.

22 CHAIR BRAIN: So, then, we have
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1 Milan and Francine. Do you want to add?

2 DR. HAZUCHA: Do you want to go

3 first?

4 DR. LADEN: I don't really have that

5 much to add. I think the questions were

6 appropriate. I liked the questions. I

7 thought they were a good way of organizing the

8 discussion.

9 And I thought that the level of

10 detail, when I first read it was appropriate,

11 although based on the discussions that we have

12 had today, I think that it is important to

13 increase the effort to integrate the

14 epidemiologic studies more in terms of their

15 strengths and limitations, in terms of

16 answering these questions. I don't think it

17 is necessarily that they are going to change

18 much, but that there are limitations to

19 integrating the epi more than has already been

20 done.

21 And also, the considerations of the

22 susceptible populations, I do think some
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1 expansion of that discussion I would

2 recommend.

3 CHAIR BRAIN: Milan?

4 DR. HAZUCHA: Yes. Actually,

5 compared to the old staff papers, I very much

6 like the approach of posing questions. But

7 one question which I thought -- we are already

8 discussed it -- which should have been posed

9 is about non-traffic sources of carbon

10 monoxide like indoor air. I believe that

11 should have been discussed here, sort of

12 potential interference, and so on, which I

13 wasn't able to find, particularly, for

14 example, for individuals with CVD, they stay

15 more indoors than venture outdoors, and so on.

16 The general response to Question 2,

17 I guess it provides sufficient details, and so

18 on. So, I am fine with that.

19 DR. MURPHY: Can I just ask a

20 question of clarification? Your point with

21 regard to more discussion of non-traffic

22 sources of CO is with regard to interpretation
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1 of the epidemiological studies? Is that how

2 you --

3 DR. HAZUCHA: No, no. For example,

4 even acute exposures, if you have, for

5 example, individuals staying at home for a

6 longer period of time, and their level may be

7 elevated, for example, during wintertime, how

8 it may impact, for example, the relationship

9 between outdoor ambient concentration and

10 indoor CO concentration. So, what impact it

11 will have on actual COHb levels? Will it

12 override the actual standard or will it be

13 below standard?

14 DR. MURPHY: The non-ambient CO?

15 DR. HAZUCHA: Yes.

16 DR. MURPHY: Of course, the standard

17 is for ambient CO.

18 DR. HAZUCHA: Yes, I know.

19 DR. BLANC: But, for example, your

20 figures, if I understand correctly, your

21 figures that you showed where you have various

22 scenarios of proportion of people that would
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1 be -- now that included, that took into

2 account what the modeling said about their

3 endogenous carboxyhemoglobin, is that correct?

4 DR. MURPHY: You're talking about

5 the figures in the last set of slides?

6 DR. BLANC: Yes.

7 DR. MURPHY: Yes.

8 DR. BLANC: Right?

9 DR. MURPHY: That is from the REA.

10 DR. BLANC: Right, but it doesn't

11 take into account their indoor non-ambient?

12 DR. MURPHY: Because the REA does

13 not have indoor sources modeled, yes.

14 DR. BLANC: Well, but that's right. 

15 So, you see how things become circular and

16 feed on themselves. It is the same

17 limitation. It's, well, wait, I can't do that

18 because I don't have that from the REA; the

19 REA doesn't do it because somewhere else it

20 says not, you know.

21 So, the graph is misleading because,

22 if you just look at the graph and say, okay,
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1 this is what you're modeling people's levels

2 would be, but the graph should at least say

3 somewhere very clearly, "By the way, this

4 doesn't actually estimate what somebody's real

5 value would be because it would be, on

6 average, 2 percent higher than this."

7 DR. MURPHY: It doesn't have the

8 indoor sources contributing, that's true.

9 DR. BLANC: Right. I think the text

10 that you are talking about is something that

11 says we know from estimates -- in fact, it is

12 modeled; it is just modeled from the 2000 data

13 on what people's average indoor contribution

14 is, right?

15 DR. MURPHY: Is that what you're

16 getting at, though?

17 DR. HAZUCHA: Yes, yes.

18 DR. MURPHY: Okay. Thank you. I

19 didn't follow it. Thank you.

20 CHAIR BRAIN: Okay. On to Question

21 3, back to Tom.

22 DR. THOM: Joe?
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1 CHAIR BRAIN: Yes?

2 DR. THOM: I guess I need, if I may,

3 just to add something on Question 2, because

4 I ended up writing a modest amount about this

5 in the next two questions.

6 I guess I am going to disagree with

7 some of the things that have been said here

8 today with regard to the Policy Assessment. 

9 Maybe it is just it is written for a

10 politician. But I found it a very convoluted

11 way of presenting information as a general

12 statement.

13 So, in my writeup, there's a lot of

14 specifics on particular issues. But let me

15 just say that, as a general statement, I

16 understood why you constructed it to pose a

17 question and, then, to attempt to respond to

18 that question. But I had to read it several

19 times before I realized that some of your

20 questions are never answered. I give you, the

21 details are written up in my little thing that

22 I submitted.
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1 So, personally, I don't think that

2 that approach serves you very well because,

3 specifically, some questions have no answer in

4 the Policy Assessment. Then, many of your

5 conclusions are basically the standard could

6 be changed or not. That is the conclusion. 

7 It's like we could have said that before we

8 started the first ISA. So, I was disappointed

9 that there was not more in the document from

10 what was said in the REA or the ISA in terms

11 of some of the risk assessments.

12 And one could come with a conclusion

13 to say the data are insufficient to warrant a

14 change in standard. I think that is a

15 legitimate thing to say.

16 But there was no conclusion. It was

17 we could change it or not.

18 DR. MURPHY: Well, as Lydia

19 described this morning, that is an acceptable

20 conclusion because, as the staff, we are not

21 making the decision on a standard. We are

22 identifying what are the appropriate policy
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1 options that are supported, reasonably

2 supported, by the information that should be

3 taken to the Administrator for their

4 consideration.

5 To the extent that you all think

6 that we have gotten too broad a range, then

7 you all need to speak to that, and in your

8 comments let us know that you think the

9 evidence doesn't support such a broad range of

10 policy options and it should be narrowed. 

11 That would be quite useful information for us.

12 DR. THOM: So, this was to be just a

13 strawman to be torn apart?

14 DR. MURPHY: No, not per se,

15 although you're welcome to do that.

16

17 It is intended to describe the

18 options that are well-supported by the

19 available evidence and the quantitative

20 analyses, and recognize that we have

21 identified what weight you might put on

22 different public health judgments and how that
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1 weight would give you a different answer.

2 This is true for all of our

3 standards, that there could have been a

4 conclusion that we thought the current

5 standard was adequate; there was no evidence

6 to suggest that we should conclude it was not

7 adequate. But the staff felt that, based on

8 all of the information we had, depending on

9 the weight you put on some of those pieces of

10 information, it might be appropriate to judge

11 it's not adequate.

12 So, we thought it was appropriate to

13 say, well, depending on the weight you put on

14 these things, what you put on the epi, what

15 you put on different benchmarks, what you put

16 on clinical significance, you might draw one

17 conclusion or another. The weight that you

18 put there is not, there's no black-and-white

19 answer to that. Some of that has a science

20 aspect to it, but some of it is more a public

21 health judgment aspect to it.

22 And it's not up to the staff to say
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1 what the standard should be. It is up to the

2 staff to describe well what the evidence and

3 the quantitative analyses can support well. 

4 We are asking you all to tell us if we have

5 done that well or not or if you have a

6 different conclusion.

7 DR. BLANC: Can you put this in

8 context? How frequently when you get to this

9 stage of policy are you in the position of

10 saying, well, you could leave the standard the

11 way it is; on the other hand, you could modify

12 the standard? Is that a typical scenario?

13 DR. MURPHY: It is not unusual. I

14 don't know how typical it is, but it is not

15 unusual.

16 DR. BLANC: But it has precedent?

17 DR. MURPHY: Oh, definitely.

18 DR. BLANC: You've done it that way

19 before?

20 And a related question: my

21 interpretation of the document was that last

22 time you did this process for carbon monoxide
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1 the position was more unequivocal that it

2 should stay the way it was?

3 DR. MURPHY: We're struggling to

4 recall. The staff paper would have been the

5 '92 staff paper, and I think it probably said

6 it was appropriate to consider retaining the

7 standard, and perhaps did not tee-up

8 alternatives at that point.

9 Now we have an expanded set of

10 evidence, and we have drawn a different

11 conclusion at this point.

12 DR. BLANC: Okay. That's helpful. 

13 Thanks.

14 CHAIR BRAIN: So, it is kind of left

15 to you as to how prescriptive you want to be

16 in suggesting retaining the standard or you

17 can give a few hints or more than a few hints,

18 if you care to, but --

19 DR. MURPHY: It is determined by the

20 evidence and the analyses and what they tell

21 us. The previous review, the '92 staff paper

22 had an exposure assessment that was done in
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1 one city. I believe it was Denver. It did

2 not have the expanded recent epidemiological

3 studies.

4 So, there are various things that

5 are now available that have made us look a

6 little more broadly at the issue and say,

7 well, depending on how much weight you give on

8 the epi studies that may be performed in areas

9 where the standard is attained, et cetera, you

10 might draw different conclusions. We have

11 teed that up for this draft assessment as our

12 initial conclusions. We are looking for how

13 well that flies with you all in terms of

14 describing what is supported by the evidence.

15 DR. PENN: So, if we don't make

16 absolute recommendations to either keep the

17 standard the same or to, let's say, lower the

18 standard, then there's going to be a couple of

19 letters that get sent to Lisa Jackson, and,

20 then, she is going to sit there and she's

21 going to make a determination based on what is

22 sitting in here now that says you could raise
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1 it or not? Then, somebody is going to ask

2 her, when she goes to sit in front of

3 Congress, "What do you recommend, raising or

4 lowering it?" She's not going to say, "Well,

5 you could raise it or not."

6 DR. MURPHY: No, she will make a

7 decision. But, as Lydia said this morning, it

8 is ususal for our proposals to have a range of

9 policy options. When we go to proposal, we

10 may say, you know, there will be language in

11 there about the Administrator -- I can't

12 remember the phrasing -- something like

13 preliminarily or tentatively judges the

14 standard to be adequate or not. Or they might

15 say judges that the level for the standard

16 should be at least as protective as the

17 current standard, and it may be appropriate to

18 consider a range of alternatives that range

19 below the current standard down to "X", and we

20 are soliciting comment on the rationale that

21 we might give to one option or another.

22 This is a public process. So, the
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1 Administrator would intend to identify the

2 appropriate range, supported by the science,

3 and clearly articulate the rationale for

4 different conclusions that might be drawn and

5 how the evidence supports that, and how public

6 health policies come into conclusions with

7 regard to that.

8 So, that, then, we receive comment

9 on that whole suite, on not just any numbers

10 and forms, but on the rationale that is used. 

11 So, people can say, "That's an inappropriate

12 rationale for a standard" or "That's not well13 supported by the science." They can say

14 whatever they need to.

15 Then, we consider all the public

16 comment and go back to the Administrator, tee

17 it all up, and they decide what's the

18 appropriate conclusion.

19 CHAIR BRAIN: And we can be part of

20 that process, if we care to say whatever --

21 DR. MURPHY: You have a front-row

22 seat in that process.
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1 CHAIR BRAIN: Right.

2 DR. BLANC: Do you view Charge

3 Question 6, which we haven't gotten to, as the

4 charge question which directly asks us whether

5 or not we think the current standard is

6 adequate?

7 DR. MURPHY: One thing I should

8 mention is in the slides, you will recall when

9 I went through the topic areas for the

10 standard, I emphasized that we were interested

11 in the Panel views on whether or not they

12 consider the current standard to be adequate

13 and the range of appropriate potential

14 alternatives to be considered.

15 One reason I was trying to emphasize

16 it in the slides is we neglected to clearly

17 say that in the charge questions that came to

18 you, but we are quite interested, obviously,

19 as Lydia said this morning, in your views on

20 the adequacy of the current standard, the

21 range of alternatives that might be

22 appropriate to consider.
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1 CHAIR BRAIN: And it certainly

2 sounds like Charge Question 11 kind of invites

3 us, "What are the Panel's views regarding the

4 appropriateness of staff's initial conclusions

5 related to considering a secondary" -- no, I

6 guess that's just a secondary standard.

7 DR. MURPHY: Yes. We did it more

8 clearly on the secondary. We didn't do it --

9 CHAIR BRAIN: Right. No. 7.

10 But we should make sure that we

11 discuss and see whether there's consensus,

12 right?

13 DR. BLANC: You know, it might be

14 slightly out of arithmetic order, but I have

15 to say that the answer to that question will

16 taint every other answer to the charge

17 questions to an extent -- color, not taint,

18 inform.

19 (Laughter.)

20 CHAIR BRAIN: Taint is tainted?

21 DR. BLANC: Yes. Or am I wrong

22 about that?
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1 CHAIR BRAIN: Let's take a few

2 minutes. Some preliminary feelings as to the

3 adequacy of the current standard?

4 DR. ROBERTS: Could I ask a question

5 of EPA that is sort of, at least in my mind,

6 relevant to that?

7 If the current standard were to be

8 retained, and the levels are so low, does that

9 allow agencies to unrestrict and pollute back

10 up to the level of the standard? I mean I

11 know that is a loaded question, but it sort of

12 addresses what our conclusions might be in

13 this overall answer.

14 CHAIR BRAIN: So, you are saying, is

15 that an invitation to pollute?

16 DR. ROBERTS: Well, yes. I mean I

17 am asking conceptually, is it, yes.

18 DR. MURPHY: I wouldn't answer you

19 directly, but say to you that our job is to

20 judge the adequacy of the current standard,

21 not necessarily to judge the adequacy of the

22 current air quality.
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1 DR. ROBERTS: Right. That is sort

2 of what I meant, yes.

3 DR. MURPHY: We are interested in

4 having a standard that is appropriately

5 protective of public health.

6 DR. ROBERTS: Right. So, we as a

7 Committee, shouldn't just say, well, the

8 concentrations are so low it doesn't matter

9 what the standard is set at; they're low?

10 CHAIR BRAIN: Right.

11 DR. ROBERTS: We actually --

12 CHAIR BRAIN: The standards matter.

13 DR. ROBERTS: We actually need to

14 say it the way you just did. If those levels

15 are where they should be, the ambient levels,

16 then the standard should be lower.

17 CHAIR BRAIN: If that is warranted.

18 DR. ROBERTS: Yes, if the science

19 warrants it.

20 DR. MACIOROWSKI: Can I just jump in

21 here for a second?

22 This gets in that really kind of
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1 fuzzy area. This is fascinating topic in a

2 lot of ways.

3 (Laughter.)

4 If you have an ideological position

5 that it should be this, based on your personal

6 opinion, we don't care to hear it in this

7 forum because this is the Clear Air Scientific

8 Advisory Committee. So, the advice here,

9 actually, should be based in science, and you

10 are providing a scientific set of advice and

11 opinions to the Administrator.

12 I need to say that because, had

13 prior to your being seated on this Panel, had

14 you written all kinds of letters on behalf of

15 this advocacy group or this industry group --

16 or I'm just making this up -- you would not be

17 allowed to serve because you would have had a

18 preconceived notion of what that science

19 should say. In our ethics screening, we would

20 sort of -- so, there's always this kind of

21 tension between keeping the scientific advice

22 primarily scientific.
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1 Now, having said all of that, a lot

2 of this depends on how it is couched. And I

3 am going to sort of relate this back to how we

4 do an ethics review.

5 Dr. So-and-So from University X has

6 a paper that says, "Based on the science, I

7 have looked at a risk assessment scenario, and

8 this range of values is more or less

9 scientifically-validated and should be

10 protective."

11 That is different than sort of

12 saying, coming together with a letter -- and

13 this is really a whole different topic. We

14 just had a range of academics who had a very

15 strong policy position on what the agency

16 should do on something not related to air at

17 all. Because they have a preconceived notion

18 specifically on the issue coming before the

19 Science Advisory Board, that would be

20 construed as a perception of a lack of

21 impartiality, and we would basically recuse

22 them from service.
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1 So, as a science advisory board, you

2 guys are sort of in that area where it is fine

3 to have a scientific opinion. It is based on

4 your research. It is based on data. It is

5 based on information available to you.

6 Once you start to cross that line

7 into advocating for a particular position, as

8 long as it is based on science, you can do

9 whatever you want. It is when it starts to

10 sort of say, "Well, it should just be more

11 protective because...." or "It should be less

12 stringent because....", where it becomes, say

13 -- I hate to use the word "factions", but God

14 knows we have them, in terms of what it is.

15 So, I just kind of wanted to clarify

16 that point in terms of the focus here ought to

17 be on we reviewed the science; the science

18 supports this. The science does support this. 

19 You know, there's a range in here, and of that

20 range -- this became a big issue several years

21 back -- is there a valid range of scientific

22 interpretations around that range?
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1 And say -- I'm making this up again

2 -- somebody sort of says, "Hey, the

3 Administrator says we're going to consider 1

4 to 10," and you start saying, "No, no, it

5 should be 3 to 7," based on the data. Those

6 kinds of things are perfectly fine for you to

7 do.

8 And actually, in past years we have

9 actually tried our best to move away from this

10 as best we can. CASAC used to sort of approve

11 the standard, but it is an advisory body, not

12 an approving body. So, in sort of how federal

13 advisory committees, and so on, are set up,

14 and how they kind of play out, the advice that

15 you provide the Administrator is taken

16 seriously. It is taken seriously by OAQPS. 

17 It is taken seriously by ORD. But it is

18 advisory. The Administrator is free to make

19 decisions based on other information that may

20 not be scientific in a specific case.

21 I don't know if that helps or not,

22 but I thought this is always a little bit of
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1 a -- here's another example: if you were a

2 scientific FACA, you were a representative

3 FACA, you would be representing a

4 constituency, and then we would be more than

5 happy to have your opinion on that

6 constituency on a representative FACA, but

7 this is not that kind of federal advisory

8 committee. It is a scientific advisory

9 committee.

10 So, this is always kind of an issue

11 that gets a little strange at times to talk

12 about and interpret, but, hopefully, that

13 helps. If you have any questions, I will try

14 my best to answer them.

15 CHAIR BRAIN: No, I think that helps

16 a lot. So, given the necessity of basing your

17 opinions on science and on the evidence, does

18 anybody want to talk briefly about whether

19 they feel the current standard is adequate or

20 whether the evidence suggests something

21 different, something lower, or a different

22 format, form?
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1 Mike?

2 DR. KLEINMAN: I just wanted to

3 frame it because I had responsibility for

4 Question No. 7.

5 CHAIR BRAIN: Uh-hum.

6 DR. KLEINMAN: So, the bottom line

7 was the staff recommends -- I want to read

8 this, so I get it right -- "The data provides

9 support for retaining or revising the current

10 eight-hour standard."

11 I think, overall, when we come down

12 to it, the Panel will agree with that sort of

13 at the bare minimum. But, with the

14 epidemiological evidence providing data that

15 shows that at the current exposure levels,

16 which are below the actual level of the

17 standard, health effects are accruing, and

18 therefore, the evidence might be leaning in

19 the direction of suggesting a revision

20 downward of the existing standard.

21 CHAIR BRAIN: So, is that an

22 emerging consensus of the evidence suggests,
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1 for heaven's sakes, don't think about a higher

2 standard; don't make it lax, and if anything,

3 it should be heading downward a little bit?

4 DR. THOM: I think it is given to

5 say that we would never support raising the

6 number beyond 9.

7 Mike, I agree 100 percent with what

8 you said. My only quandary is you say, okay,

9 fine. So, one might consider dropping the

10 level down.

11 But, in the opening slides, there

12 were a couple of them that had 9 to 3 parts

13 per million, for example. And I thought,

14 well, 3, that sounds good to me. But there

15 are no data to make a statement that 3 is a

16 good mark to use for a standard, at least that

17 I'm aware of. So, I think there is a problem

18 with putting a number.

19 DR. KLEINMAN: This is what I think

20 where that range comes from. Using the

21 benchmarks of 1.5 percent carboxyhemoglobin

22 and 1.8 and 2, you can generate, using the CFK
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1 equations, what exposures would do, and then,

2 using the risk model, come up with what

3 percent of the population would exceed those

4 benchmarks.

5 So, they picked that range to

6 protect various numbers or various percentages

7 of the population ranging from 99.9 percent to

8 whatever it was. I think 95 percent was what

9 the lower was.

10 DR. THOM: But, once again, that is

11 the coronary artery disease. I mean those

12 data were generated --

13 DR. KLEINMAN: And they are using

14 them as a benchmark.

15 DR. THOM: That is sort of a --

16 okay.

17 DR. KLEINMAN: Right.

18 DR. THOM: For better or for worse,

19 that's what it was.

20 DR. KLEINMAN: Yes. So, that is

21 where the range came from. So, they could

22 recommend or we could recommend a range based
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1 on just coronary artery disease, couched in

2 the terms that this would not necessarily

3 protect everybody who is susceptible. There

4 is this whole other block of susceptible

5 individuals that seem to be showing effects,

6 based on the epidemiology at substantially

7 below that.

8 DR. THOM: Right. It is

9 substantially less than 3 parts per million.

10 DR. KLEINMAN: What?

11 DR. THOM: At less than 3 parts per

12 million.

13 DR. KLEINMAN: At less than 3 parts

14 per million, but --

15 DR. MURPHY: Can I interject just a

16 minute?

17 This is great conversation, and I

18 hate to interject.

19 DR. KLEINMAN: That's okay.

20 DR. MURPHY: But there's one thing I

21 just want to make sure you all read in terms

22 of how we describe some of the considerations
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1 here.

2 And when we walked through the

3 question on levels with health effects, and we

4 talked a bit about the epidemiological data,

5 and we made a point of looking closely at the

6 study areas, where we had epidemiological

7 studies, and identified whether or not the

8 current standard was attained or exceeded. We

9 found that in many, most of those studies, the

10 current standard was not met during some

11 period of that study.

12 So, while the common concentrations

13 to which people may have been exposed were

14 below the standard, the standard was not met.

15 So, to us, those studies are actually less

16 useful in answering the question of at what

17 level below the current standard might there

18 be effects.

19 So, we tried to sift through the

20 studies and say, which studies actually were

21 performed in areas and during time periods

22 when the standard was exceeded? When we
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1 focused on some of the key health outcomes

2 that the ISA focused on, we came to just a

3 couple of study areas, most prominently the

4 Atlanta study area, where we had three

5 studies, but all in the Atlanta area, and one

6 of which was statistically-significant.

7 So, when we walk through saying,

8 okay, if we are going to give weight to the

9 epi, it comes down to that, and that's what

10 might lead us toward -- and in that study

11 area, I believe the second highest eight-hour

12 average concentration was about 4.9 ppm. So,

13 presumably, you would want a value below that,

14 if that study is telling you that you have

15 effects when a potential standard of 4.9 was

16 attained.

17 So, just to help you understand some

18 of the logic that we constructed to identify

19 the rationale that might support different

20 alternatives for the standard, that's one view

21 of the epi study. We needed to take into

22 account, was the current standard met or not
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1 in these study areas? Because, conceivably,

2 the outcomes we saw could have been driven by

3 exposures associated with levels above the

4 standard, since they did exist during those

5 studies.

6 So, hopefully, that is useful to

7 you. That is described in the document.

8 CHAIR BRAIN: All right. So, I

9 think this is a discussion well-started, not

10 completed yet. Why don't we go back to Charge

11 Question 3?

12 DR. BLANC: Well, can I just add

13 something?

14 CHAIR BRAIN: Yes.

15 DR. BLANC: I think that it would be

16 sufficient for us to address whether the body

17 of the scientific evidence weights in favor of

18 a more restrictive standard without committing

19 ourselves to a body of evidence recommendation

20 of what that standard can be.

21 I don't think that we should be

22 prevented from saying the direction that we go
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1 just because we can't go beyond that. Because

2 I think the reason that we can't is because we

3 weren't provided the data to scientifically

4 assess because, in fact, some of the things

5 that have been pointed out just aren't in the

6 document.

7 But I think we have a preponderance

8 or a body of evidence which weights more in

9 favor of a more restrictive standard than in

10 favor of keeping the standard as it is. I

11 think that we should make that clear.

12 I think that there are a number of

13 issues that would be marshaled, scientific

14 issues, that would support that conclusion,

15 many of which have been brought up around the

16 table already today.

17 But, to summarize some of them, most

18 saliently, the population at risk is probably

19 larger than has been estimated, that there

20 were some sources in the exposure estimation

21 that might tend to underestimate effect,

22 including, as we heard, near-roadside exposure
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1 and the tail of endogenous production in

2 certain subsets.

3 And finally, the observation that

4 there aren't good data that allow them to

5 combine modeling of indoor non-ambient sources

6 with the ambient and the endogenous together,

7 meaning that the numbers of people that exceed

8 certain levels of exposure are going to be far

9 larger in number and in proportion than the

10 tabular estimates show.

11 So, when I look at all of those

12 scientific issues combined, that certainly

13 weights in favor of not remaining with the

14 status quo.

15 CHAIR BRAIN: I suspect your summary

16 of a movement toward lowering the standard

17 will probably be shared. But why don't we

18 return to it and see whether we want to --

19 DR. DAHMS: I have a question of

20 Paul.

21 Do you think that the ISA should

22 have been couched in different terms, so that
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1 the information was more readily available

2 with the idea, with some view, some analysis

3 of the studies that were included relative to

4 these --

5 DR. BLANC: Oh, relative to the last

6 point that was made, whether some of the

7 studies -- what proportion and to what extent

8 the epidemiologic studies met or didn't meet

9 the 9 ppm current standard? I mean this is

10 the first we have sort of heard that argument. 

11 So, it is hard for me to say. Absent the

12 information, I really can't --

13 CHAIR BRAIN: There is still time in

14 the policy document. It seems to me the

15 policy document can do that. Out of all the

16 information in the ISA, here are the ones that

17 we think are particularly important because --

18 DR. MURPHY: In table --

19 DR. BLANC: No, no, I'm talking

20 about in the ISA.

21 DR. MURPHY: Oh, but it is in the

22 policy document.
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1 DR. BLANC: Yes, yes. I'm not

2 saying you didn't put it there.

3 CHAIR BRAIN: And maybe that is just

4 the right place for it.

5 DR. PAGAN: The ISA presents the

6 author's averaging, just an averaging time

7 that actually dilutes the time periods of the

8 study. So, it is a low level.

9 DR. BLANC: Well, some of the data

10 are from outside the United States as well

11 that are quite germane. But, nonetheless,

12 that is the epidemiologic data is pretty

13 convincing that there is an effect. It is

14 more relevant to me to what the population at

15 risk is rather than this specific question,

16 which is why I didn't really focus on it as

17 much.

18 CHAIR BRAIN: This is a really

19 important point and it needs to be front and

20 center. This sounds like something that will

21 be in the two-page letter in one form or

22 another.
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1 So, let's return to exactly what we

2 want to say a little later. Let's continue

3 with Q/A No. 3. So, back to you Tom.

4 DR. DAHMS: Charge Question 3?

5 CHAIR BRAIN: Yes.

6 DR. DAHMS: All right.

7 CHAIR BRAIN: Which is about links

8 with the ISA, which we have been talking

9 about.

10 DR. DAHMS: Yes. The one major

11 issue I had with this was that, the one major

12 concern that I had was that all of the work

13 that was done for the documents in the late

14 1990s just sat, waiting for this study on

15 altitude and extreme conditions. I don't

16 recall any reference to that document. It may

17 have been referred to. It may be in a

18 bibliography, but there is no description of

19 the outcome of that and how that should impact

20 our view of the Denver data.

21 Does the Denver data, does that

22 altitude of 4800, 5200 feet make any
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1 difference in the way we should view Denver

2 versus LA, based on -- who did this study, the

3 NRC, National Research, who did that study on

4 altitude and --

5 DR. MURPHY: Yes, it is the NRC. It

6 is the NRC.

7 DR. DAHMS: Okay, but, you know,

8 there's no discussion of that in here. Given

9 the fact that there is an indefensible delay,

10 I think that is why the courts got kind of

11 snippy with us, that we needed, you know,

12 there needs to be some information in here

13 about that study. Was it found to be just a

14 delay? Was there no guidance from that study

15 at all?

16 DR. MURPHY: Yes, we can certainly

17 provide more description of the study. It is

18 mostly an air quality analysis. It talks

19 about controls, I believe, also. I don't

20 think it gets at what you are thinking it

21 might get at. But we can certainly augment

22 our document to describe more completely
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1 what's in that.

2 DR. DAHMS: I mean, because based on

3 what was shown here, that the numbers of

4 people at risk in Denver are greater than

5 those in LA, right?

6 DR. MURPHY: And that has to do with

7 the distribution, the air quality distribution

8 for the study area in Denver.

9 DR. DAHMS: But it has nothing to do

10 with the physiologic parameters in APEX for

11 people being at altitude?

12 DR. GRAHAM: I think there's one

13 adjustment. I don't have it in front of me,

14 but not all the variables adjusted for

15 altitude.

16 DR. MURPHY: He's saying there's one

17 variable that may have an influence on

18 altitude that would be included in the

19 analysis, but it is unlikely that is a large

20 driver behind the results that we are seeing

21 here. It is just the air quality

22 distributions, more likely.
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1 DR. GRAHAM: Right.

2 DR. DAHMS: And that's all, the only

3 comments I had on Charge Question 3.

4 CHAIR BRAIN: Milan? Francine?

5 DR. HAZUCHA: As I already mentioned

6 in the REA, I would like to see here as well,

7 when there is a discussion of all the studies,

8 to give the changes in real units. It doesn't

9 have to be, you know, a big description of the

10 results, but simply state that 4.2 percent

11 translates into 22 seconds from approximately

12 9 minutes.

13 I would like to also see maybe at

14 least to give the reader some guidance

15 because, most likely, the readers will be non16 scientists, and basically say, well, do we

17 know anything about the long-term effects of

18 such shortened time to angina here? Is the

19 frequency of angina because of those one or

20 two times a year exposures to carbon monoxide

21 when the COHb level may reach 2 percent? Will

22 it impact in any way on frequency, on future
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1 frequency of angina, and so on, or the

2 severity of angina?

3 And if we don't have data, then we

4 will say, well, we would like to address it,

5 but we do not have data.

6 And then, I have other minor

7 comments which I am listing here.

8 CHAIR BRAIN: Francine?

9 DR. LADEN: I don't really have

10 anything to add.

11 CHAIR BRAIN: Okay. Anybody else

12 want to say anything about Charge Question 3?

13 (No response.)

14 All right. Let's now move on to

15 Charge Question 4. Dr. Kaufman, are you out

16 there and ready to take us through this

17 question?

18 DR. KAUFMAN: I'm here.

19 So, Charge Question 4 relates to

20 Section 2.22. This is whether the

21 quantitative analysis of exposure and dose

22 reflects what is in the REA. Part A, it
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1 doesn't reflect what is in the REA. I think

2 that my comments would be not whether it

3 reflects what's in the REA, but whether what

4 is in the REA is what we want to have

5 reflected finally.

6 I think it does accurately reflect

7 what is in the Draft REA that we have been

8 looking at and is the version that we have

9 now. The questions that were raised this

10 morning about whether sort of both the micro11 environmental question about what's the

12 quantitative analysis of the carboxyhemoglobin

13 levels versus the approach that I think I

14 would advocate, which is to try to further go

15 down this road of understanding the

16 attributable increase, increment of

17 carboxyhemoglobin due to ambient

18 contributions.

19 I think it would make it a cleaner

20 analysis of exposure and dose because you

21 would no longer have the sort of clouding at

22 the bottom end by the endogenous levels and
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1 the other background sources of the exposure

2 to indoor sources, and so forth.

3 But I know there's others on the

4 Committee who don't see it this way. But that

5 was mine, my thoughts.

6 Then, the question, does the Panel

7 find the presentation to be technically-sound,

8 clearly-communicated, and appropriately9 balanced? I thought that the discussion was

10 quite lucid, cogent, and I thought it was

11 well-done.

12 So, those are my comments. I did

13 have, there were some written comments

14 submitted by Dr. Thom, I think, and then Milan

15 also had some comments which were on the first

16 part, coming from a slightly different place. 

17 I think he should probably state them.

18 So, that was all I had.

19 DR. THOM: My comments were mostly,

20 again, the stylist stuff. So, the details are

21 there. It is more to do with the language

22 used. I just didn't think it was terribly
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1 focused.

2 DR. HAZUCHA: Again, as I commented

3 on the REA, I would like to see the APEX more

4 shown, particularly the COHb module. As I

5 mentioned, hemoglobin levels and effective

6 rates, for example, may be, if possible. The

7 CO is another variable. The rest I have

8 really problems because there are some

9 clinical data, but not enough really to

10 incorporate it in the model.

11 But, initially, SES, because there

12 are low-income groups there which were located

13 close to traffic areas, high-traffic areas,

14 they would be more affected than high-income

15 groups.

16 So, if it is possible to turn out

17 APEX, taking into consideration these other

18 factors and inputs, that would be desirable.

19 DR. MURPHY: As I think we discussed

20 this morning --

21 DR. HAZUCHA: Yes.

22 DR. MURPHY: -- it is a question of
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1 having the data to support that in terms of

2 the distribution of different SES groups or

3 different races within the simulated

4 population, which in this case was CHD. It is

5 just, if you've got the data and can point us

6 to the studies, that would be something to

7 consider, although I'm not sure timing-wise if

8 that could be worked into the model, given its

9 current design.

10 DR. BLANC: So, Joel, you don't have

11 my written comments, I think, because they

12 were distributed in hard copy.

13 So, I agree that the issue is not

14 whether the policy document reflects the REA,

15 but, really, whether we want it to reflect the

16 REA. Without trying to make the agency crazy

17 by hearing two diametrically-opposed views, I

18 think the solution to it is to present the

19 data that allows the reader to construct the

20 cumulative exposure or to look at the

21 incremental exposure, so that the data are

22 there for all three, the endogenous, the
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1 ambient contribution, and the indoor air

2 contribution.

3 And I actually think that is

4 probably more important for the policy

5 document even than the REA, although it is

6 hard for the policy document to present new

7 data that haven't come out of either the ISA

8 or the REA. So, that is more a technical

9 issue.

10 But I think that would be a way of

11 solving both of our concerns, would be to have

12 the three pieces there separately and

13 additively, so that one could see, depending

14 on what your assumptions were, what data you

15 have.

16 CHAIR BRAIN: Anyone else on Charge

17 Question 4? Yes, Tom?

18 DR. DAHMS: Yes. I was concerned

19 that the other studies besides Allred dealing

20 with the controlled exposures were not given

21 any space in this section. So, it looks kind

22 of imbalanced to me to focus absolutely
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1 everything on the Allred study.

2 Then, there are a couple of minor

3 things. One that has just irritated me all

4 the way through this, and it is the lack of

5 understanding by whoever is writing this about

6 the fact that carbon monoxide binds to reduced

7 hemoglobin. That was stated in the ISA. It

8 was stated in the REA. Now it shows up again

9 here. That is just not correct.

10 I know where it comes from. It

11 shows up in Appendix B of the REA on page B-5

12 where there is a fiddle with the equation,

13 saying that in order to make the math work,

14 they've got to assume that carbon monoxide

15 binds to reduced hemoglobin. Then, that got

16 carried through all the text, which presents,

17 you know, something that's just absolutely not

18 true, because carbon monoxide, relative to

19 infinity, carbon monoxide pumps oxygen off all

20 the time.

21 All right, the next thing that

22 bothers me, on page 2-9, line 1, the
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1 statement, "or increased cardiac output" makes

2 absolutely no sense, but that has also been

3 carried through. It is also definitely not

4 clear to the reader what is meant.

5 The preceding sentence is discussing

6 cardiovascular disease in the context of

7 coronary artery disease. The reason I bring

8 it up, the normal compensatory mechanism in

9 healthy people is the increased blood flow

10 through vasodilatation, not vasodilatation and

11 increased cardiac output.

12 So, the current verbiage does not

13 make sense and needs to be changed to

14 something like an increased blood flow. Then,

15 that makes the earlier discussion --

16 CHAIR BRAIN: You mean local blood

17 flow, not --

18 DR. DAHMS: Yes, local flow, not

19 massive, not the whole cardiac output, because

20 the diseased heart has enough trouble

21 producing increases in cardiac output.

22 So, those are just whining issues
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1 that have been aggravating, as a reader, all

2 the way through this.

3 DR. BLANC: Dr. Dahms, could I ask a

4 clarification? When you said that you felt

5 the policy document didn't address the

6 epidemiologic literature sufficiently, you

7 meant the epidemiologic literature in terms of

8 adverse cardiovascular outcomes? Or what

9 aspect of the non-cardiac other health

10 effects -- where is that coming from?

11 DR. DAHMS: In my statement just

12 before this?

13 DR. BLANC: Yes.

14 DR. DAHMS: No, I was talking about

15 the Kleinman study, the Sheps study, the other

16 controlled human --

17 DR. BLANC: Oh, the other controlled

18 human studies? Okay.

19 DR. DAHMS: Yes.

20 DR. BLANC: Do you feel that both

21 the cardiovascular epidemiologic literature

22 and, then, the literature or the discussion of
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1 other health effects, and potentially other

2 at-risk groups, is sufficient in the policy?

3 DR. DAHMS: No, and that is what I

4 said in my response to Charge Question 2, that

5 I think that that really needs to be

6 addressed.

7 DR. BLANC: For both pieces then?

8 DR. DAHMS: Both pieces.

9 DR. BLANC: Okay.

10 DR. DAHMS: Because, otherwise, it

11 looks like you are kind of hanging out the

12 whole thing to dry on the Allred study. That

13 is the appearance that it gives. That may not

14 have been the intent, but that is the

15 appearance that it gives. And it is

16 disconcerting to all of us, I think.

17 CHAIR BRAIN: When you say, "epi",

18 you are both talking bout more controlled

19 human exposures as well as genuine, more

20 traditional epi? You mean both of those

21 should be --

22 DR. DAHMS: No, I'm talking about,
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1 when you talk about the controlled human

2 subjects studies --

3 CHAIR BRAIN: There's more than

4 Allred?

5 DR. DAHMS: -- there's more than

6 Allred.

7 CHAIR BRAIN: Right.

8 DR. DAHMS: And when you are talking

9 about cardiovascular disease, there is

10 epidemiology and the controlled.

11 CHAIR BRAIN: Right.

12 DR. BLANC: And then, when you talk

13 about the other effects, there's just whatever

14 there is on the other effects. Some of it is

15 animal studies. Some of it is --

16 DR. DAHMS: Well --

17 DR. BLANC: I mean you are talking

18 about the issues of, what about in pregnancy,

19 what does it mean? What about in these

20 others? Yes, okay.

21 DR. MURPHY: If I could ask -- now

22 I'm a little confused. I meant to ask Dr.
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1 Dahms what you meant when you made your

2 overview comments with regard to lack of

3 emphasis or discussion of the epi. Because it

4 wasn't clear to me what you were looking for

5 exactly, what you felt was missing.

6 We did discuss the epi in going

7 after different questions. We tried to talk

8 about troubles that we have in integrating the

9 epi with the clinical, because, of course, we

10 have no COHb measurements in the epi. We have

11 no personal exposure measurements with the

12 epi.

13 So, what is it that you are thinking

14 isn't here that needs --

15 DR. DAHMS: But you have no COHb

16 measurements in all of the modeling. You have

17 estimates.

18 DR. MURPHY: Sure. Yes, and it

19 is --

20 DR. DAHMS: So, you must have

21 estimates or the epidemiologists could equally

22 come up with estimates if they had access to
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1 the APEX model.

2 DR. MURPHY: They don't have

3 estimates of exposure. Their estimate or

4 surrogate for an exposure estimate is the

5 ambient monitor concentration. The epi

6 studies look at those relationships, the

7 ambient monitor concentration to the different

8 types of outcomes. They don't have in those

9 studies any presentation of what were those

10 people who had the various health outcomes

11 exposed to, in terms of their total cumulative

12 exposure to CO, and they certainly don't have

13 the COHb measurements.

14 We try to discuss that in this

15 document in terms of a challenge that we face

16 in integrating the epi studies with what we

17 know so strongly about CO from the wealth of

18 evidence over the years and from some of the

19 clinical controlled studies.

20 DR. BLANC: Well, but you actually

21 have very little positive to say about the

22 epidemiologic literature and lots and lots and
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1 lots to say about its limitations. So, again,

2 I don't know what you intended, but the net

3 result is to discount the epidemiological --

4 DR. PENN: But could I just add

5 something to that, sort of as an outsider to

6 this group?

7 In trying to read this from the

8 perspective of a reasonably intelligent

9 person, reading it but not being involved with

10 all this stuff, the ISA is loaded with epi

11 data. There's also clearly mention of the

12 Allred studies and the Kleinman and the Sheps

13 studies.

14 But, as you go through the document

15 we looked at this morning, and then go through

16 the Policy Assessment, Paul is completely

17 right, it really reads like, yes, we've got

18 this epi stuff over there, but here's the

19 reason why it's no good, and here's the reason

20 why it's no good. So, we're going to all talk

21 about coronary artery disease. That is the

22 message that really comes across.
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1 I have comments on it for Question 5

2 that would probably fit with Question 2, just

3 pointing out what I think are real

4 inconsistencies in the way EPA has read the

5 information that you've already collected and

6 given to us that is in the ISA. It just seems

7 like the ultimate response in the PA is

8 unbalanced.

9 DR. MURPHY: And that is appropriate

10 for you to tell us, but one thing to keep in

11 mind, of course, the ISA is looking at the

12 most recently-available information. Of

13 course, that is dominated by the epi. We

14 haven't had more recent clinical studies.

15 Whereas, on the Policy Assessment,

16 what we are trying to say is, what evidence do

17 we have that is going to inform our judgment

18 of the standard? We have to look across all

19 the types of evidence we have. More recently,

20 we have a wealth of new epi, and we try to

21 bring that to bear, but we have this

22 longstanding clinical dataset. We have our
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1 knowledge that goes over years and years in

2 terms of how CO operates mechanistically, some

3 of the ways that we know it to operate, some

4 of what we've got new information indicating

5 potentially additional mechanisms, and putting

6 it all together.

7 So, it is not the intent that the

8 Policy Assessment should match or reflect the

9 different amounts of pages, if you will, given

10 to one type of study or another that the ISA

11 has. No, it should look at the evidence and

12 say, what does that evidence, how do we look

13 at all that evidence and have it inform our

14 decisionmaking in terms of the standard?

15 We struggle with the epi because, as

16 I point out, the largest number of these

17 studies were conducted at times when they are

18 exceeding the current standards. So, when we

19 are faced with this question of, is the

20 current standard adequate, and if not, what

21 might be potential alternatives, more

22 important to us is any epidemiological studies
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1 that might be conducted in areas that have met

2 the standard. So, that limits us a bit.

3 Then, we recognize things that the

4 ISA says and that folks on the Panel have said

5 in terms of limitations, uncertainties

6 associated with drawing conclusions from epi.

7 CHAIR BRAIN: That seems like a

8 classic problem in environmental health, to

9 have the bulk or a lot of studies above the

10 standard, where you, then, have the challenge

11 of trying to extrapolate to or beneath the

12 standard.

13 DR. MURPHY: But it certainly tells

14 us --

15 CHAIR BRAIN: I mean I think we are

16 talking about nuance, aren't we? I mean we

17 are really in the main talking about a little

18 more emphasis on those other studies.

19 DR. MURPHY: Yes, and I think the

20 ISA tells, what they are using those studies

21 to tell us is that CO is likely causally

22 related to these outcomes. Those studies, at
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1 whatever concentration they are conducted at,

2 inform that understanding. And we try to

3 reflect those statements as well in the Policy

4 Assessment, but we have to, then, go out at

5 another layer down and say, okay, at these

6 lower concentrations, what do we know about

7 whether or not CO is harmful and causing harm

8 in the exposed population?

9 CHAIR BRAIN: But, again, we really

10 haven't heard any evidence that suggests that

11 it is highly non-linear or there's a threshold

12 or something. I think we are mainly operating

13 with reduced oxygen delivery is bad, even if

14 it is small; it is less bad, but it is still

15 bad.

16 So, I guess I find myself less

17 troubled by epi studies that may, in part,

18 exceed the current CO standard. I don't see

19 that as quite as much of a problem as you have

20 suggested.

21 DR. BLANC: I mean listen to your

22 first sentence that talks about epidemiology. 
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1 "In considering the epidemiologic studies in

2 the case of CO, we recognize that there is a

3 coherence between the available clinical and

4 epidemiologic evidence with regard to the

5 health effects of CO in the cardiovascular

6 system (primarily for ischemic-related

7 events)."

8 So, already, you are narrowing it

9 that it is mostly ischemic. We would argue

10 that some of the data for congestive failure

11 is as convincing and a larger relative risk.

12 You are saying that we recognize

13 that there is a coherence. Well, your ISA

14 said that it supports causality; it is not jut

15 coherence. Coherence is one component of a

16 causal relationship. In fact, it met causal

17 criteria on a bunch of different criteria.

18 I am just saying how it reads, not

19 what your intent was. I can't read your mind.

20 Then, the very next sentence is, "As

21 noted above, however, we also recognize

22 several gaps between the two lines of evidence
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1 which complicate their integration,

2 particularly with regard to ambient exposures

3 and ambient concentrations associated with

4 health effects concern."

5 I think what we are trying to say

6 is, you know, give the epidemiology a couple

7 of more pluses before you start. Because, to

8 the even non-causal reader, it comes off as a

9 complete discounting or as much of a

10 discounting as you can get away with of the

11 epidemiologic literature. Now that may not be

12 your intent, but that is how it comes across.

13 DR. PENN: And the idea is not to

14 diss the studies from 20 years ago because, I

15 mean, Mike and Tom individually have said,

16 when I just talked to them today, could you

17 repeat these experiments today, if you wanted

18 to? And the answer is almost surely not, for

19 reasons of cost and all kinds of other things.

20 So, these are one-time studies which

21 all happened to occur within about two years

22 of each other and that are never going to get
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1 repeated. So, we are not dissing those

2 studies at all. It is just that, in addition

3 to those studies, which point to the clear

4 interaction of high CO exposures and the

5 cardiovascular sequelae to those, you have all

6 of these other instances that you guys have

7 presented to us.

8 In one case, there were 31 studies. 

9 In one case, there were 27 studies. There are

10 a whole bunch of them in figures 5-2 through

11 5-4 that really talk about other stuff that is

12 related in not necessarily a one-to-one way,

13 but in a very clear way to the results that

14 were reported in 1989 and 1991.

15 So, at least the two of us, and I

16 suspect a lot of people around this table,

17 feel there should be more emphasis on that

18 because, in reality, the kind of data you are

19 going to get in the future are going to be epi

20 data. You are not going to get controlled

21 clinical studies.

22 So, there's sort of, I think,
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1 considerable strength to the information

2 presented in the ISA that would support an

3 argument for the health effects of the CO

4 exposure that doesn't really come through from

5 the PA.

6 DR. HAZUCHA: I hear repeatedly that

7 there is no threshold, and I guess it is

8 coming from all that study where the

9 regression line was extended over and across

10 to zero.

11 The threshold is your endogenous

12 production. So, that is your threshold. You

13 cannot go below that. And endogenous

14 production will be always above zero.

15 DR. KLEINMAN: Going back to the

16 epi, I just want to point out that we

17 shouldn't feel bad about it. We are using

18 almost entirely the epi data for PM standards,

19 and primarily because the clinical studies

20 with particles were relatively robust. You

21 couldn't find health effects in a controlled

22 exposure study at anywhere near the levels
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1 that we are seeing in epidemiology for PM.

2 I don't think the CO studies are any

3 worse than the studies of particulates. I

4 think there are a lot more of those.

5 So, I don't think the epi should be

6 discounted just on the basis that we don't

7 have a good metric for the dose, when we are

8 using the ambient exposure data.

9 CHAIR BRAIN: Okay, very useful.

10 Anything else in regard to this

11 charge question? Anything more about Charge

12 Question 4?

13 (No response.)

14 We're doing very well. I would like

15 to suggest that we go on to one more charge

16 question to give us enough time tomorrow to

17 look at the draft letter and the draft PA

18 responses. We will look at both of those to

19 see whether we have really succeeded in

20 putting on paper a consensus.

21 So, Tom has told me that he is ready

22 to proceed with Charge Question 5. Then,
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1 Arthur may chime in as well.

2 DR. DAHMS: Given the discussion we

3 have had today, I think I've got to go back

4 and review the uncertainties in that chapter

5 for sure, to make sure that they are all dealt

6 with sufficient robustness, because we have

7 certainly raised more uncertainties. But, on

8 the first blush, it seemed like they were

9 dealt with appropriately; they were all

10 brought up.

11 One other issue I had, which was

12 dealing with this ST segment change on the

13 current review of page 2-32, line 25 to 28,

14 about the ST segment indicators, where they

15 were pulled apart, in my view, and it was

16 referred back to ISA page 48, with the

17 uncertainty about the meaning of ST segment

18 changes.

19 It says page 48. I assumed this to

20 be 5-48 in the ISA. And there is no line

21 reference because, in reading that entire

22 page, there's no indication that the ST
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1 segment on anything I can read on that page is

2 brought into question. So, that raised real

3 alarm bells with me that somebody is not being

4 careful with what they are documenting.

5 DR. MURPHY: Would you like us to

6 clarify?

7 DR. DAHMS: Sure.

8 DR. MURPHY: It is the first full

9 paragraph on page 5. You're right, it should

10 be 5-48. The sentence is while the exact

11 physiological significance of the observed ST

12 segment changes among individuals with CAD is

13 unclear, while recognizing that the depression

14 is an indicator of myocardial ischemia.

15 The point is not to question or to

16 say it is unclear what ST segment depression

17 means. It is to say the ST segment response

18 that was observed in the clinical studies is

19 decreased time to seeing the ST segment

20 change, being on the order of 3 to 5 percent. 

21 What is the physiological significance of that

22 is unclear.
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1 DR. DAHMS: It needs to be stated

2 that way.

3 DR. MURPHY: More clearly, you're

4 right.

5 DR. DAHMS: That is certainly -- a

6 poor choice of words. That is also a reason

7 for the level of uncertainty in using, as

8 Milan has pointed out, and we have all pointed

9 out, of using one of the concerns about

10 pointing out what are very small changes in

11 time to angina and time to ST segment changes.

12 The next thing I had was back to

13 this same old thing we have been talking about

14 all along, which was, how do you interpret the

15 epidemiologic data? Is it either part of the

16 continuum going down to everything from

17 endogenous baseline above or is there some

18 extraneous effect of something we don't

19 understand that is being looked at in the

20 epidemiologic data?

21 You know, the whole thing deals with

22 throwing out the request of this Panel to look
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1 at the numbers of people who might be exposed

2 at 1 percent carboxyhemoglobin, which is what

3 we voted on last time, and the decision was

4 made to not do that or to discount that data

5 and not show it because of the supposed

6 overlap between that and the baseline

7 endogenous numbers.

8 I still have concern that the model

9 is giving too big of a splay to the endogenous

10 carboxyhemoglobin levels. It leads to my

11 uncertainty in the model of overestimating the

12 exposure because of that. But that gets

13 mitigated dramatically because of my concern,

14 my other concern that was raised earlier today

15 by Paul and others that we are really

16 underestimating the number of people exposed

17 because we are just looking at people with

18 coronary artery disease, and not everyone

19 else.

20 DR. MURPHY: Can I ask a question? 

21 We are interested in understanding, when you

22 all are saying, we would like to rerun, if
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1 there's time, or whatever, or in some way get

2 estimates from our exposure analysis for a

3 larger simulated population that might not

4 just be limited to an estimated population

5 with coronary artery disease, diagnosed and

6 undiagnosed, but expanded larger to other

7 heart disease.

8 When we go forward into the Policy

9 Assessment, the outputs of the REA that are

10 there are in terms of percentage of that at11 risk population. It is not in terms of

12 numbers of people.

13 In the writeup in the Policy

14 Assessment, we go on to talk about the much

15 larger size of the larger cardiovascular

16 disease population as being an important

17 consideration in interpreting those results

18 from the REA.

19 So, we are struggling a little bit

20 to understand what you all think is missing so

21 much from that. I mean, obviously, the REA

22 could have used a different population if you
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1 all would say that the data presume that those

2 benchmarks are appropriate for that, but in

3 the Policy Assessment we are saying that we

4 are concerned about the full cardiovascular

5 disease population, and that is a large

6 population, much larger than that which is

7 simulated. We don't put actual numbers from

8 the simulation into the Policy Assessment,

9 only the percentages.

10 So, I am just curious about it.

11 DR. DAHMS: Well, yes, I struggle

12 with what you are going to put in that bin

13 based on what we know about disease states and

14 the whole mechanism, the linchpin mechanism,

15 of denying or providing insufficient oxygen to

16 a tissue. What disease states exacerbate

17 cardiovascular disease? I mean there are

18 various types of cardiovascular disease that

19 are not due to, I mean, well, heart disease

20 that are not due to inability of vessels to

21 dilate, at least as I understand it.

22 I mean you could have, I guess, a
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1 severely -- Paul, you can help with this. But

2 it would seem to me you would have a massively

3 infarcted heart leading to heart failure, that

4 the rest of the heart is not necessarily full

5 of rigid coronary vascular disease. I don't

6 know. Could they still dilate?

7 I don't know. In other words, I am

8 looking for the two-hit thing that you've got,

9 rigid vessels that can't dilate and you're

10 taking away oxygen. To me, you've got to have

11 two hits to get an effect, from what we know,

12 physiologically know.

13 All the work that Steve has been

14 doing and others looking at tissue effects of

15 carbon monoxide, that brings on a whole

16 different thing. Most of them are at much

17 higher levels than we are dealing with.

18 But I am trying to figure out what

19 in the world to put in that bin.

20 DR. BLANC: I mean I think that what

21 you say may be literally true, but I don't

22 think that directly answers your question. 
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1 But I think that what you say may be literally

2 true, but since in the text, for example, you

3 say, you know, Draft REA, Section 6.2, and it

4 refers back, and it is all integrated, it may

5 be true that you may not put real numbers; you

6 may just use percentages. But since the other

7 document does have real numbers, the

8 collective interpretation is to downplay it.

9 So, it is true, literally, that,

10 yes, you talked about percentages without

11 putting the actual numbers. So, you could

12 leave it the way you have it if the REA

13 changes and includes the bigger numbers.

14 But I will point out, though, that

15 you do go back and forth. So, that at one

16 point, you have a series of tables which

17 present everything. It would be tables 2-6

18 and 2-7 that present everything as the number

19 of people below.

20 DR. MURPHY: Percent.

21 DR. BLANC: So, everything is 99.9

22 and 99.8 or 99 -- 
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1 DR. MURPHY: Percent.

2 DR. BLANC: Yes. Yes, percent. 

3 That is sort of a related thing, but that does

4 have an inherent spin in it.

5 I think it is hard for the reader to

6 look and appreciate the difference between

7 99.8 and 99.9. It makes everything look

8 fairly trivial. But since you are talking

9 about .4 percent and .2 percent of thousands

10 and thousands of people, it is still not

11 trivial in numbers, when you tie it back into

12 the REA.

13 So, in terms of percents, what you

14 say is correct, but, then, the REA at that

15 point has to change because you are referring

16 back to it anyway. I would actually say, to

17 be consistent, you probably would want to

18 change around 2-6 and 2-7, not to talk about

19 the percent who are below the level, but the

20 percent that are above the level, just to be

21 consistent with how you have done it

22 everywhere else in the document.
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1 DR. MURPHY: Right. And just to

2 clarify why those two tables are done that

3 way, it is because now we are looking at

4 alternative standards and facing the question

5 of what should the standard do. Of course,

6 the standard, we don't want a standard to have

7 a certain number of people with an effect. We

8 want to protect a large group of people from

9 an effect.

10 So, the presentation here is, what

11 amount of that population do we want to focus

12 on in identifying the appropriate margin of

13 safety, so that we have an adequate margin of

14 safety for the population?

15 DR. BLANC: It is just hard for the

16 reader to hone in on what you may want to make

17 as the critical point. That's all.

18 DR. MURPHY: Right. And it is not

19 unusual for the REA to be focused on a more

20 specific endpoint than we are considered with

21 in the Policy Assessment because we bring in

22 the additional evidence from the ISA and
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1 elsewhere, and have a broader view, which adds

2 weight to what we pull from the ISA, or the

3 REA.

4 So, we are certainly not limited to

5 what is in the REA. That is the whole point

6 of the Policy Assessment. It delves into the

7 ISA to say, well, how do we need to view what

8 we get from the REA? We need to view it in

9 the light of these uncertainties, which makes

10 us give additional weight to some things that

11 we can't quantitatively.

12 CHAIR BRAIN: Any more discussion?

13 DR. PENN: I do. I have something.

14 CHAIR BRAIN: Yes, please.

15 DR. PENN: I don't know who is going

16 to be charged with writing up about the epi

17 data that we have been talking about, but I

18 just had a couple of things to add to that.

19 There were a couple of statements

20 that I thought were not entirely correct. 

21 Page 2-27, lines 8 through 10, the document

22 states -- and we have heard this statement
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1 before -- we did not include studies of

2 association with congestive heart failure for

3 which evidence is less clear. And it seems

4 you noted five studies in a footnote at the

5 bottom of that page, and four out of five

6 showed increased hospital admissions for

7 congestive heart failure that was associated

8 in terms of the CO.

9 On page 2-14, lines 16 through 19,

10 it says there are only small or no

11 associations between hospital admissions and

12 stroke. But if you go back to the ISA,

13 figures 5-2, 5-3, and 5-4, you see that there

14 are clear associations with congestive heart

15 failure and with stroke. And in at least two

16 of those studies, where the relative risk was

17 raised, and I think it was with the congestive

18 heart failure, but I'm not sure, in at least

19 two of those studies there were large

20 increases in relative risk where the 24-hour

21 average ambient CO levels were about .8 ppm. 

22 So, that is right at the level that we are
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1 talking about.

2 I mean we had talked about having 1

3 ppm as a cutoff. We recommended that in the

4 ISA, and you guys responded as to why you

5 didn't recommend going down to that level.

6 But here are two pretty good-sized

7 epi studies where they are talking about

8 effects at .8 ppm. So, somehow those have to

9 be, I think they should be recognized.

10 Then, there was one other issue that

11 we talked about a little bit this morning that

12 came up to me with an issue of uncertainty,

13 whether CO is a surrogate or whether its

14 effects at low concentrations can be untangled

15 from those of co-pollutants. My comment was

16 that, while there may be administrative

17 reasons for focusing on these distinctions, it

18 is not clear that there is a scientific

19 justification that is as strong.

20 Both carbon monoxide and organic

21 particles in ambient air are largely products

22 of incomplete combustion. In the real world
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1 and in most laboratory situations, where you

2 generate particles, especially from organic

3 particles, it is going to be difficult to

4 generate and, therefore, to breathe organic

5 picks without any volatiles, including CO.

6 So, there may actually be CO effects

7 at low levels when they are associated with

8 these particles. This is another issue. So,

9 I am not sure that talking about it just as a

10 surrogate or just as an absolute pollutant on

11 its own or a health risk on its own includes

12 all the possibilities.

13 DR. MURPHY: Can I just ask? I am

14 confused by your emphasis on the .8 ppm. What

15 are you --

16 DR. PENN: I have to go back to the

17 ISA. Figure either 5-2 or 5-4, and there was

18 an associated table. I have the disk

19 somewhere.

20 Paul, do you have the --

21 DR. MURPHY: No, but I understand

22 what you're saying, but it is .8 as a 24-hour
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1 average --

2 DR. PENN: Yes.

3 DR. MURPHY: -- which, of course, I

4 mean, it --

5 DR. PENN: I mean that is what was

6 reported. I mean they didn't say that at 11

7 o'clock there was 7 ppm and at 23 hours it was

8 .2 ppm. I mean the only data that we can look

9 at are the data that are presented in this

10 thing. So, they talked about a 24-hour --

11 DR. MURPHY: Right, and the

12 additional thing that we have done in the

13 Policy Assessment is look at the air monitors

14 that we have in those study areas --

15 DR. PENN: Okay.

16 DR. MURPHY: -- to see, in terms of

17 the metric for the form of the standard, that

18 statistic, were those areas in attainment at

19 the current standard or not? We can look at

20 it that way.

21 DR. PENN: Okay.

22 DR. MURPHY: So, in table 2-1, that
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1 is done in the far right two columns. So, to

2 the extent those studies are in that table,

3 they would be shown there.

4 But, Doug, were you going to speak

5 to the issue of the epidemiological --

6 DR. JOHNS: Actually, this is figure

7 5-3 in the ISA showing the associations

8 between stroke and CO. It is really not very

9 impressive. I mean the effect estimates are

10 right at about, relative risk is right at

11 about 1. Some are negative; some are

12 positive.

13 The .8 that you are referring to is

14 the standardization looking at .75 ppm

15 increase in eight-hour average. Is that where

16 you --

17 DR. PENN: Can I borrow your copy?

18 DR. JOHNS: So, this is on page

19 5-30.

20 DR. PENN: Okay. Yes. I mean part

21 of my original thing this morning is that, if

22 you look at figure, let's see, at 5-2, which
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1 is on page 5-27, the relative risk X-axis goes

2 from 1 to 1.4, but all the values are below

3 1.2. So, it looks like you've got a boatload

4 of major effects, when really the relative

5 risk for 27 out of the 31 is below 1.05.

6 If you go to the one on 5-30, yes, a

7 bunch of them are right around, either just

8 below or just above 1. But if you had a scale

9 of 1 to 1.4, then you might see that they

10 actually look more magnified than they do in

11 this particular one. And you still have six

12 that have a relative risk of about 1.4 or 1.3

13 up to 2.8. So, yes, it is six out of nineteen

14 studies, but there's an imbalance in the way

15 that the data are presented in figures 5-2,

16 5-3, and 5-4.

17 So, if you standardized all of them

18 to have the same X-axis, then you would be

19 able to compare the data slightly more easily. 

20 I mean, if you want to say, hey, look, 13 out

21 of 19 studies show barely a change, that is

22 one way. If you say six out of nineteen
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1 studies show a real change, that is another

2 way. So, it depends on, you know, how you

3 want to cut this.

4 CHAIR BRAIN: Okay. Any other

5 comments about Charge Question 5 or any other

6 responses or requests for clarification from

7 the agency?

8 (No response.)

9 We have a choice. We could recess

10 or we could do one more charge question to

11 make sure we have plenty of time tomorrow

12 morning to look at the draft documents and to

13 have lunch.

14 Dr. Thom, are you in the mood to do

15 one more? Or do you want to postpone? What

16 is the consensus?

17 DR. THOM: I collected everyone else

18 -- well, there's only one other person's

19 comments. I just saw it today.

20 Sure, I can do mine.

21 CHAIR BRAIN: Let's do it, then.

22 DR. THOM: But, then, the other
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1 people can still --

2 CHAIR BRAIN: Then, we will be in

3 great shape for tomorrow.

4 DR. THOM: All right.

5 CHAIR BRAIN: We'll do Charge

6 Question 6.

7 DR. THOM: So, Charge Question 6 is

8 asking whether the document has integrated

9 health effects from the Final ISA and risk

10 exposure information from the Second Draft REA

11 as it relates to reaching conclusions about

12 the adequacy of the current standard and

13 potential alternative standards for

14 consideration.

15 Does the Panel view the integration

16 to be technically sound, et cetera? Second, 

17 does the document appropriately characterize

18 the results of the Draft REA?

19 So, what I had submitted as

20 comments, again, you have posed it as

21 questions. In fact, in this section you did

22 answer the questions.
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1 There are some things that I found

2 at least troubling. Section 2.3.1, you state

3 the indicator for carbon monoxide is carbon

4 monoxide. That seems a little unnecessary to

5 me.

6 (Laughter.)

7 But, then, you fail to mention --

8 and I don't say this is something to be

9 stressed, but in the ISA, Chapter 3, there is

10 an extended discussion about carbon monoxide

11 as an ozone precursor and the localized

12 chemical interdependency of carbon monoxide,

13 methane, and NOx.

14 To say that there are some

15 alternative products that might in the future,

16 with future work, offer some surrogates is a

17 statement, but to carry that over from the ISA

18 into the Policy Assessment, that may have to

19 do with my own ignorance as to whether or not

20 the Policy Assessment should be so broad or

21 not. I just raise that as a question.

22 Section 2.3.2 said to consider
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1 alternatives to the current averaging times of

2 one- and eight-hour exposures. Then, a

3 question is posed, do health effects

4 assessments provide support for considering

5 different exposure times?

6 You come close to saying that you

7 should retain the one- and eight-hour

8 averaging times in this particular segment of

9 the Policy Assessment, but, then, elsewhere,

10 later on, you sort of back away from that.

11 You go on in ensuing paragraphs and

12 sections to discuss use of the 99th percentile

13 concentration base form and the exceeding14 once-per-year form. You sort of recapitulate

15 a lot of what is in the REA, which is

16 perfectly fine.

17 My trouble with this is that you

18 raise these questions, but, then, well, you

19 have already said that you viewed this as more

20 or less posing the options, rather than

21 providing the conclusion. But, see, for me,

22 the options were there before we started the
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1 first ISA revision, which was you could change

2 it or not.

3 Just in closing, I guess, my view

4 would be that the 99th percentile statistic

5 offers a more conservative regulation of

6 environmental carbon monoxide than using a

7 fixed value of 9 parts per million for an

8 eight-hour average. And therefore, it would

9 be more protective for the public health.

10 That is about covering my comments.

11 DR. MURPHY: Can I ask a clarifying

12 question? We were confused by, what part of

13 the ISA, Chapter 3, are you pointing to with

14 regard to discussion?

15 DR. THOM: Okay.

16 DR. MURPHY: So, that is an ambient

17 air quality? We were a little confused by

18 that.

19 DR. THOM: Well, in Chapter 3 of the

20 ISA they talk about --

21 DR. MURPHY: What section?

22 DR. THOM: Well, I don't know. I
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1 don't have it written down here.

2 DR. MURPHY: Oh, sorry.

3 DR. THOM: So, read Chapter 3, and

4 it will be there.

5 DR. MURPHY: But it has to do with

6 air concentrations of CO and how other

7 chemicals --

8 DR. THOM: CO may be a reflector of

9 some other pollutants. That's all.

10 Okay. Where my concern was,

11 actually, it started with the statement that

12 the indicator for carbon monoxide is carbon

13 monoxide. That was like, well, duh?

14 DR. MURPHY: Right. And maybe if I

15 could just clarify, that was a comment earlier

16 that we didn't carefully describe or explain

17 the four elements of the standard. Indicator

18 is one of the elements of a standard. For CO,

19 it is kind of a duh kind of indicator. CO is

20 what we measure. CO is the indicator. But,

21 for other pollutants, it is more complex.

22 DR. THOM: Sure.
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1 DR. MURPHY: For example, for lead,

2 the indicator is lead in total suspended

3 particles. Now there are a variety of

4 alternatives we could have made the indicator.

5 It could have been in PM10. It could have

6 been --

7 DR. THOM: So, for me, that is my

8 ignorance. It is written there because that

9 is part of how the EPA needs to couch --

10 DR. MURPHY: Right.

11 DR. THOM: -- their decisions.

12 DR. MURPHY: Right.

13 DR. THOM: Okay, fine.

14 DR. MURPHY: But we need to be more

15 clear, so you understand why it is there,

16 obviously.

17 DR. THOM: Okay.

18 CHAIR BRAIN: Or an introductory

19 sentence. There are these classic four

20 parameters, and here's the first one.

21 Paul, you have some additions?

22 DR. BLANC: They really relate -- I
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1 interpreted this question as a bit more

2 related to our discussion Question 7. They

3 are pretty integrated in a sense, aren't they? 

4 What would you describe as the nuance of the

5 difference between what you are asking in this

6 charge question and what you are asking in

7 Question 7?

8 DR. MURPHY: So, Question 7 has to

9 do with the considerations. When Dr. Thom

10 said, well, it was obvious to him at the get11 go what the -- these are my words, not yours,

12 obviously -- what the alternatives were, we

13 need to make a clear record here as to not

14 just what the alternatives are in terms of a

15 decision on the standard, but what is the

16 scientifically supported rationale for any of

17 these alternatives, and only present those

18 that are scientifically supported.

19 So, while because you are quite

20 familiar with all the evidence, it might have

21 been obvious to you, it would not be obvious

22 to the others who are not so familiar with the
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1 science.

2 So, what we are asking for here in

3 Question 7 is, have we discussed the

4 appropriate things to consider about the

5 evidence, the consideration with regard to the

6 evidence and with regard to the exposure dose

7 estimates, with regard to drawing a conclusion

8 on the current and potential alternative

9 standards?

10 In terms of 6, we are asking the

11 question of, have we integrated all of this

12 information together and described it in a way

13 that is technically sound, clearly

14 communicated, and appropriately characterized? 

15 And does it appropriately characterize the

16 results, also, of the REA, including their

17 significance?

18 Part of that might be 6b. Another

19 way to look at 6b is, did we take the results

20 of the REA, which was focused on the coronary

21 heart disease population, for which we had a

22 clinical study which gave us an exposure, a
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1 concentration response function for that

2 population, did we take that focused

3 quantitative analysis and did we describe it

4 in a broad enough or appropriate enough way

5 that the larger body of evidence supports?

6 In other words, we should not look

7 just narrowly at the REA. That is really not

8 -- I am suggesting this might be a way to

9 think about it. Should we not look just --

10 our conclusion was we should not look narrowly

11 at the REA and have that be the only thing

12 which drove any standards decision.

13 Of course, our whole process is set

14 up to look at the ISA and the evidence that we

15 have over the years, and to have that inform

16 our interpretation of the REA. Together, we

17 look at the information. We recognize the REA

18 will inherently be narrower than the full bulk

19 of the evidence.

20 So, I am kind of rambling at this

21 point. Sorry, I think it is late for me.

22 DR. THOM: So, what you have just
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1 said, what you were trying to get at with

2 these questions, I guess I didn't understand

3 at all. But I would say that the Policy

4 Assessment doesn't even begin to address what

5 you just said you were after.

6 And the reason I say that is because

7 you are establishing your perspective

8 regarding coronary artery disease ST segment

9 depression with a particular carboxyhemoglobin

10 level. So, the current standard, the data

11 would not support changing or diminishing the

12 current standard based upon the rigid EKG

13 changes that the literature has documented.

14 However, if you take the broader --

15 which this is recapitulation again -- of all

16 the epidemiology data, where there is clear

17 inference that the standard as it exists today

18 is probably not stringent enough, that is to

19 say, there is a risk of cardiac

20 decompensation, whether you want to call it

21 congestive heart failure, a progression of

22 cardiac decompensation associated with carbon
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1 monoxide levels substantially lower than 9

2 parts per million for eight hours, then the

3 point would be that your Policy Assessment

4 falls short of adequately describing the data

5 as it has already been presented in the ISA

6 and the REA.

7 DR. MURPHY: Right. And this is one

8 thing I alluded to earlier. I am going to

9 forget the words you used, because that is

10 what I was reacting to.

11 You are saying the epidemiological

12 studies clearly show effects at levels below

13 the current standard. But we would say look

14 at those studies because most of those studies

15 were conducted in areas during time periods

16 when the current standard was exceeded.

17 DR. THOM: Those data are not

18 available to the literature.

19 DR. MURPHY: We looked at the study

20 areas as described in studies.

21 DR. THOM: Okay.

22 DR. MURPHY: This is in our document.
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1 DR. THOM: Okay. I'm not arguing,

2 but that's not available to us.

3 DR. MURPHY: It is. It is in the

4 document.

5 DR. THOM: Now it is.

6 DR. MURPHY: That's what we tried to

7 describe for you. It is in the document that

8 you all have been reviewing. So, we recognize

9 it is not in the ISA, and we are all moving at

10 breakneck speed here. But when we get the

11 information over in the Policy Office, what

12 matters to us is, well, wait a minute, were

13 those studies, was the standard exceeded?

14 And if they are exceeded, that still

15 speaks to this larger issue that everyone

16 thinks is so important, which is, of course,

17 we see this cogency, this coherence, between

18 the epidemiological studies and the clinical

19 studies. We are seeing the types of outcomes

20 that you might expect, based on what we know

21 from the clinical studies. They show that

22 quite well.
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1 But when we look at it and say,

2 well, what do they tell us about the current

3 standard, we also say, well, look at those

4 study areas and let's look at what the air

5 quality was in those studies. Actually,

6 during some of the studies, they were

7 exceeding the standard. So, it could still be

8 showing us that coherency and that cogency,

9 but it is at levels that were above the

10 current standard.

11 So, if we want to ask the question

12 and say, what do these studies tell us about

13 meeting the current standard and being below

14 the current standard, and any potential

15 effects there, we need to look at what studies

16 have we got where we met the standard. Then,

17 it limits what we do look at.

18 DR. BLANC: But, then, there were

19 still studies that did.

20 DR. MURPHY: There are some, yes.

21 DR. BLANC: Right.

22 DR. MURPHY: And we identified them,
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1 and that is what we say when we talk about --

2 DR. BLANC: Right.

3 DR. MURPHY: -- the alternative

4 standards. When we say a range of standards,

5 well, if you look at the epi studies that

6 we've got, well, that might lead to some of

7 the lower end of the range of studies.

8 DR. BLANC: Right.

9 DR. MURPHY: If you would put weight

10 on those epi studies, recognizing

11 uncertainties, recognizing limitations that

12 this Panel has, for example, raised on those

13 studies.

14 DR. BLANC: So, one thing you would

15 like feedback on, for example, is our response

16 to the analysis that appears only in the

17 policy document in terms of ambient levels in

18 the studies that occurred in America, because

19 you don't actually talk about the ambient

20 levels, I suppose, on the studies from Taiwan

21 and other places? So, you are limiting it to

22 the U.S. studies.
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1 DR. MURPHY: We don't have air

2 quality data for those.

3 DR. BLANC: Right. So, you are

4 asking, you know, is the cup half empty or

5 half full, for example. You would like

6 feedback from us on, given those limitations,

7 how do we interpret the policy implications of

8 the epidemiologic literature, right? I mean

9 that is what you are saying.

10 DR. MURPHY: Well, I think this is

11 part of Question 7, which is what do you think

12 regarding our discussion of considerations

13 relating to the adequacy of the current and

14 alternative -- because the considerations, as

15 we raised them here, are, well, when we look

16 at the epi, we say it is very strong in terms

17 of this cogency and coherence. It gives us

18 our likely causal relationship.

19 It seems to be that many of these

20 studies, though, are when we exceeded the

21 standard. So, that means it is good we've got

22 a standard, and this is a good standard to
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1 have. But do we need it to be lower? Let's

2 look again.

3 DR. BLANC: And so, you would like

4 feedback from us, again, to repeat, on whether

5 or not our view of that would be, yes, some of

6 these studies are from times when the levels

7 were exceeded, but some weren't? And

8 therefore, the bulk of the scientific evidence

9 would weigh towards a more conservative

10 standard. That is the feedback you want from

11 us?

12 Do we view it that way or do we view

13 it, well, so many of them were with the

14 standard exceeded that we have to actually not

15 bring to bear the epidemiologic evidence at

16 all? It is not relevant because too many of

17 them were above the standard?

18 I mean that is our purview, is what

19 you are saying, right? We should tell you our

20 scientific interpretation of that evidence, in

21 light of those potential limitations?

22 DR. MURPHY: Right. And the Panel
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1 did provide comment to us with regard to the

2 epi studies. On the ISA, there was a bullet

3 which I think we cite at a place or two within

4 the Policy Assessment in terms of the

5 potential for co-pollutants to pose

6 confounding -- so, that is an issue as part of

7 the uncertainties.

8 But this Charge Question 7 is really

9 getting at, have we raised the appropriate

10 considerations? And some of those

11 considerations are, what other evidence have

12 we got? We've got some small set of epi

13 studies that were in places where we met the

14 standard. When we focus it on those outcomes

15 most related to how we know CO to operate, we

16 get left with one study area, three studies,

17 one of which is clinically significant.

18 If we put weight on that, that seems

19 to push us towards the low end of the range

20 that we put here. That is how we constructed

21 the rationale that we present here that

22 supports the range that is presented here.
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1 So, we are asking -- I may or may

2 not be answering your question; I'm sorry --

3 but we are asking for your views on, have we

4 teed up the appropriate considerations that

5 would support this end of the range, a

6 different range, an upper end of the range, et

7 cetera? That is what we are asking.

8 CHAIR BRAIN: Have we achieved

9 enough clarity for today? Okay, let's think

10 about that.

11 The other thing I would encourage

12 everyone to do is we have five more charge

13 questions on the Policy Assessment. We really

14 have only indicated one lead person, and then

15 it is says CO Panel members. So, if you have

16 a little time this afternoon and this evening,

17 if we can all look at those other charge

18 questions, and if others can make

19 contributions, and they are rather general, so

20 I know almost everyone has been thinking about

21 many aspects. Then, the latter ones deal with

22 the welfare consideration. So, if anyone can
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1 add to those discussions tomorrow, that will

2 be terrific.

3 So, let's break now. If everyone

4 during the next few hours can pull together

5 your best shot at a consensus statement, then

6 Kyndall will print those up, and we will have

7 a chance to look at them tomorrow.

8 Again, there will be time for you to

9 improve them, but we really want to make sure

10 that they are on track and that we have

11 achieved consensus that the general thrust of

12 these statements are such that we can all

13 support them.

14 Okay, thank you for a very

15 productive day. Thank you, EPA, for your

16 presentation and for asking clarifying

17 questions.

18 We will see you tomorrow.

19 (Whereupon, at 5:06 p.m., the

20 proceedings in the above-entitled matter were

21 adjourned for the day, to reconvene Tuesday,

22 March 23, 2010.)
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A

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346:19

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361:11,12 369:16

369:19 370:8

427:5

bonds 177:6

bore 319:8

borrow 416:17

bothers 384:22

bothersome 195:19

bottom 286:11

299:22 363:6

379:22 412:5

bottom-up 164:5

bout 387:18

box 275:20

Brain 1:13,15 3:8

11:2,21 12:6,12

12:13 22:5,11

24:2 25:7 26:7

38:12,22 39:8

42:6 56:3,15 57:2

66:13 74:6 80:6

80:14,18,20 81:1

89:15 90:11,18

92:10,21 94:17

99:16,19 100:12

100:18 102:2

103:3 105:10

108:10 112:5

118:13,17 119:10

121:22 122:10,16

123:15 124:14

125:10 127:12,15

127:18,22 128:10

128:22 130:3,15

130:18,22 131:5

131:11,15 132:11

132:14,17,20

139:1 140:22

143:13 146:6

147:19 148:21

149:17,21 150:5

150:13,20 151:5,8

151:14,18 154:9

156:17 158:7,13

161:18 162:6

164:10 165:11

166:4,18 175:6,13

175:18 177:8,11

177:15,19 182:18

183:12,18 184:11

184:15,22 185:4,9

185:12 186:12

190:12 191:8,15

192:5,8,11 193:17

193:21 203:8,12

203:21 204:7,15

204:21 205:2

206:11 208:11,15

208:18 210:15,19

220:6 222:12

226:10 229:10,15

231:2 232:7,12,16

233:1,6 234:3

235:9,17 236:2

237:6 240:4,11,22

241:21 247:16,19

248:13 249:16

253:21 256:4,7,10

260:5 264:10,14

268:7 269:17

270:17 271:10,12

273:1,5 280:9

281:5,11,14,21

282:8 283:1,7

286:9,22 287:13

287:16,19 288:4,7

288:12,19 289:2,6

289:17,19 291:3

291:13,17,21

292:3,12,18

294:10 295:4

305:5 309:13,18

312:13 319:7

321:19 322:11,15

325:2,11,13,21

326:17 330:5,20

331:1 332:15,22

335:3 337:15,19

338:5,12 339:19

339:22 341:3

344:20 345:1

350:14 353:19

354:1 355:1,9,20

356:1,14 357:10

357:12,17 362:15

363:5,21 369:8,14

371:15 372:13

373:3,18 374:5,7

377:4 378:8,11

383:16 385:16

387:17 388:3,7,11

394:7,15 395:9

400:9 411:12,14

418:4,21 419:2,5

424:18 436:8

breadth 20:18

break 13:2 119:4

119:11,13 150:14

150:15 235:9

236:7,9 326:7,8

326:12 437:3

breakfast 14:9

breaking 175:19

breakneck 430:10

breakout 43:1

breathe 414:4

brief 12:14 165:13

206:16 276:21

327:17,20

briefings 275:7

briefly 119:17

164:15 166:21

169:16 237:16

258:19 274:20

362:18

bring 9:4 15:18

153:1 229:21

237:20 268:2

303:13 385:7

392:21 410:21

434:15

brings 407:15

broad 19:11,21

20:3 23:16,20

163:5 347:6,9

420:20 427:4

broaden 20:22

139:4 156:21

broader 23:7 155:7

411:1 428:14

broadly 134:15

141:8 153:10

155:1,8 238:19

282:21 304:5,18

351:6

broadly-defined

134:18 142:1

143:11 155:18

brochure 239:9

broken 44:2

brought 118:19

145:18 249:4

290:7 304:3 306:8

316:21 335:12

336:8 370:15

401:10 402:2

Bruce 178:12,12,20

178:20 180:10,10

buildup 115:14

built 108:3 258:16

bulk 49:16,17

98:10 100:7

124:12 394:9

427:18 434:8

bullet 283:2 285:9

285:16 286:10

292:16 435:2

bulleted 167:15

bullets 268:6 284:4

284:6,9

bunch 122:4 128:4

269:21 396:17

398:10 417:7

burden 233:10,12

burying 65:9

busy 15:13 16:9

bystander 291:2

B-11 181:14 184:20

B-13 181:21

B-14 234:15

B-2 181:13 184:16

184:20 234:13

B-3 229:9 234:8

B-5 384:11

C

c 160:12,13 175:14

177:4

CAD 402:12

cake 227:1

calculate 53:14

200:17

calculated 192:1

calculating 57:21

calculation 227:15

calculations 43:7

165:8 171:2 189:3

calibrate 172:16

calibrating 171:18

California 251:3

call 3:2 11:6 209:12

258:17 305:20

307:11,13 428:20

called 103:17 209:6

214:14 259:14

calls 277:11

candy 132:6

capacity 179:13,15

182:21 183:14

capillary 179:19

capture 325:8

captured 32:14

77:12

carbon 1:4 9:9,19

10:3 14:21 75:12

125:13 126:4

127:4,11 130:13
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290:18,20 321:8

341:9 349:22

377:20 384:6,14

384:18,19 407:15

413:20 420:3,3,10

420:12 422:6

423:12,12 428:22

carboxyhemoglo...

62:6 73:19 86:1

86:20 88:15

147:14 211:8,19

213:13 215:8,12

215:13 216:1

218:13 219:4

224:9,14 225:9

226:2,5 229:20

230:16 231:3

282:16 343:3

364:21 379:12,17

404:2,10 428:9

carboxyhemoglo...

142:12

cardiac 14:22

134:5,14 143:11

155:1,8,11 160:6

238:11,18 385:1

385:11,19,21

428:19,22

Cardio 292:1

cardiology 291:19

cardiovascular

117:18 129:8

134:7 139:6 142:2

150:3 156:21

278:4 283:22

285:2 293:1,4

294:7,19,21 309:5

385:6 386:8,21

388:9 396:5 398:5

405:15 406:4,17

406:18

cardiovascular-r...

283:3

care 24:5 85:21

86:7 123:14 145:4

185:16 203:6

350:18 353:20

358:6

careful 402:4

carefully 423:16

carried 128:5

134:22 384:16

385:3

carry 14:14 420:17

carrying 189:6

cars 44:18 99:10,11

99:12 100:9,11

106:8

CASAC 1:14 9:13

9:20 11:4 13:11

28:22 113:4

158:14 183:8

267:2,9,11,13

270:19 274:21

302:17 337:13

338:10 361:10

case 19:3 57:17

81:22 102:4 137:7

190:2 231:6

242:15 245:5,14

250:7 270:17

281:15 288:19

317:18 331:22

332:2,3 361:20

382:4 396:2 398:8

398:9

cases 196:4

cast 282:20

categories 96:19

248:5

category 156:21

221:17 261:14

causal 136:1,6,8

137:17 294:16

396:16,16 433:18

causality 135:16,19

396:14

causally 394:21

causative 134:12

cause 131:16,18

292:8

caused 226:4

causes 130:9

287:21

causing 288:17

395:7

caveats 156:19

cell 62:19 66:15,19

67:10,17,20

Census 32:11,19

184:2 253:6

center 373:20

central 21:8 322:20

cerebrovascular

159:10

certain 68:9,11

86:8 109:9,10

144:11 222:3

223:11 251:11

371:2,8 410:7

certainly 23:6,14

53:8 65:2 67:18

85:11 98:16 126:3

144:6 145:1

149:11 175:10

176:15 178:5

181:1,6 182:4,15

183:11 200:13

205:8 206:8

252:17 283:5

284:17 309:21

318:4 319:2

324:16 355:1

371:12 375:16,21

390:12 394:13

401:7 403:5 411:4

certified 11:1

cetera 44:18 163:3

163:4 186:7,7

193:1 247:7 255:9

306:9 351:9

419:16 436:7

CFK 180:16

206:19 209:17

210:5 364:22

CFKE 178:18,22

179:3 180:10

CHAD 45:16 46:13

252:22

chain 245:21

Chair 1:13,15 3:8

11:1,21 12:13

22:5,11 24:2 25:7

26:7 38:12,22

39:8 42:6 56:3,15

57:2 66:13 74:6

80:6,14,18,20

81:1 89:15 90:11

90:18 92:10,21

94:17 99:16,19

100:12,18 102:2

103:3 105:10

108:10 112:5

118:13,17 119:10

121:22 122:10,16

123:15 124:14

125:10 127:12,15

127:18,22 128:10

128:22 130:3,15

130:18,22 131:5

131:11,15 132:11

132:14,17,20

139:1 140:22

143:13 146:6

147:19 148:21

149:17,21 150:5

150:13,20 151:5,8

151:14,18 154:9

156:17 158:7,13

161:18 162:6

164:10 165:11

166:4,18 175:6,13

175:18 177:8,11

177:15,19 182:18

183:12,18 184:11

184:15,22 185:4,9

185:12 186:12

190:12 191:8,15

192:5,8,11 193:17

193:21 203:8,12

203:21 204:7,15

204:21 205:2

206:11 208:11,15

208:18 210:15,19

220:6 222:12

226:10 229:10,15

231:2 232:7,12,16

233:1,6 234:3

235:9,17 236:2

237:6 240:4,11,22

241:21 247:16,19

248:13 249:16

253:21 256:4,7,10

260:5 264:10,14

268:7 269:17

270:17 271:10,12

273:1,5 280:9

281:5,11,14,21

282:8 283:1,7

286:9,22 287:13

287:16,19 288:4,7

288:12,19 289:2,6

289:17,19 291:3

291:13,17,21

292:3,12,18

294:10 295:4

305:5 309:13,18

312:13 319:7

321:19 322:11,15

325:2,11,21

326:17 330:5,20

331:1 332:15,22

335:3 337:15,19

338:5,12 339:19

339:22 341:3

344:20 345:1

350:14 353:19

354:1 355:1,9,20

356:1,14 357:10

357:12,17 362:15

363:5,21 369:8,14

371:15 372:13

373:3,18 374:5,7

377:4 378:8,11

383:16 385:16

387:17 388:3,7,11

394:7,15 395:9

400:9 411:12,14
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challenge 205:16

248:19 249:2

390:15 394:10

challenging 71:15

chambers 144:12

144:16

chance 272:9 437:7

change 65:22 126:9

126:18 127:5

160:22 218:5

219:13 239:16

319:20 320:14,16

320:18 323:6

328:10 334:10

340:17 346:14,17

401:12 402:20

409:15,18 417:21

418:1 422:1

changed 54:5

114:13 137:1

167:18 175:8

206:17 257:12

274:4 283:2

285:17,17 288:9

346:6 385:13

changes 15:9 122:8

126:12,13 136:16

161:8 167:18

169:19 199:8

205:14 280:1

281:16 282:14

286:11 289:1,4,9

293:16 302:13

334:16,21 377:8

401:18 402:12

403:10,11 408:13

428:13

changing 321:3

428:11

chapter 120:2,3

121:8,17 122:6

133:19,21 134:3

135:10 146:8

153:8 162:21

165:14 166:3

176:21 204:3

213:10,11,21

257:2 313:12

327:17 401:4

420:9 422:13,19

423:3

chapters 121:18

163:7 167:1,7

characteristics

44:14 61:1,10

68:15 189:8,9

199:10

characterization

30:8 63:14 110:12

110:13 119:21

182:15 262:12

302:19 303:16,19

304:13 305:1

329:9

characterize 53:11

108:18 111:1

117:6 120:5 339:5

419:17 426:15

characterized 46:3

46:5,17 84:16

163:4,11 247:13

260:15 278:3

279:4,8 281:3

284:19 285:5

339:10 426:14

characterizes

17:18

characterizing

153:10 258:11

charge 3:21,22 4:7

4:13 5:2,11,18 6:2

6:6,19,20 7:2,9,14

7:21 8:13 13:7,18

25:11,16,19,22

26:3 81:11,12

89:19 92:20 94:20

95:8 108:14

118:18 119:2

122:11 125:11

135:11 144:5

150:16 151:2

162:10,18,19

166:5,8,15,16,21

166:22 177:21

178:2,3 185:13

194:3 203:9

226:12 237:7

254:2 256:11

260:6 264:21

265:12 268:15,17

268:21 269:8

270:12 272:6

273:21 274:22

302:17 326:3,11

327:10 330:7

339:21 354:2,4,17

355:2,16 369:10

374:4 377:3

378:12,15,19

383:16 387:4

400:11,11,15,22

418:5,10 419:5,7

425:6 435:8

436:12,17

charged 411:16

chartered 11:4

CHD 33:11,14 37:7

41:13,14 42:11,13

43:15 45:12,16,19

51:20,21 60:16

63:13,18 64:4,9

67:10,11,14,20

68:1,2 103:17,21

104:3 111:9

153:15 182:11,13

258:21 259:6,10

260:4 261:18

285:4 382:4

checks 258:17

259:5

chemical 164:2,6

289:14 420:12

chemically-induc...

289:14

chemicals 423:7

chemistry 302:9,10

CHF 282:10

chime 206:12 401:1

Chock 115:9

choice 23:1 122:21

403:6 418:9

chose 71:11

chosen 71:18,18

chronic 138:21

140:16

churches 106:1

212:20

cigarette 212:2

circles 24:21 32:16

circular 343:15

citations 335:22

cite 435:3

cities 242:12

245:18 248:9

city 117:9 173:16

351:1

claim 178:21,22

claiming 287:21

clarification 4:3,10

4:18 5:6,15,22

6:10 7:23 51:6

53:7 184:14 327:5

328:10 341:20

386:4 418:6

clarified 124:2

126:5 152:1

clarifies 294:12

clarify 41:10 43:20

67:8 84:22 167:13

191:19 244:3

250:6 284:5 305:8

310:12 360:15

402:6 410:2

423:15

clarifying 152:11

422:11 437:16

clarity 20:11 152:3

152:9 436:9

classic 394:8

424:19

clean 1:3 9:8,14

138:8 214:11

327:21

cleaner 379:19

clear 24:22 25:1

38:13 64:21 95:9

123:4,17 124:5

128:9 138:20

139:2 169:13

181:13 215:20

223:1 236:3 241:2

261:8 265:19

308:12 325:3

329:20 358:7

370:11 385:4

389:4 398:3,13

412:3,14 413:18

424:15 425:13

428:16

clearer 64:16

clearly 15:2 62:16

130:5 157:16

160:12 161:2,6

167:9 169:19

218:19 246:7

328:20 330:4

332:14 344:3

353:3 354:16

355:8 391:11

403:3 426:13

429:12

clearly-communi...

119:22 121:9

380:8

climate 15:9

301:16,21 302:2

302:13

climate-related

305:3

clinical 65:3 153:16

161:5,16 223:10

223:17 279:9,18

279:22 285:9,20

286:17 288:12

293:5 296:11,14

348:16 381:9

389:9 390:19

392:14,22 396:3

398:21 399:19

402:18 426:22

430:18,21

clinically 221:18

435:17
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73:15 80:4 126:16

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closely 315:16

367:5

closer 54:21 66:21

69:8 73:10 175:5

273:16

closest 132:7

closing 422:3

clouding 379:21

cluster 117:9

Coburn 178:9

cogency 430:17

431:8 433:17

cogent 380:10

COHb 29:16,17,20

30:1 31:1 32:8

35:2 36:17 37:3

38:7 39:15 40:15

41:4 44:11,21

45:9 46:20,22

47:19,19 48:2,22

49:2 50:4,10,20

51:4,4 53:22

57:22 59:6,9,21

60:4 67:15 70:17

70:19 71:3,5,9,12

71:20 72:9,16

73:13,15 74:14,15

75:5 78:5,15

87:13 101:10

112:22 113:9,22

114:16 116:8,10

116:12 118:9

120:11,16 122:22

123:22 124:7

140:11 144:22

145:5,13 153:16

153:19 154:5

157:4 169:5,9

170:1 178:10,15

179:9,11 181:4

193:13 207:1,8

208:12 209:10

210:9 218:4

219:13,14 220:19

222:3 231:9,12

248:4 278:2

279:10 280:3

285:10 295:11,16

295:20 296:2,13

296:17 297:8

298:6,7,14 300:8

342:11 377:21

381:4 389:10,15

390:13

coherence 279:17

396:3,13,15,15

430:17 433:17

coherency 431:8

coherent 239:13

266:16 271:17

285:20 293:5

cohorts 45:17

cold 120:15

collect 29:12 40:5

collected 263:6

392:5 418:17

collection 100:1

collective 408:8

collectively 267:1

Colome 190:4

196:13 197:7,10

200:6

color 355:17

Colorado 189:5

colors 32:13

column 155:10

220:16 241:8

columns 416:1

combination 51:2

148:7 285:10

287:11

combinations

299:16

combine 371:5

combined 36:21

85:17 371:12

combustion 413:22

come 47:21 64:13

68:8,12 92:11

95:8 133:20

142:16 145:14

146:7 169:13

171:5 174:3

186:13 204:2

212:18 221:1

224:10 225:10,11

236:6 253:13

257:3 273:3 331:8

336:13 337:3

346:12 353:6

363:11 365:2

383:7 389:22

399:4 421:6

comes 76:1 144:20

205:6 211:22

228:11 261:15

269:5,7,10 273:14

273:15 275:21,21

364:20 368:9

384:10 391:22

397:8,12

coming 12:15

15:12 16:4 56:8

89:14 106:7

120:15 133:5

211:14 215:19

220:12 228:16

359:12,18 380:16

386:10 399:8

command 245:21

commend 113:12

commended

237:17

comment 3:18

10:14,15 24:4

25:8 72:5 81:7

90:15,17 91:8,9

91:11 92:9 94:22

95:7,12,16 111:18

112:7 128:1

129:21 133:6

144:21 146:13,17

148:22 151:3

152:11 164:14,15

165:6 166:5 167:6

170:7 177:12

181:18 182:8

185:16 186:8

190:6 194:22

204:8 217:22

222:13 231:7

249:3 252:13

256:1,11 262:14

269:1 352:20

353:8,16 413:15

423:15 435:1

commented 16:20

381:2

commenting 24:14

123:19

comments 3:9

10:17 13:19 16:6

25:17 29:1 30:10

63:3,4 91:21 93:1

95:3 111:22

116:15 119:15

122:1,4 125:1

126:22 142:17

152:6 154:8

162:22 165:13

166:6,13,20 167:4

167:4,12 170:5

176:14 177:3,14

185:13 186:14

190:13 194:2

195:1 205:7 228:2

240:2 247:17

253:22 254:14

255:21 256:3

257:10 260:5

264:11 265:4,5,8

266:9 268:6,10,12

268:19 269:11,21

269:22 270:3,5,14

284:8 286:1 293:7

294:9 326:18,19

327:7,14 331:3

347:8 377:3 378:7

379:2 380:12,13

380:15,19 382:11

389:2 392:1 418:5

418:19 419:20

422:10

committee 1:3 9:9

9:15 10:6 15:16

25:4 28:22 111:18

267:2 269:19

357:7 358:8 362:8

362:9 380:4

committees 361:13

committing 369:18

common 182:18

367:12

communicate

205:18

communicated

167:9 426:14

communicating

12:21

communication

309:10,20

community 200:8

200:13

commuters 264:2

commuting 31:12

252:16,17 317:20

comparability

111:8

comparable 52:2

126:15 253:16,20

compare 48:11

73:9 126:20

222:18 253:2,5

257:15 258:1

332:9 417:19

compared 46:2

189:4 209:22

329:14 341:5

comparing 73:7

113:4 243:2

comparison 47:2

47:12 113:1,4

168:3 200:14

252:21 262:20

264:6

comparisons

180:15

compendium

270:14

compensated

273:11
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Neal R. Gross & Co., Inc.

Page 447

compensation

282:9

compensatory

385:8

complete 15:21

21:17 25:19 30:7

121:14 175:20

272:2 397:9

completed 21:7

369:10

completely 84:2

134:21 203:19

216:3 224:21

225:7 268:22

313:1,6 322:2

375:22 391:16

complex 292:7

423:21

compliance 11:8

305:22 306:3

complicate 397:1

complicated

273:12

complications

286:7

component 238:1

292:8 396:15

components 87:12

computational

58:19

computationally

71:14

conceivably 369:1

concentration

35:13 49:12 58:10

59:13 96:13,22

97:1,7,14,22 98:1

100:1 101:1 103:9

106:19,20 107:8

108:6 115:11

169:8,19 173:6

179:19 187:6,16

190:21 195:4

198:5,7 201:9

202:7,9,10,11,16

202:18 218:8

222:3 231:20,21

232:5 263:12

306:6 321:18

324:19 342:9,10

368:12 390:5,7

395:1 421:13

427:1

concentrations

31:16,21 32:1,3,4

33:18,22 37:15

49:9 96:10 97:6

98:7,9,22 100:4,6

101:18 102:11,12

102:19 103:14

107:5,7 110:16

114:5 115:2,7,17

140:7 147:11

164:20,21 165:17

172:13,22 173:17

173:19,20 174:18

174:19 186:18,21

186:22 187:14

188:16,16 192:18

193:9 197:9

198:20 201:2,8,20

201:22 202:1,16

202:19 203:1

243:2 262:16

263:7,15,18 291:1

320:7 322:21

357:8 367:12

395:6 397:3

413:14 423:6

Concentration-b...

329:17

concentration/re...

290:15

concept 128:19

138:11

conceptually

106:10,11 107:14

356:17

concern 120:19

128:6 139:12,13

141:1 158:15

203:18,21 206:5

206:13,22 229:16

235:16,19 241:22

254:16 318:21

334:16 374:12

397:4 404:8,13,14

423:10

concerned 60:7

69:14 78:20

114:21 192:14

194:9 255:16

383:18 406:4

concerning 18:19

concerns 162:20

207:14 271:1

325:9 333:18

383:11 403:9

concert 334:9

conclude 348:6

concluded 134:11

284:13

conclusion 110:6

180:14 320:13

339:8 346:6,12,16

346:20 348:4,17

349:6 350:11

353:18 370:14

421:21 426:7

427:10

conclusions 136:14

147:20 279:11

285:12 303:22

304:4 346:5

351:10,12 353:4,6

355:4 356:12

394:6 419:11

conclusive 134:12

condition 46:4 97:8

conditions 17:22

62:20 109:9,17

139:7 374:15

conducted 10:8

257:4 393:17

394:1 395:1

429:15

confer 236:3

confidence 209:5

confident 121:1

confined 25:18

268:17

confirmed 334:10

confirming 195:13

confirms 234:15

conflicts 11:13

266:17

conflict-of-interest

11:9

confounders 140:6

confounding

117:14 138:2

435:6

confuse 56:17

confused 56:15

93:3 152:2 268:4

311:8 321:7

388:22 414:14

422:12,17

confuses 211:17

confusing 175:9

212:10

confusion 56:4

71:9 76:1 175:5,7

212:5

congestive 134:17

136:11,20 137:6

137:19 143:16

159:8,16 396:10

412:2,7,14,17

428:21

Congress 352:3

conjunction 300:18

connect 242:5

connection 35:5

104:19 141:18

consensus 13:17,21

264:22 268:14

270:12 272:1,11

327:4,8 338:2

355:11 363:22

400:20 418:16

437:5,11

consequence 129:4

138:21

consequences

127:13 130:20

287:19

conservative 88:10

422:5 434:9

consider 23:6

102:20 149:12

153:4 177:5

198:10 217:19

245:16 276:1

300:16,20 301:2

304:15,20 313:8

315:11 316:18

320:14 324:20

350:6 352:18

353:15 354:12,22

361:3 364:9 382:7

420:22 426:4

considerable

168:10 399:1

considerably 62:5

65:4 170:2 239:17

consideration 11:5

18:4,12,15,22

19:2 22:2 64:11

148:12 157:19

163:2 170:19

201:19 274:19

275:22 276:5

277:16 304:22

316:18 347:4

381:17 405:17

419:14 426:5

436:22

considerations

17:15 87:21 118:7

162:21 163:7

274:18 277:21

295:8 296:6 297:4

297:12 303:15

304:3,12 310:19

313:11 339:2,4

340:21 366:22

425:9 433:12,14

435:10,11 436:4

considered 11:16

20:7 23:8 37:12

112:2 126:1 147:3

152:17 176:3

183:15 290:1

301:15 313:4
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320:15 354:14

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considering 19:10

35:19 41:3 48:3

98:18 152:18

153:21 297:8

300:8,19 301:14

312:15 317:14

323:3 355:5 396:1

421:4

consistency 92:12

156:13 258:17

consistency's 239:6

consistent 10:5

62:17 74:7 76:16

76:17 78:22 97:16

117:6 129:13

134:17 144:7,9,10

156:14 197:6

212:15 213:5

235:13 241:15

282:14 292:22

304:8 313:12

335:21 409:17,21

constant 74:18,22

75:2 115:4

constantly 233:16

constituency 362:4

362:6

constricted 269:2

construct 382:19

constructed 48:18

283:11 318:3

345:16 368:18

435:20

construed 359:20

consumption

259:15

contains 187:3

content 158:16,17

context 25:6 29:6

140:15 159:3

245:1,9 271:15

349:8 385:6

continue 21:9

276:20 285:11

374:2

CONTINUED 4:1

5:1 6:1 7:1 8:10

continues 232:21

279:7 284:11,20

285:1,4

continuum 142:7,8

335:13 403:16

contradiction

107:16

contribute 109:14

134:8

contributed 217:15

contributes 50:22

51:3

contributing

212:12 344:8

contribution 50:12

50:13,17,20 52:19

59:6,13,14 60:2,9

61:3,6 65:22 70:6

71:4 75:5 82:10

83:3,16 84:7 87:8

87:15 89:1 94:13

98:16 99:1 102:13

212:8,9,9 218:22

219:11,12,14

226:4 344:13

383:1,2

contributions 30:3

220:2 379:18

436:19

contributor 33:4

287:1

contributors 211:8

control 116:6

216:16,17 259:19

307:1,2 308:2

325:18

controlled 86:14

123:5 133:9 138:6

140:11 160:8

280:2 283:15

285:6 289:11

293:11 296:13

333:14,19 383:20

386:16,17 387:18

388:1,10 390:19

398:20 399:21

controlling 295:14

controls 260:1

306:8 375:19

convened 1:11 9:20

convention 34:4,10

305:17

conversation 14:9

89:17 275:21

310:9,11 366:17

converts 173:19

convey 290:11

convinced 78:21

227:9

convincing 89:1

133:10 141:14

148:15 155:22

215:6 373:13

396:11

convincingly

141:19 159:15

convoluted 345:10

convolution 123:13

COPD 169:11

182:4,7,10,14,19

copy 36:4 91:4

124:18 271:6

326:1,5 382:12

416:17

core 32:15

coronary 128:17

134:4,15 136:21

137:1 143:8

153:18 154:2,13

155:6,10,16 157:5

157:9 161:4,6,13

162:7 182:3

207:16 208:3

227:4 238:12,15

241:6,8 242:9

279:7 291:7

336:20 365:11

366:1 385:7

391:21 404:18

405:5 407:5

426:20 428:8

correct 41:18 53:10

63:1 67:6 70:22

71:16 72:1 91:8

93:2 103:22 156:4

231:5 252:14

259:12 282:4

343:3 384:9

409:14 411:20

corrected 79:17

correctly 43:21

70:14,21 126:2,6

181:18 185:21

261:12 289:8

342:20

correlate 335:5

correlated 55:19

57:19

correlation 55:17

correspond 307:9

308:20

correspondence

308:14

corresponds 52:13

52:13 251:17

cost 397:19

couch 424:9

couched 359:2

366:1 371:22

count 107:12,13,20

107:21

counted 107:12

country 242:5,6,11

242:13 244:15

245:18 246:4

248:14

County 253:12,12

couple 26:22

120:10 125:8

195:2 255:19

266:10 315:5

319:6 327:14

328:6 351:18

364:12 368:3

384:2 397:6

411:18,19

course 30:7 37:20

50:2 52:19 57:12

60:8 88:16 91:18

92:1 97:11 101:4

102:12 108:19

109:4,16 134:22

179:2,10 183:5

215:15 235:5

250:11 253:16

263:13 280:6

282:12 317:7

342:16 389:9

392:11,13 410:5

415:3 427:13

430:16

courts 375:10

court-ordered

21:15 276:16

cover 270:11

302:18

coverage 194:16

covered 25:21

94:19 158:2

210:18

covering 422:10

CO-aggravated

288:22

CO-induced 278:3

co-pollutants

148:13,14,17,19

413:15 435:5

CO2 65:3 179:19

crack 224:5

crazy 382:16

create 20:6 27:21

275:6

created 13:9 275:4

creates 14:16 58:16

criteria 9:18

116:20 161:19

396:17,17

critical 17:7 18:9

22:1 133:7 139:9

146:21 160:14

216:6 292:7

410:17

critique 81:15

261:12

cross 72:7 360:6
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crucial 139:21

333:9

crude 142:20

cumulative 48:18

132:12,22 382:20

390:11

cup 433:4

curious 406:10

current 18:1,20

19:7,8 31:6 33:18

34:2,2,8,8 37:14

39:7,10 48:4,12

50:14 52:3,14,21

53:17 54:16 56:6

56:10 57:1,8 82:5

84:3 98:20 111:2

111:2 113:8,20

114:3,7 118:9

121:1 143:3 149:2

149:19 163:2

174:8 180:3 201:4

202:3 249:19

261:17 263:2

276:10 277:4,6,7

277:12,17 284:14

284:20 285:1

295:9 296:21

297:20 298:1

300:5 303:13

304:7,8 305:2,14

305:19 320:17

322:5,6 323:12

325:14 337:10

348:4 352:17,19

354:5,12,20 356:3

356:7,20,22

362:19 363:9,15

367:8,10,17

368:22 372:9

382:9 385:12

393:18,20 395:18

401:13 415:19

419:12 421:1

426:8 428:10,12

429:13,16 431:2

431:10,13,14

433:13

currently 183:7,13

183:14 184:8

301:12 310:18

311:4 314:14

currently-availa...

167:8

curve 82:15 138:8

216:7 223:2

curves 321:2

cut 227:21 292:11

418:3

cutoff 227:18 413:3

CVD 341:14

C-O-N-T-E-N-T-S

3:1 4:1 5:1 6:1

7:1 8:10

D

Dahms 1:18 5:13

7:4,10,22 45:15

45:21 53:4,6,9,16

54:4,9,13 73:18

73:22 74:3,9,17

75:1 91:1,4,6,16

99:6 100:21 128:2

128:13 129:2

131:20 132:13,16

132:18 133:1

135:15 136:4,8

149:22 150:7

162:3 184:13,16

184:20 204:10

206:13 208:14,17

208:20 222:15

229:13,16 231:5

232:19 233:4,9,18

233:22 235:16,18

241:22 243:20

244:16 245:19

247:18 248:8

287:9,14,17,22

288:6,8 289:11

290:6 305:7,21

306:2,10 308:4

309:2,12,15

319:11 320:3

332:21 333:2

335:8 337:16,20

339:20 371:19

374:4,6,10 375:7

376:2,9 377:2

383:18 385:18

386:3,11,14,19

387:3,8,10,22

388:5,8,16 389:1

389:15,20 401:2

402:7 403:1,5

406:11

daily 35:14 37:4

111:12 298:19

300:22 307:6

danger 227:17

dashed 49:4,17

data 15:5 29:13

35:17 38:17 39:4

40:5,10 41:8

45:16 46:2,13

48:16 51:18 54:6

57:16 62:17 63:9

63:10,11,18,22

65:11,18,19 66:12

68:19,21 70:5

72:19 73:7,8

76:18 78:16 80:12

81:5,7 83:13,20

84:10 88:22 93:21

100:2 104:2,3

107:4 109:5 110:1

110:2,17,18

111:14 112:2

113:16,16 115:16

115:21 116:2

117:6 120:20

121:4 123:8 127:8

127:8 129:5,6,11

129:17,22 133:11

134:11,16 137:10

137:11,13,15

139:12 140:11

141:9,13,19 147:9

148:2,15 155:19

155:21 156:2,2,5

156:18 159:12

160:9 161:9 163:3

167:20 168:14

171:10,20,21

172:17,19 174:2,2

174:9,21,22

179:14,16,20

180:3,4 182:4,5

183:2,10 184:2,3

184:7 186:4

191:13,21 192:22

193:3,7,16 196:8

196:9,13,16

198:18 200:3

202:4 206:9

207:18 208:2

209:15,19 210:1,8

213:13 215:5,11

218:3 219:17

221:22 222:1,5,8

223:15 225:4,14

226:17 227:8

242:6,12 243:6

245:6,13 246:18

248:9 250:8,21

251:5 257:3,15,16

258:2,3,13 260:18

262:3,4,20 263:4

280:7 281:10

287:6 299:5,13

308:18 318:8

319:19 333:8,13

333:14 335:10

344:12 346:13

360:4 361:5 363:8

363:14 364:15

365:12 367:4

370:3 371:4 373:9

373:12 374:20,21

378:3,5 381:9

382:1,5,19,21

383:7,14 391:11

396:10 398:18,20

399:18 400:8

403:15,20 404:4

406:1 411:17

415:8,9 417:15,19

428:10,16 429:4

429:17 433:2

database 109:22

111:6 279:15

281:2,19 285:18

285:20 293:3

294:3,4,6

dataset 58:16 241:4

257:8 307:17

308:15 314:6

320:1 332:8

392:22

datasets 198:17

date 180:18 276:16

dated 118:20 326:2

Dave 27:13

day 14:3 37:5 39:20

40:1 87:20 113:18

230:8 252:6,15

309:4 437:15,21

days 14:21 29:18

40:6 48:1 246:3

266:11 310:4,5

day-by 113:17

day-to-day 115:3

deadline 21:15

deal 21:7 90:4

133:22 152:3

166:11 167:2

211:10 436:21

dealing 103:5

136:11 145:5

158:8 169:1 326:4

333:8 336:17

383:19 401:12

407:17

deals 61:17 167:21

210:21 330:8

403:21

dealt 135:12

168:11,15,21

217:1 401:5,9

decades 178:20

deceiving 56:20

decide 94:21

245:21 337:9

338:15 353:17

decided 318:10

deciding 20:9
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decisionmaking

176:18,19 393:14

decisions 24:18

245:11 247:2,6

338:4 361:19

424:11

decompensation

428:20,22

decrease 126:16

291:10,12

decreased 130:14

248:19 291:11

402:19

decreases 280:15

decreasing 126:10

decrement 222:18

deep 71:8

default 276:4

defeats 196:5

define 134:4 141:7

141:12 143:7

155:4 156:8

242:10 262:8

defined 44:7,20

45:14 134:15

146:3 154:13,17

155:1,9 238:19

328:17,21 329:19

defines 329:12

defining 44:6 75:10

75:19 262:5

definitely 21:16

214:11 332:14

349:17 385:3

definition 38:13

101:19 139:4

155:5 213:6

238:10 240:20

degree 169:20

188:22 197:22

238:3

Deidre 3:15 4:4,22

5:8,24 6:14 26:18

27:3 28:20 274:5

delay 375:9,14

deliberations 10:7

10:11

delineate 28:3

delivery 143:19

280:13,15 281:15

286:15 288:1

291:11 395:13

delves 411:6

demographic 169:2

demonstrates

114:3 115:22

density 32:12 48:19

Denver 32:9,21

33:20 35:12 38:2

39:5 49:6 53:1

54:8,10 82:2

98:20 114:11,16

114:20 168:7

172:18 189:5

242:4 248:2

252:18 253:12

298:9,12,13 351:1

374:20,21 375:1

376:4,8

Denver/LA 244:18

denying 406:15

depend 219:10

220:1 302:8

depending 109:17

179:17 300:6,17

301:5 348:8,13

351:7 383:13

depends 156:7

231:9 262:5

331:19 359:2

418:2

depicted 49:15

96:11

depression 289:22

335:5 402:13,16

428:9

Deputy 2:2 3:6

11:11,20

derive 85:15

143:10 174:6,16

239:8 332:9

derived 241:4

deriving 184:3

describe 120:14

165:16 182:16

347:17 349:2

366:22 375:22

423:16 425:4

427:3 430:7

described 181:21

246:19 254:9

286:18 304:5

346:19 369:7

426:12 429:20

describing 351:14

429:4

description 165:15

169:13 229:19

274:16 336:5

374:18 375:17

377:9

descriptions

257:21

descriptive 54:13

328:7 329:16

design 37:21

223:16 275:18

305:20 315:12

316:2 333:22

382:9

Designated 2:2 3:4

9:7

designed 17:13

18:4 20:19 223:10

223:12

designing 314:12

desirable 381:18

desk 14:21

despite 148:2

328:22

destination 272:17

330:11

detail 106:13

115:10 242:4

269:9 294:13

303:8 340:10

detailed 13:20

25:13 124:22

255:21 265:4

268:6

detailing 116:15

details 28:2 179:2

192:16 333:17

341:17 345:21

380:20

detection 188:3,7

190:15,16,18

191:1,13,16,20

192:1,14 193:10

determination

351:21

determine 334:22

determined 11:12

350:19

determines 196:22

determining 243:9

deterministic

306:16 313:9

detract 165:7

develop 103:16

138:12 224:6

developed 70:6

107:8 173:10

196:7,13 199:2

306:9,14

developing 315:14

development

172:10 180:22

275:12

develops 162:9

DFO 10:10

diagnosed 33:11

405:5

diameter 287:3

diametrically-op...

382:17

diaries 46:16

111:12 250:12,17

250:18,20,22

251:2,8,16 252:11

diary 250:8 252:1

Dickerson 1:19 4:8

104:18,18 105:4,7

150:18 151:16

162:19 165:1

differ 43:7 44:22

difference 46:10

48:14 56:5,9,22

57:4,12,13,16

59:8 93:12,18

98:3 176:8 265:17

310:13 314:6

375:1 409:6 425:5

differences 27:20

28:4 46:6 52:18

52:20 115:5

245:15,17 253:18

257:17 258:6

302:12 303:18

306:20

different 27:20

35:16,21 36:1,12

36:13,14,18 42:21

43:10,18 45:6,13

45:19 60:2 67:15

68:4,14 69:21

72:18 83:18 87:16

93:13 131:12

142:3 143:20

148:5 152:15

153:19 158:18

159:3 171:17

197:13 199:7

203:17,19 213:7

217:19 222:20

223:19 229:2

239:4,5,19 242:18

242:19 244:5

245:2,3,5 248:4

249:21 252:10

257:18,21 263:13

278:18 292:9

296:15 299:16,19

299:20 300:10

308:9,17 309:19

313:1,8 314:20

318:19 320:21,21

322:2 323:9 332:5
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differential 240:1

differently 312:9

differing 295:11

difficult 14:13

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138:1,4,19 258:7

414:3

difficulties 259:3

difficulty 105:3

diffusing 182:21

183:3,14

diffusion 169:11

179:13,15 181:18

181:21

dihalomethanes

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dilate 287:10

406:21 407:6,9

dilutes 373:7

diminished 182:21

183:13 280:13

diminishing 428:11

dinner 128:3

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dioxide 148:7

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direct 113:3 301:22

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direction 15:22

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262:7 266:9

324:16 363:19

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directions 15:7

directly 101:9

259:13 354:4

356:19 407:22

Director 2:2 3:6,10

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disagree 13:21

164:16 222:7

225:5 345:6

disappointed 346:8

disconcerting

68:17 387:16

discount 139:20

391:3 404:4

discounted 400:6

discounting 225:11

397:9,10

discounts 283:11

discuss 27:20 47:5

92:19 355:11

389:6 390:14

421:12

discussant 150:16

discussants 184:12

discussed 111:15

120:7 144:20

147:10 160:18

166:20 168:3

169:16 170:1,13

177:2 178:9

185:19 225:15

258:19 270:8

285:22 303:11

341:8,11 381:19

426:3

discusses 149:1

discussing 105:12

148:22 224:12

279:6 303:9 385:5

discussion 3:25

4:17 5:5,14,21 6:5

6:9,17,22 7:7,12

7:19,24 8:18 47:6

55:20 64:13 68:12

75:7 81:1,14 95:6

95:13,15 111:6

119:19 123:21

126:7 128:3

133:20 135:7

139:3 140:13

147:6 152:12

153:7,9,12,20

199:3 205:22

210:13 243:11

262:17 272:3,10

307:14 319:8

340:8 341:1,21

369:9 375:8 377:7

380:9 385:15

386:22 389:3

401:2 411:12

420:10 422:14

425:2 433:12

discussions 10:20

13:1 277:2,20

340:11 437:1

disease 42:1,2,2

44:1 61:20 62:19

128:15,17 134:5,6

134:8,15,16,18

136:21 137:2

141:16,22 142:2

143:8,11 150:3

153:18 154:3,14

154:21 155:1,6,8

155:11,11,16

156:3,22 157:6,9

160:6 161:4,7,13

182:3 207:17

208:4 227:4

238:13,15,18

239:8,12,22 240:8

240:20 241:6,8,9

241:11 242:7,9

243:17 244:8

262:6,8 279:7

281:20 282:7

309:5 336:20

365:11 366:1

385:6,7 388:9

391:21 404:18

405:5,7,16 406:5

406:13,16,17,18

406:19 407:5

426:21 428:8

diseased 287:10

385:20

diseases 144:12,14

169:10 182:2

278:4,5 285:2

disentangle 70:9

dish 132:6

disk 414:18

dispersion 115:6,9

display 53:11 83:20

displays 71:21

disregard 123:2

134:5

diss 397:14

dissing 398:1

distinct 98:3

112:18

distinctions 413:17

distributed 66:19

89:3,5 382:12

distribution 45:11

50:9 54:18 57:14

61:21,21 62:1

66:4 67:2 72:16

73:13 74:13 75:4

77:8,14 79:21

108:4 112:21

113:14 114:16

115:4 116:10

187:7 189:21

190:8,11 193:15

194:7 197:2,5,19

203:6 207:2

211:19 237:22

253:3 255:15

259:18,20 313:3

317:16,19 320:5

324:10 376:7,7

382:2

distributions 73:12

88:14 192:21

196:21 199:17,20

234:16 253:6

376:22

districts 168:8

diurnal 75:13

diversity 197:13

Division 3:11

DLCO 183:1

document 13:5

20:7 22:7 28:17

28:17 29:10 30:5

33:13 36:20 48:17

51:12 55:20 61:16

71:20 76:2 77:17

81:8 82:3 84:3

85:16,18 90:8,10

90:16 91:7,15

92:7,8 93:16 95:1

95:11 104:20

111:18 134:4

135:1,1,8,22

137:22 142:8

144:18 147:2

168:22 175:8,11

176:2 178:11,14

212:4,7 214:16

216:14 235:14

238:21 239:12

255:2 270:19

271:4 273:20

274:7,18 275:7,13

275:19,22 276:9

283:17 293:19

295:2,3 299:3

304:8 307:14

310:15,15 336:1

336:12 337:5,7

346:9 349:21

369:7 370:6

372:14,15,22

374:16 375:22

382:14 383:5,6

386:5 390:15

391:14 408:7

409:22 411:21

419:8,17 429:22

430:4,7 432:17

documented 114:8

115:10 330:14,15

428:13

documenting 402:4

documents 13:15
202-234-4433

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Page 452

16:5 22:1 27:21

28:5 129:10

229:18 268:5

374:13 418:12

doing 78:13 99:12

123:6,9 124:11

139:22 143:5

152:13 155:14

157:7 201:8 204:3

228:10 258:10,12

283:9 316:2

323:19 324:1,2,5

400:14 407:14

domain 31:17

41:22 45:14 194:6

domains 30:12

32:15 33:10

dominantly 101:20

dominated 392:13

dose 17:20 28:9

29:17 30:1 32:8

35:2,21 37:4,4,11

38:1 40:7,15 41:4

49:11 50:4,5,10

51:4 57:22 100:22

101:5,10 108:21

109:4 119:20

138:8 181:4

206:22 210:5,9

222:9 223:1,1

230:15 260:12

282:13 296:10

303:20 325:19

328:1 378:21

379:20 400:7

426:6

doses 286:12

dose/response

138:5,12 157:8,13

double 65:6 239:15

double-checking

78:18

doubt 203:14

Doug 416:4

downplay 408:8

downside 84:9

downstream

159:18

downward 363:20

364:3

dozen 336:3

Dr 3:5,8,15,17,23

3:24 4:4,8,9,12,14

4:15,19,22 5:4,7,8

5:12,13,17,19,23

5:24 6:4,8,11,14

6:15,16,21 7:4,5,6

7:10,11,15,16,17

7:18,22 8:16 11:1

11:20,21 12:2,5

12:12 24:12 26:18

26:18,21 27:3,4,5

27:8,9,13,16

28:19,20 38:16

39:1,12 41:10,11

41:12,20 42:4,8

42:16,17,19 43:2

43:19 44:3,5

45:10,15,18,21,22

46:18 47:3 51:5,7

51:8,10,11,15,16

51:18 52:10,11

53:4,5,6,8,9,13,16

53:19 54:4,7,9,12

54:13,19,22 55:12

55:12 56:14,16

57:3 60:13,19

61:13 62:10,13,14

62:16,22 64:12,14

64:15 65:5,6,17

66:6,8,10,11,17

67:7,22 68:8,18

68:20 69:6,7,10

69:11,13,14,18,20

70:2,4,22 71:7,16

71:17,22 72:3,4

72:10,11,20 73:11

73:16,18,21,22

74:2,3,5,9,11,17

74:19,21 75:1,3,6

75:8,9,15,16,21

75:22 76:5,6,10

76:11,13,14,22

77:1,6,7,15,16,22

78:8,10,17 79:4,5

79:10,11,13,15,17

79:19,21 80:1,9

80:17,19,22 81:3

81:20 82:7,8,12

82:13,17 83:1,5

83:17 84:4,8,14

84:17,20,21 85:5

85:7,8,11,12 86:9

86:10 87:18 88:2

88:4 89:6,9,10,12

90:7,15 91:1,3,4,5

91:6,9,16,17

92:18,22 93:17

94:2,3,6,7,9,10,16

95:18 99:6,14,18

99:21 100:15,20

100:21 101:4,14

102:9 103:7,15

104:1,6,7,9,16,17

104:18,20 105:4,7

105:15 106:12,22

107:3,10,17,18

108:1,15 119:3,8

119:14 122:3,15

122:17 123:18

124:4 125:8,11

127:14,17,20

128:2,13 129:2,20

130:12,16,19

131:3,7,14,18,20

132:13,16,18

133:1,5,12,16,18

135:15,20,22

136:4,6,8,10

137:21 139:18

141:4 144:1,1,3,4

144:9 145:14,19

145:20 146:16

148:1,10 149:11

149:20,22,22

150:6,7,12,18

151:16 152:8

154:10 156:1,4,9

157:2,17 158:12

158:17,18 160:21

162:3,19 164:14

165:1,12 166:14

166:19 170:8,9,10

171:7,22 172:2,4

172:5 173:1,12

174:5,9,13,14,15

175:2,3,10,17,21

177:9,10,13,18

178:1 180:8 181:8

181:10 182:1,9

183:5,17,19 184:1

184:13,16,19,20

185:4,6,7,9,11,15

186:8,9,16 187:20

189:14 190:1,12

190:14,20 191:2

191:11,17,19

192:6,7,10,12,13

193:4,6,17,19,20

194:1,15 199:14

201:7,17 203:5,11

203:13,18,20

204:1,12,18,22

205:3 206:13

208:14,17,20

209:3 210:17,22

213:20 214:2,3,5

214:8,10,12,15,17

214:18,20,21

215:1,4,5 217:6

218:9 219:9,15

220:1,5,9,14,15

221:5,13,15,20

222:6,15 223:5

224:20 225:5

226:13,19 229:5,7

229:9,13,16 231:5

231:7 232:11,14

232:19 233:4,9,11

233:18,20,22

234:6,11,20,22

235:1,4,16,18

237:9 240:5,15

241:1,7,10,12,13

241:14,16,19,20

241:22 242:14

243:13,20,22

244:3,16,20

245:19 246:5

247:18,20 248:8

248:10,16 250:1,3

250:5,10 252:4,5

252:12,20 253:9

253:11,13,15

254:4 256:5,6,8

256:13,21 258:14

259:10 260:7,16

260:19,21 261:4,6

261:7,13,16

262:14 268:3

269:14,20 274:2,6

274:9,11 276:20

276:21 278:7,10

278:11,14,16,19

279:3 281:1,9,13

281:17 282:1,3,9

283:5,8 284:5

286:17 287:6,9,14

287:17,22 288:6,8

288:10,16,22

289:3,7,11,13,18

289:20,22 290:6

290:14 291:9,15

291:18 292:1,10

292:13,21 293:10

293:20,22 294:2

294:15,22 295:6

298:22 299:4,13

300:2 301:7,8,10

302:15 305:7,14

305:21 306:1,2,4

306:10,13 308:4,7

309:2,9,12,15,20

310:12 311:5,7,11

311:13,14,18,19

312:1,2,4,5,6,11

312:14 313:6,18

313:21,22 314:5

314:18,19,21

315:8 316:12

317:3,12 318:1,14

318:22 319:11,15

320:3,4,6,12

321:5,13,21

322:14,18 323:7
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338:21 339:20

340:2,4 341:4,19

342:3,14,15,16,18

342:19 343:4,6,7

343:8,9,10,12,14

344:7,9,15,17,18

344:22 345:2

346:18 347:12,14

349:7,13,16,17,18

350:3,12,19

351:15 352:6

353:21 354:2,7

355:7,13,21 356:4

356:16,18 357:1,3

357:6,11,13,18,20

359:5 363:2,6

364:4,19 365:10

365:13,15,17,18

365:20 366:8,10

366:11,13,15,19

366:20 369:12,15

371:19 372:5,18

372:19,21 373:1,5

373:9 374:4,6,10

375:5,7,16 376:2

376:6,9,12,16

377:1,2,5 378:9

378:15,18 380:14

380:19 381:2,19

381:21,22 382:10

383:18 385:18

386:3,3,11,13,14

386:17,19,20

387:3,7,8,9,10,22

388:5,8,12,16,17

388:21,22 389:15

389:18,20 390:2

390:20 391:4

392:9 394:13,19

395:21 397:13

399:6,15 401:2

402:5,7,8 403:1,3

403:5 404:20

406:11 407:20

408:20,21 409:1,2

410:1,15,18

411:13,15 414:13

414:16,21 415:2,3

415:5,11,15,16,21

415:22 416:6,17

416:18,20 418:14

418:17,22 419:4,7

422:11,15,16,19

422:21,22 423:2,3

423:5,8,14,22

424:1,7,10,11,12

424:13,14,17,22

425:8,9 427:22

429:7,17,19,21,22

430:1,3,5,6

431:18,20,21,22

432:2,3,8,9,14

433:1,3,10 434:3

434:22

draft 10:1,4 11:2

16:21,22 17:3

20:2 21:11,12

28:21 29:5 30:20

31:5 58:4 91:22

111:22 112:18

113:5,6 114:9,17

168:5 254:10

255:7,7 265:13

267:18 271:14

310:15 311:2

351:11 379:7

400:17,17 408:3

418:12 419:10,18

dramatic 56:9

dramatically 137:1

404:13

drastically 19:17

draw 72:7,19 100:2

251:16 285:12

348:16 351:10

drawing 303:22

339:8 394:6 426:7

drawn 136:14

154:6 350:10

353:4

drew 213:9 278:21

drift 170:17

drive 1:12 206:9

253:3,3

driven 59:22 68:21

87:22 115:6 141:5

193:14 252:8,16

260:3 314:3

321:18 369:2

driver 39:14

193:13 201:21

215:7 261:22

376:20

drives 77:9

driving 232:6

dropping 319:13

319:14 320:7

364:9

drove 427:12

drugs 126:1

dry 387:12

due 31:16 108:8

115:5 124:6 278:1

282:9 379:17

406:19,20

duh 423:13,19

duplicating 146:2

duration 101:6

Durham 1:12

dwarfed 238:6

E

E 253:5

earlier 30:9 33:8

39:18 40:11 47:16

56:7 58:7 59:4

71:1 74:7,12

77:16 82:4 108:16

110:20 111:14,22

147:10 152:20

185:19 199:19,19

209:8 216:5 247:5

258:3 260:9 261:3

333:5 335:13

336:16 385:15

404:14 423:15

429:8

early 21:18 330:6

easier 96:7 161:5

250:2,4

easily 82:22 307:12

307:20 417:19

easily-changed

176:9

easy 143:5 271:11

282:21 327:14,15

eat 227:2

ECG 286:20

293:16

eco 27:11

ecological 274:10

ecosystems 301:18

editing 121:11,12

121:20

edits 267:14

educational 90:3

effect 72:14 128:8

128:21 132:12,22

133:3 136:1

138:19 141:20

149:14,15 155:20

156:11 182:8

194:9 202:21

221:3 222:2,11

232:3 252:15

258:4 260:10

318:17 320:8

335:17 370:21

373:13 403:18

407:11 410:7,9

416:9

effective 117:22

147:18 381:5

effectively 115:14

effects 67:1 117:15

119:21 123:8,10

124:6,8,13 147:1

147:6 149:5

155:17 258:9

277:22 278:3

279:13 280:6

281:12 283:3

284:16 285:14

297:7 300:7

301:16,16,17,20

301:21,22 302:1,2

302:3 303:17

305:3 336:1,6

363:17 366:5

367:3,18 368:15

377:17 386:10

387:1 388:13,14

396:5 397:4 399:3

399:21 407:14

413:8,14 414:6

417:4 419:9 421:3

429:12 431:15

effort 16:10 68:13

83:11 237:17

238:14 340:13

eight 30:21 96:6

104:13 105:16

176:5,9,11 229:2

229:4 295:21

429:2

eight-hour 34:3,7,8

34:13,15 35:12,15

39:7 118:9 295:14

297:5,19 298:19

298:21 300:1,15

301:6 306:5

320:10 363:10

368:11 416:15

421:2,7 422:8

either 34:1 40:18

87:10,18 145:10

216:18 295:15

317:18 338:3

351:16 383:7

403:15 414:17

417:7

EKG 282:14

428:12

elaborate 22:19

25:12

element 23:21

223:16

elements 15:10
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elephant 162:14

elevated 62:3 342:7

elevation 71:12

290:3

else's 129:16

elucidating 169:18

email 327:9

embedded 89:19

emerge 152:3

emerging 363:22

emission 165:4

emissions 115:3

146:22 163:20,21

164:4,15,17,19

emphasis 24:17

133:7 135:7 389:3

394:18 398:17

414:14

emphasize 18:16

322:16 354:15

emphasized 28:12

204:5 224:3

354:10

emphasizes 39:9

328:13

emphysema 182:19

empty 433:4

encompass 283:3

encourage 436:11

ended 313:17

314:19 345:4

endogenous 29:22

44:11 49:14 50:7

50:11,18,21 51:2

51:9 52:1,13,18

54:14 55:4,9,18

55:22 57:20 58:1

59:7,9,14 60:2,18

61:2,6,15 62:3,13

62:14 63:2,19

64:1,17,18 65:3

66:1,5 67:4 71:10

72:12,13,16 73:13

73:17 74:16,17

75:5,11,20 76:8

77:3,8,14,21

78:19,22 79:16

84:6,7 85:6,13

86:5 88:7,17 93:4

94:13 125:13,18

125:19 170:1

211:11 213:17

214:6,6 215:14,16

216:10,18 218:19

219:7 227:22

228:5,14 229:17

229:22 230:11,14

230:21 232:21

233:14 234:16

238:1 343:3 371:1

371:6 379:22

382:22 399:11,13

403:17 404:7,9

endogenous-only

49:5 53:9

endpoint 159:15

224:8 278:1

282:12,17 283:13

334:2,8 410:20

endpoints 17:21

28:10 135:8 282:6

282:12 283:4

284:1 301:20

ends 87:12 264:8

end-of 29:19 49:19

50:9 75:10

end-of-hour 29:17

30:1 37:3,5 39:15

39:22 47:19 49:11

50:4,17 51:4

57:22 58:8 59:3

59:21 60:4 71:3,5

74:14 75:18 79:14

101:10 193:13

209:10

energy 142:18

enhance 176:17

enhanced 290:7,9

enlarges 294:12

ensuing 421:11

ensure 176:18

entire 40:4,5 41:22

49:7 52:12 58:14

61:7 64:9 66:8

71:4 97:18 103:12

209:1 225:9

226:22 251:6

401:21

entirely 30:5 61:18

399:18 411:20

entitled 146:20

environment 83:3

96:4 105:22

189:19 196:2

197:18 231:11

environmental 1:1

3:10,12 31:21

172:7 194:19

379:11 394:8

422:6

environments

31:12,14 97:11

102:15 105:21

176:3,17 187:19

188:12 194:8

257:19

EPA 9:21 10:7

11:11 22:7 113:3

113:12 116:1

120:5,22 150:9

163:12 166:6

186:12 236:4

244:19,19 257:6

273:22 337:6

356:5 392:4 424:9

437:15

epi 123:3 280:7

281:19 284:1

286:6 318:15

340:19 348:14

351:8 368:9,21

387:17,20 389:3,6

389:9,10,12 390:5

390:16 391:10,18

392:13,20 393:15

394:6 395:17

398:19 399:16,18

400:5 411:16

413:7 432:5,10

433:16 435:2,12

epidemiologic

129:5,6,11 133:11

134:16 141:19

147:9 148:10

155:19 159:12

161:9 227:7 262:4

281:10 282:5

283:14 293:3

294:2 336:6

340:14 372:8

373:12 386:6,7,21

390:22 396:1,4

397:11 403:15,20

433:8 434:15

epidemiological

156:2 159:15

224:21 225:1,13

279:15 281:2

282:1 285:18

294:4,6 300:11

342:1 351:2

363:14 367:4,6

391:3 393:22

416:5 429:11

430:18

epidemiologically

155:21 221:19

epidemiologist

27:9 274:12

epidemiologists

389:21

epidemiology

14:15 116:16

137:15 138:5,14

138:22 139:20

140:4,14 156:20

333:8,13 335:10

366:6 388:10

395:22 397:6

400:1 428:16

equal 237:15

equally 137:11

321:8 389:21

equals 160:11,12

160:13 329:21

equation 174:1,3

178:10,19 181:19

181:20 195:3

196:12 198:3

199:1,10 384:12

equations 195:2

365:1

equilibrated 232:9

equilibrating 234:4

equilibrium 232:18

234:1

ER 129:9

error 163:22

especially 20:11

145:22 165:15

205:11 333:19

414:2

essentially 32:11

32:14 34:17 36:20

37:2 46:8,15

47:15 49:10 54:3

57:5 59:22 70:15

97:9 106:17

147:13 174:5

195:3

established 9:13

establishing 428:7

establishment

301:14 327:21

estimate 58:13 83:2

84:15 94:13,14

96:9 164:20

172:12 173:6

181:20 198:4

221:9 237:21

238:14,17 239:3

239:11,13 296:10

344:4 390:3,4

estimated 31:20

41:14 48:6 106:20

113:2 114:16

154:19 181:16

187:6 263:1 264:2

295:19 296:17

370:19 405:4

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29:16,16 108:21

109:12 110:8

114:9,10,12 118:8
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163:21 164:17,20

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179:11 190:22

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219:17 238:9

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221:7 227:7 271:8

293:9 330:2 366:3

everybody's 269:10

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18:13 19:13 23:2

23:18 24:15 28:14

132:15,19 138:15

152:15,21 153:3,9

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275:16 276:2,5

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284:10,14 286:7

293:5 297:1

301:19 303:17

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395:10 396:4,22

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exacerbate 406:16

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288:18

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263:5 280:5

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exactly 91:20 124:4

130:4 133:16

167:17 212:17

230:18 250:3

265:19 312:21

318:2 374:1 389:5

examine 179:5

example 29:5 35:9

35:11 40:19 66:3

67:9,21 73:12

81:10 106:6 113:4

113:11,19 125:17

159:1,8 168:14

169:7,10 176:11

178:11 179:13,15

179:17,19 181:17

182:2,7 187:2,9

192:19 213:8

217:2 245:7,14

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259:1 268:18

310:3 331:20,21

341:14 342:3,5,7

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432:12,15 433:5

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106:3

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365:3 371:7

395:18

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exceedances

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332:1 367:8,22

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433:20 434:7,14

exceeded-only-o...

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235:12

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exclusive 68:2

87:14

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excursions 43:15

Excuse 53:4

exercise 132:5

259:4,7 290:9

exhaled 231:1

exhaling 230:4

231:14,18 233:3

exhibit 109:9

exhibited 56:21

exist 85:19 209:11

210:12 294:17

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existing 315:16

325:16 363:20

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expanded 30:16

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280:7 285:18

293:4 294:5,7

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102:18 158:5

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explanation 104:21

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explicit 212:12

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exponential 196:19

exposed 35:1 36:16

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18:6 19:15 21:11

21:13 23:3,12

26:20 27:5 28:9

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105:16 108:20

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236:8 266:10

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extracted 36:11

51:20 93:20,21

extraneous 403:18

extrapolate 64:4

154:20 394:11

extrapolated 121:2

163:15

extrapolation

160:8

extreme 62:7 102:4

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113:17 183:6

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faced 393:19

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facilities 106:1,2

212:20 213:1

facing 410:4

fact 23:21 55:1,14

55:19 57:18 62:4

63:11 66:20 67:5

89:5 100:12 114:1

120:20 134:1

137:16 141:7

148:14,18 153:15

154:22 155:16

156:7,12 159:5,6

161:18 165:2

170:14,15 196:2

198:12 199:4,13

201:3 210:19

219:2 222:7,8

227:5 261:9 267:5

271:7 333:15

344:11 370:4

375:9 384:6

396:16 419:21

factions 360:13

factor 102:14

106:18 107:8

108:3 113:11

164:1 187:22

188:4,12,14 196:3

196:4,14 197:1,4

197:18,21 198:11

198:12 199:22

200:1,19,20

201:10,15

factors 96:9,19

111:15 138:1

145:16 174:16

187:4 195:19,21

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381:18

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136:12,20 137:6

137:19 143:16

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206:18 264:17

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111:7 123:22

183:7 200:3 226:9

235:6 243:11

253:6 257:1

262:15 371:8

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favor 369:17 370:9

370:10 371:13

favorably 81:8

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February 118:20

federal 2:2 3:4 9:8

10:6 11:9 361:12

362:7

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feedback 151:22

205:10 266:8

432:15 433:6

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264:22 265:5

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386:4 389:5

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fewer 48:2,3,7

168:4

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fields 115:11

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71:13 82:14 87:5

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217:12 231:6

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90:13 91:1,11,13

91:14,18 92:6

95:7 99:5 136:22

192:22 239:9

299:2,3,22 300:3

308:18 320:22

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162:2,12 163:2

229:19 232:7

250:19 265:22

270:18 281:6

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341:13 380:7

395:16 399:21

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129:13 293:15

fine 24:13 25:6

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finished 162:8

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first 10:3 12:20

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180:9 205:11

213:14 223:15

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198:20

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291:5,7,10 292:4

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385:17,18

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flower 141:2

focus 86:14,16

157:12 182:10

217:17 276:7

277:17 295:1

297:9 314:10

322:12 324:4

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360:16 373:16

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128:16 290:15

330:3 344:19

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footnote 328:22

329:11 330:1

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force 77:12

foregoing 151:11

236:11 326:14

foreign 336:11

forget 216:14

227:22 329:9

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213:6

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34:15 35:19 78:12

297:2,20 298:20

299:17 300:20

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307:11,21,22,22

308:1 312:22

313:10,14 314:1

316:19 320:15,18

320:21 321:4

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329:17,18,20

331:8,18,22 332:2

332:6 362:22

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13:15 36:21 48:16

193:8 362:22

formation 302:4

forms 34:12 36:2

299:20 307:4

313:8 353:10

formula 179:14

formulate 184:4

formulation 261:18

forth 380:2 408:15

fortunately 273:11

forum 358:7

forward 18:10 21:1

21:9,19,22 26:14

47:21 87:20 152:5

224:4 269:19

303:13 304:3

315:10 316:8

336:8 405:8

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178:10

found 120:3 146:17

167:15 169:15

176:20 197:7

235:12 302:5

327:13 329:4

345:10 367:9

375:13 420:1

four 32:21 60:14

90:5,21 114:18

136:16 157:1

211:7 212:1 256:1

295:15 328:14

330:1 412:5

423:17 424:19

fourth 117:11

211:14 300:21

305:11 306:11,12

307:9,13 308:16

308:20 309:6

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183:2

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frame 265:20

275:18 363:3

framed 277:2

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7:5 119:1 123:16

139:16 144:21

204:10 210:15

226:10 247:19

248:15 340:1

377:4 378:8

free 119:13 361:18

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frequency 42:2

127:6 131:8,19

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front 28:5 29:14

43:1 48:9 352:2

373:19 376:13

front-row 353:21

fruit 319:8

fruitful 81:2

frustration 85:9

full 51:22 141:2

307:16 402:8

406:4 407:4

427:18 433:5

fully 84:15

function 427:1

functions 48:19

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further 47:4 56:17

111:18 172:6

175:4 177:18

224:17 225:13

280:15 379:14

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110:21 130:1

181:6 377:22

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179:17 181:22

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121:9 185:16

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255:6 260:2 266:8

267:16 268:10

330:16 341:16

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167:7 240:9 252:8

266:2 270:8

generate 35:20

36:10 58:12 78:3

78:10 96:2 171:10

364:22 414:2,4

generated 35:6

58:22 83:13

115:13 207:10

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generates 139:12

generating 83:2

210:3

generic 211:1

genuine 387:19

geographic 31:16

geometric 49:18

105:17 108:4

187:10,16 189:19

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getting 88:19 129:7

159:11 162:1

163:8 201:1

208:22 254:19

273:15 274:3

276:9 344:16

435:9

give 15:21 20:20

21:1,2 22:7 26:1

45:6 47:2 72:12

81:15 92:17

105:18 112:12

146:4 156:19

190:17 205:20

264:6 266:21

267:9 271:19

295:1 296:15

299:15 335:21

338:6 345:20

348:1 350:17

351:7 352:21

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given 10:10 29:20

35:12 36:15,17

37:8,11,12,18,18

37:22 38:7 39:3

39:20 40:16 47:20

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58:10 59:10 83:11

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110:7 111:2

114:12 116:17

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163:16 202:2

205:10 236:4

251:20 258:1

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135:3 138:15

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go 9:3,5 16:13 21:4

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76:2,8 79:7 81:22

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101:17 106:13

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172:5 179:2 201:4

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222:10 228:12

237:4 242:11

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267:15 270:19

274:14 275:7,9

276:17 281:6

286:2 293:18

299:17 305:9

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391:14,15 395:4

399:13 400:15

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408:15 412:12

414:16 417:6

421:11 425:11

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goes 61:14 157:5

178:2 235:18

255:2 270:16

303:16 316:6

352:2 393:1 417:1

going 17:2,9 26:17

26:22 28:18 35:7

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57:13 65:11 66:6

74:4 77:2,4,13

79:16,19 81:21

87:1 95:17 101:5

102:12,16 119:4

123:16 128:17

129:18 132:4,7,9

138:16 142:14,16

144:15 146:7,8

150:9 151:19

158:10,22 165:16

173:15 180:6,7

193:6,14 209:1

211:9 217:20

218:19 219:1,5

221:6 224:5

225:21 227:3,15

230:12,21 234:1

242:7 245:12

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264:15,16 265:9

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268:4 271:20

272:16 274:14

287:7,15,17

298:22 301:8

306:12 313:9,15

313:17 316:14

320:16 325:17,18

327:11,20 333:4

335:2,16 340:17

345:6 351:18,20

351:21 352:1,4

359:3 361:3 368:8

371:8 389:6

391:20 392:17

397:22 398:19,19

398:20 399:15

403:16 406:12

411:15 413:5

414:3 416:4 429:8

gold 209:12

good 21:7 25:14

81:10,17 84:5

90:19 94:18 95:14

129:1 138:15

139:13 151:18

165:4,19,22 166:3

166:18 175:21

177:8,11 185:12

189:7 198:17

199:20 203:7

204:8 210:19

254:13 255:11,18

256:10 309:21

324:15 325:3

327:18,19 340:7

364:14,16 371:4

391:19,20 400:7

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233:5

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28:19,20 38:16

39:1,12 41:11,20

42:16,19 45:10,18

45:22 47:3 51:7

51:10,15,18 52:11

53:5,8,13,19 54:7

54:12,19 55:12

56:14,16 57:3

60:19 62:10,14,22

64:14 65:5,17

66:8,11 67:22

68:18 69:6,10,13

69:18 70:22 71:16

71:22 72:10,20

73:16,21 74:2,5

74:11,19 75:3,8

75:15,21 76:5,10

76:13,22 77:6,15

77:22 78:10 79:4

79:10,13,17 80:9

80:17,19,22 81:3

82:7,12,17 83:5

84:4,14,20 85:5

89:6,10 91:3,5,17

93:17 94:3,7,10

95:18 99:14,18,21

100:15,20 101:4

102:9 103:7 104:1

104:7 106:12

107:3,17 108:1,15
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180:8 183:5,17

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70:15 71:8 78:3,9

78:18,20 83:10

91:19 93:4,11,20

96:1 102:15 104:8

110:3 115:19,20

117:12 154:19

159:20,21 160:13

160:16,16 169:14

170:17 178:4,21

179:9,22 180:6,9

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181:20 182:22

183:7,16,20 184:8

186:1 189:2,9

196:16 198:3,7

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33:2 41:16 87:7

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modeling 30:12

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171:1 172:8

176:11 194:6

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178:15 180:11

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230:17 231:10,13

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232:2,6 233:14

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321:8 341:10

349:22 377:20

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407:15 413:20

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months 127:5

mood 418:14

morbidity 136:2

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morning 14:4

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265:21 268:18

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movement 371:16

moves 224:4

moving 21:21

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mufflers 102:6

multiple 29:18

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multiplying 191:6

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Murphy 3:15 4:4

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26:18,21 27:3

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86:9 91:9 104:16

152:8 156:1 157:2

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217:6 219:9 220:1

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244:3,20 246:5

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281:17 282:1

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myocardial 128:22

130:6 286:18

290:17 293:14,14

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myocardium 287:4

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N

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NAAQS 1:4 9:18

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name 266:2 326:21

narrow 19:16 20:2

20:21 23:4,13

65:12 75:14 77:13

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narrowed 347:10

narrower 159:22

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narrowly-cast

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nationally 245:10

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near 165:17,22

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190:15 195:16

200:8 255:16

312:17 314:7,9,13

314:15 317:21

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nearby 188:17

198:20

nearing 95:14

105:13

near-road 260:11

316:19 317:6

near-roadside

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near-roadway

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need 25:15 63:21

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171:19 217:11

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334:20 339:13

373:19 375:12

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non-linear 217:9

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not-to-be-exceeded

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November 116:14

Nowadays 256:16

NOx 316:3 332:3

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NO2 242:22 312:17

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248:3 250:12,17

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numerous 27:15

O

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OAR's 9:21

objections 272:21

objective 324:13

observation 247:21

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observations

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observed 121:3

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obsolete 180:4

obtained 253:6

obvious 425:10,21

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obviously 37:14

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occasionally

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occur 95:22 100:5

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occurred 432:18

occurrences 39:19

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occurring 98:13

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October 21:20

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offering 16:5

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of-hour 79:16

oh 54:12,12 75:8

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177:11 178:21

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331:13 349:17

372:5,21 386:17

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71:17 75:21 77:6

79:12 81:9 83:14

84:17 91:16 92:21

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112:11 119:17

136:9 145:1 146:6

150:13,18 151:7

160:2,15 162:19

166:8 170:10

175:1,2,17,21

177:15,20 178:1

184:11 185:9

190:1 192:8,11

195:5 201:10

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204:21 214:10

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229:10 237:3,9

240:4 241:20

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256:10 258:14

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outcomes 279:17

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outdoors 89:14

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outliers 60:14

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outlying 228:8

output 34:22 39:21

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outrageously 239:5

outside 61:12,20

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outsider 391:5

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overarching 277:5

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overemphasize

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overestimate 109:3

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overestimating

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overexposed 135:4

overhaul 180:6,7

overlap 168:10

404:6

overlapped 168:18

overlapping 168:16

overlaps 81:12

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overlay 297:3

overly-narrowly-...

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override 342:12

overview 32:6

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oxygen 143:19

157:21 183:3

278:5 280:13,15

281:14 285:3

286:15 288:1,3

289:16 291:11

335:13 384:19

395:13 406:15

407:10

ozone 210:1 302:4

310:3,3 420:11

o'clock 265:11

415:7

P

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118:2 158:10

161:1 254:22

273:15,17 392:7

399:5 400:17

pace 276:18

packet 91:2

Pagan 6:15 27:6

274:6 276:20,21

278:10,14 279:3

281:1 286:17

288:10 295:6

300:2 373:5

page 76:9 104:22

125:5,22 126:6

171:22 172:2,4

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234:14 262:21

268:9 284:7 328:9

328:12,20,22

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parameter 75:10

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Park 1:12

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part 27:21 61:16

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221:8,10 223:11

224:10 225:10,11

227:3,5,17 228:14

238:18 242:2,9

245:22 246:3

248:1,4 251:10,19

258:11 261:22

272:16 307:2,15

309:5 310:2

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342:22 353:11

367:13 371:7

376:4,11 385:9

390:10 398:16

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405:12 408:19

409:10 410:7,8

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218:22 263:1

309:11 344:1,13

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40:14,19,21 41:13

41:19 42:15 43:5

43:5,11,13,14,16

46:21,22 49:1

50:3,16,18,21

53:2 54:1 57:5,7

57:10 60:10 62:5

72:8 76:8 78:6

86:20 96:2,12

97:4,15,21 99:11

100:9,10 103:8

113:10,11,12,21

114:1,1,2 117:3

126:8,9,15,19

131:22 142:15

155:4 168:18

215:22 216:1,1,2

218:13,14 219:2,3

220:12 239:16

240:17 253:7,8

295:15,17,18,20

296:1,3 298:6,11

298:13 321:17

344:6 364:7,21

365:3,7,8 377:10

377:21 402:20

404:2 408:20

409:1,2,9,9,19,20

percentage 41:15

43:7 48:21 66:14

101:2 103:4 113:9

126:13 169:20

221:8 248:7

297:21 405:10

percentages 42:13

365:6 406:9 408:6

408:10

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62:4 76:7 143:4

298:19 300:21

307:6,7,11 313:16

319:12,18 320:5,8

329:7,21 331:11

331:12,14 332:3,4

421:12 422:4

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percentile-based

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percents 409:13

percent-days 116:7

perception 126:18

359:20

perfect 198:15

perfectly 25:6

361:6 421:16

perform 110:7

251:10,20 259:1

performance 132:5

209:14

performed 52:8

58:10 80:11 93:19

257:20 276:3

351:8 367:21

performing 91:20

110:3 259:21

period 10:15 61:8

259:15 342:6

367:11

periods 367:21

373:7 429:15

persistence 140:17

persistent 132:21

persists 203:22

person 16:7 27:11

45:19,20 53:22

77:10 96:21 252:3

259:20 290:16

321:9 326:21

334:5 391:9

436:14

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189:11 209:22

358:5 389:11

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persons 30:17

36:16,16 37:11,17

37:22 40:14,20,22

41:3 48:3,3,4

49:20 50:3,10,16

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97:9 98:6 104:1

113:9 238:12

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play 279:11 285:11

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152:6 214:16

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148:6 318:22

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77:1 85:21 106:10

117:17 124:20

137:21 156:8

158:19 165:2

189:20 191:3,9

193:7 196:10

211:12 220:21

237:14 239:6

281:18 284:17

287:11 288:16

309:21 311:14

315:8 327:4 330:6

330:10 336:12

337:2 341:20

350:8,11 360:16

367:5 372:6

373:19 382:5

393:16 398:3

399:16 402:15

408:14,16 409:15

410:17 411:5

427:21 429:3

pointed 201:19

370:5 403:8,8

pointing 238:22

392:3 403:10

422:13

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103:1 151:22

167:20

poisonous 321:8

policies 353:6

policy 6:13,19 10:2

10:7 17:1,3,12,15

18:5,9,11,17 19:4

19:17 20:2,6,16

20:19 21:12,17

22:7 23:17 24:22

27:6,12 28:11,12

29:7 35:7 36:3

87:21 116:4 141:2

141:4 145:15

146:1 153:1,5

157:14,20 162:12

223:9 225:16

246:15 247:1,6,15

255:3 271:21

274:7,15 275:2,4

276:4 277:1

278:22 297:4

299:6 301:3

302:22 303:3

304:17 310:19

313:11 327:20

328:13,18 330:9

339:7,12 345:8

346:4,22 347:10

349:9 352:9

359:15 372:14,15

372:22 382:14

383:4,6 386:5

387:2 391:16

392:15 393:8

395:3 405:8,13

406:3,8 410:21

411:6 415:13

420:18,20 421:9

428:3 429:3

430:11 432:17

433:7 435:4

436:13

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polish 175:14

politician 345:10

pollutant 14:11,12

18:7 117:3 148:5

414:10

pollutants 115:15

116:20 147:17

148:6 149:15

209:21 245:2

316:15 423:9,21

pollute 356:9,15

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66:22 85:14 106:7

146:21 147:5

211:13,15 215:21

216:16,17 217:5

227:14,16

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poor 163:8 165:16

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28:9 30:22 31:2

32:8,12,20 33:7

33:11,14 37:7,7

38:6 41:13,15,16

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44:21 45:4,11,12

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88:14,18,19 94:5

97:5,17,18,21

102:3,19 103:13

104:4 110:9

111:16 113:21

126:2 134:2,6,14

135:2 141:7,12

142:15,22 145:11

153:13,15 154:16

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157:5,12,15,17

159:16,22 160:6

161:3,7 182:10,12

182:13 183:2,15

184:4 209:11

211:20,21,22

215:22 219:3

221:10 226:21,21

226:22 237:12

238:6,11 242:8

251:6 252:1,22

259:11 260:3,4

262:9 281:22

297:11,22 298:13

300:13 365:3,7

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112:3 126:8

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148:2 263:7

268:20 275:16

299:4 304:18

329:6 398:7 399:2

415:9 417:15

429:5 435:22

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31:19 32:5 35:4

333:16 373:5

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pressure 336:10

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133:15 182:19

195:14 239:17

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purpose 18:17 19:4

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push 314:13 337:11

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133:10,12 138:17

139:19 144:15

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223:5 240:5

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316:14 321:20

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406:12 407:19

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putting 91:13

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335:9 364:18

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P-R-O-C-E-E-D-...

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37:13,16 38:4,9

38:14,17 39:2,10

39:13 41:2,4

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R

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races 382:3

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313:11,13 318:12

379:9 401:7 402:2

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432:12 433:15

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315:9 333:18

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ran 58:22

random 42:10 67:3

randomly 41:17

42:14 55:2 89:3,5

94:4 258:21

range 18:18,18

19:5,10,18 20:3

20:10,21 23:4,7

23:13,17,20

116:22 147:14

179:16 208:2,21

225:9 240:9

247:15 300:16

301:2 304:17,19

311:21 338:18

347:6,9 352:8,18

352:18 353:2

354:13,21 359:8

359:14 360:19,20

360:21,22 364:20

365:5,21,22 432:4

432:7 435:19,22

436:5,6,6

ranged 187:11

ranges 115:18

ranging 41:6 110:4

365:7

rank 135:19

ranked 108:22

rapid 276:18

rapidly 21:19

26:14

rare 161:20 198:21

rate 42:21 44:1

49:14 55:22 58:2

63:2,19 67:9

75:12 181:19,21

184:17,18 230:14

232:21 234:17

rates 42:3 44:11

63:6,11 65:4

229:22 244:2

249:5,10,11 381:6

ratio 201:11 202:19

239:7

rationale 88:6

145:17 195:10

216:13 304:16

305:12 352:20

353:3,10,12

368:19 425:16

435:21

ratios 200:21 201:9

201:10 202:15,22

ratio-to-ambient

200:17

Rats 15:1

REA 3:21 11:3

28:3,5,17 29:6

35:6 80:8,10,13

87:5 112:18 114:8

116:8 118:18

122:22 124:12

139:9,14 140:12

152:19 153:13

157:12 158:9,16

164:9 168:3

170:13 171:1,6

172:1 174:14

176:4 194:13

199:3,19 223:9

225:16 264:12

270:18 271:13

273:15 275:15,19

276:7 313:12

326:19 336:13

343:9,12,18,19

346:10 377:6

378:22 379:1,3,4

379:7 381:3

382:14,16 383:5,8

384:8,11 405:9,18

405:21 408:3,12

409:12,14 410:19

411:3,5,8 419:10

419:18 421:15

426:16,20 427:7

427:11,16,17

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reach 232:19

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reached 232:17
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reaches 219:3

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read 13:16 23:18

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334:19 340:10

345:18 363:7

366:21 391:7

392:4 396:19

402:1 423:3

reader 377:14

382:19 385:4

386:1 397:8 409:5

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readers 76:1

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readily 372:1

reading 70:21

93:15 121:10,17

146:21 149:13

201:12 391:9

401:21

reads 391:17

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ready 81:9 203:8

378:16 400:21

real 62:17 88:13

174:9,11 194:20

196:8 207:9

208:12 209:19

273:16 328:21

333:16 336:18

344:4 377:8 392:3

402:2 408:5,7

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realistic 87:11

88:12 112:22

113:13 160:5

reality 99:7 249:14

398:18

realize 254:17

realized 345:19

really 12:19 13:4,9

14:7 15:10 22:17

23:10 24:3 25:12

26:11 38:15 39:8

64:8 72:18 81:18

85:21 86:7,14,18

89:16 90:8 93:2

119:17 121:11

122:19 123:4,9

125:2 126:10

127:9 129:21

136:13,16 137:15

137:20 138:17

139:2,7,8,13,19

141:1 142:10

145:17 148:22

160:10 161:14,19

165:19,21 169:18

170:4 176:7 177:4

178:3,12 179:22

185:19 186:3,5

188:1,4 194:8,12

195:6 196:5 200:9

205:4,16 211:17

219:13 220:18,19

223:12 224:6,18

226:16 228:10

230:2,13 237:10

243:20 244:17

248:16 249:12

265:2,6,16 266:1

266:7 268:12

280:12 281:11

291:4 292:14,21

294:5 306:13

308:3,13 309:4

314:1 315:7

318:19 325:8

329:15 334:6,12

340:4 357:22

359:13 372:12

373:16,18 378:9

381:8,9 382:15

387:5 391:17,22

394:17 395:9

398:11 399:4

400:19 404:15

416:8 417:4

424:22 427:7

435:8 436:13

437:9

real-world 86:2

87:11

reason 66:18 81:4

135:11 143:18

155:13 198:2

203:18,19 217:8

224:15 250:11

252:12 354:15

370:2 385:7

391:19,19 403:6

428:6

reasonable 19:20

19:20 22:14 29:2

36:6 142:6 159:19

160:8 201:15

202:2 210:3

227:20 228:13

257:10 264:22

reasonably 20:4

28:13 210:5,10

246:17 347:1

391:8

reasons 116:15

123:6,7 224:12

225:15 397:19

413:17

recall 122:3 147:9

276:15 350:4

354:8 374:16

recapitulate 421:14

recapitulation

428:15

receive 353:8

received 12:17

recently-available

392:12

recess 418:9

recoding 104:7

recognize 63:21

72:21 110:1,6

157:14 202:4

284:17,18 347:20

394:3 396:2,12,21

427:17 430:8

recognized 239:20

339:6 413:9

recognizing 55:13

402:13 432:10,11

recollection 135:21

272:10

recommend 341:2

352:3 365:22,22

413:5

recommendation

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369:19

recommendations

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351:16

recommended

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recommends 363:7

reconvene 151:14

236:8,10 237:5

326:13 437:21

record 118:15

151:12,13 236:12

236:13 326:15,16

425:13

records 10:11

recreational 126:1

recuse 359:21

redid 217:2

reduce 195:4 226:3

250:14 335:13

reduced 113:10

127:1,2 176:13

196:3,8 255:9

285:2 286:19,20

288:1,2 289:15

296:7 384:6,15

395:13

reduces 209:5

reducing 291:5

reduction 113:2

reemphasizing

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refer 33:12 38:20

89:7 124:6 293:10

reference 228:22

293:12 374:16

401:21

references 270:7

270:10 328:6

referred 33:13

213:20 241:3

374:17 401:16

referring 73:1

94:22 171:8

190:20 246:6

409:15 416:13

refers 185:16 408:4

reflect 64:18 167:8

177:1 186:10

235:15 333:11

379:1,6 382:15

393:8 395:3

reflected 197:17

204:6 255:11

277:9 379:5

reflective 188:1

reflector 423:8

reflects 148:5

378:22 379:3

382:14

regard 63:1 152:12

153:6 244:14

277:3,6,14 284:10

300:1 302:18,20

303:5,10 304:10

304:11,21 341:21

341:22 345:8

353:7 389:2 396:4

397:2 400:10

422:14 426:5,6,7

435:1

regarding 181:3

257:20 296:16

300:6 303:22

305:1 355:3 428:8

433:12

regardless 179:8

323:15

regards 296:5,21

300:3,14 301:11

region 243:16

regional 302:13
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regression 61:12

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regular 45:20

regulation 422:5

regulations 324:22

regulatory 15:2

reiterate 228:3

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relate 36:12 249:14

359:3 424:22

related 36:1 56:1

101:5 138:18

145:13 146:21

223:3 230:16

256:2 258:5

286:13,15 298:3

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359:16 394:22

398:12 409:3

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relates 242:21

284:15 297:2

378:19 419:11

relating 154:5

292:5 433:13

relation 89:3 185:5

relationship 55:4

58:9 59:20 70:16

106:14 108:6

134:13 138:6,13

174:6,7,16,20

175:1 199:5 202:6

202:14 217:9,20

219:10 264:7

283:22 290:16

294:17 320:20

342:8 396:16

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relationships

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154:2 157:8,13

197:6 336:19

390:6

relative 126:13

137:4,4 156:10

287:15 288:2

301:6 372:3,5

384:18 396:11

412:16,20 416:10

417:1,4,12

relatively 115:4

399:20

relaxed 311:6

relevant 17:13

98:13 145:7

294:18 356:6

373:14 434:16

reliable 207:1

reliance 123:21

reluctance 324:20

rely 117:17

relying 117:8

remain 286:4,5

296:8

remaining 279:21

371:13

remains 319:22

remarkably 116:19

remarks 3:2,5,7

11:22 12:3 118:14

remember 14:3

17:11 47:13 56:7

62:8 135:18 200:7

200:9,12 269:15

269:20,21 289:7

313:16 352:12

remind 16:14 27:1

185:18 270:21

274:3

reminder 275:1

325:15

reminding 274:17

Remodeling 14:22

rename 214:15

repair 106:3,5,6,9

repeat 254:14

293:13 397:17

434:4

repeated 132:12

293:18 398:1

repeatedly 146:7

399:6

reperformed 65:21

replace 190:18

replaced 190:22

report 116:21

146:18 149:1,3,13

192:17,19 213:18

270:15,20 272:2

reported 116:18

117:19 191:12,17

191:20,22 192:2

202:5 264:9

398:14 415:6

reporting 263:14

reports 11:2

117:20 136:11

represent 110:10

111:16 136:15

165:22 184:6

195:22 242:16

248:11,14 298:8,9

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representation

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110:15 111:5

165:17 194:17

243:12 260:20

representative 64:3

64:9 73:6 186:5

251:7 252:2 362:2

362:6

representativeness

111:10

representatives

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represented 176:12

267:11,12

representing 46:12

198:18 255:15

362:3

represents 49:13

50:9 272:11

reproduce 251:19

reproducible

161:21 162:1

request 403:22

requested 270:7

requests 418:6

require 104:4

164:19 180:21

291:10 324:22

required 173:10

174:3

requirements 10:5

10:22

requires 10:10

58:17 291:11

rerun 404:22

research 1:12

360:4 375:3

researchers 180:20

residential 197:11

197:12

resides 45:14

resolve 272:14

resolved 235:21

272:13

Resource 3:19

112:17

resources 58:19

respect 36:14 37:10

37:15 68:1 122:20

243:6,7 263:17

respond 180:8

345:17

responded 413:4

responding 67:13

response 4:5 26:3

26:10 28:21 30:10

91:21 111:21

122:11,12 138:8

141:9,15 153:16

164:13 166:7

177:17 186:13

218:5 219:19

222:7,10 223:1,2

249:6 264:13

282:13 331:5

341:16 378:13

387:4 392:7

400:13 402:17

418:8 427:1

432:15

responses 124:22

153:18 270:12

296:12 400:18

418:6

responsibility

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responsive 205:10

205:15

rest 134:3,22

153:11 244:14

248:9,12,14 256:2

290:16 381:7

407:4

restrict 94:7

restrictive 310:20

310:21,22 369:18

370:9

result 31:18 49:13

56:2 115:8 147:13

157:4 199:15

200:16 290:18

296:1 391:3

resulted 255:14

results 19:15 28:7

29:6,9 35:21

36:11,22 38:3,4

39:18 47:17 48:12

48:13 52:16,22

85:2 91:20 113:20

123:3 126:8

190:17 242:18,18

244:13 245:9

247:7 248:3

255:10 376:20

377:10 398:13

405:17 419:18

426:16,19

resume 151:9

retain 320:17 421:7

retained 191:11

356:8

retaining 301:3

350:6,16 363:9

return 108:12

146:8 151:1

235:10 326:8

371:18 374:1

revamped 324:3,6

reverse 231:19

review 1:4 9:9,19

9:21,22 10:1,2,4
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17:6 21:8,10

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152:16,18 158:3

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275:6 277:22

279:14 284:11,13

285:16 293:3

294:4 302:17

303:2,18 313:7

315:18 318:4

323:17 324:4

327:20 333:12

350:21 359:4

401:4,13

reviewed 16:19

114:14 163:20

286:5 294:8

360:17

reviewers 215:9

reviewing 16:5,21

23:2 430:8

reviews 11:3 27:15

209:8 279:21

304:2 328:1

revise 270:3 327:7

revised 270:5

revising 300:19

301:4 363:9

revision 363:19

422:1

revisit 95:5

revoking 301:4

re-ask 92:19

re-zero 170:16

rhythms 15:14

rid 173:11 230:6,10

230:21 232:17

233:5 234:2

right 20:12,21 24:7

39:12,12 44:4

45:10 51:15 54:19

56:14 57:2,12

60:19 62:10,15,22

65:5,17 66:8,9

68:18 69:6,18

71:19,22 72:10,20

73:16,21 74:2,5

74:11,11 75:15

76:5,13,20,22

77:5,6 79:4,18,19

79:20 82:12 83:17

84:14 86:9,17

87:1 88:2,3,5 89:6

89:9,13,14 91:3

91:17 94:2,6,6,9,9

94:16 95:18 99:14

99:18,21 100:13

100:15,15 102:4

103:5,6,7 106:12

107:10 108:15

119:9 124:5 129:2

130:15,18 132:9

132:18 141:3

143:14 144:16

149:9 156:13

161:21 170:9

174:13 183:5,17

183:18 191:2

193:6 198:13

201:17 203:5,20

209:3 214:3,20

220:8,10,13,14

221:14,15 222:16

225:17,19 234:9

235:4 237:6

240:22 241:10,12

241:13,16 242:14

244:20 246:5

252:4,20 253:21

259:12,18 261:13

264:10 283:7

287:13,16 293:12

301:10 302:11

305:14 306:4,13

308:6 309:18

311:4,5 314:18,21

315:8 317:12

318:14 320:11,19

321:21 332:17

333:2 337:8,19

338:21 343:8,10

343:14 344:9,14

354:1 355:9,12

357:1,6,10 363:8

365:17 366:8

369:8 373:4 374:6

376:5 377:1

378:14 384:21

388:7,11 391:17

402:9 403:4 410:1

410:18 412:22

415:11 416:1,10

416:10 417:7

419:4 423:14

424:10,12 429:7

431:21 432:2,8

433:3,8 434:19,22

rigid 407:5,9

428:12

risk 3:14 9:22

16:21 17:14,17,20

18:13 19:15 21:11

21:13 23:2,12

26:20 27:5 113:2

113:18 114:6,9,10

114:12 116:12

119:21 123:9

126:2,3 134:2

135:2 137:4,5

139:10 140:5

141:7,12 142:2,15

142:22 145:8

146:2 148:3

150:10 154:16,20

154:21,22 155:3

156:10 157:16

207:4 224:19

227:4,7 237:12

238:7,11 239:3

242:3 245:4,5

246:1,3 248:22

262:10 277:8,10

295:7 297:1,22

337:2,7,9,10,18

337:21 346:11

359:7 365:2

370:18 373:15

376:4 396:11

405:11 412:16,20

414:11 416:10

417:1,5,12 419:9

428:19

risks 18:6 140:1

risk-based 295:8

296:5

Ritz 1:22 122:15,17

124:4 133:16

144:1,3,9 145:19

150:1,6,12 185:9

185:11,15 186:9

187:20 190:12,14

191:2 192:6,7,10

193:4 194:15

Ritz's 133:13

158:19 203:18

road 71:19 102:10

321:12 379:15

roads 114:20 314:7

314:9,14,15

roadway 165:17,22

195:16 198:1,13

200:9 255:17

312:18 318:16

321:10

roadways 66:22

115:11 197:12

314:11 317:21

Roberts 1:23 4:9

6:8 162:22 165:12

171:22 172:4

174:9 189:14

190:1 192:13

193:20 194:1

199:14 201:7

203:5,20 247:20

248:10 250:1

254:3,4 260:16,21

261:6,13 312:11

312:14 313:18,22

314:18,21 316:12

317:12 318:14

321:13,21 322:14

322:18 324:15

325:1,10 356:4,16

357:1,6,11,13,18

robust 159:13

178:18 399:20

robustness 401:6

role 15:6 18:8 23:6

25:4 275:2 279:11

285:12 301:5

room 25:10 162:14

root 291:14

roots 291:20

roughly 76:4 216:2

238:9

round 15:4

rounding 34:4,10

305:17

rule 21:20

rulemaking 276:15

303:3

run 29:8 299:15

335:9

running 107:1,11

107:19,20 212:17

runs 52:15 254:16

Russ 105:5,6,10

165:14

Russell 1:19 4:8

150:14 151:10,15

162:16,17

S

SAB 3:6 11:10,20

safer 186:10

safety 297:10

300:12 327:22

410:13,14

sakes 364:1

saliently 370:18

Salon 1:11

sample 94:8 213:8

251:13

sampled 94:4

sand 65:10 100:3

sat 374:14

satisfied 135:9

saves 125:2

saw 33:22 40:10

52:20 60:6 115:19

146:18 218:5,6

299:4 369:2

418:19
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saying 22:16 65:7

65:10 67:16 74:6

86:19,22 90:12

124:1 130:4,11

131:16 139:11

140:9 143:12

144:10 147:21

156:18 158:11

159:21 160:1,11

160:15 165:7

188:5 192:4

199:15 212:14

215:13 218:12

227:6 235:14

244:13 266:18,18

268:4,9 283:19

312:7,8,9 317:13

329:13 339:15

349:10 356:14

359:12 361:4

368:7 369:22

373:2 376:16

384:13 396:12,18

404:22 406:3

414:22 421:6

429:11 433:9

434:19

says 16:9 115:20

136:1 161:2 171:1

195:8 200:21

213:21 225:22

229:1 248:3 261:5

261:18 292:16

329:12 343:20

344:11 351:22

359:6 361:2,3

394:4 401:19

412:10 436:15

scale 164:7 417:8

scenario 37:13

110:22 143:2

160:2 212:22

262:22 263:3

295:13 349:12

359:7

scenarios 31:5

33:15 35:22 36:10

37:1,16 38:5,9

39:2 47:17 68:11

76:20 92:3 104:11

104:14,14 105:16

112:1 142:21

186:6 212:11

299:14 342:22

schedule 17:4,5

21:5 26:9 254:17

326:6

scheduled 10:16

11:6 119:6,8

schools 106:1

173:21

science 2:1 12:8

16:19 17:11,13

19:14 20:15 23:12

24:18,22,22 25:3

25:4 247:1,14

275:4,17 338:15

339:11,16 348:19

353:2,13 357:18

358:9,18 359:6,19

360:1,8,17,17,18

362:17 426:1

scientific 1:3 9:8,14

9:17 18:12 24:14

28:2 246:17 277:8

358:7,10,21,22

360:3,21 361:20

362:2,8 369:17

370:13 371:12

413:18 434:8,20

scientifically

246:21 370:3

425:16,18

scientifically-vali...

359:9

scientists 23:1

338:17 377:16

scope 330:9

scratching 206:14

207:5

screen 333:3

screening 358:19

se 117:22 314:17

316:9 347:14

seat 353:22

seated 358:13

seats 9:4

second 10:1 16:21

19:8 21:11 29:4

50:8 112:18 113:5

114:9,17 116:21

134:20 136:7

168:5,19 194:14

211:11 215:10

228:2 255:7

298:21 305:18

306:2,5 308:15

329:8 357:21

368:11 419:10,16

secondary 27:11

144:5 274:10,20

301:9,12,14

304:22 355:5,6,8

seconds 126:14,16

130:16 377:11

second-highest

34:6 35:13 297:19

section 76:2,9

167:13 169:1

293:6,7 294:16

320:14 336:3

378:20 383:21

408:3 419:21

420:2,22 422:21

sections 167:14,16

177:2 421:12

sedentary 256:17

257:14

see 14:6,19 21:5

32:10,13 35:19

36:2 37:2,9 38:5

41:2 47:22 49:16

50:3 52:17 56:21

57:10,13 59:5,18

60:1,8 70:5 79:6

79:11 81:5 83:15

87:10,14 95:6

98:2,21,22 101:21

102:18,21 108:3

113:7 129:21

137:15 141:20

143:21 149:16

158:5 160:4 162:9

162:11 169:18

176:6 179:7 182:8

183:22 186:14

188:5 189:15,17

195:6,10 202:13

205:21 207:22

213:6 215:3 216:6

219:15 223:8

228:12 234:8

237:9 242:17

243:8 245:15

247:22 254:15

255:5 263:9

266:16 271:3

278:11 282:3,18

282:21 298:10

308:14,18 309:6

311:18 318:18

324:9 335:17

343:15 355:11

371:18 377:6,13

380:4 381:3

383:13 395:18

400:19 412:13

415:16 416:22

417:9 421:21

430:17 437:18

seeing 57:11,15

70:11,14 87:9,16

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sidewalk 197:16

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significance 15:3

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significantly

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simple 178:12

simplistic 142:20

simply 46:21 84:10

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simulated 30:17

32:3,20 33:7 44:7

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simulations 43:22

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sine 290:2

single 29:17 58:14

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sit 351:20 352:2

site 114:18 189:17

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sitting 27:10

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situation 111:2

160:11 165:5

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121:1 280:18

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skewed 55:9 61:21

skewedness 54:5

sleeping 99:11

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36:7 39:17 40:2

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snippy 375:11

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soliciting 352:20

solid 37:19 298:7

solution 198:15

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somebody 198:12

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spin 409:4

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98:20 113:8,20

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118:10 138:14

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152:18 160:2,3

201:4 202:3

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277:4,6 295:22

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430:13,18,19,21

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subjective 334:2,8

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Substituting

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Sub-Charge 170:6

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switching 320:7

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synonymous 52:12

synthesis 17:12

system 203:15

254:20 289:21

396:6

systematic 55:3

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systematically

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S-E-S-S-I-O-N

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T

table 82:3,9 104:12

105:15 181:12

184:16 187:3,21

195:22 199:16

229:6,7 234:8,10

234:13 235:3

248:2 254:10

256:22 260:12

274:5 329:5

370:16 372:18

398:16 414:18

415:22 416:2

tables 36:21 63:4

80:12 85:1 113:5

113:6 116:9 141:5

169:15,16 187:3

299:6 408:16,17

410:2

tabular 36:21

48:16 193:8

218:11 371:10

tabulation 169:22

tail 54:15 55:10

114:15 255:15

313:2 314:3 371:1

taint 355:16,17,20

tainted 355:20

Taiwan 432:20

take 16:18 25:15

26:22 28:1 54:21

59:7 61:9 62:20

64:10 65:1 73:10

95:16 108:11

119:2,11,12,15

142:19 150:14

155:7 170:18

172:11 182:18

199:21 203:6

205:13 211:6

216:19 217:3,12

223:16 242:8

278:18,20 291:3

299:1 310:5

319:18 326:8,12

328:8 343:11

356:1 368:21

378:16 426:19

427:2 428:14

taken 10:20 16:8

96:5 123:14 145:4

148:20 189:2

223:13 226:8

307:19 347:3

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take-home 50:15

talk 41:7 135:11

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184:17 224:6

226:2 259:16

288:2 291:19,20

305:10 330:21

362:11,18 388:1

388:12 389:7

391:20 398:11

405:14 409:18

422:20 432:1,19

talked 136:12,15

136:17 150:1

152:19 153:8

181:19 260:9

310:7 319:1 325:5

335:10 336:16

367:4 397:16

408:10 413:2,11

415:10

talking 68:1 73:3

73:17 74:10

132:20 143:16

149:3 156:10

159:14 172:10

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417:14,22 418:2

426:12,19 427:4,8

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ways 143:5 205:18

219:12 228:10

299:19 308:9

316:6 358:2 393:3

weak 195:8 200:14

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239:10 278:12

302:1

wealth 63:9 390:17

392:20

website 269:18

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week 252:6,7

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weekends 252:9

weeks 25:10 127:5

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22:10,22 24:8

26:5,13 118:20

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weight 44:14 116:5

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296:14 300:9,10

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348:17 351:7

368:8 411:2,10

432:9 435:18

weights 246:20

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welfare 436:22

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well-defended

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well-known 169:7

well-started 369:9

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well-validated

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went 125:6 134:10

137:5,7,7 151:12

151:12 206:19

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237:18 250:8

264:3 269:18

326:15,15 328:5

329:2 354:9

weren't 46:8

137:10 171:12

200:13 217:4

322:1 370:3 434:7

we'l 13:6

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419:5

we're 350:3 361:3

391:20 400:14

we've 20:20 59:12

391:17 393:4

432:6 433:21

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whining 385:22

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whites 169:9

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wintertime 342:7

wish 13:21

women 144:16

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239:20,20

wonder 216:20

wondering 317:13

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128:18 132:10

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writeup 136:18

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year 15:14 21:18

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305:16,19 306:21

306:21 307:8

320:1 377:20

years 14:6 206:16

206:20 225:18

256:16 300:22

307:7 360:20

361:8 390:18

393:1,1 397:14,21

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1.7 62:12

1.75 137:7

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1:30 236:8,10,13

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10 33:1,9 151:1,7

255:22 263:12

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10:30 119:5

10:45 119:7,9

10:50 151:4

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11 355:2 415:6

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11:08 151:13

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12 3:5,7 328:4

12:36 236:12

120 3:23

122 3:24

123 3:25

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15 176:2 326:8

15,000 257:9

15-minute 205:22

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16 3:9 115:19 412:9

163 4:7,8

165 4:10,12

166 4:9

167 4:13,14

17 108:12 146:18

171 4:15

172 4:18,19,20

173 4:20

175 4:22

176 4:14

178 4:17 5:2,4

18 43:1 108:12

250:16 252:22

181 5:6,7

182 5:8

183 5:5

187 5:7

189 5:9

19 126:6 412:9

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19th 11:6 267:4,7

197 5:9

1977 115:10

1989 398:14

1990 249:11

1990s 374:14

1991 398:14

1995 33:20 34:20

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1997 33:21 34:20

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2

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71:6 72:8,15 80:2

80:3 86:20 101:15

101:22 113:10,22

120:2 131:22

151:2 153:8

162:18,20 166:5

166:21 216:1

218:13 227:19

230:4,6 231:12

232:4 233:7,7

332:17,17 333:1

339:21 341:16

344:6 345:3

364:22 377:21

387:4 392:2 409:9

415:8

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2-1 415:22

2-14 412:9

2-27 411:21

2-32 335:1 401:13

2-47 328:20

2-52 329:5

2-6 408:17 409:18

2-7 134:19 408:18

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2-8 125:22 126:6

134:20

2-9 384:22

2.0 41:6,7

2.22 378:20

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2.6 116:9

2.7 116:9

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2:57 326:15

20 12:22 64:2 100:4

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2000 82:7,8,19 84:6

84:12 85:2 86:4

88:22 114:10

172:15 176:2

199:2,11 213:13

213:18 219:17

220:22 257:8

344:12

2006 33:17 34:19

38:17,22 39:1

2009 116:14

2010 1:9 118:20

437:22

2011 21:21

205 5:11,12

207 5:13

210 5:15,17

211 5:14,18,19

214 5:22,23

218 5:24

22 1:9 3:13 49:19

76:8,15 126:16

130:16 328:12

377:11

221 5:25

222 5:21

23 415:7 437:22

238 6:2,4

24 99:17 100:14

24th 118:20

24-hour 412:20

414:22 415:10

243 6:5

25 49:1 54:1 71:6

73:20 117:3

328:12 401:13

255 6:6,8

257 6:9,10,11

26 3:14,15

27 137:3 398:9

417:5

275 6:13,14

278 6:15

279 6:17

28 3:17 401:13

28th 21:14,16,20

296 6:15

3

3 4:13 7:9 98:2,7

102:22 103:2

137:8 162:21

163:7 165:14

166:9,11,15,22

177:14 178:3

185:14 187:10

192:9 215:22

218:14 219:3

230:10,19 232:10

233:2 332:18

344:21 361:5

364:12,14,15

366:9,11,13

369:11 374:3,4

377:3 378:12

402:20 420:9

422:13,19 423:3

3-10 193:1

3-2 192:22

3-3 192:22,22

3-9 193:1

3.1 35:13

3:00 326:9

3:14 326:16

3:15 326:13

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382 7:16,17

384 7:18

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4

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46 264:3,4 328:17

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210:16 215:22

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5-4 398:11 412:13

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5-48 401:20 402:10

5.0 34:16

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50 73:20 251:18

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5200 374:22

55 251:16

59 51:13

6

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187:11 204:12

210:21 213:10,21

223:22 226:12

229:11 354:3

419:6,7 426:10

6b 426:18,19

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6-12 113:5

6-20 76:9

6-22 113:6

6-23 113:6

6-5 262:21

6.2 408:3

6.4 76:2

6.6 113:11

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60 115:21 251:18

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196:19 197:1,4

199:12 200:2

201:10

7

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253:22 355:9

361:5 363:4 415:7

425:2,7,8 426:3

433:11 435:8

7:00 75:17

7:15 272:17 273:6

7:30 272:16 273:6

75 416:14

79 229:19

8

8 6:6 254:2 256:12

333:10 411:21

412:21 413:8

414:14,22 416:13

8,706 76:22

8.0 34:16

8:00 75:17

8:29 9:2

8:30 1:13 119:4

80 295:18

800,000 51:13

9

9 3:2 34:3 46:21

126:16 130:17

231:18 305:15,21

309:7 319:22,22

320:2,10 364:6,12

372:9 377:12

422:7 429:1

9.4 34:4 298:2

305:18 306:6

9:00 273:6

9:30 10:16 273:7

90 100:9,10 168:18

220:12 298:10,13

92 52:6,9 58:11

59:19 94:3 350:5

350:21

95 50:16 321:16

365:8

96 93:6

96-person 78:20

98 313:18

98th 307:5 313:16

313:17 332:2,4

99 296:1 298:19

408:22

99th 34:15 35:14

62:4 143:4 240:17

300:21 307:5,7,11

313:15,17 319:12

319:18 320:5,8

329:7 421:12

422:4

99.8 408:22 409:7

99.9 365:7 408:21

409:7