25   say semi-quantitatively, let me say, of saying, yes, we

1  .053.

2	DR. CRAPO:    So does that mean that we

3  should be -- I mean the OAQPS should be looking at

4  possible risk assessments that go all the way down to

5  the current standard instead of stopping -- going just

6  to 200 PPB?

7	DR. ROSS:    See, we're not saying that.

8  We're just saying here's what the evidence is and it's

9  not actually required that you quantify risk estimates

10   for everything and so OAQPS is looking at what they can

11   quantify.

12	Again here I'm speaking outside my turf,

13   but there's a difference between what you can actually

14   quantify, what you can get data for and what you want

15   to quantify in risk.

16	There is -- it's certainly possible to

17   look at the evidence qualitatively as the EPA has done

18   in the past and say here's what the epidemiologic study

19   states, here are the ranges of levels shown in those

20   studies and use that to draw inferences about the --

21   whether the standard is requisite for protecting public

22   health and...

23	DR. CRAPO:    Okay, so...

24	DR. ROSS:    ...what potential levels

25   might be considered.

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1  believe there are associations and here are the range

2  of levels in those studies in which effects are found

3  knowing that there's no dividing point where there's --

4  there's never a point in an epidemiologic study where

5  effects begin and end.

6	It's a -- it's risk, sort of slope of

7  effects per part per billion, but we can describe the

8  range of those and that's the intent of that Appendix

9  Table 5A to say here are the levels of the

10   epidemiologic studies and then we had some specific

11   ranges listed in the bullet points in Chapter 5, so

12   that's intended to inform the policy decision.

13	DR. CRAPO:    Didn't I hear you say that

14   you found that some of the epidemiological data

15   supported effects where no -- none of the population

16   had exposures exceeding the current annual standard?

17	DR. ROSS:    Right.

18	DR. CRAPO:    Does that mean there were no

19   hourly excursions above the annual standard?

20	DR. ROSS:    Well, the annual standard is

21   -- is...

22	DR. CRAPO:    .053.

23	DR. ROSS:    ...53, so then what we did is

24   look at mean levels in the studies and you can -- but

25   you can even say 24-hour levels sometimes were below

1	DR. CRAPO:    So let me focus primarily on

2  the ISA on my last set of questions.  As I read the

3  ISA, its most potent argument that I -- that came out

4  to me really for there being some risk to the

5  population of adverse health effects from nitric oxides

6  dealt with the human clinical experimental data, not

7  the epidemiologic data.

8	It seemed like the epidemiologic data

9  was dismissed and that the focus was on the asthma

10   patients with -- and is that the way -- I'm questioning

11   whether the ISA should be written with that focus given

12   the kind of discussion we're having.

13	DR. ROSS:    That wasn't the focus that we

14   believed we -- I mean a lot of the emphasis here was on

15   the epidemiologic data and the conclusions draw heavily

16   from the epidemiologic data.

17	We present all of the evidence and then

18   -- but then we try to integrate and some have commented

19   we didn't do that as well as possible, so we'll try to

20   improve on that.

21	We'll try to integrate from

22   epidemiologic, clinical, and toxicological findings to

23   say what do we know about respiratory effects of NO2 or

24   the other effects?

25	DR. HENDERSON:    I think you do need to

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1  improve that because I got the impression that James

2  did.  I mean not that you threw out the epi data, but

3  that you couldn't use it in the quantitative fashion

4  and you're saying you're using it in a qualitative

5  fashion.  Is that what you're saying?

6	DR. ROSS:    We actually are trying not to

7  say which way you could use it or not, but we're just

8  trying to draw conclusions about what we think the

9  evidence says and I think we say quite -- I mean we

10   certainly meant to say quite strongly that we believe

11   the epidemiologic evidence is supportive of a likely

12   causal association between respiratory effects and NO2

13   exposure, especially short term...

14	DR. HENDERSON:    Okay.

15	DR. ROSS:    ...NO2 exposure.

16	DR. HENDERSON:    That's the short term,

17   okay.

18	DR. ROSS:    Yes.

19	DR. HENDERSON:   I'll accept that.  Dale?

20	DR. HATTIS:    Yes, just following right

21   along on that, this discussion, if you believe the

22   epidemiological evidence indicates the effects of NO2

23   more or less in the range of ambient level of

24   distributions, okay?

25	You still have to ask -- answer, I

1  you know, that it's either the high level excursions

2  that matter or it's the long term average that matters

3  or something in between.

4	And unfortunately, the epidemiological

5  evidence hasn't been analyzed to -- as far as I can

6  tell to shed light on that question because you could

7  have analyzed the epidemiological evidence in such a

8  way that you could have made your dosemetric the

9  incidence of particular high exposures rather than the

10   long term average.

11	DR. HENDERSON:    Okay, are there -- who

12   else is...

13	DR. HATTIS:    He may want to respond

14   because I just made a nasty comment about the

15   epidemiological analysis.

16	DR. AVOL:    If you had health outcomes on

17   the same time line as you had as the excursions.

18	DR. HATTIS:    Well, you could have long

19   term health outcomes that are attributable to

20   occasional excursions or you could have long term

21   health outcomes that are attributable to a long term

22   average concentration.  There's no necessary

23   relationship between the time scale for the measurement

24   of the outcomes.

25	DR. AVOL:    Parenthetically, if, in fact,

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1  think, Dr. Crapo's question.

2	Are there effects at ambient levels

3  because there are these occasional excursions to a very

4  high level or is it because there is, in fact, a long

5  term -- a long acting cumulative impairment of defenses

6  against respiratory infections that causes these

7  impairments to the growth of lung function in children

8  or things of that sort?

9	And if you think that you can't answer

10   that, then maybe the advice you have to give is -- to

11   the OAQPS people and to the public general is that

12   maybe it's safer to do risk assessments on the basis of

13   -- on both kind of bases, either long term average

14   levels or on the incidence of particular excursions to

15   very high levels because we don't know what the causal

16   factor really that's important is, okay?

17	See they -- the OAQPS people, in their

18   preliminary document that we're going to review in a

19   little while, have made the inference that, if the

20   effects -- epidemiological findings are right, then

21   they're due to high excursions.

22	Well, if you don't think that you are

23   confident of that, then it seems to me you should be

24   advising them that they should do it more than the way

25   they're doing it because it could be right that it's --

1  you're following along the line of the excursions as

2  being the important trigger in terms of either short or

3  long term health effects, that identifies a potential

4  public health population of exposure, which gets back

5  to the people alongside roadways and proximity and

6  identifies another group in the area of identifying

7  significant populations exposed.

8	SPEAKER:    Right, the susceptible

9  populations.

10	SPEAKER:    Yes.

11	SPEAKER:    Yes, exactly.

12	DR. CRAPO:    I would like to add one

13   thing.

14	DR. HENDERSON:    Sure, James.

15	DR. CRAPO:    It's not only just a couple

16   of us like Regine and I that interpreted the ISA as

17   saying that it focused on human clinical studies and

18   plus, if you look at the -- at the risk assessment

19   document on Page 12, middle paragraph, it says exactly

20   what I've been saying, that it cites the ISA as their

21   source, so I mean OAQPS interpreted it the same way I

22   did.

23	DR. HENDERSON:    There you go.

24	DR. CRAPO:    No, I think -- I think that

25   the -- I think that the ISA does, in this tenor, go

208

1  this direction and I'm really challenging it to change

2  it to be more critical of the -- of the human clinical

3  studies and the asthmatic responses and show the

4  weaknesses of that as well as the strengths much more

5  clearly and then more appropriately emphasize the

6  epidemiology because otherwise we don't have a

7  scientific basis for going onto the risk assessment.

8	DR. ROSS:    Well, clearly we can work to

9  clarify that, but all I can say is the bulk of Chapter

10   5 is really discussing epidemiologic evidence and

11   epidemiologic findings with support from clinical and

12   toxicological studies if you walk through it line by

13   line.

14	DR. CRAPO:    But part of the problem is,

15   when you did discuss the other clinical studies, you

16   didn't discuss the weakness or the weaknesses are

17   there, but they're hidden in small phrases behind whole

18   paragraphs on the positive and without any discussion

19   of the weaknesses of the positive, so when you read

20   that, the casual reader just comes out and says, wow,

21   that's got it.

22	DR. ROSS:    Okay.

23	DR. CRAPO:    And that's what I did,

24   that's what others did, that's what OAQPS did.

25	DR. HENDERSON:    Well, okay.  Thank you,

1  exposure values in the main ISA was in the figure

2  caption.

3	So I think possibly, if you can somehow

4  highlight exposure levels on the epi studies in the

5  same way that you do with the clinical studies and then

6  kind of bring that together rather than just looking at

7  relative risk factors, it might help things.

8	DR. ROSS:    So that's a good point

9  because in the clinical studies you actually have a

10   dose.  You have an actual number that you can

11   attribute.

12	So what we have tended to do is, for

13   example, on respiratory visits and hospital admissions,

14   on Page 5-15 at the top of the page, we report the mean

15   -- the range of mean concentrations from the studies in

16   which these are lower concentrations -- locations with

17   lower concentrations where studies were showing

18   associations range from 15 to 20 parts per billion with

19   maximum concentrations of 28 to 82 parts per billion.

20   That's a 24-hour average.

21	So that's the kind of data we were

22   pulling from epidemiologic studies, which is about the

23   best we can do because again you don't have a point to

24   say the whole population was exposed to a certain

25   level, but this gives you sort of an approximate range

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209

1  James, for finding that.  Maybe that's where I got --

2  you know, I just read that document, too.  I'm going to

3  ask, if the EPA needs more clarification, perhaps you

4  wish we would shut up at this point, but if you...

5	DR. ROSS:    No, no.

6	DR. HENDERSON:    But if you want...

7	DR. ROSS:    If I looked frustrated it's

8  because we were actually trying to say exactly what we

9  meant to say and I don't think we intend to trash the

10   clinical studies.  I mean we believe they are as solid

11   as they are, but we'll just try to make sure we're as

12   clear as possible when we integrate when we come to

13   conclusions about them.

14	DR. HENDERSON:    You might just read it

15   through and see why we got -- if you can figure out how

16   some of us got that impression.  Jim, did you want to

17   say...

18	DR. ULTMAN:    Yes.  One reader's

19   impression.  I thought that the tenor of the chapter,

20   in fact, the whole ISA was that the epidemiological

21   studies were providing the basis of causality, but not

22   the basis of particular exposure levels.

23	In the clinical trials and the

24   toxicological data on animals, the exposure values were

25   much more up front.  I mean the only place you saw

1  of the types of concentrations, points in the

2  distribution of the concentrations for the

3  epidemiologic studies and I'm realizing that clearly we

4  did not bring this out well enough so that it was

5  obvious to the readers.

6	So one of the things we will definitely

7  do is try to bring that kind of information out, but

8  let me ask if this is the kind of information that

9  seems helpful.

10	DR. HATTIS:    Let me try to say that that

11   is helpful by itself, but it's not fully answering the

12   issue that I think that Dr. Crapo rightly brought up,

13   which is, in fact, that if it's the high excursions

14   that matter, what you want is not only the range of the

15   means, the long term averages, but some indication of,

16   you know, if there were cities that were more variable

17   versus less variable with the same mean, you know, it

18   would be nice to have that information.  I don't

19   believe that the epi studies usually give you that.

20	DR. ROSS:    We don't have that

21   information and I don't actually think we concluded

22   that it was necessarily...

23	DR. HATTIS:    Yes.

24	DR. ROSS:    ...the high concentrations

25   that mattered here.

212

1	DR. HATTIS:    Correct.

2	DR. ROSS:    That wasn't one of the

3  conclusions.

4	DR. HATTIS:    If you -- if that -- yes,

5  that wasn't one of your conclusions, so then you need

6  to be -- to communicate the fact that there might be

7  multiple ways of doing an exposure assessment that

8  would be relevant to the prediction of the health

9  outcomes.

10	DR. HENDERSON:    Okay.  Terry, did you

11   want to say something?

12	DR. GORDON:    Just a real quick one.  So

13   a process question.  So you guys did your ISA

14   completely separate from the REA and you don't have to

15   answer this, but were you surprised that they went with

16   the benchmarks of the clinical studies only?

17	DR. ROSS:    No, and actually we do

18   work...

19	DR. GORDON:    Based on James' question

20   about the...

21	DR. ROSS:    We share information.

22	DR. GORDON:    ...tenor.

23	DR. ROSS:    No, we share information like

24   Ila said.  We try to share early drafts of information

25   as soon as we can, as soon as they're close enough to

1  PM, yes.

2	DR. SPEIZER:    And wasn't there an effect

3  that you could quantify?

4	MR. AVOL:    There was an effect, but the

5  effect was...was significant for PM.  It was...the

6  trend was certainly there for NO2, but it was stronger

7  for PM.

8	DR. HENDERSON:    Lianne?

9	DR. SHEPPARD:    Yeah, I wanted to follow

10   up on...on John's comments and Ed's follow-up and...and

11   suggest that if we can't separate the NO2 effects in

12   reality because of the way things occur in the

13   environment and in models, because it's just...because

14   they occur together in the environment, it's really

15   difficult to do, but if we can make the plausible

16   argument that decreasing NO2 will, in fact, decrease

17   the impact on the population health effects, then I

18   would say the public health perspective says that

19   that's enough and that we can argue that needing to

20   separate this is really an artificial thing and

21   that...that it doesn't matter, and we can proceed from

22   a public health perspective to say that...that

23   regulation on an NO2 will have a positive impact on the

24   public health.

25	DR. BALMES:    Lianne, right on.

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213

1  be able to inform them.

2	So we provide information to OAQPS, what

3  information we have, but it's certainly their call in

4  terms of what they feel like they can quantify because

5  what -- there are different ways to inform the policy

6  decision and the risk and exposure assessment is one

7  way, but there are also qualitative means that I'm

8  sure, when you see the policy assessment, they're going

9  to look at various ways of looking at the data.

10	So, no, I'm not going to rat out my

11   OAQPS colleagues that they did it all wrong.

12	DR. HENDERSON:    Okay, Frank?

13	DR. SPEIZER:    Can I ask Ed did your

14   in-and-out migration studies focus at all on NO2?

15	DR. AVOL:    We looked at NO2 as well as

16   BM, yes.

17	DR. SPEIZER:    And wasn't there an effect

18   that you could quantify?

19	DR. AVOL:    There was an effect, but the

20   effect was significant for PM.  It was -- the trend was

21   certainly there for NO2, but it was stronger for PM.

22	DR. HENDERSON:    Okay.  Frank?

23	DR. SPEIZER:    Can I ask, Ed, did your in

24   and out migration studies focus at all on NO2?

25	MR. AVOL:    We looked at NO2 as well as

1	DR. HENDERSON:    Someone said right on.

2  Was that...

3	DR. BALMES:    John Balmes.

4	DR. HENDERSON:    ...John Balmes?

5	DR. BALMES:    I'm complimenting her for

6  her articulate presentation of the point that I was

7  trying to make.

8	DR. HENDERSON:    Thank you, John, and

9  Terry has got his hand up.

10	DR. GORDON:    And...and...and you just

11   said what I was going to say.  In the integration of

12   the whole thing and what James is getting at, I...I

13   agree with you completely, and I was just...a warped

14   sense of thinking about things, but the epi for PM says

15   there's pulmonary effects, and the NO2 says there's

16   pulmonary effects, and what does the clinical and

17   animal tell us?  Well, the clinical and animal and NO2

18   says there's only pulmonary effects, and the epi for

19   NO2 says there's no cardiovascular.

20	So, if we try to separate PM and NO2, I

21   mean, I could make the crazy supposition that PM's not

22   causing any pulmonary effects, because it's actually

23   NO2.  PM's only causing cardiovascular effects which,

24   indeed, the animal and the human tox data says there's

25   very, very little pulmonary effects of PM, but there,

216

1  of course, is cardiovascular effects from the panel

2  studies and the animal studies.

3	So, it's...it's so tightly entwined, I

4  like what you...what you put forth.

5	DR. HENDERSON:    So, we protect public

6  health when we are reducing the NO2.  Good...good

7  point.

8	Did you have your hand up, Ted, or did

9  you just...

10	DR. RUSSELL:    I just...I don't think we

11   really want to go down that route, because there are

12   controls that will act on NO2 that won't act on other

13   combustion byproducts and vice versa.  So, I would hate

14   for us to start dreaming up standards or something that

15   could lead to controlling the wrong pollutant.

16	DR. SHEPPARD:    Well, that's why...that's

17   why my comment said, you know, if we can...if reducing

18   NO2 will, in fact, reduce the effects, because yeah,

19   it's more complicated.  I realize that.

20	DR. HENDERSON:    I think eventually, long

21   after I am dead, the Clean Air Act will be revised to

22   just multi-pollutants, and then we can say, you know,

23   regulate combustion products, for instance, rather than

24   single pollutants, and maybe that would help us with

25   our problems.

1  in.  I, obviously, won't be speaking to each person

2  individually, but they could all look at it and decide

3  if I've captured what they said properly.

4	DR. HENDERSON:    Yeah.  You can...the

5  idea is that those who are developing these paragraphs,

6  you know, you work any way you want to develop it, but

7  I can envision you drafting something and emailing it

8  to others and saying is this...have I got it, you know,

9  about right?  So...

10	DR. CRAWFORD-BROWN:    Yeah, okay.

11	DR. HENDERSON:    I've got a schedule.

12   Did...did Doug get the schedule?

13	DR. NUGENT:    Yes, and...

14	DR. CRAWFORD-BROWN:    I did, a schedule

15   of when various things should be?

16	DR. HENDERSON:    Yeah, yeah.  So, what...

17	DR. CRAWFORD-BROWN:    I got that.

18	DR. HENDERSON:    What we're hoping is in

19   about a week, that Angela and I will get these draft

20   discussions, and we can put together a letter which

21   will be sent out to all panelists on May 16th, and then

22   you'll make comments back by May 23rd, we hope, and

23   then we're going through this...we'll go through a

24   process where, you know, if you have comments on the

25   letter or there are problems, of course, we'll respond

215

1	Right now, I want to sum up where we're

2  going from here.  I hope everyone who was a lead

3  discussant realized that they're responsible for

4  getting together with others to draft a...a paragraph

5  in our letter to the Administrator.  There will be a

6  letter to the Administrator expressing our consensus

7  views on the answers to these charge questions, and so,

8  those responses will be drafted by the...the lead

9  discussant.

10	Doug, do you feel comfortable doing that

11   from overseas?  Are you there, Doug?  He's prob...is

12   anybody on the phone?

13	DR. BALMES:    Yeah, I'm here.

14	DR. HENDERSON:    Okay.  Well, we'll have

15   to get in touch with Doug, but the...the schedule...

16	DR. CRAWFORD-BROWN:    I hit the wrong

17   star-6-pound-6 combination there.

18	DR. HENDERSON:    I...I figured.  I could

19   just see you there punching the buttons.

20	DR. CRAWFORD-BROWN:    What do you mean,

21   you figured?  You figured I had the wrong combination?

22	I...I have listened to what everybody

23   said.  I've been taking notes on this and have looked

24   back through everybody's comments, and so, I feel

25   comfortable writing up a paragraph and...and sending it

1  to that.

2	So, everybody will have a chance for

3  input on the letter.  And then, the revised draft

4  letter will be posted on the web by Angela, and we have

5  a telephone...a teleconference scheduled for June 11th

6  where we will meet a legal requirement for the charter

7  CASAC to approve this letter in a public fashion so

8  that the public can express themselves if they so

9  desire.

10	And, again, as Vanessa said, we

11   didn't...when I first came on as chair, we weren't

12   doing this, but one of...there's a lawyer at EPA who

13   said we must do this, so that's why we're doing it.

14   I'm being really open about why we're doing that.

15   That's a little change.

16	But that's what we hope will happen.  We

17   hope we can stick to the schedule, and work with your

18   colleagues to get those draft paragraphs in.

19	Are there any questions

20   about that?

21	DR. SPEIZER:    Just to confirm, that's

22   just the charter members that will meet.  Right?

23	DR. HENDERSON:    That need to be on the

24   phone call, but I don't want anyone else to feel like

25   they're not in on it, because you will have your chance

217

1  to modify it and...and...and, really, we're meeting a

2  legal requirement when we have the charter phone call.

3	And, Angela, you want to tell us about

4  dinner tonight just so you can...

5	DR. NUGENT:    I set up a reservation at a

6  nearby restaurant for dinner tonight for the

7  chartered...for the members of the committee, and I'll

8  circulate a list for anyone who wants to participate to

9  join in, and there's information on that about when

10   we're...when the van will take us on over to the

11   restaurant.

12	DR. HENDERSON:    So, you...you've got it

13   written down?

14	DR. NUGENT:    Yeah, I'm going to

15   circulate that.

16	DR. HENDERSON:    I think your reservation

17   was for 6:30 tonight?

18	DR. NUGENT:    That's right, with

19   the...the van leaving at 6:15.

20	DR. HENDERSON:    Yeah.  So, just show of

21   hands, how many would like to participate in this

22   dinner?

23	SPEAKER:    Where is it?  Where is this?

24	DR. HENDERSON:    Where is it?

25	DR. NUGENT:    (inaudible).

220

1  presentation on our next document.

2  (WHEREUPON  , a brief recess was taken.)

3	DR. HENDERSON:    So, we have a new cast

4  of characters here.  Okay, we're going to start on our

5  new document now, and we have some people from the Air

6  Office present.  Maybe we could get...may we get you to

7  introduce yourselves so we all know who you are?

8	MR. RICHMOND:    Harvey Richmond, the AMPI

9  Centers Group, OAQPS.

10	DR. JENKINS:    Scott Jenkins, same.

11	DR. GRAHAM:    Stephen Gra...oop.  Hey,

12   I'm speaking into the mike.  Stephen Graham, OAQPS.

13	DR. ROSENBAUM:    Arlene Rosenbaum from

14   ICF International.

15	DR. HENDERSON:    Thank you very much.

16   Okay, and who is going to be the lead person to start

17   out?  We've got copies, I think, of the overview.

18   Everyone should have them.  So, just...

19	DR. JENKINS:    I'm going to talk for the

20   first couple of slides, and then Stephen's going

21   to...going to chime in.

22	DR. HENDERSON:    Okay, proceed.

23	DR. JENKINS:    All right.  Can I have the

24   next slide, please?

25	Okay, I'm going to talk for just as few

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221

1	DR. HENDERSON:    So, you've got a

2  good...it's seafood grill or something?  What is it?

3	DR. NUGENT:    Rockfish Seafood Grill,

4  yeah.

5	DR. HENDERSON:    We've been there before.

6  Okay, so you've got a good group.  Okay.  Well, we're

7  going to take a 15-minute break.

8	DR. ROSS:    Rogene?

9	DR. HENDERSON:    Oops.

10	DR. ROSS:    Before you leave, we were

11   talking about next steps, and I...

12	DR. HENDERSON:    Oh, yes.

13	DR. ROSS:    ...I just want to remind you

14   that our next step is a court-ordered deadline of July

15   11th for the completion of this document, putting it on

16   the web, and we're going to move forward as soon as

17   possible after this meeting and try and make revisions.

18   So, it will be good to get your letter as soon as we

19   can.

20	DR. HENDERSON:    Okay.  Well, you have

21   our schedule, and I think Angela is very good at this.

22   She's pushing us, but we'll try to meet that.  Well, we

23   have that teleconference is definitely set.  So, okay.

24   So, now we know what all the deadlines are, and we can

25   take a 15-minute break and come back at 3:00 for our

1  slides and give a little bit of background, the time

2  line, purpose and scope of documents, and then give a

3  very brief overview of our approach, and then Steve,

4  I'm going to turn it over to Stephen, and he's going to

5  talk about our risk characterization based on the air

6  quality analysis and then on the...based on the

7  exposure analysis.  Next slide.

8	So, the only thing I'm going to point

9  out on this time line slide is the...the bolded...the

10   bolded line there.  This is where we are right now.

11   We're going to be coming back to CASAC with a second

12   draft of this risk and exposure assessment document in

13   August for a meeting that, I believe, has been

14   scheduled for early September or tentatively scheduled

15   for early September, and then we're...we're planning to

16   finalize the document in November.

17	Then we move into the rulemaking process

18   with our Advanced Notice of Proposed Rulemaking in

19   December of '08.  Okay, next slide, please.

20	So, obviously, the purpose of these

21   documents is to convey the approach that we've taken to

22   assessing risks and exposures and to convey the results

23   that we've...we've obtained.  Ultimately, when we get

24   to the point of finalizing the document, it's

25   going...along with the IS...the final ISA, this is

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1  going to inform the rulemaking process.

2	The first draft, which is what we're

3  here to...to discuss today, considers recent levels of

4  NO2 as well as...as NO2 levels that are associated with

5  just meeting the...the current standard, and we can

6  talk a little bit more about why we...why we do that in

7  a minute during the discussions if there...if there are

8  questions.

9	The exposure assessment, we conducted

10   that in a single location, Philadelphia County, and in

11   subsequent drafts of the document, we're also going to

12   address levels that...levels of NO2 that are associated

13   with just meeting alternative or potential alternative

14   standards and also potentially expand the exposure

15   assessment to include additional areas, and that will

16   depend on some of the feedback that we get from the

17   committee here today.

18	Okay, just a very, very brief overview

19   of the approach that we've taken.  The exposure

20   characterization, we...we essentially proceeded in two

21   steps.  First was the air quality analysis.

22	DR. GRAHAM:    I think this is where I

23   chime in.

24	DR. JENKINS:    Oh, actually...

25	DR. GRAHAM:    I'm sorry.

1  the epidemiological literature, at least qualitatively,

2  as part of what we call our evidence-based approach to

3  assessing potential alternative standards.

4	So, for example, when we identify

5  potential alternative standards, one thing we...we can

6  do and one thing we anticipate doing is actually

7  comparing the levels of those potential alternative

8  standards to the levels that have been obs...that are

9  observed in different epidemiological studies and

10   making a qualitative comparison to inform the judgment

11   on...on an eventual decision on a standard.  So, that

12   is...at this point, that's how we envision using the

13   clinical versus the epi literature.

14	Okay, now, with the next slide, I'm

15   going to turn it over and let Stephen go ahead.

16	DR. GRAHAM:    Well, actually, I just want

17   to put both of these components in a better frame, and

18   we could have left the earlier slide up.  The exposure

19   characterization was done in these two components, and

20   they were mainly complementary, not necessarily

21   designed to have one feed into the other.

22	The air quality analysis was really a

23   broad analysis that included all the NO2 monitors

24   across the United States, and the purpose was to serve

25   as a surrogate for personal exposure, and those ambient

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225

1	DR. JENKINS:    No, no, no.  Actually, let

2  me go through this one slide, and then you go on the

3  next slide.

4	DR. GRAHAM:    Okay.

5	DR. JENKINS:    Because it's...this is so

6  general that it's not even worth your breath.

7	The...we proceeded in basically two

8  steps.  The first is the air quality assessment, and we

9  used the ambient levels derived from a combination of

10   monitors and modeling, and then the second was the

11   exposure analysis where we actually used APEX and

12   considered time spent in different micro environments.

13	With the risk characterization, we just

14   spent some time at the end of the last conversation

15   talking about how we characterize risks, and that, you

16   know, we chose potential health benchmarks from the

17   human clinical literature, and you can see them right

18   there, and, basically, we...we compare these benchmarks

19   to our estimates of exposure that were identified, that

20   we derived.

21	Now, I do want to make one comment, one

22   brief comment, on the epidemiological literature, since

23   I can see that's going to be an issue for discussion

24   today or tomorrow, at the...at the least, and that is

25   that one way that we would choose to use...we would use

1  concentrations of NO2 were evaluated at each of these

2  monitors, and we considered the spatial and temporal

3  variability in those concentrations.  And in

4  recognizing that there is this vari...variable

5  relationship between the personal exposure and the

6  ambient monitors, we decided to take a simple approach

7  to estimate on-road concentrations using those ambient

8  concentrations as input.

9	Then, the second component was the

10   exposure analysis that Scott mentioned where we did a

11   combined dispersion and exposure modeling exercise, and

12   the purpose of this was two-fold, to improve the

13   spatial characterization of the air concentrations,

14   because in most of these loctations, there are a

15   limited number of ambient monitors, and, in addition,

16   the second purpose was to simulate the contact of

17   persons with the air concentrations.

18	So, Philadelphia was...was selected as

19   that case study location.  Again, it's a more complex

20   analysis, so it wasn't like we could actually do that

21   across the United States.  And it serves about 1.5

22   million...I'm sorry...the population is about 1.5

23   million, and we did it for three years, 2001 through

24   2003, and modeled 17,000 receptors at various

25   locations, including census block centroids and

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1  linked...roadway links.  Sorry.

2	The AIRMOD portion, we considered

3  stationary sources, fugitive, and airport emissions, as

4  well as these mobile source roadway link-based emission

5  estimates, and 1-hour concentrations were estimated for

6  those locations, the census block centroids, available

7  ambient monitors that were within Philadelphia County,

8  and these major roadway links.  And APEX was used

9  taking those air concentrations as input, APEX was the

10   exposure model used which, of course, considers time

11   spent in various micro environments and the variable

12   concentrations that occur within those micro

13   environments, and we estimated longitudinal profiles,

14   exposure profiles for each of those three years for

15   each simulated person.

16	And the reason why I...I wanted to go

17   into this description of everything first is because

18   well, as I said, there isn't necessarily a direct feed

19   between one analysis and the other, but there is a

20   little bit of overlap in that for the air quality

21   analysis, we did use that information to select the

22   locations for more refined analysis in the exposure

23   assessment as well as the air quality monitors

24   themselves were used to estimate a local concentration

25   for the air concentrations that were modeled by AIRMOD.

1  mean number of exceedances that were estimated to occur

2  within a year in that particular location.

3	And I did mention that all the monitors

4  were represented here.  We had specific locations, and

5  anything that wasn't defined as a specific location,

6  they were grouped in this...these other two categories,

7  non-MSA and other CMSA/MSA.

8	DR. HENDERSON:    Would you mind, just

9  because we've just had this discussion of these

10   benchmark values, saying exactly where the benchmark

11   values came from, the 200, 250, and 300?

12	DR. GRAHAM:    Well, in...in the ISA, in

13   Chapter 5 of the ISA, there were...there were two main

14   conclusions regarding the human clinical literature.

15   One was regarding the literature on airways or on

16   the...on airways hyperresponsiveness.  So, the...the

17   first was with regard to hyperresponsiveness

18   following...following inhalation of...of an allergen,

19   and that...in that...for that, the ISA concluded that

20   effects were seen as low as 0.26 ppm for a 30-minute

21   exposure.

22	The other major conclusion regarding

23   hyperresponsiveness was with respect to responsiveness

24   following non-specific...inhalation of a non-specific

25   stimulus, and for that, the ISA concluded that effects

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1	So, if we can go to the next slide, this

2  is, I guess, a little bit more elaboration on the air

3  quality analysis, including the...the description of

4  the data that were used, and it was '95 to 2006.  We

5  separated it into two separate groups.  One we termed

6  history, the other more recent data, and then we

7  selected particular locations to...to do a more focused

8  analysis, geographic analysis, based on these criteria

9  of whether they had a high annual average concentration

10   as well as a current of p concentrations above 200 ppb

11   for...for one hour.

12	And then we looked at a variety of

13   scenarios that you see here, quality as is, just

14   meeting the current standard, and that simplified

15   version of how we estimated the on-road concentrations,

16   both for concentrations as is as well as just meeting

17   the...the current standard.

18	Next slide, please.

19	So, here's a...an example or a summary

20   of some of the data that were generated for each of

21   these scenarios, and it just provides a comparison

22   across the various simulations that were performed,

23   and, again, this is the results for the air quality

24   simulation for each of the cities, and we've got some

25   means and 98th percentiles represented.  And this is a

1  were seen at levels as low as 0.2 to 0.3 ppm for 30

2  minutes.

3	So, the...the range that we identified

4  here for this...for our assessment, 0.2 to 0.3 ppm, was

5  based on essentially those two conclusions, and the ISA

6  doesn't distinguish between 0.2 and 0.3 ppm for

7  that...for that non-specific hyperresponsiveness, so

8  we...we evaluated the range.

9	DR. HENDERSON:    That's good.  That's

10   what I thought it came from, but I just wanted to be

11   sure.

12	DR. GRAHAM:    I just want to make two

13   additional notes on this table.  These actually are

14   absolute counts of occurrences, so if there were p

15   concentration or a concentration above whatever

16   benchmark we were looking at, this is 200, a summary of

17   the 200 ppb.  If there were sequential occurrences,

18   this would...this would count that, and that's actually

19   distinguished...I'm sorry...distinct from the exposure

20   modeling, and I'll...I'll get to that in a moment.

21	The other thing to note is I did submit

22   a technical memorandum, and I noticed that this

23   contains the original analysis.  The numbers for the

24   technical memorandum are slightly different, and, for

25   the most part, you can see most locations ended up with

232

1  lower means.  It was particularly evident at the higher

2  percentiles for the on-road concentrations.

3	Next slide.

4	So, as far as the exposure analysis, I

5  probably described that in...in greater detail than

6  what was here, so we estimated the hourly

7  concentrations for simulated individuals across three

8  years and then, again, performed summary analyses to

9  determine the frequency of occurrence of these

10   exposures above those given potential benchmark levels,

11   but the difference between the absolute counts that

12   were estimated from the air quality characterization,

13   these were actually the maximum, if there was an

14   occurrence of the...I'm sorry...there was an occurrence

15   of one of these exceedances in a given day, then it was

16   counted as one.  There wasn't any counting of

17   sequential hourly exceedances for...for the exposures.

18	Next slide.

19	This is just an example of the exposure

20   results for...for the different years, and we also...I

21   guess I didn't mention that earlier.  We did do indoor

22   sources, gas stoves, and this is a summary of the

23   results, the maximum exposures that individuals, the

24   model simulated individuals, experienced, and these are

25   distributions for that, the...the CBFs, and we've got

1  different years.

2	Next, please.

3	Then, when we did a model run without

4  the indoor sources, you can clearly see the numbers of

5  individuals that are exposed to each of the potential

6  health benchmarks at least once within the year is...is

7  much lower.

8	Next slide.

9	And here's an example of results where

10   we see the fraction of the population, the asthmatic

11   population, mind you, above each of the potential

12   health benchmarks with just meeting the current

13   standard.  And that's with indoor sources, and then we

14   have without indoor sources.

15	And the next...next slide.

16	And, of course, the numbers are...are

17   lower.

18	If you hit the next slide.

19	Because we're estimating the

20   longitudinal profile, the exposure profile for each of

21   these simulated individuals, we do have ability to

22   capture whether these individuals receive multiple

23   exposures, and that's what this graph is showing, is at

24   least one exposure is in the back, and as you progress

25   towards the...the front of the graph, that's where you

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233

1  three years here, 2001 through 2003, with indoor

2  sources and one model run where we had excluded the

3  indoor sources, and it's distinct that those

4  concentrations, the exposure concentrations people are

5  experiencing, the max, was...was much less than with

6  the indoor sources.

7	Next slide.

8	And here is another example output from

9  the model where we looked at those three potential

10   health benchmark levels across the different years, and

11   this includes the indoor sources, and what we have on

12   the...the y axis is the percent.  And the focus here in

13   this analysis was on these susceptible/vulnerable

14   populations.

15	And this is asthmatics, asthmatic

16   individuals, total.  We looked at children as welll,

17   children asthmatics, and the...the results for those

18   were similar, and all of the results have been

19   presented in the document.  This is just

20   illustrative...an illustrative example.

21	And you can see that, of course, more

22   individuals are...or the fraction of the population

23   that are exposed to the lowest potential health

24   benchmark is greater than the...the higher benchmark

25   levels.  And there's some variability across the

1  would see multiple exposures, up...upwards to six for

2  each of the different benchmark levels.

3	And this one has with indoor sources,

4  and the next slide, no indoor sources for each of the

5  three years.

6	Next slide.

7	And then, where we simulated just

8  meeting the current standard, of course, the numbers of

9  individuals or the percent of individuals exposed

10   is...is greater and with indoor sources, and the next

11   slide is without indoor sources.

12	That concludes that.

13	DR. HENDERSON:    Thank you.  Does that

14   conclude the whole presentation?

15	MR. RICHMOND:    That's right.

16	DR. HENDERSON:    Okay.  So, now it's time

17   for public comments.  Do we have public commenters?

18	DR. NUGENT:    Yes, ma'am.  We have one

19   public comment from Ann Smith from CRA International,

20   and she is presenting some comments on behalf of the

21   Utility Air Regulatory Group.

22	I'd like to note for our people on the

23   line...for our members on the line that her

24   presentation is available on the website if you go to

25     HYPERLINK http://www.epa.gov/casac  www.epa.gov/casac and look u nder calendar, you'll find

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1  the meeting date for today.  It's one of the meeting

2  materials that's appended there for the...this meeting

3  record.

4	DR. SMITH:    Thank you very much.  I've

5  sent you all written comments that are going to cover

6  the topics that I...that cover the topics that I've

7  listed here.

8	If you could go to the next slide...and

9  I'm going to cover mainly two of the issues that...what

10   I'm trying to do in the comments here is not dwell on

11   the numbers that are coming out of the analysis at this

12   point but, rather, to look at the analysis as it stands

13   in its structure and the kind of data that are being

14   used to understand if we have a useful construct that

15   can be interpreted and used in policy making.

16	So, I...you can read later more or less

17   the second, third, and fourth of these comments, but

18   I'm just going to focus for the moment on the first

19   two.  One is we're talking about the benchmark issue,

20   level issue, and then I'd like to comment on the site

21   selection.

22	Next slide.

23	In order for a risk assessment to be

24   useful, it has to have some grounding back to some

25   interpretation of what the benchmarks mean in the way

1  from the lowest dose up to the highest dose in those

2  studies which was information on the previous slide,

3  and now we can break them...break these studies out

4  that are in the table into the three areas where the

5  benchmarks are set.  And the thing you'll notice is

6  that for the exposures that are around 200 ppb, the

7  lowest end of the benchmark, there are only two studies

8  that are identified in this supporting table, and

9  neither of them found a statistically significant

10   effect.

11	What this suggests also is you see not a

12   lot of appearance that the significance is more

13   frequently occurring as you go to higher and higher

14   doses.  This table goes all the way...to exposures all

15   the way up to 600 ppb exposures.

16	So, while there certainly are some

17   effects being observed for airways responsiveness down

18   in this range, it doesn't appear that there's much

19   justification to go below about the 250 ppb, at least

20   as the data have been presented and justified for these

21   benchmarks.

22	Now, I'm not going to try and argue what

23   the right benchmark level should be, but what my point

24   is is that whatever benchmarks are in the REA, they

25   need to be given some grounding in the underlying

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1  of risk.  This is particularly true if you're going to

2  be relying on concentration response functions to

3  quantify the estimates that...on benchmark levels.  EPA

4  has selected three benchmark levels.  We've talked

5  about that already, and the real question is,

6  what...what do these really mean in terms of risk?

7  What is their grounding in risk?

8	And there are some statements made in

9  the document.  The quote here comes straight from the

10   REA, that these represent the lower, middle, and upper

11   end of the range identified in the ISA as the lowest

12   levels at which controlled human exposure studies have

13   provided sufficient evidence for the occurrence of NO2

14   related airway responsiveness.

15	So, that's what it says about them, but

16   to me, the question is, well, how is that grounded in

17   what the science is saying?  And the REA actually does

18   provide Table 1 which is what shows on the next slide.

19   I've just pasted it in here to show you.

20	First, I'll point out that this table,

21   there's nothing quite like it in the ISA.  This didn't

22   come from the ISA, but this is what the REA is

23   providing in the way of backup for the justification.

24	If we go to the next slide, I've just

25   taken the data in that table and reordered it according

1  science and some explanation of just what you can take

2  them to mean from the point of view of risk.

3  Otherwise, to know that there are so many exposures or

4  so many individuals being exposed above a benchmark

5  level doesn't really tell people anything that's

6  relevant for policy making purposes.  And, ultimately,

7  the risk assessment has to be relevant for that.

8	Next slide.

9	The second point I want to turn to is

10   the question of the choice of the cities, and there's

11   no question that what is being selected in the way of

12   cities in both parts of the REA are worst case

13   conditions for exposure, and it's my belief that in a

14   good risk assessment, you really want to provide some

15   representation across the whole board of types of

16   exposures and information on how many people exposed to

17   the different levels of exposure.

18	And here you can see that the

19   exposure...the criteria in the exposure modeling is so

20   selective that only two cities in the whole country

21   actually meet the selection criteria.  EPA put in a

22   couple more criteria by reaching back in time to find

23   some more worst case cities.

24	The key point here is we're getting in

25   the exposure modeling five cities that are clearly

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1  among the worst in the country, and we have no

2  information that will come out of the REA if we use

3  only these cities to indicate what's happening in a

4  broad representative sense across the country for risk,

5  and I think that should be relevant for policy making

6  purposes in addition to what's happening in the worst

7  case.

8	Furthermore, in the air quality

9  characterization case, there are 18 cities that meet

10   the screen.  That's a less selective screen, but

11   they're all worst case.  They're all in the worst

12   90...10th percentile of exposures for the annual

13   average.  And when you have 18 cities and you're

14   showing exposures and exposure rates above benchmarks

15   in all 18 cities, one would, as an audience for this

16   REA, start to get the feeling that this is what's

17   happening across the whole U.S., that it ought to be

18   representative, but by construction, it's not

19   representative.  And so, more other cities ought to be

20   included and properly characterized as to what

21   proportion of the population in the U.S. faces those

22   additional exposures.

23	So, just to conclude on these first two

24   points alone, both the fact that the benchmark levels

25   are at levels at which effects have not been

1  representativeness within the cities based on your

2  evaluation of this document?

3	DR. SMITH:    Could you explain what you

4  mean within cities?

5	DR. SHEPPARD:    Well, you know, the

6  city...

7	MR. SMITH:    Oh, the monitors, for the

8  monitors not being in representative locations?  I

9  think the exposure modeling piece is supposed to try to

10   get at that, because what that's doing is trying to

11   monitor...come up with exposure estimates on a smooth

12   spatial area and then move people in and out of the

13   spatial orientation.  So, the exposure modeling comes a

14   lot closer to an attempt to understand how people are

15   being exposed above some benchmark level, whereas I do

16   agree that the air quality characterization, I'm not

17   sure it's very useful to know how many monitors go

18   above a benchmark level.  To me, that's really air

19   quality characterization and not risk exposure

20   characterization at all.

21	DR. SHEPPARD:    But, actually, monitored

22   air quality characterization as opposed to air quality

23   characterization.

24	DR. SMITH:    And...and...yes, and that

25   gets to my second point, or my fourth point, actually,

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1  documented, at least for what they're stated to be, and

2  the fact that the analysis is focusing only on worst

3  case cities implies that this particular REA is going

4  to characterize NO2 exposures in a way that will lead

5  to an overstatement of the nature of the problem,

6  particularly at as-is conditions.

7	And this concern is really just

8  exacerbated by the other two points that I don't have

9  time to go into here, the fact that the roll-up to...to

10   simulate exposure at the current NAAQS is so extreme

11   and also that there do appear to be inconsistencies in

12   the data between the two parts, that the air quality

13   data that's being used to assess exposures above

14   benchmarks may be highly inconsistent between the air

15   quality characterization portion and the portion that

16   does the exposure modeling.  That really needs to be

17   explored in order to make sure that both parts of the

18   REA are telling a consistent story when they're all

19   said and done.

20	Thank you.

21	DR. HENDERSON:    Thank you very much.

22   Are there questions?  Yes, Lianne?

23	DR. SHEPPARD:    Given...given your very

24   important point about representativeness of the cities

25   across the U.S., do you have any comments about

1  in the...in the comments, which is that when you get to

2  the exposure modeling, that's where you do have more

3  complete information on what exposure may look like

4  that needs to be consistent with the monitored

5  information, and the evidence that is available in the

6  tidbits of evidence that are available in the technical

7  support documents and the REA suggest that maybe

8  they're not, and until they are, you can't really trust

9  the exposure modeling, because that needs to be

10   demonstrated that they're consistent.

11	DR. HENDERSON:    Okay, are there other

12   questions?  Yes, Frank?

13	DR. SPEIZER:    Given you are being

14   critical of these sort of what you call worst case

15   cities, what proportion of the population is

16   represented by these cities?

17	DR. SMITH:    I think it should be

18   represented in the...in the document.

19	DR. SPEIZER:    Well...

20	DR. SMITH:    That information isn't

21   provided.

22	DR. SPEIZER:    Has not been.  Okay, well,

23   maybe the question is really to EPA to tell us what

24   proportion is represented by the total selected cities.

25	DR. GRAHAM:    I'm sorry, I can't answer

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1  that right now.  No, I don't mean to be like that.  I

2  don't have the populations in front of me.

3	DR. SPEIZER:    Yeah, but you probably

4  ought to be able to get that you're representing...

5	DR. GRAHAM:    Right, yes.

6	DR. SPEIZER:    ...a third of the U.S.

7  population or whatever it is.

8	DR. GRAHAM:    As I say, with

9  Philadelphia, it was 1.5 million.

10	DR. HENDERSON:    Are there other

11   questions?

12   (No response.)

13	DR. HENDERSON:    Okay, I think you close

14   out the...

15	DR. NUGENT:    Thank you.  Thank you for

16   the presentation, Dr. Smith.

17	DR. HENDERSON:    Okay, we'll go now into

18   the CASAC review.  There are three areas covered by

19   this document.  One is air quality, one is exposure,

20   and one is characteristics of health risk, and we're

21   going to start out with the air quality information and

22   analyses, and Christian Seigneur is our lead

23   discussant.

24	DR. SEIGNEUR:    Okay.  Well, I will start

25   on that.  I have several comments which I've given

1  reproducing the spatial variation that you have in the

2  measurements, and if you proceed to use the modeling

3  results after that to get the distribution exposure,

4  you simply have the wrong representation of the spatial

5  distributions over the two concentrations from the

6  model even after the adjustment.

7	So, there are two things which could be

8  done.  One would be to identify the cause for that

9  significant underprediction, whether some initial

10   inventory is incorrect and can be correct, or whether

11   the model, when applied in that region, is missing

12   something.  One possibility is that lack of NO2

13   chemistry is affecting emissions from the point source.

14   I don't know.

15	The other possibility, of course, is

16   to...if we can't identify the cause, is to use the

17   model in combination with the data and to do some data

18   fusion so that you can then keep the spatial gradients

19   that you have in the measurements.  I don't know if you

20   want to answer that right now?  Okay.

21	DR. ROSENBAUM:    Yeah, I just want to

22   point out when we did this model...the AIRMOD leveling,

23   we didn't actually try to model all the sources.  In

24   particular, we only tried to model the major roads

25   which we defined as roads that had annual average daily

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245

1  already in writing, and I don't have concerns about the

2  use of the air quality data but most...more the

3  implications of the air quality model which was the

4  second part of the analysis that you did for

5  Philadelphia.

6	My main concern was that when I looked

7  at Table 26 which shows the performance of the model

8  compared to the data at the monitors, and you showed

9  only three monitors in that table.  Performance, I

10   think, was pretty good for the two, the third and

11   the...the second and third monitors, but it was pretty

12   bad for the first.  I mean, second and third monitors

13   appear within 30, 40 percent of most of the

14   measurements.

15	The first monitor, there is a difference

16   of a ratio of about 3 between what was measured and

17   what the model did, and to me, that...that performance

18   is inadequate, because then you proceed to make an

19   adjustment by increasing the modeling values by the

20   same amount across the entire area.  As a result of

21   that, you move from a slight underprediction to a

22   slight overprediction at monitors 2 and 3, but at the

23   first monitor, you still have a significant

24   underestimation.

25	And my concern is that the model is not

1  traffic of 15,000 or greater.  So, that encompassed

2  actually only about 40 percent of the traffic

3  emissions.

4	So, there's...there's a...there's a lot

5  of emissions that are't...that weren't modeled.  The

6  reason we did it that way is because we're actually

7  looking for just the hot spots which we assumed would

8  be near the major roadways and that the...the other

9  traffic would be more evenly dispersed and wouldn't

10   create hot spots.  So, I mean, the...so that's partly

11   why you're seeing that, the discrepancy between the

12   monitor and the modeling, is that we weren't...in the

13   modeling, we weren't trying to be comprehensive in

14   giving all the sources, just the big sources where we

15   thought there might be hot spots.

16	So, on the one monitor where there's an

17   even larger discrepancy, it just so happens that that

18   monitor is not near any major roadways or point

19   sources.  So, it's...the monitor value is coming

20   primarily from the local traffic that we didn't model.

21	DR. SEIGNEUR:    Okay.

22	DR. GRAHAM:    Right.  I'm

23   sorry...and...and that's why it was corrected for a

24   factor.  The factor is attributed to sources not

25   modeled.

248

1	DR. SEIGNEUR:    Right, but I'm sure

2  you...you've done it by a factor.  You increase the

3  modeling by a constant value, and that's...that's my

4  contention, because by doing that, you increase the

5  values at all the monitors whether the underestimation

6  was very small or very large, and when you look at the

7  results of the model after integration, they still look

8  pretty bad.

9	So, my recommendation is that your

10   adjustment should be receptor specific.  You need to

11   increase the modeling results at the location where you

12   have a gross underprediction by a larger value than you

13   would adjust them at the other locations.  So, that's

14   why I was...why I was referring to data fusion.  You

15   need to do something a bit more complicated than what

16   you have done when you address the modeling results.

17   So, that was my...my main comment.

18	The other comment I have, I was a bit

19   confused on why...I understand why you roll back the

20   benchmark when you are looking at the results when you

21   only have outdoor sources so that you don't have to

22   redo all the calculations.  You simply change your

23   benchmark and scale everything.

24	I got confused when you did that when

25   you have outdoor and indoor sources, because

1  were...were massive.

2	So, rather than adjust the factor...I

3  mean, adjust all of those concentrations to have it run

4  in the model which would also take additional time, we

5  decided that it was mathematically equivalent to just

6  roll back that benchmark concentration by an

7  appropriate factor, and if you take a look at the

8  equation that's listed there, the exposure is the

9  combination, proportional combination, of the ambient

10   concentration as well as the contribution from the

11   indoor sources, and we are estimating that exposure and

12   then determining whether or not it exceeds this given

13   benchmark.

14	Well, if we adjust the air quality by a

15   given factor, you can see we multiply it by the ambient

16   concentration as well as these different proportions

17   that would be assigned to the exposure

18   concentrations...I mean, that would go into the given

19   exposure concentrations, and then you'd determine your

20   benchmark.

21	If we just divide both sides of that

22   inequality by the factor, you can see if we divide the

23   indoor source contribution by the given factor and the

24   benchmark by the factor, we will get the same answer as

25   if we rolled up the concentrations.

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249

1  mathematically, that did not make sense to me.

2	DR. GRAHAM:    Angela, the slide, if you

3  could pass that out?  Oh, you have it.  I'm sorry,

4  that's right.

5	So, for the air quality

6  characterization, I think I mentioned earlier that we

7  had raised the concentrations at each location by a

8  given factor, and that factor was determined by the

9  highest monitor, the highest annual average for each

10   year.

11	No, no, we don't need those.

12	SPEAKER:    We don't have it on the

13   slides.

14	DR. GRAHAM:    Yeah, I'm sorry.  It's the

15   slide that was passed out.  Sorry.  The hard copy.

16	So, that was the air quality, but what

17   you're referring to is what we did for the exposure

18   modeling where we actually...

19	DR. SEIGNEUR:    Right.

20	DR. GRAHAM:    ...had to roll back the

21   benchmark, and that's explained in the second section.

22   If we...I guess to make it a more efficient process,

23   instead of...because of the size of the files.  I mean,

24   we had 17,000 receptors for three years across, you

25   know, every single hour.  I mean, the size of the files

1	DR. SEIGNEUR:    Okay.  So, you mean that

2  you divided indoor sources by the same factor?

3	DR. GRAHAM:    Right.

4	DR. SEIGNEUR:    Okay.  All right.

5	DR. HATTIS:    Well, I guess I have a

6  problem, but I'll wait until later, but it seems to me

7  that you...your response doesn't completely disclose

8  that that implicitly says that the indoor sources

9  are...are changing by the same factor as the outdoor

10   sources, that your assumption of doing that must mean

11   that your indoor sources are changing by the same

12   factor as your outdoor sources, and you...that's

13   clearly not right.

14	DR. GRAHAM:    No, no, that's not what's

15   implied.  If...do you have the slide?

16	DR. HATTIS:    I've got the slide.

17	DR. GRAHAM:    Okay.

18	DR. HATTIS:    And I also read exactly

19   what you said you did, and it's not...I mean, clearly,

20   the indoor source...if you...if you increase the

21   outdoor concentrations, they will make up a total...a

22   different fraction, a larger fraction, of the total

23   exposures than indoor sources.  So, you must have

24   assumed that that's a constant fraction.

25	DR. ROSENBAUM:    I think what we did was

252

1  we scaled back the indoor sources by the same amount

2  that we scaled back the benchmark threshold so that

3  we...so that we...we made that adjustment...

4	DR. GRAHAM:    Okay, yeah, that's what

5  the...

6	DR. ROSENBAUM:    ...to...to the problem

7  that you're talking about.  If you look at

8  the...the...the final equation on the slide, you can

9  see we divided the indoor source by the same factor

10   that we divided the benchmark concentration by.

11	DR. GRAHAM:    So, it's contribution would

12   be the same in the end.

13	DR. SEIGNEUR:    Yeah, it was not clear

14   whether you had corrected the indoor sources, but now I

15   understand.

16	DR. GRAHAM:    Right, it wasn't...it

17   wasn't in the document, and I appreciate the comments.

18	DR. SEIGNEUR:    All right, good, that

19   makes sense.

20	The last major comment I have is

21   regarding the treatment of uncertainty and variability

22   in the document.  When I read the document, my

23   impression was it was a catalog of different sources of

24   uncertainty and variability, and I have two points to

25   make.

1  just...I just had two...two issues, and I guess one was

2  with that whole roll up/roll down thing, but this

3  correction makes me feel better.  So, I...I mean, I

4  think that addresses my...my issue with it.  So, thank

5  you for providing that.

6	The other issue I had here was...and

7  maybe this is my foggy brain or maybe that it wasn't

8  very clearly laid out, but it's this whole concept of

9  the on-road estimation and...and the model that

10   developed...developed the distribution for on-road

11   concentrations.  You know, I...I guess I thought it was

12   a reasonable model, but I didn't quite see why...I

13   mean, you...you generated this wonderful distribution,

14   but I didn't...I was not convinced that that

15   distribution was...was an accurate depiction of what's

16   really happening in on-road concentrations, because I

17   didn't see any comparison to real on-road data, just

18   that it, you know, you had applied this model to come

19   up with that.

20	So...and...and in this, there are some,

21   you know, a handful of monitors in the U.S. that are,

22   if not on-road, at least very near road.  I guess I

23   would have...really would have liked to see some kind

24   of sort of real-world comparisons of your...your model

25   distribution with...with the real...the real data.  It

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253

1	One is that somewhere missing are the

2  uncertainties due to the model formulation, for

3  instance.  It would be nice to add that and what

4  uncertainty can you expect from a model like AIRMOD,

5  what uncertainty can you expect from your main source

6  models which is the formatting which AIRMOD is applied

7  here.

8	And also what I'd like to see is for the

9  document to go one step further and to give the reader

10   some information on which of the sources of uncertainty

11   you think would be the most important.  Some are going

12   to be more important than others, and I think it would

13   be helpful for the document to...to give some

14   information there.

15	I don't know if you have any plans to do

16   a quantitative uncertainty analysis.  Maybe not, but at

17   least, if it was semi-quantitative that you would say,

18   you know, we expect the results, you know, to be good

19   within a factor of 2 or a factor of 10 and so on.  I

20   think that would be useful.

21	That's the end of my comments.

22	DR. HENDERSON:    Is that?  Okay, thank

23   you very much, Christian.  And Donna?

24	DR. KENSKI:    Thanks.  Mostly, I thought

25   the air quality end of this was...was well done.  I

1  would have made me feel more confident that this was

2  really useful.

3	DR. GRAHAM:    As in the modeling world

4  always, we derive the data from the literature studies,

5  and then, what are we left with after we use all of

6  those studies to derive our little factors.  It's not

7  like we can go back to those same studies and say hey,

8  look, we reproduced those concentrations.

9	Because the factors were derived

10   from...well, I think I was able to obtain 20 different

11   literature sources that contained data on

12   concentrations on-road and at distances from the

13   roadway, and that's what I used to derive these...these

14   factors and, ultimately, you see represented by

15   the...the distributions provided in the TSD.

16	So, to...to compare, I'm at a loss

17   for...for data outside of the papers that I derived the

18   information from, but as a rough cut, I mean, we could

19   see that the on-road concentrations are approximately 2

20   plus or minus...

21	DR. KENSKI:    A factor...

22	DR. GRAHAM:    ...I'm not sure how much

23   higher than the ambient monitor concentrations which is

24   consistent with what is reported in the literature.

25	DR. KENSKI:    But why not...why not

256

1  compare some real ambient measurements?  I mean, yes,

2  you took your literature models, but...but there are,

3  like I said, a handful of very close to the road

4  monitors.  I would have liked to have seen them.

5	DR. GRAHAM:    Right.

6	DR. KENSKI:    Okay.  And...and I...I

7  guess I was then struggling to figure out how those

8  on-road factors then got used in the model.  I think

9  that...that was a little fuzzy about how they got

10   applied later on.

11	DR. GRAHAM:    Right.  In the first draft

12   that's reported in the first draft document, it was

13   applied to all the monitors regardless of...of where

14   they were, and then we pulled out the monitors that

15   were within 100 meters of a major roadway and redid

16   that analysis, and that's what's reported in the

17   technical memorandum.

18	DR. KENSKI:    Right.  That's all.

19	DR. HENDERSON:    So, that's all, Donna?

20   Okay, Tim Larson, are you there on the phone?

21	DR. LARSON:    Yes, I am.

22	DR. HENDERSON:    Okay, it's...it's your

23   turn for comments.

24	DR. LARSON:    Thank you.  I would second

25   Christian's comment about the...the fact that making an

1  offset, you had in there...and I wasn't sure, but a

2  sort of a characteristic length of 10 meters from the

3  roadway, and that seemed low to me, even though

4  it...because that seems like it's in contradiction with

5  the concept of a factor of 2 difference between the

6  monitors and the on-road level.

7	If the gradients are that steep, then

8  I'm surprised, because I've seen...most of the

9  literature I've seen is on...I mean, these sort of

10   characteristic drop-off scales are on the order of 10s

11   of meters or 100 meters or something like that, and it

12   clearly depends on the meteorology at a given time,

13   but, I mean, on average, it seems...it seems like

14   that's a fairly...a fairly steep gradient right near

15   the road, and it would make the estimates on-road

16   fairly unstable...or very sensitive...excuse me...to

17   the actual values that you use at the monitor or where

18   that monitor is within the real gradient, and it seems

19   like that's probably borne out by the technical

20   memorandum where you've taken away those monitors

21   within 100 meters of the road and you get quite lower

22   exceedance values.

23	But I...I don't know whether it's...it's

24   real because...or it's because of that 10 meter

25   assumption, if that's the...unless that's a typo.  It

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257

1  adjustment that's a constant adjustment across space to

2  bring the model, the  AIRMOD predictions, and the

3  measurements in line is probably inappropriate.  I

4  mean, there's a number of...of literature...there's a

5  lot of literature on this, but...and there are models

6  that are invoked that are somewhere in scale between

7  the AIRMOD and the...the larger chemical transport

8  models.  Urban background model is one of them in which

9  there's at least some attempt made to grid and

10   aggregate those emissions, those...the other 60 percent

11   of the emissions that you're missing from smaller roads

12   and move them around with some simple...simplified

13   photochemistry.

14	And then you see from those kinds of

15   models that there's quite a difference spatially, as

16   you might expect, from, you know, the center of the

17   city versus the surrounding outer edges of the city.

18   And so, a simple adjustment across space is probably

19   underestimating the concentrations in the center of

20   town where most of the...the traffic emission densities

21   are greatest.

22	So, I would...I would second that, and

23   that's one...one comment.

24	I was a little...I wasn't...on the

25   method used for screening the exponential model with an

1  seems small to me.

2	But anyway, moving on, I had a...well, I

3  guess one of the questions had to do with the

4  appropriateness of the locations, and in looking at the

5  Philadelphia data, where people actually live, it's

6  true.

7	Philadelphia is a very...it's a very

8  residential city, and the average census centroid was

9  like 450 meters from a major road which, when you

10   look...fly over Philadelphia makes sense.  There's a

11   sort of central...a fairly small central downtown area.

12	But it seems like that's...that's not

13   representative of a lot of cities.  I mean, it's a very

14   residential single-family city compared to a lot, and,

15   you know, 90 percent of the people in New York City

16   live within 100 meters of a major road, and you're

17   saying...so, I mean, Los Angeles has its own issues

18   with respect to just the large amounts of traffic as

19   well, I mean, but Philadelphia seemed like a curious

20   choice, to me, if you're looking at what you classify

21   as worst case, because when you run the AIRMOD model

22   later on in your...in your APEX model, you're running a

23   fairly...I mean, your centroids are so far from these

24   major roads that it's not clear to me...there have got

25   to be a large number of people that you're...that are

1  living near those roads that you're just

2  underrepresenting completely by this...this kind of

3  a...an approach.

4	I don't know.  I just...I think

5  it's...it would be nice to know something...the

6  statistics...that particular plot, figure 4, I think it

7  is, would be a...would be a...an interesting plot to

8  look at as a screening tool for choice of other cities,

9  because, you know, basically, you do it in the

10   chapter...Chapter 4 or whatever it is in the ISA where

11   you look at percent of people living near roads, but I

12   think that's an important criterion, and I think

13   Philadelphia is...you could prove me wrong, but I think

14   it's a little bit on the end of the distribution where

15   people don't live near major roads.

16	So, that's...

17	DR. HENDERSON:    Tim, you are asking

18   questions, and I think the...the EPA folks here can

19   answer.  Would you like to get a reply from the...

20	DR. LARSON:    Sure.

21	DR. HENDERSON:    Okay.

22	DR. GRAHAM:    Yeah, I just wanted to

23   respond to the...the first question about the 10

24   meters, and that is, I believe, what was reported in

25   the literature that I derived the data from, and if you

260

1  just the representa...representativeness of...of

2  Philadelphia as a test case here from an air quality

3  perspective.  I think it...it's surprise...it surprised

4  me as being labeled worst case city even though it has

5  high monitor values.  Most people don't live near the

6  road.  That's my only other comment.

7	Thanks.

8	DR. HENDERSON:    Okay, and they are going

9  to be doing more cities later.  Within the next

10   version, what cities will be done, all of those on the

11   list or just...

12	DR. GRAHAM:    Do you want to respond to

13   that?

14	DR. JENKINS:    I think we'd be looking to

15   input from the panel on what cities might be

16   appropriate to expand our analysis.

17	DR. HENDERSON:    But how many more do you

18   think you...you can do?

19	DR. JENKINS:    Good question.

20	DR. GRAHAM:    Well, I think it comes down

21   to the value that's added from this analysis.  I think

22   that needs to be reviewed and...and elaborated on

23   before we would proceed, and I think that is one of the

24   charge questions.  Is it charge question 4, I think?

25	DR. LARSON:    I think I agree with you

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261

1  look at the exponential equation and did calculations

2  at various distances, you probably would see the decay

3  drop off very rapidly, but you bring up an interesting

4  point in that there are studies out there directed to

5  me as well by others, there are studies that show that

6  we do have some of these peak occurrences in the

7  concentrations that occur at greater distances from the

8  roadway, sometimes upwards to 50 or 100 meters.

9	So, we'll take that into consideration,

10   and, actually, in a sense, we had taken that into

11   consideration by removing those monitors, as reported

12   in the technical memorandum.

13	DR. HENDERSON:    Okay, thank you very

14   much.  Continue, Tim.  I just thought you might want to

15   get some answers as you go along.

16	DR. LARSON:    Yeah, no, I...I look

17   forward to the Los Angeles results, because I think it

18   will be an interesting comparison.

19	But I...I think there's this...that's

20   not me, I don't think.  Hopefully not.  Hello?

21	DR. HENDERSON:    Yeah, we can hear you.

22   We heard some static, but...

23	DR. LARSON:    Well, it wasn't me, but

24   I...I don't know.

25	Yeah, so I...my only other concern was

1  that Los Angeles, if you're doing it, would be on the

2  high end of the exposure range.  I just don't know

3  about Philadelphia.  That's my...I mean, if you...

4	DR. GRAHAM:    Well, can I respond to

5  Philadelphia?

6	DR. LARSON:    Sure.

7	DR. GRAHAM:    Yeah, well, because it came

8  out from the air quality characterization as a city

9  that had these...an exceedance or two of 200 ppb and

10   there was significant variability in the hourly

11   concentrations, and it was one of the five that we had

12   selected in addition with made that the first city to

13   be done was that we were able to get the data quickly,

14   the data required for inputs, including the travel

15   demand modeling information which is critical for this

16   analysis, and...

17	DR. LARSON:    Right.

18	DR. GRAHAM:    ...time is...is of the

19   essence here.

20	DR. LARSON:    Yeah, I...and I think it's

21   a great city to do.  I just...I just was providing my

22   own perspective on that.

23	So...and the problem is if you get...if

24   you get cities where people live closer to the road,

25   then you have a more densely urban geometry, and then

264

1  you bring up a whole set of other issues, and it makes

2  this modeling more difficult and...and brings this

3  approach into question, I mean, the AIRMOD approach.

4	DR. HENDERSON:    Okay, I think Ted is

5  next anyway.

6	DR. RUSSELL:    No, I just had...had a

7  question, too.  I'm not sure if Tim is done.  What

8  cities do you actually have the data to do, any of the

9  18 or whatever?

10	DR. GRAHAM:    No, the five that were

11   identified for the exposure analysis.

12	DR. RUSSELL:    So, that's really, those

13   are the...

14	DR. GRAHAM:    Los Angeles...

15	DR. RUSSELL:    ...five...

16	DR. GRAHAM:    Yeah.

17	DR. RUSSELL:    ...that you really have

18   the data to do.

19	DR. GRAHAM:    Right.

20	DR. RUSSELL:    Because it...I mean,

21   as...one of my comments is that it takes an impressive

22   amount of data, and I was, you know, I thought you did

23   a great job on Philadelphia save a few things.  So,

24   I'm...but, really, we're limited to those five unless

25   we really push?

1  needed 17,000?

2	DR. ROSENBAUM:    Well, we selected...it

3  turns out...well, we did Philadelphia County, and it

4  turns out that was like almost all the census blocks in

5  the county, but what...we selected them originally on

6  proximity to major roadways and then being within 10 km

7  of the major point source.

8	So, like I said, we were looking for hot

9  spots.  So, that's how we selected the receptors, and

10   we wanted to do it at the block level to make sure we

11   got the spatial variance the best we could.

12	DR. HENDERSON:    Okay, Tim, are you done,

13   or do you have more comments?

14	DR. LARSON:    Well, I mean, I...yeah,

15   I...I guess that we're too far down the road to change

16   the approach here, but I wouldn't look for hot spots

17   that way myself.  I would...I would look at the traffic

18   and where it's confined by...by the building geometries

19   in the city.  Every city has got...major city has got a

20   central area, and...and that's what I would use as a

21   criteria rather than the proximity of the census block

22   centroid to the...to the road, but, you know...because

23   we're only talking about the extremes in the

24   distribution here.  If we were talking about the means

25   in the distribution, then...then what I just said

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1	SPEAKER:    Yeah.

2	DR. HENDERSON:    Okay, yeah, that's...I

3  wasn't sure what you were asking, whether you wanted

4  more than the five or whether you can only do two more

5  and you wanted to know which if the five to do, but if

6  you can do those five, I think that would be good.

7  That's my opinion on it.

8	DR. LARSON:    I think that's right.

9	DR. GRAHAM:    Well, because we have the

10   input data, again, the issue now is...is about the time

11   when you think about the size of the...the domain.  The

12   modeling domain that we did for Philadelphia was 17,000

13   receptors.  For something like Los Angeles, it's going

14   to be at least twice that, probably longer, and I don't

15   think the computational resources used is going to be a

16   linear function.

17	DR. RUSSELL:    Of the AIRMOD computations

18   or APEX or what are you...

19	DR. GRAHAM:    I think all of it combined.

20   I...I think it's just going to take longer, much

21   longer.

22	DR. ROSENBAUM:    Yes, I think it would be

23   good to get your input on like prioritizing among that

24   list.

25	DR. HATTIS:    Why did you decide you

1  probably doesn't matter, but if you're only talking

2  about 1 percent of the population getting high

3  exposures, then these extreme cases do matter.

4	And so, it's just...it's an uncertainty,

5  because you're not going to be able to do that in this

6  current approach, and you don't have enough data to use

7  a model...a measurement based approach to get a

8  different hot spot identification procedure.  So, I

9  would...I guess I...I guess I'm just glad you're going

10   to do more cities, but I don't know how you...well,

11   anyway, we'll wait and see.

12	DR. HENDERSON:    This is the time to give

13   input.  I guess let's hear what Ted Russell has to say.

14   I mean, I want to hear what everybody has to say, and

15   then we can discuss, you know, is this the right

16   approach, or do...do others think that there's a better

17   way to do it?

18	So, Ted, why don't you go ahead?

19	DR. RUSSELL:    First, I definitely want

20   to second what Christian, Donna, and Tim have brought

21   up.  If you want my choice, it would be...since you've

22   already done Philadelphia, it's in the bag.  Then, Los

23   Angeles is the ob...obvious second choice.  I'm from

24   Atlanta, so that must be third, but also, I think

25   geographically, it's...it's different.

268

1	I'm not so worried about Phoenix, since

2  it's, you know, not that far from L.A.  It's a similar

3  kind, but it's good to know that, actually, it's really

4  the data that's limiting it, and so, that is our

5  choice.

6	And I will say I was very impressed with

7  the detail that went into this, and I recognize that it

8  is a...a significant effort to...to get that amount of

9  data and to pull this off.  So, definitely, kudos on

10   that part of it.  You know, I'd pointed out that maybe

11   there's...there's some questions on the data.

12	And then, the other point I'll just

13   bring up is I'm actually quite uncomfortable, the more

14   I think about it, with how you did the on-roadway

15   concentration adjustment with the exponential decay.  I

16   mean, when I was reading it, I was going it would

17   strike me that this should be done in some sort of a

18   Gaussian modeling framework, even if it's a very simple

19   one, I mean, just a back of the envelope Gaussian

20   modeling, one where you also include a chemical

21   conversion.

22	With your current formulation, NO2

23   concentrations can only go down from the roadway even

24   though, in fact, looking at some data that Joe...Joe

25   had at break, you know, the NO levels are much, much

1  on road or near road.

2	DR. RUSSELL:    Okay, so that...I would

3  have to look in more detail at the studies, but what

4  you're saying is that in those studies, they measured

5  where the peak was anywhere near a road?

6	DR. GRAHAM:    Well, they...that...from

7  the studies, it was on road, but I'm suggesting, based

8  on your comments as well as others, that okay, if this

9  peak is occurring somewhere at a distance from the

10   source, it's going to have that decline, and I've seen

11   that reported as well.  So, what we're capturing with

12   the calculation is basically the peak.  Where it

13   actually occurs, that's really a question here.  Is it

14   on the road, or is it near the road?

15	So, rather than characterizing what I'm

16   saying as on road, maybe I should characterize it as on

17   or near roadway.

18	DR. RUSSELL:    And from what you've done,

19   have you actually seen, essentially, a Gaussian

20   dispersion with some conversion rate gives you about

21   the same thing for a busy roadway, or is that even

22   pertinent to what you're trying to do?

23	DR. GRAHAM:    I...I haven't seen anything

24   like that, so if you had something to share with me...

25	DR. RUSSELL:    Oh, I was just hoping you

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1  higher on the roadway, right on the roadway, than the

2  NO2, and there's a variety of data that shows that the

3  peak is actually somewhat further away from the

4  roadway.  So, I'm...if I were to go and really look at

5  one part to improve it on the air quality/modeling

6  characterization, that's where I would probably spend

7  my effort.

8	I'm not as worried about it, given that

9  I'm not sure how that data's going to be used in the

10   end, except it sort of gives you a characterization of

11   it's a factor of 2 or whatever, but it would be of

12   interest to see...get a little bit better support for

13   that and to also show that it...it may not be on

14   roadway.  It may be someone sitting 50 meters away or

15   something like that, and this could be particularly

16   important in a place like Los Angeles.

17	So, I might...I would hope or at least

18   like to see that that might be one of the changes

19   between now and the next draft of this.

20	DR. GRAHAM:    Well, in a sense, you could

21   look at the concentrations that have been estimated and

22   characterized as on road.  That's really the peak

23   concentration that's being estimated, whether it

24   occurred on the road or somewhere at a distance from

25   the road.  I mean, you could characterize it as either

1  had done it.

2	DR. GRAHAM:    Oh, no.

3	DR. ROSENBAUM:    Actually, we did do that

4  with the dispersion modeling when we did do an analysis

5  of the ratios from the...the concentrations at the...at

6  the blocks to the concentrations on the roadways,

7  because we put receptors on the roadways as well.  So,

8  we did get a distribution there of the...of those

9  ratios.

10	So, it's somewhat of an independent or a

11   Gaussian...

12	DR. RUSSELL:    And what did you find?

13	DR. ROSENBAUM:    ...estimate.  I can't

14   remember off the top of my head, but I can tell you

15   that tomorrow.  I can look it up tonight.

16	And that did...that did include the

17   chemistry, too, the ozone limiting chemistry.

18	DR. HENDERSON:    Okay.  Is that yours,

19   Ted?  Okay, Jim Ultman, do you have something to add?

20	DR. ULTMAN:    Several of my comments have

21   already been covered.  I guess the mo...the thing that

22   was most on my mind was the...or I had most of the

23   problem with was this extrapolation method for ongoing

24   conditions.  I really couldn't follow it in the tech.

25   This is out of my field, so I'm probably a good...I may

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1  or may not be a good test case.  Depends on how you

2  view the document who your readership is going to be.

3	I had a really hard time understanding

4  something which I think is pretty simple, but I think

5  it needs to be cleaned up somehow, and I...we can talk

6  about this more privately if you want.  And, also, the

7  methodology that was applied was hard to follow.  I

8  mean, the equations themselves and what the variables

9  exactly meant and what you were getting at I didn't

10   understand, but then, when it came to the methodology,

11   I had a hard time, although going to the...going to the

12   annex helped a little bit, because it has some of the

13   distribution information that the...that's not present

14   in the main part of the document...not the annexes, the

15   PSD.

16	DR. GRAHAM:    Sure.

17	DR. ULTMAN:    So, one of the suggests I

18   have is...is...I made it this morning, was that it

19   would be good to move some of this up, possibly, into

20   the ISA, and I know that the two groups communicate on

21   this, but I think if you could some...put some of the

22   basic data from which the onward extrapolations are

23   derived in the main body and some of these

24   distributions in the main body, it might...of the ISA,

25   it might help when you get to this point.

1  extrapolation data versus what you get in the exposure

2  analysis.

3	So, have you looked at putting those two

4  together?  In other words, you've got on-road

5  extrapolations that you've done for the air quality,

6  but you also have, you know, you've simulated spatial

7  distributions in your exposure.  Now, can't those come

8  together?  Can't you validate one with the other

9  and...and lay some of these things to rest?

10	DR. GRAHAM:    Well, I think it's close.

11   It's probably one of these apple and oranges things,

12   because I think it's going to be a...a function of the

13   distance the receptors are to the roadway that are used

14   to generate the distribution.

15	DR. ROSENBAUM:    And we did get a

16   distribution.  I mean, I think...I think your point is

17   well taken that it would be good to compare them.  They

18   aren't an exact comparison, but just to see if we're in

19   the same ball park.

20	DR. ULTMAN:    Give more credibility to

21   both methods if they...if you could show some

22   consistency.

23	The other thing I was...this is more of

24   a, I'd say, an academic curiosity than...that something

25   that you can do something about at this point, but

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1	And there's a, I think, a logical place

2  for it in Chapter 2 when they're talking about spatial

3  variations, that a section could be put in on that.

4	And maybe even put the equations in and

5  explain the basis of the equations.  I don't know if

6  they're theoretically based or purely empirical or what

7  the assumptions are, but, certainly, there are exposure

8  equations in Chapter 2 of the ISA.  I don't see why

9  there couldn't be equations that have to do with the

10   air quality in there as well.

11	One thing I was wondering, I was just

12   curious about, and I think you were...you actually kind

13   of touched on it.  The...I'm saying you, because I

14   don't remember your first name.  I'm sorry.

15	DR. ROSENBAUM:    Arlene.

16	DR. ULTMAN:    Arlene.  One thing that

17   Arlene touched on was that you had actually gotten some

18   information from ratios of off-road to on-road

19   concentrations from your simulations, exposure

20   simulations, and I was thinking that, you know,

21   somebody else had made the comment that well, you know,

22   isn't there a way...can't we use some kind of data to

23   validate the extrapolation method, and somebody else

24   made a comment, is there really consistency between the

25   extrap...between the values you get from the

1  the...does the CHAD take...have...take account at all

2  in terms of avoidance behavior of people that have

3  compromised lung function?  In other words, if it's a

4  bad...if it's a bad ozone day, in my field, or if it's

5  a bad NO2 day in your field, they may choose to change

6  their activity patterns.  Is that in the CHAD database

7  at all?

8	MR. RICHMOND:    Yeah, this is Harvey

9  Richmond.  Not that information.  It is...they didn't

10   collect what the ozone or NO2 levels.  They caught

11   the...we matched up later temperature with it, but so,

12   to the extent in the whole large database of thousands

13   of activity days, there may be some...there certainly

14   would be some days that included high ozone and others

15   that didn't, but we don't have access to that

16   information.  It's not a variable that's captured

17   within CHAD.

18	DR. ULTMAN:    Because we did...we

19   did...there was some discussion about the...the

20   validity of doing, you know, the roll back in the...in

21   the ambient air levels as a way of dealing with the,

22   you know, trying to make your computations more

23   efficient so you don't have to repeat your computations

24   as often, and that relied on linearity of all the

25   models for that to be true.  I mean, you gave us the

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1  equation here, and it's a linear equation, but if there

2  are parameters within that equation which depend on the

3  air quality, then you can't really do what you're

4  doing.

5	You see what I'm saying?  So, in other

6  words, if there are parameters in the...if there are

7  parameters in the time activity, sub-routines that you

8  use in the CHAD, that were sensitive somehow to

9  concentration, that would make the models non-linear,

10   and then you couldn't do that.  There wouldn't be thus

11   equivalence that you're talking about.

12	So, as I said, if it's not in the CHAD

13   model, there's probably nothing you can do about it at

14   this point.

15	MR. RICHMOND:    Right.  In fact, we are

16   supporting additional research at this point to

17   actually carry out those kind of surveys to better, in

18   the future, get information on how much individuals do

19   avert any mitigating behavior on high ozone days for

20   sensitive populations, but it's research that doesn't

21   exist, for the most part, out there right now.

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

23   Now, it's open for other people who may have comments

24   on the air quality part of the risk assessment

25   document.  Whew, we've gone all the way down the line,

1  me ask the question was the population you gave

2  for...for...or somebody gave for Philadelphia was the

3  residence population, but the real population is the

4  residents plus the people who come in.  In the case of

5  Atlanta, I was just looking on the web, and it's like

6  the population of Atlanta grows by 60 percent during

7  the day.  So, that...that wasn't considered, and, of

8  course, those commuters are getting the...the most

9  exposure to ambient air pollution, so they're...they're

10   probably a big chunk of the problem.  Right?

11	DR. GRAHAM:    Yeah, in this model,

12   we're...we're not including people that come from

13   outside the domain as well as individuals that leave

14   the domain.  They end up with average concentrations

15   when they commute outside the domain.

16	DR. THURSTON:    So, you're not counting

17   people who live in the suburbs and drive into the city?

18	DR. GRAHAM:    Well, it's the whole

19   county.

20	DR. THURSTON:    It's the whole county.

21	DR. GRAHAM:    So, if there are suburbs in

22   Philadelphia and they're traveling to the inner city

23   region, then they are counted.

24	DR. ROSENBAUM:    If they live in

25   Philadelphia County.  We just...we only modeled

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1  so, George, we'll come up this way, George and then

2  Lianne.

3	DR. THURSTON:    I'm just wondering if the

4  model considers journey to workinformation?

5	DR. GRAHAM:    Yes, it does.  It has a

6  commuting database that's derived from the U.S. Census,

7  and people have a home tract...I'm sorry...a home

8  block, and they also have port blocks.

9	DR. THURSTON:    And does that apply just

10   to the people who live in the city or the commuters

11   who...

12	DR. GRAHAM:    It's the entire modeling

13   domain.

14	DR. THURSTON:    The entire, so...oh.

15	DR. GRAHAM:    All the simulated

16   individuals...

17	DR. THURSTON:    I'm sure it's an answer.

18   I don't understand it, though.

19	DR. GRAHAM:    If they were characterized

20   as...as workers, they link to different blocks.

21	DR. THURSTON:    So, but workers in there,

22   they are counted.

23	DR. GRAHAM:    Yeah.

24	DR. THURSTON:    Oh, okay.  Because, I

25   mean, like Atlanta's population...the thing that made

1  Philadelphia County.

2	DR. THURSTON:    But don't you think that

3  you might be missing a lot of people who are affected

4  by the pollutions...the pollution in Philadelphia?

5  You're missing a lot of people who might be exposed to

6  that, because you're not counting people who live

7  outside and come in for the day, because the maximum

8  concentrations are in the daytime, and the...and along

9  the roadways where they're driving, and I don't know,.

10   It seems like...

11	DR. GRAHAM:    Then you expand...you have

12   to expand the model domain, and then you have to

13   include the sources where those individuals are living.

14	DR. THURSTON:    Well, yeah.

15	DR. GRAHAM:    Right, but, I mean, you

16   have to draw the line somewhere, I guess is what I'm

17   trying to say.

18	DR. THURSTON:    Well, okay, but if you do

19   Atlanta, then you're drawing a line...you're

20   eliminating a lot of people.  Philadelphia's probably

21   not...based on these numbers, Philadelphia's not too

22   bad, because only like 10 or 15 percent of the people

23   in the city come in from outside, but you go to

24   Atlanta, there's a big chunk of people you'll be

25   missing.  Anyway, it's just a thought.

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1	DR. GRAHAM:    Well, again, it depends on

2  the boundaries for the domain.  If we run the model and

3  we see that there are so many people that are leaving

4  and so many people that are not being counted that are

5  coming in, then that could be a problem.

6	DR. HENDERSON:    Jon, did you have your

7  hand up?  I...okay, Jon has...I know you have to leave

8  early, so let's get your comment while you're still

9  here.

10	DR. SAMET:    I mean, I had this one

11   general comment in my written remarks that it would be

12   really helpful if there was some sort of overview of

13   this cascade of models and assumptions so that readers

14   could approach this.  I read this several times, and

15   really struggled to kind of get the big picture,

16   because you immediately sort of leap into the details

17   of this model and that model, and this is all

18   strung...strung together, and I think you need a...sort

19   of a start-to-finish picture somewhere up front to help

20   the reader struggle with this...or not struggle so

21   much.  The readers will still struggle, but they won't

22   struggle quite as much but something up front.

23	DR. HENDERSON:    Thank you, Jon.  Now,

24   we're coming up the road.  Did Ed have his hand up?

25   No.

1  five, or you've done work on that, but does that

2  selection of city site, especially for California, do

3  you have problems with actually measuring accurately

4  NOx concentrations due to, perhaps, higher levels of

5  nitric acid in those areas?  Is that something that has

6  to be taken into account in...in this modeling, or is

7  that just not relevant?

8	DR. GRAHAM:    I...I'm not prepared to

9  respond to that.  I apologize.  I'm not an atmospheric

10   chemist.

11	DR. LARSON:    This is Tim Larson again.

12   If you...I mean, Christian probably...Ted knows this

13   better than I, but if you look at the distribution

14   large scale of NO2 across the Los Angeles Basin,

15   there's a considerable gradient from the coast at low

16   levels eastward towards Riverside on a very large

17   scale, and it's...it's...it's not easily represented by

18   even aggregating the traffic emissions.  You have to

19   run a more sophisticated analysis.

20	And in that particular case, if you

21   don't account for the...those large-scale gradients in

22   NO2, you can be spectacularly wrong, because

23   they...they overwhelm the near-road gradients in the

24   eastern part of the basin.

25	DR. ROSENBAUM:    So, that may be a

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1	DR. POSTLETHWAIT:    For once, no.

2	DR. HENDERSON:    Okay.  Lianne, then.

3  I'm just kind of coming up the road here.

4	DR. SHEPPARD:    Yeah, I'll make more

5  comments tomorrow, but I wanted to emphasize what has

6  already been said, is that you're focusing on the

7  extremes of the distribution in counting the

8  exceedances.  So, in all of this modeling and all of

9  this data analysis, you have to get the extremes right,

10   or you're not going to be counting it right.  So, it's

11   not anywhere near as easy a problem as it typically is

12   where we're trying to get an average.  We need to get

13   the extremes right.

14	And...and there's really no information

15   in the document to assess that, and there's lots of

16   reasons to believe that they're not right, and,

17   therefore, we're undercounting.  So, I'll make this

18   point again tomorrow, because that's basically what my

19   comments are, but I think that's probably the key point

20   about predicting exceedances, is that you've got to get

21   the extremes right.

22	DR. HENDERSON:    And Kent?

23	DR. PINKERTON:    This is just a point

24   that I'm just curious about.  You'd mentioned that in

25   the selection of cities that you've identified, perhaps

1  particular problem of that city.

2	DR. LARSON:    I think it's more acute

3  there than in most areas.

4	DR. HENDERSON:    Okay.  I don't...oops.

5  Dale, did you have your hand up?  I didn't remember.

6	DR. HATTIS:    I...I have a...well, I'm

7  going to have a lot to say tomorrow, but just to...

8	DR. HENDERSON:    Now, when you say

9  tomorrow, are you talking about for air quality?

10   Because tomorrow, I'm thinking we'll go to exposure and

11   health effects.

12	DR. HATTIS:    Yeah.

13	DR. HENDERSON:    Okay, okay.

14	DR. HATTIS:    But because of the linkage

15   of...I got this in your notice that the table 26 for

16   the comparison of the three monitors was not

17   entirely...

18	DR. HENDERSON:    Get close to the mike.

19	DR. HATTIS:    ...was not entirely

20   unambiguous, let's say, first, are those the only three

21   monitors for which you've done comparisons?

22	DR. GRAHAM:    Yeah, those...those are the

23   only three monitors that are within Philadelphia

24   County.

25	DR. HATTIS:    Oh, is that right?  So,

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1  those were the only three monitors that were available

2  to you, in fact.

3	DR. GRAHAM:    In Philadelphia County,

4  right.  There was another table in there that was in

5  error.  It had like ten monitors or something like

6  that.

7	DR. ROSENBAUM:    The ten monitors

8  were...were for the whole CMSA, but we didn't model the

9  whole CMSA.

10	DR. HATTIS:    Okay, and what I saw was

11   just one number per year per monitor which suggests

12   that it's...what you're comparing is long-term

13   averages.  Is that right?

14	DR. ROSENBAUM:    Yes.

15	DR. HATTIS:    I mean, it seems to me you

16   could have compared the distribution of hourly

17   concentrations that was observed at the monitor with

18   the distribution of hour...of hourly concentrations

19   that was predicted for that monitor.  Then, that would

20   be a different kind of comparison.

21	So, I mean, I think that would be

22   something that would be, I think, of interest, but I'll

23   say that later.

24	DR. HENDERSON:    And Ed?

25	MR. AVOL:    So, I have a couple of

1  that if you don't have some credibility and confidence

2  that they relate well at the outset, then all these

3  adjustments and everything are...sort of put you

4  further away from the...from the truth, and it's hard

5  to believe where you're going.

6	DR. ROSENBAUM:    Well, as far as the off

7  road, I guess we assumed that that would be more

8  dispersed, just like the local traffic, so that it

9  wouldn't be necessarily creating hot spots, and we

10   were...we were really trying to just focus on that.

11	As far as the shipping is concerned, we

12   did look into doing that, but we didn't really have a

13   good emission inventory for the port there.  So, it

14   was...that was like a data limitation to looking at the

15   port.

16	MR. AVOL:    And rail is not part of the

17   equation?

18	DR. ROSENBAUM:    The rail...the rail was

19   also a data limitation.  We did have the...the NEI has

20   the county level estimate for rail...for rail yards,

21   but there were several rail yards, and then we didn't

22   know how to...we didn't have the information to

23   allocate, spatially allocate among the rail yards, so

24   that was another data limitation issue.

25	MR. AVOL:    And I thank you for the

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1  questions.  In fairness and disclosure, I should say

2  that conversations I have with air quality modelers are

3  sort of like an audience with the great and powerful Oz

4  in that it seems like a lot's going on behind the

5  curtain that I don't quite see or understand.  So, I

6  just...let me ask you some questions about what's going

7  on in front of the curtain, and this gets at some of

8  the questions that I think Jon Samet raised about

9  visibility and credibility and confidence about a

10   bigger picture about what's going on.

11	And so, one question or...or statement

12   that you could consider is in terms of the inventory

13   comparison, you talked about using some fugitive source

14   information and...and on-vehicle...on-road vehicle and

15   stationary sources and airports, I guess, the airport

16   information.

17	And so...so, relating from Los Angeles

18   and the California experience, it seems like the other

19   large sources such as off-road construction, chipping,

20   et cetera, I don't know how important that is in

21   Philadelphia per se, but the question would be how

22   the...your inventory compared, when you just used that

23   subcategory that you used, how that compared with the

24   AQMP for the area or the inventory, the best emission

25   inventory, that exists, and if that...it seems to me

1  comments about the major road assignments and this

2  issue about, you know, not being able to deal with

3  smaller category roads does raise some issues, and,

4  again, when you get to Los Angeles, it will be an

5  issue, although if you go down to 15,000 vehicles, it

6  will cover a lot of roads in Los Angeles.

7	But I do have a question with regard to

8  your model, and this gets some...some at what Christian

9  raised which is how well it fits and...and getting to

10   your concern about trying to identify hot spots as to

11   with air modeling and the adjustments you make, whether

12   you take into account topology or land use or other

13   issues like this which may well change the character of

14   where those hot spots show up.

15	DR. ROSENBAUM:    We did for the...when we

16   modeled the elevated sources, we did use terrain

17   elevation.  We didn't for the roadways, because

18   it's...for ground level sources, it's terrain

19   following, so it didn't really make a difference.  It

20   wouldn't...it shouldn't make a difference there.

21	MR. AVOL:    Okay.  And then, one comment

22   with regard to boundary domains, talking about

23   Philadelphia County.  I think Los Angeles is an

24   important area to take, but...but because of this issue

25   that George raises about commuter traffic, in Los

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1  Angeles, that's a big issue, and I'm not sure what the

2  domain is going to be when you characterize that, but

3  it's...it's a...a key ingredient to that is, you know,

4  commuter traffic daily into and out of the...whatever

5  the central area is that you're going to talk about

6  defines Los Angeles.

7	Finally, I just want to comment on...on

8  the table in terms of of...there was some comment about

9  uncertainty and analysis, and I appreciated table 16 on

10   page 65 in terms of talking about the different sources

11   of uncertainty in the air quality measurements and how

12   to represent.  I think it's helpful to identify that,

13   but I found it sort of frustrating that it sort of said

14   none, a little, or a lot, sort of, and the nature of

15   the magnitude of the errors.

16	And so, I was sort of left well, I

17   appreciated it identifying the sources, but I wasn't

18   quite sure what to do with this.

19	DR. GRAHAM:    Right, I...I appreciate

20   that comment, and I would say that there needs to be a

21   little more rigor there.

22	DR. HENDERSON:    Okay, are there people

23   on this...on my blind side?  Yes, Ron?  We'll go down

24   this whole...oh, I'm so sorry.  Terry?

25	DR. GORDON:    I guess the modeling by Oz

1	DR. WYZGA:    I have three comments.

2  First of all, I do want to commend you.  I think this

3  is an awful lot of work here, and I was very impressed

4  with the quality of the work.  I think you...I think

5  it's...I really appreciate it.

6	First comment was when I think of just

7  meeting the standard, it appears that what you've done

8  is, in a sense, created an upper bound with a number of

9  exceedances with rollup never being used, and I

10   wondered if it might make sense to come up with a range

11   estimate, and that would be the upper end, and the

12   lower end might be...it essentially would equate to the

13   as-is scenario, because it essentially would say that

14   where you've exceeded the standard, you would lower it

15   so that the standard is satisfied otherwise as is, and

16   if a range estimate might be, in fact, more realistic

17   than what you presented.  That...that was my comment.

18	And then, the second question was, I

19   guess, motivated by what Lianne said.  Are you really

20   trying to portray an extreme case, or are you trying to

21   portray something that's representative?  And...and

22   it's unclear in my mind.

23	DR. GRAHAM:    For which analysis?  I

24   mean, if you're considering we're estimating exposures

25   using exposure modeling under situations where

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1  has...has confused me, but not it's enlightened it.

2  The figure we have in the pie chart when you have in

3  the benchmarks of 200, 250, and 300 on page 117, to get

4  up to 300 ppm, the person is barely sleeping and

5  spending almost as much time outside in the parking lot

6  to get the 300 ppm.  So, given all the questions from

7  this table, I wonder about the modeling.

8	DR. GRAHAM:    Right, no, I...I think it's

9  maybe not explained clearly in the legend.  This...this

10   has to do where those peaks occurred.  It's not

11   suggesting that they spent more time there.  That's

12   where they ended up with the peak occurrences.

13   That...that's what it's speaking to.

14	DR. GORDON:    Okay.

15	DR. HATTIS:    The peak hour was located

16   differently.

17	DR. GRAHAM:    Right.

18	DR. GORDON:    But it's this fraction of

19   time all simulated persons in Philadelphia County spend

20   in these 12 environments.

21	DR. GRAHAM:    And receive that exposure

22   above the particular health benchmark.

23	DR. HENDERSON:    So, you might clarify

24   the legend if...not clear.  Okay, then we go down.

25   Ron?

1  conditions exist as is, I think we're trying to

2  represent exposures as they exist for the year 2001

3  through 2003 in...in that area, but then when we

4  simulate the standard, that's where it changes.  I...I

5  guess I'm not clear about what the question.

6	DR. JENKINS:    Well, one issue that you

7  might...that might not be totally clear is the purpose

8  for simulating just meeting the current standard, and

9  one of the things that we try to do in the review from

10   the big picture perspective is we try to evaluate the

11   level of public health protection that's associated

12   with an area that would be just meeting that standard.

13	So, you know, when we get into talking

14   to our management, one of the things they're going to

15   ask us is well, what happens at the current level of

16   the standard?  And so, we do these types of simulations

17   to...to look at what might happen if an area just meets

18   that standard.

19	So, we're really just looking at the

20   level of public health protection.  It wasn't...and I'm

21   not sure.  I think this could be sort of a source of

22   confusion for you which...is that...does that offer any

23   clarification for...

24	DR. WYZGA:    It...it does, but it

25   just...it's...it just seems very unrealistic, and you,

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1  in fact, say so in the document.

2	MR. RICHMOND:    Right, we certainly have

3  said we will make it clear in the document that it is a

4  hypothetical situation for what protection there would

5  be if you just met the standard, and there's no

6  intention to try to do risk reductions from that.  In

7  other words, once we get to the second phase of

8  alternative standards, we're not going to look at risk

9  reductions from the current standard to these

10   alternative standards, but it is what protection you

11   would have if you just met the standard.

12	Doing an as is which is well below all

13   the areas we've looked at and...and in the country are

14   well below, fortunately.  We've had a lot of progress

15   on NO2 reduction...NOx emission reductions.  To say the

16   lower bound is the as is situation, that would not be a

17   lower bound for air quality that would be allowed where

18   you'd just meet the standard.

19	And so, I didn't agree quite with that

20   being a lower bound.  We're certainly presenting as is

21   and will characterize those levels are considerably

22   below the current annual standard.

23	DR. SHEPPARD:    Can I speak up for a

24   second?

25	DR. HENDERSON:    Sure, go ahead, Lianne.

1  difficult, we agree.

2	DR. SHEPPARD:    Extremely.

3	DR. HENDERSON:    Okay.  Jim?  James?

4	DR. CRAPO:    I still have a question that

5  I just don't...or maybe a comment, but it seems like

6  the key thing we're trying to get at in this modeling

7  is sort of illustrated in figures 9, 10, and 11 where

8  you're looking at number of people at risk for a

9  certain exceedance, and as I read this and as I listen

10   to all the comments, one of my questions that I'd love

11   to see estimated in here is if you can find any way to

12   express the confidence interval we have around that.  I

13   know you can't calculate a real confidence interval,

14   but the...but it's the kind of thing Ed was bringing

15   up, that the level of accuracy needs to be somehow

16   incorporated into this more than just in the paragraph

17   that says we had all these assumptions.

18	And it's important for a couple of

19   reasons, because I think when people see these tables,

20   there's a tendency to say well, that's what it is, and

21   now you multiply that and count the number of people

22   that I can do something with health on, and...and some

23   expression of the confidence interval would be helpful.

24	And the other thing it might really do

25   for you is help you understand how many cities you want

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1	DR. SHEPPARD:    I just wanted to follow

2  up, because the..the summarization of the data is based

3  on exceedances at the hourly level.  So, in that sense,

4  it's...it's definitely about the extremes of the

5  distribution, because you're looking at the number of

6  high values that you're simulating.

7	So, you know, while...while you may be

8  focusing on meeting the stand...or, excuse me, as is

9  that's well below the standard, that's an annual

10   average, but everything you're summarizing is based on

11   hourly data and tallies of exceedances, and when you're

12   getting, you know, for thousands of measurements,

13   you're getting one and two numbers, you know, numbers

14   of that size, you're talking about the extreme of a

15   distribution very far out on the tails.

16	MR. RICHMOND:    Right, because we're

17   trying to relate it to...this is just relating for the

18   clinical based health endpoints where the effects are

19   on that scale.  So, I mean, that...that's why.  That's

20   the motivation for that.

21	DR. SHEPPARD:    Right, but it

22   becomes...the modeling exercise changes dramatically

23   when you focus on the tails than when you're focusing

24   on the mean.

25	MR. RICHMOND:    Sure, much more

1  to...want to study, because you've got to estimate

2  whether you could really improve that with ten cities

3  versus two or three.  I mean, once you've done

4  Philadelphia and Los Angeles, if our confidence

5  intervals are just huge around these things, you

6  maybe...you may have made your point, and there may not

7  be any value in doing more if your air margins are too

8  large, and it kind of sounds like they might be from

9  what I'm hearing on all the assumptions.

10	I just throw that out, as I'm curious

11   how you...how you respond to that or could you figure a

12   way to express something of that nature.

13	DR. GRAHAM:    It's something we are going

14   to investigate how, because we do take those comments

15   to heart, and it's not something we've finalized right

16   now.

17	DR. CRAPO:    Yeah, I don't have any

18   concrete way to do it myself, but I...but I think it

19   would probably lead me to decide you want to do...it's

20   really valuable to see what this tells you, but you

21   might not get a lot more information after you've done

22   it a couple of times.

23	DR. GRAHAM:    Yeah, we've had some

24   discussions recently about some sensitivity analyses

25   that we can perform to try and get at that number

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1  you're looking for, the...these intervals.  So, we're

2  going to look into that.

3	DR. CRAPO:    Okay.

4	DR. HENDERSON:    Okay.  I don't see any

5  more hands.

6	One thing I want to ask the people from

7  the Air Office.  I chose, because of the number of

8  charge questions you had listed under three different

9  areas, to just look at one area at a time.  If...in

10   looking through these charge questions for the air

11   quality information, it seems to me we've addressed

12   most of them, but I'm going to ask you, is there

13   anything in here that you wanted to know from this

14   committee that we have not addressed?

15	DR. JENKINS:    I don't think so.

16	DR. HENDERSON:    One thing, Christian,

17   you're going to be the one who's summarizing all this,

18   and there are six charge questions.  I listened, and I

19   think they were all addressed in some way, but because

20   we had so many people commenting on this other than

21   just the...the few that were assigned to look at it, I

22   think Christian would probably enjoy your sending, you

23   know, your comments, what you think is really critical

24   to him so he can develop a paragraph.

25	Now, you tell me, Christian, would that

1  part of this document.

2	DR. NUGENT:    And, Rogene, if I might

3  add, could everyone also cc me on that so I can have

4  a...be a switchboard?

5	DR. HENDERSON:    Definitely, cc it to

6  Angela.  I mean, you want to send it to Angela and cc

7  me, because she is the one who will be pulling them

8  together.

9	As far as the...your pre-meeting

10   comments, everyone should know that whatever letter

11   goes to the Administrator, we attach your comments

12   unedited, too.  So, if you want to change anything that

13   you've written in the pre-meeting comments, just change

14   them and send them to Angela, and when we do send it

15   in, that's what will be attached.

16	You have quite a bit of time for that,

17   because it will take us a while to come to...I mean,

18   the last date on this, is what, May something.  May

19   what?  You all have the thing, but I just want to know

20   if you...your pre-meeting comments, if you want to

21   modify them, modify them, and your individual comments

22   always go with the letter, and they're very important.

23   They contain a lot of detail that we don't have the

24   time to discuss in the meeting, so be sure you do that.

25	And, okay, we've got something from...

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1  be helpful to you?

2	DR. SEIGNEUR:    Yeah, that would be

3  useful if people send me an email with their comments.

4	DR. HENDERSON:    Okay.

5	DR. SEIGNEUR:    My email address is my

6  last name at aol.com.  You can do that tonight.

7	DR. HENDERSON:    Yeah, Ted?

8	DR. RUSSELL:    If I might, actually, I

9  think all of us who are writing up any part, I mean,

10   certainly, I would like the same for the participants

11   on my ques...my part on the ISA.  So, I think just...I

12   don't know.  I wouldn't mind getting them tonight, if

13   possible.

14	DR. HENDERSON:    That has happened in the

15   past where we've done it overnight, and then we...and

16   it really facilitates things.  So, if you have

17   something for a lead discussant on any of these issues

18   that would be helpful in them developing the paragraph,

19   go ahead and get it to them like tonight, if you can,

20   because it can...now is the time when they can be

21   working on their laptop and...and doing their thing.

22	So...and I really like the way we did it

23   when we just did it overnight.  So, why don't we try to

24   do that, and we will develop as much of our writing as

25   we can, covering both the first document and the first

1	DR. GRAHAM:    Thank you, Rogene.  There

2  was one thing on the air quality characterization.  In

3  the comments, I think it was Tim Larson had suggested

4  that we review some of the literature on street canyons

5  to improve the exposure estimations.  I mean, in a

6  sense, what we've done has not necessarily taken those

7  into account.  So, to derive some sort of a

8  relationship between the street canyon exposures and

9  that would...would occur on a typical roadway, I...I

10   would be interested if he could refer to me to some of

11   those...those citations, that would be wonderful.

12	DR. LARSON:    I can't hear.  You're

13   breaking up.

14	DR. HENDERSON:    Tim, did you hear that?

15	DR. LARSON:    I didn't hear the last

16   part.  Sorry.

17	DR. GRAHAM:    Yes, I was sug...yeah,

18   there you go.  I was requesting if you had some

19   specific citations for the street canyon information as

20   far as a relationship, that would be wonderful.

21	DR. LARSON:    Yeah, I think there are

22   four of them in my written comments, some recent

23   summaries, some recent papers.  Look at those as well,

24   and I can...I can send something on to a Angela for Ted

25   as well.

1	I mean, there's this really nice...I may

2  have mentioned it before, but there's this really nice

3  Danish THOR system, it's called, air GIS that has a lot

4  of supplemental information but is an operational model

5  that's already implemented in numerous cities

6  throughout Europe.

7	DR. HENDERSON:    Okay, and as I said, try

8  to get your...your comments in to the lead discussants

9  tonight, if at all possible, and we meet at 6:15 if you

10   want to go eat with us.  And we start tomorrow morning

11   at what time?  8:30, and we do have our breakfast.

12   Right?

13	SPEAKER:    Can we leave things in this

14   room overnight?

15	DR. NUGENT:    Yes, it will be locked up.

16   I wouldn't leave your laptop materials.

17	DR. HENDERSON:    And thank you for a good

18   day's work.  I think we did a good job today.

19   (WHEREUPON,   the SESSION   was concluded at 4:47 p.m.)

20

21

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25

1	CERTIFICATE OF REPORTER

2  COMMONWEALTH OF VIRGINIA

3  AT LARGE:

4  I do hereby certify that the witness in the foregoing

5  transcript was taken on the date, and at the time and

6  place set out on the Title page hereof by me after

7  first being duly sworn to testify the truth, the whole

8  truth, and nothing but the truth; and that the said

9  matter was recorded stenographically and mechanically

10   by me and then reduced to typewritten form under my

11   direction, and constitutes a true record of the

12   transcript as taken, all to the best of my skill and

13   ability.

14   I further certify that the inspection, reading and

15   signing of said deposition were waived by counsel for

16   the respective parties and by the witness.

17   I certify that I am not a relative or employee of

18   either counsel, and that I am in no way interested

19   financially, directly or indirectly, in this action.

20

21

22

23

24   CHARLES DAVID HOFFMAN, COURT REPORTER / NOTARY

25   SUBMITTED ON MAY 01, 2008

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1	CAPTION

2

3

4  The foregoing matter was taken on the date, and at the

5  time and place set out on the Title page hereof.

6  It was requested that the matter be taken by the

7  reporter and that the same be reduced to typewritten

8  form.

9  Further, as relates to depositions, it was agreed by

10   and between counsel and the parties that the reading

11   and signing of the transcript, be and the same is

12   hereby waived.

13

14

15

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0

0.2 229:1,4,6

0.26 228:20

0.3 229:1,4,6

053 17:1 199:22

200:1

06 41:10

07 41:11

08 221:19

1

1 2:5 47:5,9 48:3

49:1 50:23 56:15

62:18 63:12

76:20 117:14

143:11 235:18

265:2

1.2 108:21

1.2...you 108:17

1.5 18:17 225:21,22

242:9

1.6-1 57:11

1:00 138:17,23

10 24:11

191:17,21 251:19

256:2,24 258:23

264:6 277:22 292:7

100 75:17 161:7

254:15 256:11,21

257:16 259:8

10s 256:10

11 147:5 292:7

113 192:22

117 287:3

11th 217:5 219:15

12 205:19 287:20

120 62:2

13 142:13

14 42:16

15 16:24 38:12,17

67:5,7 146:3

208:18 277:22

15,000 245:1 285:5

15-minute 219:7,25

16 286:9

16-2 192:21

16th 216:21

17 42:10 44:1

17,000 225:24

247:24 263:12

264:1

18 42:12 75:15

238:9,13,15 262:9

1964 58:19

1965 53:12

1976 117:13 142:10

1992 145:22 146:13

1993 142:11

1995 36:18

1998 38:12

1-hour 226:5

2

2 15:21,22,25

63:20,24 68:16

77:16,21 84:23

108:11,16,22 143:7

243:22 251:19

253:19 256:5

267:11 271:2,8

2.4.5 67:21

2.5 19:19 28:11

191:17,21 195:8

2.5.4 68:20

20 142:14 144:25

208:18 253:10

200 128:11 161:7

197:9 200:6 227:10

228:11 229:16,17

236:6 261:9 287:3

2001 225:23 231:1

289:2

2002 35:6

2003 16:23 35:6

225:24 231:1 289:3

2005 16:23

2006 152:25 227:4

2007 54:24

2008 2:5 54:25

70:20

21 173:23

23rd 216:22

24 39:24 179:10

241 19:20

24-hour 199:25

208:20

25 24:13

250 228:11 236:19

287:3

26 16:19 104:14

243:7 281:15

28 208:19

29 142:2,15

29th 43:8

3

3 20:5,16,17 35:6

68:13 77:18

143:8 173:18

174:15 190:23

243:16,22

3.11 96:15

3.1-1 108:5,23

112:1

3.12 96:10 141:3

142:22

3.1-2 104:17

105:2 112:13

3.4.5 115:14

3:00 219:25

30 142:2,16 229:1

243:13