U.S. ENVIRONMENTAL PROTECTION AGENCY

SCIENCE ADVISORY BOARD STAFF OFFICE

CLEAN AIR SCIENTIFIC ADVISORY COMMITTEE (CASAC) OXIDES OF NITROGEN (NOx)PRIMARY REVIEW PANEL

PUBLIC MEETING

MARRIOTT AT RESEARCH TRIANGLE PARK

4700 Guardian Drive

Durham, North Carolina 27703

MAY 2, 2008

2

1	U.S. ENVIRONMENTAL PROTECTION AGENCY

2	SCIENCE ADVISORY BOARD STAFF OFFICE

3		CLEAN AIR SCIENTIFIC ADVISORY COMMITTEE (CASAC)

4		OXIDES OF NITROGEN (NOx)PRIMARY REVIEW PANEL

5	May 2, 2008

6	DR. HENDERSON:	Welcome, everybody, back

7  for our second day.  We think we're in pretty good

8  shape time-wise, we finished our air quality discussion

9  for the REA yesterday, so I think we can, excuse me,

10   start with a discussion of the exposure analysis

11   section.  It looks like we may have time, as we go

12   through, we want to discuss this, all of this in great

13   depth, but later in the morning we may have time to

14   start writing up some of our consensus replies to the

15   Administrator, so you might keep that in mind.

16	But let's start off with our discussion

17   of the exposure analysis section and Pat Kinney, who

18   just joined us, will lead, hi, Pat, will lead us off.

19	DR. KINNEY:	Okay, get right into it

20   here.  I wasn't sure how far you'd gotten yesterday,

21   'cause I was teaching yesterday afternoon. I'm sorry I

22   wasn't able to be here in person yesterday or even on

23   the phone for very long.  So my understanding, my

24   assumption is that we're talking about Chapter 7 of the

4

1  checked out some rates for Philadelphia, I think the

2  rates that were used, which came out to be around 17

3  percent for childhood asthma, is a pretty good number

4  from what I could tell, but it raised that sort of

5  general generic issue of how specific, how

6  geographically specific the data are that are used in

7  the exposure assessment.  I think it applies to other

8  aspects of it as well, not just, not just the asthma

9  question.

10	You know, I'm thinking about sort of the

11   fine field geography of a place like Philadelphia and I

12   know that the economic and racial patterns are pretty

13   distinct there like they are in many other cities, and

14   I just wanted to make sure that the staff who are doing

15   the risk assessment keep in mind potential unique

16   aspects of the inner city that may impact on their

17   exposures and health risks due to NO2.  Not only, you

18   know, are asthma prevalence rates greater in some inner

19   city neighborhoods but also there might tend to be

20   simultaneously higher than average exposures to traffic

21   emissions on roadways.  I know from my experience in

22   New York that people that live in the city spend a lot

23   more time commuting by foot and along roadways, and to

24   the extent that those sidewalk commutes are not

25   accounted for in the exposure assessment, that is a

3

1	DR. HENDERSON:	It's surely Chapters 5

2  and 7, and I think answering the charge questions under

3  the--

4	DR. KINNEY:	Okay, so I'll go through

5  my chart the way  I've answered those charge questions.

6  Overall, as I say in my written comments, I thought

7  this was a really good effort by, by staff at EPA.

8  Very comprehensive, technically sound, the writing is

9  very, is very clear, and the interpretation of the

10   results I think are quite good.  There are of course,

11   you know, some areas where any critical reviewer will

12   find areas for improvement and I certainly did as well.

13   One of the fundamental issues in terms of the, I guess

14   this comment mainly focuses on Chapter 7, and the order

15   of my comments was sort of structured around the charge

16   questions rather than sort of being sequentially going

17   through the document.

18	So the issue of focusing on asthmatics

19   as a sensitive subpopulation I thought was very

20   reasonable, given what we know about health effects.

21   In my initial review I was not clear about whether the

22   asthma prevalence that was used for the exposure

23   assessment work was based on sort of Philadelphia inner

24   city asthma rates, I went and when I dug into the

25   technical support document and also went online and

5

1  source of potential underestimate of some of the

2  extreme exposures.

3	So if it can be done, it should be, and

4  if it can't be done it should just be discussed as an

5  uncertainty that, you know, goes at the end of the

6  document.

7	Another thing, along those lines is air

8  conditioning prevalence,  which I wasn't clear from the

9  discussion whether sort of average regular air

10   conditioning were used or whether, you know, sort of

11   urban specific rates, inner city specific and income

12   specific rates, where you just, 'cause that'll impact

13   the indoor/outdoor relationship, and it may be the

14   indoor/outdoor relationship would be somewhat stronger

15   in the inner city if air conditioning is not as

16   prevalent.

17	So that sort of stuff, the kind of

18   questions where we try to really understand all these

19   exposure determinants and also risk determinants on a

20   finer SES, racial scale in a city I think is important

21   to think about, either to directly model it or else

22   just discuss it as an uncertainty.

23	The question of modeling of the air

24   pollution concentrations based on stationary and mobile

25   sources I thought was very well done for the most part

6

1  and appropriate, using the best available models.  I

2  think that I was a little, I had a question about the

3  reliance for the mobile source emissions only on major

4  roadways as opposed to all roadways, and I'd like to at

5  least know in the, in the main document to what extent

6  that, the omission of the non-major roads results in

7  potentially any downward bias or exposure for the,

8  again, in the urban corridor where there may be lots of

9  roads where people drive but maybe they're not, they're

10   not called major roadways, so I just want to make sure

11   those are accounted for.  Or if they're not, give us

12   some discussion about, you know, how much, how big of

13   an issue that might be.

14	In terms of microenvironments that were

15   chosen for the apex modeling, I think they make good

16   sense. I was unclear about and I think in looking more

17   carefully at the technical support document, I think it

18   became more clear that pedestrian, a pedestrian

19   microenvironment I don't think was explicitly modeled,

20   and again, going back to what I was saying before, the,

21   you know, I'm thinking about kids walking from their

22   apartment to their school or taking the bus to their

23   school, I don't think it's fair to necessarily just

24   assume that the exposures they receive during those

25   commuting times are the same as the home exposures,

8

1  7 or section 7 and the same is true I think at the

2  beginning of section 5  and section 6, that we need to

3  have, particularly section 6, we need to have sort of

4  a, more of a background, a conceptual discussion about

5  what, what the context is for the analysis that's going

6  to be presented.  It sort of jumps right into

7  methodology without, without really helping the reader

8  understand how these, these two major analyses, the one

9  in chapter 6 and the one in section 7, how they relate

10   to the overall question of assessing risks of NO2.  So

11   we need the context, the rationale for the particular

12   approach and then in the objectives of that and then go

13   into the method, which is, which is very well

14   described.

15	So I think that's it for now.  The rest

16   are just detailed comments.

17	DR. HENDERSON:    Thank you, Pat.  Is Doug

18   Crawford-Brown on the phone today?

19	DR. CRAWFORD-BROWN:    Yes. I'm here.

20	DR. HENDERSON:    Great, Doug.  It's time

21   for your comments on the exposure analysis chapters.

22	DR. CRAWFORD-BROWN:    Okay, give me just

23   a second here, I got to open up that file, I closed it

24   down a second ago.  The first thing, while I'm getting

25   it open here, the first thing I'll say is that I

7

1  both because they're at lower elevation and they're

2  also more likely to be along roadways, where cars are

3  emitting NO2, NOx and NO2.

4	I think the uncertainty assessment was

5  quite, quite good as a first effort, I'm sure that that

6  section will expand as, as more and more comments are

7  received, but I thought it was a really good first

8  effort to think about comprehensively all the

9  uncertainties that are present in the analysis.

10	I concurred with the staff decision to

11   base the risk assessment work on the chamber, human

12   chamber study results for choosing the benchmarks.  I

13   thought there was a good discussion about the

14   epidemiologic work. I tend to agree that for this kind

15   of analysis and the, because of the problems with

16   co-pollutant confounding in the epidemiologic studies

17   that it's really hard to figure out how to isolate an

18   NO2 effect from those studies.  And so although I'm

19   certainly interested in hearing what others think about

20   that, but I, so I concur with the decision that was

21   made to, to stick to the chamber results in this

22   particular part of the document.

23	Then I think beyond that it's largely a

24   series of specific comments, there is one general

25   comment that I think occurs at the beginning of chapter

9

1  actually found it to be a well described plan if you

2  have knowledge of what is a relevant ambient

3  concentration to use.  So I think what I'll focus on

4  here is that if we know the ambient concentration, then

5  it's possible through the plan that they've laid out to

6  get a good estimate of the individual exposure and the

7  whole population exposure.  The problem that obviously

8  arises is, and I don't know how they're going to deal

9  with this, the difficulty of figuring out exactly what

10   that ambient level is.  I saw two ways of doing it in

11   there.

12	One way is the, the use of the

13   monitoring results, the other way is the use of this

14   sort of first principle approach, where you actually

15   have source streams, inventories, and dispersion and so

16   forth.  And when I originally read through, I was, as I

17   mention in my comments, I was originally thinking that

18   the monitoring results became a kind of input into the

19   more person specific variability analysis that was

20   done, it was pretty clear to me after about two-thirds

21   of the document that I was mistaken about that, that

22   the monitoring results are an alternative way, as far

23   as I can tell, an alternative way of getting at the

24   exposures of the population based solely on ambient

25   exposures.

10

1	So one thing I'll ask the EPA is just

2  to, if they can just make sure that I'm absolutely

3  right about that, that the monitoring results are one

4  way of doing it , and the second way, which does the

5  individual exposures

6  is instead based entirely on first principles, but in

7  any event, I had sort of thought that those two might

8  have been at least compared against each other, or the

9  recommendation was that they would be compared against

10   each other and perhaps the comparison might be used in

11   a kind of uncertainty analysis.

12	DR. HENDERSON:    Would you like for the

13   EPA to --

14	DR. CRAWFORD-BROWN:    And I didn't see

15   that.

16	DR. HENDERSON:    Doug, would you like for

17   the...

18	DR. CRAWFORD-BROWN:	Let me stop with

19   that and just make sure, first, that I've understood

20   correctly that those are two alternative approaches.

21	DR. HENDERSON:	Okay, Doug, they, they,

22   they will tell you.

23	DR. GRAHAM:    Thanks, Doug.  Yes, I could

24   say they were two alternative approaches, but there was

25   overlap with the monitor information, the monitors that

12

1  correct that there literally are in the end two sets of

2  results that will come out, one will be a kind of

3  natural exposure scenario based on the monitoring

4  results and the other will be for the test cities or

5  whatever we would call them, a much more detailed

6  inter-subject variability distribution?

7	DR. GRAHAM:    Are you referring to the

8  comparison between the air quality analysis and the

9  exposure analysis?

10	DR. CRAWFORD-BROWN:    Yes.  Yeah, I was,

11   I wasn't -- my understanding was that, when I read it,

12   it sounded like the air quality analysis was an

13   alternative way of asking the kind of risk-based

14   question, right?  In the, in the air quality analysis,

15   I think what's being proposed is that there's a kind of

16   margin of exposure approach being used, where you look

17   at what fraction of the population is above some

18   ambient air concentration.

19	DR. GRAHAM:    Right, but in the air

20   quality analysis, there is no relationship between the

21   population that are, say, surrounding that particular

22   monitor, at least with the data that are presented

23   right now.

24	DR. CRAWFORD-BROWN:	Then I guess then

25   I didn't understand in the decision making process how

11

1  were within the Philadelphia county for the exposure

2  analysis, the more complex analysis, those monitor data

3  were used to adjust for local concentrations in the

4  dispersion model, air, air concentrations.

5	DR. CRAWFORD-BROWN:    In the sense of

6  being, of having the model results normalized against

7  the monitoring results?

8	DR. GRAHAM:    Right, that's correct.

9	DR. CRAWFORD-BROWN:    Okay, and, and is

10   there reasonable comfort that the monitoring results

11   are good estimates of ambient exposures for people,

12   because I thought we had this issue of the monitors not

13   necessarily being located at places that were

14   representative of actual exposures to individuals.  Oh,

15   I guess if you're going to do the normalization, it

16   doesn't matter whether the monitoring results are

17   representative or not, you're just mo -- you're, you're

18   adjusting the model to fit the monitoring results, but

19   you're not using those locations as the places where

20   exposures are getting estimated.  Is that right?

21	DR. GRAHAM:	That's right, but if there

22   were individuals that resided in that centroid, the

23   census block centroid, then those, those would be used.

24	DR. CRAWFORD-BROWN:	Okay.  Okay, so

25   I'm relatively comfortable with that.  Am I also

13

1  the chapter, what was it, I don't have it in front of

2  me here, how the chapter on air quality monitoring

3  results were going to be used to compare against the

4  inter-subject variability result.

5	It's, my understanding was that the

6  inter-subject variability result was going to be used

7  to ask what fraction of the population has a personal

8  exposure above some threshold value we'll call it, or

9  some sort of benchmark value. And, but I was reading it

10   and thinking that a similar thing was being proposed

11   for the air quality one, but instead of comparing it

12   against an actual personal exposure, there was going to

13   be a comparison against an ambient exposure level. But

14   maybe I'm wrong about that.

15	MR. RICHMOND:    This is Harvey Richmond.

16   The air quality analysis is not intended to address the

17   population -- it's not an estimate of population

18   exposure given of course all the time spent indoors,

19   given indoor sources, you know, given the different

20   location of people away from the monitors or on the

21   road, so I don't, you don't think we view those as

22   alternatives that should be compared.  I think there

23   was some discussion whether or not you wanted to

24   evaluate parts of the exposure model just in terms of

25   the air quality characterization, against the air

14

1  quality characterization, you know, in those two

2  elements, that's one thing, but we're not trying to

3  compare or say they should be compared, they shouldn't,

4  between the air quality characteri

5	DR. CRAWFORD-BROWN:	Oh, okay, I mean,

6  it may just be my reading of the document that at some

7  point I began to think that the, that there really were

8  two different ways in which you were going to go about

9  assessing the, the, the need for further controls, the

10   degree of exposure to the general population, and that

11   one was the use of the air quality results, the

12   monitoring results and one was this sort of first

13   principle,

14   but what I'm starting to hear now is that really the

15   air quality monitoring results are playing the role of

16   normalizing the more detailed stuff that goes on in the

17   chapter that I reviewed, which is the inter-subject

18   variability chapter.

19	MR. RICHMOND:    Right, well, they're also

20   looking at whether or not just at the monitors alone do

21   you have exceedances of these benchmarks, not answering

22   the question about what population, but it helps us

23   focus on what cities might have the potential just at

24   the monitors alone.

25	DR. CRAWFORD-BROWN:    Okay, well, I'm not

16

1	So I'm not going to push that any

2  further, I will say that there obviously is a point at

3  which you've shot past the reasonableness of the

4  resolution and this, as laudable as it is, is sort of

5  pushing the envelope on that.  And that's all I would

6  say.

7	DR. HENDERSON:    Thank you, Doug.  Dale?

8	DR. HATTIS:	Yeah, I have considerably

9  more difficulty with several aspects of the analysis.

10   One, and perhaps the most serious one was dealt with

11   yesterday with this adjustment for the changing of the

12   outdoor concentrations, the ambient concentrations,

13   while holding constant the effective amounts of the

14   indoor source-related exposures.   That appears to have

15   been dealt with, although it was certainly inadequately

16   described in the document.  That having been said, you

17   know, I still need to see that really fully fleshed

18   out, you know, in an altered write-up.

19	The second important problem relates to

20   the adjustment of the source plus dispersion model

21   predictions to correspond to the observed data from the

22   air quality monitors, which is what was, we started to

23   talk about yesterday.  The current comparison is based

24   on only three different locations where there were the

25   three available sets of monitoring data, but it was

15

1  going to push this anymore, I guess what I came at it

2  from the angle of a decision that was being made, I

3  just wasn't clear what role those two kinds of pieces

4  of information were playing in the decision, but I

5  guess what you're saying is you will provide that to

6  the policymakers, the decision makers, and it's up to

7  them to decide how to weight those two pieces of

8  information in in setting a sort of final standard

9  there.  So that makes me comfortable then.

10	The last thing I'll say is that, in a

11   remark that's similar to something I've made in some

12   other contexts on CASAC, I begin to wonder whether the

13   level of detail on inter-subject variability

14   distributions, as laudable as it is and as much as I

15   like running these sorts of models, shoots beyond our

16   ability to really make good estimates of these

17   inter-subject variability distributions.  So there's,

18   there's one part of me that says, well, yeah, just do

19   absolutely the best job you possibly can and generate a

20   whole inter-subject variability distribution, but

21   there's another part of me that wonders whether we've

22   shot past the level of resolution of inter-subject

23   variability by doing all of this, you know, census

24   block, census tract kinds of centroid analyses and then

25   putting in inter-subject variability distributions.

17

1  based only on long term averages, and that's just not,

2  because you're, you're really trying to model the

3  hourly concentration distribution and the hourly

4  ambient outside levels do drive, although they don't

5  correspond completely, but they do drive the indoor

6  concentrations through the air exchange rates.   It's

7  important that the distribution of hourly outdoor

8  concentrations after adjustment, you know, correspond

9  reasonably, so you, with the, with the predictions for

10   those monitors.  So you really must make the prediction

11   on the basis of the distributions of hourly

12   concentrations at the, the three monitors for which you

13   have observations and show that comparison, otherwise I

14   don't think that anybody should believe that you've got

15   the hourly ambient drivers correct.

16	Secondly, I'm pretty sure that a simple

17   additive adjustment will not be right.  I mean, I

18   expect that because conditions like, you know, the

19   turbulence of the atmosphere and things of that sort

20   likely to be exerting multiplicative influences on

21   concentration.  I bet you that you're going to be

22   better off with a multiplicative mode of adjustment

23   rather than an additive mode of adjustment of the

24   difference between the, whatever remaining difference

25   there is.  Now an additive mode of adjustment, you

18

1  know, could be expected if you, if you just, just, if

2  you're just adding sources essentially that you hadn't

3  modeled, but I expect that in fact you're going to need

4  to multiply this, this overall distribution.  Anyhow,

5  you'll have to see that by making the comparison,

6  showing the comparison, and showing that after you've

7  made your adjustment, the distribution that you get

8  corresponds to what's at the actual monitors.

9	If there's a huge difference in the

10   variance between your predicted hourly ambient levels

11   and your observed hourly ambient levels, then you need

12   to do something more fancy.  Now I'm not sure exactly

13   what that will be, 'cause I haven't got the comparison

14   in front of me, but clearly you're much more likely to

15   come to grief comparing the two distributions than you

16   are comparing the means, and there's, as we discussed

17   yesterday, there's some, there's some signals of

18   trouble in just comparing the means, because the

19   difference among the monitors is, as predicted by the

20   models is much different than the difference among the

21   models, monitors that's actually observed.

22	Okay, so that's the second issue.  The

23   third issue relates to the same correction in another

24   way, and that is basically when you're adjusting the

25   model predictions to the outdoor ambient

20

1  height adjustment comparing the expected concentrations

2  at the heights of the human receptors versus the height

3  of the monitors that you're using to calibrate your,

4  your exposure model.  So, so that's a, the third

5  problem essentially.

6	The fourth issue is the representation

7  of a few key sources of variability in the apex

8  exposure modeling, which inadvertently I think

9  artificially truncate likely distributions of

10   variability and certainly uncertainty. Some examples of

11   this, the first of the air exchange distributions are

12   contingent on temperature in the presence or absence of

13   air conditioning. Overall I don't have any objection to

14   the idea of using log normal distributions with very

15   broad limits in this case, .1 to 10 air changes per

16   hour.  However, the detailed results seem to show

17   different patterns with temperature in arbitrarily

18   blocked into a few ranges and I think you, there

19   doesn't seem to be any great consistency in the

20   observations that I saw , or a theory to say what it

21   should be like.  So a better description of the data as

22   a whole I expect might be produced by a more extensive

23   regression study using temperature and some transformer

24   of temperature as a continuous variable, either in a

25   fixed effects or a mixed effects modeling of

19

1  concentrations, you're essentially using the heights of

2  the outdoor monitors to adjust everything to, and what

3  you want to do is to make predictions at the heights of

4  the human receptors, which you have said, I think

5  reasonably are 1.8 meters above the ground.

6	So by not, by, by essentially correcting

7  the model predictions to the, to the monitor

8  observations, you haven't got the height adjustment

9  right.  So I would have you make the height, add in the

10   height adjustment for the particular monitors that

11   you've got, and that means you can't completely dismiss

12   the, I mean, the, the, currently the discussion in the

13   document, you know, makes a comparison that says, well,

14   not, most of the monitors aren't 15 meters, they're

15   mostly four or five meters and that's not such a big

16   difference.  I think you need to model that difference.

17   I think you need to model, and basically there's two

18   kinds of models that I, I try to use in preliminary

19   calculations, I try to use either a simple exponential

20   decline with height or more like a gaussian decline

21   with height, and, you know, your model itself probably

22   has vertical distance in it, so you might even have a

23   better way of making that adjustment from your aeromod

24   than I would just from first principles.

25	So anyhow, you do need to make that

21

1  differences among cities for the air conditioner

2  predictor variable.

3	Secondly, you've got a, NO2 removal rate

4  distribution, and I just completely object to the

5  narrow fixed limits used this removal rate

6  distribution, based on 6 values from a study in 1993 by

7  Schleisser.  The abstract of Schlesser's paper makes it

8  clear that all 6 observations were made in a single

9  house, and that there are additional complications from

10   the presence of HONO, an apparently lived NOX species.

11   So you've got to, basically, you just can't do a

12   uniform - between the limits - of those 6 observations

13   collected from a single house, you've got to expand

14   that distribution beyond that, even with a log normal

15   or more, or a broader distribution, depending on some

16   expert opinions- as to how broad, likely, the overall

17   distribution among real houses is likely to be.  Houses

18   are likely different in their contents, and they are

19   going to absorb at NO2 at different rates, and that

20   variability is totally missed in your current

21   representation of it.

22	The uniform distribution with its fixed

23   boundaries is particularly inappropriate, or it's

24   limited, as you can see.  I also strongly object to the

25   use of the uniform distributions of the concentrations

22

1  of NO2 from gas stoves.

2	The very breadth of the bounds were

3  derived coordinate, 188 parts per billion, argues

4  against the uniform distribution in favor of something

5  much more skewed, like a log normal.  Log normal

6  guarantees a positive contribution, but it doesn't have

7  the unfortunate property of implying a zero chance that

8  the things are outside those limits.  Also, if you are

9  in fact doing a, some sort of a mass balance type

10   model, then you should be entering this contribution

11   not in the form of a concentration, but in the form of

12   mass units. So you should have a certain number of

13   molls of Nitrogen Oxide produced per your cooking

14   events.  Because the concentration implications will

15   differ according to variability of your house,

16   characteristics and your air exchange rates and all

17   that, and that's not, you know, necessarily represented

18   by this range that you've got here.

19	So, that's, and finally, the assumption

20   that all the cooking events, contributed to the indoor

21   NO2, last exactly one hour, which appears to be what

22   you assume, I think, also, artificially limits the

23   variability of the NO2 inputs, and therefore, exposures

24   that are represented in the model.  So, if you're going

25   to do this presence type calculation, which I,

24

1  was excluded because it was incomplete, it was out of

2  the calculation.  And yet, the exceedances are going to

3  depend quite a bit on the monitor siting.  And, so I

4  just wasn't sure we could make enough sense out of

5  that.  Another problem, which I think you stated pretty

6  clearly earlier, is that the monitor distribution

7  doesn't really represent the population distribution.

8  And so, the counts don't, necessarily, align that well

9  with the population.  And, so I have a lot of trouble

10   with that whole calculation, and I'd like to see

11   something done that, at least, directly acknowledges

12   that the major differences in monitor siting

13   characteristics in counting exceedances, and how that

14   aligns with the population in some kind of a gross

15   sense.

16	With the apex modeling section, you

17   know, you all have been working with that model for a

18   long time, and you've made a lot of progress with it,

19   and I think that's really great.  There's obviously a

20   lot of assumptions in that, and the devil's in the

21   details, but it does look quite thorough, and it looks

22   like you've thought about a lot of the important

23   sources of variability, and the incorporation of the

24   day-to-day correlation of activities with individuals

25   over time, I think, is a really good new enhancement.

23

1  actually, counseled against in favor of a concentration

2  response function the last time we met, but if you're

3  going to do this, it's clear that the, you've got to

4  try to model the extremely high concentration tail of

5  the distribution as well as you possibly can.  And you

6  mustn't artificially limit the variability that's built

7  into the model in the ways that you've done so far.

8  That having been said, the adjustments are not so

9  difficult as to use some alternative distributions as,

10   you know, might first be implied.  I mean, so, 'cause a

11   lot of these things can be just changed as parameters

12   of the model, but you do need to rerun the model with

13   some altered sets of parameters described in these

14   variability distributions for the indoor exposures.

15	DR. HENDERSON:   Okay, thank you, Dale,

16   and Lianne?

17	DR. SHEPPARD:   So, as I mentioned

18   yesterday, my biggest concern is with variability,

19   because you're counting exceedances.  In, was it,

20   chapter five, the direct air quality analysis section,

21   where you're looking at monitors.  It appeared to me

22   that the monitors were treated as completely, or the

23   monitor years were treated as completely exchangeable,

24   so it didn't really matter what year, or whether the

25   monitor was near a road or not.  If, for instance, it

25

1  And, particularly important, when you're counting

2  exceedances and wanting to look within person.  So,

3  that's a good addition.

4	I had problems with the air mod

5  predictions.  Like Dale, I think that the simple

6  comparison of the means with the monitor means is

7  completely inadequate.  Here we're calcula-, we're

8  looking at the exceedances and relying on the

9  distribution, and then particularly, the tails of the

10   distribution, and getting the means to align is not,

11   necessarily, going to get the tails right at all, and

12   in particular, predictions tend to be a whole lot

13   smoother than the data in general.  And so, there's a

14   very high chance that you're under-predicting the

15   variability, and therefore, getting the tails wrong.

16   So, and then, we heard yesterday that several important

17   sources of variability of NO2 were left out,

18   suggesting, again, the variability's not being

19   captured.  So, I think the, that it's, there's a very

20   good chance we're undercounting because of the way the

21   modeling's being done, and that needs to be addressed

22   head on.

23	I had a couple other less important

24   comments.  I wasn't as clear about the diurnal cooking

25   pattern description.  And I was a little bit worried

26

1  that that smooths the exposure too much.  Let's see.

2  And this is, I think for clarity, I think it's

3  reasonable to say that exposures for asthmatics and

4  non-asthmatics are the same, state that up front, and

5  then, a lot of the language in 7.9 will be clearer, I

6  think, assuming that that's an assumption that people

7  feel comfortable with, stating explicitly.  So, I'd be

8  interested in your comments about the variability,

9  'cause I think that is crucial to counting exceedances.

10	DR. HENDERSON:   Okay, let's let everyone

11   make, anybody else who wants to comment on - -

12	DR. SHEPPARD:   Can we hear from, can we

13   hear from EPA first?

14	DR. HENDERSON:   That's, okay, you want to

15   hear that now, okay.

16	DR. GRAHAM:   And you mean specifically on

17   the air mod, the modification with the monitors and the

18   adjustment, is that what you mean?

19	DR. SHEPPARD:   I think that's a big piece

20   of it.  I'm also worried about the air quality analysis

21   as well with treating the monitors exchangeably, and

22   not representing population exposure, but the, so I

23   think that that, the variability of those monitors does

24   not necessarily align at all with the population

25   exposure, and that could be a problem.  And, also, from

28

1	DR. SHEPPARD:   But within those time

2  periods, there's not really a distinction about whether

3  how many monitors are included or excluded based on

4  siting characteristics.  So, I guess, at a minimum, I'd

5  like to see that distinction be made, because I think

6  that that matters.  The ones near roads are going to

7  have more exceedances than the ones that are not near

8  roads.  And in some ways, it's captured by the time

9  periods, because there were different, the sitings were

10   different in the different time periods.

11	DR. GRAHAM:   Yeah, in the TSD, I did

12   provide a table as an example for Boston, where we had,

13   whether the monitor was operating at a given year, as

14   well as whether it met the completeness criteria.  And

15   you can see that it is variable over time.  And

16   interestingly, I was looking at it the other day, and I

17   saw that, in fact, more monitors were determined

18   incomplete in the more recent time period than

19   previously, but consistently, there was probably about

20   thirteen monitors within any given year.

21	DR. HENDERSON:   So, Lianne, do you want

22   some more answers?

23	DR. SHEPPARD:   I think we need to hear

24   about the air mod, too.

25	DR. RUSSELL:   Yeah, particularly about

27

1  year to year, and city to city, which monitors are

2  sited near roads will matter in terms of what the

3  counts look like.  And that's all buried in this

4  analysis in a way that it's not clear.  But, yeah, but

5  the key question about the variability is really the

6  air mod.

7	DR. GRAHAM:   Right, but as far as the air

8  quality, I recognize that we did have, well, what we

9  did, I'll explain that first.  I mean, we broke it up

10   into these two five-year periods, recognizing that, of

11   course, there are going to be monitors that are

12   operating, or, perhaps, they didn't meet that valid

13   year criteria, so they would be, perhaps, in one year

14   and out the next year, which is why we grouped them

15   into these five-year periods, so we could, at least,

16   capture, or represent the area fairly well.  And that's

17   why the site years were considered the unit, rather

18   than, okay, well, this year, we had a different set of

19   monitors.  And then, we had this many exceedances, and

20   then the next year, we had possibly a different set of

21   monitors.  So, it was, really, to try and characterize

22   a time period in the region better than, you know,

23   doing it sequentially, because then we'd have less

24   monitors for each given year.  So, is that sufficient

25   for the air quality?

29

1  the variability.

2	DR. GRAHAM:   Yeah, and if you could

3  reframe the question, please.

4	DR. SHEPPARD:   So, when, in general, when

5  you predict, your predictions are smoother than the

6  data.  And you made an adjustment based on annual

7  average.  And your counting exceedances, which is

8  focusing on the tail of the distribution.  So, if you

9  don't get the whole distribution right, you're not

10   going to count the exceedances right, because you're

11   not, because the exceedances are up in the upper tail.

12   And so, the table 26, that compares the means, is not

13   targeting the aspect, I mean, it's an important aspect

14   of the distribution, but it's completely insufficient

15   for getting at the question about whether your

16   predictions are capturing the quantity of interest,

17   which is being able to calculate exceedances.

18	DR. ROSENBAUM:   Well, actually, we did

19   look a little bit at the comparing the variances, and

20   because we didn't model all of the sources, we only

21   modeled the on-road, the major roads and some of the

22   point sources, actually, the model variance is higher

23   than the monitor variance, because we applied a

24   temporal profile to the on-road emissions.  So, we get

25   this variant, we have an implied hour-to-hour variance

30

1  on the on-road emissions.  So, it, actually, it turned

2  out that, like I said, that the variance was higher

3  with the model results than the monitor results before

4  we made the adjustment.  But your point is well taken.

5  I mean, several people have said that, have pointed out

6  that it was a very simple adjustment we made for the

7  sources that weren't modeled.  And we should probably

8  go back and look at that, and we'll go look at that and

9  see if we can make a better adjustment that's

10   stratified in some way, either regionally or temporally

11   stratified to reflect that better, and to try to match

12   the variance better.

13	DR. SHEPPARD:   Yeah, I think it's

14   important to, when the summaries that show that you've

15   done a reasonable job need to talk about more features

16   of the distribution than just the mean, and

17   particularly, need to focus on that upper tail that's

18   so important.

19	DR. KINNEY:   One simple thing, this is

20   Pat.  One simple thing you can do, of course, is just

21   look at the full, you know, plot histograms of

22   concentrations for the observed and the predicted for

23   the given site over a year, that, of course, masks

24   what's really contributing to the variability.  So,

25   another thing you can do, in addition, is do some

32

1  buses to school.  We had personal monitors on them.

2  And we were monitoring fine particles, not NO2, but we

3  also were monitoring NO2 at the central, at the van

4  right there at their school.  And, again, what you see

5  is, and we were also monitoring traffic at the highway

6  right next to the, on the Major Deegan.  And when the

7  traffic was the greatest in the morning, we saw the

8  highest NO2 levels.  In the afternoon, we saw nearly as

9  high traffic levels, but not as high NO2.

10	Really, the highest levels of NO2 and

11   fine particles are in the morning, and that make sense,

12   because the wind speeds are lower, and the mixing

13   height is much lower in the morning.  And so that

14   morning, going to school in the morning is when these

15   kids get a big exposure.  And I think the model should

16   reflect that.  The second, I mean, in terms of ambient

17   exposures, that's a big time period for them.

18	The second thing is, you know, I just

19   want to step back from this an listen.  I've been

20   listening to Dale's comments and the others' comments,

21   and you know, I know that we were told that it's too

22   hard to do the epidemiology, but it seems the

23   challenges in doing these exposure estimates are far

24   beyond the challenges involved in the, doing, applying

25   epidemiology.  And then, of course, you're using data

31

1  representative diurnal plots of the model data and the

2  observed data to give the reader a sense of, you know,

3  how they, how similar they look in amplitude.  And

4  then, you know, people also do Fourier analyses, where

5  they disentangle the daily variance, the weekly

6  variance, and the annual variance, and thing, you know,

7  and are they rough, you know, you might do really well

8  on one part of the variance, but not on the other.  You

9  know, if they all do pretty well, that's very

10   reassuring.

11	DR. HENDERSON:   Okay, any more on that

12   point?  Now, are there any other comments on the

13   exposure analysis, yeah, George?

14	DR. THURSTON:   Well, a couple of things.

15   First of all, I wanted to agree with what Patrick

16   Kinney was saying about the morning exposures of

17   children.  And I think the document contained some

18   results that we published from our Bronx studies

19   showing the differential between the, our van at ground

20   level the measurements at the top of the school

21   buildings when we were doing those studies.

22	But, one of the things we observed, and

23   I'm sure this is documented elsewhere, that some of the

24   biggest exposures the children got was right around the

25   time they're going to school, walking and riding on

33

1  that don't consider the interactions with particles and

2  the real world, and you're not considering the broad

3  breadth of the population, which you consider in the

4  epidemiology.

5	The epidemiology has so many strengths

6  that it makes it just the most obvious.  And after

7  listening in the last hour, I just don't understand the

8  decision by the staff to not consider the epidemiology,

9  and to do risk assessments.  And, yes, you have

10   co-pollutant models, and, you know, I really feel

11   strongly that the single pollutant models are the way

12   to go for this.  You're supposed to do a conservative

13   analysis.

14	That's a conservative analysis, and you

15   have this, the co-pollutant models that show you that

16   it's robust to the inclusion of those, so it's not some

17   artifact.  I think it's the way to go, and everything

18   I've heard this morning, tells me that, it makes that

19   conviction even stronger.  Thank you.

20	DR. HENDERSON:   Frank?

21	DR. SPEIZER:   Well, I was going to make,

22   somewhat, the same point that George just made, in the

23   sense that I thought we weren't yet prepared to talk

24   about the health effects side of this.  And only

25   because Pat raised the issue that he agreed with staff

34

1  in doing, in not doing the epidemiology, I would argue

2  that we don't leave this hotel until we convince staff

3  that they must do the epidemiology side of the risk

4  assessment.  So, I would put that on the agenda as

5  saying, I am forcefully objecting to Pat's agreeing

6  with staff.  Now, if you want to talk about it now, we

7  can, or we may want to talk about it a little bit

8  later.

9	DR. HENDERSON:   We'll be sure and talk

10   about it later, but I'm glad you made the point.  Now,

11   is there any more, are there any more comments on the

12   exposure analysis?  Yes, Ed?

13	DR. AVOL:   I have two small comments,

14   really, questions for staff.  And that is, with regard

15   to the emission strengths and functions that were

16   listed and specified in the document, there's one case

17   with regard to the selection of the upper air stations,

18   and the choices that were made.  So, for Philadelphia,

19   you used Washington Dulles data; for Phoenix you used

20   Tucson data; for Los Angeles, you used San Diego data;

21   and I guess there's sort of a question because of the

22   distances as to how relevant those selections are.  And

23   I understand, and maybe, it's because that's the only

24   data that was available, but I, so, it makes me worry

25   or wonder, sort of, how good that relationship is over

36

1  What was the other question, I'm sorry?

2	DR. AVOL:   Freeway speeds.

3	DR. ROSENBAUM:   Oh, the speed, yeah.

4  Actually, we looked at that, and we thought they seemed

5  high, too.  And, in fact, we talked to the people in

6  Philadelphia that we got the data from, and they, also,

7  thought they looked a little high.  But, and that was

8  what the, you know, that came out of the model.  And it

9  was, actually, verified somewhat against a small amount

10   of monitored data of, you know, of traffic.  So, it's

11   just, you know, it's something that's not a

12   well-characterized variable in the model.  But that's

13   what came out of the model, and so that's what we used.

14	DR. HENDERSON:   That doesn't sound good

15   to me because I think the model should reflect reality.

16	DR. GRAHAM:   Well, it's something that

17   could be considered in additional sensitivity analyses

18   to see if it is an important parameter.  You're so old

19   fashion, Rogene.

20	DR. HENDERSON:   I know.  Call me an

21   experimentalist.  Okay, now, are there other things

22   that people want to bring up about the exposure?  I

23   would like to know from the EPA staff over here if we

24   have addressed the questions, the charge questions

25   you've listed here.  There are six of them.  Have we

35

1  those distances.

2	And then, secondly, on table 20, about

3  average calculated speeds that are used in the

4  modeling, coming from Los Angeles, it's hard to imagine

5  that there actually are average speeds of 63 to 65

6  miles an hour on the freeway.  But, that's what's used

7  here, and it, that seems to me to be high.  And so, I

8  just have a question about how and where that comes

9  from.

10	DR. HENDERSON:   Do you want to answer

11   that?

12	DR. ROSENBAUM:   Well, as far as the upper

13   air data, that's like what's available.  So, I mean,

14   that was the clo-, those were the closest available

15   data on the upper air.  I think that, Christian might

16   be able to speak to this better, but I think that the

17   upper air, it's not as variable as the surface data so

18   that it's not, you know, it's better to use something

19   closer, but it's not as serious to use something

20   farther away.  Do agree with that?

21	DR. SEIGNEUR:   Yes, well, I guess, you

22   know, since it's the only thing you have available,

23   there is not much choice then.  I think that's the

24   answer.

25	DR. ROSENBAUM:   Yeah, right, of course.

37

1  addressed those, are we giving you the information you

2  need?  Is there something that you wanted advice on

3  that we haven't spoken to?

4	DR. ROSENBAUM:   Just one point of

5  clarification, as far as, a couple of people mentioned

6  about the pedestrian commuting.  There is a, we do have

7  a micro-environment, outdoors near roadway, that covers

8  when people are walking.  And that is, that's one of

9  the activities that's listed in the CHAD database.  So,

10   it is covered to the extent that the activity patterns

11   in the CHAD database show people outdoors on the

12   sidewalk.  Now, it's not inner-city specific, or you

13   know, whatever.  It's what, just whatever is in the

14   CHAD database.

15	DR. GRAHAM:   And also, along the same

16   lines, it was the commuting.  It may have been

17   misleading, or shall I say misstated in the document.

18   We do, if, of course, an individual is on a bus, a

19   child, then that person is modeled implicitly in that

20   micro-environment.

21	DR. HENDERSON:   Okay, of the people who

22   are on the phone, are you silent because you don't have

23   questions, or do you, anybody on the phone need to,

24   want to ask questions?

25	DR. BALMES:   This is John Balmes.  I

38

1  don't want to ask a question.  I just want to say that

2  I totally agree with George and Frank that we need to

3  talk about the use of the epidemiology.  And I was just

4  holding my fire till later.

5	DR. HENDERSON:   I understand, okay.

6	DR. GORDON:   And this is John.  I don't

7  have anything to say right now, but I'll join in the

8  discussion later with interest.

9	DR. HENDERSON:   Okay, well, then can we

10   move on to, oops, I'm sorry.

11	DR. AVOL:   Will you have the resources to

12   model all five cities?

13	DR. GRAHAM:   I don't think I can answer

14   that right now.  Resources, I think the limiting factor

15   here is the time, and I could probably safely say, I

16   don't think there's time to do all five cities.

17	DR. WYZGA:   So, do you want some advice

18   as to the cities that you should choose?

19	DR. GRAHAM:   Right, we did ask that, I

20   think.

21	DR. HENDERSON:   Asked for that, yes.

22	DR. GRAHAM:   As far as prioritizing,

23   which would be the next cities to, perhaps, look at,

24   and I think I heard a vote for Los Angeles and Atlanta

25   yesterday.

40

1  commute in.  And I'm gathering that's not included in

2  the analysis.  You're only analyzing residents, or

3  maybe if you include the outlying counties, then it

4  would be inclusive, but I don't know if you're going to

5  do that in Atlanta.  I just raise that concern about

6  the commuters, because they get some of the biggest

7  exposures.  There's probably a lot of people with

8  asthma who drive in to Atlanta, and so, that's

9  something to keep in mind when choosing Atlanta, and

10   when analyzing Atlanta.

11	DR. RUSSELL:   And if I might, actually,

12   for Los Angeles, as well as Atlanta, as well as

13   Detroit, how much of the urban area are you expecting

14   to get?  I mean, let's start with Los Angeles.  Is it

15   Los Angeles County, and that's it?  And for Atlanta, is

16   it just Fulton County, or not even that, or do you have

17   a real feel for what fraction of the population you're

18   going to capture?

19	DR. GRAHAM:   Right, and I guess this

20   opens up an additional discussion, because time is the

21   limiting factor here.  It becomes a matter of how many

22   receptors are we actually going to model.  I mentioned

23   earlier that Philadelphia, we looked at 17,000

24   receptors, and we're in the process of investigating

25   ways or methods to reduce the number of receptors that

39

1	DR. WYZGA:   I guess one of the questions

2  of Atlanta, Detroit, and Phoenix, is there a difference

3  in the terms of the quantity of air quality data for

4  the three cities?

5	DR. GRAHAM:   Well, I think Los Angeles

6  would have more air quality.

7	DR. WYZGA:   Right, of the three, yeah.

8	DR. GRAHAM:   Right, and Atlanta and

9  Detroit?

10	DR. WYZGA:   And Phoenix, I think were the

11   other three candidates you had.

12	DR. GRAHAM:   Phoenix is probably the

13   least, I think.

14	DR. WYZGA:   The least, okay.

15	DR. GRAHAM:   Yeah, so probably, Detroit

16   and Atlanta.  I think Detroit is fairly limited, too.

17   I don't have the numbers in front of me, but I guess,

18   that would be a good criteria for selection, too.

19	DR. HENDERSON:   Any more?  Yes, George?

20	DR. THURSTON:   Well, I'll just raise

21   again the issue with Atlanta.  I know you're just doing

22   the residents, but I think you'll give the impression

23   that you're doing an analysis for the city of Atlanta,

24   when 60 percent of the people who are there during the

25   day when the NOX levels are highest are commuters who

41

1  are modeled, while not losing too much information.

2  So, then, in reducing the number of receptors, we can

3  expand the actual modeling domain.  So, for something

4  like Los Angeles, I mean, it would be extremely

5  important, as well as Atlanta, if we are going to

6  extend it outside of a given county, we're going to

7  have to reduce the number of receptors that are

8  actually modeled.

9	DR. ROSENBAUM:   And the other

10   consideration is the, since we're doing the major

11   roadways, is how many roadway links, because that's the

12   number of sources.  So, and then it gets into how you

13   define what's a major roadway.  For Philadelphia, we

14   defined it as 15,000 annual average daily traffic in

15   one direction.  So, I mean, there's a couple of knobs

16   you can play with to adjust the number of sources, the

17   number of receptors.  And then that plays into how big

18   a modeling domain you can model.  So, there's just a

19   lot of considerations.

20	DR. HENDERSON:   Go ahead, Rob.

21	DR. WYZGA:   Please, if you do Atlanta, I

22   may have some data that would of some help to you,

23   including some new personal exposure data.

24	DR. GRAHAM:   That's great, thanks.

25	DR. HENDERSON:   Okay, very good, Lianne?

42

1	DR. SHEPPARD:   So, my recommendation on

2  how to move forward, given you have limited time, is to

3  first make sure that you can actually, that you're

4  doing the job you think you're doing in Philadelphia

5  with respect to the prediction of ambient.  And, maybe,

6  that, if you can't be reassured that you can capture

7  that variability well enough, maybe that's enough to

8  suggest that, for the purposes of estimating

9  exceedances, this is not the way to go.  And then shift

10   the energy into the epi.

11	DR. HENDERSON:   Okay, well, with that,

12   let's proceed and, at least, start on our discussion of

13   the - -

14	DR. LARSON:   Rogene?

15	DR. HENDERSON:   Yes.

16	DR. LARSON:   Can you hear me?  This is

17   Tim Larson calling here.

18	DR. HENDERSON:   Yes, I can hear you.

19	DR. LARSON:   Yeah, thanks.  So, in the

20   exposure assessment, the, it seemed like, one of the

21   biggest chunks of the exposure above 300 ppb was these

22   near-road exposures, not the on-road, but the near-road

23   exposures.  And I was just curious.  Is this due to

24   like a one-hour encounter near the road of a few

25   people, or is this, or is this just, I mean, of a

44

1  discussion.

2	So, first, with regard to the chapters

3  in the document, and beginning with the chapter three,

4  the at-risk populations, yesterday, we talked and had a

5  discussion about vulnerability and susceptibility, and

6  talked about the distinction and usage in both the ISA

7  and in this current document.  Although, in the context

8  of public health, it might be of more important just,

9  to just be counted, rather than to argue whether it's

10   susceptible or vulnerable, because both are potentially

11   at risk here.

12	Yesterday, Steve Kleeberger recommended

13   that an expanded table of at-risk populations be

14   identified, and I think that's appropriate here,

15   because it's more than just the three categories that

16   are discussed here.  In here, you talk about disease,

17   which operationally means airway responsive hyper, I

18   mean, airway hyper-responsive asthmatics.  Then you

19   talk about age, sort of, in children and older adults.

20   And you talk about proximity to roadways, but even with

21   regard to proximity to roadways, for example, there's a

22   whole host of people that, I think, would expand that

23   population that include residents that live there,

24   schoolchildren that attend school at, near busy

25   roadways, a range of occupational exposures that you

43

1  number of people, or is this just a few people that are

2  being exposed continuously over many hours near the

3  road?  Do you know?

4	DR. GRAHAM:   Without having the actual

5  data in front of me, I can suggest that, of course, we

6  do have less individuals that are exposed to that

7  highest concentration.  So, it is suggesting that, of

8  those people that are receiving those high

9  concentrations, there are very few of them, and that's

10   where they would occur.  I can't respond other than

11   that way, at this point, without the data in front of

12   me.

13	DR. LARSON:   It seems like an important

14   micro-environment, as has been mentioned, and just to

15   reemphasize that point, because it seems to be driving

16   the highest exposures in your analysis.

17	DR. HENDERSON:   Thank you, Tim.  Are

18   there any other comments before we move to health?

19   Well, we have some strong feelings on the health we've

20   already heard.  We'll led Ed Avol is going to lead off

21   on this one, and we may not finish it before the break,

22   but we'll get a good start.

23	DR. AVOL:   Thank you.  So, I have a

24   couple comments on the chapters, and then I'll come

25   back to the five questions to sort of start the

45

1  brought up.  But also, in addition to the highway

2  patrol, and the toll collectors, and the bus drivers,

3  you talked about there's truck drivers.

4	There's rail workers.  There's off-road

5  construction operators.  There's the port and dock

6  workers in other communities.  There's commuters, both

7  workers and children on school buses.  And then,

8  there's a whole SES component, in terms of proximity to

9  roadways that raises, sort of, these issues.

10	And on the disease side, of course,

11   there's obesity, and we talked about, in cardiovascular

12   disease, and COPD, and diabetes.  But there are other

13   risk categories as well, in terms of the genetics.

14   The, again, SES itself may be a category, and smokers

15   in terms of increased NOX exposure.  So, I think

16   there's a large, a larger, a much larger universe of

17   at-risk populations that need to be, sort of,

18   considered here.

19	With regard to the chapters on health

20   risks, which here, sort of, operationally is just

21   airway  responsiveness, and I guess, that flows from, I

22   understand that flows from the ISA, and we had that

23   discussion yesterday, but, and it's sort of started

24   already this morning.  I think that there's going to

25   be, you're going to get a couple of comments about the

46

1  fact that it's more than just airway responsiveness,

2  and I think - -

3	DR. BALMES:   Could you repeat that?  Ed,

4  we couldn't hear for a second.

5	DR. AVOL:   I'm sorry.  I think that, in

6  terms of the health, there's more than just airway

7  responsiveness, and you know, in some ways, I think,

8  with apologies to physicists, I think there's sort of a

9  grand unification theory at work here.

10	And I think that, you know, if you look

11   at lung function growth decrements, and respiratory

12   illness, and epi,  the epidemiological effects, and

13   lung host defenses, and immunity, and airway

14   inflammation, respiratory emergency admissions, and

15   even cardiovascular disease, which currently is weak,

16   and mortality, I think there's a number of things.  And

17   yesterday, Frank Speizer suggested tallying up pluses

18   and minuses to look at this, sort of whole thing.  And

19   I think if you look at, sort of, make a list of, sort

20   of, short term NO2 effects, and look at adverse

21   respiratory effects, which you categorize as

22   sufficient, and list a whole host of them, and

23   cardiovascular effects, which you list as inadequate.

24	Mortality is suggestive.  You sort of

25   have a balance in one direction, and in long-term NO2,

48

1  speak.  The animal data shows biological plausibility.

2  But it's the epidemiology that shows, sort of, the real

3  world perspective.  And I agree, it's not always clean.

4  It's not simple.  It's not a single exposure.  But,

5  it's what really happens.  And so, I think, that's,

6  sort of, something that has to be taken into account

7  here.

8	In the range of benchmark values

9  discussion that you have, I think the range is

10   reasonable, but the question I have is, given the

11   uncertainties associated with the measurement area, and

12   the misclassification, that even when you adjust and

13   take them into account, the improvements in whatever

14   modeling differences you're going to come up with, I

15   wonder if that's just not overwhelmed, but those are

16   small errors compared to the uncertainty that you have

17   around the whole aspect, and whether it's worth

18   worrying a lot about refining there, when you have a

19   much bigger, overall uncertainty about it.

20	So, with regard to the five questions

21   that were charged to us in terms of the

22   characterization of health risks, in my judgment, the

23   question, is the documentation clear and appropriately

24   balanced.  I think it's not always the case and not

25   completely.  And so, I think it needs a little bit of

47

1  you look at morbidity, which ends up being suggestive,

2  based on both our work in children's health study, and

3  Mike Brower's Netherlands birth cohort.

4	And even though there are some

5  inconsistencies in cross studies, there's still a

6  biological plausibility from animal toxicology here.

7  And there's some discussion about the inadequacy of,

8  the current inadequacy of mortality data and the

9  long-term data.  But still, I think in all of this,

10   there's a, sort of, a general preponderance of

11   information that sort of sways it in a direction.

12	And there's a discussion here about an

13   effects threshold.  And sort of an interest in it in

14   the document.  And it's not clear to me, I mean,

15   there's not a focus, per se, in the epidemiological

16   work on an effects threshold, necessarily, but at

17   least, to an issue that I'll come back to in a moment.

18	And so, again, in this context, that

19   sort of grand unification, you have, sort of, clinical

20   research.  You have the toxicology.  And you have the

21   epi work.  And each of them, I think, provides some

22   components here.  The controlled exposures have, and

23   the data, which you sort of weight on, sort of shows

24   hyper responsive airways as being, sort of, the

25   information that you, sort of, hang your hat on, so to

49

1  work there.

2	With regard to questions two and three,

3  on the range of effects and so forth, I think because

4  of the uncertainty issues, I'm just not sure where the

5  benchmark discussions leave us.  So, I think the values

6  chosen are reasonable, but I think you need to do a

7  better job about establishing what's meaningful and

8  worthwhile in the document to be more convincing.

9	I think discussion yesterday on question

10   four about the data input for Philadelphia, about the

11   model output, about adjustments, about moving, you

12   know, alternate, all, or other communities that could

13   be tested, such as Los Angeles or Atlanta, sort of, I

14   think make moving to a richer data area like Los

15   Angeles may be more scientifically interesting and

16   appealing to do this, in terms of better emissions,

17   inventory data, better monitoring data, more traffic.

18   But I think the decisions you, the discussions you

19   raised yesterday about modeling domains and commuter

20   activity into and out of the area, and downwind

21   photochemistry, I think, are going to make that a

22   challenging undertaking as well.  And so, all in all, I

23   think question four is, sort of, a work in progress

24   that sort of be continued.

25	And then, finally, with question five, I

50

1  think that there have been a number of concerns

2  expressed about it.  But in my opinion, you know, and

3  sort of by way of analogy, reality tv is sort of

4  currently in vogue.  And so, I think epi may not be

5  unilaterally decisive, but it's the real world.  And

6  so, I think, you need to give it more measure and

7  stature here in the document.

8	DR. HENDERSON:   Thank you, Ed.  And,

9  John, are you on the phone?

10	DR. BALMES:   I am.

11	DR. HENDERSON:   Okay, it's your turn.

12	DR. BALMES:   My son is calling me 'cause

13   he just woke up, but I'll try to ignore him.  So, I

14   have a lot of agreement with Ed's comments.  I'll just

15   go through the questions.  With regard to question one,

16   I think that the staff did a fairly good job of

17   characterizing the health evidence concerning NO2

18   exposures.  In fact, I sort of, I like the fact that

19   this a much shorter version of what's in the ISA, so

20   it's easier to get one's mind around.  But, I guess I

21   have the same concerns that I have with the ISA, that I

22   think the long term exposure to NO2, and its effects on

23   growth of lung function in children is, I find the data

24   more compelling than the staff did in the ISA, and

25   that's, of course, reflected here as well.

52

1  California Air Resources Board, and I always thing

2  about trying to explain to my non-physician colleagues

3  on the Board a risk assessment like this.  And to try

4  to explain to them, you know, a little delta and airway

5  responsiveness in asthmatics, as opposed to, you know,

6  sort of real world morbidity endpoints like going to

7  the hospital, or going to the emergency department.  I

8  think it's going to be really problematic, especially

9  given, well, I'll just leave that alone.  I was going

10   to make a politically inappropriate comment.  I think

11   the benchmark values are reasonable.

12	And then, the question four, to what

13   extent is the assessment, interpretation, and

14   presentation of initial health risk result technically

15   sound, clearly communicated, appropriately

16   characterized.  I think, again, the staff has done a

17   good job with the exception that I would have really

18   preferred to have morbidity endpoints to be used.

19	And, you know, again, well, turning to

20   question five, while I understand the rationale for the

21   staff judgment that's presented in section 4.233, I'm

22   just not persuaded that the judgment is the correct

23   one.  I think that, although many of the epi studies on

24   the effects of short term exposure to NO2 have been

25   conducted outside of the United States, and there's a

51

1	And I do agree with Ed that, sort of,

2  the overall gestalt, which I think staff shares, is

3  that NO2 does cause short term respiratory health

4  effects, but it's, when you go through everything

5  that's written down, and you end up using airway

6  responsiveness as, sort of, major health endpoint for

7  the risk assessment, it seems like it waters down the,

8  sort of, large body of evidence, much of which is

9  epidemiological.  I, actually, find the epi, I do

10   controlled human exposure studies, and I, actually,

11   find the epi evidence more convincing about health

12   effects with regard to NO2 exposures, than I do the

13   controlled human exposure data.  That's in part because

14   my lab has generated some relatively negative data with

15   regard to NO2 exposures, to show my bias.

16	With regard to question two, again, I

17   understand why the staff decided to use the

18   experimental data on airways responsiveness in

19   asthmatic adults to identify potential health benchmark

20   values to characterize risk, but I would have

21   preferred, as I've already said, to see asthma epi data

22   used.  I find asthma exacerbation data, you know,

23   hospital admission, emergency department admission,

24   much more compelling, and much more, much easier for

25   policy audiences to understand.  I mean, I'm now on the

53

1  relatively small number of U. S. studies that have

2  been, U. S. cities that have been studied, you know, I

3  think the entire body of epi literature is consistent.

4  And so, I think you could develop a concentration

5  response.

6	Now, I know the staff is also concerned

7  that this is problematic because of the, of

8  co-pollutant effects, and I agree with George Thurston

9  strongly that, if you're trying to public health

10   protective, then you can use, you could use single

11   pollutant NO2, you could derive a single pollutant NO2

12   concentration response.  It might be not entirely

13   reflective of the independent NO2 effect.  I'm sure it

14   isn't, but it still would be public health protective.

15	And I just have to say for the nth time

16   that trying to tease out an independent effective NO2

17   isn't possible.  We're never going to be able to do it.

18   And, just like we can never tease out independent ozone

19   effects, or independent PM effects, yet we were able

20   to, sort of, use, we use epi data for ozone and PM in

21   risk assessment work.

22	I guess my last comment would be

23   regarding the controlled human exposure data.  It is

24   experimental, but it's, there's not that much of it.

25	Even using, or even basing a lot of the

54

1  assessment on the meta-analysis that Larry Folensbee

2  did for the '93 effort, you know, there's a fair amount

3  of variability in those results.  The subsequent

4  results are also variable, with regard to allergens

5  responsiveness, and it's not even, it's probably even

6  an underestimate of the effects, since the people that

7  participate in controlled human exposure studies are

8  adults, to be adult asthmatics, not children, and also

9  they're relatively mild asthmatics.

10	Now, I know the staff knows this.  So,

11   hanging our hat on something that's hard for lay folks

12   to understand isn't exactly the greatest, doesn't

13   really have a large end, even pooling studies, and is

14   only representative of a sub-fraction of the asthmatics

15   that are potentially at risk, I think is, isn't real

16   world, and the epi data, I think, would be a better way

17   to approach this.

18	DR. HENDERSON:    Thank you John. James?

19	DR. CRAPO:    I'm going to agree with the

20   previous speakers, I think that the staff needs to step

21   back in terms of the health risk assessment on this and

22   look at another way to do it. Let me also go through

23   the questions and sort of tell you why I think that.

24   The first question is in terms of was the assessment of

25   the overall health evidence balanced and the answer is

56

1  happened.

2	But the laboratory can see a small shift

3  in a spirometry value. But the subject feels healthy,

4  they don't require any medication, they don't realize

5  you did anything to them and most of them would tell

6  you nothing happened that day. These are people who

7  have twitchy airways and occasionally are around an

8  animal or a cat or a dusty environment and they have a

9  little reaction of airways and it's a very common event

10   in their lives.

11	They treat these as insignificant

12   events. I think that taking that and then- when you put

13   that together with these studies that were used to do

14   this, there were 3 of them done in the same laboratory,

15   and not reproduced by any other laboratory worldwide,

16   really raises criteria question of- A- Is it real? And

17   then B- Is it significant?

18	I think it forms a very poor basis to do

19   a quantitative risk assessment around. So my answer to

20   question #1 is it was not a balanced assessment of that

21   and the wrong endpoints were chosen. The second

22   question was whether or not the, well it's the same

23   question, it's based on this particular airway

24   responsiveness, so that's another issue. I think the

25   benchmark values are appropriate in the sense that they

55

1  no, it was not. The choice by the group was to look at

2  the human health clinical studies in an uncritical

3  fashion and accept it without applying rigorous

4  criteria to it's value. And so what was done was to

5  choose the effect that had a quantitative number

6  associated with it, with the lowest observed effect,

7  but without asking if it was reproducible and

8  consistent and clinically significant.

9	Therefore, doing the exact opposite of

10   the Hill criteria. I mean, it fails every Hill

11   criteria. I want to say that I agree that the

12   epidemiology is the strongest evidence and does, I

13   think, meet those criteria, provide a basis for going

14   forward. I think there's also a tendency not to

15   understand exactly what's being measured.

16	When you measure airway and hyper

17   reactivity in a subject like this, you have to remember

18   that asthmatics have twitchy airways and they're

19   sensitive to lots of things- to temperature, to

20   moisture, to common allergens or dust. In this case,

21   the ability to stimulate a reaction measured by a

22   usually very tiny change in FPP-1 on a spirometer in

23   response to some challenge is a test in which the

24   subject is unaware of any effect. In most of these

25   cases, the subject is totally unaware that anything

57

1  represent the high end of what's clinically- what's

2  observed in their environment. I mean you couldn't go,

3  you couldn't take them much higher because there's no

4  values up there. So you're looking at a reasonable set

5  of values, but it's being designed around the question

6  of perhaps 0.26 ppb, well ppm, causes airway hyper

7  sensitivity.

8	Therefore, by finding an exceedence of

9  that, maybe once a year, you've said that there's one

10   day one child might have a spirometry measure....I mean

11   you're asking how often that happens.

12	What I'm trying to say is it's am

13   insignificant event but you're actually asking the

14   question, how many times in a year would a certain

15   number of people have the potential of this event

16   happening and that's probably the wrong question given

17   that your best data is epidemiology. The epidemiology

18   says that you can get a change in respiratory

19   morbidity, they say ER admissions, by a 20 ppb drop in

20   the 24 hour daily average. Perhaps you're endpoints

21   should be designed around that.

22	You ought to be asking how many areas

23   have a exposure pattern where a different standard

24   could drop the, if you assume you met it, how many

25   people would have a 20 ppb drop in their daily 24 hour

58

1  exposure. How many times would that occur to a

2  population? So I'm trying to suggest you do as an

3  endpoint that's related to the epidemiology and the

4  only one you've got there is a 20 ppb drop. So I think

5  it's possible to ask how many days have enough

6  elevation and enough change that you could cut those

7  out and how many days would be vulnerable to that kind

8  of thing.

9	Therefore, direct it right at the

10   epidemiology instead of the clinical science. The

11   assessment of the health risks, because the endpoints

12   are not chosen to be ones that I can accept as likely

13   to be clinically significant or statistically valid, I

14   think you can't really assess it. I mean there coming

15   from a negative assessment for question 4 so you can't

16   do that because the endpoint chosen was wrong. It would

17   be,  I think you could use much of the same technology

18   though in the way I just described and apply the

19   epidemiology very effectively.

20	The last question really relates to the

21   same question again. I strongly concur with those that

22   are arguing we ought to stay here today until we agree

23   to do the study focused on the epidemiology as the

24   critical endpoint that we can hang our hat on.

25	DR. HENDERSON:    Thank you James. Is

60

1  argument for it. My take on the epi results for NO2 is

2  that NO2 central site monitoring is a good marker for

3  day to day variability or spatial variability in air

4  pollution.

5	In particular, related to motor vehicle

6  exhaust emissions. So it's a nice marker of those

7  exposures. So it's perfectly fine to use those studies,

8  as long as the results are presented as NO2 as a

9  measure, as a proxy for general day to day or spatial

10   variations in air pollutions. But, I don't think it's

11   fair to interpret those results where we see effects at

12   very low levels of NO2 in the ambient atmosphere as

13   really representing NO2 per se effects.

14	So as long as we're clear about it, I

15   think it's fine to use that data in the risk assessment

16   but it has to be couched properly. One important aspect

17   of this is that indoor NO2 is the dominant exposure for

18   people who have gas stoves which is very common in many

19   cities. So really understanding the relationship

20   between central siting and personal exposures to NO2 is

21   something that creates a great deal of uncertainty and

22   again sort of argues for the central site data as not

23   just representing NO2. So I'm uncomfortable just taking

24   it at face value and using it in a risk assessment as

25   an NO2 exposure response relationship. That's it for my

59

1  Terry on the phone.  Is Terry... Pat Kinney?

2	DR. KINNEY:    Going down the list of

3  charge questions, the second one which addresses

4  whether the benchmark values are....basically what are

5  the views of us on the benchmark values. I...My concern

6  about the range that was given is that the.....clearly,

7  as John Balmes has mentioned, the subjects that are

8  looked at in clinical studies are not a representative

9  set from the general population and particularly don't

10   have good representation of the most sensitive tail of

11   the general population distribution and even when you

12   look at asthmatics in the laboratory, they're not the

13   most severe asthmatics. So if you're going to use sort

14   of lowest effect values from clinical studies I think

15   it's really important to make some adjustment for this

16   problem. How to do it quantitatively I'm not sure.

17	I wouldn't simply take sort of the

18   lowest effect obtained in laboratory settings and say

19   that's the relevant benchmark in the general

20   population. Of course this does relate to the other

21   issue that's being discussed, which is whether the

22   epidemiologic findings ought to play a larger role,

23   because clearly there you do have the full distribution

24   of people represented in your findings. So it's very

25   tempting to go with that and I think that is an

61

1  comments.

2	DR. HENDERSON:	Thank you , Pat. I'm

3  going to skip down to Ed Postlethwait because I know he

4  has to leave a little early. So Ed can you give us your

5  comments?

6	DR. POSTLETHWAIT:    Thanks Rogene. I

7  agree with everything that's been said so far. I

8  thought James did a very nice job of going through it

9  question by question.

10	What I picked up from this, and perhaps

11   this is a bit trivial, but in terms of the titling of

12   the chapter with the information that's presented,

13   there seems to be an implicit assumption that exposure

14   as predicted here equates to 100% of a health outcome.

15   And we know there's implicit, inherent variability in

16   populations. And so the question is, are we predicting

17   or are we attempting to predict a worst case scenario

18   here, in terms of if somebody is exposed, then at that

19   event negative outcome will occur.

20	Or are you trying to say, gee, if the

21   asthmatic population we've selected to be the target as

22   receptive to potential health risk from exposure, how

23   many of those people get exposed and then how many

24   exposed people suffer a bronchial spasm event or

25   whatever outcome you want to pick.

62

1	MR. RICHMOND:    This is Harvey Richmond.

2  Clearly, closer to the latter in that we clearly

3  discuss in the chapter that we would not expect all

4  asthmatics exposed to this level to see even the

5  response we're talking about. So we have caveated.

6  That's why we've used the word potential health effect

7  benchmark, not health effect benchmark. It's some

8  unquantified fraction. We're saying the evidence is not

9  there for us to quantify, but some significant fraction

10   we're expecting would, but we're not making any attempt

11   to quantify whether that's 10% or 15% or whatever

12   because we don't think the evidence allows us to

13   quantify what fraction. But there's enough evidence at

14   those different benchmarks and certainly would be an

15   increase, we would expect, at higher levels that they

16   have the potential to experience the responses observed

17   in the clinical studies.

18	DR. POSTLETHWAIT:    Is there a way to put

19   boundaries on the numbers?

20	MR. RICHMOND:    As to what fraction? I

21   haven't seen, out of the clinical data, our ability to

22   do that so far. If others on the committee think

23   there's data, I'd like to see what specifics they point

24   to. The meta analysis that was done by phones took all

25   the individual data from those studies but it just

64

1  up....

2	DR. HENDERSON:    Okay, Kent do you want

3  to go?

4	DR. PINKERTON:    Well, thank you, and I

5  certainly agree with all the comments that have been

6  made and will add perhaps just a repetitive comments on

7  some of these issues.

8	I think that it is important to look at

9  the full breadth of potential health effects that are

10   there.  I know that airway hyper-responsiveness seems

11   to be the easiest measure to use, but I think it's also

12   important to consider all other indicators as well as

13   potential things that you would want to examine.

14	I think that the selection for using a

15   one hour average makes a lot of sense, but I'm somewhat

16   concerned because of some of the points that have been

17   made about long term effects of No2, so we assume that

18   it's an acute exposure to a relatively high level, as

19   high as we would see in ambient conditions for No2 that

20   may elicit these kinds of responses under special

21   conditions for those who may be challenged with an

22   allergen or something like that.

23	So again it's really a specialized

24   population but the question really comes up is some of

25   the issues that we're dealing with in the Southern

63

1  looked at if there was a positive or negative response

2  without, and I think 76% of the subjects within the .2

3  to .3 range fell in as having a positive response. But

4  it didn't deal with the quantification of the magnitude

5  of that response. Therefore, not all the response might

6  be clinically significant as James Crapo was talking

7  about. So we don't feel comfortable quantifying that

8  percentage in terms of a degree of response that would

9  be judged as either adverse or clinically significant.

10	DR. POSTLETHWAIT:    Well, perhaps

11   something to think about then is to either bring those

12   caveats to the forefront a little more....

13	MR. RICHMOND:    Right, we clearly could

14   communicate it better....

15	DR. POSTLETHWAIT:    ...and again,

16   depending upon who the target audience is you're really

17   trying to write thing, as opposed to the folks in this

18   room, is the presentation of the data that looks like

19   you're predicting numbers of people are going to suffer

20   an adverse event as opposed to a potential adverse

21   event. That's really all I have to add.

22	DR. HENDERSON:    Thank you Ed. Now is

23   Steve on the phone?

24	DR. NUGENT:    He was planning to be on

25   the phone but maybe because we moved this discussion

65

1  California children's health study which seemed to

2  indicate very clearly that there are reductions in lung

3  growth function in children and that that  has been

4  continually associated with No2, even when we adjust

5  for the co-pollutants so I think that really is an

6  important finding.

7	I'm also thinking about the benchmarks

8  that you've used, they seem to be as appropriate as you

9  could possibly do, I think that seems very reasonable

10   but I'm also concerned that for some of the studies

11   that have come out of Australia, the children there

12   where they actually have shown differences based upon

13   levels of No2 that may be present indoors.  I realize

14   that you're dealing with an outdoor situation, but

15   again those differences were well below the hundred

16   parts per billion where they saw those distinct

17   differences.

18	And again, I would just echo the

19   feelings that you've heard repeatedly this morning, and

20   that is that I think to dismiss the epidemiological

21   studies are...would be a mistake.  I think that there

22   are things that you can do to try to make the most of

23   those, the best of that, and also the modeling that

24   you're taking about doing in these cities, it seems as

25   though you have lots of plans that are there that seem

66

1  fairly reasonable but again, it would be wise to use

2  those resources in the best way possible whether it be

3  that or further analysis of epidemiological studies or

4  human clinical studies.  Thank you.

5	DR. HENDERSON:    Thank you Kent.  John

6  Samet are you there?

7	DR. SAMET:    I am here, I've been

8  listening with interest.  So I'm getting more persuaded

9  that the epidemiological data, some of it should be

10   used, perhaps in addition to some of the clinical

11   studies as an endpoint.  The....I think John Balmes

12   said that well, you know we can we look at the effects

13   of ozone and we look at the effects of PM and we can

14   identify the effects of No2 and epidemiological

15   studies, I do think that there has to be much more

16   caution around interpreting the quantitative estimates

17   from epidemiological studies on No2 and again I think

18   that's because of the particular relationship of No2 to

19   other mixture of components, formation of secondary

20   particles, in some places a contribution to ozone and

21   so on and I think those are what was in that figure

22   that is now in Chapter One of the ISA, some of those

23   relationships that are complicated and really can't be

24   teased out with multi-variable models.

25	The evidence for short term effects,

68

1  done.  If all the thinking were done following on

2  Frank's comment, no one would ever leave the hotel room

3  because it would just take too long.  There's a lot of

4  difficult issues here, so I guess that's where I sit at

5  the moment.

6	DR. HENDERSON;  Thank you John.  Rich

7  Schlesinger are you still.

8	DR. SCHLESINGER:    I'm here can you hear

9  me?

10	DR. HENDERSON:    Yes, very well Rich.

11	DR. SCHLESINGER:    Okay, well being

12   towards the end of the list, almost everybody has

13   covered all the issues that I had written down and

14   maybe then some, but just some the issues.  One was

15   raised yesterday and Ed Avol raised it again and that

16   needs to be a better separation of the definition of

17   vulnerable versus susceptible.   As I said yesterday

18   and apparently others have felt there was confusion in

19   terms of the definition used or they gave a definition

20   and then made it confusing by putting everything both

21   definitions.

22	The... I would like a better

23   justification for the benchmark that they did use, both

24   in terms of what Kent said in terms of some of the

25   lower levels found in indoors causing an effect, and

67

1  some of it does come from the Australian intervention

2  study which is useful.  There's complimentary data from

3  asthma, asthma panels, and other kinds of studies, so I

4  think to focus on asthma there again with support from

5  the toxicological studies, is reasonable and probably

6  if that's to be the case, then the risk assessment

7  document needs to do a better job in sort of making

8  that case and putting together these two bodies of

9  data.

10	I think the probably the most difficult

11   aspect of moving to use the epidemiological data is how

12   to interpret.  There's two things, I mean one is the

13   quantitative estimate of effect and then the

14   interpretation of that because I think given some of

15   the limitations of the data available, these

16   complicated relationships among variables, the fact

17   that we truly are dealing with a mix looking at one

18   component of it, I think the interpretation of these

19   kinds of numbers in a causal framework, that is to say

20   this is the burden of disease attributable to No2

21   specifically,  has to be carefully and cautiously made.

22	I think we have to think about what

23   these estimates mean in terms of potentially bounding

24   estimates or are they under estimates I mean I think

25   there's some difficult thinking that would need to be

69

1  even if they ignored that, I still needed a better

2  justification, based on the data set that they did use

3  which was presumably the clinical studies.

4	The other issue, in spite of my

5  toxicology background, I do feel that and given the

6  caveats and the use of epidemiology that we all know

7  about, that it should not have just been discounted in

8  terms of the development here and that it needs to be

9  considered and based on that consideration, EPA may

10   decide that there are valid reasons why they can't use

11   this, or can't use that, but this to me looked like

12   just a outright decision not to consider it without

13   necessarily evaluating it to the extent that it should

14   be evaluated and that's my two cents, given everything

15   else that was said.

16	DR. HENDERSON:    Okay Rich well thank

17   you.  And now we have Frank Speizer.  It's your turn

18   to....

19	DR. SPEIZER:    Well my bias is on the

20   table and most everybody has said most of the things

21   that I was going to bring up.

22	I was really quite shocked that with

23   fifty studies that has been done, that we were just

24   going to cast it aside.  Now one of the concerns is

25   that is how to do this and I do want to go home today,

70

1  and it may be that we need to sort of have a more... a

2  greater discussion with Harvey and his group as to how

3  we can help him if if that's necessary.   I mean it

4  seems to me that if we don't do this, we're going to be

5  here five years from now, some of us will be here five

6  years from now, going through the same argument,

7  because the studies that are going to be done are going

8  to provide similar kind of information.  Well it may be

9  a little more biological markers and stuff but we're

10   going to have the same problem of the mixture.  So I

11   think we need to sort of at least figure out, if I mean

12   certainly do the risk assessment, and see what the

13   flaws are and hopefully those flaws can lead to a

14   better direction to where things will go in the future.

15	The...I think that's an important

16   component of doing the analysis using the epi data.  I

17   would propose that it might be appropriate for a

18   sub-committee of this group to be involved before we

19   see the next draft as Harvey does some of these

20   analyses, certainly it would be better for us to look

21   at it than for OMB to look at it, and I am concerned

22   that OMB will look at it and I think it might be better

23   to have a sub-group.  Now I don't know whether that's

24   feasible or doable, but I'm sure there are people who

25   have some expertise around the table that might be able

72

1  look at particle interaction

2	DR. THURSTON:    Oh, you know me so well,

3  no I'll be brief because I think all the points have

4  been made really.  I first of all I want to say that I

5  think we are in good shape, I think we're in good shape

6  with the documents that we have as a stepping off point

7  for doing what needs to be done.  And I think that the

8  ISA has got to connect the epi and the controlled

9  exposure assessments better and give the basis for you

10   know...  that's what it should do because that's the

11   gap there.   And I think that will give us the basis

12   for doing the risk assessment. And I think at this

13   point I would say to take the Philadelphia analysis and

14   dot all the Is and cross all the Ts, listen to all the

15   advice and that's enough of that kind of analysis

16   because I think it tells us what it needs to tell,

17   doing more cities.

18	I mean just listening to the discussions

19   of trying to do L.A. and Atlanta, and I don't think

20   they have time to do all those and when they're done

21   with it you're going to be talking about such a small

22   percentage of America being considered and such a

23   narrow population base within those cities, that it's

24   not going to have any kind of....I mean it's a useful

25   exercise that do once at Philadelphia and to learn

71

1  to at least react to what Harvey will do with these

2  data and maybe we should have a discussion about that.

3	DR. HENDERSON:    Yes, I agree, when I

4  came to this meeting I thought that really in depth

5  questions that faces us here is this multi-pollutant

6  problem, and as we have all said, it's not easy, it's

7  something that no one has a magic answer for but  I

8  think you're right within this group, there can be wise

9  advice as to how to handle this.  This is something...I

10   would like to ask the folks in the air office, in what

11   way can we help you with this major problem.  The

12   agencies moving sort of multi-pollutant approach but

13   you're not there yet I mean and it's not something we

14   just say say you do that, so maybe Karen can tell us

15   how we can help her.

16	DR. MARTIN:    What I'm going to ask you

17   back first is if we are about at the point of taking a

18   mid-morning break, it would give us an opportunity to

19   collect our thoughts, with regard to the issues you

20   have raised and I'd be happy to say some words on this

21   point, perhaps right after the break, that would give

22   you instantaneous reaction.

23	DR. HENDERSON:    That sounds good now we

24   had two more people listed here, I don't want to

25   neglect them, George is going to tell us so we need to

73

1  about that, but I think at this point what we really

2  need to do is do the next stage of analysis, which is

3  to consider the entire US, or at least all the major

4  cities in the US, and do an epi analysis and yes there

5  are uncertainties but we can document those

6  uncertainties.  And that's when you can look at the

7  multi-pollutant analysis and get an idea of what the

8  uncertainties of the estimates from the single

9  pollutants might be, and document the uncertainties but

10   do the analysis, do what will tell the decision makers

11   what they need to know and will give us some more a

12   broad breath of information and I think that's more

13   doable than trying to do several more cities of this

14   intense modeling, with its own huge uncertainties as

15   well that have to be documented and I think Frank's

16   idea of the sub-committee is a wonderful one.   I'd be

17   glad to participate in such a sub-committee and try and

18   work with the staff to choose how to go about getting

19   the co-efficience to use where, if they need the kind

20   of help because I know they have their own experts so

21   that's about it.

22	DR. HENDERSON:    Thank you and Ron did

23   you want to add something?

24	DR. WYZGA:    Sure, let me say I think

25   it's obvious that we have to go out and try use the epi

74

1  data.   I think we shouldn't ignore the clinical data,

2  I think you've done a lot of work along those lines,

3  and I think you need to refine along some of the

4  suggestions that have been made, but I will say that in

5  using the epi data is going to be a challenge, you know

6  as Frank said, the devil's going to be in the details.

7	You've got a lot of questions with

8  respect to which study to choose, etcetera but one of

9  the major problems is the fact that when you look at

10   the ISA and sort of  the emphasis of the discussions,

11   we've spoken about how important some of the peak

12   exposures are, exposures near roadways, etcetera.

13   When you look at the epi studies, they tend to do use

14   twenty four hour averages, and so you know you're

15   looking at something quite different from the hourly

16   average and that's going to be a challenge, and I think

17   that we need to reconcile these two and to think about

18   how we're going to reconcile it, and you know that's

19   something that I think we all need to put our thinking

20   caps on, and think about how to do that.

21	DR. HENDERSON:	Thank you Ron, and

22   let's take Karen's suggestion and we'll take a  fifteen

23   minute break, come back about 10:35 or 40, and then

24   have a really good discussion on how we can attack this

25   problem.

76

1  with from our perspective and hopefully to provide some

2  context in terms of from our perspective again what we

3  think might be most productive in terms of the

4  discussions you're now about to have.

5	And I would like to -- I would to raise

6  two general points here.  The first point relates as

7  much to process as substance, but I think it's relevant

8  here.

9	As I -- as I am sure you all know, the

10   process that we are working -- doing these NAAQS

11   reviews now call for us to produce different kinds of

12   documents than we did before and we now have an

13   integrative science assessment, we now have a

14   quantitative risk assessment document, and that  both

15   of those documents are to be followed by an advanced

16   notice of proposed rule making, which captures a policy

17   assessment and historically that's been in a staff

18   paper, which you would be seeing now at the same time

19   that you're seeing a quantitative risk assessment

20   document and that document has historically provided a

21   broader perspective from a policy perspective for

22   thinking about quantitative risk assessment, but we

23   don't have that now because our process has changed.

24	And all that is salient to the issue

25   about what we are or are not doing with regard to

75

1	DR. LARSON:    Rogene, when people are

2  putting their thinking caps on, Tim Larson...

3	DR. HENDERSON:    Oh Tim...

4	DR. LARSON:    Yes, this seems like an

5  opportunity to rethink where we put and how we design

6  No2 networks, because I mean if we had the data  near

7  the roads as well as away from the roads right now, we

8  could probably do a better job of combining these two

9  approaches but right now we're got at least one hand

10   behind our back so it's something to think about as an

11   opportunity going in the future.

12	DR. HENDERSON:    Okay thank you.  Tim

13   we're going to take a break.

14   (WHEREUPON  , a brief recess was taken.)

15	DR. HENDERSON:    Let's move on or expand

16   our knowledge of the problem and I really appreciate

17   your doing this because it is a problem.  We all want

18   to discuss it.  It's the biggest problem we address and

19   so, Karen, the floor is yours and we'll appreciate your

20   expanding our knowledge in this area.

21	DR. MARTIN:    Okay.  I'll start by saying

22   I'm sure I didn't promise to solve the problem and my

23   purpose in the remarks I would like to offer aren't --

24   aren't so much expanding knowledge, but to try to

25   provide some context for what you have been struggling

77

1  considering epi studies.  I've heard the phrase a

2  number of times today that we are dismissing the epi

3  studies and I know our quantitative risk assessment

4  doesn't present any quantitative risk assessment based

5  on information from epi studies, but I would suggest to

6  you that it most surely doesn't dismiss them and it

7  most importantly doesn't dismiss them from a subsequent

8  policy consideration context.

9	There are lots of ways to think about

10   what epi evidence tells us.  One way to think about it

11   is to extract concentration response functions and do

12   quantitative risk assessment.

13	Another way to think about them is to

14   ask questions like what were the air quality levels and

15   patterns in areas where we have signals from epi

16   studies that tell us something about health effects?

17	Were those areas in areas that exceed

18   current standards or that attain current standards?

19	Those kind of questions have some

20   quantitative component to them, but they don't have

21   quantitative risk assessment associated with them, but

22   they still tell us a whole lot about things

23   policymakers need to know in assessing the adequacy of

24   the current standard and potential alternative

25   standards.

78

1	And what I would like to say here is

2  that we fully intend to think about the epi evidence in

3  those contexts in the next document that we produce so

4  that I just want to make real sure you understand that,

5  because this draft quantitative risk assessment didn't

6  draw from epi CR functions to play out quantitative

7  risk assessment -- assessments per se, there's nothing

8  about this document that was intended to convey the

9  notion that somehow we're dismissing that evidence from

10   the broader qualitative policy considerations.

11	So that was -- that was just one general

12   point I wanted to make and that would have been made in

13   the kind of document we used to produce.

14	The second point I wanted to make was,

15   to the extent that we are open to thinking about how we

16   might incorporate information from epi studies into the

17   next draft of a quantitative risk assessment, we have

18   pondered all the kinds of challenges that you have

19   raised.

20	We are not oblivious to those challenges

21   and it's those challenges that caused us to take the

22   position that we took in this document.

23	If we are to move off that position, we

24   would very much appreciate from this group, perhaps in

25   the discussions you now have, somewhat more specificity

80

1  that we saw a pretty high potential that, even if we

2  went down the road of selecting specific CR functions

3  from specific studies and applying them in specific

4  example cities, in the end, if all we end up with are

5  numbers that say, well, these are numbers that show

6  that if you reduced air pollution in general, you would

7  achieve a benefit in public health protection, but if

8  they aren't numbers that say, if you reduce NO2 in

9  particular by this degree you will achieve benefits in

10   public health protection, then the question I would

11   pose back to you is would we have produced numbers that

12   meaningfully inform the review of an NO2 standard, not

13   an air pollution standard?

14	So those are clearly the kinds of

15   questions we need to grapple with and in our grappling

16   with them, and in our grappling with the notion of also

17   the averaging time associated with effects, the very

18   short-term peaks that we can see in clinical studies

19   that we can tease out in the exposure assessment that

20   we've done, how well represented is that evidence in

21   epi studies that use 24-hour averages or long-term

22   averages?

23	How well -- how well does one body of

24   evidence help to provide plausibility for the other

25   body of evidence when we have significantly disparate

79

1  as to how we might go about surmounting some of those

2  challenges in more concrete ways and I just make a

3  couple more observations.

4	In past reviews of PM and ozone, one of

5  the things that greatly helped us move forward in

6  bringing epi evidence into more quantitative assessment

7  was the fact that we had the ability to look at

8  multi-city studies, multi-pollutant analyses within

9  multi-city studies that helped us better reach

10   inferences about the extent to which that information

11   informed judgments about PM per se, ozone per se, as

12   opposed to just the broad mix of air pollution and I

13   think the observations you were making, the same as we

14   have observed, is that, in the case of NO2, that's

15   going to be much harder to do.

16	It's going to be much harder to do just

17   because of the atmospheric chemistry involved and the

18   correlations among these pollutants.

19	It's also going to be harder to do

20   because we don't have the breadth and depth of

21   multi-city epi studies that focused on NO2 and that

22   found independent NO2 effects, not just in single

23   pollutant models, but in multi-pollutant models.

24	So those are the kind of constraints

25   that we are very well aware of and caused us to say

81

1  averaging times?

2	There's more I could say, but I'm not

3  sure it's worth my taking more of your time and mine

4  talking about it, but I did want to say that we fully

5  recognize all of these challenges and when we looked at

6  it, our sense was it wasn't clear to us that the

7  numbers we would get out of an epi-driven quantitative

8  risk assessment would do more than tell us that we have

9  a clear air pollution effect as opposed to tell us

10   something about quantitative levels of an NO2 standard

11   beyond what we would get from looking at the epi

12   evidence in a more qualitative way, which we fully

13   intend to do.

14	DR. HENDERSON:    James, go ahead.

15	DR. CRAPO:    Karen, I want to say that I

16   hear you, and I agree with you, and I sympathize with

17   you completely.  I think you hit it right on the money.

18	I would say that I am far less

19   impassioned about stricter standards for NO2 than I was

20   about particulates in ozone for exactly the reasons you

21   just outlined.

22	Having said that, I think our first

23   decision, and your decision and our decision to

24   evaluate it, is do we think that our country should

25   have a short-term standard for NO2?

82

1	I think, looking at all the data, again

2  I'm less impassioned, but I think the answer is yes to

3  that based on primarily the epidemiology, but that's --

4  it starts there because if you're not -- you have to

5  decide I think it should be a standard.

6	Then -- then my next issue is, if we are

7  going to recommend a standard, what would we recommend

8  and how would we defend it?

9	And so I sort of look at the very end

10   point, if that's where -- if that's where we're going

11   to possibly end up.  When I get to that end point, I

12   know that I can't defend by saying that we've done this

13   analysis and we think 50,000 asthmatics will have at

14   least one day a year in which they have an undetectable

15   clinically insignificant airway constriction that would

16   only be made with a spirometer.   We're not going to

17   sell that to anybody, including ourselves.

18	I think the only way we could defend it,

19   if we do it right there, is by saying that we believe

20   that setting the standard at this level will result in

21   this -- a reduction in hospital admissions or morbidity

22   of some kind -- not necessarily mortality, but

23   morbidity, exacerbations or hospital admissions let's

24   say, ER visits for asthma, and we think there -- we

25   think that this level would result in this many

84

1  suggesting we need to get at, which I completely agree

2  with you, there are two things epi can tell us.

3	One, epi can tell us the estimate of how

4  many hospital admissions we think might be reduced in

5  going from a standard of this to this and coming up

6  with a number which would have, I'm sure we all agree,

7  huge uncertainty bounds around it.

8	The other thing to do is ask the

9  question what were the air quality levels and air

10   quality patterns and profiles in the areas where we saw

11   effects and what level of a standard of a given

12   averaging time would we need to cause reductions in NO2

13   levels to occur in that area?

14	That's another way to look at epi

15   information as sort of a quasi quantitative way, if you

16   will.  I would suggest that, if you look back at the

17   history of decision making on PM and ozone, that is

18   more the way we looked at the epi evidence even in

19   those reviews than by decisions driven on the specific

20   quantitative estimates of risk with large uncertainty

21   bands around them that came out of the quantitative

22   risk assessments we did in those reviews, so that we

23   don't need to do a quantitative risk assessment to use

24   epi to answer the kind of question you're postulating.

25	We could do both, of course, and have a

83

1  reductions in that important parameter.

2	That's the only one I can come up with

3  that I think that I could defend long term and so what

4  I'm really suggesting is that we -- at least as we

5  explore this, we look for a way to do the risk analysis

6  that could give us that answer, tell us if there is a

7  standard, so that -- but that means we've got to do the

8  analysis around a parameter that's going to give back

9  results and right now the only number that I see from

10   this is maybe a 20 PPB -- how many people in the risk

11   category at a certain standard would have a drop of 20

12   PPB -- this is a 24-hour average, I understand that --

13   to figure out what the average time was and figure out

14   what period of time, but you've got to do something

15   with that so that it relates back to our epidemiology

16   and that's sort of where I am.

17	I'm not sure how to do it, but I -- but

18   I can envision that as the only answer that I could end

19   up defending of changing the standard.

20	DR. MARTIN:    If I could just...

21	DR. HENDERSON:    Go ahead.

22	DR. MARTIN:    If I could just react to

23   that as a way to help the thinking that goes into your

24   subsequent discussion, there are -- taking your

25   scenario of what you're trying -- what you're

85

1  broader characterization of the information, but I'm

2  just saying it isn't -- the quantitative risk

3  assessment alone isn't the only way to use that

4  evidence.

5	DR. HENDERSON:    I'm interested, Karen,

6  in -- you know, you said that this type of analysis

7  that we're looking for would be part of a policy

8  assessment.  You know our problems with the last policy

9  assessment, which was not a policy assessment.

10	In your mind, will there truly be a real

11   policy assessment document developed?

12	DR. MARTIN:    The best way I know how to

13   answer that is comments they made at the last meeting

14   we had and that is it is our intent to produce a policy

15   assessment in the context of the next document we

16   produce, which will be the ANPR, according to our

17   current process, and to do the kind of assessment that

18   we would have historically done in staff papers.  That

19   is our intent.

20	I can't offer guarantees because no one

21   of us alone determines the final outcome of these

22   things, but that is clearly our intent.

23	DR. HENDERSON:    Okay.  I want to hear

24   other people's thoughts.  I mean what Karen has pointed

25   out is the new process has prevented us from seeing the

86

1  kind of data we want as early as we would like and

2  that's not a good thing.

3	So, as part of the problem we're facing

4  here, we would like to see what the agency can do with

5  the epi data, not to do a quantitative risk assessment,

6  but to do the type of thing to answer the question

7  where we see it and epi studies where we see effects

8  associated with NO2 levels, you know, how can we lower

9  the level to avoid that I guess is what you were

10   saying.  I think I said that right.  George?

11	DR. THURSTON:    Well, I guess I'm not

12   ready to roll over on doing a quantitative assessment

13   because I think that's what needs to be done and I

14   would say the uncertainties in the process that was

15   just described regarding the writing of the ANPR are

16   far larger than the uncertainties involved in doing a

17   quantitative risk assessment using epidemiology, so

18   that I think that we should do our work and not rely on

19   the kindness of strangers.  So -- and we should do the

20   best work we can and make it as complete as possible.

21	Now, in reference to the multi-city

22   study question, first of all, I don't think that they

23   are the gold standard they're made out to be sometimes,

24   but I think they are important and they provide

25   information, but I would say my own assessment looking

88

1	DR. HENDERSON:    Great.  You know, I

2  don't think there's anybody arguing that we don't need

3  to use the epi data as we set standards.  It's just

4  that there's this peculiar mind set that you can't give

5  CASAC a staff paper.

6	It might contaminate it in some way and

7  I don't know what -- I shouldn't say it quite that way,

8  but we need that analysis in order to make -- to meet

9  our congressional mandate to advise and recommend a

10   setting of the standards to the agency and without that

11   staff analysis, we're left to do just what -- you know,

12   to do -- just at the present time to look at a

13   quantitative risk assessment that will have huge

14   variabilities associated with it, but you're saying you

15   want that done.

16	DR. THURSTON:    Yes, I am and I think

17   others are saying that.

18	DR. HENDERSON:    Well, I want to hear...

19	DR. THURSTON:    Yes, ask around.

20	DR. LARSON:    Regine, this is Tim Larson

21   calling.  Yes, I was intrigued by James' idea about the

22   daily metric and the hospital admissions because, if

23   you go to a risk assessment model that predicts daily

24   averages rather than hourly values, I think some of

25   this variability and queasiness about the particular

87

1  at the multi-city studies is that they have confirmed

2  what we have seen in doing meta-analysis of multiple

3  individual level studies, at least the conclusions of

4  those.

5	And so -- and we do have a multi-city

6  study for NO2 that shows its resilience against the

7  inclusion of other pollutants and that is the Canadian

8  work by Burnett using mortality.

9	Now, you know, that's another decision

10   whether we want to do it for mortality as well as

11   hospital admissions, but I do think that answers the --

12   you know, that question has been asked and answered.

13	We've done -- someone has done the

14   multi-city study and has shown -- and shown that

15   principle proven, okay, for mortality.

16	Now, it hasn't been done for hospital

17   admissions to your knowledge, but I don't think it

18   needs to be.  I think we have enough studies.

19	We can do a meta-analysis, come up with

20   an estimate, move forward, and come up with

21   quantitative analyses and we have time to do that and

22   we have time to give the American people an

23   understanding of the width and breadth of the problem

24   that is associated -- the health risks that are

25   associated with NO2.

89

1  risk exposure model will be diminished just because

2  you're averaging and the fact that the 24-hour average

3  is a much more robust measure.

4	So I -- there's an appeal in that if

5  that's there the health data is taking us.  I think it

6  also diminishes some of the uncertainty in the exposure

7  analysis exercises.  That's just a thought.

8	DR. HENDERSON:    Any response?  Harvey?

9	MR. RICHMOND:    Well, I would like to

10   hear from the committee.

11	DR. HENDERSON:    Yes.

12	MR. RICHMOND:    I thought we heard a lot

13   in the fall in the discussion of ISA about concern

14   about that it was really the clinical evidence and tox

15   evidence supported concern about peak hourly type

16   exposures.

17	The exposure situations, analysis,

18   certainly that Steven has produced, you know, talks

19   about peak exposures and on road and we've heard a lot

20   of concern about that in the study suggesting proximity

21   to roadways where people don't sit for 24 hours.

22	So I would ask back for the other health

23   experts on this committee, when James Crapo said that

24   we probably need a short-term standard, are we talking

25   about 24-hour standards or are we talking about

90

1  one-hour standards?

2	Because one of the things we have to do

3  also is decide what alternative standards -- it could

4  be a pretty broad range, but we will have to decide

5  what alternative standards we're going to analyze in

6  this next phase and we don't have a lot of time, so I

7  would be interested in feedback as well on this

8  averaging time issue to sharpen it a bit.

9	DR. CRAPO:    I would argue that the

10   really important thing is that we establish a

11   short-term standard, the precedence of looking at that

12   and having one, and the form of it is less important

13   than that you form one and I would -- I would pick the

14   form that you can best defend as the first one.

15	It's going to go on for years, but your

16   question is what can you defend as you go to this very

17   important change?

18	DR. LARSON:    Well, again you've already

19   got the hourly predictions, so you could easily come up

20   with an aggregation of 24-hour averages.  So that's not

21   really a big deal.  I'm not saying you said it was, but

22   I think that's -- that's a fairly straightforward

23   analysis.

24	DR. BALMES:    This is John Balmes.  I

25   agree with what Tim is proposing as something

92

1  or a comment.

2	Isn't the Federal Reference Method now a

3  continuous one hour or continuous and then an

4  accumulation of the one-hour measurements to make the

5  24-hour average?  Is that correct?  If that's

6  correct...

7	DR. THURSTON:    They don't use bubblers

8  anymore.

9	DR. SPEIZER:    Pardon?

10	DR. THURSTON:    They don't use bubblers

11   anymore.

12	DR. SPEIZER:    Right.  That's the old

13   fashioned way, but if that is correct and you've got

14   the data in the Federal Reference Method at hourly

15   levels, there are a considerable amount of work that's

16   been done on modeling the 24-hour averages and, indeed,

17   you could have -- you could have a peak one-hour

18   measure as your -- as your standard and you get all the

19   information you need.

20	DR. HENDERSON:    Well, okay.  Pat?

21	DR. KINNEY:    One way that we -- I think

22   that's emerging from this discussion, one way that you

23   can link the exposure and risk assessment to the

24   epidemiologic findings in a semi-quantitative way would

25   be to do a couple of exposure -- practical exposure

91

1  worthwhile to consider and I agree with James' context

2  that getting any kind of short-term standard would be

3  sort of a major advance and I think actually the epi

4  data, in terms of asthma and exacerbation are -- fit a

5  24-hour averaging time better than an hourly averaging

6  time.

7	DR. HENDERSON:    So you're recommending,

8  because you have more data at 24 hours, to have the

9  short-term standard be for 24 hours?

10	DR. BALMES:    I'm recommending

11   considering that at this point.

12	DR. KLEEBERGER:    Yes, this is Steve

13   Kleeberger.  I would agree with John and all the

14   discussions going on.

15	You know, I recently found transitional

16   epi studies that support a role for short-term

17   high-peak exposures related to death in infants

18   attributed to SIDS and these are three replicated

19   studies in Canada and two in the United States I

20   believe and they all associate with daily peaks of NO2

21   and averaging across 24 hours I think would give you --

22   at least in terms of these kinds of studies would be

23   the most appropriate way to go.

24	DR. HENDERSON:    Okay, Frank?

25	DR. SPEIZER:    I have sort of a question

93

1  things.

2	I mean one clear thing is, in Section 6,

3  do some work on 24-hour averages, as well as for the

4  peak levels, using the ambient data and then, in

5  Section 7, likewise, you know, why not -- why not look

6  at the 24-hour average personal exposures that you're

7  modeling and importantly add an analysis of how, in the

8  apex modeling process, you end up -- what you end up

9  seeing in the relationship between the central site

10   modeled 24-hour average levels are in the apex analysis

11   and the distribution of personal exposures.

12	What is the relationship between those

13   two quantities?   Because the epidemiologic results

14   obviously are based on the central site type monitoring

15   and it would be very I think informative to our

16   thinking to understand, based on a careful analysis of

17   exposure activities and spatial distributions and

18   everything else, how the sort of typical personal

19   exposures relate to that central site data.

20	DR. HENDERSON:    Thank you, Pat.  Harvey,

21   did that sound -- are we telling you anything here?

22	MR. RICHMOND:    I guess I heard certainly

23   that the data is more available, the epidemiological

24   data, on a 24-hour basis, but I guess I'm asking this

25   committee's expert judgment in a sense.

94

1	Is that really where you believe the

2  health effects -- sort of the source of the health

3  effects, that's it's the 24-hour average or one-hour

4  average?

5	Because again there's a huge difference

6  between looking at alternative peak one-hour standards

7  and looking at 24-hour average standards and the epi is

8  at much lower levels.

9	As Pat Kinney said, is it a signal for

10   on a road as opposed to truly those low NO2 24-hour

11   averages?  Do we really mean to imply that?

12	DR. HENDERSON:    George?

13	DR. THURSTON:    Well, I just have a, you

14   know, clarification question.

15	You say there's a huge difference

16   between looking at the 24-hour and the one-hour.  In

17   what context?  In what sense do you mean that?

18	MR. RICHMOND:    I expect an analysis of

19   analyzing short-term hourly NO2 standards and again we

20   haven't talked levels.

21	Say if it was at our benchmarks in the

22   .2 to .3 range, you know, what kind of 24-hour

23   standards would we be looking at?

24	The epi doesn't point so far because we

25   haven't done that analysis of what their quality levels

96

1  the epi supports going down at 24-hour averages?

2	DR. THURSTON:    Oh, I can't give you a

3  number.

4	MR. RICHMOND:    Well, that's the problem.

5	DR. CRAPO:    I will.

6	DR. THURSTON:    Well, I would have to

7  think about it.

8	SPEAKER:    In a nutshell.

9	DR. CRAPO:    No, seriously, the way I

10   would answer that is I want to know what level we would

11   have to set the standard at that would result in a 20

12   part per billion decrease for a significant segment of

13   our population.

14	SPEAKER:    For what average, 24 hours?

15	DR. CRAPO:    For a 24-hour average

16   because that's what the epidemiologic data...

17	MR. RICHMOND:    But a 20 PPB decrease

18   from as-is levels, the current...

19	DR. CRAPO:    Yes.

20	MR. RICHMOND:    ...air quality levels?

21	DR. CRAPO:    Yes, yes.  I mean there's...

22	MR. RICHMOND:    Because that 20 PPB was

23   chosen just as a standardized increment to...

24	DR. CRAPO:    I understand that.  I'm just

25   saying that -- saying that that overall exposure on a

95

1  -- other than to say it's below the annual standard.

2	The epi effect estimates are for a

3  standardized change, but there's no -- they're linear.

4  They're, you know, generally linear in nature down to

5  very low levels.

6	So the epi -- I would still like to see

7  how that informs a choice of alternative 24-hour

8  standards if that's what we're talking about.

9	DR. THURSTON:    Well, I would just say I

10   agree with James Crapo's advice, which is to look at --

11   I think the impetus is to get a short-term standard to

12   protect public health and you just -- you have to work

13   with what you've got and I hope that, in the next five

14   years, that people will, you know, look more deeply at

15   these questions that are identified in this process,

16   but you've got to work with what you've got and go with

17   an averaging period where you've got the strongest

18   epidemiological data to support it.

19	So that's the way I would choose between

20   the one-hour and the 24-hour.  You've got most of the

21   studies and you're going to base your risk analysis

22   mostly on a 24-hour average and, you know, that's the

23   way I would go.

24	MR. RICHMOND:    In your interpretation of

25   the epi, what are the appropriate range that you think

97

1  24-hour average...

2	MR. RICHMOND:    Right.

3	DR. CRAPO:    ...is -- is associated with

4  those health benefits.  Why -- I just used -- because

5  that's your data.  I would use my gold standard and I

6  would say, well, then I've modeled -- if I set the

7  standard at this level for a 24-hour average, how many

8  -- and then I -- I would find a level at which -- at

9  which it didn't change anything in the country.  So you

10   can set it at this level.  Everybody is...

11	MR. RICHMOND:    Well...

12	DR. CRAPO:    ...below it and so it

13   doesn't have any impact.

14	MR. RICHMOND:    Well, the...

15	DR. CRAPO:    Then I would try it down in

16   increments until I started to see how many million

17   people would benefit with a 20 PPB benefit.

18	MR. RICHMOND:    You're going to see

19   current levels are variable.  They're clearly below the

20   current standard, they're in .03, but there's not a

21   uniformity.  There's going to be a variety.  L.A. has

22   higher levels than I would suspect Atlanta and smaller

23   cities.  Applying the epi, you're going to see a

24   continuous decrease no matter, you know, what levels

25   look at based on...

98

1	DR. CRAPO:    But that's exactly what I'm

2  saying and I'm arguing that you want to draw me a

3  curve, so let's -- I don't care.  Let's center it at

4  point -- for 24 hours, what's a reasonable one, .01 or

5  something?  I don't know.

6	Anyway, pick some number at which there

7  is no exceedance by anyplace in the entire United

8  States and then sequentially drop it and calculate how

9  many people in the United States would have a 20 PPB

10   decrease and give me a curve of that so we can see how

11   far you have to drop it before you start to get a

12   significant portion of the population with the benefit

13   and then you can start to analyze your data.  So it

14   will be -- it's a curve function, so draw us the curve.