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 U.S. ENVIRONMENTAL PROTECTION AGENCY

 + + + + +

 CLEAN AIR SCIENTIFIC ADVISORY COMMITTEE

 OZONE REVIEW PANEL

 + + + + + 

 PUBLIC MEETING

 + + + + +

 FRIDAY, MAY 20, 2011

 + + + + +

 The meeting convened in the

Chancellor's Ballroom of the Carolina Inn, 211

Pittsboro Street, Chapel Hill, North Carolina,

at 8:30 a.m., H. Christopher Frey, presiding.

CASAC MEMBERS PRESENT:

H. CHRISTOPHER FREY

JONATHAN M. SAMET, CHAIR*

GEORGE A. ALLEN

JOSEPH D. BRAIN 

ARMISTEAD (TED) RUSSELL

HELEN SUH 

KATHLEEN WEATHERS*

PANEL MEMBERS PRESENT:

ED AVOL

JOHN BAILAR

MICHELLE BELL

DAVID CHOCK

WILLIAM MICHAEL FOSTER 

JUDITH GRAHAM

DAVID GRANTZ

JACK HARKEMA

DANIEL JACOB

STEVEN KLEEBERGER 

FREDERICK J. MILLER
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HOWARD NEUFELD

JAMES ULTMAN

SVERRE VEDAL*

PETER WOODBURY

SCIENCE ADVISORY BOARD STAFF:

HOLLY STALLWORTH, DESIGNATED FEDERAL OFFICER

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

Presentation on Scope and Methods Plan for 

Health Risk Assessment 8

Public comment 60

Exposure Analysis Issues 77

Health Risk Assessment Issues 121

Presentation on Scope and Methods Plan for 

Health Risk Assessment 198

Air Quality Considerations 244

Ecological Effects, Ecosystem Services 264

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

2 (8:35 a.m.)

3 DR. FREY: Okay, let's come to

4 order. Good morning. I am one of the

5 mysterious voices on the phone from yesterday. 

6 My name is Chris Frey, and I'm a member of the

7 panel. I wasn't able to be here in person

8 yesterday, but I was on the phone. And John

9 is not able to be here today, and -- John

10 Samet, you're on the phone? Or maybe not yet. 

11 So we've traded places.

12 DR. SAMET: I'm here. I'm here.

13 DR. FREY: Oh, good.

14 DR. SAMET: Yes.

15 DR. FREY: Okay, welcome. So, the

16 purpose of today is to do what is called a

17 consultation on the scope and methods plan for

18 the health risk and exposure assessment, and

19 the scope and methods plan for the welfare

20 risk and exposure assessment. 

21 A consultation is a little bit

22 different than a review. So, yesterday, you
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1 had lead discussants, and the lead discussants

2 are -- have the responsibility to develop a

3 consensus statement and response to a charge

4 question, and we'll be working with Dr. Samet

5 to develop a consensus letter that we as a

6 panel will review through teleconference in a

7 few weeks.

8 In contrast, with a consultation,

9 we're not obligated nor required to reach a

10 consensus. There will be a very brief letter

11 to the administrator that simply states that

12 we held a consultation today on these two

13 scope and methods plans, and the letters will

14 have an attachment of the individual member

15 comments.

16 So, anything you would like to

17 convey in writing to the US EPA, you will need

18 to do so under your name as your individual

19 written comments. And if there's something

20 that you hear in the discussion today that you

21 agree with, if you want to communicate that to

22 EPA, you should do that in your written
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1 comments. And likewise, if there's something

2 you would like to take issue with, you would

3 need to do that in your own comments.

4 So, we're not going to try to

5 reach a consensus on each issue. What we will

6 do today is EPA will make a presentation on

7 the -- first the scope and methods plan for

8 the health risk and exposure assessments, and

9 then we will have member comments on the

10 exposure and health risk analysis issues

11 regarding that scope and methods plan.

12 Once we get through that, then EPA

13 will present on the welfare scope and methods

14 plan, and then we will have individual

15 comments.

16 Now, there are identified

17 discussants for each of these scope and

18 methods plans. I will call in those people

19 first. But any Panel Member will have an

20 opportunity to provide comments during the

21 discussion today. And as I said earlier, I

22 would encourage you as we go through the
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1 discussion to think about either revising your

2 written comments, or if you haven't submitted

3 written comments, think about what you might

4 want to submit in writing, and I'm sure Holly

5 will work with us to set a deadline for when

6 those should be submitted.

7 Any other procedural points,

8 Holly? Okay. Any questions on what's meant

9 by a consultation? Okay, good. All right,

10 so, with that, I would like to invite the US

11 EPA to please go ahead and present to us on

12 the scope and methods plan for the health risk

13 assessment.

14 MS. WEGMAN: Good morning. This

15 is Lydia Wegman again. Thank you all for

16 returning, and again, thank you all for your

17 work yesterday.

18 My team here is going to be

19 presenting in a moment. I'll just quickly

20 introduce folks, and then I want to just say

21 a couple of words about resources before I

22 turn it over to this team of ours, which has
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1 done a great job in my view on the scope and

2 methods plan.

3 This is Dr. Zach Pekar. Dr. Bryan

4 Hubbell is sitting back here. He's been

5 leading the team, Dr. John Langstaff and Dr.

6 Travis Smith, and they will be key presenters

7 today on the scope and methods plan. 

8 Before I take a seat in the back,

9 there were some comments yesterday, and there

10 have been comments throughout, expressing

11 concerns about resources, and the points we've

12 made in the scope and methods plan about

13 resources. 

14 I just want to let you all know

15 that I think from reading the newspapers you

16 all know that it is a time of shrinking

17 resources for the federal government, and

18 especially for EPA. And in putting what we

19 put into the plan, we wanted to alert you that

20 what we are putting together may be

21 constrained by the resources that are

22 available to do the analyses that we are
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1 setting out. 

2 We are trying to do as much work

3 in-house as we are able to, to minimize the

4 need for additional contract dollars, and we

5 do have really a team of outstanding folks who

6 will do as much work in-house as we can. But

7 -- and we want to do as much of the analyses

8 as we can, but part of what we're asking for

9 your advice on is how to prioritize the

10 different tasks that we've laid out. Because

11 if we do have limited resources, we want to

12 know what you view as the most important

13 things to do with those resources.

14 So, it's not that we want to limit

15 our work; it's that we realize we may be

16 limited by the amount of money available to

17 us. And so, that's the advice we're seeing

18 from you. Okay, thank you.

19 MR. LANGSTAFF: Okay, so Zach and

20 I are presenting the overview of the plan for

21 the Ozone Health Assessment; the purpose of

22 the plan and this meeting is to get feedback
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1 on the methods we're proposing for assessing

2 risk under different air quality scenarios. 

3 I'll be talking about the exposure modeling,

4 and the risk assessment based on clinical

5 studies and Zach will cover the risk

6 assessment based on epi studies.

7 In the last review, we estimated

8 exposure and risk for the general population,

9 children and asthmatic children for different

10 air quality scenarios.

11 We did this for 12 cities across

12 the US. In this review, we might only be able

13 to do this for three cities. We planned on

14 using the most recent three-year period for

15 air quality with complete data for this

16 analysis, and we'll be using the quadratic

17 rollback approach to adjust the distribution

18 of hourly ozone concentrations to reflect 

19 attainment of the current standard and

20 alternative standards.

21 The last review we took into

22 account policy relevant background. In this
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1 review, we're not really even using that term. 

2 We're going to put a focus on contributions

3 from natural background and international

4 transport in more detail. And to be able to

5 do this, we have four global simulations of

6 those being done using the GEOS-Chem model,

7 and one is natural background, where there is

8 no anthropogenic emissions anywhere globally;

9 one where you have only anthropogenic

10 emissions outside North America, but the

11 emissions in North America are set to zero; a

12 third where the emissions in the US,

13 anthropogenic emissions, are set to zero, and

14 a fourth with current conditions.

15 And we'll be taking into account

16 the anthropogenic methane emissions

17 appropriately. Some runs to use it for the

18 same value for those for the different

19 scenarios, but we're factoring that in

20 properly.

21 The APEX model estimates the

22 distribution of exposures of the population. 
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1 It does this by simulating many individuals. 

2 It uses a database of diaries to mock the

3 locations and activities of individuals and

4 calculates their exposures while they're doing

5 different activities in different

6 microenvironments.

7 A physiological model estimates

8 their ventilation rates, and combining that

9 with their exposures, the lung function effect

10 is estimated.

11 We'll be analyzing five groups,

12 five population groups: the general

13 population, school-aged children, asthmatic

14 school-aged children, outdoor workers, and

15 elderly. In the last review, we did not look

16 at outdoor workers, although we did it in the

17 review prior to that, and this is the first

18 time we're breaking out the elderly as a

19 separate group.

20 So, we'll be -- some new analyses

21 we'll be doing: one is doing our analysis of

22 the different conditions that are associated
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1 with high exposures and risk, hot blazing

2 attributes, activities, microenvironments,

3 locations and things like that.

4 We'll be estimating fractional

5 contributions to exposure and risk from

6 international and national sources, using

7 those four GEOS-Chem runs to do that. This is

8 not straightforward because nonlinearities of

9 ozone formation and that -- the response of

10 ozone to changes in emissions will depend on

11 the levels of other pollutants.

12 And so, you can actually have

13 situations where your emissions are reduced,

14 but your ozone increases. So, it's not a

15 straightforward problem to estimate these

16 fractional contributions. And we'll be doing

17 a qualitative analysis of the effect of the

18 air quality index on people's behavior and how

19 that affects their exposures.

20 So, we'll be modeling both

21 variability and uncertainty of exposure and

22 risk, and variability is built into the APEX
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1 model. The results of each model run reflect

2 this variability, and the results of the model

3 are given as distributions of exposures,

4 population distributions, and the types of

5 variability of the model are population

6 demographics, which we have at each census

7 tract, the physiology of individuals, ozone

8 concentrations, which vary by hour and then

9 across space, activity patterns, and then the

10 variables that go into calculating indoor

11 concentrations and indoor exposure, such as

12 air exchange rates, ozone decay and deposition

13 rates, penetration factors and air

14 conditioning.

15 In order to estimate uncertainty,

16 we're using a two-dimensional Monte Carlo

17 approach, as we did in the last review. This

18 time, we'll be extending the quantitative

19 assessment of uncertainty to include the lung

20 function risk estimates.

21 So, this risk assessment looks at

22 lung function in terms of FEV1 decrements
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1 greater than 10, 15 and 20 percent, and the

2 policy assessment will address the public

3 health significance of these particular cut

4 points. And the last review, population level

5 exposure response functions were combined with

6 the distributions from APEX to give us these -

7 - the risk lung function. 

8 In this review, we're using

9 improved model based on work by McDonnell,

10 Stewart and Smith, that allows to estimate the

11 lung function decrements for individuals in

12 the APEX model. We'll use the old method

13 also, so we can compare the results of the

14 two. 

15 In both of these methods, the

16 exposure response relationships are derived

17 from clinical studies. So, the new model

18 allows us to estimate lung function decrements

19 for each simulated individual, and should

20 result in more accurate estimates of risk for

21 this end point.

22 It predicts changes in FEV1 based
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1 on individuals' physiology and time varying

2 ventilation rates and ozone exposures, which

3 APEX estimates for every minute for each

4 individual, and a person's changes in FEV1 at

5 a given time depend on the values of these for

6 the previous few hours.

7 The authors fit the model using

8 data from several clinical studies, where the

9 ages range from 16 to 35, and ozone exposures

10 were between 80 and 400 ppb. We are -- we

11 planned to obtain data from other additional

12 studies that have lower lowest ozone, and

13 hopefully children. Otherwise, it's going to

14 be problematic to extend this to children. 

15 We have data from a recent EPA

16 study by Kim and others, that have exposure at

17 60 ppb and there are other studies out there

18 that have exposures at 40 ppb. 

19 Once we obtain all this data, we

20 will refit the model using that data to get a

21 better handle on the range of exposures, and

22 we'll be able to do a quantitative analysis of
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1 the uncertainty of these risk assessments. 

2 And now, I'll turn it over to Zach.

3 DR. FREY: Maybe while we're

4 waiting, are there any clarifying questions

5 for John Langstaff? I see Ted and Ed.

6 DR. RUSSELL: Couple questions. 

7 So, you're going to be using APEX. And is

8 that going to be done in-house or out of

9 house?

10 MR. LANGSTAFF: That's being done

11 in-house.

12 DR. RUSSELL: That will be done

13 in-house?

14 MR. LANGSTAFF: Yes.

15 DR. RUSSELL: Because that depends

16 how many possible cities you can do.

17 MR. LANGSTAFF: Right, correct. 

18 DR. RUSSELL: The second. You

19 said you're going to -- you treat methane

20 properly in your slides, but when I read the

21 document, it was very unclear what you're

22 going to do with methane and why.
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1 MR. LANGSTAFF: Right. So, when

2 we wrote the scope and methods plan, we

3 thought that we were going to have to do this

4 adjustment to the model results, but we've --

5 the model run is now being done with correct

6 methane inputs, and so, we're not going to

7 need to do that adjustment of the model

8 results. That's not to say that the models

9 are correct, but as far as the models, we're -

10 -

11 DR. RUSSELL: Anthropogenic

12 methane emissions specifically?

13 MR. LANGSTAFF: Right. So, we're

14 doing those reductions. Right, appropriately.

15 DR. HUBBELL: And it's understood

16 we're looking at the mixing ratios, rather

17 than trying to take the emissions of methane

18 and zero them out in a particular way,

19 although it would be nice to model that

20 through. But most of the -- and maybe Daniel

21 can talk about that.

22 DR. RUSSELL: So, you're not
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1 treating the methane, anthropogenic methane --

2 directly?

3 MR. LANGSTAFF: Actually -- well,

4 I mean it's in there sort of as a constant

5 concentration across the globe. I mean you

6 can do model runs of the emissions, but since

7 the methane has a long lifetime, you need to

8 model, you know, decades to bring that up to

9 speed. 

10 So, we're adjusting the methane

11 concentration that's in the model to reflect

12 these differences in emissions, and it's not

13 exactly straightforward because you can't just

14 say, "there's 20 percent." You're reducing 20

15 percent emissions, so you take 20 percent off

16 that concentration because it's a feedback

17 factor in those other things.

18 So, there's some uncertainty in

19 how we're going to do that, but yes.

20 DR. JACOB: For natural methane

21 concentrations, we use the data from the ice

22 spores. So, we know what the concentration
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1 was before human activity.

2 MR. LANGSTAFF: Right.

3 DR. JACOB: So, the natural ozone

4 concentrations, as you decided from GEOS-Chem,

5 uses pre-industrial methane. Now, we also did

6 a run with present day methane and other

7 global anthropogenic sources shut off. So, if

8 we wanted to single out the effect of methane,

9 which is about 5 ppb, we could do it. 

10 DR. RUSSELL: So, then just count

11 the North American methane versus --

12 DR. JACOB: This we haven't done,

13 and as John pointed out, that might be

14 difficult to do. Well, it's very small. I

15 mean the North American anthropogenic

16 emissions are very, very small contribution to

17 the global anthropogenic source of methane,

18 which is largely from livestock and rice

19 paddies and natural gas.

20 MR. LANGSTAFF: Yes, so, we're

21 making our adjustment, but it's not going to

22 have much effect.
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1 DR. HUBBELL: Yes, and our plan --

2 we're considering adding a chapter to this

3 document, to focus on international

4 contributions to ozone and risk. One of the

5 things we've been discussing is the need to

6 separate out methane from other precursors

7 because of the difference in the time it takes

8 for it to fully affect the ozone

9 concentrations, and that's why we're more

10 interested in breaking it out, and not

11 treating it like other international

12 emissions, which would directly affect shorter

13 term ozone.

14 DR. FREY: Okay, Ed, did you have

15 a question?

16 MR. AVOL: Yes, I have a quick

17 question. So, you said you'd use the 2008 to

18 2010 data, and that makes sense because I

19 guess that's the most recent available. But

20 I have a question about how generally

21 representative 2008 to 2010 is in terms of --

22 MR. LANGSTAFF: Well, those years
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1 are generally lower, I guess, than previous

2 years. So, we're going to -- we'll consider

3 doing a couple earlier years, which also for

4 the exposure might be important to match up

5 with the time period of GEOS-Chem runs. 

6 That's not so important with the risk because

7 the exposures depend on temperatures, which

8 are related to the ozone. So, it's sort of

9 more important to match up for the model runs

10 for the exposure. The risk doesn't depend on

11 the temperatures.

12 MR. AVOL: Yes, that's what it

13 seems like. I mean however you decide, it

14 seems like it's worth the paragraph or some

15 comment about what you did and why you did it.

16 MR. LANGSTAFF: Right.

17 DR. FREY: Just keeping in mind

18 this is mainly clarification, and we want EPA

19 to finish their presentation. Then we can do

20 the consultation. But are there other

21 clarifying questions? Fred.

22 DR. MILLER: Can you, as you go,
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1 identify what's going to be in-house and

2 what's going to be out house? Because I am

3 already prioritizing based on your

4 presentation. There are several things that

5 I want you not to do because they're a waste

6 of time. Is that okay?

7 MR. LANGSTAFF: Okay, well,

8 that'll be useful.

9 DR. MILLER: And yet I don't know;

10 it might be something that is a trivial thing

11 to extend, or it may be that it costs you big

12 bucks to go outside. So, as you're describing

13 these things, could you please kind of give us

14 a sense of where the responsibility will lie?

15 MR. LANGSTAFF: Yes. It's all in16 house.

17 DR. MILLER: Oh, Lydia. Were you

18 politicking for money? What do you mean

19 there? 

20 DR. HUBBELL: To be clear on that,

21 what John is saying is it's all in-house right

22 now, but some of the things that we've
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1 identified as uncertainties, other things that

2 could be addressed, would be required to go

3 outside. 

4 DR. FREY: Okay, Zach, I think

5 you're -- okay, one last clarifying comment. 

6 David?

7 DR. CHOCK: Have you prioritized

8 what to do based on the availability of your

9 resources?

10 MR. LANGSTAFF: No, we haven't. 

11 We're going to do what we set out in the plan. 

12 The parts of the plan say if available --

13 resources are available. We haven't

14 prioritized yet because we don't know if

15 there's going to be any resources available.

16 DR. JACOB: I have one clarifying

17 question about in-house versus outside work. 

18 So, the GEOS-Chem values that you're using,

19 are they coming from Harvard, or are they

20 coming from ICF? Because I know ICF has a

21 contract with EPA now to generate -- to repeat

22 essentially exactly the same GEOS-Chem
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1 calculation that we've done at Harvard. And

2 I was wondering --

3 MR. LANGSTAFF: Right, yes. ORD

4 is doing that essentially. So, we're going to

5 use those. That part is being done by a

6 contractor, but that's ORD work, and ICF is

7 doing those runs.

8 DR. JACOB: So, ICF is doing the

9 work for ORD, and you're going to get them

10 from --

11 MR. LANGSTAFF: Right, yes. If we

12 can -- if somehow we could use those other

13 runs you're doing, that would be useful.

14 DR. JACOB: You already have them. 

15 That's what I don't understand.

16 MR. LANGSTAFF: Well, I think they

17 need to be published, or -- they need to be

18 published I think to use them. But that would

19 be very useful to be able to use those.

20 DR. FREY: Okay. 

21 DR. JACOB: Yes, that is a waste

22 really.
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1 DR. MILLER: You can get this

2 published and available, and this is the kind

3 of duplication that is just not acceptable in

4 today's environment.

5 DR. HUBBELL: I don't know if John

6 wants to comment on the process reason or not? 

7 No? Okay, John does not wish to comment.

8 DR. FREY: Okay, Zach. I think

9 the floor is yours.

10 DR. PEKAR: Okay. So, I'll just

11 go ahead and -- and -- my goal here is --

12 there's a fair amount of content in the

13 presentation. The overview of the risk, the

14 epi based risk assessment, is what I'm going

15 to be covering. There's a fair amount of

16 content in the presentation, but I'm much more

17 interested in hearing you guys talk about the

18 content, rather than me go on about it. So,

19 I'm going to try to move through this fairly

20 quickly.

21 So, just taking a look at what we

22 did in the last review. John had mentioned
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1 this. We modeled 12 urban study areas, using

2 epidemiology based effect estimates. I think

3 there may be some people on the CASAC Panel

4 that are not familiar with the risk assessment

5 that was done for ozone. So, I will give a

6 little bit of background here.

7 We assessed risk for as-is current

8 conditions, as well as simulated attainment of

9 the current standard at that point, and then

10 also looking at what kind of risk reductions

11 would be associated with a simulated

12 attainment of alternate standard levels. 

13 That's pretty much the way we do these NAAQS

14 risk assessments.

15 For the last review, we focused

16 exclusively on short-term exposure related

17 endpoints: morbidity and mortality endpoints. 

18 They're listed here.

19 I'm not going to go through them

20 in detail, but we did not consider any long21 term -- the term, even though that's a complex

22 term, any kind of long-term seasonally
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1 averaged peak kind of endpoints. And

2 ultimately, the estimates, the risk estimates,

3 did provide -- did play a role in the decision

4 regarding the eight-hour standard. 

5 So, obviously that's a little more

6 complicated statement, but they were used from

7 a policy standpoint. 

8 In the design of the risk

9 assessment, or working on the design of the

10 current risk assessment, we started by setting

11 a series of policy related questions. So,

12 what did -- what kind of questions did we want

13 to address with the risk information? 

14 Obviously beginning with the

15 nature and magnitude of public health impacts. 

16 So what are the nature and magnitude of public

17 health impacts under the current conditions,

18 and if we attained the current standard? And

19 what is the magnitude of risk reduction under

20 alternate standard levels that we might

21 consider? That's pretty standard fare.

22 We are interested in how those
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1 risks vary across urban study areas. So,

2 let's say that we end up modeling 10 to 20

3 urban study areas. We'd be interested in

4 looking at how varied the risk reductions are

5 under alternate standard levels across those

6 study areas, and what the reasons for that is. 

7 It helps us understand the nature of the risk

8 -- risk results and estimates.

9 I think the next three bullets we

10 have addressed in varying levels and past

11 analyses, but I think it's fair to say that

12 this is an area that we're really focusing

13 more on for this risk assessment. Those of

14 you who are familiar with the PM NAAQS risk

15 assessment, we did some of the same kind of

16 work I described for that analysis.

17 So, we are interested in looking

18 at the representativeness of the urban study

19 areas that we model. So, if we model again,

20 let's say, 12, 14 -- whatever number of urban

21 study areas we decide to model, we're

22 interested in knowing how representative those
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1 modeled study areas are of larger urban study

2 areas across the US.

3 So did we model study areas that

4 fall within the upper distribution with

5 regards to potential ozone risk? Did our

6 study areas sort of generally cover the

7 distribution and what is the nature of the

8 study areas that we modeled? I think that's

9 useful. 

10 Then we were interested in

11 characterizing -- in looking at uncertainty

12 and variability. And I'll talk a little bit

13 more about that in a few slides. Then

14 ultimately we also would like to make some

15 kind of statement about the overall confidence

16 that we have in the risk estimate -- the risk

17 estimates. That's always an important but

18 sort of challenging task to take on.

19 So, this slide just provides a

20 flow diagram of the way that we conduct one of

21 these ozone risk assessments. This is

22 obviously very similar to a number of the
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1 other NAAQS that we look at, for instance PM. 

2 Just to go over it very briefly,

3 obviously there's a lot of complexity in each

4 one of these modeling element boxes. But just

5 to touch on it briefly, with regards to air

6 quality, we have to characterize recent air

7 quality we use, monitor data, obviously,

8 within an urban study area to -- as the basis

9 for characterizing current air quality. We

10 have to simulate alternate standard levels by

11 using some kind of rollback. I'll touch on

12 that later.

13 Then I think a point that John

14 mentioned that I'd like to reiterate is this

15 issue of characterizing what we used to call

16 policy relevant background. We're now looking

17 at obviously -- if you look at the total ozone

18 levels characterized by monitors, we'd like to

19 be able to apportion that into various source

20 categories, whether it's non-North American,

21 international, anthropogenic. It's maybe

22 North American anthropogenic. Then US
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1 anthropogenic, looking for instance at natural

2 background, trying to divide that risk

3 estimate into its various components. We

4 think that that would be useful.

5 Next box down is concentration

6 response functions. We use epidemiology based

7 to effect estimates. I'll talk about the

8 endpoints we're considering modeling in a

9 slide or two. Then the final box at the

10 bottom in terms of inputs; we have to have a

11 characterizing of baseline incidence rates. 

12 So, we can't model an endpoint if we don't

13 have baseline incidence rates.

14 Some of the long term -- what's

15 termed long term exposure studies look at

16 genetically differentiated populations in

17 terms of the response to respiratory effects. 

18 That would be problematic for us to include in

19 the risk assessment because we don't have

20 baseline incidence rates for specific subsets

21 of the population. Not that we can't use

22 those kinds of studies in the evidence
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1 analysis that goes into the ultimate decision,

2 but we may not be able to include those in the

3 risk assessment, for instance, because we

4 wouldn't have the baseline incidence rates.

5 Then we have to have population

6 data. So, we have to be able to enumerate the

7 populations that we're modeling for a given

8 endpoint. And then obviously the rest of the

9 flow diagram shows that these various modeling

10 inputs and elements go into a risk model, and

11 then we end up generating the risk estimates

12 on the right-hand side.

13 So, now, what I'd like to do is

14 talk about specifically what we're planning to

15 do hopefully that is somewhat new, or touch on

16 sort of new elements of this risk assessment. 

17 I need to go through various components of

18 that.

19 So, these slides sort of track

20 that flow diagram that I just presented. So,

21 beginning with air quality characterization. 

22 So, for the previous risk assessment, I think
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1 we've already touched on this. Yes, so, we're

2 just going to move ahead. 

3 In terms of the monitor based

4 exposure surrogate, I think most people here

5 are familiar with the fact that we have a

6 number of monitors within a city. We tend to

7 use those monitors to construct an exposure

8 surrogate, a composite monitor, that usually

9 matches what was done in the underlying epi

10 study.

11 For this analysis, we're

12 considering that, but we're also considering

13 the use of Voronoi neighbor averaging, which

14 is a spatial interpolation technique for

15 generating -- and it's basically for getting

16 sort of a composite monitor estimate by taking

17 a weighted -- a distance weighted average of

18 the monitor values within an urban study area.

19 I can talk about this a little

20 more if we want to get into this, but part of

21 the reason for doing this, which I'll touch on

22 in a second, is that we're considering doing
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1 the risk assessment within BenMAP, which is a

2 risk population health impact model that we

3 have in EPA. And it has some sort of

4 automated procedures for doing some of the

5 spatial interpolation techniques.

6 So, if we find, for instance, that

7 if we use a composite monitor approach where

8 we've matched monitors to an epi study, and if

9 we use the VNA approach, Voronoi Neighbor

10 Averaging, and we get essentially a similar

11 kind of estimate, it may be fairly and more

12 efficient to use the VNA approach.

13 So, this is one of the sensitivity

14 analyses we're looking at for how to structure

15 your exposure surrogate and modeling risk. 

16 So, there's obviously some detail there that

17 I'm sort of moving through fairly quickly, but

18 just to touch on that issue, we can re-visit

19 it if people are interested.

20 And then just the final bullet. 

21 We're going to simulate attainment of the

22 current alternate standard levels, using
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1 quadratic rollback. John had already touched

2 on that. 

3 So, in terms of risk

4 characterization, selection of health effects

5 endpoints, there was some discussion yesterday

6 with regards to the ISA on this topic, and

7 we're certainly open to more feedback from the

8 Committee on this.

9 For short-term exposure, well, why

10 don't we just stop for a second. We're likely

11 to, again, as we usually do, focus on

12 endpoints that were classified in the ISA as

13 either having a cause or a likely causal

14 degree of support.

15 And with regards to short term

16 exposure, that means that we're going to be

17 modeling respiratory morbidity endpoints. I'm

18 not going to get into those in detail here,

19 but that category, and also short-term

20 mortality endpoints.

21 So, these are going to be sort of

22 a similar set of endpoints with updated
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1 studies to what we would've done in the last

2 review. But I think the point that is

3 particularly of interest here is we're also

4 considering modeling long-term, and I put that

5 in quotes, because there are a variety of

6 different metrics that are used in these

7 studies, in maybe a seasonally-averaged peak

8 hourly estimate, for instance, and there are

9 other metrics obviously. But we're

10 considering looking at long-term respiratory

11 morbidity that was classified as having a

12 likely causal association in the ISA.

13 There are a variety primarily of

14 asthma related hospital admissions studies in

15 specific cities, some areas of California,

16 that we're looking at possibly. 

17 We're also considering looking at

18 long-term respiratory related mortality. Let

19 me just be very clear, considering as -- we're

20 saying considering because that's what we're

21 doing right now. We're definitely interested

22 in feedback from you.
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1 If you look at the Jerrett study,

2 I think the point that we would point out is

3 that when you look specifically at respiratory

4 related mortality, my understanding is that

5 was not something that was called out in

6 previous studies.

7 Often in past studies, looking at

8 long-term related mortality, they looked at

9 more aggregated mortality categories, and

10 didn't look specifically at the respiratory

11 category in particular; when they did that in

12 the Jerrett study, they saw a more

13 statistically significant effect.

14 If we combine that with the fact

15 that some of these other long-term morbidity

16 studies looked in particular at respiratory

17 causes, and saw associations, we think there

18 may be a little bit more support there for

19 that mortality category, but once again, we're

20 interested in your feedback.

21 And then the final bullet down

22 here. For the PM NAAQS, we looked at modeling
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1 mortality across a much larger set of cities

2 than just the case studies, and we're again

3 considering that here for ozone. Because when

4 we do it modeling and mortality for instance

5 across the ACS set of cities, that allows us

6 to look at a representativeness issue, and I

7 can talk about that in a second. 

8 That also give us a much broader

9 assessment of ozone's public health impact,

10 not just in the subset of cities we looked at,

11 but at sort of a near national or sort of a

12 more -- a broader look at the urban impact

13 across the country.

14 Considering -- continuing with

15 risk characterization, the selection of urban

16 study areas. I'm going to hit this very

17 quickly. We're essentially going to use

18 criteria we've used in the past, which is do

19 we have good air quality data in these cities? 

20 Do these cities provide good coverage

21 geographically and demographically for

22 different parts of the country? Are they
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1 represented with effect estimates of interest

2 in some epi-studies that we're focusing on? 

3 And one point I would like to

4 highlight here in the final bullet is that if

5 we decide to look at long-term related end

6 points, then we might want to look at the

7 relationship at some of the long-term -- the

8 peak to mean sort of air quality statistics

9 across the cities to make sure that we include

10 cities, for instance, that have very peaky

11 ozone levels, versus cities that have more

12 sort of uniform peak kind of metrics, to make

13 sure that we've covered a range of those

14 cities.

15 We did this with PM, looking at

16 the relationship between, for instance, daily

17 averages and annual averages. It's more

18 complicated, much more complicated, with ozone

19 because it's not as cleanly defined that way. 

20 But we might want to look at that kind of an

21 air quality metric to make sure that we're not

22 excluding a city. 
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1 Sorry about that for moving away

2 from the mic. That we're not excluding cities

3 that might have an interesting relationship in

4 terms of flatter or more peaky air quality

5 distributions.

6 Methods for adjusting uncertainty

7 and variability. So, I think the point to

8 highlight here, just to sort of move quickly,

9 is that we're considering the use or we're

10 planning to use the World Health

11 Organization's four-tiered approach to

12 addressing uncertainty and variability.

13 Basically, they provide a

14 structured means for looking at moving from a

15 qualitative treatment of these factors through

16 to sensitivity analyses and ultimately

17 probabilistic simulation. They specified a

18 degree of complexity should be linked to the

19 nature of the analysis for conducting how the

20 information is going to be used, the

21 complexity of the risk assessment itself.

22 Clearly based on the WHO
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1 assessment, we would probably do a full

2 probabilistic uncertainty and variability

3 characterization. We don't always have all

4 the information to do that with, but we will

5 certainly include a qualitative discussion and

6 detail of uncertainty and variability will

7 include a number of sensitivity analyses, some

8 of which I've already mentioned, and we will

9 include a probabilistic simulation, which

10 reflects confidence intervals in the effect

11 estimates.

12 This is typically what we've done

13 in the past, but this will be a little more

14 structured. 

15 And then the representativeness

16 analysis: Essentially what we're going to do

17 -- let's say that we model 12 urban study

18 areas. We're interested, as I said before, in

19 looking at how those urban study areas compare

20 to urban areas in the U.S. in general. 

21 We can do that in a number of

22 ways. One way is by looking at ozone risk
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1 related parameters, baseline incidence rates,

2 effect estimates when we have them across

3 individual cities, possibly demographic

4 profiles of the cities, air quality

5 statistics. And we can look at how our 12

6 urban study areas compared to a much broader

7 set of the urban areas across the U.S., and

8 once again see whether our urban study areas

9 fall within the upper distributions of those

10 various parameters, or if they're more evenly

11 spread, or for some parameters, they fall 

12 towards the lower end and we have concern in

13 that case that we may not have captured the

14 higher risk profile urban study areas.

15 I think that's probably unlikely. 

16 Once again, this is something that we did for

17 the PM NAAQS, and I think it was well

18 received, and I think provided our management

19 with a little more information in terms of how

20 our case studies mapped to urban areas in the

21 US in general.

22 The national scale mortality
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1 estimates -- or the mortality estimates across

2 a larger number of cities would also play a

3 role here. We could look at how our mortality

4 estimates for the case studies that we model

5 compare to a much broader set of mortality

6 estimates; incidence per 100,000 -- various

7 statistics we can look at across a broader set

8 of urban areas.

9 And then I think the final point

10 that I'll make is that we're considering --

11 we're planning to use the -- the environmental

12 benefits mapping and analysis program, or

13 BenMAP, to model our urban study areas.

14 This platform has been used

15 extensively for many years in supporting the

16 RIAs, the Regulatory Impact Analyses, that we

17 do for the NAAQS. So, it's not a new program. 

18 It has a lot of pedigree to being used, and it

19 has been used to model individual cities, but

20 it hasn't been used specifically for the NAAQS

21 risk assessment.

22 Using a modeling platform like
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1 this has a lot of benefits. Once you set it

2 up, you can run many different sensitivity

3 analyses. You can put different effect

4 estimates in there. You can look at different

5 lags. You can run various sensitivity

6 analyses.

7 There are also QA benefits. If

8 you use a program like this that has been

9 validated in a number of ways, you're much

10 more confident that you're not going to be

11 introducing errors, as compared with using

12 data sets, databases and shifting data around. 

13 So, that's all I'll say with that.

14 So, that's the -- I think that's

15 the end of the presentation.

16 DR. FREY: Okay, thank you, Zach. 

17 Are there any quick clarifying questions? Ed?

18 MR. AVOL: I just have one

19 question about the representativeness issue. 

20 And you alluded to the peakiness of some urban

21 areas. And so -- and this whole focus sort of

22 on urban areas. And so, downwind, or a non-
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1 urban area, the shape of that ozone curve is

2 much more broader, which has implications when

3 you take into account physical activity and

4 the duration and exposure, and when people are

5 out and about.

6 And so, I'm not -- it's not clear

7 to me how that -- how that -- in terms of

8 risk, how that segment is going to be

9 considered, and whether those people are at

10 higher risk, but not being considered in this

11 sort of analysis.

12 DR. PEKAR: I mean I certainly

13 would say that some of the urban study areas

14 we're going to include would have outlying

15 suburban areas included in them, where you

16 might have larger demographics that are

17 active, depending on how we decided to define

18 polygons for the study areas. 

19 So, if you're looking at LA, we

20 may have one - which is what we've done in

21 the past - have one urban area that we have an

22 exposure surrogate for. This is one of those
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1 times when with -- you know, it's a resource

2 issue again. I mean you can also divide these

3 areas, and this has been done clearly for PM. 

4 Into separate polygons, you can get exposure

5 surrogates for different polygons, and then

6 look at how these might differ.

7 Those exposure surrogates would

8 then have different peak sort of different --

9 different peak ratios, and you might be able

10 to look at differences in risk. Having said

11 that, that's the kind of thing we need input

12 from you on. I mean if there's a certain

13 issue that you think is very, very critical

14 for us to look at, we could really use that

15 input because we can only do so many of these

16 more segmented --

17 MR. AVOL: I understand the

18 resource issue. I just want to -- and I'm

19 happy to see that you're looking at the

20 representativeness. I just would say to the

21 extent that you look and see that everything

22 doesn't look like this, and there are some
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1 communities that look like that.

2 DR. PEKAR: Right. So, one way of

3 thinking about that is if we were going to

4 include a number of cities in the national

5 distribution, maybe to try to include some

6 areas that might be more representative of

7 what you're talking, even if it's a suburban

8 area to throw some of those in, and look at

9 how those would be covered. I'm not sure.

10 DR. HUBBELL: Let me just ask

11 specifically. Is there a specific area in

12 California that you think might be good --

13 MR. AVOL: No, but the classic

14 example for us in California would be again,

15 downtown Los Angeles Riverside, compared to

16 Lake Arrowhead or places east, where you have

17 -- you don't have that NOx titrations. So,

18 you have those longer, broader many hours of

19 ozone at elevated levels. Elevated in terms

20 of elevated ozone, not elevated just in terms

21 of elevation.

22 DR. HUBBELL: Right. I think that
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1 would be really good for us to choose

2 something, a very broad area like that, that

3 has that difference in gradient. I think that

4 would be really useful.

5 MR. LANGSTAFF: I'll just mention

6 that with the exposure and the clinical risk,

7 we include those areas. So, we got that. We

8 include the downwind areas.

9 DR. FREY: Okay, Fred Miller, and

10 then Helen Suh wanted to ask some clarifying

11 questions.

12 DR. MILLER: Can you clarify for

13 me -- you said that you would be separating

14 out the contribution of US anthropogenic,

15 anthropogenic from Canada and Mexico, and

16 outside of North America. What is the value

17 of identifying the fractional contribution of

18 these, when they all lump into something you

19 can't control anyway? I don't understand what

20 that is going to give you.

21 DR. HUBBELL: Well, I don't agree

22 with the statement that we can't control --
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1 DR. MILLER: Well, it's a

2 clarification. I don't understand.

3 DR. HUBBELL: Well, what I'm

4 saying is we're taking the position that there

5 are -- there is truly natural background that

6 is something that is uncontrollable. One

7 could argue there are things you can do even

8 there to try to manage fires and things like

9 that. But what we're trying to do is identify

10 the fact that the science is telling us that

11 the ozone continues to cause risk as you go to

12 lower levels.

13 So, the question is of the risk

14 that's associated with those exposures, how

15 much is associated with different sources that

16 may be affected by different types of

17 policies? There are policies that can affect

18 US emissions. There are policies that can

19 affect Canadian and Mexican emissions, perhaps

20 a little differently, and then there are

21 policies that can in the long-term affect

22 international emissions, and that's what we're
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1 trying to do.

2 DR. FREY: Okay, Helen and then

3 Jim.

4 DR. SUH: I have a clarifying

5 question. This is about the mortality. Do

6 you plan to look at mortality separately for

7 respiratory and CV, or is it just all cause,

8 or -- I know -- I know for the long-term, it

9 was for the respiratory, but I want to know

10 for the short-term.

11 DR. PEKAR: Yes, the short-term I

12 think we would do in a -- in the past, we

13 looked at those individual categories, and I

14 think we continued to do that again. I'm just

15 trying to make sure we've updated the

16 functions with the latest versions of the

17 various time series studies.

18 Yes, so we would definitely have

19 them --

20 DR. HUBBELL: Again, one of the

21 benefits of using the BenMAP platform is it

22 has a very large database of functions already
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1 built into it, including cost specific types

2 of functions, and it's very easy to add new

3 functions as we get the information. So, to

4 the extent that we have updated functions

5 based on either individual cities or multi6 city studies for different cost specific

7 categories, we'll try to incorporate those.

8 DR. SUH: I know you've done that

9 before, but under what --

10 DR. FREY: Use the mic. Thanks.

11 DR. SUH: I know you've used it

12 before, but can you remind me where.

13 DR. HUBBELL: Well, it's used in

14 all the regulatory impact analyses that we do

15 for all our major regulations. It's also been

16 used to produce several publically available

17 peer-reviewed publications, but looking at

18 ozone, looking at PM, and looking at a number

19 of different types of control strategies and

20 so forth.

21 So, it has been used. It's been

22 peer-reviewed. It was peer-reviewed back in
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1 2004. It has continually been updated, as we

2 go through, in terms of adding functions,

3 adding different ways of bringing in different

4 air quality modeling information and

5 monitoring data.

6 So, we've tried to keep it very

7 much up to date, based on the current

8 literature, and again it has been -- it has

9 been gone through peer review and it has been

10 published. Also, as it says here, it's also

11 available on our website. So, anybody can

12 download it. 

13 Anybody can use it, and we also

14 have public training available. So, it's

15 pretty accessible to the public in terms of

16 providing comment. 

17 DR. FREY: Okay, Joe.

18 DR. BRAIN: I have a clarifying

19 question too. Help me out as to how these two

20 presentations, John and Zach's, are linked. 

21 And the first one, there's international

22 transport APEX. Again, looking at a variety
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1 of different populations. But then in your

2 presentation, it all came down to a single

3 health outcome, FEV1. Is that the same

4 platform that's being used now for a larger

5 variety of health outcomes? 

6 I don't quite understand how they

7 -- are they separate efforts, or do they

8 overlap?

9 DR. HUBBELL: They are separate

10 but overlapping efforts. They start from the

11 same basis of air quality information, which

12 is why you see the same discussions about

13 background concentrations and you see the same

14 discussion about the monitored data that will

15 be used to inform the different risk

16 characterizations.

17 Where they depart is that for the

18 exposure modeling, we take another model, the

19 APEX model, and take those concentrations, and

20 put those through this more complicated model,

21 which has to incorporate time and activity

22 patterns, has to incorporate different
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1 microenvironments, as opposed to the

2 epidemiology based approach, where we're

3 taking the monitored concentrations directly

4 as a surrogate for exposure, and that's the

5 real difference.

6 Then we populate the epidemiology

7 functions with those exposure surrogates.

8 DR. BRAIN: So, the first one is

9 really more sophisticated, more granular? I

10 guess my question is then why are you only

11 looking at FEV1 as the health outcome, when

12 there are many others, morbidity, mortality,

13 that in some ways seem more significant.

14 MR. LANGSTAFF: Well, the exposure

15 outcomes are based on clinical human studies

16 of exposure. So, they're not -- and that's

17 the primary endpoint we have for those, and we

18 have good quantitative information on, as

19 opposed to the epi studies, which is more sort

20 of a statistical association. 

21 DR. HUBBELL: Yes, there are very

22 few at this point. There's a few that are
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1 coming out now, but there are very few

2 epidemiology studies that have used modeled or

3 actual monitored personal exposure. And so,

4 in order to be able to use that personal

5 exposure information, you have to have an

6 exposure response relationship, and we simply

7 don't have those for those epi studies.

8 Now, again, those are going to be

9 becoming available over the next cycle, but

10 not now. 

11 DR. PEKAR: And I think just to

12 add a little bit, one thing is -- I'm not sure

13 how much of this will actually come into play,

14 but we might be able to use some of the

15 results of what John is doing to help

16 interpret some of the trends, the patterns

17 that we see in the risk information to a

18 certain extent because of characterizing

19 different -- the nature in detail of different

20 exposures in different cities. If we're

21 modeling epi in the same ones, we might be

22 able to talk about uncertainty a little bit.
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1 DR. HUBBELL: Well, not

2 uncertainty so much as heterogeneity and

3 understanding that if we see a different

4 exposure pattern, and in several of the cities

5 that we have modeled epidemiology functions

6 for, it might help us interpret those, and

7 say, "Well, if you have higher personal

8 exposure relative to the ambient

9 concentrations in New York compared to Texas,

10 well, that might explain why you see a

11 different magnitude or significance of the

12 underlying relationships." 

13 DR. BRAIN: I would encourage

14 including heterogeneity as much as you can in

15 the second analysis. I think that really will

16 drive a lot of our decisions.

17 DR. FREY: Okay, we have Ed and

18 then Steven on clarifying questions.

19 MR. AVOL: So, is it appropriate

20 now to ask about the populations that they're

21 going to be considering?

22 DR. FREY: If that's a clarifying
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1 question, I think so.

2 MR. AVOL: So, you alluded to

3 children as being one of the issues that

4 you're going to be addressing. But my

5 question is you defined children as up to age

6 18. So, NIH defines it up to 21, and in fact,

7 males in terms of -- since you're looking at

8 lung function, FEV1 as an outcome, males,

9 actually, the lung development and growth

10 continues on into their early 20s. 

11 And so, in terms of looking at

12 potentially sensitive at-risk populations,

13 you're truncating it a little bit short.

14 MR. LANGSTAFF: Okay, that's a

15 good point.

16 DR. FREY: Okay, Steve?

17 DR. KLEEBERGER: So, this is a

18 clarification question, or a clarification

19 point. So, this is -- this area is way out of

20 my expertise. But you had mentioned something

21 about genetics and genetic susceptibility, and

22 so forth. You had mentioned how you're going
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1 to deal with that. Could you explain that

2 again?

3 DR. PEKAR: Sure. Yes, I sort of

4 glossed over that. I think when we were

5 looking at the long-term study summarized in

6 ISA, and starting to consider the endpoints

7 that we would model for risk, there were a

8 number of studies that when we looked at them

9 in more detail, we were actually looking at

10 populations that are differentiated

11 genetically for predisposition of respiratory

12 effects.

13 Just to be fair, there are people

14 here that are way more -- have a lot more

15 expertise than I do in this regard, but the

16 reality is we can't include those in a

17 quantitative risk assessment at this point,

18 because we don't have baseline incidence of,

19 for instance, asthmatic hospital admissions

20 for that particular population. And if we

21 don't have those baseline incidence rates for

22 a very specially defined population, we can't
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1 include them in the risk assessment because

2 the effect estimates adjust the baseline

3 incidence rates.

4 Now, having said that, I wanted to

5 be very clear that those kinds of studies

6 could play a prominent role in the evidence

7 discussion that we advance to management when

8 they think about standards, which is obviously

9 a very critical factor that's considered when

10 the decisions are made, often the risk

11 information is more supportive. But I was

12 just trying to make that point.

13 DR. FREY: Okay, any other

14 clarifying questions at this point? I don't

15 see any. So, EPA, thank you very much for

16 your presentations, and appreciated your

17 input. We will move now to the public

18 comments. Before we get into the individual

19 public comments, I just wanted to check who is

20 actually here. We have three speakers listed,

21 one by telephone is Nicole Downy. Are you on

22 the line?
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1 DR. DOWNEY: Yes, I am.

2 DR. FREY: Okay, good. Another is

3 Julie Goodman, and she's here. Okay, all

4 right. We have a third one who is not going

5 to speak. So, we have, as I understand, two

6 public commenters on the agenda. 

7 Okay, so the ground rules are:

8 five minutes, strictly enforced. Then, if

9 there are clarifying questions from the Panel,

10 we can entertain those. So, Nicole, if you're

11 ready, please proceed.

12 DR. DOWNEY: Okay. Good morning,

13 members of CASAC. Thank you for the

14 opportunity to speak today. I'll be talking

15 mostly about the use of policy-relevant

16 background in the standard-setting process and

17 in the health risk assessment.

18 My basic arguments are that

19 estimates of policy-relevant background should

20 be paired in time and space at a very high

21 resolution for health risk assessments. An

22 estimate of the uncertainty due to systematic
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1 model underprediction at high ozone values

2 needs to be included in the health risk

3 assessment, and that policy-relevant

4 background should actually include some

5 emissions necessary to maintain a basic level

6 of public health, including food, shelter,

7 heat and the public health infrastructure. 

8 So, in the 2006 criteria document

9 in the current ISA, EPA discussed PRB in a

10 mean sense, i.e., 15 to 30 ppb. The form of

11 the standard, however, is aimed at the highest

12 extremes. So, the fourth highest three-year

13 average, NDA 8.

14 When regulations were aimed at

15 sort of greater than 85 ppb, this approach was

16 justified by arguing that PRB tends to be low

17 under high-ozone conditions. And this was

18 true for high ozone levels, but at levels

19 currently proposed for the 2011 NAAQS

20 reconsiderations, so 60 to 70 ppb, this

21 assumption is no longer valid.

22 But Fiori et al. and Wang et al.,
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1 which were the studies used for PRB in the

2 2006 and 2011 and current ISA, showed that the

3 influence to policy-relevant background peaks

4 between 50 to 70 ppb, in an illustration of

5 the different between PRB calculated at

6 seasonal means versus the annual fourth

7 highest values shown in Figure 1.

8 Previously, EPA has used monthly

9 averaged diurnal cycles of PRB for health risk

10 assessments. Again, this approach was

11 justified by arguing that the influence of PRB

12 was low for high-ozone events. As shown in

13 Figure 1, in the range of 60 parts per

14 billion, this is not the case. PRB can

15 represent a significant portion of observed

16 ozone, and its contributions should be taken

17 into account in the health risk assessments.

18 Importantly, this contribution

19 varies seasonally with elevation and with

20 ozone concentration, as observed by Fiori et

21 al. 2002 and 2003. We therefore recommend

22 that estimates of PRB be paired with
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1 observations at the highest spatial and

2 temporal resolution possible. EPA currently

3 has hourly estimates of PRB for 2006, '07 and

4 '08, from new high-resolution model runs

5 conducted at Harvard University.

6 It is well documented that models

7 tend to underpredict the frequency of high8 ozone events, partially due to numerical

9 limitations. The most recent version of GEOS10 Chem demonstrates the difficulties in

11 predicting the frequency of high-ozone days

12 above approximately the 98th percentile. This

13 is shown in Figure 2.

14 The numerical limitations that

15 limit models' ability to predict peak ozone

16 events extend to PRB simulations, and it is

17 likely that peak PRB estimates are also

18 underpredicted. The error associated with

19 this systematic underprediction of high-ozone

20 events should be quantified and effects of

21 this air should be propagated through the

22 health risk assessment process.
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1 Finally, the ISA defines policy2 relevant background as ambient ozone

3 concentrations in the absence of anthropogenic

4 emissions of all ozone precursors. This

5 includes eliminating all sources of combustion

6 and all emissions from agriculture.

7 This scenario itself would have

8 significant negative public health impacts. 

9 No allowance is included for the basic

10 sustenance of life and health in the United

11 States. This becomes more important as the

12 health effects of ozone are calculated for

13 lower and lower levels.

14 A more reasonable approach would

15 be to include emissions to sustain a basic

16 standard of living, including shelter, food,

17 heat and the public health infrastructure. 

18 EPA should optimize the health

19 benefits predicted from reducing ambient ozone

20 levels with the basic needs of human society. 

21 Thank you.

22 DR. FREY: Okay, thank you. Are
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1 there any clarifying questions? Daniel?

2 DR. JACOB: I just simply would

3 like to say that I totally endorse what Nicole

4 just said, and I'll add some input into that. 

5 Well, not into what she prepared, but into the

6 results that she used. I think she

7 interpreted perfectly, and this should

8 definitely be considered.

9 DR. FREY: Okay. Other questions? 

10 Well, thank you, Nicole. 

11 DR. DOWNEY: Thank you very much.

12 DR. FREY: Sure. Our next speaker

13 is Julie Goodman. 

14 DR. GOODMAN: Thank you for the

15 opportunity to speak again on behalf of API. 

16 The scope and methods plan relies heavily on

17 information assessed in the first draft ISA,

18 but many of the conclusions presented are not

19 reliable bases for determining health

20 endpoints to focus on in the risk assessment.

21 The core set of risk estimates

22 must be based on factors that are most likely
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1 indicative of the true risk of individuals in

2 the population. For risk estimates based on

3 controlled human exposure studies, EPA plans

4 to determine the exposure levels at which FEV1

5 decrements between 10 and 20 percent will

6 occur, using a model for estimating FEV1

7 responses that was originally developed by

8 McDonnell et al. in 2007.

9 This model is based on controlled

10 human exposure studies conducted between 1981

11 and '92 that did not evaluate exposures less

12 than 80 ppb, and has been shown to overpredict

13 responses at lower concentrations for more

14 recent studies.

15 EPA should construct a new

16 statistical model based on all of the

17 available controlled ozone exposure studies. 

18 This model should incorporate a threshold,

19 because the biological mechanism of ozone20 induced lung function decrements is known to

21 have a threshold.

22 In addition, the model should
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1 reflect the evidence that group mean FEV1

2 decrements associated with exposure to 60 ppb

3 or less are not statistically different than

4 those with filtered air. 

5 I would like to point out although

6 there's perhaps a small debate over whether

7 effects occur at 60 ppb, EPA and CASAC have

8 all agreed that there's no differences between

9 40 ppb and filtered air, indicating a

10 threshold of at least 40.

11 EPA's approach to assessing the

12 epidemiology evidence in ISA did not consider

13 many of the limitations and uncertainties

14 associated with the underlying studies. EPA

15 focused on the positive associations reported

16 in the studies, whether they were

17 statistically significant or not, and often

18 discounted null results. And this led to the

19 consistency of the results being routinely

20 overstated. 

21 EPA also did not appropriately

22 weigh the evidence for causality, and for
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1 these reasons, conclusions of causal or likely

2 to be causal are generally overstated, and

3 there is a high possibility that the actual

4 risk for a given endpoint is or approaches

5 zero.

6 Given the degree of uncertainty

7 associated with the causal relationships in

8 the ISA, and even greater uncertainty

9 associated with other classifications, only

10 health points for which ozone is deemed causal

11 by EPA's definition should be considered in

12 the core risk assessment; thus, only studies

13 of respiratory morbidity associated with

14 short-term exposure to ozone should be

15 considered in the core risk assessment, and

16 health endpoints classified as likely causal

17 should only be considered in the sensitivity

18 analyses.

19 EPA should not consider including

20 long-term respiratory mortality as part of the

21 core risk assessment. Several large studies

22 have examined long-term ozone exposure and
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1 respiratory and cardiopulmonary mortality and

2 have not reported positive associations. And

3 this is acknowledged in the ISA.

4 Only the follow-up study of the

5 ACS cohort by Jerrett et al. in 2009 has

6 reported an association with long-term

7 respiratory mortality and the study has many

8 limitations that weaken the evidence for

9 causality.

10 So, together the evidence for an

11 association between long-term exposure to

12 ozone and mortality is overwhelmingly null,

13 and one weakly positive study with several

14 limitations is not sufficient to suggest a

15 causal relationship or be used in a risk

16 assessment. Thus, this endpoint should not be

17 evaluated in the core risk assessment or

18 sensitivity analyses.

19 Another issue is that many of the

20 studies relied on for causal associations in

21 the ISA reported results that did not achieve

22 statistical significance, and it is assumed
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1 these results will be used in the risk

2 assessment.

3 If so, the core set of risk

4 estimates must include the case that the

5 possible risk is zero. In addition, some of

6 the multi-city studies reported decreases in

7 community-specific mortality for certain

8 cities of interest. If EPA does include the

9 endpoint of short-term mortality in the risk

10 assessment, it must address how these

11 community-specific negative effect estimates

12 will be used.

13 EPA does not plan to consider a

14 threshold concentration response model in the

15 short-term core analysis, or in the

16 sensitivity analyses of the risk assessment,

17 because the ISA concludes there is little

18 support in the literature for a population

19 threshold for short-term ozone exposure

20 related effects.

21 And this is not true, however, as

22 the controlled exposure studies clearly show
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1 a threshold effect, as I've discussed in

2 written and oral comments before. I believe

3 the evidence suggests that 60, but clearly we

4 all agree, at 40 ppb.

5 In addition, a short-term exposure

6 threshold for effects on lung function in

7 response to ozone is also consistent with

8 biological data that support a mode of action

9 related to antioxidant defenses. Because the

10 controlled studies and proposed modes of

11 action for respiratory morbidity support the

12 existence of a threshold, a threshold CR model

13 should be used for the core set of risk

14 estimates, and other models can be used in the

15 sensitivity analyses.

16 Finally, EPA plans to use

17 distributed lag models for CR functions when

18 available, but will consider information in

19 the ISA to determine if there is biological

20 support for selecting a specific lag period

21 for a given health effect. EPA appears to be

22 open to using different lag periods for
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1 different cities, and this raises questions

2 regarding the biological plausibility of the

3 reported associations.

4 If there is no biological

5 justification, lag periods --

6 DR. FREY: Thirty seconds.

7 DR. GOODMAN: -- should not differ

8 by city for any given endpoint. Instead, EPA

9 should decide a priori which lag models has

10 the most biological plausibility for each

11 health endpoint, and then use that model in

12 the core risk assessment.

13 So, in conclusion, EPA's plan for

14 the risk assessment for ozone-related health

15 effects should carefully consider these points

16 so the core set of risk estimates can be based

17 on factors that are most likely indicative of

18 the true risk of individuals in the

19 population. Thank you. 

20 DR. FREY: Thank you, Julie. You

21 had five seconds to go. Are there any

22 clarifying questions? Yes, Fred?
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1 DR. MILLER: Could you clarify,

2 because I tend to agree about the

3 standardization of lag, but what if these

4 areas that they pick, the lag actually

5 reflects major differences, like in

6 ventilation with the windows open and things

7 of that nature? So, would that modify what

8 you're talking about? 

9 I can understand if you're talking

10 about comparable areas, that it should be

11 whatever the standard lag is. But could there

12 be situations whereby it's different because

13 of major dynamics of how the area is and

14 ventilation and things of this nature?

15 DR. GOODMAN: Yes, there could

16 definitely be differences, but that's based on

17 biology. So, as opposed to sort of letting

18 the statistics drive it and saying using

19 different lags because the statistics are

20 something different, there should be a

21 biological justifiable reason for using

22 different lags.
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1 DR. FREY: Any other questions? 

2 Yes, John?

3 DR. BAILAR: I'm a little

4 concerned about the weight that you and EPA

5 both put on whether or not data attain a 5

6 percent significance level. You do it in

7 different directions, but I think you're

8 giving it too much attention. 

9 That 5 percent was originally

10 devised for application to laboratory and

11 field experiments that could be repeated when

12 there were questions about the results. And

13 it has been validated by now a good many

14 decades of experience as useful in that

15 context.

16 It was not devised, and I think is

17 not appropriate, for use with observational or

18 one-time studies, things that can't be

19 repeated, where you have to rely much more on

20 your sense of the context, the whole Gestalt

21 of the available knowledge, and I think you

22 should pay much less attention to whether
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1 something is above or below that artificial

2 number.

3 DR. GOODMAN: Well, I think my

4 main concern is that -- particularly with the

5 observational studies that it's not just one. 

6 You have many, many studies, and in some,

7 there is statistical significance and some

8 there aren't, and some the point estimate is

9 above one and some below one.

10 And so, the idea is you need to

11 look at everything together, and if altogether

12 you see consistency, everything is above one,

13 be it statistically significant or not, that's

14 stronger evidence for causality than if it

15 jumps back and forth.

16 I think statistical significance

17 is one of the considerations when you consider

18 all the data together.

19 DR. BAILAR: It is one, but only

20 one, and I would not give it very much weight. 

21 DR. FREY: Okay, any other

22 clarifications? All right, well, thank you,
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1 Julie. All right, my understanding is that

2 those were the only two public commenters who

3 wanted to speak, and so I will close out the

4 public comment session.

5 We will now begin our consultation

6 discussion on the exposure analysis issues. We

7 have four discussants identified, who I

8 presume have prepared some remarks. We'll

9 start with those, and then we'll open it up to

10 a broader discussion by all Panel Members. 

11 So, I'd like to start with Daniel

12 Jacob, and then George Allen, Ted Russell, and

13 David Chock. So, Daniel, the floor is yours.

14 DR. JACOB: So population exposure

15 is not at all my area. So, I have absolutely

16 nothing useful to say.

17 (Laughter.)

18 DR. FREY: Well, nonetheless, if

19 you could say it into the mic.

20 DR. JACOB: Yes, okay. Well, I

21 can say it into the mic as well. Population

22 exposure is definitely not my area. I read
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1 the chapter. I thought it was reasonable, but

2 I'm not an expert. So, I don't have anything

3 useful to say. What I have something useful to

4 say is about the treatment of the

5 international and national component. 

6 It is for this afternoon, but I

7 will not be here. So, I don't know if I can

8 say something now, or -- ?

9 DR. FREY: Well, perhaps you

10 should do it now then.

11 DR. JACOB: Okay, thank you. It

12 won't take very long. So, I was very

13 interested by the way EPA was proposing to

14 deal with the international and national

15 component. 

16 I had an offline discussion with

17 Ted Russell yesterday about how to deal with

18 a bias in those model estimates. Because, as

19 Nicole pointed out, that bias could actually

20 have some important indications, as we

21 consider lower standards, and I think that the

22 model is good that it's not perfect. And
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1 there's some regions and some seasons where

2 it's doing worse than others.

3 I think there's a good way to try

4 to debias the model, following the terminology

5 of Ted, by -- if you use the CASTNET sites

6 that are regionally representative, and then

7 you look at the bias between the model and the

8 observations at the CASTNET sites, and then

9 apportion this bias to the different

10 contributors, so the international pollution

11 and then the North American pollution

12 contribution. 

13 And the reason for this, for doing

14 this, the reason I think this is the best

15 method is because when I look at the model

16 simulation of ozone at high altitude in the

17 free troposphere, comparison with ozone, with

18 satellites, there's no systematic bias at

19 northern mid-latitudes, even various seasons,

20 different altitudes, different regions. 

21 So, I think that most of the bias

22 in the model arises at trying to reproduce the
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1 surface conditions, and may reflect

2 topography. It may reflect some uncertainties

3 in the chemistry, such as isoprene, halogens,

4 and so on. And so, therefore, this is why I

5 think that the Bison model (phonetic) can be

6 apportioned to the different contributors in

7 a way, in a proportional way.

8 DR. HUBBELL: Can I ask one

9 clarifying question on that, which is, one of

10 the concerns we've had about trying to do bias

11 adjustment for GEOS-Chem or other background

12 ones is the grid resolution usually is not as

13 good as some of the more regional models, and

14 there's concern about, you know, you got a

15 monitor that may not be necessarily just

16 reflecting background, and may have local

17 sources or other things contributing to it

18 that you can't pick up with something like the

19 GEOS-Chem model.

20 So, the question is, are we really

21 adding additional problems when we try to do

22 bias correction using the CASTNET sites?
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1 DR. JACOB: Well, you know, bias

2 at a particular site will always be difficult

3 to interpret. But I think that I was focusing

4 more on regional skill corrections, such as

5 the fact that the southeast in the summertime

6 is too high in the model background.

7 DR. HUBBELL: So, would you do an

8 average bias correction then, rather than

9 monitor to grid cells and individual grid

10 cells? Would you interpolate sort of a bias -

11 -

12 DR. JACOB: I would be very wary

13 about using individual grid cells because,

14 particularly in the west, a lot of the data

15 are urban, and clearly, the model will not

16 reproduce properly urban data. And then you

17 also have local topography issues.

18 So, what I would suggest is again

19 using the CASTNET sites because we're getting

20 away from at least the urban issues. And then

21 using some kind of regional smoothing, and --

22 with the understanding that there will be
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1 local areas that are not accounted for. Those

2 I don't know how to deal with properly.

3 DR. HUBBELL: Okay, but regional

4 smoothing sounds like something we could do --

5 DR. JACOB: And using the CASTNET

6 sites.

7 MR. LANGSTAFF: I have a question

8 related to that. So, I can see the model has

9 large grid cells. And so, it's not really

10 designed to compare with individual sites. 

11 You might average some sites, but when it's

12 monitoring the current conditions that the

13 ozone surfaces are more uneven, but if you're

14 modeling natural background, I wonder if you'd

15 expect to be less biased because the ozone

16 surface would be more smooth, or is that not

17 the case?

18 DR. JACOB: Well, there would

19 still be bias because of chemistry and

20 topography. That would affect the natural

21 background as well as the pollution

22 enhancement.
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1 MR. LANGSTAFF: So, you think the

2 bias might be in the same direction?

3 DR. JACOB: Yes.

4 MR. LANGSTAFF: Okay. 

5 DR. JACOB: I think that the bias

6 would apply to all these contributions the

7 same way. Let me give an example. Imagine

8 that there's a bias because we're not

9 accounting properly for some local NOx source

10 or isoprene chemistry or halogen chemistry. 

11 Well, you know, that bias will propagate to

12 the natural component in the same way as to

13 the pollution component.

14 MR. LANGSTAFF: Yes, but I'm

15 wondering, for example, if you have an area

16 that is high on NOx emission on the current

17 day, so the model might be biased there, but

18 when you reduce the NOx emissions to natural

19 sources, then the ozone could be higher, and

20 so I wonder if the bias couldn't go the other

21 direction in a case like that.

22 I mean, we see cases where the
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1 natural background run gives you guys higher

2 than urban areas. So, you'd say, "Well, the

3 bottle is biased high there." But then if you

4 --

5 (Simultaneous speaking.)

6 DR. JACOB: That wouldn't be an

7 issue with the CASTNET site. You got to go

8 away --

9 MR. LANGSTAFF: Right, right,

10 right.

11 DR. JACOB: This is why I'm really

12 insisting on using CASTNET.

13 MR. LANGSTAFF: Okay, yes.

14 DR. JACOB: Not using the AQSB as

15 a CASTNET.

16 MR. LANGSTAFF: Got it.

17 DR. FREY: Okay, Daniel is that --

18 okay, thank you. Good. I did want to make,

19 I guess, two points before I call on George. 

20 One is that after we go through the four

21 discussant comments, I will give an

22 opportunity for Panel Members on the phone to
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1 comment, and I think that includes John Samet,

2 who was on the phone. Are there other Panel

3 Members on the phone?

4 DR. WEATHERS: Yes, Kathy

5 Weathers.

6 DR. FREY: Okay, great. And the

7 second thing is that we would like to get the

8 written comments from the Panel Members on

9 this consultation in two weeks. So, June 3rd

10 is two weeks from today. So, just please keep

11 that in mind. 

12 You may find it convenient to

13 change your comments today while we're still

14 here, or on your flight home. So, sooner is

15 great, but no later than June 3rd. With that,

16 George?

17 MR. ALLEN: Thanks, Chris. First,

18 a general comment. I'd like to thank EPA for

19 making the BenMAP tool available to the

20 community. I think it's a great tool. Has a

21 lot of wide range of applications beyond how

22 it's being used here. That's great.
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1 Those kinds of tools are just

2 extremely valuable over a very large scope,

3 specifically on this section in general. Ed

4 kind of stole my thunder here already, but I

5 am concerned about the unusual nature of '08

6 to '10.

7 In much of the eastern half of the

8 country, '09 was an extreme outlier, and

9 neither '08 and even more so '10 were at most

10 normal or below normal. So, taken together as

11 a three-year period, they are probably some of

12 the cleanest three years in history by a

13 significant margin, depending which metric you

14 use since we started measuring ozone.

15 Now, most of that, I think, is

16 meteorology. Some of it might've been the

17 profound economic bump we hit, but I think by

18 and large it is meteorology, and I provide

19 some Region One plots, because they were

20 there, and I didn't have to do them, in my

21 comments that make it clear how unusual '09

22 was, and put '08 and '10 in context for Region
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1 One at least.

2 My question is, I know EPA for

3 their trends work does do meteorological

4 corrections, and I guess one question I'd have

5 here is, is that something that could or

6 should or would be done here, or would you

7 perhaps broaden the range of years to include

8 some years that are more balanced? Meaning

9 some high years to counterbalance the low

10 years?

11 EPA Kameler et al. from '07 in

12 atmospheric environment published a nice

13 technique for corrections, and in my comments. 

14 It's on the EPA Trends website. They have a

15 little map of the value of the correction over

16 the eastern two-thirds of the US, and it's

17 quite distinct.

18 In fact, if you look at the

19 extremes between '03 and '07, there's a

20 correct range of more than 10 ppb. That's a

21 lot. So, this is a big issue if you're going

22 to be using any three-year period to estimate
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1 exposure from that. So, that's a huge

2 question there. And that needs to be

3 addressed in the plan and hopefully

4 implemented. Hopefully somehow, not just

5 addressed, but implemented in some way that

6 avoids that problem.

7 My only other comment is on the

8 issue regarding the spatial heterogeneity of

9 ozone across -- primarily across urban areas. 

10 In rural areas, at least if you don't do

11 vertical stuff, it's fairly homogeneous. Of

12 course, if you do vertical stuff, then we're

13 back to huge ranges with elevation, but that's

14 a different story.

15 A lot of sites, cities, take

16 Boston for example, because it's one of the 12

17 in the last time around. It's also one that

18 I'm very familiar with. There's really only

19 going to be one core urban site that

20 represents, say, a five-mile radius of

21 downtown Boston, and that's the Roxbury NCOR

22 site. 
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1 There's two other sites that are

2 near Boston. One is actually not too far from

3 it, but out on the harbor. Not -- I mean,

4 physically it's not floating, but it's out on

5 Long Island, out on the harbor, away from the

6 core downtown and local NOx titration sources. 

7 The other one is Lynn, and not far

8 from where I live, about 12 miles to the

9 northeast. Those are the two sites, actually

10 very similar slope of almost one, intercept of

11 almost zero. But then when you look at either

12 of them versus the Roxbury site, the

13 correlation is still decent, and the slope is

14 a fairly narrow one, but I show a plot of Lynn

15 versus Roxbury. But there's an intercept of

16 about 9 ppb, and I don't know in the

17 conceptual framework that you folks are

18 working with whether -- I mean, sure if

19 everything goes up and down the same, that's

20 good, and it does. But when you have an

21 offset like that, is that a problem in terms

22 of your approach? I'm not sure, but it could
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1 be.

2 And I think that should be

3 addressed because you may find this in other

4 areas as well. Like I said, in the

5 requirements for ozone monitoring in urban

6 areas that are, say, a million or so,

7 generally you're only going to have one

8 monitor in the core urban area.

9 You have some outlying -- I mean,

10 in eastern Mass there's a lot of ozone

11 monitors. But if you want to reflect the core

12 urban population where the people live and

13 where most of your epi population is going to

14 be, that's a different story. And as we've

15 noted before, exposure misclassification can

16 really do a number on your estimate of the

17 effect.

18 And so, that is a challenge

19 because of the urban titration effect in

20 medium-sized cities. As I said yesterday,

21 L.A. is not Houston is not Atlanta is not New

22 York is not Boston. All these cities
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1 spatially are different. So, you need to

2 hopefully get some local expertise for the --

3 maybe you're only picking two cities this time

4 just for budget constraints, I don't know. 

5 But seek out local expertise to better

6 understand the issues.

7 An example I gave was the Boston

8 Blue Hill site. It's only ten miles from

9 Boston, but it's up 600 feet, and it's very

10 different than any other site in the metro

11 Boston area. Unless you know the area

12 locally, you may not pick up on that, and you

13 may miss or misuse that kind of information. 

14 So, that's a concern there. I

15 mean, I guess the point there is, seek local

16 expertise. People don't understand the siting

17 and the Gestalt of the area in question. And

18 I think that's essentially the core of my

19 comments. Thanks.

20 DR. FREY: Okay. Thank you,

21 George. Ted?

22 DR. RUSSELL: Okay. Yes, a few
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1 things. 

2 DR. WEATHERS: Ted, could you speak

3 into the mic?

4 DR. RUSSELL: Yes, I'm getting to

5 the mic. So, in terms of the quadratic

6 rollback, I know that this was something that

7 was not -- there was some confusion on exactly

8 how it was done last time. And I think that

9 just needs to be better explained this time

10 around. A diagram would help.

11 One thing that I think you're

12 going to have to do this time, particularly

13 with discussion of the PRB, is address how you

14 will modify concentrations lower than the PRB,

15 and with reasons why. 

16 And I think if you look at Table

17 3-6 in the ISA, that can give you some

18 guidance as how you might do that. Actually,

19 that table suggests that it may not have to be

20 modified very much, except at the very low

21 levels. But again, if we're looking at the

22 levels of ozone we're looking at, particularly
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1 for the standard, I mean we're starting to

2 look at much more time being spent at these

3 sort of lower ozone levels.

4 As Daniel mentioned yesterday, we

5 talked about what to do with debiasing the

6 PRB, and we discussed how you would apportion

7 the bias to different parts of the

8 contributions to the PRB.

9 And I think -- you know, I won't

10 be quite so prescriptive as Daniel. I think

11 what -- as to how you'd want to do it, I can

12 see what Daniel is doing. I would say that's

13 something you guys have to spend a fair amount

14 of time thinking about, assessing, justifying,

15 and spelling out very, very clearly in the

16 REA, not only what you did but why you did it,

17 and the implications. And then also assessing

18 what the uncertainty is associated with the

19 method you used, and what the PRB -- the

20 uncertainty in the PRB.

21 So, again, it's primarily just

22 giving the thought and making sure that you
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1 justify what you've done and spell it out. 

2 So, that's that on what to do about the PRB. 

3 Just keep in mind, I think you have to be very

4 careful since you are going to be mixing

5 observed and modeled quantities. So, there's

6 that issue.

7 It was not apparent from what I

8 read why you would use the GEOS-Chem from 2006

9 to 2008 in observations from 2008 to 2010. 

10 It'd be really nice if those overlapped, and

11 as has been pointed out before, paired, very

12 closely paired in time and space.

13 I can actually see moving back

14 from 2008 to 2010 for multiple reasons, not

15 only to match GEOS-Chem, but as George has

16 pointed out, there was both meteorological

17 issues on the East Coast, but also the

18 recession. 

19 In the modeling that we've done,

20 we see that the recession has had a real

21 impact on ozone levels that -- you may not

22 want to use 2009 and 2010 just because they
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1 are different. The Southeast hasn't quite had

2 the same issues meteorologically as the

3 Northeast, but we still see the recession and

4 lower ozone during those two periods. 

5 Spell out better how you're going

6 to treat the methane. I mean, it really was

7 unclear, and I think you have to do that. And

8 what -- again, how that treatment impacts your

9 results. Just discuss the uncertainties. 

10 There's the issue of number of

11 cities. Oh, actually another thing I think

12 the REA is going to have to do is look at the

13 likely change of PRB levels over time, and the

14 implications of those on the potential health

15 benefits and welfare benefits over time.

16 I think, particularly with what

17 we're seeing, just doing sort of a stationary

18 assessment will not get that answer correct. 

19 In terms of the number of cities

20 it would be, three poses some real problems. 

21 But now you're talking many more than three

22 from the sounds of it.
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1 DR. PEKAR: Let me just be clear

2 about that. Three on the exposure, detailed

3 exposure modeling that John was talking about. 

4 But for the epi side, which is a little easier

5 to run from a resource standpoint, a larger

6 number.

7 DR. RUSSELL: Well, let me say I

8 hope it's more than three. You know, and

9 three I'm not sure -- we'd learn something

10 from it. And finally, just make sure that

11 the mathematical presentation is correct on

12 data. There were just some minor issues last

13 time. But that's it.

14 DR. FREY: Okay, thank you, Ted. 

15 David Chock?

16 DR. CHOCK: Okay, I only have a

17 few points to make. You're talking about 12

18 urban areas, and you're going to use the

19 consolidated human activity database. One

20 concern I have is that some of the database is

21 very old, 1980s. And you do have some new

22 database that was created in 2009, the RTI
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1 NSAS database. 

2 But again, the database may not be

3 too big because it's really -- I mean, if

4 you're talking about on a per city basis. So,

5 that could be a concern in describing

6 adequately the CHAD human activities, for

7 example.

8 And in the uncertainty area, you

9 talk about the model formulation uncertainty. 

10 That is going to be very difficult to address,

11 I suppose. Maybe you ought to be more

12 specific on that.

13 On the quadratic rollback, I would

14 recommend that you first look into how

15 different percentiles -- formulation would be

16 relative to, let's say, the mean value. 

17 Because the more extreme you are, the greater

18 the answer then associated with it. In fact,

19 the form may be different for different areas

20 as well. So, that's not straightforward issue

21 as well. That's all I have.

22 DR. FREY: Okay, thank you, David. 
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1 Let's see. Before we get into Panel Members

2 who are here, let me just give an opportunity

3 if there are Panel Members on the phone who

4 would like to make some comments. John Samet

5 or Kathleen Weathers?

6 DR. SAMET: I don't know about

7 Kathy. This is John. I'll make just a few

8 comments about the -- I'm about to run out of

9 battery, hang on one second. Let's see, I'm

10 still here?

11 DR. FREY: You're still here, yes.

12 DR. SAMET: Okay. So, let me just

13 make a few comments. One, there was a little

14 bit of discussion. Of course, every time I

15 hear this now I get a sense of deja vu, but I

16 think it'll be very important to just up front

17 in the document be very explicit about how --

18 what is being done now different from what was

19 being done the last go-round, and how changes,

20 let's say, perhaps in both response functions

21 or whatever, how they relate if changed to new

22 evidence that has accumulated.
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1 So, I think that should be really

2 very explicit. The term "policy-related

3 background" has certainly taken on a life of

4 its own, and I hear a shift in terminology,

5 and I -- that's fine, but the word and the

6 concept is certainly there.

7 And I think whatever is said, and

8 I heard the discussion about sort of sources

9 and trying to support policy directive and

10 what might be the most critical sources, still

11 I think you'll have to bridge off from a

12 concept that has been there before. So, I

13 think that needs to be discussed explicitly.

14 I guess the only other comment:

15 I'm still struck by George Allen's comments. 

16 I remember that one high point in Milton. The

17 question is whether the modeling that would be

18 done becomes so location-specific that

19 generalizability becomes an issue, given that

20 only a limited number of locations are going

21 to have the more detailed modeling effort.

22 So, I guess the question of
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1 generalizability will be quite critical. So,

2 those are my two main comments.

3 DR. FREY: Okay, thanks, John.

4 DR. WEATHERS: If I can just add

5 briefly, this follows on and underscores what

6 Ted and Daniel said, which is the importance

7 of using field data and CASTNET in particular,

8 but other field data as well, to anchor, to

9 prepare, and to make possible the debiasing or

10 spatial smoothing and honing of the model is

11 just incredibly important.

12 So, another voice for urging EPA

13 to use those data in creative ways. 

14 DR. FREY: Okay, thank you. 

15 Helen, you wanted to make a comment.

16 DR. SUH: Just a couple things. 

17 One is about the APEX model. One of the

18 concerns I have is that when you do the

19 modeling, especially for the elderly group,

20 who don't spend a lot of time outside, I'm

21 worried actually that the concentrations --

22 the exposures you're going to predict are
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1 going to be very low. And I'm wondering about

2 whether there has been some thoughts about

3 what that impact might be of having extremely

4 low exposures, but perhaps not so much

5 variability on your subsequent examination of

6 the impact on FEV1.

7 And so -- because there is a

8 chance, because indoor ozone levels are so

9 low, and people spend so much time inside,

10 especially the elderly, that actually you

11 might get very, very low predictions of

12 exposure.

13 And so, the question is what

14 impact would that have on your FEV1 and your

15 estimates of risk, and then if you're going to

16 take those estimates of risk and take it one

17 step further, and compare it to maybe what's

18 been found in the controlled laboratory

19 studies, or in the epi studies, it's going to

20 be a little bit of a mismatch. 

21 And so, I think there should be

22 some -- it makes me nervous because then
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1 there's going to be these estimates of risk,

2 and there's going to show that there's really

3 -- you know, at these very, very low levels,

4 there's not been any laboratory studies done

5 at those very, very low levels.

6 And so, from the personal exposure

7 to ambient ratios that's in the ISA, there's

8 like 0.1 or 0.2. So, if you take the, if you

9 just carry it forward, I'm worried there's

10 going to be a mismatch between the exposures

11 that you estimate, the controlled laboratory

12 studies that you're using to develop the dose

13 response curves, and then the subsequent

14 estimates of risk; I think that should just be

15 thought about because then you're going to

16 have to try to carry it forward, and maybe

17 you're going to try to relate it to what's

18 been found in the epi studies, and it might

19 not all go together.

20 So, I think there has to be some

21 thought. That's why APEX makes me nervous,

22 especially for the elderly group, because they
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1 just don't spend that much time outside. So,

2 I guess I don't know what the answer is,

3 truthfully.

4 MR. LANGSTAFF: Yes. I mean I

5 think it'll agree with the clinical studies,

6 but you know, if the elderly are indoors most

7 of the time at lower exposure, but they also

8 have lower ventilation rates, and to get the

9 FEV decrement you need the higher ventilation

10 rates and higher exposure at the same time.

11 So, you're right; they're going to

12 be very low. Very low.

13 DR SUH: And I'm not sure it's

14 going to be a great use of your time and

15 resources.

16 MR. LANGSTAFF: Well, it'll be

17 consistent with our clinical studies, but it

18 might not be consistent with the epi studies.

19 DR. SUH: Yes. I just think in

20 terms of prioritization, and thinking about it

21 -- but I also think you need to think about

22 the results that come out, and whether or not
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1 they're going to help you at all, given that,

2 one, the mismatch between the clinical data

3 and the exposure data that's going to be

4 missed. And so, just something to think

5 about. 

6 The other thing, actually I was

7 wondering, and maybe this isn't for you guys. 

8 It's for the ISA people. Given that you guys

9 aren't really going to use the PRB that was --

10 you're going to use some other variations on

11 the theme, but maybe that should be talked

12 about in the ISA as well, because the ISA only

13 really talks about the traditional PRB

14 definitions.

15 DR. HUBBELL: And to be clear,

16 they are talking about some of the other

17 things too, but they still call it PRB. Yes,

18 we agree.

19 DR. SUH: But I think there should

20 be consistency across terminology.

21 DR. HUBBELL: We agree. We have

22 discussed it. We just need to get our
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1 terminologies a little straighter. And I take

2 very clearly John's point that there needs to

3 be a bridge, to make sure people understand

4 that we're talking about concepts that are

5 related to the same thing we talked about last

6 time. We're just trying to evolve them a bit.

7 DR. SUH: Okay.

8 DR. FREY: Okay, Judy, and then

9 anyone else? Fred and John.

10 DR. GRAHAM: I had a few comments

11 on the exposure side and its linkage to the

12 health. The first comment is on page 19. 

13 This is the area where it says you're going to

14 be doing exposure modeling for 3, 6, 9, 12

15 urban areas, depending upon resources. And I

16 thought you had good criteria for how you

17 would select them in case you don't have the

18 money to do all 12.

19 I think that you should state even

20 in your plan why -- can all these criteria be

21 met with just three areas? Because if you

22 want to meet your criteria, suppose it takes
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1 four areas no matter what. I think that

2 should be clearly stated so you don't really

3 have an option for prioritization. You know,

4 there'd be a threshold there.

5 My other concern, perhaps a

6 greater concern, is Zach was talking about

7 doing a health assessment for 12 urban areas. 

8 And I thought, "That's terrific. Twelve here,

9 three here." So, maybe that's a clarification

10 point. I mean, how can you do a health

11 assessment on 12 urban areas, if there's only

12 been an exposure assessment on three?

13 DR. PEKAR: So, to clarify, you

14 know the epi-based risk assessment that I was

15 talking about is going to be based on exposure

16 surrogate monitor levels. You know, getting

17 sort of a central site kind of representative

18 monitor, or some version of that, that then

19 it's combined with the effect estimates and

20 the baseline incidence rates. 

21 What John is talking about is

22 doing the much more detailed moving
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1 populations around in a modeling framework

2 through exposure gradients, and in building

3 profiles for a set of modeled individuals. He

4 does not, at this point -- I mean maybe in an

5 ideal world, maybe in the future, we'll link

6 this more detailed exposure with epi, and

7 we'll be able to have a more fused approach

8 towards risk modeling.

9 But right now, they're different. 

10 His is not a precursor to my analysis. Not

11 mine, but our analysis.

12 DR. GRAHAM: Okay. In terms of

13 going back to the prioritization issue again,

14 it says in there that you're considering

15 modeling indoor sources of ozone. I presume

16 that you're going to be doing the sensitivity

17 analysis since there aren't that many indoor

18 sources.

19 To a bigger issue: CHAD. I mean,

20 I think the world of CHAD. I mean, I'm

21 basically the first one that ever funded it. 

22 So, I think it's a great thing, obviously. My
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1 question is to use it for activity patterns

2 today. A lot of the studies in CHAD are

3 before 1990, and I have to worry about even

4 1995, 1998 sorts of activity pattern data,

5 particularly since we're so interested in

6 kids, and activity patterns have changed.

7 I mean, what used to be a kid

8 outside playing is now a kid inside texting. 

9 So, I think that there ought to be some sort

10 of professional evaluation as to the relative

11 accuracy of using some of these CHAD databases

12 today. 

13 This brings up the ATUS data

14 files. I personally am not familiar with

15 them, but from what you said there, they sound

16 pretty doggone good to me, and looks like it's

17 a big probabilistic sample.

18 And you say you may not consider

19 it -- you may not be able to use it because of

20 resources. Again, if it's really good, if

21 it's had -- there's a lot of metadata, if it's

22 had a high level of QA, if it's probabilistic,
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1 if it's high quality, I don't see how you can

2 not use it.

3 I mean, I know your resource

4 constraints are real at your level, and I know

5 even Lydia has problems. But, I mean, there

6 is still pockets of money, and some of these

7 things just have to be done. 

8 So, I guess that's my only things

9 on the exposure side. 

10 DR. FREY: Okay, Fred.

11 DR. MILLER: Well, Judy and I

12 think alike on a lot of things. So, I'll just

13 re-echo exactly what she said, because they

14 are very valid points, and the aspect of the

15 activity and the focus on children just can't

16 be underestimated because there's absolutely

17 no way that CHAD represents the current

18 activity levels for most children today. And

19 that's a blank buster, okay?

20 I don't think you have established

21 as well as what Judy gives you credit for on

22 the -- if you're only going to do three, how
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1 they would be selected. Because for example,

2 I would think that you could take -- you would

3 want to have geographic areas. So, you would

4 take a city from each of three geographic

5 areas, and you take the dirtiest one with the

6 highest population.

7 You don't specifically go into

8 that here. I'm sure that you've thought about

9 it and you have that in mind, but what this

10 really needs to be done at some point is to

11 lay out exactly what your decisions were on

12 that.

13 And in regard to Chapter 2 on page

14 1, line 26, I'm wondering about if a portion

15 of the analyses -- because George brought up

16 about the atypicalness of the recent years and

17 the recession and Ted has mentioned it. Is it

18 possible to take one city, and look at moving

19 averages across time, 2006, '07 and '08; '07,

20 '08 and '09; '08, '09, '10 or whatever, and to

21 carry that forward so that you really can

22 establish how the risk analysis estimates
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1 change with air quality. And you'd also get

2 a sense as to whether it's been reduced or

3 increased over time.

4 And so, I'm concerned about not

5 having atypical and picking something when it

6 -- you could be able -- now, it may be that

7 functionally you can't do this because the

8 amount of work required is the same as doing

9 like 12 cities. That's something that you

10 could give me feedback.

11 But to the extent that you can

12 look at, in a given area, how the air quality

13 has changed and then the estimates so that you

14 can see how it moves, it gives us some sense

15 of how confident we are that we're really

16 capturing what's the amount of risk that's

17 really involved, and of course that would also

18 relate as levels have changed.

19 In your exposure analysis part,

20 you talked about the age-specific on page 4-5,

21 and you did piecewise linear fits to the age

22 categories. You forced them to join at the
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1 age boundaries, but why not use isotonic

2 regression, and let the data determine where

3 the cut points are?

4 Or, you even -- since you're using

5 this for a mathematical aspect to fit a smooth

6 curve through the entire data, it wasn't clear

7 to me why you need to do it piecewise on those

8 age intervals. And in that regard, I want to

9 bring up the question of -- you were talking

10 about basically around age 8 as the lowest.

11 Why would you think that ozone

12 exposures, and this kind of goes to what Zach

13 would be doing, there aren't data for children

14 exposed to ozone at lower levels than what

15 McDonnell did, and that was around the age 8

16 to 10?

17 But why would you expect that

18 ozone wouldn't affect children age, say, 3 to

19 6 years the same way as they would the older

20 children? And in that way, you could use data

21 that are in the literature. Like I give a

22 reference, Peconi et al., in 2007, where you
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1 have pulmonary function data and FEVs for 3 to

2 6 year olds. And so, you could continue this

3 on down.

4 So, I would encourage you to look

5 at that because I think it gives you a

6 spectrum of the population, and if you can't

7 do it, then I think you need to defend why you

8 feel that you can't go below it. Because the

9 relationships appear in terms of a

10 normalization of what Bill McDonnell did to

11 body surface area, where children respond the

12 same as adults in terms of that kind of

13 change.

14 So, I would think there's a

15 normalization you can do that would justify

16 being able to take it to lower levels, and

17 that would increase your overall power. 

18 The other area that I -- there's

19 two other areas that I want to comment on

20 right now, and by the way, since I'm always

21 reluctant to give my opinion, whatever you

22 don't receive from me in writing, you can
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1 consider that I agree with it. Okay? So,

2 that's a simple way to say I have looked at

3 the entire document. So, I'm giving you my

4 feedback.

5 For whatever it's worth, if I

6 don't point something out here, I think I

7 totally agree with what you're doing.

8 So, one of the things that has

9 bothered me in every one of these assessments

10 is the conflation issue. And one occurrence

11 for 10 people has to involve less risk than 10

12 occurrences for one person. And you have got

13 to find a way to overcome that.

14 I don't see, if you go to a

15 modification and adding data into CHAD, why

16 you can't have a tag identifier such that, if

17 you select that individual and you put them

18 back into the pool, you can keep track of how

19 many times they're selected.

20 So, in terms of the health

21 importance, there's a big difference, and

22 we've grappled around this in previous
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1 discussions, but no way to actually hand it. 

2 And so, it might be, if you're getting to a

3 transition in terms of database and your

4 sampling, that might be something that you can

5 maybe start to address. I throw that out

6 there because it's always troublesome.

7 The last thing that I want to

8 comment about has to do with your part on page

9 317 about maybe examining averting behavior,

10 if resources are available. And my view is

11 that, don't waste a penny on it, and I'll tell

12 you why I feel strongly that way. 

13 Risk aversion is a negative

14 factor. If you take risk aversion to its

15 ultimate, then you're left with letting

16 pollution increase, and we simply have to stay

17 indoors and wear masks and so on. What -- I

18 have failed to understand how, understanding

19 the risks with risk aversion helps us protect

20 people in wanting to be able to do normal

21 daily activities, and not have to when we have

22 orange level alert and stay indoors and that.
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1 So, maybe I missed what is the

2 contribution of averting behavior can do, but

3 as it stands now, I wouldn't do it. So, I'll

4 stop and I'd really ask you to clarify for me. 

5 Maybe I missed how this is going to help.

6 DR. HUBBELL: Well, again, this is

7 an area that has been emerging over the last

8 several years as a study topic in

9 epidemiology. The concern I have going into

10 this, and I think this is one of the reasons

11 why the literature has been evolving, is that

12 we do have an AQI, and we do actually ask

13 people to look at that AQI and respond.

14 So, whether we think it's a

15 positive thing or a negative thing that they

16 have to do this, they are doing it. And the

17 concern I have, and one of the reasons why

18 we're looking at it in the exposure side, as

19 well as thinking about it from the epi side,

20 is that the epidemiological relationship that

21 we see now has embedded in it this response,

22 this behavioral response to the AQIs.
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1 So, people are going indoors,

2 potentially engaging in unhealthy activities

3 by sitting in front of the TV, but they're

4 reducing their ozone exposures. And so, you

5 might then see a growing disconnect between

6 the ambient concentrations that are used in

7 the epi studies, and the personal exposures

8 that are really driving whether or not people

9 see an actual effect.

10 So, you can have the unfortunate

11 occurrence that you get a potential observed

12 reduction in the effect estimate that is

13 associated with ambient concentrations that is

14 driven by a reduction in personal exposure,

15 due to averting behavior.

16 That's not something I think we

17 want to attribute to being that ozone has

18 become more healthy for you. What it means is

19 that we've shifted the risk from air pollution

20 to potentially these other behaviors, and

21 there's a cost associated with those.

22 And so, what we want to do is make
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1 sure we understand that so that we don't

2 improperly attribute what we see in the epi

3 data to an improvement in the relationship

4 between ozone and health.

5 MR. LANGSTAFF: Yes, and I'd like

6 to say one other thing in response to your

7 comment, and that is it's likely a small

8 effect on exposures.

9 DR. MILLER: I'm not sure that

10 that would be the case if you're taking the

11 at-risk populations. In fact, I definitely

12 don't agree with you. Someone who has

13 pulmonary health considerations, they follow

14 those alerts. People that have children with

15 asthma, they let their kids do or not do

16 things based upon those index -- and I

17 understand now what you're getting at, and I

18 will change my written comments accordingly,

19 because that's part of the reason why I always

20 label my things preliminary, and then you'll

21 get the final. But I see where you're coming

22 from now. Thank you.
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1 DR. FREY: Okay, great. John, you

2 were next.

3 DR. BAILAR: I had two comments

4 about these two planning documents together,

5 and a couple about this welfare document. 

6 First is I think each of these

7 plans should include an explicit statement up

8 front about how EPA will deal with apparently

9 relevant and important information that's

10 published after the release of the final ISA

11 report.

12 It is okay with me to say that

13 you'll ignore any such information, but this

14 should be clear in the report itself. I think

15 also that both of them should say somewhere --

16 they lay out a minimum in scope and methods

17 and that more will be added if study shows a

18 need for that.

19 With respect to the welfare

20 document specifically, I'd like to see an

21 analysis that is more explicit in examining

22 the roll of co-pollutants as confounders,
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1 which could be dealt with by such methods as

2 modeling standardization or stratification

3 versus co-pollutants that may act in synergy

4 with ozone, which cannot be dealt with that

5 way.

6 And finally, I think that the

7 welfare document should say that there are no

8 other known welfare issues, or say what is

9 being omitted. 

10 DR. FREY: Okay, good. Other --

11 yes, Ed?

12 MR. AVOL: I just want to follow

13 up on something Fred said. I also had

14 problems with the conflation issue and the

15 APEX on page 3-8, and my issue is slightly

16 different. We learned in elementary school

17 that multiplication is commutative; that one

18 times ten equals ten times one. But I think

19 it doesn't here, and it doesn't here because

20 of the issue -- among other things, because of

21 the issue I raised yesterday, which is that of

22 attenuated responses. 
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1 So, repeated exposures for some

2 people they behave differently. And somehow,

3 that is not going to get translated from the

4 exposure here to the health risk, if you just

5 take that commutative property.

6 DR. FREY: Good. Other comments

7 on exposure analysis issues? Yes, Peter?

8 DR. WOODBURY: I guess just a

9 question. This isn't my area, that is the

10 human exposure, but I just had a question

11 about the discussion of changes in behavior of

12 children, and my question is should we be

13 considering what other portions of the

14 government might be recommending in terms of

15 children's activity levels? 

16 We have a problem with obesity,

17 and we want children to be active. So, it

18 obviously makes sense to look at how

19 children's behavior has changed over time. I

20 guess my question is does it also make sense

21 to look at what is being recommended in terms

22 of children's activity levels?
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1 DR. FREY: Yes, good. Anyone want

2 to pick up on that? I mean it seems like in

3 a way that's almost an analogous to the

4 avoidance discussion that from a public health

5 perspective, if we were to model avoidance

6 into the exposure assessment, that might

7 actually bias the assessment.

8 If it's a normative issue to

9 promote outdoor activity from children, maybe

10 it's appropriate to use data that

11 overrepresents that, even though that's not

12 the current -- it seems like that's the

13 discussion point. Are there any thoughts on

14 that? Ed?

15 MR. AVOL: CDC recommends 150

16 minutes a week of exercise. It's probably

17 higher for children.

18 DR. HUBBELL: One thing I'll point

19 out on that is that one of the -- an

20 additional benefit of looking at it from the

21 exposure side in terms of averting behavior is

22 that it actually shows that penalty. 
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1 In other words, if people are

2 staying indoors, and not exercising or having

3 activity because of concern about ozone

4 exposures, and we can identify that, and we do

5 have a survey that we're looking at that may

6 give us some additional information on that,

7 that is a penalty that can be identified, and

8 that can be then matched against these CDC

9 recommendations, and saying, well, these kids

10 are spending 20 minutes or 30 minutes inside

11 more a day, and that means that they're going

12 to have to make it up, or they will not get

13 that benefit as recommended by CDC.

14 So, it does give you that -- that

15 information.

16 DR. FREY: Good. Other -- yes,

17 Helen?

18 DR. SUH: The surveys, aren't they

19 really focused in LA and Houston? I mean so

20 would you expect the same avoidance behavior

21 in areas -- because I mean I know that the AQI

22 gets different attention in different areas. 
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1 And I know for example Houston and LA are sort

2 of a -- sort of a -- but I'm wondering if

3 there's data for other areas that perhaps

4 don't have that same -- 

5 DR. PEKAR: Certainly the NCES

6 survey that was completed recently and that

7 we're pulling data in depending on time and

8 resources focused on a larger number of cities

9 across the country.

10 So, it had a larger set of

11 responders. Although I'm not sure that -- my

12 recollection, which I should know off the top

13 of my head, is that we did not cover children

14 within that particular survey. I want to say

15 that it was adults 18 to 55, I think. I'm

16 looking at Susan. Maybe she remembers. 

17 Thirty-five and up, thank you.

18 MR. LANGSTAFF: But you're right;

19 it's city-specific. I think that study looked

20 at five cities.

21 DR. SUH: I think it might be an

22 important thing in some places, but perhaps in
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1 others, it's --

2 DR. HUBBELL: Yes, and we've seen

3 that in the epidemiology as well that you see

4 a bigger response when you're -- you see a

5 bigger response in places that are more

6 familiar with ozone episodes and have more

7 ability to react in ways because they can go

8 inside with the air conditioners.

9 DR. FREY: Ed?

10 MR. AVOL: Full disclosure. CDC

11 recommends 150 minutes a week of physical

12 activity for all of us, not just children.

13 DR. HUBBELL: Running after our

14 kids, for some of us.

15 DR. FREY: Fred?

16 DR. MILLER: I was curious. On

17 page 4-1, line 18, you talk about doing

18 analyses with asthmatic school children. Do

19 you already have the lung-function data

20 available for those kids? And if not, where

21 are you going to get it? Because I sure would

22 like a copy.
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1 MR. LANGSTAFF: No, I don't have

2 it, and I'm not sure if it's available. If it

3 isn't, then we can't really do it.

4 DR. MILLER: And I don't think it

5 is, but I mean clearly the ATS is the -- there

6 are people there to contact to find out, but

7 in the different modeling that I do, I'm

8 always looking for these kinds of subgroups. 

9 I have stuff for COPD individuals and how

10 their mucus flow rates change, and things of

11 that -- and the affect of the amount of ozone,

12 and the affect of the amount of particles and

13 that. But you've brought up a very important

14 group in terms of the asthmatic attacks and

15 the children. 

16 So, to the extent that you can

17 track down that data, it would be great. I

18 just am not aware of any. But again, I've

19 sort of been out of touch. Ed, you might

20 know.

21 MR. AVOL: I don't know of it

22 being grouped in that way, but there is --
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1 there certainly is some data.

2 DR. FREY: Okay, anybody else? I

3 guess one observation is, I was one of the

4 discussants on the ISA chapter 4 on the

5 exposure, and I don't recall seeing really

6 anything specifically about BenMAP in that

7 chapter. And maybe this is really more for

8 NCEA than it is for OAQPS, but I guess having

9 a foundation in the ISA that supports the use

10 of BenMAP would be useful, and I may have

11 missed it if it's somewhere else in the

12 document. But just wanted to mention it since

13 I know John Vandenberg is in the room.

14 DR. HUBBELL: And it's not an

15 exposure model, to be clear. So, it really

16 doesn't belong in an exposure discussion. It

17 really is as a risk framework --

18 DR. FREY: Yes, well, there was

19 some discussion in that chapter on

20 concentration fields over space and time, and

21 it seems like BenMAP -- that's a component of

22 what BenMAP addresses. And so, the methods in
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1 BenMAP as it pertains to that would certainly

2 be appropriate in Chapter 4, and then perhaps

3 some of the health related aspects of BenMAP

4 ought to be dealt with in some of the other

5 chapters in the ISA, which I didn't review. 

6 So, I don't know that it isn't there. But I

7 just wanted to encourage that linkage.

8 DR. FREY: Any other comments? 

9 I'd like to take a quick break. Are there any

10 other comments from the panelists on the

11 phone, John Samet, Kathy Weathers, on exposure

12 issues before we break?

13 DR. SAMET: This is John. 

14 Nothing.

15 DR. WEATHERS: No.

16 DR. FREY: Okay. Let's take a

17 nine-minute and 59 second break, and we'll

18 reconvene at 10:40.

19 (Whereupon, the foregoing matter

20 went off the record at 10:31 a.m. and resumed

21 at 10:42 a.m.) 

22 DR. FREY: Okay, I'm confident
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1 that everyone will find their seats

2 momentarily. What I'd like to do, my goal is

3 to try to get a little bit ahead on the agenda

4 because many of you have to leave a little bit

5 earlier than the scheduled adjournment.

6 So, EPA is on notice that if we

7 get through the health risk assessment issue

8 discussion on the health scope and methods

9 plan that they're ready to go on the welfare

10 scope and methods plan presentation before

11 lunch. So, that's my goal is to try to get us

12 there.

13 The discussants on the health risk

14 assessment issues are John Bailar, Fred

15 Miller, Judy Graham and Michelle Bell, and all

16 are present. So, I'd like to go ahead and get

17 started with that, starting with John Bailar.

18 DR. BAILAR: I've found over the

19 years that it's much easier to critique a good

20 document than one that is lousy. If it's

21 really bad, you can dismiss it in a few

22 sentences, but if it's really good, things
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1 just keep tumbling out.

2 In that context, I have four pages

3 of comments that are meant to make a really

4 good thing even better. I'm not going to go

5 through all of these because you have them in

6 writing, and I'll only mention the ones that

7 might raise some issues for discussion.

8 DR. FREY: John, could you move

9 the mic a little closer?

10 DR. BAILAR: Better? Okay, I'm a

11 little concerned about the use here of data

12 from volunteers, which are generally drawn

13 from local residents. They may therefore

14 carry the effects of any prior exposures with

15 them.

16 I'd be pretty cautious about

17 assuming that a person with past exposures to

18 substantial levels of ozone or other

19 pollutants would respond just like a person

20 without that exposure, and I would not want to

21 guess which direction such an affect, if any,

22 might go.
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1 Spatial and temporal heterogeneity

2 within an area raises issue quite different

3 from such heterogeneity across areas, and this

4 could use some discussion. 

5 I'd like to see more about -- in

6 Table 3-2 about how study participants were

7 selected. This was a table listing some

8 studies. I'm a little concerned about

9 possible bias, and the first bullet on page

10 316 does not really address the problem of

11 non-representativeness within specific

12 categories, or demographic descriptors.

13 The survey statisticians quite

14 broadly recognize that anything short of

15 random sample with a high response rate may be

16 seriously biased.

17 You say that several activities

18 will be undertaken if sufficient resources are

19 available, but what is the priority ranking of

20 these if you can do some but not others? This

21 seems to require some thought now, rather than

22 later; when you know what the resource
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1 limitations are, you might not have enough

2 time to get it properly sorted out.

3 I'm concerned, as others are,

4 about the selection of urban areas for study. 

5 That's an important aid to understanding the

6 proposed plan. I remain concerned about the

7 use of 12 urban areas to represent the entire

8 urban population of the US. 

9 These 12 should be examined

10 separately and compared. I think you plan to

11 do that. Only if they are in pretty good

12 agreement should they be combined into a

13 national figure. But I do not see a

14 description of this critical comparison,

15 including criteria for judging whether they

16 are sufficiently similar to provide a reliable

17 combined estimate.

18 If they are not sufficiently

19 similar, reasons for differences should be

20 sought and to the extent possible the effect

21 of differences should be estimated.

22 This could be in the form of a
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1 sensitivity analysis, or perhaps by allocating

2 each US city to a category that closely

3 matches one or more of those areas.

4 I understand you may not be able

5 to do 12 areas, but I would recommend at least

6 6 that are deliberately chosen to provide

7 variety because of the need to understand both

8 the degree of variation and, to the extent you

9 can, the determinants of variation.

10 It's not clear to me how you're

11 going to select the modeling elements that

12 you'll take as core, versus those for the

13 sensitivity analysis. If you're going to make

14 the selection after you look at results, say

15 so with some comment on how you will choose. 

16 Otherwise give the reader some guidance about

17 your choices prior to analysis.

18 There is a paragraph here that

19 helps, but it doesn't go far enough, given the

20 criticality of this phase of the analysis.

21 I can skip that. I talked

22 yesterday about problems with multi-pollutant
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1 models, where things are -- the significance

2 of things rises and falls with other

3 pollutants that are in or out of the model. 

4 That is a matter that requires a

5 lot of attention from people who really

6 understand modeling, and the -- the

7 interpretation of the various kinds of

8 coefficients coming out of the models. I

9 don't want to go over all that again, but it's

10 something that is -- really does require a lot

11 of experience and understanding.

12 I'm not a fan of the WHO tier

13 classification because to me, it gives zero

14 guidance to the analyst. The words in the WHO

15 descriptors of tiers are subject to a vast

16 range of interpretations and distortions, and

17 there are no sharp divisions among the tiers

18 anyway.

19 I think it can be useful for

20 describing what was done after the fact, but

21 I suggest that this section be deleted or

22 replaced with a more informative statement.
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1 Nature surely does not provide

2 dose response relationships that follow any

3 simple mathematical formula for any

4 heterogeneous population, and this should be

5 said now and then in various places in your

6 document, as well as a lot of other kinds of

7 documents.

8 The goal is purely empirical to

9 find some curve that fits pretty well, and is

10 mathematically tractable. For example, a

11 small recognized subpopulation of acutely

12 sensitive persons can produce a distinct blip

13 in the toe of the dose response curve, such

14 that low dose risks estimated by a linear

15 model are substantially underestimated, or an

16 unknown physiologic mechanism may bend the low

17 dose curve in unexpected ways, like vinyl

18 chloride.

19 With respect to resources, I would

20 give high priority to long-term understanding

21 of real individual responses. It's remarkable

22 that signals related to central monitors are
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1 so clear, and I would expect that better

2 information about what people actually inhale,

3 especially indoors, would add a lot to what we

4 know about low dose effects.

5 It would make the signal a good

6 bit sharper. I don't know which way the

7 signal would move, but it would be a lot

8 clearer I'm sure, if you understood much more

9 about what people are actually breathing. 

10 Finally, I would pay more

11 attention in this document to mortality, which

12 is more likely to drive any change in

13 standards than physiologic measures or

14 morbidity. Thank you.

15 DR. FREY: Thank you, John. Fred?

16 DR. MILLER: Well, I'll start

17 with, make the problem CASAC's, rather than

18 yours, on a couple of these things.

19 You indicate throughout this

20 document you'd get additional things if

21 resources are available. I strongly urge you

22 to have a strategic priority list, and
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1 establish it now, but moreover, come to CASAC

2 for a consultation. So, later we can't say,

3 well, why didn't you do so and so? And why

4 didn't you do this and that? That we get the

5 buy in up front.

6 Because you've just identified so

7 many things I think that -- that you'd like to

8 be able to do, but if I'm sensing the mood of

9 the -- well, we won't call whose mood it is,

10 but anyway, I don't think you're going to be

11 able to do as much as what you want, and I

12 think it's very important that you define up

13 front what your base levels are of things that

14 you're going to do, and then how you would add

15 things in and in what order, and have that

16 reviewed and agreed by CASAC because that

17 really makes it much simpler later for you to

18 defend why you picked this versus that.

19 And so, I think this group can

20 sort of be the scapegoat for you. So, that's

21 my reasoning for that, offering that

22 suggestion.
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1 When you go to the particular

2 health things that you were going to examine,

3 to me, you have enough to do already, and I

4 wouldn't expand to some of the additional

5 health categories that you've discussed in

6 here. 

7 For example, to me, the picture is

8 not clear on birth weight, and I guess I would

9 like feedback from the rest of the panel if

10 they really think it is that clear. When I

11 read the material, I saw too many plus/minus,

12 plus/minus, and then this overall statement to

13 say, well, we think it's suggestive, blah,

14 blah.

15 So, I think you have enough, given

16 the resource constraints, that that's just

17 something that should wait a later time for

18 actually trying to incorporate.

19 I feel the same way about the

20 long-term exposure mortality. We have this

21 one study by Jerrett, and the others are

22 plus/minus in that, and I know that mortality
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1 will drive the eventual analyses in terms of

2 dollars that Executive Orders require to be

3 done, and I was hoping that the ISA discussion

4 would come down clearer on how well these data

5 are available for prime time at this point.

6 I personally feel that the cases -

7 - if you have to take short-term mortality

8 versus long-term mortality, the case is

9 infinitely stronger for short-term mortality

10 than it is for long-term, and it's not clear

11 to me if CASAC as a group agrees in terms of

12 the long-term mortality that that is worth the

13 investment of your resources.

14 So, it might be something that

15 others on the panel comment and tell me I'm

16 full of it. So, who knows? I agree with

17 placing greater weight on using concentration

18 response relationships that reflect the

19 adjusted single-city estimates obtained from

20 multi-city studies because to me it represents

21 the best of both worlds. And so, I think you

22 have articulated a very good reasoning for
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1 your strategy there.

2 I do, however, have a problem with

3 no thresholds. I think you should clarify how

4 you're going to handle risk below however you

5 want to call the term, PRBs, or this

6 apportionment and that. Because you're

7 basically making a policy judgment when it

8 should be a scientific one.

9 I think the science -- personally,

10 I think the science says that there is an

11 effective biological threshold. I'll give you

12 the example, analogous to PM. When I was up

13 at -- I've forgotten the name of the

14 institute. It was on CSPAN, and it was on PM. 

15 It was a thing about there's no threshold for

16 particulate exposures. I showed a slide with

17 a single particle on it. I said, if you

18 really buy into this theory a single particle

19 can kill you, I doubled it. I covered the

20 screen with dots of particles, and I pointed

21 out. And each time I would ask, raise your

22 hand if you think that this can kill you. I
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1 never got anybody to raise their hand even on

2 the full one, and guess what? I said, that

3 doesn't even represent one microgram per cubic

4 meter of particles.

5 There's got to be an effective

6 biological threshold for most endpoints for --

7 and what it comes down to is because of the

8 tolerance distribution variability, you can

9 identify usually individual thresholds, but

10 not necessarily population thresholds. But I

11 don't -- I don't agree with adding risk when

12 you're at levels that are ozone exposures that

13 you can't control.

14 I mean it just seems

15 counterintuitive to what we're trying to do. 

16 So, maybe this is something that others will

17 weigh in and say no, but I personally endorse

18 an effective biological threshold for ozone,

19 and I think it has clearly been shown that

20 it's somewhere in this -- down in the PRB

21 range. It's certainly not at 60.

22 The reason I say it's not at 60 is
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1 that yes, the Kim study had adequate power and

2 showed statistically significant, but not

3 clinically relevant pulmonary function

4 changes; however, the PMN influx was 40-some

5 percent above controls at that same exposure

6 level and that is significant. The

7 inflammation aspects of that study are

8 clinically relevant. The pulmonary function

9 aspects aren't. So, you have that. Now, you

10 go down to the 40s, and you basically fade

11 away into the background, and so I think that

12 if it were such that we didn't have effective

13 biological thresholds on most of these things,

14 people would end up dying on a lot more

15 occasions and different things.

16 And so, there is an aspect of

17 homeostasis and the ability of the body to

18 repair itself. We don't have -- in terms of

19 cancer, you have natural killer cells

20 circulating that are knocking off and killing

21 these cells. So, the aspect of using no

22 threshold just is counterintuitive to me in
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1 terms of biomedical research. So, I think you

2 got to be clear on how you're going to handle

3 that and defend what you're going to do.

4 You bring up on page 518 about

5 using the ICD-9 to ICD-10, and to me, this is

6 an absolutely must activity that -- and I

7 would suggest that you draw in the main

8 players at CDC now and be able to get that

9 code-change in place. Because it really does

10 affect the strength of the analyses that

11 you're trying to do.

12 I don't know who all read that,

13 but there has been a change in that, and --

14 and the way you lay it out here, I mean to me

15 it's critical that you're able to use the

16 newer codification.

17 I also didn't quite understand,

18 and I'd ask you to clarify, the cause-specific

19 admissions in ER visits. And the reason I

20 give this -- it's actually a personal example

21 because my wife died a couple months ago, and

22 it relates exactly to why I'm asking this
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1 question. And that is what about an emergency

2 room visit, or a hospital admission for

3 pneumonia, but it's really aspiration

4 pneumonia due to swallowing dysplasia from a

5 stroke or others? How -- and that occurs. My

6 wife died of it.

7 How -- you are lumping these

8 together, or are you able to -- is -- is the

9 death certificate and the information that you

10 have specific enough that you can separate

11 those kinds of cases out, because aspiration

12 pneumonia in the elderly is a very common

13 phenomenon. And so, I raise it as to say I'm

14 not sure how you can handle it, or if you can

15 delineate.

16 And I would ask in terms of some

17 of the variance estimation procedures that

18 you're doing, and this is brought out on page

19 519; don't you have sufficient sample size to

20 use asymptotic variance estimates on a lot of

21 these things? And maybe you are doing it, but

22 it didn't come through, and this might be a
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1 point for clarification because the document

2 is, you know, at the 30,000 foot level to

3 allow us to understand what you're planning to

4 do, and from that perspective, it's a very

5 good document. But some of these kinds of

6 things, it just will help for you to

7 articulate more what they are.

8 And the last -- well, next to the

9 last, I do want to echo Dr. Bailar's comments

10 about not relying on the tier thing of WHO. 

11 Now, Dr. Graham, sitting to my left, has had

12 a lot more experience with the WHO, but I find

13 that usually WHO comes out with something that

14 tries to please everyone and ends up not doing

15 it.

16 Well, maybe not this time but --

17 well, anyway, I -- I'm reluctant to get into

18 just a step because there's so many different

19 caveats and things. And so, I'd really

20 appreciate more if you'd defend and lay out

21 what your reasoning and logic path was. And

22 if that ends up corresponding to the guidance
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1 that they provided, fine. But I wouldn't just

2 say, well, we followed the WHO tier guidance.

3 And the last point I wanted to

4 make is on -- related to the material on page

5 522. And it -- I wanted to ask the question,

6 can you fix the values of these model

7 estimates that don't have enough data, and

8 then incorporate the probabilistic assessment

9 for those elements having sufficient

10 information to assign the probabilities?

11 If I go by what's written there,

12 one would never be able to do a probabilistic

13 assessment because a universe of data would be

14 needed. And so, that might just need

15 clarification, but it didn't come through to

16 me how you were going to achieve that. So,

17 those are my comments.

18 DR. FREY: Okay, thank you, Fred.

19 DR. HUBBELL: If I could clarify

20 one thing?

21 DR. FREY: Sure.

22 DR. HUBBELL: On this issue of the
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1 emergency room visits -- and we're very sorry

2 for your loss. The way that we do it is we --

3 we match what's in the epi study, and the idea

4 is that if classification that's used in the

5 epi study, and the classification we use in

6 the risk assessment may both contain the error

7 that you're talking about, but the idea is

8 that the error is going to be the same, and

9 it's just noise added to the overall signal.

10 So, while it may be true that

11 those people are not affected by air pollution

12 in the same way because of the misdiagnosis of

13 the cause of death, it's going to be the same

14 in the epi study, and that noise is going to

15 be the same exact response.

16 DR. MILLER: Yes, it's noise, but

17 at leads to overestimation of the true risk.

18 DR. HUBBELL: But the epidemiology

19 affect estimate also includes that same -- in

20 other words, if there are -- if there are

21 people included in the baseline rate that is

22 being modeled through the epi study, and those
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1 folks really are not responsive, it's going to

2 show up in both places.

3 DR. MILLER: Okay, okay.

4 DR. HUBBELL: And the second thing

5 I wanted to get some clarification on is on

6 this question of thresholds and biological

7 thresholds.

8 At this point, our interpretation

9 is that the epi literature would mean that we

10 wouldn't want to apply the -- a function with

11 a threshold. But if were to consider

12 different cut points, in the past, especially

13 for PM when this has been considered, if you

14 are going to apply a threshold when there

15 hasn't been a threshold estimated in the epi

16 function, you have to adjust the slope of the

17 concentration response function to account for

18 the fact that all those observed excess deaths

19 that you actually modeled with the linear

20 function would actually only be occurring

21 above a particular threshold point.

22 So, I was wondering if there's
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1 some comment on do you think that that type of

2 an adjustment procedure is -- is appropriate

3 if you're going to put a -- some type of a

4 threshold based on a biological observed

5 threshold in a lab study or clinical study?

6 DR. MILLER: To me, it's quite

7 appropriate. To me, I don't think we've had

8 enough discussion as a panel on this

9 mortality, as well as the threshold's

10 agreement or not.

11 I'm giving you my view, and I

12 thought in the previous assessment that you

13 did not accumulate risk for exposures below

14 the background level.

15 DR. HUBBELL: And that's correct. 

16 I mean you're looking at differences. You're

17 looking at risk above different background

18 levels.

19 DR. MILLER: Correct.

20 DR. HUBBELL: But because of what

21 we're doing now in this breakout, the natural

22 background is a small component, and then
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1 there's these other elements that we would not

2 want to say there's no risk there. It's just

3 that risk is apportioned between these other

4 sources, and the international and the methane

5 and other sources.

6 DR. MILLER: So, are you getting

7 at fractionating those, and then saying, would

8 you adjust those?

9 DR. HUBBELL: Yes

10 DR. MILLER: I see.

11 DR. HUBBELL: It gets a little

12 complicated, and I'm just trying to --

13 DR. MILLER: Yes. Maybe --

14 Michelle, I see you starting to raise your

15 hand. I'm going to punt because I'm -- this

16 is more in the people's exposure area than --

17 DR. BELL: Yes, we're jumping

18 ahead a little bit because this is one of my

19 comments. I actually thought the use of no

20 threshold was appropriate. I liked it, but I

21 hear what you're saying about really dealing

22 with more than one issue.
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1 One is, is there actually a

2 threshold? And the second issue is if there

3 is a threshold, is it below natural background

4 levels? And in the epidemiological

5 literature, that's as far as we can get. Like

6 if there is a biological threshold at 0.000001

7 ppm, from a policy standpoint, I don't

8 actually care. Right? Because we're never,

9 never going to get there.

10 So, my comment on the threshold

11 point I thought it was appropriate to use it

12 because that's what the epi literature says,

13 but we do need to distinguish whether or not

14 you're talking about health risks from ozone

15 levels that are natural background and so on

16 and so on.

17 So, I would suggest breaking it

18 out in that way, and not ignoring that issue. 

19 I think if you apply this artificial

20 threshold, other than picking a number out of

21 the air, I don't know what you're going to do. 

22 And if you pick a number out of the air, you
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1 need to do sensitivity analysis, which is not

2 really helpful because you're just picking

3 multiple numbers out of the air.

4 So, I thought the current

5 approach, I think you need to expand the

6 language on that, as for most of the document. 

7 Just get into more detail. But I thought the

8 underlying thought process behind that was

9 fine. And I know that this issue of natural

10 background thresholds is stuff that many of

11 you have already thought about. So, I would

12 just flush that out more.

13 DR. FREY: Looks like there's

14 several people that want to follow on this

15 point. David and John, did you want to say

16 something? Okay. 

17 DR. CHOCK: I have a comment

18 actually. Because you're using a non-linear

19 model and we are really addressing a specific

20 urban area. And so, there's our baseline. 

21 So, if you want to extrapolate the model

22 results to high concentration and low
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1 concentration, you have to base on that

2 baseline to be safe. Statistically it is

3 logical -- it's a logical way to do it.

4 You cannot arbitrarily move it

5 down to the -- PRB level, and then do the

6 extrapolation. So, that's really my concern. 

7 You have to base it on the baseline survey

8 that we use, not the extrapolation.

9 DR. FREY: John?

10 DR. BAILAR: With respect to

11 individual thresholds, I think you really have

12 to understand mechanisms before you can make

13 reasoned judgments. What I have in mind is

14 that if ozone acts through some mechanism

15 that's also a product of some other exposure,

16 you may be dealing with a subpopulation that

17 has already reached that threshold before you

18 add any ozone. So, their ozone threshold is

19 effectively zero.

20 That's why you really need to

21 understand the mechanisms in order to talk

22 intelligently about individual thresholds. 
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1 With respect to a population threshold, my

2 sense of things is that it's the minimum of

3 all the individual thresholds of interest. 

4 That's quite apart from the question of

5 whether you can demonstrate such a threshold,

6 where the effective sample size may be tiny. 

7 But again, the whole concept of threshold

8 begins to sort of fray at the edges.

9 DR. FREY: Judy?

10 DR. GRAHAM: For virtually my

11 entire career, I've been disturbed by the term

12 threshold because, what's its definition? I

13 think everybody has their own personal

14 definition, and even if you write it down,

15 even if you write it down in the document,

16 people will still impose their personal

17 definition on it.

18 To a degree, a biological

19 threshold is almost a research threshold, and

20 I often point to, in the old days, you looked

21 at pulmonary edema by doing lung weight, wet

22 weight/dry weight. Then it's protein washout. 
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1 Then it's -- you inject radioactive material

2 and see if it leaks into the lungs.

3 So, you go down and down. Now,

4 there's morphological procedures, and you

5 measure the thickness. So, the threshold for

6 pulmonary edema keeps decreasing. The

7 threshold for -- if you want to call it the

8 threshold for lowest effective level observed,

9 look at human clinical studies.

10 I mean we used to be pretty high. 

11 So, we exercised the more extent of the

12 duration of exposure, increase the sample

13 sizes, had more sophisticated measurements,

14 decrease the variability, had better

15 statistics. So, we kept getting -- we keep

16 driving these numbers lower, lower, lower.

17 Threshold for what? Okay, we

18 could -- I mean ozone will break the double

19 bond, the carbon double bond. Well, so? A

20 molecule of ozone might break one carbon21 carbon double bond. But is that a -- is that

22 a threshold, or is a threshold mortality? Is
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1 the threshold pulmonary function? Is the

2 threshold inflammation?

3 So, people get all confused by

4 this term. And then when you go to an

5 English-speaking person, as opposed to a

6 science-speaking person, the word threshold

7 has still a different definition.

8 See, I like keeping the science a

9 science. If 0.0001 ppm ozone causes an

10 adverse health affect, I'd like to know it. 

11 I know that that's like there's no way in the

12 world that you can think about regulating

13 that. I know that's an impractical thing, but

14 scientifically the science is what the science

15 is.

16 And so, we could discuss that. 

17 Then you can say, okay, now, here I put my

18 policy on top of it. We have to be realistic. 

19 There is this background, because what I see

20 happening is the science is driving the lowest

21 effective concentration lower and lower.

22 The world in terms of precursors
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1 to ozone is driving the policy-relevant

2 background up, up, up. They're going to slam

3 right into each other. Not today, but I mean

4 at some point in time, they're going to slam

5 into each other. And then what are you going

6 to do?

7 So, I mean I guess I prefer

8 discussion of it, and maybe you have to have

9 definitions, but this word threshold is just

10 a very, very difficult one to do. If I ruled

11 the world, I'd remove the word from the

12 lexicon.

13 But now where there is a

14 threshold, if you will, there can be a policy

15 definition of a threshold for acceptable

16 effects, a threshold for the definition of

17 adversity. So, you might say that at 0.0001

18 ppm ozone there's a change in FEV1 20 years

19 from now. But a policymaker could say, yes,

20 you're right. We measured that change. But

21 I as the policymaker don't find it to be

22 adverse.
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1 Now, we're not trying to define

2 policy here, but I'm saying that policy can

3 draw a line that maybe science cannot draw a

4 line.

5 DR. FREY: Okay, Fred.

6 DR. MILLER: Yes. As far as the

7 probability for a 0.0001 ppm ozone causing an

8 effect, as a statistician, it exists on a set

9 of Lebesgue measure zero. Okay, and you can

10 go look at that.

11 If you don't agree that there's an

12 effective biological threshold, then there's

13 no role for homeostasis. And so, when you

14 take those two concepts, then maybe it's not

15 the science thing, but maybe it has to be

16 defined from policy of what you can do. But

17 I do not endorse adding increments of risk, no

18 matter what the exposure. It is

19 teleologically not even appealing. And I hope

20 I go up, but I'm probably going to go down. 

21 So, you know -- so, I'm not sure how you can

22 accommodate everybody's views because I know
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1 what Judy is saying, and she's thought a lot

2 about this. But I also know the real world

3 has got to have effective thresholds.

4 Now, determining where they are,

5 maybe, is a problem, but it goes back to the

6 million-mouse study at Pine Bluff. You can't

7 mathematically show a curve that is -- that

8 defines the threshold or improve it anymore

9 than you can that there isn't. 

10 So, it's in this argumentative

11 level, but it's got to -- you should be able

12 to identify a level at which exposure says,

13 I'm not going to consider that you're getting

14 additional risk. And the reason that I say

15 this is if you have a lot of the exposures at

16 those levels, you falsely aggregate the risk

17 when it's really not there.

18 And so, that's my concern about --

19 and I don't know how you solve it. But I mean

20 maybe other people have views about this, but

21 I'm just not willing to give up on it at this

22 point.
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1 DR. PEKAR: Just to be clear too,

2 with the PMX risk assessment, one other option

3 that we did was we used the lowest measured

4 level. So, we said when we talked to

5 management about the risk assessment that we

6 had incidence estimates, and we identified at

7 what point an LML had been reached; not saying

8 that the concentration response function did

9 not continue below that, but just that this

10 degree of coverage within epi study gave us

11 greater confidence in being pretty -- having

12 greater confidence about what the function was

13 doing.

14 Not again that that's actually a

15 threshold at that point, but you could focus

16 on that with greater confidence. And so,

17 that's another wrinkle to --

18 DR. HUBBELL: And of course one of

19 the -- ozone concentrations these days go

20 very, very low. So, it doesn't have as much

21 of a practical implication as it does with PM,

22 using the LML.
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1 DR. FREY: Good. Sounds like a

2 challenge.

3 DR. BRAIN: I think we probably

4 beat this horse hard enough. I mean it's like

5 automobile safety. Is there a safe limit

6 where there's no injury. You know, it's a

7 gradual function; I think thresholds and other

8 bright lines aren't terribly useful.

9 DR. VEDAL: This is Sverre Vedal

10 here. I just want to put in a plug for the

11 sensitivity analyses that have been sort of

12 trashed. I actually find those to be

13 informative, and I agree with Michelle. I

14 mean you don't want to go hog-wild about that

15 and select a number of them, but I find them

16 actually quite insightful.

17 The way they're insightful is it

18 really determines how much of the risk

19 estimate is actually driven by the information

20 at the lower concentrations. So, I would like

21 to see it.

22 DR. SAMET: This is Jon Samet. I
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1 don't like to agree with -- I think you're

2 right on. I mean there's a lot of issues here

3 and sensitivity analysis is the way to go. 

4 DR. FREY: Okay, thank you.

5 DR. MILLER: And I would agree to

6 go that way, but that has got to be part of

7 the base resources because it does allow you

8 to separate out what is my area of concern. 

9 So, I would defer, and I agree that that's one

10 way to handle it. But that better be part of

11 the base analyses.

12 DR. SAMET: Sure, sure.

13 DR. FREY: Okay, we actually still

14 have to hear discussant comments from Judy and

15 then Michelle, since I assume your other

16 comments were just related to the discussion

17 at that moment. So, Judy.

18 DR. GRAHAM: Okay, a few general

19 comments. I can't help but say that OAQPS,

20 through their staff papers and how through

21 these risk analyses, they've created the gold

22 standard for chemical risk assessment. And
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1 it's -- there's -- there's just an amazing,

2 rich history there. You guys have big shoes

3 to fill, and I know you know it.

4 I also take note, as I said in my

5 written comments, that you adhere to most and

6 maybe even all of the NRC's committee's

7 recommendations on model being used for

8 regulatory purposes. That is unfortunately

9 exceedingly rare to see.

10 And so, I think I would like to

11 applaud you for that, and I think you ought to

12 pat yourself on the back for that, that that

13 would add credibility to your entire plan to

14 say that you're dealing with that.

15 My other comment about resources:

16 this was actually of all the comments I made

17 on the ISA in this, this was the hardest one

18 to write. I was trying to think about how can

19 I put my attitude about this resource

20 limitations in writing that would be polite

21 enough for people to read.

22 That was a real struggle. I came
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1 up with words totally unacceptable, and so you

2 can -- if that was my polite, you can imagine

3 what my impolite was. I know I'm preaching to

4 the choir, but I want to say it anyway.

5 Ozone is one of the very, very,

6 very few pollutants for which adverse effects

7 are observed in large numbers of people at

8 ambient concentrations. That is an oh my god. 

9 Our standard now is at three decimal places,

10 0.075.

11 So, when you think about that, to

12 protect the people according to the Clean Air

13 Act, and of course I wouldn't even think about

14 using the words compliance costs, there's a

15 real value in having accuracy.

16 There's a -- and so, penny-wise

17 and pound-foolish comes to mind. How can you

18 not get the resources to do what's important? 

19 Not resources for everything, but like I said

20 earlier on the exposure. I mean three cities

21 versus 12 cities. I mean to make a case, and

22 then for the people that control the money to
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1 think in prioritization terms from their

2 perspective.

3 You know, don't make you be the

4 only prioritizers here, but have higher levels

5 of management do the priorities, and think

6 about public health risks and the value of

7 being more precise, and that's where you guys

8 are going.

9 A few specific comments. Most of

10 mine were on the exposure side. On page 4-4,

11 again, you get into this resource limitation

12 about perhaps being able to use or not use

13 Bill McDonnell's 2010 paper. 

14 So, I mean I don't want to twist

15 your arm, but I'm saying if that brings value

16 to the analysis, then you almost have to do

17 it. You mentioned you were going to use the

18 Kim data. I don't think that's clearly laid

19 out in here, but -- so, you're finding ways to

20 incorporate some of the newer human clinical

21 data into your sophisticated analysis.

22 My concern is you guys are really
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1 working very, very hard, and you're going to

2 come up with something that's quite beautiful. 

3 And then, I or someone else is going to shoot

4 you down by saying, but you didn't use the

5 McDonnell data. So you have all this work,

6 and so you have to -- you have to also, just

7 like a physician might practice defensive

8 medicine, you have to practice defensive --

9 defensive regulation.

10 And so, there's some of these

11 resource things where you know it has to be

12 done scientifically. I mean just, good luck

13 to you. That's it.

14 DR. FREY: Okay, thank you, Judy. 

15 Michelle?

16 DR. BELL: So, overall, I thought

17 this document was very nice. One of the

18 comments I have is I think it's really useful

19 to define short-term exposure and long-term

20 exposure in this document.

21 This document actually did better

22 than the ISA in that there was an attempt to
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1 define it. There's a typo. You say short2 term exposure is greater than 24 hours. I

3 think you mean less than or equal to 24.

4 But that definition that's used

5 does not match -- let me correct the typo. It

6 does not match what's in the ISA. So, I

7 really liked that there was an effort to

8 define it, but it needs to be more flushed

9 out, and it needs to match what's in the ISA. 

10 Otherwise, it's just going to be a big mess.

11 And I wanted to comment on some

12 things that I thought were appropriate that we

13 were specifically asked to think about. And

14 one was the use of the fused modeling output

15 with the monitor data, and whether or not that

16 was appropriate, and EPA is considering that. 

17 I think that's very appropriate.

18 I think that's preferable to using

19 the model data alone. I think that should be

20 one of your many different types of analyses

21 where you don't supplant using model -- excuse

22 me, don't supplant using monitor data alone as
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1 well. But I thought the idea of using the

2 fused monitor model data was appropriate.

3 I also thought having sensitivity

4 analysis to include some health outcomes for

5 which you have maybe suggested causality but

6 not as much certainty, I thought that was

7 appropriate to include as a sensitivity

8 analysis.

9 I'm not so sure about the birth

10 outcomes endpoint, which has been mentioned. 

11 The drawn pregnancy outcomes in ozone is

12 pretty uncertain, much more than it is for

13 particles. And some people argue even that's

14 uncertain. So, I think you may be pushing it

15 a little too far to include that health

16 outcome, but I like the concept of including

17 those.

18 In terms of BenMAP, one of the

19 questions was is BenMAP appropriate to use. 

20 I think it absolutely is appropriate to use. 

21 I think it is definitely the way to go. I

22 think the write up of BenMAP in this document
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1 needs to be changed. Because if you read the

2 document, it talks about how with BenMAP, we

3 can produce this and with BenMAP, we can

4 accommodate this analysis.

5 Every single one of those things

6 you could've done outside of BenMAP. You

7 could've done it before BenMAP existed. So,

8 I think that you definitely can use BenMAP,

9 but I think you want to -- I mean there's no

10 reason to misportray BenMAP. It's pretty

11 great as-is.

12 So, I think that you want to --

13 one of the comments Zach made was that BenMAP

14 has gone through peer review, and eliminates

15 more possibility for making errors, and so on.

16 I think there's a way to kind of

17 word BenMAP in that framework. And what you

18 really mean is you can do things really

19 efficiently and completely in BenMAP, rather

20 than having to reinvent the wheel. So, I

21 would just reword the BenMAP discussion in

22 that framework to avoid confusion.
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1 Thresholds we've already gone

2 over. I got a little concerned over all the

3 different sensitivity analyses that are going

4 on, like you're going to get distributed lag

5 models. Well, that's great. You're going to

6 look at the covariants in the models. That's

7 great too. But it kind of started to seem

8 kind of kitchen sink to me, like, "We're going

9 to throw in everything."

10 There were two problems with that. 

11 One is that you're not going to have all this

12 flexibility. It's not like you're choosing

13 among millions of concentration response

14 functions. Therefore, you can take the one

15 that meets all of these criteria. 

16 So, it wasn't laid out in the

17 document what you're going to do if the short18 term mortality estimate doesn't meet all those

19 criteria, but the hospital admissions for

20 respiratory causes does. You know, and how

21 that's going to work.

22 And as a second example, I think
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1 you may be adding in a bit too much. I liked

2 almost all of them, but just to pick on one,

3 you talk about the models that you use

4 interaction term between ozone and

5 temperature. We understand that. And the

6 models that did that, they just threw it in.

7 I mean they're -- to just throw in

8 a variable for interaction between temperature

9 and ozone, knowing the relationship between

10 temperature and ozone, I mean doesn't -- isn't

11 -- it is very different to interpret. And

12 just because something is mathematically

13 possible doesn't mean it's always a good idea.

14 So, I think again I appreciate the

15 effort to try to be inclusive, but I think you

16 may be pushing things too far on the

17 sensitivity analysis, and I'll give that as

18 one example of something that I would omit

19 entirely.

20 I don't think you need it. You're

21 not going to have it for almost any health

22 outcome; you'll have it for some. But I
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1 would just give careful thought -- recommend

2 giving careful thought to all of them to say

3 which ones do -- which ones do I really want

4 to include, and which ones do I not? And I

5 think you'll eliminate at least maybe one or

6 two of them.

7 Just two more points on the city

8 specific analysis. I think there needs to be

9 not more thought, because I know you've done

10 the thought, but more discussion of what

11 really does this mean. Because the way I read

12 the document, you're going to take the

13 locally-derived studies where possible, and

14 then the rest of the cities you're going to

15 fill it in.

16 So, that means you're going to

17 have different -- different concentration

18 response functions from different study

19 designs, from different authors applied to

20 different cities, if I'm reading this

21 correctly. That's not directly comparable in

22 the same way.
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1 The local study may not be the

2 best study. But I do appreciate the need and

3 desire to try to get in some of these

4 community specific factors that modify the

5 effect. So, if you are going to do it, I

6 think that it is -- definitely want to go for

7 the Bayesian estimates and not the maximum

8 likelihood estimates, which is what is planned

9 in the document. But I just want to really

10 endorse that for sure.

11 I think you need to give more

12 thought -- maybe not more thought, but more

13 discussion to what are you going to do if the

14 Bayesian estimate is negative, but the overall

15 negative is overwhelmingly positive? Are you

16 going to put in that ozone is protective or

17 not harmful in this city? Because that's what

18 you're saying you're going to do, and so --

19 and maybe you are, but I would like to see

20 more discussion of that. 

21 And my final points goes to the

22 ICD codes. We actually recently did an
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1 analysis where we weren't trying to

2 investigate ICD codes, but we found people are

3 really not consistent on their ICD codes at

4 all.

5 Like even if you look at hospital

6 admission for pneumonia or hospital admissions

7 for COPD. There will be like five or six

8 different sets of ICD codes that people use. 

9 They'll be overlapping, but they won't be

10 exact. And so, the way I read the document

11 and also from Brian's clarification, you're

12 going to match the ICD codes in the incidence

13 codes to the ICD codes in the epidemiological

14 study, which I think sounds great, but what

15 are you going to do if they differ?

16 So, like in Detroit, you have this

17 set of ICD codes, and then in Atlanta, you

18 have a different set of ICD codes to define

19 COPD hospital admissions. 

20 It's starting to become a problem,

21 and you're stuck with what the epi studies

22 did, but I just think that -- I mean it's
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1 amazing. You'll read lots of studies and meta

2 analyses that don't even recognize that this

3 happened. And I'm not suggesting that it

4 would change the overall estimates a whole

5 lot, but it does matter. It's an additional

6 level of uncertainty. 

7 So, that was something else that I

8 think should be thought about. And that's all

9 my comments. 

10 DR. FREY: Okay, thank you,

11 Michelle. Other comments? Fred?

12 DR. MILLER: Following up on what

13 Michelle said about the McDonnell, I would not

14 even do the -- use the resources to compare it

15 to the old. I would just fit the McDonnell to

16 the additional data. Because it's clearly a

17 more defined model, and able to cover a number

18 of different factors.

19 And so, why do you feel like you

20 have to justify and compare it to the old? 

21 So, it just is, to me, an area that you could

22 say this is a newer model. It fits more
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1 different scenarios, and we're going to refit

2 it in the sense of lowering the exposure data

3 that are now available in that. But the

4 overall functional form of the model is very

5 powerful, and is defensible.

6 So, save some of those dollars and

7 time. Now, if it's just a matter of going off

8 tonight, and punching the button and the

9 computer does it all, that's a different

10 story. But I have a feeling that none of the

11 analyses that you guys are going to have to do

12 are so simple.

13 DR. FREY: John?

14 DR. BAILAR: A 30-second tutorial

15 on modeling. We all tend to think in terms of

16 linear models. There are a lot of reasons for

17 that. Linear models are simpler than non18 linear models. Most of the theory has to do

19 with linear models. Our computer programs are

20 set up to deal with linear models, but if

21 there's a curvilinear relationship, that can

22 cause all kinds of havoc. It can create or
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1 hide evidence of covariance of synergy. It

2 can expand generally, though rarely contract,

3 confidence bounds. It can do a lot of other

4 things.

5 So, before you use linear models

6 for any of this, and I'm talking not just

7 about this but EPA generally and the world in

8 general, before you apply a linear model, you

9 should look at the data to see if things

10 really look linear. And if not, there are

11 ways around that.

12 You can put in non-linear terms

13 like squares and cubes. You can stratify and

14 look at different pieces of data. There are

15 a lot of tricks you can use to get around it,

16 but if you make the fundamental mistake at the

17 beginning of creating non-linear data as

18 linear, you can end up wrong.

19 DR. HUBBELL: I wonder if I might

20 be able to respond to one thing that Michelle

21 said about the negative estimates. We haven't

22 laid it out in here, and we're all
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1 investigating it and evaluating this, and my

2 colleagues may or may not want me to go into

3 this yet. 

4 But in the global burden of

5 disease process that's going on right now,

6 where they're trying to develop concentration

7 response relationships for a number of

8 different endpoints, one of the things we've

9 moved towards, and I was a big supporter of

10 this, so I'm curious to see what the reaction

11 is, is we don't -- when we do our estimation

12 of traditional epidemiological models, we're

13 using normal priors.

14 Basically, we're allowing the

15 parameters to be normally distributed, without

16 any truncation of zero, regardless of

17 biological plausibility. What we're doing now

18 in the -- and that may be appropriate because

19 of the hypothesis testing process, but in

20 terms of risk applications, what we're now

21 doing in the global burden of disease study is

22 to refit a Bayesian adjusted concentration
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1 response relationship with a non-negative

2 prior.

3 So, basically, you're assuming

4 that you -- you know, it's not biologically

5 plausible to go and have a positive effect of

6 ozone or a PM on health, and therefore you are

7 truncating it at zero, and refitting the

8 distribution.

9 In our case, we're using a gamma

10 prior, but the point being is that it allows

11 for a lot of weight to be put at zero, but it

12 doesn't allow you to go negative. And my

13 question is whether this is something that the

14 Panel has any thoughts on, as a way to try to

15 get around this issue of negative numbers.

16 DR. BELL: I think it's

17 appropriate for global burden of disease. I'm

18 not sure it's appropriate here because these

19 processes have different goals. I mean global

20 burden disease is not a regulatory process,

21 although it might get used in that way. So,

22 I agree with you for global burden, and you
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1 may notice I didn't complain about it then.

2 So, I think that's good. I think

3 here it's starting to get dicey. Because

4 you're saying, "I believe this part of the

5 science, but I don't believe that part of the

6 science." And I think kind of conceptually it

7 makes sense, but I mean I think -- I think it

8 will be perhaps perceived and portrayed as

9 that you're picking and choosing the science. 

10 "Well, these show an effect testament, so I'll

11 pull them out. And these don't, so I'll move

12 those numbers up to zero."

13 I don't know that we can -- can do

14 that in a justifiable way. I mean I think

15 conceptually it's fine, but I think that this

16 is going to be the gold standard. This is

17 going to be -- has to be so defensible. And

18 if the effects are real, we don't have -- you

19 don't need to do that. You don't want to do

20 that.

21 And so, I think it's starting to

22 get to a slippery slope, where you're picking
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1 and choosing. I certainly wouldn't want

2 people to decide how problematic environmental

3 exposure is to human health by picking which

4 study is based on, "Well, this is the one I

5 believe, and this is the one I don't believe." 

6 And that's what it sounds like to me in a --

7 in this context, not for global burden of

8 disease.

9 I mean I just don't see how you're

10 going to say, "This is the overall effect that

11 we believe that includes these negative

12 estimates, but I don't believe them." That's

13 why I believe the overall effect. I have a

14 lot more faith in the multi-city estimate than

15 I do in the individual estimates, even the

16 individual Bayesian estimates.

17 You have to have a little bit. 

18 You have to have a lot. But pointing to the

19 Bayesian estimate, versus using the MLEs, and

20 I think everybody's on that page, which is --

21 DR. HUBBELL: You're saying you

22 don't want go full Bayesian? Because the
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1 Bayesian prior -- this is what everybody at

2 the GBD study basically said is, "Well, we're

3 not coming to these evaluation of these

4 empirical data with no knowledge. We don't

5 have any biological studies that suggest that

6 it's actually good for you."

7 In other words, it's bringing in

8 the clinical knowledge that says --

9 DR. BELL: Okay, well, let me give

10 it to you another way. So, if the affect

11 estimate for the individual city, the Bayesian

12 estimate is higher, are you going to pull it

13 down? Higher than the overall average, are

14 you going to pull it down? And you're not. 

15 You're saying.

16 DR. HUBBELL: No, because the

17 gamma function allows for those tails.

18 DR. BELL: Because you designed a

19 statistical function that picks and chooses to

20 say, "I don't believe the ones on the low end,

21 but I believe the ones on the high end." And

22 we can go round and round about this, but I
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1 mean my personal view is that it starts to

2 become a slippery slope, and it looks like

3 you're picking and choosing.

4 I guess my view is I want the EPA

5 to be much more technical and defensible than

6 global burden, which as you know is a

7 different goal. So, I think it's appropriate

8 there, but I mean I think it's starting to get

9 into dangerous territory here because I mean

10 the fact that we build a function around it,

11 like we're picking and choosing, and you're

12 not saying that the effect estimate for a city

13 shows -- the Bayesian estimate is much higher

14 than my overall estimate. You're going to use

15 it.

16 DR. HUBBELL: Yes.

17 DR. BELL: You're not going to

18 say, "Well, I'm going to shrink all of them. 

19 I'm going to pick and choose." I mean they're

20 all shrunken a little bit, but you're not

21 saying that one is wrong. You're just saying

22 the one at the low end is wrong. 
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1 So, if you believe the average,

2 and you believe the high end, you can't say

3 you don't believe the low end.

4 DR. HUBBELL: It's actually not

5 saying that exactly, but if you -- what we're

6 saying is --

7 DR. BELL: It is.

8 DR. HUBBELL: Okay, well, let me

9 just --

10 DR. BELL: You designed a

11 statistical function so that we can - you know

12 have that function mathematically pick and

13 choose for us, but you designed the function

14 based on priors that we decided. We decided

15 that zero -- like that number -- we picked

16 zero.

17 DR. HUBBELL: Well because

18 biologically -- there's no plausibility for

19 that. There's no -- there's no reason to

20 bound the upper end based on the clinical

21 studies.

22 DR. BELL: Well, this is why I
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1 have more faith in your overall estimate than

2 I do in the -- in the individual estimates. 

3 Anyway, so, that's my view. These are the

4 type of -- if I thought of it, five other

5 people are going to think of it. So, these

6 are the types of issues I think you want to

7 make sure is as defensible as you can in terms

8 of whatever you choose.

9 And I believe that the approach is

10 not to throw away the overall estimate, but to

11 do multiple approaches. So, if you are going

12 to do locally derived estimates with the 

13 Bayesian, you could also do your house, the

14 multi-city overall as well. So, you're not

15 throwing it away.

16 DR. MILLER: I'm not a skier, but

17 this is a slippery slope to me that is a very

18 logical one. Anyone who argues that exposure

19 to ozone is good for you --

20 DR. BELL: That's not what anyone

21 is arguing.

22 DR. MILLER: Well, no, you're
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1 basically saying you got to take the negative

2 of that and --

3 DR. BELL: No. I'm saying that if

4 someone is going to say, "I'm throwing out

5 these," they have to -- they are picking and

6 choosing. And you need to have a

7 justification for that. If a justification

8 says, "I believe that ozone is bad for you,"

9 then you're going to fit a mathematical

10 function to adjust the ones that you think are

11 wrong because you think they're wrong.

12 DR. MILLER: They're not adjusting

13 them. They're counting them with weight zero.

14 DR. BELL: That's how you're

15 adjusting them.

16 DR. MILLER: Yes, and it's

17 perfectly logical. It's the same way as if

18 you take your argument to the extreme. Let's

19 take the ATS's decision about the -- anything

20 not greater than 10 percent is just not

21 clinically relevant. You know? You can go

22 anywhere on this stuff. 
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1 You have to at some point in time

2 use your judgment about what you think is

3 real.

4 DR. BELL: That's right, and my

5 judgment is I think the overall effect

6 estimate has more certainty than the

7 individual city-specific estimates. And

8 that's my judgment. So clearly, EPA is going

9 to do what they're going to do.

10 This is what they're done before,

11 this type of thing --

12 DR. MILLER: That's fine. But

13 they weren't saying that they weren't going to

14 compare it to the overall. They're saying

15 this is one of the analyses that they want to

16 do to see what affect it has. That's what I

17 understood. It wasn't that --

18 DR. BELL: No, I exclusively said

19 that. They're going to do the multi-city as

20 well.

21 DR. MILLER: Okay, so, there

22 really isn't an argument.
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1 DR. BELL: I've already made my

2 point. I don't want to argue my point with

3 you anymore. I don't have anything else to

4 say on it.

5 DR. MILLER: I don't think there

6 was an argument with what they planned to do

7 is what I'm saying.

8 DR. BELL: I think that I had my

9 written comments, and I think that they

10 understand my point, whether it's agreed with

11 or not.

12 DR. FREY: John?

13 MR. LANGSTAFF: I just want to

14 make -- there's an analogist situation. I

15 mean the -- these 12 versions, they have some

16 errors associated with them, and we do

17 measurements. We know they're greater than

18 zero, but sometimes measurements are less than

19 zero because there's a distribution of errors.

20 But if we truncate those that are

21 negative to zero, then we bias the overall

22 average. So, I think that's kind of the thing
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1 she's -- that Michelle is talking about.

2 DR. FREY: Okay. Other comments

3 on health risk assessment issues by any other

4 Member of the Panel?

5 DR. ULTMAN: I want to ask for

6 clarification.

7 DR. FREY: Can you use the

8 microphone? Thanks.

9 DR. ULTMAN: I want to ask for

10 clarification. As I read the document, I

11 understood that you're going to be evaluating

12 the risk of the particular exposure relative

13 to the background level by -- by calculating

14 both the risks and then doing some type of a

15 subtraction. Is that right?

16 But couldn't you also do it more

17 at kind of the input end -- at the input end

18 of things? I'm talking about the laboratory

19 studies now. In the laboratory studies you're

20 doing it the same way for the laboratory

21 studies. That's the way the document would

22 seem to -
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1 MR. LANGSTAFF: Yes, that's --

2 DR. ULTMAN: It would seem to say

3 that. I would've thought you would've worked

4 on the response point first before you

5 calculated the risk, and calculate the -- you

6 know, the FEV1 decrement at the exposure

7 condition that you were interested in, minus

8 the FEV1 decrement that is estimated at the

9 background level, take the difference there,

10 and then calculate the -- the risk based on

11 that, rather than go through the whole risk

12 analysis on both of those.

13 Is that -- am I making any sense? 

14 I'm not sure.

15 MR. LANGSTAFF: Might make sense.

16 DR. ULTMAN: The reason I'm

17 bringing it up is because of the non-linearity

18 that was brought up by John before. Because

19 if there's a linearity in that process of

20 conversion from decrement of FEV1 to the risk,

21 it would make more sense to do the -- do the

22 adjustment on the decrement first, and then
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1 calculate the risk.

2 As you get into the details,

3 you'll -- of doing the calculations, I think

4 you'll see that's -- whether it makes sense,

5 or whether that's something you really can't

6 do. I'm just not sure of all the details of

7 all these -- of the process of how you go

8 through. But you might want to consider doing

9 the adjustment first, and then doing the risk

10 on the adjusted values, rather than trying to

11 adjust everything at the end.

12 DR. FREY: Okay. Yes, Ed?

13 MR. AVOL: One small comment

14 compared to the major discussions that have

15 happened, and this has to do with the

16 assessment of spatial homogeneity of ozone

17 across urban areas.

18 So, say you're going to use this

19 based on FRM monitoring -- we understand that

20 ozone in fact is not homogeneous, certainly

21 not in an urban area because of NO titration

22 near roadways.
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1 So, we know there are sort of

2 going to be peaks and valleys, if you will,

3 about the exposure but we're not going to pick

4 that up because of network doesn't allow for

5 that. At the end of that discussion, you say

6 you're going to -- you know, if you think that

7 it's -- that there is substantial spatial

8 heterogeneity, then you're going to somehow

9 enhance by more closer linking ozone levels to

10 demographics, and you're going to undertake

11 some sort of procedure to do something about

12 it.

13 So, I don't know if that requires

14 some clarification, or if you just want to

15 think about that, or rephrase that. But it is

16 a little confusing.

17 DR. PEKAR: I think that's another

18 thing that when Fred was talking about

19 identifying priorities, there are various ways

20 to calculate exposure surrogates when you're

21 dealing with monitor data.

22 So, we've talked internally about
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1 a number of different ways. First of all,

2 this is speaking just to the epi based risk. 

3 You know, you could take the monitors you

4 have, and look at where the populations are

5 located, where mobility patterns are, and do

6 a weighted aggregate kind of monitor value

7 based on where you think the populations are,

8 not that those monitors still capture

9 necessarily some of the gradients you're

10 talking about.

11 But at least rather than taking --

12 you know, a composite monitor where you just

13 took an average across the monitors without

14 any kind of weighting, you might weight the

15 monitors by where you think populations are.

16 The problem then is that doesn't

17 link to what was done in the epi studies. So,

18 we have this -- which we were talking

19 internally a little bit about. Do you do your

20 best to get a representative monitor value

21 that represents where people are by weighting

22 monitors, or do you try to match what was done
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1 in the epi because that reflected a certain

2 exposure surrogate with its problems?

3 And so, we -- we, you know, are

4 trying to consider that. I think we'll have

5 to see what kind of prioritization we do with

6 some of these efforts and our time. Because

7 these things take time.

8 MR. AVOL: Yes, I think that's

9 perfectly fair and appropriate, but I think

10 that it is a -- going to be a decision about

11 prioritization. I think you have to be up

12 front, and say, "Here's where we are, and

13 here's why we chose to do it."

14 DR. PEKAR: Right.

15 DR. FREY: For those on the phone,

16 Sverre, Kathy, John, any further comments on

17 this topic? 

18 DR. WEATHERS: Not from me.

19 DR. VEDAL: Not from me either. I

20 think we're following a template that can be

21 not quite uncomfortable with, at least

22 understand it. You know, it'll work -- I'm
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1 sure we'll have other observations.

2 DR. FREY: Okay. 

3 DR. SAMET: And this is John. I

4 think I'm a little bit in the spirit of some

5 of the concerns that Michelle voiced, just to

6 support that. I have to step away. I'll

7 probably be back on in a while, I hope. Okay?

8 DR. FREY: Okay, thanks, John.

9 DR. SAMET: Okay, thanks.

10 DR. FREY: All right, any other

11 comments from the Panel? I'm going to make a

12 couple of comments. There are actually two

13 issues I want to address. One is the comments

14 we heard on the WHO guidance, and I should

15 disclose I was on that working group.

16 I'm not going to argue that it

17 should or shouldn't be used, but I did want to

18 give some perspective on it. One is that the

19 notion of a tiered approach to uncertainty

20 analysis that might start with, say,

21 qualitative or deterministic, and then some

22 form of sensitivity and then one or two
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1 dimensional probabilistic analysis is really

2 not unique to that document. And there are

3 probably other references that could be cited

4 alongside that, or potentially in place of it.

5 I think EPA has been using that

6 notion in some of the other NAAQS assessments,

7 and typically, as I recall, it has been

8 described as being adapted and not taken

9 verbatim from WHO that -- and maybe the

10 language in this scope and methods plan seems

11 a little more prescriptive in the way that it

12 is talking about using WHO.

13 And so, I think what EPA has done

14 in the past, that the other CASAC panels have

15 generally supported, and so, I'd be a little

16 concerned about having inconsistency across

17 panels in pollutants in how EPA is dealing

18 with the notion of a tiered approach, and I

19 think it's perfectly legitimate for EPA to

20 adapt, or whatever it finds useful in that

21 make use of it. And it's not -- I don't think

22 it's intended to be highly prescriptive.
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1 I think it is offered for use if

2 it's -- if it's useful. I understand, I

3 haven't seen it myself, that EPA is in the

4 process of developing some probabilistic

5 guidance related to cumulative risk

6 assessment, and I think that's in draft form,

7 and I have no idea when that will be

8 available. And John Langstaff may know more

9 than I do about all things uncertainty within

10 the agency.

11 But anyway, I think the key points

12 are I don't think that's a unique expression

13 of a tiered approach. And I think the tiered

14 approach is helpful in just explaining the

15 thought process by which EPA decided to do a

16 particular kind of analysis, and I think EPA

17 is free to adapt or modify as they see fit. 

18 I think that would be consistent with other

19 NAAQS reviews that CASAC has looked at.

20 So, I just wanted to offer that

21 perspective. And so, I can pause for a minute

22 and see if there's any follow up on that. 
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1 DR. MILLER: I appreciate the

2 clarification because I think it's more a

3 matter of the way it was worded here --

4 DR. FREY: Yes, I think so.

5 DR. MILLER: -- coming across

6 prescriptive. I mean what you've described

7 and what Judy has told me sidebar here. It

8 certainly allows for adaptive. And I think

9 it was more just how it was written here

10 because your clarification has certainly been

11 very useful.

12 DR. FREY: Okay, good. 

13 DR. WOODBURY: Just to add a

14 little bit to this discussion of uncertainty

15 analysis and approaches, and again this is

16 nothing new, but just to make sure it's in

17 this -- added to this context is -- you know,

18 we can all put distribution functions on

19 whatever parameters we want, and we can

20 propagate them. But we're looking for insight

21 here about the implications of the results.

22 So, focusing on the most important
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1 variables, whether something's actually known,

2 there's a basis for the distribution

3 functions, or where there's really systemic

4 uncertainty, and something needs to be done to

5 address that. You might not want to fit a

6 function to it. It's a what-if scenario.

7 So, I guess I'm elaborating a bit

8 on Dr. Frey's comments. The other thing is to

9 just really, in my view, keep a very sharp eye

10 on sources of bias and interactions. Again,

11 we can propagate uncertainties, and we can

12 make the bounds as large as we want, but we're

13 really looking for the things that matter. 

14 DR. FREY: Yes. That's an

15 excellent point. The other thing I wanted to

16 come back to was just that we've heard a lot

17 of discussion about prioritizing and laying

18 out kind of a road map for what the priorities

19 are, being prepared to make decisions, and

20 Fred Miller even suggested consulting with

21 CASAC on that.

22 I guess I wanted to just point out
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1 as a practical matter the first draft REA

2 comes out. I guess it's scheduled for October

3 for a November review by this Panel. Then the

4 second draft REA would come out in May of 2012

5 for a possible July review by this panel.

6 So, that would seem to be the next

7 formal opportunity for CASAC to comment on

8 priorities. On the other hand, if CASAC is

9 commenting in priorities in May, and say it

10 takes a month or so to finalize that, and then

11 EPA needs to get its second draft REA done by

12 October, it doesn't give a lot of time to

13 respond to that.

14 So, I guess I would like to give

15 an opportunity for EPA. Have you gotten what

16 you needed from us today? Is there anything

17 you were hoping to hear from this panel that

18 you haven't heard from that would help you? 

19 So, just open for a little bit of opportunity

20 for whatever inputs you're looking for. 

21 DR. HUBBELL: Thank you very much. 

22 I mean we've really heard a lot of actually
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1 very helpful advice so far. I think there's

2 obviously a lot of work to do in terms of

3 taking what you've given us, and matching that

4 with what we thought of as sort of the

5 priority elements that we needed to work with.

6 One area that was mentioned

7 earlier by I think Dr. Miller regarding areas

8 that need more discussion, and that -- one of

9 those is long-term mortality. We talked about

10 thresholds quite a bit, and we've now talked

11 about sort of dealing with negative estimates

12 some, but this question of what do we do with

13 long-term mortality: it is a -- potentially a

14 big hitter in terms of having an impact in

15 terms of discussions about -- about health

16 impacts. 

17 Just for disclosure on this, one

18 thing we have seen in our applications to date

19 of looking at long-term mortality functions

20 using the Jerrett study, and there's a paper

21 by -- by Neil Pham and some others within our

22 group that, as estimated, recent conditions of
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1 PM and ozone, and what's the health impacts

2 associated with those, and it includes an

3 estimate of ozone related mortality based on

4 the Jerrett study.

5 And one thing we've noted is that

6 unlike PM, when you apply the long-term

7 function -- long-term exposure based function

8 for ozone, you're not hugely greater than some

9 of the bounds of the short-term mortality

10 estimates from some of the existing meta

11 analyses.

12 So, it's not as -- it's not as

13 influential as the different between long-term

14 PM mortality and short-term PM mortality, but

15 it's still important and it represents

16 potential importance because it's a different

17 functional form. It's a different form of

18 exposure that might be different than an

19 eight-hour maximum standard, and that's why it

20 has a great deal of importance to us.

21 It's not just because of the

22 impact, but because of the way it would affect
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1 our thinking of the form of the standards. 

2 So, we would like some additional input from

3 you on should we be looking at these long-term

4 types of health functions? And if not

5 premature mortality, what else might we

6 consider as a way to represent risk associated

7 with repeated peak exposures or longer term

8 exposures?

9 DR. VEDAL: Brian, just a point of

10 clarification. I mean in terms of the long11 term mortality stuff, Jerrett paper, which is

12 the only one out there, I mean you -- the

13 reason for the restricted impact the fact that

14 it's basically COPD mortality?

15 DR. HUBBELL: Yes, and that does

16 have something to do with the fact that it's

17 respiratory mortality rather than -- then all

18 cause mortality. But again, there's some

19 question about how are we interpreting the

20 non-respiratory mortalities associated with

21 ozone. There's some questions about should we

22 be interpreting the cardiovascular deaths in
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1 the same way we did the respiratory deaths,

2 and there's -- there's -- I'm not -- I agree

3 with you that that is --

4 DR. VEDAL: Why would we? I mean

5 there's no evidence of cardiovascular deaths

6 from long-term exposure elevated.

7 DR. HUBBELL: Yes, right.

8 DR. BELL: I think it'd be fine to

9 include as a sensitivity analysis. I mean how

10 far down in uncertainty do you want to go? 

11 Like I wouldn't go all the way to birth

12 outcomes, but I might go to long-term

13 mortality.

14 I just think that discussion both

15 in ISA and whatever the results are from this

16 project can include the information on briefly

17 summarizing why these outcomes were not

18 included in the main analysis, or why for that

19 one it's just a single study. It's really not

20 a cohort. I mean it is in terms of health

21 response, but it is not in terms of exposure.

22 We don't have their exposure over
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1 their time. We just know where they were at

2 the moment. So, those types of issues I

3 thought would be useful, but I mean to me, I

4 think it's appropriate to include as long as

5 it's not in the base analysis.

6 DR. VEDAL: Well, I mean it gets

7 to issues of, you know, the whole issue of

8 where it buys on our -- our causal framework,

9 right? And then they -- the perennial

10 question is whether we have a risk -- formal

11 risk assessment carried out for things where -

12 - where we don't meet the sort of higher

13 levels of causation.

14 Now, in this case, there'd be an

15 argument that we're doing that. We should

16 probably be doing it for a number of

17 endpoints, where we have the same sort of

18 grading of causation, although I think maybe

19 the mortality and long-term mortality issue is

20 perhaps a little bit of a one off because of

21 its significance.

22 But I've sort of waffled on this
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1 one way or the other. You know, whether we

2 want to do a formal risk assessment for things

3 that are lower down on our causal ladder. 

4 Just because when you do a risk assessment, it

5 takes on a life of it's own that is perhaps

6 overly influential.

7 But I think I agree with Michelle. 

8 I would -- at least in terms of the restricted

9 endpoint that we've been talking about, I

10 think it would be informative.

11 DR. FREY: Yes, Fred?

12 DR. MILLER: Sverre, could you

13 clarify what you said about the Jerrett and

14 the COPD mortality? Was that the -- any

15 respiratory mortality, or was this

16 subclassification --

17 DR. VEDAL: I can't remember. I

18 can't remember specifically COPD or a more

19 general respiratory, but I think even if it is

20 in a general category of respiratory, it

21 probably is driven by COPD.

22 DR. MILLER: Yes, and I guess I
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1 have to express my personal bias, since 95

2 percent of COPD is related to smoking. Only

3 five percent of the cases are not. I really

4 would keep this in the supplementary kind of

5 thing, and not elevate it to a full scale risk

6 assessment. 

7 DR. BELL: They account for

8 smoking, but I still agree with you.

9 DR. HUBBELL: And on that -- on

10 that particular point, the point that is

11 often made is that it's -- it is deaths in

12 people with COPD. So, it's not necessarily

13 saying that it's the air pollution causing

14 the COPD as much as potentially leading to a

15 premature death in someone with COPD as well.

16 DR. MILLER: I think the

17 sensitivity --

18 DR. FREY: Other comments? Any

19 other questions from EPA to the Panel?

20 DR. HUBBELL: Just expanding on

21 that, are there others based on everyone's

22 understanding of the literature? Are there
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1 other endpoints associated with longer term

2 exposures that we should be considering for

3 the risk calculations, or is it really the end

4 of the discussion about long-term exposures?

5 DR. BELL: Why are you looking at

6 me?

7 DR. HUBBELL: Because you're a key

8 epi person. Because Sverre is on the phone.

9 DR. BELL: Sverre, I'm looking at

10 the speaker. I mean I would actually just sit

11 down with a list of not just long-term, but

12 all the health outcomes the way they've been

13 categorized, causal, likely causal, suggestive

14 causal and so on, and just decide how far down

15 you're going to go on the list.

16 If you're going to include long17 term respiratory -- long-term exposure and

18 respiratory mortality, you don't want to leave

19 off something that you said had the same level

20 of uncertainty. So, I would just try to make

21 it consistent, and I would not go all the way

22 down the list to birth outcomes, but I mean I
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1 -- that's how I would do it.

2 DR. HUBBELL: One of our issues

3 that we run into with ISA, and again this is

4 not a fault of the ISA, it's just the way it's

5 structured, is that they tend to make

6 statements about causality for broader

7 categories than individual endpoints.

8 So, for example, they'll make a

9 statement about likely causal or causal for

10 respiratory morbidity. Well, that's not

11 exactly how the endpoints are divided up in

12 terms of the epidemiology. And so, it's

13 choosing amongst those is often a very

14 different task because when you say, "Well, do

15 we have sufficient evidence for this one

16 endpoint to determine that it is a likely

17 causal?" And then we don't usually get that

18 kind of advice from the ISA.

19 DR. BELL: And I would choose, of

20 the endpoints that have been clustered, I

21 would choose the one with the strongest

22 evidence to be representative of that
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1 category. And I would word it that way,

2 because you're not going to get every health

3 endpoint, right?

4 DR. MILLER: In view of Dr. Frey's

5 clarification about when this first draft is

6 available, it seems like rather than coming

7 back with the -- an immediate prioritization,

8 if in this first round exercise, you are

9 basically going primarily with all of the base

10 things that you feel, and you may make some

11 limited progress on some of the others, it

12 seems like at that point in time would be good

13 to, as part of our meeting, to discuss your

14 prioritization at that point of what you have

15 left.

16 DR. FREY: Yes.

17 DR. MILLER: So, I would modify

18 what I said earlier, because I think that's a

19 good strategy.

20 DR. PEKAR: That's actually

21 exactly what we were sort of thinking.

22 DR. FREY: Great. Are we at a
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1 good point with the health scope and methods

2 plan? So, question. We can either break now

3 for lunch, and then I know we lose Daniel in

4 an hour.

5 DR. JACOB: I can be here until

6 1:30.

7 DR. FREY: OKAY. Or, we could ask

8 Travis to present, and he assured me he didn't

9 need a full 30 minutes. At least get that,

10 and if anyone had to pressingly leave, have a

11 chance for some quick comments, and then break

12 for lunch.

13 I'm sort of tempted to go with the

14 latter, unless anyone is really hungry. Okay,

15 well, that's self-policing, because if

16 everyone looks hungry, and someone starts

17 making comments. So, Travis, what do you

18 think? Can you give us a presentation in 20

19 minutes or less?

20 DR. SMITH: Certainly.

21 DR. FREY: Okay, do you want to

22 give it a shot? And by the way, thank you
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1 Zach. And I guess Brian and John are still at

2 the table. So, I'll thank you later. And

3 while we're waiting for the video, just a

4 reminder that comments are due June 3rd.

5 So, your revised pre-meeting

6 comments, or if you hadn't submitted pre7 meeting comments, but now you would like to do

8 so, everyone is welcome and encouraged to do

9 that. 

10 DR. HUBBELL: Holly, do you have

11 the slides? Because we can pull them off and

12 put them on there. Travis didn't realize he

13 was supposed to bring a jump drive.

14 DR. STALLWORTH: The email would

15 be from whom?

16 DR. HUBBELL: It'd be from Travis,

17 I believe.

18 DR. SMITH: I had emailed you

19 initially with the slides, and then I emailed

20 you later with the PDF. 

21 DR. STALLWORTH: When did the PDF

22 come? Was that yesterday?
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1 DR. SMITH: Wednesday.

2 DR. STALLWORTH: They're posted

3 but --

4 DR. HUBBELL: We could download

5 them, and put them on the USB. Maybe we need

6 to delay and eat, and then come back, since

7 there's a technical glitch.

8 DR. FREY: Holly, should we wait

9 for this, or take our break now?

10 DR. STALLWORTH: I don't know. 

11 DR. FREY: Yes, we don't actually

12 have any further public comments. That's a

13 good suggestion. Well, since we're waiting,

14 why don't we go ahead and take our lunch break

15 now. But let's try to keep it to 45 minutes,

16 and we'll start at 12:45.

17 (Whereupon, the foregoing matter

18 when off the record at 12:02 p.m., and resumed

19 at 12:47 p.m.) 

20

21

22
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1 A-F-T-E-R-N-O-O-N S-E-S-S-I-O-N

2 12:47 p.m.

3 DR. FREY: All right, so, Dr.

4 Travis Smith will be presenting on the welfare

5 scope and methods plan. Dr. Smith, the floor

6 is yours.

7 DR. SMITH: Gee, thank you. I'm

8 competing with the trickle in from lunch here. 

9 So, this'll be pretty brief, I think, which --

10 and we can move onto the comments, and people

11 will be ready to get out of here at the end of

12 a Friday afternoon.

13 So, this is just going over the

14 scope and methods for the welfare assessment

15 plan. And it's kind of in the same vein of

16 this morning, it's just trying to get input

17 and comment on the methodology that we've kind

18 of laid out, and the framework we've laid out

19 of how we want to go about this.

20 This is a very quick background

21 for the secondary standard that as of the

22 review completed in 2008, and prior to that
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1 the secondary standard for the ozone NAAQS set

2 is identical to the primary standard.

3 But as part of the current

4 reconsideration, the EPA has proposed a

5 separate secondary standard, using the W126

6 metric, and I'm not sure what the exact -- the

7 current -- July I think is the --

8 DR. HUBBELL: Well, we don't know.

9 DR. SMITH: We don't know. So,

10 that's -- so, to kind of lay out what the kind

11 of framework we're using is, and this is kind

12 of built off of what was done in the NOx SOx

13 secondary analysis that was just -- or is also

14 still in the process of being completed at

15 some point.

16 I want to lay this out as kind of

17 an idea how we're trying to think about doing

18 this, and one is that obviously there's the

19 ambient ozone exposure, which leads to some

20 ecological effects, and then there's a series

21 of four different types of kind of following

22 the SAB report, and the millennium report. 
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1 We're looking at four different types of

2 ecosystem services that there's kind of the

3 direct regulating, cultural and provisioning

4 services that are directly affected by some of

5 the ecological effects, and then there's

6 supporting services that are affected by the

7 ecological effects.

8 So, it's kind of an intermediate

9 affect, or an indirect affect. And part of

10 the reason for wanting to lay it out in this

11 structure, and also I should say this is not

12 intended to be a complete list of everything

13 we're going to look at. This is just to kind

14 of give an idea of how the framework is going

15 to work.

16 Part of the idea of laying it out

17 in this structure is that there are some

18 ecological effects that are very clear, things

19 like the biomass loss or the visible foliar

20 injury. There's a very clear affect of

21 ambient ozone on that end of that ecological

22 affect.
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1 In some cases, there's a very good

2 tie; how we can connect that to an ecosystem

3 service. In other cases it's not so clear. 

4 And then there's other ecological effects. We

5 don't have -- from the ISA, there's either

6 conflicting data, or there's a number of data

7 and it was not fully linked together, and the

8 studies weren't -- we don't have good

9 ecological data on everything, but there are

10 others we can look at.

11 Part of the reasoning for laying

12 it out in this kind of structure is to allow

13 us to lay out what we do know. We do know

14 that there's a biomass loss, or we -- I think

15 -- system model conductance that we can talk

16 about, but we're not clear how it's going to

17 connect to an ecosystem service, and this way

18 we can lay out what we do know, and then lay

19 out as qualitatively as we can the parts that

20 we don't know, partly so they're out there for

21 the scientific community to see where are the

22 gaps in our knowledge so that we can use those
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1 in the future. 

2 Because there are things we think

3 are important, but we can't -- we just don't

4 have the information to put them into a risk

5 assessment at this point, but we do want to

6 have them laid out so that they're available.

7 So, the first step of this, and

8 I'm not going to belabor the exposure surface

9 too much in the -- we've already had a lot of

10 discussion on exposure, but the big difference

11 for the welfare assessment is that we need to

12 interpolate an exposure surface to include

13 areas with few or no monitors.

14 So, a rural area where there's no

15 monitors there. And so, there is going to be

16 -- we do have to have a different exposure

17 surface that accounts for these areas that

18 just don't have very good monitor data.

19 So, the last risk assessment did

20 look at several methods. We've kind of

21 building off of that, and we're also looking

22 at two different methods, the model detainment
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1 test software, that uses the 2005 -- the

2 current version that we have uses the 2005

3 CMAC, and ambient model data, which is the 12-

4 kilometer grids, and it couples -- and it

5 fuses that with the monitor data from 2004 to

6 2006. And we have then one surface based on

7 that set of data.

8 Another method we're thinking

9 about using is the Voronoi Neighbor Averaging

10 Interpolation, which the BenMAP actually has

11 a tool that allows to do that from BenMAP. 

12 The difference of that would allow us to use

13 more recent monitor data, which would be from

14 2008 to 2010, which not to get back into the

15 discussion earlier, that was the big

16 discussion earlier as far as whether those are

17 the correct years.

18 So, whatever we do with those,

19 that will certainly be something we'll lay out

20 as to how we're going to assess which of those

21 works best, and try to decide how we're going

22 to use that. Which one works best to cover
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1 both east to west? There are differences in

2 the eastern US and the western US.

3 So, some of the main ecological

4 effects that we really have very good

5 information from the ISA: one is the

6 concentration response functions for biomass

7 loss. Those come from -- there's 11 tree

8 species. They're basically the same as for

9 the last review, and really the difference

10 we're going to have is we're just going to

11 have a new exposure surface to compare that

12 with. 

13

14 We do have a foliar injury in the

15 incidence data from the Forest Health

16 Monitoring Program, and the FIA data, and the

17 National Parks Service also has a list of

18 ozone sensitive species. Those are species

19 that are thought to exhibit foliar injury at

20 ambient levels.

21 Then we also have concentration

22 response functions for the domestic crops
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1 species from data, which is the equivalent

2 more or less of the biomass loss data for non3 agricultural species.

4 So, the first thing we're going to

5 try to do is look at a national scale

6 vegetation effect, which is more or less to

7 create a potential biomass loss surface for

8 those 11 species, using the new ozone exposure

9 data and the FIA species, the most up to date

10 FIA species range data, and it'll also have

11 the National Foliar Injury occurrence maps,

12 just as -- these are kind of a broad picture

13 look at the effects of ozone on these

14 vegetation.

15 Then there's also comparing those

16 to the endangered species critical habitats,

17 which are a -- those are obviously a

18 nationwide system of areas.

19 And so, you kind of skip to

20 ecosystem services now, and we're really kind

21 of looking at several models, and this is

22 actually trying to put valuation on some of
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1 the ecosystem services, as opposed to just

2 what the service is. 

3 And so, where we have recreational

4 services, or recreational use, and we have

5 timber loss, crop loss, some of those are easy

6 to value. Some are not. These are some of

7 the models that we're looking at for using to

8 put valuation on things. One is the AGSIM

9 which puts using the data. There's the FASOM

10 model, which also gets into timber species.

11 Both of these are going to be

12 somewhat dependent on AGSIM. We can

13 potentially run in house. FASOM is an

14 external proprietary model that we're -- that

15 will not be run through the EPA.

16 Then we've also been talking with

17 the forest service on the use of the I-Tree

18 model, which looks at urban ecosystems, and

19 specifically models VOC emissions, building

20 energy use, pollution removal and carbon

21 storage, and sequestration within urban

22 forestry settings.
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1 So, kind of a new thing that we're

2 doing in this risk assessment from the last

3 risk assessment. We've included the idea of

4 trying to look at some case study areas, and

5 what we're hoping is that we can then do some

6 more refined analysis using the FIA species

7 range data.

8 Species don't have the same

9 abundance throughout their range. They don't

10 have -- there's a lot of different things. 

11 They don't occur at every point within their

12 range. So, we wanted to try to go into some

13 areas where we could really get a much more

14 refined analysis to try to assess on a more

15 controlled scale what is the real -- the real

16 potential biomass loss, or the percent of the

17 area that might be affected by foliar injury

18 within these areas where we have better data?

19 And so, some of the selection

20 criteria, we came up with that as these

21 current areas -- we needed areas obviously

22 with kind of expected elevated ozone levels,
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1 and we also needed availability of vegetation

2 mapping, including estimates of species cover,

3 which is not -- there's a lot of vegetation

4 maps that cover them nationally, but they

5 don't really get into species cover in a way

6 that we could apply at this level.

7 We wanted to come up with adequate

8 geographic coverage to include -- including

9 urban and natural settings, but trying to get

10 a nationwide look because the ecosystems are

11 highly variable across the country, and that's

12 just how they are.

13 We also needed there to be current

14 -- we wanted there to be ozone sensitive

15 species there, or otherwise they would be kind

16 of a -- we wouldn't have much to talk about. 

17 Then we do primarily have the 11 species where

18 we have the concentration response functions

19 for biomass loss.

20 So, the first set of places we

21 were looking at is the national parks. 

22 There's this ongoing project with USGS to
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1 produce vegetation mapping. They include data

2 points with estimated species cover in those

3 areas, and they are pretty detailed maps, a

4 strength.

5 Not all the parks are done at this

6 point, but a number of parks are done, and the

7 mapping is, if not by all the same people, at

8 least using a similar method. So, they should

9 be as comparable as you can get across park

10 units.

11 There is the list of ozone

12 sensitive species for parks, and then we also

13 have GIS information for trails and other

14 recreation areas that we can look at how that

15 might be affected by biomass loss or foliar

16 injury and other things.

17 Then we also have the national

18 parks. We do have park use data. There are

19 a few parks that have willingness to pay

20 studies in relation to the ecosystem services.

21 So, the parks are a very good

22 source of information to try to get at some of
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1 the non-provisioning service ecosystem

2 services, primarily what are considered the

3 cultural ecosystem services of recreational

4 use.

5 So, the potential parks we've

6 thought of: the Great Smoky Mountains National

7 Park, Rocky Mountain National Park, and then

8 the Kings and Sequoia National Parks in

9 California. Some things we can look at are

10 certainly the percent of vegetation cover

11 affected by foliar injury. That's just taking

12 the combination of the estimated percent

13 species coverage areas within the park, and

14 applying that to the polygons of -- in GIS,

15 applying that to the polygons and really kind

16 of getting just a rough estimate.

17 It's not that this is not data

18 that's going to be highly variable. There's

19 going to be a lot of uncertainty in it, but it

20 is an estimate we can come up with. And then

21 we can also look at very species specific

22 biomass loss, where we have estimates of
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1 actual area cover per species that we do have

2 a concentration response function per proposed

3 biomass loss.

4 We can then really look at how

5 much actual biomass loss might we expect for

6 that species within the park. And then we can

7 look at the recreational areas, and make

8 estimates of how much -- what percentage of

9 the recreation areas within the park might be

10 expected to be affected by visible foliar

11 injury, or biomass loss or habitat loss.

12 This is something that we're

13 trying to go in the area of. This is going to

14 be very hard to quantify specific to an

15 ecosystem service, but given willingness to

16 pay studies when available, we might be able

17 to make some estimates of an expected affect

18 on the recreational value to the people using

19 the parks.

20 Within urban areas, a couple of

21 areas we've looked at is San Diego County in

22 particular. Before coming to the EPA, I lived
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1 in San Diego. So, I'm familiar with this. 

2 There's a multi-species conservation plan that

3 has very good vegetation mapping. So, we

4 might have an availability.

5 Boulder, Colorado has a regional

6 planning -- regional planning -- regional

7 plan. I'll get that out. And that does have

8 good vegetation area as well, and those are

9 some areas that we do know are ozone -- they

10 also share some ozone sensitive species with

11 nearby parks. And so, we do have information

12 about those areas.

13 As far as ecosystem services, we

14 can look at similar things to the national

15 park areas, where we also might be able to

16 include more specific information to some of

17 the wetland data, where we do have -- we do

18 know in places like San Diego how much money

19 gets spent by the county on dealing with

20 sediment runoff and other things that are part

21 -- that would be a wetland functioning.

22 Then we also might apply the I-
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1 Tree model, which the I-Tree model may or may

2 not overlap with the specific case study areas

3 that have been used in Chicago and several

4 other areas. That would be another way to

5 look at the urban ecosystem services. And

6 that is it.

7 DR. FREY: Excellent. Thank you. 

8 Are there any clarifying questions from the

9 Panel?

10 DR. GRANTZ: In the plan, there

11 was a lot of angst over whether to use AGSIM

12 or FASOM, which I commented on, and I couldn't

13 understand why it was there. Is that simply

14 a cost issue?

15 DR. HUBBELL: It's a cost and

16 access issue, as Travis said. We've been able

17 to bring AGSIM in house because we were able

18 to get the code from --

19 DR. GRANTZ: because it was

20 inexplicable the way you --

21 DR. HUBBELL: Right. Preferably,

22 we would use FASOM because it is an integrated
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1 -- but Bruce McCall at Texas A&M is the only

2 one who can run it, and it costs money, and we

3 can't get it. 

4 DR. GRANTZ: You ought to say that

5 then.

6 DR. FREY: Yes, Howard?

7 DR. NEUFELD: A couple things as I

8 was listening to this. Can you -- in terms of

9 trying to get the economic costs for natural

10 ecosystems, can you use some of these papers

11 that have been written by the ecological

12 economists, looking at the value of ecosystem

13 services? I mean I know one of them have been

14 ecosystem services three times the total world

15 GDP or something. I don't know if those are

16 useful or not.

17 DR. FREY: Well, there's two types

18 of -- there's the value of everything studies,

19 which is the Constanza study that you're

20 referring to. Then there's the value of

21 marginal changes, which are the ones you can

22 use.
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1 So, what we're looking for is

2 actually studies that allow us to look at the

3 willingness to pay for marginal or incremental

4 changes in ecosystem services associated with

5 an ozone exposure. Those are much more

6 difficult to get. And so, we're still looking

7 at trying to get those, but there are some

8 studies, and that's what Travis was referring

9 to is there are some studies that, for

10 example, look at recreational values due to

11 foliar damage.

12 There's also studies that look at

13 particular types of changes in other services

14 that -- for example, habitat and things like

15 that. So, there are some out there, but

16 getting those incremental changes is a lot

17 harder. 

18 DR. NEUFELD: The other thing was

19 you were talking about percent cover of

20 species affected by ozone, and trying to

21 figure out how to do that, whether you had

22 vegetation maps and so on.
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1 Can you -- if you are lacking

2 those things, can you combine different data

3 sets? For example, there are tons of

4 ecological data sets of lists of species and

5 the frequency of those species, and there are

6 allometric equations then relating leaf area

7 and so on. So that if you didn't have a

8 vegetation map, but you knew what kind of

9 forests were in the general area, could you

10 sort of make best guesses by saying, "Okay,

11 it's probably following this distribution?"

12 DR. SMITH: I think we probably

13 could. I say that without looking -- but I

14 think at this point, in what we're trying to

15 do, we're kind of looking for what's the best

16 available information out there. Something

17 like that might work in areas where we don't

18 otherwise have good vegetation mapping. And

19 so, it might be very possible to include that.

20 It might be worth looking at those

21 in the context of the places that we do know

22 something about and see how well they match.
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1 DR. NEUFELD: Yes, right.

2 DR. SMITH: And then we could

3 potentially expand to other areas that we

4 thought were important.

5 DR. NEUFELD: Okay. And I think

6 too when you look at cover affected by ozone,

7 other than just looking at the polygons, I

8 mean Art Chappelka's data is -- and John

9 Skelly's and other people's data, show a very

10 clear impact of elevation. And the frequency

11 of the trees and the percent of the canopy

12 that's affected by ozone dramatically changes

13 with elevation, sometimes non-intuitively,

14 because of changes also with moisture as you

15 go up and down.

16 So, I think you need to take

17 elevation into account. The other thing would

18 be that in forested areas, you -- I don't know

19 how you're going to account for it, but ozone

20 is dramatically reduced as you go through the

21 canopy.

22 We did some brief studies, and
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1 found that by the time you go to the height of

2 the herb layer, about a meter off the ground,

3 it was 50 percent of what was above the

4 canopy. So, it was reduced by half. And that

5 also was affected by elevation.

6 On a ridge top, it was only

7 reduced by a maximum of 20 percent. So, you

8 had these confounding variables or extra

9 variables that you need to -- otherwise, you

10 overestimate the ozone impact on everything in

11 the under story. 

12 DR. HUBBELL: All right.

13 DR. NEUFELD: Then the last thing,

14 on the I-Tree model. Is this the same model

15 that comes out of the Southern Experiment

16 Station? Because the Auburn campus, for

17 example, was -- just designated a tree campus. 

18 And so, they also had out of the Southern

19 Experiment Station a model assessing the

20 economic impact of the trees on the campus,

21 according to their size and state of health,

22 and vigor and all that kind of stuff. I'm not
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1 sure if that's the same thing or something

2 different, but that might be a model --

3 DR. HUBBELL: Something we should

4 look at, yes.

5 DR. NEUFELD: Then they end up

6 giving an economic impact of the trees on that

7 campus.

8 DR. HUBBELL: Do you know who the

9 principal on that one was?

10 DR. NEUFELD: Well, the person you

11 could contact to find out more about it would

12 be Art Chappelka. 

13 DR. HUBBELL: Okay. 

14 DR. FREY: Okay, thank you. Let

15 me just check and see how is on the phone. 

16 Kathy, are you on the phone?

17 DR. WEATHERS: Yes, I am, and I

18 have a question. 

19 DR. FREY: Okay, let me just check

20 is Sverre on the phone? And John Samet? 

21 Okay, so, Kathy, you had a clarifying

22 question?
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1 DR. WEATHERS: Yes, on the VNA

2 interpolation, what's the spatial resolution

3 for that?

4 DR. HUBBELL: The spatial

5 resolution is determined by the user. You can

6 limit it to a certain distance around the

7 monitors, or you can do unlimited averaging as

8 well. 

9 One of the things that Travis was

10 talking about was -- was trying to do these

11 kinds of integrated assessments using the

12 model data, coupled with the monitor data, and

13 BenMAP can do that as well. It's a process

14 called Enhanced Voronoi Neighbor Averaging,

15 which basically means you're combining the

16 model gradient with the monitor data to be

17 able to interpolate those ratios. 

18 We've always been a little

19 cautious about doing just straight VNA in

20 rural areas. What we have found in the last -

21 - the last time that this was used for the REA

22 was that it worked fine in the eastern US,
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1 even for relatively rural areas, because you

2 had such a dense monitoring network. But in

3 the western areas, it doesn't perform quite as

4 well.

5 So, there was -- that's what the

6 question about what's the best way to get a

7 good surface that covers both the east and the

8 west; that's still something we're evaluating.

9 DR. FREY: Okay, Kathy, is that

10 it?

11 DR. WEATHERS: Yes.

12 DR. FREY: Okay, thanks. Joe?

13 DR. BRAIN: Could you educate us a

14 little bit more about the options and where

15 this is going? You know, gets back to the

16 possibility that this would be a separate

17 secondary standard in the W126 metric. Is it

18 possible that this standard would be more

19 stringent than the primary standard, or what? 

20 How do you see the options moving forward? It

21 sounds like you know a lot of interesting

22 data, but where do you see the range of
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1 options being?

2 DR. HUBBELL: I think it's quite

3 early to think about the range of options, but

4 in terms of the proposed standard for the --

5 for the current proposal, I don't have the

6 maps that would show which one is more

7 stringent or less stringent. But obviously,

8 if you are measuring in rural areas, such

9 areas that we're not traditionally covering

10 with, our urban monitoring network. So, it

11 does kind of change the complexion of where

12 you'd be concerned about affects, and what

13 you'd be looking for compliance with.

14 But the range of the proposed

15 standard was seven to 15 ppm hours I think was

16 what the proposal was, and it was on one of

17 our earlier slides. It was the one that was

18 in the introduction to the ISA yesterday had

19 the range that was proposed.

20 Again, it is a different form, so

21 it is not directly comparable in terms of

22 eight-hour versus, say, one hour. It's eight-
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1 hour versus a cumulative weighted seasonal sum

2 of concentrations.

3 DR. BRAIN: And all the

4 consideration of the PDR looms as large or

5 larger here as well?

6 DR. HUBBELL: It does. In fact,

7 if you're thinking about monitoring or

8 attainment in places like national parks,

9 where background becomes much more of an

10 issue, then yes. It becomes potentially a

11 larger issue relative to the urban peak areas,

12 for example.

13 So, yes, those are -- those are

14 all the same exact questions that exist. 

15 DR. FREY: Okay, let's see. I

16 know we had Howard and then Fred, and I can't

17 resist saying that the first draft policy

18 assessment is due out a year from now. So,

19 it's not that far before we'll be addressing

20 these questions.

21 DR. HUBBELL: Yes, but let's wait

22 for that to occur.
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1 DR. FREY: So, I guess Howard was

2 first. 

3 DR. NEUFELD: With response to the

4 previous couple slides earlier, where you were

5 talking about the 11 tree species and their

6 response functions, are you looking into the

7 hourly ozone distribution of those exposures? 

8 Because back then, when a lot of those were

9 done, I know when I did mine, which I'm still

10 trying to get published, we did percents of

11 ambient, because that's what we were told to

12 do.

13 And then someone had the brighter

14 idea that you shouldn't just do percents of

15 ambient. You should cap it so that you don't

16 have unrealistically high concentrations if

17 the ambient goes up to 100, and you're zapping

18 with 200 or 300.

19 So, I'm wondering if you looked at

20 that, and decided did they cap their maximum

21 concentrations since you don't compare a study

22 that capped it with one that didn't cap it? 
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1 Like I think if I get mine

2 published, which I hope to do, we -- you know,

3 it was so long ago that we didn't cap them. 

4 So, you may have a caveat there about that the

5 highest ozone concentrations of those response

6 functions. 

7 DR. SMITH: I'll check with them

8 as far as doing that. We're working with them

9 on exactly what was in those studies, and

10 there are additional species that ORD looked

11 at that the data -- there were some studies

12 that were excluded because they didn't -- the

13 methodology wasn't comparable.

14 And so, there are -- in addition

15 to those 11 species, there are other species

16 that there were studies for, but the study

17 wasn't comparable, and that's something that

18 we -- I'll work with them, and we'll be trying

19 to decide exactly what those studies say to

20 make sure we are using comparable information.

21 DR. NEUFELD: I mean it's hard

22 when you're in a teaching institution, but if
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1 we can get this published, we can probably

2 double the size of your sample method.

3 DR. HUBBELL: That'd be great. 

4 How many more drafts? Two more drafts and --

5 DR. NEUFELD: I need a

6 statistician is what I need.

7 DR. HUBBELL: Okay. 

8 DR. FREY: Fred?

9 DR. MILLER: Following up on Dr.

10 Brain's clarification, question on the PRBs. 

11 Does the amount of modeling support for the

12 health in that are coincide for what's needed

13 for the welfare? Or, do you have to go down

14 separate avenues in the way that you're doing

15 that?

16 DR. HUBBELL: Well, we'll be

17 having to calculate the different index value,

18 but the hope is to use the same GEOS-Chem

19 modeling, which just means an additional

20 calculating eight-hour averages and things

21 like that that match with the health indexes. 

22 We're going to have to be calculating these
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1 cumulated index values, but it will still be

2 based on the hourly data, yes.

3 DR. FREY: Yes, David?

4 DR. CHOCK: One quick question. 

5 Are you going to incorporate the water stress,

6 temperature stress, on the ozone effect?

7 DR. SMITH: I don't -- it'd be

8 great if we could. I don't know. I can't

9 answer positively yes or no on that at this

10 point. It certainly does -- unfortunately

11 dealing with ecosystem of any form that

12 there's so many variables. To account for

13 every variable would be great. In reality,

14 that's going to be somewhat less than easy.

15 DR. HUBBELL: But in all cases, if

16 we've identified one of those issues, we'll

17 certainly treat it qualitatively at the very

18 least, but we are limited by some of the data

19 that's available.

20 DR. FREY: Any other clarifying

21 questions? Seeing none, let's move onto the

22 input from the discussants on -- we had two
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1 groups of topics. One is air quality

2 considerations. The other is eco-effects and

3 ecosystem services. In the air quality group,

4 we have Daniel, Jacob, George Allen, Ted

5 Russell and David Chock. And I know that

6 Daniel is going to be leaving us in a little

7 bit, but do we have enough time that -- please

8 give us your wisdom?

9 DR. JACOB: Well, I already talked

10 this morning on the PRB issue. One question

11 I had was the Europeans are using AOT40

12 metric, that's in vegetation. Is -- it would

13 actually I think make your results more

14 sensitive to the background, right?

15 Okay, all right. I guess bottom

16 line question is to what extent is your choice

17 of metrics for the effect of ozone on

18 vegetation affect the sensitivity to

19 background ozone?

20 DR. HUBBELL: I don't -- we have

21 not investigated that, and I don't know

22 whether -- has ISA looked at that at all,
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1 Jeff? Come on up here.

2 DR. HERRICK: This is Jeff Herrick

3 from NCEA. I think you're asking what kind of

4 metrics we are -- they might be using to look

5 at, and as for background, AOT40 wouldn't --

6 obviously wouldn't consider any hourly

7 concentrations below 40.

8 So, I would think there would be

9 less of a background, but then there's a few

10 peaks in the spring that could -- that could

11 accumulate with that. And with the W126, it's

12 a smooth similarly weighted function. So,

13 there actually would be a little more

14 weighting from that.

15 The data I've seen is the

16 background -- I mean if you look at Al

17 Lefohn's comments, it -- it's still quite

18 small. Still quite small, in fact, because it

19 weights those concentrations very low.

20 So, everything below 60 with the

21 W126 is weighted fairly low.

22 DR. JACOB: Well, that's my whole
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1 point. So, W1s6 wouldn't be too sensitive of

2 a background, but Aot40, which I understand

3 counts linearly any enhancement --

4 DR. HERRICK: Yes, anything above

5 40.

6 DR. JACOB: Yes, well, that would

7 have a huge background sensitivity. Because

8 40 is about the level of a background that

9 would elevate the --

10 DR. HERRICK: And that's one of

11 the reasons that in the last review we decided

12 to use the W126, because it makes more sense,

13 I think intuitively and scientifically, to --

14 that you shouldn't weight the same something

15 like a 45 parts per billion as much as you

16 weight 100 parts per billion.

17 So -- but they're very, very well

18 correlated. So, we looked at all the monitors

19 for the whole country, and we looked at W126

20 and AOT40, and it's pretty much a linear

21 relationship between them. So, they're very

22 similar. But if there's weird things
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1 happening at a certain site, they might

2 deviate.

3 And I think the W126 just does a

4 better job of characterizing the exposure, in

5 my personal opinion. So, I think -- and also,

6 we probably won't be looking at AOT40, because

7 we don't have any concentration response

8 functions for our studies that use AOT40. We

9 have AOT60. We're sort of bound by the work

10 that's already been done in the late '90s with

11 the tree species.

12 So, all we -- the only metrics

13 that we have to work with are W126, SUM06 and

14 AOT60, and some -- and some other things.

15 DR. JACOB: So, what are Europeans

16 basing their AOT40 --

17 DR. HERRICK: They're basing it on

18 European tree species. So, they have European

19 Beech, Norway spruce, things that don't

20 generally grow naturally in the US. And they

21 also have a lot of crop data with AOT40, but

22 it's very similar to W126. You could -- we've
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1 looked into making a transition between the

2 two metrics.

3 DR. JACOB: But I suspect it might

4 be different in terms of sensitivity to the

5 background. 

6 DR. HERRICK: I think that might

7 be true, and I think using W126 would be a

8 better way of looking at the background.

9 DR. NEUFELD: There's also a

10 slight distinction -- if I have this right,

11 the official European usage of AOT40 is only

12 if the radiation level is above a certain

13 point. 

14 Essentially, they're assuming that

15 there's only in effect if the plants have

16 their stomata open. But if plants open their

17 stomata at night, then AOT40 would miss that.

18 DR. FREY: Okay, thank you. 

19 George, the floor is yours.

20 MR. ALLEN: Thanks, Chris. I

21 guess start with the broad comments first. 

22 Daniel and I have had some discussions, and
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1 this actually goes back to the ISA as well. 

2 So, it really covers both processes. So,

3 primary and secondary.

4 As noted before, the last two

5 years '09 and '10, were unusually low years. 

6 And then it occurred to Daniel and I, well,

7 you know GEOS-Chem for this round is going to

8 be '06 through '08, and if you look at at

9 least the northeast, and I think this issue is

10 for most of the eastern US, '06 through '08

11 were relatively normal years 

12 when you take them as a whole. '07 was higher

13 than usual. '08 was lower than usual, and '06

14 was usual.

15 So, there's two things going on

16 here. One, I would be -- it would be nice to

17 sink the GEOS-Chem output with the

18 observational data in a temporal sense. And

19 again, you really don't want to be picking a

20 three-year period where you are clearly going

21 to be underestimating what the normal exposure

22 would've been, be it plants or people.
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1 So, I would strongly encourage

2 both the primary and secondary process to use

3 '06 to '08. Yes, it's not the most recently

4 available data, but it's probably the most

5 relevant in terms of what's going on at this

6 point in time.

7 If you look at the overall trend

8 plots, those years fit in very nicely. And

9 ozone levels have stopped dropping rapidly in

10 most areas. We picked the low-hanging fruit,

11 and I think some of the trends have just about

12 flattened out. Washington Summit is flat for

13 those ten years. That tells a big story in

14 terms of regional ozone.

15 If I were a regulator, I'd be a

16 little concerned, seeing such a flat lack of

17 trend, but actually that's the state's

18 problem. They have to do the SIPs. So, if I

19 were a state SIP person, I'd be worried. 

20 A more general comment, which

21 might be a little heretical, and please feel

22 free to interrupt me if I go off the deep end
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1 here, but I know this process is resource

2 constrained, both primary and secondary. My

3 view of it is that -- two things.

4 The primary is probably more

5 important in terms of protecting public

6 health. Not that welfare is not important. 

7 It is. But if you had to -- if you have

8 resource constraints, then I would encourage,

9 and especially EPA is talking about going from

10 12 to three or four cities to do the urban

11 analysis on.

12 I would encourage resources to be

13 not completely pushed over to the primary, but

14 properly apportioned in a rational manner. 

15 And there's another argument for that. I mean

16 in theory, a type -- a decent protective

17 primary will also have benefits for the

18 welfare standard as well, without any doubt.

19 You reduce the sources. You're

20 reducing the regional, which means you're

21 reducing the rural. So, that's just a

22 thought, a concept. To the extent that
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1 resources are constrained, it might be worth

2 thinking about.

3 Getting back to the -- okay, in

4 the 2010 NPRM, we had upper range of 70 for

5 primary, and a very wide range of seven to 15

6 for the W126. Now, the question is, "Okay,

7 what's controlling?"

8 Well, if you go with 70 for the

9 primary, you have to go much closer to the low

10 end of the secondary, meaning seven. At 15,

11 it does nothing. It's there on paper, but it

12 doesn't change anything. You don't change

13 much of anything in terms of actual welfare

14 exposures until you approach the low end of

15 that range.

16 There's another rationale for

17 maybe moving resources around it, unless

18 there's strong evidence that you would go for

19 a controlling secondary. 

20 All right, that's the big picture

21 stuff. Minor comments on chapter 2. It makes

22 note of class 1 air sheds. In the past, I
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1 don't think that's been notable, other than

2 for regional haze where they've been a big

3 player, but I guess the question is will more

4 emphasis and attention be paid to protecting

5 the class 1 air shed areas? That's one

6 question.

7 The next paragraph talks about

8 portable monitors, and I'm hoping that they're

9 referring to the things with FEM stickers,

10 like the 2B technologies, which is out in

11 actually a very nice package. And so, we have

12 robust data.

13 Remote sensing, I don't know how

14 useful remote sensing data is for ozone. If

15 you're doing total column ozone, you have --

16 the stratosphere kind of messes that up. So,

17 I'm not sure how much value that'll be, but

18 I'm not really an expert in that.

19 And then there's a piece on the

20 section to that one, looking at gradients and

21 elevation. There is some work that may not

22 have been published that I did with the
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1 Appalachian Mountain Club on Mount Washington

2 back in the late '80s, that actually formed

3 the basis for the Korek et al 1993 paper that

4 figures into the primary standard.

5 But we did measurements of the

6 summit, and at the base of Mount Washington,

7 and have a lot of good vertical gradient data,

8 summertime only. But those data do exist, and

9 could be made available if that helps. I

10 believe that's it. Thanks.

11 DR. FREY: Okay. Any follow-up to

12 George's comments?

13 DR. HUBBELL: Let me just mention

14 about the resource issue. While I appreciate

15 the sentiment, and it would be nice if we

16 could do that, unfortunately we have a

17 resource constrain; not only a dollar

18 constrain, but people. People are not 100

19 percent fungible between ecological and

20 health. And so, you can't just switch those

21 back unfortunately.

22 So, our welfare folks will
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1 continue to focus on the ecological things

2 that they're experts in, and we have to kind

3 of work within those constraints. But it'd be

4 nice if we had that ability.

5 DR. HERRICK: As far as the

6 portable ozone monitors, those refer to 2B

7 technology monitors.

8 DR. HUBBELL: That's great. Good.

9 DR. FREY: Fred? Oh, I'm sorry.

10 DR. JACOB: Could you respond to

11 the comment about using 2006 versus 2008 --

12 DR. HUBBELL: Yes. You know, it's

13 an interesting point to be made about trends

14 versus deviations from trends, and that's what

15 -- the one thing that I was a little concerned

16 about when I saw your original comment with

17 the plot is that there's clearly been a

18 downward trend, and I don't know that anybody

19 is -- you know, looked to see whether that --

20 that consistency of the flattening and whether

21 or not we should assume that we're on a new

22 trend that's -- or a different part of a
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1 curve.

2 But it makes me a little bit

3 nervous to simply say, "We'll only use 2006 to

4 2008." I think using a longer period maybe

5 makes some sense, or thinking about it, or

6 trying to detrend the data so we can get an

7 idea of what actually would be the -- the new

8 balance equilibrium conditions that we would

9 be returning to.

10 There is some of that lowering

11 that may be permanent. You know, shut downs

12 or other things may be permanent. We don't

13 know for sure. But I'm just a little cautious

14 about saying, "Well, it was a good year in

15 terms of low ozone, and we have to assume

16 that it's going to go back to the old."

17 So, I think we need to do some

18 evaluation to determine how to -- you know,

19 obviously a met adjusting can help with some

20 of this, but at the met adjusted data, but

21 whether or not we can adjust for economic

22 trends that are either permanent or not
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1 permanent, I don't know. But certainly

2 looking at a broader average would make some

3 sense, perhaps without maybe just saying,

4 "Well, I'm only going to look at this 2006 to

5 2008 period."

6 DR. JACOB: What about this

7 concern that was expressed this morning about

8 making sure that the background estimates and

9 --

10 DR. HUBBELL: Well, that's clearly

11 the reason to use 2006 to 2008. And the

12 question is can we do some type of an

13 adjustment, and then maintain that adjustment

14 in looking at the additional years? I don't

15 have an answer for that, but I definitely

16 think it's important to try to at least match

17 the data that we do have. But how we extend

18 that to additional years, I need -- we need to

19 think about it.

20 MR. ALLEN: And I would strongly

21 encourage that that linkage be kept in mind,

22 because I think it's very important. And in
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1 terms of '09, I mean if you look at the Summit

2 Mount Washington smooth data in my primary ISA

3 comments, '09 is no different than the

4 previous four years.

5 So, at that level, both vertically

6 and spatially regional, it was a normal year. 

7 But at the ground, it wasn't. So, in terms of

8 source and major trends, if you look -- and if

9 you look at a few other sites like that, you

10 may find that there really isn't a lot of

11 trending when you go back to that larger

12 scale, which would support using '06 to '08.

13 I understand the concerns, and --

14 but I am also very -- I can't emphasize too

15 much the trying to link it with GEOS-Chem date

16 period. I think that's extremely important. 

17 DR. FREY: It was Fred and then

18 Howard.

19 DR. NEUFELD: If I could make a

20 real quick comment?

21 DR. FREY: Go ahead.

22 DR. NEUFELD: -- 20 year trend,
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1 and covered many of the same national parks

2 and so on, and just chock full of data.

3 DR. MILLER: I wanted to go to

4 what George was talking about on relative

5 prioritization. I understand people are

6 interchangeable, and I agree.

7 But if they were dollars that had

8 to go outside of EPA, I would actually put a

9 higher priority on the welfare than I would

10 the health, and the reason I say that is it's

11 extremely unlikely that anything that's done

12 for the health is going to change the range

13 compared to what happened for the last round

14 of the 60 to 70, and you have those analyses

15 in place.

16 And so, you're going to be doing

17 some sensitivity, and updating that but

18 getting this welfare, the CT thing down, and

19 making it locked, and realizing you need a

20 different primary compared to secondary, if

21 you had to, getting that in place is going to

22 be more important for the welfare at this
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1 point.

2 So, I actually say that the health

3 is very important, but it's probably the

4 things you're going to do aren't going to

5 change the story compared to the previous

6 revision, whereas it could have a big impact

7 relative to the welfare.

8 DR. HUBBELL: And some of this

9 depends on the results of the new

10 reconsideration package. And if we get a

11 secondary standard, then --

12 DR. MILLER: Well, my crystal ball

13 says -- in fact, I'll be willing to put out

14 all the money in my wallet on the table, and

15 tell you that it will be implemented. It's

16 going to be 0.070, and it's going to be the

17 CT. Anybody want to bet against me. But we

18 don't have to wait long to find out. I never

19 keep more than $1,000.00. No, I think there's

20 maybe $60 in here.

21 DR. FREY: Okay. Ted, you're up

22 next.
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1 DR. RUSSELL: First, the comments

2 from this morning still hold in terms of how

3 you use GEOS-Chem in determining the PRB. I

4 think that however you choose to debias it,

5 you just have to really be careful in how you

6 justify it.

7 I'm a little bit -- that concern

8 gets a little bit heightened now that you're

9 talking about possibly using CMAC to help

10 develop the ozone surfaces. Not that that's

11 necessarily wrong, but that just adds a new

12 uncertainty.

13 So, I'm not saying don't do it;

14 just make sure you justify it, and provide

15 what sort of uncertainty that implies. And it

16 could be that between that and VNA, you're

17 talking about one or two ppb everywhere, which

18 would be a good estimate of what level of

19 uncertainty you're really talking about.

20 So, again, just specify that. Do

21 the analysis, and show that it's a reasonable

22 thing to do. And in the end, provide the
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1 uncertainties for the whole thing. 

2 I'm not sure, but I think this is

3 something you need to do is really look at how

4 you adjust the values below the PRB again. I

5 mean if you're looking at the W126, probably

6 not a big thing. But you just want to make

7 sure that you've looked at that.

8 I think you need to get back to

9 NCEA. I'm sure you're getting back all the

10 time, and when I start reading the -- these

11 documents, there's some more work that needs

12 to be done in the ISA as to their -- the

13 support for your analysis, in particular what

14 sort of model evaluations need to be done in

15 terms of 126, how well it reproduces 126,

16 W126, and what the trends have been in the

17 W126 over the years, and how that might be --

18 how that also will look in the future.

19 So, that again is another issue is

20 providing an analysis of what's going to

21 happen to the background at 126 in the future. 

22 And with that, I think those -- oh, the other
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1 thing is when you make a choice as to which

2 national parks you might use, some overlap

3 with what was done in the NOx SOx secondary

4 would be good, as much as possible. Just to

5 be really good for the next time around on the

6 NOx SOx as well, to really have certain areas

7 really well characterized and analyzed.

8 DR. FREY: Ted, you're not aiming

9 for a NOx SOx ozone secondary standard are

10 you?

11 DR. RUSSELL: No, no. Certainly

12 not after trying even two. 

13 DR. HUBBELL: You thought that the

14 ANC based standard was complicated, right?

15 DR. FREY: Okay, thank you, Ted. 

16 David Chock?

17 DR. CHOCK: I don't really have

18 any comments. 

19 DR. FREY: Anyone on the phone

20 have comments on air quality considerations? 

21 I guess "anyone" meaning Kathy. 

22 DR. WEATHERS: Nothing additional.
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1 DR. FREY: Okay, anyone else in

2 the room have a comment? All right, well, if

3 not, then let's proceed to the ecological

4 effects. Oh, I'm sorry, Peter.

5 DR. WOODBURY: Yes, I didn't

6 really separate out my comments as to air

7 quality versus others, but I did have one that

8 -- there was discussion that consistency with

9 the health risk assessment is desirable, and

10 that's certainly true. But -- and I think it

11 has come up over the discussion today and

12 yesterday. There's a number of reasons why

13 exposure modeling should differ between these

14 two.

15 So, obviously with a different

16 method applies a different approach. And

17 again, we've already discussed places where

18 vegetation is occurring, a concern about some

19 rural areas with little monitoring. 

20 I guess just a comment perhaps is:

21 we do have monitors in many rural areas, and

22 I think it's important not to overstate the
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1 uncertainty about ozone exposures in rural

2 areas. For many of these areas, especially

3 the low elevation ones, I think they can be

4 characterized fairly well.

5 I should say low elevation areas

6 in the eastern half of the country. 

7 Obviously, there are challenges with the

8 mountainous areas, particularly in the West. 

9 I'll stop there.

10 DR. FREY: Okay, thank you. So,

11 yes, we'll move onto ecological effects and

12 ecosystem services, and, I guess, Peter,

13 would you like to continue with your ecosystem

14 comments?

15 DR. WOODBURY: Sure. Again, I

16 think this has been covered already, and this

17 is still I guess on the exposure side, but the

18 whole issue of policy-relevant background, how

19 it's going to be estimated -- and again, these

20 points have come up through the discussion. 

21 I'm not going to repeat them, but just please

22 go back to the discussion yesterday, anything
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1 related to this issue, including the point

2 about the challenges that models such as GEOS3 Chem currently have with estimating

4 preindustrial background.

5 So, again, that's an uncertainty

6 for policy-relevant background now, and

7 relevant to this topic as well. 

8 I'm skipping through some things

9 that we've already discussed here, so bear

10 with me. It's a good cause. Just try not to

11 be too repetitive. 

12 It's certainly useful to use the

13 FIA data, and just to comment on vegetation

14 cover or vegetation frequency and occurrence

15 data: there's a lot of data in FIA on that,

16 not just for tree species. So, pay attention

17 to that as a source of vegetation data.

18 And again, this came up yesterday,

19 but we should be thinking about impact on

20 sensitive species and sensitive populations

21 within species, and those -- the sensitive

22 populations just can't be mapped. Some of
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1 them may be gone. We may never be able to map

2 those.

3 So just some acknowledgment of

4 that issue. As far as choosing sites, you may

5 want to look at Acadia National Park. I don't

6 know how it stacks up in terms of exposure

7 levels, but there is a database of -- of both

8 surveys of natural vegetation in the park and

9 open-top chamber experiments located in the

10 park from a number of years ago that have been

11 published. So, there are site-specific data

12 there that might be useful.

13 For the figure on ecosystem 

14 services, it's mentioned in there that a more

15 comprehensive list is needed, and I agree with

16 that. I think it's a great idea to try to be

17 more comprehensive in that list, even if

18 everything can't be addressed quantitatively. 

19 So, in particular, pay attention to chapter 10

20 in the ISA. Some of those claimant related

21 issues.

22 I would encourage the staff to not
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1 get overly focused on -- at the regional scale

2 for forests looking at biomass effects, and

3 similarly for urban areas. I'm not sure that

4 tree biomass increment is going to be the most

5 sensitive -- well, I don't think that that

6 will be the most sensitive nor the most

7 important ecological impact in urban areas or

8 in most forests, especially mixed species

9 forests.

10 So I think, again, this discussion

11 came up with the ISA, mixtures of sensitive

12 and insensitive species. We should be looking

13 for almost a more dramatic effect on the

14 ozone-sensitive species. Kind of an enhanced

15 negative competitive effect on them. We might

16 see no effect at all on total biomass

17 production in the forest.

18 To the extent that those sensitive

19 species have particular value, that could be

20 quite important. And again, this has come up

21 before, but we don't have data. We don't have

22 data on the ozone sensitivity of most plant
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1 species.

2 I guess this is -- I'm going to be

3 a little bit long-winded on the next point

4 because I feel very strongly about it. For

5 economic impacts, some of the literature on

6 ozone -- on economic impacts of ozone on

7 vegetation has looked at kind of a national

8 effect. Say, what's the effect on a sensitive

9 species such as ozone? You know, what is the

10 effect on a total soybean production in the

11 country? What's the effect on the return to

12 farmers? Kind of these rather gross economic

13 impacts.

14 I am not in favor of giving those

15 very much weight. I think it's very important

16 to look at ozone impacts on a more local

17 scale. So, in an area with ozone, if Farmer

18 X in an area with higher ozone exposure has a

19 decreased yield, that is an economic impact on

20 that farmer.

21 And just because some other farmer

22 in a low ozone area in the US, or in another
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1 country, these are global commodities, just

2 because they got a higher income because they

3 had less ozone and they got a higher relative

4 yield, I don't think those costs and benefits

5 should cancel each other out.

6 So, when you kind of look at the

7 larger national impacts, you're looking at a

8 net economic impact. And I think that's the

9 wrong way to look at it. I think it's an

10 important effect if you're shifting income

11 from some farmers to others because of ozone. 

12 So, I think there are ways to

13 still quantify those impacts, but it needs to

14 be kind of disaggregated. Does that make

15 sense?

16 DR. HUBBELL: It makes sense. 

17 There's some issues with that, but it makes

18 sense.

19 DR. WOODBURY: Well, I think in

20 fact it can be done in some fairly simple but

21 informative ways, without -- in addition to

22 the, say, more equilibrium market modeling
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1 approaches.

2 And on a similar vein, maybe it

3 wouldn't cost us much to import more soybeans

4 from another country, but that also -- that's

5 an impact that should be looked at. It

6 shouldn't just be kind of swept into the grand

7 scheme of, "It only costs us 0.1 cents more

8 for each block of tofu." 

9 I guess for the FASOM model, I

10 understand your motivation that you'd like to

11 model effects on forest economics, the

12 forestry sector. I would question whether the

13 FASOM model is really capable of modeling

14 ozone impacts on forest production. Is it

15 capturing the important processes, such as

16 competition between sensitive and less

17 sensitive species? I really doubt that it is.

18 DR. HUBBELL: It actually doesn't

19 at all.

20 DR. WOODBURY: If you would plug

21 in a very simplistic kind of growth decrement

22 into FASOM, and I guess I would question with
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1 accrued parameterization of a model that may

2 not be representing the key processes, how

3 much information do you get out the other end? 

4 I don't have an answer for that, but you can

5 hear that I have serious questions about how

6 much value you'll get. 

7 DR. HUBBELL: Well, the only thing

8 on that is that we -- and this -- it's an

9 important question about how to deal with

10 forest yield changes, and we have -- in the

11 past we've really struggled with this in terms

12 of you have these individual biomass loss

13 functions, and then we've tried to follow

14 those through. 

15 We played with using the ZELIG

16 model, which is stand-alone model, to try to

17 get those interactions. It was very difficult

18 to try to apply because there was so few

19 species that we actually had data on.

20 So there were some real questions

21 about how to play this out through this, and

22 some of the stuff that Travis mentioned about
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1 doing more mapping of where the sensitive

2 species are and things like that, was an

3 attempt to give a flavor of the information

4 without trying to take it all away to model it

5 through the economic models.

6 I mean, ideally, if we were able

7 to have a broader set of species response

8 functions, we could get the ZELIG modeling and

9 the results of those models at the stand level

10 would be fed into FASOM, and it would be

11 output that way. But if they said we could

12 actually provide that, then FASOM is a very

13 good tool because it allows you to look at

14 competition between agricultural and forest

15 uses of land, and that's a benefit to do that.

16 It has been used. What it was

17 really developed for and used for has been

18 climate programs, looking at sequestration

19 things. So, it'd be great it we could do more

20 with it, and I think this is one of those

21 things where ideally we'd like to be able to

22 push forward on this. This is a gap, an area
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1 that needs a lot more development.

2 We tried several years ago to

3 decide whether we could actually expand the

4 number of species that we cover by using some

5 homology mapping, using some various different

6 approaches to try to say, "Well, what's

7 driving that concentration response

8 relationship?" It didn't do very well. We

9 haven't been able to identify the factors that

10 determine ozone sensitivity based on the

11 available data because it's so sparse. 

12 So, it's a real area that is very

13 limited, but yet is identified as one of, 

14 potentially, the bigger impacts, and you've

15 seen some of the studies in China, where they

16 -- they really did try to do these types of

17 estimates of yield losses and its impacts on

18 timber production, but also carbon

19 sequestration. And they've been enormously

20 impacted by ozone, but we can't do something

21 similar here because we don't have the data,

22 which is unfortunate.
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1 DR. WOODBURY: Well, again, as

2 you're aware, the exposure response functions

3 for tree species are available for seedlings

4 only. That's another important limitation. 

5 So you have a couple of scaling uncertainty

6 issues, and that's quite a large one, whether

7 mature trees in forests are more sensitive or

8 less sensitive than seedlings. We don't have

9 a clear picture of that.

10 I guess I would just encourage you

11 again to think about -- focus on some of the

12 species where there are adequate data to

13 suggest that there are stand-level impacts. 

14 So, it may be on monocultures of sensitive

15 tree species.

16 Perhaps focusing on those might be

17 -- might give you a more robust result,

18 although obviously only for a subset. But I

19 guess I just agree with the issue you brought

20 up, that we don't have data to parameterize a

21 model like ZELIG. That doesn't mean that it's

22 going to be any easier to do in a more
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1 simplistic model. That's not -- that's just

2 a non sequitur to me.

3 DR. HUBBELL: Your point is about

4 the total change in biomass versus its

5 apportioning between species. That's a really

6 important issue, and unfortunately not one

7 that we can do much about at this point. 

8 DR. WOODBURY: Again, on the

9 forestry side, I would encourage you to look

10 at, if there's a likelihood of losses of -- of

11 forest increment production, that's an

12 important impact, whether or not there's an

13 impact at the national and global sawlog

14 market level.

15 DR. HUBBELL: One other response

16 to your question about apportioning to

17 individual farms versus the overall welfare

18 impacts. One caution -- the reason why I

19 exercise caution in that is there are two

20 things that go on. One is a yield effect and

21 the second is a price effect. What happens

22 when you have globally lower yields is that
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1 the prices go up.

2 And so, everybody benefits from

3 that, in terms of a price per unit. So, one

4 thing we've heard from farmers, not

5 necessarily that I agree that they're correct

6 in their interpretation is they don't

7 necessarily want their yields increased as a

8 global sense. They want their individual

9 yields increased so they can get more benefit,

10 and that's what the -- the relative yield is

11 important for who gets the benefit, but

12 everybody benefits from higher prices.

13 And so, there's -- you have to be

14 sure in terms of thinking about looking at

15 yield versus the value of that yield. In many

16 ways, I'd rather just look at the yields, and

17 say there's a yield impact, but once you get

18 into putting in into dollars, you really do

19 have to take into account the market

20 interactions. Otherwise, it gets a little

21 shaky in terms of interpretation. But yields

22 you certainly can look at how gets yield
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1 increases and yield losses.

2 DR. FREY: Daniel had a --

3 DR. JACOB: Is it just farmers'

4 dollars that matters? 

5 DR. HUBBELL: Well, this is the

6 other half of it. And when you do the AGSIM

7 modeling for example, it calculates what is

8 called producer surplus and consumer surplus,

9 which is the excess amount of value that each

10 group gets. And what you're looking at really

11 is the net welfare change, and that's what I'm

12 sure you don't like because --

13 DR. WOODBURY: That's exactly what

14 I don't like. That's right.

15 DR. HUBBELL: But you're right;

16 the consumers benefit when there's higher

17 yields. They do because the prices go down.

18 DR. WOODBURY: So, with this kind

19 of model, if we only have one soybean, it

20 will be extremely valuable, and it won't, you

21 know, doesn't matter.

22 DR. GRANTZ: There is the other
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1 issue that if yields go down, you're using

2 more and more marginal land to produce enough

3 food to feed people. So, there are much

4 larger scale issues here.

5 DR. HUBBELL: There are very large

6 scale issues.

7 DR. GRANTZ: Let me just finish. 

8 And it also depends an awful lot on the crops

9 that you are discussing. For example, in

10 parts of California, we grow 100 percent of

11 the country's supply of a lot of different

12 things. So, it makes a big different whether

13 it's that or whether it's a commodity that's

14 grown everywhere.

15 DR. HUBBELL: Yes.

16 DR. GRANTZ: So, I tend to think

17 the economic modeling makes an awful lot of

18 sense because it's actually what people will

19 pay attention to, and it provides a uniform

20 currency, so to speak, across all these

21 climates.

22 DR. HUBBELL: Thank you.
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1 DR. WOODBURY: So, I had similar

2 questions about the I-tree model. I think I'm

3 familiar with -- the progenitor to this was

4 called U4. I believe that's the same -- so,

5 again, I would say what are the -- what are

6 the sensitive impacts in urban areas that

7 you're looking at and does this model really

8 allow you to get at that in a way where you're

9 really getting a robust estimate out the other

10 end?

11 So, for example, interactions with

12 temperature and moisture status will be

13 critical, I think, for ozone impacts on

14 vegetation wherever it occurs, including urban

15 areas. I'm sure this model is not accounting

16 for any of those interactions. 

17 So we've had some sort of

18 discussion of sensitivity analysis,

19 uncertainty analysis. I guess I would hope

20 that the approach for this upcoming analysis

21 will -- will sort of take into account the

22 discussion we've already had on the human
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1 health side. Some of these same issues.

2 Quantitative uncertainty analysis

3 is, I think, going to be more helpful than

4 sensitivity analysis per se, if the definition

5 is that sensitivity analysis is investigating

6 the sensitivity of a model to changes in the

7 input without any regard for the likelihood of

8 those changes.

9 So just an encouragement to again

10 think about quantitative uncertainty analysis

11 for the factors that are important, and pay

12 equal attention to potential sources of bias

13 and interactions among variable. I think

14 those, again, can have a lot of impact on the

15 outcome. Whether variables are correlated or

16 not and do we understand that, is just as

17 important as how many variables get treated as

18 probabilistic values.

19 So I think some of the sources of

20 uncertainty, you've got a list there, and

21 again, I just encourage you to look back

22 through the discussion of today and yesterday
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1 at some other sources of uncertainty. That's

2 it. Thanks.

3 DR. FREY: Okay, thank you. Let's

4 see. Next I guess David Grantz. The floor is

5 yours.

6 DR. GRANTZ: I'll try hard not to

7 repeat things we've been hammering on. The

8 big aspect of any welfare approach is going to

9 come back to the NCLAN and the tree growth

10 data because that's what we know, and

11 especially for the NCLAN crop data. That's

12 where we can actually do some real economic

13 modeling, and it's been done in the past and

14 probably will be done again.

15 So, I think it's very appropriate,

16 as we said yesterday, for the ISO study, to

17 use the NCLAN data, the CR functions that we

18 developed then. But again with the caveat

19 that I mentioned yesterday, that some of the

20 varieties that are available now are less

21 sensitive. And we discussed whether there's

22 actually published data on that. But
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1 anecdotally they are less sensitive than they

2 were in the NCLAN days.

3 So, that's important and at least

4 should be considered during the sensitivity

5 type analyses. Going back to your Figure 1 or

6 2, visibility seemed -- not visibility, sorry. 

7 Visible injury seems to have an awfully big

8 role in your model. It's in the second square

9 and it propagates everywhere.

10 I would be really careful with

11 visible injury. It doesn't correlate with

12 anything in terms of other measures of damage. 

13 What it does correlate beautifully with is

14 aesthetic value. And so as you have these

15 willingness to pay studies in national parks

16 and elsewhere, and other types of recreational

17 uses, it's very important, and I would really

18 run with that if you can, to the extent that

19 you can.

20 I'd be very careful about using

21 that as a surrogate, and I kind of see that

22 slipping in here. It's not a very good
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1 surrogate for much else, actually.

2 Oh, let's see here. Yes, then we

3 get back to the thing I beat on yesterday with

4 stomatal conductance. I think, first of all,

5 as we discussed yesterday, the ISA is going to

6 have to go back. The author is going to have

7 to go back and reconsider really what we know

8 about the effective ozone on stomatal

9 conductance, whether it's up, whether it's

10 down, whether that's species or condition

11 sensitive. But I don't think you better take

12 the stream flow data from Sandy McLaughlin's

13 study and run with it, and I think that's what

14 your diagram indicates.

15 I think that would be -- would

16 open you to tremendous criticism. It's not

17 going to be justifiable, I think. 

18 And then the last thing I wanted

19 to say simply is that -- and as you're well

20 aware, many of these things are not going to

21 be able to be monetized very easily. But

22 don't let that discourage you. I think we
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1 really have to make a stab at how things might

2 be, and in my written comments, I use the

3 example of bees.

4 We don't really know that ozone --

5 you know, eats up pheromones or whatever, so

6 that bees can't track, but it might. And if

7 it did, that could be monetized in terms of

8 pollination services, which are a fee for

9 service.

10 So, there are little tricks like

11 that that you might be able to use, but in

12 general, aside from some of the NCLAN data,

13 you're going to have a very hard time putting

14 dollars on this. But I encourage you to take

15 the first step to do that.

16 DR. HUBBELL: If I might ask a

17 question about the declining sensitivity. You

18 said that's not published yet or it is

19 published?

20 DR. GRANTZ: Well, we were talking

21 with Jeff about that yesterday. It's sort of

22 known. People know that if you have ozone-
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1 sensitive cultivar, you don't grow it as the

2 ozone goes up. So, I have my own lab data on

3 various cotton varieties in California, and

4 the new ones are less sensitive than the old

5 ones, but I don't know that that's in the

6 published literature. It's not from us.

7 DR. HUBBELL: One question I have

8 about that, just because this is something

9 that we've talked about for several years now,

10 is that I would expect that was certainly true

11 up until the introduction of the genetically

12 modified varieties, but for the GMOs, unless

13 they've dramatically changed the way they're

14 doing this, which they may have, is that they

15 had a much more limited set of varietals that

16 were regional-specific varietals at first

17 because they're producing these lines.

18 It used to be farmers would save

19 their seed, and they would save a fraction,

20 and they would develop their own varieties

21 based off of the hybrids that they had, and so

22 forth. But that wasn't occurring, at least in
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1 the first six or seven years of the

2 introduction of the GM crops.

3 And I'm wondering whether that has

4 bred out the ozone tolerance that you're not

5 getting the same tolerance since you're

6 stacking for different traits.

7 DR. GRANTZ: Well, that will

8 depend on the baseline variety into which

9 they're putting these traits. Remember that

10 NCLAN was done in the '70's.

11 DR. HUBBELL: Right. And overall,

12 if you think that overall nationwide, you've

13 got less -- less ozone sensitive, then that

14 would make some sense. If they were -- you're

15 right. Based on the seed --

16 DR. GRANTZ: Well, it's anecdotal. 

17 I can't point to a published paper.

18 DR. HUBBELL: Okay.

19 DR. GRANTZ: Although I will look

20 into that. Maybe there is some data. But

21 there's a lot of anecdotes of varieties that

22 were just dropped from production. There's a
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1 famous potato variety that John Skelly always

2 talked about. 

3 DR. HUBBELL: And I just don't

4 know which ones they started with.

5 DR. GRANTZ: So, I can tell you

6 that the original Pima cotton varieties that

7 came into California from Arizona were

8 selected without ozone, and were extremely

9 ozone sensitive. Since then, they've selected

10 ozone varieties from that parental stock in

11 California, and it's much more ozone

12 resistant.

13 DR. HUBBELL: Are those the ones

14 they're using to put BT in for the -- the --

15 DR. GRANTZ: To some extent, some

16 of the PhytoGen lines, yes. 

17 DR. HUBBELL: Okay, all right. I

18 would be really interested to see if they --

19 if there's actually been publications on that. 

20 We would love to --

21 DR. GRANTZ: Yes, that's a

22 problem. I'm not sure that there has been. 
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1 For one thing, because nobody's doing ozone

2 studies in crops like that anymore. There's

3 no funding.

4 DR. HUBBELL: Right. But at least

5 if we could figure out -- I guess if we could

6 figure out which varieties they ended up

7 putting the genes into for the -- for the --

8 because you know for soybeans, the last time

9 I heard, it was almost an 80 percent or more

10 of the crop was being planted to the Roundup11 ready soybeans, and for cotton, it wasn't

12 nearly as much. But for certain parts of the

13 country, it's a lot.

14 DR. GRANTZ: For soybeans,

15 apparently, there hasn't been a real change in

16 sensitivity.

17 DR. HUBBELL: Yes.

18 DR. GRANTZ: But in cotton, I

19 believe there is.

20 DR. HUBBELL: All right.

21 DR. GRANTZ: Thank you.

22 DR. FREY: Howard?
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1 DR. NEUFELD: Thank you. I'll try

2 to hit on what hasn't been hit on so far. I

3 have a question about the model, the FASOM,

4 and the other models you're using. And I

5 threw in here -- and I'm not a modeler, so

6 this may be useless. But Huang Chen at Auburn

7 has this model DLEM, Dynamic Land Ecosystem

8 Model.

9 So, he's been looking at using

10 that to estimate, say, ozone impacts on

11 forests in China, on carbon storage and growth

12 and productivity, Smoky Mountains also. I

13 understand its physiological component uses

14 PNEC, but it seems to me that it might be

15 adaptable. It might be able to -- you stick

16 TREGRO instead, or something like that. But

17 anyway, I suggest you look into that model,

18 because it's been published a lot in recent

19 years.

20 We had a paper just came out on

21 China few weeks ago. It looks like a really

22 good model. I'm trying to remember back to my
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1 forestry days, but foresters would go out and

2 measure growth and so on at their established

3 plots and they always have a certain error

4 associated with that growth, and it's fairly

5 low on a yearly basis. 

6 So I'm wondering about signal to

7 noise ratio here. You know, how do you

8 separate out just the normal variation from a

9 signal due to ozone? Because you may, over 70

10 years, you might see a significant impact on

11 the growth of the tree, but on any particular

12 year, how would you distinguish the noise from

13 the signal? That's a difficult thing to

14 reconcile.

15 I'd argue as a botanist that there

16 might very well be a threshold, and Dave and

17 I were talking ozone. They might even like a

18 little ozone. It may stimulate the

19 antioxidant defenses against pathogens and

20 other things. May even then predispose them

21 to be less sensitive to ozone. 

22 Something to consider; I talked to
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1 Henry Lee about this, where some of the NCLAN

2 studies showed an increase in ozone at the

3 lowest level of ozone exposure, and then it

4 went back down.

5 DR. HUBBELL: An increase in?

6 DR. NEUFELD: In yield or biomass. 

7 And -- but Henry said at the time when -- when

8 -- if those studies were repeated, about half

9 the time that disappeared. So, it's not clear

10 if that's real or it was just an artifact of

11 maybe that chamber happened to be in a funny

12 position in the field. Things like that.

13 I think I'm a little leery about -

14 - and there's no alternative, so you just have

15 to deal with it, but the fact that Peter

16 brought up the idea we just have seedlings to

17 work with to develop the impacts on adult

18 trees.

19 There is that one study Art has,

20 looking at growth rings of adult tulip poplar

21 in the Smokies and black cherry. But I would

22 think that seedlings' data may overestimate
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1 the actual mature tree response for a variety

2 of reasons.

3 The biggest one being the

4 depletion of ozone through the canopy so that

5 where you expose a seedling, every single leaf

6 gets the high ozone, but in a forest canopy,

7 only the outer leaves are getting that ozone. 

8 Then it's depleted down through the canopy so

9 that the tree is not seeing the profile that

10 the monitor is telling you.

11 And also, I would just emphasize

12 that the only study I know of in the

13 literature showing the adult tree more

14 sensitive than the seedling is the one on the

15 red oaks by Samuelson and Hanson. I don't

16 know of any other studies, so I would be

17 careful about generalizing that to all three

18 species. 

19 I'm going to be a little heretical

20 here. I worked in the national parks, you

21 know, and we were right on the main trail at

22 Clingman's Dome. Thousands of people would go
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1 by and look at us measuring things on plants,

2 and think we were crazy, and what were we

3 doing and stuff. 

4 I don't think a single person,

5 unless they were -- the only person who ever

6 knew what we were doing was Lyle Krieger, who

7 40 years ago was working on ozone, and he just

8 happened to be on vacation. But I would

9 guarantee, I would take the money in your

10 wallet and bet that not a single --

11 DR. MILLER: Sixty-two dollars.

12 DR. NEUFELD: Sixty-two dollars. 

13 I'll be $62.00 not a single person you asked

14 walking on the trail to Clingman's Dome would

15 even A, know what foliar injury is to ozone,

16 or 2, would care, or would even ever see it.

17 Now, if you showed them a healthy

18 leaf and an injured leaf, and asked them which

19 they're prefer, they would tell you. But

20 anyone walking in the park is there to look at

21 the views. They're not going to see foliar

22 injury. And on adult trees, it's 150 feet up
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1 in the air. I mean, Art had to hire tree

2 climbers to grab the leaves and drop them down

3 so they could assess the ozone injury.

4 So I'd be very careful about the

5 aesthetic impact. I mean to me, essentially

6 it is zero because people don't see it. 

7 DR. HUBBELL: Is that true, do you

8 think, in all seasons, all places? Or places

9 that have leaf viewing as a primary activity,

10 would it have more impact in those areas?

11 DR. NEUFELD: Most people don't

12 look at leaves. They would look at flowers,

13 and even if the plant has foliar injury,

14 they're going to --

15 DR. HUBBELL: Like in the fall?

16 DR. NEUFELD: In the fall, ozone

17 injury becomes masked by fall leaf color. And

18 so you can't tell. In fact, that's why we

19 don't do surveys in the fall after about the

20 end of August, because then you can't tell if

21 that's natural leaf senescence due to the

22 fall, or whether it's actually ozone injury.
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1 So I just think that the public

2 doesn't notice. I echo Dave's thing about

3 dealing realistically with the ozone

4 responses. I think that's important. 

5 Ollinger's model assumes a linear decline, but

6 there's no model I know of that includes

7 sluggishness or I would say non8 responsiveness, which I think it important. 

9 Let me see if I have anything else

10 here that I -- oh, I don't know how you can

11 handle it, but I was thinking, "Okay, if

12 you're projecting what the impacts of ozone

13 are, CO2 is going up two ppm a year. We know

14 it ameliorates the ozone effects. 

15 I don't know of any studies that

16 are looking at the tertiary interactions with

17 temperature. There are some data on

18 precipitation effects. You could use the

19 Palmer drought severity index if you're trying

20 to get an idea of what that's doing to the

21 responsiveness. It's going to mute the

22 response to ozone.
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1 So, on a large scale, you could

2 maybe get at least a handle qualitatively on

3 what you might expect in those kinds of years. 

4 I'm not sure what you mean by the percent of

5 trails affected by ozone injury. I think

6 that's where you're trying to get this

7 aesthetic impact, but I'm not sure that's a

8 useful way to go about it.

9 And related to crops, there are

10 some papers now coming out showing that

11 because of climate change, farmers are

12 extending their growing season, planting

13 earlier, going farther in the fall. So I

14 don't know if you're accounting for that in

15 the models. I don't know if that increases

16 yield, or how that affects yield.

17 And those are most of my comments. 

18 Otherwise, I thought this was a -- it's an

19 ambitious plan. So -- but I thought it was

20 well done.

21 DR. GRANTZ: Can I make a couple

22 of quick comments?
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1 DR. FREY: Yes, sure. Go ahead,

2 David.

3 DR. GRANTZ: Just related to

4 things that Howie said, I agree with almost

5 everything Howie said, but I think the

6 aesthetic aspect is perhaps more important

7 than, for example, Sequoia Kings Canyon, where

8 we see leaves retained for two years instead

9 of six years, things like that.

10 And so, when you look up, which

11 everybody does, walking in the pine forest or

12 a redwood forest, is a big difference. Plus,

13 we're seeing browning, leaf browning for a

14 number of reasons, some of which may be

15 related to ozone.

16 The other is this important point

17 of gradients of ozone through canopies. It is

18 true there's a substantial depletion of ozone

19 as you go vertically through a canopy, and

20 we've shown this even in a cotton canopy,

21 which is only a meter tall.

22 But it is also important to
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1 remember that light declines even faster. So,

2 the photosynthesis is weighted on the outside

3 where the ozone is. So the effect in a

4 practical sense is possibly not as big as

5 Howie implied.

6 DR. FREY: Okay, Kathy, are you

7 still with us on the phone?

8 DR. WEATHERS: Yes, I am. The

9 challenge of being the caboose is that

10 everyone has said the kinds of -- made the

11 kinds of points I like to make. So I'll just

12 underscore very quickly three of the

13 overarching points. 

14 DR. FREY: Okay. 

15 DR. WEATHERS: So, again,

16 underscoring what Ted had to say about being

17 very clear about debiasing the models, and

18 where the sensitivities are I think is also

19 something I'd like to see. Said that before

20 as well.

21 And taking that one step further,

22 most of this analysis will be about linking
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1 models. And that's a huge challenge and will

2 be a challenge in this analysis. And so

3 reviewing the process, so kind of taking the

4 debiasing and sensitivity analyses steps

5 further and applying them to the model

6 linkages, I think, will be incredibly

7 important as well.

8 So, it's not always clear that the

9 spatial or the temporal or just the data

10 output from one model, how it interfaces with

11 running another model. The -- the ozone

12 surface modeling is a great example of that.

13 So, linking models and the process

14 by which models will be linked, I think, needs

15 to be addressed. I agree with Peter as well

16 about species effects and lack of data, and

17 also about focusing on ecosystems services.

18 I think that biomass, maybe with

19 the exception of ag systems, or water,

20 especially at the watershed scale, looking at

21 the effects of ozone is going to be very, very

22 difficult. So I think it's worth
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1 reconsidering some parts of the ecosystems

2 services that you're looking to make links to,

3 even indirect links.

4 And I think those are the main

5 points that I'd like to make. So I agree with

6 David and Howard and Peter and Ted's comments.

7 DR. FREY: Okay, great. Howard?

8 DR. NEUFELD: Just one other

9 thing. Can you just -- I'm not sure I

10 remember if you mentioned this or not, but in

11 terms of the elevational component, you also

12 changed the -- when you're doing, say,

13 simulations or models, will you change the

14 dynamic of the ozone exposure from the

15 sinusoidal kind of pattern at low elevations,

16 or the flat pattern at high elevation?

17 DR. HUBBELL: Yes, I don't know

18 that we've worked through all the way, but to

19 the extent that we're doing the gridded

20 estimates of hourly ozone, it would -- grid21 by-grid, if it's a grid that's over a high

22 elevation, it'll reflect that profile, versus
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1 at the lower elevations it'll have a different

2 profile.

3 So, it's grid-by-grid and hour-by4 hour. So, to the extent that the model is

5 capturing that, it'll be in the profile. I

6 don't know how other models capture that. I'm

7 just not sure.

8 DR. FREY: Other comments? The

9 floor is open. Brian and Travis, is there

10 anything you were hoping to hear feedback on

11 that hasn't been addressed yet?

12 DR. HUBBELL: I don't think so. I

13 think we've got a lot of really great

14 information. And again, certainly encourage

15 if you think of other publications that would

16 be helpful to fill in some of these data gaps,

17 please provide those, as they'll be really,

18 really helpful.

19 DR. FREY: Okay, last chance.

20 DR. STALLWORTH: We're adjourned.

21 DR. FREY: All Right. Thank you.

22 DR. HUBBELL: Thanks very much to
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1 the panel for both the discussions yesterday

2 and today. They've been extremely helpful for

3 EPA. Appreciate it. 

4 DR. FREY: And just remember: your

5 written comments are due June third.

6 (Whereupon, the foregoing matter

7 when off the record at 2:10 p.m.) 

8

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135:22

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191:20 198:8,10

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126:5 141:19

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255:17 257:10

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297:11

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103:5,17 104:2

149:5 155:9

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184:20

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close 77:3

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Club 254:1

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Coast 94:17

code 229:18

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174:3,8,12,13,13

174:17,18

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cohort 70:5 204:20

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colleagues 178:2

color 295:17

Colorado 228:5

column 253:15

combination

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combine 38:14

232:2

combined 15:5

106:19 132:12,17

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236:15

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103:22 137:1

139:4 144:22

146:15 166:2

199:16 200:4

212:22 213:6

220:7 224:7

226:20 245:1

264:11 265:20

268:20 282:9

comes 141:7

145:13 164:17

200:2 234:15

coming 24:19,20

56:1 118:21 134:8

182:3 198:5 210:6

227:22 297:10

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24:5 26:6,7 53:16

77:4 85:1,18 88:7

99:14 100:15

105:12 113:19

115:8 118:7

133:15 139:15

149:1 151:10

152:17 163:15

167:11 191:13

200:7 214:17

250:20 255:11,16

258:20 264:2,20

266:13

commented 229:12

commenters 61:6

77:2

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85:8,13 86:21

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100:2 105:10

118:18 119:3

121:6 128:8,10

130:3 145:9

146:17 150:19

162:14,16,19

163:5,16 165:9

166:18 169:13

175:9,11 188:9

189:2 194:16

195:11,12,13

199:8 207:18

211:11,17 212:4,6

212:7 213:12

214:10 245:17

248:21 252:21

254:12 258:3

261:1 263:18,20

264:6 265:14

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301:6 302:8 303:5

Committee 1:3

36:8

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commodity 279:13

common 144:12

communicate 5:21

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173:4 217:21

community-speci...

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172:21 225:9

238:21 241:13,17

241:20

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42:19 44:5 82:10

101:17 175:14,20

187:14 220:11

240:21

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45:11 48:15 57:9

132:10 191:14

259:13,20 260:5

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comprehensive

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127:20 139:17

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251:22

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158:14

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97:5 106:5,6

116:9,17 123:3

153:6 159:18

162:8 165:22

257:7 261:7

264:18

concerned 75:4

86:5 111:4 130:11

131:8 132:3,6

170:2 196:16

238:12 250:16

255:15

concerns 8:11

80:10 100:18

195:5 258:13

concludes 71:17

conclusion 73:13

conclusions 66:18

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284:10

conditioners 125:8

conditioning 14:14

conditions 11:14

12:22 27:8 28:17

62:17 80:1 82:12

201:22 256:8

conduct 30:20

conductance

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conducted 64:5

67:10

conducting 41:19

confidence 30:15

42:10 160:11,12

160:16 177:3

confident 45:10

111:15 128:22

conflation 114:10

120:14

conflicting 217:6

confounders

119:22

confounding 234:8

confused 156:3

confusing 192:16

confusion 92:7

169:22

connect 217:2,17

consensus 5:3,5,10

6:5

conservation 228:2

consider 22:2

27:20 28:21 59:6

68:12 69:19 71:13

72:18 73:15 76:17

78:21 108:18

114:1 148:11

159:13 191:8

194:4 203:6 245:6

291:22

consideration

239:4

considerations

3:18 76:17 118:13

244:2 263:20

considered 46:9,10

60:9 66:8 69:11

69:15,17 148:13

226:2 283:4

considering 21:2

32:8 34:12,12,22

37:4,10,17,19,20

39:3,14 41:9

44:10 57:21

107:14 121:13

167:16 208:2

consistency 68:19

76:12 104:20

255:20 264:8

consistent 72:7

103:17,18 174:3

197:18 208:21

consolidated 96:19

constant 19:4

Constanza 230:19

constrain 254:17

254:18

constrained 8:21

251:2 252:1

constraints 91:4

109:4 138:16

251:8 255:3

construct 34:7

67:15

consultation 4:17

4:21 5:8,12 7:9

22:20 77:5 85:9

137:2

consulting 199:20

consumer 278:8

consumers 278:16

contact 126:6

235:11

contain 147:6

content 26:12,16

26:18

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198:17 232:21

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continue 113:2

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58:10

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contribution 20:16

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contributions 11:2

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contributors 79:10

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52:19 141:13

164:22

controlled 67:3,9

67:17 71:22 72:10

101:18 102:11

223:15

controlling 252:7

252:19

controls 142:5

convened 1:11

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conversion 190:20

convey 5:17

COPD 126:9 174:7

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206:14,18,21

207:2,12,14,15

copy 125:22

core 66:21 69:12,15

69:21 70:17 71:3

71:15 72:13 73:12

73:16 88:19 89:6

90:8,11 91:18

133:12

correct 17:17 18:5

18:9 87:20 95:18

96:11 149:15,19

167:5 219:17

277:5

correction 80:22

81:8 87:15

corrections 81:4

87:4,13

correctly 172:21

correlate 283:11,13

correlated 246:18

281:15

correlation 89:13

corresponding

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230:7 240:4 275:5

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111:17 160:18

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covariants 170:6

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219:22 224:2,4,5

225:2 226:10

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233:6 266:14

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28:10,17,18 31:9

35:22 53:7 62:9

63:2 82:12 83:16

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152:4 215:3,7

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currently 62:19

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84:17 93:4,10,12

100:6 211:3 244:4

244:6 248:22

249:6 278:2

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21:18 31:7 33:6

39:19 45:12,12

53:5 54:14 72:8

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100:8,13 104:2,3

108:4,13 112:2,6

112:13,20 113:1

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122:10 124:3,7

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epidemiology 27:2

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169:15 188:16,19

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100:19 101:10

102:22 136:3

148:12 251:9

265:2 268:8

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25:4 35:10 39:17

42:16 91:18

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establish 110:22

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estimate 13:15

14:15 15:10,18

30:16 32:3 34:16

35:11 37:8 61:22

76:8 87:22 90:16

102:11 117:12

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161:19 170:18

173:14 181:14,19

182:11,12 183:12

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202:3 226:16,20

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190:8 201:22

225:2 226:12

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29:8 30:17 32:7

33:11 40:1 42:11

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66:21 67:2 71:4

71:11 72:14 73:16

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110:22 111:13

139:19 144:20

146:7 160:6 173:7

173:8 175:4

177:21 181:12,15

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Europeans 244:11

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evaluating 178:1

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far 18:9 89:2,7

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270:11 277:4

278:3 286:18

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faster 299:1

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191:12 194:15

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184:13 186:10

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functions 15:5 32:6

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170:14 172:18

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gamma 179:9

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48:3 49:20 56:8

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106:15 107:13,16

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157:5 158:20

159:13 165:8,17

166:1,3 167:10

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176:11 178:5

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187:8,9,13,19

189:11 191:18

192:2,3,6,8,10

194:10 195:11,16

208:15,16 210:2,9

214:13 216:13,14

217:16 218:8,15

219:20,21 220:10

220:10 221:4

222:11 226:18,19

227:13 233:19

237:15 242:22

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249:7,15,20 250:5

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257:4 259:12,16

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260:16 262:20

265:19,21 268:4

269:2 275:22

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284:5,6,17,20

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good 4:4,13 7:9,14

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49:1 55:18 58:15

61:2,12 75:13

78:22 79:3 80:13

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105:16 108:16,20

120:10 121:6

122:1 123:16

129:19,22 130:4

132:11 136:5

139:22 145:5

161:1 166:12

171:13 180:2

182:6 185:19

198:12 210:12,19

211:1 213:13

217:1,8 218:18

220:4 225:21

228:3,8 232:18

237:7 254:7 255:8

256:14 261:18

263:4,5 266:10

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66:13,14 73:7

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gotten 200:15

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gradient 49:3

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listed 27:18 60:20

listening 230:8

listing 131:7

lists 232:4

literature 53:8

71:18 112:21

116:11 148:9

151:5,12 207:22

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42:13 43:19 50:20

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96:4 98:13 101:20

105:1 129:3,4

130:9,11 131:8

150:11,18 168:15

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193:19 195:4

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291:18 292:13

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livestock 20:18

living 65:16

LML 160:7,22

local 80:16 81:17

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locally 91:12

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locally-derived

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locations 12:3 13:3

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location-specific

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logic 145:21

logical 153:3,3

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missed 104:4 116:1

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mistake 177:16

misuse 91:13

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mixing 18:16 94:4

mixtures 268:11

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mobility 193:5

mock 12:2

mode 72:8

model 11:6,21 12:7

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56:19 74:7,14

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NCLAN 282:9,11

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NCOR 88:21

NDA 62:13

near 39:11 89:2

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nearby 228:11

nearly 289:12

necessarily 80:15

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need 5:17 6:3 9:4

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171:20 173:2,11

180:19 186:6

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needs 62:2 65:20

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newspapers 8:15

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Norway 247:19

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noted 90:15 202:5

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notion 195:19

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NOx 48:17 83:9,16

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NPRM 252:4

NRC's 163:6

NSAS 97:1

null 68:18 70:12

number 29:20

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48:4 52:18 59:8

76:2 90:16 95:10

95:19 96:6 99:20

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178:7 184:15

193:1 205:16

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numbers 152:3

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numerical 64:8,14

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OAQPS 127:8

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obesity 121:16

obligated 5:9

observation 127:3

observational

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observations 64:1

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observed 63:15,20

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obtain 16:11,19

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obviously 28:5,14

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33:8 35:16 37:9

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occasions 142:15

occur 67:6 68:7

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occurred 249:6

occurrence 114:10

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occurrences 114:12

occurring 148:20

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offer 197:20

offered 197:1

offering 137:21

OFFICER 2:17

official 248:11

offline 78:16

offset 89:21

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okay 4:3,15 7:8,9

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23:6,7 24:4,5

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45:16 49:9 51:2

53:17 57:17 58:14

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61:3,7,12 65:22

66:9 76:21 77:20

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NEAL R. GROSS

COURT REPORTERS AND TRANSCRIBERS 

1323 RHODE ISLAND AVE., N.W. 

(202) 234-4433 WASHINGTON, D.C. 20005-3701 www.nealrgross.com 

C E R T I F I C A T E

This is to certify that the foregoing transcript 

In the matter of: 

Before: 

Date: 

Place: 

was duly recorded and accurately transcribed under 

my direction; further, that said transcript is a 

true and accurate record of the proceedings. 

 

 ----------------------- Court Reporter 

345

Ozone Review Panel

US EPA Clean Air Advisory Committee

05-20-11

Chapel Hill, NC